Religious harmony performs a key role in preserving political and worldwide stability. Internationally it's far crucial to stay in a non-violent and harmonious environment, mainly in a society composed of believers of various races and religions. Relations among religions are normal. Failure to hold religious harmony can plunge society into battle and chaos. Therefore, the cause of this newsletter is to record in element the elements that affect the sustainable harmony among multi-religious societies. The record additionally emphasized that elements including acceptance, knowledge, cooperation, fairness, and justice are crucial elements in preserving religious harmony. Therefore, this paper pursuits to shape a solid idea of multi-sectarian harmony in society. It must additionally contribute to the improvement of a multi-religious society. Try to hold and construct a sturdy dating among them. Religious harmony is vital to make sure solidarity and team spirit amongst believers of more than one religion. A multi-religious society is a network with one-of-a-kind religions, including Islam, Buddhism, Hinduism, Christianity, etc. To stay in a non-violent and harmonious society, it's far very crucial to just accept believers from different religions in a selected network. From the angle of Islam, Islam is a faith that accepts the range of religions on this international however denies that every one religion is proper. So is the case in almost all religions. Religious pluralism may be described because of the range of religions on this international; however, withinside the idea of religious pluralism, it could be described because of the perception that every religion on this international is absolute truths. Pluralists trust that every one religion withinside the international is actual and have to be respected. It could be very crucial to recognize that everyone's proper statements are legitimate and deserve the same appreciation. This handiest method that fans of one religion have to be given different reality statements, including Muslims, Jews, Hindus, and others. However, from the angle of Islam, Islam accepts more than one religion however does now no longer understand that every one religion is proper. Recognizing the origins of various religions in a multi-religious society is the important thing to making sure harmony and solidarity withinside the international. Recognizing that religious range in a multi-religious society is a crucial component in preserving social harmony. For example, Muslims who cost the lifestyles of different religious groups (including Buddhists, Hindus, and Christians) can enhance inter-religious members of the society and deal with them kindly. Therefore, the popularity of the lifestyles of the religious range must be visible as a resounding component for a selected network. Everyone residing in a multi-religious society has to recognize and be given religious freedom. One must accept and appreciate the beliefs of different religions. Respect for the lifestyles of the religious range additionally contributes to political and countrywide stability. Respect also can enhance interreligious members of the society via way of means of acknowledging the lifestyles of various religious groups. Mutual appreciation, cooperation, tolerance, knowledge, and kindness are crucial elements in residing in a multi-ethnic and religious society. To hold a harmonious society, all multi-religious believers must have the proper and freedom to exercise their faith. It must now no longer be abandoned (Abdullah et al., 2016). Islam has usually emphasized the idea of justice (alAdl). All divine religions are of belief of religious harmony. By studying different religions, it is very clear that all religions are of the view to respect other religions and followers of different beliefs.

This study was conducted to investigate heavy metal contamination and potential health risk of ground water of selected municipal solid waste (MSW) disposal sites of Khyber Pakhtunkhwa (KP) Pakistan. For this purpose a total of 30 composite samples of both surface and ground water were collected from dumpsites of Abbottabad, Bannu and Peshawar. The collected samples were analyzed for physico-chemical parameters and heavy metals by following standard methods. Results indicated that pH values were found within the acceptable limits specified by national environmental quality standards (NEQS) and world health organization (WHO). Mean concentrations of heavy metals were within NEQS and WHO limits, except for Ni which exceeded the NEQS and WHO limit of 0.02 mg/L in all samples, Similarly, Mn exceeded the limit set by NEQS and WHO (0.5 mg/L) in the ground water samples collected from Bannu dumpsite. The multivariate analysis indicated that the heavy metal contamination of the groundwater of the selected dumpsites was anthropogenic. The pollution index (PI) values (PI≥100) of Mn and Ni indicated very high pollution at individual levels while collectively based on heavy metals pollution index (HPI) values (HPI ≥ 200) the ground water of all the selected dumpsites were found highly polluted. Whereas, the hazard index (HI) values (HI ≥ 5) suggested adverse health effects. It was concluded that the ground water of all the dumpsites was highly polluted with heavy metals particularly Ni and Mn thus, posing a high health risk.

Inflammatory bowel diseases (IBD), including Crohn's disease and ulcerative colitis, is a disease of chronic inflammatory conditions of the intestinal tract due to disturbance of the inflammation and immune system. Symptoms of IBD include abdominal pain, diarrhea, bleeding, reduced weight, and fatigue. In IBD, the immune system attacks the intestinal tract's inner wall, causing chronic inflammation and tissue damage. In particular, IL-6 and IL-17 act on immune cells, including T cells and macrophages, to amplify the immune responses so that tissue damage and morphological changes occur. Of note, excessive calorie intake and obesity also affect the immune system due to inflammation caused by lipotoxicity and changes in lipids supply. Similarly, individuals with IBD have alterations in liver function after sustained high-fat diet feeding. In addition, excess dietary fat intake, along with alterations in primary and secondary bile acids in the colon, can affect the onset and progression of IBD because inflammatory cytokines contribute to insulin resistance; the factors include the release of inflammatory cytokines, oxidative stress, and changes in intestinal microflora, which may also contribute to the disease progression. However, interfering with de novo fatty acid synthase by deleting the enzyme acetyl-CoA-carboxylase 1 in intestinal epithelial cells leads to the deficiency of epithelial crypt structures and tissue regeneration, which seems to be due to Lgr5+ intestinal stem cell function. Thus, conflicting reports exist regarding high-fat diet effects on IBD animal models. This review will focus on the pathological basis of the link between dietary lipids intake and IBD and cover currently available pharmacological approaches.

The purpose of this paper is to develop WebSecuDMiner algorithm to discover unusual web access patterns based on analysing the potential rules hidden in web server log and user navigation history. Design/methodology/approach: WebSecuDMiner uses equivalence class transformation (ECLAT) algorithm to extract user access patterns from the web log data, which will be used to identify the user access behaviours pattern and detect unusual one. Data extracted from the web serve log and user browsing behaviour is exploited to retrieve the web access pattern that is produced by the same user. Findings: WebSecuDMiner is used to detect whether any unauthorized access have been posed and take appropriate decisions regarding the review of the original rights of suspicious user. Research limitations/implications: The present work uses the database which is extracted from web serve log file and user browsing behaviour. Although the page is viewed by the user, the visit is not recorded in the server log file, since it can be access from the browser's cache.

It is a theoretical exportation for mass transpiration and thermal transpiration of Casson nanofluid over an extending cylindrical surface. The Stagnation point flow through porous matrix is influenced by magnetic field of form strength. Appropriate similarity functions are availed to yield the transmuted system of leading differential equations. Existence for the solution of momentum equation is proved for various values of Casson parameter β, magnetic parameter M, porosity parameter Kp and Raynolds number Re in two situations of mass transpiration (suction/injuction). Moreover, uniqueness results are discussed and for skin friction factor are established to attain accuracy for large injection values. Thermal and concentration profiles are delineated numerically by applying Runge-Kutta method and shooting technique.

Prosthetics have come a long way since their inception, and recent advancements in materials science have enabled the development of prosthetic devices with improved functionality and comfort. One promising area of research is the use of auxetic metamaterials in prosthetics. Auxetic materials have a negative Poisson's ratio, which means that they expand laterally when stretched, unlike conventional materials, which contract laterally. This unique property allows for the creation of prosthetic devices that can better conform to the contours of the human body and provide a more natural feel. In this review article, we provide an overview of the current state of the art in the development of prosthetics using auxetic metamaterials. We discuss the mechanical properties of these materials, including their negative Poisson's ratio and other properties that make them suitable for use in prosthetic devices. We also explore the limitations that currently exist in implementing these materials in prosthetic devices, including challenges in manufacturing and cost. Despite these challenges, the future prospects for the development of prosthetic devices using auxetic metamaterials are promising. Continued research and development in this field could lead to the creation of more comfortable, functional, and natural-feeling prosthetic devices. Overall, the use of auxetic metamaterials in prosthetics represents a promising area of research with the potential to improve the lives of millions of people around the world who rely on prosthetic devices.

Utilization of medicine derived from plants has been documented in various traditional systems of medicines throughout the world for different diseases. Therefore, the current research work was carried out to evaluate the phytochemical and biological potential of Ficus carica L ethanolic leaf extract. For this purpose, physicochemical and phytochemical analysis, total phenolic and flavonoids contents was performed. Antioxidant potential was determined by FRAP, DPPH and H2O2 assay. Proteinase inhibition, heat induced hemolysis and BSA denaturation assay was carried out for inflammation. Antiglycation potential was assessed by fructosamine assay, Congo-red assay and estimation of free carbonyl groups. In-vivo antidiabetic, anti-obesity, effect on liver and kidney were investigated by high fat high sugar diet model. FTIR, HPLC and LCMS/MS analysis was performed to find out the compounds. Tablet based formulation was developed using wet granulation method and tested for physicochemical parameters. Results shows that total phenolic and flavonoids content was (333 mg GAE/g) and (123 mg RE/g) respectively, H2O2 assay shows 35.6% free radical inhibition potential, DPPH assay shows (IC50) inhibitory concentration at 0.58 mg/mL, and 88.769 µg/g Fe2SO4 solution FRAP values. Proteinase inhibition assay, Heat induced hemolysis and BSA-denaturation assay shows percentage inhibition of 28 ± 0.01, 55 ± 0.03 and 51.2 ± 0.05 respectively. In Antiglycation activity β-amyloid formation assay shows absorption of 0.017, Fructosamine assay shows inhibition of 19.4±0.06 and free carbonyl group estimation shows inhibition of 17.0±0.03. In in-vivo study FLE at (500 mg/kg) significantly decreased total bilirubin (p ≤ 0.001), decreased (p ≤ 0.05) alanine transferase, aspartate aminotransferase, alkaline phosphatase, decreased blood glucose, triglycerides and total cholesterol (p ≤ 0.01) while HDL (p ≤ 0.01) was significantly increased in comparison to obesity and diabetic-obesity groups. Different functional groups presence was confirmed by FTIR spectrum. HPLC analysis revealed the existence of ferulic acid, rutin, chlorogenic acid, coumarin and thymoquinone and these results are corelated by LC-MS/MS. Pre-compression characterization showed angle of repose (33.04°), bulk density (0.54 g/cm3), tapped density (0.73 g/cm3), compressibility index (35.179 %) and Hausner’s ratio (1.35), while the post-compression characterization showed weight variation 826±4.17 mg, thickness 10.50±0.25 kg/cm2, friability 0.57 %, and disintegration time 8.19 min. From the above results it is concluded that F. carica L. leaves extract has strong antioxidant, antidiabetic and hypolipidemic potential and can be used for an obesity and diabetes treatment.

This article describes in detail the numerical modeling of a CZTS (copper zinc tin sulfide) based kesterite solar cell. The Solar Cell Capacitance Simulator -one-dimension (SCAPS-1D) software was used to simulate MO/CZTS/CdS/ZnO/FTO structured solar cells. The parameters of different photovoltaic thin-film solar cells are estimated and analyzed using numerical modeling. The effects of various parameters on the performance of the photovoltaic cell and the conversion efficiency are discussed. Since the response of the solar cell is also contingent on its internal physical mechanism, J-V characteristic measures are insufficient to characterize the behavior of a device. Different features, as well as different potential conditions, must be considered for simulation, disregarding the belief in the modeling of a solar cell. With a conversion efficiency of 25.72%, a fill factor of 83.75%, a short-circuit current of 32.96436 mA/cm2 and an open-circuit voltage of 0.64V, promising optimized results have been achieved. The findings will be useful in determining the feasibility of fabricating high-efficiency CZTS-based photovoltaic cells. The efficiency of a CZTS-based experimental solar cell is also discussed. First, the effects of experimentally developed CZTS solar cells are simulated in the SCAPS-1D environment. The experimental results are then compared to the SCAPS-1D simulated results. The conversion efficiency of an optimized system increases after cell parameters are optimized. Using one-dimensional SCAPS-1D software, the effect of system parameters such as the thickness, acceptor and donor carrier concentration densities of absorber and electron transport layers, and the effect of temperature on the efficiency of CZTS-based photovoltaic cells is investigated. The proposed results will greatly assist engineers and researchers in determining the best method for optimizing solar cell efficiency, as well as in the development of efficient CZTS-based solar cells.

