Background: Twitter is a major tool for communication in emergencies such as natural disasters. This online social network allows the user to produce content, and it is not designed exclusively for news releases, as opposed to other service providers. Aim: The aim of this study is to investigate Twitter uses in natural disasters and pandemics. Methods: The included studies reported the role of Twitter in natural disasters. The studies that report in settings other than the natural disasters (such as man-made disasters) and other social media were excluded. Electronic databases for a comprehensive literature search including MEDLINE, Web of Science, CINAHL, PsycINFO, Cochrane Register of Controlled Trials (CENTRAL) and EMBASE were used to identify the records that match the mentioned inclusion criteria published till May 2020. The study characteristics were extracted from the qualified studies including year of publication, findings, and geographical location of the study conduct. A narrative synthesis for this literature review was used. Results: The search identified 822 articles of which 780 articles were removed, 256 were not available, 311 papers were not relevant, 16 were duplicated articles, and 197 were non-related to the emergencies. 45 articles met the selection criteria and were included in the review. eleven themes were found in the narrative synthesis including early warning, disseminating information and misinformation, advocacy, personal gains, assessment, various roles of organizations, public mood, geographical analysis, charity, using influencers, and trust. Conclusions: It is recommended that influential individuals be identified in each country and community before disasters occur so that the necessary information can be disseminated in response to disasters. Preventing the spread of misinformation is one of the most important issues in times of disaster, especially pandemics. Disseminating accurate, transparent, and prompt information from relief organizations and governments can help. Also, analyzing Twitter data can be a good source for understanding the mental state of the community, estimating the number of injured people, estimating the points affected by natural disasters, and modeling the prevalence of epidemics. Therefore, various groups such as politicians, the government, non-governmental organizations, aid workers, and the health system can use this information to plan and implement interventions.

The Ministry of Health (MOH) in the Kingdom of Saudi Arabia (KSA) established a National School-based Screening Program (NSBSP) for health screening of school-going children. Students from specific grades were systematically screened for several health problems including obesity, visual and auditory problems, dental cavities, scoliosis, and attention-deficit/hyperactivity disorder (ADHD). This cross-sectional study aimed to determine the prevalence of these health problems among primary school students based on secondary data obtained from the NSBSP. We included 444,259 screened school children from the 1st and 4th grades of 50% of the selected schools (both private and public) across the KSA during the academic year 2018-2019. Among them, the most prevalent health problems identified were dental cavities (38.7%), eye refractory errors (10.9%), and overweight and obesity (10.5%); the less prevalent problems included ADHD (2.81%), auditory problems (0.6%), and scoliosis (0.48%). A greater prevalence of most health problems was observed in girls than boys. The NSBSP successfully aided the detection of health conditions with high and low prevalence among primary school students in the KSA, and thus, identification of health problems of specific concern. Implementation of effective school health services for the prevention, early detection, diagnosis, and treatment of these health problems is imperative.

Schistosomiasis, a crippling ailment that afflicts over 220 million people worldwide. Yet or up till now, there is no vaccine for schistosomiasis, and chemotherapy relies heavily on a single drug, the praziquantel. The present study was undertaken to investigate the therapeutic effect of Monophosphoryl Lipid A (MPLA) as an adjuvant in soluble egg antigen (SEA) vaccinated mice against the deleterious pathological impacts induced in hepatic tissues of mice by Schistosoma mansoni infection. In addition, to study the associated parasitological, immunological and biochemical parameters. Parasitological parameters showed that intraperitoneal injection of MPLA into SEA-vaccinated and S. mansoni-infected mice was effective to a significant degree in reducing the worm and egg burden, granuloma count and diameter as well as the total area of infection in their livers versus SEA-untreated but infected ones. In addition, MPLA showed ameliorative action on the elevated liver oxidative stress marker, including malondialdehyde (MDA) and decrease in the level of the antioxidant enzymes, reduced glutathione (GSH) and catalase (CAT) which may have a role in the liver damage and fibrosis due to S. mansoni infection. In conclusion, treatment with MPLA has multi-functions in attenuating the deleterious impacts of S. mansoni infection in mice livers. Its effects are mediated through a reduction of ova count, worm burden, granuloma diameter and amelioration of antioxidant defense systems, and liver function biomarkers.

A contrasting empirical evaluation will be provided with the aim of suggesting that the reductionist approach results in experiments that are not reproducible.

Metal 3D printing technology is a promising manufacturing method, especially in the case of complex shapes. The quality of the printed product is still a challenging issue for mechanical applications. The anisotropy of the microstructure, imperfections, and residual stress are some of the issues that diminish the mechanical properties of the printed sample. The simulation could be used to investigate some technical details, and this research has tried to computationally study the metal 3D printing of austenitic stainless steel to address austenite microstructure and local yield strength. Two computational codes were developed in Visual basics 2015 to simulate the local heating/cooling curve and subsequent austenite microstructure. A stochastic computational code was developed to simulate austenite grain morphology based on calculated thermal history. Then Hall-Pitch equation was used to estimate the yield strength of the printed sample. These codes were used to simulate the effect of temperature of the printer’s chamber on microstructure and subsequent yield strength. The austenite grain topology is more columnar at a lower temperature. The percentage of the equiaxed zone will be increased at a higher chamber’s temperature. Almost a fully equiaxed austenite microstructure will be achieved at 800 C chamber’s temperature, but the last printed layer, which is columnar and can be removed by cutting then. The estimated local austenite grain size and the local yield strength in the equiaxed regions are in the range of 15 to 30 μm and 270 to 330 MPa at 800 C temperature of printer’s chamber, respectively.

The powder bed fusion (PBF) metal additive manufacturing (AM) method uses an energy source like a laser to melt the metal powders. The laser can locally melt the metal powders and creates a solid structure as it moves. The complexity of the heat distribution in laser PBF metal AM is one of the main features that need to be accurately addressed and understood to design and manage an optimized printing process. In this research, the dependency of local thermal rates and gradients on print after solidification (in the heat-affected zone) was numerically simulated and studied to provide information for designing the print process. The simulation results were validated by independent experimental results. The simulation shows that the local thermal rates are higher at higher laser power and scan speed. Also, the local thermal gradients increase if the laser power increases. The effect of scan speed on the thermal gradients is opposite during heating versus cooling times. Increasing the scan speed increases the local thermal gradients in the cooling times and decreases the local thermal gradients during the heating. In addition, these simulation results could be used in artificial intelligence (AI) and machine learning for developing digital additive manufacturing.

Computer simulation relies on well-defined experimental supported theories, models, and numerical methods. Computer simulation is an alternative to fill the gaps where the experiment is pricy or limited in engineering. Computer simulation is a high-fidelity computational technique that can work as an engineering innovation tool to try imaginative ideas beyond the available technologies. The accuracy of current computer simulation results is reliable enough to accelerate innovation for new materials and mechanical technologies without experimental validation. So, we may need to urge relying on computer simulation results without any experimental validation to accelerate engineering innovations. In addition, using high-fidelity computer simulation for engineering innovation acceleration without validation will be promoted if it is credited as a new classification. This subject and a related justification's classification in engineering have been discussed.

The Sol Hamed (SH) area is a part of the Arabian-Nubian Shield (ANS) ophiolites occurred within Onib-Sol Hamed suture zone in the southern Eastern Desert of Egypt. The ophiolitic assemblages in this area are represented by serpentinite, metagabbro and arc assemblages represented by metavolcanics. They later intruded by gabbroes and granites. Geochemically, the compatible trace elements (Cr=2426–2709 ppm, Ni=1657–2377 ppm and Co=117–167 ppm) enrichment in SH serpentinites indicate derivation from a depleted mantle peridotite source. They show affinity to the typical metamorphic peridotites. The normative compositions reflect harzburgitic mantle source. Their Al2O3 contents (0.05–1.02 wt. %) are akin to oceanic and active margin peridotites and Pan-African serpentinites. The Cr and TiO2 contents indicate supra-subduction zone (SSZ) environment. Their Al2O3/SiO2 and MgO/SiO2 ratios support the SSZ affinity and are similar to ANS peridotites with fore-arc setting. Moreover, their Al2O3 and CaO depletion is typical of fore-arc peridotites. Structurally, the area represents four deformational events can be well-known in the Neoproterozoic rocks (D1, D2, D3 and D4); D1: E–W thrust faults and related E–W (F1) folds; D2: NW–SE thrust faults and related NW–SE (F2) folds were formed; D3: conjugate NNW-trending sinistral and NNE-trending dextral transpression, as well as N–trending tight folds (F3) and D4: is E–W dextral strike-slip and dip-slip normal faults striking NNW–SSE to N–S and E–W may be related to Red Sea rifting. There are major three fault sets affected the area. The first set trend mainly NE-SW and is manifested in the volcanic-sedimentary assemblage and Gabal SH and have important role in mineralization. The second set trend E-W affecting all the basement rocks and disturbs the first fault set. The third set trend N-S affected all the rock units. Magnesite mineralization in SH serpentinites is cryptocrystalline formed due to hydrothermal alteration of the serpentinite host rocks. It is occur as snow-white veins and stock-works. These characteristics are typical of Kraubath type magnesite deposits. Gold mineralization is confined to malachite-bearing quartz veins, smoky quartz veins and alteration zones. Malachite-bearing quartz veins trending NW-SE cut through gabbroic rocks and exhibit mylonitic structure. They are fractured containing malachite and disseminated sulfide minerals. Smoky quartz veins trending NE-SW with SE steeply dipping intrude the meta-andesite. They are intensively sheared containing iron oxides in the fissures. The gold grades increase with arsenopyrite occurrences. On the other hand, the barren quartz veins are nearly vertical with E-W directions. Alteration zones with NW-SE trend and nearly vertical dip intrude metagabbros and metavolcanics. Hematite, limonite, goethite and fresh pyrite characterize these zones. They occur mainly neighboring the auriferous quartz veins.

The growth of solid particles during liquid phase sintering was modeled by the Cellular Automata method. The binary phase diagram and Fickian approach for the diffusion process were applied to simulate the chemical composition variation in liquid and solid phases during sintering. The Oswald-Ripening effect was considered during the dissolution of the solid phase in the liquid phase. It is used to define the probability of solid-phase dissolution by the liquid phase and develop the model to simulate the alloy with solid solubility. So, the microstructure could be modeled in the liquid phase sintering process.

Metal 3D printing technology is a promising manufacturing method. The quality of the printed product can pass for mechanical application, if the anisotropy of the microstructure, imperfections, deformation, and residual stress of the printed sample could be lower than the appropriate level or if they are fully illuminated. Thermal stress is one of the significant reasons for deformation in the 3D printed samples. Thermal stresses are the direct consequence of the local temperature gradient. In this research, the effect of the temperature printer’s chamber (from room temperature to 900 C) was studied on thermal stress and subsequent total deformation in the printed sample. The printed sample is a six-layers-printed walk, which could be considered as a building block of other complex shapes and give us inside about deformation. The computational results show a meaningful reduction in thermal stress and deformation at the higher temperature of the printer’s chamber. The lower final deformation of the printed sample is an important subject, especially for samples with complex shapes.

We present software on total energy calculation by quantum mechanics first principle method with a graphic user interface (GUI). Total energy calculation in this software is based on numerical analysis of time-dependent density functional (the used numerical method is finite difference time domain). QUMEC package has been equipped by common exchange-correlation energy terms with electron spin polarization calculation. With this package, users can calculate the total energy of the free particle, bulk materials, and materials with free surfaces at the atomic scale. The package is tested by several physical subjects, i.e., the surface energy of nano-LiCoO₂ and diffusion constant of lithium atoms in LiNi­_0.5Mn_1.5O₄.

This code provides computational facilities to simulate current versus time during the charging of Li-ion cells at desire constant voltage by considering multiscale physical phenomena. This code only considers a powder of active materials (at microscale or nanoscale) and a small part of electrolyte around it as a half cell. Then it is extended to a complete cell by applying correct boundary conditions. This code is very useful by modifying code parameters to understand the effect of the complex shape of active materials powder (surface area and powder size), kind of electrolyte, and the applied voltages on the charging response of Li-ion cell. As a summary, a microscale approach to the design of Li-ion cells has been provided via this code.

Owing to fascinating applications of ZnO in modern devices, it is interesting to explore its more features for future devices. Hence, herein, we have synthesized the high quality ZnO spherical nanoparticles (SNPs) through a facile green synthesis route and robust structural and biomedical studies are carried out. Hexagonal phase with 93.2% crystallinity was confirmed through XRD analysis. ZnO nanoparticles were tested for their bioactivities both in vivo (acute cytotoxicity test) and in vitro (Anti-cancer activities on liver (HepG2) and cervical (Hela) cancer cell lines, stimulatory/inhibitory effects on normal rat splenic cells and hemolytic effects on red blood cells). Results showed that ZnO SNPs has no cytotoxic effects on vital organ like liver and has no hemolytic action on red blood cells. ZnO SNPs showed inhibitory consequence on normal rat splenic cells growth at all tested concentrations. ZnO nanoparticles showed an inhibitory effect on HepG2 cell line. While showed stimulatory effect on Hela cell line. Current study presents the synthesized ZnO SNPs as highly applicable in bio-optoelectronics.

Nowadays, the human population is facing the third and may be the worst pandemic caused by human coronaviruses (CoVs). The virus was first reported in Wuhan, China on 31 December 2019 and spread within short time to almost all countries of the world. Genome analysis of the early virus isolates has revealed high similarity with SARS-CoV and hence the new virus was officially named SARS-CoV-2. Since CoVs have the largest genome among all RNA viruses, they can adapt many point mutation and recombination events; particularly in spike gene, that enable these viruses to rapidly change and evolve in nature. CoVs are known to cross the species boundaries by using different cellular receptors. SARS-CoV-2 is believed to originate in bats and transmitted to human being through an ill-defined intermediate host. In the current review, different aspects of SARS-CoV-2 biology and pathogenicity are discussed including virus genetics and evolution, spike protein and its role in evolution and adaptation to novel hosts, and virus transmission and persistence in nature. In addition, the immune response developed during SARS-CoV-2 infection is demonstrated with special reference to the interplay between immune cells and their role in disease progression. We believe that SARS-CoV-2 outbreak will not be the last and spillover of CoVs from bats will continue. Therefore, establishing intervention approaches to reduce the likelihood of future CoVs spillover from the natural reservoirs is a priority.

