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

Cytologic diagnosis of extra‐adrenal paraganglioma presenting as a peripancreatic mass is challenging with a high rate of diagnostic error. We present a case of a peripancreatic mass identified by radiology as a gastrointestinal stromal tumor. Endoscopic ultrasound‐guided fine needle aspiration (FNA) of the mass showed a moderately cellular tumor composed of small to medium sized neoplastic cells with round to oval nuclei arranged singly and in loose clusters. The cells were positive for neuroendocrine markers (synaptophysin and chromogranin) and negative for CD117. A diagnosis of a neoplasm with a neuroendocrine tumor (NET) was made on FNA cytology. The subsequent surgical resection of the tumor revealed peripancreatic paraganglioma with immunohistochemistry positive for synaptophysin, chromogranin, and S100. The latter delineates the sustentacular cells. Although paraganglioma is a well recognized tumor, a detailed comparison of peripancreatic paraganglioma versus pancreatic/gastrointestinal NET is still lacking.

This study evaluated five annual and eleven perennial Indian pasture legumes species for their nutritive value, dry matter, mineral contents and in vitro fermentation parameters, aiming to boost their potential as animal feed. Legume species significantly differed (p<0.05) in organic matter, crud protein (CP), ether extracts, fibres, and protein fractions. Clitoria ternatea (CT) a perennial had higher (p<0.05) buffer soluble protein (477), while neutral detergent soluble protein was highest in annually grown Lablab purpureus (420 g/kg CP). Atylosia scarabaeoides (AS) had higher NSC (392 g/kg DM) than SC (367 g/kg DM). Rapidly degradable fraction (51.7 g/kg tCHO) was lower (p<0.05) than other fractions of carbohydrate. Total digestible nutrients, digestible energy and metabolisable energy varied and values were higher for Desmenthus virgatus and lowest for Stylosanthas seabrana (SSe). The NE values for lactation (NEL), maintenance (NEM) and gain (NEG) were also higher for DV (6.6, 7.95 and 4.28) and lowest for SSe (3.54, 4.24 and 0.58 kJ/g DM), respectively. dry matter intake, digestible DM (DDM) and relative feed value of legumes differed (p<0.05) with mean values of 2.22% body weight, 592 g/kg DM and 102%, respectively. Annual grasses like Dolichos biflorus, Macroptilium atropurpureum, Rhynchosia minima (RM) were found better with micro minerals compared to other perennials. In vitro dry matter degradability, partition factor, short chain fatty acids and microbial protein production of legumes varied (P<0.05) and mean values were 578 g/kg DM, 5.61 mg DDM/mL, 2.42 mm/g and 352 mg/g, respectively. Gas and CH4 production (mL/g and mL/g DDM) varied (p<0.05) being lowest gas from AS (55.5) and highest from CT-blue (141), while CH4 production was lower (p<0.05) from CT-white and AS (8.24 and 9.14) and higher from Arachis glabrata (AG) and Arachis hagenbackii (AH) (15.2 and 15.1). Methane in total gas was low for DV, RM and CT-w (8.99, 9.72 and 9.51%) and loss of DE and ME as CH4 varied (P<0.05) amongst the legumes with mean values of 4.62 and 7.86%, respectively. Based on these findings, each legume offers unique benefits, allowing for tailored combinations of annual and perennial legumes to optimize rumen feed efficiency.

Enhancing spectral efficiency, especially in Non-line-of-Sight environments, is emerging as a pivotal necessity when dealing with the evolving landscape of 5G networks and beyond, sur-passing the capabilities of previous 4G systems to achieve a high information rate combined with minimal interference. Contrary to depending on the traditional Orthogonal Multiple Access (OMA) systems to tackle the issues caused by Non-line-of-Sight (NLoS) environments, advanced wireless networks are focusing on adopting innovative models such as Non-Orthogonal Multiple Access (NOMA), MIMO, IRS technology, etc. In this paper, we present technologies that can be integrated with NOMA to enhance communication reliability in environments that suffer from issues such as limited coverage and lower spectral efficiency mainly caused by huge obstacles. Our exploration includes the fundamental concepts of Cooperative NOMA (C-NOMA), Multiple Input Multiple Output (MIMO), Intelligent Reflective Surfaces (IRS), Unmanned Aerial Vehicles (UAVs), and Energy Harvesting (HV), which adds a layer of sophistication, promising not only improved connectivity but also contributing to a more reliable and environmentally friendly data trans-mission landscape.

To utilize heterosis and combining ability for grain yield and its attributing traits along with three physiological traits viz., leaf area index, chlorophyll fluorescence and chlorophyll content in bread wheat (Tritium aestivum L.) the crosses were attempted during rabi, 2019-20 in a half diallel mating scheme among 8 wheat varieties and the study was carried out during rabi, 2020-21 at Block No. D-13 field of Mahua block, Simradha research farm, Rani Lakshmi Bai Central Agricultural University, Jhansi. Analysis of variance showed significant differences for treatments. Based on per se performance the hybrids NW 5054 x PBW 723 (23.3 g), and HI 1544 x NIAW 34 (23.14 g), were identified for the higher grain yield. The hybrid HI 544 x NIAW 34 (18.41 %) was identified as the best heterotic cross for grain yield per plant and its component traits. The hybrids HI 1544 x NIAW 34 (3.40) and HI 1544 x GW 322 (2.76), as well as the parents HD 3086 (21.85) and PBW 723 (20.68), were identified as superior economic hybrids and parents based on SCA/GCA effects, per se performance for grain yield per plant, and its component trait in bread wheat. Days to heading, flag leaf length, biological yield per plant, harvest index, number of grains per spike, 1000 grain weight, spike length, leaf area index, chlorophyll fluorescence, and chlorophyll content were all positively correlated with grain yield per plant.

Hybrid power plants have recently emerged as reliable and flexible electricity generation stations by combining multiple renewable energy sources, energy storage systems (ESS), and fossil-based output. However, the effective operation of the hybrid power plants to ensure continuous energy dispatch under challenging conditions is a complex task. This paper proposes a dispatch engine (DE) based on mixed-integer linear programming (MILP) for the planning and management of hybrid power plants. To maintain the committed electricity output, the dispatch engine will provide schedules for operation over extended time periods as well as monitor and reschedule the operation in real-time. Through precise prediction of the PV and wind power output, the proposed approach guarantees optimum scheduling. The precise prediction of the PV and wind power are achieved by employing a predictor of Feed-Forward Neural Network (FFNN) type. With such a dispatch engine, the operational cost of the hybrid power plants, and the use of diesel generators (DGs) are both minimized. A case study is carried out to assess the proposed dispatch engine feasibility. A real-time measurement data pertaining to load, wind, and PV power outputs is obtained from different locations in the Sultanate of Oman. The real-time data is utilized to predict the future output power from PV and the Wind farm over 24 hours. The predicted powers are then used in combination with a PV-Wind-DG-ESS-Grid hybrid plant to evaluate the performance of the proposed dispatch engine. The proposed approach is implemented and simulated using MATLAB. The results of the simulation reveal the proposed Feed-Forward Neural Network’s (FFNN) powerful forecasting abilities. In addition, the results demonstrate that adopting the proposed DE can minimize the use of DG units and reduce plant running expenses.

Annually, more than 1.5 million preventable new hepatitis B (HBV) infections continue to occur, with an estimated global burden of 296 million individuals living with chronic hepatitis B infection. This substantial health challenge results in over 820,000 annual deaths attributed to complications such as liver cirrhosis and hepatocellular carcinoma (HCC). HBV vaccination remains the cornerstone of public health policy to prevent chronic hepatitis B and its related complications. It serves as a crucial element in the global effort to eliminate HBV, as established by the World Health Organization (WHO), with an ambitious 90% vaccination target by 2030. However, reports on global birth dose coverage reveal substantial variability, with an overall coverage rate of only 46%. This comprehensive review thoroughly examines global trends in HBV vaccination coverage, investigating the profound impact of vaccination on HBV prevalence and its consequences across diverse populations, including both high-risk and general demographics. Additionally, the review addresses the formidable challenges and facilitating factors essential for achieving WHO's HBV vaccination coverage objectives and elimination strategies in the coming decade and beyond.

In this paper, we proposed the fusion of two projection based face recognition algorithms: local binary Patterns in DCT domain and singular value decomposition (SVD) characterized by its simplicity and efficiently. Standard databases ORL are used to test the experimental results which prove that proposed system achieves more accurate face recognition as compared to individual method.

Microbial composition across substrates in mangroves, particularly in the Middle East, remains unclear. This study characterized bacterial communities in sediment, water, Terebralia palustris snail guts, and plastic associated with Avicennia marina mangrove forests in two coastal lagoons in the Sea of Oman using 16S rDNA gene MiSeq sequencing. The genus Vibrio dominated all substrates except water, which featured unique genera Sunxiuqinia and Pseudomonas. There were significant differences in bacterial communities on different substrata, in particular plastic. Snail guts harbored the highest number of unique Operational Taxonomic Units (OTUs) in both lagoons. Plastic in the polluted Sawadi lagoon with low salinity harbored distinct genera like Vibrio, Aestuariibacter, Zunongwangia, and Jeotgalibacillus absent in Qurum lagoon with higher salinity and low pollution. Sawadi lagoon exhibited higher species diversity in sediment and plastic substrates, Qurum lagoon demonstrated lower overall species diversity. The PCA indicates that environmental factors like salinity, pH, and nutrient levels significantly influence bacterial community composition across substrates. Variations in organic matter and potential anthropogenic influences, particularly from plastics, further shape bacterial communities. This study highlights the complex microbial communities in mangrove ecosystems, emphasizing the importance of considering multiple substrates in mangrove microbial ecology studies.

Background: Despite their generally favorable prognosis, hepatic fibrosis remains a possible complication for hepatitis B virus (HBV) inactive carriers. This study aimed to estimate the prevalence of significant fibrosis and associated risk factors among Omani HBV inactive carriers. Methods: A retrospective study was conducted of 200 Omani HBV inactive carriers visiting a tertiary hospital in Muscat, Oman, between January 2017 and December 2018. Significant fibrosis (stage F2 or higher) was identified using two-dimensional shear-wave elastography. Baseline clinical, laboratory, and radiological data were analyzed to determine associations. Results: Of the total sample, 106 patients (53%) were male, and the mean age was 44.6 ± 9.3 years. The prevalence of significant fibrosis was 20% (n = 40). Male gender (p = 0.007), age ≥60 years (p = 0.024), and fatty changes in liver ultrasound (p = 0.044) were found to be independent factors for significant fibrosis. Conclusion: the prevalence of significant fibrosis was relatively high among a sample of Omani HBV inactive carriers, with several sociodemographic and clinical risk factors identified. Periodic assessment of liver function is needed for patients with these risk factors; moreover, routine biochemical parameters could be useful predictors of disease prognosis. Further research is recommended to substantiate these findings.

Background: Inflammatory Bowel disease (IBD) is one of the worldwide health issues with increasing incidence. Recent data point out that those patients can have a defective immune system, rendering response to vaccinations suboptimal. Since 1990, Hepatitis B Virus (HBV) vaccination has been introduced among the compulsory childhood vaccinations in Oman. Given the questionable immunogenicity of vaccinations in IBD patients, we designed this study to quantify the immune response to scheduled HBV vaccine in IBD patients and compare it with that in a matching control cohort of healthy blood donors at Sultan Qaboos University Hospital (SQUH). Methods: This is a retrospective case-control study that was conducted between the 1st of July 2023 and the 31st of May 2024 at SQUH. Using the hospital information System (HIS), a total of 252 participants were enrolled in our study and divided into two groups. Group (1) included 126 IBD patients and group (2) included 126 healthy controls. Baseline demographics, medical comorbidities and viral serologies before and after vaccination were collected. The primary outcome of the study was to compare the long term immune response to HBV vaccine between the two groups. The secondary outcomes included identifying possible risk factors for suboptimal vaccine response. Results: One hundred and twenty-six participants were included in each group. Durable protective immune response to HBV vaccine was attained in 29 patients (23%) of the IBD group compared to 109 participants (86.5%) of the control group. There was a statistically significant association (p = 0.0156) between prednisolone treatment and low immune response to HBV vaccine. Moreover, esomeprazole usage exhibited a statistically significant association (p < 0.0001) with suboptimal response to HBV vaccine. Meanwhile, there was no statistically significant correlation between low immunogenicity to HBV vaccine and age, sex, type of IBD, comorbidities, and BMI. Conclusions: IBD patients are less immunogenic to HBV vaccination compared to healthy controls. Factors like esomeprazole and/or corticosteroid therapy might be associated with poor immune response. These findings highlight the importance of reassessing the immunogenicity of HBV vaccination and probably other protective vaccinations in all IBD patients as part of their standard of care.

The predominance of English and Latin-based large language models (LLMs) has led to a notable deficit in native Arabic LLMs. This discrepancy is accentuated by the prevalent inclusion of English tokens in existing Arabic models, detracting from their efficacy in processing native Arabic's intricate morphology and syntax. Consequently, there is a theoretical and practical imperative for developing LLMs predominantly focused on Arabic linguistic elements. To address this gap, this paper proposes ArabianGPT, a series of transformer-based models within the ArabianLLM suite designed explicitly for Arabic. These models, including ArabianGPT-0.1B and ArabianGPT-0.3B, vary in size and complexity, aligning with the nuanced linguistic characteristics of Arabic. The AraNizer tokenizer, integral to these models, addresses the unique morphological aspects of Arabic script, ensuring more accurate text processing. Empirical results from fine-tuning the models on tasks like sentiment analysis and summarization demonstrate significant improvements. For sentiment analysis, the fine-tuned ArabianGPT-0.1B model achieved a remarkable accuracy of 95%, a substantial increase from the base model's 56%. Similarly, in summarization tasks, fine-tuned models showed enhanced F1 scores, indicating improved precision and recall in generating concise summaries. Comparative analysis of fine-tuned ArabianGPT models against their base versions across various benchmarks reveals nuanced differences in performance, with fine-tuning positively impacting specific tasks like question answering and summarization. These findings underscore the efficacy of fine-tuning in aligning ArabianGPT models more closely with specific NLP tasks, highlighting the potential of tailored transformer architectures in advancing Arabic NLP.

