EXPLORING THE MEDIATING ROLE OF AFFECTIVE COMMITMENT ON ORGANIZATIONAL JUSTICE AND TURNOVER INTENTION

This study encompasses the association of the three domainsof organizational justice and its influence on employee turnoverintention. In this cross-sectional study, proportionate stratifiedrandom sampling technique was applied. Results showed thatdistributive justice and interactional justice have an inverserelationship with turnover intention and affective commitmentpartially mediated the pathway between the dimensions of justiceand employee turnover behavior. Conversely, procedural justice hasan insignificant linkage with the turnover intention. This studycontributes by developing an understanding of linkage betweenturnover intention and organizational justice and provides insightabout mediation of affective commitment

New Ectomycorrhizas in association with Poplar from Himalayan moist forests of Pakistan

Populinirrhiza pinnata and populinirrhiza khanspurensis are described and illustrated as new ectomycorrhizas from Himalayan moist temperate forests of Pakistan in association with the root system of Populus ciliata. Populinirrhiza pinnata has monopodial pinnate type of ramification. The young mycorrhizas are dark brown while the older ones are black. White sugary crystals are present on mycorrhizal system. Emanating hyphae surround mycorrhizas. Rhizomorphs are thick and branched. Populinirrhiza khanspurensis has a simple to monopodial type of ramification. The color of the young mycorrhiza is brown; some times with dark tips while the older ones are dark brown. Rhizomorph and emanating hyphae are absent. As so far no fungal partner of these mycorrhizas has been identified, these fall under the category of ‘unknown’ and ‘unidentified’ mycorrhizas.&nbsp

Fatal elizabethkingia meningoseptica cholangitis following biliary stent placement

Elizabethkingia (E.) meningosepticais a ubiquitous gram-negative bacillus belonging to the genus Chryseobacteriumand has been reported to cause nosocomial infections in both the immunocompromised and immunocompetent patients. E. meningoseptica can colonize the biliary tree after endoscopic procedures; and cholangitis, caused by this organism, is associated with a favorable prognosis. Here, we report a fatal case of cholangitis secondary to E. meningoseptica that developed following biliary stent placement. This case suggests that E. meningoseptica can be a cause of potentially fatal biliary tract infections in patients who undergo biliary tract endoscopic procedures. Clinicians must not disregard this organism as a contaminant (or colonizer) as a delay in diagnosis and treatment can lead to a fatal outcome, as seen in this case

Enhancing Credit Card Fraud Detection: An Ensemble Machine Learning Approach

In the era of digital advancements, the escalation of credit card fraud necessitates the development of robust and efficient fraud detection systems. This paper delves into the application of machine learning models, specifically focusing on ensemble methods, to enhance credit card fraud detection. Through an extensive review of existing literature, we identified limitations in current fraud detection technologies, including issues like data imbalance, concept drift, false positives/negatives, limited generalisability, and challenges in real-time processing. To address some of these shortcomings, we propose a novel ensemble model that integrates a Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest (RF), Bagging, and Boosting classifiers. This ensemble model tackles the dataset imbalance problem associated with most credit card datasets by implementing under-sampling and the Synthetic Over-sampling Technique (SMOTE) on some machine learning algorithms. The evaluation of the model utilises a dataset comprising transaction records from European credit card holders, providing a realistic scenario for assessment. The methodology of the proposed model encompasses data pre-processing, feature engineering, model selection, and evaluation, with Google Colab computational capabilities facilitating efficient model training and testing. Comparative analysis between the proposed ensemble model, traditional machine learning methods, and individual classifiers reveals the superior performance of the ensemble in mitigating challenges associated with credit card fraud detection. Across accuracy, precision, recall, and F1-score metrics, the ensemble outperforms existing models. This paper underscores the efficacy of ensemble methods as a valuable tool in the battle against fraudulent transactions. The findings presented lay the groundwork for future advancements in the development of more resilient and adaptive fraud detection systems, which will become crucial as credit card fraud techniques continue to evolve

Carbonic anhydrase influences asymmetric sodium and acetate transport across omasum of sheep

Objective Omasum is an important site for the absorption of short chain fatty acids. The major route for the transport of acetate is via sodium hydrogen exchanger (NHE). However, a discrepancy in the symmetry of sodium and acetate transport has been previously reported, the mechanism of which is unclear. In this study, we investigated the possible role of carbonic anhydrase (CA) for this asymmetry. Methods Omasal tissues were isolated from healthy sheep (N = 3) and divided into four groups; pH 7.4 and 6.4 alone and in combination with Ethoxzolamide. Electrophysiological measurements were made using Ussing chamber and the electrical measurements were made using computer controlled voltage clamp apparatus. Effect(s) of CA inhibitor on acetate and sodium transport flux rate of Na22 and 14C-acetate was measured in three different flux time periods. Data were presented as mean±standard deviation and level of significance was ascertained at p≤0.05. Results Mucosal to serosal flux of Na (JmsNa) was greater than mucosal to serosal flux of acetate (JmsAc) when the pH was decreased from 7.4 to 6.4. However, the addition of CA inhibitor almost completely abolished this discrepancy (JmsNa ≈ JmsAc). Conclusion The results of the present study suggest that the additional protons required to drive the NHE were provided by the CA enzyme in the isolated omasal epithelium. The findings of this study also suggest that the functions of CA may be exploited for better absorption in omasum

