Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of HMI on driver’s distraction on a freeway under heavy foggy condition based on visual characteristics

Abstract Connected vehicle technology relying on Human Machine Interface (HMI) achieve a dominant position in the overall safety improvement. However, the impact of HMI on the driver’s visual attention cannot be ignored, especially on the accident-prone foggy freeway. The objective of this paper is to evaluate the level of distraction caused by HMI in data analysis of drivers’ visual characteristics and to establish a generic evaluation methodology. A connected vehicle test platform has been established based on the driving simulator, in which visibility was set to the level of heavy fog and the technical condition was set in two conditions (with or without HMI). Measurement of driving behavior parameters include frequency of fixations and saccades and the proportion of fixation. The researchers compared and analyzed the driver’s visual characteristics and the degree of distraction in a combination of indices based on the AttenD algorithm, setting two technical conditions in a heavy fog. Drivers suffering more visual distraction and interference with HMI may have an impact on the driver’s driving safety. The results provide a generic approach to evaluate the HMI of a connected vehicle system and a safety assessment methodology for the connected vehicle system.
Assessing livelihood vulnerability using a Bayesian network: a case study in northern Laos

Agricultural transitions from subsistence to export-oriented production make households more reliant on volatile agricultural commodity markets and can increase households’ exposure to crop price and yield shocks. At the same time, subsistence farming is also highly vulnerable to crop failures. In this work, we define household livelihood vulnerability as the probability of falling under an income threshold. We propose the use of a Bayesian network (BN) to calculate the income distribution based on household and community-level variables. BNs reflect relationships of dependence between variables and represent all variables as probability distributions, which allows for the explicit propagation of variability and uncertainty between variables. We focus on two agricultural frontier case study areas (CSAs) in northern Lao PDR that are at different stages in the transition from subsistence to export-oriented agriculture. Because agricultural production is the main livelihood activity in both CSAs, we develop a BN that calculates the probability distribution of net household agricultural production income. BN structure and parameterization are based on data collected in 110 household surveys across both CSAs, as well as interviews with villagers, government officials, and private sector actors. We analyze the effect of crop price and yield variability, land-use portfolio, and land holdings, on the probability of having a negative net agricultural income, which reflects a household’s ability to meet its food consumption needs through cash crop sales. Results show that agricultural income is highly sensitive to rubber plantation area, rubber yield, and rubber price given the very large income potential of the crop. Households with larger agricultural areas have a lower probability of falling under an agricultural income threshold regardless of their diversification choices. Households that own more high-value cash crops are more buffered against rice yield shocks despite having higher agricultural income variability. However, low-income households are better off if they maintain a minimum level of rice sufficiency in combination with high-value cash crop production. Diversifying upland cash crops by increasing the share of cardamom (a lowvalue but low-volatility crop) at the expense of rubber (a highly lucrative crop with high price volatility) does not have a sizable beneficial impact, because returns from cardamom are significantly lower than for rubber. We show that BNs can be useful tools for the design and evaluation of rural development policies.
A Practical Method for QTc Interval Measurement

Objective The various formulae used for QT correction by heart rate (HR) require the execution of operations with the aid of calculators or applications. This study aimed to evaluate the performance of a simple rule for QTc estimation, comparing the measurements obtained with those provided by the commonly used equations of Bazett, Fridericia, Framingham, and Hodges. Methods We used the database of a previous observational study, which analyzed patients prospectively with acute pulmonary edema admitted in an emergency service. One hundred four patients were included for QTc assessment, of whom 86 patients underwent two ECG: one ECG <24h and other >24h after admission. Thus, a total of 190 ECGs were analyzed by two observers that manually measured QT and HR. QTc was obtained using the known formulae and the proposed equations: QTc = QT+2 (FC-60) for HR ≤ 90 bpm and QTc=QT+2(FC-60)-10 for HR>90 bpm. Results Bland-Altman plots show good agreement between the simple rule and Hodges equation, with a mean difference of -3,4, SD of 4.96 and 95% limits of agreement from -9,9 to 3.2. There was not a good agreement between the simple method and the other formulae. Conclusion The proposed method has good agreement with the measures of QTc by the equation of Hodges in the HR range of 40 to 130bpm in acutely ill patients. Our method may be a plausible option for quick QT correction in these subjects. Categories: Cardiology
Synthesis and Evaluation of S- and C(1)-Substituted Analogues of Lincomycin

