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Manufacturing robots are used for industrial purposes. Robots used for manufacturing purpose have the power to create products from raw materials and are capable of operating endlessly even in lights-out situations for continuous production. Manufacturing robots can be used in applications like arc welding, spot welding, materials handling, machine tending, painting, machine cutting and so on. Selecting a robot for a given application is complex. However, robot selection is used in selecting a suitable robot for the preferred output with specific application ability. In recent years, many authors used multi-criteria decision-making methods to select a robot that meets the need. This study presents a hybrid model by integrating complex proportional assessment (COPRAS) with the weighted aggregates sum product assessment (WASPAS) methods in intuitionistic dense fuzzy set to select a manufacturing robot for a particular application. Intuitionistic dense fuzzy entropy is used in calculating the weights for the criteria and intuitionistic dense fuzzy COPRAS and WASPAS are used in ranking the best alternatives where in the optimum types of robots are obtained. Here, intuitionistic dense fuzzy sets are used as it is capable of dealing with the intangible factors while selecting a robot. On the basis of the manufacturing robot selection, two comparisons are given. First, the results are compared with various λ values between 0 and 1 and second the results are compared with the fuzzy set, intuitionistic fuzzy set and the dense fuzzy set to show the effectiveness of the proposed methodology with the intuitionistic dense fuzzy set.

This paper proposes initial-boundary value problems for time-fractional analogs of Kuramoto-Sivashinsky, Korpusov-Pletner-Sveshnikov, Cahn-Allen, and Hoff equations due to a bounded domain. Adequate conditions for the blowing-up of solutions in limited time of previously mentioned conditions are displayed. The Pohozhaev nonlinear capacity strategy is considered. Illustrative examples are given for each of the investigated equations. (2010) Mathematics Subject Classifications: 34A08; 34B25; 34B15.

Hung-Yen Lee,1,2 Kamal A Mohammed,1,3 Fredric Kaye,4 Parvesh Sharma,5 Brij M Moudgil,5 William L Clapp,6 Najmunnisa Nasreen1,3 1Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine in the College of Medicine, 2Biomaterials Center, Department of Materials Sciences and Engineering, 3North Florida/South Georgia Veterans Health System, Malcom Randall VA Medical Center, 4Division of Hematology and Oncology, Department of Medicine in the College of Medicine, 5Particle Engineering Research Center and Department of Materials Science and Engineering, 6Renal Pathology, Surgical Pathology, University of Florida, Gainesville, FL, USA Abstract: MicroRNAs (miRs) are small noncoding RNA sequences that negatively regulate the expression of target genes by posttranscriptional repression. miRs are dysregulated in various diseases, including cancer. let-7a miR, an antioncogenic miR, is downregulated in lung cancers. Our earlier studies demonstrated that let-7a miR inhibits tumor growth in malignant pleural mesothelioma (MPM) and could be a potential therapeutic against lung cancer. EphA2 (ephrin type-A receptor 2) tyrosine kinase is overexpressed in most cancer cells, including MPM and non-small-cell lung cancer (NSCLC) cells. Ephrin-A1, a specific ligand of the EphA2 receptor, inhibits cell proliferation and migration. In this study, to enhance the delivery of miR, the miRs were encapsulated in the DOTAP (N-[1-(2.3-dioleoyloxy)propyl]-N,N,N-trimethyl ammonium)/Cholesterol/DSPE (1,2-distearoyl-sn-glycero-3-phosphoethanolamine-N-[cyanur(polyethylene glycol)-2000])-PEG (polyethylene glycol)-cyanur liposomal nanoparticles (LNP) and ephrin-A1 was conjugated on the surface of LNP to target receptor EphA2 on lung cancer cells. The LNP with an average diameter of 100 nm showed high stability, low cytotoxicity, and high loading efficiency of precursor let-7a miR and ephrin-A1. The ephrin-A1 conjugated LNP (ephrin-A1–LNP) and let-7a miR encapsulated LNP (miR–LNP) showed improved transfection efficiency against MPM and NSCLC. The effectiveness of targeted delivery of let-7a miR encapsulated ephrin-A1 conjugated LNP (miR–ephrin-A1–LNP) was determined on MPM and NSCLC tumor growth in vitro. miR–ephrin-A1–LNP significantly increased the delivery of let-7a miR in lung cancer cells when compared with free let-7a miR. In addition, the expression of target gene Ras was significantly repressed following miR–ephrin-A1–LNP treatment. Furthermore, the miR–ephrin-A1–LNP complex significantly inhibited MPM and NSCLC proliferation, migration, and tumor growth. Our results demonstrate that the engineered miR–ephrin-A1–LNP complex is an effective carrier for the targeted delivery of small RNA molecules to lung cancer cells. This could be a potential therapeutic approach against tumors overexpressing the EphA2 receptor. Keywords: liposomal nanoparticles, EphA2 receptor, microRNA, ephrin-A1, malignant pleural mesothelioma, non-small-cell lung cancer

Zinc and cadmium pollutants cause a significant environmental effect that cannot be ignored. Due to their considerable amount in an aqueous environment, industries are seeking suitable adsorbents that are environmentally friendly and inexpensive for removing metals from wastewater before disposing of them in surface waters. This research employed original MXene (MX) and chitosan-modified MXene (CSMX) to extract zinc (Zn(II)) and cadmium (Cd(II)) metal ions from water-based solutions. The composite material produced was analyzed using techniques such as X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Fourier Transform Infrared Spectroscopy (FTIR), and Brunauer-Emmett-Teller (BET). The effects of contact duration, pH of the solution, and initial concentration of metal ions on the adsorption process of Zn(II) and Cd(II) onto both MX and CSMX composites were investigated. MX and prepared CSMX composite presented a high adsorption capacity for both studied heavy metals, which were 91.55 and 73.82 mg/g for Zn(II) and Cd(II) onto MX, 106.84 and 93.07 mg/g for Cd(II) and Zn(II) onto CSMX composite, respectively. Furthermore, the maximum competitive adsorption capacities for Zn(II) onto MX and CSMX composites are 77.29 and 93.47 mg/g, and for are Cd(II) 60.30 and 79.66 mg/g, respectively. Hence, the removal capacities for both single and competitive metal ions were superior to CSMX composite. However, the adsorption capacities after five successive regeneration sequences were only dropped by 13.2% for Zn(II) and 17.4% for Cd(II) onto the CSMX composite compared to the first cycle. These results confirm that both metals could be efficiently terminated from wastewater, which makes the prepared CSMX composite a favorable candidate adsorbent in practical applications.

