The representation of aerosols in climate-chemistry models is important for air quality and climate change research, but it can require significant computational resources. To overcome this, simpler modules such as modal aerosol modules with three lognormal modes (MAM3) can be used. In this study, the coupling of the Carbon Bond Mechanism, version Z (CBMZ), and MAM3 chemistry modules in WRF-CAM5 was improved by adding biomass-burning emissions to both gas- and particle-phase chemistry and incorporating a conversion mechanism between volatile organic compounds (VOCs) and secondary organic carbons (SOCs). The study conducted six simulations over the western U.S. and northeastern Pacific region and compared the model’s performance with observational benchmarks such as reanalysis, ground-based, and satellite data. The results showed that the model with enhanced chemistry capabilities had a 31% and 58% reduction in root-mean-square errors (RMSE) for black carbon (BC) and organic carbon (OC) surface concentrations, respectively. The earlier release of the WRF-CAM5 version had two deficiencies that were addressed in this study. This research highlights the importance of accurate aerosol representation in climate-chemistry models for improving accuracy and reducing errors in simulations.

Several chemistry-climate models (CCM) underestimate the total column ozone (TCO) over the polar region in the Southern Hemisphere during wintertime. To evaluate potential causes of the problem, we exploit CCM SOCOLv3 to study the TCO over Antarctica sensitivity to the: (1) photo-dissociation rates of ozone for large solar zenith angles; (2) rates of the stratospheric heterogeneous reactions, and (3) intensity of the meridional flux into the polar regions due to sub-grid scale mixing processes in the model. Comparisons of the model results with the satellite-based IASI (Infrared Atmospheric Sounder Interferometer) sensor measurements showed that the most important processes for the improvement of the polar ozone simulation results are photolysis and horizontal mixing. The reasonable tuning of these factors has allowed us to improve the model representation of the ozone annual cycle over the southern polar region. The proposed increase of the horizontal mixing can be recommended for the CCMs with relatively low horizontal resolution.

Cyrene was evaluated for the first time as a potential sustainable mobile phase solvent in re-versed-phase chromatography. As a benign biodegradable solvent, Cyrene is an attractive re-placement to classical non-green organic chromatographic solvents such as acetonitrile and a modifier, co-eluent to known green solvents such as ethanol. Compared to ethanol, Cyrene is less toxic, non-flammable, bio-based, biodegradable and cheaper solvent. A fire safety spider Chart was generated to compare the properties of Cyrene to ethanol and show its superiority as a greener solvent. Cyrene's behaviour, advantages, and drawbacks in reversed-phase chromatography, including cut-off value, elution power, selectivity, and effect on the column, were investigated using a model drug mixture of moxifloxacin and metronidazole. A monolithic C18 (10 x 4.6 mm) column was used as a stationary phase. Different ratios of Cyrene: ethanol with an aqueous portion of sodium acetate buffer mobile phases were tested. A mobile phase consisting of Cyrene: ethanol: 0.1 M sodium acetate buffer pH 4.25 (8:13:79, v/v) was selected as most suitable mobile phase system for separating and simultaneously determining metronidazole and moxifloxacin. The greenness and whiteness of the method were evaluated using the qualitative green assessment tool AGREE and the white analytical chemistry assessment tool RGB12. Further potentials of Cyrene as a solvent or modifier in normal phase chromatography, liquid chromatography-mass spectrometry, and supercritical fluid chromatography are discussed.

On the primitive Earth, both L- and D-amino acids would have been present. However, only L-amino acids are essential blocks to construct proteins in modern life. To study the relative stability of homochiral and heterochiral peptides, a variety of computational methods were employed. 10 prebiotic amino acids (Gly, Ala, Asp, Glu, Ile, Leu, Pro, Ser, Thr, and Val) were previously determined by multiple previous meteorite, spark discharge, and hydrothermal vent studies. We focused on what had been reported as primary early Earth polypeptide analogs: 1ARK, 1PPT, 1ZFI, and 2LZE. Tripeptide composed of only Asp, Ser, and Val exemplified that different positions (i.e., N-terminus, C-terminus, and middle) made a difference in minimal folding energy of peptides, while the classification of amino acid (hydrophobic, acidic, or hydroxylic) did not show significant difference. Hierarchical cluster analysis for dipeptides with all possible combinations of the proposed 10 prebiotic amino acids and their D-amino acid substituted derivatives generated five clusters. Prebiotic polypeptides were built up to test the significance of molecular fluctuations, secondary structure occupancies, and folding energy differences based on these clusters. Most interestingly, among 129 residues, mutation sensitivity profiles presented that the ratio of more stable to less stable to equally stable D-amino acids was about 1:1:1. In conclusion, some combinations of a mixture of L- and D-amino acids can act as essential building blocks of life. Peptides with α-helices, long β-sheets, and long loops are usually less sensitive to D-amino acid replacements in comparison to short β-sheets.

Arctic ozone amount in winter to spring shows large year-to-year variation. This study investigates Arctic spring ozone in relation to the phase of quasi-biennial oscillation (QBO)/the 11-year solar cycle, using satellite observations, reanalysis data, and outputs of a chemistry climate model (CCM) during the period of 1979–2011. For this duration, we found that the composite mean of the Northern Hemisphere high-latitude total ozone in the QBO-westerly (QBO-W)/solar minimum (Smin) phase is slightly smaller than those averaged for the QBO-W/Smax and QBO-E/Smax years in March. An analysis of a passive ozone tracer in the CCM simulation indicates that this negative anomaly is primarily caused by transport. The negative anomaly is consistent with a weakening of the residual mean downward motion in the polar lower stratosphere. The contribution of chemical processes estimated using the column amount difference between ozone and the passive ozone tracer is between 10–20% of the total anomaly in March. The lower ozone levels in the Arctic spring during the QBO-W/Smin years are associated with a stronger Arctic polar vortex from late winter to early spring, which is linked to the reduced occurrence of sudden stratospheric warming in the winter during the QBO-W/Smin years.

Organizational climate is the ascribed psychological meanings and significance associated with the procedures, policies and practices that are recognized and rewarded in the workplace, and hence mediates the effects of environmental stimuli on individuals’ response. Safety climate is a specific organizational climate, i.e., organizational climate for safety. Previous research claimed that organizational climate provides foundation for safety climate, but without elaboration on the foundational mechanisms. This paper attempts to fill up this knowledge gap. As organizational climate is a multi-dimensional phenomenon, this paper chooses two dimensions, i.e., perceived organizational support (POS) and participative decision-making (PaDM), for illustrative purposes. Drawing on an interactive approach to forming climate perceptions, this paper introduces two interactive constructs, i.e., leader-member exchange (LMX) and team member exchange (TMX), and establishes a multiple mediation model depicting the foundational effect of organizational climate on safety climate. A random sample of Hong Kong based construction personnel is used to validate the model. The results show that both POS and PaDM are positively associated with perceived safety climate, both LMX and TMX fully mediate the effect of PaDM on safety climate, and only LMX partially mediates the effect of POS on safety climate. This study sheds light on the foundational effects of organizational climate on safety climate. POS can improve the quality of reciprocal exchange about safety matters between construction personnel and their supervisors, and hence raise construction personnel’s awareness of the priority of safety. PaDM can improve the quality of reciprocal exchange about safety matters vertically and horizontally, and hence have construction personnel aware the importance of safety. In practice, this paper suggests that project managers timely recognize and reward construction personnel’s contribution, genuinely cares about their well-being, and take their suggestions seriously in making decisions. In this way, the quality of both vertical and horizontal exchange about safety matters improves, and a sound and positive safety climate ensues.

This review considers the generation of relatively simple biomolecules, e.g., primary amino acids, resulting from the rapid collapse of bubbles in aqueous solutions containing various, low molar mass, gases. Some of the possible primary reactions occurring to produce the biomolecules are introduced and discussed. A brief discussion is included on the possible involvement of hydrodynamic cavitation, at the primordial seashore, as the initiating processes for the formation of the first organic molecules on prebiotic earth and the origins of life on Earth some 4 billion years ago.

Fostering fruitful collaboration between chemistry and physics scholars, the analysis of the differences in the practical approach to single atoms in chemistry and in physics affords a number of conceptual outcomes pointing to a more balanced relationship between chemistry and physics.

Earth-abundant transition metals like iron, nickel, copper, molybdenum, and vanadium have been identified as essential constituents of the cellular gas metabolism in all kingdoms of life. Associated with biological macromolecules, gas-processing metalloenzymes (GPMs) are formed that catalyse a variety of redox reactions. This includes the reduction of O₂ to water by cytochrome c oxidase (‘complex IV’), the reduction of N₂ to NH₄ by nitrogenase, as well as the reduction of protons to H₂ (and oxidation of the later) by hydrogenase. GPMs perform at ambient temperature and pressure, in the presence of water, and often extremely low educt concentrations, thus serving as natural examples for efficient catalysis. Facilitating the design of biomimetic catalysts, biophysicist thrive to understand the reaction principles of GPMs making use of various techniques. In this perspective, I will introduce Fourier-transform infrared spectroscopy in attenuated total reflection configuration (ATR FTIR) for the analysis of GPMs like cytochrome c oxidase, nitrogenase, and hydrogenase. Infrared spectroscopy provides information about the geometry and redox state of the catalytic cofactors, the protonation state of amino acid residues, the hydrogen-bonding network, and protein structural changes. I developed an approach to probe and trigger the reaction of GPMs by gas exchange experiments, exploring the reactivity of these enzymes with their natural reactants. This allows recording sensitive ATR FTIR difference spectra with seconds time resolution. Finally yet importantly, infrared spectroscopy is an electronically non-invasive technique that allows investigating protein samples under biologically relevant conditions, i.e., at ambient temperature and pressure, and in the presence of water.

Globally, the intensity and irregularity of weather and climate extremes are increasing due to climate change. In Ethiopia, the occurrence of extreme events has been increasing, reporting severe impacts on environment which led to losses of lives and livelihood of societies. In this study, Heat Wave Magnitude Index daily (HWMId) was used to analysis heat wave magnitude in the Middle Awash Basin of Ethiopia. Gauge data obtained from Ethiopian Meteorological Institution (EMI) for 1981-2022 period and the future projection was taken from Coupled Model Intercomparison Project Phase 6 (CMIP6) under two socioeconomic pathways (SSP 2 and SSP 5) scenarios. The findings clearly showed that the area aggregated annual temperature anomaly increasing each year, 2015 was one of the warmest year on record with an anomaly of +1.8 °C. Severe to extreme heat wave recorded particularly during the last 10 years. For the future projection, under SSP 2-4.5 forcing scenario, the annual average air temperature projected to be warmer, which increasing 1.7 ℃ to 1.8 ℃ during mid-century and 2.3 ℃ to 2.4 ℃ end of century. Meanwhile, for SSP 5-8.5 forcing, the projection indicated an increment of 2.2 ℃ to 2.5 ℃ under mid-century and 4.4 ℃ to 4.8 ℃ end of century. Concerning the severity of heat wave, extreme to very extreme heat wave projected under SSP 2-4.5 forcing scenario and supper extreme heat wave projected under SSP 5-8.5 forcing scenario, respectively. The increase in extreme events may have a negative impact on health, water availability and food security. Therefore, the result of this study are essential for making wise decisions and for developing suitable strategies for climate change adaptation and mitigation that could minimize the risk of unusually extreme weather events.

In the context of global warming and reduction in fresh water availability is presented a study of the evolution of dew, rain and evapotranspiration in the NW of Africa. The time periods are concerned with the years 2005-2020, using existing data, and years 2020-2100, using the low and high emissions representative concentration pathway scenarios RCP 2.6/8.5 from the Cordex database. A continuous decrease in rain precipitation is observed, on order of -14 mm/decade for the more credible scenario RCP 8.5. The amplitude is maximum on the coast and on the foothills of Atlas. A clear decrease in dew yields is also observed along a NW/SE axis, strongly correlated with a corresponding decrease in relative humidity (up to 7%). Chemical dew and rain data in the representative site of Mirleft correspond to the major cations Na+ > Ca2+ > Mg2+ > K+, similar to a local spring water. Concentrations in rain are about two times less than in dew water. Ionic concentrations are compatible with WHO standards. The seasonal variations of the ionic concentrations in dew and rain follow a volume dilution dependence. The expected diminution in dew and rain volumes according to the RCPs 2.6 and 8.5 should increase the dew and rain ionic concentrations in the future.

Multicomponent reactions (MCRs) have been used for more than a century; since their discovery in 1850 by Strecker. To date, MCRs route is regarded as a beneficial strategy due to its capacity to quickly produce molecular diversity and structural complexity of interest for a variety of applications. Despite having famous MRCs such as the Ugi, Passerini, Biginelli, and Hantzsch, this re-view portrays the importance of MCRs in the synthesis of desired products towards applications such as medicinal purposes, sustainable chemistry, and polymerisation. MCRs provide ad-vantages such as reducing the number of sequential multiple reactions to one step, atom economy, recyclable catalysts, mild conditions, preventing waste and reduce solvent use.

Due to metal leaching and poor catalyst stability, the chemical industry’s fine chemical and pharmaceutical sectors have been historically reluctant to use supported transition metal catalysts to manufacture fine chemicals and active pharmaceutical ingredients. With the advent of new generation supported metal catalysts and flow chemistry, we argue in this study, this situation is poised to quickly change. Alongside heterogenized metal nanoparticles, both single-site molecular and single-atom catalyst will become ubiquitous. This study offers a critical outlook taking into account both technical and economic aspects.

