Miracle-dz/UniFAR-FTUs huggingface dataset:
Arrhythmia Classification of Reduced-Lead Electrocardiograms by Scattering-Recurrent Networks

We describe an automatic classifier of arrythmias based on 12-lead and reduced-lead electrocardiograms. Our classifier composes the scattering transform (ST) and a long short-term memory (LSTM) network. It is trained on PhysioNet/Computing in Cardiology Challenge 2021 data. The ST captures short-term temporal ECG modulations while reducing its sampling rate to a few samples per typical heart beat. We pass the output of the ST to a depthwise-separable convolution layer which combines lead responses separately for each ST coefficient and then combines resulting values across ST coefficients. At a deeper level, 2 LSTM layers integrate local variations of the input over long time scales. We train in an end-to-end fashion as a multilabel classification problem with a normal and 25 arrhythmia classes. We used canonical correlation analysis (CCA) for transfer learning from 12-lead ST representations to reduced-lead ones. For 12-, 6-, 4-, 3- and 2-leads, team “BitScattered” Challenge metrics on the hidden validation set were 0.46, 0.44, 0.45, 0.46 and 0.43; and on the hidden test set were 0.10, 0.11, 0.10, 0.10 and 0.10, respectively, ranking 34th on the hidden test set.
Practical Evaluation on Serious Games in Education *

— The arrival of the new learning methodologies is in response to the reality: new generations should learn in a different way. The so-called "Millennials" are looking for another kind of stimulus. Discussions for modernizing the curriculum include various solutions to retain students' attention and, in order to ensure that teachers learn how to act with a critical attitude, they will be confident and with the developed creative skills that they will need for success in the professional world in the future. The game based learning is more than providing educational games to students, it is about changing students' access to learning and their learning approach: the goal is to enjoy the learning process itself. This paper presents a methodological tool based on an evaluation framework for integration of digital games into education (MEDGE), expanded by adding additional information from the students, MEDGE+. The evaluation framework is used on three different approaches to the educational content: robot, micro: bit and playing quiz Kahoot. MEDGE+ presents better tool for the teachers in order to follow the student’s interest when choosing appropriate educational games in the teaching process.
A Novel Multi-Scale Convolutional Neural Network for Arrhythmia Classification on Reduced-Lead ECGs

The PhysioNet/Computing in Cardiology Challenge 2021 focused on exploring the utility of reduced-lead ECGs for arrhythmia classification. Our team, AIRCAS_MEL1, proposed a novel multi-scale convolutional neural network that can classify 30 scored arrhythmias from 12-lead, 6-lead, 4-lead, 3-lead, and 2-lead ECGs. The proposed network was achieved by multiple branch networks to effectively extract the pathological information from the “detail” scale to the “approximation” scale via a series of 2-D convolution kernels (filters). The backbone of each branch network was a carefully designed 2-D convolutional neural network (CNN) with residual connection and attention mechanism, and it can adapt to multi-lead ECGs as input. The first 10 seconds of records from corresponding leads were extracted and preprocessed as inputs for end-to-end training, and the prediction probabilities of 30 categories were outputs. Finally, the proposed algorithms were evaluated on the hidden test set, and our classifiers received scores of 0.38, 0.33, 0.37, 0.43, and 0.38 (ranked 21th, 23th, 20th, 16th, and 20th out of 39 teams) for the 12-lead, 6-lead, 4-lead, 3-lead, and 2-lead versions of the hidden test set with the Challenge evaluation metric.
Computer Integrated Surgery II Applications in Hand-Focused Rehabilitation Therapy : A Critical Review of Selected Literature

The purpose of this literature review is to determine the efficacy of various hand-focused applications to stroke rehabilitation. The literature was chosen based on key areas of stroke rehabilitation: assessment metric theory, sensor and control design, engagement, and mobility. By determining how well the applications within the literature achieve their research goals, my project should have better direction in certain future developments it may have.
The chlorine dioxide controversy: A deadly poison or a cure for COVID-19?