The hetero Diels-Alder (HDA) reaction between the ambident heterodiene 3-methylene-2,4-chromandione (MCDO) and the non-symmetric methyl vinyl ether (MVE) is investigated within the Molecular Electron Density Theory (MEDT) at the B3LYP/6-311G(d,p) computational level. The aim of this study is to gain insight into the molecular mechanism and to elucidate the factors that control the selectivity found experimentally. DFT-based reactivity indices reveal that MCDO exhibits strong electrophilic character, while MVE displays a strong nucleophilic character. Meanwhile, Parr function explains the ortho regioselectivity of this HDA reaction. The highly polar nature of this HDA reaction, supported by the high global electron density transfer (GEDT) taking place at the transition state structures (TSs), accounts for the very low activation energy associated with the most favorable TS-4on. The ambident nature of MCDO allows the formation of two constitutional isomeric cycloadduct. In the case of MVE, the pseudocyclic selectivity is attained by a thermodynamic control. This polar HDA reaction displays an endo stereoselectivity and a complete ortho regioselectivity. A comparative Relative Interacting Atomic Energy (RIAE) analysis of the two diastereomeric TS-4on and TS-6on indicates a highly likeness between them, which explains the low pseudocyclic selectivity under kinetic control.

Background: Vaccinating children against COVID-19 is an essential public health approach for preventing infection in children and adults. This study aimed to explore parents' attitudes toward and the rate of COVID-19 vaccine hesitancy among children in Oman. Methods: This cross-sectional study used an online, self-administered questionnaire. The 9-item questionnaire was validated earlier and administered between June 2021 and May 2022. Multiple logistic regression was used to determine the factors associated with vaccine hesitancy. The parents received a pre-validated Google questionnaire. Responses from the parents of children younger than 11 years of age were accepted. Results: 384 participants completed the questionnaire, including 207 males (54%). The response rate was 86% (384/447). Of the 384 participants, 69% of the parents hesitated to vaccinate their children aged 1-11-year-old children). In parents of children aged 1–4 years, parental vaccination status was significantly associated with vaccine hesitancy (odds ratio [OR]: 0.116, 95% confidence interval [CI]: 0.044–0.306; p < 0.001). Additionally, vaccine hesitancy was significantly more common in mothers than in fathers (OR: 0.451, 95% CI: 0.240–0.848; p = 0.013). . Mothers of children were 77% more likely to be hesitant than fathers (.78, 95% confidence intervals (CI) = 0.50–0.1.23; p = 0.283). Conclusion: Many parents hesitated to vaccinate their children against COVID-19. Consequently, future awareness campaigns and strategies should target new vaccines. The results of our study show that the Arabic version of the 5-point Likert Scale for Vaccination Hesitancy is a valid and reliable tool.

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

Cytokine and AMH profiling were done in prepubertal Murrah buffalo heifers post-progesterone supplementation and co-synchronization protocol. Cytokines: IFNγ, IL6, IL1, IL13, TNFα, and TGFβ, and, AMH, Progesterone and Estrogen hormone estimations were done. Ovarian follicular pattern and fertility outcome were recorded. Eighteen prepubertal heifers, 15-17 months of age, 250-300 kg BWt were randomly divided into 3 groups, Group1: n=6, supplemented with altrenogest 0.044mg/kg/day/heifer orally for 14 days along with Co-synch programme; Group2: n=6, administered CIDR for 14 days and co-synch programme, Group3: n=6, received co-synch programme. Ultrasonography was done to ovarian follicle status on respective days of sampling. Pregnancy diagnosis was done around 45 and 60 post-AI. Estradiol 17-β level remained constant in altrenogest group, CIDR implanted and Control groups during the Progesterone treatment and Co-synch treatment. Estradiol levels during Co-synch were significantly less on day 9 of Co-synch (14.41 ± 1.97 pg/mL) than day 0 and on day7 in pre pubertal buffalo heifers in altrenogest group. However, no significance was observed in other groups. Progesterone levels in buffalo heifers subjected to synchronisation protocols varied significantly (P< 0.05) on day 7 of P4 treatment between altrenogest supplemented and CIDR implanted groups, as well as, Co-synch groups. Supplementation of altrenogest showed a significant (P= 0.043) increase in Progesterone levels by day 14 of altrenogest treatment. Progesterone varied significantly in all Groups on day 9 of co synch protocol [ Group 1 (P= 0.02), Group 2 (P= 0.041) and Group 3 (P= 0.007)]. Cytokine IFN-γ showed high correlation with progesterone, indicating the role of IFN-γ in puberty in buffalo heifers (r= 0.626, P< 0.01). AMH had a significant positive correlation supplemented with altrenogest with IFN-γ (r= 0.673, P< 0.01) and TGF-β (r= 0.463, P< 0.01), whereas, with TNF-α it was a negatively correlated (r= -0.34, P< 0.05). Based on Karl Pearson correlation coefficients, IL-13 and TGF-β could be considered as markers for puberty in buffalo heifers.

The present study drops the line for the flow characteristics of fly ash-based (FA) geopolymers reinforced with polypropylene (PP) fibers undergoing the extrusion process during three-dimensional printing. Applying to the Herschel-Bulkley rheological model the research is ready with the sound theoretical basis which is used to understand the flow behavior of these materials under various conditions. A combination of experimental and numerical techniques that are based on the Finite Element Method (FEM) in COMSOL has been used in this study. The results of both the experimental and simulation approaches are then compared and the behavior of the material during extrusion is then examined. The experimental results proved PP fiber content has significant effects on rheological properties. The experiments on mixes which are either devoid of fibers or possess a high content of fiber, encountered problems like a high static yield stress and material segregation. Mixes with fibers of moderate content showed smoother extrusion processes, which means that a suitable range of fiber addition exists for the fibers that optimally balance the mechanical properties and extrudability. Numerical simulations typically agreed with experimental data for fiber contents up until it reached a certain level but not above, suggesting the existence of more complex interactions inside the fibers and the necessity for the subsequent model refinements. The investigation outlines a 0.25% and 0.5% fiber content range that leads to enhanced performance without bringing the extrusion process to greater complications and further making the production of proper, architecturally printed structures possible.

The present study was conducted to explore the floristic composition, life form, and leaf size spectrum of vegetation, seasonality, and habitat condition of the Sultan Khail valley, Hindu Kush range, Pakistan. Regular trips were arranged during 2017–2019 to collect plant specimens and prepare a checklist of the flora of the area. The life form and leaf size spectrum of vegetation were determined. The plant species were also classified based on their habitat. The area is home to 332 species belonging to 234 genera and 96 families. Asteraceae (32 species) was the dominant family in the area, followed by Rosaceae (28 species) and Lamiaceae (21 species). Therophytes were found to be dominant in the area, followed by phanerophytes, while microphylls were the dominant leaf size class, followed by nanophylls. Seasonal variation in life forms showed that the spring, autumn, and winter seasons' flora was dominated by phanerophytes, while therophytes were dominant in the summer season. Seasonal variation in leaf size spectra showed that microphylls were dominant in the spring and summer, while in the autumn and winter seasons, nanophylls were dominant. The highest numbers of species were found in dry places, followed by forests. The flora of the study area is diverse. The habitat condition of the area is dry. The area's phytoclimate is thero-phanerophytic. The flora of the area is subjected to severe anthropogenic stress and needs proper conservation.

IoT is a computational perception that defines a situation, where smart objects are interconnected to the internet/ network. In the last few years, IoT objects have increased in all sectors/ fields and use in all domains of our lives. As the number of devices increases, the privacy of data becomes an important issue. To deal with this issue different techniques have been used by researchers in this field. Unfortunately, these methods have less traceability, privacy of data, and accountability. This paper aims to design a blockchain-based network architecture for Traceability, Data privacy, and Accountability (TDA). Technologies of blockchain are known as a distributed ledger of transactions record, which record the life span information with a timestamp. The major features of blockchain are persistency, decentralization, and audibility. These features help to decrease the budget and increase efficiency. Moreover, to strengthen the TDA architecture, this paper also discusses the performance of the proposed architecture.

Global warming and climate change have been the major concern for multiple disciplines. Population growth, urbanization, and industrialization are major contributing factors to such a problem by escalating the use of fossil fuels to meet their energy demands. The building sector has the largest share in using the total globally produced energy and emitting tons of greenhouse gas emissions. Emerging eco-friendly technologies such as solar and wind energy harvesting are being extensively explored but still, they are insufficient. Nature-inspired technologies can be the solution to our problem. For instance, algae are microorganisms that use water, light, and CO2 to produce energy and sustain life. Exploiting such characteristics in the built environment is termed algae building technology, a very efficient and green application for a sustainable future. Algae-integrated façades show great versatility through biomass and energy production, wastewater treatment, shading, and thermal and acoustic insulation. In this paper, algae will be introduced as a robust tool toward a greener and more sustainable future, The algae-building technology and its implementation will be demonstrated. Steps for applying this sustainable approach in Egypt will be discussed.

Transport Layer Security (TLS) is a cryptographic protocol that provides communications security between two peers and it is widely used in many applications. To reduce the latency in TLS handshake session resumption using pre-shared key (PSK) had been used. But current methods in PSK mode handshake uses a fixed session key multiple times for the lifetime of session ticket. Reuse of fixed session key should be very careful in the point of communications security. It is vulnerable to replay attacks and there is a possibility of tracking users. Paired token (PT) is a new secondary credential scheme that provides pre-shared key in stateless way in client-server environment. Server issues paired token (public token and secret token) to authenticated client. Public token represents signed identity of client and secret token is a kind of shared secret between client and server. Once client is equipped with PT, it can be used for many symmetric key based cryptographic applications such as authentication, authorization, key establishment, etc. It was also shown that it can be used for one-time authenticated key establishment using the time-based one-time password (TOTP) approach. In this paper we apply the PT and TOTP approach to TLS to achieve stateless one-time authenticated session resumption. Server executes full handshake of TLS 1.3 and issues PT to authenticated client. Then client and server can execute one-time authenticated session resumption using PT in stateless way in server side. In every runs of session resumption distinct session keys are established that the same PT can be used safely for longer lifetime. If anonymous PT is used with renewal issuing, user privacy, untraceability and forward security can be achieved easily. It will provide a huge performance gain in large-scale distributed services.

In WPA3 secure connection is executed in two sequential stages. Firstly, in authentication and association stage a pairwise master key (PMK) is generated. Secondly, in post-association stage a pairwise transient key (PTK) is generated from PMK using the traditional 4-way handshake protocol. To reduce the heavy computation of the first stage PMK caching can be used. If client and AP are previously authenticated and has PMK cache, client can skip the first heavy stage and reuse the cached PMK to directly execute the 4-way handshake. But PMK caching is a very primitive technology to manage shared key between client and AP and there are many limitations; AP has to manage stateful cache for multiple clients, cache lifetime is limited, etc. Paired token (PT) \cite{LZ} is a new secondary credential scheme that provides stateless pre-shared key (PSK) in client-server environment. Server issues paired token (public token and secret token) to authenticated client where public token has the role of signed identity and secret token is a kind of shared secret. Once client is equipped with PT, it can be used for many symmetric key based cryptographic applications such as authentication, authorization, key establishment, etc. In this paper we apply the PT approach to WPA3 and try to replace the PMK caching with the one-time authenticated key establishment using PT. At the end of the authentication and association stage AP securely issues PT to client. Then in reassociation stage client and AP can compute the same one-time authenticated PMK from PT in stateless way and compute PTK using the traditional 4-way handshake protocol. Using this kind of stateless reassociation technology AP can provide high performance service to huge number of clients.

Background/Objectives: Multiple sclerosis (MS) is a chronic neurological disorder characterized by various clinical presentations and manifestations that include biopsychosocial impediments. This study has three interrelated goals relevant to biopsychosocial functioning. The first is to compare cognitive, neuropsychological, and affective functioning and quality of life between patients with MS (PwMS) and a control group. The second is to examine whether cognitive and neuropsychological performance is affected by gender, and the third is to examine whether variation in QoL hinges on cognitive neuropsychological performance. Methods: This multicenter study was carried out among clinically stable PwMS under follow-up in two tertiary care units in urban Oman. Healthy controls, matched for age and sex, were also recruited as a comparison group. Data were collected using cognitive batteries sensitive to current reasoning ability and conventional neuropsychological batteries designed to measure verbal learning, visual-spatial ability, and processing speed. The affective range (anxiety and depressive symptoms) and quality of life (QoL) were also assessed. Results: The PwMS group scored lower on current reasoning ability, verbal learning, visual-spatial ability, and processing speed compared with the control group. The incidence of anxiety was higher in the PwMS group but there was no statistically significant difference in depressive symptoms. No significant differences were found in cognitive variables between the two sexes, except in visual-spatial ability, where women outperformed men. PwMS with low QoL scored lower on the attention and concentration indices than those with adequate QoL. According to QoL, no significant differences were observed in reasoning, verbal learning, and visual-spatial ability. Conclusions: The present sentinel study suggests that the Omani cohort with MS tends to have lower indices of current reasoning ability, visual and spatial memory and cognitive speed compared to control subjects. Gender differences are minimal, except for visual-spatial abilities where women outperform men. Quality of life significantly affects cognitive functioning. In general, the biopsychosocial impediment appears to be significant, indicating the need for comprehensive evaluation and care in the management of MS.

Financial technologies (Fintech) have become an indispensable part of most of the business infrastructure around the world. The Fintech ecosystem provides this solution by providing a suitable environment for all financial techno services to synergize. The objective of this paper is two folds; first, it aims to investigate &amp; summarize Fintech programs products, and services in Saudi Arabia. Second, it maps the sustainable development goals (SDG) and indicators of the Fintech programs in Saudi Arabia. Secondary data was collected from published reports, institutional &amp; governmental websites, official portals, and research papers focusing on the companies operating in Saudi Arabia. In the second step, the content analysis method was employed to investigate the features and characteristics of each program to map it to the sustainable development goals (SDGs). It was found that Fintech in Saudi Arabia is addressing SDGs goals 1, 2, 5 8 &amp; 17. The paper also attempted to map further the SDG indicators with the products and services which Fintech companies are offering. This study will be beneficial for the institutions and policymakers of the Fintech industry to fill the gaps in addressing SDG goals which is a global agenda for eradicating poverty and offering sustainable development opportunities.

