This article will briefly review the progress of h-BN based solid-state metal semiconductor metal (MSM) neutron detectors. In the last decade, several groups have been working on hexagonal boron nitride (h-BN) based solid-state neutron detectors. Recently, the detection efficiency of 59% has been reported. Efficient, low-cost neutron detectors made from readily available materials are essential for various applications. Neutron detectors are widely used to detect fissile materials and nuclear power plants for security applications. The most common and widely used neutron detectors are 3He based, which are sometimes bulky, difficult to transport, have high absorption length, need relatively high bias voltage (>1000 V), and have low Q-value (0.764 MeV). Also, 3He is not readily available material. Thus, there is a strong need to find an alternative detection material. 10B isotope has a high neutron absorption cross-section, and it has been tested as a coating on the semiconducting materials. Due to the two-step process, neutron capture through 10B, and then electron-hole pair generation in a typical semiconducting material, the efficiency of these devices is not up to the mark. The progress in h-BN based detectors requires a review to envision the further improvement in this technology.

Single-molecule magnets (SMMs) have garnered significant interest in the field of molecular magnetism due to their unique magnetic properties at the nanoscale. These molecular systems exhibit magnetisation behaviour reminiscent of conventional bulk magnets but with distinct advantages such as size-dependent properties and potential applications in quantum computing and high-density data storage. However, challenges remain in harnessing their properties for practical applications, including their susceptibility to degradation and limited control over their assembly and organisation.

Due to its built-up chemoresistance after prolonged usage, the demand for replacing platinum in metal-based drugs (MBD) is rising. The first MBD approved by the FDA for cancer therapy was cisplatin in 1978. Even after nearly four and a half decades of trials, there has been no significant improvement in osteosarcoma (OS) therapy. In fact, many MBD have been developed, but the chemoresistance problem raised by platinum remains unresolved. This motivates us to elucidate the possibilities of the copper and zinc (CuZn) combination to replace platinum in MBD. Thus, the anti-chemoresistance properties of CuZn and their physiological functions for OS therapy are highlighted. Herein, we summarise their chelators, main organic solvents, and ligand functions in their structures that are involved in anti-chemoresistance properties. Through this review, it is rational to discuss their ligands’ roles as biosensors in drug delivery systems. Hereafter, an in-depth understanding of their redox and photoactive function relationships is provided. The disadvantage is that the other functions of biosensors cannot be elaborated on here. As a result, this review is being developed, which is expected to intensify OS drugs with higher cure rates. Nonetheless, this advancement intends to solve the major chemoresistance obstacle towards clinical efficacy.

The research aims to improve some of the physical and hydro-physical properties of some Vertisols in the southern region (part of the eastern Houran Plateau) in Sweda Governorate at the south of Syria. Using different quantities of volcanic ash, soil samples were collected from the Al-Thahallah village from a depth of (0-30) cm, The experiment was designed according to the complete random design with one factor that represents the ash quantity (1.25, 2.5, 5) %, with three replicates for each treatment in addition to the control treatment a0. The experiment was carried out within the plastic pots during agricultural season 2018/2019, in which the wheat of the Sham variety 3 were cultivated as a cover plant. The results showed that the addition of volcanic ash at the quantity of 5% led to a significant increase in the infiltration rate by (328.60) %,%, where the filtration rate increased from 0.42 cm/hr -1 to 1.80 cm.h-1, as well as for each of the air porosity by (89) % and the volume of infiltrate water by (40) %, compared with the control. The above-mentioned addition also resulted in a decrease in both dry bulk density, total soil porosity and volumetric swelling coefficient by (18.60, 5.80, 314) % Respectively, compared to the control. The addition also contributed to the reduce in the weighted moisture content when saturation and the field capacity, at the level of significance of 5%. The research recommends adding volcanic ash to the soil at a quantity of 5%, and adding enhancements with volcanic ash at various levels such as organic waste.

We report the synthesis and characterization of Poly Methyl-Meth-Acrylate (PMMA)/Poly vinylalcohol (PVA) polymeric blend doped with different concentrations of Copper oxide (CuO) nanoparticles (NPs). The (PMMA-PVA)/CuO nanocomposite hybrid thin films (wt. % = 0%, 2%, 4%, 8%, and 16%) of CuO NPs are deposited on glass substrates via dip-coating technique. The transmittance (T%), reflectance (R%), the absorption coefficient (α), the optical constants [refractive index (n), extinction coefficient (k)], optical dielectric functions [ɛ',ɛ''] are investigated and interpreted. Tauc, Urbach, Spitzer-Fan, and Drude models are employed to calculate the optical bandgap energy (Eg) and the optoelectronic parameters of the nanocomposite thin films. The refractive index and optical bandgap energy of of (PMMA-PVA) polymeric thin film are found to be (1.5 to 1.85) and 4.101 eV, respectively. Incorporation of specific concentrations of CuO-NPs in (PMMA-PVA) polymeric thin films leads to a noticeable decrease in the optical bandgap energy and to an increase of the refractive index. Moreover, Fourier Transform Infrared Spectroscopy (FTIR) transmittance spectra are measured and analyzed for undoped and doped polymeric thin films to pinpoint the major vibrational modes in the spectral range (500 and 4000 cm-1), as well as, the nature of network bonding in both systems. Thermal stability of thin films is investigated by performing thermogravimetric analysis (TGA). The TGA thermograms confirm that both doped polymeric thin films are thermally stable at temperatures below 110°C which enables them to be attractive for a wide range of optical and optoelectronic applications. Our results indicate that optical, vibrational and thermal properties of both polymeric thin films can be tuned for specific applications by the appropriate corporation of particular concentrations of CuO-NPs.

The study titled "Molecular Choreography of DNA: Insights and Innovations" explores the intricate dance of DNA, shedding light on its structure, function, and regulation. This comprehensive review delves into the historical significance of DNA research, from Watson and Crick's double helix discovery to recent innovations in genomics and molecular biology. The review highlights DNA's roles in replication, repair, gene regulation, and chromatin dynamics, emphasizing the precision and complexity of its molecular choreography. Innovations like CRISPR-Cas9 gene editing and advanced sequencing technologies have revolutionized our understanding of DNA, opening new avenues for scientific exploration. This study aims to provide readers with a deeper appreciation of DNA's central role in life's choreographed processes.

Noncoding RNA regions have emerged as pivotal players in the regulation of various cellular processes, and their involvement in HIV/AIDS pathogenesis is an evolving field of research. This review article delves into the intricate interplay between noncoding RNA regions and AIDS, shedding light on the diverse mechanisms by which these RNA molecules influence viral replication, immune responses, and disease progression. The review highlights recent discoveries, potential therapeutic applications, and the challenges ahead, illustrating the promising prospects of noncoding RNA research in the context of HIV/AIDS.

Non-coding RNA regions have long been considered the "dark matter" of the genome, with their significance in gene regulation remaining enigmatic. However, recent advances in genomics and molecular biology have illuminated the pivotal role that non-coding RNA regions play in the fine-tuned orchestration of hemoglobin expression. Hemoglobin, the oxygen-carrying protein vital for life, is tightly regulated, and any disruption in its production can lead to severe medical conditions, such as hemoglobinopathies. This review delves into the intricate world of non-coding RNA regions, exploring how they act as master conductors in controlling hemoglobin gene expression. We will discuss various classes of non-coding RNAs, including long non-coding RNAs, microRNAs, and circular RNAs, and their specific mechanisms in fine-tuning hemoglobin levels. Additionally, we will highlight emerging therapeutic approaches that target non-coding RNA regions to ameliorate hemoglobin-related disorders. Understanding the critical role of non-coding RNA regions in hemoglobin regulation opens new avenues for precision medicine and gene therapies, offering hope for those affected by hemoglobinopathies and related conditions. This comprehensive review sheds light on the significance of these non-coding RNA regions, demonstrating that the "silent" players in the genome are, in fact, the conductors of harmony in the symphony of hemoglobin regulation.

The epigenetic mechanism of DNA methylation is essential for regulating gene expression and adaptation in plants, especially when exposed to various environmental stressors such as drought, heat, and nutrient availability. The impact of these stressors can lead to alterations in DNA methylation patterns and gene expression, which this study aims to investigate. Specifically, we are interested in understanding how DNA methylation plays a role in controlling the expression of stress-response genes, as well as genes involved in plant growth and development. To accomplish this, we are analyzing the changes in DNA methylation patterns and gene expression in response to different stressors like drought and heat. Our research findings suggest that DNA methylation is a vital regulator of plant adaptation to environmental stress, and we hope to gain further insight into these mechanisms by identifying genes that exhibit differential expression in response to stress and analyzing their DNA methylation status. This study offers valuable insights into the development of crops that can thrive under changing climate conditions.

This paper evaluates the global sustainable competitiveness of three blocks of power (US, China and EU) based on OGT (Organic Growth Theory) structure. In addition, a sensitivity analysis of COVID-19 on three measures of global sustainable competitiveness, economy, environment and social is also presented. OGT is a well-thought-through and standard framework for evaluation of any type of organiza-tion in their pathway to experience truly sustainable growth. GDP (Gross Domestic Product) is used as an economic measure; total carbon emissions equivalent is used as an environmental measure and HMI (Human Development Index) as a social measure. It is concluded that the pandemic has paused the evolution of countries to be truly world centric countries. However, the recovery plans seem to be highly aligned with the OGT scores and it is expected that the scores to improve dramatically.

Machine Learning (ML) has brought about a transformative era in reactor operations, reshaping monitoring, control, and optimization strategies. This survey comprehensively explores the diverse spectrum of ML applications in industrial reactors. From real-time sensor analysis ensuring reactor functionality to adaptive control algorithms ensuring stability, ML's impact is profound and multifaceted. The benefits of ML are equally evident in optimization, encompassing performance trend prediction, proactive maintenance, and fine-tuning of operations for enhanced efficiency. This review identifies dominant ML techniques, operations stages receptive to ML integration, core data sources, and critical input-output parameters. Aimed at both academics and practitioners, this exploration enriches reactor technologies, unlocking their full potential through insights driven by ML.

To handle the huge amount of data generated by IoT devices, Big Data processing tools make it easier. This paper discusses the Big Data concept and its main V’s characteristics. It further describes IoT-enabling technologies; nominally cloud computing such as SaaS and PaaS. The centralization and infrastructure of Big Data systems, and how Cloud Computing gives a platform access to the data from anywhere. The paper explores IoT with big data architectural solutions for various use cases across the healthcare and transportation sectors.

Innovation and technology are important tools of minerals sector efficiency and productivity im-provement. The uptake of technologies has proven important levelrs to improve the productivity of mining sector. This paper provides a comprehensive analysis of mine-level productivity by using a global data of copper, gold, and platinum from 1991-2020. Various drivers of proioductivity have been analysed to draw policy insights. Empirical findings reveal significant disparities in technical efficiency and productivity across mines and regions. A further decomposition of TFP into its different components suggest that the adoption of innovative practices and investment in technology adoption could improve the overall productivity of these commodities. The findings also suggest that an appropriate input mix and optimal scale of production could boost platinum mining productivity. Regional disparities in productivity in different commodities (e.g., South Africa vs. Zimbabwe) give policymakers with insights into how to support production scale and productivity through appropriate input mixtures.

In this paper, we discussed the motion of neutral and charged particles in Schwarzschild black hole immersed in an electromagnetic universe (SEBH). The SEBH represents a mass M coupled to an external electromagnetic field that was derived from the metric of colliding electromagnetic waves with double polarization. Our study examine how the external electromagnetic field affects the trajectory of neutral and charged particles. First, the trajectories of both photon and test particle are studied. Then, the exact solutions for the trajectories are obtained in terms of the Jacobi-elliptic integrals for all possible energy and angular momentum of test particle and photon. We have also discussed the motion of charged particle and obtained the radius of the innermost circular orbit (ISCO). It is especially interesting when the charge sign is positive since this creates a conflict between gravitational (attraction force) and electric (repulsion force). Furthermore, we discuss the Lyapunov exponent and the effective force influencing particles in SEBH spacetime.

Bismuth oxides are well-known electro-catalysts in fuel cells systems; they are usually used as anodic materials for the oxidation of low molecular weight alcohols. The utilization of BiO₂ and MnO₂ as catalysts in the pharmaceutical analysis is analytical method for the determination of heavy metal antibacterial agents in Pharmaceutical Dosage form is developed. The method is based on the voltammetric determination of heavy metal using Bidified platinum electrode by Bismuth oxide. The two components are oxidized at the Bidified electrode surface with the development of current that is linearly proportional to their concentrations in the range of 7.04*10^-7- 1*10^-3 M heavy metal. The oxidation reaction of the two components is pH-dependent, in which the buffer used is Britton-Robinson at pH = 7.00 where maximum peak current and maximum peak separation is obtained. The regression factors obtained from the calibration curves are 0.9812. The method of analysis was validated, where the limit of detection (LOD) and the limit of quantitation (LOQ) were calculated to be 1.44*10^-4 M, 4.36*10^-4 M and 1.27*10^-4 M, 3.84*10^-4 M respectively, the percentage recovery of both components was also calculated to 77 % for heavy metal.

