Curing Workplace Deviance through Organizational Justice in the Mediating Role of Job Satisfaction: The case of NGOs in Pakistan

Organizations of modern era are trying to obtain competitive advantage through human force. Unfortunately, workforce is getting involved into deviant practices in almost every organization and such workplace deviance can be a great threat which can harm the organizational performance. Most of such deviant practices are due to injustice events which happen in organization and ultimately reduce the job satisfaction of employees. Such issues of deviance and injustice have note been explored in Non-Governmental Organizations (NGOs) of Pakistan in the past which highlights a certain need to explore this area. This study has aimed to check the impact of organizational justice dimensions on workplace deviance in the mediating role of job satisfaction in NGOs of Pakistan. To do this, a sample of five NGOs was selected and 500 close ended questionnaires were personally administered to randomly selected employees. A total of 381 questionnaires complete in all the respects were included for analysis. Inferential statistical techniques were then applied to draw conclusions. The results have proved that all dimensions of organizational justice have a significant negative impact on workplace deviance and job satisfaction significantly mediate this relationship which establishes that organizational injustice lead employees to behave in deviant ways.. This research has implications for both managers and theory. Limitations and future research indications have also been given at the end of this study

Jatropha curcas leaves mulch effect on seedling emergence and growth of maize (zea mays)

Allelopathy is a process in which one plant species may usefully or adversely affect the growth of other plant species through the production of allelochemicals. During the present investigation, mulch effect of Jatropha curcas leaves was evaluated on seed germination and seedling growth of maize varieties viz. Pioneer (V1), Azam (V2) and Jalal (V3). Mulch was applied at 1 and 2 tons/hectare. Phenolic compounds were detected in Jatropha curcas leaf (131.15 mg gallic acid eq./gm extract). Mulch applied at 2 tons/hectare significantly reduced seed germination (%), germination index, relative water content, root width and seedling dry weight. From the findings of the present investigation, it was inferred that Jatropha curcas leaves exhibited phytotoxic effects on maize at high concentrations

Protection of apricot Biodiesel from Thermal Degradation by using natural antioxidants of Fagopyrum tataricum (L.) Gaertn

The present study aims to improve the oxidation stability of wild apricot kernel oil biodiesel (WAKOB) by using natural antioxidants of Tartary buckwheat (Fagopyrum tataricum (L.) Gaertn). Biodiesel was synthesized at different catalyst (NaOH) concentrations, reaction temperatures, reaction time intervals and methanol-to-oil molar ratios. Thermal oxidative stability measurements were carried out according to EN14112 using a Rancimet instrument. Our results showed a high yield of biodiesel (97±1.092) at 65oC in the presence of 1% NaOH (%w/w oil) and methanol/oil molar ratio of 9:1 and for the time duration of 60 min. Proton nuclear magnetic resonance (1H NMR) confirmed the conversion percentage of kernel oil into biodiesel, which was further evidenced by Fourier transform infrared spectroscopy (FT-IR) and refractometer analyses. Methanolic fraction of Tartary buckwheat leaves (MTBWLF) was standardized to contain the highest amount of phenolics (209 mg gallic acid/100 g). In this study, the mixture of synthetic antioxidant butylated hydroxyl toluene (BHT) (0.25%) and methanolic extract of Tartary buckwheat leaves (0.5%) ensured high oxidation stability of biodiesel samples, leading to stabilizing factor of 4.86

Health risks assessment diagnosis of toxic chemicals (heavy metals) via food crops consumption irrigated with wastewater

The present study investigated the concentration of metals in commonly grown vegetables (Luffa acutangula L., Zea mays L., Solanum melongena L.) irrigated with waste water in District Bannu, Khyber Pakhtunkhwa, Pakistan. The pH (5.80) and electrical conductivity (13 dS/m) of waste water indicated the acidic nature that is not suitable for irrigation purposes. Soil and vegetables samples were analyzed for metals concentration through flame atomic absorption spectrometry (Varian FAAS-240). The findings showed that waste water irrigated soil was highly contaminated with Cd (4.62 mg/kg) which was above permissible limits set by European Union Standard (EU 2006, 2002). The concentrations of heavy metals such as Cr and Cd in vegetables were higher than the permissible limits set by World Health Organization/Food and Agriculture Organization U.S.A guidelines 2001. The health hazard quotient (HQ) of waste water irrigated vegetables was observed higher for Ni (0.699-0.1029 mg/kg), (0.0456-0.1040 mg/kg), (0.731-0.0994 mg/kg) in Luffa acutangula, Solanum melongena and Zea mays, respectively. The study concluded that the consumption of commonly grown vegetables in waste water zone of the study area may pose potential health threats in local population