Animal-assisted pedagogy (AAP) is well known in classroom practice, but scientific evidence is still lacking. At the same time, the biggest challenge in education systems worldwide is the social in-tegration of students. In a pre-post design, 30 heterogeneous students (16f/14m) from four different school classes (grades 5-7) were interviewed (problem-centred interview) about their social inclu-sion and their social climate in class before and after being taught selected subjects with a school dog (of different breeds) for one school term. At the second measurement point, they were also asked about their perception of AAP. The data was analysed both qualitatively (Kuckartz) and in terms of the number of quotes on the main topics using MAXQDA analysis software. The presence of a dog in the classroom leads to an improved social climate and more social integration. In ad-dition, the perception of the other students and the teacher changes to a more positive and friendly image. Through AAP, a new social role is added to the classroom, where caring and bonding are prioritised. Social interaction and norms are influenced and sterotypical and individual roles can be changed. Therefore, AAP can be a key to promoting social inclusion in the school environment.

The physicochemical treatment/recovery techniques, including precipitation, membrane technology, solvent extraction, foam fractionation, adsorption, and aqueous two-phase systems, will be reviewed. The bio-treatment processes, based on microorganisms and/or enzymes consuming nutrients available in food-processing wastewater as low-cost substrates to produce valuable products, will be discussed in detail, including the production of microalga biomass in wastewater treatment systems. Finally, future research direction will be proposed to integrate the circular economy and develop integrated food processing wastewater management systems.

Alzheimer's disease (AD) is a progressive neurodegenerative brain disorder. One of the important therapeutic approaches of AD is the inhibition of β‐site APP cleaving enzyme‐1 (BACE1). This enzyme plays a central role in the synthesis of the pathogenic β-amyloid peptides (Aβ) in Alzheimer's disease. A group of potent BACE1 inhibitors with known x-ray structures (PDB ID 5i3X, 5i3Y, 5iE1, 5i3V, 5i3W, 4LC7, 3TPP) were studied by molecular dynamics simulation and binding energy calculation employing MM_GB(PB)SA. The calculated binding energies gave Kd values 0.139 µM, 1.39 nM, 4.39 mM, 24.3 nM, 1.39 mM, 29.13 mM and 193.07 nM, respectively. These inhibitors showed potent inhibitory activities in enzymatic and cell assays. The Kd values were compared with experimental values, the structures were discussed in view of the energy contributions to binding. Drug likeness of these inhibitors is also discussed. Accommodation of ligands in the catalytic site of BACE1 is discussed depending on the type of fragment involved in each structure. Molecular dynamics (MD) simulations and energy studies were used to explore the recognition of the selected BACE1 inhibitors by Asp 32, Asp228 and the hydrophobic flap. The results show that selective BACE1 inhibition may be due to the formation of strong electrostatic interactions with Asp32 and Asp228 and a large number of hydrogen bonds, π-π and Van der Waals interactions with the amino acid residues located inside the catalytic cavity. Interactions with the ligands show a similar binding mode with BACE1. These results help to rationalize the design of selective BACE1 inhibitors.

NDBs were fabricated from gum arabic (GA) and polyvinyl alcohol (PVA) in different ratios using novel techniques (casting, dehydration, and peeling). The GA/PVA blends were cast with a novel vibration-free horizontal flow (VFHF) technique, producing membranes free of air bubble defects with a homogenous texture, smooth surface, and constant thickness. The casting process was achieved on a self-electrostatic template (SET) made of poly-(methyl methacrylate), which made peeling the final product membranes easy due to its non-stick behavior. After settling of the cast membranous blind, sheets were dried using nanometric dehydration under a mild vacuum stream using a novel stratified nanodehydrator (SND) loaded with P2O5. After drying the TBM, the dry, smooth membranes were peeled easily without scratching defects. The physicochemical properties of the NDBs were investigated using FTIR, XRD, TGA, DTA, and AFM to ensure that the novel techniques did not distort the product quality. The NDBs retained their virgin characteristics, namely, their chemical functional groups (FTIR results), crystallinity index (XRD data), thermal stability (TGA and DTA), and ultrastructural features (surface roughness and permeability), as well as their microbial biodegradation ability. Comparing the two TBM’ s precursors, PVA had a higher crystallinity index (CI), more mass loss at higher temperatures, greater thermal stability due to higher heat resistance, and a higher clearance of surface roughness due to its large particle size (PS), as well as its higher permeability parameters, namely pore diameter (PD) and void volume (VV), than those for GA. Accordingly, increasing the PVA allocation in the bioplastic blends can enhance their properties except for mass loss, whereby increasing the GA allocation in the TBM blend reduces its mass loss at an elevated temperature. In addition, there is no statistical difference between the NDBs and ordinary air-dried NDBs in PS, PD, and VV, indicating that the novel procedures used did not distort their parent properties examined, as well as their ability for biodegradation. In comparison to control samples, the separated bacteria and fungus destroyed the NDBs. Pseudomonas spp. and Bacillus spp. were the two main strains of isolated bacteria, and Rhizobus spp. was the main fungus. The nanodehydration method gave the best solution for the prompt drying of water-based biopolymers free of manufacturing defects, with simple and easily acquired machinery required for the casting and peeling tasks, in addition to its wonderful biodegradation behavior when buried in wetted soil.

Ferric uptake regulation protein is a repressor protein which binds an AT rich region of DNA (the iron box). Fur binds as a dimer in a helix turn helix mode and it is activated by iron(II) and other divalent transition metal ions at elevated concentrations in a process to regulate the ion uptake. Each transition metal ion induces certain conformational changes to aid the Fur binding, both the N-terminal and C-terminal domains take part in binding to DNA in addition to His 88 and His 86 residues. The process is discussed in view of experimental reports. Fe(II), Mn(II) and Co(II) activate Fur to bind DNA experimentally but Zinc plays a structural role and does not activate Fur to bind DNA.

Rebar cages form the skeletal framework of reinforced concrete structural members. They comprise longitudinal and transverse reinforcing bars, usually connected by tie wires. Past studies have identified tie-wire connections as the "weak links" in large, prefabricated rebar cages, leading to their failure during site handling and construction stages. Recent research has explored the use of mechanical U-bolt connectors to bolster stability and safety of rebar cages while reducing their vulnerability and risk of failure. This paper presents a comprehensive experimental and numerical investigation of a new type of mechanical connector, referred to as "Cage Clamp", to enhance rebar cage stability and safety. Component-level experimental tests are conducted to determine the force-displacement response of Cage Clamp connectors for crossbar connections in different degrees of freedom. The results highlight the remarkable strength and stiffness of Cage Clamp connectors, significantly outperforming traditional tie-wire connections. Furthermore, full-scale experimental tests are performed on a circular underground pile-shaft rebar cage with Cage Clamp connectors to assess its behavior under various site handling conditions. The data obtained from these experiments are used to construct and refine detailed 3D finite element models of the rebar cages, capable of capturing the complex behavior of rebar cages with Cage Clamp connectors. Using the numerical model, a sensitivity analysis is performed to assess the effect of the number of Cage Clamps on the deflection and stability of the rebar cage. The findings show that using cage clamps to connect pick-up rebar with lateral reinforcement at every 8 to 10 feet is sufficient to ensure the stability of the cage during typical site handling conditions. The results of this study serve as a basis for establishing analysis, design, fabrication, and handling guidelines for rebar cages, contributing to safe and efficient construction practices.

We present theoretical designs of high performance optical filters in integrated silicon photonic nanowire resonators. We use mode interference in formed by zig-zag waveguide coupled Sagnac loop reflectors (ZWC-SLRs), tailored to achieve diverse filtering functions with good performance. These include compact bandpass filters with improved roll-off, optical analogues of Fano resonances with ultrahigh spectral extinction ratios (ERs) and slope rates, and resonance mode splitting with high ERs and low free spectral ranges. The analysis verifies the feasibility of multi-functional integrated photonic filters based on ZWC-SLR resonators for flexible spectral engineering in diverse applications.

Abstract: Educating healthcare workers (HCWs) to take action against monkeypox (mpox) is an important part of public health prevention efforts. The study aimed to assess the knowledge, attitudes, and willingness to vaccinate against mpox among HCWs in the Kurdistan Region of Iraq. This study utilized an online cross-sectional survey that was disseminated via Google Forms between November, 1, 2022 and January, 15, 2023, employing a convenience sampling method. The researchers utilized logistic regression to ascertain the factors associated with knowledge, attitude and willingness to vaccinate. A total of 637 HCWs were included in the analysis (ages ranged between 21 and 51 years old). The mean overall score and standard deviation of the knowledge, attitude, and willingness assessment on mpox were 8.18±3.37 out of (0–16), 3.40±1.37 out of (0–5), 2.41±1.25 out of (0–5), respectively. The multivariate logistic regression analysis showed that HCWs who heard about mpox before 2022 had a higher level of knowledge (AOR: 4.85; 95% CI: 2.81-8.36; p < 0.001). In addition, those who had less than 1 year of practice had a positive attitude about mpox (AOR: 0.35; 95% CI: 0.20-0.59; p < 0.01). Finally, none of the variable groups had the capacity to predict willingness to be vaccinated against mpox. The research revealed that HCWs exhibit a relatively low level of knowledge and attitude towards mpox, as well as a low level of willingness to receive mpox vaccinations. Further, there is an urgent need to increase their knowledge and attitude, as the success of efforts to control the global epidemic depends on them.

We propose and theoretically investigate integrated photonic filters based on coupled Sagnac loop reflectors (SLRs) formed by a self-coupled wire waveguide. By tailoring coherent mode interference in the device, three different filter functions are achieved, including Fano-like resonances, wavelength interleaving, and varied resonance mode splitting. For each function, the impact of device structural parameters is analyzed to facilitate optimized performance. Our results theoretically verify the proposed device as a compact multi-functional integrated photonic filter for flexible spectral shaping.

We theoretically investigate integrated photonic resonators formed by two mutually coupled Sagnac loop reflectors (MC-SLRs). Mode interference in the MC-SLR resonators is tailored to achieve versatile filter shapes with high performance, which enable flexible spectral engineering for diverse applications. By adjusting the reflectivity of the Sagnac loop reflectors (SLRs) as well as the coupling strength between different SLRs, we achieve optical analogues of Fano resonance with ultrahigh spectral slope rates, wavelength interleaving / non-blocking switching functions with significantly enhanced filtering flatness, and compact bandpass filters with improved roll-off. In our designs the requirements for practical applications are considered, together with detailed analyses of the impact of structural parameters and fabrication tolerances. These results highlight the strong potential of MC-SLR resonators as advanced multi-functional integrated photonic filters for flexible spectral engineering in optical communications systems.

This paper presents a novel adaptive fault-tolerant neural-based control design for wind turbines with unknown dynamic and unknown wind speed. By utilizing the barrier Lyapunov function in the analysis of the Lyapunov direct method, the constrained behavior of the system is provided in which the rotor speed, its variation and generated power remain in the desired bounds. In addition, input saturation is also considered in terms of smooth pitch actuator bounding. Furthermore, by utilizing a Nussbaum-type function in designing the control algorithm, the unpredictable wind speed variation is captured without requiring accurate wind speed measurement, observation or estimation. Moreover, with the proposed adaptive analytic algorithms, together with the use of radial basis function neural networks, a robust adaptive and fault-tolerant control scheme is developed without the need for precise information about the wind turbine model nor the pitch actuator faults. Additionally, the computational cost of the resultant control law is reduced by utilizing a dynamic surface control technique. The effectiveness of the developed design is verified using theoretical analysis tools and illustrated by numerical simulations on a high-fidelity wind turbine benchmark model with different fault scenarios. Comparison of the achieved results to the ones that can be obtained via an available industrial controller shows the advantages of the proposed scheme.

Numerous studies have established the link between ADHD and antisocial behavior, one of the most serious functional impairments caused by the disorder. However, research on protective factors that mitigate this link is still lacking. The Salutogenic Model of Health offers the “Sense of Coherence” (SOC), establishing that individuals who see their lives as logical, meaningful, and manageable are more resistant to various risk factors and diseases. The present study examines for the first time whether SOC is also a protective factor against ADHD-related different types of antisocial behaviors (severe/mild violent behavior, verbal violence, property crimes, public disorder, and drug abuse). 2260 participants aged 15-50 completed online questionnaires assessing the level of ADHD symptoms, antisocial behaviors, and SOC. An interaction between ADHD and SOC was found in predicting each type of antisocial behavior. The link between ADHD and antisocial behavior was significantly weaker for high than low SOC participants, regardless of age group. The current study found that people with high SOC are protected against the effect of ADHD on one of the most serious functional impairments, antisocial behavior. These findings suggest that SOC is a protective factor from the adverse effects of ADHD, justifying further prospective and intervention studies.

Appeals to governments for implementing basic income are contemporary. The theoretical backgrounds of the basic income notion, only prescribe transferring equal amounts to individuals irrespective of their specific attributes. However, the most recent basic income initiatives all around the world are attached to certain rules with regard to the attributes of the households. This approach is facing significant challenges to appropriately recognize the vulnerable groups. A possible alternative for setting rules with regard to the welfare attributes of the households is to employ artificial intelligent algorithms that can process unprecedented amounts of data. Can integrating machine learning change the future of basic income by perdition of vulnerable to future poverty households? In this paper, we utilize a multidimensional and longitudinal welfare data comprising one and a half million individual data and a Bayesian beliefs network approach to examine the feasibility of predicting households’ vulnerability to future poverty based on the existing households’ welfare attributes.

