Search results for: Re-excision rates

Authors: Ho Yuan-Hong, Huang Chiung-Ju

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This study conducts simulation analyses to find the optimal debt ceiling of Taiwan, while factoring in welfare maximization under a dynamic stochastic general equilibrium framework. The simulation is based on Taiwan's 2001 to 2011 economic data and shows that welfare is maximized at a "debt"⁄"GDP" ratio of 0.2, increases in the "debt"⁄"GDP " ratio leads to increases in both tax and interest rates and decreases in the consumption ratio and working hours. The study results indicate that the optimal debt ceiling of Taiwan is 20% of GDP, where if the "debt"⁄"GDP" ratio is greater than 40%, the welfare will be negative and result in welfare loss.

Keywords: debt sustainability, optimal debt ceiling, dynamic stochastic general equilibrium, welfare maximization

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Authors: Frazer Kirk, Rohen Skiba, Pankaj Saxena

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The natural history of the QAV is poorly understood due to the exceeding rarity of the condition. Incidence rates vary between 0.00028-1%. Classically patients present with Aortic Regurgitation (AR) between 40-60 years of age experiencing palpitations, chest pain, or heart failure. (1, 2) Echocardiography is the mainstay of diagnosis for this condition; however, given the rarity of this condition, it can easily be overlooked, as demonstrated here. The case report that follows serves as a reminder of the condition to reduce the innate cognitive bias to overlook the diagnosis due to the availability heuristic. Intraoperative photography, echocardiographic and magnetic resonance imaging from this case for reference to demonstrate that while the diagnosis of Aortic regurgitation was recognized early, the valve morphology was underappreciated.

Keywords: quadricuspid aortic valve, cardiac surgery, echocardiography, congenital

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Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera

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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.

Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR

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Authors: Mareen Brosterhaus, Antje Hammer, Steffen Kalina, Stefan Grau, Anjali A. Roeth, Hany Ashmawy, Thomas Gross, Marcel Binnebosel, Wolfram T. Knoefel, Tanja Manser

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Background: The identification of critical incidents in hospitals is an essential component of improving patient safety. To date, various methods have been used to measure and characterize such critical incidents. These methods are often viewed by physicians and nurses as external quality assurance, and this creates obstacles to the reporting events and the implementation of recommendations in practice. One way to overcome this problem is to use tools that directly involve staff in measuring indicators of quality and safety of care in the department. One such instrument is the global trigger tool (GTT), which helps physicians and nurses identify adverse events by systematically reviewing randomly selected patient records. Based on so-called ‘triggers’ (warning signals), indications of adverse events can be given. While the tool is already used internationally, its implementation in German hospitals has been very limited. Objectives: This study aimed to assess the feasibility and potential of the global trigger tool for identifying adverse events in German hospitals. Methods: A total of 120 patient records were randomly selected from two surgical, and one neurosurgery, departments of three university hospitals in Germany over a period of two months per department between January and July, 2017. The records were reviewed using an adaptation of the German version of the Institute for Healthcare Improvement Global Trigger Tool to identify triggers and adverse event rates per 1000 patient days and per 100 admissions. The severity of adverse events was classified using the National Coordinating Council for Medication Error Reporting and Prevention. Results: A total of 53 adverse events were detected in the three departments. This corresponded to adverse event rates of 25.5-72.1 per 1000 patient-days and from 25.0 to 60.0 per 100 admissions across the three departments. 98.1% of identified adverse events were associated with non-permanent harm without (Category E–71.7%) or with (Category F–26.4%) the need for prolonged hospitalization. One adverse event (1.9%) was associated with potentially permanent harm to the patient. We also identified practical challenges in the implementation of the tool, such as the need for adaptation of the global trigger tool to the respective department. Conclusions: The global trigger tool is feasible and an effective instrument for quality measurement when adapted to the departmental specifics. Based on our experience, we recommend a continuous use of the tool thereby directly involving clinicians in quality improvement.

Keywords: adverse events, global trigger tool, patient safety, record review

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Authors: Lin Cheng, Zijiang Yang

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Program synthesis is the task to automatically generate programs based on user specification. In this paper, we present a framework that synthesizes programs from flow charts that serve as accurate and intuitive specification. In order doing so, we propose a deep neural network called GRCNN that recognizes graph structure from its image. GRCNN is trained end-to-end, which can predict edge and node information of the flow chart simultaneously. Experiments show that the accuracy rate to synthesize a program is 66.4%, and the accuracy rates to recognize edge and node are 94.1% and 67.9%, respectively. On average, it takes about 60 milliseconds to synthesize a program.

