University of Sindh

With data from 33 nations, we illustrate the differences between cultures that are tight (have many strong norms and a low tolerance of deviant behavior) versus loose (have weak social norms and a high tolerance of deviant behavior). Tightness-looseness is part of a complex, loosely integrated multilevel system that comprises distal ecological and historical threats (e.g., high population density, resource scarcity, a history of territorial conflict, and disease and environmental threats), broad versus narrow socialization in societal institutions (e.g., autocracy, media regulations), the strength of everyday recurring situations, and micro-level psychological affordances (e.g., prevention self-guides, high regulatory strength, need for structure). This research advances knowledge that can foster cross-cultural understanding in a world of increasing global interdependence and has implications for modeling cultural change.

The hexane-extracted oil content of Moringa oleifera seeds ranged from 38.00 to 42.00%. Protein, fiber, and ash contents were found to be 26.50-32.00, 5.80-9.29, and, 5.60-7.50%, respectively. Results of physical and chemical parameters of the extracted oil were as follows: iodine value, 68.00-71.80; refractive index (40 degrees C), 1.4590-1.4625; density (24 degrees C), 0.9036-0.9080 mg/mL; saponification value, 180.60-190.50; unsaponifiable matter, 0.70-1.10%; and color (1 in. cell), 0.95-1.10 R + 20.00-35.30 Y. Tocopherols (alpha, gamma, and delta) in the oil were up to 123.50-161.30, 84.07-104.00, and 41.00-56.00 mg/kg, respectively. The oil was found to contain high levels of oleic acid (up to 78.59%) followed by palmitic, stearic, behenic, and arachidic acid up to levels of 7.00, 7.50, 5.99, and 4.21%, respectively. The induction period (Rancimat, 20 L/h, 120 degrees C) of the crude oil was 9.99 h and reduced to 8.63 h after degumming. Specific extinctions at 232 and 270 nm were 1.70 and 0.31, respectively. Many parameters of M. oleifera oil indigenous to Pakistan were comparable to those of typical Moringa seed oils reported in the literature. The results of the present analytical study were also compared with those of different vegetable oils.

Potato disease management plays a valuable role in the agriculture field as it might cause a significant loss in crops production. Therefore, timely recognition and classification of potato leaves diseases are necessary to minimize the loss, however, it is time taking task and requires human efforts. Thus, an accurate automated technique for timely detection and classification is needed to cope with the aforementioned challenges.There exist techniques grounded on machine learning and deep learning procedures that use the existing dataset i.e., ‘The Plant Village Dataset’ and perform classification into only two classes in potato leaves. Therefore, this article proposes a technique based on an improved deep learning algorithm that uses the potato leaf visual features to classify them into five classes i.e., Potato Late Blight (PLB), Potato Early Blight (PEB), Potato Leaf Roll (PLR), Potato Verticillium_wilt (PVw) and Potato Healthy (PH) class. The propose model is trained on the existing dataset i.e., “The Plant Village” that comprises of images having two ailments such as Early Blight (EB) and Late Blight (LB), and a Healthy class for potato leaves. Additionally, we have gathered the data for classes i.e., Potato Leaf Roll (PLR), Potato Verticillium_wilt (PVw) and Potato Healthy (PH) manually. A pre-trained Efficient DenseNet model has been employed utilizing an extra transition layer in DenseNet-201 to classify the potato leave diseases efficiently. Moreover, the usage of the reweighted cross-entropy loss function makes our proposed algorithm more robust as the training data is highly imbalanced. The dense connections with regularization power help to minimize the overfitting during the training of small training sets of potato leaves samples. The proposed algorithm is a novel and first technique to address and report the successful implementation for the detection and classification of four diseases in potato leaves. The algorithm’s performance was evaluated on the testing set and gave an accuracy of 97.2%. Various experiments have been performed to confirm that our proposed algorithm is more consistent and proficient to detect and classify potato leaves diseases than existing models.

