Search results for: clinical trial optimization

Authors: Melissa Langevin, Natalie Ward, Colleen Fitzgibbons, Christa Ramsey, Melanie Hogue, Anna Theresa Lobos

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Description: Root Cause Analysis (RCA) is used by health care teams to examine adverse events (AEs) to identify causes which then leads to recommendations for prevention Despite widespread use, RCA has limitations. Best practices have not been established for implementing recommendations or tracking the impact of interventions after AEs. During phase 1 of this study, we used simulation to analyze two fictionalized AEs that occurred in hospitalized paediatric patients to identify and understand how the errors occurred and generated recommendations to mitigate and prevent recurrences. Scenario A involved an error of commission (inpatient drug error), and Scenario B involved detecting an error that already occurred (critical care drug infusion error). Recommendations generated were: improved drug labeling, specialized drug kids, alert signs and clinical checklists. Aim: Use simulation to optimize interventions recommended post critical event analysis prior to implementation in the clinical environment. Methods: Suggested interventions from Phase 1 were designed and tested through scenario simulation in the clinical environment (medicine ward or pediatric intensive care unit). Each scenario was simulated 8 times. Recommendations were tested using different, voluntary teams and each scenario was debriefed to understand why the error was repeated despite interventions and how interventions could be improved. Interventions were modified with subsequent simulations until recommendations were felt to have an optimal effect and data saturation was achieved. Along with concrete suggestions for design and process change, qualitative data pertaining to employee communication and hospital standard work was collected and analyzed. Results: Each scenario had a total of three interventions to test. In, scenario 1, the error was reproduced in the initial two iterations and mitigated following key intervention changes. In scenario 2, the error was identified immediately in all cases where the intervention checklist was utilized properly. Independently of intervention changes and improvements, the simulation was beneficial to identify which of these should be prioritized for implementation and highlighted that even the potential solutions most frequently suggested by participants did not always translate into error prevention in the clinical environment. Conclusion: We conclude that interventions that help to change process (epinephrine kit or mandatory checklist) were more successful at preventing errors than passive interventions (signage, change in memory aids). Given that even the most successful interventions needed modifications and subsequent re-testing, simulation is key to optimizing suggested changes. Simulation is a safe, practice changing modality for institutions to use prior to implementing recommendations from RCA following AE reviews.

Keywords: adverse events, patient safety, pediatrics, root cause analysis, simulation

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Authors: Amy Claridge, Tishra Beeson

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Background: Maternal depression is a serious health concern impacting between 10-16% of birthing persons. It is associated with difficulty in emotional interaction and the formation of attachment bonds between parent and infant. Longitudinally, maternal depression can have severe, lasting impacts on both parent and child, increasing the risk for mental, social, and physical health issues. Rates of prenatal depression have been higher among individuals who were pregnant during the first year of the COVID-19 pandemic. Pregnant persons are considered a high-risk group for poor clinical outcomes from COVID-19 infection and may also have faced or continue to face additional stressors such as financial burdens, loss of income or employment, and the benefits accompanying employment, especially among those in the United States (U.S.). It is less clear whether individuals who gave birth during the pandemic continue to experience high levels of depressive symptoms or whether symptoms have been reduced as a pandemic response has shifted. The current study examined longitudinal reports of depressive symptoms among individuals in the U.S. who gave birth between March 2020 and September 2021. Methods: This mixed-method study involved surveys and interviews with birthing persons (18-45 years old) in their third trimester of pregnancy and at 8 weeks postpartum. Participants also completed a follow-up survey at 12-18 months postpartum. Participants were recruited using convenience methods via an online survey. Survey participants included 242 U.S. women who self-reported depressive symptoms (10-item Edinburgh Postnatal Depression Scale) at each data collection wave. A subset of 23 women participated in semi-structured prenatal and 8-week postpartum qualitative interviews. Follow-up interviews are currently underway and will be integrated into the presentation. Preliminary Results: Prenatal depressive symptoms were significantly positively correlated to 8-week and 12-18-month postpartum depressive symptoms. Participants who reported clinical levels of depression prenatally were 3.29 times (SE = .32, p < .001) more likely to report clinical levels of depression at 18 months postpartum. Those who reported clinical depression at 8-weeks postpartum were 6.52 times (SE = .41, p < .001) more likely to report clinical levels of depression at 18 months postpartum. Participants who gave birth earlier in the pandemic reported significantly higher prenatal (t(103) = 2.84, p < .01) and 8-week postpartum depressive symptoms (t(126) = 3.31, p < .001). Data from qualitative interviews contextualize the findings. Participants reported negative emotions during pregnancy, including sadness, grief, and anxiety. They attributed this in part to their experiences of pregnancy during the pandemic and uncertainty related to the birth experience and postpartum period. Postpartum interviews revealed some stressors specific to childbirth during the COVID-19 pandemic; however, most women reflected on positive experiences of birth and postpartum. Conclusions: Taken together, findings reveal a pattern of persistent depressive symptoms among U.S. parents who gave birth during the pandemic. Depressive symptoms are of significant concern for the health of parents and children, and the findings of this study suggest a need for continued mental health intervention for parents who gave birth during the pandemic. Policy and practice implications will be discussed.