Keywords: program synthesis, flow chart, specification, graph recognition, CNN

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Authors: Shaine Mehta, Neelam Parmar, Patrick White, Mark Ashworth

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Patients with a history of substance have a high prevalence of comorbidities, including asthma and chronic obstructive pulmonary disease (COPD). Mortality rates are higher than that of the general population and the link to respiratory disease is reported. Randomised controlled trials (RCTs) support opioid substitution therapy as an effective means for harm reduction. However, whilst a high proportion of patients receiving opioid substitution therapy are smokers, to the author’s best knowledge there have been no studies of respiratory disease and smoking intensity in these patients. A cross sectional prevalence study was conducted using an anonymised patient-level database in primary care, Lambeth DataNet (LDN). We included patients aged 18 years and over who had records of ever having been prescribed methadone in primary care. Patients under 18 years old or prescribed buprenorphine (because of uncertainty about the prescribing indication) were excluded. Demographic, smoking, alcohol and asthma and COPD coding data were extracted. Differences between methadone and non-methadone users were explored with multivariable analysis. LDN contained data on 321, 395 patients ≥ 18 years; 676 (0.16%) had a record of methadone prescription. Patients prescribed methadone were more likely to be male (70.7% vs. 50.4%), older (48.9yrs vs. 41.5yrs) and less likely to be from an ethnic minority group (South Asian 2.1% vs. 7.8%; Black African 8.9% vs. 21.4%). Almost all those prescribed methadone were smokers or ex-smokers (97.3% vs. 40.9%); more were non-alcohol drinkers (41.3% vs. 24.3%). We found a high prevalence of COPD (12.4% vs 1.4%) and asthma (14.2% vs 4.4%). Smoking intensity data shows a high prevalence of ≥ 20 cigarettes per day (21.5% vs. 13.1%). Risk of COPD, adjusted for age, gender, ethnicity and deprivation, was raised in smokers: odds ratio 14.81 (95%CI 11.26, 19.47), and in the methadone group: OR 7.51 (95%CI: 5.78, 9.77). Furthermore, after adjustment for smoking intensity (number of cigarettes/day), the risk was raised in methadone group: OR 4.77 (95%CI: 3.13, 7.28). High burden of respiratory disease compounded by the high rates of smoking is a public health concern. This supports an integrated approach to health in patients treated for opiate dependence, with access to smoking cessation support. Further work may evaluate the current structure and commissioning of substance misuse services, including smoking cessation. Regression modelling highlights that methadone as a ‘risk factor’ was independently associated with COPD prevalence, even after adjustment for smoking intensity. This merits further exploration, as the association may be related to unexplored aspects of smoking (such as the number of years smoked) or may be related to other related exposures, such as smoking heroin or crack cocaine.

Keywords: methadone, respiratory disease, smoking cessation, substance misuse

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Authors: Deanne McArthur, Melinda Wall, Claire Hanlon, Dana Agnolin, Krista Davis, Melanie Dennis, Elizabeth Glidden, Anne Marie Smith, Claudette Thomson

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In Canada, as prevalence rates and severity of illness have increased among patients suffering from eating disorders, wait times have grown substantially. Patients in Canada often face wait times in excess of 12 months. It is known that delaying treatment for eating disorders contributes to poor patient outcomes and higher rates of symptom relapse. Improving interim services for adult patients awaiting outpatient treatment is a priority for an outpatient eating disorders clinic in Ontario, Canada. The clinical setting currently provides care for adults diagnosed with anorexia nervosa, bulimia nervosa and binge eating disorder. At present, the only support provided while patients are on the waitlist consists of communication with primary care providers regarding parameters for medical monitoring. The significance of this study will be to test the feasibility, acceptability and efficacy of an intervention to support adult patients awaiting outpatient eating disorder treatment for anorexia nervosa, bulimia nervosa and binge eating disorder. Methods: An intervention including psychoeducation, supportive resources, self-monitoring, and auxiliary referral will be pilot-tested with a group of patients in the summer of 2022 and detailed using a prospective cohort case study research design. The team will host patient focus groups in May 2022 to gather input informing the content of the intervention. The intervention will be pilot tested with newly-referred patients in June and July 2022. Patients who participate in the intervention will be asked to complete a survey evaluating the utility of the intervention and for suggestions, they may have for improvement. Preliminary findings describing the existing literature pertaining to waitlist interventions for patients with eating disorders, data gathered from the focus groups and early pilot testing results will be presented. Data analysis will continue throughout 2022 and early 2023 for follow-up publication and presentation in the summer of 2023. The aim of this study is to contribute to the body of knowledge pertaining to providing interim support to those patients waiting for treatment for eating disorders and, by extension, to improve outcomes for this population.

Keywords: eating disorders, waitlist management, intervention study, pilot test

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Authors: Somayeh Nezami

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The management of financial and human resources of police in metropolitans requires many information and exact plans to reduce a rate of crime and increase the safety of the society. Geographical Information Systems have an important role in providing crime maps and their analysis. By using them and identification of crime hot spots along with spatial presentation of the results, it is possible to allocate optimum resources while presenting effective methods for decision making and preventive solutions. In this paper, we try to explain and compare between some of the methods of hot spots analysis such as Mode, Fuzzy Mode and Nearest Neighbour Hierarchical spatial clustering (NNH). Then the spots with the highest crime rates of drug smuggling for one province in Iran with borderline with Afghanistan are obtained. We will show that among these three methods NNH leads to the best result.