Abstract Interprovenance variation was examined in the composition of Moringa oleifera oilseeds from Pakistan. The hexane‐extracted oil content of M. oleifera seeds harvested in the vicinity of the University of Agriculture, Faisalabad (Punjab, Pakistan), Bahauddin Zakariya University (Multan, Pakistan), and the University of Sindh, Jamshoro (Sindh, Pakistan), ranged from 33.23 to 40.90%. Protein, fiber, moisture, and ash contents were found to be 28.52–34.00, 6.52–7.50, 5.90–7.00, and 6.52–7.50%, respectively. The physical and chemical parameters of the extracted M. oleifera oils were as follows: iodine value, 67.20–71.00; refractive index (40°C), 1.4570–1.4637; density (24°C), 0.9012–0.9052 mg/mL; saponification value, 177.29–184.10; unsaponifiable matter, 0.60–0.83%; color (1‐in. cell), 1.00–1.50 R+20.00–30.00Y; smoke point, 198–202°C; and acidity (% as oleic acid), 0.50–0.74. Tocopherols (α, γ, and δ) accounted for 114.50–140.42, 58.05–86.70, and 54.20–75.16 mg/kg, respectively, of the oils. The induction periods (Rancimat, 20 L/h, 120°C) of the crude oils were 9.64–10.66 h and were reduced to 8.29–9.10 h after degumming. Specific extinctions at 232 and 270 nm were 1.80–2.50 and 0.54–1.00, respectively. The major sterol fractions of the oils were campesterol (14.13–17.00%), stigmasterol (15.88–19.00%), β‐sitosterol (45.30–53.20%), and Δ 5 ‐avenasterol (8.84, 11.05%). The Moringa oils were found to contain high levels of oleic acid (up to 76.00%), followed by palmitic, stearic, behenic, and arachidic acids up to levels of 6.54, 6.00, 7.00, and 4.00%, respectively. Most of the parameters of M. oleifera oils indigenous to different agroclimatic regions of Pakistan were comparable to those of typical Moringa seed oils reported in the literature. The results of the present analytical study, compared with those for different vegetable oils, showed M. oleifera to be a potentially valuable oilseed crop.

Abstract The physico‐chemical characteristics of the seeds and seed oils of four citrus species, Mitha ( Citrus limetta ), Grapefruit ( Citrus paradisi ), Mussami ( Citrus sinensis ), and Kinnow ( Citrus reticulata ) were investigated. The hexane‐extracted oil content of citrus seeds ranged from 27.0 to 36.5%. The protein, fiber and ash contents were found to be 3.9–9.6%, 5.0–8.5%, and 4.6–5.6%, respectively. The extracted oils exhibited an iodine value of 99.9–110.0; refractive index (40 °C), 1.4639–1.4670; density (24 °C), 0.920–0.941 mg/mL; saponification value, 180.9–198.9; unsaponifiable matter, 0.3–0.5%; acid value (mg KOH/g of oil), 0.5–2.2 and color (1‐in. cell) 1.4–3.0R + 15.0–30.0Y. The oils revealed a good oxidative stability as indicated by the determinations of specific extinctions at 232 and 270 nm (2.3–4.4 and 0.6–0.9, respectively), p ‐anisidine value (2.2–3.2) and peroxide value (1.6–2.4 mequiv/kg of oil). The citrus seed oils mainly consisted of linoleic acid (36.1–39.8%). Other prominent fatty acids were palmitic acid (25.8–32.2%), oleic acid (21.9–24.1%), linolenic acid (3.4–4.4%), and stearic acid (2.8–4.4%). The contents of tocopherols (α, γ, and δ) in the oil were 26.4–557.8, 27.7–84.1, and 9.1–20.0 mg/kg, respectively. The results of the present study demonstrated that the seeds of citrus species investigated are a potential source of valuable oil which might be utilized for edible and other industrial applications.

