The article suggests that the the Gregorian calendar is unscientific and ivestiagtes why the Vaidika Pañcāṅga is mathematically accurate. It is a qualitative study and the library method of research has been carried out to support the claims. For Indic words, the International Alphabet for Sanskrit Transliteration (IAST) method is used.

A new malachite beetle, Baltamauroania mirabilicornis gen. et sp. nov., belonging to the tribe Am-auroniodini (Coleoptera: Dasytidae) embedded in Eocene Baltic amber is described and illustrated. The new genus differs from the congeners of the tribe Amauroniodini in possessing a black, elongate and subparallel body and a pronotum with scalloped lateral sides; long and 11-segmented antennae, with three apical antennomeres enlarged and forming a ‘club’, with cylindrical an-tennomere 1; tarsi shortened and compressed, 5-segmented, with tarsomeres 1 and 2 equal in length, and tarsomere 5 the longest in all legs; pubescence of the dorsal surface consisting of short strong brown semi-erect and fine adpressed hairs; punctation of dorsal surface irregular, elytra lacking grooves; pronotum almost equilateral, slightly elongate, with acute anterior and obtuse posterior angles, with wide margination of basal side and with scalloped and finely margined lateral sides; lateral edges of pronotum weakly rounded, with obtuse protuberance before middle. This is the second extinct genus and third record of the subfamily Danaceinae found in Eocene amber. The fossil records of the family Dasytidae are discussed. Three recent records of different Amauroniodini taxa from Eocene East European amber (Baltic and Rovno) shows there to have been a high Danaceinae biodiversity in both the southern coast of the Subparatethys (documented by Rovno amber) and in its northern coast (documented by Baltic amber). The phenomenon of Danaceinae diversity in the Eocene Epoch is discussed.

In the last years, molecularly targeted agents and immune based treatments (ITs) have deeply changed the landscape of anti-cancer therapy. Indeed, ITs proved to be very effective in metastatic solid tumors, where outcomes were extremely poor with standard approaches. Such a scenario has been only partially reproduced in hematologic malignancies. In acute myeloid leukemia (AML), as innovative drugs are eagerly awaited in relapsed/refractory setting, different ITs have been explored, but the results are still unsatisfactory. In this work, we will discuss the most important clinical studies to date adopting ITs in AML, providing the bases to understand how this approach, although still in its infancy, may represent a promising therapeutic tool for the next future treatment of AML patients.

This essay critically discusses the integration of queer theory into human geography while emphasizing its ties to the principles of traditional geography. The need for a separate sub-discipline called queer geography is questioned. At the same time, legitimate concerns about possible departures from the fundamental goals of geography and the risks of anachronistic interpretations in applying modern concepts to historical landscapes are acknowledged. In this discourse, we strongly advocate for values such as freedom of speech, freedom of expression, and international human rights. It is important to emphasize that it is not the intent of this essay to denigrate campaigns for feminism or equality or to disparage the scholarship that emerges from the application of queer theory. On the contrary, we recognize the emergence of gender theories out of a need to advance social justice approaches. We believe that traditional human geography, itself, is capable of comprehensively examining space, time, and the complexity of human experience and offering workable solutions within its established framework. We therefore believe that the inclusion of queer theory can be harmoniously integrated into the contours of human geography, eliminating the need for a separate sub-discipline while preserving the integrity and purpose of the discipline.

Iron oxide nanoparticles have been investigated due to their suitable characteristics for diverse applications in the fields of biomedicine, electronics, water/wastewater treatment and sensors. Maghemite, magnetite and hematite are the most widely studied iron oxide particles and have ferrimagnetic characteristics. When very small, however, these particles have superparamagnetic properties and are called superparamagnetic iron oxide nanoparticles (SPIONs). Several methods are used for the production of these particles, such as coprecipitation, thermal decomposition and microemulsion. However, the variables of the different types of synthesis must be assessed to achieve greater control over the particles produced. In some studies, it is possible to compare the influence of variations in the factors for production with each of these methods. Thus, researchers use different adaptations of synthesis based on each objective and type of application. With coprecipitation, it is possible to obtain smaller, more uniform particles with adjustments in temperature, pH and the types of reagents used in the process. With thermal decomposition, greater control is needed over time, temperature as well as the proportion of surfactants and organic and aqueous phases in order to produce smaller particles and a narrower size distribution. With the microemulsion process, the control of the confinement of the micelles formed during synthesis through the proportions of surfactant and oil makes the final particles smaller and less dispersed. These nanoparticles can be used as additives for the creation of new materials, such as magnetic bacterial cellulose, which has different innovative applications. Composites that have SPIONs, which are produced with greater rigour with regards to size and distribution, have superparamagnetic properties and can be used in medical applications, whereas materials containing larger particles have ferromagnetic applications. To arrive at a particular particle with specific characteristics, researchers must be attentive to both the mechanism selected and the production variables to ensure greater quality and control of the materials produced.

In this contribution a new configuration of a DC-DC Boost and Buck-Boost converters is proposed to track sinusoidal signals exactly, with zero tracking error. The stage is conformed by two DC-DC converters connected to the same load, this is, they are not connected in cascade. To track exactly the sinusoidal reference the control scheme is base on the indirect control algorithm and the harmonic balance method. The proposed algorithm considers a second control input with the end of cancel out the second harmonic, this second harmonic is produced by the non linearity of the model and must be cancelled since there must be a single frequency in the output. The result is such that the converters can track sinusoidal signals with exactly zero error, some numerical results are presented to corroborate the proposal.

This study analysed trends of first-time patients visiting the paediatric psychiatry clinic in a university hospital. The medical records from 2009 to 2016 of first-time patients visiting the Kyung Hee university hospital were reviewed, focusing on children in grades 1–12. We analysed the prevalence rate of psychiatric disorders per 100,000 general populations by gender and grade, and the characteristics of patients who sought outpatient care more than three times. The study included 1,467 participants, of which 931 were males (63.5%). The number of male patients per 100,000 populations significantly decreased from 4.14 in 2009 to 2.03 in 2016. While hyperkinetic disorders had the highest prevalence in males, neurotic disorders were most frequent in females. Prevalence of disruptive behaviour disorders in males and mental retardations in females decreased significantly during the study period. The factors affecting continuity were being female, studying in grades 7–12, and diagnosis of depressive, hyperkinetic, and tic disorders. Physicians should consider the new paediatric patients’ gender, grade, and expected diagnosis from their first visit to improve treatment compliance.

Pattern recognition has long been regarded as key role for crime prevention and reduction. Crime analysts and policy makers can formulate effective strategies and allocate resources with reference to spatial and temporal pattern of crime. In order the combat and prevent severe crime in New York City (NYC), this study analyzed Felony Crime data of NYC in previous 5 years (2015 2020) and discovered criminal hotspots pattern and temporal patterns with open criminal complaint data provided by New York Police Department (NYPD). This study adapt a human computer interactive appraoch to draw patterns from crime data, whereas computations and visualization are performed by Python libraries, and human to inform the decision of visualization methods, computational parameters and direction of this exploratary analysis. Density based clustering algorithms, Grid Thematic Mapping and Density Heatmap are displayed to identify hotspots and demonstrates their associations with spatial features. Timeline analysis on moments of crime occurance demonstrates seasonality where crimes are mostly commited, while aoristic analysis showed hours of day when crime is mostly committed considering their timespan. Lastly, 3D visualization improved recognition of the displacement of hotspot over time, and suggested long term hotspots in NYC in 3 D visualization. This inform strategic plans for police deployment.

Project complexity is usually considered as one of main causes of cost overruns, resulting in poor performance and thus project failure. However, empirical studies focused on evaluating its effects on project cost remain lacking. Given this circumstance, this study attempts to develop the relationships between project cost and the multidimensional project complexity elements. We establish complexity as a multidimensional factor including the task, organization, market, legal, and environment complexities. This study uses an empirical evidence-based structural model to account for the relationships between project cost and project complexity. By doing so, a quantitative assessment of multi-dimensional project complexity has been developed. The findings suggest that task and organization complexities have direct effects on project cost, while market, legal and external environment complexities have indirect effects on project cost. The practical contribution is that the findings can improve the understanding of which dimension of complexity significantly influence project cost, and the need to focus efforts on strategically addressing that complexities.

Today in times of increasing inequality, climate change, and major social challenges, education is the best way to equip citizens, scholars and leaders to implement meaningful change and prevent future crises. Biologi education and science will solve these problems to supporting sustainable development goals especially in soil remediation, clean water, education quality and clean and affordable energy. This paper will describe how biological education could solve these problems. New biology can solve the problem about hunger use biotech, use synthetic biological material to find new advance material. New biology could driving intersectorial, interdisciplinary and international connectivity, and the leveraging of existing investments in synthetic biology, materials science, allied science and technology areas, are the major challenges in delivering the Materials from Biology vision.

The New Zealand housing sector is experiencing rapid growth that boosts the national economy but also results in the loss of valuable resources. In line with the growth, the housing market for both residential and business purposes has been booming, as have house prices. To sustain the housing development, it is critical to accurately monitor and predict housing prices so as to support the decision-making process in housing sector. This study is devoted to applying a mathematical method to predict housing prices. The forecasting performance of two types of models: ARIMA and multiple linear regression analysis are compared. The ARIMA and regression models are developed based on a training-validation sample method. The results show that the ARIMA model generally performs better than the regression model. However, the regression model explores, to some extent, the significant correlations between house prices in New Zealand and the macro-economic conditions.

Construction projects are usually operating in a complex and dynamic environment in which the accumulation of many interrelated factors causes high uncertainty. Construction projects are complex and frequently involve substantial uncertainties including process complicatedness, intricate organization structure, dynamic environment, and financial strain. The study aims to categorize the influencing factors into three groups, namely construction project system, economic-market climate, and external environment. It attempts to adopt a novel analysis tool to examine the relationship between the project cost and multiple influencing factors by using Bayesian SEM. While the Bayesian SEM method has been receiving increasing attention in exploring the relationship between latent variables, construction studies still heavily rely on the covariance-based SEM approach. This study introduces several advantages of Bayesian SEM that make it more flexible and powerful than covariance-based SEM and provides the foundation of Bayesian SEM estimation and inference by illustrating this method in a project cost application.

Construction projects are usually operating in a complex and dynamic environment in which the accumulation of many interrelated factors causes high uncertainty. Construction projects are complex and frequently involve substantial uncertainties including process complicatedness, intricate organization structure, dynamic environment, and financial strain. The study aims to categorize the influencing factors into three groups, namely construction project system, economic-market climate, and external environment. It attempts to adopt a novel analysis tool to examine the relationship between the project cost and multiple influencing factors by using Bayesian SEM. While the Bayesian SEM method has been receiving increasing attention in exploring the relationship between latent variables, construction studies still heavily rely on the covariance-based SEM approach. This study introduces several advantages of Bayesian SEM that make it more flexible and powerful than covariance-based SEM and provides the foundation of Bayesian SEM estimation and inference by illustrating this method in a project cost application.