Introduction. Environmental Health in a Global World at New York University was re-designed as a class participatory effort, challenging undergraduate students to understand environmental hazards and the resultant adverse health outcomes by embracing the inherent complexity of environmental risks and proposing solutions. Methods. Following introductory lectures, students are placed into teams and assigned a specific perspective, or avatar, which includes learning to see the challenge from the perspective of a technical expert such as a biologist, an engineer, or an anthropologist. The teams then design specific systems maps to visualize the complex interactions that lead to adverse health outcomes after a given environmental exposure. The maps highlight potential leverage points, where relatively minor interventions can provide a disproportionate benefit in health outcomes. The teams then explore potential interventions and identify the potential unintended consequences of those actions, develop and advocate for innovative new strategies to mitigate risk and improve outcomes. Results and Discussion. Over the past 5 years we have taught this methodology to over 680 students with strong, student-oriented results. The teams created and presented more than 100 strategies, addressing a diverse set of environmental challenges that include water contamination, gun violence, air pollution, environmental justice, health security, and climate change. Developing the strategies helped the students understand environmental threats in a more holistic way, provided them with some agency in finding solutions, and offered an opportunity for them to improve their presentation skills. The responses in course evaluations have been enthusiastic, with many students reporting a deep impact on their college experience.

Reactions in water between the Cu2(µ-EGTA) chelate (EGTA = ethylene-bis(oxyethyleneimino)tetraacetate(4-) ion) and 2,6-diaminopurine (Hdap) in molar ratios 1:1 and 1:2 yield only blue crystals of the ternary compound [Cu4(μ-EGTA)2(μ-H(N3)dap)2(H2O)2]·7H2O (1) that has been studied by single crystal X-ray diffractometry, various physical methods (thermal stability, spectral and magnetic properties), as well as DFT theoretical calculations. In the crystal, uncoordinated water is disordered. The tetranuclear complex molecule also has some irrelevant disorder in an EGTA-ethylene moiety. In the complex molecule, both bridging organic molecules act as binucleating ligands. There are two distorted five- (type 4+1) and two six- (type 4+1+1) Cu(II) centres. Each half EGTA acts as a tripodal tetradentate Cu(II) chelator, with mer-NO2+O(ether, distal) conformation. Hdap exhibits the tautomer H(N3)dap, with the dissociable H-atom on its less basic N-heterocyclic atom. These features favour the efficient cooperation between Cu-N7 or Cu-N9 bonds with appropriate O-EGTA atoms, as N6-H···O or N3-H···O interligand interactions respectively. Bridging role of both organics determines the tetranuclear dimensionality of the complex in 1. In this crystal, such molecules associate in zig-zag chains, built by alternating ,-interactions between the five- or six-atom rings of Hdap ligands of adjacent molecules. DFT theoretical calculations (using two different theoretical models and characterized by the quantum theory of “atoms in molecules”) reveal the importance of these ,-interactions between Hdap ligands, as well as that corresponding to the referred hydrogen bonds in the contributed tetranuclear molecule.

Removing one key barrier to the industrial uptake of green chemistry and nanocatalysis in the fine and specialty chemical industry requires to fill an ongoing “talent shortage” via expanded chemistry education. In this study we show how the use of hybrid sol-gel catalysts to synthesize fine chemicals and active pharmaceutical ingredients in flow chemistry reactors illustrates new ideas to reshape chemistry education based on recent research outcomes, visualization and digital tools. Several lessons learned from the industrial and academic utilization of these materials in continuous-flow conversions conclude the study.

This study assessed farmers’ perception of climate change, estimated the determinants of, and evaluated the relationship among adaptation practices using the multivariate probit model. A survey in 300 agricultural households was carried out covering 10 sample districts considering five agro-ecological zones and a vulnerability index. Four adaptation choices (change in planting date, crop variety, crop type and investment in irrigation) were deemed as outcome variables and socioeconomic, demographic, institutional, farm-level and perceptions variables were deployed as explanatory variables. Their marginal effects were determined for three climatic variables—temperature, precipitation and drought. Age, gender and education of head of household, credit access, farm area, rain-fed farming and tenure, are found to be more influential compared to other factors. All four adaptation-options are found to be complimentary to each other. Importantly, the intensity of impact of dependent variables in different models, and for available adaptation-options, are found to be unequal. Therefore, policy options and support facilities should be devised according to climatic variables and adaptation options to achieve superior results.

The way humans use natural resources and especially freshwater, reflects their relationship with nature. It also influences the conceptual Water Resources Management (WRM) model. A historical review shows that the interplay between Humans and Nature is diachronically in constant change between two opposites: conflict and cooperation. Lessons from the past 20.000 years indicate that the WRM model is a function of two main parameters: (1) socio-economics, and (2) climate conditions. Three different Eras of the Humans-Nature relationship have been distinguished: (1) Naturalistic: Nature dominating Humans during the Last Glacial Period (100-10) kyr BC, (2) Dualistic: Nature-Humans cooperation and competition from 10 kyr BC to 1800 AD, and (3) Anthropocentric: Humans dominating Nature from 1800 AD to now. Since 2000, the Integrated WRM (IWRM) model is promoted as state-of-the-art and remains anthropocentric producing huge externalities. Its assessment during the last 20 years has given mixed results and needs to be reformulated. The new model we suggest is based on the dialectical tool for conflict resolution. It unifies Humans and Nature and enhances the social dimension of WRM. After identifying conflicts between stakeholders and the natural laws (eristic part), opposite objectives are unified to harmonize Humans with Nature (dialectical resolution). A case study of flood mitigation illustrates the eristic-dialectical methodology.

Low carbon cities are increasingly forming a distinct strand of sustainability literature. Models have been developed to measure the performance of low carbon cities. The purpose of this paper is to formulate a strategy-based model to evaluate current performance and predict future conditions of low carbon cities. It examines the dynamic interrelationships between key performance indicators (KPIs), induces changes to city plan targets and then instantly predicts the outcome of these changes. Designed generic and flexible, the proposed model shows how low carbon targets could be used to guide the transformation of low carbon cities under four strategies: (1) passive intervention, (2) problem solving, (3) trend modifying and (4) opportunity seeking. Further, the model has been applied to 17 cities and then tested on 5 cities: London, New York, Barcelona, Dubai and Istanbul. The paper concludes with policy implications to realign city plans and support low carbon innovation.

A hand-held laser-induced breakdown spectroscopy device was used to acquire spectral emission data from laser-induced plasmas created on the surface of cerium-gallium alloy samples with Ga concentrations ranging from 0 to 3 weight percent. Ionic and neutral emission lines of the two constituent elements were then extracted and used to generate calibration curves relating the emission line intensity ratios to the gallium concentration of the alloy. The Ga I 287.4 nm emission line was determined to be superior for the purposes of Ga detection and concentration determination.A limit of detection below 0.25% was achieved using a multivariate regression model of the Ga I287.4 nm line ratio versus two separate Ce II emission lines. This LOD is considered a conservative estimation of technique’s capability given the type of the calibration samples available and low power( 5 mJ per 1 ns pulse) and resolving power (λ/∆λ= 4000) of this handheld device. Nonetheless, the utility of the technique is demonstrated via a detailed mapping analysis of the surface Ga distribution of a Ce-Ga sample which reveals significant heterogeneity resulting from the sample production process.

Several sun models suggest the radioactive balance where the concentration of greenhouse gases and the albedo effect are related to the Earth's surface temperature. There is a considerable increment of greenhouse gases due to anthropogenic activities. Climate change correlates with this alteration in the atmosphere and an increase in surface temperature. Efficient forecasting of climate change and its impacts of 1.5°C global warming above pre-industrial levels could be helpful to respond to the threat of c.c. and develop sustainably. Many studies have predicted the temperature change in the coming years. The global community has to create a model that can realize good predictions to ensure the best way to deal with the warming. Thus, we propose a finite-time thermodynamic (FTT) approach in the present work. The FTT can solve problems such as the faint young sun paradox. In addition, we use different machine learning models to evaluate our method and compare the experimental prediction and results.

Climate justice as a commons is conceived as the intertemporal climate equity and equal- ity exchange amongst generations. Sustainability, intended as the interplay amongst the economy, the society, the environment, and the governance, is essential to forge the climate justice theoretical framework. On this base, the study attempts to model intertemporal choice amongst generations in these four domains, making use of an over- lapping generations (OLG) model. The proxies detected are GDP growth (economy), environmental quality (environment), and labor growth, and environmental investment (society) as assumptions. The governance dimension is captured by the di¤erence in wealth between young and old generations. The work aims at replying to the follow- ing research question: Which are the conditions for sustainable development such that climate justice holds? The intra-intergenerational exchange is de…ned in two periods, while the individual provides their preferred economic and environmental choice mix as consumption-saving. This study shows that sustainable growth is achievable only with increased young e¤ort and less leisure and consumption.

In the last decades droughts, deforestation and wildfires have become recurring phenomena that have affected both human activities and natural ecosystems in Amazonia. The time an ecosystem requires to recover from carbon losses is a crucial metric to evaluate disturbance impacts on forests. However, the factors influencing and controlling the recovery time and its spatiotemporal patterns at the regional scale are still poorly understood. In this study, we combined forest growth model, remote sensing and field plots, to map Amazonia-wide (300-ha resolution) impact and recovery time of aboveground biomass (AGB) after drought, fire and a combination of logging and fire. Our simulated results indicate that AGB decreases by 4%, 19% and 46% in forests disturbed by drought, fire and logging + fire, respectively, with an average AGB recovery time of 27 years for drought, 44 years for burned and 63 years for logged + burned areas and with maximum values reaching 184 years in areas of high fire intensity. Our findings provide two major insights in the spatial and temporal patterns of drought and wildfire in the Amazon: 1) the recovery time of the forests takes longer in the southeastern part of the basin, and, 2) as droughts and wildfires become more frequent – since the intervals between the disturbances is getting shorter than forest regeneration – potentially causing a long-lasting damage in these fragile ecosystems and a permanent degradation.

We use the third version of the Canadian Local Climate Model as a diagnostic tool to study the climatology of observed CG lightning activity at Maniwaki (latitude: 46,23°N; Longitude: 75,58°W). We examine the dependence between the hourly lightning activity and the related atmospheric variables during the warm season of sixteen years (between 1984 and 2004). The goal of this research is: a) to evaluate the atmospheric static state evolution and its moisture contents for conditions having generated lightning occurrence, b) to develop a CG lightning parameterization, and c) to verify this CG lightning parameterization on other Canadian areas. The freezing level altitude and the precipitable water content are used to estimate the static air instability and its moisture content respectively. These two parameters are served to develop the CG lightning parameterization. A comparison between the observations and simulations CG lightning occurrence and frequency at Maniwaki showed a mean absolute error rate of 27% and 55% respectively. We apply this parameterization at four Canadian regions, distributed from west to east. The simulated CG lightning results are comparable to observed CG lightning at Maniwaki and tested regions. The application of the CG lightning parameterization to the daily data enabled us to find the monthly results. This application represents a preliminary stage for validation this parameterization in regional numerical models in Canada during the historic period.

Human-Computer Interaction, including technology-aided instruction, is beginning to focus on virtual reality (VR) technology due to its ability to support immersive learning, teaching through simulation, and gamification of learning. These systems can deliver high-level multisensory learning experiences that are important in the teaching of many subjects, especially those involving abstract concepts or requiring spatial skills, such as organic chemistry. Haptic experiences with VR, however, remain a challenge. In addition, development have focused on general entertainment/gaming; VR systems in chemistry implement simulations of the chemistry laboratory and other advanced systems whereas those that support safe, game-like, immersive and multisensory learning of organic chemistry with haptics at pre-university education levels are scarce. We developed the VR Multisensory Classroom (VRMC) as an immersive learning environment within a VR head-mounted display, where learners employ hand movements to build hydrocarbon molecules and experience haptic feedback through gloves with built-in sensors and hand-tracking with the Leap Motion system. We report here the evaluation of the first prototype by learners from diverse backgrounds who reported on the ability of the VRMC to support high engagement, motivation, interest and organic chemistry learning as well as diverse learning styles. The VRMC is a novel VR classroom that supports immersive learning in molecular organic chemistry with haptics for multisensory learning.

In this paper, Rice water requirement and irrigation water requirement in Amol agro meteorological Station in 2016-2045 are forecasted based on the projected meteorological data of Hadcm3 under A2 scenario. Rice water requirements are estimated by using crop coefficient approach. Reference evapotranspiration are calculated by FAO Penman-Monteith method. Moreover, the irrigation water requirements are simulated by calibrated CROPWAT model using the meteorological parameters. The results show that both crop water requirement and irrigation water requirement present downward trend in the future. In 2016-2045, the rice water requirement and irrigation water requirement decrease by more than 9.9% under A2 scenario, respectively. Furthermore, the precipitation rise may be the main reason for the decrease in crop water requirement, while significant decrease of irrigation water requirement should be attributed to combined action of rising precipitation and a slight increase in temperature.

Atmospheric turbulence, which produces chaotic motions in the planetary boundary layer, can inhibit mixing between fast-reacting species produced or released at different locations. This segregation process modifies the effective rate at which reactions occur between these species, and are not appropriately accounted for in coarse resolution models since these models assume complete mixing of tracers within each gridbox. Here we present a few examples of LES-based simulations applied to chemically reactive species in a forested area with high emissions of biogenic hydrocarbons, an urban area rich in anthropogenic emissions; and a maritime area with high emissions of reduced sulfur species.