Prosthetic device is designed to function as a replacement for a missing limb and typically consists of suspension, liner, socket, pylon and foot components. The objectives of this research are to design a pylon component of a transtibial prosthetics by implementing auxetic metamaterial and to also validate performance of the designed pylon under quasi-static and dynamic conditions. The design and analysis processes are conducted using the finite element analysis and its effectiveness is validated by experimental testing of the prototype pylon sample. In the design process, the pylon structure is formulated by rearranging 2D re-entrant hexagon model into 3D model. It is identified from the design evaluation that the pylon exhibits the stiffness of the value of 79.24, 2371.6, and 13344 kN/m for the ligament thickness variation of 0.3 mm, 1 mm, and 2 mm, respectively. This directly indicates a capability of the stiffness tuning of the pylon by changing the ligament thickness. It is evaluated that the pylon with the ligament thickness of 0.3 mm causes the deformation of 0.53 cm during a single period of gait cycle, while the ligament thickness of the 1 mm causes the deformation of 0.4 cm. The deformation physically indicates the energy absorption of the pylon structure and hence the thinner ligament, the higher energy absorption provides. It is also found from the deformation transition of the primary and secondary bends, the negative Poisson’s ratio is occurred in 3D model transformed from 2D re-entrant hexagon.

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

The term Air Quality (AQ) pertains to the standard of air, which has a direct impact on the health and well-being of individuals. It is crucial to maintain high Air Quality (AQ), for better health and productivity. Though most of people spend more time indoors nowadays, it is not to be overlooked that the pollutant concentration in indoor air is directly linked to the outdoor air quality. Due to the changes in occupancy patterns, outdated maintenance of ventilation systems, and structural flaws in buildings, the indoor air is significantly polluted; pollutants emitted outdoors enter indoor air through open windows, ventilation systems and infiltration. In this paper, we have proposed a new technique, DTMCPM (discrete-time Markov chain (DTMC) model for the analysis and forecasting of AQ, using the power method). Specialized sensors and equipment to measure different pollutants, such as particulate matter, ozone, nitrogen dioxide, sulfur dioxide, benzene and toluene, are used to collect data by the Institute of Pakistan Air Quality Monitor in various cities; the data is converted to US EPA standard for all pollutant species. This data is used to calculate the transition matrix, steady-state values and mean return rate for the analysis of IAQ. The calculated and actual return rates have been compared and the proposed model is found to have a low average prediction error of 2.356%.

This review explores the application of the conservative management model for pain to sports-related concussions (SRCs), framing concussions as a distinct form of pain syndrome with a pathophysiological foundation in central sensitization. Drawing parallels with proven pain management models, we underscore the significance of a proactive approach to concussion management. Recognizing concussions as a pain syndrome allows for the tailoring of interventions in alignment with conservative principles. This review first covers the epidemiology and controversies surrounding prolonged concussion recovery and persistent post-concussion symptoms (PPCS). Next, the pathophysiology of concussions is presented within the central sensitization framework, emphasizing the need for early intervention to mitigate the neuroplastic changes that lead to heightened pain sensitivity. Five components of the central sensitization process specific to concussion injuries are highlighted as targets for conservative interventions in the acute period: peripheral sensitization, cerebral metabolic dysfunction, neuroinflammation, glymphatic system dysfunction, and pain catastrophizing. These proactive interventions are emphasized as pivotal in accelerating concussion recovery and reducing the risk of prolonged symptoms and PPCS, in line with the philosophy of conservative management.

This study uses the Scopus and Web of Science databases to review the forecast of electricity consumption from 2015 to 2024. Based on the keywords used in the article title, which are associated with electricity consumption forecasts, the study retrieved 821 docu-ments for additional analysis using various techniques. For frequency analysis, we used Mi-crosoft Excel; for data visualisation, we used VOSviewer; and for citation metrics and analysis, we used Harzing's Publish or Perish. Standard bibliometric variables, including publication growth, authorship patterns, collaboration, prolific authors, national contribution, most active institutions, favourite journals, and highly cited articles, are used in this study's reporting of the findings. Our analysis indicates that over ten years, starting in 2015, publications on the forecasting of electricity consumption have continued to increase. China was the country that contributed the most to research on electricity consumption. Most of the research publications on electricity consumption were published in the Journal of Energy.

Presence detection is essential in many applications, including smart homes, office automation, and public space management. Traditional technologies like infrared sensors and cameras frequently encounter obstacles due to privacy concerns, high costs, and complexity. The study provides a novel way to detect presence based on Wi-Fi signals and machine learning algorithms, utilizing the ESP8266 microcontroller. The suggested system attempts to reliably detect the presence of people in a given place by evaluating fluctuations in Wi-Fi signal strength and patterns. The theoretical basis of this strategy is investigated, including the ESP8266’s capabilities for Wi-Fi data gathering and the use of machine learning methods for data analysis. The methodology includes data collecting with the ESP8266, preprocessing, feature extraction, and training and evaluating machine learning models. This system’s potential uses include smart home automation, office occupancy tracking, and crowd management in public settings. The paper also discusses potential issues such as signal interference, data privacy concerns, and the limitations of Wi-Fi detection. Future work is also mentioned, including the suggested system’s installation and testing and enhancement proposals to improve accuracy and scalability. This research aims to provide a cost-effective, non-intrusive, and scalable presence detection system by harnessing the power of Wi-Fi signals and machine learning, enhancing intelligent environments

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.

The Pashmina and Barbari are two famous goat breeds found in the wide areas of the Indo-Pak region. Pashmina is famous for its long hair-fiber (Cashmere) production while Barbari is not-selected for this trait. So, the mRNA expression profiling in the skin samples of both breeds would be an attractive and judicious approach for detecting putative genes involved in this valued trait. Here, we performed differential gene expression analysis on publicly available RNA-Seq data from both breeds. Out of 44,617,994 filtered reads of Pashmina and 55,995,999 of Barbari which are 76.48% and 73.69% mapped to the ARS1 reference transcriptome assembly respectively. A pairwise comparison of both breeds resulted in 47,159 normalized expressed transcripts while 8,414 transcripts are differentially expressed above the significant threshold. Among these, 4,788 are upregulated in Pashmina while 3,626 transcripts are upregulated in Barbari. Fifty-nine transcripts harbor 57 genes including 32 LOC genes and 24 are annotated genes which were selected on the basis of TMM counts > 500. Genes with ectopic expressions other than uncharacterized and LOC symbol genes are Keratins (KRT) and Keratin Associated Proteins (KRTAPs), CystatinA&6, TCHH, SPRR4, PPIA, SLC25A4, S100A11, DMKN, LOR, ANXA2, PRR9 and SFN. All of these genes are likely to be involved in keratinocyte differentiation, sulfur matrix proteins, dermal papilla cells, hair follicles proliferation, hair curvature, wool fiber diameter, hair transition, hair shaft differentiation and its keratinization. These differentially expressed reported genes are critically valuable for enhancing the quality and quantity of the pashmina fiber and overall breed improvement. This study will also provide important information on hair follicle differentiation for further enrichment analyses and introducing this valued trait to other goat breeds as well.

The clinical relationship between diabetes and inflammation is well-established. Various branches of science independently have confirmed that disrupting oxidant-antioxidant equilibrium and elevated lipid peroxidation could be a potential mechanism for chronic kidney disease associated with Type 2 diabetes mellitus (T2DM). Under diabetic condition, hyperglycemia, especially inflammation, and increased reactive oxygen species generation are bidirectionally associated. Inflammation, oxidative stress and tissue damage are believed to have a role in the development of diabetes. Although the exact mechanism underlying the oxidative stress and its impact on diabetes progression remains uncertain, the hyperglycemia-inflammation-oxidative stress interaction clearly plays a significant role in onset and progression of vascular disease, kidney disease, hepatic injury, pancreas damage and, therefore holds promise as a therapeutic target. Evidence strongly indicates that the use of multiple antidiabetic medications therapy fails to achieve the normal range for glycated hemoglobin target, signifying treatment resistant diabetes. Antioxidants with polyphenols are considered useful as adjuvant therapy for their potential anti-inflammatory effect and antioxidant activity. We aimed to analyze the current major points reported in preclinical in vivo and clinical studies of antioxidants in the prevention or treatment of inflammation in T2DM. Then, we will share our speculative vision of the future diabetes clinical trials.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have triggered a recent pandemic of respiratory disease and affected almost every country all over the world. A large amount of natural bioactive compounds is under clinical investigation for various diseas-es. Especially, marine natural compounds are gaining more attention in the new drug develop-ment process. The present study has aimed to identify potential marine-derived inhibitors against the target proteins of COVID-19 using a computational approach. Currently, 16 marine clinical-level compounds were selected for computational screening against the four SARS-CoV-2 main proteases. Computational screening resulted from the best drug candidates for each target based on the binding affinity scores and amino acid interactions. Among these, five marine-derived compounds namely Chrysophaentin A (-6.6 kcal/mol), Geodisterol sulfates (-6.6 kcal/mol), Hymenidin (-6.4 kcal/mol), Plinabulin (-6.4 kcal/mol) and Tetrodotoxin (-6.3 kcal/mol) expressed the minimized binding energy and molecular interactions such as covalent and hydrophobic interactions to the SARS CoV-2 Main Protease. Using Molecular dynamic stud-ies, the Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), Radius of Gyration (ROG), and Hydrogen bonds (H-Bonds) values were calculated for SARS-CoV-2 Main Protease with Hymenidin docked complex. Additionally, in silico Druglikeness and pharmaco-kinetic property assessments of the compounds demonstrated favorable druggability. These re-sults suggested that marine natural compounds are capable of fighting SARS-CoV-2. Further, in vitro and in vivo studies need to be carried out to confirm their inhibitory potential.

As a traditional Muslim country, the problem of gender discrimination in employment among women in Pakistan is more common. If we let it develop without taking measures, it will seriously restrict the speed and quality of Pakistan’s domestic economic development in the long run. In this study, the author obtained the first-hand information on the employment status of professional women in the Rahim Yar Khan region of Pakistan through questionnaire survey, supplemented by the public data of the Federal Statistical Office of Pakistan, and combined with the existing research results of the predecessors. Sex discrimination in employment of professional women in Pakistan. Through the collection of the data obtained from the questionnaire, the author found that economic factors are one of the main factors that cause local women to encounter gender discrimination in employment. Specifically, it includes the imbalance of labor supply and demand and the pursuit of maximum profits. At the same time, the traditional Muslim culture, women's own literacy and the imperfect legal system in Pakistan are also the key factors that cause female employees in the local area to encounter gender discrimination in employment. Women’s gender discrimination in employment is a universal problem. In any country in the world, gender discrimination may exist as long as women are involved in the work. Based on Pakistan's basic national conditions and relevant professional knowledge, the author provides several suggestions for eliminating the problem of gender discrimination in employment for local female employees in Pakistan. 1) The Pakistani government should further promote the domestic economic growth, increase the number of jobs, and ease the imbalance between the supply and demand of labor. At the same time, encourage self-employment and provide corresponding policy support. A variety of measures are also intended to address local gender discrimination in employment for women. 2) The government's leadership accelerates the transformation of the concept of the whole society. On the one hand, it requires the whole society to correctly understand the social status and social contribution of women, and strives to bring the concept of equality between men and women into the hearts of the people. It is intended to encourage qualified women to go out of the family to participate in social work. At the same time, correctly guide corporate values. Enterprises should not unilaterally pursue the maximization of interests, and should take the initiative to assume social responsibilities. 3) Women should also actively and consciously improve their literacy. Including not only active learning advanced cultural knowledge and professional skills. For the professional skills that have already been mastered, you must study harder and make yourself more and more progressive. At the same time, families should guarantee that girls of the appropriate age receive the education they deserve, so that they can gather their strengths in the workplace in the future.

Hyperlipidemia is an identified risk factor for metabolic syndrome, obesity and cardiovascular complications characterized by elevated levels of lipids in blood. The present study aimed to inhibit HMG-CoA reductase with 15-oxoursolic acid through in-vivo and in-silico assessments. HFD-induced hyperlipidemia in rats was developed with a marked increase in total cholesterol (58.34 ± 0.21 mg/dl), triglycerides (45.45 ± 0.39 mg/dl), LDL-c (66.12 ± 0.10 mg/dl), VLDL-c (19.34 ± 0.16 mg/dl), and a decrease in HDL-c (10.34 ± 0.18 mg/dl). The oral administration of 15-oxoursolic acid at a concentration of 30 mg/Kg b.w significantly reduced the serum concentration of total cholesterol (42.65 ± 0.54 mg/dl), triglycerides (32.33 ± 0.16 mg/dl), LDL-c (50.34 ± 0.15 mg/dl) and VLDL-c (13.15 ± 0.45 mg/dl) respectively and an increased in the serum HDL-c (18.56 ± 0.34 mg/dl). 15-oxo ursolic acid also caused a decrease in the coronary risk index and atherogenic risk index. In-silico studies of 15-oxoursolic acid with HMG-CoA reductase showed significant interaction capability with binding energy (-9.26805 Kcal/mol). It is concluded that 15-oxoursolic acid could significantly reduce the total cholesterol, triglycerides and LDL levels in HFD-induced hyperlipidemia rats which might lead to new medication with significant hypolipidemic potential.

