Short-term Usage Research Articles

Fitting a Hearing Aid on the Better Ear, Worse Ear, or Both: Associations of Hearing-aid Fitting Laterality with Outcomes in a Large Sample of US Veterans.

Longitudinal electronic health records from a large sample of new hearing-aid (HA) recipients in the US Veterans Affairs healthcare system were used to evaluate associations of fitting laterality with long-term HA use persistence as measured by battery order records, as well as with short-term HA use and satisfaction as assessed using the International Outcome Inventory for Hearing Aids (IOI-HA), completed within 180 days of HA fitting. The large size of our dataset allowed us to address two aspects of fitting laterality that have not received much attention, namely the degree of hearing asymmetry and the question of which ear to fit if fitting unilaterally. The key findings were that long-term HA use persistence was considerably lower for unilateral fittings for symmetric hearing loss (HL) and for unilateral worse-ear fittings for asymmetric HL, as compared to bilateral and unilateral better-ear fittings. In contrast, no differences across laterality categories were observed for short-term self-reported HA usage. Total IOI-HA score was poorer for unilateral fittings of symmetric HL and for unilateral better-ear fittings compared to bilateral for asymmetric HL. We thus conclude that bilateral fittings yield the best short- and long-term outcomes, and while unilateral and bilateral fittings can result in similar outcomes on some measures, we did not identify any HL configuration for which a bilateral fitting would lead to poorer outcomes. However, if a single HA is to be fitted, then our results indicate that a better-ear fitting has a higher probability of long-term HA use persistence than a worse-ear fitting.

A spatio-temporal deep learning model for short-term bike-sharing demand prediction

<abstract> <p>Bike-sharing systems are widely operated in many cities as green transportation means to solve the last mile problem and reduce traffic congestion. One of the critical challenges in operating high-quality bike-sharing systems is rebalancing bike stations from being full or empty. However, the complex characteristics of spatiotemporal dependency on usage demand may lead to difficulties for traditional statistical models in dealing with this complex relationship. To address this issue, we propose a graph-based neural network model to learn the representation of bike-sharing demand spatial-temporal graph. The model has the ability to use graph-structured data and takes both spatial- and temporal aspects into consideration. A case study about bike-sharing systems in Nanjing, a large city in China, is conducted based on the proposed method. The results show that the algorithm can predict short-term bike demand with relatively high accuracy and low computing time. The predicted errors for the hourly station level usage demand prediction are often within 20 bikes. The results provide helpful tools for short-term usage demand prediction of bike-sharing systems and other similar shared mobility systems.</p> </abstract>

Radar-Based Multisensor Fusion for Uninterrupted Reliable Positioning in GNSS-Denied Environments

Multi-sensor integration is necessary to provide high-precision navigation solutions for autonomous vehicles. Land-vehicles often rely on global navigation satellite systems (GNSS) to acquire its position. However, there are some environments where GNSS signals are unavailable, such as indoor-parking garages, tunnels, and under bridges. Additional sensors are required to allow reliable positioning regardless of location. The vehicle’s on-board low cost inertial sensors (accelerometers and gyroscopes) are used for positioning in GNSS-denied environments. Despite their fidelity in short-term usage, inertial navigation systems (INS) are susceptible to drifts in their positioning solution due to the inherent inertial sensor errors, causing positioning errors over time in prolonged scenarios, such as indoor-parking garages. Modern land-vehicles can be equipped with a diversified set of perception systems (e.g. LiDAR, cameras) to provide information about the surrounding environment. These systems are well-studied in literature to provide accurate positioning. Yet, the performance of these systems may degrade in weather conditions such as heavy snow or rain, and may fail in degraded vision environments. The proposed research addresses some of the limitations of current positioning technologies for land vehicles by integrating low-cost on-board motion sensors with the all-weather electronic scanning radar (ESR) systems presently used in adaptive cruise control. This research employs a method of estimating the vehicle position based on multiple ESR systems. Integration with the on-board motion sensors guarantees continuous positioning estimation for uninterrupted navigation. The multi-sensor system integration utilizes extended Kalman filter (EKF) with a unique dynamic tuning approach for reliable and uninterrupted positioning. The proposed solution was examined in real GNSS-denied scenario of an indoor parking. This research has reached an uninterrupted self-contained EKF-based multi-sensor positioning system providing less than 2m error 90% of the time in a GNSS-denied environment for up to four minutes.