Chlorine dioxide has been condemned as a dangerous poison and has been touted as a cure for COVID-19. This narrative review examines the controversy surrounding the use of aqueous chlorine dioxide by investigating evidence-based research articles, government documents, press reports, and the results of the first clinical trial utilizing chlorine dioxide as a treatment for COVID-19. Chlorine dioxide was found to be employed by numerous industries for antimicrobial and other uses. Aqueous chlorine dioxide was found to be safe when ingested in low doses, but when ingested in high doses, it can cause adverse hematologic and renal effects. Additionally, chlorine dioxide was found to be a strong and rapidly acting virucide with activity against a wide range of viruses. Results of the first clinical trial utilizing chlorine dioxide to treat COVID-19 are reviewed and this molecule is found to be a safe and effective treatment. A dispassionate review of the evidence-based research literature finds preliminary evidence supporting the opinion that aqueous chlorine dioxide may be a safe and effective treatment of COVID-19, and likely for other viral illnesses as well. Further studies are needed to confirm these findings and to explore potential uses of chlorine dioxide. Key words: SARS-CoV-2, virucide, biocide, antimicrobial, oxidant, disinfectant, bleach, food additive, sterilant.
Extinction Correction and the [Fe ii] 1.26 μm/1.64 μm Intensity Ratio

From imaging observations of [Fe ii] emission in Herbig–Haro objects, I find a lower limit to the zero-extinction [Fe ii] 1.26 μm/1.64 μm intensity ratio of 2.6 and argue that this lower limit must be close to the true zero-extinction intensity ratio. My extinction determinations using this zero-extinction value yields results on well-studied HH objects consistent with results from other ionic-line spectra, whereas using nearly all theoretical values of [Fe ii] 1.26 μm/1.64 μm in the literature gives rise to unphysical results.
The method of MEMS gyroscope random error compensation based on ARMA

In order to suppress the random error of micro electro-mechanical system (MEMS) gyroscope, the method based on optimized auto regressive moving average (ARMA) model is proposed to solve problems such as poor extraction of trend items during signal preprocessing and strong subjectivity in ARMA ordering. Firstly, the trend item of MEMS gyroscope data is extracted by empirical mode decomposition (EMD) to obtain a stable and zero-mean time series. In order to reduce the subjective influence of the traditional ARMA ordering method, genetic algorithm theory is used to optimize the ordering process. Choose the order corresponding to the highest fitness function as the modeling order and use the recursive augmented least squares method to estimate the model parameters. So far, a complete mathematical model can be established. Finally, adaptive Kalman filter (AKF) is used to compensate the random error of the MEMS gyroscope. Compensate the same MEMS gyroscope signal before and after optimization. Experiments show that the accuracy of EMD de-trending and optimized ARMA is better than the traditional method. After AKF compensation, under the premise that the mean does not change, the standard deviation is reduced by 27% in this paper. The coefficients of the main random error terms are significantly reduced, which further improves the accuracy of the MEMS gyroscope.
The quality factor of quartz DETF for resonant sensors: simulation, analysis and verification

Due to the excellent material properties of crystal quartz and its simple and effective structure, the quartz double ended tuning fork (DETF) is widely used as a resonance sensing element in resonator sensors, where its quality factor has an important effect on the overall accuracy and stability of such sensors. To optimise the quality factor of quartz DETF, the influence of structural dimensions on structural and air damping is analysed, and the theoretical model used to calculate the quality factor is summarised. Further, under the premise of fabricating resonators with sufficient force–frequency sensitivity, the quality factors of quartz DETFs of different structural dimensions are simulated through finite element simulation. The theoretical model and simulation calculation of the quality factor of quartz DETFs mutually verify its effectiveness. Moreover, an experimental platform was built, and three quartz DETFs with different dimensions were fabricated to test their quality factor. The quality factors of the three DETFs in air and vacuum are 3467.3, 1925.8, 4442.4 and 32 997.6, 11 559.1, 24 795.7, respectively, which means that the environmental factors and their structural dimensions have a great influence on quality factor. With the simulation method and summarised theoretical model in this paper, the quality factor was studied with comprehensive structural damping (thermal damping loss and support loss) and air damping (resistance damping, slide film damping, and squeeze film damping). The influence of the structure size on the quality factor was analysed in detail, including the length of the decoupling region, the distance between the tines, and the length and width of the tines, and the main influencing factors were obtained, providing a basic and comprehensive reference for designing quartz DETF.
Sparse Hardy function model of regional velocity field from GNSS data

