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The rate of ICU admission among patients with coronavirus varied from 3% to 100% and the mortality was as high as 86% of admitted patients. The objective of the systematic review was to investigate the rate of ICU admission, mortality, morbidity, and complications among patients with coronavirus. A comprehensive strategy was conducted in PubMed/Medline; Science direct and LILACS from December 2002 to May 2020 without language restriction. The Heterogeneity among the included studies was checked with forest plot, χ2 test, I2 test, and the p-values. All observational studies reporting rate of ICU admission, the prevalence of mortality and its determinants among ICU admitted patients with coronavirus were included and the rest were excluded. A total of 646 articles were identified from different databases and 50 articles were selected for evaluation. Thirty-seven Articles with 24983 participants were included. The rate of ICU admission was 32% (95% CI: 26 to 38, 37 studies and 32, 741 participants). The Meta-Analysis revealed that the pooled prevalence of mortality in patients with coronavirus disease in ICU was 39% (95% CI: 34 to 43, 37 studies and 24, 983 participants). The Meta-Analysis revealed that approximately one-third of patients admitted to ICU with severe Coronavirus disease and more than thirty percent of patients admitted to ICU with a severe form of COVID-19 for better care died which warns the health care stakeholders to give attention to intensive care patients. This Systematic review and Meta-Analysis was registered in Prospero international prospective register of systemic reviews (CRD42020177095) on April 9/2020.

Spinal anesthesia with bupivacaine has side effects such as hypotension, respiratory depression, vomiting, and shivering. The side effects are dose-dependent, therefore different approaches have been attempted to avoid spinal-induced complications including lowering the dose of local anesthetic and mixing it with additives like Neuraxial opioids. To compare the Hemodynamic and analgesic effects of intrathecal fentanyl as an adjuvant with low and conventional doses of bupivacaine in patients undergoing elective cesarean section under spinal anesthesia. An institutional-based prospective cohort study was conducted on 90 patients. Data was collected with chart review, intraoperative observation, and postoperatively patient interview. Data was entered into EPI INFO and transport to SPSS version 23 for analysis of variables using one-way ANOVA, Kruskal Wallis H rank test, and chi-square. Hypotension but not bradycardia, was significantly frequent in a conventional dose of bupivacaine alone (CB) group and a conventional dose of bupivacaine with fentanyl (CBF) groups than that of the lower dose of bupivacaine with fentanyl (LBF) groups. Duration of analgesia was significantly longer in LBF (248± 35.6 minutes) and in CBF groups (260.3±40.3 minutes) than in CB group (167.10 ± 31.45 minutes). Time for the first analgesic request was significantly later in LBF (304±47.8 minutes) and CBF (294.6±99.5 minutes) groups than that in CB group (177±25.88 minutes). The Lower dose of bupivacaine is associated with less risk of hypotension and faster recovery. Adding fentanyl with the lower dose of bupivacaine in spinal anesthesia for cesarean section could provide comparable anesthesia with the lower risk of hypotension and longer postoperative analgesia.

Introduction: Medications require suitable storage conditions to ensure the potency and efficacy of medicines. Appropriate puttingaway conditions are required to ensure the potency of medications. Medication that is not maintained at the required temperature may further increase the unnecessary burden on the general population's economy due to their lack of potency and efficacy. It is crucial to reduce any wastage, including that of drugs, to increase the efficient use of these scarce resources because there are significant health implications of drug waste. Methodology: A descriptive study was done at Dilla University Teaching Hospital beginning November 02, 2022, to December 02, 2022. Twenty indicators were used to assess the practice of drug storage, utilization, and checking expiration dates were designed and variables requiring a definition for the fullness of the checklist were predefined. For each measure, the expected achievement rate was 100%. A less than 50% completion rate was seen as a critical area in need of development, while indicators with a greater than 90% attainment rate were rated as acceptable. To analyze the data, SPSS version 26 was used. Results: The study found that none of the indications for the use, storage, and checking of drug expiration dates had a 100% completion rate. Among the indicators found to be below average (50%) were medical gas storage, medication storage, critical medication arrangement, storage of medications in refrigerators without using refrigerators for other purposes, storage facilities below 25[degrees]C, presence of lockable cupboards, and storage of internal medications such as oral liquids, injectable medications, rectal medications, and segregation. Conclusion: In conclusion, the majority of the indications for the usage, storage, and checking of the expiration date of drugs were discovered to be nonexistent or done insufficiently. To improve the practice of medicine storage, use, and expiration date checking, we recommend several strategies such as regular evaluation and monitoring. Keywords: drug storage, efficacy, medication wastage, potency