We developed a novel hybrid approach for solving global optimization, computer science, bio-medical and engineering real life applications that is based on the coupling of the Whale Optimizer and Sine Cosine Algorithms via a surrogate model. We relate the whale optimizer algorithm to balance between the exploitation and the exploration process in the proposed method. There exist confirmed techniques for searching approximate best optimal solutions, but our algorithm will further guarantee that such numerical and statistical solutions satisfy physical bounds of the standard and real life functions. Our experiments with the benchmark, bio-medical, computer science and engineering real life problems have illustrated the advantages of using a newly hybrid approach based on mixing Whale Optimizer and Sine Cosine algorithms. It holds considerable potential for reducing execution time for solving standard and real life problems and at the same time improving the quality of the solution.

In recent decades, attention has been directed at anemia classification for various medical purposes, such as thalassemia screening and predicting iron deficiency anemia (IDA). In this study, a new method has been successfully tested for discrimination between IDA and β-thalassemia trait (β-TT). The method is based on a Dynamic Harmony Search (DHS). Complete blood count (CBC), a fast and inexpensive laboratory test, is used as the input of the system. Other models, such as a genetic programming method called structured representation on genetic algorithm in non-linear function fitting (STROGANOFF), an artificial neural network (ANN), an adaptive neuro-fuzzy inference system (ANFIS), a support vector machine (SVM), k-nearest neighbor (KNN), and certain traditional methods, are compared with the proposed method.

Leaf crude extract (aqueous) of Oroxylum indicum (L.) Kurz induces genomic DNA fragmentation, comet formation, and inhibition of cell proliferation in prostate cancer cell line, PC3 as assessed by agarose gel electrophoresis, comet assay, and MTT assay respectively. The bioactive compound was purified through bioassay-guided fractionation using preparative HPLC and MTT as-say. The brown and water-soluble compound was characterized using 1H and 13C nuclear magnetic resonance (NMR), fourier transform infrared (FT-IR) and electrospray ionization (ESI) mass spectrometry, and the compound was iden-tified as a glycosylated hydroquinone derivative, 2-[p-(2-Carboxyhydrazino)phenoxy]-6-(hydroxymethyl) tetrahy-dro-2H-pyran-3,4,5-triol (molecular formula, C13H18N2O8; molecular mass = 330). The identified phytocompound has not been reported earlier elsewhere. Therefore, the common name of the novel anticancer phytocompound isolated from oroxylum indicum in this current study is named as oroxyquinone. The half-maximal inhibitory concentration (IC50) of oroxyquinone on PC3 cells was 19.44 µg/ml (95% CI = 17.97 to 21.04). Oroxyquinone induced cell cycle arrest at S phases and inhibition of cell migration on PC3 as assessed by flow cytome-try and wound healing assay respectively. On investigating the molecular mechanism of inducing apoptosis, the results indicated that the oroxyquinone induced apoptosis through the p38 pathway and cell cycle arrest, however, not through caspase-3 and PARP pathways. The present study identifies a novel an-ticancer molecule and provides scientific evidence supporting the therapeutic potency of OI for ethnomedicinal uses.

Uncertainties in initial water saturation and early water breakthroughs of un-known sources and paths, which occurred in the low resistivity Lower Haushi sand-stone (LHS) reservoir at the beginning of oil production, imply that the bypassed oil can yet remain in the reservoir. In addition, the upper part of LHS is a tight oil reser-voir, which can still contain a significant amount of unrecovered oil. This opens the opportunity to produce the remaining oil instead of abandoning this reservoir. Low resistivity can exaggerate water saturation, leading to misinterpretation and premature water flooding due to inadequate oil-water contrast. Our analysis revealed a correlation between low resistivity and robust porous network connectivity, along-side elevated formation water salinity in highly porous layers. In regions of high po-rosity, sufficient oil-water contrast facilitates precise water saturation determination, affirming oil presence in all wells. However, within tight oil zones, near-complete wa-ter saturation contradicts actual oil presence. Factors contributing to saturation un-certainty and water breakthroughs were reassessed. Utilizing a 1:1 verti-cal-to-horizontal permeability ratio derived from core data enhanced simulation alignment with water production rates. Investigation into the impact of relative per-meabilities on water production was conducted. Water saturation maps were gener-ated to pinpoint remaining oil reserves. Depletion around wells is evident in lower po-rous regions, while oil persists across the entire tight reservoir, notably in two unex-plored sections.

Balancing the levels of ammonia, in poultry facilities plays a role in enhancing the welfare and productivity of animals. Various environmental factors such as temperature, humidity, ammonia concentrations, carbon dioxide concentration and exposure to light have an impact on the wellbeing and efficiency of poultry. It is essential to monitor these elements to achieve outcomes necessitating practical, reliable and cost-effective solutions. Leveraging the Internet of Things (IoT) in conjunction with LoRa-WAN (Long Range Wide Area Network) technology presents an opportunity in the industry by enhancing connectivity among devices and facilitating real time data transmission. This research introduces a hardware and software setup for monitoring conditions at poultry farms through LoRa WAN and IoT technologies. More-over researchers employed Random Forest Machine Learning prediction models to tune the concentration of Ammonia (NH3) in poultry facilities across a wide area or multiple Poultry houses. Comparative assessments were conducted to evaluate the proposed system against devices revealing a correlation exceeding 0.9830 between the sensors and standard equipment while costing 28% less than traditional tools. The prototype displayed outcomes underscoring its potential, for managing poultry facilities across multiple farms with centralized oversight.

In recent years, the digital economy has played an increasingly important role in enhancing productivity, fostering growth, and facilitating the emergence of digital banking. With the widespread adoption of digital financial services for financial inclusion, the banking sector is experiencing a demand for digital transformation. It is important to note that despite the many advantages of this change, it also disrupts the familiar banking experience that customers have grown to expect, as well as introducing potential risks to maintaining customer protection at previous levels. Many critics have raised concerns regarding customer protection and potential exposure to various risks that may arise from digital financial services, which may result in both financial and non-financial losses. These risks can impact customer retention as dissatisfied customers may switch to alternative service providers. Additionally, reputation can be affected since merely offering digital financial services may not sufficiently safeguard customers. To remain competitive, financial institutions must deliver a secure experience that aligns with customer expectations while considering economic factors and societal needs. This is why it is essential to comprehend the severity of the risk factors that influence the protection of customers in the realm of digitalized banking services and products. In this study, five factors have been identified that influence customer protection when using digital financial services in Pakistan. Based on the analysis conducted using SmartPLS, it appears that all the factors proposed in this study have a significant and positive impact on the protection of customers. In particular, the information provided remains of paramount importance when it comes to determining the level of protection that a customer is entitled to within digital financial services, followed by responsiveness, privacy, authentication, and encryption mechanisms. Due to these findings, the implementation of enhanced information security management principles becomes imperative for the development and progress of the Pakistani digital banking industry.

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

Background –The brinjal is of much importance in the warm areas of Far East, being grown extensively in India, Bangladesh, Pakistan, China and the Philippines. It is also popular in Egypt, France, Italy and United States. Preserving soil fertility throughout time by preserving organic matter and soil biological diversity, mechanical intervention, as well as exercise is highly needed in upcoming future. Effect of six different fertilizer, five organic and one synthetic fertilizers listing vermicompost, poultry manure, mustard cake, neem cake, bonemeal and N:P:K study were main concern of this investigation to find out the most suitable fertilizer for the brinjal.Result - the final growth and development through N:P:K @ 1.5%(19:19:19) outperformed all the organic fertilizers but when considering only organic fertilizer performance vermicompost@5 ton/ha was outperforming all the other organic fertilizers. Coming close to it, mustard [email protected]/ha has shown its inheritance in providing nutrients. Use of other organic fertilizers are also effective use of poultry manure can provide nitrogen in higher amount in short time. Higher temperature above 25 degree Celsius cause slow growth, temperature range between 21 to 14 degrees Celsius was found better in terms of growth of flower and fruit formation.Conclusion – our experiment demonstrate specific organic fertilizer use over other fertilizers in terms of brinjal different developemental parameters and there is even comparision between synthetic fertilizer with organic fertilizer readily available in market. Vermicompost showed promising result followed by mustard cake for this specific brinjal genotype in northern plain of Indian subcontinent.

Efficient resource allocation is crucial in clusters with frugal Single-Board Computers (SBCs) possessing limited computational resources. These clusters are increasingly being deployed in edge computing environments in resource-constrained settings where energy efficiency and cost-effectiveness are paramount. A major challenge in Hadoop YARN scheduling is load-balancing, as frugal nodes within the cluster can become overwhelmed, resulting in degraded performance and frequent occurrences of out-of-memory errors, ultimately leading to job failures. In this study, we introduce an Adaptive Multi-criteria Selection for Efficient Resource Allocation (AMS-ERA) in Frugal Heterogeneous Hadoop Clusters. Our criterion considers CPU, memory and disk requirements for jobs and aligns the requirements with available resources in the cluster for optimal resource allocation. To validate our approach, we deploy a heterogeneous SBC-based cluster consisting of 11 SBC nodes and conduct several experiments to evaluate the performance using Hadoop wordcount and terasort benchmark for various workload settings. The results are compared to the Hadoop-Fair, FOG and IDaPS scheduling strategies. Our results demonstrate a significant improvement in performance with the proposed AMS-ERA, reducing execution time by 27.2%, 17.4% and 7.6% respectively using terasort and wordcount benchmarks.

Introduction: To indentify the most effective actors(authors, countries, and journals) about composite resin restorations in the period 2000-2020.Material and Methods: An electronis research was conducted in the Scopus database by selecting the words ‘composite resin’ and ‘restoration and English language, article and review types, dentistry field. Their bibliometric data including publication title, authorship, citation count, citation dentistry, year of publication, country and institution of origin, journal of publication, study design, and keywords were extracted and analyzed.Results and Discussion: To our knowledge, this is the first bibliometric article on composite resin restorations. This study provides information about authors, institutions and countries that contribute to significant improvements in composite resin restorations. From 2000 to 2020, there were 7118 articles published from 99 countries.Articles originate primarily from the USA and Brazil. Results indicate that the USA, Brazil, Germany, Turkey, the United Kingdom, Japan, Swtizerland, Italy, Netherlands and India are the leading countries in composite resin restoration research and account for 51.8% of the total number of publications. The total number of citations are 158.404, corresponding to 22 citations per paper publication. During the time period examined, 776 hot articles and 228 classic articles on composite resin restorations were found.The journal with the most publications is ‘Operative Dentistry’. The publishing houses of the top 10 journals are from 4 countries: USA(6),Netherlands(2),Germany(1),Japan(1). The most cited article within the boundaires of this study is Ferracane’s article titled ‘Resin composite-State of the art’, which was published in Dental Materials in 2011 and received 913 citations.

This study investigates the impact of Government Consumption (GC) on Saudi Arabia’s GDP during major economic crises from 1969 to 2022, with a focus on periods marked by fluctuations in oil and non-oil revenues. By integrating these revenue streams, the research provides a more comprehensive analysis of fiscal policy effectiveness during economic downturns. Using an Autoregressive Distributed Lag (ARDL) model, the study reveals the complex role of Government Consumption (GC) in stabilizing and stimulating the Saudi economy amidst revenue volatility.Key findings indicate that while GC does not significantly influence GDP in the short term, its long-term effectiveness varies across different crises. Specifically, GC has acted as a buffer against immediate economic shocks during certain crises while providing a stimulus for economic recovery in others. For instance, during the 2020 COVID-19 pandemic, timely fiscal measures significantly boosted GDP, underscoring the importance of adaptive and proactive fiscal policies. Conversely, the 2014-2016 oil price collapse demonstrated that GC alone was insufficient to counteract economic downturns, emphasizing the need for diversified revenue strategies.These findings underscore the dual role of GC in economic stabilization and recovery. During the COVID-19 pandemic, GC played a crucial role in both mitigating negative economic impacts and supporting recovery efforts, showcasing its effectiveness in times of global disruptions. This demonstrates GC's capability as an immediate buffer against economic shocks and a stimulus for economic recovery. In contrast, during the 2014-2016 oil price collapse, GC was less effective, indicating the limitations of relying solely on government spending without broader economic diversification. This highlights the necessity of diversified revenue strategies to complement fiscal measures for long-term economic resilience.The robustness of the findings was ensured through various diagnostic tests, including checks for autocorrelation, heteroskedasticity, and stationarity of residuals. The absence of significant autocorrelation and heteroskedasticity, along with the stationarity of differenced variables, confirms the validity of the econometric models used.The study contributes to the discourse on fiscal policy in oil-dependent economies by illustrating the critical role of diversified revenue strategies and adaptive fiscal measures in enhancing economic resilience. Recommendations are offered for policymakers to optimize fiscal strategies, ensuring robust economic recovery and long-term stability in volatile markets. This research highlights the necessity for Saudi Arabia to refine its fiscal policies towards greater economic diversification and stability.

The main goal of the study is to assess the Decision criteria, and the determining factor for the sustainability of entrepreneurial startups in order to contribute towards social inclusion and capacity building. Both concepts are in the development phase and are the outcome of entrepreneurial ecosystem and individual behavior and traits. The current study observed the research problem as entrepreneurship and the entrepreneurial startups are the continuous phenomena required for every economy. The lack of an efficient ecosystem and incompetent trait of an entrepreneur drags the entrepreneurial startup to a failure. Therefore, an assessment on decision criteria and determining factors categorizing them with their importance may provide requisites to lead a successful entrepreneurial startup contributing to the social inclusion and capacity building. The study solved the research problem by statistical assessment of decision criteria and determining factors and categorizing them with their importance may provide requisites to lead a successful entrepreneurial startup. The research is built on research questions, objectives, conceptual model, and hypothesis which are tested based on the data collected. The collection of data was done through a survey questionnaire on a sample of established entrepreneurs. The study concludes that five components of decision criteria are Region, Competition, Funding Opportunities, Tax System, and Country Economic Situation, whereas the eight components Consciousness and Reliable, Pursuit Results, Flexibility, Stress Resistance, Skills Identification Exploitation Potential Market Opportunities, Leadership, Creativity and Innovation, and Delegation Decision Making of determining factor are required for a successful entrepreneurial startup to be able to work towards social inclusion and capacity building.