Classical Hardy function interpolation method is often necessary in establishment of regional velocity field. In this work, a regularization method, namely the L1-norm regularization, also called the least absolute shrinkage selection operator (Lasso), is employed to improve the traditional method. With the new method, a sparse model can be obtained with many zero elements in the parameter vector. Compared to L2-norm regularization, which is also called the Tikhonov regularization, the L1-norm regularization will select the best model automatically by making the coefficient of the unnecessary kernels zero, through solving a convex optimization problem. In this paper, the velocity field dataset derived from global navigation satellite system data is used to establish models in different directions. By comparing the interpolation accuracy of velocity at the same unknown points of Hardy function improved by Lasso and Tikhonov regularizations respectively, the feasibility of the former is verified. The results show that L1-norm regularization method has a slightly worse interpolation accuracy than Tikhonov regularization method in North and Up directions, but in East direction, the interpolation effect is much better and all directions can get great sparse performance. More specifically, the prediction accuracy of the proposed method in the East direction is improved by 17.3%, but in North and Up directions is decreased by 5.4% and 6.3% respectively in comparison with that of Tikhonov regularization method, though the sparse rates of them are over 60%. In addition, besides selecting the root mean square error as the evaluation standard for model selection, we can also select the sparse rate as the evaluation criteria to make the model much sparser if necessary. A sparse model would be beneficial in terms of better interpretability and improved variable assigning efficiency. To summarize, L1-norm regularization can be viewed as a potential alternative in velocity field modelling.
Dual-Functionalized Magnetic Metal–Organic Framework for Highly Specific Enrichment of Phosphopeptides

The highly specific enrichment of phosphoproteins and phosphopeptides from intricate biological systems is the precondition of in-depth phosphoproteome research. Herein, a novel dual-functionalized magnetic zirconium-based metal–organic framework (MOF) denoted as DFMMOF, with the purpose of combining the affinity of immobilized metal ion affinity chromatography (IMAC) and metal oxide affinity chromatography (MOAC) has been successfully synthesized. The inherent Zr–O cluster of DFMMOF particles acted as MOAC and the immobilized titanium(IV) ions served for IMAC. The obtained DFMMOF exhibited rapid magnetic separation (within 5 s), large surface area (237.9 m2 g–1), high binding capacity (100 mg g–1), and good postenrichment recovery (84.8%). Thanks to the strong affinity, low detection sensitivity (5 fmol) and high selectivity (β-casein/BSA with a molar ratio of 1:1000) for phosphopeptide enrichment were obtained using DFMMOF as absorbent. Moreover, the effective identification of phosphopeptides from real.
The effect of voltage controlled orientation order of liquid crystals in non-acrylic polymer dispersed liquid crystals films

ABSTRACT The nematic liquid crystals (LCs) are randomly dispersed material with random orientation order in polymer dispersed liquid crystal (PDLC) films. The LCs change their orientation from random to vertical as electric field is applied. This transformation of orientation order of nematic liquid crystals in the PDLC films is controlled by many factors operating simultaneously. For instance, some factors like the internal forces of attractions among the neighboring LC molecules, anchoring with polymeric matrix, ITO glass boundaries, and chemical structures of the materials are less studied. The learning of extent of vertical orientation of liquid crystal droplets in an electric field is essential to attain optimum electro optical properties of PDLCs. In this finding, bipolar and radial LCs droplets with random orientation have been observed in non-acrylic polymeric media. It is learned that with small increase of contents of external material, the extent of vertical orientation has been varied intensely. The extent of vertical orientation of LCs molecules increases as the contents of external non-acrylic polymeric material decreased. For this study, the orientations of LCs with respect to material type/contents, external applied force, and restoration of electric filed as hysteresis have been studied in details. GRAPHICAL ABSTRACT
Qatar genome: Insights on genomics from the Middle East

