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Abstract Transformer-based models have greatly improved Land Use and Land Cover (LULC) applications. Their revolutionary ability to analyze and extract key information has greatly advanced the field. However, the high computational cost of these models presents a considerable obstacle to their practical implementation. Therefore, this study aims to strike a balance between computational cost and accuracy when employing transformer-based models for LULC analysis. We exploit transfer learning and fine-tuning strategies to optimize the resource utilization of transformer-based models. Furthermore, transparency is the core principle of our methodology to promote fairness and trust in applying LULC models across various domains, including forestry, environmental studies, and urban or rural planning. To ensure transparency, we have employed Captum, which enables us to uncover and mitigate potential biases and interpret AI-driven decisions. Our results indicate that transfer learning can potentially improve transformer-based models in satellite image classification, and strategic fine-tuning can maintain efficiency with minimal accuracy trade-offs. This research highlights the potential of Explainable AI (XAI) in Transformer-based models for achieving more efficient and transparent LULC analysis, thereby encouraging continued innovation in the field.

The stigmas of saffron (Crocus sativus L.) are known as “red gold” for being the most expensive spice of the world. This medicinal crop grows well in the regions with cold winter Mediterranean climate. However, salinity can be one of the limiting factors for its cultivation in these regions. Composted manures and their co-compost with wood-derived biochar as fertilizers in saline soil can reduce the salinity stress on saffron. In this study, the composted manures from dairy farms (FYM), sheep and goats (SG) and poultry (PM) and their co-compost with wood-derived biochar (FYM-B, SG-B and PM-B) were amended in non-saline (EC1:2 0.25 dS m−1, SOM; 9.9 g kg−1) and soil with natural slight salinity (EC1:2; 1.95 dS m−1, SOM; 30.9 g kg−1) soil for two consecutive years with the total amendment rate of 65 t ha−1 for each fertilizer. The saline soil was transported from an agricultural farm (30 km away from research field); whereas, the non-saline soil was not transported and was not cultivated before. The amendment of fertilizers and sowing of corms were conducted at the same time in the mid of August. The stigma yield in saline control soil was significantly lower than non-saline control in both cropping years. In non-saline soil, all fertilizers reduced stigma yield of first-year crop by 14–60 % (P

PURPOSEThis study aimed to investigate the impact of single-nucleotide polymorphisms (SNPs) in the CD44 gene, specifically in the 3'UTR region (rs13347) and intronic region (rs187115), on the cell surface expression of CD44 protein and the risk of development of head and neck squamous cell carcinoma (HNSCC).MATERIALS AND METHODSThe study involved analysis of 85 samples and 85 healthy controls. Immunohistochemistry (IHC) and flow cytometry were used to assess cell surface protein expression using CD44 antibody. DNA from formalin-fixed paraffin-embedded tissue sections was isolated and amplified using targeted primers. Sanger sequencing of the resultant amplified products was performed to determine the genotypes of the CD44 rs13347 and rs187115 SNPs. GTEx and RegulomeDB were queried to evaluate the genotypic effects of these variants on target gene expression and regulation.RESULTSA comparison between patients with HNSCC and healthy controls revealed a significant association between CD44 rs13347 and an increased risk of HNSCC in all the analyzed models, especially the TT genotype showed a significantly higher risk with an odds ratio of 8.69 (95% CI, 2.35 to 32.09; P = .0003). However, no significant association was found between CD44 rs187115 and HNSCC in any of the models analyzed (all P > .05). Other notable findings included significant associations between CD44 rs13347 genotype and age (P = .031), number of CD44-positive tumor cells (P = .049), CD44 staining intensity (SI; P = .039), and CD44 immunoreactivity score (IRS) status (P = .019).CONCLUSIONThe T allele and homozygous TT genotype of CD44 rs13347 SNP were associated with increased susceptibility to HNSCC and decreased proportion of CD44-positive tumor cells, low SI, and reduced IRS.

Abstract Double transition metal (DTM) MXenes are a recently discovered class of two‐dimensional composite nanomaterials with excellent potential in energy storage applications. Since their emergence in 2015, DTM MXenes have expanded their composition boundary beyond traditional single‐metal carbide and nitride MXenes. DTM MXenes offer tunable structures and properties through variations in the constituent transition metals and positioning within the layered lattice. These MXenes can exist in two primary forms: ordered DTMs and solid solutions. The compositional versatility of DTM MXenes offers opportunities to enhance their performance in electrochemical energy storage applications. However, the quality, stability, and surface chemistry of DTM MXenes are influenced by several factors, including the etching process, etchant type, and synthesis route. Currently, limited literature is available on experimentally synthesized DTM MXenes, with most studies focusing on carbide‐based MXenes. Most of the articles have dedicated their efforts only to generalized synthesis strategies. Although extensive theoretical studies have explored the suitability of etchants, synthesis parameters, and methods for producing high‐quality MXene with selective terminal functional groups, their stability issues have not been thoroughly examined. This review addresses various types of DTM MXenes, their synthesis techniques, and the impact of these methods on their physicochemical properties and electrochemical performance. Additionally, it provides a critical analysis of the causes of instability in MXenes, particularly DTMs, from synthesis to application. The challenges associated with these materials are discussed, along with opportunities and prospects for enhancing synthesis, structural tuning, surface modification, and applications in electrochemical energy storage.

As the global community deals with the urgent need for sustainable development, the formulation and implementation of effective low carbon innovation policies have emerged as a critical challenge. However, the extant literature is unclear in examining low carbon innovation policy. Underpinned by institutional theory, the current study addresses the role of institutional pressure in the development of low carbon innovation policies. Additionally, the study examines the role of environmental management systems as a mediation and environmental interpretations and governance heterogeneity as moderators. Methodologically, the data were collected from the manufacturing sector of Pakistan. The findings suggest that institutional pressure greatly influences low carbon innovation policies. Furthermore, the findings from environmental management systems strongly suggest that they significantly encourage institutional pressure on low carbon innovation. Additionally, the roles of environmental interpretations and governance heterogeneity have a significant effect on the relationship. We use a non-profitability sampling technique. In October 2023, a total of 432 questionnaires were disseminated to manufacturing firms, yielding 299 valid responses for Time-1 and Time-2, respectively.