Trends focused on the Global Innovation Index (GII) as a measure for progress of nanochemistry. This paper provides projections of recent developments in the word in nanochemistry based on the Global Innovation Index as a predictor for certain Arab countries. The GII is an annual ranking of countries by its ability and performance in innovation and is calculated on a basic average from five and two pillars in two sub-indexes, the Innovation Input Index and the Innovation Output Index. Each pillar represents a trait of creativity and consists of up to five measures, with a weighted average formula for measuring their ranking. In 2008, the GII rose to 36.3 in 2016 from 0.5. The GII is smaller than the GII in Arabic countries worldwide. During the years 2013-2016, the worldwide GII was increasing while for the same period, for Arabic countries, this decline could be explained by economic and industrial wars in the Arab region.

Ferrocene and its derivatives have ecologically effective antidetane properties. In this regard, ferrocene reacts with cyclic ketones and ferrosenylcarbinols are synthesized. It should be noted that ferrocene enters into electrophilic reactions and the process takes place in an acidic environment. In addition, the yield of the new product was small compared to the reactions of ferrocene with non-cyclic ketones. This is due to the spatial structures of molecules. The elemental analysis of obtained compounds was carried out; the structures were researched by cyclic voltammograms and Chronoamperometric.

As a consequence of a three-stage synthesis from terephthalic aldehyde, a series of 3,3 '- (1,4-phenylene) perchlorates including methyl, hydrogen, acetyl, bromio, methoxy and nitro groups (R = Br, H, Me). The matching formazans were reacted with formalin in dioxane in the presence of perchloric acid to produce tetrazin ium salts. Formazans were synthesized by reacting terephthalic aldehyde phenylhydrazone with ar ene diazonium tosylates in a DMF/pyridine combination. The use of ar ene diazonium tosylates greatly simplified the separation and purification of formazans. The p henylhydrazone was produced in aqueous dioxane using the usual approach from terephthalic aldehyde and phenylhydrazine/hydrochloric acid. Individual f ormazans and tetrazinium perchlorates were isolated and characterized by elemental analysis, IR, NMR, UV spectroscopy. The electrochemical reduction of tetrazinium perchlorates was investigated using cyclic voltammetry (CV). Thus, all salts in the cathode region have two one-electron reduction peaks, which are connected to the sequential production of a radical cation and a biradical. It was discovered that donor substituents (R: OMe, Me) in the aromatic ring at position 1 accelerate tetrazinium cation reduction, whereas acceptor substituents (R: NO₂, COMe,) inhibit this process. On this premise, it was proposed that in the presence of donor substituents in the aromatic ring at position 1, the matching bis-verdazyl radicals should be easily generated. As a result, 3,3'- (1,4-phenylene) perchlorates are possible antecedents of symmetric biradical systems based on verdazyl radicals.

This study on the production of a modern natural water electrochemical antimony (II) test include the use of platinum platinum electrode electrodes. Antimony (II) was pre-concentrated on the modified electrode surface and adsorbed to the surface, oxidizing at E = -680 mV. Compared to the platinum electrode, the platinum nanoelectrode exhibited superior performance and, unexpectedly, received a higher electrochemical response. After 25 min of accumulation, time the best-defined anodic peak was obtained with 0.2 mol L^-1 KNO₃ pH 5.0. Using these parameters, the L^-1 Sb ^{2 +} calibration plot was linear over range 1 = 10⁻⁸ to 5x10⁻⁶ mol. The precision was tested by carrying out eight replicate measurements at a concentration of 2.5x10⁻⁵ mol. L^-1; the variance coefficient was 2.9%. The method was applied to analyte determination in water samples from the river. Other metal ion attack on Sb's (II) voltammetric response has been studied. In the SEM image, the nanoparticle electrode was clearly observed and characterized by X-ray diffraction and cyclic voltammetry

The outbreak of coronavirus 2 (SARS-CoV-2) has already taken on pandemic proportions and has affected more than 100 countries in recent weeks. It is imperative that global healthcare systems are prepared. Containment initiatives in Jordan, on the other hand, have decreased new cases by over 63%. The Jordanian national health system has been very pleased with its ability to adequately meet the needs of the patients diagnosed with SARS-CoV-2 pneumonia, and includes intensive care. From 2 March to 14 April 2020, between 4% and 8% of active infected patients in Jordan registered daily in intensive care. The percentage is very low.

This study explored the living situations, financial conditions, religious obligations, and social distancing of Muslims during the covid 19 pandemic. In total, 20 Muslim community members living in the Kanto region were recruited, 15 of them were included in the in-depth qualitative and five in the focus group interviews. The Snowball method was used, and the questionnaires were designed into four themes. The audio/video interviews were conducted via Zoom and NAVIO was used to analyse the data thematically. The major Muslim events were cancelled, and the recommended physical distancing was maintained during the prayers at home and in the mosques. The Japanese government's financial support to each person was a beneficial step towards social protection, which was highlighted and praised by every single participant. Regardless of religious obligations, the closer of all major mosques in Tokyo demonstrates to the Japanese community how serious they are about adhering to the public health guidelines during the pandemic. This study highlighted that the pandemic has affected the religious patterns and behaviour of Muslims from inclusive to exclusive in a community and narrated the significance of religious commitments.

Current research in the field of antimicrobials is focused on the development of novel antibiotics and antimicrobial agents to counteract the huge dilemma that the human population is mainly facing in regards to the rise of bacterial resistance and biofilm infections. Host Defense peptides (HDPs) are a promising group of molecules for antimicrobial development as they share unique characteristics suitable for antimicrobial activity including their broad spectrum of activity and potency against bacteria. AamAP1 is a novel HDP that was identified through molecular cloning from the venom of the North African scorpion Androctonus amoeruxi. In vitro antimicrobial assays revealed that the peptide displays moderate activity against different strains of Gram-positive and Gram-negative bacteria. Additionally, the peptide proved to be highly hemolytic and displaying significantly high toxicity against mammalian cells. In our study, a novel synthetic peptide analogue named A3 was designed from the naturally occurring scorpion venom host defense peptide. The design strategy depended on modifying the amino acid sequence of the parent peptide in order to increase its net positive charge, percentage helicity and optimize other physico-chemical parameters involved theoretically in HDPs activity. Accordingly, A3 was evaluated for its in vitro antimicrobial and anti-biofilm activity individually and in combination with four different types of conventional antibiotics against clinical isolates of multi-drug resistant (MDR) Gram-positive bacteria. A3 was also evaluated for its cytotoxicity against mammalian cells. A3 displayed potent and selective in vitro antimicrobial activities against a wide range of MDR Gram-positive bacteria. Our results also showed that combining A3 with conventional antibiotics displayed a synergistic mode of action which resulted in decreasing the MIC value for A3 peptide as low as 0.125 µM. These effective concentrations were associated with negligible toxicities on mammalian cells. In conclusion, A3 exhibits enhanced activity and selectivity when compared with the parent natural scorpion venom peptide. The combination of A3 with conventional antibiotics may be pursued as a potential novel treatment strategy against MDR and biofilm forming bacteria.

Nanofibres have gained increasing attention due to their advantages of having a high porous structure, narrow pore size and distribution, and a high specific surface area. One of the most efficient techniques for producing nanofibres is via electrospinning. Nanofibres are currently being used in various fields, including water filtration. Although nanofibres possess the ability to filter various components, the fibres generally have a low mechanical strength that can mitigate the performance over time. Therefore, in overcoming this issue, several studies have focused on improving the strength of the nanofibre membranes for a water filtration application. This review discusses the advantages and challenges of nanofibres for water filtration membranes and summarises the methods to increase the strength of the membranes, including solvent vapour, thermal treatment, and chemical crosslinking.

This paper has experimentally measured volcanic tufa electrical conductance. The calculations are carried out in accordance with the potential of cyclic voltammetry in a constant state. The cyclic voltammograms nanoelectrode platinum prepared electrochemically were examined in the range -0.2 to 1.2 V vs. AgCl [Cl^-]:1.0 M in the presence and absence of volcanic tuff in the aqueous solution of 1.0 M HCl. The cyclic voltammetry studies show that the Nano platinum film suffers degradation when the potential exceeds +0.85 V, and below this potential, it is quite stable. The redox reaction of the electrode is reversible. The nanoparticle platinum synthesized at low temperature and high acid concentration exhibits higher electronic conductivities. It has been observed that, relative to area under the peak aggregate tests, the use of volcanic concrete was showing a large increase in electrical conductivity. It was shown that with cyclic voltammetry, three well-defined anode peak could be achieved at a power of 0.0, 0.4 and 0.6 V versus Ag/AgCl.

It is important to increase the quality of health and medicine. A wearable system for continuous monitoring of the patient is important to overcome this issue. Thus a patient with Arrhythmia due to its low cost and success in saving the life of the patient was the right option for the care partner. In addition, the device will provide a consumer with a smart smartphone application with accurate pulse beat and body temperature data in real time. MAX 30100 and LM35 are primarily used for the detection of human heart and temperature. The performance of these sensors is generated by an arrhythmia algorithm in the esp32 segment.

An electrochemical sensing platinum nanoparticle in the tantalum electrode is provided by means of an Ion Beam Sputtering Deposition (IBSD). The electrode was made with a Pt solution, sputtered simultaneously with hydrochloric acid corrosion on tantalum substrate. In the study of heavy metal ions, for example, the platinum nanoparticle electrodes as prepared were used Square wavelength voltammetry (OSWV) Hg²⁺, Cu²⁺ and Ag²⁺. The porous electrodes were observed in a broader range by the Pt nanostructure electrode for heavy metal ions. Furthermore, the susceptibility to detection has been shown to be saturated as the thickness of the layer electrode exceeded 50 nm. For Hg²⁺ 0,003-1 M, for Cu²⁺ 0,005-3 M and for Ag²⁺ the linear detection scale is 0,009-4 M. There has also been good reusability and repeatability. In addition, a scan electron microscope (SEM) used to study platinum electrode forming process and nanostructure. This electrode will have interesting applications in sensing systems.

Today, contamination from heavy metals in the atmosphere is a global concern. Efficient detection techniques are therefore necessary if heavy metal exposure levels in different media are to be determined. The voltammetry method for in situ detection of heavy metal ions is a very sensitive electrochemical method. This thesis explores emerging developments in electrode alteration, materials production and experimental optimization. An electrochemical sensing platinum nanoparticle in the tantalum electrode is provided by means of an Ion Beam Sputtering Deposition (IBSD). The electrode was made with a Pt solution, sputtered simultaneously with hydrochloric acid corrosion on tantalum substrate. In the study of heavy metal ions, for example, the platinum nanoparticle electrodes as prepared were used Square wavelength voltammetry (OSWV) Hg²⁺, Cu²⁺ and Ag²⁺. The porous electrodes were observed in a broader range by the Pt nanostructure electrode for heavy metal ions. Furthermore, the susceptibility to detection has been shown to be saturated as the thickness of the layer electrode exceeded 50 nm. For Hg²⁺ 0,003-1 M, for Cu²⁺ 0,005-3 M and for Ag²⁺ the linear detection scale is 0,009-4 M. There has also been good reusability and repeatability. In addition, a scan electron microscope (SEM) used to study platinum electrode forming process and nanostructure. This electrode will have interesting applications in sensing systems.

In computer networks, loss of data packets is inevitable, in particular, because of the buffer memory overflow of at least one of the nodes located on the path from the source to the receiver, including the latter. Such losses associated with overflows are hereinafter referred to as congestion of network nodes. There are many ways to prevent and eliminate overloads; these methods, in the majority, are based on the management of data flows. A special place is taken by the maintenance of packages, taking into account their priorities. The article considers a number of original technical solutions to improve the quality of control and reduce the required amount of buffer memory of network nodes. The ideas of these solutions are quite simple for their implementation in the development of appropriate software and hardware for telecommunication devices.

Background: Delivery of quality family planning services depends on availability of skilled health care providers, which is often a challenge in Low- and middle-income countries. This study evaluates the effects of a targeted training program on family planning services delivered by the Lady Health Workers (LHWs) in six districts of Punjab, Pakistan. The primary goal was to enhance the quality and accessibility of family planning services, recognizing the pivotal role of LHWs in community health. Methods: Using a robust panel data difference-in-differences (DiD) approach, we analyzed the electronic medical records (EMR) of 1,410 LHWs over a nine-month period. This timeframe in-cluded both pre-training (July to December 2022) and post-training (April to June 2023) phases. Our assessment focused on the impact of training on five outcome variables: the number of follow-up clients, the number of Intrauterine Contraceptive Device (IUCD) clients, the number of condom clients, the number of modern method clients, and the number of injection clients. We also con-sidered control variables such as LHW age, LHW education, the number of eligible couples in each LHW's catchment area, and a categorical variable for the districts. Results: The positive and statistically significant (p<0.05) coefficients across various service cat-egories – Follow Up Clients [Coeff: 1.00, CI: (0.30 - 1.70)], IUCD Clients [Coeff: 0.23, CI: (-0.01 - 0.46)], Condom Clients [Coeff: 1.41, CI: (0.97 – 1.86)], Modern Method Clients [Coeff: 1.82, CI: (0.96 – 2.68)], and Injection Clients [Coeff: 0.32, CI: (0.14 – 0.50)]. These findings indicate enhanced productivity among LHWs who have received training, with results significant at the 95% con-fidence interval (CI). Conclusion: The study highlights the effectiveness of targeted training programs in boosting family planning services at the community level and offers insightful implications for policy-makers and health practitioners. While focused on six districts in Punjab, these promising results emphasize the need for ongoing training and support for frontline health workers to bolster family planning initiatives.

