Miracle-dz/UniFAR-FTUs huggingface dataset:
Area Lights Voxelization for Light Propagation Volumes

: Simulation of the area light sources direct illumination is a topic of interest in the ﬁeld of Computer Graphics. In the real world, all light sources have a surface from which light is emitted. Thus, for a physically correct simulation of the light transport in graphical applications, area light sources are required. In addition, there are complex lighting effects that can only be simulated with such light sources. In this paper, we present an improvement of the direct lighting simulation for area light sources within the real-time global illumination technique called light propagation volumes. Our method is based on a voxelization of the area light source geometry in a voxel volume of the same resolution as the light propagation volume used in the global illumination technique. With a sample for every voxel that intersects a triangle, for every triangle of the mesh, we obtain an optimal distribution of the samples needed to approximate the direct illumination of the area light source for the light propagation volumes technique.
Chronic Venous Disease in Pregnant Women Causes an Increase in ILK in the Placental Villi Associated with a Decrease in E-Cadherin

Chronic venous disease (CVD) is a multifactorial vascular disorder frequently manifested in lower limbs in the form of varicose veins (VVs). Women are a vulnerable population for suffering from CVD, especially during pregnancy, when a plethora of changes occur in their cardiovascular system. Previous studies have indicated a worrisome association between CVD in pregnancy with the placental structure and function. Findings include an altered cellular behavior and extracellular matrix (ECM) composition. Integrin-linked kinase (ILK) is a critical molecule involved in multiple physiological and pathological conditions, and together with cadherins, is essential to mediate cell to ECM and cell to cell interplay, respectively. Thus, the aim of this study was to evaluate the implication of ILK and a set of cadherins (e-cadherin, cadherin-6 and cadherin-17) in placentas of women with CVD in order to unravel the possible pathophysiological role of these components. Gene expression (RT-qPCR) and protein expression (immunohistochemistry) studies were performed. Our results show a significant increase in the gene and protein expression of ILK, cadherin-6 and cadherin-17 and a decrease of e-cadherin in the placenta of women with CVD. Overall, this work shows that an abnormal expression of ILK, e-cadherin, cadherin-6 and cadherin-17 may be implicated in the pathological changes occurring in the placental tissue. Further studies should be conducted to determine the possible associations of these changes with maternal and fetal well-being.
RNAi Screening Uncovers a Synthetic Sick Interaction between CtIP and the BARD1 Tumor Suppressor

Human CtIP is best known for its role in DNA end resection to initiate DNA double-strand break repair by homologous recombination. Recently, CtIP has also been shown to protect reversed replication forks from nucleolytic degradation upon DNA replication stress. However, still little is known about the DNA damage response (DDR) networks that preserve genome integrity and sustain cell survival in the context of CtIP insufficiency. Here, to reveal such potential buffering relationships, we screened a DDR siRNA library in CtIP-deficient cells to identify candidate genes that induce synthetic sickness/lethality (SSL). Our analyses unveil a negative genetic interaction between CtIP and BARD1, the heterodimeric binding partner of BRCA1. We found that simultaneous disruption of CtIP and BARD1 triggers enhanced apoptosis due to persistent replication stress-induced DNA lesions giving rise to chromosomal abnormalities. Moreover, we observed that the genetic interaction between CtIP and BARD1 occurs independently of the BRCA1-BARD1 complex formation and might be, therefore, therapeutical relevant for the treatment of BRCA-defective tumors.
Perceptions and knowledge of school management teams about non-communicable diseases and strategies to prevent them

Background In 2016, non-communicable diseases (NCDs) were reported to be responsible for 41 million of the world’s 57 million deaths. These deaths were reported to be associated with modifiable lifestyle behaviours, such as tobacco smoking, poor physical activity and diets of poor nutritional value. There could be a knowledge gap on NCD risk factors amongst non-health professionals. Knowledge of NCDs is, therefore, important for the implementation of preventive measures to onset of NCDs. Aim This study aimed at describing perceptions and knowledge of school management teams about NCDs and strategies to prevent them. Setting This study was conducted in Mt Frere, South Africa. Methods This explorative qualitative study using a phenomenological data collection approach was conducted amongst purposively selected school authorities in 2016–2017 to understand their perceptions and knowledge about NCDs and what can be performed to prevent them. Two focus group discussions (FGDs) were conducted using open-ended and unstructured questions guided by interview schedule. Tesch’s eight phases of thematic analysis approach was used to analyse narrative data resulting in two main themes and nine subthemes. Results Two themes (understanding and prevention of NCDs, and control measures for NCDs) and nine sub-themes emerged from the data analysis. Inconsistent description of NCDs, its causes and controls were identified amongst school management teams in the FGD. Diet, poverty, societal factors, gaps between decision makers and communities, and poor policy implementation were identified by participants as major issues in the development of NCDs. Conclusion There was no adequate knowledge on NCDs amongst the school management team participants. Improved visibility of health promotion personnel is needed to ensure community empowerment on NCDs prevention. Contribution The findings in this study will help in closing the gaps in the implementation of preventive health services for NCDs within school health.
Structural Equation Modelling of Factors Influencing Users‘ Adoption of Smart Board: A South African University Perspective

