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Load forecasting is a crucial task, which is carried out by utility companies for sake of power grids' successful planning, optimized operation and control, enhanced performance, and guaranteed reliability and adequacy. It mainly reduces the gap between demand and supply and thus assures an uninterrupted power supply and load shedding free operation. The electricity demand can be forecasted by several Artificial Intelligence (AI), Deep Learning (DL), and Machine Learning (ML) approaches of which hybrid methods are the most famous. This paper examines various present technologies and algorithms of load forecasting including digital twin (DT), data-mining (DM), federated learning (FL), and transfer learning (TL). In this work, a comprehensive assessment of forecasting with single and hybrid models is performed, their functions are reviewed and pros and cons are investigated. The Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Squared Error (RMSE) are used for performance assessment and comparison of the different models searching for best load forecasting model. The role of different experts and intelligent systems used for optimal load forecasting in power systems will be clearly elaborated along with their pros and cons, thus providing a roadmap research path for the readers, who wants to contribute to the scientific society related to this research field.

The occurrence of cascading failures poses significant risks to the stability and reliability of modern smart grids. This article presents a novel hybrid algorithm designed to assess and mitigate these failures. The technique combines advanced clustering algorithms, specifically Affinity Propagation Graph (APG) and Self-Propagating Graph (SPG), to detect critical nodes, and Unified Power Flow Controllers (UPFCs) to provide compensation to grid networks. The algorithm first uses APG to divide the network into clusters and considers the center bus as the critical node. If the center bus is not critical, SPG is applied to identify the critical node. This hybrid approach identifies the critical node in just 0.02 s (for both APG and SPG) and with improved accuracy compared to existing methods. After identifying critical nodes, UPFCs are strategically installed to regulate power flow and reduce the probability of cascading failures, with compensation taking approximately 0.14 s. Simulation results demonstrate the effectiveness of the proposed method in enhancing grid resilience and reducing the likelihood of cascading failures. By strategically deploying UPFCs at critical nodes, this approach ensures resilient grid operation in various scenarios. This research significantly contributes to the development of smart grid technologies by providing a comprehensive framework to address cascading failures in power distribution networks. The proposed method shows potential for improving the reliability and stability of power grids amid changing system dynamics and uncertainties.

Power systems are the most complicated networks that play a crucial role in daily lifestyles. To operate such systems in a stable condition, several control and protection strategies are required. Despite preventative measures, power systems still experience issues and breakdowns like power outages. However, severe and unanticipated conditions might cause damage to the entire system and causes blackout. In this article we studied the analysis of the significant blackouts and cascading failures that have been happened in Pakistan in last few years. The authors proposed a new infrastructure for Pakistan energy sector by introducing advanced energy storage system and cutting edge technology like Vehicle-to-Grid (V2G) technology that make the existing power system robust against these phenomena. The advanced energy storage systems include like solid- state batteries that play a vital role to balance supply and demand, while V2G enables electric vehicles to contribute to grid stability. The potential of these technologies is helpful to improve the grid stability and facilitate a sustainable energy transition. The role of various electric companies in Pakistan power infrastructure has also been discussed after an occurrence of such unplanned events in power system. It has been noted that the main cause of power outages is fluctuation in frequency and voltage collapse. Finally, various solutions have been proposed to overcome these problems and make sure the reliability and stability of power grid against blackout phenomena.

Stuttering is a speech disorder characterised by the repetition, prolongation, or blocking of sounds, syllables, or words, which can cause significant social and emotional difficulties for those who experience it. To help find and diagnose stuttering early, it is important for clinicians and researchers to accurately separate stuttering from normal speech. This helps them understand the disorder, find possible causes, and come up with effective interventions and treatments. The UCLASS dataset was used in this study, and 40 MFCC features were taken out to see how well different machine learning classifiers could indicate the difference between normal and stuttering speech. The major problem is the UCLASS imbalanced dataset. The authors address it with the synthetic minority oversampling technique. After machine learning experimentation’s, we propose a novel hybrid model that performs better than individual machine learning. In hybrid, the lightweight SutterNet model takes the best features from the data and then make prediction. The results indicate that the evaluated classifiers showed varying levels of performance. Overall, the results suggest that hybrid classifiers have the potential to accurately classify normal and stuttering speech, which could have important implications for the early identification and diagnosis of stuttering, as well as the development of assistive technologies and effective interventions and treatments.

Video sharing platforms like YouTube, TikTok and Instagram have gained popularity in the online space. Daily several videos are uploaded, which calls for an efficient video retrieval system that could identify near-duplicate videos that offers several advantages in content management, copyright protection, and multimedia retrieval. This will facilitate efficient content management by removal of redundant videos from large repositories to streamline storage resources and improve accessibility of multimedia collections. Additionally, this can help copyright protection and intellectual property allowing right holders to identify unauthorized copies of their original work. Moreover, in applications such as multimedia retrieval and recommendation systems, removal of near-duplicate videos can enhance user experience by providing relevant search results. AI provides a promising solution to this problem. We have proposed an effective system built on deep metric learning that solves the near duplicate video retrieval. This proposed model uses the pre-trained VGG-16 network that contains convolutional and fully connected layers to find video features. These video representations are fed to the deep metric learning framework in the form of triplets which are trained to calculate the accurate distance between similar or near-duplicate videos. For the training of the framework, VCDB dataset was used whereas for the evaluation of the model CC_WEB_VIDEO and TRECVID BBC Rushes 2007 datasets were used. Experiments have shown that mean average precision of 0.985% for the CC_WEB_VIDEO dataset is achieved thus outperforming the state-of-the-art models.

The alarming rise in road accidents underscores the urgent need for safer vehicles equipped with technologies to mitigate accidents and resulting injuries. Research in this area must consider driver fatigue and depression as they are among significant contributing factors to road accidents. This paper proposes a robust method for identifying depression in drivers using facial expression recognition technology. We leverage transfer learning, employing the VGG-16 model, for depression detection in drivers. The approach benefits from the pre-trained model’s knowledge, enabling it to adapt quickly to the task and reduces the data required for training. A dataset of images depicting normal and depressed drivers is utilized for training and testing the proposed model. The trained model analyzes a driver’s facial expressions to detect behavioral changes associated with depression. Upon detecting signs of depression, the system enables initiating a safe transfer of control from the driver to the vehicle’s automated systems. This automatic intervention aims to reduce the risk of accidents arising from impaired driver behavior. The proposed model is evaluated using various performance metrics achieving an accuracy of 96%. It also demonstrates excellent precision (98%), recall (97%), and F1-score (97%).