Background: ChatGPT is becoming a new reality. Where do we go from here? Objective: to show how we can distinguish ChatGPT-generated publications from counterparts produced by scientist. Methods:By means of a new algorithm, called xFakeBibs, we show the significant difference between ChatGPT-generated fake publications and real publications. Specifically, we triggered ChatGPT to generate 100 publications that were related to Alzheimer’s disease and comorbidity. Using TF-IDF, using the real publications, we constructed a training network of bigrams comprised of 100 publications. Using 10-folds of 100 publications each, we also 10 calibrating networks to derive lower/upper bounds for classifying articles as real or fake. The final step was to test xFakeBibs against each of the ChatGPT-generated articles and predict its class. The algorithm successfully assigned the POSITIVE label for real ones and NEGATIVE for fake ones. Results: When comparing the bigrams of the training set against all the other 10 calibrating folds, we found that the similarities fluctuated between (19%-21%). On the other hand, the mere bigram similarity from the ChatGPT was only (8%). Additionally, when testing how the various bigrams generated from the calibrating 10-folds against ChatGPT we found that all 10 calibrating folds contributed (51%-70%) of new bigrams, while ChatGPT contributed only 23%, which is less than 50% of any of the other 10 calibrating folds. The final classification results using the xFakeBibs set a lower/upper bound of (21.96-24.93) number of new edges to the training mode without contributing new nodes. Using this calibration range, the algorithm predicted 98 of the 100 publications as fake, while 2 articles failed the test and were classified as real publications. Conclusions: This work provided clear evidence of how to distinguish, in bulk ChatGPT-generated fake publications from real publications. Also, we also introduced an algorithmic approach that detected fake articles with a high degree of accuracy. However, it remains challenging to detect all fake records. ChatGPT may seem to be a useful tool, but it certainly presents a threat to our authentic knowledge and real science. This work is indeed a step in the right direction to counter fake science and misinformation.

Lack of water resources in Iran, especially in recent years, has faced the agricultural sector as the most important consumer of water resources, with serious challenges. In Iran, the agricultural sector accounted for more than 90% of water consumption. However, the focus on domestic production and self-sufficiency policy in staples (wheat, barley, maize and rice) has been emphasized in general agriculture's policy. This study was conducted to estimate the imported virtual water from the imports of basic products in Iran using defined indicators during 1961-2013. Also this study investigated the possibility of achieving self-sufficiency due to the limited water resources in Iran. The results of this study showed with the increase in cereal imports, virtual water imports from 0.28 billion cubic meters in 1961 increased to 17.6 billion cubic meters in 2013 and on average about 60% of virtual water imports in strategic products is related to wheat imports during the past 53 years. Other products in cereal (barley, maize and rice) are also indicative of the general trend of increasing imports of virtual water in development plans. The estimated long-run elasticity of virtual water imports in the cereal group compared with the country's water resources also showed that with a one percent reduction in renewable water resources of the country, the virtual water import in the main cereal group will increase equivalent to 2.89 percent and the determination coefficient more than 90 percent also confirms this negative relationship. According to this result and the emphasis on the fact that renewable water resources per capita in the country is falling increasingly, it cannot be expected that domestic production could compensate for the imports of the cereal group and virtual water imports with current technology, without increasing the water productivity and without additional harm to water resources.

This paper presents the results of an experimental investigation about target detecting with passive sonar in Persian Gulf. Detecting propagated sounds in the water is one of the basic challenges of the researchers in sonar field. This challenge will be complex in shallow water (like Persian Gulf) and noise less vessels. Generally, in passive sonar the targets are detected by sonar equation (with constant threshold) which increase the detection error in shallow water. Purpose of this study is proposed a new method for detecting targets in passive sonars using adaptive threshold. In this method, target signal (sound) is processed in time and frequency domain. For classifying, Bayesian classification is used and prior distribution is estimated by Maximum Likelihood algorithm. Finally, target was detected by combining the detection points in both domains using LMS adaptive filter. Results of this paper has showed that proposed method has improved true detection rate about 27% compare other the best detection method.

Ion channels are integral membrane proteins that facilitate the movement of ions across cell membranes, playing a key role in a range of biological processes. The high cost and time required for wet lab experiments to characterize ion channels has spurred the development of computational methods for this purpose. In our previous work, we demonstrated the effectiveness of protein language models for ion channel prediction, using a logistic regression classifier to distinguish ion channels from non-ion channels (TooT-BERT-C) and transporters from non-transporters (TooT-BERT-T). In this study, we build upon this approach by using a combination of classical machine learning classifiers and a Convolutional Neural Network (CNN) with fine-tuned representations from ProtBERT, ProtBERT-BFD, and MembraneBERT to discriminate ion channels from non-ion channels. The results of our experiments demonstrate that TooT-BERT-CNN-C, a combination of the representations from ProtBERT-BFD and a CNN, outperforms existing state-of-the-art methods for predicting ion channels, with a Matthews Correlation Coefficient (MCC) of 0.86 and an accuracy of 98.35% on an independent test set.

Lake Manzala, the largest of the northern Delta lakes of Egypt, has a great economic importance as a major natural resource of fish and salt. Unfortunately, the lake is suffering from the high inputs of pollutants from industrial, domestic, and agricultural sources. The present study aims to develop the proposed water quality management scenarios to assess and control lake pollution, the pollution sources as well as the pollution spread from the lake to the connected Mediterranean Sea. To apply study methodology, the work tasks divided into two main parts, the first part involved in modelling the lake environments by using Delft3D-WAQ hydrodynamic and water quality model to study the current status and predict the dynamic state of the Lake. This model was calibrated and validated by using various water quality datasets to simulate different scenarios. In the second part, the required lake water quality improvement scenarios were developed to solve the lake water quality problems. The study results showed that the first three developed scenarios that focusing on treatment drain effluent using primary, secondary treatment and surface wetland techniques respectively have a limited efficiency on lake water quality improvement. While the fourth scenario that involved on using biological biofilm techniques can improve lake water quality parameters. Moreover, the fifth scenario that proposed adding a new artificial inlet has a limitation due to the noted increases in lake salinity levels. The sixth scenario that proposed a diversion of some drains can improve lake water quality parameters but it can lead to a decrease in Lake water level. From water quality view point, the last scenario that applying a combination biological biofilm activated technique and also adding a new artificial inlet at northern lake region can represent the optimum scenario. Hopefully, this research will preserve the lake environment and contribute to the benefit of the man health as well. This approach could be extended to the hydrodynamic studies in similar large, shallow lakes anywhere in the world.

The cell stress response is an essential system present in every cell for responding and adapting to extracellular environmental stimulations. A major program for stress response is the heat shock factor (HSF)–heat shock protein (HSP) system that maintains proteostasis in cells and promotes cancer progression. However, less is known about how the cell stress response is regulated by alternative transcription factors. Here, we show that the SCAN domain-containing transcription factors (SCAN-TFs) are involved in repressing the stress response in cancer. SCAND1 and SCAND2 are SCAN-TFs that can hetero-oligomerize with SCAN-zinc finger transcription factors, such as MZF1(ZSCAN6), for accessing DNA and transcriptionally co-repressing target genes. We found that heat stress induced the expression of both SCAND1 and MZF1(ZSCAN6) bound to HSP90 gene promoter regions in prostate cancer cells. SCAND1 and MZF1 blocked the heat shock responsiveness of HSP90 in prostate cancer cells. Gene expression of SCAND2, SCAND1 and MZF1 was negatively correlated with HSP90 expression in patients-derived prostate adenocarcinoma. MZF1 and SCAND2 were more highly expressed in paired normal tissues than in tumor tissues in several cancer types. High expression of SCAND2, SCAND1 and MZF1 correlated with enhanced prognoses of pancreatic cancer and head and neck cancers. Additionally, high expression of SCAND2 was correlated with better prognoses of lung adenocarcinoma and sarcoma. In contrast, high expression of HSP90AA1 correlated with poorer prognoses in several cancer types. These data suggest that the stress-inducible SCAN-TFs can function as a feedback system, suppressing excessive stress response and inhibiting cancers.

Although lithium-ion batteries have extensively been used in various applications because of their high energy capacity, fracture and failure, the by-products of large strains and stresses caused by fast charging and discharging need yet to be addressed. The size effects on the mechanical behavior of the nano-sized structures are significant; however, the classical elasticity theory may not consider such effects. On the other hand, surface stress theory, as a robust and potential theory, is suitable in considering size effects in nano-scale structures. Therefore, in this paper, in order to involve the surface stress effects on the fracture behavior of Li-ion batteries, the following steps are taken. Firstly, a phase-field model is used to determine the evolution of the concentration profile. Subsequently, the stress distribution is obtained by using the surface stress theory combined with chemical equations for a planar electrode. Afterward, by using the weight function method for an edge crack in the plate, the stress intensity factor is derived for all time steps and possible crack lengths during the process. It is found that with increasing phase boundary thickness parameter or decreasing phase-separation phenomenon, the surface mechanics parameters become more influential. Furthermore, in the presence of positive surface stress, the diffusion-induced stress distribution decreases, which in turn reduces the stress intensity factor. In addition, in this paper, the two states of surface stress are compared either for elastic or total strain. Concerning stresses and concentrations, the results indicate a big difference at the beginning of the deintercalation process showing, in particular, 2% for stresses, but the differences diminish gradually.

A series of supported CuO-based nanoparticle catalysts were prepared by impregnation method and used for the synthesis of glycerol carbonate from glycerol and CO2 in the presence of 2-cyanopyridine as a dehydrant and DMF as a solvent. The effects of supports (activated alumina, silicon dioxide, graphene oxide, graphene, and activated carbon), CuO loading amount, calcination temperature, and reaction parameters on the catalytic activity of catalyst were investigated in detail. XRD, FTIR, SEM, BET, and CO2-TPD were used for the characterization of the prepared catalysts. It is found that CuO/Al2O3 shows a higher catalytic activity, which depends on the CuO loading amount and calcination temperature. The surface area and amount of basic sites of the catalyst exhibit crucial effect on the catalytic activity of CuO/Al2O3. Furthermore, there is a synergistic effect between the catalyst and 2-cyanopyridine that the former has higher activation ability for glycerol and the latter acts not only as a dehydrant, but also as a promoter for CO2 activation. Recycling experiments reveal that this catalyst can be reused at least five cycles without any inactivation. Based on the experiment results and FTIR characterization, a possible reaction mechanism for the carbonylation of glycerol and CO2 is proposed.

This study inscribes itself in the global discussion about the issue of environmental awareness, beliefs and behaviors. Here we focus on the role that cultural differences and scientific media dieting play in explaining heterogeneities in students' awareness and expectations about the two environmental issues of deforestation and species (plant and animal) extinction in the Middle East and North America. To this end, we use the cross-sectional survey data of the OECD's Program for International Student Assessment (PISA) 2015, along with seemingly unrelated Bi-variate ordered Probit modeling techniques. The results show that compared to their North American Counterparts, students' in the Middle East are 14.2% less aware of, and 14.5% less optimistic about the issue of deforestation, while 38.9% less aware of, and 59.0% less optimistic about the issue of species extinction. In addition, we found that science club attendance and broad science reading in books are the two most effective communication media for raising students awareness about the two environmental issues. In fact, every one level increase in students' awareness is found to raise their optimism by 20.4% for the issue of deforestation, and 15.0% for the issue of plant and animal extinction. Therefore raising young people environmental awareness and optimism through proper communication strategies, could be invaluable for achieving an economic development in line with our need to preserve the natural environment and ecosystem services for generations to come.

Olive mill wastewater (OMW) has serious environmental problems considering its high organic matter, especially its phenolic compounds. The OMW application in crop protection is an alternative environmentally eco-friendly method reducing the chemicals pesticides impact on human health and environment. The present work aimed to study the antifungal activity of fresh and stored OMW and its ethyl acetate extract against phytopathogenic fungi: Syncephalastrum racemosum (S. racemosum), Paramyrothecium roridum (P. roridum), Fusarium oxysporum (F. oxysporum) and Verticilium dahlia (V. dahlia). The OMW was stored at 25 and 45 °C for 3 months. Fresh and stored OMW were used non-sterile, sterile and centrifuged. Phenolic and flavonoid compounds were extracted and identified by HPLC analysis. High inhibition of studied fungi was shown by fresh OMW and its derivative compounds, while OMW storage, sterilization, and centrifugation increased mycelium growth of studied fungi, especially S. racemosum that showed a relative resistance against stored OMW effect and its ethyl acetate extract. Under storage conditions, some phenolic and flavonoid compounds disappeared (resorcinol and vanillic acid), while the concentration of other compounds increased (gallic acid, chlorogenic acid and quercetin). This work highlighted the ability to use fresh OMW as a bio-agent to protect plants from fungi diseases.

This paper investigates the role of English language proficiency (ELP) as a measure of cultural integration on U.S. immigrant families’ economic integration, as measured by annual earnings, and health care market integration, as captured by annual medical care spending. Bayesian Markov Chain Monte Carlo (MCMC) estimation of a mixed bivariate ordered probit (MBOP) model of annual earnings and medical care spending is conducted using a nationally representative pooled cross-sectional sample data from the U.S. National Health Interview Surveys (NHIS). The results reveal that limited English proficiency is associated with lower marginal earnings propensities (-$44.83, -$50.66, and -$56.97), and higher marginal medical care spending propensities ($8.09, $6.09, and $4.32) for each of the three decreasing levels of ELP. Furthermore, we find a small yet statistically significant positive 7.2% correlation between immigrant families’ annual earnings and medical care spending propensities. Therefore investing to raise immigrants’ families ELP in the U.S. would not only contribute to more effective socio-economic integration, but also strengthen the U.S. workforce and economy for decades to come.