Despite the demonstrated benefits of data monetization initiatives in achieving competitive advantages, many of these efforts struggle to realize their potential. Companies often find it challenging to sustain even initially successful data monetization initiatives due to significant data quality issues. This reflects a disconnect between advancements in data monetization research—spanning digitization, digitalization, and digital transformation—and practical implementation within companies. Consequently, misguided approaches to data monetization are relatively common. A critical prerequisite for successful data monetization is the establishment and maintenance of clean, high-quality data. This study underscores the importance of data quality by conducting an in-depth analysis of Medical Inc., a company engaged in preparing pristine customer master data for advanced customer analytics. The investigation aims to elucidate Medical Inc.’s approach to addressing data cleanliness challenges and to distill a general framework for the customer master data cleansing process. This framework illuminates a relatively unexplored aspect of data monetization supplementing existing literature on digitization, digitalization, and digital transformation.

Ceratonia siliqua L. is a medicinal plant that has long been used in traditional Moroccan medicine to treat many diseases. This study aimed to assess the impact of the stages of the immature phase of carob pulp (M1, M2, M3, M4, and M5) on phytochemical composition, antioxidant activity, and antidiabetic activity of Ceratonia siliqua L. The identification of the phenolic profile by HPLC-UV/MS-MS and the study of the antidiabetic effect by in silico, in vitro, and in vivo studies were carried out for extracts with a high content of phenolic compounds from immature wild carob pulp from the communes of Timoulit (TM), Bin Elouidane (AW), and Ouaouizerth (TG) in the province of Azilal in the Beni Mellal-Khenifra region. The results revealed a gradual increase in total sugar content over the pulp's ripening period, reaching a value of 2134 ±56.23 mg GE/100 g fresh matter (FM) for TG. The three locations showed peak values for total polyphenol content (TPC), total flavonoid content (TFC), and total condensed tannin (TCT) at the M2 stage. AW has the highest concentrations of TPC (3819 ± 226.4 mg GAE/100 g FM), TFC (1034 ± 57.08 mg QE/100 g FM), and TCT (1472 ± 28.46 mg CE/100 g FM). The DPPH assay (7892 ± 296.1 mg TE/100 g FM) and the FRAP assay (278.2 ± 7.85 mg TE/100 g FM) both demonstrate that the TG zone is a highly potent antioxidant zone. In contrast, the AW site exhibits a markedly elevated value of 725.4 ± 103.6 mg TE/100 g FM in the ABTS assay. HPLC-UV-MS/MS analysis showed that the methanolic extracts of immature carob pulp (MEICP) from the three areas contained several different chemical compounds. The most prevalent were 3-O-p-coumaroyl-5-O-caffeoylquinic acid, quercetin 3-methyl ether, gallic acid, and galloylquinic acid. Immature carob pulp extract. (ICPE) from AW showed the strongest in vitro inhibition of pancreatic α-amylase (IC50 = 0.405 µg/mL) and TG extracts were most potent against intestinal α-glucosidase (IC50 = 0.063 µg/mL). In vivo, AW, TG, and TM extracts significantly reduced postprandial glycemia in rats, with AW having the greatest effect. These results highlight the antidiabetic potential of ICPE. The 3-O-p-Coumaroyl-5-O-caffeoylquinic acid showed a better affinity for α-amylase compared to acarbose and interacted significantly with several amino acid residues of the enzyme. Similarly, this molecule and 3,4-Dicaffeoylquinic acid demonstrated a strong affinity for α-glucosidase, suggesting their potential as natural inhibitors of enzymes involved in carbohydrate metabolism. Most of the compounds are not substrates of P-glycoprotein and exhibit high intestinal absorption. Furthermore, the majority of these compounds do not act as inhibitors or substrates of CYP450 enzymes, reinforcing their suitability for development as oral medications. These results underscore the potential of immature carob pulp as a promising antidiabetic agent.

Breast cancer is the second cause of fatality among all cancers for women. Automatic classification of breast cancer lesions in mammograms is a challenging task due to the irregularity and complexity of the location, size, shape, and texture of these lesions. The intensity dissimilarity has been found between breast cancer tissues and normal tissues, when a multi-spectral anatomical mammographic screening scans have been done. In this work, two approaches have been evaluated to classify the breast tumor lesions. The first one is through Gabor wavelet features and the second one is Statistical features. Subsequently, support vector machine, Multilayer Perceptron and KNN classifiers have been used with computer based method for breast tumor classification.

We introduce an information theoretic framework for a quantitative measure of originality to model the impact of various classes of biases, errors and error corrections on scientific research. Some of the open problems are also outlined.

Oxidative stress and chronic inflammation, both at the systemic and central level, are critical early events in atherosclerosis and Alzheimer’s disease (AD). Purpose. To investigate the oxidative stress, inflammatory, and Tau-phosphorylation lowering effects of pomegranate polyphenols (PP) (punicalagin, ellagic acid, peels, and arils extracts). Methods. We used flow cytometry to quantify protein expression of proinflammatory cytokines (IL-1β) and anti-inflammatory mediators (IL-10) in THP-1 macrophages, as well as M1/M2 cell-specific markers (CD86 and CD163) expression in human microglia HMC3 cells. IL-10 protein expression was also quantified in U373-MG human astrocytes. The effect of PP on human amyloid beta 1-42 (Aβ1-42)-induced oxidative stress was assessed in microglia by measuring ROS generation and lipid peroxidation, using respectively two ′,7′-dichlorofluorescein diacetate (DCFH-DA) and thiobarbituric acid reactive substances (TBARS) tests. Neuronal viability and cell apoptotic response to Aβ1-42 toxicity were assayed using the MTT (3-(4, 5-dimethyl thiazolyl-2)-2, 5-diphenyltetrazolium bromide) assay and the annexinV-FITC apoptosis detection kit; respectively. Finally, flow cytometry analysis was also performed to evaluate the ability of PP to modulate Aβ1-42-induced Tau-181 phosphorylation (pTau-181). Results. Our data indicate that PP was significantly (p<0.05) effective in countering Aβ1-42-induced inflammation through increasing the anti-inflammatory cytokines (IL-10) (in U373-MG astrocytes and THP1 macrophages) and decreasing proinflammatory markers (IL-1β) expression in THP1 macrophages. PP was also significantly (p<0.05) effective in inducing the phenotypic transition of THP-1 macrophages and microglial cells from M1 to M2 by decreasing CD86 and increasing CD163 surface receptor expression. Moreover, our treatments have a significant (p<0.05) beneficial impact on oxidative stress, illustrated in the reduction of TBARS and ROS generation. Our treatments have significant (p<0.05) cell viability improvement capacities and anti-apoptotic effects on human H4 neurons. Furthermore, our results suggest that Aβ1-42 significantly (p<0.05) increases pTau-181. This effect was significantly (p<0.05) attenuated by arils, peels, and punicalagin and drastically reduced by ellagic acid treatments. Conclusion. Our results are attributed to PP's anti-inflammatory, antioxidant, anti-apoptotic, and anti-Tau pathology potential. Future studies should aim to extend our knowledge of the potential role of PP on A1-42-induced neurodegeneration, mainly its association with the tauopathy involved in AD.

The landscape of clinical management for metastatic melanoma (MM) and other solid tumors has been modernized by the advent of immune checkpoint inhibitors (ICI), including programmed cell death-1 (PD-1), programmed cell death-ligand 1 (PD-L1), and cytotoxic T lymphocyte antigen 4 (CTLA-4) inhibitors. While these agents demonstrate efficacy in suppressing tumor growth, they also lead to immune-related adverse events (irAEs), resulting in exacerbation of autoimmune diseases such as Rheumatoid arthritis (RA), Ulcerative colitis (UC), and Crohn’s disease (CD). The immune checkpoint inhibitors offer promising advancements in the treatment of melanoma and other cancers, but they also present significant challenges related to irAEs and autoimmune diseases. Ongoing research is crucial to better understand these challenges and develop strategies for mitigating adverse effects while maximizing therapeutic benefits. In this manuscript, we addressed this challenge using network-based approaches by constructing and analyzing molecular and signaling networks associated with tumor-immune cross-talk.. Our analysis revealed that IL6 is the key regulator responsible for irAEs during ICI therapies. Furthermore, we conducted an integrative network and molecular-level analysis, including virtual screening, of drug libraries, such as the Collection of Open Natural Products (COCONUT) and the Zinc15 FDA-approved library, to identify potential IL-6 inhibitors.. Subsequently, the compound amprenavir was identified as the best molecule that may disrupt essential interactions between IL6 and IL6R responsible for initiating signaling cascades underlying irAEs in ICI therapies.

Listwaenite rocks are widely spread in Fenja area of the Semail ophiolite of Oman and in Islam Abad area of the Neyriz ophiolite of Iran. There are three types of listwaenites found in these regions: silica-, carbonate-, and carbonate-silica (which includes dolomite, calcite, and magnesite. The alteration of host harzburgites started with hydrothermal alteration to serpentinite, followed by carbonation and silicification of serpentinite. Calcite- and magnesite-dolomite- listwaenites are more abundant in the Fenja area of Oman, while dolomite-listwaenites are more abundant in Islam Abad area in Iran. The mineralogy of listwaenites varies in both Iran and Oman; common minerals include quartz, calcite, goethite, magnesite, dolomite, serpentine, hematite, magnetite, Cr-mica, and Cr-spinel The major element chemistry of the different types of listwaenites in both Fenja and Islam Abad area generally comparable, and is largely similar to that of hydrothermally carbonated harzburgites, serpentinite, and listwaenites worldwide, despite spanning extraordinary and highly variable contents in major oxides, such as CaO, SiO2, MgO and LOI. Relict texture and common occurrence of Cr-spinel as well as the high concentrations of Cr, Ni and Co suggest that the protolith of the listwaenites in both regions was serpentinized harzburgites and serpentines. In comparison to the primary mantle and chondrite in spider diagrams, the Neyriz listwaenites have higher trace and REE element abundances than comparable listwaenites in the Fenja region. Harzburgite-normalized patterns of trace elements and REE in serpentinite and listwaenites overlap the average composition of harzburgite. PM-normalized trace element and REE patterns for serpentinized harzburgite and serpentinite show enrichment in Cs, U, Pb and Sr, with no Eu anomaly, comparable to mantle wedge serpentinites. The variable and high abundances of Ca, Mg, Ba, Zr, Sr, Pb, Zn, Mo and W in the carbonate- and silica-carbonate listwaenites, with unique Si enrichment and Mg, Na2O, Zr, Y, Ba, Sr, Rb, Cu, Pb, Sc, Cs, Nb, Mo and W. depletion in silica listwaenites are indicative of large fluctuations in major and trace element mobility. Cr, Ni and Co were immobile during alteration Enrichment in Ca and Si could occur by internal or late outside supply. Ca, Mg and Si are conceivably the foremost mobile major components amid harzburgite and serpentinite carbonation with mobilization confirmed by formation of quartz and Mg-carbonate in silica-carbonate listwaenites and quartz in silica listwaenites. The listwaenites in Islam Abad and Fenja area were formed due to hydrothermal alteration of serpentinite along thrust faults and shear zones which acted as pathway for Ca and/or Si rich fluids. The intensity of deformation in Islamabad listwaenites has been higher than Fenja listwaenites as indicated by higher abundance of trace elements.

Abstract composite silver nanoparticles were synthesised using melanin broth and Arabic gum as a reducing and binding agent. The reactions are carried out with water because it is a non-hazardous solvent. The produced composites either had specified diameters (average diameter of 50 nm) with high silver loading or lower loading composites with tuneable morphologies and electrical properties. UV-IR, gamma, and conventional light are used to characterise the synthesised composite silver nanoparticles. Furthermore, measurements are carried out of the dielectric constant, refractive index, energy gap, optical and electrical conductivities, and refractive index coefficients. The silver nanoparticle formation was validated by UV-Vis measurement of the sample, which demonstrated a distinct peak at a wavelength of 420 nm. The characteristics of the composite silver nanoparticles are also quantified using several methods, including XRD, SEM, and particle size analysis.

Aortic dissection is a clinicopathological entity caused by rupture of the intima leading to a high mortality if not treated. Over time, diagnostic and investigative methods, antihypertensive therapy, and early referrals have resulted in improving outcomes according to registry data. Some data has also emerged from recent studies suggesting a link between Human Cytomegalovirus (HCMV) infection and aortic dissection. Furthermore, the use of microRNAs have also become increasingly widespread in the literature. These have been noted to play a role in aortic dissections with elevated levels noted in studies as early as 2017. This review aims to provide a broad and holistic overview of the role of miRNAs, while studying the role of HCMV infection in the context of aortic dissections. The role of long non-coding RNAs, circular RNAs and microRNAs are explored to identify changes in expression during aortic dissections. The use of such biomarkers may one day be translated into clinical practice to allow early detection and prognostication of outcomes and drive preventative and therapeutic options in the future.

The Coronavirus 2 (SARS-CoV-2) infection is a global pandemic that has affected millions of people worldwide. The advent of vaccines, however, has permitted some restitution. Aside from the respiratory complications of the infection, there is also a thrombotic risk attributed to both the disease alongside the vaccine. There are no reliable data for the risk of thromboembolism in SARS-CoV-2 infection in patients managed out with the hospital setting. A literature review was performed to identify the pathophysiological mechanism of thrombosis from the SARS-CoV-2 infection including the role of Angiotensin-Converting Enzyme receptors. The impact of the vaccine and likely mechanisms from thrombosis following vaccination was also clarified. Finally, the utility of the vaccines available against the multiple variants is also highlighted. The systemic response to SARS-CoV-2 infection is still relatively poorly understood, but several risk factors have been identified. The roll-out of the vaccines worldwide has also allowed the lifting of lockdown measures and a reduction in the spread of the disease. The experience of the SARS-CoV-2 infection, however, has highlighted the crucial role of epidemiological research and the need for ongoing studies within this field.