A microwave assisted method for synthesis of 2-substituted benzimidazoles has been developed. The combination of molar ratio N-phenyl-o-phenylenediamine:benzaldehyde (1:1) using microwave irradiation and only 1% mol of Er(OTf)3 provide an efficient, environmental and mild access to a diversity of benzimidazoles under solvent-free conditions.

This review presents an updated overview of research concerning Leishmania protein structures, primarily sourced from the Protein Data Bank (PDB), that play a role in the metabolic pathways of the Leishmania parasite. Furthermore, we assess the current progress in the identification and development of bioactive chemical agents aimed at addressing this substantially overlooked tropical disease. We have analyzed experimental data obtained from in vitro, in vivo and in silico sources. This data has been categorized into four main areas: a) vector taxonomy and geographic distribution; b) parasite taxonomy and geographic distribution; c) enzymatic functions of proteins engaged in parasite/host interactions throughout various developmental stages (such as oxidoreductases, transferases, hydrolases, lyases, isomerases, ligases, and cytokines); and d) established and experimental treatments employing bioactive chemical compounds. Our objective is to establish a foundational point of reference for research efforts concentrating on the elucidation of interaction mechanisms and the processes of ligand-protein activation/inactivation, specifically linked to Leishmania infections. Consequently, we emphasize enzymes recognized for their involvement in the biochemical pathways incited during Leishmania infection episodes. This review encapsulates the current understanding, offering insights to inform and direct future explorations aimed at targeting proteins and pathways to enhance the management of Leishmania-related diseases.

In-cloud ice mass accretion on wind turbines is a common challenge faced by energy companies operating in cold climates. On-shore wind farms in Scandinavia are often located in regions near patches of forest, the heterogeneity length scales of which are often less than the resolution of many numerical weather prediction (NWP) models. The representation of these forests--including the cloud water response to surface roughness and albedo effects related to them--must therefore be parameterized in NWP models used as meteorological input in ice prediction systems, resulting in an uncertainty that is poorly understood and to present date not quantified. The sensitivity of ice accretion forecasts to the subgrid representation of forests is examined in this study. A single column version of the HARMONIE-AROME 3D NWP model is used to determine the sensitivity of the forecast of ice accretion on wind turbines to the subgrid forest fraction. Single column simulations of a variety of icing cases at a location in northern Sweden were examined in order to investigate the impact of vegetation cover on ice accretion in varying levels of solar insulation and wind magnitudes. In mid-winter cases, the wind speed response to surface roughness was the primary driver of the vegetation effect on ice accretion. In early season cases, the cloud water response to surface albedo effects plays a secondary role in the impact of in-cloud ice accretion, with the wind response to surface roughness remaining the primary driver for the surface vegetation impact on icing. Two different surface boundary layer (SBL) forest canopy subgrid parameterizations were tested in this study that feature different methods for calculating near-surface profiles of wind, temperature, and moisture, with the ice mass accretion again following the wind response to surface vegetation between both of these schemes.

Large-scale hydrological modeling in China is challenging given the sparse meteorological stations and large uncertainties associated with atmospheric forcing data.Here we introduce the development and use of the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) in the Heihe River Basin(HRB) for improving hydrologic modeling, by leveraging the datasets from the China Meteorological Administration Land Data Assimilation System (CLDAS)(including climate data from nearly 40000 area encryption stations, 2700 national automatic weather stations, FengYun (FY) 2 satellite and radar stations). CMADS uses the Space Time Multiscale Analysis System (STMAS) to fuse data based on ECWMF ambient field and ensure data accuracy. In addition, compared with CLDAS, CMADS includes relative humidity and climate data of varied resolutions to drive hydrological models such as the Soil and Water Assessment Tool (SWAT) model. Here, we compared climate data from CMADS, Climate Forecast System Reanalysis (CFSR) and traditional weather station (TWS) climate forcing data and evaluatedtheir applicability for driving large scale hydrologic modeling with SWAT. In general, CMADS has higher accuracy than CFRS when evaluated against observations at TWS; CMADS also provides spatially continuous climate field to drive distributed hydrologic models, which is an important advantage over TWS climate data, particular in regions with sparse weather stations. Therefore, SWAT model simulations driven with CMADS and TWS achieved similar performances in terms of monthly and daily stream flow simulations, and both of them outperformed CFRS. For example, for the three hydrological stations (Ying Luoxia, Qilian Mountain, and ZhaMasheke) in the HRB at the monthly and daily Nash-Sutcliffe efficiency ranges of 0.75-0.95 and 0.58-0.78, respectively, which are much higher than corresponding efficiency statistics achieved with CFSR (monthly: 0.32-0.49 and daily: 0.26 – 0.45). The CMADS dataset is available free of charge and is expected to a valuable addition to the existing climate reanalysis datasets for deriving distributed hydrologic modeling in China and other countries in East Asia.

The research was conducted in the Kırklareli stream, which flows southwest through the city of the same name toward the village of Kavaklı. The aim of the study is to evaluate water analysis results and assess the potential that the European Union drinking water standard for lead can be achieved in the Kırklareli stream by reliance on the low solubility of lead phosphate minerals. The present study used Visual MINTEQ 3.1 for all water chemistry simulations. The European Union drinking water standard for lead, which is 10 μg L⁻¹, is exceeded at least once and as many as three times at seven of the ten sites during the 2018 sampling season. Although the database solubility of hydroxypyromorphite is exceeded in most samples, it appears this may be the result of major ion substitutions in the hydroxypromorphite that forms in the Kırklareli stream which increases the effective solubility of lead in the stream.

The following paper describes an economical, multiple model predictive control (EMMPC) for an air conditioning system of a confectionery manufacturer in Germany. The application consists of a packaging hall for chocolate bars, in which a new local conveyor belt air conditioning system is used and thus the temperature and humidity limits in the hall can be significantly extended. The EMMPC calculates the optimum energy or cost humidity and temperature set points in the hall. For this purpose, time-discrete state space models and an economic objective function with which it is possible to react to flexible electricity prices in a cost-optimised manner are created. A possible future electricity price model for Germany with a flexible EEG levy was used as a flexible electricity price. The flexibility potential is determined by variable temperature and humidity limits in the hall, which are oriented towards the comfort field for easily working persons, and the building mass. The building mass of the created room model is used as a thermal energy store. Considering electricity price and weather forecasts as well as internal, production plan-dependent load forecasts, the model predictive controller directly controls the heating and cooling register and the humidifier of the air conditioning system.

The construction industry is one of the most fatal industries, so it is important to pay more attention to safety solutions. Even though work-related accidents are known as major waste in construction projects, little attention has been paid so far to incorporating safety into the lean construction framework. In this research, lean construction theory is reviewed through the lens of safety. That being so, the identified challenges in previous research on improving safety in construction projects are categorized and those related to the concept of lean project delivery are introduced. Then, the principles of the lean construction framework are explained and the relevant changes for incorporating safety into the framework are introduced and discussed. It is expected that this hybrid model would further enrich the lean construction framework. The careful attention of project executives to this model may improve the safety situation in construction projects.

Land surface temperature (LST) is a critical parameter for land surface and atmospheric interactions. However, the applicability of current land surface temperature estimates for field-level hydrological, agricultural, and ecological operations is still challenging due to their coarse spatiotemporal resolution. In the current article, we have downscaled 100 m LST to 10 m by using high-resolution Sentinel-1,2 optical-microwave data and three different models- 1) Thermal Sharpening (TsHARP); 2) Thin Plate Spline (TPS); and 3) Random Forest (RF). The extensive analysis was performed at agricultural farms in the semi-arid (IARI) region of India during the winter and summer seasons of 2020-21 and 2021-22, arid (CAZRI) and per-humid (UBKV) region (2021-2022). The calibration accuracy of the RF model was shown to better agreement with the coefficient of determination (R2) of 0.982, root means square error (RMSE) 0.181 and normalized root means square error (RMSE) 0.061 with their lower values of standard errors over three diverse agro-climatic zones. The findings demonstrate that the validation accuracy of models' varied according to the agroclimatic zones, although RF and TPS consistently outperformed as compared to the TsHARP models.

Cheese consumption provides humans with minerals, proteins, carbohydrates, and vitamins. In Mexico, several cheese varieties are produced, each with its texture, scent, and flavor. The artisanal cheeses made in the states of Tabasco and Chiapas —including, among others, the varieties named crema (cream), doble crema (double cream), oaxaca, panela, fresco, bola, poro, Cotija, and asadero— have a high demand in the domestic and foreign markets. The intensification of anthropic activity in these states causes an increased emission to the environment of contaminants like heavy metals, which could reach human foodstuffs through the food chains. In particular, heavy metal contents in cheeses consumed daily by these states' local population might represent a public health risk. Because of that, our objectives in this work were to determine the concentrations of lead, cadmium, nickel, copper, zinc, and iron in artisanal cheeses produced in the states of Tabasco and Chiapas, and to determine the values of the Hazard Quotient (HQ), Total Hazard Quotient (THQ), and Cancer Risk Total (CRT) for adult and young men and women. The results of our analyses of cheese samples from the states of Tabasco and Chiapas showed that the average concentrations (mg kg-1) of cadmium (0.0023±0.002, 0.0023±0.002 mg kg-1, respectively for each state), lead (0.0047±0.00, 0.0051±0.002), nickel (0.0039±0.0046, 0.0031±0.0039), copper (0.0199±0.021, 0.0202±0.022), zinc (0.1611±0.18, 0.194±0.21), and iron (61.84±4.23, 65.76±6.61 mg kg-1), the first three values lower than the limits established by the FAO/WHO and Codex Alimentarius. The value of THQ that we obtained was less than one, and that of CRT was within the limits established by the US-EPA, which means that the consumption of artisanal cheeses from Tabasco and Chiapas by humans does not imply a risk of disease or cancer.

Chemistry is the last natural science discipline to embrace prepublishing, namely the publication of non-peer reviewed scientific articles on the internet. After a brief insight into the origins and the purpose of prepublishing in science, we conduct a concrete analysis of the concrete situation, aiming at providing an answer to several questions. Why the chemistry community has been late in embracing prepublishing? Is this in relation with the slow acceptance of open access publishing by the same community? Will prepublishing become a common habit also for chemistry scholars?

The snow melt from the High Atlas is a critical water resource in Morocco. In spite of its importance, monitoring the spatio-temporal evolution of key snow cover properties like the snow water equivalent remains challenging due to the lack of in situ measurements at high elevation. Since 2015, the Sentinel-2 mission provides high spatial resolution images with a 5 day revisit time, which offers new opportunities to characterize snow cover distribution in mountain regions. Here we present a new data assimilation scheme to estimate the state of the snowpack without in situ data. The model was forced using MERRA-2 data and a particle filter was developed to dynamically reduce the biases in temperature and precipitation using Sentinel-2 observations of the snow cover area. The assimilation scheme was implemented using SnowModel, a distributed energy-balance snowpack model and tested in a pilot catchment in the High Atlas. The study period covers 2015-2016 snow season which corresponds to the first operational year of Sentinel-2A, therefore the full revisit capacity was not yet achieved. Yet, we show that the data assimilation led to a better agreement with independent observations of the snow height at an automatic weather station and the snow cover extent from MODIS. The performance of the data assimilation scheme should benefit from the continuous improvements in MERRA-2 reanalyses and the full revisit capacity of Sentinel-2.

Frequent employee resistance to innovation is one of the main barriers of change failure in a health care organization and one of the negative stimuli of employment relationships. Identifying the reasons of resistance is a topical issue for every organization, as the speed of change can affect their competitiveness. Consequently, it is helpful not only to know the causes of potential resistance but also to be ready to control any implicit opposition. The organizational climate and the attitude of the staff play an important role in understanding and accepting innovation. Purpose of the study is to develop a model, which would facilitate the choice of an appropriate strategy necessary to enable the health care organization to eliminate or at least to reduce resistance to often essential innovative changes. The article analyses the root causes of resistance and identifies strategies that help to mitigate or eliminate staff resistance for innovation. Use of suggested model can make easier reducing staff resistance to change processes and thus speed up the implementation of innovations. This methodology can be used to eliminate the reasons for staff resistance to change in health care institutions of different countries, but it was tested in Lithuania and achieved good enough results.

Species have shown their habital variations in responding to climate change, especially during the spring and summer spawning seasons. The species distribution model (SDM) is considered the most favorable tool to study the potential effects of climate change on species distribution. Therefore, we developed the ensemble SDM to predict the changes in species distribution of Portunus trituberculatus among different seasons in 2050 and 2100 under the climate scenarios RCP4.5 and RCP8.5. The results of SDM indicate that the distribution of this species will move northward and have obviouse seasonal variations. Meanwhile, the suitable habitat for the species will be significantly reduced in summer, with loses rates ranging from 45.23% (RCP4.5) to 88.26% (RCP.8.5) by 2100s. Habitat reduction will mainly occur in the East China Sea and southern part of the Yellow Sea, while there will be a small increase in the northern Bohai Sea. These findings will be important to manage the ecosystem and fishery, provide an information forecast of this species in the future, and maintain species diversity if the seawater temperature rises.

