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Background: Medical students are confronted with substantial academic and psychological stressors during their education. Studies report that examination stress can have a noteworthy effect on the leukocyte count of students. This study aimed to evaluate the physiological effects of examination stress on the total and differential leucocyte cell count in medical students at Peoples University of Medical and Health Sciences for Women, Nawabshah. Methods: A cross-sectional comparative study was conducted from April to October 2019, with 110 MBBS students, divided into two groups of 55 students using a non-probability randomized sampling technique with first-year and second-year female students, whereas hypertensive, diabetic, and with any psychiatric disease were excluded. Blood samples were taken before and during the examination. Data were analyzed by SPSS version 23. All the continuous variables were analyzed by the t-test for Mean±S.D while all the numerical variables were analyzed by Student’s t-test. Results: Pre-exam complete blood count (CBC) test reports of first-year students showed Neutrophils, Lymphocytes, Eosinophil, and Monocytes cell counts of 69.2182, 28.5455, 1.61, 1.2545 cell /microliter whereas complete blood count during exams showed 69.909, 27.9636, 1.41and 1.2000 cells/ microliter. In the second-year student, complete blood count before and during the exam showed Neutrophils 66.5273 to 64.0182, Lymphocytes 31.236 to 30.036, Eosinophil 1.92 to 1.76, and Monocytes 1.473 to 1.364 cells/microliter, the decreased values showing that there is an influence of exam stress on white blood cells. Conclusion: Exams in medical schools can be stressful enough to induce a substantial decrease in blood cell parameters among medical students.

This study investigates the influence of Withania somnifera root powder (WSRP) on different aspects of common carp (Cyprinus carpio), including growth, hematobiochemical parameters, antioxidant status, nonspecific immune response, and resilience to bacterial infections. Over a 60-day period, 180 common carp fingerlings (11.73 ± 0.52 g) were subjected to diets supplemented with increasing WSRP levels (0 (control), 1% (WSRP1), 2.5% (WSRP2.5), and 4% (WSRP4)). Nonspecific immune parameters were evaluated using serum samples collected at intervals of 0, 20, 40, and 60 days. After the feeding trial, the fish underwent experimental challenge with Aeromonas hydrophila, and relative percentage survival (RPS) was monitored for 14 days. The findings revealed a considerable (p 0.05) in serum glucose and cortisol levels compared to other groups. In conclusion, WSRP proves valuable for enhancing growth, blood parameters, antioxidant balance, immune response, and infection resistance in common carp, especially at 2.5%–4% dietary supplementation levels. In the future, it will be crucial to study the long-term effects of WSRP supplementation on fish health, as well as its potential for large-scale aquaculture and economic viability in the aquafeed industry.

Abstract Date palm is an important domestic cash crop in most countries. Sudden Decline Syndrome (SDS) causes a huge loss to the crop both in quality and quantity. The literature reports the significance of early detection of disease towards preventive measures to improve the quality of the crop. The number of prevailing detection methods limits to consideration of a certain aspect of disease identification. This study proposes a new hybrid fuzzy fast multi-Otsu K-Means (FFMKO) algorithm integrating the date palm image enhancement, robust thresholding, and optimal clustering for significant disease identification. The algorithm adopts a multi-operator image resizing cost function based on image energy and the dominant color descriptor, the adaptive Fuzzy noise filter, and Otsu image thresholding combined with K-Means clustering enhancements. Besides, we validate the process with histogram equalization and threshold transformation towards enhanced color feature extraction of date palm images. The algorithm authenticates findings on a local dataset of 3293 date palm images and, on a benchmarked data set as well. It achieves an accuracy of 94.175% for successful detection of SDS that outperforms the existing similar algorithms. The impactful findings of this study assure the fast and authentic detection of the disease at an earlier stage to uplift the quality and quantity of the date palm and boost the agriculture-based economy.

