With reference to electromagnetic interaction and Abdus Salam’s strong (nuclear) gravity, 1) Square root of ‘reciprocal’ of the strong coupling constant can be considered as the strength of nuclear elementary charge. 2) ‘Reciprocal’ of the strong coupling constant can be considered as the maximum strength of nuclear binding energy. 3) In deuteron, strength of nuclear binding energy is around unity and there exists no strong interaction in between neutron and proton. $G_s\cong 3.32688\times {10}^{28}{\mathrm{m}}^3{\mathrm{kg}}^{-1}{\sec }^{-2}$ being the nuclear gravitational constant, nuclear charge radius can be shown to be, $R_0\cong \frac{2G_s{m}_p}{c^2}\cong 1.24\mathrm{fm}.$ $e_s\cong \left(\frac{G_s{m}_p^2}{\hslash c}\right)e\cong 4.716785\times {10}^{-19}\mathrm{C}$ being the nuclear elementary charge, proton magnetic moment can be shown to be, ${\mu }_p\cong \frac{e_s\hslash }{2m_p}\cong \frac{e{G}_s{m}_p}{2c}\cong 1.48694\times {10}^{-26}\mathrm{J}{.\mathrm{T}}^{-1}.$ ${\alpha }_s\cong {\left(\frac{\hslash c}{G_s{m}_p^2}\right)}^2\cong 0.1153795$ being the strong coupling constant, strong interaction range can be shown to be proportional to $\exp \left(\frac{1}{{\alpha }_s^2}\right).$ Interesting points to be noted are: An increase in the value of ${\alpha }_s$ helps in decreasing the interaction range indicating a more strongly bound nuclear system. A decrease in the value of ${\alpha }_s$ helps in increasing the interaction range indicating a more weakly bound nuclear system. From $Z\cong 30$ onwards, close to stable mass numbers, nuclear binding energy can be addressed with, ${\left(B\right)}_{A_s}\cong Z\times \left\{\left(\frac{1}{{\alpha }_s}+1\right)+\sqrt{\sqrt{30\times 31}}\right\}\left(m_n-m_p\right)c^2\approx Z\times 19.66\mathrm{MeV}.$ With further study, magnitude of the Newtonian gravitational constant can be estimated with nuclear elementary physical constants. One sample relation is, $\left(\frac{G_N}{G_s}\right)\cong \frac{1}{2}{\left(\frac{m_e}{m_p}\right)}^{10}\left[\sqrt{\frac{G_F}{\hslash c}}/\left(\frac{\hslash }{m_{e}c}\right)\right]$ where $G_N$ represents the Newtonian gravitational constant and $G_F$ represents the Fermi’s weak coupling constant. Two interesting coincidences are, ${\left(m_p/m_e\right)}^{10}\cong \exp \left(1/{\alpha }_s^2\right)$ and $2G_s{m}_e/c^2\cong \sqrt{G_F/\hslash c}.$

New setting is introduced to study the global powerful alliance. Global powerful alliance is about a set of vertices which are applied into the setting of neutrosophic graphs. Neighborhood has the key role to define this notion. Also, neighborhood is defined based on strong edges. Strong edge gets a framework as neighborhood and after that, too close vertices have key role to define global powerful alliance based on strong edges. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs excluding empty, path, star, and wheel and containing complete, cycle and r-regular-strong are investigated in the terms of set, minimal set, number, and neutrosophic number. Neutrosophic number is used in this way. It’s applied to use the type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number. It’s called “modified neutrosophic number”. Summation of three values of vertex makes one number and applying it to a set makes neutrosophic number of set. This approach facilitates identifying minimal set and optimal set which forms minimal-global-powerful-alliance number and minimal-global-powerful-alliance-neutrosophic number. Two different types of sets namely global-powerful alliance and minimal-global-powerful alliance are defined. Global-powerful alliance identifies the sets in general vision but minimal-global-powerful alliance takes focus on the sets which deleting a vertex is impossible. Minimal-global-powerful-alliance number is about minimum cardinality amid the cardinalities of all minimal-global-powerful alliances in a given neutrosophic graph. New notions are applied in the settings both individual and family. Family of neutrosophic graphs has an open avenue, in the way that, the family only contains same classes of neutrosophic graphs. The results are about minimal-global-powerful alliance, minimal-global-powerful-alliance number and its corresponded sets, minimal-global-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-global-powerful alliances, minimal-t-powerful alliance, minimal-t-powerful-alliance number and its corresponded sets, minimal-t-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-t-powerful alliances. The connections amid t-powerful-alliances are obtained. The number of connected components has some relations with this new concept and it gets some results. Some classes of neutrosophic graphs behave differently when the parity of vertices are different and in this case, cycle, and complete illustrate these behaviors. Two applications concerning complete model as individual and family, under the titles of time table and scheduling conclude the results and they give more clarifications and closing remarks. In this study, there’s an open way to extend these results into the family of these classes of neutrosophic graphs. The family of neutrosophic graphs aren’t study deeply and with more results but it seems that analogous results are determined. Slight progress is obtained in the family of these models but there are open avenues to study family of other models as same models and different models. There’s a question. How can be related to each other, two sets partitioning the vertex set of a graph? The ideas of neighborhood and neighbors based on strong edges illustrate open way to get results. A set is global powerful alliance when two sets partitioning vertex set have uniform structure. All members of set have more amount of neighbors in the set than out of set and reversely for non-members of set with less members in the way that the set is simultaneously t-offensive and(t-2)-defensive. A set is global if t=0. It leads us to the notion of global powerful alliance. Different edges make different neighborhoods but it’s used one style edge titled strong edge. These notions are applied into neutrosophic graphs as individuals and family of them. Independent set as an alliance is a special set which has no neighbor inside and it implies some drawbacks for these notions. Finding special sets which are well-known, is an open way to purse this study. Special set which its members have only one neighbor inside, characterize the connected components where the cardinality of its complement is the number of connected components. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

To understand the mystery of final unification, in our earlier publications, we proposed that, 1) There exist three atomic gravitational constants associated with electroweak, strong and electromagnetic interactions; and 2) There exists a strong interaction elementary charge (e_s) in such a way that, it's squared ratio with normal elementary charge is close to inverse of the strong coupling constant. In this context, starting from lepton rest masses to stellar masses, we have developed many interesting and workable relations. We noticed that, electroweak field seems to be operated by a primordial massive fermion of rest energy 585 GeV. It can be considered as the zygote of all elementary particles and galactic dark matter. Proceeding further, with a characteristic fermion-boson mass ratio of 2.27, quarks can be classified into quark fermions and quark bosons. Considering strong charge conservation and electromagnetic charge conservation, fractional charge quark fermions and quark bosons can be understood. Quark fermions that generate observable massive baryons can be called as Fluons. Quark bosons that generate observable mesons can be called as Bluons. By considering a new hadronic fermion of rest energy 103.4 GeV, rest masses of fluons and bluons can be estimated and there by baryon masses and meson masses can be estimated.

Here we analyze three well-known conjectures: (i) the existence of infinitely-many twin primes, (ii) Goldbach’s strong conjecture, and (iii) Polignac’s conjecture. We show that the three conjectures are related to each other. In particular, we see that in analysing the validity of the Goldbach’s strong conjecture, one must consider also the existence of an infinite number of twin primes. As a consequence of how we approach this analysis, we also observe that if this conjecture is true, then so is Polignac’s conjecture. Our first step is an analysis of the existence of infinitely-many twin primes numbers. For this, using the formula 4((n−1)!+1) ≡ −n (mod n(n + 2)) – satisfied if and only if (n, n + 2) are twin primes –, together with Wilson’s theorem, we obtain conditions that must be met for two numbers to be twin primes. Our results, obtained from an analytic and functional study, lead us to conclude that there may exist infinitely-many twin primes. Next, we consider the validity of the Goldbach’s strong conjecture. After showing that the conjecture is true for the first even numbers, we notice a pattern that we analyze for any even number, reducing it to three cases: (i) when the even number 2n is two times a prime number n; (ii) when the even number 2n is such that n = 2m, with 2m − 1 and 2m + 1 twin primes; (iii) all other cases, i.e., for any 2n even number ∀n ∈ N with n > 1, n prime or not, with independence of n = 2m being 2m−1 and 2m+1 twin primes or not. In this last case we show that one can always find a certain r ∈ N such that 1 < r < n satisfying that n−r and n+r are primes, so that their sum is 2n. In this case we use the reduction to absurd method, and our results lead us to conclude that Goldbach’s strong conjecture is true to the best of our calculations, as well as the Polignac’s conjecture.

We prove a quasi-pseudometric version of the strong Ekeland principle proved by P. Georgiev and T. Suzuki.

The purpose of this paper is to bring to light a method through which the global in time existence for arbitrary large in H¹ initial data of a strong solution to 3D periodic Navier-Stokes equations follows. The method consists of subdividing the time interval of existence into smaller sub-intervals carefully chosen. These sub-intervals are chosen based on the hypothesis that for any wavenumber m, one can find an interval of time on which the energy quantized in low-frequency components (up to m) of the solution u is lesser than the energy quantized in high-frequency components (down to m) or otherwise the opposite. We associate then a suitable number m to each one of the intervals and we prove that the norm ||u(t)||_H1 is bounded in both mentioned cases. The process can be continued until reaching the maximal time of existence T_max which yields the global in time existence of strong solution.

At nuclear scale, we present three heuristic relations pertaining to strong and electroweak coupling constants. With these relations, close to beta stability line, it is possible to study nuclear binding energy with a single energy coefficient of magnitude $\left(\frac{1}{{\alpha }_s}\right)\left[\frac{e^2}{4\pi {\epsilon }_0{R}_0}\right]\approx 10.0\text{MeV}\text{.}$ With reference to up and down quark masses, it is also possible to interpret that, nuclear binding energy is proportional to the mean mass of $\left[\left(2m_u+m_d\right)\text{and}\left(m_u+2m_d\right)\right]\approx 10.0\text{MeV}.$

We construct a repeated quantum game with public goods by the quantum entanglement and strong reciprocity. By using the paradigm of quantum game analysis, we obtain that both the quantum entanglement and strong reciprocity are helpful to intensify cooperation and achieving Pareto optimality. In addition, under an example which is greenhouse green viable planting industry, we verify that the quantum entanglement and strong reciprocity have a positive role in cooperation.

We report the strong coupling between plasmonic surface lattice resonances (SLRs) and photonic Fabry-Pérot (F-P) resonances in a microcavity embedded with two-dimensional periodic array of metal-insulator-metal nanopillars. For such a plasmonic-photonic system, we show that the SLR can be strongly coupled to the F-P resonances of both the odd- and even orders, and that the splitting energy reaches as high as 138 meV in the visible regime. We expect that this work will provide a new scheme for strong coupling between plasmonic and photonic modes.

Nondipole terms in the atom-laser interaction arising due to the presence of a magnetic component in an electromagnetic wave and its inhomogeneity lead to nonseparability of the center-of-mass (CM) and electron variables in the neutral atom and, as a consequence, to its acceleration. We investigate this effect as well as the accompanying excitation and ionization processes for the hydrogen atom in strong (1012 - 2×1014 W/cm2) linearly polarized short-wavelength (5eV ≲ℏω≲ 27 eV) electromagnetic pulses of about 8 fs duration. The study has been carried out within the framework of a hybrid quantum-quasiclassical approach in which the coupled time-dependent Schrödinger equation for an electron and the classical Hamilton equations for the CM of an atom are simultaneously integrated. Optimal conditions with respect to the frequency and intensity of the electromagnetic wave for the acceleration of atoms without their noticeable ionization are found in the analyzed region.

We review the basics of nuclear binding energy scheme assumed to be associated with the existence of a new strong elementary charge associated with square root of reciprocal of the strong coupling constant.

We examine data assimilation coupling between meteorology and chemistry in the stratosphere from both weak and strong coupling strategies. The study was performed with the Canadian operational weather prediction Global Environmental Multiscale (GEM) model coupled online with the photochemical stratospheric chemistry developed at the Belgian Institute for Space Aeronomy, described in Part I. Here, the Canadian Meteorological Centre’s operational variational assimilation system was extended to include errors of chemical variables and cross-covariances between meteorological and chemical variables in a 3D-Var configuration, and we added the adjoint of tracer advection in the 4D-Var configuration. Our results show that the assimilation of limb sounding observations from the MIPAS instrument on board Envisat can be used to anchor the AMSU-A radiance bias correction scheme. Also, the added value of limb sounding temperature observations on meteorology and transport is shown to be significant. Weak coupling data assimilation with ozone-radiation interaction is shown to give comparable on meteorology whether a simplified linearized or comprehensive ozone chemistry scheme is used. Strong coupling data assimilation, using static error cross-covariances between ozone and temperature in a 3D-Var context, produced inconclusive results with the approximations we used. We have also conducted the assimilation of long-lived species observations using 4D-Var to infer winds. Our results showed the added value of assimilating several long-lived species, and an improvement in the zonal wind in the Tropics within the troposphere and lower stratosphere. 4D-Var assimilation also induced a correction of zonal wind in the surf zone and a temperature bias in the lower tropical stratosphere

The strong coupling between individual quantum emitters and resonant optical micro/nanocavities is beneficial to understand light and matter interactions. Here we propose a plasmonic nanoantenna placed on a metal film to achieve an ultra-high electric field enhancement in the nanogap and ultra-small optical mode volume. The strong coupling between a single quantum dot and the designed structure is investigated in detail by both numerical simulations and theoretical calculations. When a single QD is inserted into the nanogap of the silver nanoantenna, scattering spectra show remarkably large spectral splitting and typical anti-crossing behavior of the vacuum Rabi splitting, which can be realized in the scattering spectra by varying the nanoantenna thickness. Our work shows a possible way to enhance light-matter interaction at a single quantum emitter limit, which can be useful for future quantum and nanophotonic applications.

