First molecular survey of tick-borne protozoan and bacterial pathogens in the questing tick population in Bangladesh.

Questing ticks carry various tick-borne pathogens (TBPs) that are responsible for causing tick-borne diseases (TBDs) in humans and animals around the globe, especially in the tropics and sub-tropics. Information on the distribution of ticks and TBPs in a specific geography is crucial for the formulation of mitigation measures against TBDs. Therefore, this study aimed to survey the TBPs in the questing tick population in Bangladesh. A total of 2748 questing hard ticks were collected from the pastures in Sylhet, Bandarban, Sirajganj, Dhaka, and Mymensingh districts through the flagging method. After morphological identification, the ticks were grouped into 142 pools based on their species, sexes, life stages, and collection sites. The genomic DNA extracted from tick specimens was screened for 14 pathogens, namely Babesia bigemina (AMA-1), Babesia bovis (RAP-1), Babesia naoakii (AMA-1), Babesia ovis (18S rRNA), Theileria luwenshuni (18S rRNA), Theileria annulata (Tams-1), Theileria orientalis (MPSP), Anaplasma marginale (groEL), Anaplasma phagocytophilum (16S rRNA), Anaplasma bovis (16S rRNA), Anaplasma platys (16S rRNA), Ehrlichia spp. (16S rRNA), Rickettsia spp. (gltA), and Borrelia (Bo.) spp. (flagellin B) using genus and species-specific polymerase chain reaction (PCR) assays. The prevalence of the detected pathogens was calculated using the maximum likelihood method (MLE) with 95 % confidence interval (CI). Among 2748 ixodid ticks, 2332 (84.86 %) and 416 (15.14 %) were identified as Haemaphysalis bispinosa and Rhipicephalus microplus, respectively. Haemaphysalis bispinosa was found to carry all the seven detected pathogens, while larvae of R. microplus were found to carry only Bo. theileri. Among the TBPs, the highest detection rate was observed in A. bovis (20/142 pools, 0.81 %, CI: 0.51-1.20), followed by T. orientalis (19/142 pools, 0.72 %, CI: 0.44-1.09), T. luwenshuni (9/142 pools, 0.34 %, CI: 0.16-0.62), B. ovis (4/142 pools, 0.15 %, CI: 0.05 - 0.34) and Bo. theileri (4/142 pools, 0.15 %, CI: 0.05-0.34), Ehrlichia ewingii (3/142 pools, 0.11 %, CI: 0.03-0.29), and Babesia bigemina (1/142, 0.04 %, CI: 0.00 - 0.16). This study reports the existence of T. luwenshuni, E. ewingii, and Bo. theileri in Bangladesh for the first time. The novel findings of this study are the foremost documentation of transovarian transmission of B. bigemina and E. ewingii in H. bispinosa and also provide primary molecular evidence on the presence of E. ewingii and Bo. theileri in H. bispinosa. Therefore, this study may shed light on the circulating TBPs in ticks in the natural environment and thereby advocate awareness among physicians and veterinarians to control and prevent TBDs in Bangladesh.

Metal-sulfide/polysulfide functionalized layered double hydroxides - recent progress in the removal of heavy metal ions and oxoanionic species from aqueous solutions.

Water constitutes an indispensable resource for global life but remains susceptible to pollution from diverse human activities. To mitigate this issue, researchers are committed to purifying water using a variety of materials to remove harmful chemicals, such as heavy metals. Layered double hydroxides (LDHs), with their intriguing, layered structure and chemical behavior, have attained substantial attention for their effectiveness in removing heavy metal cations and various inorganic oxoanions from water. To enhance the efficiency, considerable endeavors have focused on functionalizing LDHs with different chemical species. Intercalation with metal sulfides has proven to be particularly effective, facilitating heavy metal absorption through multiple mechanisms, including ion-exchange, reductive precipitation, and surface sorption. This review concentrates on the synthesis and performance of polysulfide (Sx, x = 2-5), Mo-S, and Sn-S anion intercalated LDHs for heavy metal cations and inorganic oxoanion sorption, along with their mechanisms. Furthermore, the discussion includes prospects for expanding the chemistry of metal sulfide intercalated LDHs, with existing challenges and future outlooks.

Royal Poinciana Biodiesel Blends with 1-Butanol as a Potential Alternative Fuel for Unmodified Research Engines.

