This study challenges the prevailing belief in the necessity of complex models for accurate forecasting by demonstrating the effectiveness of parsimonious econometric models, namely ARCH(1) and GARCH(1,1), over deep learning robust approaches, such as LSTM and 1D-CNN neural networks, in modeling historical volatility within pre-emerging stock markets, specifically the Moroccan and Bahraini stock markets. The findings suggest reevaluating the balance between model complexity and predictive accuracy. Future research directions include investigating the potential existence of threshold effects in market capitalization for optimal model performance. This research contributes to a deeper understanding of volatility dynamics and enhances forecasting models’ effectiveness in diverse market conditions.

This paper provides an overview of the current state-of-the-art digital twin and digital thread technology in industrial operations. Both are transformational technologies that have the advantage of improving the efficiency of current design and manufacturing. Digital twin is an important element of the Industry 4.0 digitalization process; however, the huge amount of data that are generated and collected by digital twin offer challenges in handling, processing and storage. The paper aims to report on the development of a new framework that combines the digital twin and digital thread for better data management in order to drive innovation, improve the production process and performance, and to ensure continuity and traceability of information. The digital twin/thread framework incorporated behavior simulation and physical control components, in which these two components rely on the connectivity between the twin and thread for information flow and exchange to drive innovation. The twin/thread framework encompasses specifications that include organizational architecture layout, security, user access, cloud computing set-up, and hardware and software requirements. It is envisaged that the framework will be applicable to enhancing optimization of operational processes and traceability of information in the physical world, especially in Industry Shipyard 4.0.

Pseudomonas aeruginosa is an opportunistic Gram-negative bacterium that remains a prevalent clinical and environmental challenge. Quorum sensing (QS) molecules are effective biomarkers in pinpointing the presence of P. aeruginosa. This study aimed to develop a convenient-to-use whole-cell biosensor using P. aeruginosa reporters individually encapsulated within alginate-poly-L-lysine (alginate-PLL) microbeads to specifically detect the presence of bacterial autoinducers. The PLL-reinforced microbeads were prepared using a two-step method involving ionic crosslinking and subsequent coating with thin layers of PLL. The alginate-PLL beads showed good stability in the presence of a known cation scavenger (sodium citrate), which typically limits the widespread applications of calcium alginate. In media containing synthetic autoinducers, such as N-(3-oxo dodecanoyl) homoserine lactone (3-oxo-C12-HSL) and N-butanoyl-L-homoserine lactone (C4-HSL) or cell-free supernatants of planktonic or flow cell biofilm effluent of wild P. aeruginosa (PAO1), the encapsulated bacteria enabled a dose-dependent detection of the presence of these QS molecules. The prepared bioreporter beads remained stable during prolonged storage at 4 and -80 °C and were ready for on-the-spot sensing without the need for recovery. This whole-cell biosensor demonstrates the practicality of the encapsulated bioreporter for bacterial detection based on specific QS molecules.

The aim of this research work is to study the influence of temperature, solar irradiation and wind dust on the production of solar energy. In addition, it aims to study the assessment of water quality, in particular groundwater used for cooling and cleaning photovoltaic panels (quality analysis). it's an important source, stable and sustainable can be used entirely for cooling and cleaning PV modules from the sales dust, in order to improve their performance. To date, all research studies carried out in this context of cooling and cleaning using water have not taken account of the nature of this water. We have taken a sample of water from a well in a rural area in the Darra Tafilalet region of Morocco. This region has an arid and semi-arid climate, with very high temperatures and dust-laden winds, particularly in summer. These meteorological characteristics influence the efficiency of cells, particularly photovoltaic (PV) panels, reducing their performance. Next, the water sample was analysed in the laboratory. The results obtained show that the groundwater in this area is very sensitive to cooling and cleaning photovoltaic panels. Moreover, these results indicate that the temperature, solar irradiation and wind-blown dust have a significant influence on energy production.

The transition to sustainable energy systems in the Middle East and North Africa (MENA) region addresses critical challenges of environmental protection, energy security, and socio-economic resilience. Using neo-institutional theory, this paper examines the intricate relationship between formal and informal institutions and their significant impact on the region’s energy transition. Despite the MENA region’s abundant renewable energy resources, numerous institutional barriers, such as governance inefficiencies, regulatory inconsistencies, and entrenched socio-cultural norms, significantly hinder this transition. Through a review of existing literature, this study presents a comprehensive analytical framework designed to overcome these barriers, with a focus on the Just and Sustainable Energy Transition model. This strategic model emphasizes equity, sustainability, and inclusive governance as pillars for reform. The study offers detailed recommendations for institutional change and underscores the importance of collaborative efforts among governments, industry stakeholders, and international partners to unlock the MENA region’s renewable energy potential, advance global sustainability goals, and ensure a more secure and resilient energy future.

Aluminum wire is a common material for wire bonding due to its resistance to oxidation and low price. It does not melt when becoming a free air ball (FAB) during the electronic flame-off (EFO) process with wettability, and is applied by wedge bonding. This study used 20μm Zn-Coated Al-0.5wt.%Si (ZAS) wires to improve the FAB shape after the EFO process, while maintaining stability of the mechanical properties, including the interface bonding strength and hardness. In order to test circuit stability after ball bonding, the current-tensile test was performed. During the experiment, it was found that 80nm ZAS with wire bonding has lower resistance and higher fusing current. For the bias tensile test, the thicker Zn film diffused into the Al-Si matrix easily, after which the strength was reduced. The ball-bond interfaces had no change in their condition before and after the bias. Accordingly, ZAS could be a promising candidate for ball bonding in the future.

The main purpose of our research is the evaluation of the efficacity of solvent polarity on phenolic composition, as well as the antibacterial, and antioxidant activities of extract of Moroccan Mentha aquatica L., leaves. To attempt these objectives, the HPLC-DAD was used to identify the biomolecules. The total amount of phenolic and flavonoid content was determined using the Folin-Ciocalteu and aluminum trichloride processes as well as the DPPH, RP, and TAC tests were used to evaluate the antioxidant capabilities. In addition, by employing both in vitro and in silico analysis through the microdilution method, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of the extracts were assessed against multidrug-resistant bacteria. Furthermore, the High-Performance Liquid Chromatography (HPLC) analysis indicated that all extracts of M. aquatica were abundant in noteworthy phytochemical compounds, especially gallic acid, vanillic acid, chlorobenzoic acid, quercetin, and kaempferol. Furthermore, the results indicated that the total phenolic content was higher in hydroethanolic extract (62.19 ± 1.19 mg GAE/g DW) in contrast to the acetonic and aqueous extracts (22.22 ± 0.64, and 22.44± 0.57 mg GAE/g DW) respectively. Similarly, the aqueous ethanol extract contained the greatest flavonoid concentration, with values of 29.15± 0.09 mg QE/g DW when compared with the other extracts. The seam extract poses excellent antioxidant power with an IC50 of 0.06 ± 0.00 mg/mL for the DPPH test, and lower RP with EC50 of 80± 0.00 µg/ml when compared with acetonic and aqueous extract (370± 0.00 and 460± 0.01 µg/mL) respectively. Moreover, the hydroethanolic extract has a high level of TAC 75.09± 2.00 mg EAA/g DW, followed by aqueous extract carrying a value of 28.53 ± 1.36 mg EAA/g DW. The antibacterial capacity is ranged between 0.78 ± 0.05 mg/mL and 12.60 ± 0.00 mg/L. The results of the in-silico study demonstrated that quercetin, vanillic acid, and naringenin components contribute to the antioxidant capability. While gallic acid, kaempferol, and quercetin components are attributed to the antibacterial capacity.

There is a need for strategic healthcare workforce planning to address shortages and ensure universal health coverage, aiming to optimize work-force per population ratio, distribution, and competencies. Amidst rising demands exacerbated by aging populations and events like the COVID-19 pandemic, strategic workforce planning becomes crucial for addressing healthcare inequalities by forecasting needs, bridging skill gaps, and adapting to changing demographics and care models. Israel has invested in strategic planning to tackle healthcare workforce challenges; however, globally there is insufficient planning informed by health labor market analysis, which hinders efforts to address healthcare inequalities. The paper reviews national policies in Israel, Australia, Germany, and Norway, ex-amining statistics and government publications to highlight strategic plan-ning considerations and address challenges in healthcare workforce plan-ning. This paper focuses both on the critical role of physicians in healthcare systems, and on the changing borders between healthcare professions and different national contexts which demand more context dependent strategic workforce planning. We highlight common themes among national policies, including the need for data collection, increasing the capacity of domestic training programs, and the need to address geographic maldistribution of physicians. Ultimately, we aim to guide policy in the development of a re-silient and sustainable healthcare workforce capable of meeting diverse community needs and promoting equity in healthcare services.

In order to make full use of the complementarity of existing navigation systems to improve the navigation and positioning accuracy, this paper investigates the visual/INS integrated navigation system based on the factor graph optimization (FGO) algorithm. In the traditional visual/INS integrated navigation system, there is often the problem of image blurring due to the rapid change of light and shadow captured by the vision sensor and the attitude change of the carrier, which leads to the decrease of the positioning accuracy of the combined navigation system. Therefore, this paper firstly introduces Retinex algorithm and BID algorithm to carry out the design of image de-blurring method; then implements the visual/INS integrated navigation algorithm based on the factor graph optimization method; finally, the experimental scheme is designed, comparative experiments are carried out, and the researched method is verified by using the public dataset. The experimental results show that the combined navigation algorithm realized in this paper has high accuracy, and its positioning accuracy is improved by 40% compared with visual positioning.

Taiwan developing offshore wind power to promote green energy and self-electricity production. In this study, a Light Detection and Ranging (Lidar) was set up at Chang-Hua development zone one on the sea and 10km away from the seashore. At Lidar location, WRF (3.33km & 2km grid lengths) model and WAsP were used to simulate the wind speed at various elevations. Three days mean wind speed of simulated results were compared with Lidar data. From the four wind data sets, developed five different comparisons to find an error% and R-Squared values. Comparison between WAsP and Floating Lidar was shown good consistency. Lukang meteorological station 10 years wind observations at 5m height were used for wind farm energy predictions. The yearly variation of energy predictions of traditional and TGC wind farm layouts are compared under purely neutral and stable condition. The one-year cycle average surface heat flux over the Taiwan Strait is negative (-72.5 (W/m2) and 157.13 STD), which represents stable condition. At stable condition TGC (92.39%) and 600(92.44%), wind farms were shown higher efficiency. The Fuhai met mast wind data was used to estimate roughness length and power law exponent. The average roughness lengths are very small and unstable atmosphere.

Deep Learning (DL) oriented document processing is widely used in different fields for extraction, recognition, and classification processes from raw corpora of data. The article examines the application of deep learning approaches, based on different neural network methods, including Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), and Convolutional Neural Networks (CNN). The compared models were combined with two different word embedding techniques, namely: Bidirectional Encoder Representations from Transformers BERT and Gensim Word2Vec. The models are designed to evaluate the performance of architectures based on neural network techniques for the classification of CVs of Moroccan engineering students at ENSAK(National School of Applied Sciences of Kenitra, Ibn Tofail University). The used dataset included resumes collected from engineering students at ENSAK in 2023 for a project on the employability of Moroccan engineers in which new approaches were applied, especially machine learning, deep learning, and big data. Accordingly, 867 resumes were collected from five specialties of study (Electrical Engineering, Networks and Systems Telecommunications, Computer Engineering, Automotive Mechatronics Engineering, Industrial Engineering). The results revealed good performance of the proposed models based on the BERT embedding approach compared to models based on the Gensim Word2Vec embedding approach. Accordingly, the CNN-GRU/Bert model achieved slightly better accuracy with 0.9251 compared to other hybrid models.

Analytical instruments used for scientific research and education are often expensive. This limitation poses a challenge for schools and educators in low-income countries to provide practical science training to students. To address this problem, the improvisation of analytical instruments and instructional materials has emerged as a viable solution. By incorporating practical experiments into science education, students have the opportunity to engage directly with scientific instruments, conduct investigations, and collect data. This hands-on approach fosters a deeper understanding of scientific principles, enhances critical thinking skills, and cultivates scientific mindsets among students. Herein, we review and discuss, step-by-step, the approach of using a smartphone for quantitative analysis, referred to as smartphone digital image colorimetry (SDIC). SDIC, with its practicality and accessibility, utilizes smartphone digital cameras for image acquisition and the freely available image processing programs, such as ImageJ and smartphone Apps, for image quantification. Using SDIC can enable students in low-income countries to develop essential scientific skills, including critical thinking, data interpretation, and an evidence-based approach to scientific research. By leveraging the ubiquity and affordability of smartphone technology, SDIC offers an accessible and cost-effective approach to practical science education, bridging the gap between theory and practice in resource-constrained settings.