Stemming is an essential step in various Natural Language Processing (NLP) applications and is used to reduce different variants of the query words to a standard form to avoid the vocabulary mismatch issue in Information Retrieval (IR) systems. Due to specific grammatical rules and complex morphological structures, finding an effective stemming algorithm in Urdu is a challenging task. Although, several stemming algorithms have been proposed for the Urdu text stemming; however, none of them extract the stem from multilevel inflected forms. In this context, according to the best of our knowledge, this is a first effort towards the proposition and evaluation of a novel Urdu Text Stemmer (UTS) that can deal with multi-level inflection forms in Urdu text. The experimental evaluation of the proposed scheme has been conducted on the text-based and word-based custom-developed corpus. The proposed stemming technique is rigorously evaluated and compared with state-of-the-art stemming algorithms. Experimental results demonstrate that UTS outperforms existing Urdu stemmers and achieves an accuracy of 94.92% and 91.8% on word corpus and text corpus, respectively. We also evaluated our proposed system in an Information Retrieval application for Urdu, using the Collection for Urdu Retrieval Evaluation (CURE) dataset. Our approach for information retrieval outperformed and improved both recall and precision metrics.

Abstract This paper aims to extend the application of the Ostrowski inequality, a crucial tool for figuring out the error bounds of various numerical quadrature rules, including Simpson’s, trapezoidal, and midpoint rules. Specifically, we develop a more comprehensive class of Ostrowski-type inequalities by utilizing the weighted version of Riemann–Liouville (RL) fractional integrals on an increasing function. We apply our findings to estimate the error bounds of Hadamard-type inequalities. Our results are more comprehensive, since we obtain the results of the existing literatures as particular cases for certain parameter values. This research motivates researchers to apply this concept to other fractional operators.

Globally, there is an increase in a number of bone disorders including osteoarthritis (OA), osteomyelitis, bone cancer, and etc., which has led to a demand for bone tissue regeneration. In order to take use of the osteogenic potential of natural herbs, mesoporous bioactive glass nanoparticles (MBGNs) have the ability to deliver therapeutically active chemicals locally. MBGNs influence bioactivity and osteointegration of materials making them suitable for bone tissue engineering (BTE). In the present study, we developed Peganum Harmala (P. harmala) loaded MBGNs (PH-MBGNs) synthesized via modified Stöber process. The MBGNs were analyzed in terms of surface morphology, chemical make-up, amorphous nature, chemical interaction, pore size, and surface area before and after loading with P. harmala. A burst release of drug from PH-MBGNs was observed within 8 h immersion in phosphate buffer saline (PBS). PH-MBGNs effectively prevented Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) from spreading. Furthermore, PH-MBGNs developed a hydroxyapatite (HA) layer in the presence of simulated body fluid (SBF) after 21 days, which confirmed the in-vitro bioactivity of MBGNs. In conclusion, PH-MBGNs synthesized in this work are potential candidate for scaffolding or a constituent in the coatings for BTE applications.

The exponential increase in textual unstructured digital data creates significant demand for advanced and smart stemming systems. As a preprocessing stage, stemming is applied in various research fields such as information retrieval (IR), domain vocabulary analysis, and feature reduction in many natural language processing (NLP). Text stemming (TS), an important step, can significantly improve performance in such systems. Text-stemming methods developed till now could be better in their results and can produce errors of different types leading to degraded performance of the applications in which these are used. This work presents a systematic study with an in-depth review of selected stemming works published from 1968 to 2023. The work presents a multidimensional review of studied stemming algorithms i.e., methodology, data source, performance, and evaluation methods. For this study, we have chosen different stemmers, which can be categorized as 1) linguistic knowledge-based, 2) statistical, 3) corpus-based, 4) context-sensitive, and 5) hybrid stemmers. The study shows that linguistic knowledge-based stemming techniques were widely used for highly inflected languages (such as Arabic, Hindi, and Urdu) and have reported higher accuracy than other techniques. We compare and analyze the performance of various state-of-the-art TS approaches, including their issues and challenges, which are summarized as research gaps. This work also analyzes different NLP applications utilizing stemming methods. At the end, we list the future work directions for interested researchers.

Abstract In this article, we introduce a class of functions U ( p ) $\mathfrak{U}(\mathfrak{p})$ with integral representation defined over a measure space with σ-finite measure. The main purpose of this paper is to extend the Minkowski and related inequalities by considering general kernels. As a consequence of our general results, we connect our results with various variants for the fractional integrals operators. Such applications have wide use and importance in the field of applied sciences.

In this paper, we prove several new integral inequalities for the k-Hilfer fractional derivative operator, which is a fractional calculus operator. As a result, we have a whole new set of fractional integral inequalities. For the generalized fractional derivative, we also use Young's inequality to find new forms of inequalities. Such conclusions for this novel and generalized fractional derivative are extremely useful and valuable in the domains of differential equations and fractional differential calculus, both of which have a strong connections to real-world situations. These findings may stimulate additional research in a variety of fields of pure and applied sciences.

Abstract DC–DC converters has significant role in the applied power electronic systems, distributed power systems, computers, home appliances and communication equipment. A converter must remain within the specified range of operation. The main goal of this paper is to discuss the nonlinear behavior of forward converter and highlighted the application of the 0-1 test by applying it on the forward converter. As forward converter may contains electronic components, which cause instability in the system. So, it is necessary to understand its behavior when specifications of components are changed. To study chaotic behavior, 0-1 test will be applied on the forward converter, which is a novel technique outperform in unearthing the subtle chaotic behavior in deterministic dynamical systems. The forward converter goes from period-1, period-2, period-4 and finally become chaotic when the load resistance is varied. This variation in the behavior of the forward converter are analysis through 0-1 test for chaos. Moreover, time series plot, phase portrait and Bifurcation diagram for forward converter is also drawn for the validation of results obtained from 0-1 test. Test algorithm is applied via MATLAB and simulation of forward converter via MultiSim by varying its load resistance.