Keywords: GIS, Hot spots, nearest neighbor hierarchical spatial clustering, NNH, spatial analysis of crime

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Authors: D. M. Bassuney, W. A. Ibrahim, Medhat A. E. Moustafa

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As awareness of the variable nature of food industrial wastewater and its environmental impact grows, a more stable treatment reactor is needed to treat such wastewater. In this paper, a performance of 5-compartment lab-scale Anaerobic Baffled Reactor (ABR) treating high strength wastewater with high pH variation was studied under three organic loading rates (OLRs). The reactor showed high COD removal efficiencies: 92.67, 97.44, and 98.19% corresponding to OLRs of 2.0, 3.0, and 4.8 KgCOD/m3 d, respectively. The first compartment showed a good buffering capacity and a distinct phase separation occurred in the ABR.

Keywords: anaerobic baffled reactor, food industrial wastewater, high strength wastewater, organic loading, pH

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Authors: B. G. Sampath, K. C. R. Perera, W. A. S. I. Wijesuriya, V. P. C. Dassanayake

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In this paper the design, development and testing of a stabilizer control system for a Quad-rotor is presented which is focused on the maneuverability. The mechanical design is performed along with the design of the controlling algorithm which is devised using fuzzy logic controller. The inputs for the system are the angular positions and angular rates of the Quad-Rotor relative to three axes. Then the output data is filtered from an accelerometer and a gyroscope through a Kalman filter. In the development of the stability controlling system Mandani Fuzzy Model is incorporated. The results prove that the fuzzy based stabilizer control system is superior in high dynamic disturbances compared to the traditional systems which use PID integrated stabilizer control systems.

Keywords: fuzzy stabilizer, maneuverability, PID, quad-rotor

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Authors: Vahdettin Sariyel, Birol Dag

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In this research, it is aimed to determine the effects of several environmental factors on adaptation and some yield parameters of Saanen goats reared under intensive conditions at a private farm in Konya province. Gestation rate, twins rate and litter size were evaluated as reproductive traits. Gestation rate was determined as 93.8% and 90.5% for 2011 and 2012 years respectively. Twins rate was determined as 59.35 % and 70.00 % for 2011 and 2012 years respectively. Litter size was 1.49 and 1.46 for 2011 and 2012 years respectively. Survival rates of kids from birth to weaning at three months of age were found as 87.74 % and 98.54 % for 2011 and 2012 years respectively.

Keywords: gestation rate, reproduction, saanen, twins rate, vitality

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Authors: C. Recchia, M. Bourel, B. Recchia

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Microorganisms (viruses, bacteria, fungi) are responsible for most communicable diseases, threatening human health. For domestic use, chemical agents are often criticized because of their potential dangerousness, and natural solutions are needed. Application of the “dry microfine steam” (DMS) technology was tested on a selection of common pathogens (SARS-CoV-2, enterovirus EV-71, human coronavirus 229E, E. coli, S. aureus, C. albicans), on different innate surfaces, for 5 to 10 seconds. Quantification of the remaining pathogens was performed, and the reduction rates ranged from 99.8% (S. aureus on plastic) to over 99.999%. DMS showed high efficacy in the elimination of common microorganisms and could be seen as a natural alternative to chemical agents to improve domestic hygiene.

Keywords: steam, SARS-CoV-2, bactericidal, virucidal, fungicidal, sterilization

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Authors: Theodore Halnon, Martin Bojowald

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In relativity, time is relative between reference frames. However, quantum mechanics requires a specific time coordinate in order to write an evolution equation for wave functions. This difference between the two theories leads to the problem of time in quantum gravity. One method to study quantum relativity is to interpret the dynamics of a matter field as a clock. In order to test the relationship between different reference frames, an isotropic cosmological model with two matter ingredients is introduced. One is given by a scalar field and one by vacuum energy or a cosmological constant. There are two matter fields, and thus two different Hamiltonians are derived from the respective clock rates. Semi-classical solutions are found for these equations and a comparison is made of the physical predictions that they imply.

Keywords: cosmology, deparameterization, general relativity, quantum mechanics

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Authors: H. Zengin, M. E. Turan, Y. Turen, H. Ahlatci, Y. Sun

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This study aimed for improving wear resistance of AM60 magnesium alloy by Ti addition (0, 0.2, 0.5, 1wt%Ti). An electric resistance furnace was used to produce alloys. Pure Mg together with Al, Al-Ti and Al-Mn were melted at 750 ⁰C in a stainless steel crucible under controlled Ar gas atmosphere and then poured into a metal mould preheated at 250 ⁰C. Microstructure characterizations were performed by light optical (LOM) and scanning electron microscope (SEM) after the wear test. Wear rates and friction coefficients were measured with a pin-on-disk type UTS-10 Tribometer test device under a load of 20N. The results showed that Ti addition altered the morphology and the amount of b-Mg₁₇Al₁₂ phase in the microstructure of AM60 alloy. b-Mg₁₇Al₁₂ phases on the grain boundaries were refined with increasing amount of Ti. An improvement in wear resistance of AM60 alloy was observed due to the alteration in the microstructure by Ti addition.