Relationship between Social Media Marketing and Consumer Buying Behavior

The social media has become an integral part of our lives with the introduction of 3G, 4G technology in Pakistan it has become possible for people to stay connected from anywhere any time. The purpose of this study is to find out that if any relationship between social media marketing and consumer buying behavior exist if their existence affected each other in any significant way. For this purpose an online survey was conducted and 100 people responded who were active users of social media in the region of Peshawar an unstructured/ structured questionnaire was designed to collect information from the respondents. The research findings and results confirms that there is a positive relationship between social media marketing and consumer buying behavior as well as that social media can be used as an effective marketing tool in region of Peshawar

Predicting Divorce Prospect Using Ensemble Learning:Support Vector Machine, Linear Model, and Neural Network

A divorce is a legal step taken by married people to end their marriage. It occurs after a couple decides to no longer live together as husband and wife. Globally, the divorce rate has more than doubled from 1970 until 2008, with divorces per 1,000 married people rising from 2.6 to 5.5. Divorce occurs at a rate of 16.9 per 1,000 married women. According to the experts, over half of all marriages ends in divorce or separation in the United States. A novel ensemble learning technique based on advanced machine learning algorithms is proposed in this study. The support vector machine (SVM), passive aggressive classifier, and neural network (MLP) are applied in the context of divorce prediction. A question-based dataset is created by the field specialist. The responses to the questions provide important information about whether a marriage is likely to turn into divorce in the future. The cross-validation is applied in 5 folds, and the performance results of the evaluation metrics are examined. The accuracy score is 100%, and Receiver Operating Characteristic (ROC) curve accuracy score, recall score, the precision score, and the F1 accuracy score are close to 97% confidently. Our findings examined the key indicators for divorce and the factors that are most significant when predicting the divorce

Knowledge, attitudes, and practices of the general population of Pakistan regarding typhoid conjugate vaccine: findings of a cross-sectional study

Typhoid fever, a common enteric disease in Pakistan, caused by Salmonella typhi, is becoming an extended drug-resistant organism and is preventable through the typhoid conjugate vaccine (TCV). Public adherence to preventive measures is influenced by knowledge and attitude toward the vaccine. This study investigates the knowledge, attitudes, and practices of the general population of Pakistan toward TCV. The differences in mean scores and factors associated with typhoid conjugate vaccine knowledge, attitudes, and practices were investigated. A total of 918 responses were received with a mean age of 25.9 ± 9.6, 51% were women, and 59.6% had graduation-level education. The majority of them responded that vaccines prevent illness (85.3%) and decrease mortality and disability (92.6%), and typhoid could be prevented by vaccination (86.7%). In total, 77.7 and 80.8% considered TCV safe and effective, respectively. Of 389 participants with children, 53.47% had vaccinated children, according to the extended program on immunization (EPI). Higher family income has a higher odds ratio (OR) for willingness toward booster dose of TCV [crude odds ratio (COR) = 4.920, p–value <0.01; adjusted odds ratio (aOR) = 2.853, value of p <0.001], and negative attitude regarding the protective effect of TCV has less willingness toward the booster dose with statistical significance (COR = 0.388, value of p = 0.017; aOR = 0.198, value of p = 0.011). The general population of Pakistan had a good level of knowledge about the benefits of TCV, and attitude and practices are in favor of the usage of TCV. However, a few religious misconceptions are prevalent in public requiring the efforts to overcome them to promote the usage of vaccines to prevent the disease and antibiotic resistance

Deep GRU-CNN model for COVID-19 detection from chest X-rays data

In the current era, big data is growing exponentially due to advancements in smart devices. Data scientists apply varied learning-based techniques to identify the underlying patterns in the big medical data to address various health-related issues. In this context, automated disease detection has now become a central concern in medical science due to rapid population growth. It reduces the mortality rate by diagnosing the disease correctly and early enough. The novel virus disease COVID-19 has spread all over the world and is affecting millions of people. Many countries are facing a shortage of test kits, vaccines, and other resources due to substantial growth in COVID-19 cases. In order to accelerate the testing process, scientists around the world have sought to create revolutionary novel alternative methods for the detection of the deadly virus. In this paper, we have proposed a hybrid deep learning model based on a convolutional neural network (CNN) and gated recurrent unit (GRU) for diagnosing the virus from chest X-rays (CXRs). In the proposed model, CNN is used to extract features, and GRU is used as a classifier. The model has been trained on 424 CXRs images with 3 (COIVD-19, Pneumonia, and Normal) classes. The proposed model achieved encouraging results of 0.96, 0.96, and 0.95 in terms of precision, recall, and f1-score, respectively. These findings indicate how deep learning can significantly contribute to the early detection of COVID-19 patients using X-ray scans. Such indications can pave the ways to mitigate the deadly disease. We believe that this model can be an effective tool for medical practitioners for the early diagnosis of coronavirus from CXRs

Efficacy of Hydroxychloroquine and Tocilizumab in Patients With COVID-19: Single-Center Retrospective Chart Review.

