: Cattle farming is an ancient practice, with roots in the early Neolithic era that has retained its status in the food industry today, with global beef market revenue amounting to $385.7B, as of 2018. Hence, cattle maintenance is naturally essential to cater to nutritional requirements of modern civilization. This extensive review aims to provide a holistic overview of cattle microbiome, analysing the native microbial composition within respiratory tract, gastrointestinal tract, reproductive tract, and skin. The dysbiosis associated with various diseases such as bovine respiratory disease, bovine digital dermatitis, mastitis, Johne's disease, uterine diseases (metritis and endometritis) and metabolic disorders (ruminal acidosis and ketosis) has been discussed. Moreover, various non-antibiotic microbial therapies including phage therapy, prebiotics and probiotics have been examined as potential means to reduce disease-associated dysbiosis. In general, this review highlights the importance of the microbiome in maintenance of health in cattle and its potential in alleviating bovine diseases, with an aim to enhance cattle health and production.

This paper explores the relationships between marketing strategies, social media platforms, the adoption and diffusion of products and services, and organizational resilience to gain an understanding of the ability of organizations to cope with disruptive events (e.g., COVID-19). This can be achieved through effective marketing strategies and the efficient use of social media platforms. In fact, resilience thinking can help organizations maintain their operations by increasing the adoption and diffusion of their products and services through the use of effective marketing strategies. To achieve this article’s objectives, a literature review is conducted to help develop a conceptual framework that highlights a clear relationship between the previously discussed concepts. In addition, the novel nature of the relationship between marketing strategies and organizational resilience is dissected and its significance for organizations is demonstrated. In fact, the findings of this study suggest that effective marketing strategies that consider the "what," "who," and "how" dichotomies and the efficient use of social media to promote the adoption and diffusion of products and services can significantly enhance the resilience of organizations. These relationships can serve as a starting point for further studies examining and empirically analyzing marketing strategies and their positive effect on strengthening organizational resilience.

The study aimed to evaluate the after-effects of the COVID-19 pandemic on the sleep quality and patterns of women across different cultural settings within Iraq, spanning the period of 2022. A cross-sectional survey was administered to a diverse cohort of women from multiple provinces in Iraq. The survey measured various parameters, including sleep duration, onset latency, and disturbances. The post-pandemic period has seen a notable decline in sleep quality among the female population. Contributing factors include psychological stress, lifestyle changes due to the pandemic, and ongoing socio-economic challenges. The impact on sleep quality exhibited variation across different cultural groups, indicating a significant cultural influence on the pandemic's psychological aftermath. The study concludes that the post-pandemic phase has adversely affected the sleep health of women in Iraq, with cultural factors playing a critical role in these changes. There is a pressing need for culturally sensitive public health strategies to address sleep disturbances and mitigate their long-term effects on women's health. Public health initiatives should be tailored to address the specific cultural contexts within Iraq to improve sleep health among women. Further research is warranted to explore the long-term consequences of disturbed sleep patterns and the effectiveness of different intervention strategies.

Sentence stimuli pervade psycholinguistics research. Yet limited attention has been paid to the automatic construction of sentence stimuli. Given their linguistic capabilities, this study investigated the efficacy of ChatGPT/AI tools in generating sentence stimuli. In three psycholinguistic experiments, this study examined the acceptability and validity of AI-formulated auditory sentences and written sentences in two languages: English and Arabic. Participants gave English AI-generated stimuli similar to or higher acceptability ratings than human-composed stimuli, but the opposite was observed for Arabic AI-generated stimuli. The validity of AI-developed stimuli relied on the study design, with only Experiment 2 demonstrating the target psycholinguistic effect (L1/L2 morphosyntactic prediction). These results highlight the promising role of AI as a stimuli developer which could facilitate psycholinguistic research and increase its diversity. Implications for psycholinguistic research were discussed.

This study investigates the impact of the economic downturn induced by the COVID-19 pandemic on nutritional health disparities among women. The research aimed to understand how economic challenges have influenced dietary choices, access to nutritious food, and overall nutritional well-being in different socioeconomic groups of women.Utilizing a mixed-methods approach, the study combined quantitative data from national health and economic databases with qualitative insights from interviews conducted with a diverse group of women. The quantitative analysis focused on trends in nutritional health indicators and economic variables pre- and post-pandemic. Simultaneously, the qualitative component explored personal experiences and perceptions related to nutrition and economic hardships during the pandemic.The findings revealed a significant correlation between the economic downturn and worsening nutritional health among women, especially in low-income and marginalized communities. Women in these groups reported reduced access to healthy food options, increased reliance on less nutritious food due to budget constraints, and a general decline in dietary quality. This decline was less pronounced in higher-income groups, highlighting a clear disparity.Moreover, the study observed that the pandemic exacerbated pre-existing nutritional inequalities, with vulnerable groups experiencing a more pronounced impact. The research also noted that community support systems and public health interventions played a crucial role in mitigating some of these effects.In conclusion, the COVID-19 pandemic has not only posed a direct health challenge but has also indirectly affected women's nutritional health through economic strain. The study underscores the need for targeted nutritional support and economic policies that prioritize the health of women, particularly those from socioeconomically disadvantaged backgrounds.

Autonomous aircraft are the key enablers of future urban services, such as postal and transportation systems. Digital Twins (DT) are promising cutting-edge technologies that can transform the future transport ecosystem into an autonomous and resilient system. However, since DT is a data-driven solution based on AI, proper data management is essential in implementing DT as a Service (DTaaS). One of the challenges in DT development is the availability of real-life data, particularly for training algorithms and verifying the functionality of DT. The current article focuses on data augmentation through synthetic data generation. This approach can facilitate the development of DT in case the developers do not have enough data to train the Machine Learning (ML) algorithm. The current twinning approach provides a prospective ideal state of the engine used for proactive monitoring of the engine’s health as an anomaly detection service. In line with the track of Unmanned Aircraft Vehicles (UAV) for Urban Air Mobility in Smart Cities applications, this paper focuses specifically on the common Hybrid turbo-shaft in drones/helicopters. However, there is a significant gap in real-life similar synthetic data generation in the UAV domain literature. Therefore, Rolling Linear Regression and Kalman Filter algorithms were implemented on noise-added data, which simulate the data measured from the engine in a real-life operational lifecycle. For both thermal and hybrid models, the corresponding DT model has shown high efficiency in noise filtration and a certain amount of predictions with a lower error rate on all engine parameters, except the engine torque.

Hepatitis C Virus (HCV) is the main causative factor for liver cirrhosis and the development of liver cancer, with a confirmed ~ 180 million infections worldwide. E2 is an HCV structural protein responsible for virus entry to the host cell. Heat Shock Protein A5 (HSPA5), also termed BiP and GRP78, is the master regulator of the unfolded protein response mechanism, where it mainly localizes in the lumen of the Endoplasmic Reticulum (ER) in normal conditions. Under the stress of HCV infection or carcinogenesis, HSPA5 is upregulated. Consequently, HSPA5 escapes the ER retention localization and translocates to the cytoplasm and plasma membrane. Pep42, a cyclic peptide that was reported to target explicitly cell-surface HSPA5 in vivo. Owing to the high sequence and structural conservation between the C554-C566 region of HCV E2 and the Pep42, then we propose that the HCV E2 C554-C566 region could be the recognition site. The motivation of this work is to predict the possible binding mode between HCV E2 and HSPA5 by implementing molecular docking to test such proposed binding. Docking results reveal the high potent binding of the HCV E2 C554-C566 region to HSPA5 substrate-binding domain β (SBDβ). Moreover, the full-length HCV E2 also exhibits high binding potency to HSPA5 SBDβ. Defining the binding mode between HCV E2 and HSPA5 is of significance, so one can interfere with such binding and reducing the viral infection.

Cancer is the second major cause of disease-related dead worldwide, and its accurate early diagnosis and therapeutic intervention are fundamental for saving the patient’s life. Cancer, as a complex and heterogeneous disorder, results from disruption and alteration of a wide variety of biological entities, including genes, proteins, mRNAs, miRNAs, and metabolites that eventually emerge as clinical symptoms. Traditionally, diagnosis is based on clinical examination, blood tests for biomarkers, histopathology of biopsy, and imaging (MRI, CT, PET, US). Additionally, omics biotechnologies help to further characterize the genome, metabolome, microbiome traits of the patient that could have an impact on the prognosis and patient’s response to the therapy. The integration of all these data relies on gathering of several experts and may require considerable time, and, unfortunately, it is not without the risk of error in the interpretation and therefore in the decision. Systems biology algorithms exploit Artificial Intelligence (AI) combined with omics technologies to perform a rapid and accurate analysis and integration of patient’s big data and support the physician in making diagnosis and tailoring the most appropriate therapeutic intervention. However, AI is not free from possible diagnostic and prognostic errors in the interpretation of images or biochemical-clinical data. Here, we first describe the methods used by systems biology for combining AI with omics and then discuss the potential, challenges, limitations, and critical issues in using AI in cancer research.

Intelligent Transportation Systems (ITS) encompasses technologies, services, and applications facilitating communication between vehicles (V2V) and between vehicles and fixed infrastructure (V2I and I2V). This mutual interaction constitutes a Vehicular Ad-Hoc Network (VANET) which supports a plethora of applications targeting critical transportation aspects, such as safety, mo-bility, and environmental considerations. Dedicated Short Range Communications (DSRC), op-erating on the 5.9 GHz band, is pivotal for such exchanges. We introduced an innovative algorithm designed to identify jamming attacks and transition the Safety Application to a secure fail-safe mode. This algorithm leverages a dual-metric strategy, incorporating both distance and PDR measurements. Field tests confirm that our algorithm adeptly recognizes the activities of deceptive jammers, ensuring a prompt shift of the safety application into its fail-safe state. This paper delves into these countermeasures, evaluating their efficiency via mathematical modelling, simulations, and on-ground testing. Findings acknowledge that these strategies bolster the reliability of safety applications in jamming scenarios. Furthermore, the approaches propounded align with ongoing standardization endeavours by relevant authorities, ensuring communication mediums remain unhindered.

Counterfeiting and theft have always been problems that incur high costs and results in considerable losses for the international markets. In this research paper, we will address the issue of counterfeiting while using RFID technology in retailer systems or other industries by presenting a new anti-counterfeiting and anti-theft system for the retailer market. This system will address the two above mentioned issues and provide a solution that can save the retailer systems millions of dollars yearly. This proposed system will achieve the objective of preventing or minimising the counterfeiting and theft of tagged products. At the same time, it will provide a strong indication for suspiciously sold or obtained items. Furthermore, we conducted a security analysis to prove the correctness of our protocol on the basis of the strand spaces.

In this work, zinc oxide (ZnO) thin film has been fabricated on glass substrate using pulse laser ablation (PLA) technique. The effect of laser pulses of 1000, 1500, 2000 pulses at laser energy 700 mJ as well as, laser energy of 600, 700, and 800 mJ at fixed laser pulses of 1500 pulse, with methanol as a solvent on the structural properties of prepared films using XRD, SEM and EDX. XRD results revealed that the ZnO thin films have hexagonal structure with polycrystalline in nature with preferred orientation of (002). Crystalline size was increased with the increasing of the pulses and at energy of 700 mJ and pulse of 1500 pulse seemed nanostructure like tree leaf. In addition, narrow FWHM and no phase change have been observed in all cases. SEM images showed that for all cases the films were homogenous with some island and cluster then cracking started to obtain with the increasing of increase the pulse number. EDX analysis showed that the prepared films were free of defects and contaminations.

Acute lower respiratory tract infection is a major health problem that affects more than 15% of the total population of Saudi Arabia each year. Epidemiological studies conducted over the last three decades have indicated that viruses are responsible for the majority of these infections. The epidemiology of respiratory viruses in Saudi Arabia is believed to be affected mainly by the presence and mobility of large numbers of foreign workers and the gathering of millions of Muslims in Mecca during the Hajj and Umrah seasons. Knowledge concerning the epidemiology, circulation pattern, and evolutionary kinetics of respiratory viruses in Saudi Arabia are scant, with the available literature being inconsistent. After reviewing the available data on epidemiology and evolution of respiratory viruses, this study examines the effect of varying vaccination rates across different age groups during the 2019/2020 influenza season in Saudi Arabia. Utilizing an age-structured SEIR (Susceptible–Exposed–Infectious–Recovered) model, it develops customized vaccination policies by considering age-specific incidence rates. This pioneering research segments the population into five age groups—infants and school-aged children, junior and older youth, young adults and adults, middle-aged, and seniors—across five regional areas in Saudi Arabis: Eastern, Central, Northern, Western, and Southern. A contact matrix, compiled from multiple sources, is used to delineate the dynamics of influenza transmission. The study undertakes a thorough comparison of three distinct vaccination scenarios: no vaccination, national vaccination, and optimized vaccine allocation policy, under various potential pandemic situations. It examines their impact on vaccination campaigns in terms of the total number of infections, mortality, and morbidity rates. The results emphasize the crucial impact of population demographics on disease transmission and vaccine distribution. According to the findings, the optimized vaccination scenario proved to be the most effective strategy in all scenarios.

The Internet of Things technology opens the horizon for a broader scope of intelligent applications in smart cities. However, the massive amount of traffic exchanged among devices may cause security risks, significantly when devices are compromised or vulnerable to cyber-attack. An intrusion detection system is the most powerful tool to detect unauthorized attempts to access smart systems. It identifies malicious and benign traffic by analyzing network traffic. In most cases, only a fraction of network traffic can be considered malicious. As a result, it is difficult for an intrusion detection system to detect attacks at high detection rates while maintaining a low false alarm rate. This work proposes an integrated framework to detect suspicious traffic to address secure data communication in smart cities. This paper presents an approach to developing an intrusion detection system to detect various attack types. It can be done by implementing a Principal Component Analysis method that eliminates redundancy and reduces system dimensionality. Furthermore, the proposed model shows how to improve intrusion detection system performance by implementing an ensemble model.