Abstract The rise of Electric Vehicles (EVs) has introduced significant advancement and evolution in the electricity market. In smart transportation, the EVs have earned more popularity because of its numerous benefits including lower carbon footprints, higher performance, and sophisticated energy trading mechanisms. These potential benefits have resulted in widespread EV adoption across the world. Despite its benefits, energy management remains the biggest challenge in EVs and it is mainly because of the lack of Charging Stations (CSs) near EVs. This creates a demand for an effective, secure and reliable energy management framework for EVs. This study presents a secure data and energy trade paradigm based on Blockchain (BC) in the Internet of EVs (IoEV). BC technology prepares for the high volume of EV integration that serves as the foundation for the next generation, and to assist in developing unique privacy-protected BC-based D-Trading and storage Models. Entities evaluated for the proposed model include Trusted Authority (TA), Vehicles, Smart Meters, Roadside Units (RSU), BC, and Inter-Planetary File System (IPFS). In addition, E-trading involves several phases, including the acquiring E-trading demand requests, E-trading response requests, request matching and token assignment. Moreover, account mapping is performed using a Mayfly Pelican Optimization Algorithm (MPOA), which is created by merging the Mayfly Algorithm (MA) and Pelican Optimization Algorithm (POA). Various security features are used to protect data and energy trade in IoEV, including encryption, hashing, polynomials, and others. The testing results revealed that the MPOA outperformed the state-of-the-art results regarding memory consumption, trading rate, transaction cost, and trading energy volume with values of 4.605 MB, 91%, 0.654, and 90 kW, respectively.

Abstract Background Sono-photodynamic therapy (SPDT), which combines photodynamic (PDT) and sonodynamic (SDT) therapies with sensitizers, offers new avenues for cancer treatment. Even though new sensitizers for SPDT have been synthesized with great success, few of them are effectively used. The limited tumor-targeting specificity, inability to transport the sensitizers deeply intratumorally, and the deteriorating tumor microenvironment limit their anti-tumor effectiveness. The current study was carried out aiming at high-frequency ultrasound-assisted drug delivery of chia, cress and flax conjugated hematite iron oxide nanoparticles (CCF–HIONP) for photothermal–photodynamic lung cancer (LCA) treatment in vitro and in vivo as activated cancer treatment up-to-date modality. Materials and methods The study was conducted in vitro on human LCA cells (A-549) and the study protocol application groups in vivo on Swiss albino mice treated with benzo[a]pyrene only and were not received any treatment for inducing LCA, and only after LCA induction the study treatment protocol began, treatment was daily with CCF–HIONP as HIFU–SPDT sensitizer with or without exposure to laser (IRL) or high-frequency ultrasound (HIFU–US) or a combination of laser and/or high-frequency ultrasound for 3 min for 2 weeks. Results Revealed that HIONP can be employed as effective CCF delivery system that directly targets LCA cells. In addition, CCF–HIONP is a promising HIFU–SPS for HIFU–SPDT and when combined with HIFU–SPDT can be very effective in treatment of LCA–A549 in vitro (cell viability decreased in a dose-dependent basis, the cell cycle progression in G0/G1 was slowed down, and cell death was induced as evidenced by an increase in the population of Pre-G cells, an increase in early and late apoptosis and necrosis, and an increase in autophagic cell death) and benzo[a]pyrene LCA-induce mice in vivo (decreased oxidative stress (MDA), and ameliorated enzymatic and non-enzymatic antioxidants (SOD, GR, GPx, GST, CAT, GSH, and TAC) as well as renal (urea, creatinine) and hepatic (ALT, AST) functions, induced antiproliferative genes (caspase 3,9, p53, Bax, TNFalpha), suppressed antiapoptotic and antiangiogenic genes (Bcl2,VEGF respectively) and effectively reducing the growth of tumors and even leading to cancer cell death. This process could be attributed to photochemical and/or high-frequency sono-chemical activation mechanism HIFU–SPDT. Conclusions The results indicate that CCF–HIONP has great promise as an innovative, effective delivery system for selective localized treatment of lung cancer that is activated by HIFU–SPDT.

Abstract Background While melanomas commonly harbor losses of 9p21, on which CDKN2A resides, the presence of additional tumor suppressor elements at this locus is incompletely characterized. Here we assess the expression levels and functional role of microRNA-876-3p (miR-876), whose gene also maps to 9p21. Methods Expression of miR-876 was assessed in human tissues and cell lines using quantitative miRNA reverse transcriptase polymerase chain reaction (qRT-PCR). MIR876 copy number was determined in The Cancer Genome Atlas (TCGA) melanoma cohort. The consequences of regulation of miR-876 expression were assessed on melanoma cell colony formation, migration, invasion, apoptosis, cell cycle progression, and drug sensitivity in culture, and on in vivo tumor growth in a xenograft model. Genome-wide transcriptomic changes induced by miR-876 overexpression were determined using RNA sequencing (RNA-Seq). Results miR-876 expression was significantly decreased in primary melanoma samples when compared with nevi, and in human melanoma cell lines when compared with human melanocytes. Analysis of the TCGA cohort revealed deletions in MIR876 in > 50% of melanomas. miR-876 overexpression resulted in decreased melanoma cell colony formation, migration, and invasion, which was accompanied by cell cycle arrest and increased apoptosis. Intra-tumoral injections of miR-876 significantly suppressed melanoma growth in vivo. RNA-Seq analysis of miR-876-treated tumors revealed downregulation of several growth-promoting genes, along with upregulation of tumor suppressor genes, which was confirmed by qRT-PCR analysis. Computational analyses identified MAPK1 (or ERK2) as a possible target of miR-876 action. Overexpression of miR-876 significantly suppressed luciferase expression driven by the MAPK1/ERK2 3’ UTR, and resulted in decreased ERK protein expression in melanoma cells. MAPK1/ERK2 cDNA overexpression rescued the effects of miR-876 on melanoma colony formation. miR-876 overexpression sensitized melanoma cells to treatment with the BRAF inhibitor vemurafenib. Conclusions These studies identify miR-876 as a distinct tumor suppressor on 9p21 that is inactivated in melanoma and suggest miR-876 loss as an additional mechanism to activate ERK and the mitogen activated protein kinase (MAPK) pathway in melanoma. In addition, they suggest the therapeutic potential of combining miR-876 overexpression with BRAF inhibition as a rational therapeutic strategy for melanoma.

Introduction: In this study, we aimed to determine the functional dominance of the right and left hemispheres of the operated patients and the effectiveness of postoperative pain therapy when the patients underwent surgery on the same or different sides with the dominant hemisphere. Methods: The patients were given a Miles test for the dominant eye in the preoperative period and were instructed while the key was in front of the patient to take the key and open the door to determine the dominant hand. For the dominant foot, the patient was given the command of “move your foot” in a calm environment and accepted as the foot that he carried the dominant foot. After routine spinal anesthesia and elective knee arthroplasty surgery, patients underwent Patient Controlled Analgesia device, 24th hour Numeric Rating Scale (NRS) scores, and the amount of total applied analgesic and additional analgesic were recorded. Results: When the clinical characteristics of the patients were examined, there were 38 patients on the right side of the dominant eye, 34 on the left side, 67 on the right hand dominant side, 5 on the left side, 49 on the right foot dominant side, and 23 on the left side. The NRS score on the surgical side was compared with the dominant foot, dominant eye, and dominant hand. There was no statistically significant difference between the NRS pain scale and other variables except those opposed to the dominant eye (p>0.05). The NRS pain scale median (median: 3.0) was found to be significantly lower in patients who were operated on the same side as the dominant eye (p=0.016). Conclusion: According to the results of our study, the NRS score was not changed in patients operated on the same side of the dominant foot and hand, whereas the NRS score was lower in patients operated on the same side with the dominant eye.

