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Background: During the pandemic, Corona virus forced many people, especially students, to spend more time than before on the computer and smartphone to study and communicate. The poor posture of the body may have worse effect on its body parts , most of which is the cervical spine (forward head posture). Objective: To assess the incidence of neck pain and the associated factors among undergraduate medical students related to position during E learning Subjects and Methods: Cross-sectional study was conducted among medical students in three Iraqi universities during 2021. The sample size was 152. Online questionnaire by Google forms sampling method were used to collect the data which was analysed using SPSS 25. Results: The percentage of students who suffered cervical pain was (80.3%) of the 152 who participated in this study and the majority of those who suffered pain were complained from increase pain during the pandemic (72.1%). This study also showed the students recumbent on the floor 67 (44.1%) more than those who use the table and chair 62 (40.8%) during E-learning. The percentage of students who use the phone for more than 4 hours were (73.7%). Conclusion: there is a relationship between poor posture and cervical pain during E-learning in the pandemic. Most of students were suffering from neck pain with greatest percentage were in those who student in recumbent on the floor and when using chair and table.

Objective: To determine the frequency of dyslipidaemia in type-2 diabetic patients and to compare the frequency of dyslipidaemia in patients with and without microalbuminuria in type 2 diabetes. Study Design: cross-sectional study. Place and Duration of Study: Department of General Medicine, Combined Military Hospital Quetta Pakistan, from Dec 2018 to Jun 2019. Methodology: All patients who fulfilled the inclusion criteria and visited General Medicine department of Combined Military Hospital Quetta with type II diabetes mellitus were included in the study. Blood sample following an 8-12 hours fasting over the last night and 24 hour urine sample for microalbuminuria was collected to assess the outcome i.e. frequency of dyslipidaemia and also its frequency with and without microalbuminuria. Result: A total of 165 patients with type 2 diabetes mellitus were included. Ninety nine (60%) were males and 66 (40%) were females with the mean age of 48.08 ± 7.63 years. Overall, dyslipidaemia was found in 48 (29.1%) patients, dyslipidaemia was noted in 29 (17.6%) with microalbuminuria and 19 (11.5%) without microalbuminuria. Chi-square test revealed that dyslipidaemia was significantly more in patients of diabetes mellites having microalbuminuria than those not having it (p-value=0.01). Conclusion: Abnormal lipid metabolism was present in significantly more in patients with microalbuminuria as compared to those without microalbuminuria suffering from type II diabetes mellitus.

Objective: To find an association between Hyperuricemia and Hypertension in patients presenting in outpatients department for regular check-up. Study design and Setting: Case Control Study design conducted at Pak Emirates Military Hospital Rawalpindi (PEMH), Medical Outpatient department (OPD) from 4th Feb, 2017 to 4th Aug, 2017. Methodology: A total of 200 patients, with 100 cases and 100 controls fulfilling the selection criteria were included in the study, which were selected from Medical OPD of PEMH. An informed written consent was taken. The Demographic such as age, gender were obtained. Veriable upon selection into study group, the blood samples were taken and two groups of patients were made on the basis of normal or raised uric acid levels. The Serum Uric Acid (SUA) was measured in the patients. Then blood pressure was measured by using sphygmomanometer by researchers themselves. If BP level was >140/90mmHg on 2 separate occasions, or patient is already a known case of hypertension, then hypertension was labeled. Results: The mean age (years) in the study was 54.79 + 8.96. There were 136 (68%) male and 64 (32%) female patients. The frequency and percentage of hypertension in cases and control groups was (84%) and (41%) patients respectively which was statistically significant with a p-value of 0.000. The Odds ratio was found to be 7.55. Conclusion: It was concluded that there was an association found between Hyperuricemia and Hypertension

IntroductionThe opioid epidemic is a modern public health emergency. Common interventions to alleviate the opioid epidemic aim to discourage excessive prescription of opioids. However, these methods often take place over large municipal areas (state-level) and may fail to address the diversity that exists within each opioid case (individual-level). An intervention to combat the opioid epidemic that takes place at the individual-level would be preferable.MethodsThis research leverages computational tools and methods to characterize the opioid epidemic at the individual-level using the electronic health record data from a large, academic medical center. To better understand the characteristics of patients with opioid use disorder (OUD) we leveraged a self-controlled analysis to compare the healthcare encounters before and after an individual’s first overdose event recorded within the data. We further contrast these patients with matched, non-OUD controls to demonstrate the unique qualities of the OUD cohort.ResultsOur research confirms that the rate of opioid overdoses in our hospital significantly increased between 2006 and 2015 (P ConclusionsInformatics-based methodologies, like those presented here, may play a role in better understanding those individuals who suffer from opioid dependency and overdose, and may lead to future research and interventions that could successfully prevent morbidity and mortality associated with this epidemic.