Cadmium Sulfide nanoparticle (CdS-LA hybrid nanoparticles) was synthesized here by a green approach using the precursor cadmium acetate and sodium sulphide along with the extract of a plant Lathyrus aphaca L. containing the phytochemicals which were responsible for surface modification of nanoparticles. The nanoparticle was used to evaluate their inhibition potential against species of bacteria and fungi. The nanoparticles were characterized by XRD which demonstrates the hexagonal crystal structure. SEM confirms the homogenous surface appearance of the CdS-LA hybrid crystalline structure. EDX analysis confirms surface modification of nanoparticles by phytochemicals. FTIR confirmed the Cd-S linkage laterally with the related functional groups and the presence of metabolites on the surface of nanoparticles. The UV-visible spectroscopy confirmed the peak at the characteristic wavelength range but a slight shift occurred in the peak of the CdS nanoparticles due to the presence of the phytochemicals. This study particularly provides an environment-friendly strategy to synthesize the CdS nanoparticles capped by Lathyrus Aphaca L. extract that are biologically active due to the mediation of the plant extract. CdS-LA hybrid nanoparticles have shown inhibition potential against various species of bacteria and fungi and realize the biological importance of the green synthesis of nanoparticles especially mediated with the plant extract.

Although the connection of implant abutments to implant analogs and implant bodies has been evaluated separately, comparative evaluation of connections to implant analogs and implant bodies has not been evaluated. The objective of this study was to identify whether torque applied during laboratory manufacturing and during restoration cementation affects the compatibility between the implant body-abutment and the implant analog-abutment, as well as to spot any structural differences. Three different implant system with internal conical connection (Bioinfinity, Dant, and Dentist) were used. For each group, straight abutments (n=20) were tightened to implant analogs (n=10) and implant bodies (n=10) with hand tightening and using torque wrench device. The fitting of componenets were evaluated for each group using linear and volumetric micro-CT analysis. For linear analysis, when the mean differences (difference between measurements of the linear distance of abutments during hand tightening and applying torque) values between implant analog and implant body were compared within groups, There was no statistically significant difference observed in all groups (p> 0.05). Throughout the fabrication and clinical phases, it is recommended to tighten the abutments on the analogs with a torque wrench instrument to minimize the risk of prosthetic incompatibility.

"The wisdom of crowd'' is so often observed in social discourses and activities around us. The manifestations of it are, however, so intrinsically embedded and behaviorally accepted that an elaboration of a social phenomenon evidencing such wisdom is often cheered as a discovery; or at least an astonishing fact. One such scenario is explored here, namely conceptualization and modeling of a food safety system, a system directly related to social cognition. Food safety is an area of concern these days. Models representing the food safety systems are recently published to study the effect of interactions between important entities of the system. For example, Knowles’s model finds conditions leading to a more efficient and dependable system of entities like consumers, regulators and stores with specific focus on regulators behavior and their impact on the food safety. The first contribution of this paper is reevaluation of Knowles’s model towards a more conscious understanding of ``the wisdom of crowd'' effects on inspection and consuming behaviors. The second contribution is augmenting of the model with social networking capabilities, which acts as a medium to spread information about stores and help consumers find stores which are not contaminated. Simulation results reveal that stores’ respecting social cognition improve effectiveness of the food safety system for consumers and stores both. Simulation findings also reveals that an active society has a capability to self-organize effectively even in the absence of any regulatory compulsion.

Trypanosomes are the extracellular protozoan parasites that cause human African trypanosomiasis disease in humans and nagana disease in animals. The disease is endemic in African countries where tsetse flies which act as a vector for the transmission of disease are present. The animals infected by these parasites become useless or workless and disease can become fatal if not treated. Old drugs used for treatment have many side effects and some are responsible for death in 5% of the patients. The parasite possesses a major surface protein known as variant surface glycoprotein. The immune system of the host develops antibodies against this antigen but due to antigenic variation, parasites evade the immune response. Currently, no vaccine is available that provides complete protection. Only partial protection using certain antigens in murine models was investigated. The tools of molecular biology and immunology have enabled a novel approach to the development of vaccines against trypanosomes. Immunization is the sole method for the control of disease because the eradication of the vector from endemic areas is an impossible task. Genetic vaccines can carry multiple genes encoding different antigens of the same parasite or different parasites. DNA immunization induces the activation of both cellular immune response and humoral immune response along with the generation of memory. This review highlights the importance of DNA vaccines and advances in the development of DNA vaccines against T. brucei.

Background: Understanding factors associated with protective immunity against emerging viral infections is crucial for global health. Pakistan reported its first COVID-19 case on February 26, 2020, but compared to other countries, it experienced relatively low COVID-19-related morbidity and mortality between 2020 and 2022. The underlying reasons remain unclear. Our research aims to shed light on this crucial issue. Methods: We conducted serial household surveys over 16 months (Rounds 1-4, July 2020 - November 2021) in urban (Karachi) and rural (Matiari) Sindh, sampling 1100 households and 3900 individuals. Our comprehensive approach included measuring antibodies in sera, testing a subset of respiratory samples for COVID-19 using RT-PCR and antigen tests, and measuring Hemoglobin, CRP, Vitamin D, and zinc in Round 1. Results Participants showed 23% (95% CI 21.9-24.5) antibody seroprevalence in round 1, increasing across rounds to 29% (95% CI 27.4-30.6), 49% (95% CI 47.2-50.9) and 79% (95% CI 77.4-80.8). Urban residents had 2.6 times (95% CI 1.9-3.6) higher odds of seropositivity than rural residents. Seropositivity did not differ between genders. Individuals aged 20-49 had 7.5 (95% CI 4.6-12.4) times higher odds of seropositivity compared to children aged 0-4. Most participants were asymptomatic, with no reported mortality. Vitamin D deficiency was linked to seroprevalence. COVID-19 was confirmed in 1.8% of individuals via RT-PCR and antigen tests. Conclusions: The data suggests a steady increase in humoral immunity in Pakistan, likely due to increased transmission and potential cross-protective immunity, which may be associated with asymptomatic disease, leading to the reduction of morbidity and mortality observed.

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

An in-silico WES approach using the Galaxy platform was adopted in the current study to predict the genetic basis of Premature Ovarian Failure (POF), where three affected patients in a Saudi Arabian family of seven, found associated with X-linked recessive mutations. The current analysis discovered 518,054 variants using FreeBayes variant caller that had 1,461,864 effects on variable sites in the genome revealed by SnpEff software. The causal genetic mutations were filtered and annotated with the ClinVar database using the GEMINI tool. This tool retained 369 pathogenic mutations harboring 130 genes. Among the total, 268 variants positioned on 69 genes are shared with three affected individuals, 61 variants on 23 genes are shared by any two of the affected individuals, and 40 of the variants on 38 genes are present in any one of the affected sample. Two mutations in one of the already POF-associated, POF1B gene were also observed e.g. (i) g.84563135T>A; p.M349L and (ii) g.84563194C>T; p.R329Q in the two affected individuals i.e. IV-I-C & IV-6 in the current data. This gene consists of 17 exons that span the region of >100 kb. The putative function of this gene in regulating the actin cytoskeleton due to homology with myosin tail and maintains a number of oocytes during fetal ovary development. In a nutshell, this Galaxy pipeline facilitates all-in-one to pinpoint not only the known pathogenic gene mutations for this disorder but few other novel genetic variants as well, whose gene-disease association may be validated by further experimental studies.

Mitochondrial Encephalohepatopathy (MEH) is an autosomal recessive neurodevelopmental disorder usually accompanied by microcephaly, white matter changes, cardiac and hepatic failure. Here, we applied the whole-exome sequencing (WES) framework on a trio family data with unaffected non-consanguineous parents and proband (neonate girl) with this inherited disorder. A total of 2,928,402 variants were observed with 2,613,746 SNPs, 112,336 multiple nucleotide polymorphisms (MNPs), 72,610 insertions, 113,207 deletions and 16,503 mixed variants. These variations are responsible for 82,813,631 effects on various genomic regions. Our pipeline uncovered candidate gene mutations from these variants and retained a handful of 5,277 variants harboring 3,598 genes, out of which, 8 genes codes for non-coding RNA while 178 genes are those with high impact severity. Among these 178 variants, 125 are de-novo variants that are not previously reported in the ClinVar database. Consistent to previous studies, the leftover high impact severity genes are involved in encephalopathy, Leigh syndrome, Charcot–Marie–Tooth disease, global developmental disorder, seizures, spastic paraplegia, premature ovarian failure, mitochondrial myopathy-cerebellar, ataxia-pigmentary, retinopathy syndrome, ocular and retinal degeneration, deafness, intellectual disability, cardiofacioneurodevelopmental syndrome etc. All these clinical features were also observed in the patient studied. The current analysis highlights and expands the genetic architecture of the MEH phenotype. Furthermore, this pipeline on trio family data significantly broadens the concept of its usefulness as a first-tier diagnostic method in the detection of complex multisystem phenotypic disorders.

Different materials prepared by appropriate synthesis methods and applying different post syn-thesis processes could be used as hole transport layer in perovskite solar cells. In the present work annealing was employed to enhance physical properties of copper oxide (CuO) thin films fabricated via spin coating technique and the effects of annealing on their optical, morphological, electrical and structural properties were investigated. The XRD findings revealed the polycrystalline structure with large crystallite size. Optical spectra showed larger transmission beyond the visible region, reduced absorption, and a decrease in bandgap energy from 1.93 eV to 1.81 eV. The Ag phonon modes at 299.22 and 304 cm-1 shown by the Raman shift confirmed the development of the CuO pure phase. FTIR spectra showed the Cu-O stretching band at 759, 764 and 446 cm−1. SEM revealed the agglomeration of nano crystallites with large grains on the surface. The carrier type conductivity of annealed CuO thin films was determined via two-point hot probe technique. Low resistivity values were determined via four-point probe method. These findings indicate that CuO thin films may be successfully used as a companion with an n-type layer in p-n junction solar cells, and a hole transport layer in perovskite solar cells.

In Pakistan, 2018 National Nutrition Survey reported 40% of under five children were stunted. This study assesses the effectiveness of nutritional supplementation in reducing stunting among under-five children in two rural districts in Sindh, Pakistan. This was a mixed-method quasi-experimental study with intervention and control population. 3397 and 3277 under-five children participated in the baseline and end-line surveys. Both study areas were matched for demographic and economic circumstances. The participants received nutrient supplements underpinned by nutrition behaviour change communication for appropriate complementary feeding practices and hand hygiene targeted at primary caregivers during the first 1000 days of an infant's life. The impact was assessed using the difference in difference analysis with kernel propensity score matching to adjust the differences among control and intervention populations.

Brazil, Russia, China, India, and the Republic of South Africa (BRICS) represent developing economies facing different energy and economic development challenges. The current study aims to forecast energy consumption in BRICS at aggregate and disaggregate levels using the annual time series data set from 1992 to 2019 and to compare results obtained from a set of models. The time-series data are from the British Petroleum (BP-2019) Statistical Review of World Energy. The forecasting methodology bases on a novel Fractional-order Grey Model (FGM) with different order parameters. This study contributes to the literature by comparing the forecasting accuracy and the forecasting ability of the FGM(1,1) with traditional ones, like standard GM(1,1) and ARIMA(1,1,1) models. Also, it illustrates the view of BRICS's nexus of energy consumption at aggregate and disaggregates levels using the latest available data set, which will provide a reliable and broader perspective. The Diebold-Mariano test results confirmed the equal predictive ability of FGM(1,1) for a specific range of order parameters and the ARIMA(1,1,1) model and the usefulness of both approaches for energy consumption efficient forecasting.

The mutation databases have vital importance in detecting genetic mutation and their corresponding phenotypes. The emergence of next generation sequencing genetic technologies has accelerated this process, and the growth of genetic disease identification has created a need for quality control and documentation of mutation-related information. Ethnic-specific mutation databases offer valuable information for researchers, and the article evaluates the homogeneity and effectiveness of these databases. The aim to raise awareness of NEMDBs to healthcare professionals, the general public, and researchers studying genetic disorders. The article also recommendations to improve the effectiveness of these databases.