This research work investigates the experimental work of a single-cylinder diesel engine operated with royal poinciana biodiesel blends with various proportions of 10, 20, and 30% volume with 1-butanol as an effective ignition-improving additive. The test blends were indicated as D90RP7B3 (90% diesel + 7% royal poinciana biodiesel + 3% butanol), D80RP14B6 (80% diesel + 14% royal poinciana biodiesel + 6% butanol), D70RP21B9 (70% diesel + 21% royal poinciana biodiesel + 9% butanol), and pure royal poinciana biodiesel (RP100) and diesel. The significant findings or results obtained during the experimentation are that BTE is suitable for blend D90RP7B3, and the least BSFC is found for blend D90RP7B3 in the 0.24 kg/kWh range. The inline cylinder pressures are found to be suitable for the blend D90RP7B3 in the range of 7 MPa; HRR is ideal for both the blends D90RP7B3 and D80RP14B6 in the range of 90 and 88 kJ; D90RP7B3 possesses adequate ignition delay at full load conditions 16° in crank angle advance; maximum A/F ratios are well suitable for the blend D90RP7B3 in the ratio 11:1 at higher loads. Volumetric efficiency is achieved well for all the blends and diesel; the emissions released from the royal poinciana blends, such as CO, CO2, HC, and NOX, were reduced by 14.12, 8.33, 11.1, and 18.8% compared to standard diesel. Hence, royal poinciana blends with 1-butanol can be considered the best fuels in the automobile sector.

Enhancing Wear Resistance of UHMWPE Composites with Micro MoS2 and Nano Graphite: A Taguchi-DOE Approach.

This study presents an in-depth investigation into the wear characteristics of ultrahigh-molecular-weight polyethylene (UHMWPE) composites reinforced with microsized MoS2 and nanosized graphite particles. The objective is to enhance the wear resistance of the UHMWPE by examining the effects of various parameters and optimizing the wear performance. To achieve this goal, wet wear tests were conducted under controlled conditions, and the results were compared between composites with micro MoS2 and nano graphite reinforcements. The Taguchi method was employed to design the experiments (DOE) using an L9 orthogonal array. Four key parameters, namely, reinforcement percentage, load, speed, and track radius, were varied systematically to analyze their impact on wear characteristics, including wear rate, frictional forces, and the coefficient of friction (COF). The data obtained from the experiments were subjected to analysis of variance (ANOVA) to identify the significant factors affecting wear behavior. Subsequently, the optimal wear parameters were determined through regression analysis, allowing for the prediction of wear characteristics under the optimum conditions. This research not only provides insights into the comparative performance of micro MoS2 and nano graphite reinforcements in UHMWPE composites but also offers a comprehensive approach to optimizing wear resistance by employing advanced statistical and experimental techniques. The findings contribute to the development of more durable and wear-resistant materials with potential applications in various industries, such as those investigated in the study, which are commonly employed, such as automotive, aerospace, medical devices, or manufacturing.

Removal of heavy metal ions from wastewater using two-dimensional transition metal carbides.

Water is an indispensable material for human life. Unfortunately, the development of industrial activities has reduced the quality of water resources in the world. Meantime, heavy metals are an important factor in water pollution due to their toxicity. This study highlights the method for the capture of heavy metal ions from wastewater using the procedure of adsorption. The adsorption of toxic heavy metal ions (Pb2+, Hg2+, and Cd2+) on Ca2C as well as Cr2C carbide-nitride MXene monolayers is investigated using the density functional theory. We have carried out the optimization of the considered MXenes by nine DFT functionals: PBE, TPSS, BP86, B3LYP, TPSSh, PBE0, CAM-B3LYP, M11, and LC-WPBE. Our results have shown a good agreement with previously measured electronic properties of the Ca2C and Cr2C MXene layers and the PBE DFT method. The calculated cohesive energy for the Ca2C and Cr2C MXene monolayers are -4.12 eV and -4.20 eV, respectively, which are in agreement with the previous studies. The results reveal that the adsorbed heavy metal ions have a substantial effect on the electronic properties of the considered MXene monolayers. Besides, our calculations show that the metal/MXene structures with higher electron transport rates display higher binding energy as well as charge transfers between the metal and Ca2C and Cr2C layers. Time-dependent density functional analysis also displayed "ligand to metal charge transfer" excitations for the metal/MXene systems. The larger Ebin for the Pb@Ca2C as well as Pb@Cr2C are according to larger redshifts which are expected (Δλ = 45 nm and 71 nm, respectively). Our results might be helpful for future research toward the application of carbide-nitride MXene materials for removing wastewater pollutants.