Abstract Background Warfarin patients who need dental extraction face the problem of bleeding and no sufficient hemostasis results in dry socket and postoperative pain. This study aimed to evaluate and compare the efficacy of the topical application of tranexamic acid-soaked absorbable Gelfoam (TXA-Gel) and saline-soaked absorbable Gelfoam (saline-Gel) in relieving postoperative pain following bilateral simple extraction of permanent mandibular molars in warfarin patients. Methods This was a randomized, triple-blinded, split-mouth, active-controlled clinical trial. It was performed at the Department of Oral and Maxillofacial Surgery, Faculty of Dentistry, Damascus University, between November 2021 and October 2023. 60 bilateral permanent mandibular molars, which were indicated for simple extraction in 30 warfarin patients randomly assigned into two groups according to the topical hemostatic agents after extraction used: Group 1: control group, saline-Gel (n = 30). Group 2: TXA-Gel (n = 30). A simple randomization method was performed by flipping a coin. The primary outcome measure was the visual analogue scale (VAS). The intensity of pain was evaluated at the baseline (t0), and on the 1st (t1), 2nd (t2), 3rd (t3), 4th (t4), 5th (t5), 6th (t6), and 7th (t7) days following extraction. The Kolmogorov–Smirnov test and the Mann-Whitney U test were performed. The level of significance was set at 0.05 (p

Abstract Based on a structural family of thirty-two NR2B-selective N-Methyl-D-Aspartate receptor (NMDAR) antagonists, two phenylpiperazine derivatives labeled C37 and C39 were conceived thanks to molecular modeling techniques, as novel NMDAR inhibitors exhibiting the highest analgesic activities (of pIC50 order) against neuropathic pain, with excellent ADME-toxicity profiles, and good levels of molecular stability towards the targeted protein of NMDA receptor. Initially, the quantitative structure-activity relationships (QSARs) models were developed using multiple linear regression (MLR), partial least square regression (PLSR), multiple non-linear regression (MNLR), and artificial neural network (ANN) techniques, revealing that analgesic activity was strongly correlated with dipole moment, octanol/water partition coefficient, Oxygen mass percentage, electronegativity, and energy of the lowest unoccupied molecular orbital, whose the correlation coefficients of generated models were: 0.860, 0.758, 0.885 and 0.977, respectively. The predictive capacity of each model was evaluated by an external validation with correlation coefficients of 0.703, 0.851, 0.778, and 0.981 respectively, followed by a cross-validation technique with the leave-one-out procedure (CVLOO) with Q2 cv of 0.785, more than Y-randomization test, and applicability domain (AD), in addition to Fisher’s and Student’s statistical tests. Thereafter, ten novel molecules were designed based on MLR QSAR model, then predicted with their ADME-Toxicity profiles and subsequently examined for their similarity to the drug candidates. Finally, two of the most active compounds (C37 and C39) were chosen for molecular docking and molecular dynamics (MD) investigations during 100 ns of MD simulation time in complex with the targeted protein of NMDA receptor (5EWJ.pdb).

Recently, there has been significant interest in biodiesel since it depends on renewable resources, which is essential given the increasing depletion of fossil fuels. Using palm oil in biodiesel production is an innovative application of botanical resources in this sector. Simulation research examined how blending palm oil with Iraqi conventional diesel influences engine performance. The impact of several mixtures, consisting of different proportions (5%, 10%, 15%, and 20%) of palm oil and diesel, on engine fuel consumption, volumetric efficiency, torque, brake mean pressure, brake power, and thermal efficiency was evaluated in each case. The study found that using palm oil fuel at a mixing ratio of 20% resulted in a 4% increase in fuel consumption. Furthermore, a 3% enhancement in volumetric efficiency was also noted. Again, there was a noticeable reduction in the torque, power, and average adequate pressure levels across all diesel fuel mixing ratios compared to diesel fuel, which exhibits the highest value.

Organic dye pollutants present in wastewater pose a significant global challenge. Among pollutants, the synthetic dye Rhodamine B (RB) stands out due to its non-biodegradable nature and associated neurotoxic, carcinogenic, and respiratory irritant properties. Extensive research has been conducted on the efficacy of adsorption and photodegradation techniques for the removal of RB from wastewater. While adsorption and advanced oxidation processes (AOPs) have gained considerable attention for their effectiveness in recent years, the underlying behaviors and mechanisms of these technologies remain incompletely understood. Therefore, a comprehensive summary of recent research progress in this domain is imperative to clarify the basics and present the up-to-date achievements.This review provides an in-depth exploration of the fundamentals, advancements, and future trajectories of RB wastewater treatment technologies, mainly encompassing adsorption and photodegradation. This work starts with a general introduction of outlining the sources, toxicity, and diverse applicable removal strategies. Subsequently, it thoroughly examines crucial techniques within non-photochemical, photochemical, and adsorption technologies, such as UV light assisted AOP, catalyst assisted AOP, ozonation, Fenton system, electrochemical AOP, and adsorption technology. The primary objective is to furnish a broad overview of these techniques, elucidating their effectiveness, limitations, and applicability. Following this, the review encapsulates state-of-the-art computational simulations pertaining to RB adsorption and interactions with clays and other adsorbents. Lastly, it delves into column adsorption of RB dye, and elucidates various influencing factors, including bed height, feed concentration, pollutant (RB) feeding or flow rate, and column regeneration. This panoramic review aims to provide valuable insights into suitable techniques, research gaps, and the applicability of non-photochemical, photochemical, and adsorption technologies in the treatment of wastewater containing RB dye.

For their pungency and tanginess, ginger rhizomes (Zingiber officinale) are often used in cooking. Ginger has long been used in traditional medicine and home remedies to treat pain and inflammation. This research tests Z. officinale (EOZ) essential oils’ chemical composition, insecticidal, and antioxidant properties in vitro and in silico. EOZ yielded 0.69% of root mass with 23 chemicals. The main chemicals in EOZ were α-zingiberene (23.850%), Geranial (14.160%), and (E,E)-α-farnesene (9.980%). EOZ demonstrated noteworthy antioxidant activity in all tests, with an IC50 of 9.53 ± 0.41 mg/mL in the DPPH test and an EC50 of 87.46 ± 3.19 mg/mL in the FRAP system. The results indicate that EOZ has strong efficacy against C. maculatus, even at low concentrations (1.00 μL/100 g). Note that EOZ killed 20 ± 0% and 13.33 ± 4.44% of adult C. maculatus in inhalation and contact tests, respectively. High concentration (20.00 μL/100 g) resulted in 100% adult mortality in inhalation tests and 96.67 ± 4.44% mortality in contact testing. We then used molecular docking to identify EO major component binding modes by targeting insecticidal and antioxidant protein structures 1R20 and 1R4U. This research helps create insecticides and antioxidants from common ginger essential oil.

Optical coherence tomography (OCT) helps identify coronary artery disease of different etiologies. Vasospasm from OCT catheter is a rarely reported complication that is more commonly seen in the right coronary artery. We report a case of OCT-catheter induced vasospasm of the left anterior descending artery that resolved with administration of nitroglycerine. Interventionalists need to weary of the occurrence of catheter-related coronary artery spasm to avoid stenting when not necessary.