Information and communication technologies (ICTs) have grown rapidly, becoming an integral part of today’s society and affecting how daily activities are conducted worldwide. They have transformed the education landscape and today’s classrooms have evolved from traditional blackboards to whiteboards and then to smart boards. The smart board technology (SBT) is considered one of the innovative teaching and learning technologies for different levels in education. However, the challenge is the low adoption of the SBT in teaching and learning environments by educators, particularly in Higher Education Institutions (HEIs). Therefore, the purpose of this study was to explore factors affecting the adoption of smart board technology. Using an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model, a quantitative, cross-sectional survey was utilised to gather data from 224 academics from a South African university. Findings revealed that the adoption of smart board technology at the university is low and smart board features are inadequately used. Additionally, results showed that social influence and attitude toward using technology were significantly the key factors affecting users’ intentions to adopt smart boards. Facilitating conditions had a very strong statistically significant effect on users’ behaviour to use smart boards.
Geometric relation based point clouds classification and segmentation

The inherent disorder and irregularity of 3D point clouds pose great challenges to classification and segmentation tasks. To tackle these problems, we propose a geometric relation based point clouds classification and segmentation network. Specifically, we design two novel modules named geometric relation based convolution (GRC) and relational attention interpolation (RAI) to infer the local relations of point clouds. In GRC module, the convolutional weights and local features are both reasoned from predefined local geometric relations between the central point of each local point clouds and its neighboring points. The global shape awareness is obtained by stacking convolutional layers of the GRC. In RAI, a relational attention interpolation approach is proposed for the segmentation task. The attentional weights of different neighboring points are inferred from local relations of geometry and features, which is capable of guiding RAI to pay more attention to the relevant points and be sensitive to the boundaries of segments. Experimental results show that the proposed method makes full use of the geometric relations between local points, and presents good performance on both classification and segmentation tasks.
QuadNet: A Hybrid Framework for Quadrotor Dead Reckoning

Quadrotor usage is continuously increasing for both civilian and military applications such as surveillance, mapping, and deliveries. Commonly, quadrotors use an inertial navigation system combined with a global navigation satellite systems receiver for outdoor applications and a camera for indoor/outdoor applications. For various reasons, such as lighting conditions or satellite signal blocking, the quadrotor’s navigation solution depends only on the inertial navigation system solution. As a consequence, the navigation solution drifts in time due to errors and noises in the inertial sensor measurements. To handle such situations and bind the solution drift, the quadrotor dead reckoning (QDR) approach utilizes pedestrian dead reckoning principles. To that end, instead of flying the quadrotor in a straight line trajectory, it is flown in a periodic motion, in the vertical plane, to enable peak-to-peak (two local maximum points within the cycle) distance estimation. Although QDR manages to improve the pure inertial navigation solution, it has several shortcomings as it requires calibration before usage, provides only peak-to-peak distance, and does not provide the altitude of the quadrotor. To circumvent these issues, we propose QuadNet, a hybrid framework for quadrotor dead reckoning to estimate the quadrotor’s three-dimensional position vector at any user-defined time rate. As a hybrid approach, QuadNet uses both neural networks and model-based equations during its operation. QuadNet requires only the inertial sensor readings to provide the position vector. Experimental results with DJI’s Matrice 300 quadrotor are provided to show the benefits of using the proposed approach.
Feature Extraction using Downsampling for Person Re-identification with Low-resolution Images

: We investigate whether a downsampling process of high-resolution pedestrian images can improve person re-identiﬁcation accuracy. Generally, deep-learning and machine-learning techniques are used to extract features that are unaffected by image resolution. However, it requires a large number of pairs of high- and low-resolution images acquired from the same person. Here, we consider a situation in which these resolution pairs cannot be collected. We extract features from low-resolution pedestrian images using only a simple downsampling process that requires no training resolution pairs. We collected image resolution datasets by changing the focal length of the camera lens and the distance from the person to the camera. We conﬁrmed that the person re-identiﬁcation accuracy of the downsampling process was superior to that of the upsampling. We also conﬁrmed that the low-frequency components corresponding to the output of the downsampling process contain many discriminative features.
A New Morphing Wing Mechanism Using Smart Actuators Controlled by a Self-Tuning Fuzzy Logic Controller