Detection of anomalies in video surveillance plays a key role in ensuring the safety and security of public spaces. The number of surveillance cameras is growing, making it harder to monitor them manually. So, automated systems are needed. This change increases the demand for automated systems that detect abnormal events or anomalies, such as road accidents, fighting, snatching, car fires, and explosions in real-time. These systems improve detection accuracy, minimize human error, and make security operations more efficient. In this study, we proposed the Composite Recurrent Bi-Attention (CRBA) model for detecting anomalies in surveillance videos. The CRBA model combines DenseNet201 for robust spatial feature extraction with BiLSTM networks that capture temporal dependencies across video frames. A multi-attention mechanism was also incorporated to direct the model’s focus to critical spatiotemporal regions. This improves the system’s ability to distinguish between normal and abnormal behaviors. By integrating these methodologies, the CRBA model improves the detection and classification of anomalies in surveillance videos, effectively addressing both spatial and temporal challenges. Experimental assessments demonstrate that the CRBA model achieves high accuracy on both the University of Central Florida (UCF) and the newly developed Road Anomaly Dataset (RAD). This model enhances detection accuracy while also improving resource efficiency and minimizing response times in critical situations. These advantages make it an invaluable tool for public safety and security operations, where rapid and accurate responses are needed for maintaining safety.

Information technology has significantly impacted society. IoT and its specialized variant, IoMT, enable remote patient monitoring and improve healthcare. While it contributes to improving healthcare services, it may pose significant security challenges, especially due to the growing interconnectivity of IoMT devices. Hence, a robust IDS is required to handle these issues and prevent future intrusions in a appropriate time. This study proposes an IDS model for the IoMT that integrates advanced feature selection techniques and deep learning to enhance detection performance. The proposed model employs Information Gain (IG) and Recursive Feature Elimination (RFE) in parallel to select the top 50% of features, from which intersection and union subsets are created, followed by a deep autoencoder (DAE) to reduce dimensionality without losing important data. Finally, a deep neural network (DNN) classifies traffic as normal or anomalous. The Experimental results demonstrate superior performance in terms of accuracy, precision, recall, and F1 score. It achieves an accuracy of 99.93% on the WUSTL-EHMS-2020 dataset while reducing training time and attains 99.61% accuracy on the CICIDS2017 dataset. The model performance was validated with an average accuracy of 99.82% ± 0.16% and a statistically significant p-value of 0.0001 on the WUSTL-EHMS-2020 dataset, which refers to stable statistical improvement. This study indicates that the proposed strategy decreases computational complexity and enhances IDS efficiency in resource-constrained IoMT environments.

The aim of the present study was to explore the correlation between the land-use/land cover change and the flash-flood potential changes in Zăbala catchment (Romania) between 1989 and 2019. In this regard, the efficiency of GIS, remote sensing and machine learning techniques in detecting spatial patterns of the relationship between the two variables was tested. The paper elaborated upon an answer to the increase in flash flooding frequency across the study area and across the earth due to the occurred land-use/land-cover changes, as well as due to the present climate change, which determined the multiplication of extreme meteorological phenomena. In order to reach the above-mentioned purpose, two land-uses/land-covers (for 1989 and 2019) were obtained using Landsat image processing and were included in a relative evolution indicator (total relative difference-synthetic dynamic land-use index), aggregated at a grid-cell level of 1 km2. The assessment of runoff potential was made with a multilayer perceptron (MLP) neural network, which was trained for 1989 and 2019 with the help of 10 flash-flood predictors, 127 flash-flood locations, and 127 non-flash-flood locations. For the year 1989, the high and very high surface runoff potential covered around 34% of the study area, while for 2019, the same values accounted for approximately 46%. The MLP models performed very well, the area under curve (AUC) values being higher than 0.837. Finally, the land-use/land-cover change indicator, as well as the relative evolution of the flash flood potential index, was included in a geographically weighted regression (GWR). The results of the GWR highlights that high values of the Pearson coefficient (r) occupied around 17.4% of the study area. Therefore, in these areas of the Zăbala river catchment, the land-use/land-cover changes were highly correlated with the changes that occurred in flash-flood potential.

Primary failure of tooth eruption (PFE) is a rare odontogenic defect and is characterized by failure of eruption of one or more permanent teeth. The aim of the study is to identify the genetic defect in a family with seven affected individuals segregating autosomal dominant non-syndromic PFE. Whole genome single-nucleotide polymorphism (SNP) genotyping was performed. SNP genotypes were analysed by DominantMapper and multiple shared haplotypes were detected on different chromosomes. Four individuals, including three affected, were exome sequenced. Variants were annotated and data were analysed while considering candidate chromosomal regions. Initial analysis of variants obtained by whole exome sequencing identified damaging variants in C15orf40 , EPB41L4A, TMEM232, KMT2C , and FBXW10 genes. Sanger sequencing of all family members confirmed segregation of splice acceptor site variant (c.1013-2 A > G) in the KMT2C gene with the phenotype. KMT2C is considered as a potential candidate gene based on segregation analysis, the absence of variant in the variation databases, the presence of variant in the shared identical by descent (IBD) region and in silico pathogenicity prediction. KMT2C is a histone methyltransferase and recently the role of another member of this family (KMT2D) has been implicated in tooth development. Moreover, protein structures of KMT2C and KMT2D are highly similar. In conclusion, we have identified that the KMT2C gene mutation causes familial non-syndromic PFE. These findings suggest the involvement of KMT2C in the physiological eruption of permanent teeth.

