Molecular characterization of rotavirus indicates predominance of G9P[4] genotype among children with acute gastroenteritis: First report after vaccine introduction in Pakistan.

Globally, Group A rotavirus (RVA) is the leading cause of acute gastroenteritis in children under 5 years old, with Pakistan having the highest rates of RVA-related morbidity and mortality. The current study aims to determine the genetic diversity of rotavirus and evaluate the impact of Rotarix-vaccine introduction on disease epidemiology in Pakistan. A total of 4749 children, hospitalized with acute gastroenteritis between 2018 and 2020, were tested at four hospitals in Lahore and Karachi. Of the total, 19.3% (918/4749) cases were tested positive for RVA antigen, with the positivity rate varying annually (2018 = 22.7%, 2019 = 14.4%, 2020 = 20.9%). Among RVA-positive children, 66.3% were under 1 year of age. Genotyping of 662 enzyme-linked immuno sorbent assay-positive samples revealed the predominant genotype as G9P[4] (21.4%), followed by G1P[8] (18.9%), G3P[8] (11.4%), G12P[6] (8.7%), G2P[4] (5.7%), G2P[6] (4.8%), and 10.8% had mixed genotypes. Among vaccinated children, genotypes G9P[4] and G12P[6] were more frequently detected, whereas a decline in G2P[4] was observed. Phylogenetic analysis confirmed the continued circulation of indigenous genotypes detected earlier in the country except G9 and P[6] strains. Our findings highlight the predominance of G9P[4] genotype after the vaccine introduction thus emphasizing continual surveillance to monitor the disease burden, viral diversity, and their impact on control of rotavirus gastroenteritis in children.

Inhibition of mitochondrial calcium transporters alters adp-induced platelet responses.

INTRODUCTION: ADP-stimulated elevation of cytosolic Ca2+ is an important effector mechanism for platelet activation. The rapidly elevating cytosolic Ca2+ is also transported to mitochondrial matrix via Mitochondrial Ca2+ Uniporter (MCU) and extruded via Na+/Ca2+/Li+ Exchanger (NCLX). However, the exact contribution of MCU and NCLX in ADP-mediated platelet responses remains incompletely understood. METHODS AND RESULTS: The present study aimed to elucidate the role of mitochondrial Ca2+ transport in ADP-stimulated platelet responses by inhibition of MCU and NCLX with mitoxantrone (MTX) and CGP37157 (CGP), respectively. As these inhibitory strategies are reported to cause distinct effects on matrix Ca2+ concentration, we hypothesized to observe opposite impact of MTX and CGP on ADP-induced platelet responses. Platelet aggregation profiling was performed by microplate-based spectrophotometery while p-selectin externalization and integrin αIIbß3 activation were analyzed by fluorescent immunolabeling using flow cytometery. Our results confirmed the expression of both MCU and NCLX mRNAs with relatively low abundance of NCLX in human platelets. In line with our hypothesis, MTX caused a dose-dependent inhibition of ADP-induced platelet aggregation without displaying any cytotoxicity. Likewise, ADP-induced p-selectin externalization and integrin αIIbß3 activation was also significantly attenuated in MTX-treated platelets. Concordantly, inhibition of NCLX with CGP yielded an accelerated ADP-stimulated platelet aggregation which was associated with an elevation of p-selectin surface expression and αIIbß3 activation. CONCLUSION: Together, these findings uncover a vital and hitherto poorly characterized role of mitochondrial Ca2+ transporters in ADP-induced platelet activation.

TNF plays a crucial role in inflammation by signaling via T cell TNFR2.

TNF, produced largely by T and innate immune cells, is potently proinflammatory, as are cytokines such as IFN-γ and IL-17 produced by Th1 and Th17 cells, respectively. Here, we asked if TNF is upstream of Th skewing toward inflammatory phenotypes. Exposure of mouse CD4+ T cells to TNF and TGF-ß generated Th17 cells that express low levels of IL-17 (ROR-γt+IL-17lo) and high levels of inflammatory markers independently of IL-6 and STAT3. This was mediated by the nondeath TNF receptor TNFR2, which also contributed to the generation of inflammatory Th1 cells. Single-cell RNA sequencing of central nervous system-infiltrating CD4+ T cells in mouse experimental autoimmune encephalomyelitis (EAE) found an inflammatory gene expression profile similar to cerebrospinal fluid-infiltrating CD4+ T cells from patients with multiple sclerosis. Notably, TNFR2-deficient CD4+ T cells produced fewer inflammatory mediators and were less pathogenic in EAE and colitis. IL-1ß, a Th17-skewing cytokine, induced TNF and proinflammatory granulocyte-macrophage colony-stimulating factor (GM-CSF) in T cells, which was inhibited by disruption of TNFR2 signaling, demonstrating IL-1ß can function indirectly via the production of TNF. Thus, TNF is not just an effector but also an initiator of inflammatory Th differentiation.