: Seasonal influenza (a.k.a flu) is responsible for considerable morbidity and mortality across the globe. The three recognized pathogens that cause epidemics during the winter season are influenza A, B and C. The influenza virus is particularly dangerous due to its mutability. Vaccines are an effective tool in preventing seasonal influenza, and their formulas are updated yearly according to WHO recommendations. However, in order to facilitate decision-making in the planning of the intervention, policymakers need information on the projected costs and quantities related to introducing the influenza vaccine, in order to help governments obtain an optimal allocation of the vaccine each year. In this paper, an approach based on a Controlled Elitism Non-Dominated Sorting Genetic Algorithm (CENSGA) model is introduced to optimize the allocation of influenza vaccination. A bi-objective model is formulated to control the infection volume, and reduce the unit cost of the vaccination campaign. An SIR (Susceptible–Infected–Recovered) model is employed for representing a potential epidemic. The model constraints are based on the epidemiological model, time management, and vaccine quantity. A two-phase optimization process is proposed: guardian control followed by contingent controls. The proposed approach is an evolutionary metaheuristic multi-objective optimization algorithm with a local search procedure based on a hash table. Moreover, in order to optimize the scheduling of a set of policies over a predetermined time to form a complete campaign, an extended CENSGA is introduced with a variable-length chromosome (VLC) along with mutation and crossover operations. To validate the applicability of the proposed CENSGA, it is compared with the classical Non-Dominated Sorting Genetic Algorithm (NSGA-II). The results are analyzed using graphical and statistical comparisons in terms of cardinality, convergence, distribution and spread quality metrics, illustrating that the proposed CENSGA is effective and useful for determining the optimal vaccination allocation campaigns.

The open communication is an exigent need for future power system where the time delay is unavoidable. In order to secure the stability of the grid, the frequency must remain within its limited range which is achieved through the load frequency control. The load frequency control signals are transmitted through communication networks which induces time delay that could destabilize the power systems. So, in order to guarantee the stability the delay margin should be computed. In this paper, we present a new method for calculating the delay margin in load frequency control systems. The transcendental time delay characteristics equation is transformed to frequency dependant equation. The spectral radius is used to find the frequencies at which the roots crosses the imaginary axis. The crossing frequencies are determined through the sweeping test and the binary iteration algorithm. A one-area load frequency control system is chosen as case study. The effectiveness of the proposed method has been proved through comparing with the most recent published methods. The method shows its merit with less conservativeness and less computations. The PI controller gains are preferable to be chosen large to reduce the damping, however, the delay margin decreases with increasing the PI controller gains.

Sodium glucose cotransporter 2 inhibitors (SGLT2i) are currently available for the management of type 2 diabetes mellitus. SGLT2i act by inhibiting renal SGLT2, thereby increasing glucosuria and lowering serum glucose. Recent trials are emerging supporting a role for SGLT2i irrespective of the diabetic status pointing towards that SGLT2i have other mechanisms of actions beyond blood sugar control. In this review, we will shed light on the role of this group of medications that act as SGLT2i in non-diabetics focusing on pre-clinical and clinical data highlighting the mechanism of renoprotection and effects of SGLT2i in the non-diabetic kidneys.

In the present work, three different atmospheric plasma sprayed (APS) alumina coatings were fabricated using three fused and crushed alumina powders of different particle size fine, medium and coarse. The influence of the particle size on thermal properties and micro-structural features of the produced coating were investigated by thermal insulation test and detailed image analysis technique, respectively. The analyzed micro-structural features include the total porosity, pore size (fine, medium, and large) and cracks. All types of cracks were considered in calculations as voids and were evaluated according to their sizes as pores. All spray parameters except the particle size were fixed throughout the spraying process. The results revealed that the fine starting powder has produced the densest coating with the lowest total porosity and that the total porosity increases with an increasing particle size. This was expected as powders of smaller particle size will reach a higher in-flight temperature and velocity than powders of bigger particle sizes as long as the same spray parameters are applied. However, a detailed image analysis investigation on the three produced coatings showed that the fraction of fine pores and cracks versus the total porosity is substantially higher in coatings produced by using fine starting powders than those produced using medium and coarse powders. In this work, a connection between the thermal insulation and the porosity fraction, which includes fine pores and cracks, was revealed.

The use of miniplates for stabilizing bones after orthognathic surgeries, has become increasingly popular for their effectiveness in ensuring stability and promoting swift recovery. However, the post-surgical fate of these miniplates remains a subject of contention among surgeons. Some advocate for their removal, while others suggest leaving them in place. The aims of this study, is to evaluate the incidence, causes, and potential risk factors associated with the removal of miniplates in orthognathic surgeries. A comprehensive meta-analysis was conducted by reviewing studies from various databases like PubMed, Google Scholar, Research Gate, Embase, and Scopus, focusing on publications from 1989 to 2023. Ten studies encompassing a total of 1603 patients which conformed to the inclusion criteria were selected and included in the meta-analysis. With M:F ratio range from 4:1 to 109:141. Total number of miniplates inserted was 5595, and total number of miniplates removed were 294 (5.3%). The most common reasons for miniplates removal were, infection was reported in 161 cases (2.9%), followed by miniplates exposure (34 cases, 0.6%) and palpable plates (23 cases 0.4%). Other indications included pain, patient’s preference, and temperature sensitivity. Relatively less common reasons that resulted in miniplates removal include, sinusitis, second surgery and dental pathology. The mean duration of miniplates removal was 5.5 months with the majority of miniplates (56.1%) were removed from the mandible compared to maxilla. In conclusion, this meta-analysis underscores the importance of miniplate removal in cases where hardware causes diverse complications and physical discomfort. The primary reasons for miniplates removal were infections and plates exposure, with the mandible being the most common site for removal. These findings emphasize the need for continued monitoring to assess the fate of miniplates in orthognathic surgery and provide valuable insights for future clinical decision-making.

Let $G$ be a group with identity $e$ and $R$ be a commutative $G$-graded ring with nonzero unity $1$. Graded semi-primary and graded $1$-absorbing primary ideals have been investigated and examined by several authors as generalizations of graded primary ideals. However, these three concepts are different. In this article, we characterize graded rings over which every graded semi-primary ideal is graded $1$-absorbing primary and graded rings over which every graded $1$-absorbing primary ideal is graded primary.

The measurements of the proton electromagnetic form factors in the time-like region using the initial state radiation technique are reviewed. Recent experimental studies have shown that initial state radiation processes at high luminosity electron-positron colliders can be effectively used to probe the electromagnetic structure of hadrons. The BABAR experiment at the B-factory PEP-II in Stanford and the BESIII experiment at the $\tau$-charm factory BEPC-II in Beijing have measured the time-like form factors of the proton using the initial state radiation process $e^{+}e^{-}\to pbar{p}\gamma$. The two kinematical regions where the photon is emitted from the initial state at small and large polar angles have been investigated. In the first case the photon is in the region not covered by the detector acceptance and is not detected. The Born cross section and the proton effective form factor have been measured over a wide and continuous range of the the momentum transfer squared $q^2$ from threshold up to ~42 (GeV/c)$^2$. The ratio of electric and magnetic form factors of the proton has been also determined. In this report, the theoretical aspect and the experimental studies of the initial state radiation process $e^{+}e^{-}\to p\bar{p}\gamma$ are described. The measurements of the Born cross section and the proton form factors obtained in these analyses near the threshold region and in the relatively large $q^2$ region are examined. The experimental results are compared to the predictions from theory and models. Their impact on our understanding of the nucleon structure is discussed.

The aim of this paper is to investigate the amenability modulo an ideal of Banach algebras with emphasis on applications to homological algebras. In doing so, we show that amenability modulo an ideal of A^** implies amenability modulo an ideal of A. Finally, for a large class of semigroups, we prove that l¹(S)^** is amenable modulo Iσ^** if and only if an appropriate group homomorphic image of S is finite where Iσ is the closed ideal induced by the least group congruence σ.

The vast rise in the number of Internet-connected devices necessitates a more accessible spectrum. As a result, Cognitive Radio was already proposed as a solution to the problem of restricted spectrum resources by utilizing available spectrum which is assigned to primary users. This method allows the secondary user to utilize the spectrum whenever the primary user is not using it, and it does so without intruding with the primary user. Whenever the secondary user detects the spectrum, it faced some issues, such as complexity in sensing leading to a lack of noise value, and the primary user is hidden to all secondary users. In order to tackle these challenges, an adaptive threshold matched filter detector and a cooperative matched filter detector are utilized in this paper to detect the spectrum. The probability of detection (Pd), probability of miss detection (Pm), and probability of false alarm (Pf) are the metrics used to assess sensing accuracy. To simulate suggested detectors, the MATLAB R2020a software was utilized. In comparison to earlier studies, the simulation conclusions reveal that the detection process starts with lower SNR values.

Product counterfeiting is an on-going problem in supply chains and retail environments, Recently an anti-counterfeiting protocol to address this issue via cost-effective use of auto-identification technologies such as radio-frequency identification (RFID) was proposed by researchers.Yet the use case of re-selling the same product was not been fully addressed which might cause serious problem for the exciting and proposed schemes and transactions. This paper proposes an extended RFID-based anti-counterfeiting to address the use case of the original buyer reselling the same item to a second buyer. The extended scheme will be followed by a formal security analysis to show that the proposed protocol satisfies the requirements of security correctness and is resistant to compromise through security attacks.

The new pandemic coronavirus disease 2019 (COVID-19) is a worldwide threatening health issue. Early progression of this disease starts in the lung airways with an exaggerated inflammation, triggered by the viral infection and characterized by a “cytokine storm” that can lead to lethal lung injuries. In the absence of an effective anti-viral molecule and until the formulation of a successful vaccine, anti-inflammatory drugs might offer a complementary tool for controlling the associated complications and thus decreasing the subsequent fatalities. Drug repurposing for several molecules has emerged as a rapid temporary solution for COVID-19. Among these drugs, Thalidomide, a historically emblematic controversial molecule that harbors an FDA approval for treating Erythema Nodosum Leprosum (ENL) and multiple myeloma (MM). Based on only one-case report of positive outcomes in a patient treated amongst others with Thalidomide, two clinical trials on the efficacy and safety of Thalidomide in treating severe respiratory complications in COVID-19 patients were registered. Conversely, the absence of any substantial, promising evidence on Thalidomide usage in that context along with the discontinued studies on the efficiency of this drug in similar pulmonary diseases might cause a significant obstacle for carrying on clinical studies. In this review, we will discuss the theoretical effectiveness of this drug in attenuating inflammatory complications that are encountered in patients with COVID-19 while pinpointing the lack of evidence that is needed to move forward with this drug.

Humans have extremely variable skin pigmentation and melanin production influenced by genetics, UV exposure, and some medications. A significant number of skin illnesses that result in pigmentary abnormalities have an impact on patients’ physical appearance as well as their psychological and social well-being. Skin pigmentation can be divided into two basic categories: hyperpigmentation, where pigment appears to overflow, and hypopigmentation, where pigment is reduced. Albinism, melasma, vitiligo, Addison's disease, and post-inflammatory hyperpigmentation, which can be brought on by eczema, acne vulgaris, and drug interactions, are the most common skin pigmentation disorders in clinical practice. Anti-inflammatory medications, antioxidants, and medications that inhibit tyrosine, which prevents the production of melanin, are all possible treatments for pigmentation problems. Skin pigmentation can be treated orally and topically with medications, herbal remedies, and cosmetic products, but a doctor should always be consulted before beginning any new medicine or treatment plan. This review article explores the numerous types of pigmentation problems, their causes, and treatments, as well as the 25 plants, four marine species, and 17 topical and oral medications now on the market that have been clinically tested to treat skin diseases.

Abstract: To overcome the environmental impact of cement production in cocnrete , the construction industry is adopting eco-friendly approaches, such as incorporating alternative and recycled materials, minimizing carbon emissions in concrete production. One such material that has gained prominence is Ground Granulated Blast Furnace Slag (GGBFS),. This study focuses on investigating the compressive strength of concrete at 28 days of age by examining the influences of several factors, such as temperature, water-to-binder ratio (w/b), GGBFS-to-binder ratio (GGBFS/b), fine aggregate, coarse aggregate, and superplasticizer. A statistical modeling approach was employed to comprehensively analyze these parameters and assess their impact on the compressive strength. To accomplish this, the study collected and analyzed data from the literature, resulting in a dataset of 210 observations. The dataset was divided into training and testing groups, and statistical analyses were performed to assess the relationships between the input parameters and compressive strength. The correlation analysis revealed insignificant relationships between the input parameters and compressive strength, indicating that multiple factors affect the strength. Different models, such as linear regression, nonlinear regression, quadratic, full quadratic models, and artificial neural networks (ANN) were employed to predict the compressive strength. The findings of this study contribute to a better understanding of the factors that influence the compressive strength of concrete containing GGBFS. The results underscore the importance of considering multiple parameters to predict strength accurately.

In this work, we adapt the fine-tuning algorithm of the Naïve Bayesian (FTNB) classifier to make it more suitable for imbalanced datasets. In particular, we boost misclassified instance probability terms by an amount that is disproportional to the harmonic mean of actual and predicted classes. The intuition is that discriminative attributes when the instance is misclassified would have small probability term pair values in both the actual class due to data scarcity and the predicted class due to weak correlation. Conversely, if both values are relatively high, then the attribute has good data coverage (support) and it should not be a cause for misclassification. Since the harmonic average is dominated by the smaller value and we have an imbalanced dataset, we should enact a large update if both or either term probabilities of actual and predicted classes are small. We used several benchmark datasets (60 different balanced and imbalanced datasets) to determine if the poor performance of the NB classifier is due to the scarcity of data and compared the performance of the proposed algorithm with NB, original FTNB, and other relatively new SOTA Ensemble Imbalanced Classifiers. Our empirical results reveal that the new proposed algorithm significantly outperforms all other classifiers.