Seyfe Lake is an important part of the natural ecosystem of Central Anatolia and lies within a 1487 km² closed basin. Groundwater withdrawal for irrigation and recent climatic change have caused lake area to decrease for decades and to completely disappear briefly in August 2008. Groundwater quality is crucial for sustainable irrigation in the Seyfe Basin. A key finding of this study is the difference in the Hardie-Eugster alkalinity-to-calcium ratio of the lake water and that of most groundwater wells in the basin. This difference in the chemical signature of Seyfe Lake and basin groundwater means the evaporative salinization pathway of most groundwater discharged into the lake cannot account for the composition of Seyfe Lake. The ratio of actual evapotranspiration to precipitation will increase under current climate change projections. A second finding, with implications for soil salinization, is that most groundwater in Seyfe Basin has a Hardie-Eugster alkalinity-tocalcium ratio greater than unity, meaning soil alkalization will accompany soil salinization.

The virtual airport hub business model is an innovative solution supported by digital technologies, the implementation of which in continental air transport may lead to a reduction in energy consumption and to a reduction in greenhouse gas emissions. The prerequisites for the implementation of the described solution are: striving to implement the GHG emission reduction strategy laid out in the Paris Agreement (2015) and the European Green Deal (2019) as well as the EU digitalization strategy (2020). The use of predictive analitics to identify the mobility needs of population and operational capabilities of the sector, gives an opportunity to plan travel flows and to create an appropriate set of direct connections among regional airports every day. The results of the analysis of data from 2019 on the amount of energy consumption and GHG emissions indicate that in Europe, it would be possible to achieve reduce GHG emissions by 5% without reducing the number of passengers using air transport. The study was prepared after conducting literature studies, data analysis and using the method of formulating scenarios. The proposed solution has the features of an innovative business model, the implementation of which allows for obtaining more favorable effects using already available resources.

Hybride halide perovskite materials gain enormous attention for their semiconducting properties, higher power conversion efficiency and potential applications in a wide range field of studies along with their two key limitations: stability and toxicity. In spite of great progress made on the halide perovskites and many promising research developments, overcoming these limitations is not realized yet. Therefore, coordination engineering of new framework for obtaining alternative new halide perovskite materials and fundamental understanding of the coordination chemistry and electronic interactions forming the structure of these newly engineered halide perovskite materials might be one way in order to overcome the issues related to both stability and toxicity. In this review, the current development of halide perovskite families, both lead halide perovskites and lead free halide perovskites followed by coordination engineering of the new frameworks to engineer new halide perovskite materials will be reviewed comprehensively. Moreover, all the concerns of the fundamental ideas of coordination chemistry and electronic interactions that are keys in forming the halide perovskite structures are discussed in detail and form the main aim of this review. Interestingly, we also discuss recent potential energy applications beyond photovoltaic and this review has completed with an essential and open question: ‘what could happen in the future of halide perovskites?’ in order to excite commercial enterprises and research institutions again as well as to get motivating new predictions on the future continuity of this field.

89Zr-radiolabelled proteins functionalised with desferrioxamine B are a cornerstone of diagnostic positron emission tomography. In the clinical setting, 89Zr-labelled proteins are produced manually. Here, we explore the potential of using a microfluidic photochemical flow reactor to prepare 89Zr-radiolabelled proteins. The light-induced functionalisation and 89Zr-radiolabelling of human serum albumin ([89Zr]ZrDFO-PEG3-Et-azepin-HSA) was achieved by flow photochemistry with a decay-corrected radiochemical yield (RCY) of 31.2±1.3% (n = 3) and radiochemical purity >90%. In comparison, a manual batch photoreactor synthesis produced the same radiotracer in a decay-corrected RCY of 59.6±3.6% (n = 3) with an equivalent RCP >90%. The results indicate that photoradiolabelling in flow is a feasible platform for the automated production of protein-based 89Zr-radiotracers, but further refinement of the apparatus, and optimisation of the method is required before the flow process is competitive with manual reactions.

A model of the early RNA world is proposed. Nearly self-complementary sequences that could adopt double-stranded, smallhairpin-like (shRNA), structures would be selected for due to their greater hydrolytic stability. These would be phosphorylated attheir 5' ends. We suppose that dehydrating conditions arise (perhaps intermittently) in the early environment allowing amino acidsto condense with these RNA molecules. The resulting phosphate-amino acid anhydrides would play the role of early, charged,tRNAs. A crude genetic code could emerge owing to the greater resistance of some amino acid-shRNA pairings to hydrolysisrelative to others. Early on there is no division of labor between mRNAs and tRNAs; the same molecules perform both functions.But the first systems would have encoded little in the way of protein sequence information. Rather they would have served as catalysts for the random polymerization of amino acids. It is speculated that the selective advantage inhering in such systems lay intheir ability to supply raw materials for the formation of coacervates within which the various molecules essential to proto-lifecould be concentrated. This would greatly facilitate the necessary chemistries. The evolution of homochiral protein and RNA populations is discussed. An appealing feature of this model is its ability to explain the transition from phosphorylated amino acids to the 3' ester-linked aminoacyl-tRNAs employed by modern life.

In the last 20 years, a huge amount of experimental results about halogen bonding (XB) has been produced. Most of the systems have been characterized by solid state X-ray crystallography, whereas in solution the only routine technique is the titration (by using ¹H and ¹⁹F NMR, IR, UV-Vis or Raman spectroscopies, depending on the nature of the system), with the aim of characterizing the strength of the XB interaction. Unfortunately, the titration techniques have many intrinsic limitations and they should be coupled with other, more sophisticated techniques to have an accurate and detailed description of the geometry and stoichiometry of the XB adduct in solution. In this review, it will be shown how crucial information about XB adducts can be obtained by advanced NMR techniques, as Nuclear Overhauser Effect-based Spectroscopies (NOESY, ROESY, HOESY…) and diffusion NMR techniques (PGSE or DOSY).

Achieving and sustaining stability for economic growth remain the greatest and most immediate development challenge for Ethiopia. For natural resource-based economies especially maintaining stability and growth depends fundamentally upon climate change adaptation and mitigation. The close links between climate and Ethiopia’s economy are reflected by the strong relationship between GDP growth rate and rainfall variability. A study by the World Bank projects that unless steps to build resilience are effective, climate change will reduce Ethiopia’s GDP growth by between 0.5 and 2.5% each year. Along with the challenges posed by climate change, a number of development opportunities are emerging in response to climate change which includes access to international climate finance. The international response to climate change in the form of external development finance plays a key role to support developing countries in their transition to a low-carbon, climate-resilient and sustainable development pathway. Therefore, this study was conducted to assess the flow and the overall contribution of climate finance to sustainable development in Ethiopia. Specifically, focused on outlining how climate finance is currently reconciled in the existing Ethiopian climate change governance and its contribution to sustainable development. In order to achieve these objectives, data were collected from different sources. The Rio Marker methodology applied to review climate financial flow over the 5 year period. The result reveals that, climate change is central to development agendas despite its recent emergence in the mainstream, with various initiatives under way to combat or reduce its impacts in Ethiopia. In addition, the amount of climate finance from the developed countries to Ethiopia shows some fluctuation for the past five years. In general, the overall flow of climate finance mostly targeted climate adaptation actions which spur and enable the transition towards climate-resilient growth and sustainable development.

This study assessed stakeholders’ perception on the prospects and challenges of practising Climate–Smart Agroforestry in the Asunafo North Municipal Assembly in the Ahafo Region in Ghana. Interviewer administered questionnaires were used to collect cross-sectional data from 250 cocoa, food and cash crop farmers drawn from four (4) communities using simple random sampling. And nine (9) in-depth interviews were also conducted to elicit key stakeholder perspectives. Stakeholders also held the view that Climate-Smart Agroforestry encourages the use of stress-tolerant crop varieties, increase income, improve soil productivity, diversify farm produce, urges the reduction of input supply and recommends the timely usage of the inputs, ensures better market system for farm produce, cost of production decreases during the practice of Agroforestry, agro-ecological functions and Climate-Smart Agroforestry can best help adapt to the threats of climate change in the agriculture sector. The challenges included insecure tree ownership right, fast-declining soil fertility and long maturity period of Agroforestry trees, land tenure issues, illegal tree logging (chainsaw operators) on farms, lack of practical understanding of the approach, inadequate knowledge and information and inadequate supportive facilities in the study area. The study recommends further studies on the existing forest policy and legislations and its implications on the practice and adoption of Climate-Smart Agroforestry in respond to climate change in the area.

An existing simplified simulation model of global climate, population, economy, and governance is extended, through statistical and other data analysis, to include several measures of human well-being and population displacement. The revised model is used to explore (in testing to the year 2060) vicious cycles and causal cascades that, some have warned, could lead to acceleration of climate change in the coming decades. Model scenario testing addresses two uncertainties, namely the strength of the effect of climate change on governance erosion, and the strength of the “heat trap” effect from physical tipping points such as ice loss and permafrost thaw. This testing indicates that a strong heat trap effect could very well accelerate climate change, but that even a strong governance erosion effect is unlikely to do so. Governance erosion would hurt human well-being but is probably not much of a climate threat per se. These results are tentative but point to the possibility of formally modeling causal cascades beyond what the larger climate models have done to date.

Rapid climate change requires more powerful and precise modeling methods to forecast future climate variability. The GSTARIMA Model is efficient, combining space-time analysis with the Autoregressive Moving Average (ARIMA) Model. The integration of heteroscedasticity error and the Kriging method can strengthen the Model's ability to handle the problem of non-constant error variance in the GSTARIMA Model and forecast at unobserved locations of climate observations. This paper's Systematics Literature Review (SLR) is presented comprehensively with the principal aim of developing a thorough understanding of applying the GSTARIMA Model with heteroskedasticity error and the Kriging Method in climate forecasting following the Data Analytics Lifecycle methodology. The Systematic Literature Review (SLR) process consists of three main stages. We sourced the articles from databases such as Scopus, Dimensions, and EBSCO-Host The subsequent stage involved conducting a comprehensive literature review using the PRISMA method to ensure rigor and depth. Additionally, we performed bibliometric analysis to enhance rigor. Lastly, we conducted a gap analysis session to scrutinize existing research on the GSTARIMA Model and identify new opportunities. This literature review reveals that integrating GSTARIMA Model with heteroscedasticity errors and the Kriging method is suitable for climate forecasting. This research inspires researchers to contribute to the improvement and refinement of the Model, making it a more potent and valuable tool in climate forecasting.

We describe the development and validation of a HPLC-MS/MS method to assess the pharmacokinetics and tumour distribution of ZST316, an arginine analogue with inhibitory activity towards dimethylarginine dimethylaminohydrolase 1 (DDAH1) and vasculogenic mimicry, and its active metabolite L-257 in a xenograft model of triple negative breast cancer (TNBC). The method proved to be reproducible, precise, and highly accurate for the measurement of both compounds in plasma and tumour tissue following acute and chronic (five days) intraperitoneal administration of ZST316 (30mg/Kg daily) in six-week-old SCID mice inoculated with MDA-MB-231 TNBC cells. ZST316 was detected in tumour tissue and plasma after 1 hour (6.47 and 9.01M, respectively) and 24 hours (0.13 and 0.16M, respectively) following acute administration, without accumulation during chronic treatment. Similarly, the metabolite L-257 was found in tumour tissue and plasma after 1 hour (15.06 and 8.72M, respectively) and 24 hours (0.17 and 0.17M, respectively) following acute administration of ZST316, without accumulation during chronic treatment. The half-live after acute and chronic treatment ranged between 4.4-7.1hrs (plasma) and 4.5-5.0hrs (tumour) for ZST316, and 4.2-5.3hrs (plasma) and 3.6-4.9hrs (tumour) for L-257. The results of our study demonstrate the a) capacity to accurately measure ZST316 and L-257 concentrations in plasma and tumour tissue in mice using the newly developed HPLC-MS/MS method, b) rapid conversion of ZST316 into L-257, c) good intra-tumour penetration of both compounds, and d) lack of accumulation of both ZST316 and L-257 in plasma and tumour tissue during chronic administration. The new HPLC-MS/MS method is useful to investigate the in vivo effects of ZST316 and L-257 on vasculogenic mimicry, tumour mass, and metastatic burden in xenograft models of TNBC.

In this paper we illustrate a new, simple and complementary ground-based methodology to retrieve the vertically resolved atmospheric precipitation intensity through a synergy between measurements from the National Aeronautics and Space Administration (NASA) Micropulse Lidar network (MPLNET), an analytical model solution and ground-based disdrometer measurements. The presented results are obtained at two mid-latitude MPLNET permanent observational sites, located respectively at NASA Goddard Space Flight Center, USA, and at the Universitat Politècnica de Catalunya, Barcelona, Spain. The methodology is suitable to be applied to existing and/or future lidar/ceilometer networks with the main objective of either providing near-real time (3h latency) rainfall intensity measurements and/or to validate satellite missions, especially for critical light precipitation (<3 mm hr⁻¹).