Determinants of stunting among under-five children: Evidence from Cambodian Demographic and Health Survey 2021-2022.

BACKGROUND: Epidemiological and nutritional modifications are causing an increase in stunting in many low- and middle-income countries (LMIC), which will eventually result in juvenile diseases and mortality. Therefore, this study aimed to identify the influential factors contributing to stunting among under-five children in Cambodia. METHODS: A secondary dataset consisting of 3268 under-five children was extracted from the latest Cambodian Demographic and Health Survey (CDHS)-2021/2022 dataset. The Chi-square test and Boruta algorithm were used for covariate selection, and logistic regression approaches were used to determine the influence of demographic, socioeconomic and other factors on the presence of stunting. RESULTS: Findings revealed that about 21% of under-five children were stunted, and the prevalence of stunting was higher in rural areas than in urban areas. The prevalence of child stunting was lower in families with highly educated parents. A child whose father had a secondary education had 0.71 times lower (adjusted odds ratio [AOR]: 0.71, 95% CI: 0.520-0.969) chance of stunting than a child whose father had no education. Findings revealed that Ratnak Kiri, Mondul Kiri, Stung Treng, Pursat and Kampot had a greater prevalence of stunting than other places, ranging from 27.11% to 35.70%, whereas Banteay Meanchey, Phnom Penh and Kandal had the lowest rates, ranging from 12.80% to 16.00%. Results of the Boruta algorithm and logistic regression suggested that under-five stunting is significantly influenced by factors such as the child's age, size at birth, mother's age at first birth, mother's body mass index (BMI), father's educational status, cooking fuel, and wealth index. CONCLUSIONS: It is necessary to take initiatives for reducing the prevalence of stunted children prioritising the identified factors that ultimately help to reduce the burden of child health. The authors believed that the findings of this study will be helpful for policymakers in designing the appropriate policies and actions to achieve the Sustainable Development Goals (SDGs) by reducing stunting among under-five children in Cambodia.

Development of Biocompatible Electrospun PHBV-PLLA Polymeric Bilayer Composite Membranes for Skin Tissue Engineering Applications.

Bilayer electrospun fibers aimed to be used for skin tissue engineering applications were fabricated for enhanced cell attachment and proliferation. Different ratios of PHBV-PLLA (70:30, 80:20, and 90:10 w/w) blends were electrospun on previously formed electrospun PHBV membranes to produce their bilayers. The fabricated electrospun membranes were characterized with FTIR, which conformed to the characteristic peaks assigned for both PHBV and PLLA. The surface morphology was evaluated using SEM analysis that showed random fibers with porous morphology. The fiber diameter and pore size were measured in the range of 0.7 ± 0.1 µm and 1.9 ± 0.2 µm, respectively. The tensile properties of the bilayers were determined using an electrodynamic testing system. Bilayers had higher elongation at break (44.45%) compared to the monolayers (28.41%) and improved ultimate tensile strength (7.940 MPa) compared to the PHBV monolayer (2.450 MPa). In vitro cytotoxicity of each of the scaffolds was determined via culturing MC3T3 (pre-osteoblastic cell line) on the membranes. Proliferation was evaluated using the Alamar Blue assay on days 3, 7, and 14, respectively. SEM images of cells cultured on membranes were taken in addition to bright field imaging to visually show cell attachment. Fluorescent nuclear staining performed with DAPI was imaged with an inverted fluorescent microscope. The fabricated bilayer shows high mechanical strength as well as biocompatibility with good cell proliferation and cell attachment, showing potential for skin substitute applications.

Performance gain and electro-mechanical design optimization of microneedles for wearable sensor systems.