There has been no significant efficacy in treatment for osteosarcoma (OS) metastasis after nearly four decades of trials. This motivates us to elucidate OS therapies according to their four bidirectional mutation stages. To refresh the OS therapy status quo, the historical developments and clinical advancements are briefly described. However, the main issue of metastasis remains unresolved, accounting for 90% of pulmonary metastasis deaths. Thus, this metastasis problem is related to immune evasion and chemoresistance that are being induced after long-term treatment by the use of immunotherapy for tumorigenesis. Therefore, it is rationale to discuss the relationship cycles of mutation stages including tumorigenesis, metastasis, immune evasion, and chemoresistance. Even though many combinational and targeted therapies have been developed to intensify these mutation treatments, successful clinical translations with higher cure rates are still rare. Through this review, an in-depth understanding of the bidirectional relationship between the four OS mutation stages and their respective therapies is provided. Herein, we summarise the medicines used to treat tumorigenesis, including COLGALT2 inhibitors, Tra2B, and AGAP1, miR-148a and miR-21-5p EVs, and the lncRNA LIFR-AS1. Following the medicines used to treat metastasis are AXL, miR-135a-5p, mRNA BCL6, TGFβ1, Tim-3, SOCS5, CASC15, KLF3-AS1, PDCD4, ATG5, and Rab22a-NeoF1. Then the medicines used to treat immune evasion are N-cadherin, anti-IL-9, USP12 inhibitor, IgG-4+ B-cells, LAP inhibitor, anti-Wnt2 mAb, anti-αvβ8 integrin, HK2-mediated IκBα, IDO inhibitor with NO, and TGF-βRII with anti-IgG1. Finally, the medicines used to treat chemoresistance are DHFR, FPGS, HSP-90AA1, XCT-790, ATKI, and IGF1. As a result, this contribution is expected to serve as a reference and guide for scientists and clinicians.

This study examines the moderating effect of trained human capital on the associations of accounting information systems, generalized auditing software, and technology adoption with the performance of external auditors among Saudi listed companies. This study used a survey-based methodology. The final sample consisted of 136 responses with an 8% response rate. Using Smart-PL4 analysis, the results showed that there is a positive correlation between accounting information systems and external auditors. Conversely, a negative relationship between generalized auditing software and external auditors has been documented. In addition, this study reported a negative association between technology adoption and external auditors. However, the results highlight the positive relationship between trained human capital and external auditors. Overall, this study provides valuable insights for accounting and auditing policymakers on how external auditors’ performance is influenced by several factors in the Saudi audit market.

Despite the 12-lead electrocardiogram (ECG) being the gold standard in evaluating clinical presentations of arrythmias of various kinds, several notable limitations, namely in accuracy and localization, have recently garnered concern with respect to administering appropriate therapeutic measures. The following text puts these limitations under the spotlight, highlighting the difficulty and challenging nature of standard ECG analysis and therapeutic measures, while simultaneously showing a novel body surface electrocardiographic mapping system that utilizes 3D spatial imaging and pinpoint localization algorithms in order to compensate for the shortcomings of the standard ECG, thereby providing higher precision data collection. We provide a brief overview of the novel device in a selection of arrhythmic demographics, along with its validity and reliability, while illustrating the benefits and positive outcomes of its utility.

The new emergence and re-emergence of arbovirus infections vectored by Aedes mosquitoes have been spread across Southeast Asia, Central Africa, United States, tropical Oceania and become a major of public health concerns. These arbovirus diseases found to have a similar vector, symptoms of the diseases and environments. The situation has become complicated without any specific vaccine or treatment for the diseases. As far as we concern, vector control is the best defense with many challenges, a scattered breeding site and biological behavioral sometimes, more difficult to control. Herein, we present a review of studies on current techniques proposed to combat arbovirus infections vectored by Aedes mosquitoes. A crucial gap in a vector control program is the inability to eliminate and destroy the cryptic breeding site by using conventional control methods. The idea and proper concept of using mosquitoes to bring insecticide to their oviposition site had been getting more interest in people to explore. Autodissemination is a self-delivery technique by manipulating the behavior of mosquitoes, carrying the insecticide and disseminate to cryptic breeding sites. This technique has shown a promising result in some countries and can be considered as additional tools in a vector control program

Big Data classification has recently received a great deal of attention due to the main properties of Big Data, which are volume, variety, and velocity. The furthest-pair-based binary search tree (FPBST) shows a great potential for Big Data classification. This work attempts to improve the performance the FPBST in terms of computation time, space consumed and accuracy. The major enhancement of the FPBST includes converting the resultant BST to a decision tree, in order to remove the need for the slow K-nearest neighbors (KNN), and to obtain a smaller tree, which is useful for memory usage, speeding both training and testing phases and increasing the classification accuracy. The proposed decision trees are based on calculating the probabilities of each class at each node using various methods; these probabilities are then used by the testing phase to classify an unseen example. The experimental results on some (small, intermediate and big) machine learning datasets show the efficiency of the proposed methods, in terms of space, speed and accuracy compared to the FPBST, which shows great potential for further enhancements of the proposed methods to be used in practice.

The water quality of the river is becoming deteriorated due to human interference. It is essential to understand the relationship between human activities and land-use types to assess the water quality of a region. GIS has the latest tool for analyzing the spatial correlation. Land use land cover and change detection is the best illustration to show the human interactions on land features. The study assessed water quality index of upper Ganga River near Haridwar, Uttarakhand and spatially correlated them with changing land use to reach a logical conclusion. At the upper course of Ganga along 78 Km long from Kaudiyala to Bhogpur, water samples were collected from five stations. For water quality index the physicochemical parameters like pH, EC, DO, TDS, CaCO3-, CaCO3, Cl¯, Ca++, Mg++, Na+, K+, F-, Fe2+ were considered. The result of the spatial analysis was evaluated through error estimation and spatial correlation. The root mean square error between spatial land use and water quality index of selected sampling sites was estimated as 0.1443. The spatial correlation between land-use change and site-wise differences in water quality index has also shown a high positive correlation with R² = 0.8455. The degree of positive correlation and root mean square error has strongly indicated that the water quality of the river at the upper course of Ganga is highly impacted through human activities.

The second-order factor effect of burner optical ports and edge inter-matrices (EIM) and the first-order factor of pressure on the soot formation process and behavior of premixed sooting flames in a high-pressure burner are numerically investigated here. Three-dimensional computational fluid dynamics (CFD) simulations of a premixed flame C₂H₄/air at p = 1.01 and 10 bar using a one-step chemistry approach are first performed to justify the satisfied predictability of the prospective axisymmetric two-dimensional (2D) and one-dimensional (1D) simulations. The justified 2D simulation approach shows the generation of an axial vorticity around the EIM and axial multi-vorticities due to the high expansion rate of burnt gases at the high pressure of 10 bar. This leads to the development of axial multi-sooting zones, which are manifested experimentally by visible luminous soot streaks, and to the boosting of soot formation conditions of a relatively low-temperature field, < 1800 K, and a high mixing rate of gases in combustion around and above the EIM location. Nevertheless, a tolerable effect on the centerline soot volume fraction (f_V) profile, f_V < 3%, is manifested only at high heights above the burner of the atmospheric sooting flame C₂H₄/air ϕ = 2.1, and early at the high pressure of 10 bar of this flame, f_V < 10%. Enhancing the combustion process reactivity by decreasing the rich equivalence ratio of the fuel/air mixture and/or rising the pressure results in the prior formation of soot precursors, which shifts the sooting zone upstream.

In this paper, a local meshless method (LMM) based on radial basis functions (RBFs) is utilized for the numerical solution of various types of PDEs, due to the flexibility with respect to geometry and high order of convergence rate. In case of global meshless methods, the two major deficiencies are the computational cost and the optimum value of shape parameter. Therefore, research is currently focus towards localized radial basis function approximations, as the local meshless method is proposed here. The local meshless procedures is used for spatial discretization whereas for temporal discretization different time integrators are employed. The proposed local meshless method is testified in terms of efficiency, accuracy and ease of implementation using regular and irregular domains.

The primary distribution systems are comprised of power lines delivering power to utility feeders from substations. The inspection and maintenance of damaged and broken power system insulators are of paramount importance for continuous power supply and public safety. hence, to identify any faults and defects in advance a periodic inspection of power line insulators and other components be ensured beforehand. To automate the process and reduce operational cost and risk Unmanned Aerial Vehicles (UAVs) are being extensively utilized. As they present a safer and efficient way to examine the power system insulators and their components without closing the power distribution system ensuring continuous supply to the end-users. To achieve these objectives in this work a novel dataset is designed by capturing real images using UAVs and manually generated images collected to overcome the data insufficiency problem. Deep Laplacian pyramids based super-resolution network is implemented to reconstruct high-resolution training images. To improve the visibility of low light images a low light image enhancement technique is used for the robust exposure correction of the training images. Using computer vision-based object detection techniques to identify faults and classify them according to classes they belong. A different fine-tuning strategy is implemented for fine-tuning the object detection model to increase detection accuracy for the specific faulty insulators. To improve the faults detection several flight path strategies are proposed for efficient inspection. Such strategies overcome the shuttering effect of insulators along with providing a less complex, time, and energy-efficient approach for capturing video stream of the power system components. Performance of different object detection models is presented for selecting the suitable one for fine-tuning on the specific faulty insulator dataset. Our proposed approach gives a less complex and more efficient flight strategy along with better results. For defect detection, our proposed method achieved an F1-score of 0.81 and 0.77 on two different datasets. Our approach is based on real aerial inspection of in-service porcelain insulators by extensive evaluation of several video sequences showing robust faults recognition and diagnostic capabilities. Our approach is demonstrated on data acquired by a drone in Swat Pakistan.

The modulation of Nrf2 activity has been reported to be implicated in the pathology of various neurological disorders, including epilepsy. Previous studies have demonstrated that Nrf2 is activated in the post-status epilepticus rat model, however, the spatio-temporal, as well as cell type-specific expression of Nrf2 following brief epileptic seizures remains unclear. Here, we evaluated how an acute epileptic seizure affected the expression of Nrf2 and its downstream genes in the cortex and the hippocampus up to 1-week following the induced seizure. We found that after a pentylenetetrazol-induced seizure, Nrf2 significantly increased at 24 h at the mRNA level and 3 to 6 h at the protein level in the cortex. In the hippocampus, the Nrf2 mRNA level peaked at 3 h after the seizure, and no significant changes were observed in the protein level. Interestingly, the mRNA level of Nrf2 downstream genes peaked at 3-6 h after seizure in both the cortex and the hippocampus. A significant increase in the expression of Nrf2 was observed in the neuronal population of CA1 and CA3 regions of the hippocampus, as well as in the cortex. Moreover, we observed no change in the co-localization of Nrf2 with astrocytes neither in the cortex nor in CA1 and CA3. Our results revealed that following a brief acute epileptic seizure, the expression of Nrf2 and its downstream genes is transiently increased and peaked at early timepoints after seizure predominantly in the hippocampus, and this expression is restricted to the neuronal population.

In this work, a highly efficient, molybdenum disulfide (MoS2) based near infrared (NIR) heterojunction photodetector is fabricated on a Si substrate using a cost-effective and simple drop casting method. A non-stoichiometric and inhomogeneous MoS2 layer with a S/Mo ratio of 2.02 is detected using energy dispersive X-ray spectroscopy and field emission scanning electron microscope analysis. Raman shifts are noticed at 382.42 cm-1 and 407.97 cm-1, validating MoS2 thin film growth with a direct bandgap of 2.01 eV. The fabricated n-MoS2/p-Si photodetector is illuminated with a 785 nm laser at different intensities, and demonstrate the ability of the photodetector to work in both regions, the forward biased and reverse biased from above 1.5 V and less than -1.0 V. The highest responsivity, R is calculated to be 0.52 A/W while the detectivity D* is 4.08 x 10^10 Jones for an incident light intensity of 9.57 mW/cm2. The minimum rise and fall times are calculated as 1.77 ms and 1.31 ms for an incident laser power of 9.57 mW/cm^2 and 6.99 mW/cm^2 respectively at a direct current bias voltage of 10 V. The demonstrated results are promising for the low-cost fabrication of a thin MoS2 film for photonics and optoelectronic device applications.