Keeping in mind the increasing trend and need for serious games in science education, we have done a systematic literature review. These papers show the trends and patterns of research carried out in this field from the year 2011 to 2020. Specifically, we investigated country-wise concentration and the most common evaluation methods. Literature is reviewed from IEEEexplore, Springer, and Scopus. Moreover, we discussed the role of Augmented Reality(AR) games in teaching physics. Lastly, we have discussed the positive and negative aspects of serious games in science education in particular, and the trend of using serious games in the past decade in education in general.

The goal of the next generation World Wide Web is machine readability through linked databases. To improve web search, integration, and mining in local languages like Urdu, there is a growing need to develop ontologies and vocabulary in these languages. The majority of people use the web in local languages for agriculture, social media interaction, news, etc. How to create agents for the integration of web data. In our country, the literacy ratio is very low and IT literacy is negligible. More comprehensive information for its target audience is only possible through the World Wide Web. Our first target is to improve and enhance the use of social media and the web in local languages. That will encourage its constructive use in Urdu for society and the economy. The Web in natural languages is the source of income for small and medium enterprises. The semantic web is concerned with linked databases and structured data. In this work, we are focused on some selected ontologies to be translated into natural languages. Expertise in Ontology Engineering helps us in job production. Ontology Engineering has extensive freelancing opportunities. Only if the web is correctly interpreted in regional languages is an economic boost achievable. A standardized foundation for data sharing and reuse on the internet is provided by the Semantic Web. In other words, a group of standards and technology that enables computers to comprehend the semantics (meaning) of material on the Web.

Inspired by the definition of degenerate multi-poly-Genocchi polynomials given by using the degenerate multi-polyexponential functions. In this paper, we consider a class of new generating function for the degenerate multi-poly-Bernoulli polynomials, called the type 2 degenerate multi-poly-Bernoulli polynomials by means of the degenerate multiple polyexponential functions. Then, we investigate their some properties and relations. We show that the type 2 degenerate multi-poly-Bernoulli polynomials equals a linear combination of the weighted degenerate Bernoulli polynomials and Stirling numbers of the first kind. Moreover, we provide an addition formula and a derivative formula. Furthermore, in a special case, we acquire a correlation between the type 2 degenerate multi-poly-Bernoulli numbers and degenerate Whitney numbers.

In this paper, we introduce a new class of Laguerre-based Hermite-Fubini numbers and polynomials and investigate some properties of these polynomials. We establish summation formulas of these polynomials by summation techniques series. Furthermore, we derive symmetric identities of Laguerre-based Hermite-Fubini numbers and polynomials by using generating functions.

In this paper, we introduce a new class of degenerate Hermite-Fubini numbers and polynomials and investigate some properties of these polynomials. We establish summation formulas of these polynomials by summation techniques series. Furthermore, we derive symmetric identities of degenerate Hermite-Fubini numbers and polynomials by using generating functions.

Type 2 diabetes mellitus (T2DM) is a global health concern driven by factors such as obesity, sedentary behavior, and poor diet. This study uses data from the 2017-18 Bangladesh Demographic and Health Survey (BDHS) to analyze regional and individual predictors of diabetes and predi-abetes. Employing a Bayesian multinomial mixed-effects model, we account for regional varia-bility and individual factors like age, gender, BMI, residence, wealth, education, employment, and hypertension. Our results indicate significant regional differences and associations between de-mographic and health-related factors with diabetes risk. Younger individuals and those with higher BMI are more likely to be diabetic, while hypertension significantly increases diabetes risk. We applied machine learning (ML) models, including logistic regression, decision trees, k-nearest neighbor, linear discriminant analysis, and random forest, to classify diabetic status using these predictors, assessing their accuracy through 10-fold cross-validation. Logistic regression and linear discriminant analysis demonstrated robust performance across various response distributions. Simulation studies further examined the impact of different response distributions on model performance, revealing significant differences in classification accuracies. This approach of esti-mating parameters with a Bayesian model, applying ML for prediction, and conducting simulation studies to explore various scenarios highlights the importance of integrating these methodologies for effective diabetes prediction, providing insights for public health strategies to mitigate T2DM's impact.

The current study emphasizes on optimizing a suitable ratio of enzymatically hydrolyzed potato powder (EHPP) and whole milk powder (WMP) to produce a quality yogurt by evaluating the physicochemical and rheological properties. The results showed that the addition of EHPP decreased the pH towards acidic conditions which resulted in the high acidity of yoghurt. The proximate composition showed that EHPP increased the ash, protein, water holding capacity (WHC) while fat, synersis, color parameters and total solid were decreased when compared to control yoghurt (CY) sample. Moreover, texture profile (TPA) analysis showed that the addition of EHPP decreased the hardness and cohesiveness while springiness did not show significant difference. Furthermore, rheological properties revealed that EHPP decreased the storage modulus (G’) and loss modulus (G”) when compared with control. In addition to this, sensory analysis revealed that the treatment P4M (1:3) was found as optimum ratio regarding taste, flavor, and aroma. Besides this, scanning electron microscopy (SEM) confirms that the high amount of EHPP resulted in the void holes while CY showed dense gel structure. The prepared yogurt with EHPP provides an excellent flavor, satisfying sweetness and homogeneous texture. These findings suggest the optimum formulation ratio of prepared yogurt was found to be P4M (1:3) for desirable attributes and consumer acceptance. The prepared yogurt from the EHPP presents the potential industrial applications.

Whole genome pooled sequence data of 12 Pakistani Teddy goats is analyzed for positive selection signatures as their breed defining characteristics. Selection imprints left in the Teddy genome are unveiled by genomic differentiation after the successful paired-end alignment of 635,357,043 reads with (ARS1) reference genome assembly. Pooled-heterozygosity ( ) and Tajima’s D (TD) are applied for validation and getting better hits of selection signals, while pairwise F_ST statistics is conducted on Teddy vs. Bezoar (wild goat ancestor) for genomic differentiation. Annotation of regions under positive selection reveals 59 genes underlying production and adaptive traits. score ≥ 5 detected six windows having highest scores on Chr. 29, 9, 25, 15 and 14 that harbor HRASLS5, LACE1 and AXIN1 genes which are candidate for embryonic development, lactation and body height. Secondly, TD value of ≤ -2.2 showed 4 windows with very strong hits on Chr.5 & 9 harbor STIM1 and ADM genes related to body mass and weight. Lastly, F_ST analysis generated three strong signals with threshold ≤ 0.42 on Chr.12 & 5 harbor ITGB1 gene associated with milk production & lactation traits. Other significant selection signatures encompass genes associated with wool production, prolificacy, immunity and coat colors. In brief, this study identified the genes under selection in this Pakistani goat breed that will be helpful to refining future breeding policies and converging required productive traits within and across other goat breeds and to explore full genetic potential of this valued livestock species.

Antibiotic resistance (ABR) is an emerging global threat to public health. Substantial evidence has indicated that community pharmacists (CPs) can play a critical role in managing the ever-increasing threat of antibiotic resistance. The study aimed to determine the knowledge, attitude, and practices of CPs (n=180) towards antibiotics and antibiotic resistance as well as to improve the rational use of antibiotics. Two phases of mixed methods (quantitative and qualitative) online study were conducted in Pakistan from August 2019 to March 2020 by using validated questionnaires and semi-structured interview data. Different statistical methods were used to tabulate the quantitative data whereas inductive thematic analysis was conducted to categorize themes from the qualitative data and draw conclusions. Approximately 64.4% were male (mean: 29-33 years old). Overall, CPs had good knowledge of and were familiar with superbugs and their roles in ABR (65.6%, Median=1, IQR=1) although they were poor in differentiating some antibiotic groups with their respective ABR patterns (31.1%, Median=1, IQR=1). Most CPs have a positive attitude towards antibiotics with most (90.0%) having identified ABR as a critical issue in public health (Median=1, IQR=0). Overall, CPs' practices towards antibiotics were reasonable where they tend to educate patients about the rational use of antibiotics (52.8%, Median=1, IQR=1). Two main themes (antibiotics and counseling of patients) were related to self-medication with while educational interventions are the sub-theme. ABR is multifactorial where the subthemes related to budget, time constraints incompetent staff, the absence of CPs, the lack of training, enforcement of laws and regulations are the need of the hour in Pakistan. Effective antibiotic stewardship programs, patient education, and awareness campaigns about antibiotics and ABR along with training of the CPs are important factors that have to be addressed in a timely manner.

Extensive polymorphism screening of elacestrant dihydrochloride, an Active Pharmaceutical Ingredient (API), was conducted using various methods and solvents. The solubility assessment and polymorph screening of elacestrant dihydrochloride (referred to as elacestrant throughout the paper) utilized both crystalline and amorphous forms of the API as input material with 40 non-conventional solvents, employing slow cooling, maturation, and/or evaporation. Crystalline material underwent further screening via anti-solvent addition, polymer templating, and solvent-drop grinding. A total of 7 new polymorphs were identified. No solvated forms were identified, but some samples contained notable water content, tentatively classified as hydrated forms. Comprehensive solid-state characterization data for representative crystalline samples of each polymorph is presented. Polymorph A exhibited the highest melt (225-226 °C, onset). Thermal analysis of polymorphs B, C, D, E, F and G showed an endothermic-exothermic event (with an onset temperature between 136 and 184 °C), indicating a form conversion, followed by a melt at 205-222 °C (onset), consistent with the previously identified and most stable form of elacestrant. This suggests that these materials convert to the most stable form prior to melting. Pattern G does not show an endothermic-exothermic event, but after desolvation, the material melts at 222 °C (onset temperature).

Our environment has been significantly impacted by man-made pollutants, primarily due to industries make substantial use of synthetic chemicals, resulting in significant environmental consequences. In this research investigation, the co-precipitation approach was employed for the synthesis of cellulose-based ferric oxide (Fe₂O₃/cellulose) and copper oxide nanoparticles (CuOx-NPs). Scanning electron microscopy (SEM) analyses were conducted to determine the properties of the newly synthesised nanoparticles. Furthermore, the synthesized nanoparticles were employed for eliminating chromium from aqueous media under various conditions, including temperature, contact time, adsorbent concentration, adsorbate concentration, and pH. Additionally, the synthesised materials were used to recover Cr(VI) ions from real samples, including tap water, seawater, and industrial water, and the adsorptive capacity of both materials evaluated under optimal conditions. The synthesis of Fe₂O₃/cellulose and CuOx-NPs proved to be effective, as indicated by the outcomes of the study.

The need for cohesive detection and defence methods against cyberattacks is significant now more than ever before to enforce security and privacy of user data and information. The inevitable increase in demand for home and flexible working from employees quite recently has meant there is a lack of awareness and training for cyberattacks. Hence, they have become prominent as attackers are aware of this and are benefitting from individuals’ lack of knowledge in how to better protect themselves and their confidential information. Employees are becoming more susceptible to such attacks and falling victim to these, resulting in economic losses for companies, data losses and decreased faith.

Pakistan is an important country located in South Asia and ranks the world's sixth most populous country. It has diverse landscapes with their own specific vegetation. The country specific vegetative diversity has a great ecological and economic impact on the conservation of local fauna. It has huge potential for sustainable beekeeping industry if properly exploited. Beekeeping in Pakistan is mainly focused in Khyber Pakhtunkhwa and central and north regions of Punjab provinces but nowadays it is growing rapidly across the country. Honey produced in Pakistan enjoys good repute in the Middle East due to its unique taste and quality. Pakistan exports around 4000 tons of the honey with the worth of about $ 23.00 million to Arab countries every year.

Motivated by Kim-Kim [19] introduced the new type of degenerate poly- Bernoulli polynomials by means of the degenerate polylogarithm function. In this paper, we define the degenerate poly-Frobenius-Euler polynomials, called the new type of degenerate poly-Frobenius-Euler polynomials, by means of the degenerate polylogarithm function. Then, we derive explicit expressions and some identities of those numbers and polynomials.

In this paper, we introduce a new type of degenerate poly-Fubini polynomials and numbers, are called degenerate poly-Fubini polynomials and numbers, by using the degenerate polylogarithm function and derive several properties on the degenerate poly-Fubini polynomials and numbers. In the last section, we also consider the degenerate unipoly-Fubini polynomials attached to an arithmetic function, by using the degenerate polylogarithm function and investigate some identities of those polynomials. In particular, we give some new explicit expressions and identities of degenerate unipoly polynomials related to special numbers and polynomials.

In this paper, we construct the degenerate poly-Fubini polynomials, called the type 2 degenerate poly-Fubini polynomials, by using the modified degenerate polyexponential function and derive several properties on the degenerate poly-Fubini polynomials and numbers. In the last section, we introduce type 2 degenerate unipoly- Fubini polynomials attached to an arithmetic function, by using the modified degenerate polyexponential function and investigate some identities for those polynomials. Furthermore, we give some new explicit expressions and identities of degenerate unipoly polynomials related to special numbers and polynomials.