Shale gas and coalbed methane are energy sources that partly or even mainly consist of methane stored in an adsorbed state in the pores of the organic-rich rock and coal seams. In this study, the graphene nanoslit model is employed to model the nanometer slit pores in shale and coal. The Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) modelling methods are used to investigate the mechanisms of adsorption and displacement of methane in the slit pore. It was found that the CVFF forcefield resulted in the largest adsorption amount, while the PCFF forcefield resulted in the least. The COMPASS and COMPASS II force fields led to similar results. As the width of the slit pore increases, the adsorption amount of gas molecules increases, and the number density profile of adsorbed methane molecules alters from a single adsorption layer to multi-adsorption layers. The minimum slit pore width at which methane molecules can penetrate the slit pore was found to be 0.7 nm. Moreover, it is demonstrated that by lowering the temperature, the adsorption rate of the methane increases since the adsorption is an exothermic process. Enhancing methane recovery was investigated by the injection of gases such as CO2 and N2 to displace the adsorbed methane. The comparison of adsorption isotherms of gas molecules provided the following order in terms of the amount of adsorption: CO2&gt;CH4&gt;N2.

Background: The practices of various health-care professionals have been improvised to accommodate the on-going covid-19 pandemic situation. Different guidelines have been set in place to ease the process of re-opening of non-elective healthcare services like out-patient physiotherapy clinics. Although the measures taken should be guided by evidence based information, major consensus amongst practicing therapists needs to guide the India physiotherapy clinics. Objective: To identify and present the opinions of different physiotherapists about the various strategies for re-opening the out-patient physiotherapy clinics. Methods: An online cross-sectional survey was conducted. Over 169 participants were selected to participate in the survey according to the pre-decided inclusion and exclusion criteria. The data was collected and saved via google forms. Result and conclusion: A majority of respondents had a consensus over different strategies for re-opening the physiotherapy OPDs. These were regarding different measures to be adapted including modifications in the clinic infrastructure and the practice pattern. This would help in smoothly re-instating the physiotherapy services post the covid-19 lockdown.

Genetic variability in rice breeding program plays the very crucial role. It provides outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For the understanding of population structure and genetic relationship among the different rice lines is indispensable prior to setting of correlation among dynamic alleles and traits. In the present investigation, genetic diversity and population structure of 116 rice accessions by using 64 polymorphic SSR markers was targeted for the evaluation of the genetic relatedness and diversity. Genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% of the variation was likely due to differences within groups. The study suggests that the population structure and genetic relatedness should be considered when working with the core collection of 116 rice germplasm lines for association mapping, aiming to establish marker-trait associations.

DevOps is an emerging practice to be followed in the Software Development life cycle. The name DevOps indicates that it’s an integration of the Development and Operation team. It is followed to integrate the various stages of the development cycle. DevOps is an extended version of the existing Agile method. DevOps aims at continuous integration, Continuous Delivery, Continuous Improvement, faster feedback and security. This paper reviews the building blocks of DevOps, challenges in adopting DevOps, Models to improve DevOps practices and Future works on DevOps

This article introduces ten similarity measures that utilize cosine and cotangent functions to compare (m,n)-rung orthopair fuzzy sets, this a super class of q-rung orthopair fuzzy sets. Further, we applied our established weighted similarity measures to medical diagnosis, pattern recognition,and building material problems and also presented the comparison between established measures with the existing cosine and cotangent measures of q-rung orthopair, pythagorean and intuitionistic fuzzy sets. Lastly, we considered a numerical example that demonstrates the effective and scientific application of these similarity measures in plant leaf disease classification. Furthermore, we present graphical interpretations to demonstrate the effectiveness of our established measures.

Global emerge of zoonotic novel corona virus (COVID-19) became a pandemic and its effect to mankind is talk of the town now a days. This tiny, invisible enemy has affected every country in the world and almost every living directly or indirectly and nationwide complete lockdown has triggered a short-term environmental impact. Since 2003, corona virus came into existence in the form of Severe Acute Respiratory Syndrome (SARS) and more evolved Middle East Respiratory Syndrome (MERS) in 2012. This time, at the end of December 2019, outbreak of novel corona virus COVID-19 (also known as SARS-CoV₂, nCoV-2019) draw attention as global health emergency. World Health Organization (WHO) report says that the outbreak of this virus is so immense, it has already affected 35,57,235 people and caused death to 2,45,150 people worldwide and 46,433 Indians got affected with 1568 death as on 5^th May 2020 (2:00 am) and these numbers are increasing exponentially day by day. Virologist, micro-biologist and science community are hammering their head very hard to find out cure and vaccine against this powerful virus and to prevent mass demise of mankind. In order to curb the spread of COVID-19, Janta curfew on 22.03.2020 and nationwide complete lockdown was implemented in India for 21 days (phase-I, from 25.03.2020 to 14.04.2020) to stop community transmission of third stage, for 19 days (phase-II, 15.04.2020 to 03.05.2020) and 14 days (phase-III, 04.05.2020 to 17.05.2020) complete lockdown to minimize the community transmission effect. During complete lockdown and quarantine period a drastic change in Earth’s atmosphere, including reduction in emission of greenhouse gases, air pollution (~50% fall in air quality index), noise pollution, water pollution and solid waste pollution, have been recorded by government agencies as well as private agencies. In this paper we considered data of Janta curfew, phase-I and phase-II lockdown to link between geological and environmental aspect related to environmental impact due to emerge of COVID-19 and massive reduction in pollution level during complete lockdown in India. We propose future lockdown strategies to minimize the emission of greenhouse gas by ~100 Mt to ~200Mt (3.33% to 6.66%) of GHG_total per year by 2-4 days per month nationwide lockdown or ~70 Mt to ~140 Mt (2.33% to 4.66%) of GHG_total per year by 2-4 days per month complete lockdown of energy sectors only.

The exceptional Jordan algebra is the algebra of $3 \times 3$ Hermitian matrices with octonionic entries. It is the only one from Jordan’s algebraic formulation of quantum mechanics which is not equivalent to the conventional formulation of quantum theory. It has often been suggested that this exceptional algebra could explain physical phenomena not currently explained by the conventional approach, such as values of the fundamental constants of the standard model of particle physics, and their relation to gravitation. We show that this is indeed the case; and this also unravels the connection between general relativity and the weak force. The exceptional Jordan algebra also predicts a new U(1) gravitational interaction which modifies general relativity, and which provides a theoretical basis for understanding the Modified Newtonian Dynamics (MOND).

Over the past two decades, persistent occurrences of harmful algal blooms (HAB; Karenia brevis) have been reported in Charlotte County, southwestern Florida. We developed data-driven models that rely on spatiotemporal remote sensing and field data to identify factors controlling HAB propagation, provide a same-day distribution (nowcasting), and forecast their occurrences up to three days in advance. We constructed multivariate regression models using historical HAB occurrences (213 events reported from January 2010 to October 2017) compiled by the Florida Fish and Wildlife Conservation Commission and validated the models against a subset (20%) of the reported historical events. The models were designed to specifically capture the onset of the HABs instead of those that developed days earlier and continued thereafter. A prototype of an early warning system was developed through a threefold exercise. The first step involved the automatic downloading and processing of daily Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua products using SeaDAS ocean color processing software to extract temporal and spatial variations of remote sensing-based variables over the study area. The second step involved the development of a multivariate regression model for same-day mapping of HABs and similar subsequent models for forecasting HAB occurrences one, two, and three days in advance. Eleven remote sensing variables and two non-remote sensing variables were used as inputs for the generated models. In the third and final step, model outputs (same-day and forecasted distribution of HABs) were posted automatically on a web-based GIS (http://www.esrs.wmich.edu/webmap/bloom/). Our findings include the following: (1) the variables most indicative of the timing of bloom propagation are bathymetry, euphotic depth, wind direction, SST, chlorophyll-a [OC3M] and distance from the river mouth, and (2) the model predictions were 90% successful for same-day mapping and 65%, 72% and 71% for the one-, two- and three-day advance predictions, respectively. The adopted methodologies are reliable, dependent on readily available remote sensing data sets, and cost-effective and thus could potentially be used to map and forecast algal bloom occurrences in data-scarce regions.

Since the onset of coronavirus disease 2019 (COVID-19) pandemic, the virus kept developing and mutating into different variants over time that also gained increased transmissibility and spread in populations at a higher pace, culminating in successive waves of COVID-19 cases. The scientific community has developed vaccines and antiviral agents against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease. Realizing that growing SARS-CoV-2 variations significantly impact the efficacy of antiviral therapies and vaccines, we have summarized the appearance and attributes of SARS-CoV-2 variants for future perspectives in drug design, bringing up-to-date hints for developing therapeutic agents targeting the variants. The Omicron variant is among the most mutated form; its strong transmissibility and immune resistance capacity have prompted international worry. Most mutation sites currently being studied are located in the BCOV_S1_CTD of the S protein. Despite this, several hurdles remain, such as developing vaccination and pharmacological treatment efficacies for emerging mutants of SARS-CoV-2 strains. In this review, we present an updated viewpoint on the current issues faced by the emergence of various SARS-CoV-2 variants. Furthermore, we discuss the clinical studies conducted to assist the development and dissemination of vaccines, small molecule therapeutics, and therapeutic antibodies having broad-spectrum action against SARS-CoV-2 strains.

The paper presents attribute based characterization of nanomaterials method for computer storage and retrieval as knowledgebase. The knowledgebase permits indepth understanding and comparison between nanomaterials available with the scientists and product developers to satisfy their research and development (R & D) needs. Techniques for order preference by similarity to ideal solution (TOPSIS) is proposed to evaluate nanomaterials in the presence of multiple attributes. The method normalizes attributes to nullify the effect of different units and their values in the range of 0 to 1. The relative importance of different attributes for different applications is considered. The weight vector is derived using Eigen value formulation. The positive and negative benchmark solutions are derived. Euclidean distance of alternatives from these best and worst solution leads to the development of proximity /goodness/suitability index for ranking. Final decision is taken by decision makers by SWOT analysis and short and long term strategies of the organisation. The methodology is illustrated with the help of an example and step-by-step procedure. Results, discussion and conclusion highlights the importance and practical application.

There must exist a reformulation of quantum field theory, even at low energies, which does not depend on classical time. The octonionic theory proposes such a reformulation, leading to a pre-quantum pre-spacetime theory. The ingredients for constructing such a theory, which is also a unification of the standard model with gravitation, are : (i) the pre-quantum theory of trace dynamics – a matrix-valued Lagrangian dynamics, (ii) the spectral action principle of non-commutative geometry, (iii) the number system known as the octonions, for constructing a non-commutative manifold and for defining elementary particles via Clifford algebras, (iv) a Lagrangian with $E_8 \times E_8$ symmetry. The split bioctonions define a sixteen dimensional space (with left-right symmetry) whose geometry (evolving in Connes time) relates to the four known fundamental forces, while predicting two new forces, $SU(3)_{grav}$ and $U(1)_{grav}$. This latter interaction is possibly the theoretical origin of MOND. Coupling constants of the standard model result from left-right symmetry breaking, and their values are theoretically determined by the characteristic equation of the exceptional Jordan algebra of the octonions. The quantum-to-classical transition, precipitated by the entanglement of a critical number of fermions, is responsible for the emergence of classical spacetime, and also for the familiar formulation of quantum theory on a spacetime background.

The antibiotic or antimicrobial resistance is rapidly spreading in microbes relevant to human health. Two visible major contributory factors have been the indiscriminate overuse of antimicrobials for preventing diseases in human and to enhance the productivity in agriculture sector. To mitigate the potential threat posed by post-antibiotic era, the global health stakeholders have been making extra efforts at a war footing to formulate and implement global and national plans of action. In the current article, an endeavour is made to provide a perspective to look beyond the current focus on just use of the antimicrobials. Attention has been drawn towards various obvious and not-so-obvious self-preservation infection-prevention practices in vogue from the pre-antibiotic era whose usage has been on decline in the antibiotic era for various reasons. Particularly, the practices with a clear potential to effectively decrease the spread of pathogens through contact, curtail the evolution and dissemination of the antimicrobial resistance in local environment and its introduction into the global community, should be Identified and strengthened to make them part of comprehensive hygiene and quarantine practices. Broadly, the suggestions pertaining to the personal and community hygiene including bereavement practices, isolation and quarantine of suspected pathogen carriers, and water and environment security have been made to invoke a constructive debate and discussion among various stakeholders for their evaluation and implementation to effectively delay the development of antimicrobial resistance wherever possible and disrupt its spread to pathogens.

Despite the recent advances in melanoma therapy, the need for new targets and novel approaches to therapy is urgent. We previously reported melanoma actives that work via binding and downregulating spliceosomal proteins hnRNPH1 and H2. In a separate study, we reported that these compounds were non-toxic to Balb/C mice at 50 mg/kg suggesting their utility in in vivo studies. In the present study, we aimed to determine the therapeutic potential of these compounds by testing them in A375 cell-line derived xenograft in nu/nu mice. Animals were randomized into four groups (n=12/group) to receive subcutaneous administration of vehicle, 10 mg/kg vemurafenib, and 25 mg/kg 2155-14 and 2155-18 three times per week for 15 days along with a control group. The results revealed that both 2155-14 and 2155-18 significantly decreased the growth of A375 tumors, which was comparable to vemurafenib. These results were confirmed by tumor volume, weight, and histopathological examination. In conclusion, these results suggest a therapeutic potential of targeting spliceosomal proteins hnRNPH1 and H2.