Some new lichen records from Pakistan

During a survey of the lichens in the state of Azad Jammu and Kashmir, many specimens were collected from the Jhelum and Neelum valley and characterized using morpho-anatomical, molecular and chemical test methods. Two taxa new for Pakistan, i.e., Physciella chloanta and Xanthoparmelia protomatrae s. l., were found in the collection while Physconia enteroxantha represent range extensions within Pakistan. Morpho-anatomical descriptions, ecology and distribution are provided

Development of Weft Knitted Heating Pads on V-bed Hand Flat Knitting Machine by Using Conductive Yarns

In this investigation weft knitted heating pad was developed on V-bed hand flat knitting machine by using acrylic, polyester as a main yarns  and three different copernic, thermotech –N, thermaram  as conductive yarns with both all knit and inlaid insertion. Moreover time period for heating of yarn, recovery time of yarn for making weft knitted heating pad, structural comparison of different conductive yarn as copernic, thermaram ,thermotech –N  and main yarn as acrylic yarn, polyester yarn was studied. Through analysis conductive yarn that inlaid in the acrylic yarn showed satisfactory heating performance for different time periods and retained more heat rather than polyester yarn. Copernic conductive yarn and thermotech-N conductive yarn had high resistance when compared with thermaram conductive yarn that generated more heat. Acrylic yarn when used as main yarn having conductive thermotech-N yarn inlaid in its structure had produced better heating and retaining properties for the weft knitted heating pad

Enhancing credit card fraud detection: an ensemble machine learning approach

In the era of digital advancements, the escalation of credit card fraud necessitates the development of robust and efficient fraud detection systems. This paper delves into the application of machine learning models, specifically focusing on ensemble methods, to enhance credit card fraud detection. Through an extensive review of existing literature, we identified limitations in current fraud detection technologies, including issues like data imbalance, concept drift, false positives/negatives, limited generalisability, and challenges in real-time processing. To address some of these shortcomings, we propose a novel ensemble model that integrates a Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest (RF), Bagging, and Boosting classifiers. This ensemble model tackles the dataset imbalance problem associated with most credit card datasets by implementing under-sampling and the Synthetic Over-sampling Technique (SMOTE) on some machine learning algorithms. The evaluation of the model utilises a dataset comprising transaction records from European credit card holders, providing a realistic scenario for assessment. The methodology of the proposed model encompasses data pre-processing, feature engineering, model selection, and evaluation, with Google Colab computational capabilities facilitating efficient model training and testing. Comparative analysis between the proposed ensemble model, traditional machine learning methods, and individual classifiers reveals the superior performance of the ensemble in mitigating challenges associated with credit card fraud detection. Across accuracy, precision, recall, and F1-score metrics, the ensemble outperforms existing models. This paper underscores the efficacy of ensemble methods as a valuable tool in the battle against fraudulent transactions. The findings presented lay the groundwork for future advancements in the development of more resilient and adaptive fraud detection systems, which will become crucial as credit card fraud techniques continue to evolve

Design of Multiplexers for IoT-Based Applications Using Stub-Loaded Coupled-Line Resonators

This paper presents the design of microstrip-based multiplexers using stub-loaded coupled-line resonators. The proposed multiplexers consist of a diplexer and a triplexer, meticulously engineered to operate at specific frequency bands relevant to IoT systems: 2.55 GHz, 3.94 GHz, and 5.75 GHz. To enhance isolation and selectivity between the two passband regions, the diplexer incorporates five transmission poles (TPs) within its design. Similarly, the triplexer filter employs seven transmission poles to attain the desired performance across all three passbands. A comprehensive comparison was conducted against previously reported designs, considering crucial parameters such as size, insertion loss, return loss, and isolation between the two frequency bands. The fabrication of the diplexer and triplexer was carried out on a compact Rogers Duroid 5880 substrate. The experimental results demonstrate an exceptional performance, with the diplexer exhibiting a low insertion loss of 0.3 dB at 2.55 GHz and 0.4 dB at 3.94 GHz. The triplexer exhibits an insertion loss of 0.3 dB at 2.55 GHz, 0.37 dB at 3.94 GHz, and 0.2 dB at 5.75 GHz. The measured performance of the fabricated diplexer and triplexer aligns well with the simulated results, validating their effectiveness in meeting the desired specifications.publishedVersio

Sequence and phylogenetic analysis of virulent Newcastle disease virus isolates from Pakistan during 2009–2013 reveals circulation of new sub genotype

AbstractDespite observing the standard bio-security measures at commercial poultry farms and extensive use of Newcastle disease vaccines, a new genotype VII-f of Newcastle disease virus (NDV) got introduced in Pakistan during 2011. In this regard 300 ND outbreaks recorded so far have resulted into huge losses of approximately USD 200 million during 2011–2013. A total of 33 NDV isolates recovered during 2009–2013 throughout Pakistan were characterized biologically and phylogenetically. The phylogenetic analysis revealed a new velogenic sub genotype VII-f circulating in commercial and domestic poultry along with the earlier reported sub genotype VII-b. Partial sequencing of Fusion gene revealed two types of cleavage site motifs; lentogenic 112GRQGRL117 and velogenic 112RRQKRF117 along with some point mutations indicative of genetic diversity. We report here a new sub genotype of virulent NDV circulating in commercial and backyard poultry in Pakistan and provide evidence for the possible genetic diversity which may be causing new NDV out breaks