A reliable and affordable energy supply is a fundamental prerequisite for reducing poverty, promoting investment, and boosting economic growth in the developing world. Among the different challenges that developing countries face, chronic energy crises are harrowing. The crises result from the unsatisfactory state of the central grid, a misguided energy mix, and ill-informed policies, among other things. The possibility of solving energy crises through a variety of alternative solutions is worth exploring. This review discusses two paths of energy development side by side: a traditional “hard” path of energy development (i.e., central grid extension powered by fossil fuels and nuclear energy expansion) and a relatively recent “soft” path of energy development, which is based on energy conservation and the deployment of renewable energy resources. This paper focuses on one central axis of the discussion: centralization vs. decentralization. This discussion, in turn, has technological, economic/business, and political dimensions. Finally, the paper discusses the significance of the debate from meeting the developing world’s energy demands. The paper intends not to prefer one or another path of energy development, nor it gives recommendations on diffusing or adopting those development paths. Instead, it explores the literature’s central arguments that might help frame the questions for further research. While this debate could be used to ask interesting questions that might help solve the energy crisis in the developing world, the discussion informs countries to advance policies specific to their circumstances under the umbrella of a sound and thoughtful energy productivity policy framework.

Generic object detection is one of the most important and flourishing branches of computer vision and has real-life applications in our day to day life. With the exponential development of deep learning-based techniques for object detection, the performance has enhanced considerably over the last 2 decades. However, due to the data-hungry nature of deep models, they don't perform well on tasks which have very limited labeled dataset available. To handle this problem, we proposed a transfer learning-based deep learning approach for detecting multiple pigs in the indoor farm setting. The approach is based on YOLO-v2 and the initial parameters are used as the optimal starting values for train-ing the network. Compared to the original YOLO-v2, we transformed the detector to detect only one class of objects i.e. pigs and the back-ground. For training the network, the farm-specific data is annotated with the bounding boxes enclosing pigs in the top view. Experiments are performed on a different configuration of the pen in the farm and convincing results have been achieved while using a few hundred annotated frames for fine-tuning the network.

Animal behavior analysis is a crucial tasks for the industrial farming. In an indoor farm setting, extracting Key joints of animal is essential for tracking the animal for longer period of time. In this paper, we proposed a deep network that exploit transfer learning to trained the network for the pig skeleton extraction in an end to end fashion. The backbone of the architecture is based on hourglass stacked dense-net. In order to train the network, key frames are selected from the test data using K-mean sampler. In total, 9 Keypoints are annotated that gives a brief detailed behavior analysis in the farm setting. Extensive experiments are conducted and the quantitative results show that the network has the potential of increasing the tracking performance by a substantial margin.

Motivation by the definition of the type 2 poly-Bernoulli polynomials introduced by Kim-Kim [9], in the present paper, we consider a new class of new generating function for the Fubini polynomials, called the type 2 poly-Fubini polynomials by means of the polyexponential function. Then, we derive some useful relations and properties. We show that the type 2 poly-Fubini polynomials equal a linear combination of the classical of the Fubini polynomials and Stirling numbers of the first kind. In a special case, we give a relation between the type 2 poly-Fubini polynomials and Bernoulli polynomials of order r. Moreover, inspired by the definition of the unipoly-Bernoulli polynomials introduced by Kim-Kim [9]. We introduce the type 2 unipoly-Fubini polynomials by means of unipoly function and give multifarious properties including derivative and integral properties. Furthermore, we provide a correlation between the unipoly-Fubini polynomials and the classical Fubini polynomials.

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

Kim-Kim [12] introduced the new type of degenerate Bernoulli numbers and polynomials arising from the degenerate logarithm function. In this paper, we introduce a new type of degenerate poly-Euler polynomials and numbers, are called degenerate poly-Euler polynomials and numbers, by using the degenerate polylogarithm function and derive several properties on the degenerate poly-Euler polynomials and numbers. In the last section, we also consider the degenerate unipoly-Euler polynomials attached to an arithmetic function, by using the degenerate polylogarithm function and investigate some identities of those polynomials. In particular, we give some new explicit expressions and identities of degenerate unipoly polynomials related to special numbers and polynomials.

The impact of monetary policies and their implementation by exchange rate covered the economic condition of Ghana. The social inclusion and conversion factors change the implemented policies of nations, where the real price, trade, technology, a price rate and price level of ratio take an important part of growth. The reform of the financial sector favors the free floating of the exchange rate and global trade by under the premise of flexible exchange rates. The tragedy of country growth and exchange rate toward a trajectory of growth with the growth-enhancing effect through social inclusion, conversion factors, price level ratio, exchange rate, merchant rate, export and trade services. The research study is based on secondary study and social inclusion equity indicators with public resources, building human resources and social protection for economic development has determined. The monetary policies are classified by the different evidence and trade indicators. The significant influence of growth and internal policies has affected trade and exchange rates with growth and reserve policies. The results have computed by linear regression and it proved that social inclusion and alternative conversion factors impact on the global trade and create short term binary relationship.

We analyze damage propagation modeling of turbo-engines in a data-driven approach. We investigate subspace tracking assuming a low dimensional manifold structure and a static behavior during the healthy state of the machines. Our damage propagation model is based on the deviation of the data from the static behavior and uses the notion of health index as a measure of the condition. Hence, we incorporate condition-based maintenance and estimate the remaining useful life based on the current and previous health indexes. This paper proposes an algorithm that adapts well to the dynamics of the data and underlying system, and reduces the computational complexity by utilizing the low dimensional manifold structure of the data. A significant performance improvement is demonstrated over existing methods by using the proposed algorithm on CMAPSS Turbo-engine datasets.

The main purpose of this paper is to introduce a new class of $q$-Hermite-Fubini numbers and polynomials by combining the $q$-Hermite polynomials and $q$-Fubini polynomials. By using generating functions for these numbers and polynomials, we derive some alternative summation formulas including powers of consecutive $q$-integers. Also, we establish some relationships for $q$-Hermite-Fubini polynomials associated with $q$-Bernoulli polynomials, $q$-Euler polynomials and $q$-Genocchi polynomials and $q$-Stirling numbers of the second kind.

The study is an attempt to enquire into the preference of undergraduate students, after a considerable and over a year-long experience with Online Teaching and Learning (OTL), under the emergency preventive measure of switching from the traditional face-to-face classes to online. The study followed an exploratory approach, with a quantitative survey followed by a qualitative one, and a convenient sampling method to collect responses from a substantial sample size. The study is positioned after more than a year of remote classes by the undergraduate student, and hence represents highly experienced reflections and preferences from these students, as compared to other studies conducted last year. The study has profound implications in considering, and questioning, the importance of on-campus classes, and significance of the physical presence of a tutor in the class, and its effect on the learning experience of undergraduate students.

Accurate and reliable measurement of real-world walking activity is clinically relevant, particularly for people with mobility difficulties. Insights on walking can help understand mobility function, disease progression, and fall risks. People living in long-term residential care environments have heterogeneous and often pathological walking patterns, making it difficult for conventional algorithms paired with wearable sensors to detect their walking activity. We designed two walking bout detection algorithms for people living in long-term residential care. Both algorithms used thresholds on the magnitude of acceleration from a 3-axis accelerometer on the lower back to classify data as “walking” or “non-walking”. One algorithm had generic thresholds, while the other used personalized thresholds. To validate and evaluate the algorithms, we compared the classifications of walking/non-walking from our algorithms to the real-time research assistant annotated labels and the classification from an algorithm validated on a healthy population. Both the generic and personalized algorithms had acceptable accuracy (0.83 and 0.82 respectively). The personalized algorithm showed the highest specificity (0.84) of all tested algorithms, meaning it was the best suited to determine input data for gait characteristic extraction. The developed algorithms were almost 60% quicker than the previously developed algorithms, suggesting they are adaptable for real-time processing.

This paper discusses the development process regarding a group of four Augustana College seniors' research. The project is a mobile app for Android built-in Android Studio called Augustana Health and Dining. This application will improve the dining experience at Augustana College, provide additional health metrics for personal use and promote healthier lifestyles. The app features the menus of various on-campus dining areas, with calories, allergens, and other essential food information. It also includes a profile section that will display campus meal credits and a calorie counting metric that can be used to track calories consumed to display this information to users so they can make more informed choices on their meals and health.

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

Kim-Kim [19] studied the type 2 degenerate poly-Bernoulli numbers and polynomials by using modified degenerate polylogarithm function. In this paper, we construct the type 2 degenerate poly-Cauchy polynomials and numbers of the second kind, called degenerate poly-Cauchy polynomials and numbers of the second kind by using degenerate polylogarithm function and derive several properties on the degenerate poly-Cauchy polynomials and numbers of the second kind. Furthermore, we consider the degenerate unipoly-Cauchy polynomials of the second kind and discuss some properties of them.

It shows the monetary investigation in west countries the big flow in economy by the gross value change effects, also the value of debt policy with debt management strategies to control the budgetary risk of long-term economy from sustainability. The intellectual policies of inflation, GDP, trade, and services and merchandise trade has effected on the West African country’s monetary policies. The implication of trade by a lag of exchange rate indicators has a positive and significant effect. The estimated results reflect the dynamic implication of trade with liquidity and proper monitoring policies. The GDP, gross value (GVA), debt policies, equity of public administration, trade in service and merchandise trade is positive and significant, all are significant. We suggest the optimum control of liquidity with trade service policy recommendations in different countries. The research method was based on 5 countries from the 16 countries of western African and elaborated by their individual indicators with the least square method. The gross value of debts and public administration controlled the development aim of an entire state with strategic and planned environment for state and reduce the level of inflation in small and enterprise section and the results analyzed the policy makers implement planned in implication of trade with domestic currency and long run endogeneity. The results analyzed the monetary policies affecting the level of growth of an individual country.

Kim-Kim [20] studied the type 2 degenerate poly-Bernoulli numbers and polynomials by using modified degenerate polylogarithm function. In this paper, we construct the new type of degenerate poly-Cauchy polynomials and numbers of the second kind, called the new type of degenerate poly-Cauchy polynomials and numbers of the second kind by using degenerate polylogarithm function and derive several properties on the degenerate poly-Cauchy polynomials and numbers of the second kind. Furthermore, we consider the degenerate unipoly-Cauchy polynomials of the second kind and discuss some properties of them.

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

In this paper, we introduce a new class of $(p,q)$-analogue type of Fubini numbers and polynomials and investigate some properties of these polynomials. We establish summation formulas of these polynomials by summation techniques series. Furthermore, we consider some relationships for $(p,q)$-Fubini polynomials associated with $(p,q)$-Bernoulli polynomials, $(p,q)$-Euler polynomials and $(p,q)$-Genocchi polynomials and $(p,q)$-Stirling numbers of the second kind.

Cardiac amyloidosis is caused by amyloid fibrils that deposit in the myocardial interstitium, causing restrictive cardiomyopathy and eventually death. The electromechanical, inflammatory, and autonomic changes due to amyloid deposition result in arrhythmias. Atrial fibrillation is by far the most common arrhythmia. Rate control strategy is generally poorly tolerated due to restrictive filling physiology and heart rate dependance, favoring adoption of rhythm control strategy. Anticoagulation for stroke prophylaxis is warranted irrespective of CHA2DS2Vasc score in patients with favorable bleeding profile; data on left appendage closure devices is still insufficient. Ventricular arrhythmias are also not uncommon and the role of implantable cardioverter-defibrillator in cardiac amyloidosis is controversial. There is no evidence of improvement in outcomes when used for primary prevention in these patients. Bradyarrhythmia is most commonly associated with sudden cardiac death in cardiac amyloidosis. Pacemaker implantation can help provide symptomatic relief but does not confer mortality benefit.

Computation of Discrete Fourier Transform (DFT) is a challenging task. Especially, on computational machines/embedded systems where resources are limited. The importance of Fourier Transform (FT) cannot be denied in the field of signal processing. This paper proposes a technique that can compute Discrete Fourier Transforms for a matrice or vector with the help of matrix multiplication. Moreover, this paper discusses the trivial methods used for computation of DFT along with methods based on matrix multiplication used to compute discrete Fourier Transform in addition to the shortcomings. The proposed method can help in the calculation of a Discrete Fourier Transformation matrix by truncation of values from the proposed generic method which can help in computing DFT of varying lengths of vectors. On legacy computing machines and programming environments, having support for matrix multiplication, the proposed methodology can be implemented.