The study is presenting the partial shading effects on Photovoltaic arrays. In recent study we are focusing on the photovoltaic array affecting our Solar out of all other atmospheric conditions. Different factors such as atmospheric conditions, configuration of PV cells, shades of nearby objects affects the parameters of Photovoltaic arrays. While harvesting maximum energy from photovoltaic panel it is greatly affected by the partial shading due to different manmade and natural structures. Many of the available models are studied to attain the objectives of maximum power point but two diode model is the most efficient in order to succeed in harvesting concentrated energy through photovoltaic panel. Software to compile the research study will be MATLAB which is very useful for learners and it is a hardest to achieve the MPPT in such conditions. Different studies performed for getting maximum power point but results are unsatisfactory. Many of the available models are studied to attain the goal of MPPT but double diode model is the most efficient because its make possible to get maximum power through PV panel.

PURPOSE: Lung protective ventilation (LPV), defined as a tidal volume (Vt) ≤8cc/kg of predicted body weight, reduces ventilator-induced lung injury but is applied inconsistently. MATERIALS AND METHODS: We conducted (1) a prospective, quasi-experimental, cohort study of adults mechanically ventilated admitted to intensive care units (ICU) in the year before, year after, and second year after implementation of an electronic medical record based LPV order, and (2) a cross-sectional qualitative study of ICU providers regarding their perceptions of the order. We applied the Reach, Efficacy, Adoption, Implementation, and Maintenance (RE-AIM) framework to evaluate the implementation. RESULTS: There were 1405, 1424, and 1342 in the control, adoption, and maintenance cohorts, representing 95% of mechanically ventilated adult ICU patients. The overall prevalence of LPV increased from 65% to 73% (p

BACKGROUND: Multimodal analgesia (MMA) may reduce opioid use after surgery for Chiari malformation type I. An MMA protocol was implemented after both posterior fossa decompression without dural opening (PFD) and posterior fossa decompression with duraplasty (PFDD). METHODS: Scheduled nonsteroidal antiinflammatory drugs (ketorolac or ibuprofen) and diazepam were alternated with acetaminophen, and as-needed oxycodone or intravenous morphine. The primary outcome was total opioid requirement over postoperative days 0 to 2. RESULTS: From 2012 to 2017, 49 PFD and 29 PFDD procedures were performed, and 46 of 78 patients used the protocol. Patients with PFD required less opioids than patients with PFDD. Among patients with PFDD, patients with MMA protocol usage had a lower mean opioid requirement than patients with no MMA protocol usage (0.53 ± 0.49 mgEq/kg versus 1.4 ± 1.0 mgEq/kg, P = .0142). In multivariable analysis, MMA protocol usage status independently predicted a mean decrease in opioid requirement of 0.146 mg equivalents/kg (P = .0497) after adjustment for procedure and surgeon. Statistically significant differences were not demonstrated in antiemetic requirements, discharge opioid prescriptions, total direct cost, and length of stay. CONCLUSIONS: A protocol of scheduled nonsteroidal antiinflammatory drugs alternating with scheduled acetaminophen and diazepam was associated with opioid use reductions.

Climate change can significantly affect water quality, in addition contributing non-stationarity and deep uncertainty that complicates water quality management. But most of the total maximum daily load (TMDL) implementation plans crafted to meet water quality standards in the USA are developed assuming stationary climate and at best a small number of land use futures, although neither assumption seems reliably justified. To address this challenge, this study employs robust decision making (RDM) methods, commonly used to help develop water supply plans, to stress test the proposed Enhanced Watershed Management Plan (EWMP), a TMDL implementation plan, for the Tujunga Wash, the largest subwatershed of the Los Angeles River, over a wide range of climate and land use futures. We find that climate change could significantly reduce the ability of the Tujunga EWMP to meet water quality goals; however, meeting the city’s goals for increasing permeable land cover offsets the risk of non-compliance in the face of climate change uncertainties. This study also introduces innovations in RDM analyses, including: treatment of the deeply uncertain incidence of extreme precipitation events, an explicit link between RDM scenario discovery methods and the specification of signposts for adaptive policy pathways, and the use of (imprecise) probabilistic climate projections to inform the choice among robust adaptive policy pathways. The paper also contributes to a larger debate over how to address climate and other uncertainties in regulatory processes involving water quality.