The dynamics of suspended sediment involves inherent non-linearity and complexity as a result of the presence of both spatial variability of the basin characteristics and temporal climatic patterns. As a result of this complexity, the conventional sediment rating curve (SRC) and other empirical methods produce inaccurate predictions. Deep neural networks (DNNs) have emerged as one of the advanced modeling techniques capable of addressing inherent non-linearity in hydrological processes over the last few decades. DNN algorithms are used to perform predictive analysis and investigate the interdependencies among the most pivotal water quantity and quality parameters i.e., discharge, suspended sediment concentration (SSC), and turbidity. In this study, the Long short-term memory (LSTM) algorithm of DNNs is used to model the discharge-suspended sediment relationship for the Stony Clove Creek. The simulations were run using primary data on discharge, SSC and turbidity. For the development of the DNN models and examining the effects of input vectors, combinations of different input vectors (namely discharge, and SSC) for the current and previous days are considered. Furthermore, a suitable modelling approach with an appropriate model input structure is suggested based on model performance indices for the training and testing phases. The performance of developed models is assessed using statistical indices such as root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). Statistically, the performance of DNN-based models in simulating the daily SSC performed well with observed sediment concentration series data. The study demonstrates the suitability of the DNN approach for simulation and estimation of daily SSC, opening up new research avenues for applying hybrid soft computing models in hydrology.

Background: Measuring vital signs has always been a central task for Critical Care Nurse´s (CCNs) and Registered Nurse Anesthetist`s (RNAs) providing care in the post-anesthesia care unit (PACU) and a prerequisite for their decision-making. Properly measuring and understanding pediatric vital signs is a challenge in younger pediatric patients up to 36 months old. Purpose: gain a greater understanding of CCNs' and RNAs' perceptions of decision-making regarding the level of vital sign monitoring children require in the PACU. Method: A qualitative study design involving the critical-incident technique was used. Interviews were carried out with a purposeful sample of CCNs and RNAs (n=17) from two different hospitals. Findings: According to the nurses' experience, grounds for decisions concerning children’s need of vital-sign monitoring were both adequate and inadequate. They used actions to adjust the monitoring of vital signs to optimise conditions for assessment and the prospects of a safe recovery for the child. Conclusions: Evidence-based care and safety are compromised when the technology has limitations and is not adapted for children. Its use means that experience and clinical assessment are relied on to a greater extent. This not only makes experience important for reliable assessment, but also means that greater risks are accepted.

: We report on a direct correlation between macroscale structural variations and the gas sorption capacities of an ion gel. Here, we chose 1-ethyl-3-methylimidazolium bis(trifluoromethyl sulfonyl)imide ([Emim][TF2N]) and poly(vinylidene fluoride)-co-hexafluoropropylene (PVDF-HFP) as the ionic liquid and host polymer, respectively. The CO2 sorption in the thin films of IL-polymer was measured by the gravimetric method. The results of our experiment show that the trend of CO2 uptake of these mixtures is non-linearly correlated with the content of IL. Here we highlight the variation in the molecular structure of the polymers is the main reason behind the observed trend. The presented data suggest the possibility of using the composition of mixtures containing IL and polymers to realize a synergistic gain for gas sorption in these mixtures.

Given the Income enabling nature of education as stipulated by human capital theory, it can be postulated that “ceteris paribus”, households with formally educated heads experience less food insecurity and monetary poverty than those with uneducated heads. We test this claim in the case of Burkina Faso, using the 2014 National Survey on Households Living Conditions, along with semi-parametric modeling techniques. In its design the study uses households “willingness and ability” to spend annually on food consumption a per-capita amount above the food poverty line of 102,040 CFA Franc to characterize “household food security”, and households “unwillingness or inability” to spend above the overall poverty line of 153,530 CFA Franc to characterize “monetary poverty”. In addition, the study relies not only on single equation multivariate probit and logit specifications, but also on both fully parametric and semi-parametric bivariate probit representations of food insecurity and monetary poverty. The results show that relaxing the linearity and independence assumptions through joint semi-parametric bivariate modeling captures better the true effects of heads of households’ educational attainment on households' food insecurity and monetary poverty. In fact, compared to households headed by someone with no education, those headed by someone with a primary, secondary or higher education are respectively 19.8% , 49.7% and 118.9% less likely to experience food insecurity, and respectively 40.1%, 77.0% and 172.3% less likely to experience monetary poverty in Burkina Faso. In addition, the experience of food insecurity and monetary poverty are highly correlated at 92.7%, suggesting that educational policies that alleviate poverty in Burkina Faso should also impact positively food security in the country.

Relying on Random Utility Theory (RUT) as the guiding mechanism for the Data Generating Process (DGP), this paper uses households consumption choices on cooking fuel, drinking water, and sanitation from the 2014 United States Agency for International Development's (USAID) Demographic and Health Survey (DHS) data on Burkina Faso, to characterize and investigate the inter-linkages between health consciousness and environmental consciousness, and their relationship with wealth in a low income country context. We achieve this by specifying sequentially three econometric modeling frameworks: the first one being independent binary probit (IBP) models to describe each choice process, followed by a fully parametric trivariate probit (FPTP) model to account for choice dependency, and finally by a semi-parametric trivariate probit (SPTP) model to further relax the linearity assumption. Based on the Akaike Information criteria (AIC) and the estimated Trivariate model correlation coefficients, the SPTP framework is found to be the best specification for describing the observed consumption behaviors. The results show that increased wealth level raises households health and environmental consciousness, while leaving the relative preference ordering over the elements in the household consumption basket unchanged.

The incidence of Type 1 Diabetes (T1D) in the Arab world, particularly, oil and gas rich Gulf Cooperative Council (GCC) countries has more than doubled in the last twenty years. Therefore, there is a dire need for careful systematic familial cohort studies, especially in high-risk populations. Several immunogenetic factors affect the pathogenesis of the disease. Genes in the human leukocyte antigen (HLA) account for the major genetic susceptibility to the disease. The triggering agents initiate disease onset by destruction of pancreatic β-cells. The autoantibodies against glutamic acid decarboxylase (GADA), insulinoma antigen-2 (IA-2A), insulin (IAA), and zinc transporter-8 (ZnT-8A) comprise the most reliable biomarkers for T1D in both children and adults. Although three of the GCC countries, namely Kuwait, Saudi Arabia and Qatar are among the top 10 countries with high incidence rate of T1D, no proper diagnostic and prediction tools were applied in the region. Understanding the disease sequelae in a homogenous gene pool with high consanguinity in the GCC could help solve the challenges in understanding pathogenesis, as well as hasten the prevention of T1D. Arab states must incorporate T1D predictive and intervention policies on a war-footing basis to minimize the burden of this serious disease.

In this work, pure TiO₂ and nano-magnetic of Fe₃O₄/TiO₂ were synthesized for degradation of 2,4-dichlorophenol (2, 4-DCP) as an organic pollutant. A range of analytical techniques including XRD, DRS, FESEM, and VSM were employed to reveal the crystal structure, morphology and property of the nanocomposite. The XRD results showed the prepared samples including 100% anatase phase. We obtained the band gap energy 2.9 and 2.8 eV for pure TiO₂ and Fe₃O₄/TiO₂ respectively. VSM results demonstrate that easy, fast separation and redispersion of Fe₃O₄/TiO₂ sample can be realized. We obtained 62% and 31% degradation of 2,4-DCP in the presence of Fe₃O₄/TiO₂ and pure TiO₂ under visible light respectively.

Recent astronomical observations with respect to measurements in distant supernovas, cosmic microwave background and weak gravitational lensing confirm that the Universe is undergoing a phase of accelerated expansion and it has been proposed that this cosmological behavior is caused by a hypothetical dark energy which has a strong negative pressure that allows explain the expanding universe. Several theoretical ideas and models related dark the energy includes the cosmological constant, quintessence, Chaplygin gas, braneworld and tachyonic scalar fields. In this paper, we have obtained new relativistic stellar configurations considering an anisotropic fluid distribution with a charge distribution which could represents a potential model of a dark energy star. In order to investigate the effect of a quadratic equation of state in this anisotropic model we specify particular forms for the gravitational potential that allow solving the Einstein-Maxwell field equations. For these new solutions we checked that the radial pressure, metric coefficients, energy density, anisotropy factor, charge density , mass function are well defined and are regular in the interior of the star. The solutions found can be used in the development of dark energy stars models satisfying all physical acceptability conditions but the causality condition and strong energy condition are violated. We expect that these models have multiple applications in astrophysics and cosmology.

Solar cell layers technology has achieved global standing in the solar cell layers deposition process, and it covers the innovative methods and techniques in significant applications. Recent solar cell layers technology has an advanced interest in a refined approach to enhance performance and highlights the importance of recent proficient procedures for manufacturing. For example, the application is used to search for novel materials for solar cells' layers to clarify the current energy crisis. The technological process and various types of solar cells depend on climate change. Among them, layers of solar cells and silicon wafer solar cells are very encouraging. Solar cell layers technology has led to solar cells being a more reasonable active option in design and production. The productivities facilitated by new solar cells still need to be enhanced for the various processes involved in the additional enhancement from Copper Indium Gallium Selenide (CIGS) microfilms to solar cell crystal structure dye-sensitized solar cells. The hydrophobic coating works as an anti-dust coating, enhancing efficiency and decreasing the cost of cleaning solar cells. In Saudi Arabia Majmaah City, most solar projects are in dry regions, where the dusty weather reduces solar cell efficiency. Therefore, combining these two properties and applying an anti-reflective and superhydrophobic coating will increase solar cell efficiency by 20%. Solar cells' crystal structure results are substituted with layers or new materials to balance environmental impact and toxic nature.

Oil revenues and external debt might have stimulated economic growth in the oil exporting countries via investment in capital projects. The paper estimated economic growth on oil revenues and external debt after controlling public investment and population growth over the period 1970-2015. Following the confirmation of the order of integration, our analysis is based on autoregressive distributed lag bound testing to cointegration approach. The key findings are that oil revenues and public investment contributes to Nigeria’s economic growth. However, our findings also indicate that external debt and population growth retards growth. The study suggests that minimizing fiscal deficits and unnecessarily foreign loans by creating tax avenues through the development of the non-oil sectors would reduce the dependency syndrome on a single commodity (oil) in Nigeria.

Extracellular vesicles (EV), including exosomes and microvesicles, are released from various cells and alter recipient cell phenotypes and fates by their biomolecules. Here we review current knowledge about tumor EVs and how they prompt malignant cell communication with tumor-associated cells, such as cancer-associated fibroblasts, tumor endothelial cells, and immune cells. We delineate the major pathways and molecular players that influence each step of cancer initiation, progression, and resistance. Of note, cancer exosomes involve immunosuppression by tumor-associated macrophages, myeloid-derived suppressor cells, and regulatory T cells. Moreover, tumor exosomes can induce the apoptosis of killer T cells and immune checkpoint of dendritic cells and attenuate natural killer cells. An in-depth understanding of EV biology is essential to ensure the clinical development of exosome/EV-based therapeutic products, which will be of benefit to exosome manipulation in cancer management.

Background: Understanding the distribution of HPV types in cervical cancer cases is crucial for evaluating the effectiveness of HPV screening and vaccination in reducing cervical cancer burden. This study aimed to assess genotype prevalence among 178 cervical cancer cases detected during a 20-year screening period in Northern Norway and compare the potential efficacy of HPV vaccines in preventing cervical cancer. Methods: A total of 181 formalin-fixed paraffin-embedded (FFPE) tissue samples from women diagnosed with cervical cancer between 1995 and 2015 in Troms and Finnmark, Norway, were analyzed using a 45-type HPV DNA test. The results were compared to a 7-type HPV mRNA test targeting oncogenic types included in the nonavalent HPV vaccine. Results: Invalid HPV test results were observed in 1.7% (3/181) of the samples and were subsequently excluded from further analysis. Among the remaining cases, 92.7% (165/178) tested positive for HPV using any test combination. HPV DNA was detected in 159 cases (89.3%), while HPV mRNA was detected in 149 cases (83.7%). The most prevalent HPV types were 16 and 18, responsible for 70.8% of the cases, with the nonavalent vaccine types accounting for 86.6% of cases. HPV 35 was identified in eight cases (4.5%). Conclusion: The bivalent/quadrivalent HPV vaccines have the potential to prevent 76.4% (126/165) of HPV-positive cervical cancer cases, while the nonavalent vaccine could prevent 93.3% (154/165) of cases. Tailoring screening strategies to target HPV types with the highest oncogenic potential may improve cervical cancer detection and enable targeted interventions for high-risk individuals. The use of a 7-type HPV mRNA test holds promises as an advantageous approach.

Background: A plethora of data supports HPV-based screening to be the preferred strategy for cervical cancer prevention. The shift to a more sensitive firstline test brings the need of effective triage up for discussion. Currently, most algorithms apply cytology as triage of HPV-DNA positive women. This study compared the performance of a 7-type HPV-mRNA test to cytology. Methods: From 2019-01-01, until 2021-12-31, cervical samples from 58,029 women were examined at the University Hospital of North Norway. 30.5% (17,684/58,029) fulfilled the criteria for HPV-DNA primary screening. All positive samples were triaged by cytology and followed-up according to national guidelines through 2022. Additionally, a 7-type HPV-mRNA test was applied. Study endpoint was histologically confirmed high grade lesion (CIN2+). Results: 5.6% (990/17,684) had positive HPV-DNA test, 97.2% (962/990) with valid HPV-mRNA results. 55.5% (534/962) had abnormal cytology (ASC-US+) and 35.1% (338/962) had positive HPV-mRNA test. 13.9% (134/962) had CIN2+. Sensitivity (CIN2+) of cytology versus the HPV-mRNA test was 76.1% (102/134)) versus 73.1% (98/134)), p=0.67. The specificity was 47.8% (396/828) versus 71.0% (588/624), p<0.001. PPV was 19.1% (102/534) and 29.0% (98/338), p<0.001 respectively. The number of colposcopies per CIN2+ detected by cytology and HPV-mRNA test was 5.2 and 3.1. Conclusion: The 7-type HPV mRNA test was significant more specific than cervical cytology in triage of HPV-DNA positive women. Using this biomarker as threshold for colposcopy may better balance the benefits and harms of screening.