Polymeric based nanoparticles are garnering significant interest for their potential in drug delivery. Specially, nanopolymers that have been functionalized with molecules, such as proteins or peptides, are a versatile vehicle for drug delivery. Curcumin (Cur) is one of the most commonly studied anticancer compounds and is widely acknowledged as having positive effects on human health. However, its insolubility and low bio-distribution greatly hinder the exploitation of its beneficial traits. In this study, our team created a nano delivery system which utilized a nanopolymer called PCL-PEG (poly(ε-caprolactone)-poly (ethylene glycol)). This system was functionalized with A6 peptide to enable targeted delivery of Cur. The system was designed with advantageous nanoparticles (NPs), including a stable zeta potential (–32.7), small size (54.3), uniform surface morphology, and high hydrophilicity (13.72°). In addition, targeted delivery systems exhibited high encapsulation efficacy (93 ± 0.89 %), and drug loading (16.7 ± 0.9 %), and were characterized by a slow and gradual release profile with a release of approximately 83.13 ± 0.12%. The MTT assay results showed that the formulation known as Cur-NPs-A6 caused a significant increase in cell death in MDA-MB-231 cancer cells (IC50 = 23.31 ± 0.85 µM). The designed delivery system did not cause any harm to the noncancerous MCF-10A cells (normal group). Furthermore, the results of both the RT-qPCR and invasion assays demonstrated that the designed system was able to effectively activate the apoptosis pathway and inhibit cell invasion. Our findings suggest that the use of the designed smart delivery system, which is functionalized with A6 peptide that has a high affinity for CD44 receptor - known to be upregulated in numerous malignant conditions, could be a highly efficient approach to treating cancer.

In recent years, natural polymers have replaced synthetic polymers for antibacterial orthopedic applications owing to their excellent biocompatibility and biodegradability. Zein is a biopolymer found in corn. The lacking mechanical stability of zein is overcome by incorporating bioceramics e.g. mesoporous bioactive glass nanoparticles (MBGNs). In present study, pure zein and zein/Zn-Mn MBGNs composite coatings were deposited via electrophoretic deposition (EPD) on 316L stainless steel (SS). Zn and Mn were co-doped in MBGNs in order to make use of their antibacterial and osteogenic potential, respectively. A Taguchi design of experiment (DoE) study was established to evaluate the effect of various working parameters on the morphology of the coatings. It was observed that coatings deposited at 20 V for 5 min with 4 g/L concentration (conc.) of Zn-Mn MBGNs showed highest deposition yield. Uniform coatings with highly dispersed MBGNs were obtained adopting these optimized parameters. Scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-Ray diffraction (XRD), and fourier transform infrared spectroscopy (FTIR) were employed to investigate the morphology and elemental composition of zein/Zn-Mn MBGNs composite coating. Surface properties i.e. coating roughness and wettability analysis concluded that composite coatings were appropriate for cell attachment and proliferation. For adhesion strength various techniques including tape test, bend test, pencil hardness test, and tensile test were performed. Wear and corrosion analysis highlighted the mechanical and chemical stability of coatings. Colony forming unit (CFU) test showed that zein/Zn-Mn MBGNs composite coating was highly effective against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) due to the presence of Zn. The formation of hydroxyapatite (HA) like structure upon immersion in simulated body fluid (SBF) validated the in vitro bioactivity of the coating. It was concluded that zein/Zn-Mn MBGNs coating synthesized in this work can be used for bioactive and antibacterial orthopedic applications.

An earthquake is a natural event by its general definition. This natural event is a disaster that causes significant damage, loss of life, and other economic effects that will damage the state. The possibility of predicting a natural event such as an earthquake will minimize the reasons mentioned. Data collection, data processing, and data evaluation were carried out in this study. Earthquake forecasting was performed using the data and the RNN (Recurrent Neural Network) method. The study was carried out on seismic data with a magnitude of 3.0 and above belonging to Düzce Province between 1990 and 2022. In order to increase the learning potential of the method, the b and d values of the earthquake were calculated and included in the data set, except for the earthquake magnitude. The determination of earthquakes in a specific time interval in regions of Turkey, the classification of earthquake-related seismic data using artificial neural networks, and the production of predictions for the future reveal the importance of this study.

Maxillofacial fractures are a prevalent occurrence, and the widespread use of miniplates to stabilize and secure these fractures during surgery is common. However, the post-surgical fate of these miniplates remains a subject of contention among surgeons. Some advocate for their removal, while others suggest leaving them in place. This study aims to perform an extensive meta-analysis of pertinent studies to ascertain the destiny of miniplates employed in maxillofacial surgery and discuss the consequences of either their extraction or retention. To execute this meta-analysis, an exhaustive search was conducted across multiple databases, encompassing PubMed, Scopus, and Google Scholar. Keywords such as "titanium miniplates," "screws," "maxillofacial surgery," "complications," and "removal" were utilized to identify pertinent studies. The search was constrained to studies published between 1989 and 2022. The analysis encompassed only studies reporting outcomes related to miniplates in maxillofacial surgery, including complication rates and removal frequencies. Eleven studies conformed to the inclusion criteria and were incorporated into the meta-analysis, encompassing a total of 2240 patients. All the studies had a retrospective design, with the largest study involving 800 patients. The overall complication rate was determined to be 13.3%. The most prevalent reasons for miniplate removal included patient preference, tooth extraction, and infections. The average time span for miniplate removal was 10.7 months, with the most prolonged reported duration being 24 years. These findings imply that immediate removal might not be imperative in the majority of instances. In conclusion, our meta-analysis underscores the necessity of removing miniplates in cases where hardware leads to a variety of complications and physical discomfort. Principal factors driving plate removal included patient requests, tooth extractions, and infections. Ordinarily, plate removal took place within the span of 6 to 12 months, with the mandible being the most frequent site for removal. These findings accentuate the significance of extended monitoring to assess the trajectory of miniplates in maxillofacial surgery and provide valuable insights for future clinical decisions. To validate these conclusions and gain deeper insights into the factors influencing plate removal in maxillofacial surgery, further research with larger participant cohorts and standardized outcome reporting is imperative.

This study presents the consecutive modification of orange peel (OP) by NaOH and sodium dodecyl sulfate (SDS) for simultaneous elimination of basic dyes from the binary system and modeling the adsorption process using an intelligent tool. The natural and modified biosorbents were characterized by variety of analyses such as: field emission scanning electron microscopy with energy dispersive X-ray, N2 physisorption and Fourier transform infrared spectroscopy techniques. The influence of various variables on dye removal like pH, the quantity of biosorbents, dyes concentration, contact time, and temperature in the binary system were investigated and optimized by an artificial neural network (ANN) model as an intelligent tool. The optimum quantity of the sorbent was found to be 0.30 g for orange peel (OP) and 0.25 g for NaOH-treated OP (NOP) and SDS-decorated NOP (SNOP) at pH = 7. The kinetics and thermodynamics investigations showed that the removal of dyes obeyed the pseudo-second-order kinetic model and were spontaneous and exothermic in nature. Moreover, in order to describe the mechanism of sorption process, desorption studies of dyes were carried out. The desorption percentages of methylene blue (MB) in water and HCl were found to be in the range of 1.93%–4.76% and 18.87%–28.76%, respectively; in addition, the desorption percentages of crystal violet (CV) in water and HCl were obtained to be in the range of 4.11%–7.41% and 32.84%–43.00%, respectively; which could be a recommendation ion exchange or electrostatic attachment of dyes onto biosorbents. The ANN predictions matched with the experimental data very well (0.95308 < R2 < 0.99191 and 0.98335 < R2 < 0.99773 for MB and CV, respectively) which indicated high accuracy of the ANN model. In addition, the relative importance of each parameter was calculated by Garson’s equation.

Anion exchange membrane (AEM) electrolysis is hampered by two main issues: stability and performance. Focusing on the latter, this work demonstrates a highly active NiMo cathode for hydrogen evolution in AEM electrolysis. We demonstrate an electrolyzer performance of 1 A cm⁻² at 1.9 V (total cell voltage) with a NiMo loading of 5 mg cm⁻² and an iridium black anode in 1 M KOH at 50 °C, that may be compared to 1.8 V for a similar cell with Pt at the cathode. The catalysts developed here will be significant in supporting the pursuit of cheap and environmentally friendly hydrogen fuel.

This study aimed to assess prescription transfer and medicines collection through Wasfaty, an electronic prescription service recently introduced in Saudi Arabia. A link to a cross-sectional online questionnaire was sent to all students and staff at the University of Jeddah, targeting beneficiaries who received e-prescriptions at the University Medical Centre (n = 2067). The questionnaire comprised 20 items under the following sections; demographics, patient perceptions and satisfaction with the Wasfaty service, and the availability of medicines. Of the 217 questionnaires received, the majority were filled by females (n = 125, 57.6%). Most were satisfied with the initial registration process of Wasfaty (n = 183, 84.1%). However, almost one-third of the participants reported that they could not find the prescribed medicines (n = 64, 29.7%), and most of them had to look for another pharmacy to obtain their treatment (n = 138, 63.9%). Respondents voiced their displeasure owing to the lack of access to certain pharmaceuticals, including anti-hypertensives and antidiabetics. This pilot study identified some challenges relating to the use of the Wasfaty service. Further attention to these challenges is required from the service providers, and a large-scale national study is warranted.

Solar radiation prediction is an important process in ensuring optimal exploitation of solar energy power. Numerous models have been applied to this problem, such as numerical weather prediction models and artificial intelligence models. However, well-designed hybridization approaches that combine numerical models with artificial intelligence models to yield a more powerful model can provide a significant improvement in prediction accuracy. In this paper, we propose novel hybrid machine learning approaches that exploit auxiliary numerical data. The proposed hybrid methods invoke different machine learning paradigms, including feature selection, classification, and regression. Additionally, numerical weather prediction (NWP) models are used in the proposed hybrid models. Feature selection is used for feature space dimension reduction to reduce the large number of recorded parameters that affect estimation and prediction processes. The rough set theory is applied for attribute reduction and the dependency degree is used as a fitness function. We investigate the effect of the attribute reduction process with thirty different classification and prediction models in addition to the proposed hybrid model. Then, different machine learning models are constructed based on classification and regression techniques to predict solar radiation. Moreover, other hybrid prediction models are formulated to use the output of the numerical model of Weather Research and Forecasting (WRF) as learning elements in order to improve the prediction accuracy. The proposed methodologies are evaluated using a data set that is collected from different regions in Saudi Arabia.

Background: Aquaponics are food production systems advocated for food security and health. Their sustainability from a nutritional and plant health perspective is, however, a significant challenge. Recirculated aquaculture systems (RAS) form a major part of aquaponic systems, but knowledge about their potential to benefit plant growth and plant health is limited. The current study tested if the diversity and function of microbial communities in two commercial RAS were specific to the fish species used (Tilapia or Clarias) and sampling site (fish tanks and wastewaters), and whether they confer benefits to plants and have invitro antagonistic potential towards plant pathogens. Results: Microbial diversity and composition was found to be dependent on fish species and sample site. The Tilapia RAS hosted higher bacterial diversity than the Clarias RAS; but the latter hosted higher fungal diversity. Both Tilapia and Clarias RAS hosted bacterial and fungal communities that promoted plant growth, inhibited plant pathogens and encouraged biodegradation. The production of extracellular enzymes, related to nutrient availability and pathogen control, by bacterial strains isolated from the Tilapia and Clarias systems, makes them a promising tool in aquaponics and in their system design. Conclusions: This study explored the microbial potential of the commercial RAS with either Tilapia or Clarias as a tool to benefit the aquaponic system with respect to plant growth promotion and control of plant diseases.

Opportunistic networks, an evolution of mobile Ad Hoc networks (MANETs), offer decentralized communication without relying on preinstalled infrastructure, enabling nodes to route packets through different mobile nodes dynamically. However, due to the absence of complete paths and rapidly changing connectivity, routing in opportunistic networks presents unique challenges. This paper proposes a novel probabilistic routing model for opportunistic networks, leveraging nodes' meeting probabilities to route packets towards their destinations. The model dynamically builds routes based on the likelihood of encountering the destination node, considering factors such as last meeting time and acknowledgment tables to manage network overload. Additionally, an efficient message detection scheme is introduced to alleviate high overhead by selectively deleting messages from buffers during congestion. Furthermore, the proposed model incorporates cross-layer optimization techniques, integrating optimization strategies across multiple protocol layers to maximize energy efficiency, adaptability, and message delivery reliability. Through extensive simulations, the effectiveness of the proposed model is demonstrated, showing improved message delivery probability while maintaining reasonable overhead and latency. This research contributes to the advancement of opportunistic networks, particularly in enhancing connectivity and efficiency for Internet of Things (IoT) applications deployed in challenging environments.

