Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating the Impact of Air Pollution on Healthcare-Seeking Behaviour by Applying a Difference-in-Differences Method to Syndromic Surveillance Data

Syndromic surveillance data were used to estimate the direct impact of air pollution on healthcare-seeking behaviour, between 1 April 2012 and 31 December 2017. A difference-in-differences approach was used to control for spatial and temporal variations that were not due to air pollution and a meta-analysis was conducted to combine estimates from different pollution periods. Significant increases were found in general practitioner (GP) out-of-hours consultations, including a 98% increase (2–386, 95% confidence interval) in acute bronchitis and a 16% (3–30) increase in National Health Service (NHS) 111 calls for eye problems. However, the numbers involved are small; for instance, roughly one extra acute bronchitis consultation in a local authority on a day when air quality is poor. These results provide additional information for healthcare planners on the impacts of localised poor air quality. However, further work is required to identify the separate impact of different pollutants.
A Series Stacked IGBT Switch Based on a Concentrated Clamp Mode Snubber for Pulsed Power Applications

Clamp mode snubbers are very well suited for the series structure of the insulated-gate bipolar transistors (IGBTs) in pulsed power applications. They properly meet the necessities expected from them such as the fast operating of the series IGBTs since they have no effect on the gate side. In addition, they can provide safe voltage condition for the IGBTs in short circuit faults, which are very probable in pulsed applications. The clamp mode snubber can perform its voltage balancing task whenever the power capacity of the snubber can support the injected powers due to the voltage unbalancing factors. This paper initially introduces the main factors injecting power to the snubbers. Then, it will be illustrated that the exact injected power to each predetermined snubber cannot be determined due to the uncertainties about the effect of the voltage unbalancing factors. Although it is impossible to determine the exact value of the power injected to each snubber, the total injected powers to the snubbers can be calculated. Therefore, as an effective remedy, this paper proposes a concentrated snubber. Using the proposal, all the injected powers are conducted to a centralized circuit and can be easily managed. In addition, analytical expressions are provided for proper dimensioning of the proposed concentrated snubber elements. Furthermore, the performance of the proposed concentrated snubber is evaluated using simulations and experimental prototyping.
Phase Compensation and Image Autofocusing for Randomized Stepped Frequency ISAR

Randomized stepped frequency (RSF) waveforms are attractive for inverse synthetic aperture radar (ISAR) imaging due to their synthetic-bandwidth system architecture and outstanding electronic counter-countermeasure characteristics. However, the extra complexities of the RSF radar’s frequency oscillator and the target echo model make phase compensation and image autofocusing more complicated. In this paper, we introduce a novel method for the phase compensation and image autofocusing of RSF-ISAR. The new method consists of the following two stages: the first is a parametric coarse compensation for target radial motion, and the second is a non-parametric fine compensation for motion residuals and radar system imperfection. Two target models, a naive target consisting of unit point scatterers and a Yak−42 target obtained from field experiments, are used for numerical analysis, which shows the effectiveness and superiority of the proposed method.
The Role of Technology-Based Education and Teacher Professional Development in English as a Foreign Language Classes

The swift development of technology has had a considerable effect on teaching, especially in foreign language classes, and the rising procedure of using creative technology to help teachers’ instruction and learning indicates the growing domination of technology in academic environments. In addition, teacher professional development significantly affects enhancing the teaching quality, especially the quality of educational activities within the class. Nevertheless, the shortage of workshops on professional development education made educators reliant on informal education where they worked and learned collectively with classmates in mini-groups to enhance their technology usage. The functions of technology-based instruction in the process of learning have not been taken into account in the professional development programs in the Chinese context so far, and consequently, this review takes a look at this issue. In a nutshell, this review of literature has suggestions for academics, theoreticians, and experts in search of inspecting the roles of technology in teacher professional development programs.
The Effect of Increasing Temperature on Welfare of Plantation Farmers