Food security (FS) during infancy is associated with lifelong outcomes. New Zealand is a developed economy that reports poor childhood nutrition-related health statistics, particularly among minority children, yet has no measure of FS applicable to infancy. The objective was to develop a FS index for New Zealand infants and examine its association with demographic covariates and health outcomes. Within a large (n=6853) nationally representative cohort, variables describing infant food consumption, breastfeeding, and maternal food-related coping methods were collected from mothers during late infancy. A FS index was derived using confirmatory factor analysis. Associations were assessed by logistic regressions and described using odds ratios (OR) and ≥95% confidence intervals (CI). 15% of the cohort was highly FS, 43% tenuously food insecure (FIS), and 16% highly food insecure (FIS). Infants from minority ethnic groups had lower odds of being food secure, as did those born to the youngest mothers, mothers who smoked, or lived in low-income households. FIS infants had higher odds of morbidity. Interventions to improve infant FS should focus on improving dietary quality, and give particular consideration to minority infants. We identified that FIS shows wide ethnic and socioeconomic inequity, and is associated with poorer health. The most important driving factors of FIS included poor quality weaning diets, and poverty and its proxies. Any interventions to improve infant FS should focus on increasing fruit and vegetable consumption to recommended intake levels, and give particular consideration to minority infants.

Tsygankoite, ideally Mn8Tl8Hg2(Sb21Pb2Tl)Σ24S48, is a new sulfosalt discovered at the Vorontsovskoe gold deposit, Northern Urals, Russia. It occurs as lath-like elongated crystals up to 0.2 mm embedded in calcite-dolomite-clinochlore matrix. The associating minerals also include aktashite, alabandite, arsenopyrite, barite, cinnabar, fluorapatite, orpiment, pyrite, realgar, routhierite, sphalerite, tilasite, titanite, etc. The new mineral is non-fluorescent, black, opaque with a metallic lustre and black streak. It is brittle with an uneven fracture and no obvious parting and cleavage. Its Vickers hardness (VHN10) is 144 kg/mm2 (range 131–167) and its calculated density is 5.450 g cm-3. In reflected light tsygankoite is white; between crossed polars it is dark-grey to black. It is strongly anisotropic: rotation tints vary from light-grey to dark-grey to black. Pleochroism and internal reflections are not observed. The chemical composition of tsygankoite (wt.%, electron-microprobe data) is: Mn 6.29, Fe 0.02, Cu 0.02, Ag 0.01, Hg 5.42, Tl 26.05, Pb 5.84, As 3.39, Sb 30.89, S 21.87, Se 0.01, total 99.81. The empirical formula, calculated on the basis of 90 atoms pfu, is: Mn8.06Tl8.00(Hg1.90Fe0.03Cu0.02Ag0.01)Σ1.96(Sb17.85As3.18Pb1.98Tl0.97)Σ23.98(S48.00Se0.01)Σ48.01. Tsygankoite is monoclinic, space group C2/m, a = 21.362(4) Å, b = 3.8579(10) Å, c = 27.135(4) Å, β= 106.944(14)°, V = 2139.19(17) Å3 and Z = 1. The five strongest diffraction peaks from X-ray powder pattern [listed as (d,Å(I)(hkl)] are: 3.587(100)(112), 3.353(70)(-114), 3.204(88)(405), 2.841(72)(-513) and 2.786(99)(-514). The crystal structure of tsygankoite was refined from single-crystal X-ray diffraction data to R = 0.0607 and consists of an alternation of two thick layer-like arrays, one based on PbS-archetype and second – on SnS-archetype. Tsygankoite has been approved by the IMA-CNMNC under the number 2017-088. It is named for Mikhail V. Tsyganko, mineral collector from Northern Urals, who collected the samples where the new mineral was discovered.

Aerosol optical depth (AOT) was measured at Xavier University of Louisiana (29.96ᵒ N, 90.11ᵒ W and about 3m above sea level) using a hand-held sun photometer. AOT was measured at two different wavelengths (green at 505nm and red at 625nm) during the period from Sept-2017 to Feb-2018. In this study, we investigate the relationship between AOT and temperature, precipitation, barometric pressure and relative humidity. The maximum monthly average value for green AOT was 0.176 (measured in September) and the minimum monthly value is 0.040 (measured in January). For the red AOT the maximum monthly average value was 0.123 (measured in September) and the minimum is 0.034 (measured in December). The AOT–temperature relationship was predominantly positive, meaning that high AOT values correspond to high temperatures and low AOT values correspond to low temperatures. Relationship between AOT and rainfall is negative, meaning high rainfall averages are associated with low AOT values. AOT and atmospheric pressure have a predominantly negative relationship. The relationship between relative humidity and AOT is a complicated one and is hard to qualify as relative humidity varies very little during the study period.

In this paper, we investigate the Green measure for a class of non-Gaussian processes in $\mathbb{R}^{d}$. These measures are associated with the family of generalized grey Brownian motions $B_{\beta,\alpha}$, $0

In this paper, a positive answer to the open question of Fabino et al. is given, and the concept of I\c sik type set valued contractions is introduced and fixed point theorem for such contractions is established. Examples to support main theorems are given, and an application to integral inclusion is given.

Study of differential equation theory has come a long way with applications in the various fields. In 1961, Zygmund and Calderón introduced the notion of derivatives on metric Lr which proved to be better in applications than approximate derivatives. But most of the studies involved are on fuzzy set theory, so it seems likely that intuitionistic fuzzy Lr - norm - based derivatives deserve study. In the study, the fuzzy derivative is extended to intuitionistic fuzzy derivatives with respect.to Lr - norm - based derivatives using intuitionistic fuzzy number valued functions. The efficacy of the proposed method is established by proving the associated theorems along with numerical examples. Further, the Cauchy problem is also studied with respect to intuitionistic fuzzy setting.

One of the challenges in the healthcare sector is making accurate forecasts across insurance years for claims reserve. The state-of-the-art envisages various methods for estimating the claims reserve but without being applied to systems that do not present huge variability and heterogeneity, such as the healthcare sector. The methodology is based on generalized linear models using the Overdispersed Poisson distribution as shown in the state-of-the-art. In this context, we developed a method to estimate the parameters of the quasi-likelihood function using a Gauss-Newton algorithm optimized through a genetic algorithm. The genetic algorithm plays a crucial role in glimpsing the position of the global minimum to ensure a correct convergence of the Gauss-Newton method, where the choice of the initial guess is fundamental. The proposed methodology has been entirely developed using MATLAB and has been applied to estimate the claims reserve in the healthcare system of the Tuscany Region in Italy, as case study. The results obtained were validated by comparing them with the state-of-the-art by measuring the confidence intervals of the Overdispersed Poisson distribution parameters. Therefore local healthcare authorities could use the proposed and improved methodology to allocate the resources dedicated to healthcare and global management.

In applied mathematics, statistics, operation research, physics, and engineering mathematics, confluent representations of hypergeometric functions in one and two variables are known to exist, and their occurrence in a variety of applications is also well recognised. In this article, we intend to present a new derivation of the extended Watson summation theorem for the Kim et al. given series 4F3. We assessed four attractive integrals involving generalized hypergeometric function as an application. With a few particular cases, this note will come to an end. In the results given above, symmetry appears on its own.

The purpose of this systematic review is to examine the various articles published in the field of neuropsychology of anxiety research in terms of publication type and volume, methodology, and subject matter. The significance of this topic derives from the clinical and functional consequences of cognitive symptoms. Generalized anxiety disorder refers to the cluster of clinical symptoms characterized by predominant anxious anticipation and difficulty controlling worry. In order for the review to be systematic and reproducible, a search of the PsycINFO, Scopus, PubMed, Elsevier databases and an analysis using the PRISMA method are suggested. After analyzing the research data, empirical studies evaluating the clinical neuropsychology of generalized anxiety disorder are discussed.

This article develops applications of the generalized method of lines to numerical solutions of the time-independent, incompressible Navier-Stokes system in fluid mechanics. We recall that for such a method, the domain of the partial differential equation in question is discretized in lines (or more generally in curves), and the concerning solutions are written on these lines as functions of the boundary conditions and the domain boundary shape.

This article develops dual variational formulations for a large class of models in variational optimization. The results are established through basic tools of functional analysis, convex analysis and duality theory. The main duality principle is developed as an application to a Ginzburg-Landau type system in superconductivity in the absence of a magnetic field. In the first sections, we develop new general dual convex variational formulations, more specifically, dual formulations with a large region of convexity around the critical points which are suitable for the non-convex optimization for a large class of models in physics and engineering. Finally, in the last section we present some numerical results concerning the generalized method of lines applied to a Ginzburg-Landau type equation.

Two extensions of the generalized double Lomax distribution are introduced - the spliced-scale generalized double Lomax distribution and the exponentiated generalized double Lomax distribution. Their properties are studied. Usefulness of the new distributions is shown by fitting them to stock returns datasets.

The paper presents a modified finite element method for nonlinear analysis of 2D beam structures. To take into account the influence of the shear flexibility, a Timoshenko beam element was adopted. The algorithm proposed enables using complex material laws without the need of implementing advanced constitutive models in finite element routines. The method is easy to implement in commonly available CAE software for linear analysis of beam structures. It allows to extend the functionality of these programs with material nonlinearities. By using the structure deformations, computed from the nodal displacements, and the presented here generalized nonlinear constitutive law, it is possible to iteratively reduce the bending, tensile and shear stiffnesses of the structures. By applying a beam model with a multi layered cross-section and generalized stresses and strains to obtain a representative constitutive law, it is easy to model not only the complex multi-material cross-sections, but also the advanced nonlinear constitutive laws (e.g. material softening in tension). The proposed method was implemented in the MATLAB environment, its performance was shown on the several numerical examples. The cross-sections such us a steel I-beam and a steel I-beam with a concrete encasement for different slenderness ratios were considered here. To verify the accuracy of the computations, all results are compared with the ones received from a commercial CAE software. The comparison reveals a good correlation between the reference model and the method proposed.

This article has two objectives. Firstly, we will use the vector variational-like inequalities problems to achieve local approximate (weakly) efficient solutions of Vector Optimization Problem within the novel field of the Hadamard manifolds. Previously, we will introduce the concepts of generalized approximate geodesic convex functions and illustrate them with examples. We will see the minimum requirements under which critical points, solutions of Stampacchia and Minty weak variational-like inequalities and local approximate weakly efficient solutions can be identified, extending previous results from the literature for linear Euclidean spaces. Secondly, we will show an economical application, using again solutions of the variational problems to identify with Stackelberg equilibrium points on Hadamard manifolds and under geodesic convexity assumptions.

The main goal of this article is to demonstrate the impact of environmental data on the spreading of Covid-19. In this research, data has been collected from 70 cities/provinces that are affected by Covid-19. Here, environmental data refers to temperatures, humidity and population density in each of these cities/provinces. This data has been analyzed using statistical models such as Poisson, Quasi-Poisson and negative Binomial. It is found that a negative Binomial regression model is the best fit for our data. Our results reveal that average high temperature is the vital factor to slow down the spread of Covid-19. In addition, higher population density found to be an important factor for the quick spreading of Covid-19 where it is quite impossible to maintain the social distance and the virus can spread easily.

This paper analyzes the robust dissipativity of uncertain stochastic generalized neural networks (USGNNs) with Markovian jumping parameters and time-varying delays. In practical applications most of the systems refer to uncertainties, hence, the norm-bounded parameter uncertainties and stochastic disturbance are considered. Then, by constructing an appropriate Lyapunov-Krasovskii functional (LKF) and by employing integral inequalities LMI-based sufficient conditions of the considered systems are established. Numerical simulations are given to show the merit of the presented results.