Introduction the outbreak of the Israel-Gaza conflict, initiated by a major attack on the civilian population in Israel provided a tragic opportunity to study the community wide association between severe emotional stressors related to acts of war and the incidence and clinical characteristics of Takotsubo cardiomyopathy (TCM) in this scenario. Methods Eight consecutive cases of TCM diagnosed during the first 50 days of the Israel-Gaza conflict were retrospectively collected from two southern medical centers who provided care to most of the war victims throughout the period of monitoring. The medical records were thoroughly reviewed and analyzed. Results During the monitoring period, the incidence of TCM increased substantially compared to the control period. Eight patients were included in the analysis. All patients were female and 100% of patients presented within the first 3 weeks of conflict whereas after this initial phase, despite the continuing war, the incidence of TCM reverted to pre-conflict levels. Two patients (25%) were under 50 years of age. All patients had hazardous clinical characteristics including severe left ventricular (LV) dysfunction (≤35%) and prolonged QTc interval (>500 ms). Five patients (62.5%) experienced complications. Nevertheless, no in-hospital mortality was reported. Conclusions Repeated exposure to severe emotional stress, on both personal and national level, due to mass crisis such as war is associated with an increased incidence of TCM potentially with high-risk phenotype in comparison to TCM following other, less potent, psychological insults.

In the Lemongrass (Cymbopogon citratus), the investigations showed a wide range of active molecules their biological properties. However, most of these studies were conducted on the wid varieties, while cultivated plan addressed. This study aimed to characterize the biomolecules and biological activities of Lemongrass growing us African conditions sons in in Marocco. Marocco. Phenolic compound profiles of aqueous (AE) E) ethanol ethanol (EE), (EE), and methanol (ME) extract: fractions were obtained with steric exclusion chromatography on Sephadex 050 gel and identified by LC-MS/MS polyphenols (TPC), flavonoids (TFC), and antioxidant activities (FRAP: scavenging value and TAC: Total Antioxidant C the fraction were evaluated as well as the antimicrobial activity Obtained results showed that the ME contained e compounds (ie. Apigenine-7-0-rutinoside and myricitine-3-0-rutinoside). The AE showed the presence of five mole kaemiferol-3-0-glucuronide), while EE showed the presence of three molecules (Le. Quercetine-3-0-rutinoside). Reg chemical characterization, the rization, e highest value of Total phenolic content (TPC) was obtained in conten btained in AE ΑΕ (25) (4.60-0.29 mg highest value of Total flavonoids content (TFC) was obtained Ined in ME (29) (0.7±0.08 mg/g). Concerning the antioxide the highest FRAP was obtained in ME (29) (97.89%) and the highest total antioxidant capacity (TAC) was obtained (89.89%) Correlation between FRAP, TPC, and TFC was noted poly in fractions of AE and ME. All tested extracts of and their fractions showed a significant antimicrobial effect. The lowest minimum inhibitory concentration (MIC) wa for ME against E. col. Extracts biological activities and their fractions were governed by their active molecules. Ther new and clarify a novel aspect of bioactive molecules in the extracts of cultivated C. citratus Equaly, throughout this we clarified the relationship between identified molecules and their biological properties including antioxidant and comparative studies new activities, which is new for the study area. This study is suggested to be a reference. assays of other biological activities for the study plant

The classification of kidney tumors has undergone a remarkable evolution since the early 19th century, reflecting advances in medical science and technology. This historical overview traces the development of renal tumor classification, beginning with early clinical observations and macroscopic descriptions to the integration of molecular diagnostics in contemporary classifications. The establishment of international organizations like the World Health Organization (WHO) facilitated collaboration and standardization in tumor classification, leading to refined classifications and standardized nomenclature. Advancements in histological and molecular studies, particularly genetic analyses, revolutionized the understanding of renal cell carcinomas, enabling precise categorization based on molecular characteristics. The journey from rudimentary classifications to sophisticated systems based on detailed histological, immunohistochemical, and molecular criteria underscores the continuous evolution of kidney tumor classification. This article provides a comprehensive overview of this evolution, highlighting the contributions of scholars and the impact of technological advancements on our understanding and management of kidney tumors.

On 17 October 1947, Niels Bohr was made a knight of the Order of the Elephant by the King of Denmark in view of his outstanding achievements and contributions to science. Bohr designed his own coat of arms that featured a pattern of Yin and Yang (Tai Chi symbol) to symbolize the wave-particle complementarity. However, Bohr’s Yin-Yang diagram (YYD) was neither drawn based on the principles of quantum mechanics, nor did it originate from the traditional Taoist YYD. Scientists still have doubts about the legitimacy of using YYD as the icon of the wave-particle complementarity, because the YYD belonging to quantum mechanics itself is unknown so far. This article reports the YYDs existing in quantum mechanics and justifies the role of YYD in the wave-particle duality by showing that any system, whether classical or quantum, has an ideal YYD as long as it satisfies Bohr’s principle of complementarity (BPC). The deviation of a deformed YYD from the ideal YYD indicates the extent to which a real system satisfies BPC. This article constructs the quantum YYD by the complex quantum trajectory of a particle tunneling via a step barrier, which displays the continuous transition between the wave behavior and the particle behavior. It appears that the YYD designed by Bohr in his coat of arms resembles the YYD generated by tunneling motion, not only in appearance but also in the governing equation.

The black hole (BH) phenomenon is an intraluminal restenotic lesion. It was identified by intravascular ultrasound (IVUS) and optical coherence tomography (OCT) after intracoronary brachytherapy and drug-eluting stent implantation. Despite the similarity in the mode of action of brachytherapy and drug-eluting stent implantation, the BH phenomenon appears to be uncommon after drug-eluting stent implantation. Specifically, the BH phenomenon is better identified by OCT than by IVUS. Herein, we present a case of in-stent restenosis with suspected BH phenomenon on IVUS confirmed by OCT.

In Taiwan, mountainous areas account for approximately two-thirds of the total area. The steep terrain and concentrated rainfall during typhoons cause landslides, which pose a considerable threat to mountain settlements. Therefore, models for analyzing rainfall-induced landslide hazards are urgently required to ensure adequate land use in mountainous areas. In this study, focusing on Pingtung County in southern Taiwan, we developed a landslide hazard index (IRL) to land use. Using FORMOSA-2 and SPOT-5 satellite images, data were collected before and after four typhoons (one in 2009 and three in 2013). The ArcGIS random tree classifier was used for interpreting satellite images to explore surface changes and disasters, which were used to analyze slope disturbances. The product of the maximum 3-h rolling rainfall intensity and effective accumulated rainfall was used as a rainfall trigger index (IRT). Considering environmental and slope disturbance factors, an index of slope environmental strength potential (ISESP) was developed through logistic regression (LR). Landslide hazard to land use was estimated using IRT and ISESP. The average coefficient of agreement (Kappa) was approximately 0.71 (medium to high accuracy); the overall accuracy of slope environmental strength potential analysis was approximately 80.4%. At a constant ISESP, IRT increased with the increasing hazard potential of rainfall-induced landslides. Furthermore, IRT and ISESP were positively correlated with landslide occurrence. When large ISESP values occur (e.g., fragile environment and high land development intensity), small IRT values may induce landslides.

Marketing is the manner of how to make our sales the best in the market, our prices the most accessible, our clients satisfactory, and thus our brand is the largest distributed. This needs sophisticated and advanced understanding of the total network related. Indeed, marketing data may be seen in different forms such as qualitative and quantitative. However, in the literature, it is easily noticed that large bibliography may be collected about qualitative studies, against few studies on the quantitative point of view. This is a major drawback that makes the marketing science still focusing on the design, although the market is strongly depending on quantities such as money and time. Indeed, marketing data may be a time series such as brand sales per specified periods, brand related-prices over specified periods, market shares, ..., etc. The purpose of the present work is to investigate some marketing models based on time series due to brands. We will precisely study the effect of the time scale on the persistence of brands sales in the market and on the forecasting of such a persistence according to the characteristics of the brand and the related market competition or competitors. Our study is acted on a sample of Saudi brands during the period November 22, 2017 to December 30, 2021.

The Range–Doppler (R-D) model is extensively employed for the geometric processing of Synthetic Aperture Radar (SAR) images. Refining the sensor motion state and imaging parameters is the most common method for achieving high-precision geometric processing using the R-D model, comprising a process that involves numerous parameters and complex computations. In this study, we introduce a novel approach to improve the positioning accuracy of the R-D model, implementing a low-order polynomial to compensate for the original imaging errors without altering the initial positioning parameters. We also design low-order polynomial compensation models with different parameters. The models are evaluated on various SAR images from different platforms and bands, including spaceborne TerraSAR-X and GF3-C images, manned airborne SAR-X images, and unmanned aerial vehicle-mounted miniSAR-Ku images. Furthermore, image positioning experiments involving the use of different polynomial compensation models and various numbers and distributions of Ground Control Points (GCPs) are conducted. The experimental results demonstrate that geometric processing accuracy comparable to that of the classical rigorous positioning method can be achieved even when applying only an affine transformation model to the images. Compared to classical refinement models, however, the proposed image-compensated R-D model is much simpler and easy to implement. Thus, this study provides a convenient, robust, and widely applicable method for the geometric positioning processing of SAR images, offering a potential approach for the joint-positioning processing of multi-source SAR images.

In the present paper, we investigate the impact of the timescale factor on the quality of life index behavior on specific time intervals characterized by the presence of socio-economic, political, and/or health severe movements such as pandemics and crises. We essentially aim to show that effectively the quality of life measuring based on a single index in the existing studies may be described more adequately by a variable index due to the social, political, economic, and also healthy environment. The variability discovered is expressed by the existence and the estimation of a multi-index instead of a single one relatively to many factors. Our focus is mainly on the effect of the COVID-19 pandemic on the quality of life. Our model is applied empirically to a sample corresponding to Saudi Arabia as a case of study during the period from January 1990 to December 2021 as the main period affected by the COVID-19 pandemic. The sample is based on social media conversations and texts discussing and describing the satisfaction with the quality of life. The study confirms effectively that the role of the timescale factor is more described when considering a multi-index rather than measurement on the whole time interval.

Nanopeening treatment was applied to the AISI 420 steel to decrease its sensitivity to the tribocorrosion damage. Microstructural investigation highlighted that the Nanopeening treatment led to a high plastic deformation and nanostructured surface layer with 110 µm depth. . In order to study the combined effect of corrosion and mechanical wear, tribocorrosion tests were performed on non–treated and nanopeened samples in boric acid and lithium hydroxide solution, considering both continuous and intermittent sliding. It was found that the AISI 420 steel is sensitive the synergism between mechanical friction and electrochemical corrosion with a domination of abrasive wear. Adhesive wear was also detected in the wear track. Indeed, the mechanical wear was pronounced under intermittent sliding because of hard wear debris generation from the repassivated layer during rotating time. The Nanopeening treatment led to enhance mechanical performance and corrosion properties. Such improvement could be explained by the high plastic deformation resulting in the nano-structuration of grains and increasing hardness of AISI 420 steel.

Ni-Al alloys have good corrosion-resistant properties making them preferable as a material of choice compared to ordinary metals. A good understanding of the phase diagram and thermodynamic properties of the Ni-Al alloy binary system is essential in determining relevant industrial applications of the system. The Ni-Al phase diagram is being reassessed since those found in the literatures are based on very old experimental studies. The phase diagram and thermodynamic properties of the Ni-Al alloy is determined using the Thermo-Calc 2022b software over a temperature range of 200 K to 2000 K and 1 atm of pressure. A total of nineteen fields (including elemental Al and Ni) comprising of five single solid phases, one liquid phase, and twelve double regions was obtained from the equilibrium calculation. The thermodynamic calculation has six invariant reactions comprising of two eutectic reactions (914.83 ± 0.025 K and 1641.80 ± 0.025 K), three peritectic reactions (1123.55 ± 0.025 K, 1400.72 ± 0.025 K and 1642.65 ± 0.025 K), and one peritectoid reaction (913.96 ± 0.025 K). The solubility of Al in Ni is also determined. The Thermo-Calc temperature – composition of the Ni-Al alloy is compared with the existing experimental studies to identify the physical properties of the different thermodynamic properties of the Ni-Al alloy binary system.

water resources in Morocco have been severely influenced by climate change (CC) and pro-longed drought, particularly, in the pre-Saharan zone. The Tafilalet region faces increasing pres-sure due to high demographic growth, increased demand for water, excessive groundwater con-sumption, and investment in agriculture. Using the Water Evaluation and Planning System (WEAP), this study assessed land cover and elevation and created future scenarios using the Standard Precipitation Index (SPI) and Standard Groundwater Level Index (SGI) to monitor hy-droclimate drought conditions in the Ziz watershed from 1989 to 2022. Results show decreasing precipitation, particularly from 2010-2020, with the last four years being the most challenging (SPI<-2). SPI and SGI have a high correlation, suggesting precipitation impacts groundwater in-dicators. Future scenarios predict a high risk of CC, with a 30% decrease in annual precipitation accumulation by 2100 under the optimistic scenario SSP126. Minimum temperature is expected to increase by 1.08°C (SSP126) and 2.61°C (SSP585), and maximum temperature by 1.05°C (SSP126) and 2.93°C (SSP585). Keywords: Climate Change, Water Resources, SPI, SGI, WEAP, Ziz watershed, Drought

Three different fields intersect in search of an understanding of the point-of-origin of modern-age diseases: 1) D-amino acids and their role under stress conditions; 2) evolutionary origin of the mitochondrion organelle in the eukaryotic cell; and 3) gut microbiota and human healthHere it is first suggested that D-amino acids function as universal signaling agents, after having evolved as prokaryotic communication, part of an organic communication process that governs the basic activities of all the cells and coordinates cell action.Mitochondria (symbiotic prokaryotic organelles), are creative source of D-amino acids as signaling agents in the central nervous system and in the neuroendocrine systems.Amino acids racemases catalyzes the conversion between the L-enantiomers ( protein building blocks) into D-enantiomers (signaling agents).It is suggested that hectic modern life may affect human health by causing stress to the gut microbiota. These affected, gut microbiota then secrete D-amino acids that enter the blood stream, as signaling agents, causing communication errors in the central nervous system, and in the neuroendocrine systems due to excessive quantity of D-amino acids.Treating gut microbiota with inhibitors of amino acids racemases or finding D-amino acid scavengers may be used in developing novel therapeutic strategies for diseases related to the central nervous system and neuroendocrine systems caused by stressed gut microbiota.