Agricultural productivity is a determining factor in achieving food security in Indonesia. Increase in agricultural productivity yields is strongly influenced by climate change. Extreme climate change has resulted in crop failure due to land drought and flooding. The existence of this incident provides an opportunity to decrease the welfare of farmers, especially plantation farmers in Indonesia. The purpose of this study was to determine the effect of temperature on the welfare of plantation farmers in Indonesia. The data used in this study was sourced from the 2018 National Socio-Economic Survey (SUSENAS) data, with a total of 66,754 households in Indonesia. The analytical method used is Ordinary Least Square (OLS). The results of this study indicate that an increase in temperature causes drought, and has an impact on decreasing agricultural productivity. The decrease in the production of agricultural products certainly reduces the income of farmers, which results in a decrease in the level of welfare of farmers. Government policies in terms of climate engineering are needed, as well as assistance programs for farmers to maintain the welfare of farmers.
Robust polymer-HfO2 thin film laminar composites for tactile sensing applications

A method for high resolution tactile sensing for robotic end-effectors used in variable environmental conditions is required for practical robotic applications, such as heavy industry, construction, military and space applications. In this work, a robust, flexible tactile sensor based on a capacitive sensing mechanism with high sensitivity and stability that can operate between −60 °C and 120 °C was developed. The active sensing thick film was composed of a 2:2 connective polymer-ceramic laminar composite. A stress-sensitive elastomer (Arathane 5753 A/B) was used as the primary compliant layer within the laminar architecture, and a HfO2 thin film was used as the dominating dielectric layer to improve the sensitivity of the sensor. The sensors were fabricated on a flexible polyimide film (Kapton) to conform to the end-effector geometry. The fabricated sensor showed good sensitivity and cycle stability (between 0 and 360 kPa). The capacitance change due to temperature variations were studied in detail. Three different capacitive sensor architectures were developed to study the influence of the HfO2 layer on the sensitivity of the sensor. Thermomechanical loading cycles were performed with in situ electrical acquisition to characterize the sensor. Chemical and structural characterization of the HfO2 layer deposited on a flexible substrate was implemented using conductive atomic force microscopy, Raman spectroscopy and x-ray photoelectron spectroscopy, and the optical properties were analyzed by the ultra-violet visible spectrophotometer.
Soil Amendments Enhanced Summer Squash Yield, Fruit Composition, Quality, and Soil Enzymes Activity

Summer squash, Cucurbita pepo was field grown under fourteen soil treatments: Sewage Sludge (SS); Horse Manure (HM); Chicken Manure (CM); vermicompost; inorganic fertilizer (Inorg); commercial organic fertilizer (Org); and no-mulch (NM) control treatment. Soil treatments were also mixed with biochar to make a total of 14 treatments to assess the impact on 1) squash fruit yield and quality, 2) fruit vitamin C, total phenols, and soluble sugars content, and 3) soil microbial activity expressed as urease and invertase secretions. Results revealed that SS treatments increased squash yield and fruit number by 114 and 116 %, respectively compared to NM control treatment. Fruits of plants grown in Inorg mixed with biochar (InorgBio) increased fruits vitamin C, total phenols, and soluble sugars by 73%, 52%, and 7%, respectively compared to Inorg with no-biochar treatment. However, biochar was not consistent in increasing soil urease and invertase activities. The use of animal manure is an affordable way to reduce dependence on mineral fertilizers. Results revealed that the addition of biochar to Org fertilizer increased squash fruit weight and numbers of fruits compared to Org not treated with biochar. No single amendment increased all fruit composition and soil urease and invertase activities.
Study the Relationship between the Nicotine and Lipid Profile with Some Hematology Parameters in Serum of Smoker and Non-Smoker Blood Samples