Therapeutic Efficacy of Ivermectin in Novel Coronavirus Disease-2019 Patient Admitted at the Ward of a Tertiary Care Hospital: A Retrospective Study

Objective: An observational, retrospective, institution-based study to observe the pattern of ivermectin use related to patients’ characteristics. Methods: Patient data including short-term diagnosis, investigations done, and drug usage data were captured in a predesigned, structured case report form; and suspected adverse events were recorded in the standard suspected adverse drug reaction reporting form recommended by the “Central Drug Standard Control Organization,” India. The study was for a period of 7 months from August 01, 2020, to February 28, 2021. A total of 4,552 patients were recruited in this study and followed up till their discharge or death. The comparison was made between not given and given of ivermectin among patients. Results: Data were summarized by routine descriptive and statistical analysis. The mean age (years), length of stay (days) onset from hospitalization, pulse rate, systolic blood pressure (SBP), and temperature did not show significant change. However, respiratory rate was found to decrease significantly (p < 0.001), and oxygen saturation (SpO2) was found to increase significantly (p < 0.001) in the ivermectin-treated group. It was also observed that a positive correlation with a highly significant value (p < 0.000) between age (years), length of stay (days) onset from, pulse rate, SBP, and temperature and ivermectin usage while a negative correlation with highly significant value (p < 0.000) between SpO2 and ivermectin usage was obtained. Conclusion: As per the studied parameters, a significant correlation was observed in combinations of the treated and untreated groups. Further research suggested the dose-dependent efficacy of ivermectin usage in the novel coronavirus disease-2019 patients.

Word Usage Change and the Pandemic: A Computational Analysis of Short-Term Usage Change in the Italian Reddit Community

The COVID-19 pandemic has affected every aspect of our lives. Our work assesses whether it has also impacted the usage of the Italian language, particularly its lexicon. We create a new corpus of Italian texts taken from Reddit and apply a recent unsupervised usage change detection method on two sub-corpora, one with data from 2019 and one with data from 2020. The focus of our investigation is short-term usage change. The results for the first 10-top candidates and for a selection of candidates among the top-100 are analyzed, to show that usage change has indeed happened.

The Efficacy and Safety of Short-Term Tolvaptan Usage in Patients with Acute Decompensated Heart Failure.

Patients admitted with acute decompensated heart failure (ADHF) have a poor prognosis and poor quality of life due to dyspnea and edema. Tolvaptan, a vasopressin V2 receptor antagonist, is an effective water diuretic. This study aimed to evaluate the efficacy and safety of a short course of tolvaptan to treat volume overload in patients with ADHF. We conducted a phase III, multicenter, randomized, double-blind, placebo-controlled study to evaluate the efficacy and safety of a short course of tolvaptan (15 mg/day for 4 days) in hospitalized ADHF patients with volume overload despite the use of conventional diuretics. The primary end-point was the change in body weight after 4 days of treatment. The secondary end-points were the change in intake/output balance, change in serum sodium/potassium concentrations, physician/patient assessed signs and symptoms of heart failure after 4 days of treatment, and all-cause mortality in 1 month. A total of 110 patients were screened, and 91 were randomized to receive 15 mg/day of tolvaptan for 4 days (n = 46) or matching placebo (n = 45). Compared to the placebo-treated patients, tolvaptan significantly reduced body weight (-1.36 ± 2.13 kg in the tolvaptan group vs. -0.59 ± 1.27 kg in the placebo group, p = 0.0394). The tolvaptan group also had a negative intake/urine volume balance compared to the placebo group (-509.3 ± 2788.2 ml vs. 975.5 ± 1903.1 ml, p = 0.0059). The safety profile of tolvaptan was acceptable. Tolvaptan significantly reduced volume overload in hospitalized ADHF patients with volume overload despite the use of conventional diuretics.