Abstract Profiling social media users is an analytical approach to generate an extensive blueprint of user’s personal characteristics, which can be useful for a diverse range of applications, such as targeted marketing and personalized recommendations. Although social user profiling has gained substantial attention in recent years, effectively constructing a collaborative model that could describe long and short-term profiles is still challenging. In this paper, we will discuss the profiling problem from two perspectives; how to mathematically model and track user’s behavior over short and long periods and how to enhance the classification of user’s activities. Using mathematical equations, our model can define periods in which the user's interests abruptly changed. A dataset consisting of 30,000 tweets was built and manually annotated into 10 topic categories. Bi-LSTM and GRU models are applied to classify the user’s activities representing his interests, which then are utilized to create and model the dynamic profile. In addition, the effect of word embedding techniques and pre-trained classification models on the accuracy of the classification process is explored in this research.

Wild birds could be a reservoir of medically relevant microorganisms, particularly multidrug-resistant Enterococcus spp. Resistant bacteria's epidemiology and transmission between animals and humans has grown, and their zoonotic potential cannot be ignored. This is the first study to evaluate the status of vancomycin resistant enterococci (VRE) in various wild bird species using meta-analysis and a systematic review. In this study, the pooled prevalence was obtained by analyzing data from published articles on the occurrence of VRE in wild bird species. It's unclear how the antibiotic resistance gene transfer cycle affects wild birds. Google Scholar and PubMed were used to conduct the research. The data and study methodology was assessed and extracted by two reviewers independently, with a third reviewing the results. Heterogeneity between study and publication bias were analyzed using the random effect model. Thirty-eight studies were included in the meta-analysis. 382 out of the 4144 isolates tested, were VRE. The pooled prevalence of VRE among wild birds was estimated at 11.0% (95% CI; 6.9 –17.2%; I2 = 93.204%; P

Background: Rheumatic diseases are chronic diseases that affect joints, tendons, ligaments, bones, muscles, and other vital organs. Detection of rheumatic diseases is a complex process that requires careful analysis of heterogeneous content from clinical examinations, patient history, and laboratory investigations. Machine learning techniques have made it possible to integrate such techniques into the complex diagnostic process to identify inherent features that lead to disease formation, development, and progression for remedial measures. Methods: An automated diagnostic tool using a multilayer neural network computational engine is presented to detect rheumatic disorders and the type of underlying disorder for therapeutic strategies. Rheumatic disorders considered are rheumatoid arthritis, osteoarthritis, and systemic lupus erythematosus. The detection system was trained and tested using 70% and 30% respectively of labelled synthetic dataset of 100,000 records containing both single and multiple disorders. Results: The detection system was able to detect and predict underlying disorders with accuracy of 97.48%, sensitivity of 96.80%, and specificity of 97.50%. Conclusion: The good performance suggests that this solution is robust enough and can be implemented for screening patients for intervention measures. This is a much-needed solution in environments with limited specialists, as the solution promotes task-shifting from the specialist level to the primary healthcare physicians.

Abstract Background Globally, non-communicable diseases (NCDs) are increasingly the primary cause of mortality and morbidity among women. Like many developing countries, Bangladesh also faces a growing burden of NCDs. The “Multisectoral Action Plan for Prevention and Control of Non-communicable Diseases, 2018–2025” signifies Bangladesh’s commitment to comprehensively combating the rising burden of NCDs. This study investigates the perceptions of those involved in developing the action plan and if/how a gender lens was incorporated into its implementation. Methods In-depth interviews were conducted with 25 key individuals involved in a high-level committee to develop and implement Bangladesh’s multisectoral action plan to address the burden of NCDs. Data were collected between July and November 2021, and thematic analysis was conducted. Results The findings revealed that interviewees believed the multisectoral action plan adopted a population-wide approach without considering gender-specific needs. This study presents the explanations for this inattention under five themes: (1) A population-level approach to NCD prevention; (2) Understanding women’s health beyond reproductive health; (3) Absence of gender-specific programs; (4) Lack of consideration of gender constraints on physical activity; and (5) Lack of collaborative efforts to address NCDs beyond the health ministry. Conclusion In conclusion, governments in countries like Bangladesh can develop more effective strategies to reduce the disease burden of NCDs among women by recognizing and addressing the gendered nature of preventive health. This can be achieved by promoting gender-responsive research, programs, and policy initiatives that consider women’s specific health concerns, ultimately leading to better health outcomes for all.

Abstract Background Globally, MAFLD becomes in the top list of causes of liver disease. Its effect ranges from steatosis, metabolic steato-hepatitis to MAFLD-related cirrhosis and hepatocellular carcinoma. There is a growing evidence that MAFLD-related HCC seems to be different from HCCs of other causes pathologically, so the purpose of our study was to assess the effect of MAFLD on the prognosis of HCC regarding outcome after management of HCC and survival rate in comparison to a group of patients with HCV-related HCC. Results Twenty-nine patients with MAFLD related HCC were included in group A, while 58 patients with HCV related HCC were enrolled as group B. Both groups were matched regarding age and gender. The mean age in group A and B was 58.86 (±8.47) years and 60/05(± 6.83) years respectively. Comparison between both groups regarding tumor burden and characteristics of HCC, type of management, and post intervention follow-up showed no significant statistical difference between both groups except for lymph node metastases which was higher in patients with HCV related HCC with p = 0.045. Also, a significant difference between both studied groups regarding AFP was detected; the median of AFP in MAFLD-related HCC was (7.2 ng/ml) but much higher in HCV-related HCC group (129.2 ng/ml) with p = 0.001. Conclusion Our data showed no significant difference between the two studied groups regarding outcome of HCC or survival rate except for AFP level before and after management which was higher in HCV patients related HCC. Although both of inclusion and exclusion criteria were strict to the criteria, so the number of participants in the research were not large enough; to our knowledge, this is the first study on MAFLD-HCC in Egypt and Africa. More studies on prospective bases are essentially needed to stand on solid conclusion about the nature and outcome of MAFLD-related HCC.

Abstract Microalgae are widely exploited for numerous biotechnology applications, including biofuels. In this context, Chlamydomonas debaryana and Chlorococcum sp. were isolated from Fez freshwater (Morocco), and their growth and lipid and carbohydrate production were assessed at different concentrations of NaCl, NaNO3, and K2HPO4. The results indicate a small positive variation in growth parameters linked to nutrient enrichment, with no considerable variation in carbohydrate and lipid levels in both algae. Moreover, a negative variation was recorded at increased salinity and nutrient limitation, accompanied by lipid and carbohydrate accumulation. Chlorococcum sp. showed better adaptation to salt stress below 200 mM NaCl. Furthermore, its growth and biomass productivity were strongly reduced by nitrogen depletion, and its lipid production reached 47.64% DW at 3.52 mM NaNO3. As for Chlamydomonas debaryana, a substantial reduction in growth was induced by nutrient depletion, a maximal carbohydrate level was produced at less than 8.82 mM NaNO3 (40.59% DW). The effect of phosphorus was less significant. However, a concentration of 0.115 mM K2HPO4 increased lipid and carbohydrate content without compromising biomass productivity. The results suggest that growing the two Chlorophyceae under these conditions seems interesting for biofuel production, but the loss of biomass requires a more efficient strategy to maximize lipid and carbohydrate accumulation without loss of productivity.