7β-(3-ethyl-cis-crotonoyloxy)-1α-(2-methylbutyryloxy)-3,14-dehydro-Z-notonipetranone (ECN), a sesquiterpenoid obtained from a natural origin (Tussilago farfara)has proved to be effective in minimizing various side effects associated with opioids and nonsteroidal anti-inflammatory drugs. The current study focused on investigating the effects of ECN on neuropathic pain induced by partial sciatic nerve ligation (PSNL) by mainly focusing on oxidative stress, inflammatory and apoptotic proteins expression in mice. Neuropathic pain was induced in mice by PSNL surgery performed on day 1 and ECN (1 and 10 mg/kg, i.p.), was administered once daily for 11 days, starting from the third day after surgery. ECN post-treatment was found to reduce hyperalgesia and allodynia in a dose dependent manner. ECN significantly reversed the severity of neuropathic pain by improving distress symptoms and survival rate. ECN remarkably reversed the histopathological abnormalities associated with oxidative stress, apoptosis and inflammation. Furthermore, ECN prevented the suppression of antioxidants (glutathione, glutathione-S-transferase, catalase, superoxide dismutase, NF-E2-related factor-2 (Nrf2), hemeoxygenase-1 and NAD(P)H: quinone oxidoreductase) by PSNL. Moreover, pro-inflammatory cytokines (tumor necrotic factor alpha, interleukin 1 beta, interleukin 6, cyclooxygenase-2 and inducible nitric oxide synthase) expression was reduced by ECN administration. Treatment with ECN was successful in reducing caspase-3 level consistent with the observed modulation of pro-apoptotic proteins. Additionally, ECN showed protective effect on the lipid content of myelin sheath as evident from FTIR spectroscopy which showed the shift of lipid component bands to higher values. Thus, anti-neuropathic potential of ECN might be due to inhibition of oxidative stress, inflammatory mediators and pro-apoptotic proteins.

The most important plastic resins used for wire coating are Polyvinyl Chloride (PVC), Nylon, Polysulfone and Low-high density polyethylene (LDPE / HDPE). In this article,the coating process is performed using elastic-viscous fluid as a coating material for wire coating in a pressure type coating die. The elastic-viscous fluid is electrically conducted in the presence of an applied magnetic field. The governing non-linear equations are modeled and then solved analytically by utilizing an Adomian decomposition method (ADM). The convergence of the series solution is established. The results are also verified by Optimal Homotopy Asymptotic Method (OHAM). The effect of different emerging parameters such as non-Newtonian parameters α and β, magnetic parameter M and the Brinkman number Br on solutions (velocity and temperature profiles) are discussed through several graphs. Additionally, the current result also compares with the published work already available in the literature.

The brick manufacturing sector in Bangladesh is experiencing rapid growth, leading to notable environmental and health concerns. The primary objective of this research is to examine the Savar Upazila, a region of significant economic significance owing to its favorable brick manufacturing conditions and proximity to Dhaka city. Brick kilns, among other sources, constitute significant contributors to air pollution. The study utilized primary and secondary data to examine brick kiln emissions' effects on the surrounding area's environment and public health. The collection of primary data was conducted in multiple zones within Savar Upazila, which is home to a significant number of brick kilns. The utilization of secondary data provided valuable insights regarding the toxic pollutants discharged by these kilns and the corresponding health risks they pose. The participants provided accounts of various health ailments, such as dermatological conditions, optical difficulty, and respiratory complications, further aggravated by brick kilns' incidents. The prevalence of crop losses, soil degradation, and reduced agricultural yields was confirmed by 74% of the respondents. The trees and crops in the surrounding area experienced adverse effects due to the deposition of dust particles. During periods of inactivity, the concentrations of sulfur oxide (SOx) were between 6 and 9 times lower compared to periods of operation. Similarly, nitrogen oxide (NOx) levels were observed to be 4 to 6 times lower during non-operational phases. The degradation of water quality in adjacent bodies has been attributed to the deposition of dust and ash originating from brickfields, resulting in substantial repercussions on aquaculture. A significant proportion of participants indicated experiencing diverse health issues, notwithstanding the employment prospects generated by brick kilns, thereby underscoring the adverse consequences on both the environment and the local economy.

Asthma causes chronic coughing, wheezing, dyspnea, and chest pressure. This study assessed asthmatic patients' knowledge, attitudes and awareness of bronchial asthma and proper education on its meaning, risk factors, symptoms, diagnosis, management, and prevention practice. We performed a cross-sectional interventional asthma KAP survey in Erbil, Iraq. We adapted a validated study questionnaire from KAP studies in other nations to the Erbil situation and culture. In Erbil, Kurdistan, Iraq, two major hospitals' asthma clinics were studied. We chose 250 asthmatic ICU patients from October 2018 to July 2019. Health education was comprehensive. The health education program used a Kurdish PowerPoint with a printout. 25 groups got two-weeks of one-hour health education pre-intervention. Each group was questioned before, 2 and 12 weeks after health education. All data were analyzed by SPSS v26. The mean age of the respondent was 37.52±15.16 with 48.7 % respondent having a positive family history of asthma. After 2weeks of health education intervention, respondent have a higher knowledge score, positive attitudes compared to pre-education and after 12 weeks of education with a significant difference (P < 0.001) with improvised prevention practice. Health education programs led to considerable improvements in asthmatic patients' knowledge, attitudes, and practices regarding their condition. After receiving health education for a period of two weeks, the majority of the participants answered correctly regarding asthma, its causes, and the elements that trigger asthma attacks.

Migraine is a neurological disorder characterized by severe disabling headaches with a substantial global burden and elevated morbidity rates. Extensive research has established a clear association between migraine and sex/gender, with a notably higher incidence reported in females, reaching up to 18%, which is three times greater compared to males. Additionally, women commonly experience more intense pain and greater frequency of migraine symptoms, both with and without aura, highlighting the differential impact of sex/gender on migraine presentation. This review comprehensively examines the pathophysiology of migraine, with a particular focus on the effects of sex hormones in migraine pathophysiology and the central nervous system. Furthermore, we explore various treatment modalities tailored to gender differences, including pharmacological interventions and emerging therapeutic approaches. Furthermore, we explored alternative treatment strategies such as nutraceuticals and behavioural techniques, including mindfulness and cognitive behavioural therapy. This review aims to provide a comprehensive overview of the multifaceted nature of migraine and the diverse therapeutic approaches available for their management.

The paper presents a thorough examination of the burgeoning field of utilizing manufacturing waste for sustainable energy generation, aligning with the global imperative for resource efficiency and clean energy solutions. With the manufacturing sector being a significant contributor to waste generation, this study explores innovative approaches to transform waste materials into valuable resources, thereby mitigating environmental impacts and contributing to a circular economy. This work critically reviews current trends, emphasizing technological advancements, policy interventions, and market dynamics shaping the manufacturing waste utilization landscape. Noteworthy developments, such as advanced sorting technologies and the integration of digital solutions, are discussed in detail, showcasing their role in enhancing the efficiency of waste management processes. The study outlines future trends in the field, anticipating a shift towards closed-loop systems guided by circular economy principles. This comprehensive review aims to contribute to the discourse on sustainable waste management and energy generation by providing a holistic perspective on the field's current state and offering insights into the future trajectories that will propel manufacturing waste toward a more sustainable and circular future. The synthesis of technological innovation, collaborative efforts, and evolving regulatory frameworks presents a compelling case for the continued exploration of manufacturing waste as a valuable resource in the pursuit of a more sustainable and energy-efficient world.

Microplastics, which are plastic particles smaller than 5 mm in size, are a growing environmental concern since they have been found in oceans, rivers, lakes, and even on land. These tiny particles can escape water filtration systems and end up in water bodies as well as through the degradation of the larger plastic products causing serious environmental and food safety concerns. This research represents the magnitude of this pollution, characterization of microplastic contamination, its type of polymer, and possible sources of this pollution in the rivers around Dhaka, Bangladesh. Quantitative analyses were done following the method suggested by the NOAA and other conventional methods. Among the rivers, Buriganga has the highest microplastic pollution with 3.654 items/L in surface water and 43.125 items/kg in sediment. The concentration in Shitalakshya and Turag rivers are 3.011 items/L and 2.051 items/L in surface water and 34.875 and 17.875 items/kg in sediment respectively. ANOVA test revealed a significant difference between the concentration level of microplastic in the surface water of the Burigana and Turag rivers. A positive correlation between the concentration level of microplastic in the surface water and the sediment was also found. On average 58% of the microplastics were found to be fibrous in surface water. Qualitative analyses were done to find the characteristics and chemical composition of the microplastics. Through the use of FTIR spectroscopy, the study identified different kinds of synthetic polymers in the sample including polyamide (Nylon), polyethylene (PE), polystyrene (PS), polypropylene (PP), polyethersulfone (PES), polyvinyl chloride (PVC), and polyethylene terephthalate (PET) and polyethylene were the most abundant polymer in the samples. This study involved the investigation of three distinct rivers located in the vicinity of Dhaka city

Thai basil is a renowned medicinal plant and a rich source of bioactive antioxidant compounds having several health benefits, with actions to prevent of cancer, diabetes and cardiovascular disease. Plant cell and tissue culture technologies can be routinely established as an important, sustainable and low-cost biomass source for the production of high-value phytochemicals. The current study aimed at developing an effective protocol for the production of Thai basil leaf derived callus cultures with sustainable and high production of biomass and antioxidants as an alternative of leaves production. MS basal medium with various concentrations of plant growth regulators (PGRs) compatible with nutraceutical applications (i.e., gibberellic acid (GA3) and 6-benzylaminopurine (BAP) either alone or in combination with naphthalene acetic acid (NAA)) were evaluated. Among all tested PGRs, the combination BAP:NAA (5 mg/L:1 mg/L) yield maximum biomass accumulation (fresh weight (FW): 190 g/L and dry weight (DW): 13.05 g/L) as well as enhanced phenolic (346.08 mg/L) production. HPLC quantification analysis indicated high productions of chicoric acid (35.77 mg/g DW) and rosmarinic acid (7.35 mg/g DW) under optimized callus culture conditions. Antioxidant potential was assessed using both in vitro cell free and in vivo cellular antioxidant assays. Maximum in vitro antioxidant activity DPPH (93.2 % of radical scavenging activity) and ABTS (1322 µM Trolox equivalent antioxidant capacity) was also observed for the extracts from callus cultures grown on optimal conditions. In vivo cellular antioxidant activity assay confirmed the effective protection against oxidative stress of the corresponding extract by the maximum inhibition of ROS and RNS production. Compared to commercial leaves, callus extracts showed higher production of chicoric acid and rosmarinic acid associated with higher antioxidant capacity. In addition, this biological system also has a large capacity for continuous biomass production, thus demonstrating its high potential for possible nutraceutical applications.

Zinc nanoparticles (ZnNPs) open new opportunities for biomedical applications as a strategy against microbes and dye removal in an efficient way. The composite ZnNPs using Rhododendron arboreum (R. arboreum) stem bark were synthesized and characterized for UV-visible spectroscopy (UV-vis), Fourier transform infrared spectroscopy (FTIR), energy dispersive X-ray spectroscopy (EDX), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The synthesized nanoparticles showed zones of inhibition of 23±0.09, 18±0.1 and 16±0.05 mm, against the Klebsiella pneumoniae (K. pneumoniae), Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli strains. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values against K. pneumoniae, S. aureus, and E. coli were found to be 34±0.21 and 72.71±0.47, 47±0.11 and 94.86±0.84 and 94±0.18 and 185.43±0.16 µg/mL, respectively. The biosynthesized ZnNPs resulted in significant eradication of the outer and inner membranes of the bacterial cells. Likewise, the synthesized ZnNPs showed time-dependent photocatalytic degradation activity and revealed 65% methyl orange dye degradation with an irradiation period of 6 hours. The findings of this study suggest the suitability of the novel R. arboreum stem bark-based ZnNPs as an effective ameliorant against bactericidal activities and photocatalysts for the removal of hazardous water contaminants.

Aiming at the limitations of single-functionality, limited applicability, and complex designs prevalent in current metasurfaces, we propose a terahertz multifunctional and multiband tunable metasurface utilizing a VO2-metal hybrid structure. This metasurface structure comprises a top VO2-metal resonance layer, a middle polyimide dielectric layer, and a gold film reflective layer at the bottom. This metasurface exhibits multifunctionality, operating independently of polarization and incident angle. The varying conductivity states of the VO2 layers, enable the metasurface to achieve various terahertz functionalities, including single-band absorption, broadband THz absorption, and multiband perfect polarization conversion for linear (LP) and circularly polarized (CP) incident waves. Finally, we believe that the functional adaptability of the proposed metasurface expands the repertoire of options available for future terahertz device designs.