The concerning rise in emergence and prevalence of resistant strains to drugs of M. tuberculosis has ,the prompted researchers to look for new and effective treatments. With this motive, biscoumarins were identified as the lead molecules on a whole-cell-based screening of several less explored low molecular weight bioactive compounds against M. tuberculosis strains. Among the screened biscoumarins, the highest dock score derivatives were synthesized (a-h) using a programmable microwave synthesizer for better yields and reaction control. The synthesized derivatives were evaluated against H37Rv, H37Ra, M. smegmatis, an MDR surrogate model, and other bacterial strains for the structure-activity response. Assessment of the synthesized library against mycobacterial strains led to the identification of compounds (f and d) as lead anti-tuberculosis agents. Compounds (f and d) exhibited less toxicity against human cell lines. At the same time, it displayed enjoyable activity wherein MIC concentrations were observed to be 16- and 32 µg/mL against the susceptible H37Rv, and H37Ra strains of M. tuberculosis and MIC value of 128 µg/mL for M. smegmatis, respectively. For mechanistic insights and identification of drug binding targets, molecular docking and dynamic simulations were employed for a panel of 16 mycobacterial enzymes essential for mycobacterial growth and survival. These in silico studies revealed the DprE1 enzyme as a druggable target for the anti-tuberculosis activity of the selected biscoumarins derivatives. Further investigation is underway in our laboratory, leading to its development as an anti-tuberculosis drug (animal model studies).

The four solvent extractives obtained from aerial parts of Leucophyllum frutescens were evaluated for their Total Antioxidant Activity (TAA) by ammonium molybdate method, scavenging potential by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and Trolox-Equivalent Antioxidant Capacity (TEAC) assays, metal-reducing potential by Cupric Reducing Antioxidant Capacity (CUPRAC) and Ferric Reducing Antioxidant Power (FRAP) assays, Total Phenolic Content (TPC), Total Flavonoid Content (TFC) and their biological activities. The study concluded that BULE exhibited total antioxidant activity (226.235±1.222 mg AA.Eq.gm-1 DE±S.D) by molybdate method, CHLE exhibited more scavenging potential (DPPH 209.589±8.500 mg trolox Eq.gm-1 DE±S.D and TEAC 210.166±7.954 mg trolox Eq.gm-1 DE±S.D) and reducing potential (CUPRAC 646.889±16.889 mg trolox Eq.gm-1 DE±S.D & FRAP 472.981±15.625 mg trolox Eq.gm-1 DE±S.D). Phytochemical quantification concluded high TPC by BULE (189.369±1.393 mg GA.Eq.gm-1 DE±S.D) and high TFC by CHLE (232.458±1.589 mg Qu.Eq.gm-1 DE±S.D). Strong inhibition of α-glucosidase and urease enzymes was observed by HELE (IC50 0.3321±0.007 mg.ml-1±SD) and BULE (IC50 4.09±0.357 mg.ml-1±SD) extractives, respectively. The hemolytic effect shown by hexane extract (HELE) was higher with HA50 25.545±0.927 ug.ml-1±SD whereas methanol (MELE), chloroform (CHLE), and butanol (BULE) exhibited hemolytic effects at higher concentration with HA50 400.067±1.364, 321.394±1.332, and 332.957±0.465 µg.ml-1±SD, respectively. GC-MS profiling of HELE of L. frutescens was performed for qualitative analysis. The principal phytochemicals tentatively identified by GC-MS analysis of HELE accounts for fatty acids (60.221%), lignans (17.687%), ketones (3.358%), phenols (2.584%), sesquiterpenes (1.265%), and aldehydes (0.345%).

A formulation of the Density Functional Theory (DFT) is constructed as an application of the method of maximum entropy for an inhomogeneous fluid in thermal equilibrium. The use of entropy as a systematic method to generate optimal approximations is extended from the classical to the quantum domain. This process introduces a family of trial density operators that are parametrized by the particle density. The optimal density operator is that which maximizes the quantum entropy relative to the exact canonical density operator. This approach reproduces the variational principle of DFT and allows a simple proof of the Hohenberg-Kohn theorem at finite temperature. Finally, as an illustration, we discuss the Kohn-Sham approximation scheme at finite temperature

Image registration (IR) is a process that deforms images to align them with respect to a reference space, making it easier for medical practitioners to examine various medical images in a standardized reference frame, such as having the same rotation and scale. This document introduces image registration using a simple numeric example. It provides a definition of image registration along with a space-oriented symbolic representation. This review covers various aspects of image transformations, including affine, deformable, invertible, and bidirectional transformations, as well as medical image registration algorithms such as Voxelmorph, Demons, SyN, Iterative Closest Point, and SynthMorph. It also explores atlas-based registration and multistage image registration techniques, including coarse-fine and pyramid approaches. Furthermore, this survey paper discusses medical image registration taxonomies, datasets, evaluation measures, such as correlation-based metrics, segmentation-based metrics, processing time, and model size. It also explores applications in image-guided surgery, motion tracking, and tumor diagnosis. Finally, the document addresses future research directions, including the further development of transformers.

Nowadays, brain signal processing is performed rapidly in various brain-computer interface (BCI) applications. Most researchers focus on developing new methods for the future or improving the basic implemented models to identify the optimum standalone feature set. Our research focuses on four ideas. One of them introduces future communication models, and the others are for improving old models or methods. These are: 1) new communication imagery model instead of speech imager using the mental task: Due to speech imagery is very difficult, and it is impossible to imagine sound for all of the characters in all of the languages. Our research introduces a new mental task model for all languages that call Lip-sync imagery. This model can use for all characters in all languages. This paper implemented two lip-sync for two sounds, characters or letters. 2) New combination Signals: Selecting an inopportune frequency domain can lead to inefficient feature extraction. Therefore, domain selection is so important for processing. This combination of limited frequency ranges proposes a preliminary for creating Fragmentary Continuous frequency. For the first model, two s intervals of 4 Hz as filter banks were examined and tested. The primary purpose is to identify the combination of filter banks with 4Hz (scale of each filter bank) from the 4Hz to 40Hz frequency domain as new combination signals (8Hz) to obtain well and efficient features using increasing distinctive patterns and decreasing similar patterns of brain activities.3) new supplement bond graph classifier for SVM classifier: When SVM linear uses in very noisy, the performance is decreased. But we introduce a new bond graph linear classifier to supplement SVM linear in noisy data. 4) a deep formula recognition model: it converts the data of the first layer into a formula model (formula extraction model). The main goal is to reduce the noise in the subsequent layers for the coefficients of the formulas. The output of the last layer is the coefficients selected by different functions in different layers. Finally, the classifier extracts the root interval of the formulas, and the diagnosis does based on the root interval. For all of the ideas achieved the results of implementing methods. The results are between 55% to 98%. Less result is 55% for the deep detection formula, and the highest result is 98% for new combination signals.

During the dry season, glaciers contribute significantly to the water supply downstream, especially in areas with seasonal rainfall. It is important to have physical-based glacier models, which are more advanced in quantifying the future dynamics of glaciers and melt distribution. Toward this purpose, an investigation of different numerical modeling tools and their approach is conducted and planned further to incorporate a glacier module into a spatially distributed model called mHM (Mesoscale Hydrological Model, mhm-ufz.org). An open-source tool called MATILDA (Modeling Water Resources in Glacierized Catchments) is used beforehand to implement the glacier entities to the application catchment Maipo Basin in Chile. Due to limited time availability and source of data, the glacier melt of the MATILDA model is integrated into the mHM model to see what the implications would be if the glacier module was implemented from scratch in mHM. The analysis of the glacier hydrology resulting from the Maipo-Glacier model was carried out by comparing the modeled glacier flows with the total observed flows. To assess the credibility of the models, the results are compared based on three goodness-fit measures, specifically r^2Coefficient of Determination), NSE (Nash-Sutcliffe Efficiency), and KGE (Kling-Gupta Efficiency). Application of the mHM model in the Maipo basin in Central Chile is performed by using prepared input datasets, showing that the approach is viable as evidenced by a Kling-Gupta Efficiency of 0.80 and Nash-Sutcliffe Efficiency of 0.70 from the starting periods of 1950 to 2020. Overestimation by the mHM model occurs during the late summer season, particularly when temperature decreases. The MATILDA model is used on glacier melt distribution, forcing data is prepared from regional datasets, and a glacier profile is constructed from ice thickness datasets. According to the model, the average KGE result for the years 2012–14 and 2015–18 was respectively 0.44 and 0.41. Glacier melt produced by Matilda is in the range of 58-68 % of the total runoff and the glacier area decreased by 22-23% during the simulation period from 2012-14 and 2016-2018. A pilot sub-basin Olivares is used in the coupling mHM model with initializing MATILDA glacier melt. The new model is underestimated during the seasonal transition in the initial days of the simulation. A considerable portion of the ablation period might be missed as a result of the initial storage quality, true glacier extent, and height distribution being understated. As a conclusion, the mHM Model was capable of predicting runoff well in a mountainous region and could also serve as a monitoring tool for watershed management. There are differences in results between the two models because of the different spatial resolutions and methodologies. MATILDA have a glacier retreat routine that gives better result for the glacier characteristics such as. A new glacier dynamics model needs to be implemented in the future to develop intermediate complexity, bridge catchment, and glacier scales after using the mHM, MATILDA, and mHM with MATIDLA model for analysis of glacier and highlighting the model's deficiencies in the initial period of simulative assessments.

Lifestyle physical activity (PA) and nutrition are known to be effective interventions in preventing and managing obesity related comorbidities is adult populations, but less so in children and adolescents. We examined the effectiveness of lifestyle interventions in children from minority ethnic populations in western high-income countries. Our systematic review included 53 studies involving 26045 children from minority ethnic populations within western countries, who followed lifestyle intervention programs lasting between 8 weeks and 5 years with an aim to prevent and/or manage childhood obesity and associated comorbidities, including adiposity and cardiometabolic risks. Studies were heterogenous in terms of lifestyle intervention components (nutrition, PA, behavioural counselling) and settings (community vs. schools and after schools). Our meta-analysis included 31 eligible studies and showed no significant effects of lifestyle interventions when they focused on body weight and body mass index (BMI) outcomes [pooled BMI mean change = -0.09 (95% CI -0.19, 0.01), p=0.09]. This was irrespective of the intervention program duration (< 6 months vs. ≥ 6 months), type (PA vs nutrition/combined intervention) and weight status (overweight or obese vs no normal weight), all showed no significant effects in the sensitivity analysis. Nonetheless, 19 of the 53 studies reported reduction in BMI, BMI z scores and body fat percentage. However, majority of lifestyle interventions adopting a quasi-design with a combined primary and secondary obesity measures (11 out of 15 studies), were effective in reducing obesity comorbidities of cardiometabolic risks including metabolic syndrome, insulin sensitivity, and blood pressure in children with overweight and obesity. Preventing childhood obesity and associated comorbidities in children from high-risk ethnic minority groups is best achieved using a combined PA and nutrition intervention approach, which jointly target preventing obesity and cardiometabolic disease primary and secondary outcomes, especially measures of diabetes, hypertension, and cardiovascular disease.

This paper presents designing an attitude motion control strategy for a half-car model using an anti-jerk predictive controller. Anti-jerk predictive controller based on active aerodynamics surfaces is employed to deal with the anticipated future road maneuvers and improve vehicle ride performance by canceling out external jerks acting on the vehicle body. The body jerks are produced during vehicle traversing on a double lane-change maneuver, acceleration, or braking. The control strategy helps the vehicle to achieve a realistic operation of the active aerodynamic surface to improve the vehicle’s ride performance, i.e., ride comfort and road holding during cornering, acceleration, or braking. The anti-jerk predictive controller is developed based on the predictive control strategy, which predicts future road inputs and uses them to compensate for the vehicle’s attitude motion. The simulation results show that the proposed control strategy effectively reduces the effects of vehicle body jerks transmitted to the passengers, improving ride comfort without degrading vehicle handling. The anti-jerk predictive controller successfully tracks the desired attitude position by canceling the external body jerks.

Dynamic Realistic Failure Process Analysis (DRFPA) is a numerical software based on FEM it is firstly validated by comparing with the experimental test. Such validation is carried out under two consistent concrete specimens under uniaxial compression. After validation, DRFPA is used to study the influence of two parallel pre-existing crack inclination angles on the fracture of concrete under dynamic loads. The evolution of wing cracks and secondary cracks is investigated by observing the initiation, coalescence, and propagation of them. Meanwhile, the relationship between failure mode and inclination angles is discussed via analyzing the acoustic emission events. Finally, it is concluded the relationship between inclination angles of pre-cracks and performance/stability of concrete structure.

Clustered regularly interspaced short palindromic repeats or CRISPR, one of the major technological tools from nature's toolbox, has revolutionized the scientific world with its potential use in humans and plants. CRISPR Cas9 was first known as an adaptive immune system of bacteria. It is a system that cleaves foreign DNA. It has been exploited to be used as a genome editing tool for correcting genetic diseases in humans, for plants to create stress-resistant plants, and for a variety of different purposes. This review provides a basic overview of its applications in different areas of biological research. It has immense potential for a variety of researches, but it's still a mystery for science. It feels like scientists just know a tip of an iceberg.

Nowadays, speed up development and use of digital devices such as smartphones have put people at risk of internet crimes. The evidence of present crimes in a computer file can be easily unreachable by changing the prefix of a file or other algorithms. In more complex cases, either file divided into different parts or the parts of a file that has information about the file type are deleted, where the file fragment recognition issue is discussed. The known files are divided into different fragments, and different classification algorithms to solve the problems of file fragment recognition. A confusion matrix measures the accuracy of type recognition. In the present study, first, the file is divided into different fragments. Then, the file fragment features, which are obtained from Binary Frequency Distribution (BFD), are reduced by 2 feature reduction algorithms; Sequential Forward Selection algorithm (SFS) as well as Sequential Floating Forward Selection algorithm (SFFS) to delete sparse features that result in increased accuracy and speed. Finally, the reduced features are given to 3 classifier algorithms, Multilayer Perceptron (MLP), Support Vector Machines (SVM), and K-Nearest Neighbor (KNN) for classification and comparison of the results. In this paper, we proposed the algorithm of file type recognition that can recognize 6 types of useful files ( pdf, txt, jpg, doc, html, exe), which may distinguish a type of file fragments with higher accuracy than the similar works done.