Non-linear Eq.s occur as a sub-problem in a wide variety of engineering and scientific domains. To deal with the complexity of Non-linear Eq.s, it is often required to use numerical procedures, which are the most suitable method to employ in certain circumstances. Many classic iterative approaches have been regularly employed for various situations; nevertheless, the convergence rate of those methods is low. In many cases, an iterative approach with a faster convergence rate is needed. This is something that classical methods like the Newton-Raphson Method (NRM) cannot provide. As part of this investigation, a modification to the NRM has been suggested to speed up convergence rates and reduce computational time. Ultimately, this research aims to improve the NRM, resulting in a Modified Iterative Method (MIM). The proposed method was thoroughly examined. According to the research, the convergence rate is higher than that of NRM. The proposed method delivers more accurate results while reducing computational time and requiring fewer iterations than earlier methods. The numerical findings confirm that the promised performance is correct. The results include the number of iterations, residuals, and computing time. This innovative technique, which is appropriate to any Non-linear equation, produces more accurate approximations with less iteration than conventional methods, and it is appropriate to any Non-linear equation.

The COVID-19 pandemic has resulted in the threat of death. Some older people feel they are not ready to face the end of their lives, so psychosocial problems arise, such as loneliness, anxiety, and depression. This research study aims to explore some psychosocial aspects, namely spirituality, social support, depression, anxiety, and loneliness in the elderly during the pandemic. The research design was cross-sectional. The total sample was 142 people selected using the purposive sampling method. Data collection used various scales to look at spirituality, depression, anxiety, and loneliness. The results showed that median spirituality and social support scores were high. The median depression and loneliness scores were mild. The average anxiety score for the elderly was normal. Based on the Pearson and Spearman correlation tests, relationships were shown between spirituality and anxiety scores, social support and anxiety scores, anxiety and depression scores, and loneliness and depression scores. The elderly need spirituality and social support when facing the end of life, and during the COVID-19 pandemic, to prevent the emergence of psychosocial problems. Social support and high spirituality must be maintained, even though the pandemic has subsided, in case such a health crisis occurs again. Abstrak Kecemasan, Depresi, Kesepian, Spiritualitas, dan Dukungan Sosial pada Lansia Saat Pandemi COVID-19. Pandemi COVID-19 mengancam banyak jiwa. Sebagian dari lansia merasa belum siap menghadapi akhir kehidupan seperti kematian sehingga muncul masalah psikososial seperti kesepian, cemas, dan depresi. Penelitian ini bertujuan untuk mengetahui aspek psikososial lansia yaitu spiritualitas, dukungan sosial, depresi, kecemasan, dan kesepian selama pandemi COVID-19. Desain penelitian yang digunakan adalah cross-sectional. Jumlah sampel sebanyak 142 orang yang dipilih dengan metode purposive sampling. Pengumpulan data menggunakan berbagai kuisioner untuk melihat spiritualitas, depresi, kecemasan, dan kesepian. Hasil penelitian menunjukkan bahwa median skor spiritualitas dan dukungan sosial termasuk tinggi. Nilai median depresi dan kesepian tergolong ringan. Rata-rata skor kecemasan lansia adalah normal. Berdasarkan uji korelasi Pearson dan Spearman, ditunjukkan hubungan antara skor spiritualitas dan kecemasan, skor dukungan sosial dan kecemasan, skor kecemasan dan depresi, serta skor kesepian dan depresi. Lansia membutuhkan spiritualitas dan dukungan sosial dalam menghadapi akhir kehidupan maupun saat pandemi COVID-19 untuk mencegah munculnya masalah psikososial. Dukungan sosial dan spiritualitas yang tinggi harus tetap dijaga, walaupun pandemi COVID-19 sudah mereda, agar mampu bertahan jika krisis kesehatan muncul kembali. Kata Kunci: depresi, dukungan sosial, kecemasan, kesepian, spiritualitas

Synergistic integration based on some transition-metal (TM) derived compounds is a unique and appealing technique, especially toward oxygen evolution reaction (OER) under alkaline circumstances. Herein, we present a cobalt-selenide (CoSe2) and cobalt-oxide (Co3O4) based composite (CSCO-2) material through a wet chemical method. As-prepared catalyst has been analyzed for various physicochemical characterizations. CSCO-2 offers efficient OER performance in 1.0 M KOH with an overpotential of 252 mV at current density of 20 mA/cm2, with a low Tafel slope value of 69 mV/dec. Importantly, as-prepared catalyst shows stability of 48 h for longer electrochemical performance as a potential candidate for OER.

Developing countries face the problem of otogenic intracranial complications especially in paediatric population because of poor hygiene, malnutrition and low immunity. Active epithelial type Chronic Suppurative Otitis Media (CSOM) can be the cause of potentially fatal complications, one of these is otogenic brain abscess. Having an estimated annual incidence to be approximately 0.5 per 100,000 children, it is associated with high mortality. We describe a unique case of otogenic brain abscess secondary to Active epithelial CSOM being neglected for two years and finding an unexpected foreign body in the right ear canal in a 12-year-old boy. The consultation was sought when the headache became intense and hemiparesis appeared. Our case is unique regarding both the clinical presentation and the causative organism. The patient underwent craniotomy, with elective capsulotomy, drainage of abscess and placement of a ventriculoperitoneal shunt. This was followed by a modified radical mastoidectomy two weeks later and an uneventful recovery.

The brines from desalination plants need to be disposed of due to their strong impact on the environment. Membrane operations, like direct contact membrane distillation (DCMD), provide a possible solution to reduce the amount of brine while producing further desalinated water. In this study, an exergy analysis of a laboratory membrane distillation unit working with brines from reverse osmosis (RO) is analyzed. Exergy analysis enables us to assess the energy lost in entropy generation; therefore, it commits us to identify the less efficient configuration of the DCMD module. Unlike other exergy analyses for distillation, in this study, only module inputs and outputs were incorporated. The exergy is calculated at different infeed temperatures, for both in-out and out-in feed configurations of hollow fiber membrane modules. Also, exergy difference, flux, and exergetic efficiency for both configurations are calculated. At high feed temperatures, there is an increase in both flux and exergy change, which increases water recovery and feed side exergetic efficiency. The highest flux that is obtained in the out-in configuration is 13.3 kg/h.m2 while it is only 6.23 kg/h.m2 for the in-out system of the module. Also, these exergy changes and feed efficiencies are higher in the out-in module configuration than in the in-out module configuration. Conversely, the exergetic efficiency of the permeate is higher at lower feed temperatures, due to the lower accumulation of concentration polarization along the membrane wall.