CdIn2Se4@chitosan heterojunction nanocomposite with ultrahigh photocatalytic activity under sunlight driven photodegradation of organic pollutants.

This research focused on synthesizing a CdIn2Se4@Ch nanocomposite by doping CdIn2Se4 into chitosan using a photolysis assisted ultrasonic process. The aim was to enhance the photodegradation efficiency of ofloxacin and 2,4-dichlorophenoxyacetic acid under sunlight. The synthesized CdIn2Se4@Ch nanocomposite was investigated via different techniques, including XRD, XPS, FTIR, TEM, DSC, TGA, UV-Vis and PL. The study also investigated the influence of various reaction parameters, including the effects of inorganic and organic ions. The synthesized nanocomposite demonstrated exceptional efficiency, achieving 86 % and 95 % removal rates, with corresponding rate constants of 0.025 and 0.047 min-1. This performance surpasses that of CdIn2Se4 by approximately 1.35 and 2.25 times, respectively. The values of COD were decreased to 78 and 86 % for ofloxacin and 2,4-dichlorophenoxyacetic, while the TOC values decreased to 71 and 84 %, respectively, from their premier values. The improvement in performance is associated with the introduction of CdIn2Se4 into chitosan, resulting in the self-integration of Cd into the catalyst. This creates a localized accumulation point for electrons, enhancing the efficiency of charge separation and further reducing the surface charge of chitosan. Experimental evidence suggests that superoxide and hydroxyl radicals play a significant role in the photodegradation of pollutants. Additionally, the nanocomposite exhibits excellent stability and can be reused up to five times, indicating remarkable stability and reusability of the developed photocatalyst.

Comparative simulation of nonlinear radiative nano casson and maxwell fluids with periodic magnetic force and sensitivity analysis.

This study investigated cyclic magneto-hydrodynamic radiative effects in Casson and Maxwell fluids, including nonlinear radiation and Arrhenius activation energy. It promotes non-Newtonian fluid use in diverse fields like industry, manufacturing, sciences, medicine, and engineering. Using boundary layer approximations, non-dimensional equations are formulated. For numerical solutions, widely recognized explicit finite difference method (EFDM) has been utilized. To ensure the robustness of EFDM results, stability and convergence tests are performed. Exploration involve a detailed sensitivity analysis by using RSM, offering a thorough understanding of influential parameters. These analyses explore complex interactions among physical parameters, affecting Nusselt number, skin friction, and Sherwood number. Maxwell fluid's velocity is more affected by periodic magnetic force than Casson fluid, during the presence of nonlinear radiation. Additionally, nonlinear thermal radiation has a greater impact on temperature and concentration profiles compared to linear radiation for both fluids. Moreover, Casson fluid has a stronger influence on the average heat transfer rate compared to Maxwell fluid with nonlinear thermal radiation which is 8.6 % greater than the Maxwell fluid. On the other hand, at constant thermal radiation (Ra), due to decrease of Brownian motion (Nb), the rate of heat transfer is reduced by 1.2 % and 0.3 % respectively for Maxwell and Casson fluid. Also, for thermophoresis parameter (Nt), this rate is reduced by 2 % and 1.6 % respectively. The investigation also revealed that the Ra exhibits a positive sensitivity towards average Nusselt number, while Nb and Nt are displayed a negative sensitivity.

Antifungal plant flavonoids identified in silico with potential to control rice blast disease caused by Magnaporthe oryzae.