New thioglycosides and C(1)-alkylated thioglycosides (S-ulosides) of lincomycin were synthesized, and their antibiotic activities were determined. The S-aryl and S-arylalkyl analogues 11a – 11i were obtained by S-glycosylation of the sulfoxides 7 with arenethiols, or by S-alkylation of the thiol 14 with alkyl bromides. Lincomycin derivatives 27, 32a, 32b, 38a, 38b, 44, and 47 were prepared via Henry reaction or Michael addition of the lincosamine-derived 1-deoxy-1-nitropyranoses 22. The S-alkyl derivatives showed a similar activity and specificity as lincomycin. Lipophilic S-uloside analogues were two- to fourfold less active than the parent antibiotic, whilst the hydrophilic analogues were inactive.
Sociodemographic Determinants of Physical Inactivity of People Aged 60 Years and Older: A Cross-Sectional Study in Poland

Purpose The aim of the study was to evaluate general physical activity (PA) level on the basis of leisure time and transportation physical activity (LTPA and TPA), assess the percentage of persons not meeting PA recommendations by the World Health Organisation (WHO), and evaluate the relationship between selected sociodemographic factors and physical inactivity. Methods The paper is based on data (n = 7,347) retrieved from five large-scale surveys (2014-2018) used to collect information on the PA of Polish society. In order to meet the aim of the paper, we selected a sample of 2,023 Poles aged ≥ 60 years old. In each wave, the Polish long version of the International Physical Activity Questionnaire was used. Mann–Whitney U and Kruskal-Wallis tests were used to investigate the differences between the types and volume of PA and sociodemographic variables. Relationships between physical inactivity and analysed variables were evaluated using log-linear analysis. To capture relationships between physical inactivity and a set of explanatory variables, a predictive model was built. Results The total average energy expenditure amounted to 1879.5 ± 2352.5 MET-min/week, including LTPA (938.5 ± 1491.9 MET-min/week) and TPA (944.8 ± 1322.4 MET-min/week). Over the course of the last two years of the study, the average value of MET-min/week increased significantly (p < 0.05); however, prohealth WHO norms are not met by nearly 40% of Poles. Sex determines the volume of LTPA and TPA (p < 0.05) but does not determine the inactivity of seniors. Place of residence and education differentiate participation in LTPA and TPA. The lower the education level and the smaller the place of residence, the greater the inactivity. Conclusions The target for future interventions should be people aged 60+ living in villages and small towns (especially those with primary education). It is necessary to undertake educational and motivational programmes promoting PA. It is essential to develop detailed recommendations and to create a friendly and supportive environment.
Identifying Human Daily Activity Types with Time-Aware Interactions

Human activities embedded in crowdsourced data, such as social media trajectory, represent individual daily styles and patterns, which are valuable in many applications. However, the accurate identification of human activity types (HATs) from social media is challenging, possibly because interactions between posts and users at different time are overlooked. To fill this gap, we propose a novel model that introduces the interactions hidden in social media and synthesizes Graph Convolutional Network (GCN) for identifying HAT. The model first characterizes interactions among words, posts, dates, and users, and then derives a Time Gated Human Activity Graph Convolutional Network (TG-HAGCN) to predict the HATs of social media trajectory. To examine the proposed model performance, we built a new dataset including interactions between post content, post time, and users from the open Yelp dataset. Experimental results show that exploiting interactions hidden in social media to recognize HATs achieves state-of-the-art performance with high accuracy. The study indicates that interactions among social media promotes ability of machine learning on social media data mining and intelligent applications, and offers a reference solution for how to fuse multi-type heterogeneous data in social media.
Reinforced Superhydrophobic Anti-Corrosion Epoxy Resin Coating by Fluorine–Silicon–Carbide Composites

