Mild traumatic brain injury (mTBI) or concussion accounts for the bulk of all head injuries and represents a major health concern. Although an mTBI event may not manifest in neurobehavioral impairment, repeated injuries, known as repeated mTBI (rmTBI), can result in a cumulative effect that may progress to long-term cognitive and functional deficits. To date, there is no FDA-approved drug for TBI in general and rmTBI in particular. In previous studies, we have demonstrated the neuroprotective role of mitoquinone (MitoQ), a mitochondrial antioxidant, in an open head injury model and a model of repeated mild TBI (rmTBI) at a chronic time point (30 days). In this work, we set out to assess the neuroprotective potential of MitoQ at acute (3 days) and subacute time points (7 days) post-injury in a controlled cortical impact model of rmTBI. C57BL/6 male mice were injected intraperitoneally with MitoQ (5 mg/kg) one hour after the first mTBI, and three days after the first injury in both the 3-day and 7-day MitoQ + rmTBI subgroups, with an additional injection four days after the second injection in the 7-day group. Cognitive function was evaluated using the Morris water maze (MWM) while gross and fine motor functions were evaluated by the pole climbing, grip strength, and ladder rung tests. Dihydroethidium (DHE) staining was performed to evaluate oxidative stress while qRT-PCR was used to measure the gene expression of different antioxidant enzymes. Also, immunofluorescence staining was performed on brain tissue to assess the degree of microgliosis and astrocytosis. Our results showed that MitoQ conferred significant protection on days 3 and 7 post-injury against fine motor function impairment induced by rmTBI. Moreover, MitoQ enhanced cognitive function and reduced astrogliosis, microgliosis, and levels of oxidative stress on day 7 post-injury. However, antioxidant gene expression generally remained unaffected. In light of our results, MitoQ administration may be considered a preventive approach that helps to alleviate the neurological manifestations associated with rmTBI early before symptoms progress to long-term deficits.

Meningiomas are the most prevalent primary intracranial tumors. The majority are benign but can undergo dedifferentiation into advanced grades classified by World Health Organization (WHO) into Grades 1 to 3. Meningiomas tremendous variability in tumor behavior and slow growth rates complicate their diagnosis and treatment. A deeper comprehension of the molecular pathways and cellular microenvironment factors implicated in meningioma survival and pathology is needed. This review summarizes the known genetic and epigenetic aberrations involved in meningioma, with a focus on Neurofibromatosis type 2 (NF2) and non-NF2 mutations. Novel potential biomarkers for meningioma diagnosis and prognosis are also discussed, including epigenetic-, RNA-, metabolomics, and protein-based markers. Finally, the landscape of available meningioma-specific animal models is overviewed. Use of these animal models can enable planning of adjuvant treatment, potentially assisting in preoperative and postoperative decision-making. Discovery of novel biomarkers will allow, in combination with WHO grading, more precise meningioma grading, including meningioma identification, subtype determination, and prediction of metastasis, recurrence, and response to therapy. Moreover, these biomarkers may be exploited in the development of personalized targeted therapies that can distinguish between the 15 diverse meningioma subtypes.

A series of waterborne polyurethane (WBPU)/modified lignin amine (MLA) adhesives was prepared using modified lignin amine (MLA) as a chain extender by a prepolymer mixing process. A successful Mannich reaction was achieved during the synthesis of MLA by reacting lignin with bis(3-aminopropyl)amine. Higher tensile strength, Young’s modulus and thermal stability were recorded for WBPU/MLA adhesives with higher MLA contents. The WBPU/MLA adhesive materials were used to coat PVC substrates. The adhesive strength increased with increasing MLA content. More importantly, the MLA also enhanced the WBPU/MLA coating in terms of adhesive strength at moderately high temperatures as well as under natural weather exposed conditions. The adhesive strength was essentially unaffected with 6.48 mole% MLA in the WBPU/MLA coating after exposure to natural weather conditions for 180 days.

The shape memory alloys belong to the smart materials thanks to their thermomechanical proprieties' reply to thermal or to mechanical loading. These materials can change shape, stiffness, displacement, natural frequency, and many mechanical characteristics in response to stress or to heat such as conduction, convection or radiation. However, heating by convection or conduction are the most useful and studied methods unlike radiation. Therefore, this paper aims to study the radiation effect on the shape memory alloy behavior

Three kinds of inorganic alkali are introduced into tetraethylenepentamine (TPEA) and polyethyleneimine (PEI) modified MCM-41 as the CO2 adsorbents. FT-IR and TGA are used to characterize the surface groups and the thermal stability of adsorbents. Chemical titration method is used to measure the alkali amounts of adsorbents. Thermo-gravimetric analysis with 10%CO2/N2 as the simulated flue gas is used to test the CO2 adsorption performance of adsorbents. The results show that all three kinds of inorganic alkali containing adsorbents exhibit promoted CO2 adsorption capability than traditional TPEA and PEI modified samples. Ca(OH)2 and PEI modified samples exhibit the highest adsorption capacity and stable regeneration property. The introduction of inorganic alkali changes the chemical adsorption mechanism between CO2 and increases the effective alkali amounts due to its hydroxyl groups. The CO2 adsorption capacities have a linear dependence relation with the alkali amounts of adsorbents, indicating that alkali amount is a critical factor for novel adsorbents exploring.

Dynamic visualizations have been developed to exchange information that transforms over time across a broad range of professional and academic contexts. However, these visual tools may impose substantial demands on the learner’s cognitive resources that are very limited in current knowledge. Cognitive load theory has been used to improve learning from dynamic visualizations by providing certain design techniques to manage learner cognitive load without adding any oral/written explanations. This systematic review examined a series of experimental studies assessing the roles of these design techniques in learning tactical scenes of play through dynamic visualizations. Electronic databases PubMed and Google Scholar were used to search relevant articles. Eleven studies were eventually included for the systematic review based on the eligibility criteria. The present review revealed that adapting design techniques to the level of learners’ expertise, type of depicted knowledge, and level of content complexity is a crucial part of effective learning.

Corrosion inhibitors are the natural or synthetic compounds that have the ability to inhibit the average of corrosion and reduce the damage of the mild steel. Enormous organic inhibitors nowadays employed in the corrosion domain but excluded due to costly. Comparatively cheap, and stable organic compound, namely 3-((4-nitrobenzylidene)amino)coumarin, have been utilized as an excellent corrosion inhibitor in hydrochloric acid for mild steel. The inhibition efficiency has been figured regarding to weight loss method. The corrosion inhibitor was identified according to spectroscopic techniques namely Fourier transform infrared and nuclear magnetic resonance in addition to micro-elemental analysis. Inhibition efficiency for the studied inhibitor was 71.4% that, at the highest studied concentration.

The objective of this study is to conduct a mineralogical and chemical characterization of the mortars Roman archaeological site of Volubilis to rebuild spare mortars for restoration. We take samples of mortar, broken tile palate garden, and pavement mosaic Falavius Germanus houses. The analysis by X-ray diffraction reveals the coarse mortar Flavius Germanus is made of quartz and calcite with feldspar and probably, mica and dolomite in small amounts. The binder end is formed calcite and quartz. However, the broken tile mortar is formed by coarse particles, clay base mixed with a binder phase dominated by calcite. These results allowed us to reformulate spare mortars for the restoration of damaged Roman mosaics. The mortars are made up by 63.6% of lime and 36.4% of sand(with 4.19% of large grain, 71, 04% of coarse sand, 24.22%, of fine sand and 0.55% fines parts).The performance of these mortars was tested by mechanical testing.

Abstract: Cherubism is a rare genetic disorder characterized by painless bilateral expansion of the mandible and maxilla. We present an unusual case of a 50-year-old female patient with Ramon syndrome, a rare variant of cherubism, accompanied by gingival fibromatosis. The patient exhibited symptoms of short stature, mental retardation, rheumatoid arthritis, epilepsy, hirsutism, and gingival enlargement. Clinical examination revealed generalized gingival inflammation with plaque and attachment loss. Radiographically, bilateral defined multilocular radiolucencies were observed in the mandibular body and ramus. The patient underwent a non-surgical phase, including oral hygiene motivation and periodontal debridement, followed by a surgical phase involving gingivoplasty and internal bevel gingivectomy with open flap debridement. Histopathological analysis confirmed the presence of fibroblasts, multinucleated giant cells, and fibrous connective tissue. The patient's son also presented with bilateral facial swelling and similar radiographic findings, indicating familial inheritance of cherubism. The case demonstrates the clinical, radiographic, and histopathological features of cherubism associated with gingival fibromatosis and highlights the challenges in diagnosis and management. Regular follow-up and maintenance are essential for long-term stability and prevention of recurrence. This report contributes to the limited literature on cherubism in older patients and emphasizes the importance of early identification and intervention in affected individuals.

The stringency of GMO regulation affects trade of agricultural products among countries. On that account, our investigation attempts to shed the light on the complexity of the impact of genetically modified organisms (GMO) regulations among countries on bilateral trade with a focus on GMO approvals. We develop a framework extending Xiong and Beghin (2014) and their decomposition of export supply and imports demand effects. Our approach encompasses the supplemental effect of GMO regulation laxity in production on the exporter’s productivity. It decomposes three effects that impact bilateral trade flows between trade partners: productivity in the source country, sorting cost from bilateral dissimilarity in regulations, and stringency impact on import demand. We estimate the model using a panel dataset of corn trade and two econometric approaches (PPML, Heckman sample-selection). We find that GMO laxity in production of exporters has the most prominent and robust effect of enhancing bilateral trade of corn. The effect of GMO laxity in demand appears to be smaller than the export booster effect of GMO adoption. Finally, bilateral dissimilarity in regulations does not appear to matter, once we account for the impact of GMO in production of the exporters and laxity in demand differentiated for importer and exporters. Hence, GMO approval regulations have dominating multilateral effects rather than bilateral ones.

Persistent organic pollutants (POPs) accumulation and hypoxia are two factors proposed to adversely alter adipose tissue (AT) functions in the context of excess adiposity. Studies have shown that preadipocytes exposure to dioxin and dioxin-like POPs have the greatest deleterious impact on rodent and immortalized human preadipocyte differentiation, but evidence on human preadipocytes is lacking. Also, hypoxia is known to strongly interfere with the dioxin-response pathway. Therefore, we tested the effects of pre-differentiation polychlorinated biphenyl (PCB)126 exposure and subsequent differentiation under hypoxia on human subcutaneous adipocytes (hSA) differentiation, glucose uptake and expression of selected metabolism- and inflammation-related genes. Pre-differentiation PCB126 exposure lowered the ATP content, glucose uptake and leptin expression of mature adipocytes but had limited effects on differentiation under normoxia (21% O2). Under hypoxia (3% O2), preadipocytes ability to differentiate was significantly reduced as reflected by significant decreased lipid accumulation and downregulation of key adipocyte genes such as PPARγ and adiponectin. Hypoxia increased glucose uptake and GLUT1 expression but abolished the adipocytes insulin response and GLUT4 expression. Expression of pro-inflammatory adipokine IL-6 was slightly increased by both PCB126 and hypoxia, while IL-8 expression was significantly increased only following the PCB126-hypoxia sequence. These observations suggest that PCB126 do not affect human preadipocyte differentiation, but do affect the subsequent adipocytes population, as reflected by lower ATP levels and absolute glucose uptake. On the other hand, PCB126 and hypoxia exert additive effects on AT inflammation, an important player in the development of chronic diseases such as type 2 diabetes and cardiovascular diseases.

The aim of this paper is the presentation of an analytical model of insulator flashover and its application for air at atmospheric pressure and pressurized SF6. After a review of the main existing models in air and compressed gases, we develop a relationship of flashover voltage on the basis of an electrical equivalent circuit and the thermal properties of the discharge. The model includes the discharge resistance, the insulator impedance, and the gas interface impedance. The application of this model to a cylindrical resin-epoxy insulators in air medium and SF6 gas with different pressures gives results close to the experimental measurements.

Due to its application as an anti-cancer drug, pazopanib (1) has attracted the interest of many researchers and several studies on pazopanib synthesis have been reported over the years. This paper provides a novel route for synthesizing N,2,3-trimethyl-2H-indazol-6-amine (5) which is a crucial building block in the synthesis of pazopanib from 3-methyl-6-nitro-1H-indazole (6). By alternating between the reduction and two methylation steps compound 5 was obtained in comparable yield (55.0%) to what has been reported (54%). Noteworthy, the last step of N2-methylation also yielded N,N,2,3-tetramethyl-2H-indazol-6-amine (5’) as a new compound ever reported. Furthermore, the data presented in this paper can serve as instrumental for future research aimed at further refining the synthesis process of pazopanib.