This study investigated the trends of registered Death and Birth in Nigeria using Generalized Linear Models. Annual data on Death and Birth was collected from National Population Commission for the period of 2004 to 2017. The Natural increase calculated revealed a positive trend in the natural increase in Nigeria from 2004 to 2017. Evidence from summary statistics revealed some level of over dispersion (variance > mean). This study explored Poisson Regression Models and Negative Binomial Regression Models using two links (identity and log). The results revealed a positive increase in registration of birth and death rates in Nigeria and among the competing the models, Negative Binomial regression model with identity link emerged as the best model for modeling birth and death rates registration in Nigeria. Data on numbers of deaths and causes of death are essential if countries are to determine priorities, formulate and monitor policies for public health care as well as other government policies that may be based on such data

The aim of this paper is to obtain Karush-Kuhn-Tucker optimality conditions for weakly efficient solutions to vector equilibrium problems with the addition of constraints in the novel context of Hadamard manifolds as opposed to the classical examples of Banach, normed or Hausdorff spaces. More specifically, classical necessary and sufficient conditions for weakly efficient solutions to the constrained vector optimization problem are presented. As well as some examples. The results presented in this paper generalize results obtained by Gong (2008) and Wei and Gong (2010) and Feng and Qiu (2014) from Hausdorff topological vector spaces, real normed spaces and real Banach spaces to Hadamard manifolds, respectively.

Live fuel moisture content (LFMC) influences fire activity at landscape scale and fire behavior in laboratory experiments. However, field evidences linking LFMC to fire behavior are very limited despite numerous field experiments. In the present study, we reanalyze a shrubland fire dataset with a special focus on LFMC to explain this counterintuitive outcome. We found that this controversy might result from three reasons. First, the range of experimental LFMC data was too moist to reveal significant effect with the widespread exponential or power functions. Indeed, LFMC exhibited a strong effect below 100%, but marginal above this threshold, contrary to these functions. Second, we found that the LFMC significance was unlikely when the size of the dataset was smaller than 40. Finally, a complementary analysis suggested that 10 to 15% of random measurement error in variables could lead to an underestimation by 30 % of the LFMC effect. The effect of LFMC in field experiments is thus stronger than previously reported in the range prevailing during the actual French fire season and in accordance with observations at different scales. This highlights the need to improve our understanding of the relationship between LFMC and fire behavior to refine fire danger predictions.

The asymmetric bimodal exponential power (ABEP) distribution is an extension of the generalized gamma distribution to the real line via adding two parameters which fit the shape of peakedness in bimodality on real line. The special values of peakedness parameters of the distribution are combination of half Laplace and half normal distributions on real line. The distribution has two parameters fitting the height of bimodality, so capacity of bimodality is enhanced by using these parameters. Adding a skewness parameter is considered to model asymmetry in data. The location-scale form of this distribution is proposed. The Fisher information matrix of these parameters in ABEP is obtained explicitly. Properties of ABEP are examined. Real data examples are given to illustrate the modelling capacity of ABEP. The replicated artificial data from maximum likelihood estimates of parameters of ABEP and distributions having an algorithm for artificial data generation procedure are provided to test the similarity with real data.

In this paper we consider type II bivariate generalized power series Poisson distribution as a compound Poisson distribution with bivariate generalized power series compounding distribution. We obtain some properties, p.m.f. and conditional distributions. In addition we also give a brief discussion about the multivariate extension of this case. Then we introduce type II bivariate generalized power series Poisson process and consider a bivariate risk model with type II bivariate generalized power series Poisson model as the counting process. For this model we derive distribution of the time to ruin and bounds for the probability of ruin. We obtain partial integro-differential equation for the ruin probabilities and express its bivariate transform through two univariate boundary transforms,where one of the initial capitals is fixed at zero.

The fourth industrial revolution (4IR) can offer significant benefits to the construction sector, improving productivity, efficiency, collaborative efforts, and product quality while promoting safety and sustainability. However, research on the application of 4IR technologies in construction is scarce in developing countries. It is crucial to understand the ability of construction companies to adopt new technologies and identify factors influencing the success of technology implementation. In this study, a questionnaire-based survey was conducted with construction professionals to evaluate the level of technological development of the construction market in an emerging economy, assess the potential for innovation implementation, and identify factors that might influence technological development. Although respondents recognized the importance of digital transformation, the results showed that most innovations are in the early stages of implementation in the construction sector, particularly technologies that are essential for the consolidation of the 4IR. Understanding the factors underlying this reality can support the development of strategies to foster innovation and harness the advantages of the 4IR in the construction industry in developing countries.

Alpinia oxyphylla is a traditional Chinese medicinal plant, with a medicinal history of more than 1,700 years. Ring leaf blight (RLB) disease, caused by pestalotioid species, is an important disease of A. oxyphylla, seriously affecting the yield and quality of fruits. The causal agent of RLB disease has not been systematically identified and characterized so far. In this study, thirty-six pestalotioid strains were isolated from the leaves and stems of A. oxyphylla collected from 6 cities of Hainan province, China. Based on multi-locus phylogeny (ITS, tef-1α and tub2) and morphological characteristics analyses, seventeen species belonging to three genera (Neopestalotiopsis, Pestalotiopsis and Pseudopestalotiopsis) were identified and six new species (N. baotingensis, N. oblatespora, N. olivaceous, N. oxyphylla, N. wuzhishanensis and N. yongxunensis) were described. Pathogenicity tests revealed that strains of Neopestalotiopsis species caused more severe ring leaf blight on A. oxyphylla than strains of Pestalotiopsis and Pseudopestalotiopsis under wounded inoculation conditions.

The quasi-experimental study examines the role of contemporary technologies, such as artificial intelligence and humanoid robots, in enhancing sustainability education for future teachers, emphasizing their impact on shaping sustainable beliefs in future generations. Involving 112 pre-service teachers, the research compares various contemporary and traditional learning methods. Pre- and post-test evaluations were conducted to assess changes in participants’ understanding of sustainability concepts and the variability of their responses. Results reveal significant improvements in sustainability awareness, with methods involving humanoid robots showing higher response variability. The study also identifies the development of new literacies crucial for effectively utilizing advanced technologies in promoting environmental sustainability. While artificial intelligence and humanoid robots match the efficacy of traditional methods, they notably engage young educators more effectively in sustainability topics. These findings highlight the need to integrate such technologies into educational framework to deepen the understanding of environmental issues and prepare youth for future challenges. However, further research is required to explore long-term effects and broader demographics. The research contributes significantly to educational technology and sustainability in education, showcasing the transformative potential of incorporating contemporary technologies in educational settings.

New biomedical technologies are examined in depth and the legal and ethical challenges they pose. Key issues such as gene editing, the application of artificial intelligence in the medical field, and the protection of biological information data are analyzed. At the same time, we also found that technological advances in the development of the enormous potential of biomedicine, but also raises a series of ethical and legal issues. To this end, the paper proposes a series of effective response strategies aimed at providing guidance to policy makers, researchers, and healthcare professionals to ensure the rational and safe application of new technologies. Solutions to these challenges are elaborated. When it comes to gene editing, the article stresses the responsibility of scientists not only to push the boundaries of technology, but also to ensure that edited genes are in the public interest and respect individual rights. To this end, strict regulatory mechanisms should be put in place to ensure that gene editing is carried out only in certain and ethical circumstances. Although AI technology has brought many conveniences to the medical field, it also involves data privacy protection, the transparency of the AI decision-making process, and the impact of AI on traditional medical models. Therefore, it is necessary to formulate corresponding regulations to regulate its application, ensure the fairness and transparency of AI decision-making, and promote its integration and development with traditional medicine. The importance of the protection of biometric data was also emphasized. In biomedical research, a large number of personal biological information data, such as genome and proteome, are often involved. This data should be effectively protected to prevent data leakage and misuse. To this end, it is necessary to strengthen data security measures and establish standards and norms for data sharing and utilization to ensure the rational use and protection of data.

(1) Background: Patients with type 2 diabetes mellitus (T2DM) are at higher risk of cancer but how these two diseases associate is still debated. The goal was the assessment of the overall incidence of cancer among patients with newly diagnosed T2DM in Hungary. Summarizing, incident T2DM is associated with a significantly higher overall risk of incident cancer, with a reverse correlation of age. Newly registered T2DM patients were suggested to be screened for cancer within 6 months. (2) Methods: A nationwide, retrospective, longitudinal study was performed using a Hungarian database. The incident T2DM and diabetes free Hungarian population were included in the study. The primary endpoints were the overall and site-specific incidence and annual percentage change of the incidence of cancer in both populations. (3) Results: The overall incidence of cancer in patients amounted to 29.4/1000 and 6.6/1000 with or without T2DM, respectively, and the OR (95%CI) of cancer of the T2DM group was 4.32 (4.14-4.53), p<0.0001. The risk of having cancer was age-dependent, having the highest odd in the age group 18-39. The incidence of cancer was declining in the non-diabetic but was unchanged in T2DM population. The average lag time of diagnosing a cancer after the detection of T2DM was 3.86 months.; (4) Conclusions: Iincident T2DM is associated with a significantly higher overall risk of incident cancer, with a reverse correlation of age. Newly registered T2DM patients were suggested to be screened for cancer within 6 months.

Cancer, a globally prevalent and often deadly disease, holds promise for improved treatment through the integration of innovative medical technologies and interdisciplinary collaborations. Despite advancements, current cancer therapies lack a specific focus on addressing recurrence and targeting cancer stem cells (CSCs), known contributors to relapse. In this study, we utilized three types of cancer cells and generated three types of CSCs derived from them to conduct proteomic analysis and identified shared cell surface biomarkers as potential targets for a comprehensive treatment strategy. The selected biomarkers underwent evaluation through shRNA treatment, revealing contrasting functions in cancer and CSCs. Knocking down the identified protein showed promising results in regulating epithelial-mesenchymal transition (EMT) and stemness via the ERK signaling pathway. This led to a reduction in resistance to anticancer agents, ultimately enhancing the overall anticancer effects. Additionally, the biomarker's significance in clinical patient outcomes was confirmed using bioinformatics. Our study suggests a novel cancer treatment strategy that addresses existing limitations in current anticancer therapies.

Droughts are a common occurrence in various climates and are primarily caused by a prolonged decrease in rainfall. Several factors contribute to droughts, including temperature, wind speed, relative humidity, rainfall timing, amount, and intensity during the growing season. The objective of this study is to establish a new index, named soil moisture and evapotranspiration revealed drought index (SERDI), for displaying dry and wet conditions based on combining both soil moisture and evapotranspiration (Penman-Monteith) to improve drought early warning and its severity globally. For validation of the SERDI with other indices such as LST, VHI, NDVI, and NDWI, different ways used such as R-square, RMSE, MAPE, and P-value to estimate the accuracy, variability of data, the forecast conditions, and how the significance of data. The results showed that the low RMSE and high r² were found between SERDI with LST and VHI. In contrast, the low R- square and high RMSE were between SERDI with NDVI and NDWI in most of the semi-arid areas. Furthermore, most of the semi-arid areas from Iran, Iraq, Syria, Jordan, and Israel experienced moderate and severe dry conditions, except some parts of these regions had normal conditions in Iran and Syria. The SERDI analysis revealed a strong correlation between (LST) and a moderate correlation with (VHI) across all study areas. However, the relationship between other indices, like (NDWI) and (NDVI), varied depending on the regions. To conclude, SERDI can be used globally for detecting drought based on soil moisture and evapotranspiration.

Several rheumatologic diseases are primarily distinguished by their involvement of bone tissue, where it not only serves as a mere target of the condition but often plays a pivotal role in its pathogenesis. This scenario is particularly prominent in chronic inflammatory arthritis such as rheumatoid arthritis (RA) and spondyloarthritis (SpA). Given the immunological and systemic nature of these diseases, in this review, we report an overview of the pathogenic mechanisms underlying the specific bone involvement, focusing on the complex interactions that occur between bone tissue's own cells and the molecular and cellular actors of the immune system, a recent and fascinating field of interest defined osteoimmunology. Specifically, we have comprehensively elaborated on the distinct pathogenic mechanisms of bone erosion seen in both rheumatoid arthritis and spondyloarthritis, as well as the characteristic process of aberrant bone formation observed in spondyloarthritis. Lastly, chronic inflammatory arthritis lead to systemic bone involvement, resulting in systemic bone loss and consequent osteoporosis, along with increased skeletal fragility.