Keywords: magnesium alloy, titanium, SEM, wear

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Authors: Robert E. Kenney, Efrain Antunez, Samuel Nodal, Ameer Malik, Richard B. Aguilar

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Physician burnout has gained much attention during the COVID pandemic. After-hours workload, HCC coding, HEDIS metrics, and clinical documentation negatively impact career satisfaction. These and other influences have increased the rate of physicians leaving the workforce. In addition, roughly 1% of the entire physician workforce will be retiring earlier than expected based on pre-pandemic trends. The two Medical Specialties with the highest rates of burnout are Family Medicine and Primary Care. With a predicted shortage of primary care physicians looming, the need to address physician burnout is crucial. Commonly reported issues leading to clinician burnout are clerical documentation requirements, increased time working on Electronic Health Records (EHR) after hours, and a decrease in work-life balance. Clinicians experiencing burnout with physical and emotional exhaustion are at an increased likelihood of providing lower quality and less efficient patient care. This may include a lack of suitable clinical documentation, medication reconciliation, clinical assessment, and treatment plans. While the annual baseline turnover rates of physicians hover around 6-7%, the COVID pandemic profoundly disrupted the delivery of healthcare. A report found that 43% of physicians switched jobs during the initial two years of the COVID pandemic (2020 and 2021), tripling the expected average annual rate to 21.5 %/yr. During this same time, an average of 4% and 1.5% of physicians retired or left the workforce for a non-clinical career, respectively. The report notes that 35.2% made career changes for a better work-life balance and another 35% reported the reason as being unhappy with their administration’s response to the pandemic. A physician-led primary care-focused health organization, Cano Health (CH), based out of Florida, sought to preemptively address this problem by implementing several supportive measures. Working with >120 clinics and >280 PCPs from Miami to Tampa and Orlando, managing nearly 120,000 Medicare Advantage lives, CH implemented a number of changes to assist with the clinician’s workload. Supportive services such as after hour and home visits by APRNs, in-clinic care managers, and patient educators were implemented. In 2021, assistive Artificial Intelligence Software (AIS) was integrated into the EHR platform. This AIS converts free text within PDF files into a usable (copy-paste) format facilitating documentation. The software also systematically and chronologically organizes clinical data, including labs, medical records, consultations, diagnostic images, medications, etc., into an easy-to-use organ system or chronic disease state format. This reduced the excess time and documentation burden required to meet payor and CMS guidelines. A clinician Documentation Support team was employed to improve the billing/coding performance. The effects of these newly designed workflow interventions were measured via analysis of clinician turnover from CH’s hiring and termination reporting software. CH’s annualized average clinician turnover rate in 2020 and 2021 were 17.7% and 12.6%, respectively. This represents a 30% relative reduction in turnover rate compared to the reported national average of 21.5%. Retirement rates during both years were 0.1%, demonstrating a relative reduction of >95% compared to the national average (4%). This model successfully promoted the retention of clinicians in a Value-Based Care setting.

Keywords: clinician burnout, COVID-19, value-based care, burnout, clinician retirement

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Authors: Faten Khanfir, Mohamed Tlili, Ali Medeb Hamrouni, Raki Selmi, M. S. Khalfi, Faten Ben Amor

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Introduction: dental implant failure is a major concern for the clinician and the patient. Objectives: The aim of our study is to investigate the way in which 100 Tunisian dentists carried implant treatment for their patients from the early phase of planning and selection of patients to the placement of the implant in order to look for the implant failure factors. Results: significant correlations were found between failure rates > 5 and their corresponding factors as the number of implants placed (p = 0.001<0, 05), smoking (0.046 <0.05), unbalanced diabetes (0.03<0.05), aseptic protocol (= 0.004< 0.05) and the drilling speed (0,002<0.05) Conclusion: It seems that the number of implant placed, smoking, diabetes, aseptic protocol, and the drilling speed may contribute to dental implant failure.

Keywords: failure, implants, survey, risk, osseointegration

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Authors: Sophie Baudel, Aline Duplaa, Jean Muller, Stephan Lauriol, Yann Bernard