The short-term effect of a mHealth intervention on gestational weight gain and health behaviors: The SmartMoms Canada pilot study

Gestational weight gain (GWG) has been shown to impact several maternal-infant outcomes. Since healthcare provider guidance on weight gain and healthy behaviors alone has failed to help women to meet guidelines during pregnancy, a practical adjunctive approach is to deliver evidence-based behavior change programs through mobile interventions. The present study aimed to assess the short-term effect of the SmartMoms Canada app to promote adequate GWG and healthy behaviors. Twenty-nine pregnant women were recruited in this app-based intervention trial to test whether a higher app usage (≥ 3.8 min·week−1) between 12–20 gestational weeks and 24–28 gestational weeks improved GWG, diet, physical activity, and sleep, compared to women with a lower app usage (< 3.8 min·week−1). Two-way mixed ANOVA for repeated measures was used to estimate the effect of the app usage and time, as well as their interaction on GWG and healthy behaviors. The likelihood ratio was used to examine the association between app usage categorization and GWG classification. Cramer's V statistic was used to estimate the effect size for interpretation of the association. Pregnant women using the SmartMoms Canada app more frequently had a higher moderate-to-vigorous physical activity (MVPA) daily average when compared with women with a lower usage (mean difference: 17.84 min/day, 95% CI: 2.44; 33.25). A moderate effect size (28.6% vs. 15.4%; Cramer's V = 0.212) was found for the association between app categorization and rate of GWG, representing a greater adherence to the GWG guidelines in women in the higher app usage group vs. the lower app usage group. Considering other physical activity, diet, and sleep variables, no app categorization effect was observed. A short-term higher usage of SmartMoms Canada app has a positive effect on objectively-measured MVPA.

Short-Term Forecast of Bicycle Usage in Bike Sharing Systems: A Spatial-Temporal Memory Network

Bike-sharing systems have made notable contributions to cities by providing green and sustainable mobility service to users. Over the years, many studies have been conducted to understand or anticipate the usage of these systems, with the hope to inform their future developments. One important task is to accurately predict usage patterns of the systems. Although many deep learning algorithms have been developed in recent years to support travel demand forecast, they have mainly been used to predict traffic volume or speed on roadways. Few studies have applied them to bike-sharing systems. Moreover, these studies usually focus on one single dataset or study area. The effectiveness and robustness of the prediction algorithms are not systematically evaluated. In this study, we propose a Spatial-Temporal Memory Network (STMN) to predict short-term usage of bicycles in bike-sharing systems. The framework employs Convolutional Long Short-Term Memory models and a feature engineering technique to capture the spatial-temporal dependencies in historical data for the prediction task. Four testing sites are used to evaluate the model. These four sites include two station-based systems (Chicago and New York) and two dockless bike-sharing systems (Singapore and New Taipei City). By assessing STMN with several baseline models, we find that STMN achieves the best overall performance in all the four cities. The model also achieves superior performance in urban areas with varying levels of bicycle usage and during peak periods when demand is high. The findings suggest the reliability of STMN in predicting bicycle usage for different types of bike-sharing systems.

Investigation of the effects of lipoic acid and dihydrolipoate on experimental renal ischemia-reperfusion model

