Miracle-dz/UniFAR-FTUs huggingface dataset:
THE EFFECT OF INCLINED PLANAR FABRIC FEATURES ON THE BEHAVIOR OF A LOADED ROCK MASS

THE SOURCES OF STRESS-DEFORMATION ANISOTROPY IN ROCKS AND ROCK MASS ARE DISCUSSED AND STRONG CORRELATIONS ARE SHOWN TO EXIST WITH THE ANISOTROPIES IN ASSOCIATED ROCK FABRIC FEATURES. THE ORTHORHOMBIC ELASTIC MATERIAL IS USED AS A THEORETICAL MODEL SINCE IT CAN REPRESENT BOTH AN ANISOTROPIC HOMOGENEOUS ROCK MASS AS WELL AS THE MORE COMMON CASE OF A ROCK MASS CONSISTING OF A SYSTEM OF PARALLEL LAYERS HAVING DIFFERENT THICKNESSES AND PROPERTIES. THE PROBLEM CONSIDERED IS THAT OF A ROCK MASS LOADED ON ITS HORIZONTAL SURFACE BY A LONG LOAD OF UNIFORM WIDTH AND PRESSURE, AND HAVING THE DIRECTIONS OF THE SYMMETRIES IN ITS FABRIC PATTERN INCLINED TO THE HORIZONTAL. THIS IS REPRESENTED THEORETICALLY BY A LOADED HALF-PLANE IN WHICH THE DIRECTION OF THE MAXIMUM MODULUS IS SIMILARLY INCLINED. THE ANALYSIS IS BASED ON THE FINITE ELEMENT METHOD USING A SIMPLE TRIANGULATED MESH. THE RESULTS SHOW THE MARKED EFFECT OF THE INCLINED ANISOTROPY AS REFLECTED BY CHANGING PATTERNS IN THE MAGNITUDE AND ORIENTATION OF THE PRINCIPAL STRESSES AND THE TOTAL DISPLACEMENTS.
Zig-Zag and Shuttle Run Training on the Results of the Agility of Karateka

The agility of Karate athletes is still low. It is evident that when participating in the match, the athlete’s movements appear to be less agile when avoiding the opponent’s attack. The purpose of this study was to analyze zig-zag and shuttle run training in improving agility in Karateka. This study used a quasi-exsperimen method with a pre-test and post-test design control group. The population in this study were all Karateka athletes consisting of 20 male athletes and 18 female athletes. The sample used was 20 male athletes who were still actively training. Data collection methods used observation, tests and documentation. Data analysis techniques used quantitative analysis. The results showed that shuttle run training had a significant effect on increasing agility (tit equal to 60.42 more than ttab equal to 2.26). Ziq-zaq exercise gives a significant effect on increasing agility (thit equal to 159.06 more than ttab equal to 2.26). Ziq-zaq run training is more effective in increasing agility compared to shuttle run training (thit equal to 26.64 more than ttab equal to 2.26). The conclusion of this study is that training with the zig-zag run method is more effective in increasing agility in Karateka. The implication of this research is expected to increase the element of agility for athletes so that achievement can be achieve.
Self-organisation in tourism planning: complex dynamics of planning, policy-making, and tourism governance in Santa Elena, Ecuador

This research explores the dynamic interplay between self-organised tourism planning and formal, linear and institutionalised tourism governance structures in the Santa Elena province, Ecuador. Complexity theory provides a framework and a language to understand actor-led, non-linear, bottom-up, and highly contextualised self-organised planning efforts that can change the future of tourism destinations amidst unstable and changing tourism governance conditions
Graphrpe: Relative Position Encoding Graph Transformer for 3d Human Pose Estimation

The graph neural network has been playing increasingly important roles in 2D-3D lifting based single-frame human pose estimation. However, it still suffers from inferior modeling of local and global associations between 2D nodes. To this end, we introduce two relative position encoding approaches and propose a novel graph-transformer structure "GraphRPE. " The model consists of two components: graph relative position encoding (GRPE) and universal relative position encoding (URPE). GRPE embeds graph structure prior information into the attention map to correct the self-attention weights and prompt appropriate interactions between 2D nodes, both locally and globally. On the other hand, URPE introduces the Toeplitz matrix to address the limited representation capability of the transformer. In addition, we investigate several graph edge types and their impacts on the results. Extensive experimental results demonstrate that our proposed method achieves SOTA performance on the Human3.6M dataset.
CHRONIC AND INTERVENTIONAL PAIN

Background and Objectives: Large-scale application of Quantitative Sensory Tests (QST) is impaired by lacking standardized testing protocols. One unclear methodological aspect is the number of records needed to minimize measurement error. Traditionally, measurements are repeated 3 to 5 times, and their mean value is considered. When transferring QST to a clinical setting, reducing the number of records would be desirable to meet the time constraints encountered in a routine clinical environment and to reduce the testing burden to chronic pain patients. However, there might be a trade-off between measurement error and number of records. We determined the measurement error of a single versus the mean of 3 records of pressure pain detection threshold (PPDT), electrical pain detection threshold (EPDT), and nociceptive withdrawal reflex threshold (NWRT) in 429 chronic pain patients recruited in a routine clinical setting. Methods:We calculated intraclass correlation coefficients and performed a Bland-Altman analysis. Results: Intraclass correlation coefficients were all clearly greater than 0.75, and Bland-Altman analysis showed minute systematic errors with small point estimates and narrow 95% confidence intervals. Reducing the number of records from traditionally 3 to only 1 did not lead to relevant measurement error in PPDT, EPDT, or NWRT. Conclusions: This study contributes to a standardized QST protocol, and based on the minimal measurement error of 1 single record of PPDT, EPDT, and NWRT, we submit to reduce the testing burden. This would allow saving time, resources, and patient discomfort.
Who Adds Value to Ventures? Understanding the Roles and Relative Contributions of Key Advisors in High-Technology Startups