In this preliminary investigation, a concise molecular docking study using the Pyrx program screened thousands of compounds against the active site of HIV-1 reverse transcriptase. The Virtual Screening library was employed to assess binding energetics scores, focusing on identifying candidates with high Vina Scores. Eight compounds, including Tetrophan, Imatinib, Amentoflavone, Alprazolam, Bilobetin, Bafetinib, Nilotinib, and Ginketin, emerged as promising candidates with significant binding energies.Recognizing compounds that strongly bind to HIV-1 reverse transcriptase holds potential for antiretroviral drug development in the fight against HIV infection. Subsequently, the study evaluated the toxicity properties of these candidates using pKCSM. Amentoflavone, a natural biflavonoid found in Ginkgo biloba and Nilotinib, a tyrosine kinase inhibitor, demonstrated lower overall toxicity profiles compared to other candidates. Further toxicity analysis using Pro-Tox-II revealed Amentoflavone's higher predictive LD50, lower toxicity class, and reduced probabilities of hepatotoxicity, carcinogenicity, mutagenicity, and moderate immunotoxicity compared to Nilotinib. While Nilotinib, a pharmaceutical drug, exhibited higher probabilities of adverse effects in these categories. In summary, Amentoflavone and Nilotinib present as promising candidates with lower toxicity concerns. Amentoflavone, as a natural substance, showcases a more favorable toxicity profile than Nilotinib, offering valuable insights for potential therapeutic applications.

We present simple relations for nuclear stability and nuclear binding energy with respect to three gravitational constants associated with electroweak, strong and electromagnetic interactions.

Ship pilots and maritime safety administration have an urgent need for more accurate and earlier warnings on strong wind gusts. This study firstly investigates the “Oriental Star” cruise ship cap-sizing event in 2015, one of the deadliest shipwreck events in recent years, and explores all related hydro-meteorological components in a global mesoscale model. It is found that, rather than the missing signal in raw surface wind prediction, the cumulus precipitation variable (CP) increases dramatically during the accident occurrence, which significantly corresponds to the sub-grid strong wind gust. The effective lead-time can be extended from 24hr (deterministic model) to 48hr (en-semble model). This finding is then verified in another two recent deadly cruise boat accidents. The introduction of the new variable is bearing the hope of improvement to the current maritime safeguard system, on predicting sub-grid strong wind gusts for small-size cruise boats in offshore and inland rivers. Finally, an automatic-response system is developed to provide economical con-vection prediction via Inmarsat email communication, aiming to explore operational severe con-vective gust early-warning and appropriate numerical mesoscale model application.

This paper first explains the theory of the origin of force from a new perspective, explaining that the origin of all forces is caused by the "missing of energy in the time dimension" (non-conservation in a certain period of time), and constructs a unified theory of force on this basis. Then, through the unified theory of force, the following phenomena are reinterpreted: (1) The common origin of the inverse square law of gravitation and electromagnetic force; (2) The origin of the repulsive force of electrons and protons at small distances; (3) The mystery of the rotation curve of galaxies and the new explanation of "dark matter"; (4) explain the origin of the magnetic field; (5) Predict that moving magnets have the same radiation effect as charged particles (electron magnetic moments also have radiation effects); (6) Reinterpret Maxwell's displacement current; (7) Reinterpret synchrotron radiation and bremsstrahlung; (8) Explain that the strong and weak forces are short-range forces; (9) Predict the true structure of black holes and the origin of gravitational waves;(10) Possible explanation for the origin of the speed of light.

An attempt is made to model the atomic nucleus as a combination of bound and free or unbound nucleons. Due to strong interaction, bound nucleons help in increasing nuclear binding energy and due to electroweak interaction, free or unbound nucleons help in decreasing nuclear binding energy. In this context, with reference to proposed 4G model of final unification and strong interaction, recently we have developed a unified nuclear binding energy scheme with four simple terms, one energy coefficient of 10.1 MeV and two small numbers 0.0016 and 0.0019. In this paper, by eliminating the number 0.0019, we try to fine tune the estimation procedure of number of free or unbound nucleons pertaining to the second term with an energy coefficient of 11.9 MeV. It seems that, some kind of electroweak interaction is playing a strange role in maintaining free or unbound nucleons within the nucleus. It is possible to say that, strong interaction plays a vital role in increasing nuclear binding energy and electroweak interaction plays a vital role in reducing nuclear binding energy. Interesting observation is that, Z can be considered as a characteristic representation of range of number of bound isotopes of Z. For medium, heavy and super heavy atoms, beginning and ending mass numbers pertaining to bound states can be understood with 2Z+0.004Z^2 and 3Z+0.004Z^2 respectively. With further study, neutron drip lines can be understood. Based on this kind of data fitting procedure and by considering the mass ratio of pions and electroweak bosons, existence of our 4G model of electroweak fermion of rest energy 584.725 GeV can be confirmed confidently.

The idea of strong and weak adjacencies between vertices has been generalized into fuzzy graphs and intuitionistic fuzzy graphs (IFGs) and it is an important part of making decisions. However, one or two membership degrees are not always sufficient for making decisions on real-world problems that need an answer of types “yes, neutral, and no". Consequently, in previous work, we generalized the concept into picture fuzzy graphs (PFGs) where each element in the PFG has membership, neutral, and non-membership degrees. Moreover, we constructed the notion of the coloring of PFGs based on strong and weak adjacencies between vertices. In this paper, we investigate some properties of the chromatic number of PFGs based on the concept of strong and weak adjacencies between vertices. According to the properties, we construct an algorithm to find the chromatic number of PFGs. The algorithm is usefull when we work with large PFGs. Further, we improve the method to implement the PFG’s coloring for determining traffic signal phasing at an intersection. A case study has also been done to evaluate the method.

As there exist no repulsive forces in strong interaction, in a hypothetical approach, strong interaction can be assumed to be equivalent to a large gravitational coupling. Based on this concept, strong coupling constant can be defined as a ratio of the electromagnetic force and the gravitational force associated with proton, neutron, up quark and down quark. With respect to the product of strong coupling constant and fine structure ratio, we review our recently proposed two semi empirical relations and coefficients 0.00189 and 0.00642 connected with nuclear stability and binding energy. We wish to emphasize that- by classifying nucleons as ‘free nucleons’ and ‘active nucleons’, nuclear binding energy can be fitted with a new class of ‘three term’ formula having one unique energy coefficient. Based on the geometry and quantum nature, currently believed harmonic oscillator and spin orbit magic numbers can be considered as the lower and upper “mass limits” of quark clusters.

Culex quinquefasciatus is an important target for vector control because of its ability to transmit pathogens that cause disease. Most populations are resistant to pyrethroids and often to organophosphates, the two most common classes of active ingredients used by public health agencies. A knockdown resistance (kdr) mutation, resulting in a change from a leucine to phenylalanine in the voltage gated sodium channel, is one mechanism contributing to the pyrethroid resistant phenotype. Enzymatic resistance has also been shown to play a very important role. Recent studies have shown strong resistance in populations even when kdr is relatively low which indicates factors other than kdr may be larger contributors to resistance. In this study, we examined on a statewide scale (over 70 populations), the strength of the correlation between resistance in the CDC bottle bioassay and the kdr genotypes and allele frequencies. Spearman correlation analysis showed only moderate (-0.51) and weak (-0.29) correlation between the kdr genotype and permethrin and deltamethrin respectively. The frequency of the kdr allele was an even weaker correlate. These results indicate, in contrast to Aedes aegypti, assessing kdr in populations of Culex quinquefasciatus is not a good surrogate for phenotypic resistance testing.

A Berry geometrical phase is identified in a strongly metastable system containing dynamically responsive clathrate hydrate structures within a crystal-fluid material. High energy degeneracy in the associated chemistry produces local stability and false vacuum conditions that lead to non-extensive and non-additive contributions in the fundamental thermodynamic relation. Application of Ginzburg-Landau theory and the scaling laws reveals a coherence length and a penetration depth for a macro-scale dual superconductor. The coherence length determines non-extensive volume changes whilst its inverse gives the Higgs mass. The penetration depth determines the extent of QCD vacuum suppression whilst its inverse gives the vector boson mass together with indirect manifestation as non-additive hyperbolic curvature. Simultaneous emergence of the Ginzburg-Landau superconducting phase transition is consistent with gauge-invariant coupling of the scalar field to the Yang-Mills action in QCD. The discovery of an energy gap in the gradient energy term of the system Lagrangian is associated with a critical correlation length revealed in the transition from a gapped to a gapless superconducting state. Together with the emergence and absorption of the Higgs-like scalar field, a mechanism for describing a renormalized QCD mass gap arises.

Metal nanoparticles supporting plasmons are widely used to enhance electromagnetic fields, resulting in strong light-matter interactions at the nanoscale in a diverse range of applications. Recently, it has been shown that when metal nanorods are periodically arranged with proper lattice periods, surface lattice resonances (SLRs) can be excited and near fields can be greatly enhanced over extended volumes. In this work, we report significant near field enhancement over even larger volumes by placing the metal nanorod array within a Fabry-Pérot (F-P) microcavity. Results show that taking advantage of strong coupling between the SLR and the photonic F-P resonances, the electric field intensity of the bonding split mode can be enhanced by up to 1935 times, which is about three times of the enhancement of the SLR, and the greatly enhanced field can extend over most of the F-P microcavity. We further show that the F-P resonances of both odd and even orders can strongly couple to the SLR by varying the nanorods position from the middle of the microcavity. We expect that the proposed plasmonic-photonic coupling system will find promising applications in nanolasers, nonlinear optics and sensing.

In this paper, the authors employ Mountain Pass Lemma, the method of weak solution regularization and Lyapunov function method to derive the unique existence of globally exponential stable positive stationary solution of a single-species model with diffusion and delayed feedback. The obtained stability criterion illuminates that under some suitable conditions, a certain internal competition is conducive to the overall stability of the population, and a certain amount of family planning is conducive to the overall stability of the population. A numerical example and three tables show the effectiveness of the proposed methods.

With reference to our earlier published views on large nuclear gravitational constant , nuclear elementary charge and strong coupling constant , in this paper, we present simple relations for nuclear stability range, binding energy of isotopes and magic proton numbers.

Cotton is the most ubiquitous and profitable fiber with diverse industrial and domestic applications. Grown in over 100 countries, it has a global market value of about $40 billion and employs over 350 million people from fields to textile mills, contributing about 7% of total labor-force recruitment in developing economies. Cotton has an indeterminate growth habit and an extensive tap root system affected by soil physicochemical and environmental conditions. There is a consensus among experts that conventional cotton cultivation still has a long way to attain sustainability, which is essential if cotton will maintain its competitive edge over other natural and synthetic fibers like hemp, polyesters, and rayon. Despite several efforts already committed to growing cotton sustainably, sustainability has eluded cotton cultivation globally because of the intense farm inputs (freshwater, pesticides, and heavy-duty equipment) needs, especially in developing economies. Some of the technological advancements towards achieving the goal of sustainable cotton cultivation include the development of new varieties, improved irrigation and mulching and precision agriculture techniques, application of remote sensing and Unmanned Aerial Systems (UAS) combined with image processing, and the introduction of autonomous and multi-purpose robotic platforms for growing and harvesting cotton. This review attempts to evaluate the successes already achieved by stakeholders in moving cotton towards sustainable production and identify areas where efforts are still needed to reach sustainable production and improved profitability goals for cotton with projections for future research directions.

The inherited ‘EIA’ process at Brexit is based on a ‘Project’ period from Inception tothe start of construction works. The ‘Incompleteness’ of the process covers andidentifies stages that will impact on the environmental cycle: construction period,operational life, de-commissioning and a return to acceptable environmental footprint.A master environment structure-plan framework is required to commence with theupgrading of the complete ‘EIA’ process, embracing separate limbs for the UK’spriority environmental targets for climate change, and other major adverse effectswhich result in serious ‘harm’ to the UK environment. The identification of the processfor ‘incompleteness’ requires effective sustainability, and inclusion of effectivemanagement tools, for the essential ‘monitoring/control/recording’ proceduresthroughout the project life and the natural environmental cycle. This will allow theopportunity for a new approach to a structured ‘Suite of EIAR Directives’, to enable a‘EIAR’ regime that ‘will remain fit and proper for UK purpose’.

Maximum likelihood estimation (MLE) is a popular method for parameter estimation in both applied probability and statistics but MLE cannot solve the problem of incomplete data or hidden data because it is impossible to maximize likelihood function from hidden data. Expectation maximum (EM) algorithm is a powerful mathematical tool for solving this problem if there is a relationship between hidden data and observed data. Such hinting relationship is specified by a mapping from hidden data to observed data or by a joint probability between hidden data and observed data. In other words, the relationship helps us know hidden data by surveying observed data. The essential ideology of EM is to maximize the expectation of likelihood function over observed data based on the hinting relationship instead of maximizing directly the likelihood function of hidden data. Pioneers in EM algorithm proved its convergence. As a result, EM algorithm produces parameter estimators as well as MLE does. This tutorial aims to provide explanations of EM algorithm in order to help researchers comprehend it. Moreover some improvements of EM algorithm are also proposed in the tutorial such as combination of EM and third-order convergence Newton-Raphson process, combination of EM and gradient descent method, and combination of EM and particle swarm optimization (PSO) algorithm.

This study focuses on examining various approaches for Tensor Decompositions (TDs) and their potential applications in satellite imaging (SI) and deep learning (DL). The research highlights how these decompositions can contribute to the advancement of SI and DL, providing valuable insights for future utilization of TDs in research. It explores how these techniques contribute to the advancement of SI and DL methods, providing insights into their potential applications and suggesting future research directions. The study aims to enhance the use of TDs techniques to further advance research efforts in these fields. More importantly, the current investigation offers a thorough analysis of the potential advantages and reasons for employing TDs techniques in different domains, including satellite imaging and deep learning. The aim is to enhance research outcomes by utilizing TDs. The review also identifies unresolved issues and proposes future directions for further investigation in this field. Fundamentally, these proposed open problems will open new grounds to the research community to articulate, innovate, and provide more real-life applications to improve the current state of the art by delving into a wider vision for a higher-level performance of both satellite imaging (SI) and deep learning (DL). Looking at the bigger scenario, this also suggests that TDs could be potentially employed to revolutionize existing machine learning technologies as well as the current space AI industry.