Five different drilling mud systems namely potassium chloride (KCl) as a basic mud, KCl/partial hydrolytic polyacrylamide (PHPA), KCl/graphene nanoplatelet (GNP), KCl/nanosilica and KCl/multi-walled carbon nano tube (MWCNT) were prepared and investigated for enhancement of rheological properties and shale inhibition. Nanoparticles were characterized in drilling mud using transmission electron microscope (TEM) analysis. Mineralogical analysis of shale was examined by X-ray diffraction (XRD). Five shale plugs were prepared using compactor cell for the determination of shale swelling. Shale swelling was determined using the linear swell meter (LSM) for 20 hours. Results revealed that basic mud and KCl/polymer mud systems shows 30% and 24% change in shale volume. MWCNT, nanosilica and GNP were added separately in the KCl mud system. 0.1 ppb of each MWCNT and nanosilica showed 32% and 33% change in shale volume. However, when the shale was interacted with WBM containing 0.1 ppb of GNP, it was found that only 10% change in shale volume occurred. The results showed that the addition of nanoparticles in the KCl mud system improved the shale inhibition. API, HPHT filtrate loss volume, plastic viscosity (PV) and yield point (YP) were improved using GNP. It is learned from the experimental work that small concentration of KCl with GNP can mitigate shale swelling compared to the mud contains higher concentration of KCl and PHPA in WBM. Thus, GNP can be a better choice for enhancement of WBM performance.

Purpose The purpose of this paper is to investigate the impact of entrepreneurial orientation and organizational culture on job satisfaction, organizational commitment and employee’s performance. Design/methodology/approach This is a quantitative approach, which is based on cross-sectional data. In total, 326 usable cases are processed to infer the results through the structural equation model. Findings The results revealed a positive and significant impact of organizational commitment, job satisfaction and organizational culture on employee’s performance. An entrepreneurial orientation has a positive and significant impact on organizational commitment. Job satisfaction is impacted by organizational commitment, while organizational culture is influenced by job satisfaction. On the other hand, entrepreneurial orientation has a non-significant impact on employee’s performance. Practical implications Employers may shape the organizational culture and boost the general level of job satisfaction of their employees. Further, the study enriches the organizational behavior literature by recognizing and empirically validating the impact of entrepreneurial orientation and organizational culture on job satisfaction, organizational commitment, and employee’s performance in the small and medium enterprises sector of Pakistan. Originality/value The findings of the current study may help in creating a better understanding of job satisfaction and delineating its association with organizational culture.

Wireless body area sensor network is a sub-field of wireless sensor network. Wireless body area sensor network has come into existence after the development of wireless sensor network reached some level of maturity. This has become possible due to the tremendous technological advancement leading to easy-to-use wireless wearable technologies and electronic components that are small in size. Indeed, this field has gained significant attention in recent time due to its applications which mostly are toward healthcare sector. Today, tiny-sized sensors could be placed on the human body to record various physiological parameters and these sensors are capable of sending data to other devices so that further necessary actions could be taken. Hence, this can be used for diagnosis of disease and for developing serious health-complication alert systems. Considering this recent hot topic, the intent of this work is to present the state-of-the-art of various aspects of wireless body area sensor network, its communication architectures, wireless body area sensor network applications, programming frameworks, security issues, and energy-efficient routing protocols. We have tried to cover the latest advancements with some discussion on the available radio technologies for this type of network. Future visions and challenges in this area are also discussed.

Previous research shows that selecting an appropriate theory or model has always remained a critical task for IS researchers. To the best of the authors' knowledge, there are few papers that review and compare the acceptance theories and models at the individual level. Hence, this article aims to overcome this problem by providing a critical review of eight of the most influential theories that have been used to predict and explain human behaviour towards adoption of various technologies at the individual level. This article also summarizes their evolution; highlight the key constructs, extensions, strengths, and criticisms from a selective list of published articles appeared in the literature related to IS. This review provides a holistic picture for future researchers in selecting appropriate single/multiple theoretical models/constructs based on their strengths and weaknesses and in terms of predictive power and path significance. It is concluded that a well-established theory should consider the personal, social, cultural, technological, organizational and environmental factors

In this study, leaves of three indigenous varieties of Mulberry namely, Morus alba L., Morus nigra L. and Morus rubra L. were investigated for their antioxidant potential and their proximate composition was determined. The yields of 80% methanolic extracts ranged between 8.28-13.89%. The contents of total phenolics (TPC), total flavonoids (TFC) and ascorbic acid (AA) ranged between 16.21-24.37 mg gallic acid equivalent (GAE)/g, 26.41-31.28 mg rutin equivalent (RE)/g and 0.97-1.49 mg/g, respectively. The antioxidant activity of leaf extracts was evaluated by measuring 1,1-diphenyl-2-picrylhydrazyl (DPPH(•)) radical scavenging actity, 2,2'-azino-bis-(3-ethylbenzthiazoline-6-sulphonic acid (ABTS(•+)) radical cation scavenging capacity and ferric ion reducing power and values ranged between 1.89-2.12, 6.12-9.89 and 0.56-0.97 mM Trolox equivalent/g of dried leaves, respectively. The investigated features reveal good nutritive and antioxidant attributes of all the varieties with mutually significant differences.