Motivated for improving the efficiency and reliability of wind turbine energy conversion, this paper presents an advanced control design that enhances the power regulation efficiency and re-liability. The constrained behaviour of the wind turbine is taken into account, by using the barrier Lyapunov function in the analysis of the Lyapunov direct method. This, consequently, guarantees that the generated power remains within the desired bounds to satisfy the grid power demand. Moreover, a Nussbaum-type function is utilized in the control scheme, to cope with the unpre-dictable wind speed. This eliminates the need for accurate wind speed measurement or estimation. Furthermore, via properly designed adaptive laws, a robust actuator fault-tolerant capability is integrated into the scheme, handling the model uncertainty. Numerical simulations are performed on a high-fidelity wind turbine benchmark model, under different fault scenarios, to verify the effectiveness of the developed design. Also, a Monte-Carlo analysis is exploited for the evaluation of the reliability and robustness characteristics against the model-reality mismatch, measurement errors and disturbance effects.

Long-term health consequences are influenced by circumstances that occur during pregnancy. The confluence of the maternal and fetal circulations occurs at the placenta, which is the first or-gan to develop. Placental pathology can provide an accurate diagnosis of inflammation inside the amniotic sac. The pathological alterations of preterm placentas provide evidence for the causes of numerous perinatal pathologies, including spontaneous preterm births. This retrospec-tive study aimed to re-examine placentas regarded as normal by the Obstetrics and Gynecology Department in our institution so that grading and staging of any evident inflammatory response could be evaluated and associated with baby gender. Eighty-four full-term placentas were col-lected after delivery. Placentas that were considered normal and were not sent to the histo-pathology department were taken. Morphological examination of fresh placenta was conducted. Full thicknesses of placenta samples were taken from central and marginal regions of placental disc. Fetal and maternal inflammatory responses syndrome were assessed. Villitis of unknown etiology (VUE) and chronic deciduitis also were evaluated in the placenta. Immunohistochemis-try (IHC) was also performed to evaluate patterns of inflammation in the placenta using an-ti-CD8 and anti-CD68 antibodies. The correlation between the silent pathologies and clinical complications or involvement of developing fetal inflammatory response syndrome was meas-ured. In this study, seventeen (20%) maternal inflammatory samples and ten (12%) fetal inflam-matory samples showed inflammatory responses. The frequency of chronic deciduitis and villi-tis of unknown etiology was more remarkable among Saudi pregnant women than the previ-ously reported findings in the literature of placental pathology. The prevalence of fetal and ma-ternal inflammatory response was greater in the placentas of mothers of males than in placentas of female mothers. Grading placental inflammation usually predict the degree of maternal an-ti-fetal cellular rejection. Fetal inflammatory response syndrome usually goes unnoticed in Sau-di Arabia. There are differences in the inflammatory response in the placenta based on the sex of the newborn. Increasing the number of placental samples that must be sent for microscopic in-spection may be preferable due to their significance in identifying the causes of chronic disor-ders.

This paper intends to discuss SSLs, how they work, their advantages and drawbacks. It will end with the author’s thoughts on the efficacy of the system and whether it is a viable solution for the majority of network security problems or if those drawbacks prevent that.

This article takes an approach to explaining the behavioral manifestations of the decision making in US companies’ offer of health insurance that is grounded not only on their cost minimizing behavior, but also in a humanness dimension based on the African concept of Ubuntu. In this way, we define an Ubuntu based Random Utility modeling framework, describing the choice process as a tripartite decision making, and implemented using a nationally representative random sample of 1,061 American companies from the Dunn and Bradstreet Business data, supplied by Survey Sampling International to the Associated Press-NORC Center for Public Affairs Research. The results from the three sequentially implemented specifications showed that the relationship between management culture and health plan offering strategy is dependent on other relevant co-variates, which when left out, leads to the problem of omitted variables bias. However, when all variables are included but assumed to enter the relationship exogenously, this results in management culture not having any statistically significant effect on companies' decisions about scope of health plan offering. When the exogeneity assumption is relaxed through a recursively Bivariate Probit model, the system of two equations produces a highly significant management culture effect. In fact, in this later case we see that companies with groups and formal committee management culture are 1.58 times less likely to choose a multiple plan strategy over a single plan strategy, hence failing to show the more wholesome plan offering that would theoretically prevail under Ubuntu style management.

In this paper, we present some new models for anisotropic compact stars within the framework of 5-dimensional Einstein-Gauss-Bonnet (EGB) gravity with a linear and nonlinear equation of state considering a metric potential proposed for Thirukkanesh and Ragel (2012) and generalized for Malaver (2014). The new obtained models satisfy all physical requirements of a physically reasonable stellar object. Variables as energy density, radial pressure and the anisotropy are dependent of the values of the Gauss-Bonnet coupling constant

In this paper, we found a new model for compact star with charged anisotropic matter distribution considering an extended version of the Chaplygin equation of state. We specify a particular form of the metric potential Z(x) that allows us to solve the Einstein-Maxwell field equations. The obtained model satisfies all physical properties expected in a realistic star such that the expressions for the radial pressure, energy density, metric coefficients, measure of anisotropy and the mass are fully well defined and are regular in the interior of star. The solution obtained in this work can have multiple applications in astrophysics and cosmology.

In this paper, we found new classes of exact models to the Einstein-Maxwell system of equations which describe the internal structure of a compact star made of strange matter considering the equation of state proposed by Rocha, Bernardo, de Avellar and Horvath in 2019. It has been assumed that this matter is composed of equal number of up, down and strange quarks and a small amount of electrons required to reaching the charge neutrality. If this hypothesis is correct, the neutron stars could be strange stars or hybrid stars with a thin crust of nuclei where the temperatures and pressures are capable of converting hadronic matter into this new stable phase of quarks. We have chosen a particular form of gravitational potential Z(x) that depends on an adjustable parameter related to degree of anisotropy of the models and the new solutions can be written in terms of elementary and polynomial functions. The obtained models satisfy all physical features expected in a realistic star and the expressions for mass, density and stellar radius are comparable with the experimental results.

In order to meet the needs of an increasingly complex research landscape, researchers engage in “collaborative prosumption” through open data sharing and reuse. Although significant gains have been achieved in this regards because of growing requirements from funding agencies, governments and journals, the question of how reuse of openly available data for new research contribute to sustainability is yet to be appropriately addressed in the literature. Therefore, relying on a three stage stratified clustered random sampling of the Journal of Applied Econometrics data archive (JAEDA), the present research provides a case study of the value of research data recycling for sustainable research and economic development. More specifically our analysis show that reformatting from wide to long format, openly shared equity price index data on eleven European countries’ extracted from JAEDA, and augmented with country level geospatial Meta data, provides a new basis for interesting descriptive analytics and spatio-temporal econometric modeling and inference. Given the ever-increasing volume of openly available research data, our study provides a first-hand insight on open data reuse, which should benefit all stakeholders in the research community, as they seek sustainable solutions for scientific productivity and progress.

Relying on the United Arab Emirates (UAE) extract from the cross-national data sample on the environmental affection and cognition of adolescent students, and seemingly unrelated bivariate weighted ordered probit regression modeling, this study adopts a national perspective to investigate the determinants of adolescent students' awareness and expectations about nuclear power technology and nuclear waste in the UAE. Identification of model parameters is achieved through maximum simulated likelihood estimation. The findings show that each level increase in UAE youth's interest in ecosystem services and sustainability raises their awareness of nuclear electrical power and nuclear waste by 13.5%, while reducing by 2.4% their level of optimism towards the technology. Furthermore, we find significant heterogeneity in youth awareness and expectations about nuclear power technology across the seven Emirates. Accounting for all other factors (including interest in ecosystem services), UAE youth awareness about nuclear electrical power technology appears to not significantly influence their expectations about the evolution of this technology for the next 20 years. Given that the UAE first nuclear power plant ``Barakah'' is scheduled to start operations end of 2019 beginning 2020, and the typical long life-span of nuclear wastes, our results provide important insights for developing sustainable nuclear energy policies and establishing a long-term nuclear energy program in the UAE.

This paper models the factors explaining households members economic well-being in Burkina Faso, with a focus on the relative influence of gender inequality in literacy status. It does so, using data from the 2014 survey on household living conditions and a semi-parametric bi-variate sample selection modeling approach. This approach compared to the classic Heckman two-step estimator is methodologically innovative because it deals simultaneously with non-random sample selection using conventional systems of two equations, non-linear covariates' effects using spline approach, and the non-normal bivariate distribution using copula functions. The graphical results from the Lorenz curves combined with the numerical Atkinson and Gini coefficients suggest that inequality in overall per-capita consumption spending among households headed by literates is higher than that of their illiterate counterparts in 2009 and 2014. However, independently of the head of household’s literacy status, the level of inequality in total economic well-being decreased from 2009 to 2014. Using the poverty indices of Watts, Sen, Foster ( alpha= 1)) we found that poverty among households headed by literates is lower than that of their illiterates counterparts for both years, although overall poverty decreased nationally between 2009 and 2014. The results also show that although the gender inequality in literacy status does not translate into inequalities in non-food wellness, it does however for food-wellness as female headed households have 38.9% less per-capita food consumption spending than their men counterparts. Combining both food and non-food consumption spending, total economic well-being also seems to exhibit gender inequality as female headed households now have relatively 26.7% less combined per-capita consumption spending.

This study uses data from the pilot project "Community Monitoring for Better Health and Education Services Delivery Project'' in Burkina Faso, to model the joint impact of generic essential drugs and nursing staff supplies constraints on access to primary health care in the country. The results show that statistical endogeneity of supply side constraints are present in the standard univariate probit specification of access to care. However, when accounted for, the resulting Trivariate Probit model shows that although shortages of generic essential drugs supply do not seem to constitute a significant barrier to access in Burkina Faso, shortages in nursing staff supply do. In fact, the likelihood of primary care access is reduced by 85.5% among those that reported having experienced a shortage in nursing staff, while paradoxically increasing by 60.3% among those that reported having experienced a shortage in generic essential drugs. A potential explanation for these findings is that overall the health care needs in the three surveyed regions in the country were more linked to primary health care services consumption from nurses, although further research would be important to clearly elucidate the position of health goods such as generic essential drugs.

This review aims at studying the phytochemistry and biological activities of some selected Apocynaceae plants. Eleven members of this family were reviewed for their phytochemistry and biological activities. Interestingly, the commonly isolated compounds reported from Mondia whitei (Hook.f.) Skeels, Secondatia floribunda A. DC, Carissa carandas, Tabernaemontana divaricate, Nerium oleander, Wrightia tinctoria, T. divaricate, Alstonia scholaris, Carrisa spinarum Linn, Thevetia peruviana and Caralluma lasiantha were triterpenoids, flavonoids, phytosterols, cardiac glycosides and lignans. All of them exhibited remarkable biological activities, mostly similar to each other. This review provides a detailed insight into the pharmacological activities of these selected members of this family.

New antibacterial agents are needed to overcome the increasing number of infectious diseases caused by pathogenic microorganisms due to the emergence of multi-drug resistant strains. In this context, halogens, especially Iodine is known since ages for its antimicrobial activity. Therefore, especially triiodides encapsulated in organometallic complexes can be helpful as new agents against microorganisms. The aims of this work was to study the biological activity of [Na(12-Crown-4)₂]I₃ against gram positive Streptococcus pyogenes, Streptococcus faecalis, the spore forming bacteria Bacillus subtilis and gram negative bacteria Escherichia coli, Proteus mirabilis, Pseudomonas aeruginosa and Klebsiella pneumoniae, as well as the yeast Candida albicans. The antimicrobial and antifungal activities of the triiodide were determined by zone of inhibition plate studies. [Na(12-Crown-4)₂]I₃ exhibited potent antimicrobial activity on gram positive Streptochocci and the yeast C. albicans. Furthermore, the gram negative bacteria P. aeruginosa and K. pneumoniae were less effectively inhibited, while E. coli and P. mirabilis proved to be even resistant.

This research contributes to the overall debate on education for sustainable development (ESD) by shed- ding lights on the contributing role of formal education to the contemporaneous dynamics of literacy, labor market participation and poverty reduction in Africa, with a focus on Burkina Faso. The study uses a semi-parametric recursive trivariate probit modeling approach, and data from the 2014 National Survey on Household Living Conditions in Burkina Faso. The results show that the embraced systemic approach in this analysis is statistically signi cant as shown by the 95% con dence intervals on the three correlation coeffcients in the model. Furthermore, education does improve literacy skills, however improved literacy skills in itself does not guaranty active labor market participation in Burkina Faso. Active labor market participation seem to be affected by labor market rates of return, and individual reservation wage (or income). When labor market rate of return is short of high literacy skilled individuals' reservation wage, then the natural response is a choice of inactivity in the labor market, by the later group. Simultaneously however, it is found that active labor market participation leads to poverty reduction; therefore, in addition to new industrial policies for structural transformation of the economy, policy makers in Burkina Faso should consider education and minimum wage reforms to give highly literate household members the incentive to be active in the labor market.

This paper investigates the effects of Inter-generational co-residence on health care market, and labor market outcomes, to see whether or not living under the same roof with at least one parent matters in health care market, and labor market behaviors in post-Affordable-Care Act (ACA) USA. The adopted analytical strategy involves not only looking at the gender differences in co-residence, and its effects on outcomes in the two markets, but also accounting for co-residence endogeneity following the recent literature. Unlike the recent literature that relies on instrumental variables methods, this study adopts a switching regression approach, defining inter-generational co-residence as an endogenous selection process using a binary probit equation, and modeled jointly with the extensive margins and intensive margins in the two markets. This novel approach results in a recursive trivariate probit model for each market, and estimated using penalized maximum likelihood methods. The results suggest that ACA by reorganizing the US health care market, seems to have reduced significantly disparities in health care access among males and females based on race, region of residence, place of birth, and citizenship. However not only do we observe significant differences in inter-generational co-residence status between males and females, we also find significant inequalities in the effects of co-residence on health care market, and labor market outcomes. In fact, co-residence is found to increase health care expenditure by 56.7% among females, while this figure increases to 74.2% among males. In addition co-residing individuals, while spending 69.7% more on health care annually are 1.22 times more likely to access health care, but 31% less likely to use health care intensively during the year. In the labor market, co-residence is found to reduce significantly hours of weekly labor supplied by 41% for females, and 55.6% for males. Furthermore co-residing individuals, while not significantly different in their likelihood of labor force participation, are 1.52 times less likely to work full time once they decide to participate, and also spend about 55.4% less time working in the labor market in post-ACA USA.