The Chiltan Formation is a potential hydrocarbon-producing reservoir in the Indus Basin, Pakistan. However, its diagenetic alterations and heterogeneous behavior lead to significant challenges in accurately characterizing the reservoir and production performance. This manuscript aims to utilize Chiltan Limestone core samples to conduct a detailed analysis of the diagenetic impacts on reservoir quality. The formation evaluation was carried out through thin section analysis, SEM-EDS and FTIR investigation, as well as plug porosity and permeability measurements under different stress conditions. In results, Petrography revealed three microfacies with distinct diagenetic features and micro-nano fossil assemblages, including intraclasts, pelloids, bioclasts, and stylolites. Diagenesis has a significant impact on petrophysical properties, leading to increased reservoir heterogeneity. The specified depositional environment exposed the alteration of the Chiltan formation during distinct diagenetic phases in marine, meteoric, and burial settings. Pore morphology and mineralogy reveals complex micro-pore structure with various carbonate mineral phases and cement types in the formation samples. The average porosity and permeability of the core samples were found to be 3.4% and 0.449 mD respectively, indicating poor reservoir quality. Stress sensitivity was determined using Klinkenberg corrected permeability, which indicated a reduction in measured and absolute permeability due to increasing confining stress, further reducing the pore throat structure of the formation. In conclusion, the Chiltan formation possesses intricate reservoir heterogeneity and varied micro-pore structure caused by diagenesis and depositional settings. The formation is classified as a low-quality reservoir due to its non-uniform pore geometry, which exhibits low petrophysical properties resulting from overburden stress. The results of this study provide solid foundation in reservoir characterization and quality assessment which has implications for exploring and exploitation of indigenous resources.

Ameloblastoma is an aggressive slow growing benign epithelial odontogenic tumor usually associated with an unerupted third molar. In this report, we present the case of a 71-year-old male with a large swelling on the left mandibular region causing a remarkable facial asymmetry. After clinical, radiological, and histopathological examinations the diagnosis of conventional ameloblastoma was made. To avoid probable recurrence our treatment choice was a segmental mandibular resection with the placement of a reconstructive titanium plate to maintain the space for subsequent bone graft.

Soil salinity is seen as a major restriction for crop production, and with water scarcity this problem becomes more complicated. Mulching is crucial to salinity dynamics management by decreasing evaporation with improving the soil’s characteristics. Using chitosan as an eco-friendly biostimulant can enhance plant defense genes during different abiotic stresses. Recently, agricultural research has recognized nanoparticles as a pioneer material due to their distinctive physicochemical features. Therefore, a lysimeter experiment was conducted to investigate the interactive effects of mulching (UNM: un-mulched, WPM: white plastic, RSM: rice straw and SDM: sawdust) and chitosan foliar application (Ch0: control, Ch1: 250 mg chitosan L-1, Ch2: 125 mg nano chitosan L-1, and Ch3: 62.5 mg nano chitosan L-1) on the biochemical soil characteristics and common beans productivity under salt affected soil conditions. Organic mulching (RSM and SDM) treatments significantly improved the soil's organic carbon, available nutrient content, and total count of bacteria. WPM treatment lowered soil EC to 6.63 dS m-1 and increased soil water content to 34.13%. The application of Ch3 caused considerable increases in the plant height, shoot dry weight, root dry weight, grain yield, and nutrient content in the seed. The total fungi count in the soil and Na% in the seed was significantly decreased due to chitosan foliar applications. Moreover, the interactive effect of different mulch materials plus foliar by chitosan applications gave a statistically similar seed yield in both seasons. Overall, this study revealed the potential of the mulching treatments and foliar application of nano chitosan in improved biochemical soil characteristics and common bean productivity under saline soil conditions.

The efficiency with which an integer may be factored into its prime factors determines several public key cryptosystems′ security in use today. Although there is a quantum-based technique with a polynomial time for integer factoring, on a traditional computer, there is no polynomial time algorithm. We investigate how to enhance the wheel factoring technique in this paper. Current wheel factorization algorithms rely on a very restricted set of prime integers as a base. In this study, we intend to adapt this notion to rely on a greater number of prime integers, resulting in a considerable improvement in the execution time. The experiments on composite numbers n reveal that the proposed algorithm improves on the existing wheel factoring algorithm by about 75%

In this study various samples were fabricated by increasing the amount of CNT from 0% to 5%. The bulk mechanical properties of the samples were measured using DMA. Alternatively, the local mechanical properties were assessed using nanoindentation technique. There is a clear trend that the behavior of the material is dependent of carbon fillers before, during and after percolation threshold. The bulk mechanical properties were reduced after the percolation threshold due to CNT agglomeration. Then the samples were exposed to acid solution for one week and one month. Regardless the amount of CNT in the matrix, there is always a gradient of properties from the skin to the core of the sample. There is a net reduction of in physical properties. However, the level of degradation was a dependent of the amount of CNT in the host polymer. At higher concentration the CNTs behave as a barrier. However due to the formation of porosity around the CNT agglomerates, the acid diffusion encounters preferential path ways. . Both techniques lead to the same observation..

Since its inception in 2019, COVID-19 has been associated with significant changes in lifestyle-related behavior, including physical activity, diet, and sleep, which are vital to maintaining our well-being. This study measures lifestyle-related behavior during the COVID-19 pandemic lockdown using a 21-item questionnaire. The responses were collected from March 2021 to September 2021. Four hundred sixty-seven participants were engaged in assessing the changes caused by the pandemic and their effect on BMI. The validity and reliability of the questionnaire were tested for 71 participants. Cronbach's alpha values for the questionnaire all exceeded 0.7, demonstrating good validity and internal consistency for it. The effect of each question regarding physical activity and dietary habits over the BMI difference was studied using ANOVA. The study shows that more than half of the participants reported snacking more between meals and increased their sitting and screen time, while 74% felt more stressed and anxious. These indications were the cause of the increase in the BMI rate for individuals in the lockdown. In contrast, 62% of the participants showed more awareness about their health by increasing the intake of immunity-boosting foods, and 56% of the participants showed an increase in the consumption of nutrition supplements. Females and married individuals tended to be healthier, so their BMI showed stability compared to others based on their gender and marital status.

Seed potato treatment is vital for plant protection, yield enhancement, and product quality. In the conducted research, the plant biostimulator Supporter was applied to evaluate its impact on potato yields. Field studies were conducted in Northeastern, Northwestern, Western, and Southwest Poland from 2015 to 2017, using a randomized complete block design with a split-plot arrangement. The use of seed treatment technology with the Supporter product resulted in increased overall and commercial potato yields and improved yield tuber structure compared to traditional cultivation methods without tuber treatment before planting. Conclusion: The application of the plant biostimulator Supporter in seed potato treatment technology brings significant benefits, including, increased potato yield and improved yield structure. The cultivation location significantly influences potato yield and tuber structure. Understanding these differences can aid in better adapting cultivation practices and selecting varieties to specific local conditions, potentially leading to increased potato crop productivity. In terms of efficiency and yield quality, further research into its application in agricultural practice is recommended, which may contribute to further increasing potato production efficiency and quality. Developing more ecological and efficient farming practices can help meet society's growing food needs.

Ultrasound, as mechanical waves with frequencies exceeding 20 thousand hertz, has found wide applications in medicine, physiotherapy, and more recently in agriculture. This study aimed to investigate the impact of ultrasound on potato yield and its parameters, particularly on seed potato yield, quantity, mass, and multiplication coefficient of potato tubers. The research was based on a three-year field experiment, utilizing the randomized block design in a split-split-plot arrangement, in the central-eastern region of Poland. The primary factor were technologies: a) technology with employing ultrasonic pre-planting treatment, b) traditional cultivation without this treatment. The secondary factors were potato varieties. Sonication of tubers was conducted using a bath-type ultrasonic device equipped with piezoe-lectric transducers. Results revealed a significant influence of cultivation technology, cultivar, and weather conditions on seed tubers yield, quantity, and multiplication coefficient of potato tubers. However, genetic traits of the examined varieties and random factors significantly affected the individual seed tuber mass and the number of shoots emerging from a single tuber. Future Outlook: Future research could focus on further optimizing ultrasound application techniques in potato cultivation, considering diverse varieties and environmental conditions. Additionally, it would be worthwhile to analyze the long-term effects of ultrasound on tuber seed potato quality and their ability to adapt to changing climatic and soil conditions. Furthermore, studies investi-gating the impact of ultrasound on other plant species could broaden our understanding of po-tential benefits in agriculture.

Conventional mechanical Fourier Transform Spectrometers (FTS) are able to simultaneously measure absorption and dispersion spectra of gas-phase samples. However, they usually need very long measurement times to achieve time-resolved spectra with a good spectral and temporal resolution. Here, we present a mid-infrared dual-comb-based FTS in an asymmetric configuration, providing broadband absorption and dispersion spectra with a spectral resolution of 5 GHz, a temporal resolution of 20 μs, and a total measurement time of a few minutes. We used the dual-comb spectrometer to monitor the reaction dynamics of methane and ethane in an electrical plasma discharge. We observed ethane/methane formation as a recombination reaction of hydrocarbon radicals in the discharge in various static and dynamic conditions. The results demonstrate a new analytical approach for measuring fast molecular absorption and dispersion changes and monitoring fast dynamics of chemical reactions, which can be interesting for chemical kinetic research and particularly for the combustion and plasma analysis community.

This paper aims to provide an adaptation of the TL-moments method to censored data. The present study concentrates on Type-I censored data. The idea of using TL-moments with censored data may seem conflicting. But our perspective in that, we may use data censored from one side and trimmed from the other side. This study is applied to estimate the two unknown parameters of the Weibull distribution. The suggested point is compared with Direct L-moments and ML methods. A Monte Carlo simulation study is carried out to compare these method in terms of estimate average, root of mean square error (RMSE) and relative absolute biases (RAB).

Backyard chickens are the most popular poultry in Bangladesh due to their production potential, and income generation. However, this farming can be a factor in zoonotic disease transmission. This study aimed to assess the knowledge, attitudes, and practices (KAP) related to biosecurity and management among backyard chicken households in Bangladesh. A cross-sectional survey was conducted among 295 households in six sub-districts of different six divisions of Bangladesh. The study used a convenient sampling technique to choose the divisions, then the districts and sub-districts. A well-structured pre-tested questionnaire was used to interview randomly selected households. In this study, most of the respondents relied on agriculture crop production (n=128) as their primary source of income, relied on scavenging for their birds’ feeding (34%), or fed their chickens whole or broken rice (32%), used tube well water (58%), used ash (38%) or sand (28%) as litter material. A significant proportion of households (40%) did not use any nest box at all. Results also showed that the most reported poultry diseases among backyard poultry farmers were Newcastle disease (49%), followed by coccidiosis (30%), fowl cholera (12%), and fowl pox (9%). In the multivariate logistic regression model, knowledge of biosecurity was associated with the household type (OR=1.4, p=0.04), knowledge of vaccination (OR=3.7, p=0.02), don’t know category (OR=4.2, p=<0.001), provision of the nest box (OR=9.5, p<0.001), training (OR=0.1, p=0.04), and air pollution (OR=0.1; p=0.04). The study found a huge knowledge gap on management and biosecurity practices present among backyard chicken farmers, which can negatively impact public health for instance in the outbreak of zoonotic diseases. Increasing farmers' biosecurity awareness through education and outreach activities could minimize the risk of disease transmission and improve both public and poultry health.

This study focuses on the difficulties of standardizing Building Information Modeling (BIM) Execution Plans (BEPs) in the Architecture Engineering Construction and Operations (AECO) sector. The main objective is to improve digital transformation by implementing more efficient methodologies. The task involves analyzing 36 BEP documents from different international organizations to identify similarities and differences in terms of content structure operational methods and project characteristics. The research highlights the necessity of implementing a uniform method to enhance collaboration and information sharing in BIM projects. The documents contain key elements such as project information goals roles collaboration procedures model structure and quality control. The paper presents a comprehensive framework for BEPs with the goal of resolving the discrepancies observed in existing methods that impede the efficiency of project delivery. This study utilizes scientometric analysis to examine literature published between 2020 and 2023. The aim is to track the progress of BEP standards identify key research topics and determine influential works in the field. The findings support the implementation of standardized guidelines to reduce inefficiencies and improve the effectiveness of Building Information Modeling (BIM) in large-scale construction projects.

Facility Management (FM) has increasingly focused on using Building Information Modeling (BIM) in large-scale development projects. To successfully integrate BIM in the FM sector, cooperation among different participants involved in various project stages must be improved. The objective of this digital revolution in FM is to enhance the efficacy of planning, constructing, and managing assets, benefiting all parties involved. However, the utilization of BIM in FM is limited due to factors such as incomplete owner understanding, insufficient data accessibility, and stakeholders' unfamiliarity with BIM procedures and standardization. Although the FM industry acknowledges BIM's significance, achieving successful implementation remains challenging. Facility managers lack a clear understanding of BIM's benefits in expediting operations and cost efficiency and the necessary skills for efficient utilization. To address this constraint, it is essential to develop an Employee’s Information Requirement (EIR) at the outset of a project, serving as a strategic plan and providing a comprehensive vision for all parties involved, particularly large-scale projects. Two essential technologies that facilitate the transition towards building operations are BIM and the Internet of Things (IoT). Incorporating these technologies is crucial to reducing time, expenses, and operational challenges throughout any project. The aim of this research is to create a Digital-Trio workflow, as a new expression, by providing a methodology for using facility management with BIM through the integration of EIR and IoT, maximizes the benefit of stakeholders strategically and operationally. It also explores how the preparation of the EIR by communicating with all parties will definitely improve the design process, sustainability, efficiency, cost, and time for any project, especially megaprojects.