Background Newer generation ultrathin strut stents are associated with less incidence of target lesion failure (TLF) in patients undergoing percutaneous coronary intervention (PCI) in the short term. However, its long-term effect on different cardiovascular outcomes remains unknown. Objectives We aim to identify the effects of newer-generation ultrathin-strut stents vs. standard thickness second-generation drug-eluting stents (DES) on long-term outcomes of revascularization in coronary artery disease. Methods We searched PubMed, Web of Science, Cochrane Library databases, and Scopus for randomized controlled trials (RCTs) and registries that compare newer-generation ultrathin-strut (< 70 mm) with thicker strut (> 70 mm) DES to evaluate cardioprotective effects over a period of up to 5 years. Primary outcome was TLF, a composite of cardiac death, target vessel myocardial infarction (TVMI) or target lesion revascularization (TLR). Secondary outcomes included the components of TLF, stent thrombosis (ST), and all-cause death were pooled as the standardized mean difference between the two groups from baseline to endpoint. Results We included 19 RCTs and two prospective registries (103,101 patients) in this analysis. The overall effect on the primary outcome was in favor of second-generation ultrathin struts stents in terms of TLF at ≥ 1 year, ≥ 2 years, and ≥ 3 years ( P value = 0.01, 95% CI [0.75, 0.96]), P value = 0.003, 95% CI [0.77, 0.95]), P value = 0.007, 95% CI [0.76, 0.96]), respectively. However, there was no reported benefit in terms of TLF when we compared the two groups at ≥ 5 years ( P value = 0.21), 95% CI [0.85, 1.04]). Some of the reported components of the primary and secondary outcomes, such as TLR, target vessel revascularization (TVR), and TVMI, showed the same pattern as the TLF outcome. Conclusion Ultrathin-strut DES showed a beneficial effect over thicker strut stents for up to 3 years. However, at the 5-year follow-up, the ultrathin strut did not differ in terms of TLF, TLR, TVR, and TVMI compared with standard-thickness DES, with similar risks of patient-oriented composite endpoint (POCE), MI, ST, cardiac death, and all-cause mortality.

In response to the energy crisis, researchers are working on creating novel materials for the electrodes of energy storage devices, particularly supercapacitors. Furthermore, in order to promote an environmentally friendly environment, the contamination of industrial effluent with various colors is becoming a significant problem that needs to be addressed right now. Ce-Mo co-doped NiO nanomaterials have been created for the first time to address this problem. The capacitive and photocatalytic performance of NiO was greatly influenced by the morphology, which was significantly altered by the co-doping of Ce and Mo. The characterization techniques like XRD, SEM, TEM, EDX, BET and XPS were used to investigate the specific physical properties of the as-prepared nanomaterials. CV, GCD, and EIS experiments were used to evaluate the electrochemical characteristics. CV analysis has revealed that among the various Ce and Mo co-doped NiO samples, Ce 0.05 Mo 0.0 5NiO based on nanowires has offered the highest specific capacitance, i.e., 1108.68 F/g. The EIS studies have revealed that Ce 0.05 Mo 0.05 NiO nanowires are highly conductive in nature. Moreover, after 10,000 CV cycles, 85.7% capacitance retention was noted for Ce 0.05 Mo 0.05 NiO nanowires. The photocatalytic performance of as-prepared nanowires was assessed against the model dye methyl red (MR). During the optical study of as-prepared co-doped NiO nanomaterials, the Ce 0.05 Mo 0.05 NiO sample has shown a reduced optical band gap of 2.95 eV, which is very helpful for the photocatalytic conduct. The optimized Ce 0.05 Mo 0.05 NiO nanowires have exhibited 97% photodegradation activity against the methyl red (MR) and strong catalytic stability (88.7%). On the basis of such astonishing performance, it is suggested that the as-reported Ce and Mo co-doped NiO material based on nanowires is a potential candidate for the application in energy storage and water purification applications.

In this study, silica in the form of raw local natural sand was added to high-density-polyethylene (HDPE) in order to develop a composite material in the form of sheets that could have potential applications in thin film industries, such as packaging, or recycling industries, such as in 3D printing. The silica/HDPE composite sheets were developed using a melt extruder followed by using a hot press for compression molding. The impact of two different particle sizes (25 µm and 5 µm) of the silica particles on selected properties such as toughness, elastic modulus, ductility, and composite density were analyzed. A considerable increase in the toughness and elastic modulus was observed from 0 wt% to 20 wt% with a 25 µm filler size. However, a general decreasing trend was observed in the material’s toughness and elastic modulus with decreasing particle size. A similar trend was observed for the ductility and the tensile strength of the sheets prepared from both filler particle sizes. In terms of the composite density, as the filler was increased from 20 wt% to 50 wt%, an increase in the composite densities was noticed for both particle sizes. Additionally, the sheets developed with 25 µm particle size had a slightly higher density than the 5 µm particle size, which is expected as the size can account for the higher weight. Results from this work aim to analyze the use of local sand as a filler material that can contribute towards maximizing the potential of such composite materials developed in extrusion industries.