The present work is focused on the numerical solution of the complete energy equation used in fluid film lubrication. The work was motivated by the fact the complete energy equation has no analytic solution that could be used for validations. Its accuracy and computation time are related to the employed numerical method and to the grid resolution. The natural discretization method (NDM) applied on different grids is systematically compared with the spectral method (the Lobatto Point Colocation Method or LPCM) with different polynomial degrees. A one dimensional inclined slider is used for the numerical tests and the energy equation is artificially decoupled from Reynolds. This approach enables to focus all the attention on the numerical solution of the energy equation. The results show that the LPCM is one or two orders of magnitudes more efficient than the NDM in terms of computation time. The energy equation is then coupled with Reynolds equation in a thermo-hydrodynamic analysis of the same 1D slider; the numerical results confirm again the efficiency of the LPCM. A thermo-hydrodynamic analysis of a two-lobe journal bearing is then presented as a practical application.

This work proposes a hollow-core photonic crystal fiber-based edible oil sensor in the terahertz (THz) range (e.g., 1.0THz ≤ f ≤ 3.0THz) and different sensing characteristics are numerically analyzed. The suggested sensor’s performance was assessed by means of COMSOL Multiphysics, a commercial program that uses the finite element approach. The computational results indicate that the relative sensitivity is 85.591%, 84.648%, 82.625%, 82.683%, and 79.161%, respectively, at f = 2.2 THz, for several types of sunflower oil, mustard oil, coconut oil, olive oil and palm oil; and the corresponding effective areas are 7.22×10-8 um2, 7.09×10-8 um2, 6.83×10-8 um2,7.09×10-8 um2, 6.5231 ×10-8 um2. In addition, the effective material loss for sunflower oil, muster oil, coconut oil, olive oil, and palm oil has been found to be 0.02561 cm-1, 0.027054 cm-1, 0.030322 cm-1, 0.028854 cm-1 ,0.035427cm-1 respectively. Moreover, the proposed sensor also has low confinement loss are 1.55×10-8 dB/m, 1.63×10-8 dB/m, 1.31×10-8 dB/m, 1.99×10-8 dB/m, 4.0345×10-8 dB/m.This proposed sensor can be fabricated using extrusion and 3D-printing technologies, and due to its augmented detecting capabilities, it can be a vital part of oil sensing devices implemented in real life such as industry fields.

This paper reports on the optimization of thin-film coating assisted self-sustainable off-grid hybrid power generation systems for cattle farming in rural areas of Bangladesh. Bangladesh is a lower middle-income country with declining rates of poverty among its 160 million people due to persistent economic growth in conjunction with balanced agricultural improvements. Most of the rural households adopt a mixed farming system by cultivating crops and simultaneously rearing livestock. Among the animals raised, cattle are considered as the most valuable asset for the small/medium-scale farmers in terms of their meat and milk production. Currently, along with the major health issue, the COVID-19 pandemic is hindering the world’s economic growth and has thrust millions into unemployment; Bangladesh is also in this loop. However, natural disasters such as COVID-19 pandemic and floods, largely constrain rural smallholder cattle farmers from climbing out of their poverty. In particular, small and medium-scale cattle farmers face many issues that obstruct them from taking advantage of market opportunities and imposing a greater burden on their families and incomes. An appropriate measure can give a way to make those cattle farmers’ businesses both profitable and sustainable. Optimization of thin-film coating assisted self-sustainable off-grid hybrid power generation system for cattle farming is a new and forward-looking approach for sustainable development of the livestock sector. In this study, we design and optimize a thin-film coating assisted hybrid (photovoltaic-battery-generator) power system by using the Hybrid Optimization of Multiple Energy Resources (HOMER, Version 3.14.0) simulation tool. An analysis of the results has suggested that the off-grid hybrid system is more feasible for small and medium-scale cattle farming systems with long-term sustainability to overcome the significant challenges faced by smallholder cattle farmers in Bangladesh.

Modern organic synthesis is majorly focused on developing environmentally benign synthetic protocols by employing green chemistry principles. Accordingly, in our recent research work, we herein report the use of modified supramolecular host cyclodextrin as an effective solid based green catalyst for accessing structurally diverse and medicinally relevant pyrimidone architectures. The catalyst and the synthesized compounds 4 (a-r) were characterized using FT-IR, NMR and GC-Mass spectroscopy. Major highlights of the reported work include: atom economical process, extremely milder reaction conditions, operational simplicity, high isolated yields, and excellent catalyst turnover number. The molecular docking studies suggest that the compound 4n has the hydrogen bonding, hydrophobic and π-pair interactions with the active site of active sites of CXT M 15 receptor.

This article discuss the effects of heat treatment and lubrication modes on the machinability of an A356 alloy (Al-Si-Mg); the alloy is studied as-received, with solution heat-treated alloy (SHT) as well as with an alloy that is solution heat-treated and then aged at 155, 180 and 220 °C. In the course of machinability evaluation, several criteria including cutting force, surface roughness, tool wears and burr analysis (chip) were studied. The results and analysis in this work indicated that the selected machinability criteria are important and necessary to effectively evaluate the machinability of A356 alloys. The machinability of both materials and tools were estimated in terms of cutting force, chip thickness ratio and burr formation, flank wear and roughness. The effects of different cutting parameters (cutting speed and feed rate) and lubrication modes (dry, mist and wet) on the machinability of the A356 cast alloy were also examined. The influence of heat treatments on the burr formation and surface quality was clearly revealed by the experimental results. Experimental work revealed that cutting forces were influenced significantly by aging and cutting speed. However, the different aging at 155, 180, and 220 °C and the cutting speed significantly affected the machinability of the A356 cast alloy. The results obtained show that a better drilling performance in terms of surface quality occurs at a high feed rate, with dry drilling and artificial aging at T6.

Bangladesh's railway system mostly uses typical manual railway crossing technique or boom gates through its 2,955.53 km rail route all over the country. The accidents are frequently happening in the railway crossings due to not having obstacle detectable and quickly operating gate systems, and also for fewer safety measures in the railway crossing. Currently, there are very few automatic railway crossing systems (without obstacle detectors) available, however, all of them are dependent on the national power grid without a backup plan for any emergency cases. Bangladesh is still running a bit behind in the power generation of its consumption, hence it is not possible to have a continuous power supply at all times all over the countryside. We aim to design and develop a smart railway crossing system with an obstacle detector to prevent common types of accidents in the railway crossing points. We design to use two infrared (IR) sensors to operate the railway crossing systems which will be controlled by the Arduino Uno. This newly designed level crossing system will be run with the help of sustainable renewable energy which is cost-effective, eco-friendly, and apply under the national green energy policy towards achieving sustainable development in Bangladesh as a part of the global sustainable goal to face climate change challenges. We have summarized the simulated results of several renewable energy sources including a hybrid system and optimized the Levelized Cost of Energy (LCOE), and the payback periods.

The danger is still very large from cross site scripting attacks. When designing web applications We must follow as much as we can prevention rules and don’t leave any loophole to our programs. Experience is a great factor for programmers to know these attacks and for a trainee programmer is a difficult task to spot all the weak points. In this article we present a tutorial on launching an XSS attack and also we propose simple solutions.

Carbon sequestration via carbon capture and storage (CCS) method is one of the most useful methods to lower the CO₂ emission in the atmosphere. Ethylenediamine (EDA) and triethylenetetramine (TETA) modified mesoporous carbon (MC) has been successfully prepared as CO₂ storage materials. The effect of various concentrations of EDA or TETA added to MC as well as activated carbon (AC) on their CO₂ adsorption capacity were investigated using high purity CO₂ as feed and titration method to quantitatively measure the amount of adsorbed CO₂. The results showed that within 60 min adsorption time, MCEDA49 gave the highest CO₂ capacity adsorption (19.68 mmol/g), followed by MC-TETA30 (11.241 mol/g). The improvement of CO₂ adsorption capacity at low TETA loadings proved that the four amine functional groups in TETA gave advantages to CO₂ adsorption. TETA functionalized MC has a potential to be used as CO₂ storage materials as it is used at low concentration. Therefore, it is more benign and friendly to the environment.

The adsorption of carbon dioxide on amino silanes-functionalized MCM-41 and SBA-15 materials is reported. The functionalization of mesoporous silicas was made by post-synthesis method, by impregnation of 3-aminopropyltriethoxysilane. The obtained materials were characterized by X-ray diffraction, scanning and transmission electron microscopies, nitrogen adsorption-desorption and X-ray photoelectron spectroscopy measurements. The carbon dioxide adsorption capacities for the samples were carried out under ambient pressures. The obtained results evidenced that amino-silanes with a terminal amine (–NH₂) were functionalized through covalent coupling of this group on the surface of the channels in the ordered mesoporous silica, meaning that the amine is anchored on the surface of the bigger pores of the MCM-41 and SBA-15 support. For functionalized materials, the CO₂ adsorption capacity of the AMCM-41 increased from 0.18 to 1.1 mmol·g⁻¹, whereas for ASBA-15, it was from 0.6 to 1.8 mmol·g⁻¹. The Lagergren kinetic algorithms were applied in order to validate the obtained results, evidencing the enhanced carbon dioxide adsorption capacity and stability of the functionalized ordered mesoporous molecular sieves.

The impacts of spice (sumac, cumin, black pepper, and red pepper) extract on Gram-positive (S. aureus and E. faecalis) and Gram-negative (K. pneumonia, P. aureginosa, C. jejuni, A. hydrophila, S. Paratyphi A, and Y. enterocolitica) food-borne pathogen bacterial strains (FBP) for their antibacterial activity and accumulation of ammonia (AMN), trimethylamine (TMA), and biogenic amines (BAs) in tyrosine decarboxylase broth (TDB) were investigated. Sumac extract exhibited the highest an-tibacterial potential against all FBP followed by cumin and peppers. Ammonia (AMN) production (844.24-543 mg/L) was strongly inhibited by sumac extract (55.10 mg/L), whilst suppression of trimethylamine (TMA) production (53.66-3.21 mg/L) was observed by sumac (1.28 mg/L), followed by red pepper (0.91 mg/L) extract. Cumin extracts stimulated the production of cadaverine, spermidine, tryptamine, and 2-phenylethylamine. Furthermore, sumac extracts inhibited hista-mine and tyramine production in the majority of FBP. This research suggests the application of sumac extracts as natural preservatives for inhibiting the growth of FBP and inhibiting the pro-duction of AMN, TMA, and BAs.

The efficiency of organic solar cells (OSCs) is influenced by various factors, among which environmental temperature plays a significant role. Previous studies have shown that the thermal stability of these cells can be enhanced by incorporating a third component into their structure. Ternary organic solar cells, in particular, have shown promising results in improving thermal stability. A well-designed electron transport layer (ETL) can significantly bolster thermal stability by facilitating efficient charge transport and reducing charge recombination. In this study, we investigated the effect of temperature on the efficiency of inverted ternary structures, ranging from 300 K to 400 K. The structures examined include FTO/SnO2/PM6:D18:L8-BO/PEDOT: PSS/Ag, FTO/Spiro-OMeTAD/PM6:D18:L8-BO/PEDOT: PSS/Ag, and FTO/PC60BM/PM6:D18:L8-BO/PEDOT: PSS/Ag. Through simulations employing three different electron transport layers—SnO2, Spiro-OMeTAD, and PC60BM—we observed that at 340 K (65°C) these structures maintained 92% of their original high efficiency of ~20% at 300 K, which represents a high level of thermal stability under the high PCE condition.

In this study, a monoethanolamine aerosol growth model was developed to investigate the aerosol growth factor. Interactions among the internal conditions in an absorber were considered in this aerosol model. Additionally, an experiment was conducted to measure aerosol particle size, for collecting in-house validation data. Sucrose was used as the aerosol nuclei instead of sulfuric acid to prevent the corrosion of equipment used in the experiment. Experimental results showed that the outlet aerosol sizes increased to the same size regardless of the sucrose concentrations. The aerosol growth model was validated using the in-house experimental data. The aerosol growth model efficiently predicted the aerosol size. For investigating aerosol growth effects, particle number concentration was determined to be the primary factor affecting aerosol growth and amine emissions. When the particle number concentration increased, the aerosol size decreased, whereas the MEA emission increased.