Dengue hemorrhagic fever (DHF) is a severe condition resulting from the dengue virus, with four serotypes known as DEN-1, DEN-2, DEN-3, and DEN-4. Genetic variations play a crucial role in influencing susceptibility to DHF. Therefore, this investigation conducted a meta-analysis to uncover genetic changes that might have remained undetected in individual studies due to small sample sizes or methodological differences. Among 2212 initially identified studies, 23 were deemed suitable for analysis based on PRISMA guidelines. Toll-like receptors (TLR) and CD209 showed significant association with DHF (odds ratios: TLR=0.56, CD209 =0.55), indicating protective effects. However, tumor necrosis factor (TNF) and human leukocyte antigen (HLA) did not exhibit a statistically significant relationship with DHF. This study emphasizes the relevance of TLR and CD209 in DHF susceptibility and resistance across diverse geographical locations.

Hyperspectral imaging (HSI) has become a key technology for non-invasive quality evaluation in various fields, offering detailed insights through spatial and spectral data. Despite its efficacy, the complexity and high cost of HSI systems have hindered their widespread adoption. This study addressed these challenges by exploring deep learning-based hyperspectral image reconstruction from RGB (Red, Green, Blue) images, particularly for agricultural products. Specifically, different hyperspectral reconstruction algorithms, such as Hyperspectral Convolutional Neural Network - Dense (HSCNN-D), High-Resolution Network (HRNET), and Multi-Scale Transformer Plus Plus (MST++), were compared to assess the dry matter content of sweet potatoes. Among the tested reconstruction methods, HRNET demonstrated superior performance, achieving the lowest mean relative absolute error (MRAE) of 0.07, root mean square error (RMSE) of 0.03, and the highest peak signal-to-noise ratio (PSNR) of 32.28 decibels (dB). Some key features were selected using the genetic algorithm (GA), and their importance was interpreted using explainable artificial intelligence (XAI). Partial least squares regression (PLSR) models were developed using the RGB, reconstructed, and ground truth (GT) data. The visual and spectra quality of these reconstructed methods was compared with GT data, and predicted maps were generated. The results revealed the prospect of deep learning-based hyperspectral image reconstruction as a cost-effective and efficient quality assessment tool for agricultural and biological applications.

IntroductionThe h-index measures researchers’ productivity by assessing simultaneously the number of publications and citations. We aimed to assess the factors that could influence h-index for hematologists practicing in academic institutions in Canada.MethodsWe identified universities with a hematology residency training programs/fellowships using the Canadian Resident Matching Service (CaRMS) website. We obtained the listing of faculty, sex, and academic ranks by consulting faculty directories or by contacting respective departments/universities, when directories were unavailable or incomplete. For each faculty member, we obtained years since Royal College of Physicians’ and Surgeons of Canada certification or equivalent, receipt of Canadian Institute of Health Research (CIHR) grants within the last 5 years, attainment of graduate degrees (M.Sc., Ph.D., other), and the h-index.ResultsThe data included information collected from 372 individuals (171 females) across Canada (Atlantic Provinces: 13; Quebec: 89; Ontario: 182; Prairie Provinces: 59; British Columbia: 29). Univariate analysis showed that male sex, practicing in British Columbia, longer duration since specialty certification, completion of an M.Sc. or a Ph.D. degree, attaining a higher academic rank and receiving CIHR funding were associated with higher h-index. The results of the univariate analysis were concordant with the multivariate analysis, except that practicing in Ontario was also associated with higher h-index.ConclusionThis study provides details on the h-index curve/parameters for academic productivity of hematologists in Canada. Importantly, based on multivariate analysis, higher h-index was associated with male sex, location of practice, years since certification, attainment of M.Sc. or Ph.D. degrees, academic rank, and recent CIHR funding.

In this paper we present a new approach to solve a risk default, under asymmetric information, between Micorfinance Institutions MFIs and borrowers excluded from the conventional financial systems (financial exlusion). To solve this problem we propose the model, as a system of two differential equations to describe the evolution of some safe and risky borrowers. In fact, the population of borrowers is divided into two compartments: Safe and Risky having an interaction, it is a SR model. With numerical simulations of the SR model, we can describe the evolution of some safe and risky borrowers. The result provides to manage the portfolios of all agencies controlled from the MFIs, by predictions of safe and risky borrowers. Then, define or redefine the management strategies of development and investment, and thus strengthen financial inclusion.

Alcohol-based fuels have gained more interest due to their production process and availability and environmental point of view so based alcohol-based fuel like fusel oil has been studied as an alternative fuel for compression ignition engine engines. The objective of this experimental study was to investigate the performance of a compression ignition engine based on a performance and emissions of cylinder single-cylinder diesel engine. To maintain the original fuel system of the engine, a fixed blending ratio of 20% v/v was used. The research findings indicated a decrease in nitrogen oxide (NO) emissions when using fusel oil–diesel (F20) compared to diesel. Still, higher fuel consumption was observed due to the lower energy content of fusel oil. However, F20 led to increased carbon monoxide (CO) emissions and hydrocarbons (HC) compared to diesel. The most significant reduction in NOx emissions by up to 20% occurred at an engine speed of 1,500 rpm and an engine load of 75%, possibly attributed to the higher water content in fusel oil. It is crucial to evaluate the trade-offs between these parameters carefully. Insight into these trade-offs may facilitate the optimization of fusel oil use as a prospective fuel alternative for internal combustion engines.

Summary: Telemedicine is a promising solution to the challenges of delivering equitable and quality primary healthcare, especially in LMICs. This review evaluated peer-reviewed literature on telehealth interventions in Indian primary care published from Jan 1, 2011 to Dec 31, 2021, from PubMed, Scopus, TRIP, Google Scholar, Indian Kanoon, and Cochrane database The majority of Indian studies focus on key health issues like maternal and child health, mental health, diabetes, infectious diseases, and hypertension, mainly through patient education, monitoring, and diagnostics. Yet, there’s a lack of research on telemedicine’s cost-effectiveness, communication among providers, and the role of leadership in its quality and accessibility. The current research has gaps, including small sample sizes and inconsistent methodologies, which hamper the evaluation of telemedicine’s effectiveness. India's varied healthcare landscape, technological limitations, and social factors further challenge telemedicine's adoption. Despite regulatory efforts, issues like the digital divide and data privacy persist. Addressing these challenges with a context-aware, technologically driven approach is crucial for enhancing healthcare through telemedicine in India.

This study addresses the challenge of effectively selecting relevant variables and providing interpretable insights in spectroscopic analysis (1100–2498 nm) of corn quality (moisture, fat, protein, and starch), incorporating variable selection techniques and explainable artificial intelligence (AI). Three variable selection algorithms were used to select 36 important variables, and through combinatorial optimization, only 11 common wavelengths were chosen. Partial least squares regression (PLSR) models were developed using the full spectral range, individual variables, and common variables. Based on the root mean square errors of prediction (RMSEP), the PLSR models with common variables outperformed individual feature variables for starch (0.22 % vs. 0.24 %) and were comparable for oil (0.05 % vs. 0.05 %), water (0.02 % vs. 0.01 %) and protein (0.12 % vs. 0.09 %). The SHapley Additive exPlanation (SHAP) method was employed to explain the PLSR model and assess the contribution of common variables. This combined approach significantly improved the accuracy and interpretability of corn prediction models, providing trust in the results and facilitating the understanding of the relationship between spectral features and corn quality attributes.