There is a growing body of evidence supporting the significant role of bacterial biofilms in the pathogenesis of various human diseases including cancer. Biofilms are polymicrobial communities enclosed within an extracellular matrix composed of polysaccharides, proteins, extracellular DNA, and lipids. This complex matrix provides protection against antibiotics and host immune responses, enabling the microorganisms to establish persistent infections. Moreover, biofilms induce anti-inflammatory responses and metabolic changes in the host, further facilitating their survival. Many of these changes are comparable to those observed in cancer cells. This review will cover recent research on the role of bacterial biofilms in carcinogenesis, especially in colorectal (CRC) and gastric cancers, emphasizing the shared physical and chemical characteristics of biofilms and cancer. This review will also discuss the interactions between bacteria and the tumor microenvironment, which can facilitate oncogene expression and cancer progression. This information will provide insight into developing new therapies to identify and treat biofilm-associated cancers, such as utilizing bacteria as delivery vectors, using bacteria to upregulate immune function, or more selectively targeting biofilms and cancer for their shared traits.

Policing duties may inherently be dangerous due to stab, blunt trauma and ballistic threats. The addition of individual light armour vests (ILAVs) has been suggested as a means to protect officers. However, the addition of the extra load of the ILAV may affect officer ability to conduct occupational tasks. The purpose of this study was to determine if wearing any of 3 different ILAVs (ILAV A, ILAV B, & ILAV C) affected occupational task performance when compared to that in normal station wear. A prospective, within-subjects repeated measures design was employed, using a counterbalanced randomization in which each ILAV was worn for an entire day while officers completed a variety of occupationally relevant tasks. These tasks included a victim drag, car exit and 5 meter sprint, step down and marksmanship task. Results showed that performance in each task did not vary between any of the ILAV or normal station wear conditions. There was less variability in the marksmanship task with ILAV B, however. The results suggest that none of the ILAVs used in this study were heavy enough to significantly affect task performance in the assessed tasks when compared to wearing normal station wear.

Fractal analysis of time series aims to extract the hidden or complex structures issued from the associated real data, such as scaling laws, non-stationary, dynamics, and so on. In the present work, the air quality index and its components are considered as time series owing fractal structures. To understand their underlying dynamics, wavelet multifractal approach is applied starting with a wavelet multifractal spectrum test to confirm the multifractality of the underlying data. Next, a new model is introduced improving the classical minmax one, provided with a statistical measure for the adequacy of the new model. The theoretical findings are applied to the north west Tabuk region of Saudi Arabia for environmental and climate data related to pollutants and factors involved in the estimation of the air quality index.

E-commerce is a rapidly evolving global trend that is having a significant impact on consumer behavior and business strategies. Despite its growing impact, e-commerce adoption by Moroccan firms remains low and research on this topic in this context is scarce. This study aims to fill this gap by investigating the main determinants influencing e-commerce adoption by Moroccan firms. We use logit, probit, and conditional mixed process-probit models to identify the critical factors driving e-commerce adoption. Our results reveal five key findings. First, newer firms that are more open to innovation and change are more likely to adopt e-commerce. Second, firms with a higher proportion of highly educated employees are more likely to adopt e-commerce. Third, the digital skills of new employees do not directly influence the likelihood of e-commerce adoption. Fourth, being listed on digital platforms increases the likelihood of e-commerce adoption. Finally, there is a positive relationship between firms engaged in innovation activities and e-commerce adoption. These findings highlight the need for additional investment in promoting modern organizational practices, reskilling workers, and implementing advanced technologies to facilitate effective e-commerce integration among Moroccan SMEs. By addressing these challenges, Moroccan firms can harness the full potential of e-commerce and contribute to the country’s economic growth and digital transformation.

In response to growing industrial demands, necessitated by larger ships and increased cargo volumes, many port authorities worldwide are undertaking a significant expansion of their infrastructure to increase their capacity. Significant expansion raises challenges such as potential congestion and environmental concerns, especially for port located in urban area as the case study explored in this paper. To address these issues, the study employs a combination of scenario analysis developed in collaboration with the port authority and logistic system simulation. This approach assesses the capacity of existing access gates to handle the increased trucking traffic and optimizes the unloading process of construction trucks at a new terminal. Key findings suggest that while the current gate capacities are adequate, optimizing unloading times at the new terminal is critical to prevent road congestion in urban area before the gate and reduce negative impacts such as sound and atmospheric pollution. The study advocates for an appointment system during peak hours to manage traffic flow effectively and underscores the importance of collaboration between the city and port authorities in managing truck traffic to mitigate congestion on the city side. Nonetheless, the study recognizes certain constraints, including the incomplete evaluation of the influence of intermodal transport on truck traffic. Furthermore, the study emphasizes the need for future research to consider the correlation between vehicle numbers and service levels, aiming to effectively adjust the time in the system.

Dictionary Learning (DL) and Sparse Representation (SR) based Classifier have impacted greatly on the classification performance and has had good recognition rate on image data. In Video Semantic Analysis (VSA), the local structure of video data contains more vital discriminative information needed for classification. However, this has not been fully exploited by the current DL based approaches. Besides, similar coding findings are not being realized from video features with the same video category. Based on the issues stated afore, a novel learning algorithm, called Sparsity based Locality-Sensitive Discriminative Dictionary Learning(SLSDDL) for VSA is proposed in this paper. In the proposed algorithm, a discriminant loss function for the category based on sparse coding of the sparse coefficients is introduced into structure of Locality-Sensitive Dictionary Learning (LSDL) algorithm. Finally, the sparse coefficients for the testing video feature sample are solved by the optimized method of SLSDDL and the classification result for video semantic is obtained by minimizing the error between the original and reconstructed samples. The experiment results show that, the proposed SLSDDL significantly improves the performance of video semantic detection compared with the comparative state-of-the-art approaches. Moreover, the robustness to various diverse environments in video is also demonstrated, which proves the universality of the novel approach.

The fluorine-less noble-gas containing anions OBONgO- and OCNNgO-have been studied by correlated electronic structure calculation and density functional theory. The obtained energetics indicates that for Ng = Kr and Xe, these anions should be kinetically stable at low temperature. The molecular structures and electron density distribution suggests that these anions are stabilized by ion-induced dipole interactions with charges concentrated on the electronegative OBO and OCN groups. The current study shows that in additional to the fluoride ion, polyatomic groups with strong electronic affinities can also form stable noble-gas containing anions of the type X-...NgO.

In the realm of the Internet of Things (IoT), a network of sensors and actuators collaborates to fulfill specific tasks. As the demand for IoT networks continues to rise, it becomes crucial to ensure the stability of this technology and adapt it for further expansion. Through an analysis of related works including Feedback-based Optimized Fuzzy Scheduling Approach (FOFSA) algorithm, Adaptive Task Allocation Technique (ATAT) and Osmosis Load Balancing algorithm (OLB), we identify their limitations in achieving optimal energy efficiency and fast decision-making. To address these limitations, this research introduces a novel approach to enhance the processing time and energy efficiency of IoT networks. The proposed approach achieves this by efficiently allocating IoT data resources in the Mist layer during the early stages. We apply the approach to our proposed system known as the Mist-based Fuzzy Healthcare System (MFHS) that demonstrates promising potential to overcome the existing challenges and pave the way for efficient Industrial Internet of Healthcare Things (IIoHT) of the future.

For 80 years high-intensity focused ultrasound (HIFU) has been a significant area for medical research. It is a non-invasive procedure which causes cell death in a highly localised area at a defined distance from the transducer. Since 2000, the clinical indications have broadened considerable as the technology has improved. This review looks back at the history of HIFU and the current clinical indications.

Introduction: Treating elbow fracture-dislocation is a challenge, especially in the situation of basal-coronoid trans-ulnar fracture. The study ams to explain whether or not the minimal invasive surgery (MIS) would be feasible in elbow dislocation with coronoid fracture. Materials & Methods: At Taipei Veterans General Hospital, patients who had elbow dislocations with coronoid process fractures underwent single one surgeon’s MIS techniques which included the fluoroscopy-guided ulnar anteromedial (FGUAM) approach in the stage of reducing coronoid process. When there is a proximal ulnar fracture, the posterior incision should be necessary, followed by the incision over the lateral or medial elbow in treating radial fractures or ligament injuries. Results: The Flow Diagram about approach recommendation was established in base of defining MIS as not to do cross-plane dissection. Anteriorly rigid fixation for the coronoid process was also emphasized. Conclusions: MIS can be achieved by multiple limited surgical incisions. However, if there is an unstable ulnar metaphysis or ligament avulsion fracture, the posterior approach has to be extended and the so-called MIS fails to be established.

Contaminants of Emerging Concern (CECs), a new category of contaminants in limelight, is a major issue of global concern. The pervasive nature of CECs and its harmful effects, such as cancer, reproductive disorders, neurotoxicity etc., make the situation alarming. The perilous nature of CECs lies in the fact that even very small concentration of CECs can cause great impacts on living beings. It also has a nature of bioaccumulation. Thus, it is the ultimate need to have efficient sensors for detection of CECs to ensure safe living environment. Electrochemical sensors are an efficient platform for CEC detection as they are highly selective, sensitive, stable, reproducible, and prompt, and can detect very low concentrations of analyte. Major classes of CECs are pharmaceuticals, illicit drugs, personal care products, endocrine disruptors, newly registered pesticides, and disinfection by-products. This review focusses on CECs, including their sources and pathways, health effects caused by them, and electrochemical sensors as reported in literatures under each category for the detection of major CECs.

3D printing is commonly used to create complex objects at a low cost. It has also been applied in the fabrication of metamaterials and metasurfaces, which alter the propagation path of electromagnetic waves. These structures have diverse applications, including enhancing beam direction, improving antenna gain and signal-to-noise ratio, and creating filters and reflectors. Metasurfaces are cheap to fabricate and their use is expected to boost antenna efficiency in 5G telecommunications and beyond. However, accurately characterizing their profile remains a significant challenge. This paper presents a low-cost fully automated 4-axis instrument for microwave metasurface charac-terization, overcoming limitations of manual methods and offering an efficient and accurate approach. This research represents a significant advancement in microwave metasurface characterization, enabling sophisticated techniques to advance wireless communication technolo-gies, as it is the case of the future 5G and millimeter-wave communication systems. The equipment has an approximate cost of $1550 USD and was able to characterize a metalens with a focal distance of 20 cm designed for signals at 30 GHz. It was possible to create 2D and 3D profiles of the intensity distribution focused by the metalens and extract parameters such as the gain (8.05 dB), 3dB depth of focus (11 cm) and full width at half maximum (2.17 cm). The comparison of the measurements with the diffraction calculations of the metalens showed a very good agreement between the in-tensity distributions and the parameters of the metalens.

Scaffoldings play a critical role as temporary structures in supporting construction processes. Accidents at construction sites frequently stem from issues related to scaffoldings, including insufficient support caused by deviations from the construction design, insecure rod connections, or absence of cross bracing, which result in uneven loading and potential collapse, leading to casualties. In this study, we introduce a deep-learning-based, augmented reality (AR)-enabled system called scaffolding assembly deficiency detection system (SADDS) to assist field inspectors in identifying deficiencies in scaffolding assemblies. Inspectors have the flexibility to utilize SADDS through various devices, such as video cameras, mobile phones, or AR goggles (i.e., Microsoft HoloLens 2), for automated detection of deficiencies in scaffolding assemblies. The training test yielded satisfactory results, with a mean average precision of 0.89 and individual precision values of 0.96, 0.82, 0.90, and 0.89 for “qualified” frames and frames with the “missing cross-tie rod,” “missing lower-tie rod,” and “missing footboard” deficiencies, respectively. Field tests conducted at two construction sites demonstrated improved system performance compared to that in the training test. However, these field tests also revealed certain limitations of the SADDS system.

GaN ultraviolet photodetector with metal-semiconductor-metal structure is achieved by growing on a periodic trapezoid column-shape patterned sapphire substrate using metalorganic chemical vapor deposition. Under 5-V reverse bias, the photodetector fabricated on such patterned sapphire substrate exhibits a lower dark current, a higher photocurrent, and a 476 % enhancement in the maximum responsivity as compare with those of the photodetector fabricated on conventional flat sapphire substrate. It is also found that the much larger UV-to-visible rejection ratio and the fact that responsivity drops in a smaller cut-off region are observed from photodetector fabricated by using a periodic trapezoid column-shape patterned sapphire substrate. These phenomena may all be attributed to the reduction of threading dislocation density and the improved quality of GaN film, as well as the internal reflection and/or scattering effect on the interface between GaN film and the periodic trapezoid column-shape pattern of the substrate.

