Study of class 1 integrons in multidrug-resistant uropathogenic Escherichia coli isolated from different hospitals in Karachi

Objective(s): Escherichia coli is the key pathogen in the family producing ESBL (extended spectrum β-lactamase) and associated with community-acquired infections. Therefore, this study was planned to determine the antibiotic susceptibility pattern of uropathogenic E. coli, prevalence of the ESBL gene group and class 1 integrons.Materials and Methods: Clinical isolates of uropathogenic E. coli were isolated from different hospitals of Karachi. Antibiotic susceptibility test was performed by Kirby-Bauer Methods. Presence of β– lactamases genes (CTX, TEM, and SHV) and integron 1 were identified by polymerase chain reaction (PCR).Results: Out of 500, 105 isolates were identified as multi-drug resistant (MDR) uropathogenic E. coli. The subject MDR isolates showed the highest resistance to aztreonam, amoxil/ clavulanic acid, ampicillin, cotrimoxazole, ceftriaxone, cefipime, and cefuroxime. Genetic analysis showed that the majority of the MDR E. coli carry CTX M1 (57.1%) followed by TEM (33.3%) and SHV (9.5%). Moreover, 79% of MDR E. coli harbored class 1 integrons, whereas all three conserved genes for class 1 integrons were present in 58% of MDR E. coli. Conclusion: This study is helpful to provide information regarding the antibiotic susceptibility pattern, distribution ESBLs and class 1 integrons among uropathogenic E. coli

Small and medium-sized enterprises in the digital business sector

The chapter is a systematic literature review of fundamental theories about small and medium business (SME) success. The chapter examines how they specifically impact digital SMEs. The chapter examined six theories: dynamic capability view (DCV), composition-based view of firm growth (CBV), resourcebased view (RBV), resource dependence theory (RDT), upper echelon theory (UET), strategic contingency theory (SCT). The results showed that RBV, DCV, and UET become relevant in articulating the value inherent to the internal resources in SMEs (which render their capabilities dynamic). In contrast, the SCT framework and the RDT model show more significance in relation to uncertainty and contingency. CBV was found to be a more pertinent framework to predict the success of SMEs. The results support CBV’s hypothesis that SMEs (including digital SMEs) are able to be competitive without extensive resource advantage, too complicated technologies, or market power. The increased deployment of CBV can be advocated as a critical determinant of digital SME success

Are trade openness drivers relevant to carbon dioxide emission? a study of emerging economies

This research is focused on an in-depth analysis of the trade drivers that influence trade openness and their impact on carbon dioxide emissions, with a concentrated examination of emerging economies from 1995 to 2020. This examination is contextualized within the scope of various trade and environmental theoretical frameworks. In our analysis, we employed a range of advanced panel regression methods, including stepwise regression for model selection, as well as Fully Modified Ordinary Least Squares (FMOLS), Panel Ordinary Least Squares (Panel OLS), and Fixed Effects Model (FEM). The long-term patterns were evaluated using Johansen co-integration tests. Additionally, the study delves into the causal links between carbon dioxide emissions and the key drivers of trade, employing Granger causality tests for this purpose. Our findings disclose a complex web of relationships, both in the short and long term, between trade openness and carbon dioxide emissions, influenced by several key factors: (i) net inflows of foreign direct investment, (ii) trade reserves, (iii) per capita income, (iv) exchange rates, and (v) gross national savings

MDVA-GAN: multi-domain visual attribution generative adversarial networks

Some pixels of an input image have thick information and give insights about a particular category during classification decisions. Visualization of these pixels is a well-studied problem in computer vision, called visual attribution (VA), which helps radiologists to recognize abnormalities and identify a particular disease in the medical image. In recent years, several classification-based techniques for domain-specific attribute visualization have been proposed, but these techniques can only highlight a small subset of most discriminative features. Therefore, their generated VA maps are inadequate to visualize all effects in an input image. Due to recent advancements in generative models, generative model-based VA techniques are introduced which generate efficient VA maps and visualize all affected regions. To deal the issue, generative adversarial network-based VA techniques are recently proposed, where the researchers leverage the advances in domain adaption techniques to learn a map for abnormal-to-normal medical image translation. As these approaches rely on a two-domain translation model, it would require training as many models as number of diseases in a medical dataset, which is a tedious and compute-intensive task. In this work, we introduce a unified multi-domain VA model that generates a VA map of more than one disease at a time. The proposed unified model gets images from a particular domain and its domain label as input to generate VA map and visualize all the affected regions by that particular disease. Experiments on the CheXpert dataset, which is a publicly available multi-disease chest radiograph dataset, and the TBX11K dataset show that the proposed model generates identical results