Minimally invasive microneedle (MN) is an emerging technology platform for wearable and implantable diagnostics and therapeutics systems. These short MNs offer pain-free insertion and simple operation. Among the MN technologies proposed to enhance interstitial fluid (ISF) extraction, porous and swellable (P-S) hydrogels absorb analyte molecules across the entire lateral surface. Currently, the design, development, and optimization of the MNs rely on empirical, iterative approaches. Based on theory of fluid flow and analyte diffusion through geometrically complex biomimetic systems, here we derive a generalized physics-guided model for P-S MN sensors. The framework (a) quantifies MN extracting efficiency [Formula: see text] in terms of its geometric and physical properties, and (b) suggests strategies to optimize sensor response while satisfying the mechanical constraints related to various skin-types (e.g., mouse, pig, humans, etc.). Our results show that, despite the differences in geometry and composition, P-S MNs obey a universal scaling response, [Formula: see text] with [Formula: see text] being MN length, diffusivity, and radius, respectively, and [Formula: see text], [Formula: see text] and [Formula: see text] are the ratio between approximate vs. exact analytical solutions, the effective biofluid transfer coefficient between dermis and skin, and the exponent for the power-law approximation, respectively. These parameters quantify the biomolecule transfer through the dermis-to-MN interface at different scaling limits. P-S MNs outperform hollow MNs by a 2-6x enhancement factor; however, the buckling-limit of insertion defines the maximized functionality of the sensor. Our model, validated against experimental results and numerical simulations, offers a predictive design framework to significantly reduce the optimization time for P-S MN-based sensor platforms.

Progress Toward Poliomyelitis Eradication - Pakistan, January 2022-June 2023.

Since the establishment of the Global Polio Eradication Initiative in 1988, Pakistan remains one of only two countries (along with Afghanistan) with continued endemic transmission of wild poliovirus (WPV). This report describes Pakistan's progress toward polio eradication during January 2022-June 2023. During 2022, Pakistan reported 20 WPV type 1 (WPV1) cases, all of which occurred within a small geographic area encompassing three districts in south Khyber Pakhtunkhwa. As of June 23, only a single WPV1 case from Bannu district in Khyber Pakhtunkhwa province has been reported in 2023, compared with 13 cases during the same period in 2022. In addition, 11 WPV1 isolates have been reported from various environmental surveillance (ES) sewage sampling sites to date in 2023, including in Karachi, the capital of the southern province of Sindh. Substantial gaps remain in the quality of supplementary immunization activities (SIAs), especially in poliovirus reservoir areas. Despite the attenuation and apparently limited geographic scope of poliovirus circulation in Pakistan, the isolation of WPV1 from an ES site in Karachi is cause for concern about the actual geographic limits of transmission. Interrupting WPV1 transmission will require meticulous tracking and sustained innovative efforts to vaccinate children who are regularly missed during SIAs and rapidly responding to any new WPV1 isolations.

Comparison of simplicity, convenience, safety, and cost-effectiveness between use of insulin pen devices and disposable plastic syringes by patients with type 2 diabetes mellitus: a cross-sectional study from Bangladesh.

INTRODUCTION: Insulin pen devices and disposable plastic insulin syringes are two common tools for insulin administration. This study aims to compare the simplicity, convenience, safety, and cost-effectiveness of insulin pens versus syringe devices in patients with type 2 diabetes mellitus (T2DM). METHODS: A cross-sectional study was conducted at 14 diabetes clinics throughout Bangladesh from November 2021 to April 2022 among adults with T2DM injecting insulin by pen devices or disposable insulin syringes at least once a day for at least one year by purposive sampling. The simplicity, convenience, and safety of insulin devices were assessed using a structured questionnaire, and the study subjects were scored based on their answers; higher scores indicated a poorer response. Total scores for simplicity, convenience, and safety were obtained by adding the scores for relevant components. Their average monthly medical expense and cost of insulin therapy were recorded. The median values of the total scores and monthly expenses were compared between pen devices and disposable syringe users. RESULTS: 737 subjects were evaluated; 406 were pen users, and 331 were vial syringe users. The pen users had lower median scores for simplicity [6.0 (5.0-8.0) vs. 7.0 (5.0-9.0), p = 0.002], convenience [4.0 (3.0-6.0) vs. 5.0 (4.0-6.0), p < 0.001], and safety [7.0 (6.0-8.0) vs. 7.0 (6.0-9.0), p = 0.008] than vial syringe users. Pen devices were more expensive than vial syringes in terms of average medical expense per month [BDT 5000 (3500-7000) vs. 3000 (2000-5000), p < 0.001], the total cost of insulin therapy per month [BDT 2000 (1500-3000) vs. 1200 (800-1700), p < 0.001] and cost per unit of insulin used [BDT 2.08 (1.39-2.78) vs. 0.96 (0.64-1.39), p < 0.001]. Non-significant differences in favor of pens were observed in HbA1c levels [8.7 (7.8-10) vs. 8.9 (7.9-10)%, p = 0.607] and proportions of subjects having HbA1c < 7% (6.9 vs. 6.3%, p = 0.991). CONCLUSION: Insulin pens are simpler, more convenient, and safe but more expensive than vial syringes. Glycemic control is comparable between pen and syringe users. Long-term follow-up studies are needed to determine the clinical and economic impacts of such benefits of insulin pens.