Hyperspectral imaging data holds great potential for the different stages of the mining life cycle in active and post-mining environments. However, the technology has yet to reach the stage of large-scale industrial implementation and acceptance. While hyperspectral satellite imagery can achieve high spectral resolution, signal-to-noise ratio (SNR) and global availability with break-through satellite systems like EnMAP, EMIT and PRISMA, limited spatial resolution poses chal-lenges for sectors like mining, which require decimetre to centimetre scale resolution for applica-tions such as reconciliation, ore/waste estimates, geotechnical assessments and environmental monitoring. Hyperspectral imaging from drones (referred to herein as Uncrewed Aerial Systems; UASs) offers high spatial resolution data relevant to the camp/ mine scale, with the capability for frequent, user-defined re-visit times. This has been made possible by the miniaturization of hy-perspectral imaging systems. Collection of data in the visible to near and shortwave infrared (VNIR-SWIR) wavelength regions enables the detection of different minerals and surface altera-tion patterns potentially revealing crucial information for exploration, extraction, re-mining, waste remediation, and rehabilitation. In this paper, we provide a review of relevant studies de-ploying hyperspectral imaging in or applicable to the mining sector, especially for the use of hy-perspectral VNIR-SWIR Uncrewed Aerial Systems. Where required, we draw on previous in-sights derived from satellite or ground-based systems. We also discuss UAS survey planning, and sampling considerations for validation and interpretation.

Abstruct Green Human Resource Management (GHRM) has emerged as an essential strategy for achieving environmental sustainability within organizations. However, there remains a significant gap in understanding its direct impact on sustainable performance. This study seeks to address these gaps by investigating the relationship between GHRM and sustainable performance, with a focus on the mediating role of green innovation and the moderating influence of transformational leadership. A cross-sectional study was conducted among Malaysian small and medium-sized enterprises (SMEs) to explore the interrelationships between Green HRM, green process and product innovation, sustainability, and the role of sustainable leadership. The study's findings reveal a positive and significant relationship between green HRM practices and sustainability, encompassing environmental, economic, and social aspects. The findings suggest that management support for environmental initiatives is a critical factor in enhancing the effectiveness and spread of green innovations, emphasizing the importance of GHM in the broader context of organizational change and sustainability. In addition, the study underscores the critical role of transformative leadership in fostering sustainable practices, particularly the significant moderator role of responsible leadership in driving sustainable business practices. In summary, this study provides a roadmap for businesses, particularly SMEs, to leverage HGRM as a strategic tool in their pursuit of sustainability.

Precision farming is transforming how antibiotics get used on farms. It fights the overuse that creates superbugs and harms nature. Farmers now have high-tech tools to use antibiotics ultra-precisely. Drones, AI, and advanced watering equipment help them pinpoint only sick plants and animals needing treatment. This shields crops while avoiding environmental damage. More careful antibiotic use makes livestock healthier and boosts harvests too. And it prevents resistant germs, where antibiotics stop working altogether. The approach helps farms in multiple ways, using fewer resources for even better results. There are some growing pains, like high costs for small farms. And questions around data privacy also cause concern. But overcoming these hurdles could help precision farming spread far and wide. This technology promises safer, greener, and more productive agriculture. Targeted use of antibiotics protects both crops and people from drug-proof germs. And nature benefits when less medicine spreads into soil and water. The future looks bright for farming with precision.

Understanding mechanisms of ageing remains a complex challenge for biogerontologists, but recent adaptations of evolutionary ageing theories offer a compelling lens in which to view both age-related molecular and physiological deterioration. Ageing is commonly associated with a progressive loss of biochemical processes and degeneration of molecular material, however, the mechanisms of diminishing function are not simply a result of aberrant expression of these pathways. Natural selection pressures are at their highest in youthful periods to select genes advantageous to maximising reproductive capacity. After sexual maturation, selective pressure diminishes, subjecting individuals to maladaptive pleiotropic gene function once beneficial for developmental growth, but pathogenic later in life. Due to this selective ‘shadowing’ in ageing, mechanisms to counter hyperfunctional genes are unlikely to evolve within a given species. These genetic ‘run-on’ programmes are not dysfunctional per se and, in fact, remain highly robust. Thus, interventions capable of optimising gene function during the ageing process represent as attractive therapeutic modalities. Caenorhabditis elegans offers a unique model to explore high-throughput screening of interventions to combat hyperfunctional pathways involved in ageing. However, the majority of research to date employ whole-life vs late-life pathway manipulation of developmental/growth-related systems to claim ageing attenuation, despite significant impairments in early-life fitness and discordance with healthspan. Here, we discuss data supporting hyperfunctional changes at a global molecular and functional level in C. elegans, and how classical lifespan-extension mutants alter these dynamics. We later discuss the relevance of such mutant models for exploring mechanisms of ageing, highlighting that post-reproductive gene manipulation represents a far more translatable approach for C. elegans research not routed within pleiotropic constraints. More so, lifespan has become a routine readout for quantifying ‘ageing’, however, we make the argument that a compression of gerospan vs lifespan extension is a more meaningful goal for anti-ageing regimes with current knowledge. Similarly, mechanisms governing lifespan are distinct from those regulating health, and slowing senescent pathology accumulation appears more applicable for the abstraction to human ageing.

The theory of Ismail's non-extensive maximum entropy solution (NME) is described in detail. It is used as an inductive inference technique for heavy-tailed queues with a non-robust mean queue length and a non-extensive "long-range" interaction. In our novel method, we substitute the non-robust mean queue length for the conventional Pollaczeck-Khinchin mean queue length. In other words, the new non-extensivity parameter q will be included in the resulting state probability function. Numerical portraits are provided to capture the influential effect of the derived formalism, , on the stable M//1 queue with heavy tails. More potentially, some applications of Hurst Exponent to social computing and connected health are provided. Conclusion with some challenging open problems and possible future research pathways are given.

In recent years, the Canadian dairy sector has faced escalating challenges due to its significant contribution to greenhouse gas emissions, particularly methane. This paper critically examines a spectrum of innovative techniques aimed at mitigating methane emissions within this sector, scrutinizing their cost-effectiveness, efficiency, compatibility with animal welfare standards, and adherence to both existing and prospective Canadian environmental legislations. The discourse commences with an exhaustive overview of contemporary methane reduction methodologies pertinent to dairy farming, followed by a rigorous analysis of their economic feasibility. This includes a detailed cost-benefit analysis, juxtaposed with the efficiency and technological advancements these techniques embody. A pivotal aspect of this examination is the alignment of animal welfare with emission reduction objectives, ensuring that strategies employed do not compromise the health and well-being of dairy cattle. Furthermore, the paper delves into the legislative landscape of Canada, evaluating the congruence of these techniques with current environmental laws and anticipating future regulatory shifts. Performance indicators for emission reduction are critically assessed, establishing benchmarks tailored to the Canadian context. This is complemented by an exploration of the market potential of these innovations, including factors influencing their adoption and scalability in the market. The analysis culminates with a synthesis of case studies and best practices within Canada, offering insights into successful implementations and drawing lessons for future endeavors. This comprehensive approach serves not only to address the immediate environmental and health impacts associated with dairy farming emissions but also contributes significantly to the overarching goal of sustainable development in the agricultural sector.

Current and dynamic developments in green technologies have led to several innovation practices in the manufacturing sector only to become the top approaches used for achieving and accelerating sustainable development (SD) in the current business markets. In addition, manufacturing firms is in need of green innovation to be able to monitor and control their operations and enhance their environmental performance. However, regardless of its many benefits, the level of green innovation adoption and implementation is still lower than expected among manufacturing industries. Thus, this study aimed to minimize the gap by developing and validating a study model underpinned by Resource based view and Institutional theories, along with the Technology-Organization-Environment (TOE) framework in combination to convince firms to adopt green innovation. The study gathered data from 179 respondents using a survey distributed to manufacturing firms, after which data was exposed to Structural Equation Modeling (PLS-SEM) approach, for analysis. Based on the approach deliverables, all the integrated constructs of the model, namely perceived benefits, top management support, coercive pressure, normative pressure and mimetic pressure all predicted green management accounting practices. Moreover, green management accounting practices were found to directly and significantly affect green environmental performance. The developed integrated model provides a clear implication to decision-makers, indicating the importance of adopting and using green practices and innovative technologies for enhancing environmental performance. Based on the results from the reviewed advanced green technologies studies, there is considerable connection between green management accounting practices and environmental performance in the context of developing economies.

Governance is one of the most essential instruments for environmental management. Biodiversity is in the core field of environmental governance. Yet environmental authorities are persistently challenged the loss of biodiversity as a very important global issue for several years due to high dependent exposure to risks. The study attempts to relook at the key governance tools that strengthen policies towards managing biodiversity within and around the national park’s survey in Moulvibazar district. The study showed that biodiversity related legislation amended was the highest in Bangladesh for the period of 2010 to 2016. The growth of policy instruments maximized at but in low environmental governance services within the same period. The study assessed that the existing environmental policy instrument is inadequate and sluggish for effective conservation, compared with several others governance tools and various performances are still below par. Governance knowledge is indispensable for biodiversity management but such knowledge is poorly identified. These results reflect the importance of effective governance for transparency that the State provides. The research is to represent a dynamic and adaptable framework that can be applied for collective governance relevant to policy integration, participation and enforcement in order to foster environmental conservation sustainability.

Arbuscular mycorrhizal fungi are soil microorganisms that provide various benefits, such as increasing soil fertility and enhancing plant growth. The present study aimed to propagate arbuscular mycorrhizal fungal spores in trap plants. Soil sampling was carried out in October 2021 on five coffee farms in the central area of Veracruz, Mexico. Soil from coffee plantations and sterile sand were mixed in pots and used for the propagation of arbuscular mycorrhizal fungi, and Sorghum vulgare was used as a trap plant. The plants were kept in a greenhouse for 120 days. The abundance of spores in the sorghum trap plants increased significantly (p

Natural Gas (NG) processing is a prominent industrial separation process. Among the available techniques, the innovative membrane process shows potential for efficient removal of impurities, including carbon dioxide (CO₂). This study focuses on utilizing breakthroughs in membrane separation to drive sustainable CO₂ extraction from natural gas. Through comprehensive research and analysis, we explore the effectiveness and feasibility of membrane-based systems in removing CO₂ impurities from NG, thus promoting greener and more sustainable industrial practices. Our findings underscore the transformative nature of membrane separation technology, presenting new possibilities for a more environmentally-friendly and sustainable approach to CO₂ extraction from natural gas.Natural Gas (NG) processing utilizes various techniques for impurity removal, with the membrane process emerging as a promising option for efficient carbon dioxide (CO₂) extraction. This research proposes the integration of a simple mathematical model into ASPEN HYSYS to design a membrane system for CO₂/CH₄ separation. The study also investigates parameter sensitivities by altering operating conditions, such as feed composition and pressure, as well as membrane properties, including selectivity. By analyzing these variables, we aim to optimize the performance and efficiency of the membrane system, facilitating the sustainable extraction of CO₂ from NG. The findings contribute to advancing the design and operation of membrane-based processes for CO₂ separation, paving the way for greener and more sustainable industrial practices. In addition, this study explores various configurations for optimizing the design of the membrane system, including single-stage with and without recycling as well as double-stage configurations. The investigation demonstrates that methane recovery can be enhanced through the recycling of the permeate stream and by implementing a double stage membrane system. These findings highlight the potential for improving the efficiency and performance of the membrane system, enabling higher methane recovery rates. By considering different configurations, this research contributes to the development of more effective and sustainable CO₂ extraction processes from natural gas.

Kininogens are multidomain glycoproteins found in the blood of most vertebrates. They are important in the blood coagulation cascade pathways - in intrinsic pathway activation leading to thrombin generation partially independently from tissue factor dependent extrinsic pathway, connecting blood coagulation with the kallikrein-kinin system. Nothing is known about the shape on atomic level therefore the endeavor to obtain the good-quality spatial structure of kininogens is important for a better understanding of their role in disease and treatment. Application of cryo-EM is important for solving the spatial structure of kininogens, drawing new frontiers in understanding the function and opening new pathways for drug development.

The importance of conflict analysis and safety considerations during work zone intervals at signalized intersections cannot be overstated, as these periods pose unique challenges and safety risks for both motorists and pedestrians. Work zones introduce temporary changes to traffic patterns, lane configurations, and signal timings, which can disrupt the flow of traffic and increase the likelihood of conflicts between vehicles and pedestrians. By conducting comprehensive conflict analysis, it is possible to identify potential conflict points, such as merging areas, pedestrian crossings, and lane transitions, and implement targeted safety measures to mitigate risks. Additionally, considering safety considerations during work zone intervals is paramount to safeguarding the well-being of road users and minimizing the occurrence of conflicts or collisions. Measures such as enhanced signage, temporary traffic control devices, and increased enforcement efforts can help promote compliance with traffic regulations and ensure the safe passage of vehicles and pedestrians through work zones. This study investigates the dynamics of traffic behavior and safety implications within work zones at signalized intersections, aiming to address key challenges and enhance intersection management strategies. Through comprehensive analysis, varying frequencies of Vehicle-to-Vehicle (V2V) conflicts were observed across different movement directions, with significant occurrences identified in specific phases of the traffic signal cycle. Specifically, 69 V2V conflicts in phase #1, 181 in phase #2, 31 in phase #3, 207 in phase #4, 1 in phase #5, 274 in phase #6, 93 in phase #7, and 186 in phase #8 were recorded. Furthermore, the examination of Vehicle-to-Pedestrian (V2P) conflicts underscored the importance of prioritizing pedestrian safety, with notable occurrences observed in phases associated with pedestrian crossing movements. Meanwhile, despite the closure of left-turn movements, instances of red light running persisted, with 69 red light running events in phase #1, 181 in phase #2, 31 in phase #3, 207 in phase #4, 1 in phase #5, 274 in phase #6, 93 in phase #7, and 186 in phase #8.To mitigate these safety concerns during work zone intervals, proactive measures are essential. Strategies include improving communication through clear signage and advanced warning systems, enhancing enforcement efforts with red light cameras and increased police presence, and investing in infrastructure improvements such as temporary pedestrian facilities. Integration of real-time data from sensors, particularly LiDAR technology, offers significant advantages in detecting conflicts and red light runners during work zone intervals. LiDAR's precise, real-time data on vehicle and pedestrian movements, combined with its 360-degree coverage and high spatial resolution, facilitates accurate detection and tracking of potential conflict scenarios, contributing to enhanced intersection safety and traffic management efficiency. This study endeavored to conduct a traffic safety analysis during work zone intervals at a signalized intersection in Baltimore City, known for its high rate of traffic crashes, utilizing LiDAR sensor technology.