The development of biosensors for target detection plays a crucial role in advancing various fields of bioscience. This work presents the development of a genosensor that exploits the colorimetric phenol-sulfuric acid sugar reaction for the detection of DNA, and RNA as specific targets, and DNA intercalator molecules. The biosensor combines simplicity and reliability to create a novel bio-assay for accurate and rapid analysis. A 96-well microplate based on polystyrene polymer was used as the platform for an unmodified capture DNA immobilization via a silanization process and with (3-Aminopropyl) triethoxysilane (APTES). After that, a hybridization step was carried out to catch the target molecule, followed by adding phenol and sulfuric acid to quantify the amount of DNA or RNA sugar backbone. This reaction generates a yellow-orange color on the wells measured at 490 nm that was proportional to the target concentration. Under the optimum conditions, a calibration curve was obtained for each target. The developed biosensor demonstrated high sensitivity, good selectivity, and linear response over a wide concentration range for DNA and RNA targets. Additionally, the biosensor was successfully employed for the detection of DNA intercalator agents that inhibit the hybridization of DNA complementary to the immobilized capture DNA. The developed biosensor offers a potential tool for sensitive and selective detection in various applications, including virus diagnosis, genetic analysis, pathogenic bacteria monitoring, and drug discovery.

Renewable nanocellulose materials received increased attention owing to their small dimensions, high specific surface area, high mechanical characteristics, biocompatibility, and compostability. Nanocellulose coatings are among many interesting applications of these materials to functionalize different by composition and structure surfaces, including plastics, polymer coatings, and textiles with broader applications from food packaging to smart textiles. Variations in porosity and thickness of nanocellulose coatings are used to adjust a load of functional molecules and particles into the coatings, their permeability, and filtration properties. Mechanical stability of nanocellulose coatings in a wet and dry state are critical characteristics for many applications. In this work, nanofibrillated and nanocrystalline cellulose coatings deposited on the surface of polymer films and textiles made of cellulose, polyester, and nylon are studied using atomic force microscopy, ellipsometry, and T-peel adhesion tests. Methods to improve coatings adhesion and stability using physical and chemical cross-linking with added polymers and polycarboxylic acids are analyzed in this study. The paper reports on the effect of the substrate structure and ability of nanocellulose particles to intercalate into the substrate on the coating adhesion.

The field of Cooperative Intelligent Transport Systems and more specifically Pedestrians to Vehicles could be characterized as quite challenging, since there is a broad research area to be studied, with direct positive results to society. Pedestrians to Vehicles is a type of Cooperative Intelligent Transport System, within the group of Early Warning Collision/Safety System. In this article, we examine the research and applications carried out so far within the field of Pedestrians to Vehicles Cooperative Transport Systems by leveraging the information coming from Vulnerable Road Users’, smartphones. Moreover, an extensive literature review has been carried out in the fields of Vulnerable Road Users Outdoor Localisation via smartphones and Vulnerable Road Users Next Step/Movement Prediction, which are closely related to Pedestrian to Vehicle applications and research. We identify gaps that exist in these fields that could be improved/extended/enhanced or newly developed, while we address future research objectives and methodologies that could support the improvement/development of those identified gaps.

In insects, Adipokinetic hormone is the primary hormone responsible for the mobilization of stored energy. While a growing body of evidence has solidified role of Adipokinetic hormone (AKH) in modulating the physiological and behavioral responses to metabolic stress, little is known about the upstream endocrine circuit that directly regulates AKH release. We evaluated the AKH-producing cell (APC) transcriptome to identify potential regulatory elements controlling APC activity, and found that a number of receptors show consistent expression levels, including all known dopamine receptors and the Pigment Dispersing Factor receptor (PDFR). We tested the consequences of targeted genetic knockdown and found that AKH expression of RNAi elements corresponding to each dopamine receptor caused a significant reduction in survival under starvation. In contrast, PDFR knockdown significantly extended lifespan under starvation whereas expression of a tethered PDF in APCs resulted in a significantly shorter lifespan. These manipulations caused various changes in locomotor activity under starvation. We used live-cell imaging to evaluate the acute effects of the ligands for these receptors on APC activation. Dopamine application led to a transient increase in intracellular calcium in a sugar-dependent manner. Furthermore, co-application of dopamine and ecdysone led to a complete loss of this response, suggesting that these two hormones act antagonistically. We also found that PDF application led to an increase in cAMP in APCs, and that this response was dependent on expression of the PDFR in APCs. Together these results suggest a complex circuit in which multiple hormones act on APCs to modulate metabolic state.

The synergistic features of a three-component, photoinitiating system (A/B/C) based on the measured data and proposed mechanism of Liu et al. are analyzed. The co-initiators/additives B and C have dual-functions of : (i) regeneration of photoinitiator A, and (ii) generation of extra radicals for enhanced conversion efficacy (CE). The synergistic effects led to higher CE for both free radical polymerization (FRP) and cationic polymerization (CP). The CE of FRP has 3 terms due to the direct (tyep-I) coupling of the triplet state of A with the monomer (M) and the coupling of the two radicals, R and R', with M. The CE of CP has a transient state proportional to the effective absorption constant (b), the light intensity (I) and initiator concentration (A0), but a steady state is independent of the light intensity (I). For the CE of FRP, the contribution from radical R had two cases: (i) linear dependence on T=bIA0, or (ii) nonlinear square root dependence T0.5. The synergistic effects led to higher conversion of FRP and CP, consistent with the measured results. The theoretically predicted new features include: (i) co-initiator [C] which always enhances both FRP and CP conversions, and (ii) co-initiator [B] which leads to more efficient FRP, but it also reduces CP.

Trace amines are a separate, independent group of biogenic amines, close in structure to classical monoamine neurotransmitters such as dopamine, serotonin and norepinephrine. G protein-coupled Trace Amine-Associated Receptors (TAAR) are mostly investigated for their involvement in the pathogenesis of neuropsychiatric disorders, but expression of TAAR family receptors is observed also in various populations of cells of the immune system. The review is focused on the basic information on the interaction of trace amines and their receptors with cells of the general immune system of humans and other mammals, as well as on data on TAARs role in the function of individual populations of myeloid and lymphoid cells. With further research on the regulatory role of the trace amine system in the pathogenesis of the immune response and determination of the biological mechanisms for their action it would be possible to develop new methods for treating diseases related to immune system dysfunctions.

Copper (Cu) is a critical element for cancer cell proliferation and considerably accumulates in the nucleus. 64Cu2+ is an anticancer radiopharmaceuticals targeting the copper requirement of cancer cells. However, intravenously injected 64Cu2+ ions primarily accumulate in the liver. Ligand complexation of 64Cu2+ would be a promising method for increasing tumor delivery by reducing liver uptake. Herein, we used three tripodal amine ligands [tris(2-aminoethyl)amine (Tren), diethylenetriamine (Dien), and tris(2-pyridylmethyl)amine (TPMA)] to enclose 64Cu2+ ions and compared their in vivo tumor and liver uptake using a tumor-bearing xenograft mouse model of the extrahepatic bile duct carcinoma cell line TFK-1. We examined intracellular Cu distribution using microparticle-induced X-ray emission (micro-PIXE) analysis for these compounds. 64Cu2+-Tren and 64Cu2+-Dien showed higher tumor uptake than 64Cu2+-TPMA and 64Cu2+ ions in TFK-1 tumors. Among the three 64Cu2+ complexes and 64Cu2+ ions, liver uptake was inversely correlated with tumor uptake. Micro-PIXE analysis showed that in vitro cellular uptake was similar to in vivo tumor uptake and nuclear delivery was the highest for 64Cu2+-Tren. Conclusively, an inverse correlation between tumor and liver uptake was observed using three 64Cu2+ complexes of tripodal amine ligands and 64Cu2+ ions. These results provide useful information for the future development of anticancer 64Cu radiopharmaceuticals.

Availability and continuous operation under critical conditions are very important in electric machine drive systems. However, such systems, are suffering from several type of failures that affect the electric machine or the associated voltage source inverter. Therefore, fault diagnosis and fault tolerance are highly required. This paper presents a new robust deep learning-based approach to diagnosis multiple open-circuit fault in three phase two level voltage source inverter for induction motor drive applications. The proposed approach uses fault diagnosis variables obtained from sigmoid transformation of the motor stator currents. The open-circuit fault diagnosis variables are then introduced to a Bidirectional Long Short-Term Memory algorithm to detect the faulty switch(es). Several simulation and experimental results are presented to show the proposed fault diagnosis algorithm effectiveness and robustness.

This study explores the potential of Eisenia fetida (Savigny) in vermicompost production within vermipits during winter months in the Rampur region of Uttar Pradesh, India. The vermipits were inoculated with 0.33 kg of E. fetida per pit, against the recommended rate of inoculation for assessment of real-time potential of earthworm on seasonal and regional grounds. The results revealed a significant increase in earthworm population, with three times production (4.1 kg) of the inoculated number (1.0 kg). The productivity dynamics of compost vs E. feida revealed a notable threefold and fourfold effectiveness, respectively. This dual advantage signifies the success of composting process, with the increased worm population indicating enhanced decomposition. The study attributes the combination of regional and edaphic factors viz., sandy loam soil with high humus content and good water passage, facilitating earthworm survival, reproduction and decomposition of agricultural waste. The loose and perforated soil structure allowed easy penetration of earthworms, transforming the soil into fertile compost. The research emphasizes the importance of soil moisture of semi-arid ecosystems thus highlighting the seasonal significance governing earthworm activity. The study provides insights into the mechanical ability of earthworms, its sensitivity to soil compaction and the influence of high hydration of the region. Inoculation during the winter period indicates increased earthworm activity setting the stage for enhanced compost production in the upcoming hot periods of summer months. The findings suggest that optimizing vermicomposting practices with altered feeding stocks, could further improvise compost and earthworm production and productivity in subsequent seasons. The study contributes for sustainable utilization of E. fetida in composting, its regional and seasonal efficacy turns trash to treasure for enhanced agricultural efficacy.

In dry season paddy farming, the alternate wetting and drying (AWD) irrigation improves water productivity, paddy production, and has the potential to decrease greenhouse gas (GHG) such as methane (CH4) and nitrous oxide (N2O) emissions when compared to continuous flooding (CF). However, there is a lack of research in Bangladesh on the effects of water management on CH4 and N2O emissions. During November 2017–April 2018, participatory on-farm trials were conducted at Feni and Chattogram districts of Bangladesh. Total 105 farmers comprising 20-hectare of land (62 farmers at Feni and 43 farmers at Chattogram district, each location having 10 hectare of land). We compared irrigation water and cost reductions, paddy yield, and CH4 and N2O emissions from paddy fields irrigated using AWD and CF irrigation methods. The CH4 and N2O emissions were determined using the Cool Farm Beta-3 methodology, and the global warming potential (GWP) was estimated using the Intergovernmental Panel on Climate Change-2014 standard approach. The mean results of randomly selected 30 farmers from two locations (15 of each) showed that AWD remarkably decreased irrigation water consumption by about 24% and increased water productivity by 224%. We estimated 23% savings for irrigation costs in AWD. By this time, AWD improved paddy production by 3% over CF. The AWD irrigation resulted in a 47% reduction in cumulative CH4 emissions having a lower CH4 emission factor (0.74 kg ha-1 day-1) than CF (1.39 kg ha-1 day-1). There was no obvious difference in N2O emission between AWD and CF. When compared to CF, AWD decreased the overall GWP by 27% and lowered the GHG intensity by 42%. The CH4 and N2O emissions did not differ substantially between Feni and Chattogram.

There is a case about a system comprising two queues of M/M(a)/1/K with a due date with FCFS service policy in each queue. Using the methods of simulation and mathematical analysis, the solution diagrams were illustrated for the fixed due date Ɵ=1 second at the phase of due date up to the commencement of the service, limited capacity K₁=5 and K₂=4, for both scenarios of different service management rate resulted. For the analytical solution, first, a SAN model from the system was created in the Mobius tool. For simulation, a java discrete systems simulation code was used. Adjustment of the initial values, selection of the scenarios for service rate, the number of the consumers in the simulation, etc. were all carried out in the simulation code.

Trace amine-associated receptors (TAARs) are a family of G protein-coupled receptors present in mammals in the brain and in several peripheral organs. Apart from its olfactory role, TAAR5 is expressed in the major limbic brain areas and regulates brain serotonin functions and emotional behaviors. However, most of its functions remain undiscovered. Given the role of serotonin and limbic regions in some aspects of cognition, we used a temporal decision-making task to unveil a possible role of TAAR5 in cognitive processes. We found that TAAR5 knock-out (KO) mice showed a generally better performance due to a reduced number of errors and displayed a greater rate of improvement at the task than WT littermates. However, task-related parameters, such as time accuracy and uncertainty have not changed significantly. Overall, we show that TAAR5 modulates specific domains of cognition, highlighting a new role in brain physiology.

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.