The World Meteorological Organization (WMO) recommends that the most recent 30-year period, i.e. 1991-2020, shall be used to compute climate normals of geophysical variables. A unique aspect this recent 30-year period is that the satellite-based observations of many different essential climate variables are available during this period, thus opening up new possibilities to provide a robust, global basis for the 30-year reference period in order to allow climate monitoring and climate change studies. Here, using the satellite-based climate data record of cloud and radiation properties, CLARA-A3, for the month of January between 1981 to 2020, we illustrate the difference between climate normal, as defined by guidelines from WMO on calculations of 30-yr climate normals, and climatology. It is shown that this difference is strongly dependent on the climate variable in question. We discuss the impacts of the nature and availability of satellite observations, variable definition, retrieval algorithm and programmatic configuration. It is shown that the satellite-based climate data records show enormous promise in providing climate normal for the recent 30-year period (1991-2020) globally. We finally argue that the holistic perspectives from the global satellite community should be increasingly considered while formulating the future WMO guidelines on computing climate normals.

The brown pelican (Pelecanus occidentalis) is a species often affected by natural and man-made disasters such as hurricanes and oil spills as well as general human activities; that subsequently receives medical care and rehabilitation. During rehabilitation, blood may be collected for various testing to help with diagnosis, treatment, and monitoring. Reference intervals for this species are limited, dated, and typically from small sample sizes. Seventy one presumed healthy brown pelicans were sampled as a part of their pre-release examination from rehabilitation at the Wildlife Center of Texas after a large volume stranding in December 2014 to January 2015, and various venous analytes were measured to establish updated reference intervals for Brown Pelicans. Fibrinogen was measured via heat precipitation and the Abaxis VSPro equine Fibrinogen cartridge to determine reference intervals, and in an attempt to validate the VSPro for use in avian species. Abaxis VS2 Avian/Reptile Chemistry panel, iSTAT CG4+, and iSTAT Chem8+ results in addition to body condition score, spun PCV, cloacal temperature and fibrinogen were measured. Proposed reference intervals for brown pelicans are presented. Fibrinogen results were not comparable between the gold standard method and the VSPro, indicating that the VSPro is not appropriate for use in brown pelicans.

Cannabis sativa is one of the oldest plants utilized by humans for both economic and medical purposes. Although the use of cannabis started millennia ago in the Eastern part of the hemisphere, its use has moved and flourished in the Western Nations in more recent centuries. C. sativa is the source of psychoactive cannabinoids that are consumed as recreational drugs worldwide. The C21 aromatic hydrocarbons are restricted in their natural occurrence to cannabis (with a few exceptions). Delta-9-tetrahydrocannabinol (Δ9-THC) is the main psychoactive component in cannabis with many pharmacological effects and various approved medical applications. However, a wide range of side effects are associated with the use of Δ9-THC, limiting its medical use. In 1966, another psychoactive cannabinoid, Delta-8-tetrahydrocannabinol (Δ8-THC) was isolated from marijuana grown in Maryland but in very low yield. Δ8-THC is gaining increased popularity due to its better stability and easier synthetic manufacturing procedures compared to Δ9-THC. Passing the U.S. Farm Bill in 2018 led to an increase in the sale of Δ8-THC in the United States. The marketed products contain Δ8-THC from synthetic sources. In this review, methods of extraction, purification, and structure elucidation of Δ8-THC will be presented. The issue of whether Δ8-THC is a natural compound or an artifact will be discussed, and the different strategies for its chemical synthesis will be presented. Δ8-THC of synthetic origin is expected to contain some impurities due to residual amounts of starting materials and reagents as well as side products of the reactions. The various methods of analysis and detection of impurities present in the marketed products will be discussed. The pharmacological effects of Δ8-THC, including its interaction with CB1 and CB2 cannabinoid receptors in comparison with Δ9-THC, will be reviewed.

Cratylia argentea is a leguminous shrub with a great potential for livestock feeding in tropical areas. However, time consuming and labor-intensive methods of chemical analysis limits the understanding of its nutritive value. Near infrared spectroscopy (NIRS) is a low-cost technology that has been widely used in forage crops to fasten the assessment of its chemical composition. The objective of this study was to develop prediction models to assess crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF) and dry matter (DM) of Cratylia based on NIRS and partial least square analysis. A total of 155 samples were harvested at different maturity levels and used for model development, whereas 107 were used for calibration and 48 for external validation. The cross-validation presented Root Mean Square Error of Prediction of 0.77, 2.56, 3.43, and 0.42; a Ratio of Performance to Deviation of 4.8, 4.0, 3.8, and 3.4; an R2 of 0.92, 0.92, 0.87, and 0.84 for CP, NDF, ADF, and DM, respectively. Based on the obtained results, we conclude the ability to predict chemical parameters of Cratylia with the current model was accurate. This way, livestock producers and researchers may use it to fasten the assessment of Cratylia’s nutritive value.

Background: Wastewater represents a health risk for populations. For sanitary safety, it is important to know their physico-chemical and microbiological qualities in order to better understand the risks incurred by the population. Objective: The aim of this study is to analyse the microbiological and physico-chemical quality of domestic wastewater in Adétikopé. Methodology: 12 wastewater samples were collected in Adétikopé from December 2022 to February 2023. Physico-chemical parameters were determined in accordance with AFNOR T90-105/ T90-023 and French standard NF T 90101. In microbiology, AFNOR was used as a reference for the detection of germs contaminating wastewater. Results were assessed in relation to European Union Criteria 98/83/EC. Results: The wastewater analyzed had a pH close to neutral, with an average pH of 7.05. The pollutant load generated ranged from 32 mg/l to 201 mg/l for BOD5, from 660 mg/l to 900 mg/l for COD and from 408 mg/l to 2080 mg/l for suspended solids. Concentrations of fecal coliforms and fecal streptococci are very high, far exceeding WHO guidelines for population health safety.

Global pollution from fossil plastics is one of the top environmental threats of our times. The end-of-life scenarios of fossil plastic, including recycling, incineration and disposal result in mi-croplastic formation, elevated atmospheric CO2 levels, and littering of terrestrial and aquatic environments by plastic waste. Currently thought-out regulations centered around banning plastics production and use and only recycling on a regional, national and global level are impeding efforts to rapidly replace fossil plastics through the use of natural alternatives. In particular, this review demonstrates how mi-crobial polyhydroxyalkanoates (PHA), a class of intrinsically natural polymers, can easily remedy for the fossil and persistent plastic dilemma. PHA are bio-based, bio-synthesized, bio-compatible, bio-degradable, and home- and industrially compostable. Therefore, they are one of the perfect replacements for our fossil plastics pollution dilemma, providing us with the benefits of fossil plastics and meeting all requirements of a truly circular economy. PHA biopolyesters are natural and green materials in all aspects of their life cycle. The review elaborates in detail how PHA’s production, consumption, and end-of-life profile are perfectly embedded in the current topical 12 Principles of Green Chemistry, which constitute the basis for sustainable product manufacturing. It is shown that it is time for a paradigm shift in plastics manufacturing, use and disposal. Hu-mankind needs alternatives to fossil plastics, which, as recalcitrant xenobiotics, contribute to the increasing deterioration of our planet. Natural PHA biopolyesters represent that paradigm shift!

Laboratory medicine is a digital science. Every large hospital produces a wealth of data each day - from simple numerical results from e.g. sodium measurements to highly complex output of “-omics” analyses, as well as quality control results and meta-data. Processing, connecting, storing, and ordering extensive parts of these individual data requires Big Data techniques. Whereas novel technologies such as artificial intelligence and machine learning have exciting application for the augmentation of laboratory medicine, the Big Data concept remains fundamental for any sophisticated data analysis in large databases. To make laboratory medicine data optimally usable for clinical and research purposes, they need to be FAIR: findable, accessible, interoperable, and reusable. This can be achieved for example by automated recording, connection of devices, efficient ETL (Extract, Transform, Load) processes, careful data governance, and modern data security solutions. Enriched with clinical data, laboratory medicine data allow a gain in pathophysiological insights, can improve patient care, or they can be used to develop reference intervals for diagnostic purposes. Nevertheless, Big Data in laboratory medicine do not come without challenges: The growing number of analyses and data derived from them is a demanding task to be taken care of. Laboratory medicine experts are and will be needed to drive this development, take an active role in the ongoing digitalization, and provide guidance for their clinical colleagues engaging with the laboratory data in research.

Viral infections inflict many serious human diseases, being responsible for remarkably high mortality rates. In this sense, both the academy and the pharmaceutical industry are continuously searching for new compounds with antiviral activity, and in addition, face the challenge of developing greener and more efficient methods to synthesize these compounds. This becomes even more important with drugs possessing stereogenic centers as highly enantioselective processes are required. In this minireview, the advances achieved to improve synthetic routes efficiency and sustainability of important commercially antiviral chiral drugs are discussed, highlighting the use of organocatalytic methods.

“Clickase” single-chain nanoparticles (Ck-SCNPs) are folded, enzyme-mimetic unimolecular polymeric nano-objects containing copper (Cu) ions able to catalyze the azide-alkyne Huisgen cycloaddition reaction in water and/or selected organic solvents, often in the presence of a reductant. Herein, we investigate the effect of morphology on catalytic activity of Ck-SCNPs synthesized by means of two different routes. An amphiphilic random copolymer composed of oligo(ethylene glycol) methyl ether methyl methacrylate (OEGMA) and 2-acetoacetoxy ethyl methacrylate (AEMA) units was used as precursor of these Ck-SCNPs. Folding was promoted through metal complexation between Cu(II) ions and beta-ketoester-containing AEMA moieties. The first route resulted in Ck-SCNPs1 containing Cu ions homogeneously distributed within each nanoparticle, whereas the second one promoted intra-chain clustering of Cu ions inside Ck-SCNPs2. A model fluorogenic “click” reaction between 9-(azidomethyl)anthracene and phenylacetylene, which was catalyzed either by Ck-SCNPs1 or Ck-SCNPs2, was used to unravel the effect of morphology on catalytic activity. This work paves the way to improve the catalytic activity of metallo-folded SCNPs through control of the intra-chain distribution of catalytic sites.

Hydrogenases are iron-sulfur enzymes that catalyze proton reduction and H₂ oxidation with outstanding efficiency. They are considered blueprints for the design of transition metal complexes, e.g. as heterogenous catalysts in the context of H₂ production from water. Moreover, hydrogenases are biological model systems for metal hydride chemistry and proton-coupled electron transfer. Depending on the composition of the active site cofactor, [NiFe]-hydrogenases are distinguished from [FeFe]-hydrogenases. The former binds a hetero bimetallic nickel/iron site, embedded in the protein by four cysteine ligands. The later, by contrast, carries a homo bimetallic iron/iron site attached to the protein by only a single cysteine. Carbon monoxide and cyanide ligands (CO/CN) at the active site facilitated detailed investigations of hydrogenase catalysis by infrared spectroscopy, owing to strong signals and redox-dependent frequency shifts. However, the details of proton transfer have not been addressed experimentally.We found that specific redox state transitions in [NiFe]- and [FeFe]-hydrogenase can be triggered by visible light to record extremely sensitive ‘light-minus-dark’ infrared difference spectra monitoring key amino acid residues as shown in the ToC figure. As these transitions are coupled to protonation changes, our data allowed investigating dynamic hydrogen-bonding changes that go well beyond the resolution of protein crystallography. In [NiFe]-hydrogenase, photolysis of the bridging hydride ligand in the ‘Ni-C’ state was followed by rapid accumulation of the ‘Ni-SI_a’ state and/or ‘Ni-L’ state. Infrared difference spectra in various isotopic media clearly indicated the formation of a protonated cysteine residue as well as hydrogen-bonding changes involving the COOH group of a glutamic acid residue and a ‘dangling water’ molecule. These findings are in excellent agreement with crystallographic analyses of [NiFe]-hydrogenase in the Ni-R state and allowed devising a molecular precise model of catalytic proton transfer. In [FeFe]-hydrogenase, an external redox dye was used to accumulate the ‘Hred’ state over the oxidized resting state ‘Hox’. Infrared difference spectra of wild-type enzyme and numerous amino acid variants indicated hydrogen-bonding changes involving the COOH groups of two glutamic acid residues. Moreover, we noted the deprotonation of an arginine residue. Crystallographic analyses of [FeFe]-hydrogenase in the Hox state failed to explain the rapid proton transfer due to a ‘breach’ in the succession of residues. To this end, our findings facilitated a molecular precise model of ‘discontinued’ proton transfer.The comparison of catalytic proton transfer in bimetallic hydrogenases emphasizes the role of the outer coordination sphere. We suggest that the stable protonation of a nickel-ligating cysteine in [NiFe]-hydrogenase has a crucial influence on the preferred direction of proton flow and catalysis (i.e., H₂ oxidation). On the contrary, proton transfer in [FeFe]-hydrogenase involves an adjacent cysteine as a relay group that promotes both proton release and proton uptake. We presume that this causes the notable bidirectionality of [FeFe]-hydrogenase. These observations must guide the design of biomimetic compounds for the production or consumption of H₂.

In this research, the photocatalytic degradation of cypermethrin using Fe-TiO2 nanoparticles supported in a biomaterial was evaluated. The nanoparticles of TiO2 were synthesized by the green chemistry method assisted by ultrasound and doped by chemical impregnation using molar ratios Fe:Ti of 0, 0.05, 0.075 and 0.1, to make efficient use of direct sunlight (λ>310 nm). All nanoparticles were immobilized on the surface of spathe of coconut palm (Cocos nucifera). The degradation was carried out at room temperature and natural pH in a flat plate solar reactor, on which the composite material was subjected. The concentration of cypermethrin was determined after 12000 J/m2 of accumulated radiation from GC-MS and the resulting material was characterized by Scanning electron microscopy (SEM), Transmission electron microscopy (TEM) image and selected area electron diffraction (SAED), Fourier transform infrared spectroscopy (FTIR), UV-Vis spectrophotometry of diffuse reflectance and BET surface area BET surface area. The best results were achieved with the use of Degussa TiO2 P-25, Fe:Ti=0 and Fe:Ti=0.05 in suspension, with percentages of degradation of cypermethrin of 99.84, 99.62, and 100%, respectively. However, the materials supported on the biomaterial of coconut, they allowed to reach degradation percentages higher than 80% with the advantage that it minimizes operating costs, since they are not necessary filtering or centrifuging processes to separate the catalyst.