Myocardial Infarction (MI), commonly known as a heart attack, is a type of cardiovascular disease characterized by the death of heart muscle cells. This condition occurs due to the blockage of blood vessels around the heart, inhibiting blood flow and causing an insufficient oxygen supply to the body. Typically, cardiovascular disease tests involve electrocardiogram (ECG) and photoplethysmogram (PPG) signals. In recent years, researchers have explored the application of Phonocardiogram (PCG) signals for cardiovascular detection due to their non-invasive, efficient, accessible, and cost-effective nature. While deep learning has been successful in object detection in digital images, its application to PCG signals for heart attack detection is rare. This study bridges this gap by introducing an enhanced technique called the Myocardial Infarction Detection System (MIDs). In contrast to previous deep learning research, this study employs a transfer learning algorithm as a classifier for MI feature datasets. Feature extraction is performed in segments to obtain more accurate MI features. Six feature extraction methods and transfer learning models based on Convolutional Neural Networks (CNN) using the VGG-16 architecture were selected as the primary components for MI identification. Additionally, this study compares these models with other CNN transfer learning models, such as VGG-19 and Xception, to assess their performance. Two experimental scenarios were conducted to evaluate MIDs performance in MI detection: experiments without hyperparameter tuning and with hyperparameter tuning. The results indicate that MIDs with CNN (VGG-16) after tuning exhibited the highest detection performance compared to other transfer learning CNN models, both with and without tuning. The accuracy, specificity, and sensitivity of MIDS detection with this configuration were 96.7%, 96.0%, and 97.4%, respectively. This research contributes to the development of an enhanced MI detection technique based on PCG signals using a transfer learning CNN.

This study explored the convergence rate of the hybrid numerical iterative technique (HNIT) for the solution of nonlinear problems (NLPs) of one variable ( f (x) = 0) . It is sightseen that convergence rate is two for the HNIT. By the HNIT, several algebraic and transcendental NLPs of one variable have been illustrated as an approximate real root for efficient performance. In many instances, HNIT is more vigorous and attractive than well-known conventional iterative techniques (CITs). The computational tool MATLAB has been used for the solution of iterative techniques.

Electrocatalytically active nanocomposites play a vital role in energy generation, conversion, and storage technologies. Transition metal-based catalysts such as nickel and iron and their pnictide (phosphide), and chalcogenide (selenide) compounds exhibit good activity for hydrogen evolution reaction (HER) in the alkaline environment. In this study, transition metals-based catalysts (Ni-P-Se, Fe-P-Se, and Ni-Fe-P-Se) solutions were prepared using a simple one-pot method. Prepared solutions were deposited on Ni foam, and different characterization techniques were used to determine the composition, structure, and morphology of as-prepared catalysts. Furthermore, it was found that Ni-Fe-P-Se as a cathode material showed better HER performance compared to other investigated materials with the overpotential value of 316 mV at 10 mA cm-2 current density and 89 mV dec-1 Tafel slope value. The stability tests of the as-prepared catalyst confirmed that the synergistic effect between various elements enhances the electrocatalytic performance for up to 24 hours, providing a fair, stable nature of Ni-Fe-P-Se based sample.

Water presents challenges in swiftly and accurately assessing its quality due to its intricate composition, diverse sources, and the emergence of new pollutants. Current research tends to oversimplify water quality, categorizing it as potable or not, despite its complexity. To address this, we developed a water quality prediction system (WaQuPs), a sophisticated solution tackling the intricacies of water quality assessment. WaQuPs employs advanced machine learning, including an ensemble learning model, categorizing water quality into nuanced levels: potable, lightly polluted, moderately polluted, and heavily polluted. To ensure rapid and precise dissemination of information, WaQuPs integrates an Internet of Things (IoT)-based communication protocol for the efficient delivery of detected water quality results. In its development, we utilized advanced techniques, such as random oversampling (ROS) for dataset balance. We used a correlation coefficient to select relevant features for the ensemble learning algorithm based on the Random Forest algorithm. Further enhancements were made through hyperparameter tuning to improve the prediction accuracy. WaQuPs exhibited impressive metrics, achieving an accuracy of 83%, precision of 82%, recall of 83%, and an F1-score of 82%. Comparative analysis revealed that WaQuPs with the Random Forest model outperformed both the XGBoost and CatBoost models, confirming its superiority in predicting water quality.

The ongoing COVID-19 pandemic has had a psychological impact on the elderly. The elderly feel lonely and depressed. Spirituality to deal with the pandemic is needed by the elderly. This study aims to determine the relationship between spirituality with depression and loneliness in the elderly. This research was conducted with a cross-sectional approach using a questionnaire on 142 elderly respondents. Based on the Spearman rank correlation test results, there is a unidirectional relationship between spirituality scores and depression scores with a p-value of 0.038 (p

One of the non-pharmacological treatments that can be done to lower blood pressure is to increase the patient's physical activity, such as Isometric Exercise and Yoga breathing exercises. Objectives: To determined isometric exercise and yoga breathing on reducing blood pressure in hypertension. Methods: This study used a pre-experimental design with a one-group pretest-postest design. The sampling technique was purposive sampling. The number of samples in this study was 25 people. Results: The paired t-test statistical test results were a decrease in blood pressure after being given the intervention of isometric exercise and yoga breathing exercises with a p-value of 0.000 (p

Developing the concept of sustainable entrepreneurship from upper echelons theory and resource-based view theory, this research explores the impact of sustainable entrepreneurship among small and medium-sized enterprises. Sustainable entrepreneurship pursues a motivating approach to the economic, social, and environmental objectives of the society. The purpose of the study is to delve into the influencing factors of sustainable entrepreneurship among SMEs. The research is based on a quantitative approach via survey to address the sustainable entrepreneurship among SMEs (e.g., Punjab) in Pakistan. Data were obtained from 330 employees working in manufacturing SME’s. Additionally, structural equation modelling (SEM) was tested to examining the hypothesized relationship. The results confirm a positive effect of sustainability orientation and entrepreneurial orientation on sustainable entrepreneurship and the moderating effect of entrepreneurial knowledge was found significant. Moreover, the results confirm a negative effect of entrepreneurial bricolage on sustainable entrepreneurship, and the moderating effect of the entrepreneurial knowledge was found to be insignificant. However, these researches carry-out the context of entrepreneurial bricolage acts as a moderator in sustainable entrepreneurship research. Based on the findings, this research provides implications for the policymakers to promote sustainable entrepreneurship to facilitate new markets and getting the foremost advantage of sustainable development in SME’s.