Madam, Safety, cost-effectiveness, efficiency and equity are all components of quality healthcare. Key factors determining quality are’ and their families’ satisfactions and better disease outcomes.1 Doctors, paramedics, pharmacists, laboratory technicians, administrative staff, pharmaceutical companies, government agencies and policymakers are the caregivers who have an essential direct or indirect role in providing, sustaining and improving health care.1 A population's health is crucial to a state's stability and growth. Quality in healthcare has been a subject of discussion across the globe for decades, with developed nations contributing the majority of its measures and recommendations6. In contrast it is still battling to fully establish and function in emerging nations like Pakistan. The health system in Pakistan comprises primary, secondary and tertiary health centres. The latter are found in a few urban cities and are run by both the public and private sectors. Private bodies include profit as well as welfare-based organizations.2,3 According to the WHO, on average, there are 6.3 hospital beds per 10,000 population in Pakistan, which is below its recommendation and much less compared to other developing nations.2 Majority of the population reside in rural areas and thus their option in various illnesses is primary or secondary health unit.3 The major drawback in such centres is lack of attendance by doctors and paramedical staff, lack of competent clinician or general practitioner along with absence of equipment, state-of-the-art laboratory and latest treatment options, all contributing to delays in diagnosis and management.4,5 There is also a lack of patient registry, long-term follow-ups, appropriate and timely referrals to higher health care centre and disease discussion between clinicians.3 Due to such weakened basic units, many patients directly visit an urbanized tertiary health center, which is a major cause of overcrowding of our hospitals. Some break-through policies which could address this dilemma is giving incentives to the assigned staff, providing commute in case of long travels, improving the infrastructure and facilities within the centers, installation of biometrics and having regular audit of attendance, number of patients treated and medications provided. Conducting education seminars regarding work ethics would also contribute towards a professional working environment leading to better patient outcomes.3,4 Creating awareness regarding the responsibility and crucial role of general practitioners in primary and secondary health units along with recognition of their importance, would also help in diverting medical community towards opting for such roles.6 ---Continue

Background: Hereditary spherocytosis (HS) is characterized by spherocytes on the peripheral smear and heterogeneous clinical presentation (mild, moderate, moderate/severe, and severe) depending upon the severity of hemolytic anemia, jaundice, and splenomegaly. The underlying cause is defects in various red blood cell membrane proteins due to pathogenic mutations. Genotype-phenotype correlation is known. Clinical Description: We report a consanguineous family with a healthy daughter, multiple pregnancy losses due to fetal hydrops, and the current daughter. She was diagnosed with fetal anemia at 22 weeks gestation, developed fetal hydrops, was born premature and developed respiratory distress, severe anemia, severe jaundice, and postnatal hemolysis. Management: The case was managed since intrauterine life till date by multispecialty coordination. Intrauterine transfusions were given during pregnancy. In the neonatal period, she received surfactant for respiratory distress syndrome, double volume exchange transfusion and phototherapy for the jaundice, and repeated blood transfusions for the hemolytic anemia, that is still continuing. Rational and sequential investigations were planned and a systematic approach used. She was diagnosed with severe HS due to a homozygous likely pathogenic variant in the SPTA1 gene (affecting formation of spectrin), and heterozygous variant of uncertain significance in the ANK1 gene (that encodes ankyrin). At 3 years she has transfusion dependent hemolytic anemia, moderate splenomegaly, and age appropriate growth and development. Conclusions: HS is a rare but manageable (albeit challenging) cause of nonimmune hydrops fetalis. Genetic diagnosis allows precise management and family counselling.