The effect of cigarette smoking on lipid profile and CBC (Complete Blood Count) of blood was investigated in this study. Spectrophotometric methods were used to estimate the amounts of nicotine, cholesterol, triglycerides, and HDL-cholesterol. The findings revealed that cigarette smokers and the duration of smoking had significantly higher levels of nicotine and cholesterol when compared to non-smokers. The data also revealed differences in the contents of hematological parameters between smokers’ and non-smokers’ blood samples, with high counts of WBC, MCHC, HGB, and PLT clearly visible in the smokers’ samples. However, there was no discernible effect on RBC, MCV, or MCH counts in the trial. Smoker samples had high PLT values (243.8 ± 84.26), while non-smoker samples had lower PLT values (229.3 ± 30.07 on average).
Elementary Education Candidates’ Integration of Technology in Science Units

This study used the framework of technological pedagogical and content knowledge (TPACK) to examine how elementary education preservice teachers integrated technology in science units that they designed after completing courses on science education and technology integration. The findings indicate that technologies included at the end of lessons were associated with higher order thinking, while those included at the beginning or middle of lessons were focused more on lower order thinking and presenting content. Further, frequently used technology-rich activities such as viewing videos and PowerPoint presentations were associated with lower order thinking, while activities such as completing an interactive whiteboard activity or having students make presentations or videos included more opportunities to develop higher order thinking. Implications from this research suggest that science educators and teacher educators should focus more on technologies that support higher -order thinking and support course work with special attention to technology in the context of designing engaging science instruction.
THE NEUKOELLN PHENOMENON: THE RECENT MOVE OF AN ART SCENE IN BERLIN.

One of the positive developments in post-Wall Berlin was the emergence of an alternative art scene, with Mitte and Prenzlauer Berg having a leading position in the early 1990s among artists as the new centres of Berlin´s creative industries. Soon, Mitte and Prenzlauer Berg became places where highly commercial creative companies arrived, and for that reason the art scene moved to Kreuzberg-Friedrichshain after no longer being able to afford the increasing rents. Nowadays we are witnessing the move of the art scene to Neukoelln, one of Berlin´s most problematic districts, with higher than average total migration, ethnic tensions, poor socio-demographic indicators and a high crime rate. The art scene in this district isn’t established as it was in Mitte. What is happening there right now is not about profit, it’s more about the idea that something is going on at the moment. Thus, it is too early for final conclusions. How does the arrival of an art scene influence Berlin´s most problematic district and what is its possible future impact? For now, we have the redevelopment of Berlin´s Neukoelln district which will ultimately lead toward gentrification. The result of such a change is rising rents and anger from the older more established residents.
Effect of real-time feedback during cardiopulmonary resuscitation training on quality of performances: A prospective cluster-randomized trial

Background: The evidence supporting delivery of quality cardiopulmonary resuscitation is growing and significant attention has been focused on improving bystander cardiopulmonary resuscitation education for laypeople. The aim of this randomized trial was to assess the effectiveness of instructor’s real-time objective feedback during cardiopulmonary resuscitation training compared to conventional feedback in terms of trainee’s cardiopulmonary resuscitation quality. Methods: We performed a cluster-randomized trial of community cardiopulmonary resuscitation training classes at Nowon District Health Community Center in Seoul. Cardiopulmonary resuscitation training classes were randomized into either intervention (instructor’s objective real-time feedback based on the QCPR Classroom device) or control (conventional, instructor’s judgment-based feedback) group. The primary outcome was total cardiopulmonary resuscitation score, which is an overall measure of chest compression quality. Secondary outcomes were individual cardiopulmonary resuscitation performance parameters, including compression rate, depth, and release. Generalized linear mixed models were used to analyze the outcome data, accounting for both random and fixed effects. Results: A total of 149 training sessions (2613 trainees) were randomized into 70 intervention (1262 trainees) and 79 control (1351 trainees) groups. Trainees in the QCPR feedback group significantly increased overall cardiopulmonary resuscitation score performance compared with those in the conventional feedback group (model-based mean Δ increment from baseline to session 5: 11.2 (95% confidence interval 9.2–13.2) and 8.0 (6.0–9.9), respectively; p = 0.02). Individual parameters of compression depth and release also showed higher improvement among trainees in QCPR group with positive trends (p < 0.08 for both). Conclusion: This randomized trial suggests beneficial effect of instructor’s real-time objective feedback on the quality of layperson’s cardiopulmonary resuscitation performance.
Impact of social determinants of health on improving the LACE index for 30-day unplanned readmission prediction