Rice blast disease, caused by the fungus Magnaporthe oryzae, poses a severe threat to rice production, particularly in Asia where rice is a staple food. Concerns over fungicide resistance and environmental impact have sparked interest in exploring natural fungicides as potential alternatives. This study aimed to identify highly potent natural fungicides against M. oryzae to combat rice blast disease, using advanced molecular dynamics techniques. Four key proteins (CATALASE PEROXIDASES 2, HYBRID PKS-NRPS SYNTHETASE TAS1, MANGANESE LIPOXYGENASE, and PRE-MRNA-SPLICING FACTOR CEF1) involved in M. oryzae's infection process were identified. A list of 30 plant metabolites with documented antifungal properties was compiled for evaluation as potential fungicides. Molecular docking studies revealed that 2-Coumaroylquinic acid, Myricetin, Rosmarinic Acid, and Quercetin exhibited superior binding affinities compared to reference fungicides (Azoxystrobin and Tricyclazole). High throughput molecular dynamics simulations were performed, analyzing parameters like RMSD, RMSF, Rg, SASA, hydrogen bonds, contact analysis, Gibbs free energy, and cluster analysis. The results revealed stable interactions between the selected metabolites and the target proteins, involving important hydrogen bonds and contacts. The SwissADME server analysis indicated that the metabolites possess fungicide properties, making them effective and safe fungicides with low toxicity to the environment and living beings. Additionally, bioactivity assays confirmed their biological activity as nuclear receptor ligands and enzyme inhibitors. Overall, this study offers valuable insights into potential natural fungicides for combating rice blast disease, with 2-Coumaroylquinic acid, Myricetin, Rosmarinic Acid, and Quercetin standing out as promising and environmentally friendly alternatives to conventional fungicides. These findings have significant implications for developing crop protection strategies and enhancing global food security, particularly in rice-dependent regions.

Prevalence and factors associated with digital addiction among students taking university entrance tests: a GIS-based study.

BACKGROUND: The surge in digital media consumption, coupled with the ensuing consequences of digital addiction, has witnessed a rapid increase, particularly after the initiation of the COVID-19 pandemic. Despite some studies exploring specific technological addictions, such as internet or social media addiction, in Bangladesh, there is a noticeable gap in research focusing on digital addiction in a broader context. Thus, this study aims to investigate digital addiction among students taking the university entrance test, examining its prevalence, contributing factors, and geographical distribution using GIS techniques. METHODS: Data from a cross-sectional survey were collected from a total of 2,157 students who were taking the university entrance test at Jahangirnagar University, Bangladesh. A convenience sampling method was applied for data collection using a structured questionnaire. Statistical analyses were performed with SPSS 25 Version and AMOS 23 Version, whereas ArcGIS 10.8 Version was used for the geographical distribution of digital addiction. RESULTS: The prevalence of digital addiction was 33.1% (mean score: 16.05 ± 5.58). Those students who are attempting the test for a second time were more likely to be addicted (42.7% vs. 39.1%), but the difference was not statistically significant. Besides, the potential factors predicted for digital addiction were student status, satisfaction with previous mock tests, average monthly expenditure during the admission test preparation, and depression. No significant difference was found between digital addiction and districts. However, digital addiction was higher in the districts of Manikganj, Rajbari, Shariatpur, and Chittagong Hill Tract areas, including Rangamati, and Bandarban. CONCLUSIONS: The study emphasizes the pressing need for collaborative efforts involving educational policymakers, institutions, and parents to address the growing digital addiction among university-bound students. The recommendations focus on promoting alternative activities, enhancing digital literacy, and imposing restrictions on digital device use, which are crucial steps toward fostering a healthier digital environment and balanced relationship with technology for students.

Evaluation of different models of general practitioners working in or alongside emergency departments: a mixed-methods realist evaluation.