The biofloc technology system (BFT) is considered to be one of the sustainable aquaculture systems, which is based on the principle of nutrient recycling with the addition of a carbon source to give dominance to heterotrophic microorganisms. The objective of this study was to evaluate the effect of sugar cane molasses and tapioca flour as carbon sources on the water quality, growth, hematology, immune status, and non-specific antioxidant status of Oreochromis juveniles. Methodologically, the experiment was carried out for 10 weeks on 225 juvenile Nile tilapia with initial body weights of 47.0 ± 1.3 g that were randomly distributed in 09 tanks (1000 L) with a stocking density of 25 tilapias per tank; the treatments were: BFT + SM (S molasses), BFT + TF tapioca flour (TF), and a control with no carbon source added. The control group was fed 100% feed, while the BFT experimental groups were fed microbial flocs along with 75% feed. The results revealed that the water quality parameters were affected by the carbon sources, but were adequate for normal fish welfare, and the biofloc volume was higher (28.94) with the TF carbon source. The growth performance, such as weight gain (98.61), survival (99.01), and improved feed conversion ratio (FCR) (1.69), was recorded in BFT + TF. Significant improvements in WBCs, HCT, HB, lymphocytes, plasma proteins, albumin, and non-specific immune factors (lysozyme activity, immunoglobulins levels, and ACH50) were observed in biofloc-reared fish with tapioca flour as the carbon source compared to the control and sugarcane molasses groups. Moreover, significant increases in catalase (CAT) and superoxide dismutase (SOD) were found in the biofloc-reared fish with different carbon sources. In conclusion, the use of BFT + TF was found to affect improving the water quality, growth, hematology, immunity, and antioxidant status of juvenile Tilapia.

Objectives: The study aimed to evaluate the impact of antenatal exposure of magnesium sulfate (MgSO4) on short- and long-term outcomes in preterm neonates born less than 32 weeks gestation. Methods: Single-center retrospective cohort study of 229 neonates born between 24 and 32 weeks gestation was conducted from January 2018 through December 2018 in a level III neonatal care unit in Kuwait. Antenatal MgSO4 exposure was collected from the medical records, and the indication was for neuroprotection effect. Brain MRI was done on 212 neonates (median gestational age 36 weeks), and brain injury was assessed using the Miller’s score. Neurodevelopmental outcome was assessed by Bayley-III scales of infant development at 36 months corrected age (N = 146). The association of exposure to MgSO4 with brain injury and neurodevelopmental outcomes was examined using multivariable regression analysis adjusting for gestational age at MRI and variables with p value

Career selection is one of the most important decisions in everyone's life. Being a student it's quite difficult to find the right career as the world is moving so fast and the competition level is too high so it is tough to choose the right job for anyone. According to the Council of Scientific and Industrial Research (CSIR) survey report, 40% of students are a bit confused about their career options. The productivity of human resources may reduce if someone chooses the wrong career. Therefore, we need an intelligent system that chooses your career based on a person's personality type. This study creates a personality profile of the person and suggests their best careers list according to their personality type after analysing the text written by the user such as a blog post, essay, or tweet. The main purpose of this project is to work on the text classification method, pre- processing of that dataset and convert it into main features and then train the model on a best-performed classification model. After applying various feature vector combinations and machine learning models that are detailed in this work, accuracies up to 93% were achieved.

The emergence of coronavirus disease 2019 (COVID-19) pandemic in Wuhan city, China at the end of 2019 made it urgent to identify the origin of the causal pathogen and its molecular evolution, to appropriately design an effective vaccine. This study analyzes the evolutionary background of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or SARS-2) in accordance with its close relative SARS-CoV (SARS-1), which was emerged in 2002. A comparative genomic and proteomic study was conducted on SARS-2, SARS-1, and Middle East respiratory syndrome coronavirus (MERS), which was emerged in 2012. In silico analysis inferred the genetic variability among the tested viruses. The SARS-1 genome harbored 11 genes encoding 12 proteins, while SARS-2 genome contained only 10 genes encoding for 10 proteins. MERS genome contained 11 genes encoding 11 proteins. The analysis also revealed a slight variation in the whole genome size of SARS-2 comparing to its siblings resulting from sequential insertions and deletions (indels) throughout the viral genome particularly ORF1AB, spike, ORF10 and ORF8. The effective indels were observed in the gene encoding the spike protein that is responsible for viral attachment to the angiotensin-converting enzyme 2 (ACE2) cell receptor and initiating infection. These indels are responsible for the newly emerging COVID-19 variants αCoV, βCoV, γCoV and δCoV. Nowadays, few effective COVID-19 vaccines developed based on spike (S) glycoprotein were approved and become available worldwide. Currently available vaccines can relatively prevent the spread of COVID-19 and suppress the disease. The traditional (killed or attenuated virus vaccine and antibody-based vaccine) and innovated vaccine production technologies (RNA- and DNA-based vaccines and viral vectors) are summarized in this review. We finally highlight the most common questions related to COVID-19 disease and the benefits of getting vaccinated.