This article examines how digitalisation is impacting the management of IT. Phase 1 of the re-search focuses on the German automotive industry, and adopts a qualitative inductive approach, based on feedback from 19 semi-structured interviews with IT managers and professionals. Five key aspects of digitalisation are identified, and a new model for the management of IT is devel-oped. Phase 2 then reviews the deployment of digital technologies in eight organisations from other industry sectors and assesses the overall impact on the management of IT. The results suggest that the transition to new IT management structures in the German automotive industry may be the forerunner of a change process that will impact more widely in other industries, in particular where digital technologies are now embedded in an organisation’s products or services. The results also provide some new perspectives on the conceptualisation of digitalisation and digital transformation, and represent a contribution to the developing theory around new tech-nology deployment and IT management in the digital era.

Antibiotics have played a crucial role in the reduction of TB incidence globally as evidenced by the fact that before the mid-20th century, the mortality rate within five years of the onset of the disease was 50%. The use of antibiotics has eliminated TB as a devastating disease, but the challenge of resistance to anti-TB drugs, which had already been described at the time of the introduction of streptomycin, has become a major global issue in disease management. Mismanagement of multidrug-resistant tuberculosis (MDR-TB) cases, resulting from intermittent drug use, prescription errors and non-compliance of patients, has been identified as a critical risk factor for the development of extensively drug-resistant tuberculosis (XDR-TB). Antimicrobial resistance (AMR) in TB is a multi-factorial, complex problem of microbes evolving to escape antibiotics, the gradual decline of antibiotic development, and different economic and social conditions. In this review, we summarise recent advances in our understanding of how Mycobacterium tuberculosis evolves drug resistance. We also highlight the importance of developing shorter regimens that rapidly reach bacteria in diverse host environments, eradicating all mycobacterial populations and preventing the evolution of drug resistance. Lastly, we also emphasise that the current burden of this ancient disease is driven by a combination of complex interactions between mycobacterial and host factors, and that only a holistic approach that effectively addresses all the critical issues associated with drug resistance will limit the further spread of drug-resistant strains throught the community.

There are gravitational field and baryonic matter (star, planet, gases etc.) in our world; gravitational field is much more fundamental for that the relativistic mass of the gravitational field of a neutron star is almost 10²¹ times the mass of the neutron star. And, it is astonishing that the relativistic mass density of the gravitational field on the surface of a neutron star can be larger than the mass density of the neutron star. It is well known that, in the weak gravitational field a light line appears a straight line while in the strong field it is a curved line. It is stressed that the result measured in the strong field is more fundamental for that in a galaxy the measurable object is generally with strong field. It results in that the way that the result measured on the Earth with weak field is used as the universal standard need be revised as gravity is studied in the scale of a galaxy. It seems that a new theory of gravity need be developed for the new observations.

Daniel Yergin’s “The New Map: Energy, Climate, and the Clash of Nations” is a remarkable and groundbreaking work that addresses the ever-changing global energy landscape and its profound geopolitical implications. In this modest book review, we aim to offer a fresh perspective by re-examining the core issues from the standpoint of political geography. The aim of this article is twofold: to enrich the existing literature on political geography and to provide valuable insights to students of geography to broaden their knowledge in this field.

Helicosporous hyphomycetes is a class of filamentous fungi that shows promising application prospects in metabolizing bioactive natural compounds. During a study of helicosporous fungi in China, six new helicosporous taxa were collected and isolated from decaying wood in Guangxi Zhuang Autonomous Region, China. Morphological comparisons with multi-gene phylogenetic analyses revealed that these six taxa belong to Helicosporium (Tubeufiaceae, Tubeufiales), and they can be recognized as three novel species, named Helicosporium liuzhouense, H. multidentatum and H. nanningense. Detailed descriptions and illustrations of the newly discovered taxa and comparisons with similar fungi are provided. In addition, a list and a key to accepted Helicosporium species are provided.

Coffee berry borer (CBB), Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae: Scolytinae), is the pest that causes the most economic damage to coffee crops. Chemical control of this insect is based on the use of insecticides that can affect the environment and nontarget organisms. Despite the fact that caffeine has shown potential as an insecticide, a caffeine-based product for field use is currently not available on the market. As a new alternative to control CBB and other coffee pests, such as Monalonion velezangeli, a caffeine-oleate was developed. The caffeine oleate formulation showed laboratory efficacy by causing mortality of more than 90% of CBB adults in preventive tests in which the insecticide was sprayed prior to insect attack on the coffee fruits. In the curative tests, in which spraying occurred after CBB infested the fruits, the formulation caused 77% mortality of the insects. Under controlled field conditions, the product kept CBB infestation below 20%, reducing the number of fruits attacked by the insect by up to 70%. In addition, no phytotoxic effects were observed in coffee plants. The insecticide was also effective against M. velezangeli causing 100% mortality. A caffeine oleate formulation that could be part of a strategy for integrated CBB management as well as other pests of coffee was developed. The components of the insecticide are food grade; the product would provide greater security to the coffee ecosystem and coffee growers.

The use of isolated supplements to enhance performance is widespread among athletes. The aim of this study was to increase knowledge about the combined effects of caffeine and New Zealand blackcurrant (NZBC) dietary supplements. In this study, two subjects each underwent four phases of four sessions in a double-blind and randomized alternating treatment single-case design. After a 3-week pre-test phase, the supplement combinations of placebo/placebo, caffeine/placebo (5 mg/kg), NZBC/placebo (600 mg), and caffeine/NZBC (5 mg/kg + 600 mg) were taken and weekly performance tests were conducted to examine their effects on relative power (W/kg) during a 20-minute time trial on a bicycle. Data were analyzed descriptively and using the Tau-U calculator from Single Case Research. The ergogenic effect of caffeine was confirmed in both subjects, with increases of 3.3% and 6.5%, while the positive effect of NZBC on performance was only seen in one subject (13.4%). The combination of caffeine and NZBC again increased performance in both subjects (2.2% and 19.2%), but the data only showed an additive effect of the supplements in one subject. Further studies are required to confirm or refute this evidence of the synergistic effects of these supplements.

To promote low-carbon and green travel, this study proposes a tripartite evolutionary game model among new energy vehicle manufacturers, consumers, and government agencies. The game strategy combinations of each party and the stability conditions of the equilibrium point in the evolutionary game system are analyzed, and the validity of the conclusions is verified through simulation results. The study shows a strong correlation between the three parties in the evolutionary game system. From the perspective of car manufacturers, the probability of producing new energy vehicles is positively proportional to the subsidy received from new energy policy, the additional revenue gained from the management of the carbon trading scheme, and the fine received for producing conventional fuel vehicles. However, from the consumer perspective, the likelihood that consumers purchase new energy vehicles is positively related to the utility value to consumers and the coverage of public charging points in the city, and inversely related to the sales price of new energy vehicles. From the government perspective, a combination of direct subsidy policies and indirect support strategies should be considered to stimulate the rapid development of the new energy vehicle industry.

Leishmaniasis is a tropical disease caused by a protozoan parasite Leishmania that is transmitted via infected female sandflies. At present, leishmaniasis treatment mainly counts on chemotherapy. The currently available drugs against leishmaniasis are costly, toxic, with multiple side effects, and limitations in the administration route. The rapid emergence of drug resistance has severely reduced the potency of anti-leishmanial drugs. As a result, there is a pressing need for the development of novel anti-leishmanial drugs with high potency, low cost, acceptable toxicity, and good pharmacokinetics features. Due to the availability of preclinical data, drug repurposing is a valuable approach for speeding up the development of effective antileishmanial through pointing to new drug targets in less time having low costs and risk. Metabolic pathways of this parasite play a crucial role in the growth and proliferation of Leishmania species during the various stages of their life cycle. Based on available genomics/proteomics information, known pathways-based (sterol biosynthetic pathway, purine salvage pathway, glycolysis, GPI biosynthesis, hypusine, polyamine biosynthesis) Leishmania-specific proteins could be targeted with known drugs that were used in other diseases, resulting in finding new promising anti-leishmanial therapeutics. The present review discusses various metabolic pathways of the Leishmania parasite and some drug candidates targeting these pathways effectively that could be potent drugs against leishmaniasis in the future.

Rheumatoid arthritis (RA) is a chronic, systemic, abnormal inflammatory immune response. It is characterized by the involvement of the synovium and multiple organs and the destruction of joints and articular cartilage. Over the past 30 years, several promising novel compounds and antibodies have been developed for the treatment of RA. The introduction of new drugs and precision medicine for all forms of RA raises several issues related to access to novel treatments by patients, optimal regimen selection, cost-effectiveness, prognosis monitoring and outcome surveillance, particularly with regarding to the development of low drug response rates, drug resistance and adverse side effects. Tremendous attention has been given to the identification of optimized drug combinations for the treatment of RA, particularly in early high-risk vulnerable and early individuals. Addressing these issues requires novel therapeutic approaches with new mechanisms and the establishment of accurate guidelines for drug selection, drug recombination, and non-chemical therapeutic efforts. In this study, we reviewed the most exciting recently established or ongoing novel drugs and methods according to the clinical trial database maintained by the United States National Library of Medicine and discussed the trends in RA drug development and challenges in the treatment, providing a reference significant for the accurate treatment of RA and the research direction in the future.

Background: There is a high bureaucratic and administrative burden associated with health care tasks (test requesting, visits scheduling, supporting documents provision) that has historically largely fallen on health care professionals, which is one among the factors contributing to low job satisfaction and lower productivity. Incorporating new professional roles that help to better respond to the needs of both patients and professionals can increase the quality and efficiency of service provision. Objective: To evaluate the impact of the clinical assistant’s introduction in the Sant Joan de Déu Barcelona Children’s Hospital’s pediatric oncology department, in terms of displacement of activity loads carried out by this new professional role and the consequent time freed up for physicians. Methodology: Observational and retrospective study using administrative data based on the analysis of the type of activity performed by clinical assistants and the measurement of the time freed up in favor of the physicians, based on in situ timekeeping, to approximate the potential skill mix productivity increase. Results: Since its implementation in the pediatric oncology department, clinical assistants have performed 13,553 requests (69.93% of the total), representing a total saving of 266.83 hours or 6.67 workweeks of 40 hours. They performed 74.25% of outpatient surgical requests in the oncology department, 87.5% of day hospital requests and 54.13% of total requests in the outpatient consultations area. Conclusion: The introduction of clinical assistants in the oncology department could be efficient to the extent that it displaces a good part of the bureaucratic and administrative tasks previously performed by health care professionals. This delegation allows them to work more closely to the maximum of their competences and the physicians to have more time for higher added value clinical tasks. In terms of efficiency, this role change enables to optimize the clinical process, reducing the cost by 56% compared to the conventional model.