Intrusion Detection System is yet an interesting research topic. With a very large amount of traffic in real-time networks, feature selection techniques that are effectively able to find important and relevant features are required. Hence, the most important and relevant set of features is the key to improve the performance of intrusion detection system. This study aims to find the best relevant selected features that can be used as important features in a new IDS dataset. To achieve the aim, an approach for generating optimized ensemble IDS is developed. Six features selection methods are used and compared, i.e.: Information Gain (IG), Gain Ratio (GR), Symmetrical Uncertainty (SU), Relief-F (R-F), One-R (OR) and Chi-Square (CS). The feature selection techniques produce sets of selected features. Each best selected number of features that are obtained from feature ranking step for respective feature selection technique will be used to classify attacks via four classification methods, i.e.: Bayesian Network (BN), Naïve Bayesian (NB), Decision Tree: J48 and SOM. Then, each feature selection technique with its respective best features is combined with each classifier method to generate ensemble IDSs. Lastly, the ensemble IDSs are evaluated using Hold-up, K-fold validation approaches, as well as F-Measure and statistical validation approaches. Experimental results using Weka tools on ITD-UTM dataset show the optimized ensemble IDSs using (SU and BN); using (CS and BN) or (CS and SOM) or (IG and NB); and using (OR and BN) with respective ten, four and seven best selected features achieves 81.0316%, 85.2593%, and 80.8625% of accuracy, respectively. In addition, ensemble IDSs using (SU and BN) and using (OR and J48) with ten and six best respective selected features, perform the best F-measure value, i.e.: 0.853 and 0.830, respectively. Indirect comparison with other ensemble IDS on different dataset is discussed.

For large-scale energy applications, conceiving low-cost and simple earth-abundant electrocatalysts are more difficult. By using an aqueous chemical technique, MnO2 was added into Co3O4 with varying concentrations to prepare MnO2@Co3O4 nanocomposite (CM). In an aqueous solution of 1 M KOH, the electrocatalyst with a greater concentration of MnO2 outperforms in terms of OER. To confirm the composition, crystalline structure, and morphology of the electrocatalyst, analytical methods such as X-ray diffraction (XRD) techniques, Fourier transformed infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) were used. At 20 mA/cm2 current density, the electrocatalyst had a lowest overpotential of 310 mV verses Reversible hydrogen electrode (RHE). The CM-0.4 electrocatalyst has a small Tafel slope value and charge transfer resistance of approximately 72 mV/dec and 74 Ω which confirm its high catalytic activity. The electrocatalyst reveals a double layer capacitance (Rct) of 18 µF/cm2 and an electrochemical active surface area (ECSA) of 450 cm2, demonstrating that addition of MnO2 impurities into Co3O4 enhances the active catalyst sites. These findings contribute to the knowledge of these kind of catalysts, that will assist in the development of novel electrocatalysts which are feasible for prospective energy generation technologies.

With the advancement of technology it has been possible to detect diseases through non-invasive techniques. Previous studies showed us that diabetes mellitus and cardiometabolic syndrome are correlated disorders. Presence of one increased the possibility of existence of other. Efficient ways has been introduced to detect these disorders through facial image analysis using texture and color features. Furthermore, Human faces can be divided into three main categories based on the anatomical growth of their bones. Based on the knowledge the question arose that what could be the relation between facial types and these different categorical but linked disorders. Primary objective of this study is to analyze the facial types which have more probability of getting diabetes and cardiometabolic syndrome. Secondary objective includes the analysis of both genders i.e. male and female to detect which one of these genders are having more chances of these long lasting abnormalities. In the first step, data was acquired from four hospitals to make sure that it is accurate, both qualitatively and quantitatively. A few specifications were considered before capturing an image such as: frontal face, a distance of 3-4 feet between the camera and the subject, white background and neutral expressions. The age group of subjects was limited from of 30 to 80 years. The dataset consists of 198 participants including both male and female with equal number of subject in three groups namely diabetic, cardiometabolic and normal group. Facial index ratio was obtained after calculating the height and width of face using the anatomical landmarks described by researchers. After that each subject was classified into their respective group based on their facial ratio. Lastly, each group having different facial index ratio of project participant was analyzed statistically. Primary results showed that a large number of diabetic patients have wider and average faces also called mesofacial and brachifacial classes of face in medical terms. Further statistical analysis showed that there is a significant difference present between diabetic and normal group with P< 0.013 using CI of 95% and P

The rice leaf folder, Marasmia exigua (Butler), is dangerous pests and negatively affecting the rice production worldwide. Protein elicitors are considered to be bio-factors that induce rice resistance against herbivores. The present study was performed with two protein elicitors, Hrip 1 (extracted from Alternaria tenuissima) and PebB1 (from Beauveria bassiana) to study their efficacy against the rice leaf folder. Three different concentrations of Hrip 1 (68.88, 46.69 and 28.44 µg/ml) and PebB1 (56.66, 39.76 and 32.62 µg/ml) were assigned to evaluate the developmental time, survival rate, and fecundity of M. exigua. Both elicitors were applied to the three-leaf stage of the rice plant where newly emerged adult insects were released. Bioassay results showed that after the application of protein elicitors, the life cycle and survival rate of the rice leaf folder were prolonged, while fecundity decreased. The concentration of protein had a significant (p

This study investigates a linear homogeneous initial-boundary value problem for a traveling string under linear viscous damping. The string is assumed to be traveling with constant speed, while it is fixed at both ends. Physically, this problem represents the vertical (lateral) vibrations of damped axially moving materials. The axial belt speed is taken to be positive, constant and small in comparison with a wave speed, and the damping is also considered relatively small. A two timescale perturbation method together with the characteristic coordinate’s method will be employed to establish the approximateanalytic solutions. The damped amplitude-response of the system will be computed under specific initial conditions. The obtained results are compared with the finite difference numerical technique for justification. It turned out that the introduced damping has a significant effect on the amplitude-response. Additionally, it is proven that the mode-truncation is applicable for the damped axially traveling string system on a timescale of order ε -1

Present study aimed at investigating the association between personality traits, perceived social support and depressive symptoms in adolescents. Through convenient sampling, total 302 students (110 males and 192 females) were recruited from different universities of Rawalpindi and Islamabad. The age range of sample was 18-25 years. In present study, The Big Five Inventory- Short Version (BFI-S) (Gerlitz & Schupp, 2005), The Multidimensional Scale of Perceived Social Support (MSPSS) (Zimet et al., 1988), and Depression, Anxiety and Stress Scale (DASS-21) (Lovibond & Lovibond, 1995) were used to access personality traits, perceived social support and depressive symptoms. Findings of the present study showed a significant positive relationship between neuroticism and depressive symptoms. However, extraversion, conscientiousness and perceived social support showed significant negative association with depressive symptoms. According to regression analysis, neuroticism is a positive while, perceived social support is significant negative predictor of depressive symptoms in young adolescents. Furthermore, findings of present study may assist in identifying the personality traits at risk of experiencing depression.

The stimulus to carry out this research was to identify and propose a secure framework for the Internet of Things (IoT). Due to the massive accessibility and interconnection of IoT devices, systems are at risk of being exploited by hackers. Therefore, there is a need to find an advanced security framework that covers data security, data confidentiality, and data integrity issues. The study uses a systematic literature review (SLR) technique and complete substantive literature is reviewed to find out the constructs and themes in the existing literature. We performed it in four steps, which were inclusion, eligibility, screening, and identification. We reviewed around 568 articles from well-reputable journals, and after exclusion, 260 articles and 54 reports were analyzed. We performed an analysis using MAXQDA in which the nodes and themes were first identified. After the classification, a qualitative model was generated using MAXQDA. The proposed model is supported by the literature so it will be useful for the IT managers, developers, and the users of IoT.