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Argos is the main satellite telemetry system used by the wildlife research community, since its creation in 1978, for animal tracking and scientific data collection all around the world, to analyze and understand animal migrations and behavior. The marine mammals' biology is one of the major disciplines which had benefited from Argos telemetry, and conversely, marine mammals biologists’ community has contributed a lot to the growth and development of Argos use cases. The Argos constellation with 6 satellites in orbit in 2017 (Argos 2 payload on NOAA 15, NOAA 18, Argos 3 payload on NOAA 19, SARAL, METOP A and METOP B) is being extended in the following years with Argos 3 payload on METOP C (launch in October 2018), and Argos 4 payloads on Oceansat 3 (launch in 2019), CDARS in December 2021 (to be confirmed), METOP SG B1 in December 2022, and METOP-SG-B2 in 2029. Argos 4 will allow more frequency bands (600 kHz for Argos4NG, instead of 110 kHz for Argos 3), new modulation dedicated to animal (sea turtle) tracking allowing very low transmission power transmitters (50 to 100mW), with very low data rates (124 bps), enhancement of high data rates (1200-4800 bps), and downlink performance, at the whole contribution to enhance the system capacity (50,000 active beacons per month instead of 20,000 today). In parallel of this ‘institutional Argos’ constellation, in the context of a miniaturization trend in the spatial industry in order to reduce the costs and multiply the satellites to serve more and more societal needs, the French Space Agency CNES, which designs the Argos payloads, is innovating and launching the Argos ANGELS project (Argos NEO Generic Economic Light Satellites). ANGELS will lead to a nanosatellite prototype with an Argos NEO instrument (30 cm x 30 cm x 20cm) that will be launched in 2019. In the meantime, the design of the renewal of the Argos constellation, called Argos For Next Generations (Argos4NG), is on track and will be operational in 2022. Based on Argos 4 and benefitting of the feedback from ANGELS project, this constellation will allow revisiting time of fewer than 20 minutes in average between two satellite passes, and will also bring more frequency bands to improve the overall capacity of the system. The presentation will then be an overview of the Argos system, present and future and new capacities coming with it. On top of that, use cases of two Argos hardware modules will be presented: the goniometer pathfinder allowing recovering Argos beacons at sea or on the ground in a 100 km radius horizon-free circle around the beacon location and the new Argos 4 chipset called ‘Artic’, already available and tested by several manufacturers.

Keywords: Argos satellite telemetry, marine protected areas, oceanography, maritime services

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Authors: Boulis M. Ibrahim, Iordanis A. Kalaitzoglou

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A micro structural pricing model is proposed in which price components account for learning by incorporating changing expectations of the trading intensity and the risk level of incoming trades. An analysis of European carbon futures transactions finds expected trading intensity to increase the information component and decrease the liquidity component of price changes, but at different rates. Among the results, the expected persistence in trading intensity explains the majority of the auto correlations in the level and the conditional volatility of price changes, helps predict hourly patterns in the bid–ask spread and differentiates between the impact of buy versus sell and continuing versus reversing trades.

Keywords: CO2 emission allowances, market microstructure, duration, price discovery

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Authors: Aisha Maroof

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Introduction: Coronavirus Disease 2019 (COVID-19) is spreading rapidly around the world with devastating consequences on patients, health care workers and health systems. Severe 2019 novel coronavirus infectious disease (COVID-19) with pneumonia is associated with high rates of admission to the intensive care unit (ICU) and they are at high risk to obtain the hospital acquire bloodstream infection (HAIs) such as central line associated bloodstream infection (CLABSI), catheter associated urinary tract infections (CAUTI) and laboratory confirm bloodstream infection (LCBSI). The chances of infection transmission increase when healthcare worker’s (HCWs) practice is inappropriate. Risk related to hand hygiene (HH) and personal protective equipment (PPE) as regards multidrug-resistant organism transmission: use of multiple gloving instead of HH and incorrect use of PPE can lead to a significant increase of device-related infections. As it reaches low- and middle-income countries, its effects could be even more, because it will be difficult for them to react aggressively to the pandemic. HAIs are one of the biggest medical concerns, resulting in increased mortality rates. Objective: To assess the effect of intervention on compliance of hand hygiene and PPE among HCWs reduce the rate of HAI in COVID-19 patients. Method: An interventional study was done between July to December, 2020. CLABSI, CAUTI and LCBSI data were collected from the medical record and direct observation. There were total of 50 Nurses, 18 doctors and all patients with laboratory-confirmed severe COVID-19 admitted to the hospital were included in this research study. Respiratory tract specimens were obtained after the first 48 h of ICU admission. Practices were observed after and before intervention. Education was provided based on WHO guidelines. Results: During the six months of study July to December, the rate of CLABSI, CAUTI and LCBSI pre and post intervention was reported. CLABSI rate decreasedd from 22.7 to 0, CAUTI rate was decreased from 1.6 to 0, LCBSI declined from 3.3 to 0 after implementation of intervention. Conclusion: HAIs are an important cause of morbidity and mortality. Most of the device related infections occurs due to lack of correct use of PPE and hand hygiene compliance. Hand hygiene and PPE is the most important measure to protect patients, through education it can be improved the correct use of PPE and hand hygiene compliance and can reduce the bacterial infection in COVID-19 patients.

Keywords: hospital acquire infection, healthcare workers, hand hygiene, personal protective equipment

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Authors: A. Majidian

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The life prediction of thermal power plant components is necessary to prevent the unexpected outages, optimize maintenance tasks in periodic overhauls and plan inspection tasks with their schedules. One of the main critical components in a power plant is condenser because its failure can affect many other components which are positioned in downstream of condenser. This paper deals with factors affecting life of condenser. Failure rates dependency vs. these factors has been investigated using Artificial Neural Network (ANN) and fuzzy logic algorithms. These algorithms have shown their capabilities as dynamic tools to evaluate life prediction of power plant equipments.