This study introduces a novel nanocomposite coating composed of PANI/CeO2 nanocomposite films, aimed at addressing corrosion protection needs. Analysis through FTIR spectra and XRD patterns confirms the successful formation of the nanocomposite films. Notably, the PANI/CeO2 nanocomposite films exhibit a hydrophilic nature. The bandgap energy of the PANI composite film measures at 3.74 eV, while the introduction of CeO2 NPs into the PANI matrix reduces the bandgap energy to 3.67 eV. Furthermore, the electrical conductivity of the PANI composite film is observed to be 0.40 S.cm-1, with the incorporation of CeO2 NPs leading to an increase in electrical conductivity to 1.07 S.cm-1. To evaluate its efficacy, electrochemical measurements were conducted to assess the corrosion protection performance. Results indicate a high protection efficiency of 92.25% for the PANI/CeO2 nanocomposite film.

A convolutional neural network (CNN) is sometimes understood as a black box in the sense that while it can approximate any function, studying its structure will not give us any insights into the nature of the function being approximated. In other terms, the discriminative ability does not reveal much about the latent representation of a network. This research aims to establish a framework for interpreting the CNNs by profiling them in terms of interpretable visual concepts and verifying them by means of Integrated Gradient. We also ask the question, "Do different input classes have a relationship or are they unrelated?" For instance, could there be an overlapping set of highly active neurons to identify different classes? Could there be a set of neurons that are useful for one input class whereas misleading for a different one? Intuition answers these questions positively, implying the existence of a structured set of neurons inclined to a particular class. Knowing this structure has significant values; it provides a principled way for identifying redundancies across the classes. Here the interpretability profiling has been done by evaluating the correspondence between individual hidden neurons and a set of human-understandable visual semantic concepts. We also propose an integrated gradient-based class-specific relevance mapping approach that takes the spatial position of the region of interest in the input image. Our relevance score verifies the interpretability scores in terms of neurons tuned to a particular concept/class. Further, we perform network ablation and measure the performance of the network based on our approach.

A simple model is developed for membrane fouling, taking into account two main fouling phenomena: cake formation, due to attached solids onto the membrane surface and pores clogging, due to retained compounds inside the pores. The model is coupled with a simple anaerobic digestion model for describing the dynamics of an Anaerobic Membrane BioReactor (AnMBR). In simulations, we investigate its qualitative behavior: it is shown that the model exhibits satisfying properties in terms of flux decrease due to membrane fouling. Comparing simulation and experimental data, the model is shown to predict quite well the dynamics of an AnMBR. The simulated flux best fits the experimental flux with a correlation coefficient r2=0.968 for the calibration data set and r2=0.938 for the validation data set. General discussions are given on possible control strategies to limit fouling and optimize the flux production. We show in simulations that these strategies allow one to increase the mean production flux to 33 L/(h.m2), whereas without control it was 18 L/(h.m2).

This scoping review comprehensively explores the existing literature on fenugreek (Trigonella foenum-graecum), a versatile herb known for its culinary and traditional medicinal uses. The review focuses on two key aspects: the hypoglycemic mechanism of fenugreek and its impact on milk production in breastfeeding women. By systematically analyzing and synthesizing the available evidence, this review aims to enhance our understanding of fenugreek's potential applications and identify research gaps for future systematic reviews. The search strategy targeted English-language animal studies published within the last five years that specifically investigated fenugreek's hypoglycemic mechanism and its effects on milk production. A total of 15,236 articles were initially identified from databases such as PubMed, Sci finder and ScienceDirect. After a rigorous selection process, including thorough evaluation of titles, abstracts, and full-texts, a subset of articles (including those titled "Impact of Fenugreek on Milk Production in Rodent Models of Lactation Challenge" and "Fenugreek Stimulates the Expression of Genes Involved in Milk Synthesis and Milk Flow through Modulation of Insulin/GH/IGF-1 Axis and Oxytocin Secretion") were included for detailed analysis. The findings 18 articles from the included studies demonstrate promising results regarding fenugreek's potential to stimulate milk production and regulate blood glucose levels. However, further research is necessary to unravel the underlying molecular pathways, establish optimal dosage guidelines, and assess long-term side effects. Overall, this scoping review offers valuable insights for lactating women seeking to enhance milk production and individuals managing blood sugar levels, providing potential alternative approaches for supporting lactation and glycemic control.

Modern engineering faces challenges in ensuring technical standards for service, durability, and sustainability. Political, administrative, and budgetary factors, coupled with climate change, pose tasks to structural integrity, affecting industries and economies. Marine infrastructures represent a strategic asset of the country as it handles a large part of the economic exchanges. This article analyzes five essential factors that play a fundamental role in the performance analysis of coastal structures: Chloride-induced corrosion, degradation models, maintenance strategies, monitoring, and climate change. Starting with reinforcement corrosion, considered as the main cause of distress, particularly in coastal zones for the long-term behavior of structures. Additional pressure from the influences of climate change is becoming evident and extreme, leading to reduction in capacity. To guarantee the lifespan, degradation models contribute by estimating the long-term performance of the asset as a strategic piece to the development of effective maintenance solutions. Additionally, quantifying the condition of the structure from monitoring data, plays a crucial part that provides information on the current situation of the structure. Finally, this review summarizes the challenges associated with the maintenance of aging marine structures considering aspects such as corrosion, monitoring, and the future challenges this area will face due to climate change.

Climate data are important in building a hydrological risk assessment model. The ClimInonda web application enables interactive and dynamic visualizations of different data collected from different weather stations in the study area on a single platform, allowing users to explore and analyze data in an easy way. This can assist decision-makers and stakeholders in understanding the current state of the environment and in identifying areas of flooding risk. Visualizations can include different types of data, such as satellite imagery, weather data, and terrain data, and can be displayed using various techniques, such as heat maps, contour maps, and 3D models by providing easy-to-understand visualizations. The different stations of the Gafsa and Kasserine governorates in the study area are included and other stations of the Algerian territory (Tebessa governorate) are incorporated. This web application also provides the capability to include each user's stations.

A possible way to valorize citrus peels, which are byproducts of the juice extraction industry, is to use them as natural biopreservatives. In this paper we present early results from a compared Solvent Free Microwave Extraction (SFME) with Hydro-Distillation (HD) and Cold Pressing (CP) of essential oils (EOs) using fresh orange peel (Citrus sinensis L. var. Valencia late), a by-product in the production of orange juice in Algeria. The EOs were analyzed by gas chromatography coupled to mass spectrometry (GC-MS). All extracted C. sinensis EOs were chemotype limonene (94.64 to 95.48%). SFME is performed without added any solvent or water. SFME increases EO yield and eliminate wastewater treatment, resulting in a great progress in terms of time and cost efficiency. In its second part, the present study was conducted to evaluate “in vitro”, the antioxidant activities of Solvent Free Microwave (SFM) extracted orange EO by using the DPPH• (2,2-di-phenyl-1-picrilhydrazyl) free radical scavenging assay. The ability of orange EO to scavenge the free radical DPPH• was high, exceeding 80%. The result of the DPPH assay gives an IC₅₀ range value of 89.25 μg/mL (0.09 mg/mL) for the studied sample. Accordingly to the scientific literature, C. sinensis EO tested in the present study presented strong antioxidant activity, when looking to its values of AAI = 1.12 μg/mL. The feasibility of biopreservation used EOs as an alternative to synthetic techniques for liquid whole egg (LWE) stored under commercial retail conditions was investigated. The orange EO extracted by SFM was screened for its antibacterial and antioxidant activities in LWE at concentrations of 0.1, 0.3 and 0.5%. The TBA-RS results showed that the EO treatments significantly (p < 0.05) reduced the lipid oxidation in LWE. The long term oxidative, microbial and organoleptical stability of the LWE during display was positively influenced by orange EO treatments. Therefore, the results obtained here confirm that EO treatment as a promising technology to extend the commercial shelf-life of liquid egg products during retail/display.

The synthesis of the presented benzo[d]thiazol-2-amine derivatives was performed by condensing-(4-chlorobenzylidene) benzo[d]thiazol-2-amine with a number of substituted phenols in the presence of potassium iodide and anhydrous potassium carbonate in dry acetone. IR spectroscopy, 1HNMRspectroscopy and spectroscopy methods were used to characterize the structural properties of newly synthesized derivatives. In order to observe the attributes of drug-like candidates of these derivatives, the number of their molecular properties was estimated. Benzo[d]thiazol-2-amine derivatives were molecularly docked with selective enzymes COX-1 and COX-2. Findings suggested that Compounds G3, G4, G6, G8 and G11 possess higher binding affinity than diclofenac sodium, when docking was performed with enzyme COX-1. Compounds G1, G3, G6, G8and G10 showed lower binding affinity than Indomethacin when docking performed with enzyme COX-2.In vitro evaluation of the COX-1 and COX-2 enzyme inhibitory activities were performed for synthesized compounds. Compounds 10 and 11 exhibited significant COX-1 and COX- enzyme inhibitory action with IC50 values of 5.0 and 10 µM, respectively. Using the hot plate method and the carrageenan-induced rat paw edema model, the synthesized compounds were screened for their biological activities, including analgesic and anti-inflammatory activities. The highest analgesic action was exhibited by derivative G11and the compound G10 showed the highest anti-inflammatory response.

According to many researchers, Abstraction is the basis of mathematics, computing, counting devices, and computer science and engineering. What is more, all of the above deal with complexity management in some way, and abstraction is the most basic mechanism of complexity management.Generative software development - whether in the sense of empowering humans by machine to create software or in the sense of reusing products - has been and is one of the serious concerns and goals of software engineering. The interesting thing is that in both views of generativity, the main issue is still, in a way, complexity management: whether this complexity management is to achieve diversity and reuse management (Czarnecki’s approach) or to Structuring from existing structures (the approach of Alexander and his followers in an object-oriented society).In this article, we will first look at complexity and its various definitions. The definitions that show, despite the different perspectives on complexity in different disciplines and domains, all point in one direction. We will conclude that complexity is rooted in multiplicity. In the following, we will formally define complexity. In the following discussion, we will look at the generative patterns of software development, and then we will look at the complexity management patterns at seven levels.In this article, the author has tried to maintain a comprehensive approach to complexity and to consider the approaches of different domains to complexity.

The novel Ionized Gas Thermoelectric Generator (IG-TEG) system that has been studied theoretically showing capabilities to continually extracting energy from the thermal energy of the ambient air, at low temperatures within the standard room temperature and below. This system does not need a temperature gradient in order to work, unlike the other TEGs that use Seebeck effect, and therefore this new system can be utilized for cooling purposes, by extracting energy instead of wasting energy in compressing the gas for cooling. This novel system was designed based on Static Ratchet Potential (SRP), which is known as a spatially asymmetric electric potential produced by an array of positive and negative electrodes. The ratchet potential produces electrical current from random Brownian Motion of charged particles that are driven by thermal energy. Ratchet potential was studied and investigated by several researches in the fields of sensing and energy harvesting. The main ratchet potential system parameter is the particles transportation, this parameter was studied under the condition of flashing ratchet potentials, and was analyzed based on several methods. In this study, a different approach is pursued to estimate particles transportation, by evaluating the charged particles distribution, and applying the other conditions of the SRP.

Mercury (Hg (II)) contamination is indefatigable global hazard which causes severe permanent damages to human health. Extensive research has been carried out to produce mercury adsorbents however they are still facing certain challenges limiting their upscaling. Herein we reported the synthesis of novel amine impregnated inverse vulcanized copolymer for effective mercury removal. Poly(S-MA) was prepared using sulfur and methacrylic acid employing inverse vulcanization method following by functionalization. The polyethylenime (PEI) was impregnated on poly(S-MA) to increase the adsorption active sites. The developed adsorbent was then characterized using Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). FTIR confirmed formation of copolymer and successful impregnation of PEI and SEM revealed composite porous morphology of the copolymer. Amine impregnated copolymer (amine@poly(S-MA)) outperformed poly(S-MA) in mercury as it showed 20 % superior performance with 44.7 mg/g maximum adsorption capacity. The adsorption data best fits the pseudo second order which indicates that the chemisorption is most influential mechanism in this case indicating the involvement of NH2 in mercury removal. The adsorption is mainly monolayer on homogenous surface as indicated by 0.76 value of Redlich-Peterson exponent (g) which describes the adsorption nature advent from R2 value of 0.99.

In this paper, we compile the fractional power series method and the Laplace transform to design a new algorithm for solving the fractional Volterra integro-differential equation. For that, we assume the Laplace power series (LPS) solution in terms of power q=1m,m∈Z+, where the fractional derivative of order α=qγ for which γ∈Z+. This assumption will help us to write the integral, the kernel, and the nonhomogeneous terms as a LPS with the same power. The recurrence relations for finding the series coefficients can be constructed using this form. To demonstrate the algorithm's accuracy, the residual error is defined and calculated for several values of the fractional derivative. Two strongly nonlinear examples are discussed to provide the efficiency of the algorithm. The algorithm gains powerful results for this kind of problem. Under Caputo meaning the obtained results are illustrated numerically, and graphically. Geometrically, the behavior of the solution declares that the changing of the fractional derivative parameter values' in their domain alters the style of the attained solution in a symmetrical meaning and fully coinciding to the ordinary derivative value'. From these simulations, the results report that the recommended novel algorithm is a straightforward, accurate, and superb tool to generate analytic-approximate solutions for Integral, and integro-differental equations of fractional order.