Organic compounds that contain poly-triazole are very important intermediates in pharmaceutical and chemical industry. Click chemistry is one of essential reactions that can form C-N bond with high atom economy. The research progress in metals catalyzed Click chemistry of azides and alkynes from the perspective of reaction mechanism is categorized and summarized.

Assessment of extreme events and climate change on reservoir inflow is important for water and power stressed countries. Projected climate is subject to uncertainties related to climate change scenarios and Global Circulation Models (GCMs’). Extreme climatic events will increase with the rise in temperature as mentioned in the AR5 of the IPCC. This paper discusses the consequences of climate change that include extreme events on discharge. Historical climatic and gauging data were collected from different stations within a watershed. The observed flow data was used for calibration and validation of SWAT model. Downscaling was performed on future GCMs’ temperature and precipitation data, and plausible extreme events were generated. Corrected climatic data was applied to project the influence of climate change. Results showed a large uncertainty in discharge using different GCMs’ and different emissions scenarios. The annual tendency of the GCMs’ is bi-vocal: six GCMs’ projected a rise in annual flow, while one GCM projected a decrease in flow. The change in average seasonal flow is more as compared to annual variations. Changes in winter and spring discharge are mostly positive, even with the decrease in precipitation. The changes in flows are generally negative for summer and autumn due to early snowmelt from an increase in temperature. The change in average seasonal flows under RCPs’ 4.5 and 8.5 are projected to vary from -29.1 to 130.7% and -49.4 to 171%, respectively. In the medium range (RCP 4.5) impact scenario, the uncertainty range of average runoff is relatively low. While in the high range (RCP 8.5) impact scenario, this range is significantly larger. RCP 8.5 covered a wide range of uncertainties, while RCP 4.5 covered a short range of possibilities. These outcomes suggest that it is important to consider the influence of climate change on water resources to frame appropriate guidelines for planning and management.

A sustainable reversed-phase chromatographic method has been developed and validated for the simultaneous determination of three active pharmaceutical ingredients, dorzolamide, brinzolamide, and timolol, used to treat glaucoma. The eco-friendly solvent isopropanol has been used as an organic mobile phase constituent. According to the Hansen space green solvent selection tool, isopropanol has a G score of 6.5, comparable to ethanol, which has a G score of 6.6. The mobile phase consists of isopropanol: aqueous sodium acetate buffer (0.1 M, pH 4.25) in the ratio of 10:90 (v/v). The flow rate was maintained at 1 mL/min. Dorzolamide and brinzolamide were detected at 254 nm, and timolol was detected at 295 nm. A high-purity silica with a polymeric C18 modification column (5 µm,150 x 4.6 mm) was used for this separation. The three compounds were eluted within 8 min. The method was validated according to ICH guidelines. The calibration curves were linear in the range of 20-70 µg/mL, 40-140 µg/mL, and 20-70 µg/mL for dorzolamide, brinzolamide, and timolol, respectively. The LODs were found to be 1.61 µg/mL, 1.60 µg/mL, and 3.16 µg/mL for dorzolamide, brinzolamide, and timolol, respectively. Good accuracy and precision were obtained for the three compounds. The greenness and whiteness of the method were indicated using the AGREE and RGB12 tools, respectively.

As recent history has shown, changing climate not only threatens to increase the spread of known disease, but also the emergence of new and dangerous phenotypes. This occurred most recently with West Nile virus: a virus previously known for mild febrile illness rapidly emerged to become a major cause of mortality and long-term disability throughout the world. As we move forward, into increasingly uncertain times, public health research must begin to incorporate a broader understanding of the determinants of disease emergence – what, how, why, and when. The increasing mainstream availability of high-quality open data and high-powered analytical methods presents promising new opportunities. Up to now, quantitative models of disease outbreak risk have been largely based on just a few key drivers, namely climate and large-scale climatic effects. Such limited assessments, however, often overlook key interacting processes and downstream determinants more likely to drive local manifestation of disease. Such pivotal determinants may include local host abundance, human behavioral variability, and population susceptibility dynamics. The results of such analyses can therefore be misleading in cases where necessary downstream requirements are not fulfilled. It is therefore important to develop models that include climate and higher-level climatic effects alongside the downstream non-climatic factors that ultimately determine individual disease manifestation. Today, few models attempt to comprehensively address such dynamics: up until very recently, the technology simply hasn’t been available. Herein, we present an updated overview of current perspectives on the varying drivers and levels of interactions that drive disease spread. We review the predominant analytical paradigms, discuss their strengths and weaknesses, and highlight promising new analytical solutions. Our focus is on the prediction of arboviruses, particularly West Nile virus, as these diseases represent the pinnacle of epidemiological complexity – solution to which would serve as an effective “gatekeeper”. We present the current state-of-the-art with respect to known drivers of arbovirus outbreak risk and severity, differentially highlighting the impact of climate and non-climatic drivers. The reality of multiple classes of drivers interacting at different geospatial and temporal scales requires advanced new methodologies. We therefore close out by presenting and discussing some promising new applications of AI. Given the reality of accelerating disease risks due to climate change, public health and other related fields must begin the process of updating their research programs to incorporate these much needed, new capabilities.

Climate change effect on human-living in verities of way such as health and food security. This study presents predicting crop yields, and production risk in the near future (2020-2029) in northern Thailand using coupling 1 km resolution of regional climate model which is downscaled using a conservative remapping method and the Decision Support System for the Transfer of Agrotechnology (DSSAT) modeling system. The accuracy of the climate and agricultural model was appropriate compared to the observations with Index of Agreement (IOA) in ranges of 0.65 - 0.89. The DSSAT modeling system predicts that rice, and maize production will decrease by 5% and 4% in northern Thailand. In addition, a short-term risk analysis of rice and maize production has shown that, in the context of climate change, maize production appears to be at a high risk of low production in the near future, while rice cultivation might be a low risk.

Land use/land cover (LULC) and climate changes are two main factors directly affecting hydrologic conditions. However, very few studies in Vietnam have investigated changes in hydrological process under the impact of climate and land use changes on a basin scale. The objective of this study is to assess the individual and combined impacts of land use and climate changes on hydrological processes for the Nam Rom river basin, Northwestern Viet Nam using Remote Sensing (RS) and Soil and Water Assessment Tools (SWAT) model. SWAT model was used for hydrological process simulation. Results indicated that SWAT proved to be a powerful tool in simulating the impacts of land use and climate change on catchment hydrology. The change in historical land use between 1992 and 2015 strongly contributed to increasing hydrological processes (ET, percolation, ground water, and water yield), whereas, climate change led to significant decrease of all hydrological components. The combination of land use and climate changes significantly reduced surface runoff (-16.9%), ground water (-5.7%), water yield (-9.2%), and sediment load (-4.9%). Overall climatic changes had more significant effect on hydrological components than land use changes in the Nam Rom river basin during the 1992–2015. Under impacts of projected land use and climate change scenarios in 2030 on hydrological process of the upper Nam Rom river basin indicate that ET and surface flow are more sensitive to the changes in land use and climate in the future. In conclusion, the findings of this study will basic knowledge of the effects of climate and land-use changes on the hydrology for future development of integrated land use and water management practices in Nam Rom river basin.

Storm Ophelia made landfall over Ireland as an extra-tropical storm on the morning of the 16th of October 2017. The storm caused major power outages, lifted roofs, caused coastal flooding in Ireland, and resulted in the loss of three lives. A model’s capability to forecast extreme weather events such as Storm Ophelia is of utmost importance and now with a changing climate, it becomes more important to improve and enhance model forecasting capability. The Weather Research and Forecasting (WRF) model V3.9 has been configured for the Irish domain and this study presents a preliminary evaluation of the Model during Storm Ophelia. Simulated wind speed and direction were compared with hourly remote sensing (lidar) and in-situ (wind speed and wind direction at 10m) observations at the coastal site of Mace Head Atmospheric Research Station on the West coast of Ireland (53.33◦ N, 9.90 49 ◦ W). The model simulation has generally small biases in the simulated wind speed and wind direction during this case study. The model also realistically simulated the magnitude and geographical distribution of the wind speed and wind direction observed during Ophelia.

We revisit the notion of climate, along with its historical evolution, tracing the origin of the modern concerns about climate. The notion (and the scientific term) of climate has been established during the Greek antiquity in a geographical context and it acquired its statistical content (average weather) in modern times, after meteorological measurements had become common. Yet the modern definitions of climate are seriously affected by the wrong perception of the previous two centuries that climate should regularly be constant, unless an external agent acted. Therefore, we attempt to give a more rigorous definition of climate, consistent with the modern body of stochastics. We illustrate the definition by real-world data, which also exemplify the large climatic variability. Given this variability, the term “climate change” turns out to be scientifically unjustified. Specifically, it is a pleonasm as climate, like weather, has been ever changing. Indeed, a historical investigation reveals that the aim in using that term is not scientific but political. Within the political aims, water issues have been greatly promoted by projecting future catastrophes while reversing the true roles and causality directions. For this reason, we provide arguments that water is the main element that drives climate and not the opposite.

Even though Greece is considered a vulnerable region in terms of climate hazards, public perception and attitude do not always identify climate change as an important environmental area of concern, especially when compared to socio-economic issues. The key issue of this paper is to investigate and analyse public perception in Greece as regards to climate change risk. Through a questionnaire survey this paper analyses trends that exist, peoples’ opinion and awareness with regards to climate risk and how willing they are to change current lifestyle, to pay or to act to minimize or to prevent the risk. Conventional wisdom of this paper is to highlight factors that influence individual perception and point out drivers of behavior change that can support efficiently future adaptation plans.

Fe[C5H5N]2[N(CN)2]2 (1) was synthesized from a reaction of stoichiometric amounts of NaN(CN)2 and FeCl2·4 H2O in a methanol/pyridine solution. Single-crystal and powder diffraction show that 1 crystallizes in the monoclinic space group I2/m (no. 12), different from Mn[C5H5N]2[N(CN)2]2 (P21/c, no. 14) due to tilted pyridine rings, with a = 7.453(7) Å, b = 13.167(13) Å, c = 8.522(6) Å, β = 114.98(6)° and Z = 2. ATR-IR, AAS, and CHN measurements confirm the presence of dicyanamide and pyridine. Thermogravimetric analysis shows that π-stacking interactions of the pyridine rings play an important role in structural stabilization. Based on DFT-optimized structures, a chemical bonding analysis was performed using a local-orbital framework by projection from a plane-wave basis. The resulting bond orders and atomic charges are in good agreement with the expectations based on the structure analysis. SQUID magnetic susceptibility measurements show a high-spin state FeII compound with predominantly antiferromagnetic exchange interactions at lower temperatures.

Alginate extraction is from seaweed, and lignin separation is from by-product corn (stalks and leaves). Alginate/lignin is a synthetic polymer rich in biological activity of great interest. Antioxidant activities of alginate/lignin were evaluated, such as total antioxidant activity, reducing power activity, DPPH free radical scavenging activity, and α – glucosidase inhibition activity. The test of anticancer activity was on four cell lines (Hep G2, fibroblast, MCF-7, and NCI H460). Determination of physical-chemistry characteristics of alginate/lignin was through FTIR, DSC, SEM_EDS, SEM_EDS mapping, XRD, XRF, and 1H-NMR. A study of acute toxicity of alginate/lignin was on Swiss albino mice. The results showed alginate/lignin possessed antioxidant activity such as total antioxidant activity, reducing power activity, especially, α – glucosidase inhibition activity, and no free radical scavenging activity. Alginate/lignin did not be typical in cancer cell lines. Alginate/lignin existed in a thermally stable regular spherical shape in the investigated thermal region. Some specific functional groups of alginate and lignin did not exist in alginate/lignin crystal. Elements such as C, O, Na, and S were popular in the alginate/lignin structure. LD0 and LD100 of alginate/lignin in mice were 3.91 g/kg and 9.77 g/kg, respectively. Alginate/lignin is the potential for application as pharmaceutical materials, functional foods, and supporting diabetes treatment.

Successful fertilization treatments targeted to improve stand productivity while reducing operational complexities and cost depend on a clear understanding of soil nutrient availability under varying environmental conditions. Soil nutrient data collected from 154 forest sites throughout the Inland Northwest, USA were analyzed to examine soil nutrient characteristics on different geologic soil parent materials and to rank soil fertility. Results show that soil parent material explains significant differences in soil nutrient availability. Soils developed from volcanic rocks have the highest CEC and are relatively high in P, K, S, Mg, Cu, Ca, and B, but generally poor in N. Forest soils developed from plutonic rocks exhibit the lowest CEC and are low in N, S, K, Mg, Cu, and Ca, but higher in P. Some soils located on mixed glacial till are low only in K, Cu, Mg, and Ca, but many glacial soils are relatively rich in other nutrients, albeit the second lowest CEC. Soils developed from metasedimentary and sedimentary rocks are among those with lowest soil nutrient availability for P and B. Sulfur was found to have the highest concentrations in metasedimentary influenced soils and the least in sedimentary derived soils. Our results should be useful in designing site-specific fertilizer and nutrient management prescriptions for forest stands growing on soils developed from these major geologies within the Inland Northwest region of the United States.