Sorghum grain processing can improve the nutritional content by promoting dietary properties that contribute to food security and economic development. The quality, nutritional content, and processing properties of sorghum bicolor grain can greatly affected by the inbred line races and variance in pericarp colour.The current study assessed the influence of the Husking Fraction Time Units (HFTU) process, which employed set time units per second (S), on the variation in the nutritional profile of fifty-one inbred line sorghum varieties based on distinct pericarp colours. When the assessment of the nutritional profile was involved: dry matter, total protein besides, namely mineral (P, K, S, Ca, Mg, Na, Fe, Zn, and Mn). The variety groups showed a significance value of (P < 0.05), indicating the study hypothesis's truth.The results demonstrated substantial impacts implied by the Husking Fraction Time Unit (HFTU) technique. This occurrence was noted when the dry matter percentage was increased in the husked products, specifically the endosperm (grits) and bran. The protein percentage redistributed by 19.2% compared to the whole grain and bran content. In comparison, the ratio of N/S was 14:1 in the S. bicolor and 12:1 in the kafirin in the bran part. Moreover, a strong correlation was observed among the examined minerals of S.bicolor and kafirin, such as the correlation between Ca: P, K: Na, and Fe: Zn attributed 80 (S) time unit, with correlation coefficients of R = 0.784 and R = 0.586, R= 517, R= 0.884, R= 0.745, and R = 0.893, respectively. At the same time, the 80 (S) time unit showed a significant effect on the colour property profile.The study results could benefit breeders and nutrition specialists in developing genotypes and processing sorghum grains, promoting research, and aiding several industrial sectors owing to the grain's adaptability and nutritional properties.

Remote sensing technologies may play a fundamental role in the environmental assessment of open-cast mining and the accurate quantification of mine land rehabilitation efforts. Here, we developed a systematic geographic object-based image analysis (GEOBIA) approach to map the amount of revegetated area and to quantify the land-use changes in open-cast mines in the Carajás region situated in the eastern Amazon. Based on high-resolution satellite images from 2011 to 2015 from different sensors (GeoEye, WorldView-3 and Ikonos), we quantified forests, cangas (natural metalliferous savanna ecosystems), mine land, revegetated areas and water bodies. Based on the GEOBIA approach, threshold values were established to discriminate land cover classes using spectral bands, and the NDVI and NDWI indices and LiDAR digital ground and slope models. The overall accuracy was higher than 90%, and the Kappa indices varied between 0.82 and 0.88. During the observation period, the mining complex expanded; for that, canga and forest vegetation was converted to mine land. At the same time, the amount of revegetated area increased. Thus, we conclude that our approach is capable of providing consistent information regarding land cover changes in mines, with a special focus on the amount of revegetation necessary to fulfill environmental liabilities.

To understand how the thinning strategies impacts on wood quality and quantity for different purposes is of interest, considering that the management of plantations is carried out with parameters that have yet to be validated for different growth conditions. This work evaluated contrasting thinning regimes applied early at two moments of the crop cycle. With an initial population of 840 trees.ha-1, two thinning with populations ranging from 700 to 400, and from 400 to 100 trees.ha-1 were applied at 1.5 and 7.3 years, respectively. Growth analyses were carried out from the ages of 1.5 to 20.8 years considering: total height, diameter at breast height, individual volume, total and commercial volume per hectare, mean annual increase and current annual increase. At final age, contrasting populations of 100, 250 and 400 trees.ha-1 were sampled to assess wood density, and mechanical properties (bending and compression on small scale clear samples). The values of individual growth and wood properties are related to a Stand Density Index to understand the effect of competition on those values. The results allow us to identify the thinning schemes that record the most significant individual and per-hectare growth (both in thinning and clear felling) and the optimal harvest time under specific growth conditions. We assessed the proportions of commercial logs for sawmill and pulp uses, providing valuable inputs for a subsequent economic analysis of thinning regimes seeking for the most convenient combination of wood products. Wood's physical and mechanical properties assessed were barely affected by contrasting levels of competition between trees, therefore the decision of the silvicultural system to implement will depend on production and economic criteria.

Pathogenicity of many bacteria including Bacillus cereus and Staphylococcus aureus depends on pore-forming toxins (PFTs), which cause lysis of host cells by forming pores in membranes of eukaryotic cells. Bioinformatic analysis revealed in over 600 PFTs a region homologous to the Lys171-Gly250 sequence in hemolysin II (HlyII) from B. cereus, which we designated as “homologous peptide”. Three β-barrel PFTs were used for a detailed comparative analysis. Two of them –HlyII and cytotoxin K2 (CytK2), – are synthesized in Bacillus cereus sensu lato; the third – S. aureus α-toxin (Hla) – is the most investigated representative of the family. Protein modeling showed certain amino acids of homologous peptide to be located on the surface of the monomeric forms of these β-barrel PFTs. We obtained monoclonal antibodies against both a cloned homologous peptide and a 14-membered synthetic peptide DSFNTFYGNQLFMK as part of homologous peptide. The HlyII, CytK2 and Hla regions recognized by the obtained antibodies, as well as an antibody capable of suppressing the hemolytic activity of CytK2, were identified in the course of the work. Antibodies capable of recognizing PFTs of various origins can be useful tools for both identification and suppression of the cytolytic activity of PFTs.

In this paper, a distinction is first made between environmental, sustainable and green chemistry; the last two are then examined in relation to the more general problem of the environmental education. A brief historical digression on the STS (Science, Technology and Society) movement tries to dissect the reasons why chemistry is seen by the general public as a problem, not as a decisive resource for the realization of the ecological transition. Although sustainable and green chemistry can be decisive in overcoming the insularity of chemical disciplines in the high school, it fails to effectively embed itself in educational practices. Specific operational goals, supporting a real scientifical and technological literacy in sustainable and green chemistry, can help chemical educators. They are provided at the end of an examination of the founding axes of sustainable and green chemistry, according to the criteria of scientific and technological literacy.

Ecological corridors function as a viable way to mitigate the environmental impact arising from forest fragmentation by interconnecting forest fragments through various techniques. In this context, the objective of this study is to propose a route for the implementation of an ecological corridor in the Itapemirim river watershed. The specific objectives were: (i) to delimit the permanent preservation areas (APP) of the Itapemirim river watershed and compare land use and land cover in the delimited areas; (ii) to calculate landscape ecology indices and select the forest fragments with the highest potential for ecological corridor implementation using Fuzzy logic; (iii) to assess costs and trace the best route for ecological corridor implementation, considering distance and physical impediments; (iv) to assess land costs and expropriation costs to delimit the ecological corridor in the study area. To map land use and land cover, the MapBiomas platform was used, based on Landsat 8 satellite images. The permanent preservation areas were delimited according to criteria established by Law No. 12.651 of May 25, 2012, which establishes parameters, definitions, and limits for APP. The characterization and structural quantification of some landscape ecology indices were performed using the QGIS 3.26 computational application, through the LecoS 3.0.1 plugin and Fragstats 4.2. The connected forest fragments were the Caparaó National Park, the Serra das Torres State Natural Monument, and the fragments selected through the application of Fuzzy logic to the landscape ecology indices. The corridor was delimited according to the lowest cost route, considering land use and land cover, APP, fragment potential, slope, and subnormal clusters. For each cost raster image, its respective statistical weights were calculated using the Analytic Hierarchy Process (AHP) hierarchical method, as well as for the analysis of priority areas for forest restoration, considering land use and land cover, APP, pedology, lithology, and biological importance. The interconnection between protected areas and fragments with the ecological corridor followed the orientation described by CONAMA nº 09/96. Based on the development of the work, the following results were identified: the highest land use and land cover class is pasture. Of the area designated for permanent preservation, 68.58% is in conflicting use with the legislation. The bare land value per hectare of the pasture class is the second highest among the bare land value per LULC values, representing 64.28% of the total. The priority area map showed that 31.86% of the area was classified as of very high or high importance and 42.97% as low or very low priority for forest restoration. Thus, it is concluded that the least cost path algorithm associated with the result generated by the multi-criteria decision method (AHP) constitutes an important tool for planning and implementing an ecological network by taking into account the primary factors for decision-making regarding the location of the best route.

This study examines the dynamic relationship between Green Human Resource Management (Green HRM), Environmental Performance (EP), Green Employee Behavior (GEB), and Environmental Knowledge and Awareness (EKAW) within the Egyptian hospitality sector context. Using Pearson correlation coefficients and regression analyses on a sample of 400 staff members from hotels and tourist villages in Egypt, the study examines Green HRM practices’ influence on EP, mediated by GEB and moderated by EKAW. The findings reveal significant positive correlations between Green HRM practices and these mediators, indicating that comprehensive environmental strategies and incentive management are pivotal in promoting eco-friendly practices among employees. The study further confirms GEB and EKAW’s substantial mediating role in enhancing EP. The results also suggest that while EKAW and GEB independently contribute to EP, their interaction and the role of environmental awareness as a potential moderator warrant further examination. This research contributes to the literature on sustainable business practices by underscoring human resource strategies’ integral role in achieving environmental sustainability goals, highlighting the importance of incentivizing green practices, and cultivating an organizational culture that prioritizes EKAW. These insights are particularly valuable for organizations seeking to enhance their ecological footprint through effective Green HRM practices.

The global textile sector, pivotal to economic development, significantly contributes to environmental degradation, prompting a shift towards sustainable raw material sources. Embracing circular economy principles, this industry is exploring the valorization of agricultural by-products. This study introduces an innovative approach to repurposing mango waste into valuable textile fibers, a byproduct of the fruit processing industry, predominantly generated during juice and jam production. The focus is on the lignocellulosic constituents of mango waste, specifically the peel, seed, and fibrous material, traditionally considered as refuse. Previous research has predominantly utilized mango peel in pectin extraction for food applications, whereas the potential of seed and fibrous content remains underexplored. This investigation endeavors to transform these fibrous by-products into high-value materials suitable for textile manufacturing. The process involved washing, drying, and comprehensive physicochemical characterization of mango fibers, emphasizing lignin quantification, revealing a composition of 12.2% lignin. An experimental design was employed to elucidate the impact of variables such as liquid-to-solid ratio, reaction duration, and sodium hydroxide concentration on lignin dissolution through alkaline hydrolysis. Optimal conditions—10% NaOH concentration, 30 mL/g liquid-to-solid ratio over six hours—achieved an 83% reduction in lignin content. The resulting fibers exhibited properties akin to conventional natural fibers, including a favorable aspect ratio indicative of their suitability for textile applications. A subsequent softening process using propylene glycol enhanced the fibers' spinability, producing a durable, textured fabric ideal for eco-conscious fashion applications, including bags, footwear, and accessories. This research demonstrates the feasibility of converting mango waste into a textile-worthy material and underscores the importance of waste revalorization in promoting sustainability within the circular economy framework.

As the world’s second largest economy, China ranks amount the world’s top nations when it comes to carbon emission, and therefore its attitude towards climate change is closely followed by all parties concerned. There have been few researches on the role of environmental governance in low-carbon city transformation process, especially the Chinese one. This paper analyses the role of government environmental regulation played in the low-carbon city transformation process by taking Shenzhen as the research object. One of the world's youngest super cities, it also happens to be the lowest carbon emission intensity city in China. Striving to explore green low-carbon development path for the whole country, Shenzhen provides practical experience for countries to cope with global climate change. However, its efforts to reduce the total carbon emissions failed, but it emphasized the carbon emission intensity, which is consistent with the international commitments made by the central government. China’s policy towards handling climate change relies on hierarchical governance arrangement. The strength of the NGOs in the country is weak and incomparable with the government’s, which has mastered most of the resources and is just a reality in China.

The pollution of the bays in Abidjan is a major concern for the Ivorian policy makers. In fact, the pollution of the bays induce high costs to the society while impacting population health dramatically. As a result, pollution reduction management of production activities has been undertaken in the Cocody Bay area. To our knowledge, no study has yet proposed a model to evaluate the cost-effectiveness of these pollution management strategies. A cost-effectiveness model, based on Monte Carlo simulation, was developed to assess the economic and environmental impacts of various scenarios characterized by a set of production practices, both in the short term and in the long term. The authors discuss the steps and input parameters of the model presented. The proposed model may serve as the basis for identifying an optimal production scenario defined as the scenario with the best incremental cost-effectiveness ratio considering a willingness to pay (WTP) threshold. The WTP, to be estimated based on the gross domestic product of Côte d’Ivoire, represents the opportunity costs associated with selecting the optimal scenario. The current framework can also be applied to other settings facing similar challenge.