The rapid expansion of livestock production sector to meet the world population demand is posing a big challenge to environmental sustainability. Plant-based feed additives extracted from food by-products could potentially result in a double outcome: improving animal zootechnical performances and mitigating environmental impacts of meat production chains. This presented study was carried out to assess the environmental impacts of the supplementation of a commercial Citrus extract feed additive (CEFA) in swine and broiler farming. Life cycle assessment (LCA) was applied to assess the impact of manufacturing and distributing 1 bag of 25 kg of CEFA and its use in feed in broiler and swine productions. With regard to CEFA manufacturing and distribution, results showed that the majority of impact came from the production of CEFA ingredients, accounting for 70% impact generated. The remaining 30% effect was divided to transportation to customer (25%), CEFA packaging (3%), CEFA manufacture, and production loss (2%). When enlarging the scope, the use of CEFA in piglet and broiler diets showed improving the measured environmental indicators, compared to such standard systems. Indeed, feed supplemented CEFA have demonstrated in elevating zootechnical performances, hence saving feed consumed. Consequently, that helped reduce environmental issues from animal feed ingredients’ agriculture. To be more specific, the supplementation of 25 kg of CEFA in feed led to a reduction of 6 tons of CO2 emitted along the life cycle of broiler production and 5 tons in the case of fattening pig. 0.7 hectares of land used had been saved as well as, 201 m3 of water (broiler) and 82 m3 (swine) were economized. Environmental performance assessment showed the interest in using this CEFA in swine and broiler diets to mitigate the environmental impacts.

One of the major concerns in structural health management (SHM) is the early detection of a growing crack. Using this, future damage due to crack propagation can be mitigated or eliminated by implementing proper repair and maintenance. Acoustic Emission (AE) is a non-destructive testing (NDT) method with potential applications for locating and monitoring fatigue cracks. The research presented in this paper focuses on SHM using AE. A novel AE signal analysis approach was proposed in order to detect crack initiation and assess small crack lengths. Experimental investigation indicated that initiation of a crack could be identified through the statistical analysis of the resulting features of the AE signals. A probabilistic AE-based model for small fatigue crack sizing was developed and the uncertainties of the model were estimated. In addition, a probabilistic model validation approach was implemented to confirm accurate estimation of the results. The outcome of this research can be used to evaluate the integrity of structures under fatigue loading. The proposed approach can also be applied as an approach to manage health and assess prognosis of structures.

Newcastle Disease (ND) remains a critical disease affecting poultry in sub-Saharan Africa. In some countries, repeated outbreaks have a major impact on local economies and food security. Recently, we developed an adenovirus-vectored vaccine encoding the Fusion protein from an Ethiopian isolate of Newcastle Disease Virus (NDV). The adenoviral vector was designed and a manufacturing process developed in the context of the Livestock Vaccine Innovation Fund initia-tive funded by the International Development Research Centre (IDRC) of Canada. The industrial-ly-relevant recombinant vaccine technology platform is being transferred to the National Veteri-nary Institute (Ethiopia) for veterinary applications. Here, we demonstrate that the instillation of the adenoviral vector through the nasal cavity can confer protection to chickens against a lethal challenge with NDV. A manufacturing process using HEK293 suspension cells cultured in stirred-tank bioreactor for the vaccine production is proposed. Taking into consideration supply chain limitations, options for serum-free media selection have been evaluated. A streamlined downstream process including a filtration, an ultrafiltration and a concentration step was de-veloped. With high volumetric yields (infectious titers up to 5 x 109 TCID50/mL) in the culture su-pernatant, the final formulations were prepared at 1010 TCID50/mL, either in liquid or lyophi-lized forms. The liquid formulation was suitable and safe for mucosal vaccination and was sta-ble for 1 week at 37˚C. Both liquid and lyophilized formulations were stable after 6 months of storage at 4˚C. Overall, a manufacturing process for adenovirus vectored vaccine was developed and protective doses were determined using a convenient route of delivery. Formulation and storage conditions were established, and quality control protocols were implemented.

This research project focuses on the optimization of the hybrid energy system together with the assistance of thin-film coatings aiming to achieve self-sustainable food and crop storage facilities which will run effectively with its own generated energy. An infrastructure will be designed and constructed that will comprise a hybrid power generation system accompanied by thin-film coated semitransparent and non-transparent construction materials for energy saving. Thin-film low emissivity (Low-E) type coatings will assist the transparent or semitransparent construction materials to reflect most of the infrared (IR-mostly heat) and UV spectra of sunlight without interrupting the visible spectrum and will lead to saving energy consumption by reducing the heat and lighting during day time

Lysine plays a crucial role in promoting development, enhancing immune function, and improving the function of central nervous system tissues. The two configurational isomers of amino acids have significantly different effects. Currently, methods for chiral recognition of lysine all have drawbacks such as expensive equipment and complicated detection processes, whereas fluorescence analysis boasts high sensitivity, strong selectivity, and simple operation. In this study, we synthesized four novel Binaphthyl-Amine (BINAM)-based fluorescent probes capable of specifically identifying the L-configuration of lysine among the twenty amino acids constituting human proteins. The enantiomeric fluorescence enhancement ratio (ef or ΔIL/ΔID) reached up to 15.29, demonstrating high enantioselectivity. We also evaluated the probe's recognition ability under different pH, reaction times, and metal ion conditions, as well as the Limit of Detection of the probe. Our findings indicate that this probe is a highly stable tool for detecting chiral lysine.

Propagation of human cytomegalovirus (CMV) in cultured cells results in genetic adaptations that confer improved growth in vitro and significant attenuation in vivo. Mutations in RL13 arise quickly during cell culture passage, while mutations in the UL128-131A locus emerge later during fibroblast passage and disrupt expression of a glycoprotein complex that is important for entry into epithelial and endothelial cells. As in vivo CMV replicates in the context of host antibodies, we reasoned that antibodies might mitigate the accumulation of adaptive mutations during cell culture passage. To test this, CMV in infant urine was used to infect replicate fibroblast cultures. One lineage was passaged in the absence of CMV-hyperimmuneglobulin (HIG) while the other was passaged with HIG in the culture medium. The former lost epithelial tropism and aquired mutations disrupting RL13 and UL131A expression, whereas the latter retained epithelial tropism and both gene loci remained intact after 22 passages. An epitheliotropic RL13+/ UL131A+ virus was isolated by limiting-dilution in the presence of HIG and expanded to produce a working stock sufficient to conduct cell tropism experiments. Thus, culture in the presence of antibodies may facilitate in vitro experiments using viruses that are genetically more authentic than has been previously possible.

COVID-19 is a severe global problem, and AI can play a significant role in preventing losses by monitoring and detecting infected persons in early-stage. This paper aims to propose a high-speed and accurate fully-automated method to detect COVID-19 from the patient's CT scan images. We introduce a new dataset that contains 48260 CT scan images from 282 normal persons and 15589 images from 95 patients with COVID-19 infections. At the first stage, this system runs our proposed image processing algorithm to discard those CT images that inside the lung is not properly visible in them. This action helps to reduce the processing time and false detections. At the next stage, we introduce a novel method for increasing the classification accuracy of convolutional networks. We implemented our method using the ResNet50V2 network and a modified feature pyramid network alongside our designed architecture for classifying the selected CT images into COVID-19 or normal with higher accuracy than other models. After running these two phases, the system determines the condition of the patient using a selected threshold. We are the first to evaluate our system in two different ways. In the single image classification stage, our model achieved 98.49% accuracy on more than 7996 test images. At the patient identification phase, the system correctly identified almost 234 of 245 patients with high speed. We also investigate the classified images with the Grad-CAM algorithm to indicate the area of infections in images and evaluate our model classification correctness.

Abstract: Thermostability of vaccines, particularly enveloped viral vectored vaccines, remains a challenge for their delivery wherever needed. Freeze-drying of viral vectored vaccines is a prom-ising approach but remains challenging due to the water removal process from the outer and in-ner parts of the virus. In the case of enveloped viruses, freeze-drying induces increased stresses on the envelope, which often leads to inactivation of the virus. In this study, we design a method to freeze-dry a recombinant Vesicular Stomatitis Virus (VSV) expressing the SARS-CoV-2 spike glycoprotein. Since the envelope of VSV is composed of 50% lipid and 50% protein, the formula-tion study focused on both the protein and lipid portions of the vector. Formulations were pre-pared primarily using sucrose, trehalose, and sorbitol as cryoprotectants; mannitol as a lyopro-tectant; and histidine as a buffer. Initially, the infectivity of rVSV-SARS-CoV-2 and cake stability were investigated at different final moisture contents. High recovery of the infectious viral titer ( 0.5 to 1 log loss) was found at 3-6% moisture content with no deterioration of the freeze-dried cakes. To further minimize infectious viral titer loss, the composition and concentration of the ex-cipients were studied. An increase from 5 to 10% of both cryoprotectants and lyoprotectant, to-gether with the addition of 0.5% gelatin, resulted in the improved recovery of infectious virus titer and stable cake formation. Moreover, the secondary drying temperature of the freeze-drying pro-cess showed a significant impact on the infectivity of rVSV-SARS-CoV-2. The infectivity of the vector declined drastically when the temperature was raised above 20°C. Throughout a long-term stability study, formulations containing 10% sugar (sucrose/trehalose), 10% mannitol, 0.5% gelatin, and 10 mM of histidine showed satisfactory stability for six months at 2-8°C. The development of this freeze-drying process and the optimized formulation minimizes the need for a costly cold chain distribution system.

The chiral recognition of enantiomers is a topic of great importance. In this study, a straightforward and effective chiral detection strategy was developed for distinguishing between tryptophan (TRP) enantiomers. The approach involved the preparation of a magnetic molecularly imprinted chitosan (MMIC) for the sample preparation, which was combined with a nitrocellulose membrane (paper-based analytical device, PAD) integrated with D-TRP covalently-grafted polymethacrylic acid (PAD_PMA_D-TRP). The discrimination between TRP enantiomers was achieved using AuNPs as a colorimetric probe. Indeed, the presence of D-TRP rapidly induced the aggregation of AuNPs due to its strong affinity to PAD-PMA_D-TRP, resulting in a noticeable color change of the AuNPs from red to purple. On the other hand, L-TRP did not induce any color change. The chiral analysis could be easily performed with the naked eye and/or a smartphone. The developed method exhibited a detection limit of 3.3 µM and it was successfully applied to detect D-TRP in serum samples, demonstrating good recovery rates. The proposed procedure is characterized by its simplicity, cost-effectiveness, rapidity, and ease of operation.

The authors present a novel sensing platform for a disposable electrochemical, non-enzymatic glucose sensor strip at physiological pH. The sensing material is based on dendritic gold nanostructures (AuNs) resembling feather branches, which are electrodeposited onto a Laser-scribed 3D-Graphene electrode (LSGE). The LSGEs were fabricated via a one-step laser scribing process on a commercially available polyimide sheet. This study investigates several parameters that influence the morphology of the deposited Au nanostructures and the catalytic activity towards glucose electro-oxidation. The electrocatalytic activity of AuNs-LSGE was evaluated using Cyclic Voltammetry (CV), Linear Sweep Voltammetry (LSV), and Amperometry, and was compared to commercially available carbon electrodes prepared under the same electrodeposition conditions. The sensor demonstrated good stability and high selectivity of the amperometric response in the presence of interfering agents, such as ascorbic acid, when a Nafion membrane was applied over the electrode surface. The proposed sensing strategy offers a wide linear detection range, from 0.5 to 20 mM, which covers normal and elevated levels of glucose in the blood, with a detection limit of 0.21 mM. The AuNs-LSGE platform exhibits great potential for use as a disposable glucose sensor strip for point-of-care applications, including self-monitoring and food management. Its non-enzymatic features reduce dependence on enzymes, making it suitable for practical and cost-effective biosensing solutions.