Popular devotions are reflections and expressions of the people’s faith. They are expressions of how people recognize God in their lives, and as a shared experience, they foster expressions of devotion and thus become a manifestation of prayer. Popular devotions as forms of prayer and worship do not contradict the Sacred Liturgy but are acknowledged as legitimate by the Apostolic See. Moreover, popular devotions, in general, lead to the cultivation of some values. One of the most popular devotions among Filipino Catholics is the devotion to the Black Nazarene, a life-sized statue of Jesus Christ kneeling in one knee carrying the cross-dressed in a maroon robe. His face is marked with wounds and blood. His head is crowned with thorns with three gold-plated metal rays on the top of his head, with his eyes looking up to heaven. The Black Nazarene devotion balances Christology from below and above, i.e., Christ does not remain crucified. Instead, he brings the hope of resurrection to those who fervently approach him with faith, hope, and love. It suffices to say that the Black Nazarene serves as a means for the Filipino faithful to encounter Christ in their lives. Given this, this paper aims to appraise the Black Nazarene Devotion as a means that contributes to the New Evangelization among Filipino Catholics. More specifically, this paper seeks to answer how the devotion to the Black Nazarene aids Filipino Catholics in their desire to sustain and grow in their faith amidst the crises and problems they are facing.

Current acceleration in digital innovations, unexpected challenges in our social interactions, acceleration to virtualization, limitation in our physical spaces, and unpredictable changes in our Old lifestyles - as originated from the COVID-19 global pandemic 2020 - continue to provide us with a framework, rapidly updating under our eyes, of the modifications our world is undergoing by pursuing into a New “digital age”. Or, as many scholars say nowadays, into the New Normal! These are shared and deep changes that concretely stress their effects on how ideally a city should function. Forcing us to reflect on the capability to achieve shared choices and visions for the future by taking vantage from both the New digital platforms and New suddenly opened paths. In the pages of this article authors, through different but shared viewpoints, propose an answer to the topic of "Governance 3.0", addressing the attempt of a radical change of those paradigms, now consolidated, within which the spatial dimensions, in which we live and act, are shaped. Also analyzing the relationship between Technocracy and Democracy as defined by Khanna, it is argued that it is possible to realize new forecasts and acquire a more democratic and participatory (inclusive) dimension of Governance, also thanks to new digital technologies, by exploring the general unconscious "feeling" of people, through anonymous data collection and without any direct or indirect interference with it. The analysis of the "Sentiment", already developed in other fields but easily exportable within the urban discipline, can be considered as the beginning of hybrid practices where digital and analogic find a compromise to make the "Urbs" more attractive and inclusive, while the "Civitas", connected to the Internet, can contribute to the optimization of services, of the "Polis" and a new social/spatial reorganization.

The world is currently facing a serious pandemic of coronavirus disease 2019 (COVID-19) which started in Wuhan, China, and was then transmitted rapidly to other countries. Countries applied different methods and procedures in an attempt to prevent or reduce and/or control the incidence of cases and manage existing ones. This paper discusses the methods and procedures applied by Kuwait to control this epidemic, and how effective they have been. The State of Kuwait followed WHO, European CDC, US CDC, and/or other countries’ institutional guidelines, and is still working on containing the disease, given the rising number of cases among Kuwaitis returning from affected areas such as the UK and USA, and migrant workers who bear the highest burden, given their cramped living conditions.

Identification of costs drivers and their influence level on building development costs play a key role in the development of construction models and improve the efficiency and effectiveness of any project. Forty-five indicators influencing building development costs in New Zealand are explored by literature review and pilot interviews. These indicators are grouped into seven categories. The determination and ranking of the cost drivers are carried out by a questionnaire survey distributed to key professionals working in New Zealand’s construction industry. Structural equation modeling (SEM) software was employed for analysis of the collected data. One of the key advantages of this powerful software is to provide the p-value according to the structure of the research model. Findings of this study indicate that the property market and construction industry factor, statutory and regulatory factor, and socio-economic factor are major factors affecting building development costs in New Zealand.

Societies around the world face serious energy problems related to the consumption of fossil fuels and the emission of dangerous radiation. To solve these problems, a new superconductor exhibiting a critical temperature higher than room temperature has been pursued but not achieved. This paper proposes a new energy generation system based on a circuit approach. Secondary to this process, a new type of superconductivity without refrigeration is demonstrated. In our previous paper [1], this system was proposed, but it did not describe the underlying theory in detail and did not mention an actual method to generate energy from the system. The present paper describes the theory of the existence of divergent current density and new superconductivity with no refrigeration. Moreover, the present paper proposes a method for extracting energy from the system by employing a voltage-controlled current source (i.e., a voltage–current converting method).The principle of the system is based on a circuit of two loops and independent current sources. First, the two electric loops are prepared, each with 4 diodes, where the diodes are oriented in the same direction within each loop, but their direction is opposite from loop to loop; four independent current sources connect the loops. In this circuit system, current is added iteratively as it flows along the loop according to Kirchhoff’s circuit law. As a result, a large current and electric potential are present along the loop. To confirm that this system works properly, it is necessary to demonstrate the presence of divergent currents in the transient state, and to do this, the present paper employs the Dirac equation and Lorentz conservation. Electric circuit software is employed to demonstrate that the presented method generates energy actually from our system.Our results confirm the presence of divergent current at a connected point of an independent current source in the transient state. Moreover, in the steady state, the theory demonstrates the Meissner effect (i.e., a London equation) and a new type of macroscopic wave function and condensation. For an initial small input current of 0.1 μA, the simulation reveals a large generating current of 7 kA and electric power of 10¹¹ W, which is much larger than unit of power from an average thermal power station; moreover, the system presents with superconducting electrical transport conditions.The present study is significant because it demonstrates theoretically the existence of divergent current density and a new type of superconductivity requiring no refrigeration. Secondly, the simulations show the generation of a large energy density that can be obtained in a small laboratory room with minimal cost.

Modelling diameter distribution is an integral part of forest management. It requires the use of a suitable probability density function or cumulative distribution function with the appropriate fitting method. In this study, we compared the suitability of eight probability density functions fitted by derivative and optimization methods used for diameter distribution estimation of forest stands. The derivation and optimization were used on A Charlier, beta, generalized beta, gamma, Gumbel, Johnson’s SB, and Weibull (2 and 3-parameter). We used data from 167 permanent sample plots from Atlantic forest (Quercus robur) and 59 temporary sample plots from tropical forests (Tectona grandis). The quality of the fits was evaluated with different indices such as Kolmogorov–Smirnov, Cramer-von Mises, mean absolute error, bias and mean squared error. The results showed Johnson’s SB function was more suitable for describing the diameter distribution of the stands. Johnson’s SB, 3-parameter Weibull and generalized beta had consistent performance regardless of the fitting methods. The quality of fits produced by gamma, Gumbel and 2-parameter Weibull was poor.

Applications of gradient method for nonlinear optimization in development of Gradient Neural Network (GNN) and Zhang Neural Network (ZNN) are investigated. Particularly, the solution of the matrix equation AXB=D which changes over time is studied using the novel GNN model, termed as GGNN(A,B,D). The GGNN model is developed applying GNN dynamics on the gradient of the error matrix used in the development of the GNN model. The convergence analysis shows that the neural state matrix of the GGNN(A,B,D) design converges asymptotically to the solution of the matrix equation AXB=D, for any initial state matrix. It is also shown that the convergence result is the least square solution which is defined depending on the selected initial matrix. A hybridization of GGNN with analogous modification GZNN of the ZNN dynamics is considered. The Simulink implementation of presented GGNN models is carried out on the set of real matrices.

To avoid loss of information and incorrect ranking, this paper proposes a method for ranking generalized fuzzy numbers, which guarantees both horizontal and vertical values are important parameters affecting the final ranking score. In this method, the normalized height coefficient is introduced to evaluate the influence of the height of fuzzy numbers on the final ranking score. The higher the normalized height coefficient of a fuzzy number is, the higher its ranking. The left area and the right area are presented to calculate the impact of vertical value on the final ranking score. The left area is considered the benefit area. The right area is considered the cost area. The fuzzy number is preferred if the benefit area is larger and the cost area is smaller. The proposed method can be employed to rank both normal and non-normal fuzzy numbers without normalization or height minimization. Numerical examples and comparison with other methods highlight the feasibility and robustness of the proposed method, which can overcome the shortcomings of some existing methods and can support decision-makers to select the best alternative.

Background: Residents of a large area of North-Eastern Italy were exposed for decades to high concentrations of perfluoroalkyl and polyfluoroalkyl substances (PFAS) via drinking water. Despite the large amount of evidence in adults of a positive association between serum PFAS and metabolic outcomes, studies focusing on children and adolescents are limited. We evaluated the associations between serum PFAS concentrations and lipid profile, blood pressure and body mass index (BMI) in highly exposed adolescents and children. Methods: A cross-sectional analysis was conducted in 6669 adolescents (14-19 years) and 2693 children (8-11 years) enrolled in the health surveillance program of the Veneto Region. Non-fasting blood samples were obtained and analyzed for perfluorooctanoic acid (PFOA) perfluorooctane sulfonate (PFOS), perfluorohexanesulfonic acid (PFHxS), perfluorononanoic acid (PFNA), total cholesterol (TC) high-density lipoprotein cholesterol (HDL-C) and triglycerides. Low-density lipoprotein cholesterol (LDL-C) was calculated. Systolic and diastolic blood pressure (BP) were measured and BMI z-score accounting for age and sex was estimated. The associations between ln-transformed PFAS (and categorized into quartiles) and continuous outcomes were assessed using generalized additive models. Analyses were stratified by gender and adjusted for potential confounders. Results: Among adolescents, significant associations were detected between all investigated PFAS and TC, LDL-C, and to a fewer extent HDL-C. Among children, PFOS and PFNA had significant associations with TC, LDL-C and HDL-C, while PFOA and PFHxS had significant associations with HDL-C only. Increased serum concentrations of PFAS, particularly PFOS, were associated with decreased BMI z-score. No statistically significant associations were observed between PFAS concentrations and BP. Conclusions: Our study supports a consistent association between PFAS concentration and serum lipids, stronger for PFOS and PFNA and with a greater magnitude among children compared to adolescents, and a negative association of PFAS with BMI.

The Simplified Spherical Harmonic (SPN) approximation was first introduced as a three-dimensional (3-D) extension of the plane-geometry Spherical Harmonic (PN) equations. A third order SPN (SP3) solver, recently implemented in the Nodal Expansion Method (NEM), has shown promising performance in the reactor core neutronics simulations. This work is focused on the development and implementation of the transport corrected interface and boundary conditions in NEM SP3 solver, following recent published work on the rigorous SPN theory for piecewise homogeneous regions. A streamlined procedure has been developed to generate the flux zero and second order/moment discontinuity factors (DFs) of the generalized equivalence theory to eliminate the error introduced by pin-wise homogenization. Moreover, several color set models with varying size and configuration are later explored for their capability of generating DFs that can produce results equivalent to that using the whole-core homogenization model for more practical implementations. The new developments are tested and demonstrated on the C5G7 benchmark. The results show that the transport corrected SP3 solver shows general improvements to power distribution prediction compared to the basic SP3 solver with no DFs or only zero order/moment DFs. The complete equivalent calculations using the DFs can almost reproduce transport solutions with high accuracy. The use of equivalent parameters from larger size color set models show better prediction in the whole-core calculations. By coupling different color set models DFs can offer the best accuracy at both eigenvalues and power distributions.

The non-linear analysis of hollow-core concrete slabs requires the use of advanced numerical techniques, proper constitutive models both for concrete and steel as well as particular computational skills. If prestressing, cracking, crack opening, material softening, etc. are also to be taken into account, then the computational task can far exceed the capabilities of an ordinary engineer. In order for the calculations to be carried out in a traditional design office, simplified calculation methods are needed. Preferably based on the linear finite element (FE) method with a simple approach that takes into account material nonlinearities. In this paper the simplified analysis of hollow-core slabs based on the generalized nonlinear constitutive law is presented. In the proposed method a simple decomposition of the traditional iterative linear finite element analysis and the non-linear algebraic analysis of the plate cross-section is used. Through independent analysis of the plate cross-section in different deformation states, a degraded plate stiffness can be obtained, which allows iterative update of displacements and rotations in the nodes of the FE model. Which in turn allows to update the deformation state and then correct translations and rotations in the nodes again. The results obtained from the full detailed 3D nonlinear FEM model and from the proposed approach are compared for different slab cross-sections. The obtained results from both models are consistent.