Applied talent is not only a builder of human civilization but also a promoter of economic development. They not only need systematic and solid engineering theoretical knowledge but also rich engineering practical experience. Applied undergraduate colleges are the cradle for cultivating applied talent and shoulder the important mission of cultivating various types of applied talent for society. With the rapid development of higher education, the number of applied undergraduate institutions has sharply increased, but the quality of applied talent cultivated by them has shown a significant decline, which greatly restricts the pace of industrial development in the world. This article proposes a new concept of promoting the "three certificates" (graduation certificate, degree certificate, and skill certificate) education model in applied undergraduate colleges, which is of great significance for the country to cultivate composite talents with the ability of "product design, production management, and product processing" at the same time.

Multilayered metallic sheets fabricated by hot metal forming processes are attractive structural components in the aerospace and automobile industry. The strength of the mechanical bond between the different layers is critical to the applicability of such components in load bearing applications. While it is well understood that the process conditions such as temperature, deformation and rate of deformation influence the bond strength, a clear functional relationship between these conditions and the bond strength has yet to be established. The objective of the current study is to investigate the joining of Aluminum-6061 alloy specimens by hot compression bonding. Hot compression tests of beam specimen pairs were conducted at different temperatures (300-500℃), with different strains and strain rates (10-2-10-1 [1sec]). Coupled thermo-mechanical finite element models were utilized to compute the time dependent thermo-mechanical fields that develop along the specimen interface. The computed values were used to map the spatial distribution of a scalar parameter J which is hypothesized to govern bond formation. Mechanical tensile tests were used to determine the bond strength and expose the bonded surfaces. It is demonstrated that the computed J distribution can be correlated well with SEM observations of the debonded surface. It is also shown that the actual bonded area can be predicted from the computations for a certain range of critical J values.

Soil erosion seriously affects vineyards. In this study, the influence of two plant covers on soil moisture and the effect of different physiographic conditions on runoff and sediment yields were evaluated in a rainfed vineyard formed by four fields (NE Spain) during 15 months. One field had spontaneous vegetation as plant cover and three fields had a cover crop of common sainfoin. The vineyards’ rows were dry and stable, whereas the inter-row areas were wet although very variable, and the corridors were wet and very stable. Soil moisture in the inter-row areas with Common sainfoin was much higher than in the rows (62% - 70%) whereas this difference was lower with spontaneous vegetation (40%). Two runoff and sediment traps (STs) were installed in two ephemeral gullies, and 26 time-integrated surveys (TIS) done. The mean and maximum runoff yields were 9.8 and 30.7 l TIS^–1 in ST2 and 13.5 and 30.2 l TIS^–1 in ST3. The mean turbidity was 333 and 19 g l^–1, and the maximum sediment yields were 41,260 and 2,778 g TIS^–1 in ST2 and ST3. Changes in the canopy covers (grapevines and plant covers) and rainfall parameters explained the runoff and sediment dynamics.

All living cells maintain a charge distribution across their cell membrane (membrane potential) by carefully controlled ion fluxes. These bioelectric signals regulate cell behavior (such as migration, proliferation, differentiation) as well as higher-level tissue and organ patterning. Thus, voltage gradients represent an important parameter for diagnostics as well as a promising target for therapeutic interventions in birth defects, injury, and cancer. However, despite much progress in cell and molecular biology, little is known about bioelectric states in human stem cells. Here, we present simple methods to simultaneously track ion dynamics, membrane voltage, cell morphology, and cell activity (pH and ROS), using fluorescent reporter dyes in living human neurons derived from induced neural stem cells (hiNSC). We developed and tested functional protocols for manipulating ion fluxes, membrane potential, and cell activity, and tracking neural responses to wounding and re-innervation in vitro. Finally, using morphology sensor, we tested and quantified the ability of physiological actuators (neurotransmitters and pH) to manipulate nerve wound re-innervation. These methods are not specific to a particular cell type and should be broadly applicable to the study of bioelectrical controls across a wide range of combinations of models and endpoints.

Background: The genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment were used to test a polygenic selection model. Methods: Average frequencies of alleles with positive effect (polygenic scores or PS) were compared across populations (N=26) using data from 1000 Genomes. A null model was created using frequencies of random SNPs. Results: Polygenic selection signal of educational attainment GWAS hits is high among a handful of SNPs within genomic regions replicated across GWAS publications. A polygenic score comprising 9 SNPs predicts population IQ (r=0.88), outperforming 99% of the polygenic scores obtained from sets of random SNPs (Monte Carlo p= 0.011). Its predictive power remains unaffected after controlling for spatial autocorrelation (Beta= 0.83). The largest polygenic score (161 SNPs) exhibits similar predictive power (Beta=0.8). Random polygenic scores are moderate predictors of population IQ (thanks to spatial autocorrelation), and their predictive power increases logarithmically with the number of SNPs, indicating an exponential reduction in noise. Conclusion: This study provides guidance for using GWAS hits together with random SNPs for testing polygenic selection using Monte Carlo simulations.

In this study, we aim to evaluate how cyclodextrin molecules affect the hydrophilicity and selec-tivity of PVDF membrane. Herein, we prepared PVDF-PVP(1-x) β-CDx membranes, with x rang-ing from 0 to 1 wt%. The membranes were deeply characterized by means of X-ray diffraction (XRD), attenuated total reflectance infrared (ATR-IR), Raman spectroscopies, Thermal gravimet-ric analysis (TGA), Contact angle measurement (CA), scanning electron microscopy (SEM) and atomic force microscopy (AFM). The study unequivocally demonstrates the effectiveness of the addition of β-CD molecules on membranes' structural, morphological, and dielectric properties. Adding 0.25wt% β-CD enhanced hydrophilicity, with CA decreasing from 72.6° to 56° and roughness decreasing from 81 to 29 nm. The PVDF-PVP(1-x) β-CDx membranes were then fully characterized using electrochemical impedance spectroscopy (EIS) to determine their dielectric properties, which clearly showed that the presence of β-CD induced polarization of the mem-brane. The separation of various dyes with different sizes and charges was utilized. These dyes included methylene blue (MB, positive, 0.504 nm), methyl red (MR, neutral, 0.487 nm), rose Bengal (RB, negative, 0.588 nm), and brilliant blue (BB, negative, 0.798 nm). Based on our re-search, we found that the membrane's selectivity is determined by both exclusion factors (such as size and dielectric properties) and inclusion inside the β-CD cage. We found that using alpha-CD instead of beta-CD led to the disappearance of dye inclusion. These findings strongly sug-gest that β-CD molecules can be a viable solution for dye removal from wastewater.

Heavy metals contamination in groundwater often occurs in various industrial processes. Stud-ies have confirmed that polysulfide could reduce hexavalent chromium to trivalent chromium, achieving the effect of in-situ stabilization. For other heavy metals contamination in groundwa-ter, whether polysulfide also had a stabilizing ability to achieve in-situ remediation. This re-search focused on heavy metals except for chromium that often contaminated in groundwater, including lead, nickel, zinc, copper, and cadmium to explore the feasibility of using calcium polysulfide (CaSx) as an in-situ stabilization technology for these heavy metals contamination groundwater. Results showed that CaSx had a great removal efficiency for heavy metals lead, nickel, zinc, copper, and cadmium. However, for nickel, zinc, copper and cadmium, when CaSx was added excessively, complexes would be formed, causing the result of re-dissolve and this would also reduce the removal efficiency. Since it is difficult to accurately control the dosage of agents for in-situ groundwater remediation, the concentration of re-dissolved nickel, zinc, cop-per, and cadmium may not be able to meet the groundwater control standards. CaSx had high lead removal efficiency, and it would not cause re-dissolution due to excessive CaSx dosing. CaSx can be used as an in-situ stabilization technique for lead contaminated groundwater.

Polymer electrolyte was used as a medium for testing the performance of microband electrodes under conditions of linear diffusion. Cyclic voltammetry and chronoamperometry experiments were performed in such viscous medium, where diffusion rates are much slower than in fluid solutions. Confirmation of the existence of such conditions from the log i vs. log v or log i vs. log t relationships in the current equation always yielded values lower than the expected value of 0.5. This could indicate impure linear diffusion profile, i. e. some contribution from radial diffusion (edge effect). However, performing these tests in monomeric solvents of similar viscosities, such as glycerol or propylene glycol, gave the desired value of 0.5. These results lead to the conclusion that current equations which are based on Fick’s laws may not be applicable for polymer electrolytes, where various obstruction to diffusion make it a more complicated process than in monomeric solvents.

This paper presents a novel method for automatic modulation classification (AMC) for cognitive radio (CR) networks based on a simple classifier that is trained with high-order cumulant. The proposed method focuses on the statistical behavior of modulated signals and includes analog modulation and digital schemes, which received less attention in the literature. The effectiveness of the proposed method is demonstrated through simulation results using high-quality generated signals under different signal-to-noise ratios (SNRs) and channel conditions. The classification performance achieved by the proposed method is superior to that of the more complex deep learning methods, making it well-suited for deployment in end units of CR networks, particularly in military and emergency service applications. The proposed method offers a cost-effective, high-quality solution for AMC that meets the stringent requirements of these critical applications.

Recently we have seen a relaxation of the historic restrictions on the use and subsequent research on the Cannabis plants, generally classified as Cannabis sativa and Cannabis indica. What research has been performed to date has centered on chemical analysis of plant flower products, namely cannabinoids and various terpenes that directly contribute to phenotypic characteristics of the female flowers. In addition, we have seen many groups recently completing genetic profiles of various plants of commercial value. To date, no comprehensive attempt has been made to profile the proteomes of these plants. We report herein our progress on constructing a comprehensive draft map of the Cannabis proteome. To date we have identified over 17,000 potential protein sequences. Unfortunately, no annotated genome of Cannabis plants currently exists. We present a method by which “next generation” DNA sequencing output and shotgun proteomics data can be combined to produce annotated FASTA files, bypassing the need for annotated genetic information altogether in traditional proteomics workflows. The resulting material represents the first comprehensive annotated protein FASTA for any Cannabis plant. Using this annotated database as reference we can refine our protein identifications, resulting in the confident identification of 13,000 proteins with putative function. Furthermore, we demonstrate that post-translational modifications play an important role in the proteomes of Cannabis flower, particularly lysine acetylation and protein glycosylation. To facilitate the evolution of analytical investigations into these plant materials, we have created a portal to host resources we have developed from proteomic and metabolomic analysis of Cannabis plant material as well as our results integrating these resources. All data for this project is available to view or download at www.CannabisDraftMap.Org

Several factors influence traffic congestion and overall traffic dynamics. Simulation modeling has been utilized to understand the traffic performance parameters during traffic congestions. This paper focuses on driver behavior of route selection by differentiating three distinguishable decisions, which are shortest distance routing, shortest time routing and less crowded road routing. This research generated 864 different scenarios to capture various traffic dynamics under collective driving behavior of route selection. Factors such as vehicle arrival rate, behaviors at system boundary and traffic light phasing were considered. The simulation results revealed that shortest time routing scenario offered the best solution considering all forms of interactions among the factors. Overall, this routing behavior reduces traffic wait time and total time (by 69.5% and 65.72%) compared to shortest distance routing.

Streptococcus mutans is a key bacterium in dental caries- one of the most prevalent chronic infectious diseases. Conventional treatment both fails to specifically target the pathogenic bacteria and at-tempts to eradicate commensal bacteria as well. Thus, caries remains one of most common and challenging diseases. The use of bacterial viruses as anti-bacterial agents, is gaining interest worldwide. Hardly any phages were described against S. mutans. The objective of this study was to isolate anti-S. mutans phages and to characterize their antimi-crobial properties. Human saliva samples were filtered and screened for potential phages. Standard double-layered agar method was used for isolation. Whole genome sequence analysis and morphology visualization by TEM, were used for anti-S. mutans phage identification. Antibacterial properties were evaluated using clinical strains and ATCC strains of S. mutans in various states. Antibacterial effect was also tested on human cariogenic dentin. One phage against S. mutans was isolated and termed SMHBZ8. This phage showed effective lytic activity in vitro against both planktonic and biofilm S. mutans cultures. Moreover, the phage showed antibacterial effect when used on cariogenic dentin. The isolation and characterization of SMHBZ8 may be the first step in developing a potential phage therapy for dental caries.

The sustainable development of resource-based cities has long been a focal point for both governmental policies and academic research. A wealth of academic literature identifies the 'resource curse' as a critical barrier to sustainable development in these urban areas. Despite extensive studies, a consensus on effective strategies to circumvent or resolve this challenge remains elusive. Recent empirical data reveals a noticeable pattern of economic growth differentiation in China's resource-based cities. Why do some resource-based cities experience economic decline while others achieve sustainable economic growth? Therefore, this paper analyzes the reasons for the divergence of economic growth in resource cities from the perspective of heterogeneity. The results of the study show that the phenomenon of the resource curse is conditional, and the heterogeneity of demo-graphic changes, geographic location and institutional environment has a significant impact on the economic growth of resource cities. These factors are investigated to elucidate the observed diversification and heterogeneity in the economic growth of resource-based cities. Building upon this analysis, the paper proposes a framework for differentiated sustainable development pathways tailored to the unique contexts of these cities. This approach not only contributes to the current understanding of the 'resource curse' but also offers novel insights for future research aiming to adopt a more nuanced and context-specific perspective in examining sustainable urban development.