Abstract Polymer‐based membranes such as polyethersulfone are widely used for hemodialysis and bio‐related applications; however, this type of membrane still fails to satisfy optimum performance in terms of clearance, safety, and bio‐adaptability. Herein, a polymer brush of polyvinylpyrrolidone is decorated on the surface of magnetic nanoparticles by using reversible addition‐fragmentation chain transfer polymerization (RAFT), and under the guidance of an external magnetic field, the prepared magnetic nanoparticles with the polymer brush system are blended with a polyethersulfone membrane during a liquid‐liquid phase inversion process. The prepared membranes with different loads of the pure magnetic nanoparticle and polyvinylpyrrolidone@magnetic nanoparticle polymer brushes are prepared, compared with the pristine membrane, the modified membrane shows a high flux value at 349 L m−2 h−1 and 99.9% bovine serum albumin protein rejection. This membrane also demonstrated improved hydrophilicity and pore structure compared with the pristine membrane. Concerning the blood biocompatibility analysis, the modified membranes acquire prolonged time for clotting factors such as prothrombin time, activated partial thromboplastin time, and thrombin time while exhibiting less fibrinogen concertation at 0.4 g L−1. Furthermore, for the first time, an innovative method for fouling detection based on magnetic field attenuation due to protein accumulation on the membrane surface is reported; the method in this work could be a positive booster for the safe use of polymeric membranes in hemodialysis and bio‐based applications.

Triple-negative breast cancer (TNBC) is the most severe form of breast cancer, characterized by the loss of estrogen, progesterone, and human epidermal growth factor receptors. It is caused by various genetic and epigenetic factors, resulting in poor prognosis. Epigenetic changes, such as DNA methylation and histone modification, are the leading mechanisms responsible for TNBC progression and metastasis. This review comprehensively covers the various subtypes of TNBC and their epigenetic causes. In addition, the genetic association of TNBC with all significant genes and signaling pathways linked to the progression of this form of cancer has been enlisted. Furthermore, the possible uses of natural compounds through different mechanistic pathways have also been discussed in detail for the successful management of TNBC.

Introduction Determining aetiology of severe illness can be difficult, especially in settings with limited diagnostic resources, yet critical for providing life-saving care. Our objective was to describe the accuracy of antemortem clinical diagnoses in young children in high-mortality settings, compared with results of specific postmortem diagnoses obtained from Child Health and Mortality Prevention Surveillance (CHAMPS).Methods We analysed data collected during 2016–2022 from seven sites in Africa and South Asia. We compared antemortem clinical diagnoses from clinical records to a reference standard of postmortem diagnoses determined by expert panels at each site who reviewed the results of histopathological and microbiological testing of tissue, blood, and cerebrospinal fluid. We calculated test characteristics and 95% CIs of antemortem clinical diagnostic accuracy for the 10 most common causes of death. We classified diagnostic discrepancies as major and minor, per Goldman criteria later modified by Battle.Results CHAMPS enrolled 1454 deceased young children aged 1–59 months during the study period; 881 had available clinical records and were analysed. The median age at death was 11 months (IQR 4–21 months) and 47.3% (n=417) were female. We identified a clinicopathological discrepancy in 39.5% (n=348) of deaths; 82.3% of diagnostic errors were major. The sensitivity of clinician antemortem diagnosis ranged from 26% (95% CI 14.6% to 40.3%) for non-infectious respiratory diseases (eg, aspiration pneumonia, interstitial lung disease, etc) to 82.2% (95% CI 72.7% to 89.5%) for diarrhoeal diseases. Antemortem clinical diagnostic specificity ranged from 75.2% (95% CI 72.1% to 78.2%) for diarrhoeal diseases to 99.0% (95% CI 98.1% to 99.6%) for HIV.Conclusions Antemortem clinical diagnostic errors were common for young children who died in areas with high childhood mortality rates. To further reduce childhood mortality in resource-limited settings, there is an urgent need to improve antemortem diagnostic capability through advances in the availability of diagnostic testing and clinical skills.

A large body of research establishes the efficacy of musical intervention in many aspects of physical, cognitive, communication, social, and emotional rehabilitation. However, the underlying neural mechanisms for musical therapy remain elusive. This study aimed to investigate the potential neural correlates of musical therapy, focusing on the changes in the topology of emotion brain network. To this end, a Bayesian statistical approach and a cross-over experimental design were employed together with two resting-state magnetoencephalography (MEG) as controls. MEG recordings of 30 healthy subjects were acquired while listening to five auditory stimuli in random order. Two resting-state MEG recordings of each subject were obtained, one prior to the first stimulus (pre) and one after the final stimulus (post). Time series at the level of brain regions were estimated using depth-weighted minimum norm estimation (wMNE) source reconstruction method and the functional connectivity between these regions were computed. The resultant connectivity matrices were used to derive two topological network measures: transitivity and global efficiency which are important in gauging the functional segregation and integration of brain network respectively. The differences in these measures between pre- and post-stimuli resting MEG were set as the equivalence regions. We found that the network measures under all auditory stimuli were equivalent to the resting state network measures in all frequency bands, indicating that the topology of the functional brain network associated with emotional regulation in healthy subjects remains unchanged following these auditory stimuli. This suggests that changes in the emotion network topology may not be the underlying neural mechanism of musical therapy. Nonetheless, further studies are required to explore the neural mechanisms of musical interventions especially in the populations with neuropsychiatric disorders.

Summary: Background: Systemic sclerosis (SSc) is a systemic life-threatening autoimmune rheumatic disease. We aimed to assess the incidence, prevalence, mortality and spatiotemporal trends of SSc in Quebec, Canada with stratification by sex and age. Methods: SSc cases were identified from Quebec populational databases from 1989 to 2019. Negative Binomial (NB) Generalized Linear Models were used for age-standardized incidence rates (ASIR) analyses and NB random walk for prevalence and mortality. A Poisson Besag-York-Mollié regression model was used for spatial analysis. Findings: 8180 incident SSc cases were identified between 1996 and 2019 with an average age of 57.3 ± 16.3 years. The overall ASIR was 4.14/100,000 person-years (95%, Confidence Interval (CI) 4.05–4.24) with a 4:1 female predominance. ASIR increased steadily over time with an Average Annual Percent Change (AAPC) of 3.94% (95% CI 3.49–4.38). While the highest incidence rates were in those aged 60–79 years old among females and >80 years old among males, the highest AAPC (∼10%) was seen in children. Standarized incidence ratios varied geographically between 0.52 to 1.64. The average prevalence was 28.96/100,000 persons (95% CI 28.72–29.20). The Standardized Mortality Ratio (SMR) decreased from 4.18 (95% CI 3.64–4.76) in 1996 to 2.69 (95% CI 2.42–2.98) in 2019. Females had a greater SMR until 2007 and males thereafter. The highest SMR was in children and young adults [31.2 (95% CI 8.39–79.82) in the 0–19-year age group]. Interpretation: We showed an increasing trend in SSc incidence and prevalence and a decline in SMR over a 25-year period in Quebec. An uneven geographic distribution of SSc incidence was demonstrated. Funding: National Scleroderma Foundation, Canadian Dermatology Foundation/Canadian Institutes of Health Research.

