Association of vitamin D with statin induced myalgia

Objective: To determine the association of serum 25-hydroxy vitamin D (25(OH) Vitamin D) deficiency with the occurrence of myalgia in patients on statin therapy. Methods: The pathology laboratory database was reviewed to identify patients tested for serum 25(OH) Vitamin D and creatine kinase. A retrospective chart review was then conducted to ascertain statin use and reporting of myalgia for patients tested concurrently for serum 25(OH) vitamin D and creatinekinase levels between January 1, 2013 and December 31, 2013. Results: Of the 825 patients tested for creatine kinase and 25 (OH) Vitamin D in 2013, 49 met the study criteria.The mean serum 25 (OH) Vitamin D level in the 24 statin induced myalgiapatients was 17.93 ± 12.07 compared to 18.99 ± 15.2 in the 25 no SIM group (p = 0.81). Conclusion: Our study reports no association between statin induced myalgia and low 25 (OH) vitamin D levels

The Nexus of Ethical Leadership, Job Performance, and Turnover Intention: The Mediating Role of Job Satisfaction

This study aims to examine the impact of ethical leadership on employees’ job satisfaction, performance, and turnover intention. A conceptual framework is developed which clearly integrates job satisfaction as a mediating mechanism in explaining the nexus among ethical leadership, job performance, and turnover intention. This framework is then analysed employing data from a sample (n = 114) of tourist companies in Lahore, Pakistan. The results reveal that ethical leadership has positive effect on employees’ job satisfaction, performance and has negative effect on their turnover intentions. Further, job satisfaction positively mediates the effect of ethical leadership on employees’ job performance and turnover intentions. The findings recommend that the demonstration of ethical leadership behaviours by managers at workplace enhances employees’ job satisfaction and performance, and decreases the intention of employees to leave the job. The main narrative of this study encompasses the imperative role of ethical leadership in the workplace where it serves as a factor that enhances employees’ job satisfaction, performance, and decreases turnover intention. This research explicitly demonstrates that in Pakistani tourism sector, ethical leadership plays a vital role to achieve performance goals. Future research could analyse the said nexus in different sectors and cultures, and may also consider other measures of individual performance. The consideration of job satisfaction as mediating variable in probing the linkages among ethical leadership, job performance, and turnover intention in the context of the workplace in Pakistan and the analysing of this linkage is novel

An Enhanced Energy Balanced Data Transmission Protocol for Underwater Acoustic Sensor Networks.

This paper presents two new energy balanced routing protocols for Underwater Acoustic Sensor Networks (UASNs); Efficient and Balanced Energy consumption Technique (EBET) and Enhanced EBET (EEBET). The first proposed protocol avoids direct transmission over long distance to save sufficient amount of energy consumed in the routing process. The second protocol overcomes the deficiencies in both Balanced Transmission Mechanism (BTM) and EBET techniques. EBET selects relay node on the basis of optimal distance threshold which leads to network lifetime prolongation. The initial energy of each sensor node is divided into energy levels for balanced energy consumption. Selection of high energy level node within transmission range avoids long distance direct data transmission. The EEBET incorporates depth threshold to minimize the number of hops between source node and sink while eradicating backward data transmissions. The EBET technique balances energy consumption within successive ring sectors, while, EEBET balances energy consumption of the entire network. In EEBET, optimum number of energy levels are also calculated to further enhance the network lifetime. Effectiveness of the proposed schemes is validated through simulations where these are compared with two existing routing protocols in terms of network lifetime, transmission loss, and throughput. The simulations are conducted under different network radii and varied number of nodes

Frequency of etiologies of acute kidney injury in Faisalabad and surrounding districts