There always exist steel cuttings, holes and cracks at the interfaces in the explosive composite plate. Multi-pass friction stir processing (M-FSP) is proposed in this research to optimize the interface microstructure and the interface connection for 1060Al/Q235 explosive composite plate. Results show that the microstructures of 1060Al after M-FSP are fine and uniform owing to the strong stirring effect and recrystallization. Micro-defects formed by the explosive welding can be repaired by the M-FSP. However, M-FSP can also form tunnel defects in the aluminum, especially when the passes are one and two. The melting block and the melting lump in the composite plates are easy to become source of crack. The shear strengths and the bending properties for the 1060Al/Q235 explosive composite plate after M-FSP are the best when the passes are three, with the tool rotation speed of 1200rpm and the forward speed of 60mm/min. The optimized interfaces for the explosive composite plate after M-FSP are mainly by the metallurgical bondings, with a certain thickness and are discontinuous. Therefore, the crack extension stress is the largest and the mechanical properties are the best.

The Capital Asset Pricing Model is a widely applied model to describe risky markets and to deduce their systematic risk. Its estimation, therefore, remains an important task in Econo-financial studies. Empirically, it focuses on the impact of return interval on the betas. Existing studies somehow turn around the same idea of measuring the value of the beta according to the uniform intervals of time during a fixed period. However, it is noticed easily, and especially in the last decade that many factors such as socio-political, and Econo-environmental ones have led to a perturbation in the timeline of the worldwide development, and especially in countries and regions having political changes. This led us to introduce a new idea of risk estimation taking into account the non-uniform changes in markets by introducing a non-uniform wavelet analysis. We aim to explain the Econo-political situation of Arab spring countries and the effect of the revolutions on the market beta. The main novelty is firstly the construction of a dynamic backward-forward model for missing data, and next the application of random non-uniform wavelets. The proposed procedure will be acted empirically on a sample corresponding to TUNINDEX stock as a representative index of the Tunisian market actively traded over the period January 14, 2016, to January 13, 2021. The chosen 5-years period is important as it constitutes the first 5-years-after the revolution and depends strongly on the Socio-Econo-political stability in the revolutionary countries.

A two scalar field model that incorporates non Riemannian Measures of integration or usually called Two Measures Theory (TMT) is introduced, in order to unify the early and present universe. In the Einstein frame, a K-essence is generated and as a consequence for the early universe, we can have an Inflation for the very early universe and then, after inflation, an early dark energy period and a late dark energy period for the present universe dark, both dark energy epochs have a consistent generation of dark energy (DE), dark matter (DM) and stiff matter. This is obtained when the scale invariance is introduced and then is spontaneously broken from the integration of the degrees of freedom associated with the modified measures. The resulting effective potentials and K-essence in the Einstein frame produce the three flat regions corresponding to the different epochs mentioned before. For the first flat region, we can associate an inflationary universe. Also assuming this first plateau, we study the inflation in the framework of the slow-roll approximation. In this scenario under the slow roll approximation, we obtain a linear combination that is a constant. The corresponding cosmological perturbations in our model are determined and we also obtain the different constraints on the parameter-space from the Planck data. The slow roll approximation can be arranged so that the transition from inflation to the next flat region can be achieved without problems. In the following two flat regions, in addition to the inflation phase, representing the Early Dark Energy and Late Dark Energy Periods, with DE and also the DM, do not need to be introduced separately, they are instead a result of a K-essence induced by the multi measures, multi field theory. Therefore the scalars generate both the DE and the DM . Also a stiff matter component is automatically generated from the K-essence theory from two scalar fields. From the perturbative analysis associated to the perturbation solution of background, we find a correlation between the two scalars. Besides, we obtain that our model during the dark epoch has a behaviour of tracking freezing mode

In the rapidly evolving landscape of genetic engineering, the advent of CRISPR-Cas technologies has catalyzed a paradigm shift, empowering scientists to manipulate the genetic code with unprece-dented accuracy and efficiency. Despite the remarkable capabilities inherent to CRISPR-Cas sys-tems, recent advancements have witnessed the integration of small molecule to augment their functionality, introducing new dimensions to the precision and versatility of gene editing applica-tions. This review delves into the synergy between CRISPR-Cas technologies and small molecule drugs, elucidating the pivotal role of chemicals in optimizing target specificity and editing efficiency. By examining a diverse array of applications, ranging from therapeutic interventions to agricultural advancements, we explore how the judicious use of chemicals enhances the precision of CRISPR-Cas-mediated genetic modifications. In this review we emphasize the significance of small molecule drugs in fine-tuning the CRISPR-Cas machinery, which allows researchers to exert meticulous con-trol over the editing process. We delve into the mechanisms through which these chemicals bolster target specificity, mitigate off-target effects, and contribute to the overall refinement of gene edit-ing outcomes. Additionally, we discuss the potential of chemical integration in expanding the scope of CRISPR-Cas technologies, enabling tailored solutions for diverse genetic manipulation challenges. As CRISPR-Cas technologies continue to evolve, the integration of small molecule drugs emerges as a crucial avenue for advancing the precision and applicability of gene editing techniques. This re-view not only synthesizes current knowledge but also highlights future prospects, paving the way for a deeper understanding of the synergistic interplay between CRISPR-Cas systems and chemical modulators in the pursuit of more controlled and efficient genetic modifications.

Ocular drug delivery is one of the most challenging administration routes due to the very low drug bioavailability. In this work, we produce and characterize mucoadhesive mixed polymeric micelles (PMs) made of chitosan and poly(vinyl alcohol) backbones graft-hydrophobized with short poly(methyl methacrylate) blocks and use them to encapsulate cannabidiol (CBD), an anti-inflammatory cannabinoid. CBD-loaded mixed PMs are physically stabilized by ionotropic crosslinking of the CS domains with sodium tripolyphoshate and spray-drying. These mixed PMs display CBD loading capacity of 20% w/w and sizes of 100-200 nm, and spherical morphology (cryogenic-transmission electron microscopy). The good compatibility of the unloaded and CBD-loaded PMs is assessed in a human corneal epithelial cell line. Then, we confirm the permeability of CBD-free PMs and nanoencapsulated CBD in cornea cell monolayers under liquid-liquid and air-liquid conditions. Overall, our results highlight the potential of these polymeric nanocarriers for ocular drug delivery.

The realization of a BRST cohomology of the 4D topological gauge-affine gravity is established in terms of a superconnection formalism. Identification of fields in the quantized theory is occurred directly as usual in terms of superconnection and its supercurvature components with the double covering of the general affine group GA¯(4,R). Then, by means of an appropriate decomposition of the metalinear double-covering group SL¯(5,R) with respect to the general linear double-covering group GL¯(4,R) one can easily obtain the enlargements of the fields while remaining consistent with the BRST algebra. This leads to the descent equations allowing us to build the observables of the theory by means of the BRST algebra constructed using a sa¯(5,R) algebra-valued superconnection. In particular, we discuss the construction of topological invariants with torsion.

Sulfated polysaccharides from seaweed are highly active natural substances having valuable applications. In the present paper, attempts have been made to discuss the physicochemical and structural features of polysaccharides isolated from red marine alga Alsidium corallinum (ACPs) and its protective effect in hepatic impairments induced by tebuconazole (TBZ) in rats. Structural features were determined using High performance liquid chromatography, Fourier transformed infrared, and solid state ¹H and ¹³C-Nuclear magnetic resonance analysis. ACPs are found to be hetero-sulfated-anionic polysaccharides that contained carbohydrates, sulfate groups and uronic acids. In vitro biological activities suggested the effective antioxidant and antimicrobial capacities of ACPs. For antioxidant testing in vivo, the biochemical analysis and plasma profiles displayed that oral administration of ACPs could mitigate blood lipid indicators, including total cholesterol, triglyceride, low and high density lipoprotein cholesterol, bilirubin, liver function indexes involving alanine aminotransferase and aspartate aminotransferase, showed that ACPs possessed obvious antioxidant activities. Besides, the intervention of ACPs potentially inhibited lipid peroxidation, protein oxidation, key enzymes of lipid metabolism (<0.001) and increased levels and antioxidant status (<0.05). Histomorphological observation confirmed that ACPs intervention could partially repair liver injuries caused by TBZ. The computational results showed that A. corallinum monosaccharides bound 1JIJ, 1HD2 and 1WL4 receptors with acceptable affinities, which together with deep embedding and molecular interactions support the antioxidant, antimicrobial and hypolipidemic outlined effects in the in vitro and in vivo findings. In view of their prominent antioxidant effects, ACPs stand for promising candidates in liver diseases and need be considered in pharmaceutical applications.

Abstract: The VSI represents a significant advancement in the assessment of gastrointestinal-specific anxiety among patients with Irritable Bowel Syndrome (IBS) and other Chronic Inflammatory Bowel Diseases (IBD). However, an Italian version of the instrument is not yet available for the reference population. This study utilized a national sample of 500 individuals, including healthy controls and patients with Ulcerative Colitis and Crohn's Disease, to test the validity and reliability of the Italian VSI. Using back-translation methodology to ensure translation fidelity, the research applied a questionnaire and the VSI through an online format to 500 participants. Data analysis revealed that the Italian VSI had excellent psychometric properties, demonstrating high internal consistency (Cronbach’s α = 0.95) and construct validity. The scale proved sensitive in detecting significant differences in visceral sensitivity among groups, highlighting its utility as a clinical and research assessment tool. Specifically, the Italian VSI exhibited a unidimensional factorial structure and maintained a strong correlation with other measures of anxiety and the severity of gastrointestinal symptoms, confirming its role in enhancing the understanding and management of IBS and IBD in Italy.

Recent years have seen dramatic growth in the number of scholarly scientific works dedicated to the topic of Artificial Intelligence (AI), banking, and finance. With the development of scientometric tools, it is now possible to map, visualize, analyze, and assess scientific activities in many fields of engineering and social sciences including Islamic banking and finance. Based on data retrieved from the Scopus database and using a qualitative method, this study investigates, evaluates, and identifies significant development, trends, and players in the application of AI in Islamic banking and finance using the Visualization Of Similarities Method (VOS) between objects in VOSviewer. From 2006 to 2022, 387 documents were retrieved from the Scopus database; Results revealed that the top five most active countries in terms of publications are Malaysia (117 documents), Indonesia (89 documents), the United Kingdom (36 documents), the USA (24 documents), and Saudi Arabia and Bahrain (24 documents each). The International Islamic University Malaysia and Universitas Indonesia came out on top of active institutions while the top funding source came from the Ministry of Higher Education, Malaysia. The comprehensive findings and analysis reported in this study serve as a roadmap for future academics to create theory and practice for applying AI in Islamic banking and finance.

AI advances integrate generative design tools in architecture, providing architects with sophisticated design options. It enables the creation of intricate, high-performing projects by exploring diverse design possibilities with AI and algorithms. Generative AI and generative design empower architects to create better-performing, sustainable, and efficient design solutions and explore diverse design possibilities. This paper leverages multimodal generative AI to enhance design creativity by combining textual and visual inputs. Blockchain technology converts design metadata into NFTs, ensuring secure, authentic, and traceable data storage. The framework addresses data ownership, legal adherence, and client-architect collaboration and is entirely scalable for digital design authentication. This research exemplifies the pragmatic fusion of Generative AI and blockchain technology applied in architectural design for more transparent, secure, and effective results. This study provides a strategy that uses generative AI technologies to achieve an efficient and creative workflow in the early stages of architectural design.

In the TANGO study, the long-term noninferior efficacy of switching to dolutegravir/lamivudine (DTG/3TC) compared to continuing tenofovir alafenamide–based regimens was demonstrated in treatment-experienced adults with HIV. However, there is limited real-world data comparing the effectiveness and safety of bictegravir/emtricitabine/tenofovir alafenamide fumarate (BIC/FTC/TAF) and DTG/3TC in Asia. This retrospective observational study, conducted at a designated HIV-care hospital from March 2019 to January 2023, aimed to address this gap. Demographic, clinical, and laboratory data, including HIV viral loads and lipid profiles, were collected and analyzed. The primary outcome was the proportion of patients with HIV RNA <50 copies/mL at week 48 in both groups, utilizing a snapshot, per-protocol–exposed population. A total of 1086 patients were included, with 511 in the DTG/3TC group and 575 in the BIC/FTC/TAF group. At week 48, 98% of patients in the DTG/3TC group and 94% in the BIC/FTC/TAF group achieved HIV RNA <50 copies/mL (p <0.01). Logistic regression analysis identified risk factors for detectable viral loads at week 48, including HIV RNA >100,000 copies/mL (AOR 5.13, 95% CI 1.42–18.53), low-level viremia (AOR 3.91, 95% CI 1.07–14.25), and record of virologic failure ≥2 times (AOR 4.21, 95% CI 1.64–10.85) before the switch. Furthermore, no significant difference was found between the DTG/3TC and BIC/FTC/TAF regimens (AOR: 1.51, 95% CI 0.70–3.24). In conclusion, the study demonstrates that the effectiveness and safety profiles of DTG/3TC and BIC/FTC/TAF were comparable in treatment-experienced adults with HIV, particularly among those with undetectable viral loads at baseline.