SiC was modified by fluorine-containing organic substance 1H,1H,2H,2H-trifluoro-noctyltriethoxysilane (FAS) to change its hydrophilicity from hydrophilic to superhydrophobic nanoparticles, and the optimum conditions for hydrophobicity were effectively explored. Then, different content of fluorine-modified SiC (F–SiC) nanoparticles were added to the epoxy resin (EP) matrix to prepare composite coating samples. The results showed that the surface of SiC was modified by FAS to show superhydrophobicity, and the dispersion in EP was significantly improved. After adding F–SiC, the hydrophobicity, wear resistance and corrosion resistance of the coating were significantly improved. In addition, the corrosion resistance of the composite coating containing different contents of F–SiC was analyzed through electrochemical and salt spray tests. The results showed that the corrosion resistance of the coating was the best when the addition amount was 3 wt %. In general, the composite coating with 3 wt % F–SiC had the best overall performance. Compared with the EP coating, the water contact angle of 3 wt % F–SiC/EP composite coating was increased by 62.9%, the friction coefficient was reduced by 73.5%, and the corrosion current was reduced by three orders of magnitude. This study provides a new idea for the development of ultra-wear-resistant and anti-fouling heavy-duty coatings.
Influence of excited states of Mg acceptors on hole concentration in GaN

The influence of the excited states of the acceptors on the hole concentration in p-type GaN is investigated theoretically and experimentally. Using the temperature dependence of the hole concentration p(T) in Mg-doped GaN epilayers, a distribution function suitable for Mg acceptors is examined. It is found that the influence of their excited states on p(T) as well as the temperature dependence of the average acceptor level cannot be ignored, when the acceptor level is deep (≥150 meV). Moreover, it is elucidated that due to their excited states the ionization efficiency of acceptors is higher at elevated temperatures than the ionization efficiency expected from the Fermi–Dirac distribution function. (© 2003 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Hardware-In-the-Loop Equipment for the Development of an Automatic Perturbator for Clinical Evaluation of Human Balance Control

Nowadays, increasing attention is being paid to techniques aimed at assessing a subject’s ability to maintain or regain control of balance, thus reducing the risk of falls. To this end, posturographic analyses are performed in different clinical settings, both in unperturbed and perturbed conditions. This article presents a new Hardware-In-the-Loop (HIL) equipment designed for the development of an automatic perturbator for postural control analysis, capable of providing controlled mechanical stimulation by means of an impulsive force exerted on a given point of the body. The experimental equipment presented here includes the perturbator and emulates its interaction with both the subject’s body and the operator performing the test. The development of the perturbator and of the entire HIL equipment is described, including component selection, modeling of the entire system, and experimentally verified simulations used to study and define the most appropriate control laws.
International tourism demand forecasting with machine learning models: The power of the number of lagged inputs

This study explores how to select the optimal number of lagged inputs (NLIs) in international tourism demand forecasting. With international tourist arrivals at 10 European countries, the performances of eight machine learning models are evaluated using different NLIs. The results show that: (1) as NLIs increases, the error of most machine learning models first decreases rapidly and then tends to be stable (or fluctuates around a certain value) when NLIs reaches a certain cutoff point. The cutoff point is related to 12 and its multiples. This trend is not affected by the size of the test set; (2) for nonlinear and ensemble models, it is better to select one cycle of the data as the NLIs, while for linear models, multiple cycles are a better choice; (3) significantly different prediction results are obtained by different categories of models when the optimal NLIs are used.
Effects of panretinal photocoagulation on macular vascular density and Foveal avascular zone area in patients with severe non-proliferative diabetic retinopathy by optical coherence tomography angiography