This panel study investigates the relationship between green logistics indices, economic, environmental, and social factors in the perspective of Asian emerging economies. This study adopted FMOLS and DOLS methods to test research hypothesis, catering the problem of endogenity and serial correlation. The results suggest that logistics operations, particularly LPI2 (efficiency of customs clearance processes), LPI4 (quality of logistics services) and LPI5 (trade and transport-related infrastructure), are positively and significantly correlated with per capita income, manufacturing value added and trade openness. While, greater logistics operations are negatively associated with social and environmental problems including, climate change, global warming, carbon emissions, and poisoning atmosphere. In addition, human health is badly affected by heavy smog, acid rainfall, and water pollution. The findings further extend and reveal that political instability, natural disaster and terrorism are also a primary cause of poor economic growth and environmental sustainability with poor trade and logistics infrastructure. Further, the application of renewable energy resources and green practices can mitigate negative effects on social and environmental sustainability without compromising the performance of economic growth. There is very limited empirical work presented in literature using renewable energy and green ideology to solve macro-level social and environmental problems, while this study will assist the policymakers and researchers to understand the importance of green concept in improving countries’ social, economic and environmental performance.

We do this research to investigate the relationship between renewable energy, public health expenditure, logistics performance indices, and economic and environmental sustainability in the ASEAN member states, through the analysis of a panel data from 2007 to 2017. The study used secondary data, which is downloaded from the World Bank Website and employs SEM (Structural Equation Modelling) model for testing hypothesis. The results show that the usage of renewable energy in logistical operations would enhance the environmental and economic performance in terms of mitigating carbon emissions and greenhouse gas emissions. While, public health expenditure and environmental performance is negatively correlated, which confirms that greater environmental sustainability with lower carbon emissions and greenhouse gases will improve human health and economic growth. Moreover, greater public health expenditure and poor environmental performance has negative effect on economic growth, inefficiency and low productivity of labor slowdown to the economic activities. For another side, the usage of renewable energy and the adoption of green practices in international logistics will develop the environmental sustainability, establish better image of a country and attract foreign direct investment inflows, and also minimize carbon emissions and public health expenditure, spurring sustainable economic growth with better export opportunities in pro-environmental countries.

Human papillomavirus (HPV) uses the cellular trafficking machinery to reach the cell nucleus and initiate a successful infection. The HPV capsid consists of two proteins: L1 (the major capsid protein) and L2 (minor capsid protein), and L2 is known to be responsible for trafficking the viral genome to the nucleus. From previous studies, we know that many cellular proteins interact with L2 and are involved in the trafficking process at different stages of the infectious entry process. To further investigate how HPV-16 achieves successful viral entry, we have performed a mass spectrometry analysis to identify novel interacting proteins that associate with incoming HPV-16 virions. We show that HPV-16 pseudovirions interact with a group of cellular cargo proteins (COPI), and here we confirm that this is mediated by the direct binding of L2, but not L1, to the COPB1 subunit. We also show that the ability of L2 to interact with COPB1 is conserved in both low- and high-risk HPV types. Furthermore, we also show that the interaction is essential for successful infection entry of multiple HPV types, thereby identifying a novel constituent of the infectious entry pathway of the HPV.

Background and objectives: The appropriate use of antibiotics is the main strategy of Antimicrobial stewardship program. This study was planned to evaluate the quality of antibiotic prescriptions, its adherence with standard guidelines and surgeons’ perception regarding antibiotic use in surgeries. Methods: A prospective cross-sectional observational and survey-based study comprised of two sections: Phase 1; to investigate the antibiotic utilization in three most common abdominal surgical procedures during 9 months (January 2017 to September 2017). The appropriateness of antibiotics was compared with evidence-based guidelines. Phase 2; the surgeon’s perspectives were evaluated through a self-administered questionnaire (13 items) during the next three months (October 2017 to December 2017). Descriptive statistics, chi-square and Fisher’s exact tests analysis were used through SPSS Statistical Package 21.0. Results: A total of 866 eligible surgical cases out of 1015 were investigated. An acute appendectomy (n= 418; 48.2%) was most common surgical intervention followed by laparoscopic cholecystectomy (n= 278; 32.1%) and inguinal hernia (n= 170; 19.7%). About 97.5% of patients received antibiotics. Among these, 9.5% adhered according to guidelines with respect to correct choice, 40% for timing, 100% for dose and route (optimal value 100%). The ceftriaxone (J01XD04; n= 503; 59.5%) was most frequently prescribed antibiotic. A 200 participants (response rate 70.6%) filled out a validated questionnaire (internal consistency; α ≥ 0.7). One hundred and thirty-eight (69%) reported the overuse of antibiotics and most of them (97%) preferred broad-spectrum antibiotics instead of narrow-spectrum. The participants reported that non-availability hospital-based guidelines (n=193; 96.5%), prescribing of antibiotics without guidelines (n=186; 93%), underestimation of infection (n=177; 88.5%), lack of consensus (n=135; 67.5%) and poor awareness about guidelines (n=122; 61%) were the main determinants in their health care settings. Conclusions: The compliance of Surgical antibiotic was far below the recommendations of guidelines. The urgent needs of awareness among surgeons and implementation of antimicrobial stewardship program were important recommended interventions for appropriate use antibiotics.

In this paper, it is defined that how the IPOs are affected by the underwriter reputation. What will happen to IPOs who are backed by reputed underwriter and who is not? And evaluate the IPOs short-run and long-run performance. Also try to explain the relationship between IPOs and underwriter. Also tried to compare some of the international return and Pakistani returns. Also determine the relation of the investor to the underwriter. There is a set of investors who have there own relationship with the underwriters how they will affect on the IPOs in the market.

Human displacement is on the rise globally, and the increase in the burden of tuberculosis (TB) is also attributed to migrations worldwide. A significant number of such displacement occur in regions with considerably higher areas of TB burden. Displacements may delay in TB diagnosis and treatment, which possibly will lead to TB transmission among healthy individuals. In this study, we assessed the association of existing determinants after a protracted internal displacement of people with the delay in TB diagnosis and treatment outcomes. A cross-sectional study was conducted on internally displaced TB patients registered at selected health facilities in three urban districts of Pakistan from March 2019 to February 2020. The univariate and multivariate logistic regression model was used to assess the delay in diagnosis and treatment outcomes. IDPs with delay in initiation of treatment beyond 30 days were at high possibility of unsuccessful TB treatment outcomes (adjusted odds ratio AOR,2.60; 95% CI 1.06-6.40). Analysis of factors that affect health seeker behavior and timely treatment showed a significant association (p<0.05) in-between age group 55-65 years (AOR, 2.66; 95% CI 1.00-7.07), female patients (AOR, 2.42; 95% CI 1.21-4.81), visited non-formal health provider (AOR, 8.81; 95% CI 3.99-19.46), self-medication (AOR, 2.72; 95 % CI 1.37-5.37), poor knowledge of TB (AOR, 11.39; 95% CI 3.31-39.1), and perceived stigma (AOR, 8.81; 95% CI 3.99-19.4). Prolong delay in treatment was associated with unfavorable treatment outcomes among IDPs, more specifically. As migrants and IDPs are more likely to experience an interruption in care due to overall exclusion from social and health care services. Therefore, it is imperative to understand the barriers in providing public health care services, particularly in preventing and treating TB.

Ethylene, a gaseous phytohormone, is emerging as a central player in the intricate web of plant developmental processes from germination to senescence under optimal and stressed conditions. It is present in different plant parts, encompassing the stems, leaves, flowers, roots, seeds, and fruits. This review aims to provide a comprehensive overview of ethylene's fascinating roles in shaping various plant growth and adaptation aspects. It intricately examines the multifaceted impact of ethylene on pivotal aspects of plant development, including but not limited to cell division and elongation, senescence, abscission, fruit and flower development, root hair formation, chloroplast maturation, and photosynthesis. This comprehensive assessment encompasses the intricate pathways of ethylene biosynthesis and signaling, providing a snapshot of the regulatory mechanisms governing ethylene production. Understanding ethylene's multifaceted functions has significant implications for agriculture, biotechnology, and our fundamental comprehension of plant biology. This review underscores the need for continued investigation into ethylene's intricate mechanisms and its potential to revolutionize plant development and crop management.

Ethylene is an essential plant hormone critical in various physiological processes. These processes include seed germination, leaf senescence, fruit ripening, and the plant's response to environmental stressors. Ethylene biosynthesis is tightly regulated by two key enzymes, namely 1-aminocyclopropane-1-carboxylate synthase (ACS) and 1-aminocyclopropane-1-carboxylate oxidase (ACO). Initially, the prevailing hypothesis suggested that ACS is the limiting factor in the ethylene biosynthesis pathway. Nevertheless, accumulating evidence from various studies has demonstrated that ACO, under specific circumstances, acts as the rate-limiting enzyme in ethylene production. Under normal developmental processes, ACS and ACO collaborate to maintain balanced ethylene production, ensuring proper plant growth and physiology. However, under abiotic stress conditions, such as drought, salinity, extreme temperatures, or pathogen attack, the regulation of ethylene biosynthesis becomes critical for plants’ survival. This review highlights the structural characteristics, examines the transcriptional, post-transcriptional, and post-translational regulation of ACS and ACO, and their role under abiotic stress conditions. Reviews on the role of ethylene signaling in abiotic stress adaptation are available. However, a review that delineates the role of ACS and ACO in abiotic stress acclimation is not available.

An efficient cooling system is necessary for the reliability and safety of the modern microchips for longer life. As microchips become smaller and more powerful, the heat flux generated by these chips per unit area also rises sharply. Traditional cooling techniques are inadequate to meet the recent cooling requirements of microchips. To meet the current cooling demand of Microelectromechanical devices (MEMS) devices and microchips, microchannel heat sinks (MCHS) technology is the latest invention that can dissipate a significant amount of heat because of its high surface area to volume ratio. This study provides a concise summary of design, material selection, and performance parameters of MCHS that are developed over the last few decades. The limitations and challenges associated with different techniques employed by researchers over time to enhance the thermal efficiency of microchannel heat sinks are discussed. The effects on the thermal enhancement factor, Nusselt number, and pressure drop at different Reynold numbers, in passive techniques (flow obstruction) i.e. ribs, grooves, dimples, and cavities change in curvature of MCHS are discussed. This study also discusses the increase in heat transfer using nanofluids and how change in coolant type also significantly affects the thermal performance of MCHS by obstructing flow. This study provides trends and useful guidelines for researchers to design more effective MCHS to keep up with the cooling demands of power electronics.

In recent years, the exploration of space has expanded beyond the confines of our home planet, Earth, and has ignited a fervor for understanding the potential of sustaining life in extraterrestrial environments. One critical aspect of this endeavor is the cultivation of plants in microgravity—a unique environment that challenges traditional notions of plant growth and development. The Microgravity Plant Habitat, a cutting-edge apparatus designed to facilitate plant growth in space, stands at the forefront of scientific innovation in the quest for sustainable life beyond Earth.This research paper aims to explore into the complexities of the Microgravity Plant Habitat, exploring its design, functionality, and the profound implications it holds for future space exploration and colonization efforts. As humanity sets its sights on venturing further into the cosmos, the ability to cultivate plants in microgravity becomes paramount, not only for nutrition but also for the profound role plants play in maintaining life support systems and contributing to the psychological well-being of space travelers. Development of such plant habitat module will result in a bioregenerative life support system that will help in future deep space exploration and colonization of extraterrestrial planets. These modules can also cut the cost of space missions. The challenge of establishing outposts on the Moon or Mars requires thoughtful consideration of nourishment strategies. Space-based agriculture faces significant hurdles due to harsh conditions and limited resources. Researchers explore innovative solutions like hydroponics and aeroponics to meet nutritional needs and enhance well-being in extraterrestrial settlements. Beyond technological prowess, creating space bases demands a holistic approach, addressing biological and psychological aspects. Navigating deep space exploration emphasizes that food isn't just a logistical challenge but a symbol of our resilience and determination to thrive beyond Earth's confines.