Air quality is a topic of growing relevance on the global agenda. Two key indicators of air quali-ty, nitrogen dioxide (NO2) and carbon monoxide (CO), represent significant hazards to human health and the environment putting the sustainability of natural resources at risk. Therefore, it is imperative to regularly monitor and reduce atmospheric pollutant concentrations to mitigate their harmful consequences. This study presents an analysis of NO2 total and CO emissions in Argentina, utilizing remote sensing data. The research aims to determine the spatiotemporal distribution of NO2 and CO emissions in Argentina from 2019 to 2021. Subsequently, it seeks to establish the influence of land uses and land cover on the emission of NO2 and CO through dif-ferent climatic, anthropic, and natural indicators. The study was carried out in Argentina during the period 2019-2021, where random points were placed for the different land covers with a total of 800 points surveyed. The year with the highest CO concentration (mol/m-2) was 2020. The values were highest for tree covers and herbaceous wetland coverage in the northern part of the country. For total NO2, the highest concentrations were reached during the years 2020 and 2021. Regarding its distribution, throughout the evaluated period, the highest concentrations of total NO2 were found in the built-up and cropland coverages, with the capital of the country and the northern region of the Buenos Aires province being the most affected areas. In addition, the concentration of CO was influenced by climatic variables (atmospheric pressure, wind speed, maximum environment temperature, Palmer index), natural (height, humidity, NDVI), and ur-ban variables (distances to mining extraction, airports, power plants, urban index) for the differ-ent uses and land covers. Finally, the concentrations of total NO2 were influenced by climatic variables (Palmer index and wind speed), natural (height and NDVI), and urban variables (dis-tance to airports, power plants, industries, service stations, and open dumpsites) for the differ-ent uses and land cover. This study contributes to sustainable environmental management, ena-bling the formulation of effective strategies for mitigating emissions and promoting the long-term health and well-being of communities.

Snow is a vital environmental parameter and dynamically responsive to climate change, particularly in mountainous regions. Snow cover can be monitored at variable spatial scales using Earth Observation (EO) data. Long-lasting remote sensing missions enable the generation of multi-decadal time series and thus the detection of long-term trends. However, there have been few attempts to use these to model future snow cover dynamics. In this study, we therefore explore the potential of such time series to forecast the Snow Line Elevation (SLE) in the European Alps. We generate monthly SLE time series from the entire Landsat archive (1985-2021) in 43 Alpine catchments. Positive long-term SLE change rates are detected, with the highest rates (5-8 m/y) in the Western and Central Alps. We utilize this SLE dataset to implement and evaluate seven uni-variate time series modeling and forecasting approaches. The best results were achieved by Random Forests, with a Nash-Sutcliffe efficiency (NSE) of 0.79 and a Mean Absolut Error (MAE) of 258 m, Telescope (0.76, 268 m), and seasonal ARIMA (0.75, 270 m). Since the model performance varies strongly with the input data, we developed a Combined forecast based on the best performing methods in each catchment. This approach was then used to forecast the SLE for the years 2022-2029. In the majority of the catchments the shift of the forecast median SLE level retained the sign of the long-term trend. In cases where a deviating SLE dynamic is forecast a discussion based on the unique properties of the catchment and past SLE dynamics is required. In the future, we expect major improvements in our SLE forecasting efforts by including external predictor variables in a multi-variate modeling approach.

In August 4 2011, United Nations Environmental Program (UNEP) submitted an unprecedented, scientific, groundbreaking Environmental Assessment Report (EAR) of Ogoniland, to the Nigerian government. This was the outcome of a 14–month intensive evaluation of the extent of pollution. It was intended that UNEP’s recommendations would be implemented to restore the devastated environment, on the one hand, and on the other, counteract the numerous environmental health issues that have for decades, plagued Ogoniland. However, five years post EAR, and, despite the seriousness of the situation, no significant resolution has occurred, both on the part of the government, and on the part of Shell Petroleum Development Company (SPDC) or Shell. To date, millions of Niger Delta residents, particularly those living in the oil-bearing communities, continue to suffer severe consequences. Although, the assessment was conducted in Ogoniland, other communities in the Niger Delta are also affected. This article explores prevailing issues, using Ogoniland (a microcosm of the Niger Delta) as an example. A multidisciplinary approach for sustainable mitigation of environmental health risks in the Niger Delta is paramount, and Environmental Management tools offer valuable strategies. Adopting UNEP’s recommendations for addressing environmental health problems requires implementing the Environmental Management/Environmental Management System (EM/EMS) model.

In the former mining district of La Carolina (southern Spain), waste materials were accumulated without first waterproofing the substrate. Additionally, these mining dams were abandoned without any type of restoration, conditions that present a significant risk of contaminating the surrounding soils and waters. Prior to carry out the necessary works for isolating these residues, morphological characterization of the contact with the base substrate is needed. For that purpose, in recent years, different indirect study techniques have been used, among which electrical to-mography stands out. In this work, a less common geophysical technique, magnetometry, both in its magnetic and gra-diometric modalities, is used as an alternative method to analyse the geometry and structure of a mining dam. The results obtained with this methodology are compared with the results provided by electrical techniques, as well as with direct data from mechanical surveys and aerial photo-graphs prior to waste deposition. The magnetic anomaly curves obtained with geometric models generated with the Mag2dc program were also analysed. This comparative study shows the use-fulness of magnetic prospecting in characterizing the base geometry of these mining structures and therefore the interest in its application to environmental characterization studies.

Gelatin industry residues are increasingly used as fertilizer and soil conditioner. However, correct residue dosage is critical for grass development and minimizing environmental impacts. This randomized block design study determined adequate dosage of Mixed Gelatin Sludge (MGS) for Marandu grass production in wet/dry seasons in Brazil. Five MGS levels (0%–200% of required nitrogen) were compared to mineral fertilizer. Agronomic/productivity characteristics, bromatological composition, macro/micro-nutrient composition of leaves, and soil chemical attributes were evaluated. Agronomic/productivity characteristics were influenced by MGS dose in both dry/rainy seasons, except for leaf blade pseudostem ratio and percentage of leaves/pseudostem. Bromatological composition was influenced by MGS doses in dry/rainy seasons except for dry/mineral material quantities. Marandu leaf tissue chemical composition was significantly influenced by MGS dose, except for potassium, boron, and iron. Chemical composition of four soil layers between 0–50 cm influenced GMS dose, except for pH, organic matter, magnesium, copper, manganese, and zinc. GMS dose for Marandu production should be 200% of nitrogen (N) requirement. GMS application increased productivity/quality of Marandu grass. Macronutrients (N, phosphorus) and micronutrients (Ca, Mg, S, Cu, and Zn) increased in Marandu grass and in the soil (Ca, S, and Na). Increased sodium (Na) level was not limiting.

This research explores and analyzes the challenges and opportunities due to globalization's impact on sustainable strategic management. The research uses a mixed-method design, combining primary and secondary data collection methods. Secondary data is sourced from various credible publications and analyzed through an extensive literature review. A case study approach is adopted, involving semi-structured interviews with six experienced managers from Tazweed Venture Capital in Jordan. The study employs a qualitative, descriptive, and analytical approach to develop a conceptual framework by exploring managers' experiences and perspectives on Globalization and its impact on Sustainable Strategic Management. The findings identify challenges of environmental degradation, economic inequality, transportation and logistics pressures, and compliance challenges for sustainability. While implementing sustainable practices incurs upfront costs, accessing renewable energy markets and financial support presents opportunities. Tazweed successfully implements sustainable strategic management, emphasizing stakeholder engagement and collaboration across departments. This research offers valuable insights and guidance for companies navigating globalization's impact on sustainability strategic management.

Background: Waterborne diseases pose a significant global public health threat, compelling enhanced comprehensive surveillance. This study investigates the current infectious disease and antimicrobial resistance (AMR) surveillance systems, including wastewater and environmental surveillance (WES), in three sub-Saharan African countries: Tanzania, Burkina Faso, and the Democratic Republic of the Congo (DRC). The three countries have their specificities regarding wastewater networks and logistic systems. So, emphasizing the need to strengthen existing disease surveillance, the paper advocates for incorporating WES systems specifically designed for countries' context to monitor waterborne and re-emerging pathogens, as well as AMR.Methods: National workshops were conducted to assess the current clinical and environmental surveillance systems and identify priority pathogens for new environmental monitoring. Data were collected through surveys from experts in academia, research, policy, and healthcare. Results: Prioritized pathogens for WES include waterborne (poliovirus, Salmonella Typhi, Vibrio cholerae), respiratory (influenza A&B, SARS-CoV-2), other (Measles and Rubella, Mycobacterium tuberculosis). Recommended AMR pathogens include drug-resistant Mycobacterium tuberculosis, Salmonella spp., methicillin-resistant Staphylococcus aureus, and extended-spectrum beta-lactamase and carbapenemase-producing E. coli. Tanzania, Burkina Faso, and the DRC employ DHSI2-based centralized electronic systems for clinical data collection, complemented by Excel and paper-based registries. The WES approach is commonly employed for monitoring poliovirus and rarely for AMR and other pathogens. Discussion and conclusions: WES is a valuable tool for early detection of locally circulating human-derived pathogens, aiding in outbreak detection, data-driven epidemic response, and prevention. The availability of WES results underscores the importance of effective sanitation for safeguarding human, animal, and environmental health. WES is a pivotal tool for integrated risk management, preventing waterborne outbreaks, protecting drinking water sources, and ultimately gaining various UN Sustainable Development Goals. The study highlights the importance of customized WES systems in line with each country's context, emphasizing localized approaches for effective monitoring of waterborne pathogens and AMR.

Improving the level of farmers' participation in collective action is an important way to promote rural revitalization and improve the sustainable livelihood level of farmers in underdeveloped areas. Based on 312 questionnaires of farmers in Shanxi Province, this paper investigates the status of farmers' participation in collective action, their sustainable livelihood level and the sustainable livelihood effect of collective action participation. The results show that: farmers' willingness to participate in collective action is strong, and the participation effect is obvious, but the participation frequency is low, and the participation time is less; The farmers' sustainable livelihood level is relatively low, Empirical research shows that the level of collective action participation will have a significant positive impact on Farmers' livelihood risk prevention, livelihood capital accumulation, livelihood mode selection and livelihood income improvement, and the frequency, time and value perception of participation in collective action will have varying degrees of impact on Farmers' sustainable livelihoods. In order to promote farmers' active participation in collective action, it is proposed to strengthen the construction of collective organizations Provide incentives and improve the quality and skills of farmers to enhance the collective concept and other policy recommendations.

This study analyses the changes in land use in the Sado estuary (West-Central Portugal) based on a multitemporal analysis of cartographic data from the 19th century and remote sensing land use maps from the 21st century, updated by field work. A GIS plotting of land-use evolution is summarized in a quantitative table. The comparison shows the changes in land use, with increasing occupation by human economic activities, including extensive agriculture and forestry, as well as localized urbanization and industrialization. The main elements of the landscape impacted by anthropogenic uses were: i) hydrography - river dams affected the flow dynamics and sedimentary processes in the estuary; ii) vegetation – increasing agriculture and forestry reduced the areas of native vegetation, nowadays mostly occupied by vineyards, pine forests and cork oaks. iii) wetlands - tidal and alluvial plains are being occupied by rice cultivation, aquaculture, industries, and ports; iv) coastal dunes – new developments are occupying large areas of Holocene coastal dunes; v) natural environment – mining and dredging affected some habitats and biodiversity. This analysis is intended to help the territorial organization of present and future economic activities, as well as to reduce environmental and social problems, promoting long-term sustainability of this rapidly evolving region.

We are experiencing an unprecedented urbanization process that alongside with physical, social and economic developments is having a significant impact on population’s health. Due to higher apprehensions of pollution, violence and poverty, our modern cities no longer ensure a good quality of life so they become unhealthy environments. This study aims to measure the socio-environmental and hematologic profile of residents of Santo André’s landfill – “Bairro Espírito Santo” by using the contextualization of the studied area. The research method is Observational type and from Retrospective cohort and by convenience sampling in Santo André in the Greater ABC region. The study determined a socio environmental profile and the hematologic diseases screening related to a close location to the landfill. The disease manifests itself within a broad spectrum of symptoms that causes changes in blood count parameters. The full blood counts analysis was performed, indicating that the blood counts of residents living near the landfill led to positive hematological changes and diseases like Leukopenia, Anemia, Neutropenia and lymphocytosis were the most common changes. However it is considered that the proof of the relation of cause- effect to environmental exposures that may trigger chronic manifestations in humans requires specific studies that are often complicated.

Diesel contamination of farming soils is of great concern because hydrocarbons are toxic to all forms of life and can potentially enter the food web through crops or plants used for remediation. Data on plant ability to uptake, translocate and accumulate diesel-derived compounds are controversial not only due to the probable diverse attitude of plant species but also because of the lack of a reliable method to distinguish petrogenic from biogenic compounds in plant tissues. The purpose of this study was to set up a GC-MS-based protocol enabling the determination of diesel-derived hydrocarbons in plants grown in contaminated soil for assessing human and ecological risks, predicting phytoremediation effectiveness and biomass disposal. To this aim two plant species Vicia sativa L. and Secale cereale L., belonging to two diverse vascular plant families, were used as plant models. They were grown in soil spiked with increasing concentrations of diesel fuel and the produced biomass was used to set up the hydrocarbon extraction and GC-MSD analysis. The developed protocol was also applied to the analysis of Typha latifolia L. plants, belonging to a different botanical family and grown in a long-time and highly contaminated natural soil. Results showed the possibility of distinguishing diesel-derived compounds from biogenic hydrocarbons in most terrestrial vascular plants, just considering the total diesel compounds in the n-alkanes carbon range C10-C26, where the interference of biogenic compounds is negligible. Diesel hydrocarbons quantification in plant tissues was strongly correlated (0.92<r2<0.99) to the concentration of diesel in spiked soils, suggesting a general ability of the considered plant species to adsorb and translocate relative low amounts of diesel hydrocarbons and the reliability of the developed protocol.

This review explores the transformative impact of sensor technologies in early disease detection. It highlights recent advancements in nanotechnology-based sensors, particularly focusing on their applications in identifying disease biomarkers at early stages. The integration of these sensors with artificial intelligence for predictive analytics in healthcare is also discussed. Applications in cancer, infectious diseases, and chronic disease management underscore their diverse utility. Challenges in sensor technology adoption and future directions, including multiplexed sensors and wearable devices, are examined. This review underscores sensors' potential in enhancing disease management and patient outcomes.