Mesoporous TiO2 nanoparticles were successfully synthesized via solvothermal. The morphology and crystal structure was characterized by UV–vis spectrum (UV-Vis), Fourier Transform Infrared (FTIR) spectroscopy, X-ray diffraction (XRD), Scanning electron microscopy (SEM) and transmission electron microscopy (TEM). All the observations confirmed that the as-fabricated mesoporous TiO2 nanoparticles were successfully synthesized with surface Plasmon resonance peak between a range of 250-350 nm, and its pattern meets with the JCPDS Standard (card No. 21-1272). TEM confirmed the mesoporous structure morphology and shows the incredible gas sensing performance due to their large accessible surface area. Furthermore, the as-prepared TiO2 nanoparticles exhibited more rapid response/recovery and higher sensitivity towards ethanol at 180°C, distinguished with isopropyl alcohol and methanol. Besides, it can be affirmed that the synthesized mesoporous TiO2 nanoparticles are a promising applicant for fabricating high-performance ethanol gas sensor in real-time monitoring.

With the advancement of technology it has been possible to detect diseases through non-invasive techniques. Previous studies showed us that diabetes mellitus and cardiometabolic syndrome are correlated disorders. Presence of one increased the possibility of existence of other. Efficient ways has been introduced to detect these disorders through facial image analysis using texture and color features. Furthermore, Human faces can be divided into three main categories based on the anatomical growth of their bones. Based on the knowledge the question arose that what could be the relation between facial types and these different categorical but linked disorders. Primary objective of this study is to analyze the facial types which have more probability of getting diabetes and cardiometabolic syndrome. Secondary objective includes the analysis of both genders i.e. male and female to detect which one of these genders are having more chances of these long lasting abnormalities. In the first step, data was acquired from four hospitals to make sure that it is accurate, both qualitatively and quantitatively. A few specifications were considered before capturing an image such as: frontal face, a distance of 3-4 feet between the camera and the subject, white background and neutral expressions. The age group of subjects was limited from of 30 to 80 years. The dataset consists of 198 participants including both male and female with equal number of subject in three groups namely diabetic, cardiometabolic and normal group. Facial index ratio was obtained after calculating the height and width of face using the anatomical landmarks described by researchers. After that each subject was classified into their respective group based on their facial ratio. Lastly, each group having different facial index ratio of project participant was analyzed statistically. Primary results showed that a large number of diabetic patients have wider and average faces also called mesofacial and brachifacial classes of face in medical terms. Further statistical analysis showed that there is a significant difference present between diabetic and normal group with P< 0.013 using CI of 95% and P

Introduction: The alleviation of suffering is a primary goal of palliative care team for patients with terminal cancer. In some cases, patients experience symptoms requiring inpatient care. The purpose of this investigation was to assess the clinical presentation and outcomes of hospitalization in patients that were admitted to the acute palliative care service. Materials and Methods: This is a retrospective descriptive study looking at admissions to an acute palliative care unit in a single center over a 24-month period. Medical records of all patients, admitted in palliative care unit from 1st January 2013 till 31st December 2014, were reviewed for reason of admission and outcome. Results: A total of 226 patients were identified and included in the present investigation. Among these 55.5 % (125) were females. The median age of the cohort was 48 (15 - 86) years. The most common reasons for admission were alteration in consciousness (19.5 %), respiratory tract infection (18 %), diarrhea and/or vomiting (14.2 %) and respiratory distress (not related to infection) (13.4 %). The median duration of hospital stay was 4 (0-27) days. Majority of the patients were discharged home (65.1 %). However, a significant portion (33.1 %) of the patients did not survive the hospitalization. Following discharge from the hospital, at 4-weeks follow-up the survival rate was 38.7 %. This dropped to 21.7 % at 8-weeks. Conclusion: Patients with advanced disease have a multitude of reasons to seek acute inpatient care. Majority of the patients were discharged following care. However, the survival rate of patients following discharge was low.

Mobile cloud computing (MCC) holds a new dawn of computing, where the cloud users are attracted to multiple services through the Internet. MCC has a qualitative, flexible, and cost-effective delivery platform for providing services to mobile cloud users with the aid of the Internet. Due to the advantage of the delivery platform, several studies have been conducted on how to address different issues in MCC. The issues include energy efficiency in MCC, secured MCC, user-satisfied applications and Quality of Service-aware MCC (QoS). In this context, this paper qualitatively reviews different proposed MCC solutions. Therefore, taxonomy for MCC is presented considering major themes of research including energy-aware, security, applications, and QoS-aware developments. Each of these themes is critically investigated with comparative assessments considering recent advancements. Analysis of metrics and implementation environments used for evaluating the performance of existing techniques are presented. Finally, some open research issues and future challenges are identified based on the critical and qualitative assessment of literature for researchers in this field.

In spite of all security issues in the cloud system, distributed cloud environment requires an access control model which should be context aware to handle all issues intelligently. It must include role activation process based on the user's context information. In role activation process, the knowledge of reason used for data collection and usage is declared; this can allow the administrator to declare the policies which are context based. Therefore, there is dynamic activation of role permission due to the association of role with context. The complications in the role based access control model reduced by classifying the users into classes or groups having their own access control standards. Access to specific resources and granting/ denying is based on requesting the user identity. Cloud environments consist of different entities, number of resources and user where general access control model fails to cover all the aspects. Here, in the proposed access control with perception reasoning, entities are extended using Extensible Access Control Mark-up Language (XACML) where trust module monitors the random and dynamic behavior of the user with recognizing and restricting the malicious user for illegal data access. By issuing and identity tag to malicious user includes classification of task and data tag with data in the database.

This research is a qualitative descriptive field research which examines the Principal’s Strategic Management Based on SWOT Analysis at the Islamic Junior High School ‘Ishlahul Muslimin’ in Senteluk, West Lombok. Data is collected through through observations, interviews, and documentation which is then analysed through data reduction, data display, and verification. The reseach subjects are the chairman of the school committee, the headmaster, the vice principals (curriculu affai; student affairs; public relations, facilities and infrastructure affairs) and teachers. This research aims to (1) describe the procedure of the MTs Ishlahul Muslimin’s Principal’s Strategic Management, (2) identify the implementation of SWOT analysis at MTs Ishlahul Muslimin Senteluk Lombok Barat, and (3) identify the internal and external factors related to MTs Ishlahul Muslimin’s program implementation. The results of this study indicate that : (a) the principal’s Strategic Management is considered to be innovative and flexible, (b) the implementation of SWOT analysis at MTs Ishlahul Muslimin Senteluk Lombok Barat has three phases: strategy formulation, strategy implementation, and strategy evaluation, and (c) the internal factors related to the program implementation at MTs Ishlahul Muslimin are learner analysis, educators analysis and curriculum analysis. The external factors include the analysis of the social environment of the community and the analysis of the role of government.