OBJECTIVES: Multimodal analgesia (MMA) may reduce opioid use among children who are hospitalized, and may contribute toward enhanced recovery after selective dorsal rhizotomy (SDR) for patients with spasticity in pediatric cerebral palsy. In this retrospective cohort study, we assess an MMA protocol consisting of scheduled nonsteroidal antiinflammatory drug doses (ketorolac or ibuprofen), alternating with scheduled acetaminophen and diazepam doses, with as-needed opioids. It was hypothesized that protocol use would be associated with reductions in opioid requirements and other clinical improvements. METHODS: Data were obtained for 52 patients undergoing SDR at an academic tertiary care pediatric hospital (2012–2017, with the protocol implemented in 2014). Using a retrospective cohort design, we compared outcomes between protocol and nonprotocol patients, employing both univariate t test and Wilcoxon rank test comparisons as well as multivariable regression methods. The primary outcome was total as-needed opioid requirements over postoperative days (PODs) 0 to 2, measured in oral morphine milligram equivalents per kilogram. Additional outcomes included antiemetic medication doses, discharge opioid prescriptions, total direct cost, and length of stay. RESULTS: Twelve patients received the MMA protocol, and 40 patients did not. POD-0 MMA initiation was independently associated with a reduction of 0.14 morphine milligram equivalents per kilogram in mean opioid requirements over PODs 0 to 2 in the multiple regression analysis (95% confidence interval 0.01 to 0.28; P = .04). No statistically significant differences were demonstrated in doses of antiemetic medications, discharge opioid prescriptions, total direct cost, and length of stay. CONCLUSIONS: This MMA protocol may help reduce opioid use after SDR. Improving protocol implementation in a prospective, multisite study will help elucidate further MMA effects on pain, costs, and recovery.

Objective: To determine frequency of vitamin D deficiency in female patients presenting with non-specific musculoskeletal symptoms.Study Design: Descriptive cross sectional.Place and Duration of Study: The study was conducted in Medical Outpatient Department (OPD), Combined Military Hospital (CMH) Quetta from 30th November 2018 to 30th May 2019.Materials and Methods: A total of 150 female patients with nonspecific musculoskeletal symptoms were included. Patients on vitamin D supplements, osteopenia, osteoporosis, chronic kidney disease, neuropathies, cancers, diabetes mellitus, iron and Vitamin B12 deficiency were excluded. Data including gender, age and presence of bone pain, muscle aches, bone tenderness and fracture was collected. SPSS v 17 was used for data analysis. Chi-square test was applied to test for associations, p value less than 0.05 was taken as significant.Results: The mean age was 37.20 + 13.30 years. Mean Vitamin D levels were 14.89 + 7.76 ng/ml with range from 3.10 to 35.67ng/ml. Participants with vitamin D3 < 10 ng/ml were 24% (n=36), < 20 ng/ml were 54% (n= 81)

This work reports the application of ensemble artificial neural networks, a machine learning technique, in the solution of short term optimal power generation on the IEEE 30-bus test system. The study, carried out using MATLAB, is being reported. The motive for using ensemble artificial neural networks has been to take advantage of multiple parallel processors computing rather than the traditional serial computation. The Bootstraps are obtained through small bags in the Bagging algorithm and are combined by averaging. Employing ensemble neural networks reduces bias and variance in machine learning so that the overall error is reduced, and hence better prediction can be achieved. The results obtained from the proposed algorithm are compared with those from the other heuristic and conventional techniques to validate the effectiveness of the proposed methodology.

Objective: To assess the prevalence of abnormal radiological changes and their impact on lung function in post tuberculosis cases. Study Design: Descriptive cross-sectional study. Place and Duration of Study: The study was conducted in medical Outpatient Department (OPD) of CMH, Quetta from 30th Nov 2018 to 30th May 2019. Materials and Methods: A total of sixty treated cases of pulmonary tuberculosis, presenting in medical OPD of CMH Quetta for regular follow-up, were included in the study. The subjects were recruited by non-probability consecutive sampling technique according to predefined inclusion criteria. Demographic data including age, gender, post treatment duration, clinical features and history of asthma, atopy, rhinitis, biomass exposure, coalmine exposure, animal and pet exposure was collected. Their lung function was assessed using spirometry and radiological changes were assessed by either chest X-ray or high resolution CT chest. Results: Among the 60 patients, mean age was 36.32 + 9.95 years. The majority (70%) of subjects were males (n=42).The mean duration post treatment was 4.79 + 4.25 years. Among the study population 51.7% (n=31) were symptomatic, 73.3% (n=44) had abnormal lung function tests. With those having abnormal lung functions tests, 23.3% (n=14) had obstructive, 43.3% (n=26) had restrictive and 6.7% (n=4) had mixed airway disease. The radiological investigations were abnormal in 80% (n=48) of the patients showing various radiological changes such as reticular shadows, nodules, pleural thickening, collapse, fibrotic bands, hilar calcifications, lung volume reduction and traction bronchiectasis. Conclusion: Our study showed that the restrictive pattern was most common finding on spirometry while, fibrotic bands were the most common radiological findings in post tuberculosis cases in our population.