By introducing environmental mediator, for avoiding randomness in selecting indicators and subjectivity in deciding interaction path coefficients to reveal interaction mechanism among forest industry, ecology and environmental capacity, structural Pressure–State–Impact–Response (PSIR) and quantitative Structural Equation Modeling (SEM) are utilized with data on thirty–one provinces of China. We can find that: (i) forest industry has a negative influence on ecology, whereas ecology has a positive influence on industry; (ii) the destructive influence that industry has on ecology is much greater than the positive effect ecology has on industry; and (iii) environmental capacity plays a partial mediating role between industry and ecology. According to these results we can conclude that: (i) forest industry and ecology are not in a symbiotic relationship and have not reached a level of ecological security; (ii) the interaction between industry and ecology is in a period of transition from antagonistic to beneficial; and (iii) industry dominates ecology. However, we prospect the following advice: (i) methods of forest industry should be changed; (ii) new modes of industrial integration and circular economy should be developed; and (iii) the ability of the environment to sustain itself should be enhanced. The level of forest ecological security to discuss the symbiotic mechanism of industry and ecology will propose to be measured in future.

Global warming, exacerbated by greenhouse gas emissions from non-green product manufacturing, necessitates a shift towards green production to safeguard ecosystems and finite resources. The United Nations Environment Programme emphasizes the importance of environmental considerations in corporate ESG criteria. Despite the higher costs of designing and manufacturing green products, which deter some companies and lead to greenwashing, efforts persist to promote sustainable goods. This study explores enhancing consumer repurchase intentions for green products through social media marketing, emphasizing green values, environmental concerns, brand image, and involvement. Findings reveal social media's role in boosting these factors, thus encouraging green repurchases. Insights are valuable for green businesses, social media groups, environmental agencies, and future research.

Smart manufacturing encompasses a category of manufacturing that employs computer-integrated capabilities and technologies to enhance supply chain optimization, production efficiency, and recyclability. Yet limited studies have been conducted to optimize these prospects from the perspective of low resource countries where such innovative studies have not been adequately explored. This paper aims to examine the implications of smart manufacturing practices (Smart Procurement, Smart Supply Chain, Smart Production Planning and Control, Automation and Industrial Robot, and Supply Chain Configuration) on pro-environmental behaviour and develop a baseline moderated mediation model to explain the relationship between smart manufacturing and pro-environmental behaviour with a role of green dynamic capability, and environmental orientation. This study is anchored on quantitative research approach, deductive reasoning, and explanatory design. Cross – sectional survey data have been obtained from 382 manufacturing companies in Ghana. Our hypotheses have been tested using Structural Equation Modelling and SMART-PLS version 3.8.9. The study has revealed that smart manufacturing practices significantly and positively relate to pro-environmental behaviour. Moreover, green dynamic capability and environmental orientation moderate the relationship between smart manufacturing and pro-environmental behaviour. The implications of the study include the emergence of a baseline model to guide policymakers, practitioners, and academicians to explain the relationship between smart manufacturing and sustainable manufacturing in the context of developing countries. Again, the social implication of the study includes the realisation of decent job and economic growth, responsible consumption and production as well as actions taken to combat climate change.

The aim of this paper is to study changes in land use and the evolution of vegetation in Cacheu River Mangroves Natural Park in the Republic of Guinea-Bissau. To do this, we will study variations in the NDVI, Normalized Difference Vegetation Index. In order to perform the calculations and subsequent analysis, images from three years— 2010, and 2017—were used, all corresponding to the same time of year so that the phenological stage is the same. To perform a more reliable analysis, the park was divided into five classes based on the main use of the land: mangals, palm forest, paddy fields, savannahs and others. Using a statistical sample, same areas were selected for each class and the corresponding NDVIs were calculated for the years in which ASTER images were available. The study made it possible to conclude that at present, management of the park is not the most suitable, given that the changes in land use observed represent a decrease in mangrove swamps, despite the fact that these forests constitute the most important ecological area of all those that make up the park. Mangals are being replaced by other land uses.

Given the context of global climate change, a worldwide increase in land surface temperature (LST) is anticipated, leading to the exacerbation and broadening of its impacts. This could jeopardize the environmental conditions in countries with a predominantly hot and harsh climate, such as Bahrain, one of the Cooperation Countries (GCC) nations. Conversely, Bahrain is currently experiencing significant population growth, leading to a surge in demand for land to accommodate the construction of additional residential developments. This circumstance allows investigation of the potential impact of land use and land cover alterations on the variation in Land Surface Temperature (LST). In order to accomplish this objective, a residential development project was executed within the timeframe spanning from 2013 to 2023. Four sets of Landsat 8 OLI/TIRS remote sensing datasets were selected, with each set corresponding to one of the four climate seasons. Each set consisted of two images: one capturing the study area before the commencement of the development process and the other depicting the study area after the completion of the development. The study area was analyzed by extracting the land surface temperature (LST), normalized difference vegetation index (NDVI), and normalized difference built-up index (NDBI) on various dates. Subsequently, correlation and regression analysis were employed to examine the interrelationships among these three variables. The findings demonstrated a notable rise in the mean land surface temperature throughout the spring and autumn seasons following the conclusion of land development activities. The findings indicate a positive and robust association between LST and NDBI across all seasons. Moreover, this relationship strengthened following the completion of development activities in the area. Conversely, there was a negative correlation between LST and NDVI prior to the region's development, which transformed into a positive relationship post-development. These results provide empirical support for the notion that small-scale residential developments contribute to a notable increase in LST, primarily driven by the expansion of impervious surfaces in built-up areas. The findings can potentially contribute to the formulation of localized adaptation strategies for small-scale residential development projects.

Pollutants accumulate in aquatic habitats as a result of mining activities. Lemna gibba and Lemna minor were used in this study to examine the accumulation capacities of Mo+, Pb+, and Cu++ in the acid fluids of the copper mining. Duckweed family includes water plants like L. minor and L. gibba. These are tiny, delicate, free-floating aquatic plants. Two reactors were assigned to L. gibba and L. minor, respectively. Throughout the course of eight days, these plants and reactor water were gathered every day. The acid mine water's pH, temperature, and electric conductivity were also tested every day. The L. gibba and L. minor were cleaned, dehydrated, and burned in a drying oven for a whole day at 300 oC. ICP-MS (Inductively Coupled Plasma Mass Spectroscopy) was used to determine the Mo+, Pb+, and Cu++ content of the plant and water samples. The concentrations of Mo, Pb, and Cu in the acid mine fluids of the copper mining were 30±4, 260±12, and 15535±322 μg L−1, respectively.in that order. When it came to extracting Mo, Pb, and Cu from the acidic fluids of the copper mining, L. gibba and L. minor performed well and efficiently compared to control samples; they did so 29 and 177 times for Mo, 30 and 109 times for Pb, and 495 and 1150 times for Cu. Considering all these findings, it has been shown that L. gibba and L. minor have the ability to efficiently remove Mo, Pb and Cu in acid mine fluids and can be good rehabilitation plants for polluted waters.

Despite being stored at 113 K and atmospheric pressure, LNG cold potential is not exploited to reduce green ships’ energy needs. An innovative system based on three Organic Ranking Cycles integrated into the regasification equipment is proposed to produce additional power and recover cooling energy from condensers. A first-law analysis identified ethylene and ethane as suitable working fluids for the first and the second ORC making available freshwater and ice. Propane, ammonia and propylene could be arbitrarily employed in the third ORC for air-conditioning. An environmental analysis that combines exergy efficiency, ecological indices and hazard aspects for marine environment and ship’s passengers, indicated propylene as safer and more environmentally friendly. The exergy analysis confirms more than 20% of the LNG potential can be recovered from every cycle to produce a net clean power of 76 kW, whereas 270 kW can be saved by recovering condensers' cooling power to satisfy some ship needs. Assuming the sailing mode, a limitation of 162 kg in LNG consumptions was determined, avoiding the emission of 1584 kg of CO2 per day. Marine thermal pollution is reduced by 3.5 times by recovering the working fluids' condensation heat for the LNG pre-heating.

Is it true that the nuclear technology applied to electric energy generation offers a clean, safe, reliable and affordable i.e. sustainable alternative? Yes it is, but its impact on the environment strongly depends on the implementation bearing residual risks due to a human factor, technical failures or natural catastrophes. A full response is therefore difficult and can first be given when the wicked multi-disciplinary problems get well formulated and “solved”. These problems have multi-dimensional nature lying at the interface between: necessary R&D effort, the industrial deployment and the technology impact in view of the environmental sustainability including the management of produced hazardous waste. This enormous complexity indicates that just a description of the problem might represent a problem. The paper proposes a holistic approach to assess the nuclear energy systems potential with respect to sustainable performance applying Multi-criteria decision analysis with a suitable objective tree and a multi-level criteria structure and examines the trading-off techniques for ranking of the alternatives. The framework proposes a multi-criteria and multi-stakeholders treatment which can be used as a pre-decisional support towards an implementation of nuclear fuel cycles adapted to national preferences and priorities. Proposed approach addresses some aspects of the environmental footprint of nuclear energy systems. Advanced nuclear fuel cycles, previously investigated by the NEA/OECD expert group WASTEMAN, are analyzed as a case study. Sustainability facets of waste management, resource utilization and economics are in focus.

Centrifugal pumps are widely employed in the oil refinery industry due to their efficiency and effectiveness in fluid transfer applications. The reliability of pumps plays a pivotal role in ensuring uninterrupted plant productivity and safe operations. Analysis of failure history data shows that bearings have been identified as critical components in oil refinery pump groups. However, traditional reliability estimation theories may not apply when data is limited or subject to right censoring. This paper addresses the complexity of estimating the Weibull distribution parameters using the maximum-likelihood method under the abovementioned conditions. The likelihood equation lacks an explicit analytical solution, necessitating the use of numerical methods for resolution. The proposed approach presented in this article leverages the Expectation-Maximization (EM) algorithm for estimating the Weibull distribution parameters. This method provides more accurate estimates of failure rates and probabilities by accounting for limited and censored data. The findings are demonstrated through a case study, showcasing the practical application of the proposed approach.

Aquaculture production is under pressure to increase its production to meet the growing demand for food from a growing population. In the Philippines, aquaculture has experienced the shift from milkfish to prawn with its attractive marketable price. Its intensification has led to negative and positive impacts making its collapse inevitable in the mid-1990s and raised a range of environmental and socioeconomic problems. This paper reviewed the environmental impacts, challenges, and disease outbreaks that overtook the industry using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method. We examined gaps and changes required to revitalize the industry to properly take-off. It considers and gives details on the impacts of shrimp culture on the environment e.g. shrimp farm management, marine pollution, disease outbreaks, climate change impacts, and socioeconomic impacts. Moreover, the presence of viral diseases such as White Spot Syndrome Virus (WSSV), Monodon Baculovirus (MBV), Infectious Hypodermal and Hematopoietic Necrosis Virus (IHHNV), Hepatopancreatic Parvovirus (HPV), and Yellow Head Virus (YHV), have caused socioeconomic impacts with approximate losses of 40,080 mt in 1997 to 51,000 mt in 2014 in the shrimp industry. Recommended strategies were considered to improve the environmental management of shrimp aquaculture, including disease management, and priorities that were highlighted for future research. This management relates to adopting good aquaculture practices on shrimp culture, proper environmental monitoring and sustainable practices at the farm level.

Accurate diagnosis for the 400 million people with rare diseases is critical for healthcare decisions, prognosis, understanding disease mechanisms, and identification of treatments. Despite advances in genome sequencing, barriers such as high interpretation costs, diagnostic expertise, throughput associated delays, and uncertain variant classifications persist, with demand exceeding capacity. Many variant classification methods focus narrowly on specific consequences, leading to the use of complex integrative pipelines that often overlook transcript variability and lack prediction transparency. To overcome these limitations, we introduce DITTO. This transparent, transcript-aware machine-learning method demonstrates superior overall performance in accuracy, recall, and precision when compared to existing tools. DITTO is publicly available at https://github.com/uab-cgds-worthey/DITTO

Factors responsible of species distribution were intensively investigated in the past, including response at different spatial scales. The aim of the present research is to review the most relevant factors explaining chironomid species distribution focusing to factors operating at different spatial scales, such as latitude, longitude, altitude, water temperature, dissolved oxygen, nutrients acting at regional, country, water basin extension. Data including chironomid species abundances from different lentic and lotic waters from Italy and other surrounding countries were analyzed with different multivariate methods: partial canonical correspondence analysis and multiple discriminant analysis. Spatial analysis included univariate Moran’I correlograms, multivariate Mantel correlograms and Moran’s Eigenvectors Maps (MEM) calculation. The results confirmed previous conclusions, that is habitat type including different running waters reaches (kryal, krenal, rhthral, potamal) and different lake types is the most significant factor in separating chironomid assemblages and spatial factors act only as indirect influencers..

Gut colonization by multidrug resistant organisms(MDROs) is a risk factor for bloodstream infections(BSI) in the early phase of Hematopoietic Stem Cell Transplantation(HSCT). We evaluated, in an exploratory study, the impact of Lactobacillus plantarum on modulation of the gut microbiome in HSCT patients colonized by MDROs. Participants were allocated to an intervention group(IG=22) who received capsules of L. plantarum(5x109 CFU) twice a day until the onset of neutropenia and a control group(CG=20). The V4 region of the 16S bacterial rRNA gene in 93 stool samples from a subset of 33 patients was sequenced(IG=20 and CG=13). Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) (PICRUSt2) program was used for prediction of metagenome functions. L. plantarum had an average 86%(±11%) drug-target engagement at 43(±29) days of consumption and it was safe, tolerable and associated with an increase in the abundance of the Lactobacillales(p=0.004). A significant increase of Lactococcus and reduction of Turicibacter(p<0.05) were identified on the second-week of L. plantarum use. Although Enterococcus abundance had a greater rise in the CG (p=0,07), there were no significant differences concerning the gram-negative MDROs. No serious adverse effects was reported in the IG. . We observed greater non-significant pyruvate fermentation to propanoate I (p=0.193) relative abundance in the IG comparing with CG. L. plantarum use was safe and tolerable by HSCT patients. Although it may have impact on Enterococcus abundance and reduction of Turicibacter, it has not showed impact on Gram-Negative MDRO abundance in MDRO gram-negative colonized HSCT patients.