Objective: Ischemic/reperfusion (I/R) causes tissue injury and the leading cause of acute kidney injury. In this study, we aimed to investigate the effects of the long and short-term usage of ALA and short-term DHLA on oxidative stress markers in the experimental renal ischemia-reperfusion model. Methods: Forty male rats (250 to 300 gr) were divided into 5 groups: control; I/R group; long-term ALA+IR group; short-term ALA+IR group; and short-term DHLA+IR group. Ischemia was carried out for 45 minutes followed by reperfusion for 4 hours. Thiobarbituric acid reactive sunstances (TBARM), catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) activities in tissue samples and serum total antioxidant status (TAS) and total oxidative stress (TOS) assayed by the spectrophotometrically. Tissue samples were investigated by histopathological analyzes. Results: TBARM (Control: 0.38±0.05. I/R: 1.37±0.17, long-term ALA-treated group:1.025±0.15, short-term ALA-treated group: 0.68±0.09, short-term DHLA-treated group: 0.38±0.04 (nmol/mg protein); p<0,001) CAT (Control: 0.12±0.02, I/R: 0.04±0.008, long-term ALA-treated group: 0.07±0.01, short-term ALA-treated group:0.06±0.008, short-term DHLA-treated group: 0.08±0.01 (k/mg protein); p<0.001), GSH-Px (Control: 0.45±0.04, I/R: 0.21±0.028, long-term ALA-treated group: 0.37±0.05, short-term ALA-treated group :0.34±0.05, short-term DHLA-treated group: 0.37±0.04 (U/mg protein); p<0.001), and serum OSI levels (Control: 1.32±0.15, I/R: 3.08±0.44, long-term ALA-treated group: 1.775±0.21, short-term ALA-treated group: 1.85±0.37, short-term DHLA-treated group: 1.53±0.21 (arbitrary unit) ; p<0.001) were improved in the long and short-term ALA-treated group and short-term DHLA-treated group compared to the I/R group. These findings were more prominent in histopathological tissue samples in the DHLA-treated group. Conclusion: We consider that both long-term and short-term ALA applications have the potential for the treatment of renal I/R damage. Besides, DHLA is more effective than ALA.

Practice Management Strategies for Imaging Facilities Facing an Acute Iodinated Contrast Media Shortage.

An unanticipated but severe shortage in iodinated contrast media (ICM) is currently affecting imaging practices across the globe and is expected to persist through at least the end of June 2022. This supply shock may lead health care systems to experience an acute imaging crisis, given that many affected facilities have contrast agent supplies that are anticipated to last only a week or two under normal operating conditions. To maximize the opportunity to continue to provide optimal care for patients with emergent or life-threatening imaging indications and thereby minimize the overall impact on patient care, practice leaders will need to quickly assess their contrast material inventories, prioritize examination indications, and reduce their expected short-term usage of ICM. This Clinical Perspective reviews ICM conservation techniques that the Yale School of Medicine has deployed or is considering deploying, depending on the severity and length of the supply shortage.

Analgesic Efficacy of Multiple Single-Shot Peripheral Nerve Blocks on Postoperative Short-Term Opioid Usage and Clinical Outcomes in a Suburban Hospital Setting.

BackgroundPreoperative single-shot peripheral nerve blocks (sPNBs) represent promising candidates for controlling postoperative pain, reducing dependence on opioid medications, and reducing postoperative constipation and ileus. However, there is not yet complete consensus regarding their efficacy. The primary aim of this study was to assess the impact of various sPNBs on patient short-term opioid demands and pain management parameters.MethodsThis single-center study retrospectively reviewed a cohort of 94 adult, elective surgery inpatients (ASA physical status I-III) scheduled for different operations. Sixty-four (68.1%) were selected for sPNB administration (group 1) and compared to the untreated group (group 0) for different clinical parameters.ResultsContrary to the starting hypothesis, a higher proportion of group 1 patients experienced increasing pain intensities during the immediate postoperative period (P < 0.05, Fisher’s exact test), while requiring more bowel care medications (P < 0.05, χ2 test). Multiple linear regression modeling, however, showed that recovery time positively correlated with the opioid amount consumed (P < 0.01). Although limited, the results obtained in this study do not support an analgesic efficacy for sPNBs.ConclusionIn conclusion, even though our data must be viewed within the limitations of our retrospective study and small group size, we did not find any compelling evidence for the efficacy of sPNB administration in the perioperative period.