Abstract Background Cigarette smoking is one of the most preventable causes of morbidities and mortalities. Since 2005, the World Health Organization Framework Convention for Tobacco Control (WHO-FCTC) provides an efficient strategic plan for tobacco control across the world. Many countries in the world have successfully reduced the prevalence of cigarette smoking. However, in developing countries, the prevalence of cigarette smoking is mounting which signifies a need of prompt attention. This scoping review aims to explore the extent and nature of Smoking Cessation (SmC) interventions and associated factors in South Asian Region (SAR) by systematically reviewing available recently published and unpublished literature. Methods The Joanna Briggs Institute (JBI) framework frames the conduct of this scoping review. PubMed, EBSCO CINAHL Complete, Cochrane Library, ProQuest Dissertation and Theses, and local websites as well as other sources of grey literature were searched for relevant literature. In total, 573 literature sources were screened. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram, finally, 48 data sources were included for data extraction and analysis. We analyzed the extracted SmC interventions through the FCTC. Factors that affect smoking cessation interventions will be extracted through manual content analysis. Results Regarding FCTC recommended smoking cessation strategies (articles), most of the articles were either neglected or addressed in a discordant way by various anti-smoking groups in SAR. Key barriers that hamper the effectiveness of smoking cessation interventions included lack of awareness, poor implementation of anti-smoking laws, and socio-cultural acceptance of tobacco use. Conversely, increased levels of awareness, through different mediums, related to smoking harms and benefits of quitting, effective implementation of anti-smoking laws, smoking cessation trained healthcare professionals, support systems, and reluctance in the community to cigarette smoking were identified as facilitators to smoking cessation interventions. Conclusion The ignored or uncoordinated FCTC’s directions on smoking cessation strategies have resulted in continued increasing prevalence of cigarette smoking in developing countries, especially SAR. The findings of this review highlight the need for refocusing the smoking cessation strategies in SAR. Strengths The review was conducted by a team of expert comprising information specialists, and senior professors bringing rich experience in systematic and scoping reviews. Every effort was made to include all available literature sources addressing cigarette SmC and associated factors in SAR. The review findings signal the need and direction for more SmC efforts in SAR which may contribute to development of effective policies and guidelines for the control of smoking prevalence. Limitations Despite efforts, potentially relevant records may have been missed due to unpublished or inaccessible articles, unintended selection bias, or those published in local languages, etc. Moreover, the exclusion of literature on under 18 participants and mentally ill smokers may limit the generalizability of findings.

Breast tissue undergoes constant physiological changes in a woman’s life because of influence of endocrine hormones during and after reproductive life. These changes may present as pain, lumpiness or both in the breast. Breast lumps are feared for cancer. Thus, it is important for women with a breast lump to receive appropriate evaluation. Clinical breast examination is first step in evaluation of breast lump. The diagnostic sensitivity of clinical breast examination is high (98%) whereas its specificity is low, averaging 48%. Ultrasound is preferred in evaluation of radiologically dense breasts and in the study of breasts with augmentation mammoplasties. Micro-calcifications on mammography are considered to be important signs of breast cancer. X-ray mammography detects microcalcifications in 30–50% of breast cancers. FNAC is a cheap, cost effective and readily available routine diagnostic with a sensitivity ranging between 89% to 98% and specificity between 98% to 100% for palpable breast lumps. When combined together triple test achieves a higher sensitivity, specificity and diagnostic accuracy than any of the investigations taken alone. We conducted a prospective study to evaluate breast masses by clinical assessment, imaging and pathological examination. Results were compared with histopathology. We concluded that triple assessment in breast lumps gives superior results than any of its modalities taken alone.

Inguinal hernia repair is one of the commonest general surgical procedures performed worldwide. Laparoscopic repair is associated with faster recovery, less post operative pain and comparable rates of recurrence. Using the stapling devices increases post TAPP chronic groin pain. We conducted a prospective trial for laparoscopic TAPP inguinal hernia repair on 43 patients in which we did not fix the mesh. The primary purpose of this study was to examine the rate of recurrence and chronic groin pain in patients undergoing TAPP mesh hernia repair for inguinal hernia. We observed that our rates of recurrence and chronic groin pain are comparable to those described previously in the literature. We concluded that laparoscopic inguinal hernia repair by TAPP approach can be done with acceptable rates of recurrences and decreased rates of post operative chronic groin pain.

Laparoscopic cholecystectomy is a widely practiced procedure for symptomatic cholelithiasis. Haemostasis of cystic artery can be achieved with clips electrocautery and ultra modern vessel sealing energy devices. Bipolar electro coagulation of cystic artery is safe and a cost effective measure in developing countries. Our aim was to establish the feasibility of bipolar electrocautery in securing cystic artery. We conducted a prospective study on 120 patients in different age and sex groups. Correctable co morbidities were not a contraindication to inclusion criteria. Anatomical variations in size, origin and number of cystic artery were noted.

Abstract Background Perforation of Meckel Diverticulum (MD) is a rare cause of pneumoperitoneum in neonates. We hereby report six cases of perforation of MD in neonates, with addition of 53 cases from systematic review of the literature. A systematic review was performed using Mesh terms “Neonate, Meckel Diverticulum, Perforation, Pneumoperitoneum.” All reports of perforated MD in the English literature were identified. Details of our 6 cases were analyzed in similar fashion. Results A total of 3027 manuscripts were screened and 59 cases including 6 of our own were identified. The vast majority (78%) were female. Fifty patients (84.7%) presented in the newborn period. Half of the cases (52.5%) had associated anomalies and 13 neonates (22%) required oxygen supplementation including CPAP or ventilatory support before surgery. In 73% of the cases, a resection of gut was undertaken. Histopathological assessment in 44 cases (74.6%) revealed no ectopic gastric mucosa. Three cases demised prior to treatment. The outcome in the vast majority was excellent with 84.7% surviving and discharged well. Conclusion Perforated MD is an unusual cause of a pneumoperitoneum in the newborns. Diagnosis is established at laparotomy and it rare to find ectopic mucosa histopathologically. The overall outcome is excellent.