Abstract: The empirical soil loss model, RUSLE, was used with a conjunction of remotely sensed data and geographic information system technology to delineate the soil erosion and watershed priorities in terms of conservation practices at seven boundary sub-watersheds (labeled as SW-00, SW-01, …, SW-06) between Iraq and Iran at Ali Al-Gharbi area, southern Iraq. The six factors of the RUSLE model, ie. the rainfall erosivity, the soil erodibility, the slope steepness length, the crop management, and management practice, were calculated or estimated using information from different data sources such as remotely sensed data and previous studies. The finding showed that the annual soil erosion loss ranges from 0 - 1890 (tons h-1 y-1) with an average of 0.66 (tons h-1 y-1). Values of soil erosion were classified into five classes: very low, low, moderate, high, and very high. The potential soil loss in the high and very high classes ranges from 14.84 to 1890 (tons h-1 y-1), and these classes occupy only 27 km2 of the study area, indicating that the soil loss is very low in the area being examined. In terms of the spatial distribution of soil loss, the northern and northeastern parts (mountains and hills) of the sub-watersheds where the slope is steeper are more likely to erode than the plain area in the southern and southeastern portions, indicating that slope, in addition to rainfall erosivity, has a dominant effect on the soil erosion rate. The study of soil erosion in the watersheds under consideration reveals that only the northern portions of the SW-00, SW-02, and SW-04 watersheds require high priority conservation plans; however, these portions are primarily located in mountain regions, making conservation plans implementation in these areas impractical. Due to low soil loss, other sub-watersheds, particularly SW-01, SW-03, SW-05, and SW-06, are given low priority.

This paper aims to investigate the feasibility of strengthening the web opening in the shear zone of RC beams by using iron-based shape memory alloy (Fe-SMA) bars. To conduct this study, numerical analysis with ABAQUS software was employed. The research was divided into six groups of beams with web openings of different lengths (150, 300, and 450 mm), prestressing levels (0%, 30% and 60%), and reinforcement diameters (14, 18, and 22 mm) of Fe-SMA bars. The results show that the presence of web openings can cause a significant reduction in the cracking and ultimate loads of the beams, with reductions ranging from 11 to 50% and 36 to 48%, respectively. However, by adding pre-stressed Fe-SMA bars around small web openings (100×150 mm), the shear capacity of the beam is restored, and the beam exhibits behavior similar to solid beams. Additionally, activating the Fe-SMA bars by 30 and 60% resulted in almost similar cracking loads but improved load-carrying capacity of the beam with small openings by 12% and 9%, respectively, compared to the solid beam. The technique proposed for enhancing shear strength is most effective for beams with small (100×150 mm) and medium (100×300 mm) web openings as it can restore both the beam’s shear strength and stiffness. However, for beams with larger web openings (100×450 mm), the use of activated Fe-SMA beams can recover almost 90% of the solid beam's shear capacity. Furthermore, reinforcing small openings with Fe-SMA bars of different diameters enhances beam shear capacity and stiffness, while for larger openings, higher Fe-SMA reinforcement ratios could potentially restore the beam's full strength and stiffness. This study emphasizes the importance of strengthening web openings in RC beams, particularly in shear zones, and provides significant insights into how to strengthen beams with web openings, thereby contributing to developing safer structures. However, further laboratory experiments are recommended to validate, complement and extend the findings of this numerical study.

This paper proposes a novel efficient multistage algorithm to extract source speech signals from a noisy convolutive mixture. The proposed approach comprises of two stages named Blind Source Separation (BSS) and De-noising. A hybrid source prior model separates the source signals from the noisy reverberant mixture in the BSS stage. Moreover, we model the low and high-energy components by generalized multivariate Gaussian and super-Gaussian models, respectively. We use Minimum Mean Square Error (MMSE) to reduce noise in the noisy convolutive mixture signal in the de-noising stage. Furthermore, two proposed models investigate the performance gain. In the first model, the speech signal is separated from the observed noisy convolutive mixture in the BSS stage, followed by suppression of noise in the estimated source signals in the de-noising module. In the second approach, the noise is reduced using the MMSE filtering technique in the received noisy convolutive mixture at the de-noising stage, followed by separation of source signals from the de-noised reverberant mixture at the BSS stage. We evaluate the performance of the proposed scheme in terms of signal-to-distortion ratio (SDR) with respect to other well-known multistage BSS methods. The results show the superior performance of the proposed algorithm over the other state-of-the-art methods.

The members of the Liliaceae family have been regarded as an excellent source of biologically active compounds. However, the work on antimicrobial potential and characterization of the bioactive fractions of Lilium philadelphicum flower is limited and needs to be explored. The present study reports the antimicrobial potential, anti-inflammatory and anticancer potential of the bioactive fraction extracted from the flower of L. philadelphicum (Red Lily) and characterization of these bioactive compounds. The antimicrobial activity was tested against nine different Gram-positive and Gram-negative bacterial strains. The minimum inhibitory concentration (MIC) values of methanolic extract of L. philadelphicum flower against Acinetobacter bouvetii, Achromobacter xylosoxidans, Bacillus subtilis MTCC 121, Candida albicans MTCC 183, Klebsiella pneumoniae MTCC 3384, and Salmonella typhi MTCC 537 were 25, 50, 12.5, 50, 100 and 50 μg mL-1, respectively. The phytochemical analysis of the extract reveals the presence of phenols, flavonoids, tannins, terpenoids, glycosides, coumarins, and quinones. The cytotoxicity of the partially purified compound against the HepG2 cell line in MTT assay demonstrates up to 90% cell viability with a bioactive compound concentration of 50 μg/ml. However, with the increase in bioactive compound concentration up to 1000 μg/ml results into nearly 80% cell viability, just a minor decline in cell viability suggests the importance of bioactive compounds for suitable therapeutic applications. Spectroscopic studies of the bioactive compound by UV-Visible spectroscopy, FT-Infra Red spectroscopy, Gas Chromatography-Mass Spectrometry (GCMS) as well as its phytochemical analysis suggests the presence of terpenoids moiety, responsible for the antimicrobial property of L. philadelphicum flower.

Abstract: Background: Aging is an important risk factor for cardiovascular diseases and con-vincing data has shown that chronic low-grade inflammation, which develops with advanced age, contributes significantly to cardiovascular risk. Objectives: The present study aimed to use ¹⁸F-FDG/¹⁸F-NaF-PET/CT imaging to respectively gauge arterial inflammation and microcalcifi-cation in healthy elderly and to assess the potential benefits of a tyrosol- and hydroxytyrosol-rich diet on these two markers of atherosclerotic plaque fragility. Methods: Eleven healthy partici-pants (mean age 75 ± 5.67 years) were supplemented for 6 months with high polyphenol-rich extra virgin olive oil (HP-EVOO), extra virgin olive oil (EVOO), or refined olive oil (ROO). The partic-ipants underwent PET/CT imaging with ¹⁸F-FDG and ¹⁸F-NaF radiotracers at baseline and after 6 months. ¹⁸F-FDG and ¹⁸F-NaF uptakes were quantified using standardized uptake values (SUV) and were categorized based on artery calcification and olive oil type. Results: A total of 324 slices of the aortas of the imaged participants were analyzed for arterial inflammation and 327 slices were analyzed for microcalcification. 18F-FDG uptake was significantly higher in the non-calcified segments than in the calcified segments (SUVmax = 2.70  0.62 and SUVmax = 2.54  0.44, respectively, p<0.042). Conversely, the non-calcified segments displayed significantly lower 18F-NaF uptake than the calcified segments (SUVmax = 1.90 0.37 and 2.09  0.24, respec-tively, p<0.0001). The 6-month supplementation with HP-EVOO induced a significant reduction in 18F-FDG uptake in both the non-calcified (2.93  0.23 to 2.75  0.38, p<0.004) and calcified seg-ments of the aortas (2.25  0.29 to 2.15  0.19, p<0.02). 18F-NaF uptake was also significantly low-er in patients supplemented with HP-EVOO (SUVmax = 1.98  0.33 at baseline compared to 1.85  0.28, after the 6-month supplementation, p<0.004), whereas no significant effect was observed with EVOO. Conversely, participants supplemented with ROO displayed a significant increase in 18F-NaF uptake (SUVmax = 1.78  0.34 to 1.95  0.34, p<0.0001). Conclusion: The present study confirmed that ¹⁸F-FDG/¹⁸F-NaF-PET/CT imaging is a valuable approach for assessing age-related arterial damage and demonstrated that a phenolic compound-rich diet reduces both arterial inflammation and atherosclerotic lesion microcalcification.

Contamination of the environment with nano- and microplastic particles exerts a threatened impact on the aquatic ecosystems and sustainable catfish aquaculture. The presence of nanoplastics has been found to have a detrimental impact on both aquatic and terrestrial ecosystems. The present study examines the effect of polystyrene nanoplastics on DNA, erythrocytes, oxidative status and renal of catfish in addition to the potential protective effects of Chlorella vulgaris bioremeditation and selenium to hinder this effect. Six equal groups of fish were used as follows: Group 1: served as a control group and received water free from PS NPs; Group 2: was exposed to PS NPs at a concentration of 5mg/L; Group 3: was exposed to PS NPs (5mg/L) + selenium (1mg/kg diet); Group 4: was exposed to PS NPs (5mg/L) + C. vulgaris (25g/kg diet); Group 5: was supplemented with C. vulgaris (25g/kg diet); and Group 6: was supplemented with selenium (1mg/kg diet). The results indicated that PS NPs induced oxidative stress by significantly elevating MDA activities and slightly reducing antioxidant biomarkers, resulting in DNA damage, increased frequency of micronuclei, erythrocyte alterations, and numerous histopathological alterations in kidney tissue. Selenium and C. vulgaris significantly ameliorated the oxidative/antioxidant status, reduced DNA damage, micronucleus frequency, erythrocyte alterations, and morphology of kidney tissue. Nevertheless, further research is needed to evaluate in detail the mechanism behind the toxicity with nano-microplatics in aquatic system.

This paper presents a theoretical framework aimed at improving IoT network cybersecurity by AI-driven anomaly detection in the context of rapid urbanization and the development of smart cities. The framework draws upon the Complex Adaptive Systems Theory, Theory of Planned Behavior, the Technology Acceptance Model, and the Socio-Technical Systems Theory, and intri-cately examines how AI might be integrated into the intricate ecosystem of smart cities to detect and mitigate cyber threats. It emphasizes AI-driven anomaly detection methods as pivotal in-struments that impact cybersecurity enhancement in smart city infrastructures. The proposed framework also highlights the crucial role that human-related factors, including user behavior and adoption, play in determining how effective AI applications are in enhancing cybersecurity in smart cities. It also recognizes the important moderating roles played by outside factors like legislative frameworks, environmental contexts, and technological breakthroughs in the relationship between AI-enabled anomaly detection and enhanced cybersecurity. The goal of this research is to shed light on the interactions between technology and socio-technical dynamics by offering a thorough theoretical understanding of AI's potential in smart city cybersecurity. It highlights the significance of taking into account a variety of contextual aspects when employing AI to strengthen the digital security of urban areas, and provides a strategic direction for future research and practical implementation.

Integrating numerous renewable resources has been extensively researched and studied to create a dependable energy system. This study investigated the best techno-economical hybrid energy system configuration while using hydrogen energy to keep the system's energy balanced. Additionally, this study aims to determine the best hybrid system configuration for the location under investigation. A novel technique of DBM (Deterministic Balanced Method) was introduced to determine the total annual energy output for the project's lifetime. This approach is used to contrast the outcomes of other HOMER software tools. Then, using HOMER, it is possible to confirm the sizing optimization results for the suggested method by comparing the power ratings and yearly energy output. A detailed comparison between our proposed method and HOMER Pro has been conducted for validation and verification. Our method has been rigorously tested in various hybrid off-grid energy systems, ensuring its applicability and reliability across different scenarios and configurations. The results of our study indicate a high degree of similarity between the proposed approach and HOMER pro for computing annual energy power for the studied energy systems. Specifically, our analysis revealed that the difference between the approaches was within a range of 5%, indicating a high level of consistency and reliability in our method. These findings suggest that our approach can be confidently applied to determine the appropriate size of hybrid energy systems accurately. Overall, our study provides valuable insights into the development of effective sizing methodologies for hybrid energy systems. After considering the amount of solar radiation and wind speed gathered by global weather data platforms like NASA and METEONORM, this paper has also included a real case study of the Cairo International Airport's hybrid renewable energy production systems. To guarantee the viability of this study, the system design was founded on an actual load that was researched and simulated. A cluster of distributed networks was finally proposed to use the excess energy and enable energy conversion processes to be used in industry and transportation applications.

This narrative review aims to summarize evidence regarding the current utilization and future applications of neuromodulation in patients with headaches, with special attention paid to migraine and chronic cluster headache. We performed a narrative review of the literature to identify studies that detail the effectiveness of neuromodulation therapies in the treatment of headache syndromes. The literature was refined to predominantly focus on systematic reviews published in the last year that have the most robust reporting of research done on this topic. Patients with headache face several challenges, including medication overuse, cost burden, non-compliance to medications due to inability to tolerate side effects, or treatments that are ineffective. Neuromodulation is an emerging field that encompasses implantable and non-implantable technologies that intervene on the signaling and perception of pain. In recent years, this technology has been used as an analgesic, and has been shown to be effective for treatment-resistant headache, particularly when used in patients with migraine and chronic cluster headache.

Businesses use technological and social media marketing to respond to the Covid-19 pandemic. This study aims to understand better the factors that impact the spread of new technologies, the effectiveness of social media advertising, and the longevity of businesses. The study used a quantitative strategy based on partial least squares structural equation modeling to learn about the phenomenon of interest as much as possible. Dhaka, Bangladesh, small and medium-sized businesses participated in the survey. According to the findings, the popularity of internet and e-business technologies may be attributed to their apparent usefulness and ease of use. It is connecting internet/e-business technology, social media marketing, and the long-term success of small and medium-sized enterprises. Still, the expense factor was insufficient to prove that SMEs engage in social media advertising. Mediating effects between components may be better understood via internet/e-business technology and social media marketing, as shown by this study. This study is the first of its kind in Bangladesh and sheds light on the resilience of SMEs in the face of the Covivirus-19 pandemic, notwithstanding its focus on the capital city of Dhaka.