The paper presents the design of an intelligent actuation control concept, self-tuning fuzzy logic Proportional-Integral-Derivative plus conventional On-Off, for a new morphing mechanism using smart materials made of Shape Memory Alloy (SMA) for the actuators. In this way, two fuzzy inference systems were developed and implemented in the self-tuning fuzzy logic controller. In the design phase, the input-output mappings of the fuzzy models were designed and a final architecture for the hybrid controller was obtained. The shapes chosen for inputs membership functions of both fuzzy inference systems were s-functions, πfunctions, respectively z-functions, while the product fuzzy inference and the center average defuzzifier were applied (Sugeno). The obtained controller was numerically and experimentally implemented using the Matlab/Simulink software. Following preliminary numerical simulations which were conducted to tune the controller, an experimental validation was performed: bench tests and wind tunnel tests. Simultaneously, the aerodynamic part of the morphing wing model was validated: optimized airfoils were experimentally validated with the theoretically-determined airfoils obtained earlier. Also, the transition point real time position detection and visualization were realized in wind tunnel tests.
THREE-DIMENSIONAL DESIGN OF A MIMO SYSTEM BASED ON SUPERSHAPE ANTENNA

In this thesis, a three-dimensional multiple-input-multiple-output (MIMO) antenna is designed for wireless applications. The MIMO consists of three antennas arranged around a triangular prismatic polystyrene foam that acts as a supporting block to form a tetrahedral configuration. This system has the capability of achieving multipath propagation; it also has the potential to improve the quality and reliability of radio signals, improve the channel capacity, and increase the communication speed and data rate. A circular microstrip patch antenna with regular spikes was designed based on the Superformulaa generic formula that describes naturally occurring shapes with six parameters. Afterward, bandwidth enhancement techniques were used to improve its performance over the ultra-wideband (UWB) frequency range. The antenna was then simulated, fabricated, and tested to ensure its performance conforms with the UWB requirements. Subsequently, three similar antennas were configured around a triangular prismatic polystyrene foam to realize the MIMO, and mutual coupling reduction was incorporated. The system was simulated, fabricated, and tested. For a unit antenna, the simulated and measured |S11(dB)| is greater than 10dB across the FCC band, the antenna shows an acceptable gain, efficiency, group delay, and radiation characteristic fulfilling the UWB requirements. The MIMO has a simulated |reflection coefficients(dB)| greater than 10dB in the entire FCC band, the inter-element isolation is greater than |15dB|, the CCL, ECC, MEG, diversity gain and TARC are acceptable for MIMO application. Our design of a miniaturized UWB circular patch antenna, a compact threedimensional MIMO with the least possible number of antennas for full 3D beam coverage that is 360 degrees in both the azimuth and the elevation, and the implementation of microstrip isolation and bandwidth enhancement techniques to boost the overall performance of the MIMO system are improvements to the state-ofthe-art in antenna system design for wireless applications.
How to Find the Key Participants in Crowdsourcing Design? Identifying Lead Users in the Online Context Using User-Contributed Content and Online Behavior Analysis

Lead users are the most valuable innovation sources in crowdsourcing design; how to identify these users is a research hotspot in the field of design and management. Existing approaches to discover lead users in the context of the online community, such as the manual method and ordering algorithm, have some limitations, for instance, low coverage and accuracy. To address these deficiencies, this article proposes a method that applies text-mining techniques, analysis of user behavior, and contributed content to identify lead users. We suggest a three-step analytical approach: First, a criterion system to evaluate the user’s leading-edge status is constructed. Second, we utilize a fuzzy analytical hierarchy process to assess the weighted value of each indicator and develop the reference sequence of the indicators. Third, grey relational analysis is employed to analyze the correlations between users’ indicators and reference sequences, and lead users are recognized based on each user’s correlation ranking. An empirical analysis is used to examine the effectiveness of the proposed method. The results reveal that the method has good precision and recall rate, can automatically process large-scale data, and has no strict requirements for respondents. Finally, the article discusses the limitations and provides possible directions for future research.
WATER QUALITY OF THE HABITAT OF TWO ENDANGERED HIGH-ANDEAN FROGS USING AQUATIC MACROINVERTEBRATES AS BIOINDICATORS

Telmatobius macrostomus and Telmatobius brachydactylus are two high Andean aquatic frogs categorized as "Endangered" by the Red List of the International Union for Conservation of Nature and by the Peruvian Legislation. With the aim of evaluating the water quality of their habitats, four bimonthly samplings in the field were carried out at 12 study sites located in the Junin and Pasco regions of Peru. Physicochemical, hydrological and microbiological variables were measured. Samples of aquatic macroinvertebrates were taken and the following water quality indices were applied: Andean Biotic Index (ABI) and Family Biotic Index (FBI). The results show that the environmental variables total dissolved solids (TDS) and total coliforms exceed the Environmental Quality Standards (ECA) for water according to Peruvian regulations. The aquatic macroinvertebrate community showed differences in its community structure between sampling stations and indicated moderate to good water quality according to the applied indices, except in the stations that would be being impacted by cattle farming and chuño production (ancestral activity whereby freeze-dried potatoes are fermented in cold, running stream water), both activities impact the water quality of the studied habitats and could influence the presence of frogs, because both species generally inhabit clean aquatic ecosystems.
Evaluation of reliability performance of distribution networks implementing demand response schemes