The Internet of Things gateways with multi-radio facilities in wireless networks can simultaneously communicate using multiple available channels. This feature enhances the carrying capacity of wireless links and thus increases the overall network throughput. However, designing an efficient resource allocation strategy is a complex task due to the decisive behavior of interference. There is only a limited number of available channels; therefore, the resource allocation requires careful planning to mitigate the effect of interference. This research proposes a backtracking search-based resource allocation scheme that maps resource allocation to the constraint satisfaction problem. Some of the resource allocation constraints are applied as soft constraints which are relaxed to find a feasible solution, provided the perfect allocation of limited resources is not possible. The proposed approach has been benchmarked through simulations and the results prove the effectiveness of the proposed approach especially in dense multi-hop network deployments.

The multipath transmission is one of the suitable transmission methods for high data rate oriented communication such as video streaming. Each video packets are split into smaller frames for parallel transmission via different paths. One path may interfere with another path due to these parallel transmissions. The multipath oriented interference is due to the route coupling which is one of the major challenges in vehicular traffic environments. The route coupling increases channel contention resulting in video packet collision. In this context, this paper proposes an Interference-aware Multipath Video Streaming (I-MVS) framework focusing on link and node disjoint optimal paths. Specifically, a multipath vehicular network model is derived. The model is utilized to develop interference-aware video streaming method considering angular driving statistics of vehicles. The quality of video streaming links is measured based on packet error rate considering non-circular transmission range oriented shadowing effects. Algorithms are developed as a complete operational I-MVS framework. The comparative performance evaluation attests the benefit of the proposed framework considering various video streaming related metrics.

In recent years, the cloud computing model has gained increasing attention and popularity in the field of information technology. For this reason, people are migrating their applications to public, private, or hybrid cloud environments. Many cloud vendors offer similar features with varying costs, so an appropriate choice will be the key to guaranteeing comparatively low operational costs for an organization. The motivation for this work is the necessity to select an appropriate cloud storage provider offering for the migration of applications with less cost and high performance. However, the selection of a suitable cloud storage provider is a complex problem that entails various technical and organizational aspects. In this research, a dynamic Decision Support System (DSS) for selection of an appropriate cloud storage provider is proposed. A web-based application is implemented using PHP and MySQL to facilitate decision makers. The proposed mechanism has been optimized in a way that enables the system to address static database issues for which a user might not acquire the best solution. It focuses on comparing and ranking cloud storage providers by using two modules: scraping and parsing. The evaluation of the proposed system is carried out with appropriate test cases and compared with existing tools and frameworks.

Due to the absence of infrastructure support, secure data dissemination is a challenging task in scalable mobile ad hoc networks (MANETs) environment. In most of the traditional routing techniques for MANETs, either security has not been taken into account or only one aspect of security concern has been addressed without optimizing the routing performance. This paper proposes Flooding Factor based Framework for Trust Management (F3TM) in MANETs. True flooding approach is utilized to identify attacker nodes based on the calculation of trust value. Route Discovery Algorithm is developed to discover an efficient and secure path for data forwarding using Experimental Grey Wolf algorithm for validating network nodes. Enhanced Multi-Swarm Optimization is used to optimize the identified delivery path. Simulations are carried out in ns2 to assess and compare the performance of F3TM with the state-of-the-art frameworks: CORMAN and PRIME considering the metrics including delay, packet delivery ration, overhead and throughput. The performance assessment attests the reliable security of F3TM compared to the state-of-the-art frameworks.

In this paper, the energy estimates for a damped linear homogeneous beam-like equation will be considered. The energy estimates will be studied for different BCs (Boundary Conditions) for the axially moving continuum. The problem has physical and engineering application. The applications are mostly occurring in models of conveyor belts and band-saw blades. The research study is focused on the Dirichlet, the Neumann and the Robin type of BCs. From physical point of view, the considered mathematical model expounds the transversal vibrations of a moving belt system or moving band-saw blade. It is assumed that a viscous damping parameter and the horizontal velocity are positive and constant. It will be shown in this paper that change in geometry or the physics of the boundaries can affect the stability properties of the system in general and stability depends on the axial direction of the motion. In all cases of the BCs, it will be shown that there is energy decay due to viscous damping parameter and it will also be shown that in some cases there is no conclusion whether the beam energy decreases or increases. The detailed physical interpretation of all terms and expressions is provided and studied in detail.

Objective : Oral squamous-cell carcinoma (OSCC) accounts for >90% of oral cancers affecting adults mostly between the fourth to seventh decades of life. The most common OSCC treatment is concomitant chemoradiotherapy (CCRT) having both loco-regional and distant control, but CCRT has acute and chronic toxic effects on adjacent normal tissue. This study aimed to determine the side effects of CCRT on the oral mucosa and to characterize the clinicopathology of oral lesions in patients with OSCC.Methods: This descriptive, cross-sectional study was certified by the Ethical Review Committee (UHS/Education/126-12/2728) of the University of Health Sciences, Lahore, Pakistan. OSSC patients (n=81) with various histological subtypes, grades, and stages were recruited, and findings on their oral examination were recorded. These patients received 70, 90, and 119 Gy of radiotherapy dosages in combination with the chemotherapy drugs cisplatin and 5-fluorouracil. Data were analyzed using SPSS 20.0.Results : The most common presentation of OSCC was a nonhealing ulcer (63%) involving tongue (55.6%). Clinical findings included mucositis (92.6%) and xerostomia of mild, moderate, and severe degrees in 11.1%, 46.9%, and 35.8% cases, respectively. Ulcers (87.7%), palpable lymph nodes (64.2%), limited mouth opening (64.2%) and fistula (40.7%) were also observed. In females, the association of radiotherapy dosage with limited mouth opening, xerostomia, and histological grading was statistically significant (PP=0.003) was also statistically significant.Conclusions : CCRT induced mucositis, xerostomia, and trismus in patients with OSCC.

In vehicular ad hoc networks (VANETs), trust establishment among vehicles is important to secure integrity and reliability of applications. In general, trust and reliability help vehicles to collect correct and credible information from surrounding vehicles. On top of that, a secure trust model can deal with uncertainties and risk taking from unreliable information in vehicular environments. However, inaccurate, incomplete, and imprecise information collected by vehicles as well as movable/immovable obstacles have interrupting effects on VANET. In this paper, a fuzzy trust model based on experience and plausibility is proposed to secure the vehicular network. The proposed trust model executes a series of security checks to ensure the correctness of the information received from authorized vehicles. Moreover, fog nodes are adopted as a facility to evaluate the level of accuracy of event's location. The analyses show that the proposed solution not only detects malicious attackers and faulty nodes, but also overcomes the uncertainty and imprecision of data in vehicular networks in both line of sight and non-line of sight environments.