This paper introduces a theory for the evolution of corporates in which the growth and sustainability strategies are developed simultaneously. Since the introduction of corporate sustainability, it has been an extra cost for risk mitigation and making ‘compensating’ positive impact. The world has reached a tipping point of volatility, mainly due to climate change but also by emergence of COVID-19, so that the applicability of existing corporate structures is under question and these poses high risk to the existence of our planet. On the other hand, the technology cost for sustainable investment has reached a parity in comparison with non-sustainable alternatives. Therefore, our proposed Organic Grow Theory introduces a step-by-step approach so that corporates can grow and be profitable without compromising the ability of future generations to meet their needs. It is concluded that, a new structure for corporate, called Founcorp, would be needed to direct corporates to evolve being a responsible legal entity.

The copper deposition on the platinum and palladium nanoelectrode has been studied using cyclic voltammetry. The use of nanoelectrode platinum and palladium are defined in the study of heavy metals. The noble nanoelectrode of metal has a typical silicone processing structure. In comparison to the nanoelectrodes, the geometry of the electrode series is complex and balanced. Nanoelectrodes of platinum are found effective in detecting heavy metal. There was regular analysis of the use of the sensors. The identification constraints down to the ng /L level was accomplished by refined electrode geometry and the stripping procedures. The process was used for the study of water sample determination. Another heavy metal ion attack voltammetric reaction was studied. The SEM picture clearly observed and characterized the nanoparticle electrode by X-ray diffraction and cyclic voltammetry.

Speckle noise corrupt the major part of ultrasound image, because of which the quality deteriorate and loss of valuable information leads to false diagnosis. A large community of images like synthetic aperture radar (SAR) image, Synthetic image, and simulated ultrasound image, require despeckling at pre-processing stage for better processing. Cleaning the speckle from image and preserving the edge details is a vital task. Nowadays not only despeckling is considered as an important process but also preserving information at boundary and edges of image is also important. As most of the algorithms able to remove speckle noise but fails to preserve the details of edges. This paper covers several recent methods for removal of speckle noise along with various metrics opted for comparisons. The distinctive part of this paper is, a mathematical and parametric review has been done. Also a table is also included which summarizes the entire paper.

Use of rhizosphere microorganisms provides an alternative or supplement to conventional plant breeding to improve water deficit tolerance of tomato plants. Experiment was carried out to explore the effect of two microbial species, AMF (Rhizophagus irregularis) and Bacillus subtilis, in single and co-application, on growth, colonization, and molecular aspects of tomato plants under drought stress. Co-inoculated plants showed less reduction in growth traits, photosynthetic pigments, colonization rate, and increased compatible solutes like proline which help in sustaining relative water content than non-inoculated plants. Inoculation considerably enhanced proline dehydrogenase activity, and significantly reduced both Δ1-pyrroline-5-carboxylate reductase Δ1-pyrroline-5-carboxylate synthetase activity causing lower proline accumulation in inoculated plants under drought stress. Co-inoculated plants showed obvious upregulation of antioxidant system, thus facilitating amelioration of oxidative stress through exclusion of reactive oxygen species. No inoculation under drought stress upregulated abscisic acid related genes expression but have no effect in plants inoculated either sole or mixed inoculation. Expression of aquaporin genes was upregulated in plants co-inoculated and with AMF alone under normal condition. However the expression of aquaporin genes were decreased or unaffected in plants inoculated with Bacillus subtilis but increased in non-inoculated plants. Co-applied AMF and bacillus subtilis substantially increase drought tolerance by upregulating proline metabolism, antioxidant enzymes and aquaporin genes. Therefore our results suggest that co-inoculation mediated drought tolerance is linked with increased proline accumulation, enhanced antioxidant enzyme activities and differential regulation of ABA biosynthetic and aquaporin genes, which is vital for osmotic adjustment of host plant.

Within the past few decades, thousands of experiments have been performed to characterize waste and biomass to estimate the bioenergy potential and product identification. There is a need to develop an integrated process model based on experimental literature, and simulation to obtain suitable products. In this study municipal solid waste (MSW) characterization and integrated process model have been developed to optimize final products in a reactor system. The process model has two modes R&amp;D and reactor control (RC) to obtain suitable products including bio-oil, char, and gases. A database was integrated based on thermokinetics, machine learning and simulation models to optimize product efficiency. The experimental data includes thermogravimetric analysis, Fourier transform Infrared Spectroscopy, Gas chromatography, and Mass spectrometry, which are linked with pyrolysis experimental setup. Feedstock-product mapping models were incorporated into the database along with the temperature, heating rates, elemental analysis, and final product concentration, which are utilized for pyrolysis reactor setup. Product feasibility is conducted based on lifecycle cost, affordability, and product efficiency. The present work will bridge the gap between experimental study and decision making based on obtained products at several experimental conditions around the world.

The most modern technique utilized to create intricate and complexly manufactured parts for a variety of applications is called additive manufacturing (AM). Fused deposition modeling (FDM) has received the greatest attention in the development and manufacturing sectors. The main objective of this study was to investigate how printing factors affected the mechanical characteristics of printed samples. Samples were produced using an FDM 3D printer in compliance with ASTM D638 using a variety of input settings, including orientation, layer thickness, speed, and infill pattern. On the printed samples, tensile tests and morphological analysis using a scanning electron microscope (SEM) were done. The findings of this study demonstrate that factors including layer thickness, printing speed, and orientation significantly affect the tensile strength of ABS printed samples. Discovering the process settings that could lead to superior mechanical and physical characteristics would undoubtedly assist designers and manufacturers worldwide as the FDM 3D printer becomes more and more crucial in manufacturing engineering parts.

In this paper, we demonstrate a useful interaction between the theory of clique partitions, edge clique covers of a graph, and the spectra of graphs. Using a clique partition and an edge clique cover of a graph we introduce the notion of a vertex-clique incidence matrix for a graph and produce new lower bounds for the negative eigenvalues and negative inertia of a graph. Moreover, utilizing these vertex-clique incidence matrices, we generalize several notions such as the signless Laplacian matrix, and develop bounds on the incidence energy and the signless Laplacian energy of the graph. %The tight upper bounds for the energies of a graph and its line graph are given. More generally, we also consider the set $S(G)$ of all real-valued symmetric matrices whose off-diagonal entries are nonzero precisely when the corresponding vertices of the graph are adjacent. An important parameter in this setting is $q(G)$, and is defined to be the minimum number of distinct eigenvalues over all matrices in $S(G)$. For a given graph $G$ the concept of a vertex-clique incidence matrix associated with an edge clique cover is applied to establish several classes of graphs with $q(G)=2$.

This study discusses the experimental assessment of the in-plane mechanical behavior of a multi-leaf stone masonry wall built from cut stone and reinforced with metal connectors (cramps and dowels). The wall, inspired by conventional multi-leaf stone walls, is meant for use in modern stone masonry buildings. The wall is constructed from two parallel load-bearing walls with a cavity between them, which aims to conceal the installation and insulation needed in modern buildings. The load-bearing walls are connected with cramps and dowels at certain intervals so that the wall works as a single section against horizontal and vertical loads. To characterize the in-plane behavior of the proposed wall, compressive, triplet, and diagonal compression tests were conducted to investigate the compressive strength, shear strength, modulus of elasticity, stiffness, ductility, and energy absorption of the wall. Compared with dry and mortar joint walls, the use of dowels increased the initial shear capacity of the wall by 11 and 19 times, respectively. The application of cramps without curving channels inside the individual stone elements decreased the compressive strength by 18%. The energy absorption of the designed walls with metal connectors was substantially increased to that of the specimens representing conventional stone walls. The results obtained show the applicability of the wall due to its higher shear strength and minimal drop in compressive strength, which is within acceptable limits.

The Kashmir valley is prone to flooding due to its peculiar geomorphic setup compounded by the rapid anthropogenic land system changes and climate change. The study assesses the impact of land use and land cover (LULC) changes between 1980 and 2020 and extreme rainfall on peak discharge and sediment yield in the Upper Jhelum Basin (UJB), Kashmir Himalaya, India using KINEROS2 model. Analysis of LULC change revealed a notable shift from natural LULC to more intensive human-modified LULC, including a decrease in vegetative cover, deforestation, urbanization, and improper farming practices. The findings revealed a strong influence of the LULC changes on peak discharge, and sediment yield relative to the 2014 timeframe, which coincided with the catastrophic September 2014 flood event. The model predicted a peak discharge of 115101 cubic feet per second (cfs) and a sediment yield of 56.59 tons/ha during the September 2014 flooding, which is very close to the observed peak discharge of 115218 cfs indicating that the model is reliable for discharge prediction. The model predicted a peak discharge of 98965 cfs and a sediment yield of 49.11 tons/ha in 1980, which increased to 118366 cfs and, 58.92 tons/ha respectively in 2020, showing an increase in basin’s flood risk over time. In the future, it is anticipated that the ongoing LULC changes will make flood vulnerability worse, which could lead to another major flooding in the event of an extreme rainfall as predicted under climate change and, in turn compromise achievement of sustainable development goals (SDG). Therefore, regulating LULC in order to modulate various hydrological and land surface processes would ensure stability of runoff and reduction in sediment yield in the UJB, which is critical for achieving many SDGs.

The Saudi government has undertaken rapid and swift actions, such as suspending Omrah and holding international flights. Such affirmative actions enhanced citizens and residents’ confidence in the government officials’ ability to fight the pandemic. However, there are more than 361,178 reported cases of Covid-19 with 6131 deaths as of December 22, 202. As nurses are the largest component of the health care workforce in Saudi Arabia, it is important that they are trained and have the skills and resources to adapt, whether on the frontline of a crisis or in a clinical environment. Nurses play a key function in fulfilling the needs of medical treatment by being the most important part of the health care delivery system.

The eruption of COVID-19 patients in 215 countries worldwide has urged for robust predictive methods that can detect as early as possible the size and duration of the contagious disease and also providing precision predictions. In much recent literature reported on COVID-19, one or more essential parts of such investigation were missed. One of the crucial elements for any predictive method is that such methods should fit simultaneously as much data as possible; these data could be total infected cases, daily hospitalized cases, cumulative recovered cases, and deceased cases, and so on. Other crucial elements include sensitivity and precision of such predictive methods on the amount of data as the contagious disease evolved day by day. To show the importance of these aspects, we have evaluated the standard SIRD model and a newly introduced Gaussian-SIRD model on the development of COVID-19 in Kuwait. It is observed that the SIRD model quickly picks up the main trends of COVID-19 development, but the Gaussian-SIRD model provides precise prediction a longer period of time.

One of the special trends in health care is the increasing availability of data and services to the cloud, especially for convenience (for example, providing a complete patient medical record without interruption) and savings (for example, economic issues). Management of health care data). However, there are limitations to using common cryptographic prototypes and access control models to address security and privacy concerns in an increasingly cloudy environment. In this paper, we explore the potential and capacity of using China's Blockchain technology to protect health care data hosted in the cloud. We also explain the real challenges of such an approach and further research is needed. Health care is a highly data-dependent domain, with large amounts of data being created, published, stored and accessed daily. For example, data are created when a patient undergoes a number of examinations (such as computed tomography or computed tomography scans) and the data need to be sent to the radiologist and then to a physician. The visit results are then stored in the hospital, and then need to be accessed later by another physician at another hospital within the network. It is clear that technology can play an important role in improving the quality of care for patients (for example, using data analytics to make informed medical decisions) and potentially costing more by allocating resources more efficiently in terms of personnel, equipment, etc. , Reduce. For example, paper-based data extraction is difficult to extract into systems (for example, it is costly and may involve data entry errors), archiving them and accessing them as needed is costly. These challenges may cause medical decisions to be incomplete, requiring repeated tests for missing information or missing data stored in another hospital in another state or country (at the expense of increased costs and no convenience). (For patients) and so on. Because of the nature of the industry, it is important to ensure the security, privacy and integrity of health care data. As a result, there is definitely a need for a secure and secure data management system.

Novel severe acute respiratory syndrome coronavirus 2 infection (SARS-Cov-2) is an acute respiratory and infectious disease. This perspective aims to provide the basic understanding of the inflammation caused by SARS-Cov-2 and relation to trigeminal ganglion (TG). Virus enters through the mucous membranes of orofacial region and reach the TG where it resides and take control of its peptides including Substance P (SP).SP is the main neuropeptide, neuromodulator and neuro-hormone of TG, associated with nociception and inflammation under noxious stimulus. SP release is triggered and consequently, it affects the immune cells, blood vessels to release the mediators for inflammation. Cytokine storming is initiated and cause respiratory distress, bronchoconstriction and death in complicated cases. Neurokinin-1 Receptor (NK-1R) antagonist and glucocorticoids may be used to alleviate the symptoms and treat this infection. SP is the main culprit seem to be involved in the triggering of inflammatory pathways in SARS-Cov-2 infection. It has direct association with cardiorespiratory rhythm, sleep-wake cycle, nociception, ventilator responses and regulates many important physiological and pathological roles. Its over-secretion should be blocked by NK-1R antagonist. However, experimental work leading to clinical trials are mandatory for further confirmation.