Abstract Objective Early and accurate prediction of patients at risk of readmission is key to reducing costs and improving outcomes. LACE is a widely used score to predict 30-day readmissions. We examine whether adding social determinants of health (SDOH) to LACE can improve its predictive performance. Methods This is a retrospective study that included all inpatient encounters in the state of Maryland in 2019. We constructed predictive models by fitting Logistic Regression (LR) on LACE and different sets of SDOH predictors. We used the area under the curve (AUC) to evaluate discrimination and SHapley Additive exPlanations values to assess feature importance. Results Our study population included 316 558 patients of whom 35 431 (11.19%) patients were readmitted after 30 days. Readmitted patients had more challenges with individual-level SDOH and were more likely to reside in communities with poor SDOH conditions. Adding a combination of individual and community-level SDOH improved LACE performance from AUC = 0.698 (95% CI [0.695–0.7]; ref) to AUC = 0.708 (95% CI [0.705–0.71]; P < .001). The increase in AUC was highest in black patients (+1.6), patients aged 65 years or older (+1.4), and male patients (+1.4). Discussion We demonstrated the value of SDOH in improving the LACE index. Further, the additional predictive value of SDOH on readmission risk varies by subpopulations. Vulnerable populations like black patients and the elderly are likely to benefit more from the inclusion of SDOH in readmission prediction. Conclusion These findings provide potential SDOH factors that health systems and policymakers can target to reduce overall readmissions.
Modeling and Control of Morphing Covers for the Adaptive Morphology of Humanoid Robots

This article takes a step to provide humanoid robots with adaptive morphology abilities. We present a systematic approach for enabling robotic covers to morph their shape, with an overall size fitting the anthropometric dimensions of a humanoid robot. More precisely, we present a cover concept consisting of two main components: a <italic>skeleton</italic>, which is a repetition of a basic element called <italic>node</italic>, and a soft <italic>membrane</italic>, which encloses the cover and deforms with its motion. This article focuses on the cover skeleton and addresses the challenging problems of node design, system modeling, motor positioning, and control design of the morphing system. The cover modeling focuses on kinematics, and a systematic approach for defining the system kinematic constraints is presented. Then, we apply genetic algorithms to find the motor locations so that the morphing cover is fully actuated. Finally, we present control algorithms that allow the cover to morph into a time-varying shape. The entire approach is validated by performing kinematic simulations with four different covers of square dimensions and having <inline-formula><tex-math notation="LaTeX">$3\times 3$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$4\times 8$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$8\times 8$</tex-math></inline-formula>, and <inline-formula><tex-math notation="LaTeX">$20\times 20$</tex-math></inline-formula> nodes, respectively. For each cover, we apply the genetic algorithms to choose the motor locations and perform simulations for tracking a desired shape. The simulation results show that the presented approach ensures the covers to track a desired shape with <italic>good</italic> tracking performances.
The Impact of Telemedicine on Parkinson’s Care during the COVID-19 Pandemic: An Italian Online Survey

