Miracle-dz/UniFAR-FTUs huggingface dataset:
Analyzing the code structures of multidimensional signals for a continuous information transmission channel

One of the directions to improve the efficiency of modern telecommunication systems is the transition to the use of multidimensional signals for continuous channels of information transmission. As a result of studies carried out in recent years, it has been established that it is possible to ensure high quality of information transmission in continuous channels by combining demodulation and decoding operations into a single procedure that involves the construction of a code construct for a multidimensional signal. This paper considers issues related to estimating the possibility to improve the efficiency of continuous information transmission channel by changing the signal distance of the code structure. It has been established that the code structures of such types as a hierarchical code construct of signals, a hierarchical code construct of signals with Euclidean metric, a reversible code construct of signals, a reversible code construct of signals with Euclidean metric have the potential, when used, to increase the speed of information transmission along a continuous channel. With a signal distance reduced by 10 percent or larger, it could increase by two times or faster. The estimation of the effect of reducing a signal distance on the efficiency of certain types of code structures was carried out. It has been established that the hierarchical reversible code construct, compared to the hierarchical code construct, provides a win of up to two or more times in the speed of information transmission with a halved signal distance. Implementing the modulation procedure has no fundamental difficulties, on the condition that for each code of the code construct the encoding procedure is known when using binary codes. The results reported here make it possible to build an acceptably complex demodulation procedure according to the specified types of code structures
COVID-19 pandemic and health related quality of life in primary school children in Switzerland: a repeated cross-sectional study.

BACKGROUND The COVID-19 pandemic and the resulting containment measures had and still have a profound impact on everyday life. Both the fear of infection and the imposed restrictions can have biopsychosocial consequences. The aim of the present study was to analyze whether there is a difference in the health-related quality of life (HRQoL) of primary school children in 2014/15 compared to in 2020, the first year of the COVID-19 pandemic. METHODS The present study included 1,712 children aged 5 to 11 years who either participated in the baseline assessment of the SOPHYA cohort study in 2014/15 or were newly recruited during follow-up of the cohort in 2020. In both surveys, the children invited for participation were identified based on registry data. HRQoL was assessed with the validated KINDL-R questionnaire, which scores HRQoL along six different dimensions. RESULTS The overall scores (82.4 [81.8; 83.0] vs. 79.6 [79,1; 80.2]), and in particular the emotional well-being scores (85.6 [84.6; 86.6] vs. 83.3 [82.4; 84.2]), were lower during the year of the pandemic (2020) compared to the survey year 2014/15. The highest decrease between 2014/15 and 2020 in the adjusted models was seen for the youngest age group (-3.9 points), followed by children from families with a high income (-3.2 points), girls (-3.1 points), Swiss citizens (-3.1 points) and children from the German-speaking part of Switzerland (-3.1 points). HRQoL was particularly low during periods with restrictions and at the height of the COVID-19 waves in 2020. CONCLUSION The SOPHYA-study showed that HRQoL, and especially emotional well-being, was lower in 5 to 11-year-old children in Switzerland during the first year of the pandemic compared to the results from the survey conducted in 2014/15. In the year of the pandemic, the scores were lowest at the height of the COVID-19 waves and their associated restrictions. As it cannot be distinguished whether fear of the disease itself or the restrictions caused this decrease in HRQoL, containment policies should keep COVID-19 infections as low as possible, but still enable children to profit from protective factors such as leisure activities, physical activity and social contact.
NTU VIRAL: A visual-inertial-ranging-lidar dataset, from an aerial vehicle viewpoint

In recent years, autonomous robots have become ubiquitous in research and daily life. Among many factors, public datasets play an important role in the progress of this field, as they waive the tall order of initial investment in hardware and manpower. However, for research on autonomous aerial systems, there appears to be a relative lack of public datasets on par with those used for autonomous driving and ground robots. Thus, to fill in this gap, we conduct a data collection exercise on an aerial platform equipped with an extensive and unique set of sensors: two 3D lidars, two hardware-synchronized global-shutter cameras, multiple Inertial Measurement Units (IMUs), and especially, multiple Ultra-wideband (UWB) ranging units. The comprehensive sensor suite resembles that of an autonomous driving car, but features distinct and challenging characteristics of aerial operations. We record multiple datasets in several challenging indoor and outdoor conditions. Calibration results and ground truth from a high-accuracy laser tracker are also included in each package. All resources can be accessed via our webpage https://ntu-aris.github. io/ntu_viral_dataset/.
THE SHAREHOLDER VALUE EFFECT OF SYSTEM OVERLOADS: AN ANALYSIS OF INVESTOR RESPONSES TO THE 2003 BLACKOUT IN THE US