The Coronavirus disease due to SARS-CoV-2 emerged in Wuhan city, China in December 2019 and rapidly spread more than 200 countries as a global health pandemic. There are more 3 million confirmed cases and around 207,000 fatalities. The primary manifestation is respiratory and cardiac but neurological manifestations are being reported in the literature as case reports and case series. The most common reported symptoms to include headache and dizziness followed by encephalopathy and delirium. Among the complications noted are Cerebrovascular accident, Guillian barre syndrome, acute transverse myelitis, and acute encephalitis. The most common peripheral manifestation was hyposmia. It is further noted that sometimes the neurological manifestations can precede the typical features like fever and cough and later on typical manifestations develop in these patients. Hence a high index of suspicion is required for timely diagnosis and isolation of cases to prevent the spread in neurology wards. We present a narrative review of the neurological manifestations and complications of COVID-19. Our aim is to update the neurologists and physicians working with suspected cases of COVID-19 about the possible neurological presentations and the probable neurological complications resulting from this novel virus infection.

Aravalli Mountain Range is an example of erosional mountains, trending NE-SW, shows numerous faults and lineaments. Udaipur area, situated south-east part of the mountain, is considered as tectonically active. So the main objective is to study relative tectonic activity of the Ahar watershed of Udaipur, Rajasthan, India. To assess relative tectonic activity of the area, geomorphic indices such as stream length gradient index (SL), asymmetry factor (Af), basin shape (Bs), valley floor width to valley height ratio (Vf), mountain front sinuosity (Smf), hypsometic integral (Hi), hypsometric curve and transverse topographic symmetry factor (T) is applied. DEM (SRTM), Google earth image and enhanced image of Landsat TM (2008) is used to extract linear features. Result of these geomorphic indices of each sub-watersheds are used to divide area from low to high relative tectonic activity classes, expressed as relative tectonic active index (Iat) and according to Iat value the sub watershed UDSW2, 3 and 4 is tectonically relatively more active than remaining part of the area. Field validation associated with evidences highlighted by using geomorphic indices as well as stream deflrction and lineament analysis reveals that the Ahar watershed of Aravalli Range, particularly the north-western flank, is most affected by tectonic activity.

This research aims to explore the complex interplay between supply chain resilience (SCR), digital supply chain (DSC), and sustainability, focusing on the moderating influence of supply chain dynamism. The goal is to understand how these elements interact within the framework of contemporary supply chain management and how they collectively contribute to enhancing sustainability outcomes. The sample size is 300 CEOs and managers. The study approach integrates quantitative research methods. Structural equation modeling (SEM) is utilized to quantitatively analyze the direct and indirect effects of SCR and DSC on sustainability. The numerous surveys we conduct among supply chain ecosystem stakeholders provide a rich picture of practical implications and contextual nuances. In sum, our early findings generally support a positive relationship between SCR and sustainability in and of itself decrying the need for more resilient supply networks for sustainability. We further find the beneficial impact of digital technologies in promoting sustainability via enhancing environmental control and controlling for efficiency in supply chains. We also offer evidence to show that supply chain dynamism compounds the positive logic between SCR and DSC and sustainability. As a final word, it must be noted that our work speaks to the burgeoning Supply Chain Dynamism as moderator literature by examining the direct and contingent effects of SCR and DSC on not only performance but sustainability. By shedding light on the moderating role of dynamism, the study provides fresh insights into the multifaceted nature of supply chain management and sustainability practices. The study's findings enhance theoretical understanding by elucidating the synergistic effects of SCR, DSC, and sustainability in dynamic supply chain settings. It augments existing theoretical frameworks by integrating concepts of resilience, digitalization, and sustainability into a comprehensive model. Practical and economical, the research offers actionable guidance for organizations aiming to improve sustainability performance through resilient and digitally advanced supply chains. By acknowledging the role of supply chain dynamism, managers can tailor strategies to manage disruptions effectively and leverage digital innovations. Economically, adopting sustainable practices can result in cost savings and competitive advantages. The research emphasizes the importance of aligning supply chain strategies with sustainability goals to drive long-term value and societal impact.

Polyaniline or PANI is a conductive polymer (CPs) with flexibility in turning into conducting properties. The drawback is mainly in terms of limited mechanical properties improvement which attracted the interest in fabrication of PANI with other polymeric materials. PANI-PVL composites film was synthesized and fabricated in this work with chronological steps according to the objectives aligned in two different phases. The first phase determines the optimum parameters to synthesize nanosized PANI. The ideal initial molar ratio, r was 1, stirring speed of 600 rpm, purified by filtration, synthesis temperature of 25 oC, washed by dopant acid, acetone and distilled water. The usage of non-ionic surfactant, Triton X-100 (TX100) with 0.1 % concentration favours the formation of smaller particle size of PANI and good dispersibility compared to the usage of anionic sodium dodecyl sulphate (SDS). The synthesis of PANI in nanosized dimension has the potential to be applied for antimicrobial applications such as gloves and antimicrobial coating of frequent contact points in the near future.

The article outlines a creative approach by fusing ideas from fuzzy contractions, graph mappings, and Kannan mappings to create a brand-new notion known as "Kannan-graph-fuzzy contraction." This combination of concepts makes it possible to create a unique framework for resolving real-world issues controlled by nonlinear models. It is anticipated that using Kannan-graph-fuzzy contractions will offer a fresh approach to discussing solution existence in situations where these ideas overlap. This strategy might have a significant impact on a lot of real-world applications, proving how practical multidisciplinary techniques are for tackling issues in the real world originating from technology and engineering. The article includes several illustrated examples based on computer simulations, making the results more explicit.

Thermoelectric (TE) waste heat recovery has attracted significant attention over the past decades, owing to its direct heat-to-electricity conversion capability and reliable operation. However, methods of system-level TE design optimization for specific application systems have not been thoroughly investigated. This work theoretically studies the performance optimization and exergy analysis of TE systems for recovering waste heat from the exhaust ducts of a gas turbine power plant. A numerical tool has been developed to solve the coupled charge and heat current equations with temperature-dependent material properties and convective heat transfer at the interfaces. Our calculations show that at the optimum design with 50 % fill factor and 6-mm leg thickness made of state-of-the-art Bi2Te3 alloys, the proposed system can reach power output of 10.5 kW for the TE system attached on a 2 m-long, 0.5 x 0.5 m2-area exhaust duct with system efficiency of 5 % and material cost per power of 0.23 $/W. Moreover, our extensive exergy analysis reveals that only 1 % of the exergy content of the exhaust gas is exploited in this heat recovery process and the exergy efficiency of the TE system can reach 8 % with improvement potential of 85 %.

This review delves into the intricate relationship between folate (Vitamin B9) intake, especially its synthetic form, folic acid, and its implications on health and disease. While folate plays a pivotal role in the one-carbon cycle, essential for DNA synthesis, repair, and methylation, concerns arise from its excessive intake. The literature underscores potential deleterious effects, such as an increased risk of carcinogenesis, disturbances in DNA methylation, and impacts on embryogenesis, pregnancy outcomes, neurodevelopment, and disease risk. Notably, these consequences stretch beyond the immediate effects, potentially influencing future generations through epigenetic reprogramming. We probe into the molecular mechanisms underlying these effects, including accumulation of unmetabolized folic acid, Vitamin B12 dependent mechanisms, altered one carbon metabolism, altered methylation patterns, and interactions with critical receptors and signaling pathways. Furthermore, we emphasize differences in the effects and mechanisms mediated by folic acid compared to natural folate. Given the widespread folic acid supplementation, it is imperative to further research its optimal intake levels, and the molecular pathways impacted by its excessive intake, ensuring the health and well-being of the global population.

We present the design and overall development of an eight degrees of freedom (DOF) based Bioinspired Quadruped Robot (BiQR). The robot is designed with a skeleton made of cedar wood. The wooden skeleton is based on exploring the potential of cedar wood to be a choice for legged robots’ design. With a total weight of 1.19 kg, the robot uses eight servo motors that run the position control. Relying on the inverse kinematics, the control design enables the robot to perform the walk gait-based locomotion in a controlled environment. The robot has two main aspects: 1) the initial wooden skeleton development of the robot showing it to be an acceptable choice for robot design, 2) the robot’s applicability as a low-cost legged platform to test the locomotion in a laboratory or a classroom setting.

The development of quantum computers seeks software developers' attention regarding security in the era of Information Technology, software security is the primary goal for our quantitative assessment of software security in the development cycle of software. Security assessment of software is identifying the key security factors of the software. A security elective provides ex-tensive strategies and calculations to ensure product safety. The security assessment is the key factor in surveying, administering, and controlling security to further enhance the nature of safety. It should be acknowledged that assessing security early on in the development process is beneficial in identifying worms, hazards, flaws, and threats. The definition and portrayal of Quantum Computing (QC) in software security will be discussed in this study. Researchers use cryptography calculations to secure our financial institutions, medical devices, military weaponry, planes, ships, vehicles, and pilots. Here authors of this study use the Fuzzy Technique for Order Preference by Similarity to Ideal Situation (FTOPSIS) to quantitatively assess the weight/rank of the quantum enable security alternatives like (Diffie-Hellman key-exchange algorithm, Quantum key distribution algorithm, Deutsch-Jozsa Algorithm, Special Deutsch-Jozsa Algorithm, Grover’s Algorithm and Quantum key distribution algorithm in GHZ state) with security factors like (Confidentiality, Integrity, Authenti-cation, Privacy, Reliability, Maintainability, Authorization, Integrity, Possessions, and Availability). Additionally, they critically analyze and select the six alternatives of quantum-based security algorithms. The nature of safety infers the ability to execute a thing on time in this exploration study, specifically 'software security'.

In this paper, we employ fuzzy Sumudu transform for solving system of linear fuzzy differential equations with fuzzy constant coefficients. The system with fuzzy constant coefficients is interpreted under strongly generalized differentiability. For this purpose, new procedures for solving the system are proposed. A numerical example is carried out for solving system adapted from fuzzy radioactive decay model. Conclusion is drawn in the last section and some potential research directions are given.

The current study was formulated with the aim of assessing the impact of the Extent of Drug addiction on the Family environment and interventions for drug-addicted youth in rural areas of Dir Lower Khyber Pakhtunkhwa, Pakistan. The study comprised a dependent variable (Extent of Drug addiction) and an independent variable (Family Environment). A sample size of 266 was randomly selected for primary data collection through structured interviews. The collected information was evaluated through descriptive analysis (frequency and percentage distribution) and inferential analysis, specifically utilizing the Chi-square Statistical Test. The study concluded that drug addiction among youth has an adverse impact on the family environment, leading to instability and violent behavior. Further, families of drug-addicted youth experience a high level of dissatisfaction in relationships, often culminating in divorce. Similarly, the families of drug-addicted are characterized by low cohesion, role conflict, and tolerance. Thus, the government should formulate polices and strategies for the prevention of drug addiction, with speedy implementation across all institutional dynamics, including family. Moreover, It is also crucial to rehabilitate the lifeblood of a nation (youth) in terms of socio-economic, emotional and psychological growth. These recommendations were put forward in the light of the current study.

This study was to designed to develop sorafenib-loaded polymeric nanoparticles, surface-modified with pluronic F-127 for the effective treatment of hepatocellular (HCC) and renal cell carcinomas (RCC). Poly lactic coglycolic acid (PLGA) was used to encapsulate different concentrations of sorafenib by a simple modified solvent evaporation method applying pluronic F-127 as a surfactant and coating agent. The preformulation and characterization studies were conducted to evaluate the incompatibilities among sorafenib, PLGA and pluronic F-127, and physicochemical properties of the formulations, respectively. The sizes of the coated and plain PLGA nanoparticles were ~140 ± 14.7 nm and ~ 120 ± 10.1 nm, respectively. It has been confirmed from the in vitro release studies that PLGA sustained the release of sorafenib, avoiding the initial burst release, while the in vivo studies demonstared that surface-modified nanoparticles have greater affinity in the target aorgans than plain PLGA nanoparticles and free drug keeping the dose constant (20 mg/kg body weight). The delivery of sorafenib-loaded polymeric PLGA nanoparticles into the target tissues and their pharmacokinetic parameters have been improved significantly compared to the reported formulations.

Bread wheat (Triticum aestivum L.) is staple of Pakistani people. However, its yield at farmer field is low as compared with its genetic potential. Integration of various crop and soil management strategies might be an option to enhance wheat productivity at farmer field. This 2-year experiment was conducted to check the influence of combine application of natural plant water extracts and biochar on the productvity of wheat during the winter season of 2015-16. The experiment consisted of seven treatment viz. (1) control (2) application of biochar (0.18 kg pot-1) alone, (3) application of sorghum water extract (SWE) alone, (4) application of moringa water extract (MWE) alone, (5) application of biochar + SWE, (6) application of biochar + MWE, (7) application of biochar + SWE+MWE. The results revealed that application of both crop water extracts in combination with biochar improved the growth and grain yield of wheat. Use of MWE in combination with biochar enhanced the grain weight, grain number and grain yield of wheat by 44, 14, and 24%, respectively than the control treatment. In crux, use of MWE in combination with biochar might be a viable option to improve the productivity of bread wheat.