The study is dedicated to analyzing the complex interaction between Artificial Intelligence (AI) and the Internet of Things (IoT) with institutional structures in the context of sustainable development. This work examines the impact of these technologies on economic and social development, identifying their potential advantages and risks. Methodologically, the research relies on information gathering and case study analysis, assessing the impact of technology in various domains, from smart cities to the manufacturing sector. The findings emphasize the necessity of integrating technological innovations into broader social and environmental initiatives, highlighting the importance of institutional transformations for achieving environmental sustainability.

Environmental legislation is moving towards global standards for ease of application and to impose sanctions and penalties when necessary, without compromising human health and biota. International environmental measures for control and monitoring of atmospheric air only monitor emissions of SO_x, NO_x, O₃, and Pb. In general, most research work in air pollution done using the analysis of elements in rainwater show analysis of trace metals such as Na, Mg, Zn, and Mn. In this work, trace metals in the rainwater at the city of Goiânia, capital of the State of Goiás, were analyzed. Goiânia is a large city set in a predominantly agricultural province located in central Brazil. Presence of trace metals in rainwater was detected, indicating atmospheric air pollution levels higher than occupational limits set by WHO.

The paper presents modelling of relationships between wind velocity distributions observed in Poland and technical requirements for wind power stations design. The wind velocities distributions for various locations in Poland are determined, and expressed in Weibull distribution parameters. Theoretical computations concerning the dependence of wind power station as function of wind speed and aire physical properties are presented. Conclusions important for design of power stations fitted to atmospheric conditions in Poland are given. Wind power plants have been an important source of electricity generation for many years.Wind power modelling with the use of wind speed is used to improve the accuracy of forecasts and analyses of the power production of wind farms.

In the decarbonization of the steel, cement, and chemical industry in Germany, green hydrogen is expected to play a crucial role. The utilization of green hydrogen in the production processes of said industries requires organizations to modify their business model, requiring sustainable business model innovation (SBMI). Numerous tools and frameworks that support organizations in the process of SBMI have been proposed in the literature in recent years. However, the applicability of these tools and frameworks for steel, cement, and chemical companies that intend to utilize green hydrogen to produce their goods remains unexplored. By conducting a systematic literature review on tools and frameworks for SBMI, a literature and practice review to identify and analyze existing green hydrogen projects of steel, cement, and chemical companies, and an evaluation of the identified tools and frameworks in an evaluation matrix, this paper aims to assess the suitability of SBMI tools and frameworks for steel, cement, and chemical companies that plan to use green hydrogen to produce their goods. Based on the evaluation, the Cambridge Business Model Innovation Process (CBMIP) was identified as the most suitable SBMI framework.

This comprehensive critical review shows how green buildings and energy optimization solutions improve indoor air quality as well as environmental quality (IEQ) and human health. Electricity-efficient green buildings create a better indoor atmosphere and save electricity. Green buildings improve occupant well-being through IAQ, thermal comfort, acoustics, and lighting. Renewable energy, green construction materials, and intelligent technologies increase sustainability and reduce environmental impact. Environmental hazards, architectural design, and societal variables can improve indoor air quality and subsequently reduce health risks linked with poor air quality. The evaluation highlights the pros and cons of low-cost IAQ sensors and equipment. These devices provide valuable insights, but calibration and validation using reference equipment are necessary to ensure accuracy and reliability. Architects, engineers, environmentalists, and policymakers are essential in creating green buildings with high IEQ. Prioritizing occupant comfort, health, and productivity ensures a sustainable and healthy future for future generations. However, continual monitoring and research are needed to improve green building practices and overcome construction problems. Intelligent models for continual on-field calibration of low-cost sensors may improve performance. Green buildings benefit occupants and the environment by optimizing energy use and using IAQ monitoring technologies.

The metaverse, a virtual world comprising a collective virtual shared space where users interact with one another through avatars and computer-generated objects, aims to closely mimic our real world by integrating elements of Artificial Intelligence (AI), immersive reality, advanced connectivity, and Web3. As metaverse technologies gain momentum across multiple sectors, including animal farming, their potential for addressing complex challenges such as climate change and sustainability in precision food production systems becomes increasingly apparent. However, it is crucial to consider the ethical implications and the role of sensor data and livestock behavior analysis in developing metaverse technologies for modern animal farming, given the sensitive and controversial nature of animal welfare. Failure to address these ethical considerations and harness the power of sensor data and behavior analysis could lead to a lack of credibility and insensitivity towards adopting metaverse technologies in the animal farming sector. It is essential to ensure that the development of metaverse technologies does not prioritize technology over animal welfare, ethics, socio-economic implications, and the potential for data-driven insights. Addressing diversity and equity in the context of animal farming and the metaverse is crucial to avoid perpetuating existing inequalities during the implementation of metaverse technologies. This groundbreaking paper ventures into unexplored territory, shedding light on the untapped potential of the metaverse for modern animal farming. While research on this topic is still in its infancy, we embark on a journey of visionary speculation, presenting a compelling technology forecast that envisions the extraordinary possibilities awaiting us in the future. By delving into the metaverse's transformative capabilities, we provide a glimpse into a world where animal farming transcends its traditional limitations and embraces a new era of efficiency, sustainability, and ethical practices.

Wetlands are one of the crucial natural resources. They provide invaluable biodiversity resources, aid in water quality improvement, support ground water recharge, help in moderating climate change and support flood control. Environment is in the other hand, where we live and something, we are very familiar with our day to day life. Geographic Information Systems (GIS), Remote Sensing and Global Positioning System (GPS) were a useful tool for wetland and environmental change analysis and to improve on the classification accuracy. This study investigates population and environmental change of Jarmet wetland and its surrounding area change analysis over the period of 1972 to 2015. The purpose of this study was to show land use/ land cover change of Jarmet wetland and its surrounding environment over years as a response to population growth. For this purpose, multi-temporal satellite imageries (Landsat MSS 1972, TM1986, ETM+ 2000, 2005 and 2015 and SRTM 2000) were obtained and used for LULC change analysis, elevation analysis and change detection analysis. ERDAS Imagine 2015, ARC GIS 10.5.1, Global Mapper11, ENVI 5.0 and DNR Garmin softwares were used to process the image data and accuracy assessment analysis. The result of LULC showed that there is spatial reduction in wetland, forest, Shrubland and grassland in the period of 43 years (1972-2015) by -1,722.8 ha, -296.2 ha, -1,718.7 ha and -661.9 ha respectively, due to increase in the farmland and plantation area as a response to overpopulation, lack of environmental policy implementation and irresponsible for natural resource degradation. The accuracy assessment of LULC change are done for recent satellite image showed the overall accuracy of 84.06% with Kappa index 75.19% this means this classification is accurately classified and handle greater than 75% of error. Finally, this study suggests that create strictly natural resource conservation law, stopping illegal expansion of farmland, educating society about the value of natural resource especially wetland and create a source of income for society rather than farming.

Morphological and phylogenetic (45S nrDNA+RPB1 gene) analyses of three glomoid spore-producing arbuscular mycorrhizal fungi revealed the presence of two new species be-longing to the genus Glomus in the family Glomeraceae. In the field, Glomus highlandensis sp. nov. was found in a saltmarsh of the Scottish Highlands and in maritime sand dunes of the Baltic Sea in Poland, both saline environments, while G. mongioie sp. nov. originates from the Italian Alps. Phylogenetic placement analysis using environmental sequences indicated that G. highlandensis could have likely worldwide distribution while G. mongioie seems to be a rare species in the world. The molecular and phylogenetic analysis provided important insights about the presence of ribosomal variants in Glomus, with potential negative implication in phylogeny and species recognition.

Water is one of the most critical factors affecting environmental health. For this reason, estimating and monitoring the behavior of water in nature and preventing water pollution before it occurs are advantageous to avoid problems that may occur in terms of environmental health. In order to predict the behavior of water, the hydrological cycle needs to be evaluated on a basin basis. At this point, hydrological models can be used to make mathematical representations of hydrologi-cal processes. These models play an essential role in predicting and monitoring problems such as poor water quality, pollution, particle and sediment transport, and proliferation of oil and petro-leum derivatives among frequently encountered issues in environmental health. In this study, a 2D surface water model was created using soil and water assessment tool (SWAT) to simulate the lotic ecosystem and existing water quality in Tatlıçay Basin and to propose solutions for im-proving environmental health in Cankiri provincial center in Türkiye. The accuracy of the input data and the validity of the model were checked with the calibration and validation studies by using the monthly or 3-monthly observation data of the General Directorate of State Hydraulic Works’ flow observation & water quality stations from 2016 to 2020. The aim was to provide the opportunity to produce fast, accurate, and practical solutions in the face of negative scenarios with this model. This modelling study obtained successful results in the calibration and valida-tion process with very few observed data. With this study, a significant contribution to the litera-ture on environmental health is made, as there aren't many examples of hydrological modeling from the Middle East.

The aim of this short communication is to find out the legal set up that complies with the environmental management in the textile sector of Bangladesh. This sector is the one of the biggest contributor to the economy of the nation. This sector contributes 81% to the total export earnings involving an immense number of stakeholders to its production processes. It is also true that this sector is largely responsible for the overall environmental pollution through its effluent discharge. The findings suggest that there are both international and national legal guidelines exist for environmental management in the said sector. In order to improve the environmental standards rehearsing lawful instruments is compulsory for the said industries.

Road traffic transportation has flourished in the process of urbanization by its advantages, but it also produces harmful environmental vibrations. The vibration problem is especially significant for production workshops with precision instruments. A field measurement was conducted to analyze the source characteristics and propagation laws of traffic-induced vibrations. Off the northern side of an urban highway lies a microelectronics workshop. When a large truck passes by, both the vibration responses on the ground and in the workshop considerably increase. Greater vibration is produced in the vertical direction than in the X and Y axes. The predominant frequency band of the vibration response caused by road traffic vehicles is lower than 20 Hz. The vertical vibration responses of the first and second floors in the workshop greatly exceed the VC-C limit because of the high daily traffic flow. Attribute to the excitation of the operation of the manufacturing equipment on the second floor, the vertical vibration level of the second floor is essentially higher than that of the first floor. Therefore, it is impossible to disregard the micro-vibration in the workplace produced by the manufacturing machinery as well as the ex-citement of the road traffic. The measured data can be used to test potential numerical models for forecasting vibrations caused by traffic on roads as well as to guide vibration assessment work throughout the planning and design stages of roads.

This article explores the cutting-edge advancement of gypsum and cement building boards infused with shape-stabilized n-octadecane, an organic phase change material (PCM). The primary focus is on improving energy efficiency and providing electromagnetic interference (EMI) shielding capabilities for contemporary buildings. The research investigates the integration of these materials into construction materials, using red-mud Carbon Foam as a stabilizer for n-octadecane (OD@CCF). Various analyses, including microstructural examination, porosity assessment, and additive dispersion, were conducted using X-ray microtomography and density measurements. Thermal conductivity measurements demonstrated the enhancement of composite boards as the OD@CCF content increased, while mechanical tests indicated an optimal additive content of up to 20%. The thermal-regulated capabilities of these advanced panels were evaluated in a custom-designed room model equipped with a homemade environmental chamber, illustrating a consistent temperature environment during heating and cooling cycles. The incorporation of OD@CCF into cement boards exhibited improved thermal energy storage properties. Moreover, the examined composite boards displayed efficient electromagnetic shielding performance within the frequency range of 3.2–7.0 GHz, achieving EMI values of approximately 18 and 19.5 dB for gypsum and cement boards, respectively, meeting the entry-level value required for commercial applications.

Sensor networks, as a special subtype of wireless networks, consist of sets of wirelessly connected sensor nodes often placed in hard-to-reach environments. Therefore, it is expected that sensor nodes will not be powered from the power grid. Instead, sensor nodes have their own power sources, the replacement of which is often impractical and requires additional costs, so it is necessary to ensure minimum energy consumption. For that reason, the energy efficiency of wireless sensor networks used for monitoring environmental parameters is essential, especially in remote networking scenarios. In this paper, an overview of the latest research progress on wireless sensor networks based on LoRa was provided. Furthermore, the analyses of the energy consumption of sensor nodes used in agriculture to observe environmental parameters were carried out. Optimization methods of energy consumption, in terms of choosing the appropriate data collection processes, as well as the settings of wireless network radio parameters were suggested. In the conducted analyses, special emphasis was placed on choosing the optimal package size. In this paper, it was proven that the adjustment of the transmission speed to the actual size of the packet is important for better energy efficiency of communication.

Natural radioactivity of 238U, 232Th and 40K for liquid and solid samples collected from Sidi Salem dam (Tunisia) and Aïn Dalia dam (Algeria) were measured using TERRA detector of rays (gam-ma, beta, and alpha), Atomic adsorption and Gamma-ray spectrometry were used to analyze the levels of radionuclides and toxic heavy metals, respectively. Toxic heavy metals (Fe, Bb, Zn, Ni, Cu, Cr and Cd) and associated health risks in surface water and sediment of dams have been in-vestigated in this present study. The radioactivity mean rates in the water samples were 1.72±0.01, 0.068±0.01 and 94.6±1.04 Bql-1 for 238U, 232Th and 40K respectively (Tunisia dam) and were 1.9± 0.24, 0.09±0.01 and 131.43±1.03 Bql-1 for 238U, 232Th and 40K respectively (Algeria dam). The 238U, 232Th and 40K radioactivity mean concentration measured in the sediment samples were 2.67±0.01, 0.18±0.012 and 197.87±2.01 Bqkg-1 respectively (Tunisian dam) and were 4.34±0.05, 0.27±0.05 and 287.61±3.34 Bqkg-1 respectively (Algeria dam). The activity concentration of 40K was higher than that of 238U and 232Th for the water and sediment samples. The mean activity concen-trations follow the order 40K > 238U > 232Th. The cumulative impact can be a serious immediate radiological health burden on the ecosystem, environment and people's health in this study area and can be transposable to any other similar region. The good knowledge of monitoring quality and quantity for the transboundary water resources and the international collaborations are es-sential to safeguard human health (women’s breasts cancer, thyroid cancer, neurological im-pact…), and avoid the conflicts, especially during these climatic upheavals of drought.