Despite recent biomedical breakthroughs and large genomic studies growing momentum, the Middle Eastern population, home to over 400 million people, is underrepresented in the human genome variation databases. Here we describe insights from Phase 1 of the Qatar Genome Program with whole genome sequenced 6047 individuals from Qatar. We identified more than 88 million variants of which 24 million are novel and 23 million are singletons. Consistent with the high consanguinity and founder effects in the region, we found that several rare deleterious variants were more common in the Qatari population while others seem to provide protection against diseases and have shaped the genetic architecture of adaptive phenotypes. These results highlight the value of our data as a resource to advance genetic studies in the Arab and neighboring Middle Eastern populations and will significantly boost the current efforts to improve our understanding of global patterns of human variations, human history, and genetic contributions to health and diseases in diverse populations.
Mind the gap: Mapping variation between national and local clinical practice guidelines for acute paediatric asthma from the United Kingdom and the Netherlands

Background: Clinical practice guidelines (CPGs) aim to standardize clinical care. Increasingly, hospitals rely on locally produced guidelines alongside national guidance. This study examines variation between national and local CPGs, using the example of acute paediatric asthma guidance from the United Kingdom and the Netherlands. Methods: Fifteen British and Dutch local CPGs were collected with the matching national guidance for the management of acute asthma in children under 18 years old. The drug sequences, routes and methods of administration recommended for patients with severe asthma and the tone of recommendation across both types of CPGs were schematically represented. Deviations from national guidance were measured. Variation in recommended doses of intravenous salbutamol was examined. Results: British and Dutch national CPGs differed in the recommended drug choices, sequences, routes and methods of administration for severe asthma. Dutch national guidance was more rigidly defined. Local British CPGs diverged from national guidance for 23% of their recommended interventions compared to 8% for Dutch local CPGs. Five British local guidelines and two Dutch local guidelines differed from national guidance for multiple treatment steps. Variation in second-line recommendations was greater than for first-line recommendations across local CPGs from both countries. Recommended starting doses for salbutamol infusions varied by more than tenfold. Conclusions: Local CPGs for the management of severe acute paediatric asthma featured substantial variation and frequently diverged from national guidance. Although limited to one condition, this study suggests that unmeasured variation across local CPGs may contribute to variation of care more broadly, with possible effects on healthcare quality.
Pressure swing adsorption separation of H2S/CO2/CH4 gas mixtures with molecular sieves 4A, 5A, and 13X

ABSTRACT Pressure swing adsorption experiments were carried out for the separation of equimolar mixtures of carbon dioxide and methane containing small amounts of hydrogen sulfide, utilizing 4A, 5A, and 13X molecular sieves. High-purity methane of zero or nearly zero hydrogen sulfide concentration was produced in the adsorption stage with 13X and 5A sieves, at high product recovery rates; high-purity carbon dioxide was obtained with the same sieves in the desorption stage. Zeolite 4A was found capable of raising considerably the hydrogen sulfide concentration in the accumulated desorption product (vs. the adsorption feed) at high recovery rates too. Adsorption selectivity values derived from the experimental results for all three gas pairs were in line with some theoretical predictions and experimental data of the literature.
Beware of Side Effects? Spillover Evidence from a Hot Water Intervention

Behavioral interventions may have unintended side effects. At worst, negative side effects may offset the intended effect. We study the effects of a hot water saving intervention on the consumption of cold water and room heating in a randomized controlled experiment in 782 buildings in Switzerland. The intervention reduces hot water consumption by 6.02 percent. Beyond the effect on the target behavior, we find a 5.44 percent decrease in energy consumption for room heating and a 2.57 percent decrease in cold water consumption. These positive spillover effects have substantial ramifications for households' utility bills, local pollution, and carbon emissions.
Measuring information in analyst reports: A machine learning approach