Hazardous chemicals like toxic organic dyes are very harmful to the environment and their removal is quite challenging. Therefore there is a necessity to develop techniques, which are environment friendly, cost-effective and easily available in nature for water purification and re-mediation. The present research work is focused on the development` and characterization of the ecofriendly polyvinyl alcohol (PVA) and alginate (Alg) hydrogel beads incorporating natural bentonite (Bent) clay as beneficial adsorbents for removal of toxic methylene blue (MB) from industrial water. PVA−Alg/Bent nanocomposite hydrogel beads with different Bent content (0, 10, 20, and 30 wt%) were synthesized via external ionic gelation method. The designed porous and steady structure beads were characterized by the use of Fourier transform infrared spectroscopy (FTIR), energy-dispersive X-ray spectroscopy (EDX), and scanning electron microscopy (SEM). The performance of the beads as MB adsorbents was investigated by treating batch aqueous solutions. The experimental results indicated that the incorporation of Bent (30 w%) in the nanocomposite formulation sustained porous structure, preserved water uptake, and increased MB removal effi-ciency by 230 % compared to empty beads. Designed beads possessed higher affinity to MB at high pH 8, 30 °C, and fitted well to pseudo-second-order kinetic model a high correlation coefficient. Moreover, designed beads had a good stability and reusability as they exhibited excellent removal efficiency (90%) after six consecutive adsorption-desorption cycles. Adsorption process was found be combination of both monolayer adsorption on homogeneous surface and multilayer adsorption on heterogeneous surface. The maximum adsorption capacity of the designed beads system as calculated by Langmuir isotherm was found to be 51.34 mg/g, which is in good agreement with the reported clay-related adsorbents. The designed PVA−Alg/Bent nanocomposite hydrogel beads demonstrated good adsorbent properties and could be potentially used for MB removal from polluted water.

The spread of the Coronavirus pandemic has been accompanied by an infodemic. The false information that is embedded in the infodemic affects people’s ability to have access to safety information and follow proper procedures to mitigate the risks. This research aims to target the falsehood part of the infodemic, which prominently proliferates in news articles and false medical publications. Here, we present NeoNet, a novel supervised machine learning text mining algorithm that analyzes the content of a document (news article, a medical publication) and assigns a label to it. The algorithm is trained by TFIDF bigram features which contribute a network training model. The algorithm is tested on two different real-world datasets from the CBC news network and Covid-19 publications. In five different fold comparisons, the algorithm predicted a label of an article with a precision of 97-99 %. When compared with prominent algorithms such as Neural Networks, SVM, and Random Forests NeoNet surpassed them. The analysis highlighted the promise of NeoNet in detecting disputed online contents which may contribute negatively to the COVID-19 pandemic.

The aim of present study was to link the gene expression profile of selected candidate genes with blood profile, growth performance and carcass traits of Barki lambs. Thirty-eight Barki lambs were divided into 3 groups (fast, intermediate and slow growing) according to growth perfor-mance. Body tissues (muscle, liver and fat) were taken from for RNA isolation and Real-time PCR. The results indicated that, the final body weight hot carcass weight were heavier (P ≤ 0.05) in fast (49.9 Kg and 24.57) than intermediate (40.7 and 19.07 Kg) and slow (30.8 and 15.10 Kg) growing animals. The blood profile of total protein, total lipids, calcium, T3 and T4 hormones did not differ among sheep groups. Genes involved in protein biosynthesis (RPL7), fatty acid oxidation (CPT1) and lipolysis (FABP4) were up regulated in fast and intermediate growing lambs in all studied tissues. While, gene-regulating lipogenesis (ADIPOQ) was expressed simi-larly in fat and liver tissues, but increased its expression in muscle of fast and intermediate growing lambs. Expression of CAPN3 was increased in fast and intermediate growing compared to slow growing lambs. In conclusion, the current study providing an evidence for the im-portance of co-expression of these genes in main body tissues linked with growth performance of Barki lambs.

Two important types of metal oxide nanoparticle catalysts Copper (II) oxide (CuO) and Cerium oxide (CeO₂) are prepared by a suitable method which was traditional precipitation (PT) method at calcination temperature of 400^oC for 5h and used for the synthesis of glycerol carbonate GC (C₄H₆O₄) from the direct reaction by the carbonylation of Glycerol GL (C₃H₈O₃) with Carbone Dioxide. The precipitation (PT) was an important route for the preparation of nanoparticles catalyst. The effects of performance of (CuO and CeO₂) nanoparticle catalysts on the conversion of glycerol GL, yield of glycerol carbonate GC, selectivity of glycerol carbonate are researched. XRD, XPS, BET, FT-IR, CO₂-TPD, H₂-TPR are used for the characterization of the prepared catalysts. Comparing the optimal performance between them under reaction conditions were 150 ^oC, 4MPa (40 bar.), 5h, and both CuO and CeO₂ catalyst amount 37.6 % (based on ratio of glycerol weight) by using 2-pyridinecarbonitrate (C₆H₄N₂) as dehydrating agent and dimethylformamide (DMF), (C₃H₇NO) as solvent. The glycerol conversion (X_GL), glycerol carbonate yield (Y_GC) and glycerol carbonate selectivity (S_GC) over 0.7g CuO are 57.151%, 47.524%, and 83.156%, respectively, and glycerol carbonate yield over 0.7 CeO₂ is 36.2185% or 35.076%, and the yield of GC could reach as high as 78.234% over 1.73g CeO₂, the both catalysts could be easily regenerated by washing with methanol and water after a reaction and then dried at 60 ^oC overnight after that calcination at 400 ^oC for 5h without loss of activity after five recycling times, In addition to, the (ICP- MS) results confirmed that the leaching of CuO and CeO₂ was below the detection limit.

The system design for Sustainable manufacturing is to consider both ecological and financial constraints. Manufacturing industry demands to advance in sustainable manufacturing by accounting in environment factors in it. All the factors that affect the environment need to be analyzed so that proper amendments or suggestions can be provided. To favour this, Computer aided life cycle inventory model has been presented for CNC milling and turning processes. Based on utilization of resources and stages, whole machining operation time can be divided into three phases named as process (milling or turning), idle and basic times. As parameters are different for evaluating the process times i.e. depth and width of cut in case of milling and initial and final diameters for turning, two different case studies has been presented one for each milling and turning process. Effect of material choice has been studied for different processes. Highly dense and hard materials takes more time in finishing the job due to low cutting speed and feed rates as compared to that of sot materials. In addition, face milling takes more time and consumes more power as compared to peripheral milling due to more retraction time caused by over travel distance and lower vertical transverse speeds than the horizontal transverse speed used in peripheral retraction process.

This paper highlights the impact of financial inclusion on individuals’ borrowing and saving decisions in the United States and the United Arab Emirates. It does so, using data from the 2014 Global Financial Inclusion database, and an empirical strategy consisting of first testing the significance of the joint bivariate model over its binary conterparts using the Lagrange multiplier test, followed by a contrast between the fully-parametric and semi-parametric specifications of the saving and borrowing equations. Based on model performance measures, the semi-parametric bivariate probit specification is identified as a better framework for describing the two processes of saving and borrowing, with a correlation coefficient of 12.3%. Although no significant difference exists between UAE and US residents in borrowing behavior, we find that US residents are 31.4% more likely to save than their UAE counterparts. In addition, and in line with the Permanent Income Hypothesis, the results reveal the absence of an income based saving or borrowing gradient in the two countries. Conversely, we found the prevalence of a gender based saving (12.4%) and borrowing (13.8%) inequality in favor of the male gender. Furthermore, access to a bank account and a debit card, companies policy of direct wage and salary transfer, and government transfer programs with direct deposit options are all financial inclusion strategies that are found to significantly raise the likelihood of saving and borrowing. As such, companies with payroll practices based on cash or physical paycheck issuing, especially in the US, should revise such policy to create more financial inclusion, and thereby more saving potential which in turn would contribute to further borrowing, investment and growth of the national economy.

Relying on the USA, Canada and Mexico extract from the cross-national data sample on the environmental affection and cognition of adolescent students (Niankara, 2019), along with seemingly unrelated bivariate weighted ordered probit regression modeling (Niankara and Zoungrana, 2018), this study reports on the convergence of technological awareness and expectations within the context of international trade. We achieve this by adopting a regional perspective in investigating the effects of affective, cognitive and situational factors on youth's awareness and expectations about genetically modified organisms (GMOs) and nuclear power technology (NPT) within the North American free trade block. Identification of model parameters is achieved using maximum simulated likelihood methods. The findings show that although it has been over 20 years as of 2015 that USA, Canada, and Mexico ratified the north American free trade agreement (NAFTA), the diffusion of technology and information within the trade block has not succeeded in homogenizing awareness and expectations about GMOs and Nuclear power technology, as observed in the youth population across the three countries. Indeed, with regards to technological awareness, compared to youth from the USA, those from Canada show 15% (GMOs) and 7.1% (NPT) more awareness respectively; while those in Mexico are respectively 34.4% and 19.5% less aware about GMOs and NPT. With respect to technological expectations, compared to youth from the USA, those from Canada and Mexico are respectively 34.4% and 39.9% more optimistic about GMOs, while 15% and 49.7% more optimistic about NPT. Overall, youth within NAFTA country members are respectively 2.5% and 6.7% more optimistic about GMOs and NPT for every level increase in their awareness about the two technologies.

Long-haul truck drivers are responsible for transporting goods valued at millions of dollars of the world economy and may have their health affected by living and working conditions. This study analyzed and synthesized the scientific findings about risk factors for the development of chronic non-communicable diseases in long-haul truck drivers. An integrative literature review was conducted. We identified 23 studies that met the inclusion criteria and evaluated the health of 7,363 drivers. The biological risks identified were age, gender, race/ethnicity, genetics, comorbidities, and were considered non-modifiable for chronic diseases. The behavioral risks, considered modifiable, were sedentary lifestyle, smoking, alcohol consumption, overweight, diet, stress, anxiety, unfavorable socioeconomic conditions. Environmental risks involved working conditions such as the number of working hours per day, week and month; time away from home, risk of musculoskeletal injury, and opportunities for rest, hours of sleep and access to health services. The results were presented in two categories: 1) biological, behavioral and environmental risks, and 2) general recommendations to promote physical, cognitive and emotional health. Macro-structural changes are needed to reorganize work and rest, improve access to health services to control risk factors, and to support behavioral and environmental changes to reduce chronic non-communicable diseases and deaths.

This work aims to generate some types of M_(j )–neighborhoods. Relationships among these M_(j )-neighborhoods and some other types of neighborhoods are discussed. Additionally, M_(j )-lower, M_(j )-upper approximations and M_(j )-accuracy in terms of M_(j )-neighborhoods are presented. Their properties, with some examples, are investigated. Finally, We addressed the comparisons among M_(j )approach and other approaches.

Rapid post-earthquake damage diagnosis of bridges can guide decision-making for emergency response management and recovery. This can be facilitated using digital technologies to remove the barriers of manual post-event inspections. Prior mechanics-based Finite Element (FE) models can be used for post-event response simulation using the measured ground motions at nearby stations; however, the damage assessment outcomes would suffer from uncertainties in structural and soil material properties, input excitations, etc. For instrumented bridges, these uncertainties can be reduced by integrating sensory data with prior models through a model updating approach. This study presents a sequential Bayesian model updating technique, through which a linear/nonlinear FE model, including soil-structure interaction effects, and the foundation input motions are jointly identified from measured acceleration responses. The efficacy of the presented model updating technique is first examined through a numerical verification study. Then, seismic data recorded from the San Rogue Canyon Bridge in California are used for a real-world case study. Comparison between the free-field and the foundation input motions reveals valuable information regarding the soil-structure interaction effects at the bridge site. Moreover, the reasonable agreement between the recorded and estimated bridge responses shows the potentials of the presented model updating technique for real-world applications. The updated FE model is considered as the digital twin of the bridge and can be used to analyze the bridge and monitor the structural response at element, section, and fiber levels to diagnose the location and severity of any potential damage mechanism.

Introduction: In the recent years alternate day dosing has been recommended in iron deficieny treatment. The aim of this study is to compare the efficacy and side effects of oral iron treatments given daily 1x1, alternate day 1x1 and 2x1 alternate day dosing in iron deficieny anemia patients. Methods: A total of 52 patients with a diagnosis of iron deficiency anemia with serum ferritin level of 25 µg/L or less were included in this retrospective study. Statistical analyzes were done with SPSS V.25. Results: The patients included in our study were between the ages of 18-51. All of the patients included in the study were female. A statistically significant increase was found between 0-14 days(p<0.001), 14-28 days(p<0.001) and 0-28 days(p<0.001) hemoglobin values in all patients. There was no statistically significant difference between 0-14 days (p=0.397) and 0-28 days(p=0.310) ferritin values in all patients. A statistically significant difference was found between 14-28 days(p<0.001) ferritin values. When the rate of change of hemoglobin and ferritin values between the groups was compared and no statistically significant difference was observed between the groups. The rate of change of ferritin values for 14-28 days was significant (p=0.012). There was no significant difference in the frequency of symptoms in the 14th day and 28th day controls for each group (p>0.05). The incidence of metallic taste and bloating symptoms was found to be statistically significant in the third control in the group with 2x1 drug use alternate day (p=0.094). Discussion: The only difference in efficacy was observed in ferritin values between 14th and 28th days. The increase in ferritin values was higher in the group that used 1x1 oral iron every day. However, since no difference was observed between the groups in terms of ferritin and hemoglobin values on days 0 and 28, all three groups were considered equally efficient. Side effects were mainly gastrointestinal side effects. Since the group that received 2x1 oral treatment alternate day had a statistically significantly higher rate of side effects, the patients’ treatment tolerance will be lower compared to the other groups. In conlusion, there is no difference in efficacy and side effects between the patient groups receiving 1x1 daily and 1x1 alternate day oral iron therapy, so 1x1 use alternate day is the most appropriate treatment method for oral iron therapy in terms of patient tolerance, adherence to treatment and pharmacoeconomics.