Keywords: life prediction, condenser tube, neural network, fuzzy logic

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Authors: Sidramappa Gaddnakeri, Lokanath Malligawad

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Any kind of research on production technology of individual crop / commodity /breed has not brought sustainability or stability in crop production. The sustainability of the system over years depends on the maintenance of the soil health. Organic production system includes use of organic manures, biofertilizers, green manuring for nutrient supply and biopesticides for plant protection helps to sustain the productivity even under adverse climatic condition. The study was initiated to evaluate the performance of different cropping systems under organic, inorganic and integrated production systems at The Institute of Organic Farming, University of Agricultural Sciences, Dharwad (Karnataka-India) under ICAR Network Project on Organic Farming. The trial was conducted for four years (2013-14 to 2016-17) on fixed site. Five cropping systems viz., sequence cropping of cowpea – safflower, greengram– rabi sorghum, maize-bengalgram, sole cropping of pigeonpea and intercropping of groundnut + cotton were evaluated under six nutrient management practices. The nutrient management practices are NM1 (100% Organic farming (Organic manures equivalent to 100% N (Cereals/cotton) or 100% P2O5 (Legumes), NM2 (75% Organic farming (Organic manures equivalent to 75% N (Cereals/cotton) or 100% P2O5 (Legumes) + Cow urine and Vermi-wash application), NM3 (Integrated farming (50% Organic + 50% Inorganic nutrients, NM4 (Integrated farming (75% Organic + 25% Inorganic nutrients, NM5 (100% Inorganic farming (Recommended dose of inorganic fertilizers)) and NM6 (Recommended dose of inorganic fertilizers + Recommended rate of farm yard manure (FYM). Among the cropping systems evaluated for different production systems indicated that the Groundnut + Hybrid cotton (2:1) intercropping system found more remunerative as compared to Sole pigeonpea cropping system, Greengram-Sorghum sequence cropping system, Maize-Chickpea sequence cropping system and Cowpea-Safflower sequence cropping system irrespective of the production systems. Production practices involving application of recommended rates of fertilizers + recommended rates of organic manures (Farmyard manure) produced higher net monetary returns and higher B:C ratio as compared to integrated production system involving application of 50 % organics + 50 % inorganic and application of 75 % organics + 25 % inorganic and organic production system only Both the two organic production systems viz., 100 % Organic production system (Organic manures equivalent to 100 % N (Cereals/cotton) or 100 % P2O5 (Legumes) and 75 % Organic production system (Organic manures equivalent to 75 % N (Cereals) or 100 % P2O5 (Legumes) + Cow urine and Vermi-wash application) are found to be on par. Further, integrated production system involving application of organic manures and inorganic fertilizers found more beneficial over organic production systems.

Keywords: cropping systems, production systems, cowpea, safflower, greengram, pigeonpea, groundnut, cotton

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Authors: Babak Qasemi-Panahi, Gholamali Moghaddam, Seyed-Abbas Rafat, Hossein Daghigh Kia, Mansoureh Movahedin, Reza Hadavi

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The objective of this study was to determine the effects of IGF-I on ovine oocytes maturation and subsequent development of embryos derived from in vitro fertilization (IVF). In vitro maturation (IVM) of oocytes and in vitro culture (IVC) of embryos was conducted with or without 100 ng/mL IGF-1. In the IGF-I treated group, mean percentage of oocyte maturation was significantly higher than the control group (57.67 ± 3.04 versus 49.81 ± 3.04%, respectively, P < 0.05). However, in comparison with control group, there was no significant effect of IGF-1 on rates of cleavage, morula, and blastocyst formation (85% versus 84%; 63% versus 65%, and 40% to 39%, respectively). These data demonstrate that IGF-I has a positive effect on ovine oocyte maturation rate, but it has not the significant outcome on embryo development.

Keywords: ovine, IGF-I, IVM, ICSI

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Authors: Abdulmagid A. Khattabi, Ahmed A. Hablous, Mofied M. Elnemry

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The carbon steel is of one of the most common mineral materials used in engineering and industrial applications in order to have access to the required mechanical properties, especially after the change of carbon ratio, but this may lead to stimulate corrosion. It has been used in models of solids with different carbon ratios such as 0.05% C, 0.2% C, 0.35% C, 0.5% C, and 0.65% C and have been studied using three testing durations which are 4 weeks, 6 weeks, and 8 weeks and among different corrosion environments such as atmosphere, fresh water, and salt water. This research is for the purpose of finding the effect of the carbon content on the corrosion resistance of steels in different corrosion medium by using the weight loss technique as a function of the corrosion resistance. The results that have been obtained through this research shows that a correlation can be made between corrosion rates and steel's carbon content, and the corrosion resistance decreases with the increase in carbon content.