Force myography (FMG) represents a promising alternative to surface electromyography (EMG) in the context of controlling bio-robotic hands. In this study, we built upon our prior research by introducing a novel wearable armband based on FMG technology, which integrates force-sensitive resistor (FSR) sensors housed in newly designed casings. We evaluated the sensors’ characteristics, including their load–voltage relationship and signal stability during the execution of gestures over time. Two sensor arrangements were evaluated: arrangement A, featuring sensors spaced at 4.5 cm intervals, and arrangement B, with sensors distributed evenly along the forearm. The data collection involved six participants, including three individuals with trans-radial amputations, who performed nine upper limb gestures. The prediction performance was assessed using support vector machines (SVMs) and k-nearest neighbor (KNN) algorithms for both sensor arrangments. The results revealed that the developed sensor exhibited non-linear behavior, and its sensitivity varied with the applied force. Notably, arrangement B outperformed arrangement A in classifying the nine gestures, with an average accuracy of 95.4 ± 2.1% compared to arrangement A’s 91.3 ± 2.3%. The utilization of the arrangement B armband led to a substantial increase in the average prediction accuracy, demonstrating an improvement of up to 4.5%.

The phylum Chloroflexota (formerly Chloroflexi) encompasses metabolically diverse bacteria that often have high prevalence in terrestrial and aquatic habitats, some even with biotechnological application. However, there is substantial disagreement in public databases which lineage should be considered a member of the phylum and at what taxonomic level. Here, we addressed these issues through extensive phylogenomic analyses. The analyses were based on a collection of >5000 Chloroflexota genomes and metagenome-assembled genomes (MAGs) from public databases, novel environmental sites, as well as newly generated MAGs from publicly available sequence reads via an improved binning approach incorporating covariance information. Based on calculated relative evolutionary divergence, we propose that Candidatus Dormibacterota should be listed as a class (i.e., Ca. Dormibacteria) within Chloroflexota together with the classes Anaerolineae, Chloroflexia, Dehalococcoidia, Ktedonobacteria, Ca. Limnocylindria, Thermomicrobia, and two other classes containing only uncultured members. All other Chloroflexota lineages previously listed at the class rank appear to be rather orders or families in the Anaerolineae and Dehalococcoidia, which contain the vast majority of genomes and exhibited the strongest phylogenetic radiation within the phylum. Furthermore, the study suggests that a common ecophysiological capability of members of the phylum is to successfully cope with low energy fluxes.

Objectives: The present study describes the draft genome sequence of a novel Bacillus sp. strain SD-4 isolated from animal feed. The study aims to get a deeper insight into antimicrobial resistance and secondary metabolite biosynthetic gene clusters (BGCs) and the association between them. Methods: The strain SD-4 was preliminarily evaluated for antibacterial activities, motility, biofilm formation, and enterotoxin production using in vitro assays. The genome of strain SD-4 was sequenced using the Illumina HiSeq 2500 platform with paired-end reads. The reads were assembled and annotated using SPAdes and PGAP, respectively. The genome was further analysed using several bioinformatics tools, including TYGS, AntiSMASH, RAST, PlasmidFinder, VFDB, VirulenceFinder, CARD, PathogenFinder, MobileElement finder, IslandViewer, and CRISPRFinder. Results: In vitro assays showed that the strain is motile, synthesises biofilm, and produces an enterotoxin and antibacterial metabolites. The genome analysis revealed that the strain SD-4 carries antimicrobial resistance genes (ARGs), virulence factors, and beneficial secondary metabolite BGCs. Further genome analysis showed interesting genome architectures containing several mobile genetic elements, including two plasmid replicons (repUS22 and rep20), five prophages, and at least four genomic islands (GIs), including one Listeria pathogenicity island LIPI-1. Moreover, the strain SD-4 is identified as a putative human pathogen. Conclusion: The genome of strain SD-4 harbours several BGCs coding for biologically active metabolites. It also contains antimicrobial resistance genes and is identified as a potential human pathogen. These results can be used to better comprehend antibiotic resistance in environmental bacteria that are not influenced by human intervention.

Angiopoietin-like proteins (ANGPTL) constitute a family of eight proteins (1–8) which play a pivotal role in the regulation of various pathophysiological processes. The current study sought to identify high-risk, “non-synonymous, single-nucleotide polymorphisms” (nsSNPs) in both ANGPTL3 and ANGPTL8 to evaluate the role that these nsSNPs play in various types of cancer. We retrieved a total of 301 nsSNPs from various databases; 79 of these candidates constitute high-risk nsSNPs. Moreover, we identified eleven high-risk nsSNPs that cause various types of cancer: seven candidates for ANGPTL3 (L57H, F295L, L309F, K329M, R332L, S348C, and G409R) and four candidates for ANGPTL8 (P23L, R85W, R138S, and E148D). Protein–protein interaction analysis revealed a strong association of ANGPTL proteins with several tumor-suppressor proteins such as ITGB3, ITGAV, and RASSF5. ‘Gene-expression profiling interactive analysis’ (GEPIA) showed that expression of ANGPTL3 is significantly downregulated in five cancers: sarcoma (SARC); cholangio carcinoma (CHOL); kidney chromophobe carcinoma (KICH); kidney renal clear cell carcinoma (KIRC); and kidney renal papillary cell carcinoma (KIRP). GEPIA also showed that expression of ANGPTL8 remains downregulated in three cancers: CHOL; glioblastoma (GBM); and breast invasive carcinoma (BRCA). Survival rate analysis indicated that both upregulation and downregulation of ANGPTL3 and ANGPTL8 leads to low survival rates in various types of cancer. Overall, the current study revealed that both ANGPTL3 and ANGPTL8 constitute potential prognostic biomarkers for cancer; moreover, nsSNPs in these proteins might lead to the progression of cancer. However, further in vivo investigation will be helpful to validate the role of these proteins in the biology of cancer.