This article presents, for the first time, the kinetics and the general conversion features of free radical polymerization (FRP) in a 3-component system (A/B/N), with [A] being the initiator, and [B] and [N] are additives, based on the proposed mechanism of Rahal et al. Higher FRP can be achieved by additives [B] and [N], via the dual function of (i) regeneration [A], and (ii) generation of extra radicals (R) via the radicals (S' and S) produced by N.The initiator (coumarin) shows a dual photo-oxidation and photo-reduction character for high efficacy. The FRP conversion efficacy (CE) depends not only on the property of the initiator [A], the additives [B] and [N}, but also the types of monomers. For example, when [A]=CoumC, [A]/NPG is more efficient than [A]/Iod, but revserse trend occurs in some monomers. However, 2-component systems (with CE=0% to 80%) are always less efficient than that of 3-component systems (with CE=70% to 86%, in TMPTA). Specific systems with [A]=coumarins, [B]=Iodonium salt, and N=NPG are analyzed. Analytical formulas for the role of each component concentration, light intensity and coupling rates on the conversion efficacy are derived.

The growing concerns about floods have highlighted the need for accurate and detailed precipitation data as extreme precipitation occurrences can lead to catastrophic floods, resulting in significant economic losses and casualties. Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM-IMERG) is a commonly used high-resolution gridded precipitation dataset and is recognized as trustworthy alternative sources of precipitation data. The aim of this study is to comprehensively evaluate the performance of GPM IMERG Early (IMERG-E), Late (IMERG-L), and Run Final (IMERG-F) in precipitation estimation and their capability in detecting extreme rainfall indices over southwestern Iran during 2001-2020. The Asfezari gridded precipitation data which are developed using a dense of ground-based observation were utilized as the reference dataset. The findings indicate that the IMERG-F performs reasonably well in capturing many extreme precipitation events (defined by various indices). All the three products showed a better performance in capturing fixed and non-threshold precipitation indices across the study region. The findings also revealed that both IMERG-E and IMERG-L have problems in rainfall estimation over elevated areas showing values of overestimations. Examining the effect of land cover type on the accuracy of the precipitation products suggest that both IMERG-E and IMERG-L show large and highly unrealistic overestimations over inland water bodies and permanent wetlands. The results of the current study highlight the potential of IMERG-F as a valuable source of data for precipitation monitoring in the region.

Nowadays, one of the biggest concern of human being is greenhouse gas emission, especially carbon dioxide emission in developed and under-developing countries. In this study, connectionist models including LSSVM (Least Square Support Vector Machine) and evolutionary methods are employed for predicting the amount of CO₂ emission in six Latin American countries, i.e., Brazil, Mexico, Argentina, Peru, Chile, Venezuela, and Uruguay. The studied region is modelled based on the available input data in terms of Million tons including oil (Million tons), gas (Million tons oil equivalent), coal (Million tons oil equivalent), $R_{ew}$ (Million tons oil equivalent), and Gross Domestic Product (GDP) in terms of billion US dollars.} Moreover, the available patents in the fields of climate change mitigation in six Latin American countries namely Brazil, Mexico, Argentina, Peru, Chile, Venezuela, and Uruguay has been reviewed and analyzed. The results show that except Venezuela, all other mentioned countries have invested in renewable energy R&D activities. Brazil and Argentina have the highest share of renewable energies which account for 60% and 72% respectively.

This study investigates how students' well-being relates to sustainable development and education for sustainability at Prince Mohammad Bin Fahd University, Saudi Arabia. The authors endeavor to answer the question "How Does Students' Well-Being Relate to Sustainable Development Via Education for Sustainable Development?" and four sub-questions. Primary data were collected by semi-structured interviews exploring the viewpoints of twenty female and male students (n=26) aged between 18 and 26. The content analysis results have identified additional well-being and education for sustainability factors that influence sustainable education and, therefore, sustainable development. These antecedents include workload, transparency, grading criteria, fairness, belonging, work-life balance, mental health support, missing emotional intelligence factors, factors related to Education for Sustainable Development, such as instructors' role models, institutional commitment, leadership, and collaboration with government. In addition, the study developed a theoretical model for the relationship between antecedents for Education for Sustainable Development, Education for Sustainable Development, and Sustainable Development in the Saudi context. Finally, the study answers four research questions: What factors contribute to education for sustainable development? What are the antecedents of education for sustainable development? How do university educators contribute to sustainable education? How do the antecedents of education for sustainable development, education for sustainable development, and sustainable development relate?

Coarse-grained molecular dynamics simulations are employed to investigate the spatiotemporal evolution of vesicles (polymersomes) by the self-assembly of randomly distributed amphiphilic BAB triblock copolymers with hydrophilic A and hydrophobic B blocks in an aqueous solution. The vesiculation pathway consists of several intermediate structures, such as an interconnected network of copolymer aggregates, a cage of cylindrical micelles and a lamellar cage. The cage-to-vesicle transition occurs at a constant aggregation number and practically eliminates the hydrophobic interfacial area between the B block and solvent. Molecular reorganization under-lying the sequence of morphology transitions from a cage-like aggregate to a vesicle is nearly isentropic. The end-to-end distances of isolated copolymer chains in solution and those within a vesicular assembly follow log normal probability distributions. This is attributed to the pre-ponderance of folded chain configurations in which the two hydrophobic end groups of a given chain stay close to each other. However, the probability distribution of end-to-end distances is broader for chains within the vesicle as compared to that of a single chain. This is due to the swelling of the folded configurations within the hydrophobic bilayer. Increasing the hydropho-bicity of the B block reduces the vesiculation time without qualitatively altering the self-assembly pathway.

Considering the significant advancements in autonomous vehicle technology, research in this field is of interest to researchers. To automatic parking, controlling steer angle, gas hatch, and brakes need to be learned. Due to the increase in the number of cars and road traffic, car parking space has decreased. Its main reason is information error. Because the driver does not receive the necessary information or receives it too late, he cannot take appropriate action against it. This paper uses two phases: the first phase, for goal coordination, was used genetic algorithms and the Cuckoo search algorithm was used to increase driver information from the surroundings. Using the Cuckoo search algorithm and considering the limitations, it increases the driver’s level of information from the environment. Also, by exchanging information through the application, it enables the information to reach the driver much more quickly and the driver reacts appropriately at the right time. The suggested protocol is called the MODM-based solution. Here, the technique is assessed through extensive simulations performed in the NS-3 environment. Based on the simulation outcomes, it is indicated that the parking system performance metrics are enhanced based on the detection rate, false-negative rate, and false-positive rate.

The aim of our study was to evaluate the impact of T. gondii status on eosinophils count (PNE), eosinophil to lymphocyte ratio (ELR) and eosinophil to neutrophil to lymphocytes ratio (ENLR) before and after can-nabis cessation in patients with psychiatric disorders. One hundred and eighty-eight patients were includ-ed in the study. T. gondii, PNE, ELR, ENLR, and urinary cannabis were measured at baseline and after 4 weeks of cannabis cessation. Highest PNE (p = .02), ELR (p = .03) and ENLR levels (p = .031) and highest increase of PNE (p = .044), and ENLR (p = .036) levels were found in patients after cannabis cessation only in the Toxo+ group. At four weeks, significant interactions between cannabis and T. gondii status for PNE (p = .038), and for ENLR (p = .043) levels were found, as well as for the evolution between baseline and 4 weeks for ENLR level (p = .049). After cannabis cessation, we found a positive correlation between negative symptoms and PNE levels at 4 weeks in the Toxo+ group. This study shows that the increase of inflammation after cannabis cessation might be modulated by T. gondii seropositivity status in patient after cannabis cessation.

Atomic force microscopy (AFM) has been extensively used for the nanoscale characterization of polymeric materials. The coupling of AFM with infrared spectroscope (AFM-IR) provides another advantage to the chemical analyses and thus helps to shed light upon the study of polymers. In this perspective paper, we review recent progress in the use of AFM-IR in polymer science. We describe first the principle of AFM-IR and the recent improvements to enhance its resolution. We discuss then the last progress in the use of AFM-IR as a super-resolution correlated scanned-probe IR spectroscopy for chemical characterization of polymer materials dealing with polymer composites, polymer blends, multilayers and biopolymers. To highlight the advantages of AFM-IR, we report here several results in studying crystallization of both miscible and immiscible blends as well as polymer aging. Then, we demonstrate how this novel technique can be used to determine phase separation, spherulitic structure and crystallization mechanisms at the nanoscale, which have never been achieved before. The review also discusses future trends in the use of AFM-IR in polymer materials, especially in polymer thin film investigation.

Condition monitoring is a primary principle for predictive maintenance. In this regard, several techniques have been employed, each of which has its strengths and weaknesses. In this work, the relationships between the electrical (ε', ε", tan δ) and chemical (Fe, Pb, Cu, Cr, Al, Si, Zn) properties of engine lubricants were investigated using soft computing models. The models' performance was evaluated considering some criteria, including RMSE and MAPE. The RBF model was determined as the best one to predict chemical properties (Fe, Pb, Cu, Cr, Al, Si, Zn) through electrical indexes (ε', ε", tan δ). The RBF’s parameters (e.g., hidden size and training algorithm) were then optimized for optimum performance. For instance, in the RBF model implemented to predict Al, the best hidden size and training algorithmic were 15 and 'trainlm', respectively. Finally, by sensitivity analysis it was observed that eliminating any of the inputs does not improve the performance of the RBF model performance. In general, the results of the current research showed that the electrical properties (e.g., ε', ε", tan δ) have the capability of estimating the contaminants in the lubricants which can improve the existing monitoring methods.

The eutrophication of open water bodies, especially in coastal water area, has received intensive public focuses in recent years. Biological treatment of organic pollutants in industrial and domestic wastewater requires microbial flora to participate. The environmental impact of these microbes, particularly in regard to the spread of antibiotic resistance genes and pathogenicity in coastal water, remains largely unknown. We initiate studies to examine antibiotic resistance genes (ARGs) in microbial flora and study the mode of antibiotic spread in the coastal waters of Bohai Bay, North China by using high performance liquid chromatography-mass spectrum analysis and quantitative polymerase chain reaction. The metabolic features of bacteria related to the presence of ARGs in the coastal area showed the enrichment of Pseudomonadale species with triple resistance properties (ampicillin, kanamycin and gentamycin) at the estuary site locating adjacent to a coastal sewage treatment plant where both type I and type II polyketide synthase genes and b-lactam type antibiotics are detected. Pseudomonadale order is phylogenetically belonged to Proteobacteria Phylum, Gamma-proteobacteria Class and contains Pseudomonadaceae family and Pseudomonas genus. QPCR analysis suggests that the percent occupation of Pseudomonadale species to total Proteobacteria in the examined stations is close to several sampling stations close to sewage treatment plants, where consistent release of organic wastes occurred.

An efficient design of conservation tillage trencher (CTT) saves time, natural resources, and conserves soil health by avoiding vigorous soil disturbance of tillage operations. A two-wheel tractor operated CTT has constructed with modified rotary shafts, toolbar frames, depth control bars, bed shapers and chisel ploughs for conservation tillage operation of sugarcane plantation. The performance evaluation of developed CTT was tested for comparing the suitability with small-scale farmer’s practice (SFP) and large farm practice (LFP). Finally, the CTT is applied for preparing sugarcane farmland in different conservation tillage methods of i) bed cum trenching (BT), ii) zero-tillage trenching (ZT) and iii) strip-tillage (ST). The performance of effective field capacities of CTT were 0.14 ha h-1, 0.12 ha h-1 and 0.14 ha h-1 for BT, ZT and ST, respectively. Developed CTT saved time 80% and 26-37% over SFP and LFP, and required 96% and 26-36% less labour than SFP and LFP, respectively. Conservation tillage required 7-10 l ha-1diesel whereas SFP and LFP required 25 l ha-1and 65 l ha-1, which reduced CO2 emission by 60-72% and 85-89% compared to SFP and LFP, respectively. Ultimately, newly developed CTT saved sugarcane land preparation costs by 86% to 90% compared to conventional tillage systems.

The solar water heater must be integrated into future residential buildings as the main energy source, which will subsequently reduce the energy cost of water heating. An original configuration for efficient Domestic Hot Water "DHW" storage tank is developed and experimentally evaluated under Saharan climate. This novel DHW configuration includes a hybrid (solar and electric) energy system with a flat plate solar collector coupled with an electric heater. Additionally, phase change material "PCM" mixture that is composed of paraffin wax and animal fat with a melting temperature between 35.58°C and 62.58°C and latent heat between 180 and 210 kJ/kg is integrated into this novel tank configuration. The experimental results indicated that hot water production by using latent heat storage could be economically attractive. In this proposed configuration, one liter of hot water may cost around 0.1362 DZD/liter (i.e., 0.00096 US$/liter) compared to 0.4431 DZD/liter for the conventional water heater, an average energy cost savings of 69.26%. On a yearly basis, the average energy cost savings may reach up to 80.25% if optimal tilt for the solar collector is adopted on a monthly basis. The flat plate collector may be vulnerable to convective heat transfer, and therefore, other solar collectors such as vacuum tube collectors may provide enhanced energy performance.