Keywords: maternal mental health, perinatal depression, postpartum depression, covid-19 pandemic

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Authors: Mohammed Mohsin Ali H., Mohamed Haneef

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The connecting rod transmits the piston load to the crank causing the latter to turn, thus converting the reciprocating motion of the piston into a rotary motion of the crankshaft. Connecting rods are subjected to forces generated by mass and fuel combustion. This study investigates and compares the fatigue behavior of forged steel, powder forged and ASTM a 514 steel cold quenched connecting rods. The objective is to suggest for a new material with reduced weight and cost with the increased fatigue life. This has entailed performing a detailed load analysis. Therefore, this study has dealt with two subjects: first, dynamic load and stress analysis of the connecting rod, and second, optimization for material, weight and cost. In the first part of the study, the loads acting on the connecting rod as a function of time were obtained. Based on the observations of the dynamic FEA, static FEA, and the load analysis results, the load for the optimization study was selected. It is the conclusion of this study that the connecting rod can be designed and optimized under a load range comprising tensile load and compressive load. Tensile load corresponds to 360^o crank angle at the maximum engine speed. The compressive load is corresponding to the peak gas pressure. Furthermore, the existing connecting rod can be replaced with a new connecting rod made of ASTM a 514 steel cold quenched that is 12% lighter and 28% cheaper.

Keywords: connecting rod, ASTM a514 cold quenched material, static analysis, fatigue analysis, stress life approach

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Authors: Veronica Sorgato, Jeremy Belhassen, Philippe Chartier, Roddy Sihanath, Nicolas Docquiere, Jean-Yves Giraud

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We analyzed the image-guided radiotherapy method used by the TomoTherapy® System (Accuray Corp.) for patient repositioning in clinical routine. The TomoTherapy® System computes X, Y, Z and roll displacements to match the reference CT, on which the dosimetry has been performed, with the pre-treatment MV CT. The accuracy of the repositioning method has been studied according to the treatment localization. For this, a database of 18774 treatment sessions, performed during 2 consecutive years (2016-2017 period) has been used. The database includes the X, Y, Z and roll displacements proposed by TomoTherapy® System as well as the manual correction of these proposals applied by the radiation therapist. This manual correction aims to further improve the repositioning based on the clinical situation and depends on the structures surrounding the target tumor tissue. The statistical analysis performed on the database aims to define repositioning limits to be used as security and guiding tool for the manual adjustment implemented by the radiation therapist. This tool will participate not only to notify potential repositioning errors but also to further improve patient positioning for optimal treatment.

Keywords: accuracy, IGRT MVCT, image-guided radiotherapy megavoltage computed tomography, statistical analysis, tomotherapy, localization

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Authors: Sunghee Nam

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Entomopathogenic fungi is a Cordyceps species that is isolated from dead silkworm and cicada. Fungi on cicadas were described in old Chinese medicinal books and from ancient times, vegetable wasps and plant worms were widely known to have active substance and have been studied for pharmacological use. Among many fungi belonging to the genus Cordyceps, Cordyceps sinensis have been demonstrated to yield natural products possessing various biological activities and many bioactive components. Generally, It is commonly used to replenish the kidney and soothe the lung, and for the treatment of fatigue. Due to their commercial and economic importance, the demand for Cordyceps has been rapidly increased. However, a supply of Cordyceps specimen could not meet the increasing demand because of their sole dependence on field collection and habitat destruction. Because it is difficult to obtain many insect hosts in nature and the edibility of host insect needs to be verified in a pharmacological aspect. Recently, this setback was overcome that P. tenuipes was able to be cultivated in a large scale using silkworm as host. Pharmacological effects of P. tenuipes cultured on silkworm such as strengthening immune function, anti-fatigue, anti-tumor activity and controlling liver etc. have been proved. They are widely commercialized. In this study, we attempted to establish a method for stable growth inhibition of P. tenuipes on silkworm hosts and an optimal condition for synnemata formation. To determine optimum culturing conditions, temperature and light conditions were varied. The length and number of synnemata was highest at 25℃ temperature and 100~300 lux illumination. On an average, the synnemata of wild P. tenuipes measures 70 ㎜ in length and 20 in number; those of the cultured strain were relatively shorter and more in number. The number of synnemata may have increased as a result of inoculating the host with highly concentrated conidia, while the length may have decreased due to limited nutrition per individual. It is not able that changes in light illumination cause morphological variations in the synnemata. However, regulation of only light and temperature could not produce stromata like perithecia, asci, and ascospores.

Keywords: optimization of culture conditions of paecilomyces tenuipes, entomopathogenic fungi optimization of culture conditions of paecilomyces tenuipes, entomopathogenic fungi silkworm larva, bombyx mori

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Authors: Jyoti Agrawal

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Introduction: Renal diseases in children and young adult can be difficult to diagnose early as it may present only with few symptoms, tends to have different course than adult and respond variously to different treatment. The pattern of renal disease in children is different from developing countries as compared to developed countries. Methods: This study was a hospital based prospective observational study carried from March, 2014 to February 2015 at BP Koirala institute of health sciences. Patients with renal disease, both inpatient and outpatient from birth to 14 years of age were enrolled in the study. The diagnosis of renal disease was be made on clinical and laboratory criteria. Results: Total of 120 patients were enrolled in our study which contributed to 3.74% % of total admission. The commonest feature of presentation was edema (75%), followed by fever (65%), hypertension (60%), decreased urine output (45%) and hematuria (25%). Most common diagnosis was acute glomerulonephritis (40%) followed by Nephrotic syndrome (25%) and urinary tract infection (25%). Renal biopsy was done for 10% of cases and most of them were steroid dependent nephrotic syndrome. 5% of our cases expired because of multiorgan dysfunction syndrome, sepsis and acute kidney injury. Conclusion: Renal disease contributes to a large part of hospital pediatric admission as well as mortality and morbidity to the children.