Alzheimer’s is a type of dementia that affects the affected person’s thinking, memory, and behavior. It is a multifactorial disease, developed by the breakdown of the neurotransmitter acetylcholine via acetylcholinesterase (AChE). The present study was designed to evaluate potential inhibitors of acetylcholinesterase that could be used as a therapeutic agent against Alzheimer’s disease (AD). For this course, synthetic compounds of the Schiff bases class of 2-mercaptobenzimidazole hydrazone derivatives (9–14) were determined to be potent acetylcholinesterase inhibitors with IC50 values varying between 37.64 ± 0.2 and 74.76 ± 0.3 μM. The kinetic studies showed that these are non-competitive inhibitors of AChE. Molecular docking studies revealed that all compounds accommodate well in the active site and are stabilized by hydrophobic interactions and hydrogen bonding. Molecular dynamics (MD) simulations of selected potent inhibitors confirm their stability in the active site of the enzyme. Moreover, all compounds showed antispasmodic and Ca2+ antagonistic activities. Among the selected compounds of 2-mercaptobenzimidazole hydrazone derivatives, compound 11 exhibited the highest activity on spontaneous and K+-induced contractions, followed by compound 13. Therefore, the Ca2+ antagonistic, AChE inhibition potential, and safety profile of these compounds in the human neutrophil viability assay make them potential drug candidates against AD in the future.

Abstract Background Neonatal gastric perforation (NGP) is a rare, serious, and life-threatening condition which needs early recognition with prompt intervention for better prognosis. Its etiology is not yet well established, but multiple speculations have been put forth for its etiopathogenesis. Few most considered are traumatic, spontaneous, or secondary to inflammatory process like necrotizing enterocolitis. This study describes the etiological and prognostic factors for patients with NGP in our experience at a single center. Results A total of 46 neonates were included. Male gender predominated with M:F being 1.7:1. Most (n=36) neonates presented within 10 days of life whereas 8 neonates presented within 15 days. At presentation, gas under diaphragm was the most common radiologic finding in 25 (54.3%) neonates. On exploratory laparotomy, it was found that greater curvature was involved in maximum number of cases (n=27), followed by lesser curvature and anterior and posterior walls of the stomach. Most of perforations were within 1–5 cm in size. Gastrorrhaphy was done in all cases, and in two cases, feeding jejunostomy was done along with repair for feeding purpose. Finally, spontaneous NGP was diagnosed in 30 (60.8%), and NEC patches on other parts of the intestine were seen in 11 patients. Postoperatively, 28 neonates developed complications in the form of sepsis (n=13), wound infection (n=10), and burst abdomen (n=5). Regarding clinical outcome, 27 (58.7%) were discharged from the hospital whereas 19 (39.3%) patients died. Conclusion Our results show that spontaneous NGP is most commonly associated with NEC in our population, usually affecting the greater curvature. We observed a high mortality rate; however, good ICU care may improve the survival.

In this article, we develop a new class of trapezium-type inequalities up to twice differentiable h-convex mappings for fractional integrals of Riemann-type. We conclude numerous existing results in literature from our general inequalities. Based on our consequences, we will obtain some quadrature formulas as applications.

This article is concerned to develop a novel generalized class of fractional impulsive delay differential equations. These equations are defined using newly discovered generalized conformable fractional operators which unify various previously-defined operators into a single form. The successive approximation method is employed and a sufficient criterion for the existence and uniqueness of the solution is developed. For the sake of illustration, three examples are provided at the end of the main results.

Glaucoma is characterized by increased intraocular pressure and damage to the optic nerve, which may result in irreversible blindness. The drastic effects of this disease can be avoided if it is detected at an early stage. However, the condition is frequently detected at an advanced stage in the elderly population. Therefore, early-stage detection may save patients from irreversible vision loss. The manual assessment of glaucoma by ophthalmologists includes various skill-oriented, costly, and time-consuming methods. Several techniques are in experimental stages to detect early-stage glaucoma, but a definite diagnostic technique remains elusive. We present an automatic method based on deep learning that can detect early-stage glaucoma with very high accuracy. The detection technique involves the identification of patterns from the retinal images that are often overlooked by clinicians. The proposed approach uses the gray channels of fundus images and applies the data augmentation technique to create a large dataset of versatile fundus images to train the convolutional neural network model. Using the ResNet-50 architecture, the proposed approach achieved excellent results for detecting glaucoma on the G1020, RIM-ONE, ORIGA, and DRISHTI-GS datasets. We obtained a detection accuracy of 98.48%, a sensitivity of 99.30%, a specificity of 96.52%, an AUC of 97%, and an F1-score of 98% by using the proposed model on the G1020 dataset. The proposed model may help clinicians to diagnose early-stage glaucoma with very high accuracy for timely interventions.

Using force myography (FMG) to monitor volumetric changes in limb muscles is a promising and effective alternative for controlling bio-robotic prosthetic devices. In recent years, there has been a focus on developing new methods to improve the performance of FMG technology in the control of bio-robotic devices. This study aimed to design and evaluate a novel low-density FMG (LD-FMG) armband for controlling upper limb prostheses. The study investigated the number of sensors and sampling rate for the newly developed LD-FMG band. The performance of the band was evaluated by detecting nine gestures of the hand, wrist, and forearm at varying elbow and shoulder positions. Six subjects, including both fit and amputated individuals, participated in this study and completed two experimental protocols: static and dynamic. The static protocol measured volumetric changes in forearm muscles at the fixed elbow and shoulder positions. In contrast, the dynamic protocol included continuous motion of the elbow and shoulder joints. The results showed that the number of sensors significantly impacts gesture prediction accuracy, with the best accuracy achieved on the 7-sensor FMG band arrangement. Compared to the number of sensors, the sampling rate had a lower influence on prediction accuracy. Additionally, variations in limb position greatly affect the classification accuracy of gestures. The static protocol shows an accuracy above 90% when considering nine gestures. Among dynamic results, shoulder movement shows the least classification error compared to elbow and elbow–shoulder (ES) movements.

Abstract The main objective of this paper is to establish some new Hermite–Hadamard type inequalities involving k-Riemann–Liouville fractional integrals. Using the convexity of differentiable functions some related inequalities have been proved, which have deep connection with some known results. At the end, some applications of the obtained results in error estimations of quadrature formulas are also considered.