Conyza canadensis is a species invading large agricultural areas throughout the world, mainly to its ability to evolve herbicide resistance. Specifically, in Hungary, extensive areas have been infested by this species due to the difficulty in controlling it with glyphosate. To corroborate this fact as resistance and not as an incorrect herbicide application, eight suspicious glyphosate-resistant C. canadensis populations from different Hungarian regions were studied. In dose-response assays with glyphosate, the LD50 and GR50 values indicated that populations 1 to 5 were resistant to this herbicide (H-5 population the most resistant). Besides, the shikimic acid accumulation tests corroborated the results observed in the dose-response assays. 11 alternative herbicides from 6 different mode of action (MOA) were applied at field doses as control alternatives on populations H-5 and H-6 (both in the same regions). The H-5 population showed an unexpected resistance to flazasulfuron (ALS-inhibitor). The ALS enzyme activity studies indicated that the I50 for H-5 was 63.3 fold higher compared to its correspondent susceptible population (H-6). Therefore, the H-5 population exhibited multiple-resistance to flazasulfuron and glyphosate, being the first case reported in Europe for this two MOA. For that reason, the other herbicides with different MOA have to be tested here.

Background: The potential of Artificial intelligent (AI) models to process and interpret large health datasets at scale could revolutionize public health and epidemiology, providing a foundation for public health. Ethics has been recognized as a priority concern in the development and deployment of AI. Because AI technology can jeopardize patient safety, privacy, and posing a new set of ethical problems that must be addressed. Objectives: We aim to provide a holistic view on what are the different ethical and legal principles that was addressed in the included studies regarding the use of AI in public health and what are the ethical challenges that can arise.Methods: Following PRISMA guideline, five bibliographic databases were used in our search: PubMed, Scopus, JSTOR, IEEE Xplore, and Google Scholar from 2015 to February 2022. Four reviewers carried out study selection and data extraction, and the data extracted was synthesized by a narrative approach. Results: This review included 23 unique publications out of a total of 1123 items that were initially identified. Different ethical principles regarding the uses of AI in public health and community health were identified and discussed distinctly in the current review. The common ethical and legal themes that this review focused on are equity, bias, privacy and security, safety, transparency, confidentiality, accountability, social justice, and autonomy. In addition, five ethical challenges were mentioned. Conclusion: Research regarding ethical and legal principles and challenges about using AI in public health specifically consider a new filed, because all previous themes are concerning the physical and patients’ area where it focuses only on the clinical settings.

The occurrence and ability of Salmonella typhimurium to withstand the effects of various antibiotics has been extensively recorded. This highlights the necessity for alternative methods to combat Salmonella infections. The current investigation aimed to ascertain the impact of benzoic acid on the extent of surface coverage and biomass of S. typhimurium biofilm after 48 and 72 hours. The findings indicated that all the different doses of benzoic acid (ranging from 3.125% to 50%) resulted in a decrease in the extent of biofilm surface coverage. Benzoic acid exhibited a substantial inhibitory effect on the biofilm biomass at all concentrations. Higher concentrations of benzoic acid led to a decrease in biofilm biomass, suggesting a concentration-dependent response. This finding implies that benzoic acid is effective in managing Salmonella infections.

Endophytic fungi isolated from plants of different ecosystems have an impressive ability to produce diverse chemical classes of bioactive secondary metabolites. In this study, the cytotoxic activity and chemical composition of the ethyl acetate extract of the white beans culture of the endophytic fungus (FWBC), Talaromyces wortmannii isolated from the widespread reed grass, Arundo donax L. were investigated. A new ceramide named talaramide (1), along with other four known compounds; stigmasterol (2), thymine (3), uracil (4), and stigmasterol-3-O-β-D-glucoside (5) were identified. The structure of compound 1 was elucidated based on extensive 1D and 2D NMR spectroscopic techniques in combination with HR-ESI-MS. The produced FWBC extract exhibited cytotoxic activity against three cancer cell lines viz., MCF7, HepG2, and A549 (IC50; 54.57 ±0.27, 57.12 ± 0.59 and 84.33 ± 1.07 µg/mL, respectively) compared to methotrexate (IC50; 80.25 ± 1.11, 83.83 ± 0.74 and 153.20 ± 2.03 µg/mL, respectively) as a positive control. It showed selectivity indices with values ranging from 1.37 to 2.11 using the normal cell line, WI38 (IC50; 115.43 ± 1.92 µg/mL). The observed cytotoxicity, combined with acceptable selectivity indices, suggests the potential of this endophyte as a source of anticancer agents. Based on previous reports, it was also suggested that the identified ceramide could be responsible for the observed cytotoxic activity of the investigated extract.

In the recent years, biochar has emerged as a remarkable biosourced material for addressing global environmental, agricultural, biomedical, and energy challenges. However, the performances of biochar rest in part on finely tuning its surface chemical properties, intended to obtain specific functionalities. In this review, we tackle surface treatment of biochar with silane and other coupling agents such as diazonium salts, titatantes, ionic/non-ionic surfactants, as well as nitrogen-containing (macro)molecules. We summarize the recent progress achieved mostly in the last five years, and correlate the nature and extent of functionalization to eye catchy end applications of the surface engineered biochar.

In today's world, the significance of reducing energy consumption globally is increasing, making it imperative to prioritize energy efficiency in the 5th Generation (5G) networks. However, it is crucial to ensure that these energy-saving measures do not compromise the Key Performance Indicators (KPIs) such as user experience, quality of service (QoS), or other important aspects of the network. To address this challenge, advanced wireless technologies have been incorporated into the design of 5G networks across various network layers. Given the rapid advancements in Artificial Intelligence (AI) and emerging technology trends such as Machine Learning (ML), which is considered a subset of AI, the integration of such trends into 5G networks has become a significant area of research. The primary objective of this survey is to analyze AI integration into 5G networks for enhanced energy efficiency. By exploring this intersection between AI and 5G, we aim to identify potential strategies and techniques for optimizing energy consumption while maintaining the desired network performance and user experience.

Introduction: Acute compartment syndrome (ACS) is a surgical emergency that requires urgent intervention in order to prevent permanent structural damage and irreversible functional disability. The diagnosis of ACS depends on a high index of suspicion, relying on the following diagnostic criteria commonly known as the 5 Ps; Pain, Paresthesia, Paralysis, Pallor, and Pulse-lessness. When the diagnosis is uncertain, intracompartmental pressure greater than 30 mmHg is suggestive of ACS. Case Presentation: We report a case of an underdiagnosed ACS, with a lack of classical presentation in a thirty-seven-years-old male patient with a history of myopathy. The patient was admitted to the emergency room due to direct trauma to his right hip, without a significant Visual Analogue Score. On his hip radiograph a subtrochanteric fracture of the right femur was demonstrated. An additional masked ipsilateral subcapital fracture was detected during the operation. The diagnosis of ACS was made during the operation while relying on the clinical appearance of the thigh and the clinical findings during surgery. Fasciotomies were performed, and open reduction with internal fixation via Proximal Femoral Nail was done. The diagnosis of ACS was confirmed later on, by the biopsy results. Conclusion: This case suggests that myopathy can mask the classical presentation of ACS. Furthermore, the extent of pain complaints and accompanying paresthesia cannot be relied on in this regard and other clinical features should be considered in order to diagnose ACS.

Background: ED overcrowding is described as one of the main issues in emergency departments (EDs) of any hospital. In Saudi Arabia, the ministry of health applied new telemedicine technology to serve patients by using the mobile application which include Sehha application and 937 medical call center. The main aim of this study is to determine the role of different telemedicine services in reducing non-urgent visits to EDs in Saudi Arabia. Methods: A cross-section study was conducted during August 2020 - May 2021 among 319 patients were using two telemedicine services in Saudi Arabia, including medical call center, and Sehha smart phone application. The primary endpoint of this study aims to determine the role of different telemedicine services in reducing non-urgent visits to EDs in Saudi Arabia. Results: This study analyzed the data from 319 patients who completed the survey provided by the Saudi Ministry of Health that concerning on information related to their health status, and ED visits. Among patients that had the intention to visit the ED (N=159), 53 of them did not go to EDs after using telemedicine services (p-value < 0.01). Regarding medical call center and Sehha application, 9.6% and 24.4%, respectively of the patients used these telemedicine services had changed their mind concerning visiting ED after taking the medical advice (p-values < 0.01).Conclusion: The implemented telemedicine services in Saudi Arabia, namely Sehha application and medical call center showed to be effective in reducing ED overload by providing medical advices to less- and non-urgent patients and deal with their minor medical issues.

Abstract: Cleft palate is a congenital condition result from incomplete fusion of palatine shelves. The current study aimed to assess the effects of vitamin B6 on the incidence of corticosteroid-induced cleft palate model. Eighteen pregnant mice were divided into three groups. Mice of control group were injected with sterile physiological saline from 11th - 14th days of gestation. Mice of group II were injected with 125 mg/kg hydrocortisone from 11th - 14th days of gestation. Mice of group III were injected with hydrocortisone as in group II and given drinking water containing 500 µg/ml of vitamin B6 from day zero of gestation until delivery. Two days after delivery, the offspring were counted, and their head circumferences were taken for statistical analysis. The heads of the offspring were fixed and processed for paraffin sectioning and stained with hematoxylin and eosin. Cleft palates were counted and statistically analyzed using ANOVA test to determine any significances (P

The COVID-19 pandemic forced the transition to emergency online learning without prior preparation or guidelines. This transition has been particularly challenging in developing countries and low-resource contexts and hindered student engagement. We aim to identify the engagement strategies which students, engaging in emergency online learning in low-resource contexts, perceive to be effective. We conducted a sequential mixed-methods study based on Moore’s interaction framework for distance education. First, we conducted a literature review and interviewed ten teachers and ten students to identify a list of engagement strategies. Then, we designed a questionnaire that examines student perceptions of these strategies. We administered the questionnaire to 313 students engaging in emergency online learning in low-resource contexts. Our analysis results showed that student-content engagement strategies, e.g. screen sharing, summaries, and class recordings, are perceived as the most effective, closely followed by student-teacher strategies, e.g. Q&A sessions and reminders. Student-student strategies, e.g. group chat and collaborative work, are perceived as the least effective. The perceived effectiveness of engagement strategies depends on the context and the students’ characteristics, e.g. gender, major, and technology access. To support instructors, instructional designers, and researchers we propose a ten-level guide for engaging students during emergency online classes in low-resource contexts.

Using a combination of pan proteomic platform associated with systemic biology analyses, we demonstrate that neonatal microglial cells derived from cortex and spinal cord expressed different phenotypes upon the physiological or pathological conditions. They also highlight great variability in protein production on both cellular and exosome levels. Bioinformatics data indicate for the cortical microglia anti-inflammatory and neurogenesis/tumorigenesis characteristics, while for the spinal cord microglia involvement in the inflammatory response. We confirmed these results by performing functional testing including neurite outgrowth assays in DRGs cell line, and glioma proliferation analysis in 3D spheroid cultures. Results from these in vitro assays indicate that the microglia located at different CNS areas reveal differential biological functions. While both microglia sources enhanced growth of DRGs axons, only the spinal microglia significantly attenuated glioma proliferation. Overall these findings are pointing to the fact that the origin of neonatal microglia affects the physio-pathological function, which may address the prevalence of the glioma in the brain in comparison with the spinal cord in adult.

We isolated two highly pathogenic avian influenza viruses (HPAIVs) of subtype H5N8 clade 2.3.4.4b from falcated duck (Anas falcata) feces and environmental water collected at an overwintering site in Japan. Our isolates were almost genetically identical to each other and showed high genetic similarity with H5N8 HPAIVs recently isolated in South Korea, a distant part of Japan, and European countries. These results suggest the potential role of falcated ducks in the dissemination of HPAIVs.

This mini-review critically summarizes the knowledge of imprinted polymer-based electrochemical sensors, for the detection of pesticides, metal ions and waterborne pathogenic bacteria, focusing on the period the last 5 years (citation of 78 papers published in 2017-2021, ie 63% of total citations). MIP-based electrochemical sensors exhibit low limit of detection, high selectivity, high sensitivity and low cost. Herein, we focused on the timely topics of water pollution by organics, inorganics and micro-organisms represented by pesticides, metal ions and bacteria, respectively. We put the emphasis on the design of imprinted polymers and their composites and coatings by radical polymerization, oxidative polymerization of conjugated monomers or sol-gel chemistry. Whilst most imprinted polymers are used in conjunction with differential pulse or square wave voltammetry for sensing organics and metal ions, electrochemical impedance spectroscopy (EIS) appears as the chief technique for detecting bacteria. This successful combination of EIS and imprinting technology should be harnessed in the coming years in the case of bacteria. Interestingly, bacteria are not always probed by bacteria-imprinted polymers; we report here their detection by monitoring specific (macro)molecules that reflect bacterial activity, for example quorum sensing signaling molecules or flagella proteins. If much has been developed in the past decade with glassy carbon or gold electrodes, it is clear that carbon paste electrodes of imprinted polymers are more and more investigated due to their versatility. Shortlisted case studies were critically reviewed and discussed; clearly a plethora of tricky strategies of designing selective electrochemical sensors are offered to “Imprinters”. We anticipate this review will be of interest to experts and new comers in the field who are paying time and effort combining electrochemical sensors with MIP technology.