Status of lipid control in Bangladeshi subjects with type 2 diabetes mellitus on lipid-lowering drugs: a multicenter, facility-based, cross-sectional study.

BACKGROUND: Achievement of lipid targets is crucial in patients with type 2 diabetes mellitus (T2DM) to mitigate the risk of cardiovascular diseases (CVD). Data on lipid-control status among patients with T2DM in Bangladesh are scarce. This study was conducted to determine the lipid-control status among patients with T2DM who were on lipid-lowering drugs in the country. METHODS: This cross-sectional study was conducted in the diabetes outpatient departments of several tertiary hospitals in Bangladesh from January 2022 to December 2022. Adults of both sexes diagnosed with T2DM for at least one year and were on the lipid-lowering drug(s) for a minimum of 3 months were included in the study by consecutive sampling. Patients' data were collected by face-to-face interviews, and blood samples were collected for fasting lipid profile. The lipid target was set at < 200 mg/dL for total cholesterol (TC), < 150 mg/dL for triglyceride (TG), < 100 mg/dL for low-density lipoprotein cholesterol (LDL-C), > 40 mg/dL for high-density lipoprotein cholesterol (HDL-C), and < 160 mg/dL for non-HDL cholesterol (non-HDL-C). RESULT: Three thousand sixty patients (age 44.7 ± 13.3 years, female 57%) with T2DM were evaluated. Overall, almost 81% of the study subjects achieved the LDL-C target. Besides, TC, TG, HDL-C, and non-HDL-C targets were achieved by 40.8, 21.6, 66.3, and 44.1% of patients, respectively. However, all the lipid parameters were under control in only 8.8% of patients. Almost 77.6% of the patients with ischemic heart disease, 81.5% of patients with stroke, and 65% of patients with CKD had LDL levels < 70 mg/dL. Only 10.03% achieved the HbA1c target of < 7%. 7.4% of patients achieved both HbA1c < 7% and LDL < 100 mg/dL and 5% achieved both HbA1c < 7% and LDL < 70 mg/dL. Advanced age (aOR 0.97, 95% CI 0.96, 0.98, p < 0.001), longstanding T2DM (aOR 0.53, 95% CI 0.39, 0.72, p < 0.001), and non-statin therapy (aOR 0.25, 95% CI 0.16, 0.37, p < 0.001) were negatively associated with lipid control (LDL < 100 mg/dL) while using oral hypoglycemic drugs or insulin (aOR 2.01, 95% CI 1.45, 2.77, p < 0.001) and having cardiovascular comorbidity (aOR 3.92, 95% CI 3.00, 5.12, p < 0.001) were positively associated with lipid control. CONCLUSION: Though most patients with T2DM achieved their target LDL level, the prevalence of both glycemic and overall lipid control was low in our study despite lipid-lowering therapy.

Design anticancer potential of Zn(II)isoleucinedithiocarbamate complex on MCF-7 cell lines: synthesis, characterization, molecular docking, molecular dynamic, ADMET, and in-vitro studies.