Abstract In this paper we establish some new results on trapezium type inequalities of coordinated distance-disturbed ( ℓ 1 , h 1 ) $(\ell _{1},h_{1})$ – ( ℓ 2 , h 2 ) $(\ell _{2},h_{2})$ -convex functions of higher orders ( σ 1 , σ 2 ) $(\sigma _{1},\sigma _{2})$ by using the Katugampola ( k 1 , k 2 ) $(k_{1},k_{2})$ -fractional integrals. As special cases of our general results, we recapture some earlier proved results.

In this paper, we at first develop a generalized integral identity by associating Riemann-Liouville (RL) fractional integral of a function concerning another function. By using this identity estimates for various convexities are accomplish which are fractional integral inequalities. From our results, we obtained bounds of known fractional results which are discussed in detail. As applications of the derived results, we obtain the mid-point-type inequalities. These outcomes might be helpful in the investigation of the uniqueness of partial differential equations and fractional boundary value problems.

The US intervention in Afghanistan following the September 11 attacks brought about adverse socio-political and economic consequences for Pakistan. Pakistan’s decision to support the US intervention in Afghanistan turned some forces in the former FATA to militancy which resulted in hundreds of terrorist attacks in various parts of Pakistan. While Pakistan adopted various counter-terrorism strategies, the terrorist attack on Peshawar Army Public School on December 16, 2014, drove it to take up a proactive and comprehensive strategy. National Action Plan (NAP), adopted with a national consensus, was the manifestation of this strategy. The NAP for the most part aimed at stopping the activities of banned terrorist groups, bringing the madrasahs (religious seminaries) under an orderly system, countering the terrorist financing, and the trial of terrorists in the military courts. In practice, however, Pakistan turned more to the war model, with intensification and expansion of military operations, and least to the criminal justice model in the fight against terrorism. The then government provided a constitutional cover for counterterrorism military actions by adopting the 21st amendment on January 6, 2015. In consequence, the terrorist incidents have massively decreased but there is little evidence that the NAP has achieved a long-lasting success. This argument builds on the fact that Pakistan’s efforts to assume key reforms promised in the NAP, particularly about Madrassas and the Criminal Justice System CJS remain Lack luster. This paper emphasizes the importance of the CJS in fighting terrorism more effectively. It argues that Pakistan can achieve the counterterrorism objective of the National Action Plan on a sustainable basis only if it reforms and strengthens the current CJS as envisaged.

Image retrieval procedures locate interest points and consider the features as the visual property of an image in computer vision. These primitive features define visual attributes as local or global features for content based image retrieval. The visual attributes of an image, include spatial information, shape, texture, object and color, describe the image category. The present research contributes feature detector by performing non-max suppression after detecting edges and corners based on corner score and pixel derivation-based shapes on intensity-based interest points. Thereafter, interest point description applied on interest point features set by applying symmetric sampling to cascade matching produced by validating dense distributed receptive fields after estimating perifoveal receptive fields. Spatial color-based features vector are fused with retinal and color-based feature vector extracted after applying L2 normalization on spatially arranged color image. Dimensions are reduced by applying PCA on massive feature vectors produced after symmetric sampling and transmitted to bag-of-word in fused form for indexing and retrieval of images. Extensive experiments are performed on well-known benchmarks corel-1000, core-10000, caltech-101, image net, alot, coil, ftvl, 102-flowers and 17-flowers. In order to measure the competitiveness, we designed a comparison of proposed method with seven descriptors and detectors RGBLBP, LBP, surf, sift, DoG, HoG and MSER. The proposed method reports remarkable AP, AR, ARP, ARR, P&R, mAP and mAR rates in many categories of image datasets.

Due to the sheer global energy crisis, concerns about fuel exhaustion, electricity shortages, and global warming are becoming increasingly severe. Solar and wind energy, which are clean and renewable, provide solutions to these problems through distributed generators. Microgrids, as an essential interface to connect the power produced by renewable energy resources-based distributed generators to the power system, have become a research hotspot. Modern research in the field of microgrids has focused on the integration of microgrid technology at the load level. Due to the complexity of protection and control of multiple interconnected distributed generators, the traditional power grids are now outmoded. Microgrids are feasible alternatives to the conventional grid since they provide an integrating platform for micro-resources-based distributed generators, storage equipment, loads, and voltage source converters at the user end, all within a compact footprint. A microgrid can be architected to function either in grid-connected or standalone mode, depending upon the generation, integration potential to the main grid, and consumers’ requirements. The amalgamation of distributed energy resources-based microgrids to the conventional power system is giving rise to a new power framework. Nevertheless, the grids’ control, protection, operational stability, and reliability are major concerns. There has yet to be an effective real-time implementation and commercialization of micro-grids. This review article summarizes various concerns associated with microgrids’ technical and economic aspects and challenges, power flow controllers, microgrids’ role in smart grid development, main flaws, and future perspectives.

An analytical method was developed and validated for the determination of fludioxonil in rice samples. Rice samples for the study were collected from different regions of Pakistan. The method was based on safe and cost-effective extraction of fludioxonil from rice grains using acetone and methanol (1:1), efficient clean-up through homogenous mixture of acidic aluminium (12 g) and activated charcoal (1 g) followed by liquid chromatographic determination with UV detection. Quantification was performed on Prospher Star C18 (5 µm, 25 × 0.46 cm) column maintaining the temperature 40 °C and detector wavelength 212 nm using mobile phase 50:50 v/v methanol-water (pH 3.3) employing flow rate 1.0 mL min−1 and 20 µL injection volume. The method showed linearity (0.01–16 mg−1) with correlation coefficient greater than 0.998. The proposed method was precisely validated for rice sample of all regions, showing recoveries higher than 98%. Rice samples collected from Badin, Multan, Hyderabad, Lahore, Jahania and Sarghoda was found to have fludioxonil residues 0.046, 0.045, 0.043, 0.040, 0.024 and 0.016 mg Kg−1 respectively, all below the maximum residual limit (MRL) level i.e. 0.05 mg Kg−1 whereas samples collected from Khanewal and Gularchi showed fludioxonil residue above MRL i.e. 0.065 and 0.058 mg Kg−1 respectively. However, fludioxonil residues was not detected in rice sample collected from city Makhdumpur.