The selection of a suitable job applicant from the pool of thousands applications is often daunting job for an employer. The categorization of job applications submitted in form of Resumes against available vacancy(s) takes significant time and efforts of an employer. Thus, Resume Classification System (RCS) using the Natural Language Processing (NLP) and Machine Learning (ML) techniques could automate this tedious process. Moreover, the automation of this process can significantly expedite and transparent the applicants’ screening process with mere human involvement. This experimental study presents an automated NLP and ML-based RCS that classifies the Resumes according to job categories with performance guarantees. This study employs various ML algorithms and NLP techniques to measure the accuracy of RCS and proposes a solution with better accuracy and reliability in different settings. To demonstrate the significance of NLP and ML techniques for RCS, the extracted features were evaluated on nine ML classification models namely Support Vector Machine - SVM (Linear, SGD, SVC and NuSVC), Naïve Bayes (Bernoulli, Multinomial and Gaussian), K-Nearest Neighbor (KNN), and Logistic Regression (LR). The Term-Frequency-Inverse-Document-Frequency (TF-IDF) feature representation scheme was proved suitable for RCS. The developed models were evaluated using the Confusion Matrix, F-Score, Recall, Precision, and overall Accuracy. The experimental results indicate that using the One-Vs-Rest-Classification strategy for this multi-class Resume classification task, the SVM class of Machine Learning classifiers performed better on the study dataset of over nine hundred sixty plus parsed resumes with more than 96% accuracy. The promising results suggest that NLP and ML techniques employed in this study could be used for developing an efficient RCS.

Background: Drought stress at different growth stages significantly alters growth, yield, and quality traits of wheat. However, great variability exists among genotypes regarding their response to drought stress. Therefore, determining the impacts of drought stress on yield and quality traits would help to select the superior genotypes. Methods: This study investigated the effects of drought stress on wheat grain yield, chlorophyll, and protein contents. Fourteen (14) recently developed elite bread wheat (Triticum aestivum L.) genotypes were used in this study for evaluation under irrigated (full irrigation) and drought conditions (half of normal irrigation). The data relating to growth, yield and protein contents were recorded. Results: Significant differences (P ≤ 0.01) were noted among genotypes for all recorded traits. Drought stress significantly reduced the days to 50 % heading, days to 50 % maturity, grain filling, plant height (cm), number of spikes per m2, chlorophyll index (SPAD), peduncle length (cm), number of grains spike-1, thousand grain weight (g) and grain yield (kg ha−1). However, protein contents were increased under drought stress. Correlation analysis showed significant positive association of grain yield with thousand grain weight, number of spikes per m2, spike length, chlorophyll index, grain filling period and number of grains spike-1 under both irrigated and drought stress conditions. The protein contents expressed positive and negative relationship with yield under drought stress and irrigated conditions, respectively. Bioplot analysis revealed that genotype ‘V-19618′ and ‘V-19600′ proved superior under drought conditions regarding grain yield and related traits, while genotype ‘V-19574′ proved better under both irrigated and drought conditions. Conclusions: These identified genotypes, i.e., ‘V-19618′ and ‘V-19600′ can be utilized in future wheat breeding programs to induce desirable characters for producing drought tolerant wheat genotypes.