Attraction of Bus Rapid Transit (BRT) for Car and Bike Owners

This study aims to find the potential of Bus Rapid Transit (BRT) to attract the vehicle owners from their personal vehicles i.e., motorcars and motorcycles. Stated preference survey (questionnaires) and interviews were conducted at BRT (Metro Bus) Stations for the prediction of the individuals shifting from their private vehicles to BRT. Questions were designed critically as per the requirements of the research related to numerous aspects of BRT use i.e., vehicle ownership of the travelers, driving license holder, demographic characteristics, choice to use BRT if the fare increases, trip purpose and their prior mode of transportation for the same trip. A total of 374 responses, as per the population of the study area (Islamabad-Rawalpindi, Pakistan), were collected. The Multinomial Logistic Regression (MNL) model has been employed for four categories of vehicle ownerships i.e., “Car owners using BRT”, “Bike owners using BRT”, “Both Car and Bike owners using BRT” and the last one which has been taken as reference category is “BRT users with no vehicle ownership”. The analysis indicated that BRT has attracted considerably private vehicle users specially the bike owners. Some socio-economic factors like income and residence location (accessibility) additionally have a major effect on the selection of BRT. In addition, it has been observed that fare increase can alter the mode choice of the BRT users and they will again prefer their own vehicles. The Travel choice model developed in the study can be very useful for policy makers and transport planners to enhance the BRT service and attraction, to mitigate traffic congestion and car ownership

Are Trade Openness Drivers Relevant to Carbon Dioxide Emission? A Study of Emerging Economies

This research is focused on an in-depth analysis of the trade drivers that influence trade openness and their impact on carbon dioxide emissions, with a concentrated examination of emerging economies from 1995 to 2020. This examination is contextualized within the scope of various trade and environmental theoretical frameworks. In our analysis, we employed a range of advanced panel regression methods, including stepwise regression for model selection, as well as Fully Modified Ordinary Least Squares (FMOLS), Panel Ordinary Least Squares (Panel OLS), and Fixed Effects Model (FEM). The long-term patterns were evaluated using Johansen co-integration tests. Additionally, the study delves into the causal links between carbon dioxide emissions and the key drivers of trade, employing Granger causality tests for this purpose. Our findings disclose a complex web of relationships, both in the short and long term, between trade openness and carbon dioxide emissions, influenced by several key factors: (i) net inflows of foreign direct investment, (ii) trade reserves, (iii) per capita income, (iv) exchange rates, and (v) gross national savings

Evolution of Metal Tellurides for Energy Storage/Conversion:From Synthesis to Applications

Metal telluride (MTe)-based nanomaterials have emerged as a potential alternative for efficient, highly conductive, robust, and durable electrodes in energy storage/conversion applications. Significant progress in the material development of MTe-based electrodes is well-sought, from the synthesis of its nanostructures, integration of MTes with supporting materials, synthesis of their hybrid morphologies, and their implications in energy storage/conversion systems. Herein, an extensive exploration of the recent advancements and progress in MTes-based nanomaterials is reviewed. This review emphasizes elucidating the fundamental properties of MTes and providing a systematic compilation of its wet and dry synthesis methods. The applications of MTes are extensively summarized and discussed, particularly, in energy storage and conversion systems including batteries (Li-ion, Zn-ion, Li-S, Na-ion, K-ion), supercapacitor, hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), and CO2 reduction. The review also emphasizes the future prospects and urgent challenges to be addressed in the development of MTes, providing knowledge for researchers in utilizing MTes in energy storage and conversion technologies

High Genetic Diversity in the Himalayan Common Bean (Phaseolus vulgaris) Germplasm with Divergence from Its Center of Origin in the Mesoamerica and Andes

The common bean is found in the Himalayan region of Pakistan with substantial morphological variability. Genetic diversity within any crop species is a precursor for genetic improvement; however, little is known about common bean genetic diversity in this region. We explored the genetic diversity in the common bean from the Himalayan region (Khyber Pakhtunkhwa, Gilgit–Baltistan, Kashmir) of Pakistan. Microsatellite genotyping was carried out for 147 samples with 40 simple sequence repeat (SSR) markers. The results revealed a clear divergence of the Pakistani population from the primary gene pool (with FST values of 0.2 with Andes and 0.27 with Mesoamerica). However, within the Himalayan germplasm, no clear evidence of spatial structure was observed (with the maximum FST values of only 0.025), probably due to the dispersal of seeds by human activity within the region. This was further elucidated by the discriminant analyses of principal components. Considering the diversity parameters, high genotypic diversity was observed for the indigenous lines (0.990), comparable to the primary gene pool (0.976 for Mesoamerica and 0.976 for Andes populations). A high genotypic diversity was observed within the Himalayan population (ranging from 0.500 for Upper Dir to 0.952 for Mansehra). Gene diversity across loci varied between 0.28 for Chitral to 0.38 for Kurram. Our results suggested a divergent and independent evolution of the Himalayan population, which might have led to the diversification of the common bean germplasm in the region postintroduction into the region. The diversity observed could also be exploited in future breeding programs for the development and introduction of climate-resilient varieties