This study investigates the stock price reaction of electric energy utility firms to the 2003 blackout in the Northeast of the USA and if the market was able to identify the responsible firm. Therefore, we employ event study methodology and select a sample of US-based electric energy utility firms. Although it took a commission almost 8 months to name the firm responsible for the blackout, investors punished FirstEnergy only two trading days after the blackout - and were right, as it later turned out. This study demonstrates this based on the analysis of abnormal stock returns and abnormal trading volumes. Our findings suggest that investors have extensive knowledge of electric energy utility firms’ responsibility as they were able to identify the culprit. This, in turn, demonstrates that electric power utility firms should ensure a high-quality grid infrastructure to avoid these negative outcomes.
A Novel COVID-19 Diagnosis Support System Using the Stacking Approach and Transfer Learning Technique on Chest X-Ray Images

COVID-19 is an infectious disease-causing flu-like respiratory problem with various symptoms such as cough or fever, which in severe cases can cause pneumonia. The aim of this paper is to develop a rapid and accurate medical diagnosis support system to detect COVID-19 in chest X-ray images using a stacking approach combining transfer learning techniques and KNN algorithm for selection of the best model. In deep learning, we have multiple approaches for building a classification system for analyzing radiographic images. In this work, we used the transfer learning technique. This approach makes it possible to store and use the knowledge acquired from a pretrained convolutional neural network to solve a new problem. To ensure the robustness of the proposed system for diagnosing patients with COVID-19 using X-ray images, we used a machine learning method called the stacking approach to combine the performances of the many transfer learning-based models. The generated model was trained on a dataset containing four classes, namely, COVID-19, tuberculosis, viral pneumonia, and normal cases. The dataset used was collected from a six-source dataset of X-ray images. To evaluate the performance of the proposed system, we used different common evaluation measures. Our proposed system achieves an extremely good accuracy of 99.23% exceeding many previous related studies.
The Global Economic Impact of Terrorism

Abstract In general, when analyzing the costs of armed conflict, the literature most often relates to civil wars or interstate conflicts. The moment of September 11, 2001 marked the beginning of a new concern in the economy, namely the economic cost of terrorism. Terrorism is a form of conflict in which acts of violence are directed at non-combatants or civilians who are usually unrelated to the political target of the group that committed it. This article analyzes existing data on the costs of terrorist acts that are committed by non-state parties or subnational groups. In this article, we will also look at the impact that terrorism has on the world economy (including both developed and underdeveloped states). We will find that although it has a significant impact on the global economy, the most devastating effects of violence are felt by underdeveloped economies whose poverty and inequality do not allow for a rapid and sustained response to terrorism.
Early Warning for the Construction Safety Risk of Bridge Projects Using a RS-SSA-LSSVM Model

Bridge engineering is an important component of the transportation system, and early warnings of construction safety risks are crucial for bridge engineering construction safety. To solve the challenges faced by early warnings risk and the low early warning accuracy in bridge construction safety, this study proposed a new early-warning model for bridge construction safety risk. The proposed model integrates a rough set (RS), the sparrow search algorithm (SSA), and the least squares support vector machine (LSSVM). In particular, the initial early warning factors of bridge construction safety risk from five factors (men, machines, methods, materials, and environment) were selected, and the RS was used to reduce the attributes of 20 initial early warning factors to obtain the optimized early warning factor set. This overcame the problem of multiple early warning factors and reduced the complexity of the subsequent prediction model. Then, the LSSVM with the strongest nonlinear modelling ability was selected to build the bridge construction early-warning model and adopted the SSA to optimize the LSSVM parameter combination, improving the early warning accuracy. The Longlingshan Project in Wuhan and the Shihe Bridge Project in Xinyang, China, were then selected as case studies for empirical research. Results demonstrated a significant improvement in the performance of the early-warning model following the removal of redundancy or interference factors via the RS. Compared with the standard LSSVM, Back Propagation Neural Network and other traditional early-warning models, the proposed model exhibited higher computational efficiency and a better early warning performance. The research presented in this article has important theoretical and practical significance for the improvement of the early warning management of bridge construction safety risks.
Moral Education at Primary Level in Selected Private Schools of Karachi: Role of Teachers and Parents