Microhardness and biological behavior of AZ91D-nHAp surface composite for bio-implants

In the present research work, friction stir processing (FSP) has been adopted for the fabri­cation of nano-hydroxyapatite (nHAP) reinforced AZ91-D Mg-alloy matrix surface com­posite (NMMSC). The NMMSC was developed to replace the conventional bio-implants materials for short-term usage. The NMMSC has been prepared by adding nHAp rein­forcement in 12.5 % volumetric proportion in the AZ91-D alloy using the grooving technique followed by FSP. The FSP parameters were selected, such as the tool rotation of 1000 rpm, 50 mm/min transverse speed, and 5 multi-passes. The base alloy, normal FSPed, and fabricated NMMSC were characterized to study their micro-hardness values and biological performances. Improvement in microhardness value in the developed composites was observed due to the smaller grain size as a result of the dynamic recrystal­lization phenomenon. The antibacterial properties of FSPed and NMMSC specimens tested against Staphylococcus aureus, Candida albicans, and Aspergillus fumigatus were found to be superior as compared to the PM. The cytotoxicity of the FSPed &amp; NMMSC specimens expressed as cell viability using MTT assay shows negligible toxicity as compared to PM and the cell viability was insignificantly decreased as the incubation period was extended. The microhardness and biological performance of NMMSC have been improved due to the grain refinement by FSP and the presence of nHAp reinforcement in the material.

Effect of short-term corticosteroid usage on acute urinary toxicity following Cs-131 prostate brachytherapy

To evaluate short-term patient reported urinary quality of life scores in patients with prostate cancer treated at our institution with and without perioperative prednisone following Cesium-131 (131Cs) prostate LDR brachytherapy. We started routinely using a perioperative 7-day course of prednisone at a dose of 5 mg per day, beginning 1 day prior to 131Cs prostate LDR brachytherapy from 2013 with goal of improving acute urinary symptomatology. One hundred consecutive patients treated with prednisone were selected, with comparison to 100 consecutive patients who were not treated with prednisone. We analyzed for differences in mean change with standard deviation (SD) in EPIC and AUA scores at 0.5-1 month and 3 months with or without prednisone by Mann-Whitney U Test. Binary logistic regression was performed to assess for impact of prednisone on postoperative urinary catheter use. Pretreatment EPIC and AUA scores were available in 197 patients. Less reduction in EPIC US score was noted at 0.5-1.0 month in the group who received prednisone with mean change of -22.9 (SD 15.4) when compared to the group who did not receive prednisone with mean change of -31.7 (SD 19.3), p < 0.01, with significance lost at 3 months. There was no significant difference in acute urinary retention requiring postoperative urinary catheter placement with perioperative prednisone (OR 1.13, p = 0.71). A short course of perioperative low-dose prednisone was associated with less severe worsening in urinary symptoms by the EPIC questionnaire at the 0.5-1.0-month timepoint suggesting some improvement in acute urinary quality of life, although differences did not remain statistically significant at 3 months.

«Что делали для нас статуэтки?» Магия и агентность в преистории Балкан и Карпат

The work of Mary Helms and Alfred Gell on cultural transformations, object colour and brilliance and their links to ritual power emphasises the most important aspect of magic for objects — its agency. The aesthetic of exotic, bright and colourful objects in the Neolithic and Copper Age of ‘Old Europe’ was central to the objects’ agency. However, the vast majority of figurines from this region was neither polished nor highly coloured, nor even decorated — sometimes showing signs of rapid production for short-term usage. Yet there is a widespread notion that figurines had the potential to produce special effects in ritual practice. Just as the agency of figurines is ‘culture-specific’ as well as context-specific, their potency depended upon a widespread underlying acceptance of what this particular class of objects could do for people. Here we pose two questions: how did figurines perform their agency? and was figurine’s agency fundamentally different from the agency of bright, colourful, exotic objects? We present four examples of the magical effects — i. e. the agency — of figurines from the Mesolithic, Neolithic and Copper Age of Old Europe: the efficacy of Lepenski Vir fish-persons; how figurines contributed to the practice of black magic in the Vinča group; the ability of the fragmentation of shiny, black Hamangia figurines to achieve significant social effects; and the arrangement of Cucuteni figurine sets to educate women about (in)fertility.

