Miracle-dz/UniFAR-FTUs huggingface dataset:
A Modified Interleaved Capacitor Clamped DC–DC Converter With Non-Resonant Soft Switching

Since the solar panels and fuel cells have low output voltage, which need to be converted to the 400 V or higher dc bus voltage in the renewable energy power generation systems, where, the high gain dc–dc converter plays a key role. Furthermore, with the requirement of the converter in low cost and high efficiency, the soft-switching interleaved boost-type converters based on switched-capacitor and voltage multiplier cell as the high gain dc–dc converters have been widely applied. However, the above-mentioned soft-switching interleaved boost-type converters in literature have resonant spikes on the switches or there are coupled inductors, which will cause the high cost due to the large stresses of the switches or low efficiency due to the high core losses of the coupled inductors. To solve the above-mentioned problems, a modified interleaved capacitor clamped (MICC) dc–dc converter with non-resonant soft-switching (NRSS) is proposed, in which only an auxiliary inductor operating in discontinuous conduction mode with few μH is used to achieve the zero-current-switching for all switches and diodes. Furthermore, the operating principle of the proposed converter is given, the interleaved boost structure is used as the front stage of the proposed converter to reduce the input current ripple and lighten the current stress on all switches and magnetic components, the MICC structure with NRSS as the output stage is proposed as a voltage multiplier module to achieve the high voltage gain. Then, the circuit parameter design for this converter is presented. Finally, a 400 W experimental prototype is built to verify the correctness and the effectiveness of the proposed topology.
Perioperative Low-Dose Ketamine for Postoperative Pain Management in Spine Surgery: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Objective Although low-dose ketamine has been shown to be generally beneficial in terms of pain control in a variety of major surgery, there is no consensus regarding the effectiveness of supplemental ketamine analgesic use exclusively in spine surgery. The objective of this systematic review and meta-analysis of randomized controlled trials (RCTs) was to assess the efficacy and safety of perioperative low-dose ketamine for pain management and analgesic consumption in patients undergoing spine surgery. Methods A comprehensive literature search was performed for relevant studies using PubMed, EMBASE, Web of Science, and Cochrane Library. Patients who received perioperative low-dose ketamine were compared to the control group in terms of postoperative pain intensity, opioid consumption, and adverse events. Patients were further categorized by ages and administration times for subgroup analysis. Results A total of 30 RCTs comprising 1,865 patients undergoing elective spine surgery were included. Significantly lower pain intensity and less opioid consumption at 12 h, 24 h, and 48 h postoperatively and lower incidence of postoperative nausea and vomiting (PONV) were observed in the ketamine group (all P < 0.05). There was no significant difference of central nervous system (CNS) adverse events between groups. However, different efficacy of low-dose ketamine was detected when patients were categorized by ages and administration times. Conclusion Perioperative low-dose ketamine demonstrated analgesic and morphine-sparing effect with no increased adverse events after spine surgery. However, this effect was not significant in pediatric patients. Only postoperative or intraoperative and postoperative administration could prolong the analgesic time up to 48 h postoperatively. Further studies should focus on the optimal protocol of ketamine administration and its effect on old age participants.
Effects of a Ketogenic Diet on Symptoms, Biomarkers, Depression, and Anxiety in Parkinson’s Disease: A Case Study