Gasca D herbal formulation is an antidiabetic medicine for the management of diabetes mellitus produced exclusively from natural ingredients. The level of some essential elements (Copper, chromium, Cobalt, Iron, Manganese, Nickel and zinc) and toxic (Cadmium, Arsenic, Mercury, and Lead) heavy metals were determined using microwave plasma-atomic emission spectrometry (MP-AES). The aim of this study is to evaluate the levels of essential and toxic heavy metals and also identify bioactive compounds present in Gasca D herbal formulation. The result shows no traces of Lead, Mercury, Zinc, Arsenic and Zinc, Iron was found to have highest concentration 67.16 + 7.5 µg/g and Cadmium lowest concentration 0.4 + 0.03µg/g. GC-MS analysis of Gasca D herbal formulation revealed the presence of 14 biologically active compounds which include N-Formyl-beta-alanine, Paromomycin, 3,4-Altrosan, Benzamide, 1,3,4-Thiadiazol-2-amine, Carbamodithioic acid, Carbonic acid, alpha-D-Glucopyranoside, Ethyl isocyanide, 2-Propanesulfinic acid, Propanamide, 2-Butenenitrile, Dicyclopropyl carbinol, Isoxazolidine, 1,5-Hexadiene 10-Azido-1-decanethiol. Conclusion: The result indicates that the mean levels of toxic metals in Gasca D herbal formulation were below WHO permissible levels. Gasca D herbal formulation also contains various bioactive compounds that can have various medicinal application which can be used for the treatment of various diseases.

This paper provides a structured and practical roadmap for practitioners to integrate Learning from Demonstration (LfD) into manufacturing tasks, with a specific focus on industrial manipulators. Motivated by the paradigm shift from mass production to mass customization, it is crucial to have an easy-to-follow roadmap for practitioners with moderate expertise, to transform existing robotic processes to customizable LfD-based solutions. To realize this transformation, we devise the key questions of "What to Demonstrate", "How to Demonstrate", "How to Learn", and "How to Refine". To follow through these questions, our comprehensive guide offers a questionnaire-style approach, highlighting key steps from problem definition to solution refinement. The paper equips both researchers and industry professionals with actionable insights to deploy LfD-based solutions effectively. By tailoring the refinement criteria to manufacturing settings, the paper addresses related challenges and strategies for enhancing LfD performance in manufacturing contexts.

Zinc finger proteins (ZFP) play important roles in cellular processes. The DNA binding region of ZFP consists of 3 zinc finger DNA binding domains connected by amino acid linkers, the sequence TGQKP connects ZF1 and ZF2, and TGEKP connects ZF2 with ZF3. Linkers act to tune the zinc finger protein in the right position to bind its DNA target, the type of amino acid residues and length of linkers reflect on ZF1-ZF2-ZF3 interactions and contribute to the search and recognition process of ZF protein to its DNA target. Linker mutations and the affinity of the resulting mutants to specific and nonspecific DNA targets were studied by MD simulations and MM_GB(PB)SA. The affinity of mutants to DNA varied with type and position of amino acid residue. Mutation of K in TGQKP resulted in loss in affinity due to the loss of positive K interaction with phosphates, mutation of G showed loss in affinity to DNA, WT protein and all linker mutants showed loss in affinity to a nonspecific DNA target, this finding confirms previous reports which interpreted this loss in affinity as due to ZF1 having an anchoring role, and ZF3 playing an explorer role in the binding mechanism. The change in ZFP-DNA affinity with linker mutations is discussed in view of protein structure and role of linker residues in binding.

Dietary factors are one of the risk factors that can impact the brain chemistry, which leads to mental distress. Based on our data mining approach, we found that mental distress in men is associated with eating unhealthy food. Our aim in this paper is to apply results from our big data analytics approach to inform system dynamics (SD) modeling to investigate the causal relationships between brain structures, nutrients from food and dietary supplements, and mental health. We perform descriptive analysis based on a large data set to estimate the SD modeling parameters. Finally, we calibrate the model towards a time series data collected for individuals on their dietary and distress patterns. The results reveal that bridging these different methodologies leads to further insights from the SD model and decreases the error of calibrated parameter values. Future research is needed to validate our initial results for investigating the relationship between mental distress and dietary intake.

The aim of this study was to investigate the knowledge, attitudes, and behaviors of family physicians regarding testicular cancer and testicular self-examination. This study was conducted with 307 physicians, including family physician specialists, family physician residents, contracted family physician specialist assistants (SAHU), and general practitioners, who agreed to participate in the study. All participants were administered a 33-item questionnaire consisting of sociodemographic questions and questions about testicular cancer and testicular self-examination, developed through literature review. Data analysis was performed using SPSS 22.0 software. 307 family physician specialists, family physician residents, SAHU residents and general practitioners participated in the study. 10.4% of the participants were working as family medicine specialists, 67.4% as family physician assistants, 13.7% as SAHU residents and 8.5% as general practitioners. The mean time spent in the profession was found to be 5.93±5.89. 65.8% of the participants thought that they had partially sufficient knowledge about testicular cancers. 57.7% of the participants stated that they did not know how testicular self-examination was performed. 49.7% of male participants stated that they had never done testicular self-exam before. While 95.8% of the participants thought that regular testicular self-examination was beneficial, 71.0% stated that they did not recommend testicular self-examination to their male patients. 53.4% of the participants thought that testicular self-examination was important; It was determined that 79.2% of them thought it was as important as breast self-examination. The rate of stating that all of the risk factors presented for testicular cancer are risks was found to be statistically significantly higher in specialist family physicians than in general practitioners and resident family physicians. The study revealed that family physicians lacked sufficient knowledge about testicular cancer and testicular self-examination, leading them not to recommend self-testicular examination to patients due to inadequate knowledge. In light of these findings, although self-testicular examination may not be recommended as a screening method, increasing awareness and knowledge among both family physicians and the public is crucial.

This study inscribes itself in the global discussion on the nurturing of pro-environmental behaviors among young people for a sustainable future. Here we focus on students' interest in Ecosystem Services and Sustainability to explain their awareness and optimism about the environmental issues of air pollution, water shortage and green gas emission in 50 countries around the world. To this end, we use the cross-sectional survey data of the OECD's Program for International Student Assessment (PISA) 2015, along with seemingly unrelated bi-variate weighted ordered Probit modeling with country specific effects. The results show that in addition to factors such as age, gender, immigration status, and economic, social and cultural status, interest in the biosphere is a significant determinant of students' environmental awareness and optimism. In fact, a one level increase in students' interest in ecosystem services and sustainability raises on average their awareness level by 15.3% for the issue of air pollution, 15.7% for the issue of water shortage, and 24.6% for the issue of green gas emission. Although students' interest in the biosphere seems to not have a significant effect on their expectations about the issue of green gas emission, it does however raise their level of optimism by 0.8% for the issue of air pollution, and 0.2% for the issue of water shortage. Furthermore, every one level increase in students' environmental awareness leads to 17.3% more optimism about the issue of air pollution, 15.8% more optimism about the issue of water shortage, and 17.4% more optimism about the issue of green gas emission. Therefore, relying on the Theory of Planned Behavior (TPB), our results imply that governments and policy makers can successfully leverage young people interests in the biosphere to effectively achieve their goals for sustainability.

model checking techniques are often used for the verification of software systems. Such techniques are accompanied with several advantages. However, state space explosion is one of the drawbacks to model checking. During recent years, several methods have been proposed based on evolutionary and meta-heuristic algorithms to solve this problem. In this paper, a hybrid approach is presented to cope with the SSE problem in model checking of systems modeled by GTS with an ample state space. Most of existence proposed methods that aim to verify systems are applied to detect deadlocks by graph transformations. The proposed approach is based on the fuzzy genetic algorithm and is designed to decline the safety property by verifying the reachability property and detecting deadlocks. In this solution, the state space of the system is searched by a fuzzy genetic algorithm to find the state in which the specified property is refuted/verified. To implement and evaluate the suggested approach, GROOVE is used as a powerful designing and model checking toolset in GTS. The experimental results indicate that the presented hybrid fuzzy method improves speed and performance by comparing other techniques

Motivated by the theoretical model of health insurance choice with Flexible Spending Accounts (FSAs) presented in Cardon 2012, this study investigates the determinants of optional coverage (SSP) and flexible spending accounts (FSA) enrollment, among the privately insured in post-affordable-care-act (ACA) USA. To this end, we rely on semi-parametric bi-variate probit methods, along with a pooled cross-section of the 2015-2016 National Health Interview Surveys. As predicted by the theoretical model, we find that SSP and FSA are complement health solutions with a positive correlation. Our results emphasize that the most important trigger factors influencing the joint probability of SSP and FSA adoption include not only insurance premium cost, but also age, education, marital status, number of work hours, region of residency, citizenship status, and annual health expenditure level. We find that controlling for these latter factors, health status is not significant especially for FSA adoption. In addition, despite the fact that the relative frequency of individuals with FSA rises with increasing levels of medical expenditure, ACA restrictions on FSA tax exclusion to an annual adjusted maximum of $2600 (in 2017 $s) seems to adversely burden individuals with greater medical expenditure, thereby reducing their likelihood of FSA enrollment in post-ACA USA. Understanding these factors is very crucial to US health care market's stakeholders, including insurance companies, firms looking to design their health insurance offerings, but also policy-makers interested in providing new tailored health solutions for reducing health risks.

By using the Sala-i-Martin version of extreme bounds analysis, which is based on the cumulative density function, cross-sectional evidence is presented on the robust determinants of the infection and case mortality rates of Covid-19. The results show that, for most part, different factors determine the infection and mortality rates in developed and developing countries. However, common factors are also apparent, including the risk environment, the number of tests per million and the percentage of population over 65. Notwithstanding the possibility that the official data represent a partial reflection of the truth, it is concluded that the results presented in this study provide useful information that may aid decision-making in the fight against the pandemic.

Along with the advantages associated with access to information and fast communication, screen time from increased digital media consumption has recently been associated with adverse effects on youth well-being. To get a clearer picture of its value for global youth based sustainability initiatives, this study investigates the effects of increased digital media consumption on youth's interests in ecosystem services, sustainability and science as a means for disease prevention. We achieve this, using data on 187821 adolescent students from 50 countries worldwide. Methodologically, we rely on a mixed bivariate ordered probit representation of youth's joint interest in the biosphere (ecosystem services and sustainability) and science as a means for disease prevention, which we then estimate using Markov Chain Monte Carlo (MCMC) Methods. We found that each level increase in adolescent students' reported frequency of news blogs visits and web browsing on broad science adversely affect their interests in ecosystem services, sustainability and science as a means for disease prevention. Although each level increase in youth's frequency of ecological website visits also reduces by 20% (with 95% CI [-0.36; -0.32]) their interests in the biosphere, it is found to increase however by 3% (with 95% CI [0.02; 0.05]) their interest science as a means for disease prevention. Overall, our results highlight heterogeneous effects of digital media consumption on adolescents' well-being in terms of their interests in ecosystem services, sustainability, and science as a means for disease prevention.

A single paragraph of about 200 words maximum. For research articles, abstracts should give a pertinent overview of the work. We strongly encourage authors to use the following style of structured abstracts, but without headings: (1) Background: Place the question addressed in a broad context and highlight the purpose of the study; (2) Methods: briefly describe the main methods or treatments applied; (3) Results: summarize the article’s main findings; (4) Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article and it must not contain results that are not presented and substantiated in the main text and should not exaggerate the main conclusions. This study presents a comprehensive literature review on the convergence of affective computing, interactive installation art, multi-dimensional sensory stimulation, and artificial intelligence (AI) in measuring emotional responses. It addresses the problem of understanding emotional response and measurement in the context of interactive installation art under artificial intelligence (AI). The study aims to fill the existing research gaps by examining three key aspects: sensory stimulation, multi-dimensional interactions, and engagement, which have been identified as significant contributors to profound emotional responses in interactive installation art. The study proposed approach involves conducting a process analysis of emotional responses to interactive installation art, aiming to develop a conceptual framework that explores the variables influencing emotional responses. The study will formulate hypotheses that make specific predictions about the relationships between sensory stimulation, multi-dimensional interactions, engagement, and emotional responses. By employing the ASSURE model combined with experimental design, the research methodology ensures a systematic and comprehensive study implementation. The implications of this project lie in advancing the understanding of emotional experiences in interactive installation art under AI, providing insights into the underlying mechanisms that drive these experiences. The contributions of this research include bridging the identified research gaps, refining theoretical frameworks, and guiding the design of more impactful and emotionally resonant interactive artworks. Ultimately, this research aims to contribute to the broader field of human-computer interaction and enhance the development of immersive and emotionally engaging interactive installations.