Background: To find out the causes of Acute Kidney Injury (AKI) in population.Methods: A total of 150 patients were enrolled from medical, surgical, gynecology and obstetrics units of Allied Hospital and Madinah Teaching Hospital, Faisalabad, Pakistan. History, physical examination and investigations were recorded on specially designed proforma. Patients were evaluated to find out the etiologies of AKI. All patients were subjected to urine analysis, complete blood count, blood biochemistry (urea, creatinine, electrolytes, uric acid, calcium and phosphorus) and ultrasound scan of the abdomen and pelvis. Renal biopsy, immunological assays, such as hepatitis B surface antigen, anti-hepatitis C virus antibody, complements level, antinuclear antibody, anti-double-stranded DNA, anti-neutrophil cytoplasmic antibody and anti-glomerular basement membrane antibody were performed in selected cases.Results: Male (36%) and female (64%). Pre-renal AKI was most common and was reported in 80 patients (53.33%). Intrinsic Renal azotemia in 56 patients (37.33%). Post renal azotemia in 14 patients (9.33%). Among 80 patients of prerenal AKI, hemorrhage in 45(56.25%), gastroenteritis in 16(20%), sepsis in 8(10%), cardiac diseases in 4(5%), hepatorenal syndrome in 3 (3.75%), peritonitis in 2 (2.50%) and burns in 2(2.50%) were the main causes of Pre-renal AKI. Among 56 patients of intrinsic renal AKI, 40(71.4%) had acute tubular necrosis (ATN), 12(21.4%) with multifactorial causes and 4(7.14%) were found to have glomerulonephritis. Among 14 patients of post renal AKI, 6(42.9%) were having calculi, 6(42.9%) were to have enlarged prostate and 2(4.3%) were having stricture urethra. In this study, contribution of obstetrical, medical and surgical etiologies were recorded as 40%, 36% and 20% respectively.Conclusions: In contrast to study reported from neighbouring country, this study shows rather increase in pregnancy related AKI

A Review on the Role of Nano-Communication in Future Healthcare Systems: A Big Data Analytics Perspective

This paper presents a first-time review of the open literature focused on the significance of big data generated within nano-sensors and nano-communication networks intended for future healthcare and biomedical applications. It is aimed towards the development of modern smart healthcare systems enabled with P4, i.e. predictive, preventive, personalized and participatory capabilities to perform diagnostics, monitoring, and treatment. The analytical capabilities that can be produced from the substantial amount of data gathered in such networks will aid in exploiting the practical intelligence and learning capabilities that could be further integrated with conventional medical and health data leading to more efficient decision making. We have also proposed a big data analytics framework for gathering intelligence, form the healthcare big data, required by futuristic smart healthcare to address relevant problems and exploit possible opportunities in future applications. Finally, the open challenges, future directions for researchers in the evolving healthcare domain, are presented

Functional quality of optimized peach‐based beverage developed by application of ultrasonic processing

The influence of thermal treatment (at 90°C for 10 min) and sonication (at 20 kHz and 130 W for 30, 60, and 90 min on room temperature) on the physicochemical properties, bioactive compounds, antioxidant activity, and organic acids of fresh formulated functional peach beverage was investigated. The results indicated that conventional pasteurization and sonication treatment did not show any significant changes in pH value and Brix amount of juice, and however, a rise in cloud value was observed under all processing conditions. The thermal treatment caused the decrement in total phenolic content (TPC), total flavonoid content (TFC), antioxidant activity (assessed by diphenyl dipicryl hydrazyl (DPPH), ferric ion reducing antioxidant power (FRAP) and 2,2'‐azino‐bis(3‐ethylbenzothiazoline‐6‐sulfonic acid) (ABTS)), and organic acids of juice, whereas sonication treatment for 90 min increased maximum the activity of bioactive compounds (TPC: 600.61 µg/100 ml; TFC: 177 µg CE/100 ml), antioxidants (DPPH: 51.87%; FRAP: 506.13 µmol Trolox/L; ABTS: 1,507.375 µmol Trolox/L), and organic acids (malic acid: 998; citric acid: 128; oxalic acid: 145; shikimic acid: 63 µg/100 ml) as compared to other treatment conditions and control. Multivariate data analysis was done by principal component analysis as it identifies patterns in data by comparing data sets which is further expressed based on their similarities and discriminations, respectively