Cisplatin is a cancer medication widely used today, but it still poses some problems due to its toxic properties in the body. To overcome this issue, a new complex has been developed as a potential anticancer drug prospect by minimizing its toxic consequences. A novel Zn(II)IleDTC complex containing isoleucine dithiocarbamate ligands has been produced and analyzed using a range of analytical and spectroscopic methods. The Zn(II) IleDTC complex were characterized using various methods, including UV-Vis spectroscopy, FT-IR, determination of melting point, conductivity, and HOMO-LUMO analysis. Furthermore, computational NMR spectrum analysis was conducted in this study. Molecular docking studies was conducted to evaluate the potential of Zn(II) isoleucine dithiocarbamate as an HIF1 inhibitor. The results showed that the Zn complex exhibited a good docking score of -6.6 and formed hydrogen bonds with ARG 17, VAL264, and GLU15, alkyl bonds with TRP27 and LEU32, and Pi-Alkyl bonds with PRO41 and ARG44. This suggests that the Zn(II) isoleucine dithiocarbamate complex could be a promising candidate for cancer treatment with potential HIF1 inhibition properties. To assess the dynamic stability and efficacy of protein-ligand interactions over time, molecular dynamics simulations was conducted for both individual proteins and protein complexes. The cytotoxicity evaluation of Zn(II) isoleucine dithiocarbamate against MCF-7 cells obtained an IC50 value of 362.70 µg/mL indicating moderate cytotoxicity and morphological changes of cancer cells causing cancer cells to undergo apoptosis. The Zn(II) isoleucine dithiocarbamate complex may have promising potential as an anticancer compound due to its significant inhibitory effect on the breast cancer cell line (MCF7). According to the ADMET study, the complex exhibits drug-like characteristics with low toxicity, further supporting its potential as a viable drug candidate.

Performance of machine learning algorithms for dementia assessment: impacts of language tasks, recording media, and modalities.

OBJECTIVES: Automatic speech and language assessment methods (SLAMs) can help clinicians assess speech and language impairments associated with dementia in older adults. The basis of any automatic SLAMs is a machine learning (ML) classifier that is trained on participants' speech and language. However, language tasks, recording media, and modalities impact the performance of ML classifiers. Thus, this research has focused on evaluating the effects of the above-mentioned factors on the performance of ML classifiers that can be used for dementia assessment. METHODOLOGY: Our methodology includes the following steps: (1) Collecting speech and language datasets from patients and healthy controls; (2) Using feature engineering methods which include feature extraction methods to extract linguistic and acoustic features and feature selection methods to select most informative features; (3) Training different ML classifiers; and (4) Evaluating the performance of ML classifiers to investigate the impacts of language tasks, recording media, and modalities on dementia assessment. RESULTS: Our results show that (1) the ML classifiers trained with the picture description language task perform better than the classifiers trained with the story recall language task; (2) the data obtained from phone-based recordings improves the performance of ML classifiers compared to data obtained from web-based recordings; and (3) the ML classifiers trained with acoustic features perform better than the classifiers trained with linguistic features. CONCLUSION: This research demonstrates that we can improve the performance of automatic SLAMs as dementia assessment methods if we: (1) Use the picture description task to obtain participants' speech; (2) Collect participants' voices via phone-based recordings; and (3) Train ML classifiers using only acoustic features. Our proposed methodology will help future researchers to investigate the impacts of different factors on the performance of ML classifiers for assessing dementia.

Ceratocystis fimbriata Causing Postharvest Fruit Rot of Pear in Punjab, Pakistan.