Pakistani society is facing numerous problems such as intolerance, violence, lying, dishonesty and sexual harassment to mention just a few. Parents and schools have a major role to play in the moral development of children. This mixed methods study examined teachers’ involvement in developing moral values in children from three private sector schools in Karachi, Pakistan. Document analysis of primary schools’ curriculum, in-depth interviews and classroom observations of nine teachers were conducted to understand how moral values are imparted through formal education. Additionally, 240 parents participated in a quantitative survey to investigate parental involvement in the moral development of children. Findings revealed inadequate focus of the schools’ curricula towards moral education, teachers’ limited perceptions and their subsequent lack of contribution to moral development of students. The quantitative data from parents showed satisfactory involvement of parents in moral growth of their children, measuring above 60% for every variable. Data also revealed that parents focus more on instructions rather than discussions about the moral values with their children. Findings highlight the need for coordinated efforts towards moral development of children involving parents, teachers and schools.
An evaluation of onasemnogene abeparvovec for spinal muscular atrophy (SMN1)

ABSTRACT Introduction Onasemnogene abeparvovec is the first systemic gene replacement therapy approved by the FDA for any inherited condition and is the second FDA-approved genetic therapy for 5q spinal muscular atrophy. Areas covered We discuss the design and preclinical development of onasemnogene abeparvovec, along with clinical trial and real-world data focusing on efficacy and safety. Expert Opinion Although onasemnogene abeparvovec is strikingly effective for the treatment of 5q SMA, it is only approved for use under the age of 2 years and there are also two other FDA-approved molecular-based treatments. Many questions remain in terms of treatment selection, possibility of dose optimization, and combinational therapies.
The Curvilinear Relation between Work Predictability and Creativity

ABSTRACT In this study, we investigate how the level of work control predictability affects employee creativity. Specifically, we examine whether supervisor and coworker support moderate the predictability-creativity relationship. We use survey data from 128 employee–supervisor dyads from a governmental organization in Belgium. Multilevel analyses demonstrated a significant inverted U-curve relationship between predictability and leader-rated creativity, indicating that too little or too much work control predictability contributes less to employee creativity compared to moderate levels of work control predictability. Moreover, supervisor and coworker support moderate this relationship in such a way that for employees who receive low support the inverted U-curve relationship is significantly stronger compared to employees that receive high support. This is the first study that focuses on work control predictability in relation to creative performance.
Revisiting the Cost-Effectiveness of HPV Co-Testing Versus Primary HPV Testing for Cervical Cancer Screening

Objectives: Consensus U.S. cervical cancer screening guidelines recommend women aged 30–65 years should be screened: (1) every 5 years with high-risk HPV testing alone; or (2) every 5 years with Pap and highrisk HPV co-testing; or (3) every 3 years with Pap alone. However, nearly 1-in-5 cancers (18.6%) are missed by HPV testing alone and 12.2% of cancers are missed by Pap testing alone. Hence, co-testing is the preferred screening method, but the cost implications are not fully known. For deeper understanding, we performed updated clinical-economic comparisons of cervical cancer screening with co-testing versus primary HPV from a U.S. perspective. Methods: A health state transition (Markov) model with one-year cycling was previously developed using epidemiologic, clinical, and economic data from healthcare databases and published literature. After updating the model, it was used to perform simulations of women receiving either 3-year or 5-year interval cervical cancer screening with either co-testing or HPV primary, starting from age 30 years and running up through age 64 years. Outcomes included total and incremental differences in costs, number of referral colposcopies (true and false positive), invasive cervical cancer (ICC) cases, ICC deaths, and quality-adjusted life years (QALYs) for cost-effectiveness calculations. J Women’s Health Dev 2021; 4 (4): 151-162 DOI: 10.26502/fjwhd.2644-28840069 Journal of Women’s Health and Development Volume 4 No 4 – December 2021 152 Results: In the 3-year and 5-year screening interval scenarios, per-patient cumulative costs of screening and management over 35 years with co-testing versus HPV primary led to cost savings of $15 and $217, respectively. These cost saving resulted from fewer referral colposcopies, fewer ICC cases, and fewer ICC deaths. Co-testing also conferred more QALYs. Costeffectiveness calculations showed co-testing as the economically dominant screening strategy by simultaneously confers greater effectiveness (i.e., more QALYs) at lower cost compared with HPV primary. National average annual cost savings of $154 to $655 million could be realized if every woman in the U.S. was routinely screened with co-testing instead of HPV primary. Conclusions: Model results demonstrate that cervical cancer screening with co-testing provides valuable clinical and economic outcomes when compared to primary HPV testing alone. These findings are relevant to healthcare payers and women’s health policy advocates seeking cost-effective cervical cancer screening options.
Pricing of Liquidity Risk: New Evidence from the Latin American Emerging Stock Markets