Introduction The present study investigated the relationship between psychological symptoms and psychosocial function and the role of relevant sociodemographic data and antipsychotic use in the prediction of psychosocial function among multiracial schizophrenia outpatients in Malaysia. Methods A total of 223 participants were recruited in this cross-sectional study conducted from December 2010 to April 2011. Psychological symptoms were assessed using the Positive and Negative Syndrome Scale whilst the psychosocial function was assessed using the Personal and Social Performance scale. Sociodemographic and treatment variables were gathered through interview or review of the medical records. Results All dimensions of psychosocial functions were inversely correlated with Positive and Negative Syndrome Scale sub-domains. Only the disorganization sub-domain significantly predicts all dimensions of psychosocial function. For social data, body mass index and employment status were significant predictors of all dimensions of psychosocial functions. Typical antipsychotics significantly predict social function negatively as compared to sulpiride (β = −0.152, P = 0.028). Discussion We found that the relationship between psychological symptoms and psychosocial functions were relatively consistent with the findings from the Caucasian population. Additionally, disorganization was the only significant predictor of all dimensions of psychosocial functions. This further emphasized the importance of cognition in psychosocial function. The roles of sulpiride, body mass index and employment status as predictors of psychosocial function were also discussed.

Three essays exploring large discrepancies between different panel datasets of cross-country estimates of gross domestic product.

This paper presents a methodology of calculating the optimal torque and speed commands for the engine-generator system of a series hybrid electric vehicle (HEV). In series HEVs, the engine-generator subsystem provides electrical energy to the dc link. This paper proposes an optimal control strategy of the engine-generator subsystem to generate a desired amount of energy within a given period of time. The optimization algorithm, based on trajectory optimization, determines the torque and speed reference signals for the engine-generator subsystem that achieve maximum efficiency. A simplified version of the controller is also presented for online implementation. The proposed control strategy is compared with nonoptimized control techniques, and simulation results show the improvements in energy efficiency.

Although interior permanent magnet synchronous machines and their cooling are designed to match the rated power, power demands other than rated may arise. One may keep the same machine dimensions and basic electromagnetic design, but increase the cooling for different operating conditions. Modifications of the cooling system can compensate for the increase in machine losses in the windings, magnets, or iron. Increasing the allowed stator current affects the machine performance in other ways as well. These include demagnetization of the magnets, and hence, shrinking of the speed range to avoid this. In this paper, these effects are studied for a baseline machine, as well as for machines with the same stator but modified rotor design. A cross-saturated model is developed and shown to be more accurate than the classic one. To account for higher stator current with higher temperatures, the effects on efficiency, torque, and speed range by changing the magnet material from the more commonly used NdFeB to SmCo are also studied and discussed.

We present a faster and simpler approach for the calculation of iron and magnet losses and torque of an interior permanent-magnet synchronous machine (IPMSM) than finite-element methods (FEM). It uses a magnetic equivalent circuit (MEC) based on large elements and takes into account magnetic saturation and magnet eddy currents. The machine is represented by nonlinear and constant reluctance elements and flux sources. Solution of the nonlinear magnetic circuit is obtained by an iterative method. The results allow the calculation of losses and torque of the machine. Due to the approximations used in the formulation of the MEC, this method is less accurate but faster than nonlinear transient magnetic FEM, and is more useful for the comparison of different machine designs during design optimization.

A lumped parameter thermal analysis of permanent magnet motor by considering real driving duty cycle is presented. As driving motors of electric vehicle, permanent magnet motors exhibit high efficiency and high power density. However, they are susceptible to suffer irreversible demagnetization and insulation failure of coils under severe thermal condition. Therefore, it is essential to accurately evaluate heat losses and precisely predict temperature distribution in driving motors under the real driving duty cycle. In this paper, an improved core loss model is employed and implemented by using finite element method. The thermal behavior of the driving motor is analyzed by means of lumped thermal parameter method. A test bench has been set up to measure the temperature distribution in the driving motor. The calculation and experiment results are compared and discussed.

Special agents for protein capture: Iterative in situ click chemistry (see scheme for the tertiary ligand screen) and the one-bead-one-compound method for the creation of a peptide library enable the fragment-based assembly of selective high-affinity protein-capture agents. The resulting ligands are water-soluble and stable chemically, biochemically, and thermally. They can be produced in gram quantities through copper(I)-catalyzed cycloaddition.