Pear (Pyrus communis) is an important deciduous fruit cultivated on a worldwide scale including Pakistan. During August 2021, a postharvest fruit rot disease was observed on several pears at various farmers market in Okara- a district of Punjab Province, Pakistan. The incidence of the disease varied from 7 to 20% with 35% disease severity. Necrotic spots (10 to 20 mm diameter) were first observed on the infected pear fruit. The spots enlarged gradually and developed into a brown, water-soaked and rotted lesion. Eventually, the whole fruit became soft, rotted and covered with a gray-brown mycelium. The isolates were obtained from the symptomatic tissues (n = 18) incubated on carrot discs that had been surface sterilized in 100-ppm streptomycin solution. After consistent sporulation of a fungus on the carrot discs, the ascospore masses formed at the tip of perithecia were transferred to malt extract agar (MEA). Primary conidia were cylindrical and hyaline (7 to 11 × 4 to 7 µm) and secondary conidia were hyaline and barrel-shaped (7 to 12 × 5 to 8 µm). Endoconidiophores with primary conidia were (12 to 27 × 2.6 to 5.5 µm). Perithecia produced on carrot discs were dark brown to black, and the base was 157 to 278 µm in diameter. Ascomatal necks were 512 to 656 µm long, dark brown to black, lighter in color at apices, tapering from base (23 to 45 µm diameter) to apex (13 to 24 µm diameter). Ostiolar hyphae were 41 to 79 µm long. Ascospores were hyaline, hat shaped, 3 to 4 µm long, and accumulated in a sticky matrix at the tips of perithecial necks. Mycelium was initially hyaline but became dark greenish brown after 7 days. Dark brown, thick-walled aleuroconidia (13 to 19.5 × 9 to 14 µm) appeared on culture plates after 2 months. Based on morphological characteristics, the fungus was identified as Ceratocystis fimbriata (Engelbrecht, 2005; Suwandi et al. 2021). To further confirm species identification, genomic DNA of two representative isolates (UO-05 and UO-06) was obtained using an extraction kit. The internal transcribed spacer (ITS) region was amplified using ITS1/4 (White et al. 1990). A BLAST search with GenBank accession nos. OR185451 and OR185456 indicated 99 to 100% identity with several C. fimbriata including type species (MH856050.1; KC493160.1; MT560374.1). Pathogenicity tests were conducted by inoculating nine disease-free pear (cv. Concord) fruit after disinfesting in 75% ethanol. A prepared spore suspension (1.0 × 106 spores/ml) was dropped on the wounds (a depth of 1 mm diameter) on the pear surface, which were made by a sterilized needle. 10 µl of a prepared spore suspension was dropped onto nine pears. Sterile water (10 µl) was dropped on the wounded sites of nine pear fruits as negative controls and all fruits were incubated in a growth chamber at 30/26°C (day/night, 90% relative humidity). Symptoms similar to those on the naturally infected fruits began after 4 to 5 days of inoculation, while controls remained healthy. The fungal isolates recovered from inoculated pears were morphologically identical to the C. fimbriata isolates originally recovered from symptomatic fruits fulfilling Koch's postulates. The pathogen has been reported to cause postharvest fruit rot of passion fruit and cucumber (Firmino et al. 2016; Li et al. 2019). To our knowledge, this is the first report of C. fimbriata causing fruit rot of pear in Punjab Province. The detection of this disease will help pear growers to take actions to monitor and prevent disease outbreak as well as develop an effective management practice when it occurs.

Heuristic Radio Access Network Subslicing with User Clustering and Bandwidth Subpartitioning.

In 5G and beyond, the network slicing is a crucial feature that ensures the fulfillment of service requirements. Nevertheless, the impact of the number of slices and slice size on the radio access network (RAN) slice performance has not yet been studied. This research is needed to understand the effects of creating subslices on slice resources to serve slice users and how the performance of RAN slices is affected by the number and size of these subslices. A slice is divided into numbers of subslices of different sizes, and the slice performance is evaluated based on the slice bandwidth utilization and slice goodput. A proposed subslicing algorithm is compared with k-means UE clustering and equal UE grouping. The MATLAB simulation results show that subslicing can improve slice performance. If the slice contains all UEs with a good block error ratio (BLER), then a slice performance improvement of up to 37% can be achieved, and it comes more from the decrease in bandwidth utilization than the increase in goodput. If a slice contains UEs with a poor BLER, then the slice performance can be improved by up to 84%, and it comes only from the goodput increase. The most important criterion in subslicing is the minimum subslice size in terms of resource blocks (RB), which is 73 for a slice that contains all good-BLER UEs. If a slice contains UEs with poor BLER, then the subslice can be smaller.

Drone Routing for Drone-Based Delivery Systems: A Review of Trajectory Planning, Charging, and Security.