The objective of this study is to examine different types of bias present in assessment tools and techniques, identify and eliminate any forms of favoritism, and suggest effective approaches for advancing equity and objectivity in assessment procedures. The research utilizes a qualitative methodology, incorporating surveys and focus group discussions with educators and students to collect data. Thematic analysis is a method employed for the purpose of analyzing qualitative data. The results suggest that students hailing from diverse cultural backgrounds perceive partiality in the language and cultural context of evaluations, leading to diminished scores. According to academic professionals, standardized tests are subject to bias, and offering accommodations that cater to linguistic and cultural diversity may improve the academic achievement of students from diverse cultural backgrounds. The findings of this research are of great importance to professionals in the domains of education, policy development, and academia who seek to improve assessment practices and promote equitable educational opportunities for all learners.

Background: A person living with HIV / AIDS bargains with stressors such as discrimination, stigma depression, and several psychological impacts. The stressors experienced by people with HIV/ AIDS will certainly have an impact on daily activities, welfare, and management of medications which in general will have an impact on the quality of life. To deal with these stressors, it is necessary to have good and proper coping from within the PLWHA. Coping strategies need to be owned and carried out by PLWHA in order to respond adaptively to the stressor conditions experienced. Purpose: The aim of this review is to describe the stress experienced and the coping strategies used among PLWHA. Methods: This literature review used keywords in the search for international references are coping strategy, stressor, HIV-AIDS. Inclusion criteria: selection of titles that are relevant to the formulation of the problem and objectives, full-text articles in English, articles published from 2019 to 2021. The exclusion criteria used were coping strategy articles that did not involve HIV patients. Search references from electronic database sources namely ProQuest, CINAHL, and ScienceDirect.Six articles that are deemed worthy of analysis are then discussed or analyzed. Results: Age, gender and sexual orientation have contributed to the emerging stressor among PLWHA. The internal and external coping strategies focusing on the problem are important for PLWHA in handling the stressor. Conclusion: People with HIV-AIDS have many stressors in their lives, but they also have proper coping strategies depending on their internal and external conditions.

Online identity-based theft is known to be one of the most serious and growing threats to victims, such as individuals and organizations, over the last 10 years due to the enormous economic damage these crimes have caused. The availability of personal information on the Internet has increased the chances of this cyber-crime. Online identity theft crime is the result of a combination of cyber-crimes on the one hand and lack of awareness and training of users on the other hand to protect personal data on the other. Education and awareness, which also contributes to early detection, is the strongest tool for consumers to safeguard themselves from online identity fraud. This paper provides a comprehensive explanation of online identity theft, the various approaches that thieves use to attack individuals and organizations and the types of fraud involved in this cyber-crime. The aim of this research is to evaluate the need for a reformulation of the concept of identity theft in order to be compatible with the evolution of behaviors and fraud.

Arabic was the language of philosophy, logic, Islamic sciences and rhetorical linguistic sciences. It was used in the writing of all sciences generally and became the language of world culture. Although the other languages of the Islamic world had a little share, but all peoples of Islamic countries; Arabs and non-Arabs, Muslims and non-Muslims attributed to that movement appreciated. Hence, Arab sciences flourished in their bright ages. Arabic language was a cultural container of the ancient Greek and Latin intellectual heritage. As the ancient Greek and Latin sciences and literatures were translated into Arabic in the bright ages of Islam. Arab language was a strong bond for them, as a common human heritage for the centuries to save it from being lost, as Muslims used it to develop their sciences and arts, as Muslims in the East used the Western sciences and literatures in the modern age, because they are not Eastern or Western, but the common efforts of all humanity. Arabic language opened for the dictionaries ​​and other tongues of cross-fertilization, civil friction and simulation. Arabic had become the language of sciences: mathematics, astronomy, engineering, logic, philosophy, mysticism, agriculture, industry and economics by the continuous efforts of scientists in their scientific research, invention, experimentation, knowledge collection and classification in various fields, where orientalists recognized the Arab leadership. That scientific and literary civilization moved to Europe through Italy, Andalusia, Crusades and the Ottoman Caliphate. Europeans learned Arabic language, literature and sciences in the centers of Toledo, Fez and cities of Maghreb.

The paper discusses how joint damage and deterioration affect the seismic response of existing reinforced concrete frames with sub-standard beam-column joints. The available simplified modeling techniques are critically reviewed to propose a robust, yet computationally efficient technique for simulating the nonlinear behavior of substandard beam-column joints. Improvements over the existing models include simulation of the cyclic deterioration of joint stiffness and strength as well as pinching in the hysteretic response, implemented considering a deteriorating hysteretic rule. A fibre-section forced-based inelastic beam-column element is developed; considering improved material models and fixed-end rotation due to bond failure, rebars-slip and inelastic extension, to simulate the deteriorating cyclic behavior of existing pre-cracked beam-column members. For the assessment of frames with substandard exterior beam-column joints, a nonlinear model for the exterior joint is developed and validated through a full-scale quasi-static cyclic test performed on a substandard T-joint connection. The proposed model allows considering structural performance in risk assessment while accounting for true inelastic mechanisms at the joints.

The canonical decomposition of a bipartite graph is a new decompositionmethod that involves three operators, parallel, series and K+S. The class of weak bisblit graphs is totally decomposable with respect of these operators, and the class of bicographs is totally decomposable with respect of parallel and series operators. We prove in this paper that the class of bipartite (P_6,C_6)-free graphs is exactly the class of bipartite graphs that are totally decomposable with respect of parallel and K+S operators. We simplify the recognition algorithm of weak-bisplit graphs to adepte with bipartite (P_6,C_6)-free graphs. As a result of this adapted algorithm, we prsent efficient solutions in this class of graphs for two optimization graph problems, the first is the maximm balanced bi-clique problem and the the second is the maximum independent set problem.

Abstract: The Internet of Things (IoT) has witnessed rapid and widespread adoption across various domains, including transportation, healthcare, education, agriculture, urban planning, smart homes, and more. Despite its transformative potential, this pervasive deployment of IoT devices has introduced new challenges, particularly concerning security and privacy threats such as unauthorized data access and device breaches. The excessive usage of these technological devices, coupled with the absence of robust security and privacy systems for user data, calls for a comprehensive approach to address these issues. In this study, we propose a novel framework designed to analyze, audit, test, and detect potential vulnerabilities within IoT environments and applications. The central components of the proposed framework include a machine learning algorithm for data classification and attack detection, along with the integration of Blockchain technology to enhance security measures. Specifically, the framework performs an in-depth analysis of user data to identify potential security or privacy vulnerabilities. Additionally, it conducts rigorous testing of smart services and automated data-collecting devices. To evaluate the effectiveness of our classification algorithm, we conducted a comprehensive implementation on a real-world IoT dataset. The results showcased the efficiency and accuracy of our approach in detecting and mitigating potential threats. Furthermore, based on our research findings, we provide valuable recommendations for enhancing security and privacy in IoT ecosystems. We also highlight emerging trends in the security and privacy domains, which can serve as valuable insights for researchers and practitioners. In conclusion, our proposed framework offers a robust and proactive approach to address the security and privacy challenges, such as unauthorized data access and device breaches posed by the widespread adoption of IoT devices. By combining machine learning algorithms and Blockchain technology, we contribute to safeguarding user data and fostering a secure environment for IoT applications. This study lays the groundwork for further advancements in the realm of IoT security and privacy, ensuring a safer and more resilient IoT landscape for the future.

Catalase can decompose hydrogen peroxide in plants under controlled and stressed condi-tions. In a stressed environment, the increase in hydrogen peroxide production makes catalase activity a major defense system for plant growth. The current study was conducted to evaluate the catalase activity of pre-isolated and identified bacterial strains Bacillus aryabhattai (AN30), Bacillus megaterium (AN24), Bacillus megaterium (AN31) and Bacillus megaterium (AN35) and their potential for rice seedlings growth promotion. These strains were characterized for quantita-tive catalase, urease, siderophores, and exopolysaccharides production using LB media. Sub-sequently, the effectiveness of these strains was checked by quantifying the catalase activity in the rhizosphere of rice seedlings. Furthermore, the catalase activity was quantified in the roots and shoots of rice seedlings. Plant growth parameters were also studied in a growth room trial. The strain AN24 showed the maximum catalase activity (1.36 mol cm-1), urease ac-tivity (1.35 mol cm 1), exopolysaccharides (4.20 µg mL-1), and siderophores (2.32%) production in LB media. All tested strains showed significantly higher catalase activity in soil compared to control. Among sole application, strain AN24 showed better results; however, consortium application of strains AN24+AN30+AN35+AN31 showed the maximum increase in catalase ac-tivity in the rhizosphere of rice seedlings. Moreover, consortium application of AN24+AN30+AN31+AN35 resulted in the highest increase in catalase activity, dry biomass of shoots and roots, shoot and root length of rice seedlings. The results showed that a consortium of these Bacillus strains with catalase activity has greater potential to enhance an antioxidant defense system and growth promotion of rice seedlings. However, further experimentation under natural conditions is required before using these strains as potential bioinoculants for improving the rice growth and yield.

Navigation systems are considered as a fast and efficient source of road information to drivers. However, they can distract drivers with more potential accidents on the road. This study examined the effect of navigation systems on driver distraction and visual search while driving in different driving conditions. An eye-tracking system was used to collect visual search data from twenty young drivers while using a driving simulator. Several factors were investigated, including the driving environment (urban and rural), the illumination level (day and night), and the display of the navigation system (large and small) as well as their interactions. Several measures related to eye movements were used in this experiment, including percentage of total Global Positioning System (GPS) fixation duration, average duration of GPS fixation, GPS fixation frequency, the percentage of total dwell duration for the road ahead, the frequency of dwelling on the mirrors and driver’s right and left side windows, and the percentage of dwellings on the mirrors and driver’s right and left side windows. Statistical analysis of the collected data was performed with repeated measures analysis of variance (ANOVA). The experiment revealed that the small GPS display creates more distraction in terms of average gaze duration and total gaze duration. Moreover, daytime driving conditions increase distraction. Regarding the driver’s visual search, the study showed that the visual search area is wider and more spread out during the day, which leads to better driving performance. This study will compare small and large navigation displays to determine which one is more effective in reducing driver distractions, and contribute to understanding driver distraction and visual search while using the navigation system display.

This paper presents a comprehensive review that highlights the characteristics of non-isolated step-up converters based on high boost voltage lifting techniques. The paper categorises the high boost techniques: multistage/multilevel, switched capacitor, voltage multiplier, voltage lift, switched inductor, and magnetic coupling. The paper also discusses in detail the advantages and disadvantages for each category such as cost, complexity, power density, reliability and efficiency. The number of passive and active components, voltage gain, voltage stress, switching frequency, efficiency and power rating are also compared. Although the paper considers coupling inductors in the context of the non-isolated converter, the focus of the entire article is on the non-isolated high voltage step-up techniques. The key contribution in this paper is the review of high boosting techniques rather than the DC /DC converters. This allows divergence of new ideas and new power converters that will help provide highly efficient and flexible power converters for several applications where the sending end voltage is very low as photovoltaic systems. In addition, many applications and control techniques of DC/DC converters are summarised in this paper.

Abuse of amphetamine-related drugs (ARDs) causes traffic accidents, violence, and overdose. In forensic toxicology, analysis for ARDs in biological samples can help identify those driving or performing other tasks under the influence of drugs, clarify the cause of death, and identify recent drug users. In this study, we validated a pseudo-isocratic UPLC-qTOF-MS method following mixed mode cation exchange (MMSPE) extraction for analysis of ARDs in blood. The procedure requires 250 μL of blood to achieve a limit of quantification (LOQ) and detection (LOD) of 20 ng/mL for all analytes. In aged animal blood samples, extraction recoveries of 63-90% and matrix effects of 9-21% were observed. Precision and accuracy for all analytes were within 20% and 89–118%, respectively. The analytical method was developed and validated in accordance with the Scientific Working Group for Forensic Toxicology (SWGTOX) Standard. It has acceptable accuracy and precision for use in doping control and forensic toxicology.

Based on the resource-based theory, the current study examines the relationship between competitive strategies and strategic alliance performance. Furthermore, big data predictive analytics is treated as a boundary condition between competitive strategies and strategic alliance performance. Big data of predictive analytics in operations and industrial management has been a focal point in the current era. There has been little attention has about big data predictive analytics influences on competitive strategies and strategic alliance performance, especially in developing countries like Pakistan. A survey instrument was used to record the responses from 331 employees of the telecom sectors companies working in Pakistan. Study findings show that big competitive strategies have a positive and significant relationship with strategic alliances performance. It was also found that big data predictive analytics plays the role of moderator between competitive strategies and strategic alliance performance. The study add a new perspective and contribution to the literature on big data predictive analytics, strategic alliance performance, and competitive strategies in Pakistan's telecom sector companies. Further, the study results explain that big data analytics is just like the companies' lifeblood in the current era. The efficient and effective use of big data analytics, companies can boost their standards in a competitive environment.