The goal of clustering is to identify common structures in a data set by forming groups of homogeneous objects. The observed characteristics of many economic time series motivated the development of classes of distributions that can accommodate properties such as heavy tails and skewness. Thanks to its flexibility, the Skewed Exponential Power Distribution (also called Skewed Generalized Error Distribution) ensures a unified and general framework for clustering possibly skewed and heavy tailed time series. This paper develops a clustering procedure of model-based type, assuming that the time series are generated by the same underlying probability distribution but with different parameters. Moreover, we propose to optimally combine the estimated parameters to form the clusters with an entropy weighing $k$-means approach. The usefulness of the proposal is showed by means of application to financial time series, demonstrating also how the obtained clusters can be used to form portfolio of stocks.

As paradigm of complex behavior, multifractals describe the underlying geometry of self-similar objects or processes. Building on the connection between entropy and multifractals, we show here that the generalized dimension of geodesic trajectories in General Relativity coincides with the four-dimensionality of classical spacetime.

In this paper, a new identity for the generalized fractional integral is defined, through which new integral inequality for functions whose first derivatives in absolute value are convex. The new generalized Hermite-Hadamard inequality for generalized convex function on fractal sets involving Katugampola type fractional integral is established. We derive trapezoid and mid-point type inequalities connected to these generalized Hermite-Hadamard inequality.

The generalized Kuramoto–Sivashinsky equation is investigated using the modified Kudrayshov method for the exact analytical solution. The modified Kudrayshov method converts the nonlinear partial differential equation to algebraic equations, as a result of various steps, which on solving the so obtained equation systems yields the analytical solution. By this way various exact solutions including complex structures are found and drawn their behaviour in complex plane by Maple to compare the uniqueness of solutions.

Early detection of neurological conditions is critical for timely diagnosis and treatment. Identifying cellular-level changes is essential for implementing therapeutic interventions prior to symptomatic disease onset. However, monitoring brain tissue directly through biopsies is invasive and high-risk. Bodily fluids such as blood or cerebrospinal fluid contain information in many forms, including proteins and nucleic acids. Particularly, cell-free DNA (cfDNA) has potential as a versatile neurological biomarker. Yet, our knowledge of cfDNA released by brain tissue and how cfDNA changes in response to deleterious events within the brain is incomplete. Mapping changes in cfDNA to specific cellular events is difficult in vivo, where many tissues contribute to circulating cfDNA. Organoids are tractable systems for examining specific changes consistently in a human background. However, few studies have investigated cfDNA released from organoids. Here, we examined cfDNA isolated from cerebral organoids. We found that cerebral organoids release quantities of cfDNA sufficient for downstream analysis with droplet-digital PCR and whole-genome sequencing. Further, gene ontology analysis of genes aligning with sequenced cfDNA fragments revealed association with terms related to neurodevelopment and autism spectrum disorder. We conclude that cerebral organoids hold promise as tools for the discovery of cfDNA biomarkers related to neurodevelopmental and neurological disorders.

Sunflower is one of the oil crops and its planting areas was listed behind Soybean, peanut and rapeseeds in China. It will encounter different kind of diseases during planting, thus limited the seeds yield. Fusarium species are the major threat to different crops nowadays, it is very important to identify the species caused diseases on different hosts, so that the potential control measures may be explored. In Inner mongolia, Sunflower Disk Rot (SDR) was found in different sunflower planting field, the average infection ratio around 8.50%, typically in some verieties, its infection ratio reach to 11.67%. The diseased receptacle were collected from different locations and Koch’s postulate was conducted. The results showed that Fusarium verticillioides was the main causal agent caused SDR. Fungicide toxicity tests shown that Fludioxonil and Flutolanil were screened out from six fungicides for controlling F. verticillioides, with EC50 values of 0.05 µg/mL (R = 0.9825) and 0.96 µg/mL (R = 0.9964) , respectively. This is the first report of SDR caused by F. verticillioides, and it will alert sunflower reseachers to include SDR in the disease list, so as to control sunflower diseases with integrated management strategy successfully.

In contrast to its traditional form, in which large, powerful companies were solely and exclusively responsible for supplies, manufacturing, and distribution, the supply chain has undergone substantial change over the past half-century. Today, nearly all supply chain processes are outsourced, thanks to the efforts of innovative, modern companies. The degree of risk associated with contemporary supply chains is greater than the majority of supply chain managers acknowledge, according to an accumulation of studies, analysts, and news outlets. Vulnerabilities within the supply chain remain a significant challenge for numerous organizations. Inadequate management of these risks—which include, but are not limited to, natural disasters, acts of terrorism, cyber assaults, the credit crisis, pandemic scenarios, and war—could lead to significant declines in profitability, productivity, revenue, competitive advantage, and other metrics. Concerns regarding the risk assessment of the supply chain remain unresolved. The objective of this article is to present a risk evaluation framework that can be effectively implemented in the assessment of supply chain risks. This study makes a fundamental contribution to the body of knowledge by providing supply chain managers with a practical instrument for assessing their processes, irrespective of the mathematical underpinnings or the diverse variables employed in risk assessment. A case study from an automotive EMS production is used to compare the outcomes of multiple aggregation methods; the conclusions are then validated by risk and FMEA specialists from the same factory.

In order to alleviate the conflict between populations and land-resource, Tianjin has adopted multi-phase reclamation projects to formed large-scale artificial reclamation land. However, the reclamation areas are susceptible to subsidence, which demonstrate a serious threat to infrastructure and people’s lives and property. The SBAS-InSAR was used to acquired surface deformation of Tianjin Binhai New Area from January 2017 year to December 2022 year, analyzed in depth the response relationship between land subsidence and reclamation projects time as well as the land use type. The results show that the Lingang Industrial Zone was the earliest to be reclaimed, with extensive reclamation completed by 2016 year, while Nangang Industrial Zone and Hangu Port started reclamation projects in 2009 year, some areas are still currently under construction. There is a strong correlation between surface deformation and reclamation time, the severe land subsidence occurred over newly reclaimed areas. Surface deformation gradually intensifies from west to east, the maximum surface settlement in Nangang Industrial Zone, Lingang Industrial Zone from the west to the east has changed from -50 mm to -890 mm,45 mm to -580 mm, respectively, reclamation area of Hangu Port with maximum surface deformation is -250 mm. Significant differences deformation among different land use types, which reclamation projects completed in the same time. Subsidence is positively correlated with surface load, in areas with higher surface loads, the surface settlement is also severer,the average surface settlement for the heavy shipyard, 67 grain storage tanks, 27 grain storage tanks, road, and bare land are -201 mm, -166 mm, -107 mm, -64 mm, and -43 mm, respectively. This study reveals significant differences of surface deformation in the reclamation completed at different times and the load is the main driving factor of settlement difference in the reclamation land completed at the same time. Which has important guiding significance for preventing and controlling geological disasters in the reclamation area and later development planning.

Due to the variation of the body coloration and the similarity of the related species, there are still some unresolved problems and debates in the taxonomic study of the genus Sycanus in China. We conducted the inter-specific phylogenetic analyses and the species delimitation for Sycanus in China based on DNA barcoding dataset of the mitochondrial cytochrome c oxidase subunit I gene of 81 samples and partial 28S rDNA sequences of 34 samples. The result showed that all the samples were divided into twelve species by integrating the results of DNA barcoding and morphological comparison. In the present paper, the genus Sycanus in China was reviewed systematically, all species were described or re-described, keyed, illustrated and photographed, among them, Sycanus taiwanensis Zhao & Cai sp. nov., Sycanus flavicorius Li & Cai sp. nov. and Sycanus hainanensis Wang & Cai sp. nov. were described as new to science. The biological informations of Sycanus falleni Stål, 1863 and Sycanus croceus Hsiao, 1979 were briefly recorded.

This qualitative research examines the quality assurance practices in private school institutions in Iligan City during the first semester of 2020-2021. The study involves interviews with 30 school administrators and document analysis to uncover key themes and sub-themes. The findings reveal the significance of clear policies, professional development for teachers, stakeholder engagement, assessment strategies, and technology utilization in quality assurance. The study also identifies challenges such as the need for standardized assessment procedures, limited resources for professional development, and the integration of technology. Moreover, it emphasizes the importance of adaptability and flexibility in the face of changing educational landscapes, particularly during the COVID-19 pandemic. Recommendations for further research include conducting a comparative analysis between private and public school institutions, investigating the long-term impacts of the pandemic on quality assurance, and exploring innovative strategies for online and blended learning environments. The paper concludes by highlighting the importance of addressing challenges and embracing new perspectives in quality assurance to improve the overall quality of education. The implications of the study emphasize the need for comprehensive quality assurance frameworks that encompass all aspects of education and the importance of ongoing evaluation and improvement. Ultimately, this qualitative research article contributes valuable insights for private school institutions and educational policymakers to enhance their quality assurance practices and provide better educational experiences for students.

The free energy principle (FEP) is a mathematical and scientific principle that describes the relationship between the physical behavior of a dynamical system and the interpretation of such behavior as carrying out inference. It blurs the boundary between the ontological mode of the system of interest and the epistemological significance it acquires through its dynamic interaction with the environment. New materialism (or neo-materialism), despite lacking a single definition, refers to a range of emerging perspectives that attempt to dismantle the long-held divisions between ontology, epistemology, and even ethics, with the aim of achieving a comprehensive transformation of naturalized thinking. In this context, new materialism provides powerful tools to reframe some of the conceptual foundations of the FEP. This paper is the first in a series that aims to systematically construct a neo-materialistic perspective for the FEP, exploring its wide-ranging implications. It serves as an introduction to the series, arguing for the justification of deploying new materialism to reframe the FEP and introducing some essential concepts to be utilized in developing a neo-materialistic account of the FEP.

The present work concerns with presenting an explicit formula for new shifted wavelet (NSW) functions. Wavelet functions have many applications and advantages in both applied and theoretical fields. They are formulated with different orthogonal polynomials to construct new techniques for treating some problems in sciences, and engineering. A new important differentiation property of NSW in terms of NSW themselves is obtained and proved in this paper. Then it is utilized together with the state parameterization technique to find solution of optimal control problem (OCP) approximately. The suggested method converts the OCP into a quadratic programming problem, which can be easily determined on computer. As a result, the approximate solution closes with the exact solution even with a small number of NSW utilized in estimation. The error bound estimation for the proposed method is also discussed. Some test numerical examples are solved to demonstrate the applicability of the suggested method. For comparison, the exact known solutions against the obtained approximate results are listed in Tables.

Few studies have examined the role of mediating mechanisms played by bricolage in the relationship between strategic flexibility and new product development, even though most of the studies view strategic flexibility as a capability to cope with environmental turbulence and promote product innovation. The bricolage approach embraces the resource-based understanding of the product development process as a concrete process of recombining resources in the process and exploring the mechanisms behind the bricolage approach. This study is the first of the kind that has examined the empirical effect of environmental turbulence on new product development through serial mediation of strategic flexibility and bricolage. Based on our results, environmental turbulence positively and significantly affects new product development through the serial mediation of strategic flexibility and bricolage. Bricolage is one of the mechanisms by which strategic flexibility may play a part in supporting product innovation. Our contribution to strategic flexibility research comes from examining the effect of strategic flexibility on bricolage and new product development from the point that environmental turbulence compels the high-tech industries to remain strategically flexible for their sustainability and growth. Besides providing new evidence on the relationship between environmental turbulence and product innovation, this research also provides new insight into the economic opportunity of new product development in transition economies such as China.