Fruit production is an important part of the gross domestic product for many countries around the world especially to those who have a strong focus on agriculture. However, long-term maintenance and yield stability of fruit production may be threatened by the ongoing climate change and its consequences like extended drought periods, heavy rain events, and floodings. Genome editing, with its progressive technological developments, offers opportunities to adapt relevant fruit plant species to new climatic conditions. Among modern genome editing techniques, CRISPR/Cas, in particular, has the potential to support breeding for those fruit plant species with extended breeding cycles, e.g., perennial fruits. In this review, we discuss CRISPR/Cas and other genome editing techniques in detail and how these techniques can be applied to support the breeding of fruit plant species for adaptation to changing climates. The chronological history of CRISPR/Cas9 systems, their associated computational tools, genomic data sources, transformation methods along with their delivery vehicles, quality improvement, environmental-stress resiliency, limitations, and future perspectives will also be discussed with respect to securing future global fruit production.

In the past few decades, the use of agricultural waste has been increasing due to the increasing demand for sustainable materials. This paper aims to review the significance of agricultural waste as a type of wealth and its potential as an alternative material in the composite field. It was found that many agricultural wastes had been utilized in various production of ecological products. The review discusses the physical, mechanical, and chemical properties of the natural fibers made from agricultural waste and the use of Pineapple Leaf Fiber Reinforced Composite to manufacture UAVs (Unmanned Aerial Vehicles). The extracted waste fibers’ physical, mechanical, and chemical properties show that these agricultural wastes can produce better advanced composite materials suitable for structural applications. The use of pineapple leaf fiber in Unmanned Aerial Vehicles manufacturing has the potential to revolutionize this industry and contribute to a more sustainable future.

miRNAs have recently attracted investigators' interest as regulators of valvular diseases pathogenesis, diagnostic biomarkers, and therapeutical targets. Evidence from in-vivo and in-vitro studies demonstrated stimulatory or inhibitory roles in mitral valve prolapse development, aortic leaflet fusion, and calcification pathways, specifically osteoblastic differentiation and transcription factors modulation. Tissue expression assessment and comparison between physiological and pathological phenotypes of different disease entities, including mitral valve prolapse and mitral chordae tendineae rupture, emerged as the best strategies to address miRNAs over or under-representation and thus, their impact on pathogeneses. In this review, we discuss the fundamental intra- and intercellular signals regulated by miRNAs leading to defects in mitral and aortic valves, congenital heart diseases, and the possible therapeutic strategies targeting them. These miRNAs inhibitors comprise of antisense oligonucleotides and sponge vectors. The miRNA mimics, miRNA expression vectors, and small molecules are instead possible practical strategies to increase specific miRNA activity. Advantages and technical limitations of these new drugs, including instability and complex pharmacokinetics, are also presented. Novel delivery strategies, such as nanoparticles and liposomes, are described to improve knowledge on future personalized treatment directions.

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

In this paper the dynamics of spatially extended infected phytoplankton with the Holling type II functional response and logistically growing susceptible phytoplankton system is studied. The proposed model is an extension of temporal model available [6], in spatiotemporal domain. The reaction diffusion system exhibits spatiotemporal chaos in phytoplankton dynamics. This is particularly important for the spatially extended systems that are studied in this paper as they display a wide spectrum of ecologically relevant behavior, including chaos. In this system stability of the system is studied with respect to disease contact rate and the growth fraction of infected phytoplankton indirectly rejoin the susceptible phytoplankton population. The results of numerical experiments in one dimension and two dimensions in space as well as time series in temporal models are presented using MATLAB simulation. Moreover, the stability of the corresponding temporal model is studied analytically. Finally, the comparison of the three types of numerical experimentations are discussed in conclusion.

We have recently proposed a pre-quantum, pre-space-time theory as a matrix-valued Lagrangian dynamics on an octonionic space-time. This pre-theory offers the prospect of unifying the internal symmetries of the standard model with gravity. It can also predict the values of free parameters of the standard model, because these parameters arising in the Lagrangian are related to the algebra of the octonions which define the underlying non-commutative space-time on which the dynamical degrees of freedom evolve. These free parameters are related to the algebra $J_3(\mathbb O)$ [exceptional Jordan algebra] which in turn is related to the three fermion generations. The exceptional Jordan algebra [also known as the Albert algebra] is the finite dimensional algebra of 3x3 Hermitean matrices with octonionic entries. Its automorphism group is the exceptional Lie group $F_4$. These matrices admit a cubic characteristic equation whose eigenvalues are real and depend on the invariant trace, determinant, and an inner product made from the Jordan matrix. Also, there is some evidence in the literature that the groups $F_4$ and $E_6$ could play a role in the unification of the standard model symmetries, including the Lorentz symmetry. The octonion algebra is known to correctly yield the electric charge values (0, 1/3, 2/3, 1) for standard model fermions, via the eigenvalues of a $U(1)$ number operator, identified with $U(1)_{em}$. In the present article, we use the same octonionic representation of the fermions to compute the eigenvalues of the characteristic equation of the Albert algebra, and compare the resulting eigenvalues with the known mass ratios for quarks and leptons. We find that the ratios of the eigenvalues correctly reproduce the [square root of the] known mass ratios for quarks and charged leptons. We also propose a diagrammatic representation of the standard model bosons, Higgs and three fermion generations, in terms of the octonions, exhibiting an $F_4$ and $E_6$ symmetry. In conjunction with the trace dynamics Lagrangian, the Jordan eigenvalues also provide a first principles theoretical derivation of the low energy value of the fine structure constant, yielding the value $1/137.04006$. The Karolyhazy correction to this value gives an exact match with the measured value of the constant, after assuming a specific value for the electro-weak symmetry breaking energy scale.

Enteroccoccus faecalis is a commensal that is responsible for numerous infections in surgical sites, urinary tract and bloodstream. It is of growing concern given its propensity to affect the elderly population where there is a high prevalence of undiagnosed degenerative valvular disease and the with more invasive procedures and implanted medical devices. Its actions are mediated by specific characteristics of the bacterium such as pili activity and biofilm formation. This confers significant resistance toward a multitude of antibiotic therapy, especially in endocarditis. The current guidelines advocate antimicrobial therapy but the emergence of resistant strains has added a degree of complexity to the management of these patients, especially with the advent of transcatheter therapies which are often used in patients who are poor surgical candidates. Their presentations are often variable with generalized symptoms and can be diagnostically challenging. We present our experience of a case study involving an octogenarian with a TAVI valve who developed endocarditis and performed a literature review to highlight treatment algorithms for these cases.

Endothelial integrity plays a major role in homeostasis and is responsive to the numerous endogenous factors released. While its functional role in vascular tone is well described, its role in the pathophysiology of cardiovascular disease is of interest as a potential therapeutic target. We performed a systematic review to provide an overview of new therapeutic and diagnostic targets for the treatment of coronary artery disease related to endothelial dysfunction. Databases of PubMed, Ovid’s version of MEDLINE, and EMBASE were interrogated with appropriate search terms. 28 studies met inclusion criteria and were included in the final systematic review. We identified inflammation, pulmonary hypertension, diabetes mellitus and Fabry disease as pathophysiological mechanisms and explored the therapeutic options related to these conditions including medications such as Canakinumab. Endothelial dysfunction has a key role in several different pathophysiological processes which can be targeted for therapeutic options. Ongoing research should be targeted at making the transition to clinical practice. Further research is also needed on understanding the amelioration of endothelial dysfunction with the use of cardiovascular medications.

Staphylococci sp. have become the primary pathogens implicated in infective endocarditis, especially within high-income nations. Coupled with the increasing burden of healthcare with aging populations and the protracted course the infections may take, these infections contribute to a significant challenge for healthcare. A systematic review was conducted using relevant search criteria from PubMed, Ovid’s version of MEDLINE, and EMBASE, and data were tabulated from randomized controlled trials (RCT), observational cohort studies, meta-analysis, and basic research articles. The review was registered with the OSF register of systematic reviews and followed the PRISMA reporting guidelines. 35 studies met the inclusion criteria and were included in the final systematic review. The role of Staphylococcus aureus and its interaction with the protective shield and host protection functions is identified and highlighted in several studies. The interaction between infective endocarditis pathogens, vascular endothelium, and blood constituents is also explored giving rise to the potential use of antiplatelets as preventative and/or curative agents. Several factors allow Staphylococcus aureus infections to proliferate within the host with numerous promoting and perpetuating agents. The complex interaction with the hosts' innate immunity also potentiates its virulence. Ameliorating these molecular pathways may serve as a therapeutic avenue for the prevention and treatment of these infections in the near future.

One of the hallmarks of the SARS-CoV-2 infection has been the inflammatory process that played a role in its pathogenesis, resulting in mortality within susceptible individuals. This uncontrolled inflammatory process leads to severe systemic symptoms via multiple pathways, however, the role of endothelial dysfunction and thrombosis have not been truly explored. This review aims to highlight the pathogenic mechanisms of these inflammatory triggers leading to thrombogenic complications. There are direct and indirect pathogenic pathways of the infection that are examined in detail. We also describe the case of carotid artery thrombosis in a patient following the SARS-CoV-2 infection, while reviewing the literature on the role of ACE2, the endothelium, and the different mechanisms by which SARS-CoV-2 may manifest both acutely and chronically. We also highlight differences from the other coronaviruses that have made this infection pandemic with similarities to the influenza virus.

Landslides are a frequent and recurrent problem in hilly regions of India and predicting them is always a challenging task. In this paper, an attempt was made to deal with this problem using advanced physical and numerical modeling methods. Detailed understanding of the initial slope failures is very interesting, and challenging at the same time, in the design and development of wireless sensor network based on early warning of landslide monitoring. A small scale physical model was developed to assess the instability through a sensor network with variable rain fall intensity. This was achieved by increasing the simulated rain water flow intensity in different time spans (dry condition, at t=0 to t= 30 min, 0.5 mm/min at t=30 to t= 60 min, 0.75 mm/min at t=60 to t=91 min and 1 mm/min at t=91 to t= 120 min). The water level and movement in the slope was recorded by rainfall sensor, vibration sensor, soil moisture sensor and a digital camera. The following changes were observed during the slope failure: a) movement of small particles at top of the slope; b) initial failure of medium size soil particle; c) scouring of soil mass; d) whole slope collapse. The obtained results clearly indicated the superiority and effectiveness of the proposed system in providing a factor of safety for the progressive slope.

Salmonella typhimurium is the predominant serovar identified in cases of salmonellosis. It is recognised for adhering to various surfaces and creating biofilm, leading to several foodborne outbreaks and antibiotic resistance. Actinomycetes are thought to possess a wide array of antibacterial characteristics that can combat different diseases. Currently, it is unclear whether it has antibiofilm properties against S. typhimurium. This study aimed to assess the antibiofilm efficacy of actinomycetes extracts against S. typhimurium ATCC 14028 by the Crystal Violet assay. Four actinomycetes isolates, EAS5, EAS7, EAA141, and EAA11, were obtained from BRIS soil in Terengganu. The actinomycetes isolates were extracted using ethyl acetate (EA). S. typhimurium was exposed to extracts for 6, 12, and 18 hours. The results showed that all EA extracts effectively prevented the S. typhimurium biofilm at 12 and 18 hours. EAAA11 was the most effective against the 12-hour biofilm, whereas EAS5 was the most effective against the 18-hour biofilm among these extracts. In conclusion, actinomycetes isolated from the BRIS soil in Terengganu show potential for controlling Salmonella infection.

Cancer is fundamentally a disease of perturbed genes. Although many mutations can be marked in the genome of a cancer or transformed cell, the initiation and progression were shown to be driven by only a few mutational events viz. driver mutations that progressively govern and execute the functional impacts. The driver mutations are thus believed to dictate and dysregulate the subsequent cellular proliferative function/decisions thereby producing a cancerous state. Therefore, identifying the driver events from the genomic alterations in a patient’s cancer cell gained large attention recently for designing better targeting therapies towards paving way for the precision cancer medicine. With rolling advancements in high-throughput omics technologies, analysis of genetic variations and gene expression profiles for cancer patients has become a routine clinical practice. However, it is anticipated that protein structural alterations resulting from such driver mutations can provide more direct and clinically relevant evidence of disease states than genetic signatures alone. This review comprehensively discusses various aspects and approaches that have been developed for the prediction of cancer drivers using genetic signatures and protein structures, and their potential application in developing precision cancer therapies.Keywords:

Low carbon supply chain management (LCSCM) strategies are required in the Indian manufacturing industries due to rapidly growing energy usage for financial and environmental concerns. LCSCM technologies face a number of challenges that limit their adoption. Eleven hurdles were selected from the literature as well as the recommendations of business and academic experts. These barriers are defined by a number of factors, including a lack of information, financial worries, environmental concerns, and governmental limits, among others. In addition, efforts are being made to quantify the most optimal relevant barriers using Multi criteria decision making (MCDM) techniques such as interpretive structural modeling (ISM) and decision-making trail and evaluation laboratory (DEMATEL). MICMAC analysis is used to estimate the sensitivity and priority of barriers based on dependency power and driving power. One of these barriers is a needed factor; three are driving elements; four barriers are linked factors; and three are self-sufficient factors. The findings of this study can help academic specialists, industry representatives, and practitioners in their ongoing attempts to adopt 'LCSCM techniques' in Indian manufacturing industries. The model is appropriately explained and applies the link between the barriers.The objective of this paper is the Evaluation and selection of most influential of Barriers to Adopt Low Carbon Supply Chain Management (LCSCM) in the Indian Manufacturing Sector is interrelated.

The ever-growing concerns about global warming and the rapid depletion of fossil fuels have triggered a rising interest in research for cleaner, more efficient and cost-effective energy generation. Organic Rankine cycle systems have immense potential to become a strong alternative to conventional methods of energy generation. However, such systems’ efficiency is limited by the performance of the incorporated gas expanders or prime movers. Conventional gas expanders often utilize ports or cam-operated valves. Ported expanders offer limited efficiency and controllability, and produce high emissions causing a large amount of heated and compressed gas to be wasted. Cam-operated valves, in contrast, increase expansion performance compared to ported expanders, however, they have no variability and adaptability to changes in system parameters such as gas pressure, temperature, dryness fraction, and load variation to name a few. On a positive note, this issue can be addressed by adopting a variable timing and fast-operating, control valve with an accurate and adaptive control mechanism at the expander inlet. A properly designed and controlled valve can greatly improve the system performance of gas expanders and pave the way for an efficient low-cost alternative energy generation. This manuscript provides a comparative review of recent progress on the design, modeling, optimization, and control aspects of valves for gas expanders. A clear pathway on the scope of further development is also drawn based on the present state of the art.