BACKGROUND: Functional constipation (FC) is a common condition in children, and information on the clinical characteristics of FC in Saudi children is scarce. OBJECTIVE: Describe the clinical profile of FC in Saudi children. DESIGN: Retrospective SETTING: Hospital that provides primary, intermediate and tertiary care. PATIENTS AND METHODS: All children diagnosed with FC according to the Rome IV criteria were included and had at least one follow-up clinic visit. Demographic and clinical data collected from medical records included the age at onset, duration of constipation, clinical features, treatment modalities, and factors associated with clinical response. Descriptive statistics and Pearson's chi-squared test were used in the statistical analysis to see how categorical study variables were linked to clinical response. A P value of ≤.05 was used to report statistical significance. MAIN OUTCOME MEASURE: Compliance and clinical response to polyethylene glycol (PEG) compared with lactulose. SAMPLE SIZE: 370 children from 0.1 to 13 years of age. RESULTS: The median (IQR) age of onset was 4 (5) years and less than one year in 14%. The median (IQR) duration of constipation was 4 months (11) and less than two months in 93/370 (25%). Abdominal pain was the most commonly associated feature (44%). Screening for celiac disease and hypothyroidism was negative. A Fleet enema was the most common disimpaction method (54%) and PEG was the most common maintenance medication (63.4%). PEG was significantly better tolerated (P=.0008) and more effective than lactulose (P

Abstract Introduction Chronic non-bacterial osteomyelitis (CNO) is a rare, non-infection- related inflammatory disorder that affects children and teens. Clinical manifestations of CNO range widely from moderate, time-limited, monofocal inflammation of the bone to extreme multifocal or chronically active inflammation of the bone. Objectives The main aim of this study was to explore the correlation between musculoskeletal (MSK) symptoms and health-related quality of life (HRQoL) in patients with CNO. Methods Children and adults with CNO and their parents were asked to answer a web-based survey. The survey consisted of multiple questions centered around demographic, clinical and therapeutic data, MSK discomfort form based on the Nordic MSK Questionnaire and HRQoL based on Pediatric Quality of Life Inventory-4 (PedsQL-4) and PedsQL rheumatology module. The inclusion criteria included diagnosis of CNO before the age of 18. Patients who had malignancies or any chronic rheumatic, MSK, neurological disease prior to CNO onset were excluded. Results There was a total of 68 participants, mostly females (66.2%), with median age 14 years and median disease duration 4.75 years. The median number of bones affected by CNO was 5 and ranged from 1 to 24 bones. Among the studied patients, 45 patients (66.2%) had MSK manifestations at the last month. The most commonly affected part was ankle and feet (26.5%). Regarding HRQoL, patients with MSK manifestations had lower scores than did patients without in PedsQL-4 (p

The apple is an important part of the human diet and is one of the most popular fruits in Morocco, with varieties that are now suitable for human consumption. This study aims to clarify several aspects of apples, such as their physical and chemical compositions and nutrient profiles. Total polyphenols, flavonoids, tannins, and anthocyanins were determined using spectrophotometer and organic acid compounds were identified by high-performance liquid chromatography-ultraviolet. The results show a significant difference between the several varieties under study in terms of their physico-chemical and phyto-chemical characteristics. In general, the studied apples are juiciness, with a percentage ranging from 60 to 71%. The pH values demonstrate how acidic the apples are. The Brix parameter denotes values greater than 13°Brix. Total polyphenols and condensed tannins (1154.65 ± 13.54 µg EAG/g and 514.09 ± 32.40 µg EAT/g, respectively) are more present in the Ahjjani variety than they are in other varieties. This demonstrates their good nutritional quality while not being consumable. However, the Story variety has a predominance of flavonoids (75.074 ± 2.309 µg QE/g) and flavones (45.074 ± 2.09 µg QE/g). The detection of organic acids has shown that the acid succinic is the most abundant in all the varieties of studied apple fruits. These results allow us to infer that non-consumable varieties are also important dietary sources of bioactive molecules, notably for polyphenols. The fact that these kinds can be used to produce other byproducts is therefore highly intriguing.

A synthetic superabsorbent polymer hydrogel nanocomposite was prepared by the free radical graft co-polymerization method. This study included the preparation of two surfaces: first sodium alginate-g-(acrylic acid-co-sodium; 4-ethenylbenzenesulfonate), SA-g-poly (Ac-co-EBS) hydrogel, and second surface hydrogel after zinc oxide loading SA-g-poly (Ac-co-EBS). Hydrogel nanocomposite was prepared from different monomers for the removal of pollutants. The physical characterizations of nanocomposite have been studied using several techniques like UV-vis, FTIR, FE-SEM, TEM, EDX, and XRD. The data from the adsorption study show that E% increases with increasing contact time, with the best agitation time of 1 h, after which the adsorption becomes constant. The increase in adsorbent amount 0.01–0.1 g, the percentage removal of tetracycline (TC) and phenol (PH) increased from 60.639–97.085 and 487.71–94.05%, respectively, and Qe decreased 606.39–97.08 to 487.1831–94.456 mg/g on hydrogel. The ∆H value is endothermic. All processes of adsorption are considered spontaneous, from a negative value of ∆G to a positive value of ∆S. The release of the TC drug was studied in conditions similar to those in the human body in terms of acidity and temperature. The cumulative release of TC drug in 3 h was 50.65%, 42.33%, pH = 7.5 and pH 1.2, respectively.

Geographical origin and environmental factors have a significant impact on the constituents and the biological properties of medicinal and aromatic plants. Herein, we investigated the Inula viscosa plant grown in El Menzel - Morocco, with a focus on the impact of geographical pronvince and solvent type on the mass yield and the biological activities of plant extracts. Chemical composition was characterized by gas chromatography/mass spectrometry (GC/MS). Antimicrobial activity was determined using the disk diffusion method and the microdilution test against eight clinical fungal, Gram-positive and Gram-negative bacterial isolates. Chemical composition results showed that the plant has good nutritional quality in terms of protein, carbohydrates, lipids and dietary fibre. In fact, alkaloids and saponisides are the most predominant chemical compounds in Inula Vuscosa. Meanwhile, eighty volatile compounds were identified, representing 95% of the total essential oil content, the main component of which is tetra-pentacontane (11.26%). Furthermore, results showed high antioxidant activity, with efficacy increasing in the order: Essential Oil > Chloroform extract > Ethereal extract > Ethanolic extract. In addition, both chloroformic extract and essential oil demonstrated significant antibacterial activity against all strains tested. This study highlights the influence of geographical variations and extraction solvents on the bioactivity of Inula viscosa, offering insights into its potential applications in pharmacology and nutraceuticals.

During Covid-19 pandemic, face masks have become a ubiquitous protective measure. This poses new challenges for surveillance systems that heavily rely on facial recognition. To address this critical issue, we present a novel enhanced surveillance system that leverages deep learning techniques to tackle two crucial tasks simultaneously: anomaly detection of masked individuals' activities and masked face completion for accurate recognition. For anomaly detection, we employ a custom-designed deep neural network capable of processing real-time video streams. Finding a dataset of anomaly events of masked individuals is a big challenge for us. We handle this challenge using efficient techniques such as Dlib library and other image processing techniques. The network is trained on a diverse dataset encompassing normal and abnormal activities of masked individuals, enabling it to identify suspicious behaviors effectively. The surveillance cameras will exchange information, using a suitable network protocol, about detected anomalies and share relevant image data to aid in decision-making and choose the best images for further processing. In the context of masked face completion, we present a novel architecture called CCGAN network that is a combination of convolutional neural network (CNN) and conditioned generative adversarial network (CGAN) to generate the hidden parts of the face in a form that is accurate and close to the original face shape, as shown in our results. We conduct extensive experiments on publicly available datasets, demonstrating superior performance in both anomaly detection and masked face completion tasks. We have achieved 90% accuracy for anomaly detection of masked people.