The stick-free flight stability is an old-fashioned and non-progressive issue; nevertheless, it is still existent, and of significant importance to the design of aircraft whose control system is reversible. The problem’s existence necessitates a deep assessment of stick-free flight stability throughout the aircraft design. Up to now, this problem has been addressed using either analytical approaches, which are only related to the static stability evaluation, or performing flight tests. In this study, the problem is handled in its entirety, from static and dynamic flight stability assessment to design criteria with a comprehensive perspective. Moreover, it is also exhibited that contrary to what has been generally proposed in the literature, limiting the problem of stick-free flight stability through static stability assessment is far from the main challenge. As a brief scope, the derivation of the control surface dynamics, a stick-free trim algorithm, and assessment rationale of the stick-free static and dynamic flight stability using a simulation approach are proposed. As a consequence, the aim is to set a broad understanding for designers related to this phenomenon and add adjunct design criteria in the design optimization process by approaching it in terms of modeling, simulation, and flight test perspective.

Since the energy sector is the main source of greenhouse gases, it has the highest potential for improvement. Improvements can be achieved by generating energy from renewable sources. Combined with thermal energy storage, concentrating solar power plants represent a promising technology for dispatchable renewable energy, ensuring a stable energy supply even in remote areas without contributing to greenhouse gas emissions during operation. However, it is important to note that greenhouse gases and other polluting emissions may occur during the manufacturing process of concentrating solar power plant components. This work analyses the design of the receiver to produce thermal energy for the existing solar dish CSP plant at the Energy Center of the Politecnico di Torino. The objective of this plant is to produce hot water for a small case study. Considering the average solar irradiance for Turin equal to 800 W/m2, the surface heat flux was obtained from the first part of the analysis, which was used to obtain the maximum internal temperature in the receiver equal to 873.7 °C. The maximum temperature obtained was a constraint for the selection of the material for the solar receiver. Of the various possibilities, copper was chosen. In the second part of the work, a Life Cycle Assessment was carried out to compare the emissions generated during the production of the main components of the CSP plant with the emissions generated by the methane-fuelled water heater that produces the same amount of water as the CSP plant. It can be concluded that the manufacture of the main components of the CSP plant results in lower greenhouse gas emissions than the operational phase of a conventional natural gas-fired water heater (1.6 kg CO2/day).

Water resources worldwide are limited, especially in desert areas like Saudi Arabia. Therefore, the rational and sustainable management of irrigation water supply is an imperative required by the conditions of space and time. This study evaluates the irrigation system through partial root-zone drying (PRD) and regulated deficit irrigation (RDI). The effect of applying the PRD and RDI systems on the efficiency and rationalization of irrigation water consumption in a greenhouse and open field cucumber was studied in addition to using the surface (S) and subsurface (SB) drip irrigation methods on irrigation efficiency. The productivity of the RDI-S regular drip irrigation treatment was considered 100% as the control on which the results of all treatments are measured. The results showed that in terms of irrigation technique, the PRD-SB technique had the highest productivity during the winter season in greenhouse cucumbers, with a general average of 13.8 kg m-2 for all irrigation levels, while the RDI-SB technique had the highest productivity during the summer season, with a general average of 16.1 kg m-2. Regarding irrigation level results, the study showed that an irrigation level of 100% is the highest productivity in all irrigation techniques, with a general average of 14.9 kg m-2 for all irrigation techniques during the winter season and 16.4 kg m-2 during the summer. However, the increase in the irrigation level to 150% did not increase productivity. In comparison, the application of the deficit irrigation technique by reducing the level of irrigation to 50% was not accompanied by a similar decrease in productivity. The study results also showed that irrigation with the PRD-SB system was the most productive in the open field at all irrigation levels, with a general average of 7.3 kg m-2. The general average of the percentage decrease in productivity in all irrigation techniques compared to reducing the irrigation percentage to 50% and 75% was 22% and 3 %. The irrigation efficiencies were higher when applying the PRD (PRD-SB) in winter. In contrast, applying a deficit irrigation system (RDI-SB) in the summer season had the highest efficiency. It could be concluded that using PRD and RDI systems for indoor and outdoor cucumber can save irrigation water.

By studying game theory, we find that the Nash equilibrium does not exist in some games or, if there is in one, does not describe a real event. Here we show that the matching pennies game with pure strategy has the solution, but this solution is a game that happens simultaneously with this game. Using this solution, we will answer the Brookings Institution's question of boycotting the elections whether the opposition's boycott of elections is, in different circumstances, a defeated strategy. A strategy that its result in most cases is a failure or political suicide and the least possible consequence by the opposition. The findings of this article show that in general, it can be concluded that the election boycott strategy is a dominated strategy, and most of the opposition groups that have used it have failed and they donated the playground to the ruling group.

Marfan syndrome is an autosomal dominant genetic connective tissue disorder that results from mutations in the fibrillin-1 gene located on chromosome band 15q 15–21. Fibrillin, a glycoprotein, is widely expressed throughout the body and contribute to elasticity and force-bearing capacity of connective tissue. In the eye, fibrillin is a key constituent of the ciliary zonules, which suspend the crystalline lens in place. The zonular defect leads to ectopia lentis that is hallmark of Marfan ocular abnormalities and occurs in 60 to 80% of cases. Other less common ocular features of Marfan syndrome are increased axial length, astigmatism, and flat cornea. Visual function in Marfan syndrome could be affected in several ways: ectopia lentis, refractive error, amblyopia, retinal detachment, cataract, and glaucoma. Management of subluxated lens starts with correction of refractive error with eyeglasses in mild cases. In more severe cases, especially when lens bisects the pupil, complete correction of refractive error is impossible without removing subluxated lens. The best method for visual rehabilitation after lens extraction is still debated. Aphakic Artisan implantation at the time of subluxated lens removal results in good visual outcomes with acceptable safety profile. Studies with longer term follow up and larger sample populations are needed to evaluate the safety of this procedure in patients with Marfan syndrome.

Cancer is one of the leading causes of death, making timely diagnosis and prognosis very important. Utilization of AI (artificial intelligence) enables providers to organize and process patient data in a way that can lead to better overall outcomes. This review paper aims to look at the varying uses of AI for diagnosis and prognosis and clinical utility. PubMed and EBSCO databases were utilized for finding publications from January 1, 2013, to December 22, 2023. Articles were collected using key search terms such as “artificial intelligence” and “machine learning.” Included in the collection were studies of the application of AI in determining cancer diagnosis and prognosis using multi-omics data, radiomics, pathomics, clinical and laboratory data. The resulting 89 studies were categorized into eight sections based on the type of data utilized and then further subdivided into two subsections focusing on cancer diagnosis and prognosis, respectively. 8 studies integrated more than one form of omics, namely genomics, transcriptomics, epigenomics, and proteomics. Incorporating AI into cancer diagnosis and prognosis alongside omics and clinical data represents a significant advancement. Given the considerable potential of AI in this domain, ongoing prospective studies are essential to enhance algorithm interpretability and to ensure safe clinical integration.

Purpose: To compare the therapeutic efficacy and safety of dorzolamide/timolol fixed-combination in newly diagnosed primary open angle glaucoma patients. Methods: In this prospective, interventional case series, newly diagnosed primary open angle glaucoma (POAG) patients that had not been treated for glaucoma were included. Patients were started on Cosopt twice a day (BID) for 1 month and then switched to three times a day (TDS) for additional 1 month. Patients underwent comprehensive ophthalmic examination, diurnal intraocular pressure (IOP), blood pressure (BP) and 24-hours heart rate (HR) measurements at baseline, month 1( BID), and month 2( TDS). IOP, systolic and diastolic pressures were measured at 8:00 AM,12:00 AM, 4:00 PM, 8:00 PM and 12:00 PM. Throughout the study, all adverse events were recorded and monitored by the investigators. Results: In 31 POAG patients that completed the study ,mean baseline IOP was 23.1±3.15 mmHg . IOP was decreased significantly 16.5 ± 2.21 at 1 month (P < 0.0001) and 13.9 ± 2.23 mmHg at 1 and 2 month follow up. (P < 0.0001) IOP was significantly lower in month 2 compared to month 1 (P = 0.0004). While Cosopt BID significantly reduced the mean 24-hour systolic BP and mean 24-hour HR from baseline (P < 0.0001), the mean 24-hour systolic BP and HR remained unchanged 2ith Cosopt TDS compared to BID (P = 0.62). Conclusions: Cosopt TDS has a superior IOP-lowering effect than Cosopt BID in POAG patients with comparable safety profile.

In this paper, a model of the hub covering the location-routing problem with simultaneous delivery and pickup should be designed in order to minimize the total costs, minimize the maximum vehicles travel time and minimize the amount of CO_2 gas emissions. Two-stage stochastic programming is used in this paper to control the uncertainty parameters of the problem. The mathematical model aims to decide the appropriate location of hubs and vehicle routing for simultaneous delivery and pickup of products. In this regard, the results obtained from the LP-Metric method show that there is a conflict between the objective functions, and with the reduction of the amount of CO_2 gas emissions and the reduction of the maximum vehicles travel time, the total costs have increased. On the other hand, by examining the economical factor, it was observed that by reducing this factor, the robustness factors are changed and the total costs of the network are reduced. MOIWO and MOALO were used to solve the problem in large scale, the result of which was the existence of a significant difference between the calculation time averages. Also, the efficiency of these methods was very high compared to the LP-Metric method and the maximum relative difference was less than 2.83%. The results of numerical examples show a higher efficiency of the MOALO than the MOIWO.

The photodegradation of azithromycin present was carried out in water using H2O2 under UV irradiation. The reaction variables considered in this study were the amount of H2O2 solution and the initial concentration of azithromycin to evaluate the performance of the photodegradation process. The azithromycin degradation was not observed in the dark during stirring for 20 minutes. The study showed efficient photodegradation of azithromycin using H2O2 as an oxidant in the presence of UV irradiation. The azithromycin degradation was affected significantly by the pH of the irradiated solution. The degradation was low at an acidic pH and showed an increasing trend as the pH changed to basic. The azithromycin degradation was increased with a higher amount (higher concentration) of H2O2. The degradation of azithromycin decreased with a higher concentration of azithromycin in the reacting solution. The highest degradation of AZT was achieved in 1 hour using a 1.0 ppm AZT solution containing 3 ml of H2O2. The experimental data obtained was well-fitted to zero-order reaction kinetics. The results of this study were found to be superior when compared with those reported in the literature, with photocatalysis using nanomaterials and photolysis using irradiation and H2O2. The UV/H2O2 system was found to be quite efficient for the photodegradation of azithromycin, and this system can be applied to degrade other organic pollutants present in industrial wastewater. To this point, such a study has not been reported specifically for AZT photodegradation.

Responsible, efficient, and environmentally conscious energy consumption practices are increasingly essential for ensuring the reliability of the modern electricity grid. This study focuses on leveraging time series analysis to improve forecasting accuracy, crucial for various application domains where real-world time series data often exhibit complex, non-linear patterns. Our approach advocates for utilizing Long Short Term Memory (LSTM) and Bidirectional LSTM (BiLSTM) models for precise time series forecasting. To ensure a fair evaluation, we compare the performance of our proposed approach with traditional neural networks, time-series forecasting methods, and conventional decline curves. Additionally, individual models based on LSTM, Bi-LSTM, and other machine learning methods are implemented for a comprehensive assessment. Experimental results consistently demonstrate that our proposed model outperforms all benchmarking methods in terms of mean absolute error (MAE) across most datasets. Addressing the imbalance between activations by consumer and prosumer groups, our predictions show superior performance compared to several traditional forecasting methods, such as the Autoregressive Integrated Moving Average model (ARIMA) and Seasonal Autoregressive Integrated Moving Average model (SARIMA). Specifically, the root mean square error (RMSE) of Bi-LSTM is 5.35%, 46.08%, and 50.6% lower than LSTM, ARIMA, and SARIMA, respectively, on the May test data.

This paper relies on accounting-based measures of country risk to investigate U.S. global banks' exposure to foreign country risk over the 2017 fiscal year as measured by the sum of cross-border risk, foreign office risk, and derivative risk claims. We achieve this using panel linear modeling methods with country level heterogeneity and time fixed effects, along with a constructed panel data of 284 observations on 71 countries distributed across 6 world regional blocks, and observed over 4 consecutive quarters starting from 4th quarter 2016 and ending with 3rd quarter 2017. The results show that on average, over the four quarters, a 1% increase in foreign banking sector's claims significantly increases U.S. global banks cross border risk exposure by 0.34%, while reducing derivative risk exposure by 0.22%, but have no significant impact on foreign office risk exposure. Similar results are observed with public sector claims which significantly increase banks' exposure to cross border risk by 0.21%, while reducing derivative risk exposure by 0.19%. Conversely however, non-bank financial sector claims are found to have no significant affect on cross-border risk exposure, but significantly reduce foreign office risk exposure by 0.09%, while increasing derivative risk exposure by 0.06%. These results indicate the presence of sectoral heterogeneities in U.S. banks' exposure to foreign counterparties' risk, and also that overall, over the course of 2017 the level of U.S. global banks' cross-border risk exposure increased, while their level of derivative risk exposure decreased, and the level of foreign office risk exposure remained relatively unchanged.

Water scarcity is a significant challenge facing Jordan today. It is a challenge in all areas that use water, and it has become certain that water is the critical factor in the population/resources equation. The water resources in Jordan have become limited with the noticeable increase in the population, mostly resulting from forced migrations in neighboring countries because of the wars and until our time. The rising natural population growth rate, along with the massive influx of refugees, has turned into a state of disproportion between the daily consumption of the population and the amount of water available. That Jordan shares most of its surface water resources with neighboring countries has exacerbated the situation. The current use of water already exceeds its renewable supply. Excessive withdrawal from aquifers, which leads to a lowering of the water table and deterioration in water quality, covered the deficit. This paper focuses on assessing the water situation in Jordan, mainly evaluating this problem and the solution being considered, the true basis for a sustainable water solution requires awareness by the population, and several governmental and non-governmental organizations are actively involved in educating residents about water shortages. The most important and 'actionable' elements of comprehensive water solutions are discussed in this paper, and these elements exist, develop extra water supplies, water harvesting, water desalination, proper wastewater reuse in the agricultural sector, and reduce the demand for drinking water. This research provides specific recommendations to address the shortage of water resources in the Kingdom and highlights the importance of water conservation and optimal use.