Heterocycles are unique precursors for the synthesis of various pharmaceuticals and agrochemicals particularly those possessing N- or O- moieties. The development of methods to prepare heterocycles is of great importance in synthesis of organic compounds, especially the heterocycles which can be found in natural products. The synthesis of nitrogen and oxygen containing heterocycles viz. coumarins, dihydropyrimidinones, imidazoles, isoxazoles and benzimidazoles represented an attractive and demanding work for chemists as these nucleus has found extensive applications in several fields such as material science, analytical chemistry and most importantly in medicinal chemistry. Organic synthesis has been attracted towards the development of new environmental friendly procedures to achieve the goals of green chemistry. The fundamental aspects of green chemistry are use of biocatalysts and environmental benign solvents under mild conditions. The present review article summarized the green synthetic methods and biological activities of nitrogen and oxygen containing heterocycles.

Cyanides, though naturally occurring, are environmental pollutants when not treated properly. Some methods used to attenuate cyanides in waste waters from industrial processes are based simply on changing the physico-chemical properties of the waste water such as the pH and temperature. The effectiveness of these methods are based on hydrolysis of the cyanide and volatilization of the hydrogen cyanide formed. Another reaction which takes place simultaneously is ultraviolet-catalysed oxidation which converts the cyanide to bicarbonates and carbonates.The changes in the cyanide degradation rate approaches a minimum faster if the cyanide solution is maintained at a higher than ambient constant temperature.

Hydroxychloroquine, a known antiviral metabolite of chloroquine, is increasingly used along with antibiotic azithromycin for the treatment of COVID-19 infection. In about one month India, the world’s largest manufacturer, delivered hydroxychloroquine for treating COVID-19 to over 50 countries. The therapy is being used across the world both for patients staying at home at the early phase of symptoms, as well as for patients hospitalized. We summarize achievements as of late April 2020, review possible modes of action and suggest avenues for the quick scale-up of production of hydroxychloroquine.

The combination of eco-respectful epoxy compounds with the humins, a by-product of biomass chemical conversion technologies, allow the obtention of materials with high added value. In this work, we propose the chemical connection study of humins with two aliphatic diepoxides through the copolymerization reactions to synthesize sustainable bio-based thermosets. The mechanism insights for the crosslinking between the epoxides and humins was proposed considering the different functionalities of the humins structure. FT-IR spectroscopy, 1 D and 2 D NMR spectroscopy techniques were used to build the proposed mechanism. By these techniques, the principal chain connections and the reactivity of all the components were highlighted in the synthesized networks.

The cross-linkable PCL-PEG analogues block-graft copolymer was designed and synthesized, which with the copolymer of the MEO₂MA and OEGMA as graft chains to improve the mPEG-b-PCL-b-mPEG copolymer the aqueous solution properties. And successfully prepared two hydrogels via a copper-catalyzed 1, 3-dipolar azide-alkyne cycloaddition reaction of alkyne-terminated poly[glycidyl methacrylate-co-2-(2-methoxyethoxy) ethyl methacrylate-co-oligo (ethylene glycol) methacrylate] [P(GMA-co-MEO₂MA-co-OEGMA)] with azide end-functionalized PCL-PEG analogues block-graft copolymer, and tetrakis (2-propynyloxymethyl) -methane (TPOM) and with azide end-functionalized PCL-PEG analogues block-graft copolymer. The copolymer's chemical structure was characterized by proton nuclear magnetic resonance spectroscopy and fourier transform infrared spectroscopy. The molecular weights of the copolymers were decided with gel permeation chromatography. The water solubility and temperature sensitivity of the copolymers were studied by taking digital photos and transmittance change measured by UV spectrophotometer at different temperatures. Fluorescence probes, surface tension, dynamic light scattering and transmission electron microscopy were used to analyze the micelles that copolymers self-assembly in aqueous solution. The sol-gel behavior of copolymer solutions at high concentrations was explored by vial inversion experiments. Finally, the network structure of the gels was observed by scanning electron microscopy. These conclusions indicate that these hydrogels are expected to be used as a new material in the field of biomedicine.

Glycerol is a subproduct of biodiesel production and represents an important problem when generated in large scale. Alternatives that can utilize this unrefined byproduct is of potential interest. It is herein described the synthesis of a series of 1,2,3-triazoles using glycerol as starting material. The key step involved in the preparation of triazolic derivatives corresponded to the Copper(I)-catalyzed Azide-Alkyne Cycloaddition (CuAAC), also known as click reaction, between 4-(azidomethyl)-2,2-dimethyl-1,3-dioxolane (3) and different terminal alkynes. The eight prepared derivatives were evaluated with regard to their fungicide, phytotoxic and cytotoxic activities. The fungicide activity was assessed in vitro against Colletotrichum gloeosporioides, the causing agent of papaya anthracnose. It was found that the compounds 1-(1-((2,2-dimethyl-1,3-dioxolan-4-yl)methyl)-1H-1,2,3-triazol-4-yl)cyclohexanol (4g) and 2-(1-((2,2-dimethyl-1,3-dioxolan-4-yl)methyl)-1H-1,2,3-triazol-4-yl)propan-2-ol (4h) demonstrated high efficiency on controlling C. gloeosporioides when compared to the commercial fungicide tebuconazole. The triazoles did not present any phytotoxic effect when evaluated against Lactuca sativa. However, five derivatives were mitodepressive, inducing cell death detected by the presence of condensed nuclei and acted as aneugenic agents in the cell cycle of L. sativa. It is believed that glycerol derivatives bearing 1,2,3-triazole functionalities may represent a scaffold to be explored toward the development of new agents to control C. gloeosporioides.

The main objective of this paper is to assess pro-environmental behavior, climate change perception, anxiety, hope and despair in different political orientations. Specific aims included to validate all the instruments; to assess whether the factor structure of the scales were valid across political orientations; to evaluate their reliability; to assess differences concerning age, gender and political orientation; to know the variables that explain pro-environment behavior; and to evaluate the moderating role of climate change perception, despair and hope in the relationship between climate change anxiety and pro-environmental behavior. Confirmatory factor analysis (CFAs), multi-group CFAs (to measurement invariance), multiple linear regressions and moderations were performed. Results showed that pro-environment behavior and climate change hope achieved the four levels of invariance across different political orientations; climate change anxiety achieved the three first levels of invariance; climate change perception and climate change despair achieved configural invariance. Climate change anxiety personal experience, climate change perception total, reality and consequences present higher values in left political orientation that in right or center. Climate change anxiety variables contribute most to explaining pro-environmental behaviors. Hope, despair and climate change perception consequences moderate de relationship between climate change anxiety and pro-environment behavior. These results open up new avenues of investigation, namely, to understand why high levels of anxiety lead to more pro-environment al behaviors.

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

Whereas many carbon cycle models track CO₂ perturbations relative to a pre-industrial equilibrium, this paper uses absolute quantities to describe atmospheric CO₂ sinks, source and flow rates. This method, when combined with the notion of source and sink resistance, and a finite biospheric reservoir, accurately describes ¹⁴C levels between 1820 and 2020 using only five external parameters. The inputs are:- global records of fossil-fuel emissions, records of CO₂ mixing-ratio and listings of atmospheric atomic weapons tests. Over the same period ¹³C flows are also accurately described given a ð¹³C value for fossil fuel and a ð¹³C value for the initial background. This top-down approach differs from complex climate models since it circumvents the necessity to catalogue individual processes. The paper proceeds to use the method to examine the anthropogenic fossil-fuel emissions contributions during the period 1750 to 2020, deducing that around 24% remains in the atmosphere, while 76% has been absorbed in the land, terrestrial biosphere and surface ocean. During the same period 13% of the total CO₂ atmospheric concentration is due to fossil fuels. However, regarding the increase, fossil fuels contributed to 38% of the rise during this period.

Climate change poses a significant threat to global food security, necessitating a thorough examination across multiple dimensions. Establishing appropriate food security evaluation indicators that align with the evolving concept of food security is imperative. This study enhances food security evaluation by refining a multi-dimensional framework and analyzing the impact of climate change across various regions from 2002 to 2021. By constructing an Food Security Index system composed of a three-tier indicator system and employing the entropy method for weighting, we assess the impacts of climate change on food security using a climate-economic model. Regression analysis reveals a negative linear relationship between mean temperatures and food security (p&lt;0.01), while precipitation impacts food security non-linearly, particularly exhibiting inverse U-shaped patterns in major grain-producing and grain-consuming areas. Extreme high temperatures consistently reduce food security, whereas extreme precipitation displays a complex, statistically significant inverse U-shaped association. In regions where production and consumption are balanced, mean temperatures have a negative effect on food security, while precipitation exhibits a positive correlation, but excessive precipitation can have adverse effects. These findings highlight the intricate interplay between climate change, regional disparities, and food security in China, emphasizing the need to consider multi-dimensional factors and regional variations in addressing food security challenges. These insights are invaluable for policy-making and planning aimed at enhancing food security in China.

Abstract: Climate change is one of the main barriers for agricultural production and productivity globally. Hence, understanding farmers’ adoption level of CSA practices and determinants is of highly important for policy decisions. Consequently, the study's purpose was to assess adoption level of multiple CSA practices and determinants of climate-smart agriculture practices in the study area. The study was conducted in Welmera Woreda, Oromia Region, Ethiopia. From the Woreda, three kebeles were identified, and 306 respondent farmers were selected. A cross-sectional household survey, focus group discussion, and key informant interviews were used. Multivariate probit model was used to examine adoption determinants of multiple climate-smart agriculture practices. According to the result, Conservation agriculture, integrated soil fertility management, and crop diversification are the most commonly practiced CSA techniques in the study area. Demographic factors result indicated that being male as compared with female farmers, has positive and significant effect on crop diversification and improved livestock feed and feeding practices. Age of farmers significantly and negatively affecting the probability of adoption of improved soil fertility management practices and crop diversification. However, it affects the adoption of agroforestry practices positively and significantly. Based on the result of economic factors, having relatively large farm land size significantly increases the adoption of conservation agriculture, improved soil fertility management, crop diversification, improved livestock feed and feeding practices, and postharvest technology practice. Better farm income increases the likelihood of uptake of improved livestock feed and feeding. Having a large number of livestock positively influences adoption of conservation agriculture and having access to credit services positively influences the implementation of agroforestry, crop diversification, and postharvest technology. In addition, institutional factors such as access to agricultural extension service and training found that significantly and positively influences the adoption of crop diversification; access to participation on farmers’ field day similarly significantly and positively influence the adoption of both conservation agriculture and improved soil fertility management practice. Awareness creation for farmers and experts about climate change and including location specific CSA practices in to agricultural program is crucial.

In the recent century, the tourism industry and within it the tourism economy are one of the most important and fundamental sectors of engaged business. E-tourism can be used as a dynamic tool in up to date areas of informative information and tourism marketing will be considered as a suitable field for the tourism industry. The aim of this study was to investigate the relationship between climate change and the amount of revenues from the tourism industry relying on a tool called e-tourism, and informing and providing services through this way so that Iran can achieve a greater share of export of a single-product oil economy combined with economic growth and sustainable development goals. The method of this research is descriptive-analytical.

This study assessed the impact of climate change on water availability and variability in two subbasins in the Upper Blue Nile Basin of Ethiopia. Downscaled future climate data from HadCM3 of A2 (medium-high) and B2 (medium-low) emission scenarios were compared to the observed climate data for a baseline period (1961 to 1990). The emission scenario representing the baseline period was used to predict future climate and as input to a hydrologic model to estimate the impact of future climate on the streamflow at three future time horizons 2020 - 2045, 2045 - 2070 and 2070 - 2100. Results suggest that medium-high emission scenario best represents the local rainfall and temperature pattern. With A2 scenario, daily maximum/minimum temperature will increase throughout the future time horizons. The minimum and maximum temperature will increase by 3.6^oC and 2.4^oC, respectively, towards the end of the 21st century. Consequently, potential evapotranspiration is expected to increase by 7.8%, though trends in annual rainfall do not show statistically meaningful trends between years. A notable seasonality was found in the rainfall pattern such that dry season rainfall amounts are likely to increase and wet season rainfall to decrease. The hydrological model indicated that the local hydrology of the study watersheds will be significantly influenced by climate change. Overall, at the end of the century, streamflow will increase in both rivers by up to 64% in dry seasons and decrease by 19% in wet seasons.

The government of Nepal (GoN) has developed and implemented climate policies, plans and frameworks such as NAPA, National Climate Change Policy, LAPA and currently in the process of developing National Adaptation Plans (NAPs). These policies and plans are in different states of its implementation with diverse opinions and perceptions of the stakeholders. The paper has explored these opinions and experiences of climate experts in Nepal on state of climate policies, inter-linkages, roles and responsibilities of ministries/departments, important factors and subjective indicators for effective implementation of the policies. Altogether 30 experts responded the questionnaire sent via the email, LinkedIn and Skype Interview in the 1^st phase of Delphi research technique. The experiences of these experts range from 2-30 years representing government, non-government sectors, media and independent experts. As per most of the experts interviewed, the policies and plans are progressing in strategic direction with national and local priorities. The LAPA is the pioneer framework to address the local climatic issues, originated in Nepal. However, lack of clarity on roles/responsibilities and coordination among the ministries/departments; clear mechanisms for implementation of these policies; lack of sensitization, decentralization and delegation of finance and technologies; capacity of the stakeholders are the major challenges identified.