The morphology, internal architecture, and emplacement mechanisms of the Central Atlantic Magmatic Province (CAMP) lava flows of the Hartford and Deerfield basins (USA) are presented. The Talcott, Holyoke, and Hampden formations within the Hartford basin constitute distinct basaltic units, each exhibiting chemical, mineralogical, and structural differences corresponding to flow fields. Each flow field was the result of several sustained eruptions that produced both inflated pahoehoe flows and subaquatic extrusions: 1–5 eruptions in the Talcott formation and 1-2 in Holyoke and Hampden basalts, where simple flows are dominant. The Deerfield basin displays the Deerfield basalt unit, characterized by pillow lavas and sheet lobes, aligning chemically and mineralogically with the Holyoke basalt unit. Overall, the studied flow fields are composed of thick, simple pahoehoe flows that display the entire range of pahoehoe morphology, including inflated lobes. The three-partite structure of sheet lobes, vertical distribution of vesicles, and segregation structures are typical. The characteristics of the volcanic pile suggest slow emplacement during sustained eruptive episodes and are compatible with a continental basaltic succession facies model. The studied CAMP basalts of the eastern United States are correlated with the well-exposed examples on both sides of the Atlantic Ocean (Canada, Portugal, and Morocco).

Understanding the distribution of rock glaciers provides key information for investigating and recognizing the status and changes of the periglacial environment. Deep learning algorithms and red-green-blue (RGB) bands from high-resolution satellite images have been extensively employed to map rock glaciers. However, the near-infrared (NIR) band offers rich spectral information and sharp edge features that could significantly contribute to semantic segmentation tasks, but it is rarely utilized in constructing rock glacier identification models due to the limitation of three input bands for classical semantic segmentation networks, like DeeplabV3+. In this study, a dual-encoder DeeplabV3+ network (DEDNet) was designed to overcome the flaws of classical DeeplabV3+ network (CDNet) when identifying rock glaciers using multispectral remote sensing images by extracting spatial and spectral features from RGB and NIR bands, respectively. This network, trained with manually labeled rock glacier samples from QiLian Mountains, established a model with accuracy, precision, recall, specificity, and mIoU (Mean Intersection over Union) of 0.9131, 0.9130, 0.9270, 0.9195, and 0.8601, respectively. The well-trained model was applied to identify new rock glaciers in a test region, achieving a producer's accuracy of 93.68% and a user's accuracy of 94.18%. Furthermore, the model was employed to two study areas in northern Tien Shan (Kazakhstan) and Daxue Shan (Hengduan Shan, China) with high accuracy, which proved that the DEDNet offers an innovative solution to more accurately map rock glaciers on a larger scale due to its robustness across diverse geographic regions.

Modern research achievements support health-promoting effects of natural products and diets rich in polyphenols. Pomegranate (PG) (Punica granatum L.) contain a considerable number of bioactive compounds that exert a broad spectrum of beneficial biological activities, including antimicrobial, antidiabetic, antiobesity, and atheroprotective properties. In this view, the reviewed literature shows that PG intake might reduce insulin resistance, cytokine levels, redox gene expression, blood pressure elevation, vascular injuries and lipoprotein oxidative modifications. Lipid parameters corrective capabilities of PG-ellagitannins are also sufficiently reported to be significantly effective in reducing hyperlipidemia (TC, LDL-C, VLDL-C, and TAGs), plasma HDL-C concentrations, TC/HDL-C and LDL-C/HDL-C ratio. The health benevolent effects of pomegranate consumption appear to be produced through the amelioration of adipose tissue endocrine function, fatty acid utilization, GLUT receptor expression, paraoxonase activity enhancement, PPAR and NFκB modulation. Although the results from animal experiments are encouraging, human findings published in this field are inconsistent and still limited in many points of view. The present review discusses and provides a critical analysis of PG's bioeffects on metabolic syndrome components, type-2 diabetes, obesity, and dyslipidemia, as well as on some cardiovascular-related diseases. A brief overview of the pharmacokinetic properties, safety, and bioavailability of PG-ellagitannins is also included.

Even after debridement and chemical root canal preparation, multispecies bacterial biofilms can still be found in root canals and dentinal tubules. This demonstrates the necessity of using suitable antibacterial endodontic sealers. Due to their well-known biological qualities, calcium silicate based root canal sealers or “bioceramic’ sealers have recently been launched and can be successful in endodontic procedures. This study's objective was to compare the impact of CerasealR, Total Fill BC SealerR, Bio-C SealerR, AH Plus BioceramicR, K-biocerR and SealiteR on the elimination of a multispecies’ endodontic biofilm at 3, 7 and 14 days. Enterococcus faecalis, Pseudomonas Aeruginosa, Candida Albicans and Proteus Mirabilis were cultured on specific agars and later grown in Brain Heart Infusion broth on hydroxyapatite discs pretreated with collagen type 1 and incubated for 18 days. The resulting biofilm was then placed on a 10mm round shaped blotting paper set on a metallic net in a 6cm petri dish with an orthodontic bend filled with the calcium silicate based root canal sealer in direct contact with the biofilm. In all tested groups, the total bacterial count has significantly decreased between day 3 and day 14 (P<0.05) with no statistically significant differences among the different sealers’ groups at all time points. Sealite group was capable of decreasing the Candida Albicans count significantly between day 3 and day 14 (P<0.05) in comparison with the bioceramic groups. All sealers had antibacterial activity against the multispecies biofilm between day 3 and day 14.

Background: Several reports indicate that long stay at home for online schools due to the COVID-19 pandemic changed the normal physical activity and body weight of school-age students. Previous studies revealed that almost 50% of school students complained of increased or decreased more than 3 kg of weight due to lower physical activity. This study aims to provide insight about the Body Mass Index (BMI) among school students during COVID-19 pandemic. Methods: A retrospective matched-longitudinal study was conducted in 2022 based on previous data about BMI-for-age percentile in school-age students aged 6 to 18 years. These data were collected the year before and during COVID-19 pandemic (2019-2021). Results: All the included students were Arabic (N = 53,580) and were not diagnosed with chronic illness. The outcomes showed that the overall percentage of students with normal weight was 54%, 56%, and 53% during the 2019-2021 years, respectively. Overweight among students increased during the COVID-19 pandemic years, as almost 10% of the students were overweight in 2019 compared with 12% in 2020 and 2021 years. Besides, obese students also increased in the 2020-2021 period compared with the 2019 year (15-17% vs. 10%). In contrast, underweight trends among students declined, as 26% reported in 2019 compared to 17-18% in 2020 and 2021. Conclusion: There are significant variations in Arabic school-age students regarding their BMI values. Obesity was highly detected among children and adolescents during the COVID-19 pandemic years compared to 2019, while underweight cases declined.

In Pakistan, the incidence of HIV/AIDS is rising, particularly among transgender individuals, who face significant marginalization in various aspects of life, leading to compromised health-related quality of life (HRQoL). This study aimed to assess the HRQoL of transgender individuals living with HIV/AIDS and explore its correlation with social disparities. Using the validated WHO EQ-5D-5L scale, HRQoL was evaluated among 106 transgender patients with HIV/AIDS from Mayo Hospital and Fountain House Hospital, Lahore, Pakistan, following ethical considerations with PACP. Data analysis employed the Mann-Whitney and Kruskal Wallis tests. The research revealed that HIV/AIDS moderately impacts the HRQoL of transgender individuals due to physical, psychological, and social factors. Comorbidities further exacerbated the HRQoL among this population. In conclusion, managing multiple health issues, including comorbidities, can substantially diminish the quality of life for transgender individuals with HIV/AIDS. Hence, comprehensive healthcare services should address both HIV/AIDS and associated comorbidities to ensure holistic care.

Background: The current review was conducted to determine the effectiveness of atenolol on all-cause mortality rate among Asian patients with chronic progressive diseases, mainly diabetes mellitus, primary hypertension, and coronary artery disease. Methods: We searched the COCHRANE, MEDLINE, TRIP, and EMBASE databases for published articles up to 31 March 2023. Studies that compared all-cause mortality rates among Asian patients who were on atenolol or other medications were included. Results: The review included 79603 Asian patients from three cohort studies. Out of the studied patients, 36046 were atenolol users and 43557 were non-atenolol users. The review revealed that atenolol users recorded lower all-cause mortality rates compared to non-users with a significant difference (OR= 0.57, CI= 0.44-0.75, P<0.001). The pooled estimate of the all-cause mortality rate was also lower among atenolol users (7.02%) compared to metoprolol tartrate users (13.15%) with a significant difference (OR= 0.50, CI= 0.47-0.53, p < 0.0001). Although the included studies were categorized as having a low risk of bias for most of the studied domains, significant heterogeneity was recorded across these studies (I2 =88%, P=0.001). Conclusion: This review found that atenolol when compared to a control or metoprolol tartrate, has a significant effect in reducing the all-cause mortality rate among Asian patients with chronic progressive disease.

Change Detection (CD) of aerial images refers to identifying and analyzing changes between two or more aerial images of the same location taken at different times. The CD is a highly challenging task due to the need to distinguish relevant changes, such as urban expansion, deforestation, or post-disaster damage assessment, from irrelevant ones, such as light conditions, shadows, and seasonal variations. Many CD papers have recently been published, where most of the papers that proposed a new model contained a comparison between their proposed and state-of-the-art (SOTA) models. While many recent studies propose new deep learning (DL) models for improving CD performance, their comparative analyses are often restricted, lacking comprehensive insights into the proposed models' real-world generalizability, robustness, and performance trade-offs across diverse change characteristics. This paper presents a novel generic framework to systematically benchmark and assess DL-based CD models through three parallel pipelines: 1) cross-testing models on diverse benchmark datasets to evaluate generalization, 2) robustness analysis against different image corruptions, and 3) multi-faceted contour-level analytics evaluating detection sensitivity to change size/complexity. The framework is applied to comparatively evaluate five state-of-the-art DL-based CD models - Changeformer, BIT, Tiny, SNUNet, and CSA-CDGAN. Extensive experiments unveil each model's strengths, limitations and biases, highlighting their relative proficiencies in generalizing across data distributions, resilience to noise corruption, and discriminative capabilities for changes of varying characteristics. The proposed benchmarking framework demonstrates significant potential for guiding the selection of suitable CD models tailored to specific application requirements by comprehensively evaluating their generalizability, robustness, and detection capabilities across diverse real-world scenarios. This systematic evaluation approach can drive future research into developing more robust and versatile CD solutions aligned with practical needs.

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

Background: COVID-19 vaccines have been a game changer in the pandemic, their extensive use was favorable compared to the burden of COVID-19 complications. Despite the low incidence of complications, it was important to analyze them carefully to understand the underlying mechanisms and predisposing factors. For instance, myopericarditis especially from mRNA vaccines, and its relatively higher prevalence in young adults and adolescents has raised a public concern about the use of this vaccine in this group. We aimed through this review to compare the age likelihood of ADEM from COVID-19 vaccines, with that reported in myopericarditis cases; secondary outcome parameters included the gender and number of doses needed to induce COVID-19 vaccines related ADEM. Methodology: A literature search has been conducted on relevant databases to retrieve all case reports/series and systematic reviews describing ADEM with possible linkage to COVID-19. Exclusion criteria included any report not including the desired outcome parameters. Our results were then qualitatively compared with a similar systematic review reporting myopericarditis from COVID-19 vaccines. Results: In 38 cases with ADEM, mean age was 49±16 compared to 25±14 in myopericarditis, females were more likely to be affected, and while most of myopericarditis cases develop after the second dose, most of ADEM cases develop after the first dose (76%). Moreover, age>56 years was more predictive of negative outcome after ADEM in the form of death or permanent vegetative state. Conclusion: The discrepancy in age, gender and number of doses needed to induce complications between ADEM and myopericarditis, signify that the tissue affected is the major orchestrator of the age, gender, and dose characteristics, and not the type of vaccines. A leakier blood brain barrier with aging, might allow easier passage of autoantibodies and cytokines into the brain while lack of inhibitory immune checkpoints in the myocardium in young age might explain the higher prevalence of those cases in young adults and adolescents.

There is a rising global concern for the ongoing outbreak of SARS-CoV-2 due to its high transmission rate and unavailability of treatment. Through the binding of its spike glycoprotein with angiotensin type 2 (ACE2), SARS-CoV-2 can efficiently get in the cells of patients and start its pandemic cycle. Herein, the biological diversity of SARS-CoV-2 infection was assessed in Babylon province of Iraq by investigating the possible genetic variations of the spike glycoprotein. A specific coding region of 795 bp within the viral spike (S) gene was amplified from 19 patients who suffered from obvious symptoms of SARS-CoV-2 infection. Sequencing results identified fifteen novel nucleic acid variations with a variety of distributions within the investigated samples. The electropherograms of all the identified variations showed obvious co-infections with at least two different viral strains per sample. Within these co-infections, the majority of samples exhibited three nonsense single nucleotide polymorphism (SNP)s, p.301Cdel, p.380Ydel, and p.436del, which yielded three truncated SARS-CoV-2 spike glycoproteins of 301, 380, and 436 amino acids length, respectively. The network and phylogenetic analyses indicated that for all viral infections were derived from multi-ancestral origins. Results inferred from the specific clade-based tree entailed that some viral strains were derived from European G-clade sequences. In conclusion, our data demonstrated the absence of any single strain infection among all investigated viral samples in the studied area, which may entail a higher risk of SARS-CoV-2 in this country. Through the identified high frequency of truncated spike proteins, we suggest that defective SARS-CoV-2 may depend on helper strains having intact spikes in its infection. Alternatively, another putative ACE2-independent route of viral infection way also suggested. To the best of our knowledge, this is the first report to describe the co-infection of multiple strains of SARS-CoV-2 in patients with COVID-19.