Polymer-based nanocarriers require extensive knowledge of their chemistries to learn functionalization strategies and understand the nature of interactions that they establish with biological entities. In this research, the poly (β-amino ester) (PβAE-447) was synthesized and characterized, aimed to identify the influence of some key parameters in the formulation process. Initially; PβAE-447 was characterized for aqueous solubility, swelling capacity, proton buffering ability, and cytotoxicity study before nanoparticles formulation. Interestingly, the polymer-supported higher cell viability than the Polyethylenimine (PEI) at 100 μg/ml. PβAE-447 complexed with GFP encoded plasmid DNA (pGFP) generated nanocarriers of 184 nm hydrodynamic radius (+7.42 mV Zeta potential) for cell transfection. Transfection assays performed with PEGylated and lyophilized PβAE-447/pDNA complexes on HEK-293, BEAS-2B, and A549 cell lines showed better transfection than PEI. The outcomes toward A549 cells (above 66%) showed the highest transfection efficiency compared to the other cell lines. Altogether, these results suggested that characterizing physicochemical properties pave the way to design a new generation of PβAE-447 for gene delivery.

Abstract The primary objective of this present paper is to establish certain new weighted fractional Pólya–Szegö and Chebyshev type integral inequalities by employing the generalized weighted fractional integral involving another function Ψ in the kernel. The inequalities presented in this paper cover some new inequalities involving all other type weighted fractional integrals by applying certain conditions on ω ( θ ) $\omega (\theta )$ and Ψ ( θ ) $\Psi (\theta )$ . Also, the Pólya–Szegö and Chebyshev type integral inequalities for all other type fractional integrals, such as the Katugampola fractional integrals, generalized Riemann–Liouville fractional integral, conformable fractional integral, and Hadamard fractional integral, are the special cases of our main results with certain choices of ω ( θ ) $\omega (\theta )$ and Ψ ( θ ) $\Psi (\theta )$ . Additionally, examples of constructing bounded functions are also presented in the paper.

Abstract In this paper, we establish some new integral inequalities involving general kernels. We obtain the related broad range of fractional integral inequalities. Also, we apply the Young inequality to find new forms of inequalities for generalized kernels. These new and motivated results generalize the results for fractional integrals such that fractional integral of a function with respect to an increasing function, Riemann–Lioville fractional integrals, Erdélyi–Kober fractional integrals, Hadamard fractional integrals, generalized factional integral integrals in addition to the corresponding k-fractional integrals.

Abstract In this paper, we establish certain generalized fractional integral inequalities of mean and trapezoid type for ( s + 1 ) $(s+1)$ -convex functions involving the ( k , s ) $(k,s)$ -Riemann–Liouville integrals. Moreover, we develop such integral inequalities for h-convex functions involving the k-conformable fractional integrals. The legitimacy of the derived results is demonstrated by plotting graphs. As applications of the derived inequalities, we obtain the classical Hermite–Hadamard and trapezoid inequalities.

Abstract We introduce new operators, the so-called left and right generalized conformable fractional integral operators. By using these operators we establish new Hermite–Hadamard inequalities for s-convex functions and products of two s-convex functions in the second sense. Also, we obtain two interesting identities for a differentiable function involving a generalized conformable fractional integral operator. By applying these identities we give Hermite–Hadamard and midpoint-type integral inequalities for s-convex functions. Different special cases have been identified and some known results are recovered from our general results. These results may motivate further research in different areas of pure and applied sciences.

Automated brain segmentation is an active research domain due to the association of various neurological disorders with different regions of the brain, to help medical professionals in prognostics and diagnostics. Traditional techniques like atlas-based and pattern recognition-based methods led to the development of various tools for automated brain segmentation. Recently, deep learning techniques are outperforming classical state-of-the-art methods and gradually becoming more mature. Consequently, deep learning has been extensively employed as a tool for precise segmentation of brain regions because of its capability to learn the intricate features of the high-dimensional data. In this work, a network for the segmentation of multiple brain regions has been proposed that is based on 3D convolutional neural networks and utilizes residual learning and dilated convolution operations to efficiently learn the end-to-end mapping from MRI volumes to the voxel-level brain segments. This research is focused on the segmentation of up to nine brain regions including cerebrospinal fluid, white matter and gray matter as well as their sub-regions. Mean dice scores of 0.879 and 0.914 have been achieved for three and nine brain regions, respectively by using the data from three different sources. Comparative analysis shows that our network gives better dice scores for most of the brain regions than state-of-the-artwork. Moreover, the mean dice score of 0.903, obtained for eight brain regions segmentation with MRBrains18 dataset, is better than 0.876 which was achieved in the previous work.

Despite their remarkable biosynthetic potential, Bacillus subtilis have been widely overlooked. However, their capability to withstand harsh conditions (extreme temperature, Ultraviolet (UV) and γ-radiation, and dehydration) and the promiscuous metabolites they synthesize have created increased commercial interest in them as a therapeutic agent, a food preservative, and a plant-pathogen control agent. Nevertheless, the commercial-scale availability of these metabolites is constrained due to challenges in their accessibility via synthesis and low fermentation yields. In the context of this rising in interest, we comprehensively visualized the antimicrobial peptides produced by B. subtilis and highlighted their prospective applications in various industries. Moreover, we proposed and classified these metabolites produced by the B. subtilis group based on their biosynthetic pathways and chemical structures. The biosynthetic pathway, bioactivity, and chemical structure are discussed in detail for each class. We believe that this review will spark a renewed interest in the often disregarded B. subtilis and its remarkable biosynthetic capabilities.