Recently, owing to the high mobility and low cost of drones, drone-based delivery systems have shown considerable potential for ensuring flexible and reliable parcel delivery. Several crucial design issues must be considered to design such systems, including route planning, payload weight consideration, distance measurement, and customer location. In this paper, we present a survey of emerging drone routing algorithms for drone-based delivery systems, emphasizing three major drone routing aspects: trajectory planning, charging, and security. We focus on practical design considerations to ensure efficient, flexible, and reliable parcel delivery. We first discuss the potential issues arising when designing such systems. Next, we present a novel taxonomy based on the above-mentioned three aspects. We extensively review each algorithm for drone routing in terms of key features and operational characteristics. Furthermore, we compare the algorithms in terms of their main idea, advantages, limitations, and performance aspects. Finally, we present open research challenges to motivate further research in this field. In particular, we focus on the major aspects that researchers and engineers need to consider in order to design effective and reliable drone routing algorithms for drone-based delivery systems.

On Coverage of Critical Nodes in UAV-Assisted Emergency Networks.

Unmanned aerial vehicle (UAV)-assisted networks ensure agile and flexible solutions based on the inherent attributes of mobility and altitude adaptation. These features render them suitable for emergency search and rescue operations. Emergency networks (ENs) differ from conventional networks. They often encounter nodes with vital information, i.e., critical nodes (CNs). The efficacy of search and rescue operations highly depends on the eminent coverage of critical nodes to retrieve crucial data. In a UAV-assisted EN, the information delivery from these critical nodes can be ensured through quality-of-service (QoS) guarantees, such as capacity and age of information (AoI). In this work, optimized UAV placement for critical nodes in emergency networks is studied. Two different optimization problems, namely capacity maximization and age of information minimization, are formulated based on the nature of node criticality. Capacity maximization provides general QoS enhancement for critical nodes, whereas AoI is focused on nodes carrying critical information. Simulations carried out in this paper aim to find the optimal placement for each problem based on a two-step approach. At first, the disaster region is partitioned based on CNs' aggregation. Reinforcement learning (RL) is then applied to observe optimal placement. Finally, network coverage over optimal UAV(s) placement is studied for two scenarios, i.e., network-centric and user-centric. In addition to providing coverage to critical nodes, the proposed scheme also ensures maximum coverage for all on-scene available devices (OSAs).

Achieving Reliability in Cloud Computing by a Novel Hybrid Approach.

Cloud computing (CC) benefits and opportunities are among the fastest growing technologies in the computer industry. Cloud computing's challenges include resource allocation, security, quality of service, availability, privacy, data management, performance compatibility, and fault tolerance. Fault tolerance (FT) refers to a system's ability to continue performing its intended task in the presence of defects. Fault-tolerance challenges include heterogeneity and a lack of standards, the need for automation, cloud downtime reliability, consideration for recovery point objects, recovery time objects, and cloud workload. The proposed research includes machine learning (ML) algorithms such as naïve Bayes (NB), library support vector machine (LibSVM), multinomial logistic regression (MLR), sequential minimal optimization (SMO), K-nearest neighbor (KNN), and random forest (RF) as well as a fault-tolerance method known as delta-checkpointing to achieve higher accuracy, lesser fault prediction error, and reliability. Furthermore, the secondary data were collected from the homonymous, experimental high-performance computing (HPC) system at the Swiss Federal Institute of Technology (ETH), Zurich, and the primary data were generated using virtual machines (VMs) to select the best machine learning classifier. In this article, the secondary and primary data were divided into two split ratios of 80/20 and 70/30, respectively, and cross-validation (5-fold) was used to identify more accuracy and less prediction of faults in terms of true, false, repair, and failure of virtual machines. Secondary data results show that naïve Bayes performed exceptionally well on CPU-Mem mono and multi blocks, and sequential minimal optimization performed very well on HDD mono and multi blocks in terms of accuracy and fault prediction. In the case of greater accuracy and less fault prediction, primary data results revealed that random forest performed very well in terms of accuracy and fault prediction but not with good time complexity. Sequential minimal optimization has good time complexity with minor differences in random forest accuracy and fault prediction. We decided to modify sequential minimal optimization. Finally, the modified sequential minimal optimization (MSMO) algorithm with the fault-tolerance delta-checkpointing (D-CP) method is proposed to improve accuracy, fault prediction error, and reliability in cloud computing.

A Double-Layer Blockchain Based Trust Management Model for Secure Internet of Vehicles.