The speed-density or flow-density relationship is a fundamental aspect of traffic flow theory. Single-regime models often face challenges in consistently fitting empirical data under diverse traffic conditions. This paper addresses the inaccuracies of single-regime models, attributing them not only to their functional forms but also to data dispersion and sample selection bias. To mitigate these issues, the data is segmented into day and night periods, leading to the creation of separate models for each. Calibration results, conducted on data from two freeways, Tehran-Karaj and Tehran-Qom, reveal distinct challenges, with the former exhibiting high dispersion and the latter showing low dispersion. Surprisingly, single-regime models demonstrate notable effectiveness when applied to distinct day and night data. Further analysis, categorizing data into day and night, results in reduced errors (20-60% improvement in R-Square), emphasizing the potential for enhanced accuracy by considering distinct regimes. Overall, the study underscores the significance of regime-specific considerations for accurate traffic flow modeling. Upon thorough evaluation, the study highlights the superiority of the neural network Multi-layer Perceptron (MLP) over traditional models. The research discusses the implications of incorporating day and night parameters into the models, emphasizing their potential for accuracy enhancement.

The adverse relationship between viral hepatitis and pregnancy in developing countries was seen as a reflection of retrospective biased hospital-based data collection by the West. However, the discovery of HEV from an epidemic of non-A, non-B hepatitis in Kashmir and documenting increased incidence and severity of hepatitis E in pregnancy from a house-to-house survey unmasked the unholy alliance. Among the family of HEV’s, genotype (gt)-1, with a unique ORF4-encoded protein enhancing viral polymerase activity and viral replication, is the sole HEV that shows this adverse relationship. The epidemics caused by HEV-gt1 and not by HEV-gt2 show adverse relationship with pregnancy. The pathogenesis of the unholy alliance is complex and at present not well understood. Possibly multiple factors play a role in causing severe liver disease in the mother including: infection, replication and damage to the maternal-foetal interface by HEV-gt1; vertical transmission of HEV to foetus causing severe foetal/neonatal hepatitis; and combined viral and hormone related immune dysfunction of diverse nature in the mother promoting viral replication. Management is multidisciplinary and needs a close watch for the development and management of ALF. Preliminary data suggest beneficial maternal outcomes by early termination of pregnancy in patients with lower grades of encephalopathy.

Trace amine-associated receptor 5 (TAAR5) is a G protein-coupled receptor that belongs to the TAARs family (TAAR1-TAAR9). TAAR5 is expressed in the olfactory epithelium and is responsible for sensing 3-methylamine (TMA). However, recent studies showed that TAAR5 is also expressed in the limbic brain regions and is involved in the regulation of emotional behaviour and adult neurogenesis, suggesting that TAAR5 antagonism may represent a novel therapeutic strategy for anxiety and depression. We used the AtomNet® model, the first deep learning neural network for structure-based drug discovery, to identify putative TAAR5 ligands and tested them in an in vitro BRET assay. We found two mTAAR5 antagonists with low to submicromolar activity that are able to inhibit the cAMP production induced by TMA. Moreover, these two compounds also inhibited the mTAAR5 downstream signalling, such as the phosphorylation of CREB and ERK. These two hits exhibit drug-like properties and could be used to develop further more potent TAAR5 ligands with putative anxiolytic and antidepressant activity.

A series of (benzoimidazol-2-ylmethyl)amine palladium(II) complexes have been employed as catalysts in the homogenous hydrogenation of alkenes and alkynes under mild conditions. A correlation between the catalytic activity and the nature of the ligand was established. Kinetic studies of the hydrogenation reactions of styrene established pseudo-first-order dependence on styrene substrate. On the other hand, partial orders with respect to H2 and catalyst concentrations were obtained consistent with the formation of palladium(II) monohydride species as the active species. The nature of the solvent used influenced the hydrogenation reactions, where coordinating solvents resulted in lower catalytic activities. Density functional theory investigations provided valuable insights into the reactivity trends and influence of complex structure on the hydrogenation reactions.

In this work, some numerical radius inequalities based on the recent Dragomir extension of Furuta's inequality are obtained. Some particular cases are also provided.

This study investigates the characteristics of formaldehyde (HCHO) concentration and its reduction in newly constructed apartment buildings in Dubai. It addresses the significant health risks of high HCHO levels due to poor ventilation and extensive use of VOC-emitting materials. The research explores the effectiveness of various mitigation strategies, including air purifiers, photocatalyst applications, and window ventilation, in the living room, master bedroom (MBR), Room 1, and Room 2. HCHO concentrations were measured under different conditions: sealed windows, operation of an air purifier with a VOCs filter, and the application of a photocatalyst. The study followed a quantitative approach, recording real-time HCHO levels over 24 hours. Results indicated that sealing windows led to HCHO concentrations surpassing the domestic standard of 0.1 ppm, with the MBR recording the highest concentration at 0.73 ppm. The air purifier showed minimal impact within the first 8 hours but achieved an 18% reduction after 24 hours of operation. Applying a photocatalyst to room surfaces resulted in a 50% reduction in HCHO levels. Ventilation through window openings significantly improved air exchange rates, with the air exchange per hour (ACH) increasing proportionally with window opening size. Smaller rooms with larger window-to-volume ratios, such as Room 1 and Room 2, maintained HCHO concentrations below the WHO standard of 0.1 ppm with partial window openings. The study concludes that window ventilation is the most effective strategy for reducing HCHO concentrations, highlighting the importance of integrating comprehensive ventilation designs in modern residential buildings to ensure healthier indoor environments in Dubai.

In recent years, the rapid expansion of urban areas has led to changes in land use, a reduction in pervious surfaces, and a disturbance in the balance between surface waters and groundwater. These urban changes, combined with inadequate drainage systems and misdirection of runoff, have resulted in severe urban floods, causing numerous fatalities and damage to urban areas. As a result, investigating the effects of flood occurrences and determining proper mitigation measures to reduce flood damage is essential. This paper aims to establish a novel economic-hydrologic model to evaluate the efficacy of Low-impact Development (LID) measures in urban Bronx River catchment, NYC. The model examines reduced peak discharge of flood and imposed damage. Initially, the EPA’s SWMM is used to simulate urban flooding based on recent extreme events. LID scenarios are then implemented, including individual and combined scenarios, to mitigate the adverse impacts of flood occurrences of high to low frequency. By means of the HEC-GeoRAS tool, highly detailed flood inundation maps are generated and seamlessly incorporated into the flood damage estimation model, namely HAZUS, to obtain estimates of the potential damage caused by floods. Using the reduced monetary damages and the implementation cost of LID measures, the benefit-to-cost (BC) ratio is then calculated. Findings indicated that the combined LID scenario is the most effective approach in peak flow reduction. Moreover, Permeable pavement outperforms infiltration trench, bio retention cell, and rain barrel in terms of benefit-to-cost ratio, with rain barrel showing the lowest ratio. The proposed evaluation system for LID measures, with a focus on flood damage reduction as a key benefit, provides valuable insights for identifying optimal scenarios and facilitating informed decision-making.

Tea and coffee are the most commonly used beverages throughout the world. Both decoctions are rich in small organic molecules such as phenolics/polyphenolics, purine alkaloids, many methylxanthines, substituted benzoic and cinnamic acids. Many of these molecules are physiologically chemopreventive and chemoprotective agents against many severe conditions such as cancer, Alzheimer, Parkinsonism, inflammation, sleep apnea, cardiovascular disorders, bradycardia, fatigue, muscular relaxation, and oxidative stress. Caffeine, a purine alkaloid, is a common metabolite of both tea and coffee aqueous decoctions and its concentration in tea/coffee depends on the fermentation process, preparation of the water extract and quality of tea leaves/coffee beans. A 250 ml of a coffee cup contains 100-150 mg caffeine while the same volume of strong tea contains 25-40 mg caffeine. The present paper presents the potential of caffeine as a potent chemopreventive agent that can be used for numerous physiological disorders.

background: The Islamic Republic of Iran has been under sanctions since 1979. These sanctions were further reinforced between the years 2005 and 2012. This study utilizes available data from Iran post-sanctions to review the impact of economic sanctions on both the mental health and the quality of life of Iranian citizens.Methods: A comprehensive scoping review was conducted to identify studies examining the impact of sanctions on health in Iran. Searches were initiated in 2012 using PubMed/Medline, Embase, Web of Science, Scopus, and the Scientific Information Database (Iranian Database) with keywords such as sanctions, implications, mental health, quality of life, civilian mental health, and Iran. Subsequent to the screening process, secondary reports and letters to the editor were excluded. Only original studies—those collecting data via observation, interviews, surveys, experiments, or literature reviews—were retained for analysis. In addition to these search strategies, reference scanning was undertaken to identify additional articles pertinent to the scope of the current study. This thorough approach facilitated the discovery of relevant and significant articles exploring the effects of sanctions against Iran on the mental health and overall well-being of its civilian population. Following the search, duplicate articles were meticulously identified and removed by the authors. Data were subsequently extracted and summarized, focusing on study characteristics and the observed effects of sanctions on civilian mental health and quality of life in Iran.Result: Out of 165 items identified in the preliminary search, ten articles met the inclusion criteria. These selected articles highlighted the pronounced effects of sanctions on various health-related domains.Conclusion: Since 2012, Iran has been subject to intensified sanctions. There is evidence to suggest that the economic sanctions, imposed by Western nations, and have exerted a negative and detrimental impact on the health of individual Iranians.

This survey proposed an evaluation model to analyze and examine different approaches to generativity. In addition to problem domain concepts, the following concepts were used to define this model: Complexity and complexity management, and Systematics view to achieve unified and integrated insight into disparate evaluation criteria. The research's approach to the said concepts is first introduced. Then, the evaluation model is presented.

Classical methods for inverse problems are mainly based on regularization theory. In particular those which are based on optimization of a criterion with two parts: a data-model matching and a regularization term. Different choices for these two terms and great number of optimization algorithms have been proposed. When these two terms are distance or divergence measures, they can have a Bayesian Maximum A Posteriori (MAP) interpretation where these two terms correspond, respectively, to the likelihood and prior probability models.

Although the phenomenon of serial killers has received great attention from media, governments, and public, very little information is known about them and very few theories are presented by researchers specifically their definition and motives for killing. Through cross tabulation analysis of top ninety-eight serial killers, this present study poses six questions that investigate the correlations between, offender's gender, offender's level of education, time span of killing, killing severity, number of victims, killer's type of abuse, motives for killing, and victim's profile. Findings show that males kill more than females and for longer time, less educated serial killers kill more horribly, female serial killers consider their family members easy target, and finally males kill most for enjoyment and sex and females kill for financial gains.

In this work, we introduce the class of h-MN-convex functions by generalizing the concept of MN-convexity and combining it with h-convexity. Namely, let M : [0, 1] → [a, b] be a Mean function given by M (t) = M (t; a, b); where by M (t; a, b) we mean one of the following functions: A_t (a, b) := (1 − t) a + tb, G_t (a, b) = a^1−tb^t and H_t (a, b) := $\frac{ab}{ta+\left(1-t\right)b}=\frac{1}{A_t\left(\frac{1}{a},\frac{1}{b}\right)}$ with the property that M (0; a, b) = a and M (1; a, b) = b. Let I, J be two intervals subset of (0, ∞) such that (0, 1) ⊆ J and [a, b] ⊆ I. Consider a non-negative function h : J → (0, ∞), a function f : I → (0, ∞) is said to be h-MN-convex (concave) if the inequality f (M (t; x, y)) ≤ (≥) N (h(t); f (x), f (y)), holds for all x, y ∈ I and t ∈ [0, 1]. In this way, nine classes of h-MN-convex functions are established, and therefore some analytic properties for each class of functions are explored and investigated. Characterizations of each type are given. Various Jensen’s type inequalities and their converses are proved.