Mapping Exposure Diversity: The Divergent Effects of Algorithmic Curation on News Consumption

Abstract Diversity is a crucial precondition for a democratic public discourse. In today’s high-choice media environments, exposure to diverse news is largely determined by individuals’ personal selection. Yet these decisions are increasingly shaped by online platforms, whose curation mechanisms may serve to expand or contract the diversity of encountered content. In a major extension of existing research, we show that positive short-term effects of platforms mask detrimental long-term effects. Drawing on a four-month tracking dataset and a comprehensive content analysis covering the online news consumption of over 10,000 German citizens, we demonstrate that even though short-term usage of platforms uniformly increases exposure diversity, long-term reliance can lead to decreases. In addition, platforms vary in their influences: News aggregators are beneficial to exposure diversity, while Twitter and search engines have a limiting effect; Facebook offers no significant influence.

Longitudinal Monitoring Reveals Persistence of Colistin-Resistant Escherichia coli on a Pig Farm Following Cessation of Colistin Use.

Colistin-resistant bacteria harboring plasmid-mediated mcr genes are of concern as they may be a cause of serious nosocomial infections. It is hypothesized that cessation of colistin use as a feed additive for pigs will reduce the occurrence and distribution of mcr genes in farms. The aim of this study was to investigate this hypothesis by longitudinal monitoring and characterizing of mcr positive Escherichia coli (MCRPE) isolates after colistin was withdrawn on a central Thailand pig farm that previously had a high frequency of MCRPE. Colistin use ceased at the beginning of 2017, and subsequently 170 samples were collected from farrowing sows and suckling piglets (n = 70), wastewater (n = 50) and farm workers (n = 50) over a 3.5-year period. Bacteria were identified by MALDI-TOF mass spectrometry and minimal inhibitory concentrations were determined by broth microdilution. The antibiogram of mcr positive E. coli isolates was determined using the Vitek2 automated susceptibility machine, and multiplex and simplex PCRs were performed for mcr-1–8 genes. MCRPE containing either mcr-1 or mcr-3 were isolated from pigs throughout the investigation period, but with a declining trend, whereas MCRPE isolates were recovered from humans only in 2017. MCRPE were still being recovered from wastewater in 2020. Most MCRPE isolates possessed the virulence genes Stap, Stb, or Stx2e, reflecting pathogenic potential in pigs, and showed high rates of resistance to ampicillin, gentamicin and tetracycline. Pulsed-field gel electrophoresis and multi-locus sequence typing showed that diverse MCRPE clones were distributed on the farm. The study identified a decline of pathogenic MCRPE following withdrawal of colistin, with pigs being the primary source, followed by wastewater. However, short-term therapeutic usage of other antibiotics could enhance the re-occurrence of mcr-carrying bacteria. Factors including the environment, management, and gene adaptations that allow maintenance of colistin resistance require further investigation, and longer-term studies are needed.

Short-term effect of dopaminergic medication on speech in early-stage Parkinson\u2019s disease

The effect of dopaminergic medication on speech has rarely been examined in early-stage Parkinson’s disease (PD) and the respective literature is inconclusive and limited by inappropriate design with lack of PD control group. The study aims to examine the short-term effect of dopaminergic medication on speech in PD using patients with good motor responsiveness to levodopa challenge compared to a control group of PD patients with poor motor responsiveness. A total of 60 early-stage PD patients were investigated before (OFF) and after (ON) acute levodopa challenge and compared to 30 age-matched healthy controls. PD patients were categorised into two clinical subgroups (PD responders vs. PD nonresponders) according to the comparison of their motor performance based on movement disorder society-unified Parkinson’s disease rating scale, part III. Seven distinctive parameters of hypokinetic dysarthria were examined using quantitative acoustic analysis. We observed increased monopitch (p > 0.01), aggravated monoloudness (p > 0.05) and longer duration of stop consonants (p > 0.05) in PD compared to healthy controls, confirming the presence of hypokinetic dysarthria in early PD. No speech alterations from OFF to ON state were revealed in any of the two PD groups and speech dimensions investigated including monopitch, monoloudness, imprecise consonants, harsh voice, slow sequential motion rates, articulation rate, or inappropriate silences, although a subgroup of PD responders manifested obvious improvement in motor function after levodopa intake (p > 0.001). Since the short-term usage of levodopa does not easily affect voice and speech performance in PD, speech assessment may provide a medication state-independent motor biomarker of PD.