The ketogenic diet has grown in popularity as an alternative or adjunct to medication therapy for Parkinson's disease (PD) and other neurodegenerative diseases (NDD). Traditional medication therapies often fail to produce desired improvements in PD symptoms and can have little or no effect on symptoms of depression and anxiety that often accompany a PD diagnosis. We document a case study involving a 68-year-old female with PD stage I and a history of mild symptoms of anxiety and depression. The subject adopted a traditional ketogenic diet (fats 70%; protein 25%; carbohydrates 5%) for 24 weeks. Baseline, 12-week and 24-week biomarkers (lab results), and scores on a depression scale, anxiety scale, and the Unified Parkinson's Disease Rating Scale (UPDRS) (parts I-III) for PD symptoms were compared. Significant improvements were observed in all health biomarkers, including a reduction in HbA1C, C-reactive protein (CRP), triglycerides, and fasting insulin, along with weight loss and reduction in cardiac risk factors. Improved high-density lipoprotein (HDL) levels were seen at 12 weeks and 24 weeks, along with improved anxiety symptoms at the 12-week and 24-week mark. Minimum improvement was seen on depression scale scores at 24 weeks. Based on our findings, the ketogenic diet is safe and effective for improving biomarkers of health, symptoms of depression, anxiety, and PD symptoms in patients with stage I PD. We recommend further clinical trial studies for more generalizable results.
Coupling dynamics model of articulated mining truck based on three-dimensional coordinate system

according to the fact that coupling dynamics model of articulated mining truck cannot meet the requirements of stability control accuracy under the condition of machine unmanned and high-speed working condition currently, this paper puts forward a driving dynamics modeling method for articulated mining truck based on three-dimensional coordinate system. This paper takes steering wheel angle as input to establish the corresponding relation mathematical equation among hydraulic system flow and pressure, splice angle of front and rear frame and output force of left and right steering hydraulic cylinder. To establish dynamics model based on three-dimensional coordinate system considering axle load transfer and interactions between front frame and rear body. Coupling between two mathematical models is done to form driving dynamic model of whole vehicle. Adopt real vehicle test data and ADAMS model to verify vehicle dynamics model and the results showed that the established driving dynamics modeling method for articulated mining truck can accurately describe vehicle dynamics response. This model will provide a reliable platform for the study of stability control strategy of vehicle driving for articulated mining truck.
Systematic Literature Review on Methodology and Manufacturing Process of Personalized Tablet using Selective Laser Sintering Technology

3-dimensional printing (3DP) technology has garnered interests as a novel candidate for future pharmaceutical manufacturing. Since the first drug product (Spritam®) has been approved for commercialization by the Food and Drug Administration (FDA), there has been an enormous opportunity for printing custom drugs using 3DP. Many 3DP methods have been documented for pharmaceutical applications in the literature. However, selective laser sintering (SLS) printing remains the least studied for pharmaceutical applications. There are many advantages and challenges in adopting an SLS method to fabricate personalized medicines, such as accurate, cheaper, and simpler ways to configure dosing for certain patient groups. In this study, we systematically reviewed all available literature investigating the technique of personalized printlets using SLS printing, and further discussed the method used in its process. A systematic searching strategy was performed in Scopus, PubMed, and Google Scholar databases using predetermined search strings. Of the 122 articles, only eight articles completely met the inclusion criteria, and they were subsequently used for data synthesis. The results showed that the printing process, spectrophotometry analysis, thermal analysis, X-ray powder diffraction and characterization of the printlet were the vital parameters in the printing method, leading to potential pharmaceutical applications in personalized medicine.
Innovation Factory for Sharing Knowledge

The introduction of an innovative organization like Digital Borgo in a strongly conservative context, made mostly by SMEs and few big companies, often with no relationships to each other modify their interests in collaborating and exchanging knowledge. Overcoming all limits, hurdles and an unfavorable mindset, we managed to define a corporate accelerator model that can represent a virtuous example, helping corporates, entrepreneurs, chambers of commerce and universities to collaborate to foster innovation. We are confident that in the future we will be able to say that our model has created a more connected ecosystem among entrepreneurs and innovating corporates, making Abruzzo a region where small cities and low cost of life becomes an advantage for setting up a great ecosystem for innovation and smart growth.
Whole-genome sequence analysis through online web interfaces: a review