Machine learning with its high precision algorithms, Precision agriculture (PA) is a new emerging concept nowadays. Many researchers have worked on the quality and quantity of PA by using sensors, networking, machine learning (ML) techniques, and big data. However, there has been no attempt to work on trends of artificial intelligence (AI) techniques, dataset and crop type on precision agriculture using internet of things (IoT). This research aims to systematically analyze the domains of AI techniques and datasets that have been used in IoT based prediction in the area of PA. A systematic literature review is performed on AI based techniques and datasets for crop management, weather, irrigation, plant, soil and pest prediction. We took the papers on precision agriculture published in the last six years (2013-2019). We considered 42 primary studies related to the research objectives. After critical analysis of the studies, we found that crop management; soil and temperature areas of PA have been commonly used with the help of IoT devices and AI techniques. Moreover, different artificial intelligence techniques like ANN, CNN, SVM, Decision Tree, RF, etc. have been utilized in different fields of Precision agriculture. Image processing with supervised and unsupervised learning practice for prediction and monitoring the PA are also used. In addition, most of the studies are forfaiting sensory dataset to measure different properties of soil, weather, irrigation and crop. To this end, at the end, we provide future directions for researchers and guidelines for practitioners based on the findings of this review

This paper offers a new indulgence to the present literature by integrating the role of fiscal decentralization (FD) in affecting ecological footprint (EF). So, this study considered the effect of FD on EF in the existence of energy consumption (EC), technological innovation (TI), gross domestic product (GDP), and trade openness (TOP) from 1990 to 2018 in Pakistan. We employ econometric methods like Bayer & Hanck cointegration, fully modified ordinary least squares, dynamic ordinary least squares, and canonical cointegration regression for empirical analysis. Moreover, the frequency domain causality test is used to conclude the causal impact of FD, EC, TI, GDP, and TOP on EF. The regression results disclose that EC, GDP, and TOP boost EF in Pakistan; however, FD and TI promote the sustainability of the environment by reducing EF. Besides, the frequency causality outcomes indicate that FD, EC, TI, GDP, and TOP have insinuations for EF in the long term. As a policy recommendation, this research suggests that Pakistan could successfully integrate strategies to increase ecological quality by allowing the lower level of government to utilize eco-friendly technological innovations.

The pomfret fish, particularly the black pomfret (Parastromateus niger), serves as a significant economic resource in South Asia, particularly in the coastal regions of Balochistan, Pakistan. This study investigates various biological parameters of Parastromateus niger collected from the Gaddani coastal area of Pakistan, focusing on length-weight relationships, gut fullness, and population demographics. A total of 117 fish specimens were collected, with females dominating the samples. Length and weight data were analyzed separately for males and females, with statistical calculations revealing strong correlations (r2 values ranging from 0.918 to 0.985) between length and weight for both sexes. Gut fullness was categorized into five levels, with the highest percentage observed during July, suggesting potential breeding activity during this period. The zooplanktons were identified as primary dietary components of Parastromateus niger. The study also highlights the importance of regulatory measures to sustainably manage fish populations, especially during breeding seasons, and calls for further research into the intensive culturing and feeding regimes of black pomfret to enhance its production. Overall, these findings contribute to a better understanding of the biological characteristics and potential for aquaculture development of Parastromateus niger in the region. [ABSTRACT FROM AUTHOR]