Machine Learning Assisted Energy Optimization in Smart Grid for Smart City Applications

Peer-to-peer electricity transaction is predicted to play a substantial role in research into future power infrastructures as energy consumption in intelligent microgrids increases. However, the on-demand usage of Energy is a major issue for families to obtain the best cost. This article provides a machine learning predictive power trading framework for supporting distributed power resources in real-time, day-to-day monitoring, and generating schedules. Furthermore, the energy optimization algorithm used in machine learning (EOA-ML) is proposed in this article. The machine learning-based platform suggested two modules: fuel trading and intelligent contracts based on machine learning implemented predictive analytical components. The Blockchain module enables peers to track energy use in real-time, manage electricity trading, model rewards, and irreversible transaction records of electricity trading. A predictive analysis component based on previous power usage data is designed to anticipate short-term energy usage in the Intelligent Contracts. This study utilizes data from the provincial Jeju, Korea’s electricity department on true energy utilization. This study seeks to establish optimal electricity flow and crowdsourced, promoting electricity between consumers and prosumers. Power trading relies on day-to-day, practical environmental control and the planning of decentralized power capitals to satisfy the demands of smart grids. Furthermore, it employs data mining technologies to obtain and study time-series research from the past electricity utilization data. Thus, the time series analytics promotes power controllingto better future efficient planning and managingelectricity supplies. It utilized numerous statistical methods to assess the effectiveness of the suggested prediction model, mean square error in different models of machine learning, recurring neural networks. The efficacy of the proposed system regarding the delay, throughput, and resource using hyperleader caliper is shown. Finally, the suggested approach is successfully applied for power crowdsourcing between prosumer and customer to reach service reliability based on trial findings. The actual and predicted cost analysis has been increased (95%). It minimizes the delay rate to (40.3%) by improving the efficiency rate.

The Effects of Clofibrate on Neonatal Jaundice: A Systematic Review.

Background:Neonatal jaundice is a prevalent disease that causes many complications, including kernicterus and even death. Previous studies have shown that clofibrate as an aryloxy isobutyric acid derivate can be effectively applied for the treatment of neonatal jaundice. Thus, this review was carried out to investigate the effects and mechanism of action of clofibrate on neonatal jaundice.Methods:The keywords such as “Clofibrate” in combination with “Neonatal jaundice” or “Neonatal hyperbilirubinemia” or “Newborn Jaundice” were used to search for relevant publications indexed in the Institute for Scientific Information (ISI), Scopus, PubMed, and Google Scholar databases. Finally, after reviewing the studies, 24 papers were included in this study.Results:Results showed that the processes of albumin-bound bilirubin transfer to the hepatocytes, hepatic uptake, and storage via ligandin, hepatic conjugation via uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1), conjugation into the bile via MRP2 represent the main action mechanism of clofibrate that turns it into the bilirubin conjugates and expels it from the bile. Besides, clofibrate has been shown to reduce the level of Total Serum Bilirubin (TSB) in infants even at a dosage of 25 mg/kg without leaving side effects.Conclusions:The results of this review revealed that clofibrate effectively reduces TSB in short-term usage and can even have a promising effect at the dosage of 25 mg/kg in full-term infants. Most studies have shown this property over a short period in term infants, and there is no evidence about long-term usage in this regard.

Effects of covid 19 and short-term hydroxychloroquine usage on retina and choroid

Effects of covid 19 and short-term hydroxychloroquine usage on retina and choroid