Background: Emergency healthcare services are under intense pressure to meet increasing patient demands. Many patients presenting to emergency departments could be managed by general practitioners in general practitioner-emergency department service models. Objectives: To evaluate the effectiveness, safety, patient experience and system implications of the different general practitioner-emergency department models. Design: Mixed-methods realist evaluation. Methods: Phase 1 (2017-8), to understand current practice: rapid realist literature review, national survey and follow-up key informant interviews, national stakeholder event and safety data analysis. Phase 2 (2018-21), to collect and analyse qualitative (observations, interviews) and quantitative data (time series analysis); cost-consequences analysis of routine data; and case site data for 'marker condition' analysis from a purposive sample of 13 case sites in England and Wales. Phase 3 (2021-2), to conduct mixed-methods analysis for programme theory and toolkit development. Results: General practitioners commonly work in emergency departments, but delivery models vary widely in terms of the scope of the general practitioner role and the scale of the general practitioner service. We developed a taxonomy to describe general practitioner-emergency department service models (Integrated with the emergency department service, Parallel within the emergency department, Outside the emergency department on the hospital site) and present a programme theory as principal output of the study to describe how these service models were observed to operate. Routine data were of variable quality, limiting our analysis. Time series analysis demonstrated trends across intervention sites for: increased time spent in the emergency department; increased emergency department attendances and reattendances; and mixed results for hospital admissions. Evidence on patient experience was limited but broadly supportive; we identified department-level processes to optimise the safety of general practitioner-emergency department models. Limitations: The quality, heterogeneity and extent of routine emergency department data collection during the study period limited the conclusions. Recruitment was limited by criteria for case sites (time series requirements) and individual patients (with 'marker conditions'). Pandemic and other pressures limited data collection for marker condition analysis. Data collected and analysed were pre pandemic; new approaches such as 'telephone first' and their relevance to our findings remains unexplored. Conclusion: Findings suggest that general practitioner-emergency department service models do not meet the aim of reducing the overall emergency department waiting times and improving patient flow with limited evidence of cost savings. Qualitative data indicated that general practitioners were often valued as members of the wider emergency department team. We have developed a toolkit, based on our findings, to provide guidance for implementing and delivering general practitioner-emergency department services. Future work: The emergency care data set has since been introduced across England to help standardise data collection to facilitate further research. We would advocate the systematic capture of patient experience measures and patient-reported outcome measures as part of routine care. More could be done to support the development of the general practitioner in emergency department role, including a core set of competencies and governance structure, to reflect the different general practitioner-emergency department models and to evaluate the effectiveness and cost effectiveness to guide future policy. Study registration: This study is registered as PROSPERO CRD42017069741. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 15/145/04) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 10. See the NIHR Funding and Awards website for further award information.

Hospital emergency departments are under huge pressure. Patients are waiting many hours to be seen, some with problems that general practitioners could deal with. To reduce waiting times and improve patient care, arrangements have been put in place for general practitioners to work in or alongside emergency departments (general practitioner­emergency department models). We studied the different ways of working to find out what works well, how and for whom. We brought together a lot of information. We reviewed existing evidence, sent out surveys to 184 emergency departments, spent time in the emergency departments observing how they operated and interviewing 106 staff in 13 hospitals and 24 patients who visited those emergency departments. We also looked at statistical information recorded by hospitals. Two public contributors were involved from the beginning, and we held two stakeholder events to ensure the relevance of our research to professionals and patients. Getting reliable figures to compare the various general practitioner­emergency department set-ups (inside, parallel to or outside the emergency department) was difficult. Our findings suggest that over time more people are coming to emergency departments and overall waiting times did not generally improve due to general practitioner­emergency department models. Evidence that general practitioners might admit fewer patients to hospital was mixed, with limited findings of cost savings. Patients were generally supportive of the care they received, although we could not speak to as many patients as we planned. The skills and experience of general practitioners were often valued as members of the wider emergency department team. We identified how the care provided was kept safe with: strong leaders, good communication between different types of staff, highly trained and experienced nurses responsible for streaming and specific training for general practitioners on how they were expected to work. We have produced a guide to help professionals develop and improve general practitioner­emergency department services and we have written easy-to-read summaries of all the articles we published.

Mo3S13 Chalcogel: A High-Capacity Electrode for Conversion-Based Li-Ion Batteries.

Despite large theoretical energy densities, metal-sulfide electrodes for energy storage systems face several limitations that impact the practical realization. Here, we present the solution-processable, room temperature (RT) synthesis, local structures, and application of a sulfur-rich Mo3S13 chalcogel as a conversion-based electrode for lithium-sulfide batteries (LiSBs). The structure of the amorphous Mo3S13 chalcogel is derived through operando Raman spectroscopy, synchrotron X-ray pair distribution function (PDF), X-ray absorption near edge structure (XANES), and extended X-ray absorption fine structure (EXAFS) analysis, along with ab initio molecular dynamics (AIMD) simulations. A key feature of the three-dimensional (3D) network is the connection of Mo3S13 units through S-S bonds. Li/Mo3S13 half-cells deliver initial capacity of 1013 mAh g-1 during the first discharge. After the activation cycles, the capacity stabilizes and maintains 312 mAh g-1 at a C/3 rate after 140 cycles, demonstrating sustained performance over subsequent cycling. Such high-capacity and stability are attributed to the high density of (poly)sulfide bonds and the stable Mo-S coordination in Mo3S13 chalcogel. These findings showcase the potential of Mo3S13 chalcogels as metal-sulfide electrode materials for LiSBs.