Keywords: glomerulonephritis, nephrotic syndrome, renal disease, urinary tract infection

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Authors: Madhushi Bandara, Dharshana Kasthurirathna, Danaja Maldeniya, Mahendra Piraveenan

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Community detection is an extremely useful technique in understanding the structure and function of a social network. Louvain algorithm, which is based on Newman-Girman modularity optimization technique, is extensively used as a computationally efficient method extract the communities in social networks. It has been suggested that the nodes that are in close geographical proximity have a higher tendency of forming communities. Variants of the Newman-Girman modularity measure such as dist-modularity try to normalize the effect of geographical proximity to extract geographically dispersed communities, at the expense of losing the information about the geographically proximate communities. In this work, we propose a method to extract geographically dispersed communities while preserving the information about the geographically proximate communities, by analyzing the ‘community network’, where the centroids of communities would be considered as network nodes. We suggest that the inter-community link strengths, which are normalized over the community sizes, may be used to identify and extract the ‘overlay communities’. The overlay communities would have relatively higher link strengths, despite being relatively apart in their spatial distribution. We apply this method to the Gowalla online social network, which contains the geographical signatures of its users, and identify the overlay communities within it.

Keywords: social networks, community detection, modularity optimization, geographically dispersed communities

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Authors: Ahmed Rashed

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Sarcoptic mange is generally recognized as one of the most serious diseases in camels in Libya. It is an extremely pruritic and contagious skin condition caused by Sarcoptes scabiei var cameli. Thirteen camels (camelis dromedaries), showing progressive infection with S.scabiei mites in skin scrapings, were chosen randomly from different affected herds at AL-Assa camel project. Ten camels were treated with ivermectin (22,23-dihydroavermectin B1, Ivomec, Merck) at a dose rate of 0.2 mg./kg.body weight. Scratching and rubbing had completely disappeared in the treated camels one week after the second injection. Two weeks after the second injection motile mites were found on only one camel, and three weeks after the second injection, no motile mites were detected. Motile mites were observed in the three untreated camels up to the end of the trial.

Keywords: ivermecti, Sarcoptes scabiei, camels, scrapings

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Authors: Najrullah Khan, Athar Ali Khan

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The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

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Authors: Joseph C. Chen, Venkata Karthik Jakka

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The main objective of this research is to optimize tensile strength and dimensional accuracy in injection molding processes using Taguchi Parameter Design. An L16 orthogonal array (OA) is used in Taguchi experimental design with five control factors at four levels each and with non-controllable factor vibration. A total of 32 experiments were designed to obtain the optimal parameter setting for the process. The optimal parameters identified for the shrinkage are shot volume, 1.7 cubic inch (A4); mold term temperature, 130 ºF (B1); hold pressure, 3200 Psi (C4); injection speed, 0.61 inch3/sec (D2); and hold time of 14 seconds (E2). The optimal parameters identified for the tensile strength are shot volume, 1.7 cubic inch (A4); mold temperature, 160 ºF (B4); hold pressure, 3100 Psi (C3); injection speed, 0.69 inch3/sec (D4); and hold time of 14 seconds (E2). The Taguchi-based optimization framework was systematically and successfully implemented to obtain an adjusted optimal setting in this research. The mean shrinkage of the confirmation runs is 0.0031%, and the tensile strength value was found to be 3148.1 psi. Both outcomes are far better results from the baseline, and defects have been further reduced in injection molding processes.

Keywords: injection molding processes, taguchi parameter design, tensile strength, high-density polyethylene(HDPE)

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Authors: Jae Ni Jang, Young Uk Kim

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Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT.

Keywords: American Society of Anesthesiologists, artificial intelligence, Chat Generative Pre-training Transformer-3, ChatGPT

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Authors: Mallika Supa-Aksorn, Buaream Maneewan, Jiraporn Rojtinnakorn

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For animals, trypsin and chymotrypsin are the 2 proteases that play the important role in protein digestion and involving in growth rate. In many animals, these two enzymes are indicated as growth parameter by feed. Although enzyme assay at optimal condition is significant for its accuracy activity determination. There is less report of trypsin and chymotrypsin. Therefore, in this study, optimization of pH and temperature for trypsin (T) and chymotrypsin (C) in economic species; i.e. Nile tilapia (Oreochromis niloticus), sand goby (Oxyeleotoris marmoratus), giant freshwater prawn (Macrobachium rosenberchii) and native chicken (Gallus gallus) were investigated. Each enzyme of each species was assaying for its specific activity with variation of pH in range of 2-12 and temperature in range of 30-80 °C. It revealed that, for Nile tilapia, T had optimal condition at pH 9 and temperature 50-80 °C, whereas C had optimal condition at pH 8 and temperature 60 °C. For sand goby, T had optimal condition at pH 7 and temperature of 50 °C, while C had optimal condition at pH 11 and temperature of 70-75 °C. For juvenile freshwater prawn, T had optimal condition at pH 10-11 and temperature of 60-65 °C, C had optimal condition at pH 8 and temperature of 70°C. For starter native chicken, T has optimal condition at pH 7 and temperature of 70 °C, whereas C had o optimal condition at pH 8 and temperature of 60°C. This information of optimal conditions will be high valuable in further for, actual enzyme measurement of T and C activities that benefit for growth and feed analysis.