Breast cancer (BC) is among the leading causes of mortality from cancer in women. Many of the available anticancer drugs have various side effects. Therefore, researchers are seeking novel anticancer agents particularly from natural compounds and in this regard, snake venom is still one of the main sources of drug discovery. Previous studies showed potential anticancer effects of Cytotoxin II (CTII) from Naja naja oxiana against the different types of cancers. In this study, a pET-SUMO-CTII vector was transformed into SHuffle® T7 Express, an Escherichia coli strain, for recombinant protein expression (rCTII) and the cytotoxic effects of this protein was assessed in MCF-7 cells. The flow cytometry assay was applied to measure the apoptosis and cell cycle. Also, mRNA levels of the Bax, Bcl2, P53, caspase-3, caspase-8, caspase-9, caspase-10, matrix metalloproteinases (MMP)-3, and MMP-9 were analyzed by quantitative real-time PCR to determine the underlying cellular pathways affected by rCTII. The results of this study showed that treatment with 4 µg mL-1 of rCTII enhanced apoptosis through the intrinsic and extrinsic pathways. Also, the increase of the cells' proportion in the sub-G1 phase as well as a reduction in S phase was observed. In addition, the expression of MMP-3 and MMP-9 was decreased in the treated group in comparison to the control group that may contribute to the reduced migratory ability of tumor cells. These experimental results indicate that rCTII has anti-proliferative potential, and so this protein could be a potential drug for BC therapy in combination with other drugs.

In many Indian regions increased wastewater is both a threat and an opportunity. Efficient wastewater treatment and reuse schemes are needed in India to face impending water and fertiliser shortages. This study explores the application potential of wastewater fertigated Short Rotation Coppice systems (wfSRC) as a cost-efficient and promising solution for treating and reusing wastewater in a specific region (400 km2, 184 settlements) of Aligarh (UP), India. Based on real data from a local wfSRC pilot site using bamboo, willow, and poplar, we analysed the system’s treatment performance, nutrient recovery, carbon sequestration potential, land requirements, biomass production potential, and cost-benefit, under various scenarios. The results show that the pilot wfSRC system is efficiently treating 250 m3/day of domestic wastewater on 6,864 m2 of land, and serving 2,500 people. The land requirements for wfSRC systems vary depending on local conditions and user requirements, ranging from 2.75 – 25.7 m2/PE which equates to a required land area in the whole study region of between 108 and 1006 ha in 2036. This would produce up to 100 DM t/ha/yr of valuable biomass. Early local stakeholder involvement and monitoring of pollutants are recommended as priorities during the planning process for large-scale implementation of wfSRC systems in India.

This study employs Geographic Information System (GIS) techniques to evaluate the walkability of Onaizah City, which serves as a representative model for a Saudi city situated in the Qassim region, north of the capital city, Riyadh. The goal is to evaluate how easily pedestrians can navigate the street network and identify areas that excel or need improvement in terms of walkability. The results offer insights for planning and development supporting sustainable initiatives. Approach; The study involves integrating GIS data, such as street layouts, land use patterns, and demographic information. By analyzing factors like integration values and choice values within the street network the study gauges’ walkability aspects. Furthermore, correlation analysis explores how spatial arrangements, influence walkability. By studying the case of a medium-sized Saudi city, which can then be applied to several Saudi cities. Cost distance analysis and cost-back correlation calculations are employed to determine pedestrian routes. Findings and Discussion; Through GIS techniques the study effectively assesses the walkability of Onaizah City by identifying three walking paths with lengths of (1401m, 1283m, and 1507m). The study reveals pedestrians' actual city distance. Weighted criteria assign 40% to heritage sites, 30% to green spaces, and 15% each to mosques/commercial sites. Preserving access to heritage sites and incorporating areas enhance walkability. Conclusion: Study enhances walkability understanding, offering data-driven planning suggestions. Urban planners prioritize pedestrian connectivity, considering GIS effectiveness and physical environment importance. Findings support walkability research and sustainable urban development.

Terminalia arjuna possesses significant cardio protective, antidiabetic and antioxidant properties as these properties are described in Ayurveda. In the present study, three flavonoids were isolated through the separation and chromatographic purification of the whole plant material of T. arjuna. Spectroscopic characterization identified one of them as a new flavonoid “Terminalone A (1)” and two known flavonoids i.e. 6-hydroxy-2-(4-hydroxyphenyl)-7-methoxy-4H-chromen-4-one (2) and 2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-4H-chromen-4-one (3). The bioactivity studies showed considerable antibacterial and antioxidant (DPPH was used as a scavenger) potential for all the three compounds 1-3 where the compound 1 showed strong antibacterial and antioxidant activity.

This paper presents a novel cheminformatics approach for the design and synthesis of hydroxyapatite/collagen nanocomposites, which have potential biomedical applications in tissue engineering, drug delivery, orthopedic and dental implants. The nanocomposites are synthesized by the co-precipitation method with different ratios of hydroxyapatite and collagen, and their mechanical, biological, and degradation properties are analyzed using various experimental and computational techniques, such as attenuated total reflection Fourier-transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, scanning electron microscopy with energy-dispersive X-ray spectroscopy, and molecular simulation. The antimicrobial activity of the nanocomposites is evaluated in vitro against several bacterial and fungal strains, demonstrating their medical potential. Additionally, in silico analyses are performed to predict the absorption, distribution, metabolism, and excretion properties and the bioavailability of the collagen samples. This work opens new avenues for the development of novel biomaterials using cheminformatics tools and methods, which can facilitate the optimization of the design and synthesis parameters, as well as the prediction of the biological outcomes. Future research directions include the investigation of the biocompatibility and bioactivity of the nanocomposites in vivo, as well as the exploration of other applications and functionalities of these nanocomposites.

Background: Low-dose aspirin (LDA) is the backbone for secondary prevention of coronary artery disease, though limited by gastric toxicity. This study was aimed to identify novel metabolites that could predict LDA-induced gastric toxicity using pharmacometabolomics. Methods: Pre-dosed urine samples were collected from male Sprague-Dawley rats. The rats were treated with either LDA (10 mg/kg) or 1% methylcellulose (10 ml/kg) per oral for 28 days. The rats' stomachs were examined for gastric toxicity using a stereomicroscope. The urine samples were analyzed using a proton nuclear magnetic resonance spectroscopy. Metabolites were systematically identified by exploring established databases and multivariate analyses to identify the spectral pattern of metabolites related to LDA-induced gastric toxicity. Results: Treatment with LDA resulted in gastric toxicity in 20/32 rats (62.5%). The orthogonal projections to latent structures discriminant analysis (OPLS-DA) model displayed a goodness-of-fit (R2Y) value of 0.947, suggesting a near-perfect reproducibility, a goodness-of-prediction (Q2Y) of -0.185 with perfect sensitivity, specificity and accuracy (100%). Furthermore, the area under the receiver operating characteristic (AUROC) displayed was 1. The final OPLS-DA model had an R2Y value of 0.726 and Q2Y of 0.142 with sensitivity (100%), specificity (95.0%) and accuracy (96.9%). Citrate, hippurate, methylamine, trimethylamine N-oxide and alpha-keto-glutarate were identified as the possible metabolites implicated in the LDA-induced gastric toxicity. Conclusion: The study identified metabolic signatures that correlated with the development of a low dose Aspirin-induced gastric toxicity in rats. This pharmacometabolomic approach could further be validated to predict LDA-induced gastric toxicity in patients with coronary artery disease.

Percutaneous vertebroplasty procedure is of major importance, given the significant increasing aging population and higher number of orthopedic procedures related to vertebral compression fractures. Vertebroplasty is a complex technique involving injection of polymethylmethacrylate (PMMA) into the compressed vertebral body for mechanical stabilization of the fracture. Our understanding and ability to modify these mechanisms through alterations in cement material is rapidly evolving. However, the rate of cardiac complications secondary to PMMA injection and subsequent cement leakage has increased with time. The following review considers the main features of PMMA bone cement on the heart, and the extent of influence of materials on cardiac embolism. Clinically, cement leakage results in life-threatening cardiac injury. The convolution of this outcome through an appropriate balance of complex material properties is highlighted via clinical case report.

In the early 2000s, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) emerged as a performant and relevant tool for identifying micro-organisms. Since then, it has become practically essential for identifying bacteria in microbiological diagnostic laboratories. In the last decade, it was successfully applied for arthropod identification allowing to distinguish vectors from non-vectors of infectious diseases. However, identification failures are not rare, hampering it widely use. Failure is generally attributed either to the absence of respective counter species MS spectra in the database, or to the insufficient quality of query MS spectra (i.e. lower intensity and diversity of MS peaks detected). To avoid matching errors due to non-compliant spectra, the development of a strategy for detecting and excluding outlier MS profiles became compulsory. To this end, we created MSProfileR, an R package leading to a bioinformatics tool through a simple installation, integrating the control quality system of MS spectra and an analysis pipeline including peak detection and MS spectra comparisons. MSProfileR can also add metadata concerning the sample that the spectra are derived from. MSProfileR has been developed in the R environment and offers a user-friendly web interface using the R Shiny framework. It is available on Microsoft Windows as a web browser application by simply navigation using the link of the package on the Github. MSProfileR is therefore accessible to non-computer specialists and is freely available to the scientific community. We evaluated MSProfileR using two datasets including exclusively MS spectra from arthropods. In addition to coherent sample classification, outlier MS spectra were detected in each dataset confirming the value of MSProfileR.

Biochar is a carbon allotrope obtained by pyrolysis of biomass, usually agro-waste. Owing to the demand for sustainable development, biochar is continuously raising much hope in the scientific community. However, in order to impart it with new properties, its modification is required, either in situ during pyrolysis, or after the carbonization process. Herein, we propose a new direct approach to obtain bimetallic copper/nickel nanoparticle-loaded on olive stone biochar. The bimetallic-coated biochar and the reference materials bare biochar, copper-loaded and nickel-loaded biochar were prepared at 400 °C under a stream of dinitrogen from olive pit powder particles impregnated first with citric acid (CA), and then with copper and nickel nitrates. We have employed citric acid in the process in order to check its effect on the structural and textural properties of biochar supporting the metallic nanoparticles. Surprisingly, citric acid induced the formation of agglomerated or even raspberry-shaped, bimetallic copper/nickel nanoparticles. Large 450-500 nm-sized agglomerates of ~80 nm bimetallic CuNi NPs were noted for B-CA@CuNi. Interestingly, for biochar material prepared with initial Cu/Ni=10 molar ratio (B-CA@CuNi10/1), the bimetallic NPs formed unusual nano-raspberries (1748 nm in size) which are agglomerates of individual 10-20 nm-sized CuNi10/1 nanoparticles. The B-CA@CuNi and reference materials were characterized by Raman spectroscopy, scanning electron microscopy (SEM)/energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD) and magnetometry. The B-CA@CuNi and B-CA@Ni materials could be attracted efficiently with a magnet, but not B-CA@CuNi10/1 due to a low nickel loading. B-CA@CuNi was tested as a catalyst for the degradation of methyl orange (MO). Discoloration was noted within 10 min, much faster than a similar material prepared in the absence of CA. B-CA@CuNi could be recycled at least 3 times with exhibit as fast discoloration catalysis performance. This paper stresses the important role of citric acid in shaping the bimetallic nanoparticles loaded in situ on biochar during the slow pyrolysis process and to enable faster catalysed discoloration of organic dye solution.

Wolbachia are intracellular endosymbionts of several invertebrate taxa, including insects and nematodes. Although Wolbachia DNA has been detected in ticks, its presence is generally associated with parasitism by insects. To determine whether or not Wolbachia can infect and grow in tick cells, cell lines from three tick species, Ixodes scapularis, Ixodes ricinus and Rhipicephalus microplus, were inoculated with Wolbachia strains wStri and wAlbB isolated from mosquito cell lines. Homogenates prepared from fleas collected from cats in Malaysia were inoculated into an I. scapularis cell line. Bacterial growth and identity were monitored by microscopy and PCR amplification and sequencing of fragments of Wolbachia genes. The wStri strain infected Ixodes spp. cells and was maintained through 29 passages. The wAlbB strain successfully infected Ixodes spp. and R. microplus cells and was maintained through 2-5 passages. A novel strain of Wolbachia belonging to the supergroup F, designated wCfeF, was isolated in I. scapularis cells from a pool of Ctenocephalides sp. cat fleas and maintained in vitro through two passages over nine months. This is the first confirmed isolation of a Wolbachia strain from a flea and the first isolation of any Wolbachia strain outside the “pandemic” A and B supergroups. The study demonstrates that tick cells can host multiple Wolbachia strains, and can be added to panels of insect cell lines to improve success rates in isolation of field strains of Wolbachia.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

A two-fold integrated research study was conducted; firstly, to understand effects of copper (Cu) and zinc (Zn) on the growth and oxidative stress in Nile tilapia, Oreochromis niloticus; secondly, to study the beneficial effects of the duckweed Lemna minor L. as a heavy metal remover from wastewater. Experiments were conducted in mesocosms with and without duckweed. Tilapia fingerlings were exposed to Cu (0.004 and 0.02 mg/L) and Zn (0.5 and 1.5 mg/L) and fish fed for four weeks. We evaluated the fish growth performance, the hepatic DNA structure using comet assay, the expression of antioxidative genes (superoxide dismutase, SOD; catalase, CAT; glutathione peroxidase, GPx and glutathione-S-transferase, GST) and GPx and GST enzymatic activity. The results showed that Zn exhibited more pronounced toxic effects than Cu. Low dose of Cu did not influence the growth whereas higher doses of Cu and Zn significantly reduced the growth rate of tilapia compared to control, but addition of duckweed prevented weight loss. Further, in the presence of a high dose of Cu and Zn, DNA damage decreased, antioxidant gene expressions and enzymatic activities increased. In conclusion, results suggest that duckweed and Nile tilapia can be suitable candidates in metal remediation wastewater assessment programs.