This paper proposes an emergency Traffic Adaptive MAC (eTA-MAC) protocol for WBANs based on Prioritization. The main advantage of the protocol is to provide traffic ranking through a Traffic Class Prioritization-based slotted-Carrier Sense Multiple Access/Collision Avoidance (TCP-CSMA/CA) scheme. The emergency traffic is handled through Emergency Traffic Class Provisioning-based slotted-CSMA/CA (ETCP-CSMA/CA) scheme. The emergency-based traffic adaptivity is provided through Emergency-based Traffic Adaptive slotted-CSMA/CA (ETA-CSMA/CA) scheme. The TCP-CSMA/CA scheme assigns a distinct, minimized and prioritized backoff period range to each traffic class in every backoff during channel access in Contention Access Period (CAP). The ETCP-CSMA/CA scheme delivers the sporadic emergency traffic that occurs at a single or multiple BMSN(s) instantaneously, with minimum delay and packet loss. It does this while being aware of normal traffic in the CAP. Then, the ETA-CSMA/CA scheme creates a balance between throughput and energy in the sporadic emergency situation with energy preservation of normal traffic BMSNs. The proposed protocol is evaluated using NS-2 simulator. The results indicate that the proposed protocol is better than the existing Medium Access Control (MAC) protocols by 86% decrease in packet delivery delay, 61% increase in throughput, and a 76% decrease in energy consumption.

Seaports play a crucial role in international trade and economic development. This study aims to analyze the existing literature on port facilities to identify research patterns and emerging areas of interest. Using the Scopus database, the researchers searched for publications related to port facilities and found a total of 178 scholarly articles. The data was analyzed using Microsoft Excel, Publish or Perish and VOS viewer. The study examined subject areas, keywords, citations, and Journal/publishers metrics, to understand the key contributors and collaborative efforts in this field. The findings revealed a lack of scholarly evaluation of port facilities literature until 1975. From 1975 to 2003, there were 57 publications with very few citations. However, interest in this field grew significantly between 2004 and 2023, with 114 publications and 496 citations. Most of the documents were written in English, and there was concentration of research efforts in specific areas. International collaboration was observed among 12 countries. The study suggests the need for more research, collaborations, and citations in the field of port facilities, particularly in areas beyond engineering and earth and planetary sciences. Logistics management, computing, and maritime should be further explored to address gaps in the current literature.

Internet of Things is smartly changing various existing research areas into new themes, including smart health, smart home, smart industry, and smart transport. Relying on the basis of “smart transport,” Internet of Vehicles (IoV) is evolving as a new theme of research and development from vehicular ad hoc networks (VANETs). This paper presents a comprehensive framework of IoV with emphasis on layered architecture, protocol stack, network model, challenges, and future aspects. Specifically, following the background on the evolution of VANETs and motivation on IoV an overview of IoV is presented as the heterogeneous vehicular networks. The IoV includes five types of vehicular communications, namely, vehicle-to-vehicle, vehicle-to-roadside, vehicle-to-infrastructure of cellular networks, vehicle-to-personal devices, and vehicle-to-sensors. A five layered architecture of IoV is proposed considering functionalities and representations of each layer. A protocol stack for the layered architecture is structured considering management, operational, and security planes. A network model of IoV is proposed based on the three network elements, including cloud, connection, and client. The benefits of the design and development of IoV are highlighted by performing a qualitative comparison between IoV and VANETs. Finally, the challenges ahead for realizing IoV are discussed and future aspects of IoV are envisioned.

Trust, as a key element of security, has a vital role in securing vehicular ad-hoc networks (VANETs). Malicious and selfish nodes by generating inaccurate information, have undesirable impacts on the trustworthiness of the VANET environment. Obstacles also have a negative impact on data trustworthiness by restricting direct communication between nodes. In this study, a trust model based on plausibility, experience, and type of vehicle is presented to cope with inaccurate, incomplete and uncertainty data under both line of sight (LoS) and none-line of sight (NLoS) conditions. In addition, a model using the k-nearest neighbor (kNN) classification algorithm based on feature similarity and symmetry is developed to detect the NLoS condition. Radio signal strength indicator (RSSI), packet reception rate (PDR) and the distance between two vehicle nodes are the features used in the proposed kNN algorithm. Moreover, due to the big data generated in VANET, secure communication between vehicle and edge node is designed using the Cuckoo filter. All obtained results are validated through well-known evaluation measures such as precision, recall, overall accuracy, and communication overhead. The results indicate that the proposed trust model has a better performance as compared to the attack-resistant trust management (ART) scheme and weighted voting (WV) approach. Additionally, the proposed trust model outperforms both ART and WV approaches under different patterns of attack such as a simple attack, opinion tampering attack, and cunning attack. Monte-Carlo simulation results also prove validity of the proposed trust model.

This study reports the characterization of protein elicitor PeBb1 derived from entomopathogenic fungus Beauveria bassiana ARSEF-2860 strain and its putative role in induced systemic resistance in Brassica rapa ssp. pekinensis against green peach aphid Myzus persicae. The sequence of purified elicitor protein was matched with the genomic sequence of a hypothetical protein BBA_10269 from B. bassiana ARSEF-2860 (GenBank Accession No. XP_008603588.1). The protein-encoding gene PeBb1 contained 534 bp cDNA encoding a polypeptide of 177 amino acids with a molecular mass of 19 kDa. The recombinant elicitor protein was expressed in Escherichia coli using pET-28a (+) expression vector and induced necrosis in the leaves of tobacco. The effects of elicitor protein on aphid M. persicae was determined by applying three different concentrations of PeBb1 (i.e., 26, 35, 53 μM) on B. rapa plants at 4-leaf stage and the treated plants were exposed to newly emerged (0−6 h old) apterous adult aphids. Bioassay results showed significant (p < 0.05) sub-lethal effects of the exogenous application of PeBb1 elicitor on M. persicae. Moreover, the RT-qPCR gene expression analyses showed a significant up-regulation of most of the key genes linked to ethylene (ET)- and jasmonic acid (JA)-associated plant defense pathways in elicitor-treated plants. These results not only recommend the putative utilization of PeBb1 elicitor protein in future biological pest control strategies against phloem-feeding insect pests such as M. persicae, but also help in better comprehension of the mechanisms through which beneficial fungi trigger the induced plant resistance.