BackgroundIntravascular imaging has been used to assess the morphology of lesions causing an acute coronary syndrome (ACS) in native vessels (NV) and identify differences between plaques that ruptured (PR) and caused an event and those that ruptured without clinical manifestations. However, there is no data about the morphological and physiological characteristics of neoatherosclerotic plaques that ruptured (PR-NA) which constitute a common cause of stent failure.MethodsWe retrospectively analyzed data from patients admitted with an acute myocardial infarction that had optical coherence tomography (OCT) imaging of the culprit vessel before balloon pre-dilation. OCT pullbacks showing PR were segmented at every 0.4 mm. The extent of the formed cavity, lipid and calcific tissue, thrombus, and macrophages were measured, and the fibrous cap thickness (FCT) and the incidence of micro-channels and cholesterol crystals were reported. These data were used to reconstruct a representative model of the native and neoatherosclerotic lesion geometry that was processed with computational fluid dynamics (CFD) techniques to estimate the distribution of the endothelial shear stress and plaque structural stress.ResultEighty patients were included in the present analysis: 56 had PR in NV (PR-NV group) and 24 in NA segments (PR-NA group). The PR-NV group had a larger minimum lumen area (2.93 ± 2.03 vs. 2.00 ± 1.26 mm2, p = 0.015) but similar lesion length and area stenosis compared to PR-NA group. The mean FCT (186 ± 65 vs. 232 ± 80 μm, p = 0.009) and the lipid index was smaller (16.7 ± 13.8 vs. 25.9 ± 14.1, p = 0.008) while the of calcific index (8.3 ± 9.5 vs. 2.2 ± 1.6%, p = 0.002) and the incidence of micro-channels (41.4 vs. 12.5%, p = 0.013) was higher in the PR-NV group. Conversely, there was no difference in the incidence of cholesterol crystals, thrombus burden or the location of the rupture site between groups. CFD analysis revealed higher maximum endothelial shear stress (19.1 vs. 11.0 Pa) and lower maximum plaque structural stress (38.8 vs. 95.1 kPa) in the PR-NA compared to the PR-NV model.ConclusionWe reported significant morphological and physiological differences between culprit ruptured plaques in native and stented segments. Further research is needed to better understand the causes of these differences and the mechanisms regulating neoatherosclerotic lesion destabilization.

This paper adds to the existing body of knowledge by incorporating the role of fiscal decentralization (FD) in influencing CO2 emissions. Therefore, this study looked at the effect of FD on CO2 emissions in the presence of nonrenewable energy consumption (NRE), renewable energy consumption (REN), gross domestic product (GDP), and trade openness (TOP) for the period 1994–2018 in Japan. Thus, the current work intends to fill this knowledge gap by employing econometric techniques such as Bayer and Hanck cointegration, dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), and canonical cointegration regression (CCR). Additionally, the frequency domain causality analysis is used in the investigation to determine the causal impact of FD, NRE, REN, GDP, and TOP on CO2 emissions. The novelty of the frequency-domain approach is that it can differentiate between nonlinearity and causality levels and show causality among parameters with different frequencies. The DOLS, FMOLS, and CCR results reveal that NRE, GDP, and TOP augment CO2 emissions in Japan, whereas FD and REN increase the quality of the atmosphere. Furthermore, the frequency causality test results show that FD, REN, GDP, and TOP have implications for CO2 emissions in the long run, while NRE raises CO2 emissions in the medium run. As a policy direction, the current study suggests expanding renewable energy consumption in Japan by emphasizing more on Sustainable Development Goals (7, 8, and 13).

Background: Inferior vena cava (IVC) malformations are rare developmental anomalies and are usually asymptomatic. Agenesis of IVC is an uncommon form of IVC malformation, and symptomatic neonatal presentation is unusual. We describe an unusual case of symptomatic venous thrombosis in the neonatal period after central venous cannulation, which was later found to have agenesis of IVC. Clinical Description: An extreme preterm (28 weeks) baby developed deep vein thrombosis of the femoral and external iliac vein after femoral venous catheterization and required anticoagulation therapy. Later, during the hospital stay, he was noted to have developed dilated abdominal veins over the flanks and paraspinal region, with the direction of flow below upward 2 months after the resolution of the thrombus. Management and Outcome: Ultrasonography (USG) color Doppler ruled out portal hypertension or persistence of IVC obstruction. Computed tomography (CT) venography resolved it to be the case of agenesis of the infrarenal portion of IVC. No consensus guidelines exist for neonatal management and it is usually conservative. Conclusion: IVC developmental anomalies including agenesis of IVC are very rare and are usually an asymptomatic condition, but can cause symptoms due to venous congestion in the lower limb or pressure from enlarged collaterals and rarely associated with deep venous thrombosis usually seen in young adults. Neonatal presentation is extremely rare. Diagnosis is by USG color Doppler and CT venography. Neonatal management guidelines are lacking and the risk of anticoagulation must be cautiously weighed against the risk of hemorrhage.