Keywords: proportion of carbon in the steel, corrosion rate, erosion, corrosion resistance in carbon-steel

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Authors: A. S. Fetisova, M. N. Erofeeva, G. S. Alekseeva, K. A. Volobueva, M. D. Kim, S. V. Naidenko

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Weaning is characterized by the transition from milk to solid food. In some species, such changes in diet are fast and gradual in others. The reasons for the weaning start are understandable. Changes in milk composition and a decrease in maternity behavior push cubs to search for additional sources of nutrients. In nature, females have many opportunities to wean offspring in case of a lack of resources. In contrast in controlled conditions the possibility of delayed weaning exists. The delay of weaning can lead to overspending of maternal resources. In addition, the main causes of weaning end are not so obvious. Near the weaning end behavior of offspring depends on many factors: intensity of maternal behavior, reduction of milk abundance, brood size, physiological status, and body mass. During the pre-weaning period dynamic of body mass is strongly connected with milk intake. It is known that some animals usually wean their offspring when it has achieved body mass in some proportion to the weight of adult animal. In turn, we put forward the hypothesis that decrease in growth rates causes the delay of weaning in Eurasian lynxes (Lynx lynx). To confirm the hypothesis, we compared the dynamic of body mass with duration of milk sucking. Firstly, to get information about duration of sucking we visually observed 8 lynx broods from 30 to 120 days postpartum. During each 4-hour observation we registered the start and the end of sucking acts and then calculate the total duration of this behavior. To get the dynamic of body mass kittens were weighed once a week. Duration of sucking varied from 3076,19 ± 1408,60 to 422,54 ± 285,38 seconds when body mass gain changed from 247,35 ± 26,49 to 289,41 ± 122,35 seconds. Results of Kendall Tau correlation test (N= 96; p< 0,05) showed a negative correlation (τ= -0,36) between duration of sucking and body mass of lynx kittens. In general duration of sucking grows in response to decrease in body mass gain with slight delay. In early weaning from 30 to 58 days duration of sucking goes down gradually as does the body mass gain. During the weaning period the negative correlation between sucking time and body mass becomes tighter. Although throughout the weaning consumption of solid food begins to prevail over the milk intake, the correlation persists until the end of weaning (90-105 days) and after it. In that way weaning in Eurasian lynxes is not a part of ontogenesis controlled only by maternal behavior. It seems to be a flexible process influenced by various factors including changes in growth rates. It is necessary to continue investigations to determine the critical value of body mass which marks the safe moment to stop milk feeding. Understanding such details of ontogenesis is very important to organize procedures aimed at the reproduction of mammals ex situ and the conservation of endangered species.

Keywords: body mass, lynx, milk feeding, weaning

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Authors: Naveed Ali

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Under the construct of the ‘traditional family’ set-up (male and female parent) in the United Kingdom, the absence of a male parental figure remains a critical factor associated with an elevated risk of criminal behavior among youths. Empirical evidence suggests that father absence significantly correlates with increased rates of juvenile delinquency and criminality. For instance, data reveals that approximately 63% of young offenders in the United Kingdom originate from single-parent households, predominantly those without a father. Moreover, research displays that boys from father-absent homes are three times more likely to exhibit antisocial behavior compared to their peers from two-parent families. This absence can negatively impact educational attainment, with children from fatherless homes being twice as likely to leave school prematurely, thereby increasing their vulnerability to peer influence and gang affiliation- key pathways into criminal activities. Both legal frameworks and social policies in the United Kingdom acknowledge the pivotal role of family stability in crime prevention. Initiatives including parenting support programs, community-based interventions, and targeted youth services seek to address the challenges faced by single-parent families and mitigate the criminogenic effects of father absence. Despite these efforts, persistent challenges remain, including the need to address the broader socioeconomic determinants of family instability and to refine legal strategies that effectively address the root causes of youth offending linked to the absence of a male parental figure. A nuanced understanding of these dynamics is essential for developing more effective legal and social interventions aimed at reducing juvenile delinquency and supporting at-risk populations within the United Kingdom. This paper will highlight the significant impact of the absence of a male parental figure on youth crime rates in the United Kingdom, underlining the need for enhanced legal and social responses. By examining the interplay between family structure and juvenile offending, the paper will underline the importance of developing more comprehensive interventions that address both familial factors and the wider socioeconomic context. The findings aim to guide policymakers and practitioners in creating more effective strategies to reduce youth crime, ultimately strengthening support systems for vulnerable families and mitigating the adverse effects of father absence on young individuals.