In this work, an analog front-end (AFE) circuit for Electrocardiogram (ECG) detection system has been designed, implemented, and investigated in an industry-standard Cadence simulation framework using advanced technology node of 45 nm. The AFE consists of an instrumentation amplifier, a Butterworth band-pass filter (with fifth-order low-pass and second-order high-pass sections), and a second-order notch filter- all are based on two-stage, Miller-compensated operational transconductance amplifiers (OTA). The OTAs have been designed employing the $g_m/I_D$ methodology. Both the pre-layout and post-layout simulation were carried out. The layout consumes an area of 0.0058 mm$^2$ without the resistors and capacitors. Analysis of various simulation results were carried out for the proposed AFE. The circuit demonstrates a post-layout bandwidth of 239 Hz with a variable gain between 44 to 58 dB, a notch depth of -56.4 dB at 50.1 Hz, a total harmonic distortion (THD) of -59.65 dB (less than 1\%), an input referred noise spectral density of $

Abstract. The remarks by the Supreme Leader of the Islamic Revolution on the toll of the famines that afflicted occupied Iran in World War I and World War II indicate a desire to incorporate these calamities in Iran’s national narrative and collective memory. His criticism of famine historiography and stated toll numbers, and the unfolding catastrophic famine in Gaza, justify and necessitate a fresh look at each famine’s historiography and toll. This article re-estimates the toll of each famine by including many overlooked and neglected primary sources and in ways not previously done. It builds a trajectory of Iran’s demographic development from 1810 to 1944, and derives the toll of each famine. The World War II famine and typhus epidemics had claimed 5.5 million. World War I famine was also more deadly, though the 1869-73 famine was not far behind. At least 15.5 million Iranians died in the two world wars, a fact nowhere reflected in the history of the conflicts. Iran’s 1944 population of 12 million was unchanged from that of 1850 and a century of population growth obliterated

By applying a running average (with a window-size= d), we could transform Discrete data to broad-range, Continuous values. When we have more than 2 columns and one of them is containing data about the tags of classification (Class Column), we could compare and sort the features (Non-class Columns) based on the R2 coefficient of the regression for running averages. The parameters tuning could help us to select the best features (the non-class columns which have the best correlation with the Class Column). “Window size” and “Ordering” could be tuned to achieve the goal. this optimization problem is hard and we need an Algorithm (or Heuristics) for simplifying this tuning. We demonstrate a novel heuristics, Called Simulated Distillation (SimulaD), which could help us to gain a somehow good results with this optimization problem.

Simple measures often couldn’t count a deep complexity. In the case of semantic complexity, conventional readability formulas share a common style, a common sort of achievements and a common borders of limitation: These formulas lack a semantics-aware approach and as a result, a precise measurement of semantic complexity couldn’t be done. In this paper, we introduce DASTEX, a novel semantics-aware complexity measure for semantic complexity of text. By DASTEX, a new layer of complexity analysis are opened for NLP, cognitive and computational tasks. This measure benefits from an intuitionistic underlying formal model which consider semantic as a lattice of intuitions. This yields to a well-defined definition for semantic of a text and its complexity. DASTEX is a practical analysis method upon this formal model. So a complete suite of idea, model and method are prepared to result in a simple but yet deep measure for semantic complexity of text. The evaluation of the proposed approach is done by 4 Experiments. The results show DASTEX is capable of measuring the semantic complexity of text in 6 application-tasks.

In Model-Driven Development (MDD), the models, their generation, and imposing changes on them (model transformation) are used for the development of software. Models provide a framework to start from the imagination and abstraction to create and accomplish the final system. Models create a slow and steady transition from whatness to howness, i.e. from the natural path of the generation of software. For supporting this path, the Logic and Functionality of software must be changeable during its evolution. Here we provide a brief introduction to the concept of Model Driven Development.

In this paper, Hybrid Automata, which is a formal model for hybrid systems, has been introduced. A summary of its theory is presented and some of its special and important classes are listed and some properties that can be studied and checked for it are mentioned. Finally, the purposes of use, the most widely used areas, and the tools that provide H.A. Support are addressed.

Galectin-3 is considered a cancer biomarker and bioindicator of fibrosis and cardiac remodeling, and, therefore, it is desirable to develop convenient methods for its detection. Herein, an approach based on the development of multivalent electrochemical probes with high galectin-3 sensing abilities is reported. The probes consist of multivalent presentations of lactose–ferrocene conjugates scaffolded on poly(amido amine) (PAMAM) dendrimers and gold nanoparticles. Such multivalent lactose–ferrocene conjugates are synthesized by coupling of azidomethylferrocene-lactose building blocks on alkyne-functionalized PAMAM, for the case of the glycodendrimers, and to disulfide‐functionalized linkers that are then used for the surface modification of citrate-stabilized gold nanoparticles. The binding and sensing abilities towards galectin 3 of both ferrocene-containing lactose dendrimers and gold nanoparticles have been evaluated by means of isothermal titration calorimetry, UV-vis spectroscopy, and differential pulse voltammetry. The highest sensitivity by electrochemical methods to galectin-3 was shown by lactosylferrocenylated gold nanoparticles, which are able to detect the lectin in nanomolar concentrations.

In this investigation magnetic γ-Al2O3 ceramic nanocomposite particles bearing epoxide functionality are prepared following a multistep process. The ultimate nanocomposite particles are named as γ-Al2O3/Fe3O4/SiO2/poly(glycidyl methacrylate (PGMA). The surface property is evaluated by carrying out the adsorption study of Remazol navy (RN), a model reactive azo dye, on both γ-Al2O3/Fe3O4/SiO2 and γ-Al2O3/Fe3O4/SiO2/PGMA nanocomposite particles. The adsorption is carried out at the point of zero charge (PZC) to neutralize the effect of particle surface charge. The adsorption rate is very fast, reached equilibrium (qe) value within five min. Due to mesoporous structure of silica layer γ-Al2O3/Fe3O4/SiO2 nanocomposite particles possessed relatively higher specific surface area and magnitude of adsorption is dependent on the total specific surface area. The introduction of epoxide functionality favored high adsorption capacity in mass per unit surface area. The adsorption process strictly followed Langmuir model. Thermodynamic equilibrium parameters implied that irrespective of surface functionality the adsorption process is spontaneous and exothermic. Pseudo-second-order rate kinetic model is more appropriate to explain the adsorption kinetics.

Silencing of the fragile X mental retardation 1 (FMR1) gene and consequently lack of synthesis of FMR protein (FMRP) are associated with fragile X syndrome, which is one of the most prevalent inherited intellectual disabilities. FMRP is a multifunctional protein involved in many cellular functions in nearly all subcellular compartments under normal conditions and under conditions of cellular stress in both neuronal and non-neuronal cell types. This is achieved through its trafficking signals, nuclear localization signal (NLS), nuclear export signal (NES), and nucleolar localization signal (NoLS), as well as its RNA and protein binding domains, and is modulated by various post-translational modifications such as phosphorylation, ubiquitination, sumoylation, and methylation. This review summarizes recent advances in understanding the interaction networks of FMRP with a special focus on FMRP stress-related functions, including stress granule formation, mitochondrion and endoplasmic reticulum plasticity, ribosome biogenesis, cell cycle control, and DNA damage response.

High dimensional datasets are highly likely to have redundant, irrelevant, and noisy features that negatively affect the performance of the classification algorithms. Selecting the most relevant features and reducing the dimensions of datasets by removing the undesired features is a dimensional reduction technique called Feature Selection (FS). In this paper, we propose an FS approach based on the Black Hole Algorithms (BHO) with a mutation technique called MBHO. Generally, BHO contains two major phases. At the exploitation phase, a set of stars are modified based on some rule and according to some objective function, the best star is selected as the black hole which attracts other stars. Furthermore, when a star gets closer to the event horizon, it will be swallowed and a new one will be randomly generated in the search space which thus is the exploration phase. However, randomness may cause the algorithm to fall into the trap of local optima, and to overcome such complications, inversion mutation is used. Furthermore, we modify a widely utilized objective function in most of the proposed works for wrapper feature selection by combining two new terms that are based on the correlation among the selected subset of features and the features and the classification label. We also utilize a transfer function, known as the V2 transfer function, to convert continuous values into discrete ones to enhance search. We assess our approach via extensive evaluation experiments using fourteen benchmark datasets. We benchmark the performance of a wrapper FS approach called Binary Cuckoo Search (BCS), and three filter-based FS approaches (namely Mutual Information Maximisation (MIM), Joint Mutual Information (JMI), and minimum Redundancy Maximum Relevance (mRMR)). Our evaluation has shown that the proposed model is an effective approach for FS, in selecting better features that enhance the performance metrics on the classifiers. Thus, MBHO can be utilized as one alternative to the existing state-of-art-approaches. We release the source codes of our implementation for the community to build on with new methods and datasets.

AI applications are transforming the technology and digital sector, seamlessly integrating into the daily interactions of individuals with the digital world. Key entry points to the internet, such as search engines, are now complemented by recommendation systems that curate content on social networks, streaming platforms, and online marketplaces. Additionally, virtual assistants have become ubiquitous across various platforms. While these groundbreaking changes are gradually extending to several industries, there remains significant untapped potential for the application of artificial intelligence in diverse domains. The renewable energy sector, in particular, continually reinvents itself through research and innovation to meet the escalating demand. Positioned at the forefront of technological evolution, this industry is well-placed to effectively adopt and tailor the innovations of artificial intelligence to its specific needs. Presently, both emerging and established tools leverage elements of AI to enhance processes and introduce functionalities that were previously unattainable. If the current trajectory persists, AI-enhanced tools have the potential to assume a role as crucial to the future of engineering as computer-aided design (CAD) software is in contemporary times.

The mechanical properties of α-chitin and chitosan biocomposite are investigated due to their broad range of potential applications in bioengineering, materials science, and environmental technology. Employing molecular dynamics (MD), and stress-strain analyses, this study comprehensively investigates biopolymers mechanical response and anisotropic mechanical behavior under uniaxial tensile loading conditions in an aqueous environment. Our computational models were validated against existing experimental data, showing high degrees of correspondence. Uniaxial tensile tests revealed that α-chitin exhibits a remarkable ultimate tensile strength (UTS) of 10.07 GPa in the crystalline chain direction (y-axis) at a high strain rate of 0.636, compared to a significantly lower UTS of 2.78 GPa in the perpendicular direction (x-axis) at a lower strain rate of 0.066. The biocomposite nanostructure, encompassing randomly distributed chitosan, reduced stiffness, maintaining remarkable flexibility as α-chitin, with a UTS of 5.03 GPa in the y-axis and 2.34 GPa in the x-axis. Further, the directional elastic modules for α-chitin were calculated as 51.76 GPa and 39.76 GPa in the x and y directions, respectively. In contrast, these values for the α-chitin-chitosan biocomposite were estimated as 31.66 GPa and 26.00 GPa, respectively. The findings provide valuable insights into the distinct mechanical properties of α-chitin and chitosan biocomposite, making a substantial contribution to optimizing these materials for specialized applications.

Background: The SARS-CoV-2 virus is a new highly pathogen virus that can suppress cell immune response (Poly ADPR process, and interferon releasing in infected cell) by viral macrodomain and create fatal pneumonia. Cytokine storm phenomenon which can create consequence of SARS COV-2 by increase of the performance of human TRPM2, is a dangerous condition for human and its body organ such as kidney, heart, and liver. it seems like prevention of beginning of these events is necessary. Material and methods: in this study drug and drug like database was used for inhibition of the viral macrodomain and human TRPM2 that can initiate of the viral cell cycle infection and human cytokine storm respectively. Ligand base drug designed, pharmacophore modeling, docking and molecular dynamic simulation was performed Results: among up to billion compounds, 20 compounds were screened by infinisee program. Then 7 compounds were selected by pharmacophore modeling. between 7 compounds, 5 compound was removed because of high similarity to ADPR and possibility of toxic effect for human RNA and DNA polymerase. One compound was losartan and selected for docking and molecular dynamic simulation. Conclusion: losartan earned a proper dock score and binding affinity to create the complexes with TRPM2 and macrodomain. Molecular dynamic simulation has shown losartan had an adequate binding free energy for human trpm2 and viral macrodomain. The inhibitory effect of losartan on these protein has shown and it could interfere in several points (PARP, PARG- macrodomain and TRPM2) and decreases oxidative stress, apoptosis, cytokine storm in COVID-19.

Nowadays, many political campaigns are using social influence (SI) in order to convince voters to support/oppose a specific candidate/party. In election control via SI problem, an attacker tries to find a set of limited influencers to start disseminating a political message in a social network of voters. A voter will change his opinion when he receives and accepts the message. In constructive case, the goal is to maximize the number of votes/winners of a target candidate/party, while in destructive case, the attacker tries to minimize them. Recent works considered the problem in different models and presented some hardness and approximation results. In this work, we consider multi-winner election control through SI on different graph structures and diffusion models, and our goal is to maximize/minimize the number of winners in our target party. We show that the problem is hard to approximate when voters' connections form a graph, and the diffusion model is the linear threshold model. We also prove the same result considering an arborescence under independent cascade model. Moreover, we present a dynamic programming algorithm for the cases that the voting system is a variation of straight-party voting, and voters form a tree.

We report an unusual transformation where a transient formation of a nitrene moiety initiates a sequence of steps where leading to a remote oxidative C-H functionalization (R-CH3 to R-CH2OC(O)R’) and concomitant reduction of the nitrene into an amino group. No external oxi-dants or reductants are needed for this formal molecular com-proportionation. Detected and iso-lated intermediates and computational analysis suggest that the process occurs with pyrazole ring opening and recyclization.