A novel algorithm for dynamic student profile adaptation based on learning styles

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.E-learning recommendation systems are used to enhance student performance and knowledge by providing tailor- made services based on the students’ preferences and learning styles, which are typically stored in student profiles. For such systems to remain effective, the profiles need to be able to adapt and reflect the students’ changing behaviour. In this paper, we introduce new algorithms that are designed to track student learning behaviour patterns, capture their learning styles, and maintain dynamic student profiles within a recommendation system (RS). This paper also proposes a new method to extract features that characterise student behaviour to identify students’ learning styles with respect to the Felder-Silverman learning style model (FSLSM). In order to test the efficiency of the proposed algorithm, we present a series of experiments that use a dataset of real students to demonstrate how our proposed algorithm can effectively model a dynamic student profile and adapt to different student learning behaviour. The results revealed that the students could effectively increase their learning efficiency and quality for the courses when the learning styles are identified, and proper recommendations are made by using our method

A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics

This is an accepted manuscript of an article published by IEEE in IEEE Transactions on Intelligent Transportation Systems on 04/01/2022. Available online: https://doi.org/10.1109/TITS.2021.3138255 The accepted version of the publication may differ from the final published version.The dependency on vehicles is increasing tremendously due to its excellent transport capacity, fast, efficient, flexible, pleasant journey, minimal physical effort, and substantial economic impact. As a result, the demand for smart and intelligent feature enhancement is growing and becoming a prime concern for maximum productivity based on the current perspective. In this case, the Internet of Everything (IoE) is an emerging concept that can play an essential role in the automotive industry by integrating the stakeholders, process, data, and things via networked connections. But the unavailability of intelligent features leads to negligence about proper maintenance of vehicle vulnerable parts, reckless driving and severe accident, lack of instructive driving, and improper decision, which incurred extra expenses for maintenance besides hindering national economic growth. For this, we proposed a conceptual framework for a central VHMS exploiting IoE-driven Multi-Layer Heterogeneous Networks (HetNet) and a machine learning technique to oversee individual vehicle health conditions, notify the respective owner driver real-timely and store the information for further necessary action. This article transparently portrayed an overview of central VHMS and proposed the taxonomy to achieve such an objective. Subsequently, we unveiled the framework for central VHMS, IoE-driven Multi-tire HetNet, with a secure and trustworthy data collection and analytics system. Finally, anticipating this proposition’s outcome is immense in the automotive sector. It may motivate the researcher to develop a central intelligent and secure vehicular condition diagnostic system to move this sector towards Industry 4.0.The authors would like to thank University Malaysia Pahang for providing the laboratory facilities and financial support under the University FLAGSHIP Research Grants (Project number RDU192203), International Matching Grant (No. RDU192704), and Postgraduate Research Scheme Grant (No. PGRS200325)

Permeance Based Algorithm For Computation Of Flux Linkage Characteristics Of Non-Linear 6/4 Switched Reluctance Motor (SRM)

The concept of permeance is used in the analysis of flux linkage of 6/4 SRM. The aim of this paper is to develop an efficient algorithm exploiting the nonlinear feature of the 6/4 SRM using the aforementioned concept of permeance. The first step is to generate the relevant equations related to permeances of the 6/4 SRM under study. The 6/4 SRM’s magnetization curve is then derived from the summation of mmf drops at various blocks representing the motor. The air gap permeances are derived at various angles and 3-D leakage effects are taken into account. These permeances are used for the mmf drop computation. The algorithm is capable of efficiently computing mmf drop at every block to consequently yield a complete accurate nonlinear flux linkage feature of the 6/4 switched reluctance motor. In this way, the capability of the SRM to produce the expected four times the specific output torque due to operation in high saturation region compared to an equivalent induction motor as special the attribute of the SRM is demonstrated