Clustered Red Blood Cells are observed very frequently in the thin blood smear digital images. Separating clustered Red Blood Cells from the single Red Blood Cells and splitting of clustered Red Blood Cells into single Red Blood Cells is a challenging job in the computer-assisted diagnosis of blood for any disorder in many diseases like Complete Blood Count Test, Anemia, Leukemia and Malaria etc. The mentioned problems are highly laborious in manual microscopy for the hematologists. Many techniques currently existing for the solution suffer from both under- and over- splitting problems when highly complex clusters of Red Blood Cells occur. In addition, the existing techniques are not computationally efficient. In this paper, we address the aforementioned problems, firstly by considering the boundaries of the convex hulls of clustered Red Blood Cells and secondly, by splitting the boundaries according to the number of Red Blood Cells in relation to distance measures. Furthermore, we draw circles using a mid-point circle algorithm at each boundary cleavage to give an illusion of the Red Blood Cells. The test results of the proposed technique on a standard online dataset are presented in two ways. Statistically first of all by achieving an average recall of 0.964 and precision of 0.970 while their F-measure achieved is 0.962 as well as secondly through ground truth data with visual inspections.

Background: Neonatal tetanus (NNT) is one of the childhood’s preventable diseases and a leading cause of neonatal death especially in developing countries. This study was done to determine the outcome and factors contributing to the neonatal tetanus. Materials & Methods: This cross sectional study was conducted at the Sifwat Ghayoor Memorial Government Children Hospital, Peshawar, Pakistan over a period of one year from 1st August 2015 to 31st July 2016. Hundred confirmed cases of neonatal tetanus admitted to the hospital were enrolled in the study using consecutive non probability sampling technique. Study variables were Age in days, weight, area of residence, birth order of child, gender, monthly income, mother’s education, family type, H/O antenatal visits, mode of delivery, delivery performed by trained birth attendant, health facility near home, and outcome of the disease. Results: Seventy four (74%) were male while 26(26%) cases were female. The mean age at admission was 8.34±3.54 days. Mean weight of the neonates admitted with NNT was 3.28±0.61 Kg. A great number of deliveries were taken place at home 78(78%), 70(70%) deliveries were conducted without a trained birth attendant, in a great number of cases 75(75%) materials other than antiseptic were applied to the umbilical cord, the umbilical cord was cut with non sterile instrument in 78% cases and 36(36%) patients died out of 100 (95% Confidence Interval 26.43-45.57). Conclusion: Factors leading to neonatal tetanus are; non immunization of mothers during pregnancy, home delivery, delivery by non skilled birth attendants, application of ghee/surma on umbilical cord and cutting of umbilical cord by unsterilized tools. With proper immunization, antenatal care and hygienic delivery practices, disease can be controlled and mortality can be reduced.

Geographic routing is one of the most investigated themes by researchers for reliable and efficient dissemination of information in Vehicular Ad Hoc Networks (VANETs). Recently, different Geographic Distance Routing (GEDIR) protocols have been suggested in the literature. These protocols focus on reducing the forwarding region towards destination to select the Next Hop Vehicles (NHV). Most of these protocols suffer from the problem of elevated one-hop link disconnection, high end-to-end delay and low throughput even at normal vehicle speed in high vehicle density environment. This paper proposes a Geographic Distance Routing protocol based on Segment vehicle, Link quality and Degree of connectivity (SLD-GEDIR). The protocol selects a reliable NHV using the criteria segment vehicles, one-hop link quality and degree of connectivity. The proposed protocol has been simulated in NS-2 and its performance has been compared with the state-of-the-art protocols: P-GEDIR, J-GEDIR and V-GEDIR. The empirical results clearly reveal that SLD-GEDIR has lower link disconnection and end-to-end delay, and higher throughput as compared to the state-of-the-art protocols. It should be noted that the performance of the proposed protocol is preserved irrespective of vehicle density and speed.

Recently sink mobility has been exploited in numerous schemes to prolong the lifetime of wireless sensor networks (WSNs). Contrary to traditional WSNs where sensory data from sensor field is ultimately sent to a static sink, mobile sink-based approaches alleviate energy-holes issues thereby facilitating balanced energy consumption among nodes. In mobility scenarios, nodes need to keep track of the latest location of mobile sinks for data delivery. However, frequent propagation of sink topological updates undermines the energy conservation goal and therefore should be controlled. Furthermore, controlled propagation of sinks’ topological updates affects the performance of routing strategies thereby increasing data delivery latency and reducing packet delivery ratios. This paper presents a taxonomy of various data collection/dissemination schemes that exploit sink mobility. Based on how sink mobility is exploited in the sensor field, we classify existing schemes into three classes, namely path constrained, path unconstrained, and controlled sink mobility-based schemes. We also organize existing schemes based on their primary goals and provide a comparative study to aid readers in selecting the appropriate scheme in accordance with their particular intended applications and network dynamics. Finally, we conclude our discussion with the identification of some unresolved issues in pursuit of data delivery to a mobile sink.

Wireless Body Sensor Networks (WBSNs) constitute a subset of Wireless Sensor Networks (WSNs) responsible for monitoring vital sign-related data of patients and accordingly route this data towards a sink. In routing sensed data towards sinks, WBSNs face some of the same routing challenges as general WSNs, but the unique requirements of WBSNs impose some more constraints that need to be addressed by the routing mechanisms. This paper identifies various issues and challenges in pursuit of effective routing in WBSNs. Furthermore, it provides a detailed literature review of the various existing routing protocols used in the WBSN domain by discussing their strengths and weaknesses.

Efficient and reliable systems are required to detect and monitor disasters such as wildfires as well as to notify the people in the disaster-affected areas. Internet of Things (IoT) is the key paradigm that can address the multitude problems related to disaster management. In addition, an unmanned aerial vehicles (UAVs)-enabled IoT platform connected via cellular network can further enhance the robustness of the disaster management system. The UAV-enabled IoT platform is based on three main research areas: (i) ground IoT network; (ii) communication technologies for ground and aerial connectivity; and (iii) data analytics. In this paper, we provide a holistic view of a UAVs-enabled IoT platform which can provide ubiquitous connectivity to both aerial and ground users in challenging environments such as wildfire management. We then highlight key challenges for the design of an efficient and reliable IoT platform. We detail a case study targeting the design of an efficient ground IoT network that can detect and monitor fire and send notifications to people using named data networking (NDN) architecture. The use of NDN architecture in a sensor network for IoT integrates pull-based communication to enable reliable and efficient message dissemination in the network and to notify the users as soon as possible in case of disastrous situations. The results of the case study show the enormous impact on the performance of IoT platform for wildfire management. Lastly, we draw the conclusion and outline future research directions in this field.