The recent development of whole-genome sequencing technologies paved the way for understanding the genomes of microorganisms. Every whole-genome sequencing (WGS) project requires a considerable cost and a massive effort to address the questions at hand. The final step of WGS is data analysis. The analysis of whole-genome sequence is dependent on highly sophisticated bioinformatics tools that the research personal have to buy. However, many laboratories and research institutions do not have the bioinformatics capabilities to analyze the genomic data and therefore, are unable to take maximum advantage of whole-genome sequencing. In this aspect, this study provides a guide for research personals on a set of bioinformatics tools available online that can be used to analyze whole-genome sequence data of bacterial genomes. The web interfaces described here have many advantages and, in most cases exempting the need for costly analysis tools and intensive computing resources.
Crop Residue Burning Emissions and the Impact on Ambient Particulate Matters over South Korea

In the study, crop residue burning (CRB) emissions were estimated based on field surveys and combustion experiments to assess the impact of the CRB on particulate matter over South Korea. The estimates of CRB emissions over South Korea are 9514, 8089, 4002, 2010, 172,407, 7675, 33, and 5053 Mg year−1 for PM10, PM2.5, OC, EC, CO, NOx, SO2, and NH3, respectively. Compared with another study, our estimates in the magnitudes of CRB emissions were not significantly different. When the CRB emissions are additionally considered in the simulation, the monthly mean differences in PM2.5 (i.e., △PM2.5) were marginal between 0.07 and 0.55 μg m−3 over South Korea. Those corresponded to 0.6–4.3% in relative differences. Additionally, the △PM10 was 0.07–0.60 μg m−3 over South Korea. In the spatial and temporal aspects, the increases in PM10 and PM2.5 were high in Gyeongbuk (GB) and Gyeongnam (GN) provinces in June, October, November, and December.
Association between Mineralocorticoid Receptor Antagonist and Mortality in SARS-CoV-2 Patients: A Systematic Review and Meta-Analysis

Since the onset of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, various potential targeted therapies for SARS-CoV-2 infection have been proposed. The protective effects of mineralocorticoid receptor antagonists (MRA) against tissue fibrosis, pulmonary and systemic vasoconstriction, and inflammation have been implicated in potentially attenuating the severity of SARS-CoV-2 infection by inhibiting the deleterious effects of aldosterone. Furthermore, spironolactone, a type of MRA, has been suggested to have a beneficial effect on SARS-CoV-2 outcomes through its dual action as an MRA and antiandrogen, resulting in reduced transmembrane protease receptor serine type 2 (TMPRSS2)-related viral entry to host cells. In this study, we sought to investigate the association between MRA antagonist therapy and mortality in SARS-CoV-2 patients via systematic review and meta-analysis. The systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. MEDLINE and EMBASE databases were searched for studies that reported the incidence of mortality in patients on MRA with SARS-CoV-2 infection. Pooled odds ratio (OR) and 95% confidence interval (CI) of the outcome were obtained using the random-effects model. Five studies with a total of 1,388,178 subjects (80,903 subjects receiving MRA therapy) met the inclusion criteria. We included studies with all types of MRA therapy including spironolactone and canrenone and found no association between MRA therapy and mortality in SARS-CoV-2 infection (OR = 0.387, 95% CI: 0.134–1.117, p = 0.079).
Photovoltaic power system : modelling, design and control

Photovoltaic Power System: Modelling, Design and Control is an essential reference with a practical approach to photovoltaic (PV) power system analysis and control. It systematically guides readers through PV system design, modelling, simulation, maximum power point tracking and control techniques making this invaluable resource to students and professionals progressing from different levels in PV power engineering.
An innovative framework for structural health monitoring of long-span bridges