Healthcare waste encompasses a significant quantity of hazardous substances. Poor healthcare waste management can result in serious environmental and human health risks. Asian developing countries are densely populated, and some are highly resource constrained. These countries commonly fail to practice appropriate healthcare waste management. Moreover, facilities in these countries extensively lack proper waste segregation, collection, safe storage, transportation, and disposal. This mini-review recapitulates key issues of healthcare waste management confronting Asian developing countries. Regulations, legislation, and policies are found to be recent, and their implementation varies from one another. Variation in waste generation rate is common. Contradictory methods of waste measurement used by researchers leave these variations questionable. The absence of waste management training programmes roots ignorance among staff and handlers, which leads to unsafe waste handling and causes different health risks. Unsafe and illegal recycling of hazardous waste is a threat to human health, also landfilling is often confused with open dumping, causing environmental damage. Outdated incineration plants need to be replaced with autoclaving, steam sterilisation, and comparatively reasonable new practice of pyrolysis to avoid the emission of toxic gases. The significance of proper healthcare waste management cannot be ignored, especially in Asian developing countries; substantial improvements are required in order to protect the environment and human health from serious risks.

It is universally accepted that the financial advancement of a state is essentially dependent upon the energy sector as it is essential in the growth, development, and improvement of the farming, mechanical, and defense sectors. A dependable source of energy is expected to enhance society's expectation of everyday comforts. Modern industrial advancement, which is indispensable for any nation, relies upon electricity. The principal explanation behind the energy emergency is rapidly increasing the use of hydrocarbon resources. Thus, the use of renewable resources is essential to overcome this dilemma. The consumption of hydrocarbon fuels and their discharge has destructive consequences on our surroundings. Third-generation photovoltaic (solar) cells are latest encouraging option in solar cells. Currently, dye-sensitized solar cells (DSSC) utilize organic (natural and synthetic) dye and inorganic (ruthenium) as a sensitizer. The nature of this dye combined with different variables has brought about a change in its use. Natural dyes are a feasible alternative in comparison to expensive and rare ruthenium dye owing to their low cast, easy utility, abundant supply of resources, and no environmental threat. In this review, the dyes generally utilized in DSSC are discussed. The DSSC criteria and components are explained, and the progress in inorganic and natural dyes is monitored. Scientists involved in this emerging technology will benefit from this examination.

Green innovation is an essential and burning topic for environmental and organizational performance. Therefore, this research aims to examine the effect of green innovation on environmental performance, which leads to organizational performance. Another objective is to measure the impact of two dimensions of green innovation, such as green process & green product measures, on green innovation. The second prime aim of this research is to evaluate the moderation of management commitment & human resource practices in an association between green innovation and organizational & environmental performance. A total of 320 employees provided their perspectives on a self-administrated questionnaire from the textile industry of Pakistan. We have employed SEM-based multivariate modeling to examine the data. This research has measured the reflective indicators measurement model through confirmatory factor analysis, an obvious choice of structural equation modeling to examine observed and unobserved variables and indicators using PLS-SEM (partial least square-structural equation modeling). The research findings reveal a positive & significant effect of product & process innovation on green innovation. Further, green innovation significantly impacts environmental and organizational performance. A two-way interaction (moderation) of human resource practices & green innovation does not have a cogent moderating effect on organizational & environmental performance. However, management commitment has a significant moderation between green innovation & organizational performance. A three-way interaction (moderated moderation) model finds a substantial effect on organizational attainment but an insignificant impact on environmental performance. The research outcomes significantly contribute and suggest that practitioners and policymakers must institutionalize green innovation practices in their organizations to enhance their organizational and environmental performance. HR practitioners play a vibrant role in creating green norms and organizational culture. The study findings also suggest that management commitment to green innovation advocates organization-level transformations toward adopting green practices.