Steels studs are an inevitable part of drywall construction as they are lightweight and offer the required structural stability. However, the studs act as sound bridges between the plasterboards reducing the overall sound insulation of the wall. Overcoming this often calls for wider cavity walls and complex stud decoupling fixtures that increase the installation cost while reducing the floor area. As an alternative approach, this research reveals the potential of perforated studs to improve the acoustic insulation of drywall partitions. The acoustic and structural performance is characterized using a validated finite element model that acted as a prediction tool in reducing the number of physical tests required. The results established that an acoustic numerical model featuring fluid-structure-interaction can predict the weighted sound reduction index of a stud wall assembly at an accuracy of ±1 dB. The model was used to analyze six perforated stud designs and found to outperform the sound insulation of non-perforated drywall partitions by reducing the sound bridging. Overall, the best performing perforated stud design was found to offer improvements in acoustic insulation of up to 4 dB, while being structurally compliant.

Background: Serious games are conceptualized as a broad topic and overlap segments of more modern forms of education: e-learning, edutainment, game-based learning, and digital game-based learning. Serious Games aligns with digitalization and the modern era and creates novel opportunities for learning and assessment in medical education. Escape rooms, a type of serious games, merge mental and physical aspects to reinforce critical skills useful in daily life. It challenges logic and reasoning and demands careful analysis of situations to correlate and solve different stages of the escape room under pressurized, timed conditions. Furthermore, it serves as an adequate environment to build problem-solving skills, communication skills, and leadership skills through the collaboration of people to achieve a common goal. The aim of this study was to investigate the applications of escape rooms in Medical Education. Method: This study investigated the applications of escape rooms in medical education. Serious games are expanding in education and have attained great relevance due to their intriguing and intrinsically motivating attributes. Within serious games, we focused on escape rooms in which participants are locked in a room, faced with puzzles that must be solved to ‘escape the room’. Compiling the data from the first 100 hits of medical application of escape rooms, we found 72 cases and categorized them by year, specialty, participants structure, simulation experience, and design. Results: We reported on escape rooms in medical education by the year in which they were reported, the medical specialty, the participant structure, grouped or individual, the experience design; real, hybrid, or digital, and the modality of the delivery. 72% of the escape rooms focused on four main areas: nursing education (25.0%), emergency medicine (22.2%), pharmacy (12.5%), and interprofessional education (12.5%). Most of the escape rooms had a group-based physical design and little attention was given to provide a detailed description of the design considerations, such as the pathway type (linear, semi-linear, open). Conclusion: Escape rooms are applied in a wide range of medical education areas. In Medical Education, group-based on-site escape rooms with a focus on nursing, emergency medicine, pharmacy and interprofessional education dominates the implementation landscape. To further advance the field, stronger emphasis on making explicit the design considerations will advance the research and inform implementations.

Pancreatic cancer is a fatal disease with mortality rate of 5% and a with a limited survival rate of 5 years. Despite of the extensive efforts that has been made to cure the disease it still has been considered as ‘undruggable’. It is characterized by epithelial to dense stromal tumor formation however due to lack of diagnosis options and treatment test available to detect the disease to the point at which resection of the tumor is possible, it makes it the fourth leading cause of cancer related death. The unavailable information regarding the early detection of biological markers along with the increased invasive tumor, the inherit chemoresistance against medication radiation and chemotherapy stubbornly fail the therapeutic options available. These associated problems made the scientists to reevaluate the approaches that are currently in practice and take a step back to fully understand the basic biological pathways that are involved in the pancreatic cancer, the heterogeneity of the tumor itself along with expression and a number of mutations that are observed at different locations. Clinical trial along with new approaches are nowadays focus of research to treat this tumor. The review paper describes the basic cellular pathways involved in pancreatic cancer, the gene mutations and their expression having effect on the pathology of the diseases along with treatment options that are available to treat the tumor. These efforts will help with the expansion of our knowledge to undergo the clinical trial and the synthesis of novel medicines for the prognosis of the disease.

Pollution by heavy metals is one of the most severe environmental issues that threaten global sustainability. This review presents a recent advance in electrochemical sensors for heavy metal detection Rotating Disk Platinum Electrode are discussed. This study on the production of a modern natural water electrochemical antimony (II) and cupper (II) test include the use of platinum electrode. Antimony and cupper were pre-concentrated on the modified electrode surface and adsorbed to the surface, oxidizing at E = 540 mV and E = 85 mV, respectively. After 20 min of accumulation, time the best-defined anodic peak was obtained of surface. The precision was tested by carrying out chronoamperometric measurements at a concentration of Sb⁺² and Cu⁺² 8.5x10^-8 M and 9.5x10^-7 M, respectively.

Some α-Pyrone derivatives isolated from Alternaria phragmospora fungus showed promising anti leukemic activities, while others were inactive. CRM1/XPO1 (chromosome region maintenance 1 protein, also called exportin1 or PO1 in humans) has been chosen as a target for antileukemic molecular docking study for those compounds to understand their modes of interaction and structure activity relationships. The results showed that two (2 and 4), out of six, natural α-Pyrone derivatives exhibited well-established interactions with the amino acids of the receptor, which was in agreement with the experimental anti-leukemic results of these compounds. Moreover, twenty hypothetical chemically modified α-Pyrone derivatives (7-27) have been designed. Compounds 7, 8, 22 and 24 showed more efficient docking properties than the previously considered natural compounds.

The novel coronavirus COVID- 19 disease is extremely contagious and has been spread worldwide. First COVID-19 case was identified in December, 2019 and within three months, more than one million affected cases and over 65,000 deaths have been reported. SARS-coronavirus 2 (SARS-CoV-2) also known as 2019-nCoV is a causative agent of COVID-19 disease and belongs to the SARS CoV (Severe Acute Respiratory Syndrome corona virus) family. The SARS-CoV-2 enters the human body by binding its viral surface spike protein with the host angiotensin-converting enzyme 2 (ACE2) receptors and cause infection. To prevent the virus entry and its transmission in the human body, we focused on the two domains of ACE2: i) the N-terminal extracellular binding domain (18-740 residues) reported for coronavirus spike interaction, and ii) the C-terminal cytoplasmic region (762-805 residues) to prevent the virus transmission. Therefore, we proposed: i) inhibition of receptor binding domain (RBD) of SARS-CoV-2 and human ACE2 protein may prevent the virus entry to the host and ii) inhibition of phosphorylation at Ser-787 of ACE2 protein may prevent the transmission of the virus in the COVID-19 patients. In the past, the critical role of Ser 787 in human ACE2 protein has been experimentally verified in SARS-CoV transmission, that upon binding to the receptor, SARS- CoV induces CKII- mediated phosphorylation of ACE2 at Ser-787 that in-turn facilitate virus entry to host cells, followed by replication and activation of ACE2, initiates downstream signaling leading to lung fibrosis. Therefore, in this study, we have suggested post-translational modification (PTM) O-β-GlcNAcylation, and two compounds Chloroquine and 2-hydroxybenzohydrazine might share the common pathways to prevent the COVID-19 infection in human. The addition of O-β-GlcNAcylation at same or neighboring Ser/ Thr residues results in phosphorylation inhibition and a change in protein structural and functional confirmations. Thereby, using neural networking methods, we have identified Ser/ Thr residues in ACE2 that are potential sites for phosphorylation and / or O-β-GlcNAcylation. Molecular docking showed that UDP-GlcNAc has more binding affinity with Ser-787 than the phosphoryl group. Moreover, chloroquine and 2-hydroxybenzohydrazine also showed great potential to bind at Ser-787 that may result in inhibition of Ser-787 phosphorylation and downstream signaling. Furthermore, O-β-GlcNAcylation, chloroquine and 2-hydroxybenzohydrazine showed their high affinity at ACE2-SARS-CoV-2receptor binding domain that may prevent the entry of SARS-CoV-2 into human body. In conclusion, inhibition of human ACE2 phosphorylation at Ser-787 and ACE2-SARS-CoV-2 binding domain could be promising targets against SARS-CoV-2 infection.

Bacterial infections are world-wide problem and resistant bacteria is increasing globally that lead to treatments failure. Thus, it is important to find new techniques that are effective for the treatment antibiotic-resistant microorganisms. Green medicine used for the medication of different bacterial infection. Therefore , the study aimed to evaluate the immunomodulatory activity of essential fatty acid semi carbazide (EFASC) compounds extracted from flaxseed to eradicate resistance pathogens . Crud extracts of Linum usitatissimum was extracted by hexane for extraction of EFASC. The results of LD₅₀ appear that a live suspension of E.coli was 0.49×10⁷ ,while HK E.coli was 10⁸ , 125 mg /ml were the optimum dose in stimulate immune response of EFASC which gave maximum dose of total WBC , Neutrophil and Monocyte count. The immunomodulatory activity appear that E.coli + EFASC released moderate levels of IL-4 . HK E.coli release higher IL-4 lead to increase the hypersensitivity and hyper responses of immune system. HK + EFASC immunogen revealed moderate increased in IL-12 mean level 0.99 pg /ml, HK bacteria recorded 1.49 pg/ml, while the mean of EFASC revealed no significant different compare with control. An effective protection was observed in immunized groups with HK E.coli and EFASC challenged with 100 of LD50 of a live E.coli.

Supplier selection is an important part of supply chain management (SCM) for any organisation to achieve their objectives. The problem has attracted great interest from academics and practitioners. The selection process starts with determining the most important criteria out of a wide range. Many academic researchers apply multi-criteria decision-making (MCDM) techniques for supplier selection. However, the complexity of such approaches may increase significantly, especially when considering a large number of suppliers and selection criteria. This paper proposes an integrated approach combining machine learning classification with the Analytic Hierarchy Process (AHP) to select and evaluate the most suitable supplier. A Decision Tree (DT) classifier is used to select the most important criteria, instead of applying AHP on the complete set of criteria. The applicability of the approach is demonstrated using data from Libyan companies. Results show that decision trees can successfully lead to a most important subset of selection criteria, which would lead to a less complex application of AHP.

In addition to the traditional QoS metrics of delay, delay jitter, and packet loss probability (PLP), Quality of Experience (QoE) is now widely accepted as a numerical proxy for actual user experience. The literature has reported many mathematical mappings between QoE and QoS. These QoS parameters are measured by the network providers using sampling. There are some papers studying sampling errors in QoS measurements; however there is no account of propagation of these sampling errors to QoE evaluation. In this paper, we used industrially acquired measurements of PLP and jitter to evaluate the sampling errors and correlation in measurements. Focussing on Video-on-demand (VoD) applications, we use subjective testing and regression to map QoE metrics onto PLP and jitter. The resulting mathematical functions of QoE and theory of error propagation was used to evaluate the propagated error in QoE, and this error was represented as confidence interval. Using the guidelines of UK government for sampling, our results indicate that confidence intervals around estimated QoE in a busy hour can be between MOS=1 to MOS=5 at targeted operating point of QoS parameters. These results are a new perspective on QoE evaluation, and are of great significance to all organisations that need to estimate the QoE VoD applications precisely.

Smartphone devices, particularly android devices used by billions of people everywhere in the world. Similarly, this increasing rate attracts mobile botnet attackers that is a network of interconnected nodes operated by command and control (C&C) method to expand malicious activities. At present, mobile botnet attacks carried Distributed denial of services (DDoS) that causes to steal sensitive data, remote access, spam generation, etc. Consequently, various approaches are defined in the literature to detect mobile botnet using static or dynamic analysis. In this paper, we have proposed a novel hybrid model, which is a combination of static and dynamic method that relies on machine learning to identify android botnet applications having C&C capability. The results evaluated through machine learning classifiers in which Random forest classifier outperform other ML techniques, i.e. Naïve Bayes, Support Vector Machine, and Simple logistics. Our proposed framework can achieve 97.48% accuracy in detecting such harmful applications. Furthermore, we highlight some research directions and possible solutions regarding botnet attacks for the entire community.

Chronic unpredictable environmental stress (CUES) may induce predisposition to diabetes mellitus. This study investigates the role of CUES on impaired homeostasis. Stressed group mice (n = 20) were exposed to CUES for 16 weeks. Weekly body weight, feed consumption, feed efficiency ratio, fasting blood glucose were monitored. Plasma HbA1c, plasma cortisol, plasma epinephrine and plasma insulin, serum lipids, antioxidants and carbohydrate metabolizing enzymes activity were assessed along with DNA damage and histopathological examination of liver, kidney, pancreas, spleen and skeletal muscles. Fasting blood glucose levels & HbA1c in the stressed were significantly higher compared to control (p < 0.001). Serum lipids were found insignificantly higher in stressed mice compared to control. Body weights of the stressed mice and feed efficiency ratio were found significant (p < 0.001). Plasma corticosterone, plasma epinephrine, HOMA-IR was found to be significantly higher in the stressed group (p < 0.001). Plasma insulin level was found to be significantly lower in the stressed group (p < 0.001). Significant changes were observed in antioxidants level, carbohydrate metabolizing enzymes activity, peripheral tissues and DNA integrity. CUES initiates pathogenesis of diabetes.