RNA interference is a highly conserved process in which non-coding small RNAs (sRNA) modulate gene expression at the post-transcriptional level influencing plant growth and development. Dicer-like (DCL), Argonaute (AGO) and RNA-dependent RNA polymerase (RDR) are the core elements involved in gene silencing and their gene families have been explored in many plants. However, these genes and their response to abiotic stresses have not yet been well in wheat. In this study, 82 AGO, 31 DCL, and 31 RDR genes were identified and phylogenetic analysis of these proteins showed that clustered into ten, four and four clades respectively. RNA-seq analysis revealed constitutive expression of AGO1, AGO9, and DCL2 family expression analysis in tissues under normal and stress conditions, whereas RDR1 which is known to engage in siRNA biogenesis showed higher expression levels in wheat leaf tissues. Our findings build the foundation for comparative genomics analyses of RNA silencing elements in cereal crops, as well as new insights into the functional complexity of RNA silencing in wheat stress responses, which is critical for understanding the processes underlying wheat stress responses.

The signaling complex around voltage-gated sodium (Nav) channels includes accessory proteins and kinases crucial for regulating neuronal firing. Previous studies showed that one such kinase, WEE1—critical to the cell cycle—selectively modulates Nav1.2 channel activity through the accessory protein fibroblast growth factor 14 (FGF14). Here, we tested whether WEE1 exhibits crosstalk with the AKT/GSK3 pathway for coordinated regulation of FGF14/Nav1.2 channel complex assembly and function. Using the in-cell split luciferase complementation assay (LCA), we found that the WEE1 inhibitor II and GSK3 inhibitor XIII reduce FGF14/Nav1.2 complex formation, while the AKT inhibitor triciribine increases it. However, combining WEE1 inhibitor II with either one of the other two inhibitors abolished its effect on FGF14/Nav1.2 complex formation. Whole-cell voltage-clamp recordings of sodium currents (INa) in HEK293 cells co-expressing Nav1.2 channels and FGF14-GFP showed that WEE1 inhibitor II significantly suppresses peak INa density, both alone and in the presence of triciribine or GSK3 inhibitor XIII, despite the latter inhibitors’ opposite effects on INa. Additionally, WEE1 inhibitor II slowed the tau of fast inactivation, and caused depolarizing shifts in the voltage dependence of activation and inactivation. These phenotypes either prevailed or were additive when combined with triciribine but were outcompeted when both WEE1 inhibitor II and GSK3 inhibitor XIII were present. Concerted regulation by WEE1 inhibitor II, triciribine and GSK3 inhibitor XIII were also observed on long-term inactivation and use-dependence of Nav1.2 currents. Overall, these findings suggest a complex role for WEE1 kinase—in concert with the AKT/GSK3 pathway—in regulating the Nav1.2 channelosome.

Tourette syndrome is a complex neuropsychiatric condition that manifests in childhood and is often associated with other psychiatric comorbidities. This case describes a young male with Tourette syndrome with major depressive disorder and attention deficit hyperactivity disorder (ADHD), who experienced troublesome side-effects due to his existing medications (escitalopram, risperidone and methylphenidate). In order to control his tics, ameliorate depressive symptoms, and eliminate side-effects of stiffness and sedation, risperidone was switched to cariprazine, a third-generation antipsychotic medication with D3-D2 partial agonism. In addition, the antidepressant dose was also increased. With the new combination, the patient reported good control of his tics, together with significant improvement in depressive symptoms and no side-effects. Based on this case and the reviewed literature, cariprazine might be a viable option for patients with Tourette syndrome with other comorbid illnesses, whom are prone to side effects of medication.

Background: The Covid-19 pandemic abruptly disrupted global healthcare systems, necessitating rapid adaptations. This study evaluates the impact on health systems and services in the aftermath of the first wave in the Indian context. It analyses the disruptions, adaptive measures, and changes made, as well as the challenges faced by healthcare providers and seekers. Valuable insights from this study will enhance the resilience and preparedness of healthcare systems for future challenges. Methods: The eligible studies included primary studies conducted in the Indian context that explore the impact of COVID-19 on health services provision, utilisation, and the well-being of healthcare providers and seekers. Electronic searches were conducted in six databases: PubMed, MEDLINE, Embase, Global Health, CINAHL, and the WHO database on COVID-19. The results were analysed using detailed narrative synthesis. Results: The review includes 38 articles, incorporating a total of 22,502 subjects. There has been a substantial impact on health service provision, particularly in outpatient departments (OPD) (n=19) and elective services (n=16), while emergency services continued at sub-optimal levels (n=20). Various adaptations and changes were implemented in precautionary measures, protocols, staff allocation and training, usage of personal protective equipment (PPE), preoperative, operative, and postoperative measures, as well as physical infrastructure and resources. Depression and stress (n=14), fear of contracting the infection (n=6), stigmatisation (n=5), and financial repercussions (n=5) significantly affected the mental health of healthcare providers, and healthcare seekers also faced significant challenges (n=11). Conclusion: The study reveals COVID-19's substantial impact on health services. The healthcare system responded by quickly adjusting staff management, resource allocation, and infection prevention measures. The study also highlights the mental health challenges faced by healthcare providers and the concerns of healthcare seekers regarding delays and suboptimal care. Looking ahead, the findings underscore the importance of preparedness for future pandemics, including improved healthcare infrastructure, resource optimisation, and comprehensive protocols. Lessons learned from COVID-19 should inform strategies to mitigate disruptions and ensure the well-being of healthcare providers and seekers in future outbreaks.

Agriculture sector is the backbone of developing countries for their economy. Growing world’s population is putting more pressure on agriculture sector and there is a need to develop new technology to address the crises of food safety and food shortage. Today’s agriculture has been entered in a new era where nanotechnology works as a technological advancement regarding entire agriculture crops, and food sector revolution, even though, it has prodigious applications in food production, food processing, food packaging, food storage and economic growth of industries. Moreover, nanotechnology is the best solution to solve problems related to better food and agriculture. Likewise, biotechnology, nanotechnology also raised high concerns upon safety on biodiversity, health and environment. Nanotechnology is providing efficient alternatives to increase the crop production by managing the insect/pests in agriculture in an eco-friendly manner. It also promotes plant efficiency to absorb nutrients. However, the concerns are very high regarding regulation, safety and approval of nanotechnology products by risk assessment authorities. The suggested review includes stupendous applications of nanotechnology in food and agriculture sector along with its prospective merits and associated risks.

There must exist a reformulation of quantum field theory which does not refer to classical time. We propose a pre-quantum, pre-spacetime theory, which is a matrix-valued Lagrangian dynamics for gravity, Yang-Mills fields, and fermions. The definition of spin in this theory leads us to an eight dimensional octonionic space-time. The algebra of the octonions reveals the standard model; model parameters are determined by roots of the cubic characteristic equation of the exceptional Jordan algebra. We derive the asymptotic low energy value 1/137 of the fine structure constant, and predict the existence of universally interacting spin one Lorentz bosons, which replace the hypothesised graviton. Gravity is not to be quantized, but is an emergent four-dimensional classical phenomenon, precipitated by the spontaneous localisation of highly entangled fermions.

Persistent post market quality evaluation helps produce clear information on the current quality status of the different brands of a given drug and hence introduces biopharmaceutically and therapeutically equivalent list of the products to the prescribers and users of it. This in turn facilitates access to essential medicines by breaking the high cost barrier imposed by few expensive brands of the product. This study was aimed at determining the quality and evaluating equivalence of doxycycline hyclate capsules and tablets in Jimma, Ethiopia. Ten brands of doxycycline hyclate capsules and tablets were tested for physic-chemical parameters. All investigated brands of doxycycline complied with the USP for dosage unifor¬mity, assay of active ingredient and single-point dissolution tests. One brand, D09 failed both hardness and friabilty tests. Comparisons of dissolution profiles applying fit factors confirmed that only brands D04, D06 and D07 had similarity with innovator. Ratio test approaches also showed significant variability existence between test products and comparators. This may question the product’s being categorized as a <biowaiver> to mean in-vitro dissolution evaluation suffices its market approval. This work, however, found equivalence problems between ‘comparators’ and interchangeability issues among doxycycline different brands already distributed in the market.

The flipped classroom is gaining prominence as an active learning pedagogy to engage a new generation of students. However, all courses do not lend themselves to a fully flipped design and instructors are often reluctant to flip lectures. In this study, I experimented with a “partial” flipped classroom design in a first-year undergraduate economics course. In this partial flipped format, traditional lectures were substituted with micro-lectures and the remaining class time was devoted to activities like quizzes, group work and student presentations. The full lectures were panopto recorded and put up on the e-learning site, Blackboard. This format enabled me to combine the benefits of a traditional lecture with a flipped classroom design. In order to evaluate the effectiveness of the partial flipped classroom format, I compared the final exam scores of students in the partial flipped classroom with those in the control group, which followed a traditional lecture-based approach. The key results from the analysis revealed that students in the partial flipped classroom performed better in the final exams vis-à-vis students in the traditional classroom format. Furthermore, the partial flipped classroom format was associated with lower odds of students failing in the module. This format also resulted in better student engagement, more flexibility and enhanced student-tutor interaction within the classroom.

Abstract: A. baumannii exhibits resilience in harsh environments and progressively develops resistance to diverse antibacterial agents over time. This adaptability poses a significant challenge in treating an infection caused by this bacterium within healthcare settings. The presence of peptidoglycan, a crucial precursor for cell wall synthesis, contributes to this challenge. Peptidoglycan serves not only as a structural support in bacterial cells but also provides protection against adverse environmental conditions. The synthesis of the peptidoglycan layer involves a group of substrates such as N-acetylglucosamine (GlcNAc) and N-acetylmuramic acid (MurNAc), within a three-partitioned process occurring in the membrane, periplasmic space, and cytoplasm of each bacterium. Initiated in the cytoplasm and extending to the inner cell membrane, this synthesis starts with the production of nucleotide precursors. The first step involves the synthesis of UDP-GlcNAc, orchestrated by Glm (GlmS, GlmM, and GlmU) enzymes using fructose-6-phosphate. Subsequently, enzymes from the Mur family, namely MurB, MurA, MurD, MurC, MurI, MurF, and MurE, synthesize UDP-N-acetylmuramyl-pentapeptide (UDP-Mpp) from UDP-GlcNAc. Concurrently, on the cytosolic side, the production of membrane-surrounded undecaprenyl phosphate occurs, involving membrane-side proteins MraY and MurG in the biosynthesis of peptidoglycan. This review emphasizes updated information on Mur family proteins, encompassing physicochemical properties, nature of binding site, number and type of binding site residues, functional domain details, three-dimensional structural aspects, and their functions within bacterial cells. Special attention is directed towards their enzymatic role in peptidoglycan biosynthesis due to the limited availability of precursors in the market. Additionally, the review provides a comprehensive summary of existing inhibitors and ongoing efforts in identifying new targeted inhibitors, recognizing these enzymes as potential candidates for antibacterial drug design and discovery.

The growing demand for high-power DC Fast Charging (DCFC) stations for Electric Vehicles (EVs) is expected to lead to increased peak power demand and reduction of grid power quality. To maximize the economic benefits and station utilization under practical constraints set by regulatory authorities and DCFC station operators, this study explores and provides methods for connecting DCFC stations to the grid employing low power interconnection rules and Distributed Energy Resources (DERs). The system uses automotive Second Life Batteries (SLBs) and Photovoltaic (PV) systems as energy buffers and local energy resource to support EV charging and improve the station techno-economic feasibility through load shifting and charge sustaining. The optimal sizing of the DERs and the selection of the grid interconnection topology is achieved by means of a Design Space Exploration (DSE) by means of exhaustive search approach to maximize the economic benefits of the charging station and to mitigate high-power demand to the grid. Without loosing of generality, this study considers a range of DER sizes, grid interconnection specifications, and related electricity tariffs of American Electric Power (AEP) Ohio and the Public Utility Commission of Ohio (PUCO). Various scenarios and strategies have been defined to account for the interconnection requirements of the grid to the DCFC with DERs. The system’s techno-economic performance of different scenarios has been analyzed and compared using a multitude of metrics.

Fever remains an integral part of the acute clinical diseases management, esp. viral, for which effective therapeutics remain desired. However, the presence of often confusing fever reduction recommendations for COVID-19 in the public domain during the pandemic, as late as 28 April 2021, seems to suggest the reduction of any ‘uncomfortable’ fever ranging from 37.8 - 39oC, as opposed to WHO fever reduction guidelines (≥39oC), urgently need attention. The confusion could percolate down into different agencies who look up to these agencies for guidance in framing their own, denying the benefits of fever to populations, and effectively undo whatever successive WHO’s guidelines have achieved in the last two decades. The existence of conflicting guidelines in public domains which are open to interpretations has consequences to public health and the healthcare infrastructure, on implementation. For controlling acute infectious diseases, esp. viral, the fever remains the most important enabler. Historically, our chief obstacles to harnessing the benefits of fever in acute clinical diseases with limited therapeutics had been: a) widespread myths about ‘fevers’ arising from a general misunderstanding of basic facts; b) presence of confusing guidelines by different agencies which are open to alternate interpretation. The article attempts to briefly indicate the benefits of fever in disease resolution, dispel myths, underline vagueness in illustrative national guidelines and the need to align them with evidence-based WHO guidelines, as it has the potential to perpetuate myths/confusion in masses leading to adverse impact on disease management – more morbidity and mortality from diseases including COVID-19.