Wheat stripe rust (yellow rust [Yr]), caused by Puccinia striiformis f. sp. tritici, is an economically important disease of wheat worldwide. Virulence information on P. striiformis f. sp. tritici populations is important to implement effective disease control with resistant cultivars. In total, 235 P. striiformis f. sp. tritici isolates from Algeria, Australia, Canada, Chile, China, Hungary, Kenya, Nepal, Pakistan, Russia, Spain, Turkey, and Uzbekistan were tested on 20 single Yr-gene lines and the 20 wheat genotypes that are used to differentiate P. striiformis f. sp. tritici races in the United States. The 235 isolates were identified as 129 virulence patterns on the single-gene lines and 169 virulence patterns on the U.S. differentials. Virulences to YrA, Yr2, Yr6, Yr7, Yr8, Yr9, Yr17, Yr25, YrUkn, Yr28, Yr31, YrExp2, Lemhi (Yr21), Paha (YrPa1, YrPa2, YrPa3), Druchamp (Yr3a, YrD, YrDru), Produra (YrPr1, YrPr2), Stephens (Yr3a, YrS, YrSte), Lee (Yr7, Yr22, Yr23), Fielder (Yr6, Yr20), Tyee (YrTye), Tres (YrTr1, YrTr2), Express (YrExp1, YrExp2), Clement (Yr9, YrCle), and Compair (Yr8, Yr19) were detected in all countries. At least 80% of the isolates were virulent on YrA, Yr2, Yr6, Yr7, Yr8, Yr17, YrUkn, Yr31, YrExp2, Yr21, Stephens (Yr3a, YrS, YrSte), Lee (Yr7, Yr22, Yr23), and Fielder (Yr6, Yr20). Virulences to Yr1, Yr9, Yr25, Yr27, Yr28, Heines VII (Yr2, YrHVII), Paha (YrPa1, YrPa2, YrPa3), Druchamp (Yr3a, YrD, YrDru), Produra (YrPr1, YrPr2), Yamhill (Yr2, Yr4a, YrYam), Tyee (YrTye), Tres (YrTr1, YrTr2), Hyak (Yr17, YrTye), Express (YrExp1, YrExp2), Clement (Yr9, YrCle), and Compair (Yr8, Yr19) were moderately frequent (>20 to <80%). Virulence to Yr10, Yr24, Yr32, YrSP, and Moro (Yr10, YrMor) was low (≤20%). Virulence to Moro was absent in Algeria, Australia, Canada, Kenya, Russia, Spain, Turkey, and China, but 5% of the Chinese isolates were virulent to Yr10. None of the isolates from Algeria, Canada, China, Kenya, Russia, and Spain was virulent to Yr24; none of the isolates from Algeria, Australia, Canada, Nepal, Russia, and Spain was virulent to Yr32; none of the isolates from Australia, Canada, Chile, Hungary, Kenya, Kenya, Nepal, Pakistan, Russia, and Spain was virulent to YrSP; and none of the isolates from any country was virulent to Yr5 and Yr15. Although the frequencies of virulence factors were different, most of the P. striiformis f. sp. tritici isolates from these countries shared common virulence factors. The virulences and their frequencies and distributions should be useful in breeding stripe-rust-resistant wheat cultivars and understanding the pathogen migration and evolution.

In this article, a hybrid asynchronous particle swarm optimization-genetic algorithm (APSO-GA) is proposed for the removal of unwanted lower order harmonics in the cascaded H-bridge multilevel inverter (MLI). The APSO-GA is applicable to all levels of MLI. In the proposed method, ring topology based APSO is hybrid with GA. APSO is applied for exploration and GA is used for the exploitation of the best solutions. In this article, optimized switching angles are calculated using APSO-GA for seven-level and nine-level inverter, and results are compared with GA, PSO, APSO, bee algorithm (BA), differential evolution (DE), synchronous PSO, and teaching–learning-based optimization (TLBO). Simulation results show that APSO-GA can easily find feasible solutions particularly when the number of switching angles is high; however, the rest of all stuck at local minima due to less exploration capability. Also, the APSO-GA is less computational complex than GA, BA, TLBO, and DE algorithms. Experimentally, the performance of APSO-GA is validated on a single-phase seven-level inverter.