Keywords: trypsin, chymotrypsin, Oreochromis niloticus, Oxyeleotoris marmoratus, Macrobachium rosenberchii, Gallus gallus

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Authors: Daniel Scherman, Daniel Madani, Shanu Gambhir, Marcus Ling Zhixing, Yingda Li

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Objective: This study aims to identify clinical factors that may predict failed endoscopic lumbar spine surgery to guide surgeons with patient selection during the initial learning curve. Methods: This is an Australasian prospective analysis of the first 105 patients to undergo lumbar endoscopic spine decompression by 3 surgeons. Modified MacNab outcomes, Oswestry Disability Index (ODI) and Visual Analogue Score (VAS) scores were utilized to evaluate clinical outcomes at 6 months postoperatively. Descriptive statistics and Anova t-tests were performed to measure statistically significant (p<0.05) associations between variables using GraphPad Prism v10. Results: Patients undergoing endoscopic lumbar surgery via an interlaminar or transforaminal approach have overall good/excellent modified MacNab outcomes and a significant reduction in post-operative VAS and ODI scores. Regardless of the anatomical location of disc herniations, good/excellent modified MacNab outcomes and significant reductions in VAS and ODI were reported post-operatively; however, not in patients with calcified disc herniations. Patients with central and foraminal stenosis overall reported poor/fair modified MacNab outcomes. However, there were significant reductions in VAS and ODI scores post-operatively. Patients with subarticular stenosis or an associated spondylolisthesis reported good/excellent modified MacNab outcomes and significant reductions in VAS and ODI scores post-operatively. Patients with disc herniation and concurrent degenerative stenosis had generally poor/fair modified MacNab outcomes. Conclusion: The outcomes of endoscopic spine surgery are encouraging, with a low complication and reoperation rate. However, patients with calcified disc herniations, central canal stenosis or a disc herniation with concurrent degenerative stenosis present challenges during the initial learning curve and may benefit from traditional open or other minimally invasive techniques.

Keywords: complications, lumbar disc herniation, lumbar endoscopic spine surgery, predictors of failed endoscopic spine surgery

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Authors: Rikson Gultom

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Hate Speech and Abusive language on social media is difficult to detect, usually, it is detected after it becomes viral in cyberspace, of course, it is too late for prevention. An early detection system that has a fairly good accuracy is needed so that it can reduce conflicts that occur in society caused by postings on social media that attack individuals, groups, and governments in Indonesia. The purpose of this study is to find an early detection model on Twitter social media using machine learning that has high accuracy from several machine learning methods studied. In this study, the support vector machine (SVM), Naïve Bayes (NB), and Random Forest Decision Tree (RFDT) methods were compared with the Support Vector machine with genetic algorithm (SVM-GA), Nave Bayes with genetic algorithm (NB-GA), and Random Forest Decision Tree with Genetic Algorithm (RFDT-GA). The study produced a comparison table for the accuracy of the hate speech and abusive language detection model, and presented it in the form of a graph of the accuracy of the six algorithms developed based on the Indonesian-language Twitter dataset, and concluded the best model with the highest accuracy.

Keywords: abusive language, hate speech, machine learning, optimization, social media

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Authors: Hadis Pouyafar, D. Matin Alaghmandan

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Gallium arsenide (GaAs) solar cells are widely used in applications like spacecraft and satellites because they have a high absorption coefficient and efficiency and can withstand high-energy particles such as electrons and protons. With the energy crisis, there's a growing need for efficiency and cost-effective solar cells. GaAs cells, with their 46% efficiency compared to silicon cells 23% can be utilized in buildings to achieve nearly zero emissions. This way, we can use irradiation and convert more solar energy into electricity. III V semiconductors used in these cells offer performance compared to other technologies available. However, despite these advantages, Si cells dominate the market due to their prices. In our study, we took an approach by using software from the start to gather all information. By doing so, we aimed to design the optimal building that harnesses the full potential of solar energy. Our modeling results reveal a future; for GaAs cells, we utilized the Grasshopper plugin for modeling and optimization purposes. To assess radiation, weather data, solar energy levels and other factors, we relied on the Ladybug and Honeybee plugins. We have shown that silicon solar cells may not always be the choice for meeting electricity demands, particularly when higher power output is required. Therefore, when it comes to power consumption and the available surface area for photovoltaic (PV) installation, it may be necessary to consider efficient solar cell options, like GaAs solar cells. By considering the building requirements and utilizing GaAs technology, we were able to optimize the PV surface area.

Keywords: gallium arsenide (GaAs), optimization, sustainable building, GaAs solar cells

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Authors: Bhim Kumar Dahal

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Transportation network development in the developing country is in rapid pace. The majority of the network belongs to railway and expressway which passes through diverse topography, landform and geological conditions despite the avoidance principle during route selection. Construction of such networks demand many low to high embankment which required improvement in the foundation soil. This paper is mainly focused on the various advanced ground improvement techniques used to improve the soft soil, modelling approach and its predictability for embankments construction. The ground improvement techniques can be broadly classified in to three groups i.e. densification group, drainage and consolidation group and reinforcement group which are discussed with some case studies.  Various methods were used in modelling of the embankments from simple 1-dimensional to complex 3-dimensional model using variety of constitutive models. However, the reliability of the predictions is not found systematically improved with the level of sophistication.  And sometimes the predictions are deviated more than 60% to the monitored value besides using same level of erudition. This deviation is found mainly due to the selection of constitutive model, assumptions made during different stages, deviation in the selection of model parameters and simplification during physical modelling of the ground condition. This deviation can be reduced by using optimization process, optimization tools and sensitivity analysis of the model parameters which will guide to select the appropriate model parameters.