Discovered as an apparent pattern, a universal relation between geometry and information called the holographic principle has yet to be explained. This relation is unfolded in the present paper. As it is demonstrated there, the origin of the holographic principle lies in the fact that a geometry of physical space has only a finite number of points. Furthermore, it is shown that the puzzlement of the holographic principle can be explained by a magnification of grid cells used to discretize geometrical magnitudes such as areas and volumes into sets of points. To wit, when grid cells of the Planck scale are projected from the surface of the observable universe into its interior, they become enlarged. For that reason, the space inside the observable universe is described by the set of points whose cardinality is equal to the number of points that constitute the universe’s surface.

This paper presents a new method for approximating the classical arcsine function. The proposed approximating methodology is simpler in its approach than other classical approaches and undeniably innovative. It is based on matrix representation besides the basic interpolation to approximate the inverse trigonometric function. It provides an efficient model which allows for reliable and precise calculations. The results are as per our knowledge unseen results in the previous literature.

The present paper is concerned with the study of the quality of life index. Such an index has become an important index for measuring the well-being of individuals. However, the quality of life index is always a subjective, intangible, and often hard to quantify with precision due to the lack of quantitative models dealing with. The main goal of the present paper is thus to propose a mathematical, quantitative model for the measurement of a quality of life index. The main novelty is firstly the construction of a wavelet dynamic multiscale model to quantify and investigate the effect of time scale on the quality of life index measuring. The proposed procedure is acted empirically on a sample corresponding to Saudi Arabia as a case of study during the period from 2003 to 2020 as part of the 2030-vision plan. Saudi Arabia has implemented the so-called 2030-vision plan where the quality of life improvement is one of the main goals to be attempted. The findings show that wavelets are capable to localize the time-wise behavior of the index contrarily to classical studies which estimate a global view of the index. Moreover, the study shows the link between the quality of life behavior and many other indices.

The relative operating characteristic (ROC) curve is a popular diagnostic tool in forecast verification, with the area under the ROC curve (AUC) used as a verification metric measuring the discrimination ability of a forecast. Along with calibration, discrimination is deemed as a fundamental probabilistic forecast attribute. In particular, in ensemble forecast verification, AUC provides a basis for the comparison of potential predictive skill of competing forecasts. While this approach is straightforward when dealing with forecasts of common events (e.g. probability of precipitation), the AUC interpretation can turn out to be oversimplistic or misleading when focusing on rare events (e.g. precipitation exceeding some warning criterion). How should we interpret AUC of ensemble forecasts when focusing on rare events? How can changes in the way probability forecasts are derived from the ensemble forecast affect AUC results? How can we detect a genuine improvement in terms of predictive skill? Based on verification experiments, a critical eye is cast on the AUC interpretation to answer these questions. As well as the traditional trapezoidal approximation and the well-known bi-normal fitting model, we discuss a new approach which embraces the concept of imprecise probabilities and relies on the subdivision of the lowest ensemble probability category.

Session-based recommendations which aim to predict subsequent user-item interaction based on historical user behavior during anonymous sessions can be challenging tasks. Two main challenges need to be addressed and improved: (1) How to analyze these sessions to accurately and completely capture users’ preferences, and (2) how to identify and eliminate any interference caused by noisy behavior. Existing methods have not adequately addressed these issues since they either neglected the valuable insight that can be gained from analyzing consecutive groups of items or failed to take these noisy data in sessions seriously and handled them properly, which can jointly impede recommendation systems from capturing users’ real intentions. To address these two problems, we designed a multi-order semantic denoising (MSD) model for session-based recommendations. Specifically, we grouped items of different lengths as varying multi-order semantic units to mine the user’s primary intention from multiple dimensions. Meanwhile, a novel denoising network was designed to alleviate the interference of noisy behavior and provide a more precise session representation. The result of extensive experiments on three real-world datasets demonstrated that the proposed MSD model exhibited improved performance compared with existing state-of-the-art methods in session-based recommendation.

This paper presents a comprehensive study on the application and optimization of automotive thermoelectric generators (ATEGs), focusing on the crucial role of heat exchangers in enhancing energy conversion efficiency. Recognizing the substantial waste of thermal energy in internal combustion engines, our research delves into the potential of TEGs to convert engine waste heat into electrical energy, thereby improving fuel efficiency and reducing environmental impact. We meticulously analyze various heat exchanger designs, assessing their influence on the TEG's output power under different exhaust gas flow rates and temperatures. Furthermore, we explore the impact of TEG material properties on the overall energy conversion effectiveness. Our findings reveal that specific heat exchanger designs significantly enhance the efficiency of waste gas heat exchange, leading to an improved performance of the TEG system. We also highlight the importance of thermal insulation in maximizing TEG output. This study not only contributes to the ongoing efforts to develop more sustainable and efficient vehicles but also provides valuable insights into the practical application of thermoelectric technology in automotive engineering. Through this research, we aim to pave the way for more environmentally friendly transportation solutions, aligning with global efforts to reduce fossil fuel dependence and mitigate environmental pollution.

Ganoderic Acid (GA), a major bioactive compound isolated from an oriental medicinal mushroom, i.e. Ganoderma tsugae, has traditionally been found to have significant medicinal properties. As a result of GA's poor solubility in water, formulation poses several challenges. Additionally, the traditional method of administering it via alcohol always results in unfavorable patient side effects. In order to overcome these problems, Ganoderma Tsugae extracts obtained by ethanol extraction were encapsulated in nanodispersions by ultrasonic cavitation and solvent evaporation to maximise bioavailability. Resultant nanodispersions contained Ganoderic acid in a hydrophobic core with a mean particle size of no more than 200 nm and a very narrow particle distribution. An analysis of the interactions between the control variables and the process optimisation was conducted using the Response Surface Methodology (RSM). Based on the results of the experiment, it was found that the particle size of nanodispersions was influenced by the Hydrophilic-Lipophilic Balance (HLB) number and the evaporation temperature. Moreover, the physical stability of micellar systems is generally determined by the organic phase within them. Regarding formulation stability, the zeta average of the nanodispersions remained virtually unchanged in solutions with different pH levels and short-term storage (14 days) at room temperature. Overall, it has been demonstrated that Ganoderic acid nanodispersions can be efficiently generated by combining ultrasound cavitation and solvent evaporation.

The integration of robotic devices into healthcare settings for rehabilitation purposes represents a rapidly advancing field with significant benefits for both therapists and patients. However, standalone robot systems face limitations such as inefficient processing of patient data and logistical challenges for patients, such as travel time to rehabilitation centers. To address these shortcomings, this paper proposes the integration of cyber-physical systems into rehabilitation robotics. Cyber-physical systems leverage network connectivity and real-time data processing to enhance the efficiency and convenience of robot-based rehabilitation. By seamlessly integrating sensors, actuators, and computational algorithms, cyber-physical rehabilitation systems empower therapists to more effectively treat patients by providing actionable insights derived from comprehensive data analysis. This enables therapists to tailor treatment plans precisely to each patient’s unique needs, ultimately leading to improved outcomes. Additionally, cyber-physical rehabilitation systems facilitate remote monitoring and intervention, allowing therapists to oversee patient progress and make timely adjustments to treatment protocols without the need for in-person visits. This not only saves patients valuable time and resources but also ensures continuity of care, particularly for individuals residing in remote or underserved areas. Furthermore, cyber-physical rehabilitation systems enable collaborative decision-making by facilitating communication and information sharing among healthcare professionals, further enhancing the quality and efficacy of rehabilitation services. In summary, integrating cyber-physical systems into rehabilitation robotics represents a significant advancement in leveraging technology to optimize patient care and outcomes, promising to revolutionize rehabilitation therapy.

Due to the fact that abrasive media can deform flexibly in abrasive flow machining (AFM) making this method easily to polish the complex holes and the curved surface of the hard machining shapes. Although abrasive media dominate the polishing behavior in AFM process, the mechanism of the abrasive media are not easy to understand because of the high viscous gels, therefore, many finishing works need lots of time to design AFM process. Power laws of the abrasive gels is studied here to evaluate the non-Newtonian flow of abrasive gels in complex holes polishing firstly, at the mean time different abrasive gels are utilized to finish the complex holes to follow the results by non-Newtonian flow calculation. Moreover, traditional AFM has difficulty to achieve a uniform roughness of radial distribution in the complex holes polishing because of the non-uniform abrasive forces. So a helical passageway is proposed to create a multiple motion of abrasive medium and to obtain the even surface of the complex holes in AFM process.

We seek to examine effective collaboration when engaging in value cocreation with the customer for mobile financial services in EMs. Our study is a motivation for multi-stakeholder engagement in value cocreation with financial inclusion of all consumers including marginalized populations. Furthermore, our work discovers that social sustainability is a product of social creativity and results in financial inclusion. We apply a qualitative descriptive methodology utilizing exemplars from extant research and phenomenology to analyze the data from the contexts of Ghana and Kenya. The results show that value is co-created for mobile financial services in networks in emerging markets when actors integrate resources for social and environmental sustainability as essential elements for mobile financial inclusion.

Background: Studies have demonstrated the link between vitamin D-related genetic variations and non-skeletal outcomes. We aimed to identify all available data on the association of vitamin D-related genetic variations with non-alcoholic fatty liver disease (NAFLD). Methods: Potentially eligible studies were identified from Embase and Medline databases from inception to June 2022 using search strategy that comprised terms for “Vitamin D” and “NAFLD”. Eligible study must report the association between vitamin D-related genetic variations and presence, severity or response to treatment of NAFLD. Data were extracted from each eligible study. Results: A total of 3,495 articles were identified. After systematic review, twelve studies were in-cluded. A total of 26 genetic variations were identified. Presence of NAFLD was associated with variations of GC (rs222054, rs222020, rs10011000, rs7041), VDR (rs2228570, rs11168287, rs10783219, rs4752), CYP24A1 (rs3787557, rs6068816, rs2296241, rs2248359) and CYP27B1 (rs4646536). Severity of NAFLD was associated with variations of GC (rs4588), VDR (rs2228570, rs4334089), CYP2R1 (rs10741657), DHCR7 (rs1544410, rs3829251, rs12785878) and CYP24A1 (rs3787557, rs6068816, rs6097809, rs6127119, rs2248359, rs3787554, rs4809960, rs6022999). Response to calcitriol treatment was associated with variation of VDR (rs10735810). Conclusions: Multiple vitamin D-related genetic variations were associated with NAFLD, indi-cating the role of vitamin D in the pathogenesis of NAFLD.

Questions：SAP in mountainous cities of China serve as crucial carriers for species and wild food, constituting potential green infrastructure. These patches should be recognized as locally specific resources. This study investigates the transformation characteristics of the landscape patterns of SAP, along with their elements, across urban-rural gradients, providing foundational support for the planning of conservation and utilization strategies. Location: Yongchuan area of Chongqing in southwest China. Methods: The study investigated urban-rural gradient-based transformation of SAP. A four-direction transect space was selected and divided into uniform sample squares. Fragstats 4.3 calculated the landscape index of SAP, and Spearman correlation coefficients in SPSS were used to evaluate the influence of landform and artificial factors on agroforestry patch transformation. Results: 1) Patch area (PA), Plaque density (PD), and CLUMPY of SAP systematically transform, showing increased SAP areas and higher connectivity with greater distance from the city, resulting in reduced patch fragmentation. However, Edge density (ED) and Largest plaque index (LPI) exhibit irregular transformation patterns. 2) With increased distance from the city, woodland patch area and connectivity increase, leading to decreased fragmentation, dispersal, and lower fractal dimensions. Conversely, Cultivated land follows the opposite trend. garden land patch area, fractal dimension, fragmentation, and dispersal all increase, while connectivity decreases. 3) Landscape pattern transformations of SPA are significantly influenced by artificial factors. Woodland patches are influenced similarly by landform and artificial factors. In contrast, cultivated land and garden land patches are more significantly impacted by artificial factors. Conclusions: SAP exhibit differentiated conservation and utilization measures across urban-rural gradients. Small patches located far from urban centers may benefit from systematic conservation measures to prevent further fragmentation and erosion in peri-urban areas.

To decrease privacy risks, consumers may choose to misrepresent when they are asked to offer personal information. This paper examines the impact of consumer misrepresentation on a monopolistic firm and consumers with an economic model. The results show that consumer misrepresentation may benefit the firm but hurt consumers. In addition, consumers misrepresentation may encourage the firm to provide higher personalized service level in certain scenarios, such as, when the unit cost of personalized service is low. Thirdly, when consumers misrepresent, and the firm only covers part of the market, a greater unit value of consumer’s privacy information will reduce the firm’s profit, but a greater unit cost of personalized service increases the firm’s profit.