Aim: To describe the changes of optical coherence tomography angiography (OCTA) characteristics in severe non-proliferative Diabetic Retinopathy(S-NPDR) eyes. And study the effect of Panretinal photocoagulation(PRP) on these characteristics.Methods: This is a prospective study including 31 eyes from 18 consecutive patients with S-NPDR and 31 eyes of healthy subjects. We measured macular vascular density (VD) and foveal avascular zone(FAZ) area by an OCTA device. All patients with S-NPDR underwent PRP treatment. In S-NPDR eyes, the VD and foveal avascular zone(FAZ) area were assessed at 1 week before PRP, 1 month, 3 months and 6 months following PRP.Results: Compared with the normal control group ,in superficial retinal capillary plexus (SCP), macular VD decreased in S-NPDR group expect foveal VD. In foveal ,p=0.7;In parafoveal and perifoveal, p＜0.001. In deep retinal capillary plexus (DCP), macular VD was also lower in S-NPDR group. In foveal, p=0.01. In parafoveal and perifoveal, p＜0.001. And FAZ area expanded in S-NPDR eyes(p=0.05). In S-NPDR eyes , at 3 months after PRP, foveal VD in DCP increased significantly(p=0.04). At 6 months after PRP, foveal VD increased both in SCP and DCP (P=0.01,P=0.008,respectively). At 6 months after PRP,FAZ area decreased (p=0.04). Conclusions : Patients with S-NPDR have retinal microcirculation disorder, and PRP can partially improve the macular microcirculation. VD and FAZ can be used as sensitive indicators for follow-up observation of diabetic retinopathy.
Investigating Cognitive Processes in Foreign Language Learning: Use of Introspective Measures

Findings in foreign language research are dependent on the data elicitation measures that the researcher selects in order to answer the target research questions. The present article provides a detailed account of the different introspective measures that researchers commonly opt for to collect data about learners’ learning processes, which are unobservable. The focus will be placed on various methods, like verbal reports and stimulated recalls. In addition to describing the procedures for every elicitation measure, the researcher reviews some of the studies that used such tools. The aim is to provide researchers with some insights into how effectively they can have access to learners’ internal thought processes. This will help in adjusting teaching practices according to learners’ needs.
Perspectives in ESG equity investing

The research on sustainable finance has intensified in the past decade. In this survey, we synthesize recent academic results and models on socially responsible investing (SRI) in equity markets. We split our review into six thematic parts: data issues, investor preferences, link with financial performance, portfolio integration, climate change risk, and theoretical models.
ANALYSIS THE INFLUENCE OF CORPORATE SOCIAL RESPONSIBILITY ON RETURN ON EQUITY (ROE)

Introduction: Firm is definite as a legal entity that operates due to economic policy. It is not only oriented to achieve maximum profit, but in addition it also needs to build a good reputation through corporate social responsibility to maintain the existence of the firm through the competition. Therefore, ISO 26000 can be chose by the firm as an indicator in implementing good corporate social responsibility activities. The seven factors that consist in ISO 26000 are corporate governance, human rights, labour practices, the environment, fair operating practices, consumer issues, and community involvement and development. Going forward from the process, the firm can measure the success of operational activities and corporate social responsibility activities through financial performance indicator, such as: Return on Equity (ROE). Methods: This study is using causal comparative research method which represents the relationship between one variable to another variable, by using the facts that have been occurred (ex post facto). The sample that used in this study are the manufacturing firms that listed on Bursa Efek Indonesia (BEI) since 2009 till 2015. Results: The results of this study indicate the different effects of significance on corporate social responsibility to financial performance of the firm, in which corporate social responsibility has positive significant effect to Return on Equity (ROE) in the manufacturing firms that listed on Bursa Efek Indonesia (BEI). Conclusion and suggestion: The managerial implication that can be carried out by company management is to maintain a balance of social responsibility disclosure between the interests of stakeholders and company management. Until in the end, the company's activities can run well, namely achieving profits from the company's operational activities, as well as benefits from corporate social responsibility activities. Various activities that can be carried out by companies, namely increasing disclosure of social responsibility which is still included in a low proportion, especially fair operating practices, such as: anti-corruption, responsible involvement in political affairs, fair competition, promotion of social responsibility, and respect for rights. create.
The predictive role of individual differences of the work performance of Lithuanian driving examiners