The structure of turbulent flow over non-flat surfaces is a topic of major interest in practical applications in both engineering and geophysical settings. A lot of work has been done in the fully rough regime at high Reynolds numbers where the effect on the outer layer turbulence structure and the resulting friction drag is well documented. It turns out that surface topology plays a significant role on the flow drag especially in the transitional roughness regime and therefore, hard to characterize. Survey of literature shows that roughness function depends on the interaction of roughness height, flow Reynolds number and topology shape. In addition, if the surface topology contains large enough scales then it can impact the outer layer dynamics and in turn modulate the total frictional force. Therefore, it is important to understand the mechanisms underlying drag increase from systematically varied surface undulations in order to better interpret quantifications based on mean statistics such as roughness function. In this study, we explore the mechanisms that modulate the turbulence structure over a two-dimensional (2D) sinusoidal wavy surface with a fixed amplitude, but varying slope. To accomplish this, we model the turbulent flow between two infinitely wide 2D wavy plates at a friction Reynolds number, $Re_{\tau}=180$. We pursue two different but related flavors of analysis. The first one adopts a roughness characterization flavor of such wavy surfaces. The second one focuses on understanding the non-equilibrium near surface turbulence structure and their impact on roughness characterization. Analysis of the different statistical quantifications show strong dependence on wave slope for the roughness function indicating drag increase due to enhanced turbulent stresses resulting from increased production of vertical velocity variance from the surface undulations.

The current study applied a new approach for the interpolation and regionalization of observed precipitation series to a smaller spatial scale (0.125° by 0.125° grid) across the Upper Indus Basin (UIB), with appropriate adjustments for the orographic effect and changes in glacier storage. The approach is evaluated and validated through reverse hydrology, guided by observed flows and available knowledge base. More specifically, the generated corrected precipitation data is validated by means of SWAT-modelled responses of the observed flows to the different input precipitation series (original and corrected ones). The results show that the SWAT- simulated flows using the corrected, regionalized precipitation series as input are much more in line with the observed flows than those using the uncorrected observed precipitation input for which significant underestimations are obtained.

AbstractThe emergence of AI-powered deepfakes, manipulatively realistic synthetic media, raises unprecedented challenges for human information processing and decision-making. This paper explores the cognitive and emotional consequences of exposure to deepfakes, delving into how these digitally fabricated experiences can reshape perception, trust, and social interactions. By reviewing existing research and outlining potential methodological approaches, this paper aims to establish a framework for investigating the multifaceted impact of deepfakes on the human brain.BackgroundThe digital age has ushered in an era of unprecedented information abundance and accessibility. Yet, this abundance breeds vulnerability, particularly with the emergence of AI-powered deepfakes. These hyper-realistic synthetic media creations present a potent threat to the fundamental trust and integrity of information sources. Deepfakes have infiltrated various domains, from entertainment and social media to politics and journalism, blurring the lines between truth and fabrication. Consequently, understanding the cognitive and emotional consequences of encountering deepfakes becomes crucial for navigating this increasingly deceptive landscape.ObjectivesThis research aims to: Investigate how exposure to deepfakes impacts various cognitive functions, including perception, attention, memory, and decision-making. Elucidate the emotional responses elicited by deepfakes and their underlying neural mechanisms. Evaluate the role of individual differences, such as susceptibility to deception and emotional sensitivity, in mediating the impact of deepfakes. Develop a comprehensive framework for understanding the multifaceted influence of deepfakes on the human brain. Results (anticipated)This research is expected to yield insights into: The specific cognitive and emotional processes altered by deepfakes, providing evidence for potential mechanisms of deception and manipulation. The neural circuitry involved in detecting and responding to deepfakes, leading to the development of more effective detection methods. The influence of individual differences (e.g., age, cognitive style) on susceptibility to deepfakes, informing targeted interventions and educational efforts.ConclusionBy deciphering the impact of deepfakes on the human brain, this research will offer valuable tools for mitigating the harmful consequences of misinformation and promoting responsible use of this powerful technology. Ultimately, understanding how deepfakes manipulate our cognitive and emotional landscape is not merely a scientific pursuit, but a critical step towards ensuring a future where truth prevails in the digital world.

Invasive species are significant threats to global agriculture and food security being the major causes of crop loss. An operative biosecurity policy requires full automation of detection and habitat identification of the potential pests and pathogens. Unmanned Aerial Vehicles (UAVs) mounted thermal imaging cameras can observe and detect pest animals and their habitats, and estimate their population size around the clock. However, their effectiveness becomes limited due to manual detection of cryptic species in hours of captured flight videos, failure in habitat disclosure and the requirement of expensive high-resolution cameras. Therefore, the cost and efficiency trade-off often restricts the use of these systems. In this paper, we present an invasive animal species detection system that uses cost-effectiveness of consumer-level cameras while harnessing the power of transfer learning and an optimised small object detection algorithm. Our proposed optimised object detection algorithm named Optimised YOLO (OYOLO) enhances YOLO (You Only Look Once) by improving its training and structure for remote detection of elusive targets. Our system, trained on the massive data collected from New South Wales and Western Australia, can detect invasive species (rabbits, Kangaroos and pigs) in real-time with a higher probability of detection (85–100 %), compared to the manual detection. This work will enhance the visual analysis of pest species while performing well on low, medium and high-resolution thermal imagery, and equally accessible to all stakeholders and end-users in Australia via a public cloud.

COVID-19 pandemic has caused a large-scale havoc in almost every country across the globe, putting major challenges for the healthcare system in many parts of the world. Several of the laboratories are running in the race with undying efforts for developing potential vaccine, drugs or therapeutics to treat or prevent the infection. However, with the limited time window and high rate of infection, the task is very big for humanity to find a cure. With hundreds of genomic data of SARS-CoV-2 virus isolates from humans are being submitted almost every day, it is coming into knowledge that virus is mutating, slower in countries with sporadic cases, but higher in countries experiencing large outbreak. These types of mutations in virus may bring challenges in vaccine or therapeutic development for use in each and every country, as each hotspot region may have their own pattern of mutations in virus with ongoing outbreak. In our current study, we retrieved non-synonymous mutation data of around 12,225 SARS-CoV-2 virus samples isolated from humans globally, and discovered all mutations that are collectively happening in antibody epitope regions of the virus country-wise. We found a few numbers of epitope regions in SARS-CoV-2 that are highly conserved collectively in all variants and may be used for epitope-based vaccine development for whole world. We also found epitope regions that are conserved collectively in SARS-CoV-2 variants country-wise and can be used for customized epitope-based vaccine development in each different country.

In this study, we surveyed over 600 participants to determine: a) major causes to mental stress during the pandemic and its future impacts, and b) diversity in public perception and acceptance (specifically for children) of Covid-19 vaccination. Statistical results and intelligent clustering outcomes indicate significant relationships between sociodemographic diversity, mental stress causes, vaccination perception, and Covid-19 infections. For instance, statistical results indicate significant dependence between mental stress due to Covid-19 and gender (p = 1.7e-05). Over 25% of males indicated work related stress comparing 35% in females however, females indicated more stressed (17%) due to relationships comparing to males (12%). Around 30% of Asian/Arabic participants don’t feel vaccination being safe as compared to 8% of white-British and 22% of white-European indicating significant dependence (p = 1.8e-08) with ethnicity. More specifically, vaccination acceptance for children is significantly dependent to ethnicity (p = 3.7e-05) where only 47% participants show willingness towards children’s vaccination. Primary dataset in this study along with experimental outcomes identifying sociodemographic information diversity with respect to public perception and acceptance of vaccination to children and potential stress factors might be useful for public and policy makers to be better prepared for future epidemics as well as working globally to combat mental health issues and running more effective vaccination campaigns.

In this paper, we introduce a new class of Hermite-Fubini numbers and polynomials and investigate some properties of these polynomials. We establish summation formulas of these polynomials by summation techniques series. Furthermore, we derive symmetric identities of Hermite-Fubini numbers and polynomials by using generating functions.

Ovarian lymphoma is an infrequent disease, accounting for less than 1% of all non-Hodgkin lymphoma diagnosis. Symptoms include abnormal vaginal bleeding or discharge, abdominal pain, and urinary obstruction due to the large mass. In our case, a 60-year-old woman, underwent a total abdominal hysterectomy and bilateral salpingo-oophorectomy, as she presented with low-grade follicular lymphoma (FL) in both the ovaries, and the left ovary was observed to be enlarged. The tumor is categorized as lymphoma based upon immunohistochemical markers. Computed tomography (CT) scan of the chest, abdomen, and pelvis and bone marrow biopsy are important for the staging of primary lymphoma of the ovary. The first-line chemotherapy regimen includes rituximab, cyclophosphamide, doxorubicin hydrochloride (hydroxydaunorubicin), vincristine sulfate (Oncovin), and prednisone (R-CHOP) for rapidly proliferative non-Hodgkin lymphoma (NHL). Lymphomas with slower growth patterns can be treated with Bendamustine-Rituximab and don’t need aggressive R-CHOP treatment.

Intracortical microelectrodes that can be implanted have the ability to capture fast-changing neuron action potentials in the living brain. Despite this potential, many obstacles must still be overcome for reliable, long-term, high-quality recordings and accurate analysis of brain activity. These challenges include improving recording quality, enhancing recording stability, increasing recording capacity, and adding multi-functional features. One potential approach to enhance implantable microelectrodes involves the advancement of materials, refinement of implantation methodologies, and augmentation of the number of sites for recording. However, these challenges are still being actively researched, and advancements in microelectrode technology are underway. The difficulties with implantable microelectrodes are evaluated, and solutions are presented from different perspectives. The latest advancements in microelectrode technology are reviewed and condensed, and future possibilities are explored.

As technology advances, people are increasingly adopting IoT (Internet of Things) devices in smart cities. These devices are equipped with sensors that are connected everywhere, from energy infrastructure and transportation to telecommunications, health and human services, waste management, public safety, and more. People want to access sensor data anytime and everywhere to make better decisions and improve their lives. To achieve this, a sensor integration model has been developed where multiple sensors are integrated under one gateway to manage and share sensor data. However, effective sharing of sensor data requires data security, privacy, confidentiality, fairness, effective architectural design, and low communication and computation costs. These issues need to be addressed in the sensor integration model in smart cities. Existing storage models face challenges in managing sensor data effectively. To overcome these issues and hurdles, a data storage framework leveraging blockchain technology has been proposed within the sensor integration model. This framework ensures data security, privacy, confidentiality, and a fair and transparent financial model, all while minimizing communication and computation costs.

AbstractThe escalating impact of artificial intelligence (AI) has birthed the fascinating technology of deepfakes, capable of meticulously crafting hyper-realistic audio-visual manipulations. Within the realm of healthcare, this technology presents a double-edged sword, brimming with potential for revolutionizing various facets of care delivery while simultaneously harboring significant ethical and practical challenges. This research delves into the complex narrative surrounding AI deepfakes in healthcare, meticulously analyzing both the exciting opportunities they offer, and the inherent risks associated with their implementation.Background:Traditional healthcare practices face limitations in patient engagement, accessibility, and training efficacy. Deepfakes, with their ability to simulate real-world scenarios and interactions, emerge as a potential solution, offering personalized patient education, immersive mental health interventions, remote consultations with virtual avatars, and realistic training simulations for medical professionals.Objective:This research aims to comprehensively understand the multifaceted impact of AI deepfakes in healthcare systems. It seeks to: Identify and analyze the potential benefits of deepfakes in specific healthcare applications. Assess the ethical and practical challenges associated with deepfake implementation in healthcare settings. Propose recommendations for safe, responsible, and ethical integration of deepfakes within the healthcare system.Results/Conclusion:The research findings illuminate a landscape replete with opportunities and challenges. Deepfakes offer the potential to enhance patient education, personalize mental health interventions, facilitate remote consultations, and revolutionize medical training. However, concerns regarding misinformation, ethical breaches, data privacy, and technical limitations pose significant challenges.The conclusion emphasizes the need for a balanced approach that capitalizes on the innovative potential of deepfakes while mitigating potential harm. Collaborative efforts involving healthcare professionals, technologists, and policymakers are crucial for establishing ethical frameworks, ensuring responsible development, and harnessing the positive power of deepfakes to build a future where healthcare benefits from cutting-edge technology while prioritizing patient well-being and ethical principles.

Green ICT has received significant attention in organizations to reduce global warming since last decade. Several maturity models have been proposed for tracking green ICT practices in organizations. Current literature shows that SMEs around the world try to follow some common strategies such as virtualization, consolidation of devices, energy efficiency and disposal of ICT equipment for greening ICT. The increasing interest for green ICT practices in organizations is not only due to the desire to attain environment-friendly atmosphere but mainly because of sustaining business goals such as cost reduction, competitive advantages and stakeholders’ pressure. Nevertheless, due to the lack of green ICT knowledge, organizations, specially SMEs, tend to ignore those practices. Therefore, this research proposes a framework that provides combination of existing green and sustainable ICT maturity models by mapping them with the strategies the businesses are already following. Out of this framework, a web application has been developed that provides questionnaire for SMEs to identify their present situation of green ICT practices and guidelines for improvement. The results have been analyzed by testing the application in some SMEs of Finland and Bangladesh. Finally, a survey has been conducted to attain SMEs’ perception about the possibility of sustainable development of businesses through this application.