A Retrospective Study on the Outcome of Coronavirus Disease 2019 (COVID-19) Patients Admitted to a District General Hospital and Predictors of High Mortality.

BACKGROUND: The clinical features and severity of coronavirus disease 2019 (COVID-19) vary between patients and countries. Patients with certain conditions are predisposed to poor outcomes compared with those without medical conditions, such as diabetes, dementia, and hypertension (HTN). METHODS: The aim of this retrospective study was to assess factors associated with higher mortality in patients with COVID-19 infections and to identify the reason for hospital admission in these patients. The study was performed on patients admitted between 1 and 31 March 2020. Data collection was done retrospectively from electronic medical records. RESULTS: There were 269 patient admissions during this period, of which 147 were included in this audit. The mean age of COVID-19-positive patients was 62.8 years and 65.9 years for COVID-19-negative patients during this period. Forty-seven patients requiring hospital admission were COVID-19 positive and 93 were COVID-19 negative. There were no COVID-19 swabs in the seven patients included in the audit. Approximately 50% of the COVID-19-positive patients presented with fever and shortness of breath (sob), followed by dyspnea and cough (seven patients). The most common comorbidity was HTN, followed by type 2 diabetes mellitus (T2DM) and ischemic heart disease (IHD). The survival rate was 72.3% in COVID-19-positive patients and 80% in COVID-19-negative patients. The average length of stay was 14.4 days for COVID-19-positive survivors compared to 7.8 days for COVID-19-negative survivors. Most patients who tested positive for COVID-19 infection received oseltamivir vaccination and antibiotics. The presence of HTN, diabetes mellitus (DM), age, and organ failure was associated with a high mortality risk. CONCLUSION: Our study supports the findings of previous studies that diabetes, HTN, coronary artery disease, old age, and organ failure were associated with high mortality in patients admitted to hospitals with COVID-19 infections.

State-transition dynamics of resting-state functional magnetic resonance imaging data: model comparison and test-to-retest analysis.

Electroencephalogram (EEG) microstate analysis entails finding dynamics of quasi-stable and generally recurrent discrete states in multichannel EEG time series data and relating properties of the estimated state-transition dynamics to observables such as cognition and behavior. While microstate analysis has been widely employed to analyze EEG data, its use remains less prevalent in functional magnetic resonance imaging (fMRI) data, largely due to the slower timescale of such data. In the present study, we extend various data clustering methods used in EEG microstate analysis to resting-state fMRI data from healthy humans to extract their state-transition dynamics. We show that the quality of clustering is on par with that for various microstate analyses of EEG data. We then develop a method for examining test-retest reliability of the discrete-state transition dynamics between fMRI sessions and show that the within-participant test-retest reliability is higher than between-participant test-retest reliability for different indices of state-transition dynamics, different networks, and different data sets. This result suggests that state-transition dynamics analysis of fMRI data could discriminate between different individuals and is a promising tool for performing fingerprinting analysis of individuals.

Amorphous K-Co-Mo-Sx Chalcogel: A Synergy of Surface Sorption and Ion-Exchange.

Chalcogel represents a unique class of meso- to macroporous nanomaterials that offer applications in energy and environmental pursuits. Here, the synthesis of an ion-exchangeable amorphous chalcogel using a nominal composition of K2 CoMo2 S10 (KCMS) at room temperature is reported. Synchrotron X-ray pair distribution function (PDF), X-ray absorption near-edge structure (XANES), and extended X-ray absorption fine structure (EXAFS) reveal a plausible local structure of KCMS gel consisting of Mo5+ 2 and Mo4+ 3 clusters in the vicinity of di/polysulfides which are covalently linked by Co2+ ions. The ionically bound K+ ions remain in the percolating pores of the Co-Mo-S covalent network. XANES of Co K-edge shows multiple electronic transitions, including quadrupole (1s→3d), shakedown (1s→4p + MLCT), and dipole allowed 1s→4p transitions. Remarkably, despite a lack of regular channels as in some crystalline solids, the amorphous KCMS gel shows ion-exchange properties with UO2 2+ ions. Additionally, it also presents surface sorption via [S∙∙∙∙UO2 2+ ] covalent interactions. Overall, this study underscores the synthesis of quaternary chalcogels incorporating alkali metals and their potential to advance separation science for cations and oxo-cationic species by integrating a synergy of surface sorption and ion-exchange.