The enormous demand of energy and depletion of fossil fuels has attracted an ample interest of scientist and researchers to develop materials with excellent electrochemical properties. Among these materials carbon based materials like carbon nanotubes (CNTs), graphene (GO and rGO), activated carbon (AC), and conducting polymers (CPs) have gained wide attention due to their remarkable thermal, electrical and mechanical properties. On this account, the present review article summarizes the history of ESDs and the basic function of various types of ESDs. Further, the various nanomaterials used in energy storage devices for the past few years have also been discussed in detail. In addition, the future trend in the development of highly efficient, cost-effective and renewable energy storage materials have also been highlighted. Keywords: Batteries, Capacitor, Conducting polymer, Graphene, Energy devices

Following the US exit from Afghanistan, the debate revolves around why US intervention in Afghanistan, the longest and one of the most expensive in its history, has failed in defeating the Taliban and realising a durable state-building. The debate considers endogenous factors that explore US and Taliban strategies and exogenous factors that underline the role of regional and extra-regional actors in determining the outcome of the Afghan conflict. This paper, therefore, focuses on faults and inconsistencies within and across US strategies in Afghanistan, i.e., the use of military force, political settlement, and state-building. It also examines US strategies vis-à-vis conflict in Afghanistan under four US administrations – from Bush to Biden – to ascertain why these strategies proved ineffective. These strategies have been analysed by following the conceptual framework of Game Theory. The paper argues that US strategies for entering Afghanistan were detached from the ground realities, which was the critical factor for its failure to achieve the desired outcome of the conflict. Bibliography Entry Shad, Muhammad Riaz, and Sajid Iqbal. 2021. "From Intervention to Exit: An Analysis of Post-9/11 US Strategies in Afghanistan." Margalla Papers 25 (2): 23-34.

Energy and environmental concepts have been extensively studied in the past. However, these studies often lacked integrated analysis of energy, monetary, public, and ecological aspects to assess energy and environmental issues. This article provides analyzation of the G7 nations’ qualitative, social, cultural, and health achievement in the energy poverty indexes. These include the energy economics and climate change of energy poverty, by using DEA like a composite indicator. The G7 countries’ combined energy consumption is equal to 34% of the world’s total, whereas the GDP is 50% of the global total. As a result, this article develops a comprehensive series of energy, financial, societal, and environmental indicators that are up to date. Such indicators are utilized to assess energy financial, societal, and EPI using a mathematical composite indicator. Canada has the greatest EPII score, indicating that it can deal better than the other G7 countries with energy independence, productivity expansion, and social impact, and France’s and Italy’s the second tier. While Japan has a 0.50 EPI grade and the United States will have the lowest, the G7 countries are growing faster. Finally, we propose a policy framework for enhancing the research area. The energy, societal, and EPI were created by combining these elements. In terms of energy independence, economic growth, and sustainability practices, Canada beats the other G7 countries according to the data. France and Italy are in the 2nd and 3rd places, respectively. Despite having a higher level of economic development than the G7 countries, Japan has a 0.50 Environmental Performance Index rating, whereas the United States has a minimum average Environmental Performance Index rating. Finally, in order to improve the study’s subject, we propose a policy framework.

Rotary Inverted Pendulum (RIP) mimics the behavior of many practical control systems like crane mechanism, segway, unicycle robot, traction control in vehicles, rocket stabilization, and launching. RIP is a fourth-order nonlinear open-loop unstable dynamical system and is widely used for testing the effectiveness of the newly developed control algorithms. In this paper, a Hybrid Control Scheme (HCS) based on energy balance and fuzzy logic controllers is proposed to implement the swing up and stabilization control of RIP. In the proposed control scheme, the fuzzy logic-based state feedback gains are dynamically tuned in real-time by minimizing the absolute error between the desired and actual states to get robust control performance. The proposed HCS is also compared with the conventional Linear Quadratic Controller (LQR) for this application. The comparative results show that the proposed fuzzy logic-based hybrid control scheme gives the optimal control performance in terms of achieving satisfactory transient, steady-state, and robust responses from a given RIP system, as compared to the conventional LQR based control scheme. The proposed control scheme is also relatively less complex with a low computational cost and provides desired response characteristics as compared to the existing ones in the literature.

Due to high biocompatibility, bioactivity, and natural occurrence in bones and teeth, synthetic calcium hydroxyapatite (CaHAp) is a widely applied biomaterial in tissue engineering, including orthopedic surgery and dentistry. However, the brittle nature and low strength reduce its durability, which can be improved by doping metal ions. Rubidium (Rb) is an essential trace element that works as an antibacterial agent in the human body; therefore, it can be doped in synthetic Ca-HAp to promote its durability. In this work, Rb-doped calcium hydroxyapatite (Rb-HAp) nanoparticles are synthesized by the coprecipitation method at low temperatures. Phase purity, crystallinity, doping level, and mechanical properties are investigated by X-ray diffraction (XRD), inductively coupled plasma optical emission spectroscopy (ICP-OES), and micro-hardness tester. It is observed that a minute quantity (≈ 0.02%) of Rb remained in the apatite structure when 5% of Rb+ is doped via in situ method. Moreover, small dopant concentration did not affect the crystal structure and the tensile strength of HAp.

Introduction Unfortunately, like many other health risks, smoking rate has been on the rise in developing countries. Half of current smokers in the world reside in only three countries of Asia that include India. Many smoking cessation interventions that were developed and successfully implemented in the context of developed countries have not been equally successful in South Asia. Hence, there is a dire need of culturally relevant smoking cessation interventions. We propose a scoping review with objectives to explore the extent and nature of interventions for smoking cessation and its associated factors in South Asian Region by systematically reviewing the available published and unpublished literature.Methods and analysis The review has been registered in Joanna Briggs Institute (JBI) systematic reviews register and details are given in the Methodology section. The updated framework of JBI for scoping review methodology will be used as guide for conduct of this scoping review. Electronic databases (PubMed, CINAHL plus, Proquest Theses and Dissertations, EBSCO Dentistry and Oral Sciences, and Wiley Cochrane Library), reference lists of selected studies and grey literature will be considered for inclusion in this review. The literature search is anticipated to be carried out in December–January 2020. Initially, two reviewers in consultation with a librarian will develop search syntax followed by search from the selected sources. Consequently, the reviewers will screen all the titles, abstracts and full articles to establish relevance of each study for inclusion. Factors associated with smoking cessation will be coded and categorised applying qualitative content analysis, while interventions extracted from the literature will be described with the stated level of effectiveness.