Traditionally, medical care and research in Parkinson’s disease (PD) have been conducted through in-person visit. The recent Coronavirus Disease 2019 (COVID-19) pandemic has profoundly impacted the delivery of in-person clinical care. We conducted an online survey to investigate the impact of COVID-19 on access to telehealth care, interviewing both PD patients and neurologists. Survey responses were collected from 1 March to 31 May 2021 through an anonymous, self-reported questionnaire, on the ‘Qualtrics’ platform. In total, 197 patients and 42 neurologists completed the survey. In our sample, 37.56% of PD patients and 88.10% of neurologists reported having used alternatives to in-person visits, while 13.70% of PD patients and 40.48% of neurologists used telemedicine. Data showed that respondents were generally satisfied with the use of telemedicine during the COVID-19 pandemic. The relational dimension between patient and neurologist seems to be the factor that most positively affected the telemedicine experience, contributing greatly to a more patient-centred care. Current findings suggest the need to improve the access to telehealth services for patients with PD. The technology has the potential to improve the care of frail patients, especially when availability of face-to-face visits is limited.
Determining the Investor's Strategy During the COVID-19 Crisis Based on CVaR Risk Measure

The realized investment operations of each investor are based on the analysis in such a way that a certain certainty of the invested financial amount and a satisfactory return is ensured during the implementation. Therefore, when investing, the investor decides which products or securities to invest in and chooses when the investor should make the chosen investment. In this way, the investor is faced with the question of the possible return of his investment strategy based on the optimization model of portfolio selection based on the CVaR risk measure. The investor decides based on certain assumptions, including the assumption of the emergence of a crisis, e.g., the crisis caused by the virus. The paper presents the impact of the crisis on investor decision-making through the CVaR risk measure, which was realized on historical data of the components of the Dow Jones Industrial Average (DJIA) stock index in both crisis and pre-crisis periods.
Automatic Lane-Changing Trajectory Planning: From Self-Optimum to Local-Optimum

Existing lane-changing (LC) algorithms in general prioritize self-interest above the benefits of others. We argue that an autonomous vehicle should be socially responsible during lane change without causing excessive impact on its surroundings. Thus, in this paper, we propose an LC algorithm that could generate a trajectory to optimize the overall benefits of the subject vehicle and others in its vicinity. This is mainly achieved by introducing Longitudinal Control Model to characterize the driving behaviors of neighboring vehicles, and drivers’ needs such as comfort, efficiency, and safety are simultaneously satisfied. We combine macro and micro comparative analysis to evaluate the advantage of our approach against existing algorithms. Our findings reveal that the vehicle controlled by our algorithm is capable of safely performing the LC maneuver while causing the least amount of impact. This is reflected in the decrease in total cost of all vehicles and the increase in traffic speed and throughput in its vicinity. In addition, we use HighD dataset for further validation and demonstrate that our algorithm is practically sound. Application of this research can lead to improved autonomous driving technology.
Domestic Cat Sound Classification Using Learned Features from Deep Neural Nets

The domestic cat (Feliscatus) is one of the most attractive pets in the world, and it generates mysterious kinds of sound according to its mood and situation. In this paper, we deal with the automatic classification of cat sounds using machine learning. Machine learning approach for the classification requires class labeled data, so our work starts with building a small dataset named CatSound across 10 categories. Along with the original dataset, we increase the amount of data with various audio data augmentation methods to help our classification task. In this study, we use two types of learned features from deep neural networks; one from a pre-trained convolutional neural net (CNN) on music data by transfer learning and the other from unsupervised convolutional deep belief network that is (CDBN) solely trained on a collected set of cat sounds. In addition to conventional GAP, we propose an effective pooling method called FDAP to explore a number of meaningful features. In FDAP, the frequency dimension is roughly divided and then the average pooling is applied in each division. For the classification, we exploited five different machine learning algorithms and an ensemble of them. We compare the classification performances with respect following factors: the amount of data increased by augmentation, the learned features from pre-trained CNN or unsupervised CDBN, conventional GAP or FDAP, and the machine learning algorithms used for the classification. As expected, the proposed FDAP features with larger amount of data increased by augmentation combined with the ensemble approach have produced the best accuracy. Moreover, both learned features from pre-trained CNN and unsupervised CDBN produce good results in the experiment. Therefore, with the combination of all those positive factors, we obtained the best result of 91.13% in accuracy, 0.91 in f1-score, and 0.995 in area under the curve (AUC) score.