Studies on the Removal of Malachite Green from Its Aqueous Solution Using Water-Insoluble ß-Cyclodextrin Polymers.

The rising global pollution of natural waters by dyes has brought to light the need for adaptable and efficient removal techniques. To create water-insoluble ß-cyclodextrin (ß-CD) polymers like CA/-CD, TA/-CD, and MA/-CD, several organic acids including citric acid (CA), tartaric acid (TA), and malic acid (MA) were cross-linked with ß-cyclodextrin in this study. The obtained polymers were characterized by different advanced analytical techniques such as FTIR, SEM, and UV-vis spectrophotometry. Malachite green dye was removed from aqueous solutions using the synthesized polymers by adsorption. The adsorption investigation was conducted under several conditions, including pH, adsorbent mass, dye concentration, temperature, contact time, adsorption isotherm, and kinetics. The adsorbent CA/ß-CD shows the highest adsorption of MG dye in all of the conditions because it contains a high number of carboxyl groups. The negatively charged carboxyl ions of CA/ß-CD attract the positively charged MG dye electrostatically and remove MG from aqueous media with an efficiency of 91%. As a result, the findings indicated that water-insoluble polymers based on ß-cyclodextrin are well-suited as inexpensive adsorbents to remove colors from aqueous media.

Did the COVID-19 pandemic affect levels of burnout, anxiety and depression among doctors and nurses in Bangladesh? A cross-sectional survey study.

INTRODUCTION: COVID-19 has caused severe disruption to clinical services in Bangladesh but the extent of this, and the impact on healthcare professionals is unclear. We aimed to assess the perceived levels of anxiety, depression and burnout among doctors and nurses during COVID-19 pandemic. METHODS: We undertook an online survey using RedCap, directed at doctors and nurses across four institutions in Bangladesh (The Sheikh Russel Gastro Liver Institute & Hospital (SRNGIH), Dhaka Medical College Hospital (DMCH), Mugda Medical College Hospital (MMCH) and M Abdur Rahim Medical College (MARMC) Hospital). We collected information on demographics, awareness of well-being services, COVID-19-related workload, as well as anxiety, depression and burnout using two validated questionnaires: the Hospital Anxiety and Depression Scale (HADS) and the Maslach Burnout Inventory (MBI). RESULTS: Of the 3000 participants approached, we received responses from 2705 (90.2%). There was a statistically significant difference in anxiety, depression and burnout scores across institutions (p<0.01). Anxiety, depression and burnout scores were statistically worse in COVID-19 active staff compared with those not working on COVID-19 activities (p<0.01 for HADS anxiety and depression and MBI emotional exhaustion (EE), depersonalisation (DP) and personal accomplishment (PA)). Over half of the participants exhibited some level of anxiety (SRNGIH: 52.2%; DMCH: 53.9%; MMCH: 61.3%; MARMC: 68%) with a high proportion experiencing depression (SRNGIH: 39.5%; DMCH: 38.7%; MMCH: 53.7%; MARMC: 41.1%). Although mean burnout scores were within the normal range for each institution, a high proportion of staff (almost 20% in some instances) were shown to be classified as experiencing burnout by their EE, DP and PA scores. CONCLUSION: We identified a high prevalence of perceived anxiety, depression and burnout among doctors and nurses during the COVID-19 pandemic. This was worse in staff engaged in COVID-19-related activities. These findings could help healthcare organisations to plan for future similar events.

Person identification with arrhythmic ECG signals using deep convolution neural network.