Keywords: criminality, family law, legal framework, the united kingdom perspective

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Authors: Muhammad Abid

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Utilization of renewable energy resources for energy conservation, pollution prevention, resource efficiency and systems integration is very important for sustainable development. In this study, we perform energy and exergy analyses of a wind turbine, located on the roof of Mechanical Engineering Department, King Saud University, and Riyadh, Saudi Arabia. The turbine is part of a hybrid photovoltaic (PV)-wind system with hydrogen storage. The power output from this turbine varies between 1.5 and 5.5 kW with a rated wind speed of 12 m/s and a cut-in wind speed of 2.4 m/s. We utilize a wide range of experimental data in the analysis and assessment. We determine energy and exergy efficiencies. The energy efficiency changes between 0% to 45% while the exergy efficiency varies between 0% and 31.3%. We also determined some of the exergoeconomic parameters that are the ratios of energy and exergy loss rates to the capital cost (R en and R ex), respectively. (R en) changes between 0.96% and 59.03% for different values of velocity while R ex has a maximum value of 53.62% for the highest wind speed.

Keywords: exergy, efficiency, performance evaluation, wind energy

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Authors: Vivek Bhat, Rohini Kelkar, Sanjay Biswas

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Introduction: Cancer patients are at increased risk of bacterial infections. This may due to the disease process itself, the effect of chemotherapeutic drugs or invasive procedures such as catheterization. A wide variety of bacteria including some emerging pathogens are increasingly being reported from these patients. The incidence of multidrug-resistant organisms particularly in the Gram negative group is also increasing, with higher resistance rates seen to cephalosporins, β-lactam/β-lactam inhibitor combinations, and the carbapenems. This study documents the bacteriological spectrum of infections and their resistance patterns in cancer patients. Methods: This study includes all bacterial isolates recovered from infections cancer patients over a period of 18 months. Samples included Blood cultures, Pus/wound swabs, urine, tissue biopsies, body fluids, catheter tips and respiratory specimens such as sputum and bronchoalveolar lavage (BAL). All samples were processed in the microbiology laboratory as per standard laboratory protocols. Organisms were identified to species level and antimicrobial susceptibility testing was performed manually by the disc diffusion technique or in the Vitek-2 (Biomereux, France) instrument. Interpretations were as per Clinical laboratory Standards Institute (CLSI) guidelines. Results: A total of 1150 bacterial isolates were cultured from 884 test samples during the study period. Of these 227 were Gram-positive and 923 were Gram-negative organisms. Staphylococcus aureus (99 isolates) was the commonest Gram-positive isolate followed by Enterococcus (79) and Gr A Streptococcus (30). Among the Gram negatives, E. coli (304), Pseudomonas aeruginosa (201) and Klebsiella pneumoniae (190) were the most common. Of the Staphylococcus aureus isolates 27.2% were methicillin resistant. Only 5.06% enterococci were vancomycin resistant. High rates of resistance to cefotaxime and ciprofloxacin were seen amongst E. coli (84.8% & 83.55%) and Klebsiella pneumoniae (71 & 62.1%) respectively. Resistance to carbapenems (meropenem) was high at 70% in Acinetobacter spp.; however all isolates were sensitive to colistin. Among the aminoglycosides, amikacin retained good efficacy against Escherichia coli (82.9%) and Pseudomonas aeruginosa (78.1%). Occasional isolates of emerging pathogens such as Chryseobacterium indologens, Roseomonas, and Achromobacter xyloxidans were also recovered. Conclusion: The common infections in cancer patients include respiratory, wound, tract infections and sepsis. The commonest isolates include Staphylococcus aureus, Enterococci, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa. There is a high level of resistance to the commonly used antibiotics among Gram-negative organisms.

Keywords: bacteria, resistance, infection, cancer

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Authors: S. Belgherras Bekkouche, T. Benouaz, S. M. A. Bekkouche

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Tokamak plasma is far from having a stable background. The study of turbulent transport is an important part of the current research and advanced scenarios were devised to minimize it. To do this, we used a three-wave interaction model which allows to investigate the occurrence drift-wave turbulence driven by pressure gradients in the edge plasma of a tokamak. In order to simulate the energy redistribution among different modes, the growth/decay rates for the three waves was added. After a numerical simulation, we can determine certain aspects of the temporal dynamics exhibited by the model. Indeed for a wide range of the wave decay rate, an intermittent transition from periodic behavior to chaos is observed. Then, a control strategy of chaos was introduced with the aim of reducing or eliminating the weak turbulence.

Keywords: wave interaction, plasma drift waves, wave turbulence, tokamak, edge plasma, chaos

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Authors: Suk-Hyun Yu, Heeyong Kwon

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Recently PM-10 has become a social and global issue. It is one of major air pollutants which affect human health. Therefore, it needs to be forecasted rapidly and precisely. However, PM-10 comes from various emission sources, and its level of concentration is largely dependent on meteorological and geographical factors of local and global region, so the forecasting of PM-10 concentration is very difficult. Neural network model can be used in the case. But, there are few cases of high concentration PM-10. It makes the learning of the neural network model difficult. In this paper, we suggest a simple input balancing method when the data distribution is uneven. It is based on the probability of appearance of the data. Experimental results show that the input balancing makes the neural networks’ learning easy and improves the forecasting rates.

Keywords: artificial intelligence, air quality prediction, neural networks, pattern recognition, PM-10

Procedia PDF Downloads 227