Driver examiners are one of the first traffic safety agents as they ensure that candidates with bad skills do not participate in the traffic as licensed drivers. The aim of this study is to evaluate the role of individual differences for the occupational performance of driving examiners in Lithuania. 103 male examiners and 10 their supervisors participated in the study. Examiners filled in the self-report questionnaires: NEO-PI-R personality questionnaire, the scale of attitudes towards traffic safety, and situational judgement test assessing communication competence. Job performance rates were obtained from supervisors using the routine procedure implemented in the organization. Examiners rated by supervisors as more proficient are those who have higher conscientiousness, agreeableness, openness to experience, extraversion and lower neuroticism as well as high communication competence and more positive attitude towards traffic safety. Communication competence was the only significant predictor of better job performance of driver examiners when controlling for interaction between tested variables. Although the data allowed to distinguish psychological characteristics of examiners who were rated as performing better at their work, the predictive role of individual differences was modest. Other research strategies and variables should be applied in order to reach more comprehensive results in this field.
A feature-optimized Faster regional convolutional neural network for complex background objects detection

In recent years, convolutional neural networks are playing an increasingly important role in the ﬁeld of object detection. However, the complex background of the detected image, the limited receptive ﬁeld by the ﬁxed geometry of the convolution kernel when building the model, and the positioning and pooling deviation from the region of interest are still important factors that affect the detection accuracy. In this paper, an improved algorithm is proposed for target detection based on Faster regional convolutional neural network. In the bounding box positioning phase, an improved interpolation algorithm-Newton’s parabolic interpolation is proposed instead of bilinear interpolation, after ROI size normalized by extending a parallel branch of tensor to weaken the negative impact of complex background on prospects in the phase of feature extraction using neural network recently popular attention CBAM mechanism model and the deformable convolution. Without bells and whistles, a series of experiments show that our method has higher target detection accuracy on the datasets PASCAL VOC2007, VOC2012, COCO 2014 and DIOR. Hence, the method is effective for actual target recognition tasks in complex background environ-ments. The authors hope
Impact of Urban Canopy Parameters on a Megacity’s Modelled Thermal Environment

Urban canopy parameters (UCPs) are essential in order to accurately model the complex interplay between urban areas and their environment. This study compares three different approaches to define the UCPs for Moscow (Russia), using the COSMO numerical weather prediction and climate model coupled to TERRA_URB urban parameterization. In addition to the default urban description based on the global datasets and hard-coded constants (1), we present a protocol to define the required UCPs based on Local Climate Zones (LCZs) (2) and further compare it with a reference UCP dataset, assembled from OpenStreetMap data, recent global land cover data and other satellite imagery (3). The test simulations are conducted for contrasting summer and winter conditions and are evaluated against a dense network of in-situ observations. For the summer period, advanced approaches (2) and (3) show almost similar performance and provide noticeable improvements with respect to default urban description (1). Additional improvements are obtained when using spatially varying urban thermal parameters instead of the hard-coded constants. The LCZ-based approach worsens model performance for winter however, due to the underestimation of the anthropogenic heat flux (AHF). These results confirm the potential of LCZs in providing internationally consistent urban data for weather and climate modelling applications, as well as supplementing more comprehensive approaches. Yet our results also underline the continued need to improve the description of built-up and impervious areas and the AHF in urban parameterizations.