Keywords: cement, improvement, physical properties, strength

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Authors: Pugazhenthan Thangaraju

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Background: Since the pandemic began, more than millions of people have become infected with COVID-19. Globally, researchers are working for safe and effective treatments for this disease. Remdesivir is a drug that has been approved for the treatment of COVID-19. Many aspects are still being considered that may influence the future use of remdesivir. Aim: To assess the safety and efficacy of Remdesivir in hospitalized adult patients diagnosed with moderate and severe COVID-19. Methods: It was a record-based retrospective cohort study conducted between April 1st, 2020 and June 30th, 2021 at the tertiary care teaching hospital All India Institutes of Medical Sciences (AIIMS), Raipur Results: There were a total of 10,559 medical records of COVID-19 patients of which 1034 records were included in this study. Overall, irrespective of the survival status, there was statistical significant difference observed between the WHO score at the time of admission and discharge. Clinical improvement among the survivors was found to be statistically significant. Conclusion: Remdesivir's potential efficacy against coronaviruses has so far been limited to in vitro studies and animal models. However, information about COVID-19 is rapidly expanding. Several clinical trials for the treatment of COVID-19 with remdesivir are now underway. However, the findings of this study support remdesivir as a promising agent in the fight against SARS-CoV-2.

Keywords: Remdesivir, COVID-19, SARS-CoV-2, antiviral, RNA-dependent RNA polymerase, viral pneumonia

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Authors: Dan Geneau, Mary Claire Geneau, Seth Lenetsky, Ming -Chang Tsai, Marc Klimstra

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Introduction— Horizontal force-velocity profiling (HFVP) involves modeling an athletes linear sprint kinematics to estimate valuable maximum force and velocity metrics. This approach to performance modeling has been used in field-based team sports and has recently been introduced to ice-hockey as a forward skating performance assessment. While preliminary data has been collected on ice, distance constraints of the on-ice test restrict the ability of the athletes to reach their maximal velocity which result in limits of the model to effectively estimate athlete performance. This is especially true of more elite athletes. This report explores whether athletes on-ice are able to reach a velocity plateau similar to what has been seen in overground trials. Fourteen male Major Junior ice-hockey players (BW= 83.87 +/- 7.30 kg, height = 188 ± 3.4cm cm, age = 18 ± 1.2 years n = 14) were recruited. For on-ice sprints, participants completed a standardized warm-up consisting of skating and dynamic stretching and a progression of three skating efforts from 50% to 95%. Following the warm-up, participants completed three on ice 45m sprints, with three minutes of rest in between each trial. For overground sprints, participants completed a similar dynamic warm-up to that of on-ice trials. Following the warm-up participants completed three 40m overground sprint trials. For each trial (on-ice and overground), radar was used to collect instantaneous velocity (Stalker ATS II, Texas, USA) aimed at the participant’s waist. Sprint velocities were modelled using custom Python (version 3.2) script using a mono-exponential function, similar to previous work. To determine if on-ice tirals were achieving a maximum velocity (plateau), minimum acceleration values of the modeled data at the end of the sprint were compared (using paired t-test) between on-ice and overground trials. Significant differences (P<0.001) between overground and on-ice minimum accelerations were observed. It was found that on-ice trials consistently reported higher final acceleration values, indicating a maximum maintained velocity (plateau) had not been reached. Based on these preliminary findings, it is suggested that reliable HFVP metrics cannot yet be collected from all ice-hockey populations using current methods. Elite male populations were not able to achieve a velocity plateau similar to what has been seen in overground trials, indicating the absence of a maximum velocity measure. With current velocity and acceleration modeling techniques, including a dependency of a velocity plateau, these results indicate the potential for error in on-ice HFVP measures. Therefore, these findings suggest that a greater on-ice sprint distance may be required or the need for other velocity modeling techniques, where maximal velocity is not required for a complete profile.   

Keywords: ice-hockey, sprint, skating, power

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Authors: Manjunath A. P., Al-Ajmi G. M., Al Shukri M., Girija S

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Introduction: This study aimed to compare the ability of hysteroscopy and ultrasonography to diagnose uterine polyps. To correlate the ultrasonography and hystroscopic findings with various clinical factors and histopathology of uterine polyps. Methods: This is a retrospective study conducted at the Department of Obstetrics and Gynaecology at Sultan Qaboos University Hospital from 2014 to 2019. All women undergoing hysteroscopy for suspected uterine polyps were included. All relevant data were obtained from the electronic patient record and analysed using SPSS. Results: A total of 77 eligible women were analysed. The mean age of the patients was 40 years. The clinical risk factors; obesity, hypertension, and diabetes mellitus, showed no significant statistical association with the presence of uterine polyps (p-value>0.005). Although 20 women (52.6%) with uterine polyps had thickened endometrium (>11 mm), however, there is no statistical association (p-value>0.005). The sensitivity and specificity of ultrasonography in the detection of uterine polyp were 39% and 65%, respectively. Whereas for hysteroscopy, it was 89% and 20%, respectively. The prevalence of malignant and premalignant lesions were 1.85% and 7.4%, respectively. Conclusion: This study found that obesity, hypertension, and diabetes mellitus were not associated with the presence of uterine polyps. There was no association between thick endometrium and uterine polyps. The sensitivity is higher for hysteroscopy, whereas the specificity is higher for sonography in detecting uterine polyps. The prevalence of malignancy was very low in uterine polyps.

Keywords: endometrial polyps, hysteroscopy, ultrasonography, premalignant, malignant

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Authors: Federico Pittino, Thomas Arnold

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The shredding of waste materials is a key step in the recycling process towards the circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need for frequent maintenance of critical components. Maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for one year, and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for the efficient operation of industrial shredders.

Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning

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Authors: Brendan Mooney

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Context: Feelings and emotions are commonly misunderstood and the terms often used interchangeably, leading to potential negative impacts on individuals' mental well-being and relationships. The distinction between these two fundamentally different experiences of human life is crucial for effective psychological practice and communication. Research Aim: The aim of this study is to outline the disparities between feelings and emotions, emphasising the significance of this differentiation in psychological practice to enhance clients' observation, decision-making, problem-solving, and communication skills. Methodology: This research utilises a conceptual model developed by the author in 2017 based on clinical experience, client observations, and feedback. The model serves to guide effective clinical practice by providing clear definitions and understanding of feelings versus emotions. Case study examples were utilised to support the efficacy of the model. Findings: The study highlights that recognising and expressing feelings rather than emotions is more empowering and conducive to resolving unresolved issues, thereby fostering better psychological well-being and interpersonal relationships. Theoretical Importance: This research underscores the importance of clarifying fundamental definitions related to feelings and emotions in enhancing psychological interventions and preventing various relationship conflicts and individual issues. Data Collection and Analysis Procedures: Data was collected through the author's clinical experience and interactions with clients, informing the development of the Feeling Emotions Mental (FEM) model. Analysis involved synthesising observations and feedback to elucidate the distinctions between feelings and emotions. Questions Addressed: What are the disparities between feelings and emotions? How does the confusion between these two fundamentally different experiences of human life impact individuals' mental well-being and relationships? Why is it essential to differentiate between feelings and emotions in psychological practice? Conclusion: The study advocates for a clear understanding of feelings versus emotions to support clients in addressing unresolved issues and improving their overall psychological functioning and communication skills, thereby preventing potential conflicts and relationship challenges.

Keywords: couples, mental, misinformation, misunderstanding, relationships

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Authors: M. Graus, K. Westhoff, X. Xu

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The climate change causes a change in all aspects of society. While the expansion of renewable energies proceeds, industry could not be convinced based on general studies about the potential of demand side management to reinforce smart grid considerations in their operational business. In this article, a procedure model for a case-specific data-driven decision support for industrial energy management based on a holistic data analytics approach is presented. The model is executed on the example of the strategic decision problem, to integrate the aspect of renewable energies into industrial energy management. This question is induced due to considerations of changing the electricity contract model from a standard rate to volatile energy prices corresponding to the energy spot market which is increasingly more affected by renewable energies. The procedure model corresponds to a data analytics process consisting on a data model, analysis, simulation and optimization step. This procedure will help to quantify the potentials of sustainable production concepts based on the data from a factory. The model is validated with data from a printer in analogy to a simple production machine. The overall goal is to establish smart grid principles for industry via the transformation from knowledge-driven to data-driven decisions within manufacturing companies.

Keywords: data analytics, green production, industrial energy management, optimization, renewable energies, simulation

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Authors: Mohammed S. Bhader, Abdullah A. Ghaddaf, Anas Alamoudi, Amal Abualola, Renad Kalantan, Noura Alkhulaifi, Ibrahim Halawani, Mohammed Alhindi

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Background: Noninvasive neurally adjusted ventilatory assist (NAVA) is a relatively new mode of noninvasive ventilation with promising clinical and patient-ventilator outcomes for preterm infants. The aim of this systematic review was to compare NAVA to nasal continuous or positive airway pressure (NCPAP) or intermittent positive airway pressure (NIPP) for preterm infants. Methods: We searched the online databases Medline, Embase, and CENTRAL. We included randomized controlled trials (RCTs) that compared NAVA to NCPAP or NIPP for preterm infants < 37 weeks gestational age. We sought to evaluate the following outcomes: noninvasive intubation failure rate, desaturation rate, the fraction of inspired oxygen (FiO2), and length of stay in the neonatal intensive care unit (NICU). We used the mean difference (MD) to represent continuous outcomes, while the odds ratio (OR) was used to represent dichotomous outcomes. Results: A total of 11 RCTs that enrolled 429 preterm infants were deemed eligible. NAVA showed similar clinical outcomes to NCPAP or NIPP with respect to noninvasive intubation failure (RR for NAVA versus NCPAP: 0.82, 95% confidence interval (CI): 0.49 to 1.37), desaturation rate (RR for NAVA versus NCPAP: 0.69, 95%CI: 0.36 to 1.29; RR for NAVA versus NIPP: 0.58, 95%CI: 0.08 to 4.25), FiO2 (MD for NAVA versus NCPAP: –0.01, 95%CI: –0.04 to 0.02; MD for NAVA versus NIPP: –7.16, 95%CI: –22.63 to 8.31), and length of stay in the NICU (MD for NAVA versus NCPAP: 1.34, 95%CI: –4.17 to 6.85). Conclusion: NAVA showed similar clinical and ventilator-related outcomes compared to the usual care noninvasive respiratory support measures NCPAP or NIPP for preterm infants.

Keywords: preterm infants, noninvasive neurally adjusted ventilatory assist, NIV-NAVA, non-invasive ventilation, nasal continuous or positive airway pressure, NCPAP, intermittent positive airway pressure ventilation, NIPP, respiratory distress syndrome, RDS

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Authors: B. S. Premalatha, Kausalya Sahani