Purpose: The main aim of this study is to compare two different cultures in terms of ethical and legal use of music sharing technology. Students’ perceptions of downloading from web and sharing music with each other varies across cultures. Such practices have caused significant losses to music and film industry. Methodology/Sampling: Primary data was collected from Morocco and US university students on a pretested questionnaire. Besides frequency distributions, chi-square, t-test and confirmatory factor analysis were used as inferential tools. Findings: Results showed a considerable difference in between Moroccan and American students’ attitude in terms of music files sharing and downloading. Compare to Moroccans, American students were more aware of ethical, and legal aspects of music file sharing and download from web. Practical Implications: Research findings suggests music industry should focus on making music products more affordable and create awareness towards music piracy through promotional campaigns keeping in mind the cultural differences of end users. The research findings will set a platform for further comparative studies in the same context. Keywords: File Sharing, Piracy, Free downloads, Cross-Culture.

Permanent magnet synchronous machines (PMSMs) are widely used as traction machines in the hybrid and electrical vehicles (HEVs) due to their high power density, wide field weakening range and high efficiency. An optimized and efficient design of PMSMs depends upon the driving cycle requirements and consideration of losses of every subsystem in the traction drive. Efficiency of a traction drive over a driving cycle is more important than the efficiency of the traction machine at one operating point. This paper presents an approach for the design of PMSMs based upon the average driving cycle efficiency (ADCE) of traction drive for an urban series hybrid bus for a specific driving cycle. It includes the efficiency of machine, inverter as well as the energy utilized by their cooling systems. The proposed approach was applied to two different machines to demonstrate its validity.

To reduce cost and improve efficiency, a novel design concept of a traction motor for electric vehicle based on a driving cycle is proposed. In comparison with conventional design method of electric motors, the proposed design concept considers the real load condition and highlights special requirements of electric vehicle. Based on the proposed approach, an interior permanent magnet traction motor is designed with high average efficiency overall operation region. The thermal behavior of the designed traction motor is investigated and the temperature distribution in key parts under the driving cycle is obtained. To verify validity and generality of the proposed designed concept, a surface mount permanent magnet traction motor is designed and evaluated by experiment.

High power Interior Permanent Magnet Synchronous Machines (IPMSM) are used extensively in hybrid vehicle applications due to their high power density, wide speed range and better efficiency. In general, a high power IPMSM and its cooling is designed according to its rated power. Depending upon the application, specific power demand (other than rated) may arise to run the same machine at less or more than rated current. One may like to keep the same machine but change its cooling. Modification in machine cooling can compensate for the increase in machine losses due to its current change. The design of such a machine needs special attention because every machine designed for rated current may not be used continuously at current greater than that. In this paper, the operational range of a baseline machine design is presented and analyzed at less as well as more than rated current, using a cross saturated dq model. It is imperative to consider the demagnetization limit of permanent magnets in the analysis of machine operation. Different machine designs are presented and compared for torque-speed profile and efficiency at different current conditions with increased machine cooling. Machine design with increased width of permanent magnets provides more wider operating region at the cost of reduction in its efficiency for higher speeds.

This paper presents the methodology to design an optimal speed controller (total losses minimization) of an IPMSM for traction applications. IPMSMs have high efficiency, however to exploit that efficiency it is required to design an optimal control, with the capability to accurately calculate and command the current components for the whole range. The speed controller is optimized by calculating the optimal trajectory between two points, defined by their torque and speed. The trajectory calculation is made in two stages: current space vector calculation based on the concept of maximum torque per ampere and optimal trajectory calculation. The first stage corresponds to the calculation of the optimal magnitude and angle of the current space vector for any given torque and speed point, maximum torque per ampere is the control technique selected for the IPMSM model inversion. The second stage involves calculating the currents that define the trajectory from one point to another, with minimal copper losses. The proposed optimization is numerical, constrained, based on the steepest descent method. Simulation and experimental results are presented to validate the proposed methodology.

This paper presents a faster and simpler approach for the calculation of iron and magnet losses of an IPMSM than Finite Element Analysis. It uses large elements and takes into account the magnetic saturation and magnet eddy currents. The machine is represented by its magnetic equivalent circuit, consisting of non-linear and constant reluctance elements and flux sources. Solution of non-linear magnetic circuit is obtained by an iterative method. The results allow the calculation of losses and efficiency of the machine. Owing to the approximations used in the formulation of the magnetic equivalent circuit, this method is less accurate but faster than non-linear transient magnetic FEM, and is more useful for the comparison of different machine designs during design optimization process.