BACKGROUND: During the initial phases of the COVID-19 pandemic, there was an unfounded fervor surrounding the use of hydroxychloroquine (HCQ) and tocilizumab (TCZ); however, evidence on their efficacy and safety have been controversial. OBJECTIVE: The purpose of this study is to evaluate the overall clinical effectiveness of HCQ and TCZ in patients with COVID-19. We hypothesize that HCQ and TCZ use in these patients will be associated with a reduction in in-hospital mortality, upgrade to intensive medical care, invasive mechanical ventilation, or acute renal failure needing dialysis. METHODS: A retrospective cohort study was performed to determine the impact of HCQ and TCZ use on hard clinical outcomes during hospitalization. A total of 176 hospitalized patients with a confirmed COVID-19 diagnosis was included. Patients were divided into two comparison groups: (1) HCQ (n=144) vs no-HCQ (n=32) and (2) TCZ (n=32) vs no-TCZ (n=144). The mean age, baseline comorbidities, and other medications used during hospitalization were uniformly distributed among all the groups. Independent t tests and multivariate logistic regression analysis were performed to calculate mean differences and adjusted odds ratios with 95% CIs, respectively. RESULTS: The unadjusted odds ratio for patients upgraded to a higher level of care (ie, intensive care unit) (OR 2.6, 95% CI 1.19-5.69; P=.003) and reductions in C-reactive protein (CRP) level on day 7 of hospitalization (21% vs 56%, OR 0.21, 95% CI 0.08-0.55; P=.002) were significantly higher in the TCZ group compared to the control group. There was no significant difference in the odds of in-hospital mortality, upgrade to intensive medical care, need for invasive mechanical ventilation, acute kidney failure necessitating dialysis, or discharge from the hospital after recovery in both the HCQ and TCZ groups compared to their respective control groups. Adjusted odds ratios controlled for baseline comorbidities and medications closely followed the unadjusted estimates. CONCLUSIONS: In this cohort of patients with COVID-19, neither HCQ nor TCZ offered a significant reduction in in-hospital mortality, upgrade to intensive medical care, invasive mechanical ventilation, or acute renal failure needing dialysis. These results are similar to the recently published preliminary results of the HCQ arm of the Recovery trial, which showed no clinical benefit from the use of HCQ in hospitalized patients with COVID-19 (the TCZ arm is ongoing). Double-blinded randomized controlled trials are needed to further evaluate the impact of these drugs in larger patient samples so that data-driven guidelines can be deduced to combat this global pandemic

Concept mapping and conceptual change texts: a constructivist approach to address the misconceptions in nanoscale science and technology

Nanoscale Science and Technology (NST) is a rapidly evolving field with profound implications for various industries and our everyday lives. However, misconceptions among learners can hinder their ability to grasp the fundamental concepts of NST, thereby impeding their potential contributions to this advancing domain. Concept maps (CM) and conceptual change texts (CCT) are graphical and written representations of knowledge that enable learners to visualize relationships between concepts and assess the coherence of their understanding. In this pursuit, we engage with the concept of rehabilitation for misconceptions, viewing the learning process as a transformative journey akin to cognitive rehabilitation. Through this CM-CCT constructivist approach, learners are encouraged to engage in critical reflection, self-questioning, and peer discussions, which facilitate the identification of misconceptions. Moreover, CM-CCT provide a structured framework for presenting accurate information about NST, offering a clear depiction of the hierarchical and interconnected nature of nanoscale phenomena. The aim of this study was to evaluate the effectiveness of CM-CCT in correcting the misconceptions of undergraduate university students regarding nanotechnology and the taxonomy of nonmaterial. Prior to the implementation of the CM-CCT, an assessment of pre-existing knowledge of the students was performed through the structure of the observed learning outcomes (SOLO) taxonomy. A quasi-experimental research design was carried out. A total of 70 undergraduate university students, divided into two intact groups, were cross-examined for the study. Further, before and after the instructional tools, an achievement test based on nanotechnology and classification of nonmaterial was conducted, covering all six cognitive domains of the Bloom taxonomy of educational objectives. Data analysis revealed that the instructional tools based on constructivist approach had a statistically significant impact on students for elimination of their misconceptions about nanotechnology, nano science and classification of nonmaterial