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Background: Voice is multidimensional which convey emotion, feelings, and communication. Voice disorders have an adverse effect on the physical, emotional and functional domains of an individual. Self-rating by clients about their voice problem helps the clinicians to plan intervention strategies. Voice handicap index is one such self-rating scale contains 30 questions that quantify the functional, physical and emotional impacts of a voice disorder on a patient’s quality of life. Each subsection has 10 questions. Though adapted and validated versions of VHI are available in other Indian languages but not in Telugu, which is a Dravidian language native to India. It is mainly spoken in Andhra Pradesh and neighbouring states in southern India. Objectives: To adapt and validate the English version of Voice Handicap Index (VHI) into Telugu language and evaluate its internal consistency and clinical validate in Telugu speaking population. Materials: The study carried out in three stages. First stage was a forward translation of English version of VHI, was given to ten experts, who were well proficient in writing and reading Telugu and five speech-language pathologists to translate into Telugu. Second Stage was backward translation where translated version of Telugu was given to a different group of ten experts (who were well proficient in writing and reading Telugu) and five speech-language pathologists who were native Telugu speakers and had good proficiency in Telugu and English. The third stage was an administration of translated version on Telugu to the targeted population. Totally 40 clinical subjects and 40 normal controls served as participants, and each group had 26 males and 14 females’ age range of 20 to 60 years. Clinical group comprised of individuals with laryngectomee with the Tracheoesophageal puncture (n=18), laryngitis (n=11), vocal nodules (n=7) and vocal fold palsy (n=4). Participants were asked to mark of their each experience on a 5 point equal appearing scale (0=never, 1=almost never, 2=sometimes, 3=almost always, 4=always) with a maximum total score of 120. Results: Statistical analysis was made by using SPSS software (22.0.0 Version). Mean, standard deviation and percentage (%) were calculated all the participants for both the groups. Internal consistency of VHI in Telugu was found to be excellent with the consistency scores for all the domains such as physical, emotional and functional are 0.742, 0.934and 0.938. The validity of scores showed a significant difference between clinical population and control group for domains like physical, emotional and functional and total scores. P value found to be less than 0.001( < 0.001). Negative correlation found in age and gender among self-domains such as physical, emotional and functional total scores in dysphonic and control group. Conclusion: The present study indicated that VHI in Telugu is able to discriminate participants having voice pathology from normal populations, which make this as a valid tool to collect information about their voice from the participants.

Keywords: adaptation, Telugu Version, translation, Voice Handicap Index (VHI)

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Authors: Lazzat M. Zhamaliyeva, Nurgul A. Abenova, Gauhar S. Dilmagambetova, Ziyash Zh. Tanbetova, Moldir B. Ahmetzhanova, Tatyana P. Ostretcova, Aliya A. Yegemberdiyeva

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Introduction: There are many reasons for the weak training of family doctors in Kazakhstan: the unified national educational program is not focused on competencies, the role of a general practitioner (GP) is not clear, poor funding for the health care and education system, outdated teaching and assessment methods, inefficient management. We highlight two issues in particular. Firstly, academic teachers of family medicine (FM) in Kazakhstan do not practice as family doctors; most of them are narrow specialists (pediatricians, therapists, surgeons, etc.); they usually hold one-time consultations; clinical mentors from practical healthcare (non-academic teachers) do not have the teaching competences, and the vast majority of them are also narrow specialists. Secondly, clinical sites (polyclinics) are unprepared for general practice and do not follow the principles of family medicine; residents do not like to be in primary health care (PHC) settings due to the chaos that is happening there, as well as due to the lack of the necessary equipment for mastering and consolidating practical skills. Aim: We present the concept of the family physicians’ training office (FPTO), which is being created as a friendly learning environment for young general practitioners and for the involvement of academic teachers of family medicine in the practical work and innovative development of PHC. Methodology: In developing the conceptual framework and identifying practical activities, we drew on literature and expert input, and interviews. Results: The goal of the FPTO is to create a favorable educational and clinical environment for the development of the FM residents’ competencies, in which the residents with academic teachers and clinical mentors could understand and accept the principles of family medicine, improve clinical knowledge and skills, and gain experience in improving the quality of their practice in scientific basis. Three main areas of office activity are providing primary care to the patients, improving educational services for FM residents and other medical workers, and promoting research in PHC and innovations. The office arranges for residents to see outpatients at least 50% of the time, and teachers of FM departments at least 1/4 of their working time conduct general medical appointments next to residents. Taking into account the educational and scientific workload, the number of attached population for one GP does not exceed 500 persons. The equipment of the office allows FPTO workers to perform invasive and other manipulations without being sent to other clinics. In the office, training for residents is focused on their needs and aimed at achieving the required level of competence. International methodologies and assessment tools are adapted to local conditions and evaluated for their effectiveness and acceptability. Residents and their faculty actively conduct research in the field of family medicine. Conclusions: We propose to change the learning environment in order to create teams of like-minded people, to unite residents and teachers even more for the development of family medicine. The offices will also invest resources in developing and maintaining young doctors' interest in family medicine.

Keywords: educational environment, family medicine residents, family physicians’ training office, primary care research

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Authors: F. Hamidi, N. Amiri, H. Mishmast Nehi

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The Bilevel Programming (BP) model has been presented for a decision making process that consists of two decision makers in a hierarchical structure. In fact, BP is a model for a static two person game (the leader player in the upper level and the follower player in the lower level) wherein each player tries to optimize his/her personal objective function under dependent constraints; this game is sequential and non-cooperative. The decision making variables are divided between the two players and one’s choice affects the other’s benefit and choices. In other words, BP consists of two nested optimization problems with two objective functions (upper and lower) where the constraint region of the upper level problem is implicitly determined by the lower level problem. In real cases, the coefficients of an optimization problem may not be precise, i.e. they may be interval. In this paper we develop an algorithm for solving interval bilevel linear fractional programming problems. That is to say, bilevel problems in which both objective functions are linear fractional, the coefficients are interval and the common constraint region is a polyhedron. From the original problem, the best and the worst bilevel linear fractional problems have been derived and then, using the extended Charnes and Cooper transformation, each fractional problem can be reduced to a linear problem. Then we can find the best and the worst optimal values of the leader objective function by two algorithms.