How to quantify the informational content of analyst reports? In this short methodological paper, we propose a measure of information contribution (IC), defined in the spirit of Shapley values. We use natural language processing to identify topics for over 90,000 analyst reports for S&P 500 stocks between January 2018 to May 2020. Next, we build the IC measure as the average cosine distance between the topic distribution for a particular report and any subset of competitor reports. A first preliminary finding is that the informational content of reports in "crowded stocks" is 41% lower than for reports in low-coverage stocks. Second, team-authored reports are 36% more informative than individual reports and women-authored reports are 12% more informative than men-authored reports.
Variability in Ferroalloy Furnace Tapping – Insights from Modelling

During tapping of pyrometallurgical smelters, molten products from the furnace operation are periodically removed from the vessel. Variations in the quantities of alloy and slag obtained from each tap are undesirable and can cause disruption to upstream and downstream operations, resulting in economic losses and safety risks to plant personnel. In the present work an integrated reduced-order model of a ferroalloy furnace tapping system was used to assess the sensitivity of the process to various operating parameters, and describe the statistical impact of random changes in the system over a large number of tapping cycles. The effect of implementing simple control measures to determine the best point to stop a tap is also presented.
Centralized Procurement and Delivery Times: Evidence from a Natural Experiment in Italy

We study how delivery times and prices for hospital medical devices respond to the introduction of centralized procurement. Our identification strategy leverages a legislative change in Italy that mandated centralized purchases for a sub-set of devices. The statutory centralization generated a reduction in prices and an increase in delivery times for centralized purchases relative to non-centralized purchases. We use data on quantities and on suppliers to discuss the mechanisms potentially underlying our findings.
Temporal Reframing Elicitations Can Improve the Emergency Savings Intentions of Gig Workers

Gig Economy workers often face do-it-yourself financial savings, more granular earnings structures (versus being salaried employees), and proportionally greater financial uncertainty whether psychologically perceived or real (e.g., income uncertainty). This paper extends prior work on temporal reframing (e.g., which has used specific amounts, such as saving a set amount per day) to explore in a lab setting with UK-based participants whether eliciting emergency savings decisions in temporal frames may make a difference even without specific amounts (e.g., how much would you like to save per day in pounds) and relative to completely unstructured savings decisions (e.g., how much would you like to save). Given the emergency savings context, we further examine exogenously varying levels of income risk on intentions to participate in recurring savings into an emergency saving fund. The investigation provides evidence that eliciting savings using more granular temporal frames (e.g., how much would you save per day versus how much would you save per month) increases savings, but likely through different psychological mechanisms as compared to when savings choices are offered with specific amounts. Whereas prior literature has shown mixed evidence for the independent worker segment and precautionary savings, this investigation supports the perspective that under moderate income variability, independent workers will also increase their intentions for precautionary savings, although under high income variability these increases may start to reverse (e.g., inverted U-shaped outcome response to increasing income variability) after controlling for small stakes risk and loss aversion and other demographics.
Partisan Conflict and Corporate Credit Spreads

I document a positive relationship between partisan conﬂict and corporate credit spreads. A one standard deviation increase in partisan conﬂict is associated with a 1.97 basis point increase in the next one-month corporate credit spreads after controlling for bond-issue information, ﬁrm characteristics, macroeconomic variables, uncertainty measures, and sentiment measures. The result holds when using instrumental variable to resolve endogeneity concerns. I further ﬁnd that partisan conﬂict has a greater impact on corporate credit spreads for ﬁrms with higher exposure to government policies, including government spending policy, tax policy, trade policy and regulation policy. Firms that are actively involved in political activities are also more sensitive to changes in political polarization. Intensiﬁed partisan conﬂict affects excess bond premium and inﬂuences credit spreads primarily via discount rates.