ABSTRACT This paper aims to analyze whether the liquidity risk is priced in Latin-American emerging stock markets. For that, we test the performance of the liquidity augmented version of Fama-French three and five factor models and Carhart four factor model since there is not yet a consensus about their suitability for these markets. Two versions of a liquidity factor were constructed based on two proxies that consider different dimensions of liquidity and are more appropriate for low frequency data. The GRS statistics showed Latin American average returns are better explained by the liquidity augmented Fama-French five-factor model. When estimated by GMM-IVd, due to the possible endogenous problems caused by liquidity, the results of the models did not significantly change. The results were robust to the January Effect. Furthermore, when the sample period was divided into two subperiods, both were statistically significant, although the explanatory power was greater in the second subperiod.
An analytical model for multihop LoRaWAN networks

LoRaWAN is one of the most popular LPWAN technology due to the facility to implement applications that require a low cost, low energy consumption, low data rate, and large coverage area. A LoRaWAN network is composed of end-devices that transmit data to gateways, forming a single-hop star topology. Multihop networks are receiving the attention of the LoRaWAN community since it allows to extend the coverage area and improve the energy efficiency,thus prolonging the network lifetime. In this paper, we propose an analytical model for multihop LoRaWAN networks.We investigate the energy consumption, throughput, delay, and packet delivery ratio of single-hop and multihop relaynetworks. The results showed that the network performance could be improved with relay nodes, giving insights to newmultihop proposals for LoRaWAN.
Modeling Cold Start in a Polymer-Electrolyte Fuel Cell

Polymer-electrolyte fuel cells (PEFCs) are electrochemical devices that create electricity by consuming hydrogen and oxygen, forming water and heat as byproducts. PEFCs have been proposed for use in applications that may require start-up in environments with temperatures below 0 degrees C. Doing so requires that the cell heat up, and when its own waste heat is used to do so, the process is referred to here as ``cold start. '' However, at low temperatures the cell's product water freezes, and if the temperature does not rise fast enough, the accumulation of ice in the cathode catalyst layer (cCL) can reduce cell performance significantly, extending the time required to heat up. In addition to reducing performance during cold start, under some conditions the accumulation of ice can lead to irreversible structural degradation of the cCL.The objective of this dissertation is to construct and verify a cold-start model for a single PEFC, use it to improve understanding of cold-start behavior, and to demonstrate how this understanding can lead to better start protocols and material properties. The macrohomogeneous model that has been developed to meet the objective is two-dimensional, transient, and nonisothermal. A key differentiating feature is the inclusion of water in all four of the possible phases: ice, liquid, gas, and membrane. In order to predict water content in the ice, liquid, and gas phases that are present in the porous media, the thermodynamics of phase equilibrium are revisited, and a method for relating phase pressures to water content in each of these phases is developed. Verification of the model is performed by comparing model predictions for cell behavior during parametric studies to measured values taken from various sources. In most cases, good agreement is observed between the model and the experiments. Results from the simulations are used to explain the trends that are observed. The verified cold-start model is deployed to determine a cold-start protocol and cCL properties that enable better performance. Criteria include not only minimizing start time but also exposure to high cCL ice pressures and cold-start energy while at the same time maximizing power available from the cell during the cold-start process.
The effect of air-velocity in dry kilns upon the drying rate and final moisture content

By experimenting on a single species with given dimensions the variables are reduced to the remaining three factors. The effect of varying the dry-bulb temperatures and wet-bulb depressions and keeping the air-circulation rates constant has been shown (1,2,3,4,5,8,9,11) The effect of air-velocity upon drying rate however, has been shown in only a few publications, (5,6,9,10) all but one of which was exploratory.
An Investigation into the Channel of Public Expenditure to Boost Industrial Productivity in Pakistan

It is a fact that public expenditure has a strong association with industrial productivity. The industrial sector recorded slow growth of 5.43%, which adds 20.90% to the GDP of Pakistan (2017-2018). This study aims to find the effects of public expenditure on Total Factor Productivity (TFP) in the industrial sector of the country. The study constructed two different models. In the first model, the study used time series data from 1975 to 2018, and the growth of adjusted TFP was calculated by the growth accounting method. In the second model, the study collected data from 1977 to 2018 and checked the impact of government expenditure on the TFP growth in the industry. The unit root tests, Ordinary Least Square (OLS), and Vector Error Correction Model (VECM) were employed. The findings of the study revealed that public expenditures on education were significant and positively related to TFP growth in industries. Public expenditure on health, agriculture, and inflation had a significant and positive association with TFP growth in the industries. Foreign direct investment had a negative but significant impact on TFP growth. The results of the present study suggest that industrial productivity can be increased by increasing the expenditure on education and health.