This article aims to investigate gaps in the law and policies on e-waste management in communi-ties of Thailand and suggests a guideline for improving, developing, and designing legal measures and state policies for more effective enforcement of the law on e-waste management in communities. The findings reveal that the currently applicable law of Thailand lacks effective approaches and rules for e-waste management. Also, there is not any implementation of key envi-ronmental principles for e-waste management in communities, such as the Polluter Pays Principle (PPP) that requires manufacturing companies to take part in being responsible for disposal ex-penses or the Public Participation principle that requires users, manufacturers, distributors, and government agencies to take parts in disposing e-waste. As a result, problems of e-waste in com-munities of Thailand have been continuously increasing. According to such problems, the authors suggest that legal measures on e-waste management in communities should be specifically de-signed by implementing key environmental principles as a basis in determining formats and guidelines of e-waste management, especially participation of all sectors that can help in solving and reducing e-waste in communities that is harmful to health, sanitation, and environment.

Harnessing the Remarkable Bio-Remediation Potential of Vernonia spp. for the Sustainable Restoration of Hydrocarbon-Polluted Clay Soil in Ogoni Land, Nigeria This study explores the potential of utilizing Vernonia spp. for eco-friendly bio-remediation of hydrocarbon-polluted clay soil in Ogoni Land, Nigeria. The aim is to find a sustainable and effective solution that promotes the restoration of the polluted soil while minimizing the use of external additives. The process of bio-remediation can occur naturally, through natural attenuation or intrinsic bio-remediation. However, it has been observed that in certain cases, the addition of fertilizers, oxygen, or organic matter is required to enhance the effectiveness of bio-remediation. In this research, we focus on the bio-remediation potential of Vernonia spp., a native plant species known for its strong phytoremediation abilities. By harnessing the remarkable bio-remediation properties of Vernonia spp., we seek to restore the hydrocarbon-polluted clay soil in Ogoni Land in an environmentally friendly and sustainable manner. Our methodology involves conducting greenhouse experiments to assess the bio-remediation efficiency of Vernonia spp. in different soil conditions. We will analyze the soil's physical and chemical properties, as well as the degradation of hydrocarbons over time. The experimental results will provide valuable insights into the effectiveness of Vernonia spp. in removing hydrocarbon pollutants from clay soil. Through this study, we aim to develop a cost-effective and sustainable approach to restore hydrocarbon-polluted clay soil in Ogoni Land. By leveraging the natural bio-remediation potential of Vernonia spp., we can potentially reduce the reliance on external additives, thus minimizing the environmental impact associated with traditional remediation methods. The research article explores methods to promote the growth of pollution-eating microbes in order to enhance bio-remediation. Bio-remediation refers to the use of naturally occurring organisms to break down harmful substances into less toxic or non-toxic forms. In situ bio-remediation involves treating the contaminated material directly at the site, while ex-situ bio-remediation involves removing the contaminated material for treatment elsewhere. This study specifically investigates ex-situ bio-remediation techniques for hydrocarbon-contaminated clay soil. The researchers found that the application of room dry and wet blended bitter leaf showed promising results in the bio-remediation of hydrocarbons in the clay soil. Using Vernonia galamensis, a concentration as high as 0.55 ug/ml was achieved, while Vernonia amygdalina yielded a concentration as high as 0.67 ug/ml when applied at 35g and 40g respectively, based on the wet blended approach. These findings highlight the effectiveness of wet blended Vernonia species in the bio-remediation process.During the remediation process of the clay soil, the pH levels showed a trend of increasing from acidic to normal to alkaline. This can be attributed to the remediation of excessive metals present in the soil. After 40 days, the pH of the clay soil reached 6.97 when treated with 40 grams of Vernonia galamensis, and 7.00 when treated with 40 grams of Vernonia amygdalina. Interestingly, while the remediation efficiency of HC (hydrocarbon) decreased with increasing mass of Vernonia galamensis, the remediation efficiency of HC increased when using Vernonia amygdalina. These observations highlight the varying effects of different Vernonia species on hydrocarbon remediation.The highest remediation values were observed when using Vernonia galamensis at 35g and Vernonia amygdalina at 40g. These particular amounts of these Vernonia species demonstrated effective remediation of the targeted pollutants. However, in comparison to other metals, the remediation effects were relatively lower for zinc (Zn), with only approximately 0.25 ug/ml being remediated. This suggests that the remediation potential of the Vernonia species may vary depending on the specific contaminant.The higher remediation effects observed for Zn metal in the soil can be attributed to the wet blended preparation method of the Vernonia species. In contrast, the room dried Vernonia species exhibited the lowest performance in remediating the soil, with approximately 0.17 ug/ml and 0.10 ug/ml remediation for galamensis and amygdalina, respectively. Both Vernonia leaf extracts achieved a remediation of 0.5 ug/ml for chromium. The sun dried and room dried methods also showed considerable remediation potential, with values above 0.4 ug/ml. The level of significance for the model was attained at 0.05, and the r2 value was appreciable. These findings indicate the effectiveness of different preparation methods and Vernonia species in soil remediation

Starting from the fact that the units of local self-government of the Republic of Serbia are not sufficiently oriented towards innovations related to human resources and the environment, the application of quantitative research tradition examines the positioning and understanding of certain procedures and decisions of human resources management regarding the functioning of the environmental protection system, on the one hand, and future strategies for changing the given system, on the other. A series of 105 face-to-face interviews were conducted during the whole of 2016 in 105 of the 191 municipalities in the Republic of Serbia. Examination of the attitudes of the local self-government was carried out using a specially designed closed electronic questionnaire. The results of the multivariate regressions show that the most important predictor of the possible improvement of the environment is the size of the municipality. The remaining variables (e.g., human resources policy, human resources service) did not have significant effects on the ability to improve the environment. In more than half of local self-governments, there was no clearly defined human resources strategy in the field of environmental protection, an environmental protection service, an Environmental Action Plan, as well as an employment plan for waste management in local governments, etc. The research has shown that top managers of local governments agree that the management of human resources in environmental protection represents a significant opportunity to improve the quality of the environment. The results of the research can be used to improve the organization of human resource competence in environmental protection and the quality of a working and sustainable environment in the area of local self-government.

Background: Autonomic balance measurement (ABM) is a valuable tool in clinical practice for assessing the functioning of the autonomic nervous system (ANS), which controls involuntary bodily functions. Here we summarize the current understanding of the utility of autonomic balance measurement in clinical practice. Methods: A narrative review of relevant literature was conducted, focusing on studies investigating the use of autonomic balance measures in various clinical settings. Results: ABM holds potential benefits in clinical practice, including aiding in diagnosing autonomic dysfunction, monitoring treatment efficacy, and predicting potential health complications. ABM can be crucial for diagnosing various conditions, including cardiovascular diseases (Heart failure, arrhythmias, and hypertension), neurological disorders (Parkinson's disease, Alzheimer's disease, and diabetic neuropathy), in sports medicine athletes can undergo ABM to optimize training regimens, enhance performance, assessing the impact of training stress, preventing overtraining, and promoting overall well-being and probably to assess potential health risks, in metabolic syndromes ABM can aid in the early detection of autonomic neuropathy, a diabetes-related complication, allowing for timely intervention and better management of the disease, and psychiatric disorders (Anxiety, depression, and post-traumatic stress disorder). In addition, ABM can be helpful in monitoring of treatment efficacy, by tracking changes in autonomic balance, clinicians can assess if treatments for conditions impacting the autonomic nervous system are effective. ABM can also be helpful in predicting outcomes by facilitating early recognition of future health complications in certain populations. However, limitations exist, including non-specificity, variability in measurements, and limited evidence for routine use in specific clinical settings. Conclusion: Incorporating autonomic balance measurement into routine clinical assessments provides a more comprehensive understanding of a patient's health. It complements traditional diagnostic methods, offering additional insights into the body's regulatory mechanisms. While autonomic balance measurement offers potential benefits, careful interpretation and consideration of its limitations are crucial for its effective use in clinical practice. ABM remains a valuable and versatile tool in clinical practice for a deeper understanding of the autonomic nervous system, enabling early detection, targeted interventions, and improved management of various medical conditions across different specialties.

Environmental literate citizenship is a lifelong learning process that aims to develop citizens who have the knowledge, skills, and commitment to make responsible decisions that will affect the quality of the environment. The purpose of the present study was to evaluate the environmental literacy levels of nursing students in terms of sustainable environmental by considering the dimensions of environmental literacy. It was also aimed at understanding the correlation among dimensions of environmental literacy and revealing the factors affecting the dimensions of environmental literacy. This research was designed as a descriptive study in the survey model. A total of 278 nursing students participated in this research. It was revealed that students obtained a high score for use and concern from the dimensions of environmental literacy, their attitudes towards the environment were moderate; however, nursing students took the lowest points for the environmental knowledge component, which indicates that students need support in environmental knowledge. It was put forward that there were statistically significant differences based on gender and taking environmental related courses with dimensions of environmental literacy. All dimensions of environmental literacy were found to be positively correlated with each other, ranging from low to moderate relations.

The “Pay-as-you-throw” scheme, PAYT, is an economic instrument of waste management that implements the “polluter pays” principle by charging inhabitants of municipalities according to the amount of residual, organic and bulky waste they send for third-party waste management. When combined with well-developed infrastructure to collect the different waste fractions (residual waste, paper and cardboard, plastics, bio waste, green cuttings, many recyclables) as well as with a good level of citizen’s awareness, its performance has frequently been linked to high collection rates of recyclables. However, the establishment and operation of PAYT systems can require significant resource inputs from municipalities. In this paper, PAYT is analysed through a case study from the German County of Aschaffenburg, covering nearly 20 years of implementation across 173,000 inhabitants. Key performance indicators applied include temporal trends in the county’s recyclables collection rate, waste treatment fees for residents and municipal waste management costs, benchmarked against German municipalities not implementing PAYT.

This study examines the complex relation among environmental taxes, productive capacities, urbanization, and their collective effects on environmental quality in Africa, drawing on two decades of data from twenty African countries. It situates the study within the broader discourse on sustainable development and economic growth, emphasizing the Environmental Kuznets Curve (EKC) framework to examine the relationship between economic development, characterized by urban expansion and increased productive capacities, and the adoption of environmental taxes amidst the continent’s diverse economic and environmental environments. Using advanced econometric techniques, including the Cross-Section Augmented Autoregressive Distributed Lag (CS-ARDL) model and the Dynamic Common Correlated Effects Mean Group (DCCEMG) estimator, the study addresses data challenges such as cross-sectional dependence and slope heterogeneity. The results provide important insights into the dynamics of environmental quality in relation to economic and urban growth and the role of environmental taxation. The study proposes tailored policy strategies aimed at strengthening sustainable development initiatives in line with international agreements such as the Paris Agreement and the Sustainable Development Goals. These strategies advocate for a nuanced application of environmental taxes and the promotion of productive capacities to enhance environmental sustainability across the African continent.

Abstract: The study focuses on how socio-economic and demographic indicators affect fertilization sustainability (excessive amount of fertilization). Principally we aim to examine the significance magnitude of the effects of three socio-demographic variables such as traditional way of fertilization, rental land farming, and farmers’ younger age on over-fertilization in Bangladesh and other developing countries. In 1960s, Bangladesh state authority launched a campaign ‘Grow more Food’ to feed huge numbers of population and thus the farmers are provided chemical fertilizers and pesticides at a subsidized low price. Farmers began to use huge amount of fertilizers for gaining high yields and continued it to present causing environmental woes a lot. We interview (face-to-face, focus group discussion, and phone interview) 210 Bangladesh farmers in 2016 by semi-structured questionnaire. Data has been analyzed using General Linear Model (GLM) in Univariate Analysis of Variance. The study found the effect of traditional way of fertilization on excessive amount of fertilization is strongly significant at 1% level. Apart from, rental land farming and farmers’ younger age have a significant influence on over- fertilization; though their significance level (5% and 10% respectively) is quasi-strong. Policy makers can be able to formulate fertilizer policy on the basis of these findings.

Predators are dependent on the capture of prey to meet their energetic and nutritive requirements, imposing a regime of predation risk. Consequently, prey experience both consumptive and non-consumptive effects. Non-consumptive effects may manifest through altered growth and ontogenetic trajectories of prey species, a dynamic modulated by olfactory or other sensory cues from predators. Bactrocera dorsalis Hendel represents a great invasive threat to global horticulture. While earlier research has primarily centered on the consumptive interactions between B. dorsalis and its natural enemies, the potential consequences of non-consumptive interactions on the development of B. dorsalis have been overlooked. In this study, we investigated the impact of predation risk effects, induced by both visual exposure to the predatory mantis Hierodula patellifera Serville and its associated odor, on the life history traits of B. dorsalis. Female B. dorsalis demonstrated reduced development time in the presence of isolated H. patellifera or H. patellifera odor, yet evidenced significantly increased fecundity. Conversely, males displayed no significant change in development time. Additionally, neither female nor male body weight at death was significantly influenced by predation risk from isolated predators or predator odor. These results indicated adaptive developmental strategies of B. dorsalis when faced with risks from predators and highlight the important role of predator odor, which has the potential to lay the groundwork for improving biological control efforts and innovative approaches within pest control.

This paper discusses how mathematical models are used to predict environmental conditions. While these models are successful for larger scale phenomena, it becomes more complex for local weather or wave processes. Several approaches have been proposed to address this problem, including neural networks and statistical and mathematical models. The novelty in this approach is the use of statistical manifolds, which provide a more accurate way to estimate distances and cost functions. This work focuses on advancements in differential and information geometry for creating different types of models that can be used for environmental simulation and forecasting. These fields are vital for many institutes and centres worldwide, as they help solve challenges in areas such as meteorology, renewable energy, and aviation safety. Some potential IG applications to advance energy were given. Closing remarks with new open problems combined with the next research phase are provided.