Over the past decade, the use of biometrics in security systems and other applications has grown in popularity. ECG signals in particular are attracting increased attention due to their characteristics, which are required for a trustworthy identification system. The majority of ECG-based person identification systems are evaluated without considering the health-state of the individuals. Few person identification systems consider person-by-person health-state annotation. This paper proposes a person identification system considering the health-state annotated ECG signals where each person's beats overlap among variant arrhythmia classes. This overlapping between the normal class and other arrhythmia classes grants the ability to isolate normal beats in the train set from the Arrhythmic beats in the test set. Therefore, this paper investigates the effect of arrhythmic heartbeats on biometric recognition. An effective lightweight CNN based on depth-wise separable convolution (DWSC) is proposed to enhance the performance of person identification for several common arrhythmia types using the MITBIH dataset. The proposed methodology has been tested on nine arrhythmia types and presents how different types of arrhythmia affect ECG-based biometric systems differently. The experimental results show excellent recognition performance (99.28%) on normal heartbeats and (93.81%) on arrhythmic heartbeats, outperforming other models in terms of mean accuracy.

Beneficiation of Low-Grade Hematite Iron Ore Fines by Magnetizing Roasting and Magnetic Separation.

Present investigation includes the magnetizing roasting of low-grade iron ore fines followed by grinding and beneficiation using magnetic separation. The hematite iron ore used in the investigation contains 53.17% T Fe, 10.7% SiO2, and 4.5% Al2O3. Powdered bituminous coal of 210 µm size with an ash content of 12.5% and fixed carbon of 54.25% was used as reductant during magnetizing roasting. Optical microstructures have shown where iron and silicate minerals are found and how they are interconnected. Hematite is the most abundant material in the specimen and is found in fine- and medium-sized grains. Hematite emerged as the predominant iron-bearing mineral, accompanied by magnetite and goethite phases in smaller proportions according to XRD analyses. The primary gangue mineral identified by scanning electron microscopy is quartz, with gibbsite, feldspar, and pyrolusite present in lesser levels. The effects of iron/coal ratio, roasting time, and roasting temperature were considered as variable parameters. Hematite ore's magnetic characteristics were significantly impacted by magnetizing roasting. By selectively magnetizing roasting, hematite is transformed into magnetite. With an Fe grade of 65.25% at a recovery value of 72.5% in the concentrate, magnetic separation produced the greatest result for Fe. The performance of magnetization and therefore the magnetic separation process were shown to be significantly impacted by temperature, reductant %, and roasting duration in this investigation.

Inclined Curved Crack Composite Beam: Experimental and Computational Analysis with Recycled Aluminum Composite Materials and Comparison with an Artificial Neural Network.

This research focuses on an inclined curved crack model for a recycled aluminum composite beam at various crack depths and locations. The inclined curved crack equation of the motion, by governing a free vibration curved beam with a different depth of crack, is solved computationally via the differential quadrature method (DQM) and experimentally; additionally, the result of the natural frequency has been compared with various depths of curvature. For the first four modes of cracked beams, the computational method's output is used to determine the natural frequencies associated with mode shapes. The outcomes of the computational results suggested a structural health monitoring system to detect deterioration in composite structures when modal parameters have changed. An experimental set of results was validated using MATLAB2019a, and the outcomes were compared with an artificial neural network.

Exploring risk factors and molecular targets in leukemia patients with COVID-19: a bioinformatics analysis of differential gene expression.

The molecular mechanism of COVID-19's pathogenic effects in leukemia patients is still poorly known. Our study investigated the possible disease mechanism of COVID-19 and its associated risk factors in patients with leukemia utilizing differential gene expression analysis. We also employed network-based approaches to identify molecular targets that could potentially diagnose and treat COVID-19-infected leukemia patients. Our study demonstrated a shared set of 60 genes that are expressed differentially among patients with leukemia and COVID-19. Most of these genes are expressed in blood and bone marrow tissues and are predominantly implicated in the pathogenesis of different hematologic malignancies, increasingly imperiling COVID-19 morbidity and mortality among the affected patients. Additionally, we also found that COVID-19 may influence the expression of several cancer-associated genes in leukemia patients, such as CCR7, LEF1, and 13 candidate cancer-driver genes. Furthermore, our findings reveal that COVID-19 may predispose leukemia patients to altered blood homeostasis, increase the risk of COVID-19-related liver injury, and deteriorate leukemia-associated injury and patient prognosis. Our findings imply that molecular signatures, like transcription factors, proteins such as TOP21, and 25 different microRNAs, may be potential targets for diagnosing and treating COVID-19-infected leukemia patients. Nevertheless, additional experimental studies will contribute to further validating the study's findings.