Oil-Gan, also known as emblica, is the fruit of the genus Phyllanthus emblica L. The fruits of these trees are high in nutrients and have excellent effects on health care and development values. There are many methods for the management of diabetic nephropathy (DN). However, there is a lack of effective drugs for treating DN from throughout the disease course. The primary aim of this study was to examine the protective effects (including urine analyses, the measurement of inflammatory cytokine levels, and histological examination) and mechanisms of action of an ethyl acetate extract of P. emblica (EPE) on db/db mice, an animal model of diabetic nephropathy, as well as a secondary aim of examining the expression levels of protein kinase Cα (PKCα) in the kidney and its downregulation of vascular endothelial growth factor (VEGF) and fibrosis gene transforming growth factor-β1 (TGF-β1) by Western blot analyses. Eight db/m C57BLKS/J mice were used as the control group. Forty db/db mice were randomly divided into five groups. Treatments included vehicle, EPE1, EPE2, EPE3 (at doses of 100, 200, or 400 mg/kg EPE), or the comparative drug aminoguanidine for 8 weeks. After 8 weeks of treatment, blood samples were collected for analyses of blood glucose, insulin, and HbA1c levels, and pancreatic and kidney tissues were dissected for histological analyses. The present study indicated that the administration of EPE to db/db mice effectively controlled hyperglycemia and hyperinsulinemia by markedly lowering blood glucose, insulin, and glycosylated HbA1c levels. Administration of EPE to db/db mice decreased the levels of BUN and creatinine both in blood and urine and reduced urinary albumin excretion and the albumin creatine ratio (UACR) in urine. Moreover, EPE treatment decreased the blood levels of inflammatory cytokines, including kidney injury molecule-1 (KIM-1), C-reactive protein (CRP), and NLR family pyrin domain containing (NLRP3). Our findings showed that EPE not only had antihyperglycemic effects but also improved renal function in db/db mice. Histological examination of the kidney by immunohistochemistry indicated that EPE can improve kidney function by ameliorating glomerular morphological damage following glomerular injury; alleviating proteinuria by upregulating the expression of nephrin, a biomarker of early glomerular damage; and inhibiting glomerular expansion and tubular fibrosis. Moreover, the administration of EPE to db/db mice increased the expression levels of p- PKCα/t-PKCα but decreased the expression levels of VEGF and renal fibrosis biomarkers (TGF-β1, collagen IV, p-Smad2, p-Smad3, and Smad4), as shown by Western blot analyses. These results implied that EPE as a supplement has a protective effect against renal dysfunction through the amelioration of insulin resistance as well as the suppression of nephritis and fibrosis in a DN model.

Natural gas plays a significant role in Tunisia's energy mix. Tunisia imports 66% of natural gas (NG) from Algeria (ANG), and the rest is provided by local gas fields mainly Miskar gas (MNG). To counteract this deficit, the Power-to-Gas approach emerges as a promising solution, given Tunisia's abundant renewable energy resources. By blending green hydrogen into the NG network, it is possible to (i) address the current energy crisis, (ii) lower the carbon intensity of the gas grid, and (iii) encourage sector coupling through the use of various renewable energy sources. This study presents an overview of various interchangeability indicators and investigates accordingly the allowable ratios for hydrogen blending with two types of natural gas distributed in Tunisia (ANG and MNG). It also explores the impact of hydrogen injection on the energy content variation and various combustion parameters. The results confirm that both ANG and MNG can withstand a maximum hydrogen blend of up to 20%. The article concludes with recommendations for further experimental testing of the findings and emphasizes the need to look into infrastructure and safety requirements with regards to the Natural gas network in Tunisia. This research serves as a critical step towards harnessing the potential of green hydrogen in Tunisia.

Multimodal remote sensing data classification can enhance the model’s ability to distinguish land features through multimodal data fusion. In this context, how to help models understand the relationship between multimodal data and target tasks is the focus of researchers. Inspired by human feedback learning mechanisms, causal reasoning mechanisms, and knowledge induction mechanisms, this paper integrates causal learning, reinforcement learning, and meta learning into a unified remote sensing data classification framework and proposed the causal meta-reinforcement learning (CMRL). First, based on feedback learning mechanisms, we have overcome the limitations of traditional implicit optimization of fusion features and customized a reinforcement learning environment for multimodal remote sensing data classification tasks. Through feedback interactive learning between agents and the environment, we help them understand the complex relationships between multimodal data and labels, thereby achieving full mining of multimodal complementary information. Second, based on the causal inference mechanism we designed causal distribution prediction action, classification reward, and causal intervention reward, capturing pure causal factors in multimodal data and cutting off false statistical associations between non-causal factors and class labels. Finally, based on the knowledge induction mechanism, we designed a bi-layer optimization mechanism based on meta-learning. By constructing a meta training task and meta validation task simulation model in the generalization scenario of unseen data, we helped the model induce cross-task shared knowledge, thereby improving its generalization ability for unseen multimodal data. The experimental results on multiple sets of multimodal datasets show that the proposed method achieved state-of-the-art performance in multimodal remote sensing data classification tasks.

Since 2012, the northeast of Tunisia has been experiencing an emergence of dog rabies. Published data revealed that the disease is widespread in the north of Tunisia. Even with studies on rabies, lacking knowledge on the associated risk factors was highlighted. Therefore, we conducted a case-control study on dog rabies in northeast Tunisia to identify potential risk factors for dog rabies occurrence. The cases group (n=77) included positive dog rabies confirmed at the referral laboratory using Fluorescent Antibody Test (FAT) in 2014 and 2018. The controls group (n=77) involved all negative cases received at the laboratory and 15-days quarantine dogs that received a certificate of absence of rabies after the observation period. Univariate and multivariate logistic regression was conducted to explore the risk factors (age, sex, breed, confinement, vaccination status, presence of bites, owned or not and origin of dogs, sector, presence of rabies cases, and slaughterhouses, etc.…) related to the occurrence of rabies. The final logistic regression model revealed that unconfined dogs were almost twice as likely to be affected as confined dogs (OR=1.9; 95% CI: 1.17 to 3.27). The odds of rabies occurrence were 25 times higher in areas where rabies cases have been reported between 3 months and 1 year compared to the uninfected areas (25.7; 95% CI: 3.02-219.14). Similarly, the risk of rabies is significantly higher in dogs born in the home to the owner bitch (OR=2.41; 95% CI: 1.14-5.13). Living in areas with rabies cases in the last three months increases by 2.8 times the risk of getting rabies (2.8; 95% CI: 1.16-6.77). However, vaccination reduces by 1.6 times the risk of contracting rabies (0.6; 95% CI: 0.38-0.97). Our findings provide reliable data on dog rabies that will be very useful for decision-makers and could contribute to improving the ongoing national control program of rabies.

To estimate The potential inventory of natural gas hydrates in the Levant Basin we correlated the gas hydrate stability zone (GHSZ), modeled with locally estimated thermodynamic parameters, with seismic indicators of gas. Compilation of oceanographic measurements define the deep-water temperature and salinity to 13.8°C and 38.8‰ respectively, predicting the top GHSZ at a water depth of 1250±5 m. Assuming beneath the seafloor a hydrostatic pore-pressure, the water body salinity, and geothermal gradients ranging between 20 to 28.5°C/km, yields a useful first-order base-GHSZ approximation. Our model predicts that the entire northwestern half of the Levant Basin lies within the GHSZ, with a median thickness of ~150 m. High amplitude seismic reflectivity (HASR) imaged on an extensive 3D seismic dataset, consistently correlates with verified active seafloor gas seepage and is pervasively distributed across the deep-sea fan of the Nile within the Levant. Two main trends observed for the distribution of HASR are suggested to represent: (1) shallow gas and possibly hydrates, within buried channel-lobe systems 25 to 100 m beneath the seafloor; and (2) a regionally discontinuous bottom simulating reflection (BSR) broadly matching the modeled base GHSZ. We therefore estimate the potential methane hydrates reserve within the Levant Basin at ~4 Tcf.

In arid and semi-arid regions like Tunisia, irrigation water is typically saline, posing a soil and crop salinization risk and yield reduction. This research aims to study the combined effects of soil matric and osmotic potential stresses on tomato root water uptake. Plants were grown in pot and field experiments in loamy-clay soils and were irrigated with three different irrigation water qualities: 0, 3.5, and 7 dS/m. The Hydrus-1D model was used to simulate the combined dynamics of subsurface soil water and salts. Successful calibration and validation of the model against measured water and salt profiles enabled the examination of the combined effects of osmotic and matric potential stresses on root water uptake. Relative yields, indirectly estimated from actual and potential transpiration, indicated that the multiplicative stress response model effectively simulated measured yields and the impact of saline water irrigation on crop yields. The gradual salinization of the root zone further evidenced this effect. The scenario considering a temperature increase of 2°C had no significant impact on crop yields in the pot and field experiments.

The shoulder region has the highest incidence of acute injuries in the sport of surfing. Little is known about the strength profile at the shoulder in a surfing cohort. The primary aim of this study was to establish the reliability of a rotator cuff strength testing procedure for surfers with a secondary aim of providing a profile of internal (IR) and external rotation (ER) strength in a competitive surfing cohort. Shoulder IR and ER isometric strength was measured using a hand-held dynamometer in 13 competitive surfers. Intra-class coefficient values ranged from 0.97 to 0.98 for intra rater reliability and were lower for inter rater reliability ranging from 0.80 to 0.91. Normalised force (N/Kg) for IR strength was significantly greater than ER strength bilaterally (dominant, p= 0.007, non-dominant, p<0.001). No significant differences (p< 0.79) were found in IR strength (N/Kg) between the dominant and non-dominant arms. ER strength (N/Kg) was significantly weaker on the non-dominant arm compared with the dominant arm (p<0.02). The non-dominant arm ER to IR ratio (0.82 ± 0.15) was significantly (p=0.025) lower than the dominant (0.88 ± 0.14) The current procedure is reliable with the same clinician, results indicate musculature asymmetry specific to the external rotators.

Air quality and environmental fairness have always been an area of prime interest across the globe. The significance low-cost air quality sensing and practices spikes during the time of pan-demic and epidemics when the air becomes a threat to living beings especially human beings. The gradual innovation and enrichment in low-cost air quality sensing sensors, nodes or devices, and systems are exponentially increasing for the last three decades. This work reviews the major contributions in a) low-cost scalable air quality assessment; b) low-cost air quality sensors, sensing approaches and technologies; c) low-cost state-of-the-art gas sensors fabrication methods (MEMS and CMOS); d) low-cost gas sensors measurement configurations and assemblies; and e) low-cost air quality sensors calibration and testing systems. A systematic review of past work with a goal to assist end-users, public health facilities, state agencies, researchers, scientists and air quality protection agencies has been rendered in this work. Starting from sensors electrodes to IoT based mobile smart nodes; all have been introduced in this article.

Excretory-secretory products (ESPs) are the main research targets for investigating the hosts and helminths interaction. Parasitic worms can migrate to parasitic sites and avoid the host immune response by secreting this product. Angiostrongylus cantonensisis an important food-borne zoonotic parasite that causes severe neuropathological damage and symptoms, including eosinophilic meningitis or meningoencephalitis in humans. Benzaldehydes are organic compounds composed of a benzene ring and formyl substituents. This compound has anti-inflammatory and antioxidation properties. Previous studies showed that 3-hydroxybenzaldehyde (3-HBA) and 4-hydroxybenzaldehyde (4-HBA) can reduce apoptosis in A. cantonensis ESPs treated astrocytes. These results on the protective effect underlying benzaldehyde have primarily focused on cell survival. The study was designed to investigate the molecular mechanisms of endoplasmic reticulum stress (ER stress) and oxidative stress in astrocytes in A. cantonensis ESPs treated astrocytes and to evaluate the therapeutic consequent of 3-HBA and 4-HBA. First, we initially established the RNA-seq dataset in each group, including Normal, ESPs, ESPs+3-HBA, and ESPs+4-HBA. We also found that benzaldehyde (3-HBA and 4-HBA) can stimulate astrocytes to express ER stress-related molecules after ESP treatment. The level of oxidative stress could also be decreased in astrocytes by elevating antioxidant activity and reducing ROS generation. These results suggested that benzaldehyde may be a potential therapeutic compound for human angiostrongyliasis to support brain cell survival by inducing the expression levels of ER stress- and oxidative stress-related pathway.

The International Roughness Index (IRI) is the standard scale for evaluating road roughness in many countries in the world. The Taipei City government actively promotes a Road Smoothing Project and plans to complete the rehabilitation of the main and minor roads within its jurisdiction. This study aims to detect the road surface roughness in Taipei City and recommend appropriate IRI thresholds for road rehabilitation. A total of 171 asphalt concrete pavement sections in Taipei City with a total length of 803.49 km were analyzed and compared by IRI. The longitudinal profile of the detected road sections was measured using an inertial profiler. The statistical analysis showed that the IRI value prior to road leveling was mainly distributed between 5 and 8 m/km, while the IRI value after road leveling was mainly distributed between 3 and 4.5 m/km. This confirms that the implementation of the Road Smoothing Project has a significant effect on improving road smoothness. Moreover, based on the analysis results, it is recommended that the IRI threshold value for road rehabilitation in Taipei City be set at 4.50 m/km.

In this work, optimal consumption and investment strategies are derived for risk-averse investors under the 4/2 stochastic volatility class of models. We work under an expected utility (EUT) framework and consider a Constant Relative Risk Aversion (CRRA) investor, who might also be ambiguity-averse. The corresponding Hamilton-Jacobi-Bellman (HJB) and HJB-Isaacs (HJBI) equations are solved in closed-form for a subset of the parametric space and under some restrictions on the portfolio setting, for complete markets. Conditions for proper changes of measure and well defined solutions are provided. These are the first analytical solutions for the 4/2 stochastic volatility model and the embedded 3/2 model for the type of excess returns established in .