Background: While several drugs are in the pipeline for treatment of various grades of COVID-19 disease, none of them have shown promise until now. Medicinal plants are crucial in developing and developed countries for their primary and basic health needs owing to better tolerability, superior compatibility with human body and having lesser side effects. AEV01 , a speciality extract of kutki (Picrorhiza kurroa), is one potential medicinal herb which can be effective for mild COVID19 in elderly patients at risk of complications and aging immunity. Purpose: The efficacy and safety of AEV01 for mild COVID-19 in elderly patients at risk of complications was investigated in this study. Study design: A prospective, phase 3, randomized, multicentric, placebo controlled double blinded parallel group interventional trial. Methods: This study was conducted in elderly patients diagnosed as COVID-19 with mild symptoms. 70 patients were randomized into two groups to receive AEV01 capsule (100mg) and placebo respectively thrice daily for 30 days along with standard care of treatment as per national WHO/ICMR guidelines. Clinical improvement timelines and corresponding scores using 8-point ordinal scale and NEWS were assessed for efficacy and safety of AEV01 in COVID-19 patients. Results: AEV01 group showed a significant improvement (P=0.0001) in the normalization of the SpO₂ rate and relief from cough. There was also significant difference in time to recovery, with patients in the AEV01 drugtreated group recovering in 4.5 days as compared to Placebo in 9.1 days. ESR, LDH, serum ferritin, Neutrophil-Lymphocyte ratio (NLR), TNF- alpha, IL-6 and CD4 cell counts, which are considered as prognostic markers in COVID19 infected patients, showed a significant improvement in patients treated with AEV01. The AEV01 drug treated group showed significant clinical improvement in the 8-point ordinal scale severity rating and NEW Score from day 3 onwards which continued up to end of study. Conclusion: AEV01 has shown a significant improvement in clinical and laboratory parameters. There was also reduction in the progression of the COVID-19 disease in unvaccinated elderly patients from mild to moderate when treated at an earlier stage.

A very strong earthquake of magnitude Mw8.2 struck the coastal zone of Alaska (USA), on July 29, 2021. This earthquake was felt around the Gulf of Alaska, on a wide offshore area belonging to USA and Canada. In order to identify an anomalous geomagnetic signal before the onset of this earthquake, we retrospectively analyzed the data collected on the interval June 17 - July 31, 2021, via internet (www.intermagnet.org), at the two geomagnetic observatories, College (CMO) - Alaska and Newport (NEW)-USA, by using the polarization parameter (BPOL) and the strain effect–related to geomagnetic signal identification. Thus, for the both observation sites (CMO and NEW), the daily mean distribution of the BPOL and its standard deviation (STDEV) are carried out using an FFT band-pass filtering in the ULF range (0.001-0.0083Hz). Further on, a statistical analysis based on a standardized random variable equation was applied to emphasize the following: a) the anomalous signature related to Mw8.2 earthquake on the both time series BPOL*(CMO) and BPOL*(NEW); b) the differentiation of the transient local anomalies associated with Mw8.2 earthquake from the internal and external parts of the geomagnetic field, taking the NEW observatory as reference. Finally, on the BPOL*(NEW-CMO) time series, carried out on the interval 07-31 July, 2021, a very clear anomaly of maximum, greater than 1.2 STDEV, was detected on July 22, with 7 days before the onset of Mw8.2 earthquake

Based on the institutional theory and resource-based theory and the "institution-strategy-performance" research paradigm, this research explores the mechanism of institutional support on the innovation performance of new ventures, focusing on the mediating role of entrepreneurs and the moderating role of innovative resource acquisition. An empirical analysis based on 278 survey samples shows that: ① (formal/informal) institutional support positively affects the innovation performance of new ventures; ② entrepreneurial orientation plays an intermediary role between institutional support and innovation performance of new ventures; ③ innovation resource acquisition not only positively regulates the relationship between entrepreneurial orientation and innovation performance of new ventures, but also enhances the mediation of entrepreneurial orientation between institutional support and innovation performance. The conclusion shows that institutional support plays an important role in the innovation practice of new ventures, and can provide guidance for the innovation management practices of new ventures.

Urban areas have very complex spatial structures. These spatial structures are primarily composed of a complex network of built environments, which evolve rapidly as the cities expand to meet the growing population’s demand and economic development. Therefore, studying the impact of spatial structures on urban heat patterns is extremely important for sustainable urban planning and growth. We investigated the relationship between surface temperature obtained by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER, at 90 m spatial resolution) on the current EOS-Terra platform and different urban components based on the classification of high-resolution QuickBird imagery. We further investigated the relationships between surface temperature and building footprint and land use information acquired from the New York City (NYC) Department of City Planning. The ASTER image reveals fine-scale urban heat patterns in the NYC metropolitan region. The dark and medium-dark impervious surfaces, along with bright surfaces, generate higher surface temperatures. Even with highly reflective urban materials, the presence of impervious materials leads to an increased surface temperature. At the same time, trees and shadows are effective in reducing urban heat. The data aggregated to the census tract reveals high-temperature clusters in Queens, Brooklyn, and the Bronx region of NYC. These clusters are associated with industrial and manufacturing areas and multi-family walk-up buildings as dominant land use. The census tracts with more trees and higher building height variability generate lower surface temperatures, consistent with shadow cast by high-rise buildings and trees. The results of this study can be valuable for urban heat island modeling on the effects of building heights variability and tree shadows on small-scale surface temperature patterns. It can also help identify the risk areas during extreme heat events to protect public health.

The innovation of the new psychoactive substances (NPS) market requires the rapid identification of new substances that can be a risk to public health, in order to reduce the damage due to their use. Twelve seized products suspected to contain illicit substances were analyzed by attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), gas chromatography coupled to mass spectrometry (GC-MS), and nuclear magnetic resonance spectroscopy (NMR). Synthetic cathinones (SCat) were found in all products, either as a single component or in mixtures. Infrared spectra of all products were consistent with the molecular structure of SCat, showing an intense absorption band at 1700–1674 cm‐1, corresponding to the carbonyl stretching, a medium/strong peak at 1605-1580 cm-1, indicating stretching vibrations in the aromatic ring (C=C) and bands with relative low intensity at frequencies near 2700–2400 cm-1, corresponding to an amine salt. It was possible to identify a total of eight cathinone derivatives by GC-MS and NMR analysis: 4’-methyl-α-pyrrolidinohexanophenone (MPHP), α-pyrrolidinohexanophenone (α-PHP), 3-fluoromethcathinone (3-FMC), methedrone, methylone, buphedrone, N-ethylcathinone, and pentedrone. Among the adulterants found in these samples, caffeine was the most frequently detected substance, followed by ethylphenidate. These results highlight the prevalence of SCat in seized materials of the Portuguese market. Reference standards are usually required for confirmation, but when reference materials are not available, the combination of complementary techniques is fundamental for a rapid and an unequivocal identification of such substances.

Coronavirus (COVID19) appears to be an inflection point that is forcing a disruption in medical education. However, it is not clear what the responses of the institutions are to this pandemic and how the adaptation of new methods may impact medical education in the post COVID-19 era. Objective: The study aims to explore how medical schools in Egypt responded to COVID-19 pandemic regarding the teaching and learning/assessment for undergraduate students. Design: A mixed method exploratory two-phase study was conducted. A survey was prepared and disseminated to a convenient non-probability sample of the medical school faculty through various social platforms. Then, a focus group guide was conducted to explore in more depth the findings. Results: The staff level of preparedness for that unexpected shift was evaluated by 55.1% of the survey participants as optimum to high and a good leadership support was reported by 70 % of them. They reported conflicting views about the proper role of medical education units but reinforced the idea of Egyptian Knowledge Bank’s crucial role in this transition. Additionally, there is a communication problem with the students that leads to their detachment. Subsequently, 84.6 % of the participants reported that their schools used alternative teaching methods for small groups, large groups, pre-clinical and clinical clerkships. However, 64.1 % of the participants identified a clinical skills teaching challenge. Although, 68.4% reported that alternative methods were used for formative assessment but absence of alternative methods for summative assessment was declared by 76.3%. Conclusions: Individuals moved faster than bodies and relied on support existing outside the universities when catastrophe happened. However, institutes which have experience in adapting modern engaging learning methods should organize a better response for crisis. Online learning should be integrated in the curriculum with a fair percentage especially in the early years of medical study.

The human angiotensin-converting enzyme 2 (ACE2) has a crucial role on blood pressure control; however, ACE2 is also the primary SARS-CoV-2 (S domain) virus receptor. Inhibiting or even reducing the expression of the native ACE2 might diminish the viral entry into the cells, but may cause a failure of ACE2 biological activity, primarily in patients with comorbidities, including diabetes mellitus or hypertension. Since the ACE2 catalytic site and the SARS-Cov-2 receptor are distinct, we designed a Crispr-Cas9 model system, predicting the respective sequences for a guide RNA (gRNA) and a single-stranded oligo dideoxy nucleotide (ssODN), to introduce point mutations into the exon 1 of the human ACE2 gene, which encodes the alpha-helix, implicated on the binding of the SARS-CoV-2 envelope S protein. Protein modeling predicted that the specific substitutions of residues Phe28, Lys31, and Tyr41 for Ala at the ACE2 alpha-helix do not significantly alter ACE2 native conformation. The analysis of the impact of these mutations on ACE2 receptor function predicted a weakening of the binding of the SARS-CoV-2 protein S. An experimental genome editing of cells based on these Crispr-Cas9 elements might reduce the SARS-CoV-2 ability to enter the epithelial cell, preserving the biological activity of ACE2 enzyme.

The evolution of divaricate plants in New Zealand has been the subject of long-running debate among botanists and ecologists. Hypotheses about this remarkable case of convergent evolution have focused mainly on two different types of selective pressures: the Plio-Pleistocene advent of cool, dry climates, or browsing by now-extinct moa. Here, we review the scientific literature relating to the New Zealand divaricates, and present a list of 81 taxa whose architectures fall on the divaricate habit spectrum. We recommend a series of standardised terms to facilitate clear communication about these species. We identify potentially informative areas of research yet to be explored, such as the genetics underlying the establishment and control of this habit. We also review work about similar plants overseas, proposing a list of 47 such species as a first step towards more comprehensive inventories; these may motivate further studies of the ecology, morphology and evolutionary history of these overseas plants which could help shed light on the evolution of their New Zealand counterparts. Finally, we compile published divergence dates between divaricate species and their non-divaricate relatives, which suggest that the divaricate habit is fairly recent (< 10 My) in most cases.

Covid-19 infections are rapidly spreading worldwide with more than 100000 death and thus understanding the molecular mechanism of tropism of human cells is an urgent need for drug design. We have described here a bioinformatics approach to predict the functional aspects of non-structural nsp16 protein of Corona virus. The covid-19 7098 AA large polyprotein was degraded into sixteen proteins and last nsp16 protein was found an RlmE type rRNA methyltransferase. Nsp16 has no similarity to bacterial RlmABCD but has 25 percent similarity to the bacterial RlmE protein which methylates the U2551 2-hydroxy group of Ribose. The nsp16 proteins of different corona viruses like covid-19, bat-coronavirus, SARS and MERS have strong homology. Mrm2 and Dim1 like yeast and mammalian rRNA methyltransferases have 26-33 percent homologies but not with 2-O-capping MTase as reported previously. Rrp8 MTases also has no similarity to nsp16. We postulated that mitochondrial rRNA methylation of bronchial cells were mediated by the nsp16 protein causing inhibition of protein synthesis due to poor assembly of aminoacyl-tRNA or mRNA and peptidyl transferase at the PTC. This is one of the new molecular mechanism of corona virus cellular tropism and different than ACE-2 mediated blockage of cellular signalling to inhibit aldesterone biosynthesis with abnormal Na⁺ ions in cells. We also designed primers based on nsp16 cDNA sequence (nt 20659-21552, accession no MT121215) specific for Covid-19 diagnosis by RT-PCR.