The current study was designed to synthesize, characterize, and screen the molecular and biological activities of different metformin derivatives that possess potent antidiabetic potential with minimal side-effects. Metformin-based derivatives containing the metal complexes Cu II (MCu1–MCu9) and Zn II (MZn1–MZn9) were generated using aromatic aldehydes and ketones in a template process. The novel metal complexes were characterized through elemental analysis, physical state, melting point, physical appearance, Fourier-transform infrared (FTIR) spectroscopy, UV/visible (UV/Vis) spectroscopy, 1H nuclear magnetic resonance (NMR) spectroscopy, and 13C-NMR spectroscopy. Screening for inhibitory activity against the enzymes α-amylase and α-glucosidase, and molecular simulations performed in Schrödinger were used to assess the synthesized derivatives’ biological potential. Met1, Met2, Met3, and Met8 all displayed activities that were on par with the reference in an enzymatic inhibition assay (amylase and glucosidase). The enzyme inhibition assay was corroborated by molecular simulation studies, which also revealed a competitive docking score compared to the gold standard. The Swiss ADME online web server was utilized to compute ADME properties of metformin analogues. Lipinski’s rule of five held true across all derivatives, making it possible to determine the percentage of absorption. Metformin derivatives showed significant antidiabetic activities against both targeted enzymes, and the results of this work suggest that these compounds could serve as lead molecules for future study and development.

Saudi Arabia aims to build a sustainable and diversified economy by 2030. The automotive industry presents a key opportunity to achieve these goals through localization and the adoption of Industry 4.0 technologies. This research analyzes the impact of a developed localized production model for the automotive industry. The model promotes economic sustainability through domestic manufacturing, job creation and reduced oil dependence; environmental sustainability via the Industry 4.0 approach, which enhances customization, and social sustainability by developing human capital, transferring advanced technologies and stimulating job creation, thereby balancing the three spheres of sustainability. To attain the aim of the research, data were collected from 106 Saudi automobile companies. For the data collection, a questionnaire was designed, and authentication was performed according to the average level of use of Industry 4.0 and analysis of the level of implementation of the developed localized production model for the automotive industry of the Kingdom of Saudi Arabia. The results shows that large automobile companies in the Kingdom of Saudi Arabia are employing the developed localized production model more than medium and smaller automobile companies, and as a result of this model employment, automobile companies' customer satisfaction through customization and revenue has improved in an agile and lean manner. [ABSTRACT FROM AUTHOR]

Service recovery performance (SRP) is very important for the takaful insurance industry for maintaining and attracting new clients, which in turn serves as a competitive advantage for the survival and continued future of the businesses. If the insurance sector could not maintain SRP, then the competitive advantage of the organizations could be decayed. Therefore, under the theoretical foundation of equity theory and resource-based theory, this research has investigated the link between human resources management practices (HRMP) (such as human capital, training, job description, teamwork, empowerment, and rewards) and SRP directly and indirectly through the employee commitment. By using a convenient sampling technique data was collected from the employees working in the Takaful industry in Pakistan to empirically test the proposed hypotheses and validate the findings. Using cross research design and quantitative research approach. The Structural Equation Modeling (SEM) had presented the positive relationship between HRM practices and SRP. On the other hand, employee commitment had also mediated this relationship. As employee commitment is significantly mediated among most of the HRMP, this aspect is therefore considered to be a big contribution of the study in the context of Pakistan. Based on these findings, the current study has several important implications the practitioners and readers.