Kurt Lewin has been regarded as the father of planned change. His classical three-step model though has provided the basis for different models of change, yet has been criticized for its linearity, unsuitability for continuous change and inability to incorporate leader–follower relationship dynamics. This study has responded to various criticisms by introducing new three-step model as a replica of the three-step model while integrating it with the theory of planned behaviour. For leader–follower relationship dynamics, this study tested the impact of well-needed authentic leadership on employee perceptions during change. Following positivistic approach and deductive reasoning, this study used causal design to collect primary data through Questionnaire survey based on simple random sampling technique. The data were collected from 258 employees of three public sector hospitals of Pakistan undergoing restructuring and analysed through structural equation modelling using AMOS. The results suggest that for successful implementation of planned change, authentic leaders need to create employees’ readiness for change (unfreezing) that will in turn develop their commitment to change (moving) and behavioural support for change (refreezing). This is the first study regarding the role of authentic leadership in the context of change. The findings will help change leaders to undertake better employee-accepted change initiatives by following Lewin’s model as a tool that is still relevant to the organizational change.

Since Facebook was renamed Meta, a lot of attention, debate, and exploration have intensified about what the Metaverse is, how it works, and the possible ways to exploit it. It is anticipated that Metaverse will be a continuum of rapidly emerging technologies, usecases, capabilities, and experiences that will make it up for the next evolution of the Internet. Several researchers have already surveyed the literature on artificial intelligence (AI) and wireless communications in realizing the Metaverse. However, due to the rapid emergence and continuous evolution of technologies, there is a need for a comprehensive and in-depth survey of the role of AI, 6G, and the nexus of both in realizing the immersive experiences of Metaverse. Therefore, in this survey, we first introduce the background and ongoing progress in augmented reality (AR), virtual reality (VR), mixed reality (MR) and spatial computing, followed by the technical aspects of AI and 6G. Then, we survey the role of AI in the Metaverse by reviewing the state-of-the-art in deep learning, computer vision, and Edge AI to extract the requirements of 6G in Metaverse. Next, we investigate the promising services of B5G/6G towards Metaverse, followed by identifying the role of AI in 6G networks and 6G networks for AI in support of Metaverse applications, and the need for sustainability in Metaverse. Finally, we enlist the existing and potential applications, usecases, and projects to highlight the importance of progress in the Metaverse. Moreover, in order to provide potential research directions to researchers, we underline the challenges, research gaps, and lessons learned identified from the literature review of the aforementioned technologies.

Block diagram of the methods covered in the review for assessment of free fatty acids in oils and fats.

Abstract Metal oxide (MOx) semiconducting nanostructures hold the potential for playing a critical role in the development of a new platform for renewable energies, including energy conversion and storage through photovoltaic effect, solar fuels, and water splitting. Earth‐abundant MOx nanostructures can be prepared through simple and scalable routes and integrated in operating devices, which enable exploitation of their outstanding optical, electronic, and catalytic properties. In this review, the latest research results in this field are illustrated, highlighting the versatility of MOx nanostructures in meeting the stringent requirements to boost the efficiency of different systems. The functional properties inherently correlate to the morphology and the crystalline habit of MOx, which in most of the cases are organized in complex heterostructures. Tailoring the assembly of heterojunctions and their electronic band structure, the catalytic surface properties and the charge transport through complex networks represent the main challenge for the transition of MOx from the research to the real‐life in the field of energy conversion and storage.

Hollow-fiber liquid-phase microextraction (HF-LPME) and electromembrane extraction (EME) are miniaturized extraction techniques, and have been coupled with various analytical instruments for trace analysis of heavy metals, drugs and other organic compounds, in recent years. HF-LPME and EME provide high selectivity, efficient sample cleanup and enrichment, and reduce the consumption of organic solvents to a few micro-liters per sample. HF-LPME and EME are compatible with different analytical instruments for chromatography, electrophoresis, atomic spectroscopy, mass spectrometry, and electrochemical detection. HF-LPME and EME have gained significant popularity during the recent years. This review focuses on hollow fiber based techniques (especially HF-LPME and EME) of heavy metals and pharmaceuticals (published 2017 to May 2019), and their combinations with atomic spectroscopy, UV-VIS spectrophotometry, high performance liquid chromatography, gas chromatography, capillary electrophoresis, and voltammetry.