Die Aufmerksamkeit auf strukturelle Uberwachung von Strukturen ist in dem letzten Jahrzehnte gewachsen. Klare Fortschritte wurden in den letzten Jahren erreicht. Ins besonders bezuglich Messsensorik, Speichertechniken der Daten und Algorithmen fur das Pre- und Postprozessing der Signalen. Einigen von diesen Fortschritten wurden an die strukturelle Uberwachung von Brucken angewendet. Diese Strukturen sind entscheidende Elemente fur die Wirtschaft eines Landes, und aus diesem Grund, sind Brucke interessante Uberwachungsziele. Strukturelle Uberwachung kann nicht nur als eine versprechende Methode zur Verbesserung der Kosten bezuglich den Wartungsarbeiten betrachtet werden, sondern auch als eine mathematische Herausforderung. Dadurch ist die Wichtigkeit von statistischen Auswertungen basierend auf multivariaten Methoden gewachsen. Diese Methoden erlauben unter variierenden Wetter– und Betriebsbedingungen (z.B. Temperatur, Feuchtigkeit und Strasenverkehr) eine kontinuierliche Aussage des Schadigungsgrades der Struktur. In Rahmen dieser Arbeit ist die strukturelle Uberwachung von Brucken untersucht. Unter die Annahme, dass die Eigenfrequenzen Schadigungsempfindlich sind, multivariate Analyse sind angewendet, um Aussagen der Schadigungszustand der Brucken zu treffen. Dafur sind lineare und nicht lineare Korrelationen zwischen die dynamischen und Wetter- bzw. Betriebsbedingungen betrachtet. Ein Verfahren, die auf die kontinuierliche Modale Uberwachung, Hauptkomponenteanalyse und die Novelty Methode basiert ist vorgeschlagen. Das Potenzial und Effektivitat der Schadigungserkennung ist mit Hilfe ein pseudo-experimentelles Verfahren getestet. Dabei ist ein analytisches Modell einer Hangebrucke mit einem beschadigten Tragseil benutzt, die sich unter kontinuierlichen Wetter- und Betriebsbedingungen befindet. In Anschluss, ist das Verfahren auf einer realen Brucke untersucht. Die Ergebnisse zeigen die Machbarkeit einer kontinuierlichen Uberwachung von Strukturen. Auserdem, fuhrt die Robustheit des Verfahrens zu der Entdeckung von realer Schadigung. Trotz den geringen Einfluss der Schadigung auf die Eigenfrequenzen, fuhrt das vorgeschlagene Verfahren zu einer zuverlassigen Identifizierung der strukturellen Schadigung. Auf Grund der Eigenschaften des Verfahrens, und wie es konzipiert wurde, kann es zukunftig bei einer anderen Struktur angewendet werden, die ein kontinuierliche Uberwachungssystem verfugt.
Pre-operative predictors of difficult laparoscopic cholecystectomy: a comparative study between two scoring systems

Background: Laparoscopic cholecystectomy is considered as the gold standard in treating symptomatic gall bladder disease. It has now become the most common operation performed by general surgeons. At times laparoscopy becomes difficult and may need conversion to open cholecystectomy. Many scoring systems are developed to predict the difficulty of laparoscopic cholecystectomy pre operatively. Our study aims to determine factors predicting difficult cholecystectomy and validate 2 scoring systems i.e., risk score for conversion from laparoscopic to open cholecystectomy (RSCLO) vs. new scoring system (NSS). Methods: Patients presenting to Kempegowda institute of medical sciences from January 2014 to August 2015 with symptoms of gall stone disease were screened for cholelithiasis.100 patients undergoing laparoscopic cholecystectomy were randomly selected. Every patient was given pre-operative score, after applying their symptoms to the scoring system and these scores were compared with the intraoperative findings and post-operative outcome. Thereby, calculating the sensitivity and specificity of the scoring systems.Results: On univariate and multivariate logistic regression-BMI>27.5 kg/m2 (p=0.010), Palpable gallbladder (p=0.022), previous hospitalization for acute cholecystitis (p=0.15), Sonology: wall thickness>4 mm (p=0.0015), presence of pericholecystic edema, were found statistically significant. RSCLO system was better in predicting easy cholecystectomy i.e., low risk for conversion, while NSS was better in predicting difficult, very difficult cholecystectomies {converted cases}, its sensitivity being 100%. Conclusions: New scoring system can predict difficult cases reliably. Scoring patients preoperatively can decrease intra-op difficulties. Patients can pre-op be informed about possible risk of conversion to open cholecystectomy.
Trends in the use of radiation for meningioma across the United States