Machine reading comprehension aims to teach machines to understand a text like a human, and is a new challenging direction in Artificial Intelligence. Datasets play an important role while describing or building an algorithm for machine reading comprehension. The type of answers we required from developed algorithm depends on datasets.The datasets are classified into two types, namely datasets with extractive answers and datasets with descriptive answers. This article summarize both datasets with an example of each type to get better insight of datasets in machine reading comprehension and which datasets to use depending the requirements.

In this study, the complex interactions between the well-known Mittag-Leffler functions with two, three, and four parameters are explored. We first study the integral forms of the Mittag-Leffler function $\mathsf{E}_{\alpha, \beta}^{\rho,\kappa}(z)$ with the goal of clarifying its mathematical behaviours and features. Moreover, we create relations between these functions and generalised hypergeometric functions and Fox-Wright functions, expanding the range of their use and comprehension. We explore a number of unique situations by in-depth examination, providing insight into the subtle characteristics of these functions. This investigation advances our theoretical knowledge and opens up possibilities for future applications in a number of scientific fields. As such, this study adds to the current conversation in mathematical analysis and is an important tool for both practitioners and researchers.

The growth in the Internet of Things (IoT) devices in the healthcare sector enables the new era of the Internet of Medical Things (IoMT). However, IoT devices are susceptible to diverse cybersecurity attacks and threats that lead to negative consequences. Cyberattacks can harm not just the IoMT devices being used but also human life. Currently, several security solutions are proposed to enhance the security of the IoMT, which uses machine learning (ML) and blockchain. ML can be used to develop detection and classification methods to identify cyberattacks targeting IoMT devices in the healthcare sector. In addition, blockchain technology enables a decentralized approach to the healthcare system and eliminates some disadvantages of a centralized system, such as a single point of failure. This paper proposes a resilient security framework integrating a Tri-layered Neural Network (TNN) and blockchain technology in the healthcare domain. The TNN detects anomalies in data measured by medical sensors to find fraudulent data. Therefore, cyberattacks are detected and discarded from the IoMT system before data is processed at the fog layer. In addition, a blockchain network is used in the fog layer to ensure that the data is not altered, boosting the integrity and privacy of the medical data. The experimental results show that the TNN and blockchain models produce the expected result. Furthermore, the accuracy of the TNN model reached 99.99% on the F1-score accuracy metric.

A series of derivatives of trans-3-(2,4,6-trimethoxy phenyl)-4,5-dihydro isoxazolo-4,5-bis(aroylcarbohydrazide) and of trans-3-(2,4,6-trimethoxyphenyl)4,5-dihydroisoxazolo-4,5-bis[carbonyl-(4’phenyl)thiosemi- carbazide (9) were synthesized from trans-3-(2,4,6-trimethoxyphenyl)-4,5-dihydro-4,5-bis(hydrazenocarbonyl) Isoxazole (8). The structures of the Compounds were elucidated by elemental and spectral (IR, NMR, and MS) analysis. The compound 9 show activity against some bacterial species. Whereas, no activity was observed for compounds 10a, 10b and 10c against all bacterial species. The antioxidant activity of new compounds has been screened. Compound 9 showed higher antioxidant activity using the DPPH and ATBS method.

Proprotein convertase subtilisin/Kexin type 9 (PCSK9) is a proteolytic enzyme that indirectly regulates serum LDL cholesterol by destroying LDL receptors. In clinical studies, the main role of the proprotein convertase subtilisin/Kexin type9 (PCSK9) inhibitor in cholesterol regulation was elucidated. It is produced in the liver but is also present in the kidney and intestine. It prevents HMGCo from synthesizing cholesterol. SREBP-2 is a reductase that is induced by statins. In a dose-dependent manner, increasing SREBP-2 levels enhanced LDL-R and PCSK9 gene expression. At the minimum, two procedures have been developed to overcome the plasma level of PCSK9. This is the LDLR test, polyclonal antibodies, and sentience oligonucleotide. Lower dosage statin treatment with a proprotein convertase subtilisin/Kexin type9 inhibitor will be most efficient in lowering LDL and avoiding statin adverse effects. In multiple long-term trials, statins have been found to reduce cardiovascular mortality by 30% and stroke incidence by 20%. In this way, we conclude the role of PCSK9 in hypercholesterolemia.

Natural Fibre Reinforced Composites (NFRCs) represent a significant category of materials that has the capacity to contribute to the worldwide objectives of sustainability and environmental preservation. To maximise the potential of composite materials, it is essential to establish their high quality and cost-effective manufacture. While the basic production procedures for producing items based on NFRCs have reached a high level of development, more research efforts are needed to advance their secondary manufacturing processes, namely in the areas of machining and joining. The primary factor leading to the rejection of composite goods with holes is the damage generated during the drilling process. The present experimental study aims to examine the effectiveness of hole production during the moulding phase. A comparative analysis has been conducted to assess the mechanical characteristics of moulded and drilled holes in jute fibre reinforced epoxy composite. It was observed that the moulded holes exhibit superior performance compared to the drilled holes for jute/epoxy materials. Additionally, the load extension curves indicate that the moulded holes experience greater extension in comparison to the drilled holes.

The SnRK gene family is a key regulator playing an important role in plant stress response by phosphorylating the target protein to regulate the signalling pathways. The function of SnRK gene family has been reported in many species but is limited to Triticum asetivum. In this study, SnRK gene family in the wheat genome was identified and its structural characteristics were described. One hundred forty-seven SnRK genes distributed across 21 chromosomes were identified in the Triticum aestivum genome and categorised into three subgroups (SnRK1/2/3) based on phylogenetic analyses and domain types. The gene intron-exon structure and protein-motif composition of SnRKs were similar within each subgroup but different amongst the groups. Gene duplication between the wheat, Arabidopsis, rice and barley genomes was also investigated in order to get insight into the evolutionary aspects of the TaSnRK family genes. SnRK genes showed differential expression patterns in leaves, roots, spike, and grains. Redundant stress-related cis-elements were also found in the promoters of 129 SnRK genes and their expression levels varied widely following drought, ABA and light regulated elements. In particular, TaSnRK2.11 had higher and increased expression under the abiotic stresses and can be a candidate gene for the abiotc stress tolerance. The findings will aid in the functional characterization of TaSnRK genes for further research.

Spin dependent quantum transport properties in twisted carbon nanotube and stretched carbon nanotube are calculated using density functional theory (DFT) and non-equilibrium green’s function (NEGF) formulation. Twisting and stretching have no effect on spin transport in CNTs at low bias voltages. However, at high bias voltages the effects are significant. Stretching restricts any spin-up current in antiparallel configuration (APC) which results in higher magneto resistance (MR). Twisting allows spin-up current almost equivalent to the pristine CNT case resulting in lower MR. High spin filtration is observed in PC and APC for pristine, stretched and twisted structures at all applied voltages. In APC, at low voltages spin filtration in stretched CNT is higher than in pristine and twisted ones with pristine giving higher spin filtration than twisted CNT.

Comprehensive studies into the various causes of this ubiquitous disease have been prompted by the worldwide increase in cancer incidence. There are many potential causes of cancer, but environmental factors are of particular concern now. This abstract explores the complex link between environmental factors and the growing cancer epidemic, shedding light on the role that our immediate environment plays in the emergence of cancers. The environment can contain carcinogenic agents that gradually influence the course of cancer, including air pollutants, water contaminants, workplace exposures, and industrial activities. The ways through which environmental carcinogens may cause DNA damage and unchecked cell proliferation are discussed in this abstract. Environmental justice and the moral necessity to reduce inequities in exposure and health effects are highlighted to underline the disproportionate impact on vulnerable groups. The study presented here highlights the need for preemptive action to reduce environmental risks. Society can reduce the hidden threat posed by environmental carcinogens through strict legislation, sustainable practices, and community-driven initiatives. In order to lessen the cancer burden and secure a healthier future for all, the authors of this abstract argue that there must be a concerted effort to create surroundings that promote health and well-being.

Vaccination against Newcastle disease (ND), a devastating viral disease of chicken, is often hampered by thermal inactivation of the live vaccines, in particular in tropical and hot climate conditions. In the past “thermostable” vaccine strains (I-2) have been proposed to overcome this problem. In the current study, we compared the thermal stability of 6 commercially available ND vaccines. Subjected to 37°C as lyophilized preparation, two vaccines containing I-2 strains were more sensitive to inactivation than a third I-2 vaccine or when compared to three other vaccines based on different strains. However, after reconstitution strains proved to have a comparable tenacity. Interestingly, all vaccines retained a sufficient virus dose for protection (106 EID50) after 1 day at 37°C, still. However, experiments exposing ND-vaccines to elevated temperatures of 51°C and 61°C, clearly demonstrated inactivation of all dissolved vaccines within 2 to 4 hours. The data indicate preparation that specific factors may influence thermal stability rather than strain specific characteristics. Regardless of the ND strain used, the appropriate cold chain is mandatory for live ND-vaccines.

In the present paper, we introduced a quadratically convergent Newton’s like normal S2 iteration method free from the second derivative for the solution of nonlinear equations permitting 3 f'(x) = 0 at some points in the neighborhood of the root. Our proposed method works well 4 when the Newton method fails. Numerically it has been verified that the Newton’s like normal 5 S-iteration method converges faster than Fang et al. method [A cubically convergent Newton-type 6 method under weak conditions, J. Compute. and Appl. Math., 220 (2008), 409-412]. We studied 7 different aspects of normal S-iteration method. Lastly, fractal patterns support the numerical 8 results and explain the convergence, divergence, and stability of method.

The Indian Himalayan Region (IHR), due to its topography, geography, and active tectonics, a rough mountain zone, is among the most vulnerable zones to the landslip danger. The most cutting-edge and accurate ways for creating a landslip susceptibility model (LSM) are advanced statistical techniques. The goal of the current work was to use advanced statistical techniques to analyse and evaluate the updated landslip susceptibility for East District in the NE Himalayas of Sikkim, India. The spatiotemporal landslip inventory for the years are produced using literature surveys, historical satellite imageries and on-site observations. Slope, aspect, elevation, curvature, plane curvature, profile curvature, topographic wetness index (TWI), lithology, distance to faults, distance to streams, distance to roads, normalised difference vegetation index (NDVI), rainfall, drainage density and land use/ land cover (LULC) are some of the topographic, environmental, geologic, and anthropogenic factors that were included in the spatial database. These LCFs were chosen to study the area's periodic landslip vulnerability. An inventory of 151 landslides from historical published records, field visits and Imagery interpretations, respectively, were used in the experimental design. Information Value Model (IVM), was used to evaluate the vulnerability to landslides as determined by fifteen LCFs. The goal of the study is to reduce the number of fatalities and possible economic harm caused by the region's frequent slope instabilities. It is expected that the application of statistical algorithms would assist relevant authorities and organisations in properly planning for and managing the region's landslip threat.

The body's billions of bacteria—the microbiota—influence health and illness. The microbiome—the genetic material of these microbes—affects digestion, immunological function, and mental health. Due to bacterial variety, complicated relationships, and research technique constraints, investigating the microbiota is difficult. AI and machine learning have expanded microbiome research. Artificial intelligence (AI) systems can efficiently scan large microbiome datasets to help researchers understand microbial populations and their functions. AI-based predictive algorithms can analyze food impacts on microbial communities and forecast illness risks based on gut microbiota composition. AI helps find microbial biomarkers linked to specific health disorders, enabling early illness identification and targeted therapy. AI-driven medication development platforms also modulate microbiome to treat microbiota-related diseases. Understanding microbial populations' involvement in health and illness requires understanding complicated microbial interactions within the microbiome and between it and the host. AI systems improve human health by comprehending these complex relationships. AI in microbiota study must overcome various obstacles. Data quality and AI model interpretability are essential for accurate findings. Diverse and representative datasets avoid biases and strengthen AI-driven conclusions. AI in microbiota research requires data protection, informed permission, and appropriate use of sensitive data. AI is improving our understanding of the human microbiome and its health effects, changing microbiota research. Overcoming difficulties and adhering to ethical norms will enable the proper use of AI-driven findings, leading to microbiome insights and precision medical breakthroughs.

This paper provides orthogonal moments (OM) such as, Zernike Moments(ZM), Psuedo Zernike Moments(PZM) and Orthogonal Fourier Mellin Moments(OFMM) for the analysis of melanoma images. The moment invariants may vary with respect to geometric variations. For the analysis of orthogonal moments hundred random melanoma images and hundred non-melanoma images have been taken into consideration from the database of 570 melanoma images and 250 non-melanoma images respectively. Orthoganal moments have been computed by varying the phase angles from 10° to 40° with an equal interval of 10° degree for the orders 2, 4,8,16,32,64,128,256 respectively. For the optimal OMs Particle Swarm Optimization (PSO) technique have been used. These set of extracted optimal OMs have been further applied to classify melanoma images. Support Vector Machine (SVM) has been used for the classification of [1]sensitivity=88.78%.

Maize (Zea mays subsp. mays) is the staple food crop in the world. In this study, multi-layer perceptron (MLP), support vector machine (SVM), genetic algorithm-based multi-layer perceptron (MLP-GA), and genetic algorithm-based support vector machine (SVM-GA) hybrid artificial intelligence algorithms were used for the prediction of drought tolerance and stress tolerance indices in teosinte maize lines. Correspondingly, the gamma test technique was applied to determine efficient input and output vectors. The potential of developed models was evaluated based on statistical indices and graphical representation. Results of gamma test based on the least value of gamma and standard error indices show that day of anthesis (DOA), day of silking (DOS), yield index (YI), and gross yield per plant (GYP) information vector arrangements were determined as efficient information vector combination for drought-tolerant index (DTI) as well as the stress-tolerant index (STI). The results of MLP, SVM, MLP-GA, and SVM-GA algorithms were compared based on statistical indices and visual interpretation that have satisfactory for prediction of the drought-tolerant index and stress-tolerant index in maize crop. It has also seemed that genetic algorithm-based hybrid models (MLP-GA and SVM-GA) were found a better prediction of the drought-tolerant index and stress-tolerant index in maize crop. Similarly, the SVM-GA model has the highest potential to forecast the DTI and STI in maize crops as compared to MLP, SVM, MLP-GA models.