Keywords: best and worst optimal solutions, bilevel programming, fractional, interval coefficients

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Authors: Nour Wehbe

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The Lebanese electricity sector is at the heart of a deep crisis. Electricity in Lebanon is supplied by Électricité du Liban (EdL) which has to suffer from technical and financial deficiencies for decades and proved to be insufficient and deficient as the demand still exceeds the supply. As a result, backup generation is widespread throughout Lebanon. The sector costs massive government resources and, on top of it, consumers pay massive additional amounts for satisfying their electrical needs. While the developed countries have been investing in renewable energy for the past two decades, the Lebanese government realizes the importance of adopting such energy sourcing strategies for the upgrade of the electricity sector in the country. The diversification of the national electricity generation mix has increased considerably in Lebanon's energy planning agenda, especially that a detailed review of the energy potential in Lebanon has revealed a great potential of solar and wind energy resources, a considerable potential of biomass resource, and an important hydraulic potential in Lebanon. This paper presents a review of the energy status of Lebanon, and illustrates a detailed review of the EDL structure with the existing problems and recommended solutions. In addition, scenarios reflecting implementation of policy projects are presented, and conclusions are drawn on the usefulness of a proposed evaluation methodology and the effectiveness of the adopted new energy policy for the electrical sector in Lebanon.

Keywords: EdL Electricite du Liban, portfolio optimization, electricity generation mix, mean-variance approach

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Authors: Monika Jurkeviciute, Amia Enam, Johanna Torres Bonilla, Henrik Eriksson

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Introduction: Many evaluations of eHealth interventions conclude that the evidence for improved clinical outcomes is limited, especially when the intervention is short, such as one year. Often, evaluation design does not address the feasibility of achieving clinical outcomes. Evaluations are designed to reflect upon clinical goals of intervention without utilizing the opportunity to illuminate effects on organizations and cost. A comprehensive design of evaluation can better support decision-making regarding the effectiveness and potential transferability of eHealth. Hence, the purpose of this paper is to present a feasible and comprehensive design of evaluation for eHealth intervention, including the design process in different contexts. Methodology: The situation of limited feasibility of clinical outcomes was foreseen in the European Union funded project called “DECI” (“Digital Environment for Cognitive Inclusion”) that is run under the “Horizon 2020” program with an aim to define and test a digital environment platform within corresponding care models that help elderly people live independently. A complex intervention of eHealth implementation into elaborate care models in four different countries was planned for one year. To design the evaluation, a participative approach was undertaken using Pettigrew’s lens of change and transformations, including context, process, and content. Through a series of workshops, observations, interviews, and document analysis, as well as a review of scientific literature, a comprehensive design of evaluation was created. Findings: The findings indicate that in order to get evidence on clinical outcomes, eHealth interventions should last longer than one year. The content of the comprehensive evaluation design includes a collection of qualitative and quantitative methods for data gathering which illuminates non-medical aspects. Furthermore, it contains communication arrangements to discuss the results and continuously improve the evaluation design, as well as procedures for monitoring and improving the data collection during the intervention. The process of the comprehensive evaluation design consists of four stages: (1) analysis of a current state in different contexts, including measurement systems, expectations and profiles of stakeholders, organizational ambitions to change due to eHealth integration, and the organizational capacity to collect data for evaluation; (2) workshop with project partners to discuss the as-is situation in relation to the project goals; (3) development of general and customized sets of relevant performance measures, questionnaires and interview questions; (4) setting up procedures and monitoring systems for the interventions. Lastly, strategies are presented on how challenges can be handled during the design process of evaluation in four different countries. The evaluation design needs to consider contextual factors such as project limitations, and differences between pilot sites in terms of eHealth solutions, patient groups, care models, national and organizational cultures and settings. This implies a need for the flexible approach to evaluation design to enable judgment over the effectiveness and potential for adoption and transferability of eHealth. In summary, this paper provides learning opportunities for future evaluation designs of eHealth interventions in different national and organizational settings.

Keywords: ehealth, elderly, evaluation, intervention, multi-cultural

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Authors: Cinzia Cruder, Deborah Falla, Francesca Mangili, Laura Azzimonti, Liliana Araujo, Aaron Williamon, Marco Barbero

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Background and aims: According to the existing literature, musicians are at risk to experience a range of musculoskeletal painful conditions. Recently, digital technology has been developed to investigate pain location and pain extent. The aim of this study was to describe pain location and pain extent in musicians using a digital method for pain drawing analysis. Additionally, the association between pain drawing (PD) variables and clinical features in musicians with pain were explored. Materials and Methods: One hundred fifty-eight musicians (90 women and 68 men; age 22.4±3.6 years) were recruited from Swiss and UK conservatoires. Participants were asked to complete a survey including both background musical information and clinical features, the Quick Dash (QD) questionnaire and the digital PDs. Results: Of the 158 participants, 126 musicians (79.7%) reported having pain, with more prevalence in the areas of the neck and shoulders, the lower back and the right arm. The mean of pain extent was 3.1% ±6.5. The mean of QD was larger for musicians showing the presence of pain than for those without pain. Additionally, the results indicated a positive correlation between QD score and pain extent, and there were significant correlations between age and pain intensity, as well as between pain extent and pain intensity. Conclusions: The high prevalence of pain among musicians has been confirmed using a digital PD. In addition, positive correlations between pain extent and upper limb disability has been demonstrated. Our findings highlight the need for effective prevention and treatment strategies for musicians.

Keywords: pain location, pain extent, musicians, pain drawings

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Authors: N. Guo, C. Xu, Z. C. Yang

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In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.

Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search

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