Purpose Meningiomas are tumors originating from arachnoid cap cells on the surface of the brain or spinal cord. Treatment differs by grade but can consist of observation, surgery, radiation therapy or both. We utilized the National Cancer Database (NCDB) to compare trends in the use stereotactic radiosurgery (SRS) and external beam radiation therapy (EBRT) in the management of meningioma. Materials and Methods We queried the NCDB from 2004–2015 for meningioma patients (grade 1–3) treated with radiation therapy, either SRS or EBRT. Multivariable logistic regression was used to identify predictors of each treatment and to generate a propensity score. Propensity adjusted Kaplan-Meier survival curve analysis and multivariable Cox hazards ratios were used to identify predictors of survival. Results We identified 5,406 patients with meningioma meeting above criteria with 45%, 44%, and 11% having World Health Organization (WHO) grade 1, 2, and 3 disease, respectively. Median follow up was 43 months. Predictors for SRS were grade 1 disease, distance from treatment facility, and histology. The only predictor of EBRT was grade 3 disease. Treatment year, histology, race and female sex were associated with improved survival. Five- and 10-year survival rates were 89.2% versus 72.6% (p < 0.0001) and 80.3% versus 61.4% (p = 0.29) for SRS and EBRT respectively. After propensity matching 226 pairs were generated. For SRS, 5-year survival was not significantly improved at 88.2% compared with EBRT (p = 0.056). Conclusion In the present analysis, predictors of SRS utilization in management of meningioma include WHO grade 1 disease, distance from treatment facility and histology whereas conventional EBRT utilization was associated with grade 2 and 3 disease. Future studies need to be performed in order to optimize management of atypical and malignant meningioma.
XBarNet: Computationally Efficient Memristor Crossbar Model Using Convolutional Autoencoder

The design and verification of memristor crossbar circuits and systems demand computationally efficient models. The conventional device-level memristor model with a circuit simulator such as simulation program with integrated circuit emphasis (SPICE) to solve a memristor crossbar is time exhaustive. Hence, we propose a neural network-based memristor crossbar modeling method, XBarNet. By transforming memristor crossbar modeling to pixel-to-pixel regression, XBarNet avoids the iterative procedure in the conventional SPICE method, accelerating the runtime significantly. Meanwhile, XBarNet models the interconnect resistance and nonlinear <inline-formula> <tex-math notation="LaTeX">$I-V$ </tex-math></inline-formula> effect of memristor crossbars, which minimizes the simulation errors. We first propose a feature extraction method to bridge a memristor crossbar circuit and a neural network. Then, the network based on the convolutional autoencoder architecture is developed and the filter pruning technique is applied onto XBarNet to reduce the runtime computational cost. The experimental result shows our proposed XBarNet achieves over <inline-formula> <tex-math notation="LaTeX">$78\times $ </tex-math></inline-formula> runtime speed up and <inline-formula> <tex-math notation="LaTeX">$1.7\times $ </tex-math></inline-formula> memory reduction with only 0.28% relative error comparing to the SPICE simulator.
Do Firm Support Increase Investments? Evidence from the Aquaculture and Fish Processing Sectors in Sweden

Abstract The European Union provides firm support to the maritime sector to reach the policy objectives in the Common Fisheries Policy. This paper analyzes to what extent the investment support to aquaculture and fish processing firms in Sweden increases firm investment activity. By doing so, the paper also quantifies the amount of investments that would have been undertaken also without support (deadweight losses, DWL). The results show that the support increases investment in aquaculture with a factor of 0.65, thus with a DWL of 35%. The corresponding number for fish processing is a DWL of 77%.