Lactobacillus plantarum is a bacterium with promising applications to the food industry and agriculture and probiotic properties. So far, bacteriophages of this bacterium have been moderately addressed. We examined the diversity of five new L. plantarum phages via whole genome shotgun sequencing and in silico protein predictions. Moreover, we looked into their phylogeny and their potential genomic similarities to other complete phage genome records through extensive nucleotide and protein comparisons. These analyses revealed a high degree of similarity among the five phages, which extended to the vast majority of predicted virion-associated proteins. Based on these, we selected one of the phages as a representative and performed transmission electron microscopy and structural protein sequencing tests. Overall, the results suggested that the five phages belong to the family Myoviridae, they have a long genome of 137.973-141.344 bp, a G/C content of 36,3-36,6% that is quite distinct from their host’s, and, surprisingly, seven to 15 tRNAs. Only an average 41/174 of their predicted genes were assigned a function. The comparative analyses unraveled considerable genetic diversity for the five L. plantarum phages of this study. Hence, the new genus “Semelevirus” was proposed, which comprises exclusively the five phages. This novel lineage of Lactobacillus phages provides further insight into the genetic heterogeneity of phages infecting Lactobacillus sp.. The five new Lactobacillus phages have a potential value for the development of more robust starters through, for example, the selection of mutants insensitive to phage infections. The five phages could also form part of phage cocktails, which producers would apply in different stages of L. plantarum fermentations in order to create a range of organoleptic outputs.

In this study, the prevalent methodology for design of the industrial policy in developing countries was critically assessed, and it was shown that the mechanism and content of classical method is fundamentally contradictory to the goals and components of the endogenous growth theories. This study, by proposing a new approach, along settling Schumpeter's economic growth theory as a policy framework, designed the process of entering, analyzing and processing data as the mechanism of the industrial policy in order to provide "theoretical consistency" and "technical and Statistical requirements" for targeting the growth stimulant factor effectively.

BACKGROUND: Endoscopic placement of Self Expandable Metal Stents to relieve malignant colorectal obstruction has become a common therapeutic advancement in clinical practice. MATERIAL: In a 16 year period 167 patients had endoscopic placement of a Self Expandable Metal Stent in a center where gastroenterologists and surgeons cooperate in a daily basis, discussing indications. RESULTS: There was no operative mortality and no major complication in placement of the stent. Technical and clinical success was respectively 95.1% and 92.9%. Consultation among specialists changed the preoperative indication in 60 patients, during the same time period. CONCLUSIONS: Self expandable metal stents placement represents an important tool to treat patients with obstructing colorectal cancer and complications after colorectal resection . A proper training is required, and this training in operative endoscopy is not always available and possible. In this scenario, a close collaboration among specialists in selecting the most appropriate operative procedure is essential and brings to better results.

Work reviews the new isolated isolated cembranoid diterpene derivatives from species belonging to the family Alcyoniidae, which comprises the genera Sarcophyton, Sinularia, and Lobophytum as well as their biological properties, during 2016–2017. The compilation permitted to conclude that much more new cembranoid diterpenes were found in the soft corals of the genus Sarcophyton sp. (33 new compounds) than in those belonging to the genera Lobophytum (17) or Sinularia (8). Several methods have been used for identifying these new compounds, after extraction with organic solvents and fractionation. The fractions obtained, in some cases, were followed by TLC, and again subjected to chromatographic procedures, including semi-preparative HPLC. Beyond the chemical composition, the biological properties were also evaluated, namely anti-microbial against several Gram-positive and Gram-negative bacteria and fungi, anti-inflammatory and anti-tumoral against several types of cancer cells. Although the biological activities detected in almost all samples, they were not outstanding ones.

The human casualties from simulated nuclear detonation scenarios in New Delhi, India are analyzed, with a focus on the distribution of casualties in urban environments and the theoretical application of a nuclear-specific triage system. Model estimates of nuclear war casualties employed ESRI's ArcGIS 9.3, blast and prompt radiation were calculated using the Defense Nuclear Agency's WE program, and fallout radiation was calculated using the Defense Threat Reduction Agency's (DTRA's) Hazard Prediction and Assessment Capability (HPAC) V404SP4, as well as custom GIS and database software applications. ESRI ArcGISTM programs were used to calculate affected populations from the Oak Ridge National Laboratory's LandScanTM 2007 Global Population Dataset for areas affected by thermal, blast and radiation data. Trauma, thermal burn, and radiation casualties were thus estimated on a geographic basis for New Delhi, India for single and multiple (six) 25 kiloton (kt) detonations and a single 1 megaton (1000kt) detonation. Major issues related to the emergency management of a nuclear incident are discussed with specific recommendations for improvement. The consequences for health management of thermal burn and radiation patients is the worst, as burn patients require enormous resources to treat, and there will be little to no familiarity with the treatment of radiation victims.

Generalized zero-shot learning (GZSL) aims to simultaneously recognize both seen classes and unseen classes by training only on seen class samples and auxiliary semantic descriptions. Recent state-of-the-art methods infer unseen classes based on semantic information or synthesize unseen classes using generative models based on semantic information, all of which rely on the correct alignment of visual-semantic features. However, they often overlook the inconsistency between original visual features and semantic attributes. Additionally, due to the existence of cross-modal dataset biases, the visual features extracted and synthesized by the model may also mismatch with some semantic features, which could hinder the model from properly aligning visual-semantic features. To address this issue, this paper proposes a GZSL framework that enhances the consistency of visual-semantic features using self-distillation and disentanglement network (SDDN). The aim is to utilize self-distillation and disentanglement network to obtain semantically consistent refined visual features and non-redundant semantic features to enhance the consistency of visual-semantic features. Firstly, SDDN utilizes self-distillation technology to refine the extracted and synthesized visual features of the model. Subsequently, the visual-semantic features are then disentangled and aligned using a disentanglement network to enhance the consistency of the visual-semantic features. Finally, the consistent visual-semantic features are fused to jointly train a GZSL classifier. Extensive experiments demonstrate that the proposed method achieves more competitive results on four challenging benchmark datasets (AWA2, CUB, FLO, and SUN).

Background: Patients’ effective hand hygiene helps to reduce healthcare-associated infections, prevents the spread of nosocomial infections and communicable diseases, such as COVID-19. This study aimed to describe effective hand hygiene decisions based on the Health Action Process Ap-proach (HAPA) and whether this pattern is invariant for mental health. Methods: Data were collected cross-sectionally from patients who had previously been admitted to a hospital (N=279; study 1) and longitudinally from psychosomatic rehabilitation patients (N=1,073; study 2). The fit of the HAPA framework and changes in hand hygiene decisions regarding com-pliance, as well as social-cognitive variables of the HAPA, and mental health status were examined. Results: The trimmed HAPA framework fitted the data well (χ2=27.1, df=12, p<.01, CMIN/df=2.26, CFI=.97, RMSEA=.08). According to multi-group structural equation modeling, the HAPA model with hand hygiene behavior were found to be invariant with regard to mental health. Conclusion: The trimmed HAPA framework revealed to be a generic framework in explaining so-cial-cognitive processes relating to hand hygiene decisions. Helping individuals to perform hand hygiene recommendation requires intention formation and bridging the intention-behavior gap. This can be done by promoting planning and self-efficacy. All processes appear generic to partic-ipants with and without mental health challenges.

Throughout this paper, we will establish a comprehensive theoretical foundation and rigorously develop the methodology to investigate the structure of quotient ring S/P under the influence of symmetric generalized n-derivations, where S represents an arbitrary ring, and P signifies a prime ideal of S satisfying certain algebraic identities acting on prime ideal P without relying on the assumption of primeness or semi-primeness of the ring.

We propose a thermodynamic model describing the thermoelastic behavior of composition graded materials. The compatibility of the model with second law of thermodynamics is explored by applying a generalized Coleman-Noll procedure. We calculate the speeds of coupled first- and second-sound pulses, propagating either trough nonequilibrium or trough equilibrium states. We characterize several different types of perturbations, depending on the value of the material coefficients. Under the assumption that the deformation of the body can produce changes in its stoichiometry, altering locally the material composition, the possibility of propagation of pure stoichiometric waves is pointed out. Thermoelastic perturbations generated by the coupling of stoichiometric and thermal effects are analyzed as well.

W. L. Edge proved that the internal points of a conic in PG(2,5), together with the collinear triples on the non-secant lines, form the Desargues configuration. M. Saniga showed an intimate connection between Desargues configurations and the generalized quadrangles of order two, GQ(2,2), whose representation has been dubbed “the doily” by Stan Payne in 1973. In this paper we prove that the external points of a conic in PG(2,5), together with the collinear and non-collinear triples on the non-tangent lines, form the generalized quadrangle of order two.

In this work, we explore the extreme searching of multidimensional functions by natural gradient descent based on Dirichlet and generalized Dirichlet distributions. The natural gradient is based on describing multidimensional surface with probability distributions, which allows us to reduce changing the accuracy of gradient and step-size. In this article, we propose an algorithm of natural gradient descent based on Dirichlet and generalized Dirichlet distributions. We demonstrate that the natural gradient descent with step-size adaptation with Dirichlet and generalized Dirichlet distributions has higher accuracy and does not take a large number of iterations for minimizing test functions than gradient descent and Adam.

One of matrix equalities composed of multiple products of matrices and their generalized inverses is given by $A_1B_1^{-}A_2B_2^{-} \cdots A_kB_k^{-}A_{k+1}= A$ where $A_1$, $B_1$, $A_2$, $B_2$, $\ldots$, $A_k$, $B_k$, $A_{k+1}$, and $A$ are given matrices of appropriate sizes, and $B_1^{-}$, $B_2^{-}$, $\cdots$, $B_k^{-}$ are generalized inverses of matrices. The cases for $k = 1, 2$ and their special forms were properly approached in the theory of generalized inverses of matrices. In this note, the author presents an algebraic procedure to derive explicit necessary and sufficient conditions for the equality with $k = 3$ to always hold using certain rank equalities for the block matrices constructed by the given matrices, and then mention a key step of extending the previous work to a general situation.

This paper provides attempts to formalize Hayek’s theory of knowledge. It has been theoretically shown that exponential income distribution is a spontaneous order of the well-functioning market economy. We show that this theoretical result is supported by the empirical evidence from the United Kingdom and China. In particular, we empirically show how the income structure of China evolved towards an exponential distribution after the market-oriented economic reformation. Furthermore, we strictly prove that, if the income structure of an economy obeys an exponential distribution, the income summation over all households leads to an aggregate production function with Hicks-neutral-like technical progress, in which the technology factor is exactly equal to society’s information stock that is a result of combining all of decentralized decisions.

In this article, the geometry of pseudoparallel, Ricci-generalized pseudoparallel and 2-Ricci-generalized pseudoparallel invariant submanifolds of an almost $\alpha$-cosymplectic $(\kappa,\mu,\nu)$ space has been searched under the some conditions. We also give some characterizations for such submanifolds. I think that obtained new results contribute to differential geometry.