The Internet of Vehicles (IoV) enables vehicles to share data that help vehicles perceive the surrounding environment. However, vehicles can spread false information to other IoV nodes; this incorrect information misleads vehicles and causes confusion in traffic, therefore, a vehicular trust model is needed to check the trustworthiness of the message. To eliminate the spread of false information and detect malicious nodes, we propose a double-layer blockchain trust management (DLBTM) mechanism to objectively and accurately evaluate the trustworthiness of vehicle messages. The double-layer blockchain consists of the vehicle blockchain and the RSU blockchain. We also quantify the evaluation behavior of vehicles to show the trust value of the vehicle's historical behavior. Our DLBTM uses logistic regression to accurately compute the trust value of vehicles, and then predict the probability of vehicles providing satisfactory service to other nodes in the next stage. The simulation results show that our DLBTM can effectively identify malicious nodes, and over time, the system can recognize at least 90% of malicious nodes.

FedBranched: Leveraging Federated Learning for Anomaly-Aware Load Forecasting in Energy Networks.

Increased demand for fast edge computation and privacy concerns have shifted researchers' focus towards a type of distributed learning known as federated learning (FL). Recently, much research has been carried out on FL; however, a major challenge is the need to tackle the high diversity in different clients. Our research shows that using highly diverse data sets in FL can lead to low accuracy of some local models, which can be categorised as anomalous behaviour. In this paper, we present FedBranched, a clustering-based framework that uses probabilistic methods to create branches of clients and assigns their respective global models. Branching is performed using hidden Markov model clustering (HMM), and a round of branching depends on the diversity of the data. Clustering is performed on Euclidean distances of mean absolute percentage errors (MAPE) obtained from each client at the end of pre-defined communication rounds. The proposed framework was implemented on substation-level energy data with nine clients for short-term load forecasting using an artificial neural network (ANN). FedBranched took two clustering rounds and resulted in two different branches having individual global models. The results show a substantial increase in the average MAPE of all clients; the biggest improvement of 11.36% was observed in one client.

Cost-Efficient Network Planning for the Cross-Border Baltic Corridor-A Study.

Performing 5G coverage planning across borders introduces real-life challenges related to legalities, intercountry agreements, and binding documents. This work provides RF network modelling exercise results to provide uninterrupted 5G coverage to the Via Baltica and Rail Baltica transport corridors crossing Estonia and Latvia and on the border with Lithuania, as well as the Tallinn-Tartu-Valga and Valka-Valga roads (Latvia-Estonia), capable of cross-border 5G services. The study starts by identifying and interviewing stakeholders from different sectors of operation in the Baltic states and Europe and then provides an overview of some of the main legal acts and documents regulating the electronic communications sector in the Baltic states and Europe. Furthermore, 5G network requirements are proposed. In addition, the necessary and existing passive and active infrastructure is described, including spectrum management-related analysis, where the RF bands 700 MHz and 3500 MHz are analysed. Finally, coverage planning is performed. The network modelling results aim to foresee the number of new sites that need to be built on the said transport corridors, also examining the existing infrastructure for such purposes. Additionally, an estimated timeline for building the new sites is provided.

Deep Eutectic Solvent Coated Cerium Oxide Nanoparticles Based Polysulfone Membrane to Mitigate Environmental Toxicology.

In this study, ceria nanoparticles (NPs) and deep eutectic solvent (DES) were synthesized, and the ceria-NP's surfaces were modified by DES to form DES-ceria NP filler to develop mixed matrix membranes (MMMs). For the sake of interface engineering, MMMs of 2%, 4%, 6% and 8% filler loadings were fabricated using solution casting technique. The characterizations of SEM, FTIR and TGA of synthesized membranes were performed. SEM represented the surface and cross-sectional morphology of membranes, which indicated that the filler is uniformly dispersed in the polysulfone. FTIR was used to analyze the interaction between the filler and support, which showed there was no reaction between the polymer and DES-ceria NPs as all the peaks were consistent, and TGA provided the variation in the membrane materials with respect to temperature, which categorized all of the membranes as very stable and showed that the trend of stability increases with respect to DES-ceria NPs filler loading. For the evaluation of efficiency of the MMMs, the gas permeation was tested. The permeability of CO2 was improved in comparison with the pristine Polysulfone (PSF) membrane and enhanced selectivities of 35.43 (αCO2/CH4) and 39.3 (αCO2/N2) were found. Hence, the DES-ceria NP-based MMMs proved useful in mitigating CO2 from a gaseous mixture.