Demand Response (DR) is likely to become key to power system operation and planning in the future. In this outlook, the successful deployment of any DR scheme will be facilitated by the integration of Information and Communication Technologies (ICT), enabling Distribution System Operators (DSOs) to actively manage their networks. Various DR applications have been proposed, mostly relevant to energy markets, while few studies are yet available on DR as a means to contribute to network capacity and on the relevant reliability implications. In this work, DR is proposed as a post fault contingency action to provide capacity release in distribution networks. The reliability performance of the proposed scheme is assessed through Sequential Monte Carlo Simulations (SMCS) taking into account both electrical and ICT failures. Customer Interruptions (CI) and Customers Minutes Lost (CML) are evaluated in addition to the classical load point reliability indices. DR customers are disconnected according to a priority list with the aim of not breaching network constraints after a fault occurs. As case studies, two different DR control strategies are introduced and compared based on their reliability performance for different DR availability levels.
The Mediating Effect of Nature Restorativeness, Stress Level, and Nature Connectedness in the Association between Nature Exposure and Quality of Life

This study aimed to test the mediating effects of nature restorativeness, stress, and nature connectedness in the association between nature exposure and quality of life (QoL). Urban and rural Lithuanian inhabitants (n = 924; 73.6% were women), mean age of 40.0 ± 12.4 years (age range of 18–79) participated in the study. In total, 31% of the respondents lived in rural areas. Study participants completed an online survey form with measures on sociodemographic factors, nature proximity, nature exposure, nature connectedness, and nature restorativeness, stress, and QoL assessed by the abbreviated version of the World Health Organization’s Quality of Life Questionnaire’s (WHOQOL-BREF). Path analysis was conducted to test the mediating effects of nature restorativeness, stress, and nature connectedness in the model of nature exposure and QoL. Nature exposure was directly associated with a greater QoL (β = 0.14; B = 2.60; SE = 0.57; p < 0.001) and mediated the association between nature proximity and QoL. Nature restorativeness and lower stress levels were mediators between nature exposure and QoL. Nature connectedness was a mediator between nature exposure and QoL. A path model was invariant across genders and the urban and rural place of residence groups: patterns of loadings of the pathways were found to be similar. Nature restorativeness (β = 0.10–0.12; p < 0.01) had a positive effect on the psychological, physical, social, and environmental domains of QoL. Connectedness to nature positively predicted psychological (β = 0.079; p < 0.05) and environmental (β = 0.082; p < 0.05) domains of QoL. Enhancing nature exposure and nature connectedness might help strengthen QoL in urban and rural inhabitants.
Ant colony algorithm oriented to Job Shop scheduling problem based on self-adaptive and uneven windows

To overcome the shortcomings of ant colony algorithm in falling into local minimum value easily and its long search cycle for Job Shop scheduling problem,an improved self-adaptive ant colony algorithm based on different size window was proposed.Firstly,the self-adaptive unequal ant window was used to limit movement ranges of ants in the new algorithm.The strategy could reduce the searching cycle of ants and find new space of solution timely.Secondly,the window jumping strategy of ant was proposed by using the polymorphic characterisitics of ants.It enabled the new algorithm with the good ability to jump out of the local best.Finally,considering the circumstances under which a job was processed in different machines in the Job Shop scheduling problem,illuminating function in state transfer probability was improved.It improved the illuminating degree of ant's route.The new algorithm was simulated with the Muth and Thompson standard problem,and the simulation result showed that the convergence of the proposed algorithm was improved sharply.
Evaluation of Dimension Stone According to Resistance to Freeze–Thaw Cycling to Use in Cold Regions

1. Associate Professor, Department of Mining Engineering, Faculty of Environment, Urmia University of Technology, Urmia, Iran 2. Assistant Professor, Department of Mining Engineering, Faculty of Environment, Urmia University of Technology, Urmia, Iran 3. Ph.D. Candidate, Department of Civil Engineering, University of Calabria, 87036 Rende, Italy 4. Professor, Department of Mining, Petroleum & Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran 5. M.S., Department of Civil Engineering, Faculty of Environment, Urmia University of Technology, Urmia, Iran 6. Ph.D. Candidate, Department of Mining and Metallurgical Engineering, Yazd University, Yazd, Iran 7. Professor, Department of Civil Engineering, Korea Maritime and Ocean University, Pusan 49112, Korea 8. Associate Professor, College of IT Convergence, Gachon University, Seongnam 13120, Korea Corresponding author: geem@gachon.ac. kr