Poor therapeutic outcomes have been attributed to inter-individual and interethnic variability in cytochrome P450 (CYP450)-dependent metabolism and altered drug retention associated with P-glycoprotein (P-gp). An individualized pharmacotherapeutic approach would benefit the genetically diverse South African population. The study aim was to develop a validated, targeted, analytical method to quantify seven probe drugs and their metabolites in dried blood spots (DBS) using the Mitra™ volumetric absorptive micro-sampling device for blood collection. An Agilent liquid chromatography (LC) system coupled to a Sciex 4000 QTRAP tandem mass spectrometer (MS) was used for method optimization and validation. Targeted LC-MS/MS methods were validated according to ICH guidelines. The validated LC-MS/MS method met the required bioanalytical standards for specificity, sensitivity, linearity, accuracy, precision, carry-over, and stability. This study successfully validated the use of DBS, collected with the Mitra™ microsampling device, to measure expected probe drug and metabolite concentrations using the “Geneva phenotyping cocktail” for the purpose of simultaneous phenotyping of in vivo CYP450 metabolic activity of the CYP1A2, -2B6, -2C9, -2C19, -2D6, and -3A4 enzymes, and P-gp transport activity. However, statistical analysis using Bland-Altman plots showed that not all analytes exhibited linear distribution pharmacokinetics between DBS and plasma, which influenced the predicted vs real plasma concentrations based on measurements in a DBS matrix. These findings were attributed to the blood-to-plasma concentration ratio, the physicochemical properties and stability of the analytes, and the extraction efficiency of the Mitra™ sampler. More research is required before DBS sampling can be substituted for conventional plasma sampling

This paper reviews the requirements for the production, quality, and quality assurance of solid recovered fuels (SRF) that are increasingly used for the substitution of fossil fuels in the indus-trial utilities. The economical, technological and environmental aspects should be considered before using SRF as an alternative fuel. In general, the most important factors determining the commercial production of SRF referred to the calorific values and their available amounts adopted in the starting materials. Furthermore, the low-melting impurities and undesired constituents/elements, including chlorine, sulfur, potassium and sodium, may pose negative impacts on air pollutant emission and slagging & fouling in the process utilities. In this regard, the vent emitted from the industrial utilities must comply with the effluent standards of station-ary sources like particulate, sulfur oxides, nitrogen oxides, heavy metals (e.g., lead, cadmium, and mercury) and dioxins. For these reasons, this work will summarize the legal or regulatory requirements under development in Asian countries (i.e., Japan, South Korea, and Taiwan) and European Union (EU). Finally, the outlook of solid recovered fuel (SRF) in the waste manage-ment and industrial sectors will be addressed to echo the sustainable development goals (SDGs).

A typhoon-induced storm surge is considered one of the most severe coastal disasters in Taiwan. However, the combination of the storm surge and the astronomical tide called the storm tide can actually cause extreme flooding in coastal areas. This study implemented a two-dimensional hydrodynamic model to account for the interaction between tides and storm surges on the coast of Taiwan. The model was validated with observed water levels at Sauo Fish Port, Hualien Port, and Chenggong Fish Port under different historical typhoon events. The model results are in reasonable agreement with the measured data. The validated model was then used to evaluate the effects of the typhoon's intensity, bathymetric change, and the combination of the typhoon’s intensity and bathymetric change on the maximum storm tide and its distribution along the east coast of Taiwan. The results indicated that the maximum storm tide rises to 1.92 m under a typhoon with an intensity of a 100-year return period. The maximum storm tide increased from a baseline of 1.26 m to 2.63 m for a 90% bathymetric rise at Sauo Fish Port under the conditions of Typhoon Jangmi (2008). The combination of the intensity of a typhoon with a 100-year return period and a 90% bathymetric rise will result in a maximum storm tide exceeding 4 m, 2 m, and 3 m at Sauo Fish Port, Hualien Port, and Chenggong Fish Port, respectively. We also found that the distribution of the maximum storm tide on the east coast of Taiwan can expand significantly subject to the bathymetric rise.

Background - Technological developments induced lifestyle changes and increase population physical inactivity. This change in lifestyle can affect the male-female morphological and physical fitness differences. The aim of this study is to determine and to compare the effect of sex differences in percentage of body fat on speed and endurance running performance. Methods - 72 male and 64 female students aged 20 to 23 years participated in this study. After assessing their morphological characteristics, running performances during 30 m and 400 m, and maximum aerobic velocity (MAV) and maximal oxygen consumption (VO2max) during a 20 m shuttle running test have been estimated for each subject. Male students were re-tested after being overweighed down with a weight equivalent to the mean differences in body fat recorded between the two sexes in the form of a loaded worn vest. Results – Male presented a percentage of fat mass (17.2 ±2%) significantly (p <0.001) lower than that of women subject (25.0 ±2.5%). Running performances during 30 m and 400 m, MAV and VO2max were significantly (p<0.001) better in males. During the weighted condition, male performances during 30 m and 400 m, MAV and VO2max were attenuated by 6.89%, 14.16%, 6.48% and 10.07%, respectively but remain significantly better than those of female students. Conclusion - The persistence of sex differences after overweighting male students indicates that body fat could be responsible for ≈ 50 to 70% of the observed differences between sexes performances during short and long sprints, and 20 m shuttle running test.

Modern agent-based models (ABM) and other simulation models require evaluation and testing of many different parameters. Managing that testing for large scale parameter sweeps (grid searches) as well as storing simulation data requires multiple, potentially customizable steps that may vary across simulations. Furthermore, parameter testing, processing, and analysis are slowed if simulation and processing jobs cannot be shared across teammates or computational resources. While high-performance computing (HPC) has become increasingly available, models can often be tested faster through the use of multiple computers and HPC resources. To address these issues, we created the Distributed Automated Parameter Testing (DAPT) Python package. By hosting parameters in an online (and often free) "database", multiple individuals can run parameter sets simultaneously in a distributed fashion, enabling ad hoc crowdsourcing of computational power. Combining this with a flexible, scriptable tool set, teams can evaluate models and assess their underlying hypotheses quickly. Here we describe DAPT and provide an example demonstrating its use.

Tumour necrosis factor-α is a key mediator of inflammation in rheumatoid arthritis its discovery led to the development of highly successful anti-TNF therapy. Subsequently, other biologic drugs targeting immune pathways, namely interleukin-6 blockade, B cell depletion, and T cell co-stimulation blockade, have been developed. Not all patients respond to a biologic drug leading to a knowledge gap between biologic therapies available and the confident prediction of response. So far, genetic studies have failed to uncover clinically informative biomarkers to predict response. Given that the targets of biologics are immune pathways, immunological study has become all the more pertinent. Furthermore, advances in single cell technology have enabled the characterisation of many leucocyte subsets. Studying the blood immunophenotype may therefore define biomarker profiles relevant to each individual patient’s disease and treatment outcome. This review summarises our current understanding of how immune biomarkers might be able to predict treatment response to biologic drugs.

The genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment were used to test a polygenic selection model. Average frequencies of alleles with positive effect (polygenic scores or PS) were compared across populations (N=26) using data from 1000 Genomes. The PS of 161 GWAS significant SNPs in a recent meta-analysis was highly correlated to population IQ (r=0.863) and to the polygenic score of four alleles independently associated with general cognitive ability. High correlations with PISA scores for a subsample were observed.SNP p value predicted correlation to population IQ and factors from the two previous GWAS (r= -.25). Factor analysis produced similar estimates of selection pressure for educational attainment across the three datasets. Polygenic and factor scores computed using the top 20 significant SNPs showed very high correlation to population IQ (r=0.88; 0.9). Similar findings were obtained using 52 populations from another database (ALFRED). The results together constitute a replication of preliminary findings and provide strong evidence for recent diversifying polygenic selection on educational attainment and underlying cognitive ability.

The morphological and compositional complexities of keratinized components make feathers ingenious skin appendages adapted to diverse ecological needs. Frizzling feathers, characterized by their distinct curling phenotypes, offer a unique model to explore the intricate morphogenesis in developing a keratin-based bioarchitecture over a wide range of morphospace. Here, we investigated the heterogeneous allocation of α- and β-keratins in flight feather shafts of homozygous and heterozygous frizzle chickens by analyzing the medulla-cortex integrations using quantitative morphology characterizations across scales. Our results reveal intriguing construction of frizzling feather shaft through modified medulla development, leading to a perturbed balance of the internal biomechanics and, therefore, introducing the inherent natural frizzling compared to those from wild-type chickens. We elucidate how the localized developmental suppression of the α-keratin in the medulla interferes with the growth of the hierarchical keratin organization by changing the internal stress in the frizzling feather shaft. This research not only offers insights into the morphogenetic origin of the inherent bending of frizzling feathers but also facilitates our in-depth understanding of the developmental strategies toward the diverse integuments adapted for ecological needs.

Along with the familiar Rossby–Haurwitz waves, two-dimensional flows on the surface of a rotating sphere in the regime of zonostrophic turbulence harbour another class of waves known as zonons. Zonons are wave packets produced by energetic large-scale Rossby–Haurwitz wave modes `enslaving’ other wave modes. They propagate westward with the phase speed of the enslaving modes. Zonons can be visualized as enslaving modes’ `ringing’ in the enslaved ones with the frequencies of the former, the property that renders zonons non-dispersive. Zonons reside in high-shear regions confined between the opposing zonal jets yet they are mainly attached to westward jets and sustained by the ensuing barotropic instability. They exchange energy with the mean flow while preserving their identity in a fully turbulent environment, a feature characteristic of solitary waves. The goal of this study is to deepen our understanding of zonons’ physics using direct numerical simulations, a weakly non-linear theory, and asymptotic analysis, and ascertain that zonons are indeed isomorphic to solitary waves in the Korteweg - de Vries framework. Having this isomorphism established, the analysis is extended to eddies detected in the atmospheres of Jupiter and Saturn based upon the observed mean zonal velocity profiles and earlier findings that circulations on both planets obey the regime of zonostrophic macroturbulence. Not only the analysis confirms that many eddies and eddy trains on both giant planets indeed possess properties of zonons, but the theory also correctly predicts latitudinal bands that confine zonal trajectories of the eddies.

There is a current worldwide outbreak of a new type of coronavirus (2019-nCoV), which originated from China and has now spread to 17 other countries. Governments are under increase pressure to stop the outbreak spiraling into a global health emergency. At this stage, preparedness, transparency and sharing of information are crucial to risk assessments and beginning outbreak control activities. This information should include reports from outbreak sites, and from laboratories supporting the investigation. This paper aggregates and consolidates the virology, epidemiology, clinical management strategies from both English and Chinese literature, official news channels and other official government documents. In addition, by fitting the number of infections with a single-term exponential model, we report that the infection is spreading at an exponential rate, with a doubling period of 1.8 days.

Consumption is thus fundamentally related to sustainably because every decision pertaining to what to buy, what quantity the buy, how many to consume, or how to dispose of things has a direct influence on the natural world and the generations to come, and the overall impact of every single the customer's purchase is disastrous. A framework-based systematic literature review (SLR) was conducted to better comprehend the body of research on digital innovation and sustainability driving consumer behavior. This was done in order to acquire a deeper understanding of the studies that have already been done in this area. to provide (i) a comprehensive review of the current research landscape and (ii) a rich roadmap for future research. This study evaluated the literature especially in terms of theory, context, traits, and methodology. A total of 107 research articles published between 2013 and 2022 were found using scientific methods in the Scopus database. The findings showed that most research appears to have employed qualitative methodologies and was grounded in the setting of China and Italy. This review could help scholars better grasp the relationship between digital innovation and sustainability, opening the door for additional study and advancement in the field. Additionally, by extending the literature study and emphasizing the elements that can improve digital innovation and sustainability, practitioners will be given a better overall understanding of how to approach the problem.

Plant roots host various microorganisms around and inside their roots, known as the root microbiome. To become healthy and productive, plants should keep under surveillance niches around the roots to recognize disease-causing microbes and similarly exploit the services of beneficial microorganisms in nutrient acquisition, stress mitigation and growth promotion. Here we presented the communication strategies between plant roots and root-associated microbes in improving plant growth and yield. Understanding how plant root and root-associated microbes communicate is vital in designing ecofriendly strategies for targeted disease suppression and improved plant growth that will help in sustainable agriculture.

Sodium-glucose co-transporter 2 (SGLT2) inhibitors, originally used for diabetes mellitus, are gaining more popularity for other indications owing to their positive cardiovascular and renal effects. Initially, SGLT2 inhibitors were shown to reduce heart failure (HF) hospitalization and improve cardiovascular outcomes in patients with type 2 diabetes. Later, SGLT2 inhibitors were evaluated in patients with HF with reduced ejection fraction (HFREF) and had beneficial effects independent of the presence of diabetes. Recently, reduction in cardiovascular outcomes were also observed in patients with HF with preserved ejection fraction (HFPEF). SGLT2 inhibitors also reduced renal outcomes in patients with chronic kidney disease. Overall, these drugs have an excellent safety profile with a negligible risk of genitourinary tract infections and ketoacidosis. In this review, we discuss the current data regarding SGLT2 inhibitors in special populations including acute myocardial infarction, acute HF, right ventricular (RV) failure, patients with left ventricular assist device (LVAD), and patients with type1 diabetes. We also discuss the potential mechanisms behind the cardiovascular benefits of these drugs.