Diagnosing brain tumors using magnetic resonance imaging (MRI) presents significant challenges due to the complexities of segmentation and the variability in tumor characteristics. To address the limitations inherent in traditional methods, this research employs an advanced deep learning approach, integrating ResNet50 for feature extraction and Generative Adversarial Networks (GANs) for data augmentation. A comprehensive evaluation of ten transfer learning algorithms, including GoogLeNet and VGG-16, was conducted for the classification of brain tumors. Model performance was assessed using precision, recall, and F1-score metrics, complemented by additional metrics such as Hamming loss and the Matthews correlation coefficient to provide a more comprehensive insight. To ensure transparency in image predictions, Explainable AI techniques, specifically Local Interpretable Model-Agnostic Explanations (LIME), were utilized. The study involved the analysis of 7023 MRI images, with TumorGANet being trained on a dataset encompassing gliomas, meningiomas, non-tumorous cases, and pituitary tumors. The results demonstrate the exceptional performance of proposed model named TumorGANet, achieving an accuracy of 99.53%, precision and recall rates of 100%, F1 scores of 99%, and a Hamming loss of 0.2%.

Accurate node localization in Wireless Sensor Networks (WSNs) is crucial for applications like environmental monitoring and military surveillance. Traditional localization methods, such as trilateration, often struggle with accuracy due to signal attenuation and environmental obstructions, leading to significant localization errors in practical scenarios. This paper aims to address the limitations of traditional localization methods by developing and evaluating a hybrid localization method that enhances accuracy and robustness in node localization within WSNs. The proposed method integrates the Bounding Box approach with the Harmony Search optimization algorithm, resulting in the Bounding Box Harmony Search (BBHS) method. The BBHS method utilizes the initial geometric constraints provided by the Bounding Box approach and refines these estimates using the global optimization capabilities of the Harmony Search algorithm. Simulation results, obtained using a custom-developed WSN localization simulator, demonstrate that the BBHS method significantly reduces localization errors compared to traditional trilateration and the standalone Bounding Box method. The BBHS method consistently provides enhanced accuracy and robustness across varying network conditions, highlighting its effectiveness in practical deployment scenarios. The advancements presented in this paper suggest that hybrid methods like BBHS represent a significant step forward in WSN localization technologies. By combining geometric constraints with optimization processes, the BBHS method overcomes the drawbacks of earlier techniques, paving the way for more reliable and resilient WSN operations.

In today’s interconnected world, cybersecurity has emerged as a critical domain for ensuring the integrity, confidentiality, and availability of digital assets. Within this sphere, insider threats represent a unique and particularly insidious class of security risks, originating not from external hackers but from within the organization itself. These threats are perpetrated by individuals with inside information concerning the organization’s security practices, data, and computer systems. Traditional security measures like firewalls, intrusion detection systems, and antivirus software are often inadequate for tackling insider threats effectively, owing to their focus on external threats. This inadequacy underscores the urgent need for the development and implementation of more sophisticated, targeted detection techniques for insider threats. In response to this challenge, our research introduces an innovative approach that employs the Density-Based Local Outlier Factor (DBLOF) algorithm, fine-tuned to specifically tackle the challenges posed by the imbalanced nature of the CERT r4.2 insider threat dataset. This dataset is characterized by a highly skewed distribution, with a significant majority of benign instances and only a minimal proportion of malicious activities. Conventional detection algorithms often fail to effectively identify these rare but dangerous instances, leading to a high rate of false negatives. Our methodology capitalizes on the algorithm’s ability to focus on the local density deviation of data points, thereby enabling the precise identification of outliers that are indicative of potential insider threats. Through rigorous testing and validation processes, we have achieved outstanding results, with an of F-score 98%. These remarkable outcomes not only affirm the effectiveness of the DBLOF algorithm as a powerful tool for combating insider threats but also contribute valuable insights to the broader academic and professional discourse on cybersecurity. Importantly, our findings have practical implications, offering organizations actionable recommendations for boosting their internal security mechanisms against the complex and evolving landscape of insider threats.

Intangible cultural heritage, a vital part of our collective human legacy, faces the threat of being lost in the tide of modernization. Preserving and promoting these cultural treasures require innovative approaches that transcend traditional boundaries. In this paper, we introduce “El-FnaVR”, a groundbreaking virtual reality (VR) application that captures the vibrant essence of Marrakech’s renowned UNESCO-listed Jemaa El-Fna square, Morocco. El-FnaVR immerses users in a detailed virtual replica of the square, replete with lifelike animated characters and spatial 3D audio that reproduces the locale’s unique atmosphere faithfully capturing the location’s distinctive ambiance. This paper delves into the comprehensive five-stage design and development process of the application, highlighting its unique features and demonstrating how it replicates the diverse activities and performances at the square. A user study, conducted with participants, reveals overwhelmingly positive responses, as participants laud the application’s immersive nature, ease of use, and social appeal. The study’s findings indicate that El-FnaVR successfully evokes the sensation of being present at the Jemaa El-Fna square, and offers valuable insights into the events and traditions that define it. As a significant step towards the preservation and promotion of intangible cultural heritage.

Recently, there has been a growing interest in biodiesel due to its utilisation of renewable resources, which is particularly significant given the increasing depletion of fossil fuel stocks. The utilisation of Cresson weed in biodiesel fuel production is a pioneering application of botanical herbs within the biodiesel industry. This study compares the combustion characteristics of biodiesel fuel B10, B20, B40, B60, and D80B10M10 blends with petroleum diesel. This analysis examines the combustion process across various equivalence ratios in semi-industrial boilers. The study examines the combustion efficiency, flue gas emissions (CO, CO2, T exhaust, and HC), and flame length. Findings show that adding more biodiesel fuel to diesel fuel increases its combustion efficiency above and beyond what is possible with regular diesel fuel at high energy levels. In addition, blends like B60 and other mixtures like D80B10M10 emit lower levels of pollutants, such as CO, than diesel and increase T exhaust and CO2, which indicates the completion of combustion.

Metal-organic frameworks (MOFs) are a relatively new class of materials of unique porous structures and exceptional properties. Currently, more than 110,000 types of MOFs have been reported among the countless possibilities. In this study, we have synthesised a novel MOF using zirconium chloride as the metal source and 4,4'-dicarboxy-2,2'-biquinoline (bicinchoninic acid disodium salt) as the linker, which reacted in N,N-Dimethylformamide (DMF) solvent. Three preparation methods were employed to prepare five types of the MOF, and they were compared to optimize the synthesis conditions. The resulting MOFs, named Zr-BADS, were characterised using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), microscopy, and X-ray diffraction (XRD). By incorporating methanol into the preparation solvent, the surface area was increased to 396 m2/g. Additionally, the prepared MOFs exhibited amorphous shapes, with variations in size depending on the synthesis method. This research demonstrates the significance of the preparation method in controlling resulting particles’ properties.