This article presents and discusses analytical data on the scientific publication record from 1910 to 2020 on two topics: "climate" and "climate change/global warming/climate emergency". The goal is to visualize how the publication record on these two topics has evolved over time, from different classification perspectives (year, country, source and organization). Three hypotheses are tested using data collected from Web of Science and various graphical representations of the data. It is found that research output related to the Earth’s contemporary changing climate overtook that of general climate research in 2011, and the publication ratio has been expanding in the last decade. There are significant differences in the publication countries and sources between the two topics, and conversely less significant differences in terms of organizations publishing these works. Differentiation factors that affect the level of research output and engagement on the climate challenge include: island versus landlocked nations, specialized versus general scientific journals, academic versus institutional organizations. The future of the publication records is discussed, such as the emergence of new terms to refer to the climate challenge, such as “climate emergency”.

The German Constitutional Court’s climate verdict provides a re-interpretation of liberal- democratic core concepts and is highly relevant for liberal constitutional law in general – including EU and international law. The verdict accepts human rights as intertemporal and globally applicable; it applies the precautionary principle to these rights and frees them from the misleading causality debate. However, the court fails to address the most important violations of human rights, and it categorised climate policy as a greater threat to freedom than climate change. And the court does not make it clear that the Paris 1.5-degree limit implies a radically smaller carbon budget. Furthermore, little attention has so far been paid to the fact that the ruling implies an obligation for more EU climate protection, especially since most emissions are regulated supranationally. To be effective, the EU emissions trading system demands a reform, which should go well beyond the existing EU proposals to enable societal transformation to sustainability.

Why did inanimate materials evolve into complex organisms and societies on Earth? This is a fundamental scientific question that has captivated humans for millennia. Here we propose the Carbon-Based Evolutionary Theory (CBET) to provide novel, direct, and explicit answers to this question. The CBET identifies three key mechanisms based on some principles of physics and chemistry (e.g., laws of thermodynamics) and some features of Earth and carbon-based entities (CBEs): the driving force mechanism that provides energy, the structural mechanism that generates new functions, and the natural selection mechanism that accumulates orderliness, all for the evolution of CBEs. These mechanisms lead to the progression from chemical to biological and social evolution, marked by the escalating hierarchy of CBEs and the increase in the quantity, diversity, and orderliness of high-hierarchy CBEs. The CBET clarifies the natural roots of multiple pivotal and seemingly paradoxical social management notions, such as inclusiveness and competition, altruism and selfishness, freedom and restriction, as well as inherited advantages and acquired strengths. It advocates for the balanced, harmonious, and peaceful development of human society as well as the integration of all countries into a single harmonious social collective. The CBET unifies biology with physics and chemistry and could be a basic theory shared by the natural sciences and the social sciences. It could also be significant in the rational development of human society.

Gestational diabetes mellitus (GDM) is a hyperglycemia state that is typically diagnosed by an oral glucose tolerance test (OGTT), which is unpleasant, time-consuming, poorly reproducible, and tardy. The machine learning (ML) predictive models that have been proposed to improve GDM diagnosis are usually based on instrumental methods that take hours to get a result. Near-infrared (NIR) spectroscopy, a simple, fast and low-cost analytical technique has never been assessed for the prediction of GDM. This study aims to develop ML predictive models for GDM based on NIR spectroscopy, and to evaluate their potential as early detection or alternative screening tools according to their predictive power and time of analysis. Serum samples from the first (before GDM diagnosis) and the second (at the time of GDM diagnosis) trimester of pregnancy were analyzed by NIR spectroscopy. Four spectral ranges were considered, and 80 pretreatments were tested for each. NIR data-based models were built with single- and multi-block ML techniques. Every model was subjected to double cross-validation. The best first and second trimester models got areas under the receiver operating characteristic curve of 0.5768 ± 0.0635 and 0.8836 ± 0.0259, respectively. This is the first study reporting NIR spectroscopy-based methods for the prediction of GDM. The developed methods allow to predict GDM from 10 µL of serum in only 32 minutes. They are simple and fast, and have a great potential to be applied in clinical practice, especially as alternative screening tools to the OGTT at the time of GDM diagnosis.

Generative artificial intelligence tools are flourishing across various sciences, particularly in the educational domain. ChatGPT, with its versions 3.5 and 4.0, stands out for its multilingual capabilities, catering to both students and educators. This research aimed to evaluate the performance differences between these versions, and importantly, to compare the accuracy of ChatGPT's responses in English versus Arabic. In our study, we presented ChatGPT with 39 chemistry problems related to 6th-7th grade curriculum, including twenty-five open questions and fourteen multiple-choice questions. Each response was categorized as accurate, partially accurate, or inaccurate. Our analysis, focused on trends across versions and languages, revealed significant enhancements in version 4.0, particularly in its ability to process Arabic. However, despite these improvements, our findings indicate that responses in English consistently outperformed those in Arabic in terms of accuracy. In light of this discrepancy, we suggest that ChatGPT either incorporates additional Arabic databases into its training regimen or develops a code that adopts the following strategy to ensure more accurate responses in science education: questions should first be translated from Arabic to English, addressed, and then retranslated into Arabic before being presented to the user. This approach takes advantage of the greater accuracy of responses in English to benefit Arabic-speaking users, and it may also improve outcomes for speakers of other languages who experience less precise answers in the fields of chemistry or science education.

: Flotation performance in plants can significantly be affected by seasonal variations in different parts of the world. This is generally attributed to the changes in water temperature and pulp temperature in flotation plants, type and concentration of dissolved ions in process water. Extreme temperature conditions may be the major factor affecting flotation performance and mask the influence of water chemistry. Therefore, the interactive effects of the temperature and water chemistry should be taken into consideration, particularly for mine sites experiencing extreme temperature conditions. In this paper, effects of temperature, sulphate (SO42-), thiosulphate (S2O32-) and calcium (Ca2+) ions on the flotation performance of a Cu-Pb-Zn complex sulfide ore were investigated using a statistical experimental design and modelling approach. Batch scale kinetic flotation tests were conducted using the sequential flotation flowsheet of a bulk Cu-Pb flotation stage followed by a zinc rougher flotation stage. The results of the zinc flotation section were used for the statistical evaluation since the zinc concentrate was the product with an economic value for the mine. The results were evaluated using ANOVA analysis and regression analysis to determine the significant parameters and derive individual regression models for each flotation response with Design Expert software version 6.0.8. Individual regression models were developed using the significant main effects and their interactions for each flotation response. Then, the models were used to determine the concentration of the dissolved ions and pulp temperature required to achieve the maximum zinc recovery, maximum zinc grade or the optimum zinc grade and recovery. The details of statistical experimental design, discussions on the effects of the experimental factors and their interactions on the flotation performance and development of regression models are discussed in this paper.

The study of phytotherapy in dentistry is relevant due to the low occurrence of research in the treatment of oral pathologies, such as caries and periodontal disease. Thus, the aim of this research was to characterize the chemical composition of extracts from the leaves of Couroupita guianensis Aubl, including toxicological evaluation and the antioxidant and antimicrobial potential against Staphylococcus aureus, Streptococcus mutans and Candida albicans. Three extracts were prepared using assisted ultrasound, originating the Crude Ultrasound Extract (CUE) and Soxhlet apparatus, originating the Crude Soxhlet Extract (CSE) and the Ethanol Soxhlet Extract (ESE). In the analysis of the chemical composition, the presence of flavonoids, tannins and saponins were detected. LC-DAD analysis revealed the presence of caffeic acid, sinapic acid, rutin, quercetin, luteolin, kaempferol and apigenin in all extracts. In the GC-MS analysis, stigmasterol and β-sitosterol were identified in CUE and CSE. The antioxidant potentials, determined by the DPPH• and ABTS•+ methods, the ESE showed higher antioxidant activity (2.98 ± 0.96 and 4.93 ± 0.90, respectively). In the evaluation of toxicity, the CUE 50µg/mL and the ESE 50 µg/mL presented growth stimulation of Allium cepa roots. At a concentration of 750µg/mL, all extracts inhibited root growth. None of the extracts showed toxicity against Artemia salina. Antibacterial action was detected in all extracts, mainly against the microorganisms S. aureus and S. mutans; however, the antifungal action against C. albicans was not detected. From the results, the extracts of C. guianensis have therapeutic potential for use in the control of microorganisms in the oral microbiota.

Latterly, the development of green synthesized polymeric nanoparticles with anticancer studies has been an emerging field in academia, and in the pharmaceutical and chemical industry. Vegetable oils are potential substitutes for petroleum derivatives, as they present themselves as a clean and environmentally friendly alternative and are available in high quantities at relatively low prices. Biomass-derived chemicals can be converted into monomers with unique structures, generating materials with new properties for the synthesis of sustainable monomers and polymers. In this way, the production of bio-based polymeric nanoparticles appears as a great application of green chemistry for biomedical uses. There is an increasing demand for biocompatible and biodegradable materials for specific applications in biomedical as cancer therapy, encouraging scientists in working on research towards designing polymers, with enhanced properties and clean processes, containing oncology active pharmaceutical ingredients (APIs). The nanoencapsulation of these APIs in bio-based polymeric nanoparticles can control the release of the substances, increase bioavailability, reduce problems with volatility and degradation, reduce side effects, and increase treatment efficiency. Thus, this review aims to discuss the use of green chemistry for bio-based nanoparticle production and its application in anticancer medicine. The use of vegetable oils for the production of renewable monomers and polymers will be discussed, bringing castor oil as an ideal candidate for such application, as well as more suitable methods for the production of bio-based nanoparticles and some oncology APIs available for anticancer application.

Activated Corrosion Products (ACPs) formation and deposition pose a critical safety issue for nuclear fusion reactors. The working fluid transports the ACPs towards regions accessible to worker personnel. Predicting ACPs formation deposition and transport is fundamental for source term identification, reduction of radiation exposure assessment, maintenance plan definition, design optimization, and waste management. The code OSCAR-Fusion has been developed by the CEA (France) to evaluate the ACPs generation and transport in closed water-cooled loops for fusion application. This work aims at assessing the impact of water chemistry on the transport, precipitation, and deposition of corrosion products for the EU-DEMO divertor Plasma Facing Unit Primary Heat Transfer System. Sensitivity analyses and uncertainty quantification are needed due to the multi-physics phenomena involved in ACPs formation and transport. The OSCAR-Fusion/RAVEN code coupling developed by the Sapienza University of Rome and ENEA has been used. This work presents the perturbation results of different parameters chosen for a closed water-cooled loop considering a continuous scenario of 1888 days. The aim of this work is to assess the variation of build-up of ACPs, perturbing the alkalizing agent concentration into the coolant and the corrosion and release rates of different materials.

I describe the non-equilibrium thermodynamics and the photochemical mechanisms which may have been involved in the dissipative synthesis, proliferation, and evolution of the fundamental molecules at the origin of life from simpler and more common precursor molecules such as HCN, H2O and CO2 under the impressed UVC photon flux of the Archean. The fundamental molecules absorb strongly in this UVC region and exhibit strong coupling between their electronic excited and ground states which endows them with efficient photon disipative capacity (broad wavelength absorption and rapid radiationless dexcitation) suggestive of dissipative structuring. The autocatalytic nature of the synthesized molecules in dissipating the same photochemical potential that directed their synthesis leads to their proliferation. The non-linearity in the photochemical and chemical reaction rates provides numerous stationary states which can be reached by amplification of a molecular concentration fluctuation near a bifurcation, promoting the system into states of generally higher photon disspative efficacy. An example is given of the UV photochemical dissipative structuring, proliferation, and evolution of molecules on route to the nucleobase adenine from the common precursor molecules HCN and H2O occurring within a fatty acid vesicle. The kinetic equations are resolved under different environmental conditions, providing a non-equilibrium thermodynamic analysis of the appearance of an early important molecule for the origin of life.

Intensive application of synthetic pesticides was the routine practice of commercial agriculture during the Green Revolution to boost agricultural productivity to meet global food demand. Alongside this, the application of chemical pesticides caused adverse effects on the environment and its ecoreceptors including human health. Negative externalities arising from conventional farming instigated the call for sustainable development during the sixties to promote and balance the nexus between socially acceptable economic growth and environmental protection. Consequently, a blueprint of 17 Sustainable Development Goals (SDGs) and 169 targets including ecological stewardship and food security was drafted. Eight out of the 17 SDGs are directly linked to sustainable agriculture based on the direct impact of agriculture, judicious use of critical resources and conservation and the Principles of green chemistry. As a green chemical agent, biopesticides have been shown to have the potentials to substitute chemical pesticides with equal agricultural productivity. The adoption of bio-based pesticides via integrated pest management (IPM) has proven to be the most effective option to influence most dimensions of sustainable agriculture. Therefore, biopesticide-driven IPM if utilized with requisite education, skills and research would boost sustainable agriculture. This chapter reviews the prospects, importance, and limitations of biopesticides to sustainable agriculture and how sustainable agriculture is connected to sustainable development, Green Chemistry, and integrated pest management.