During the process of starting and growing a company, entrepreneurs seek help from their key advisors, which include its directors, advisory board members, financiers, as well as others informally affiliated with the venture. This paper examines how the various groups add value to a venture and assesses the relative value of their contributions. Through a survey of high technology entrepreneurs, we find that directors, advisory board members and informal advisors add significant value by offering their expertise in various fields. Surprisingly, investors add relatively little value, even in such key areas as strategic planning and finance. While professional venture capitalists add more value than private investors, even the venture capitalists' contribution was perceived lower than those of the other advisors in key areas. Our results suggest that the contributions of investors may have been overestimated in conventional literature.
An Adaptive Analog Temperature Compensated W-Band Front-End With ±0.0033 dB/°C Gain Variation Across −30 °C to 120 °C

This brief presents an adaptive analog temperature compensation (AATC) method that generates the optimal bias voltage to maintain constant gain of the millimeter-wave amplifier over an ultra-wide temperature range. The AATC method utilizes an exponential curve for high-order fitting the optimal bias voltage, which is generated by the piecewise exponential current of two differential MOS pairs operating in the subthreshold region, only requiring low power consumption and small chip area. To verify the effectiveness of the AATC method, a W-band front-end is fabricated in 65-nm CMOS technology. Benefiting from the AATC method, the measurement results show that the gain variation of the W-band front-end in both receive and transmit modes is less than ±0.5 dB over an ultra-wide temperature range from −30 °C to 120 °C and the corresponding gain temperature coefficient is ±0.0033 dB/°C, significantly better than the −7 dB gain variation without temperature compensation. The optimal bias voltage generation circuit based on AATC method consumes only $2~{\mu }\text{A}$ of current under 1-V supply voltage, and occupies only 0.1 mm2.
Infrastructuring : Towards an Integrated Perspective on the Design and Use of Information Technology

In this contribution we investigate how results from the ongoing discussion about ‘eInfrastructures’ can be used to improve the design of IT infrastructures in organizations. We first establish a perspective on organizational IT as ‘work infrastructure’ that focuses on the infrastructural nature of organizational Information Systems and describe challenges for designing within and for this type of infrastructure. Then we elaborate on possible use of concepts from the e-infrastructure discussion, in particular on the concept of ‘infrastructuring’ as it was developed by Star and Ruhleder (1996) and Star and Bowker (2002). Using their ‘salient characteristics of infrastructure’ we describe the methodological approach of ‘Infrastructuring’ to develop methodological and tool support for all stakeholders’ activities that contribute to the successful establishment of an information system usage (equivalent to a work infrastructure improvement). We illustrated our ideas by drawing on a case in which new work infrastructures were introduced into an organizational context and by mapping out existing and possible tool support for ‘infrastructuring’.
Deep Learning Reconstruction for Single Pixel Imaging with Generative Adversarial Networks

Single pixel imaging (SPI) enables high-resolution imaging through multiple coded measurements based on low-resolution snapshots. An inverse problem can then be solved to reconstruct a high-resolution image given the coded measurements. There has been recent interest in adoption of deep neural networks in SPI reconstruction. However, existing methods are commonly trained with pixel-wise loss terms such as the ℓ1-norm loss, which can result in spatial blurring and poor sensitivity to structural details. In this study, we propose a novel approach for deep SPI reconstruction based on an unrolled conditional generative adversarial network (cGAN) model. The generator estimates the high-resolution image using coded low-resolution measurements by iterating across a cascade of denoising and data-consistency modules. Meanwhile, the discriminator distinguishes real versus synthesized high-resolution images. The architecture is trained end-to-end via a combined pixel-wise and adversarial loss to enhance sensitivity to structural details. The proposed method is demonstrated against existing SPI reconstruction methods, and ablation studies are performed to demonstrate the individual model components. The proposed method outperforms competing methods in terms of both quantitative metrics and visual quality.
Effects of Perceived Risk and Subjective Norms on Internet Banking Adoption Amongst the Students of University of Kelaniya: A Multilevel Linear Model Analysis

Challenging technology advancements necessitate robust macroeconomic performance to support overall economic development. Within the service sector of the economy, one of the broadly studied areas of technological transformation is retail financial services; particularly consumer banking activities. Internet banking enables customers to experience a vast array of financial services through e-banking websites. Nonetheless, in practice; this phenomenon is contingent on the particular context. Hence, this research addresses the significance of subjective norms and perceived risk towards acceptance of consumer internet banking in the Sri Lankan context with special reference to private commercial banks. The sample was drawn from the students of the University of Kelaniya those who are participating in the weekend study programs. The students of the Doctor of Business Administration Course attached to the university were selected as enumerators for data collection. Data collected through self-administered questionnaires from the respondents. Initially, 400 questionnaires were distributed and 287 duly completed questionnaires were considered for the final data analysis. TAM has been extended using the subjective norms and perceived risk variables and dimensions of the variables were measured by a five-point Likert scale. Cronbach’s alpha was used to check reliability. To test the hypotheses, ANOVA, ANCOVA, and multilevel linear models were used. The empirical evidence supported three hypotheses indicating the significance of the variables/constructs on the adoption of internet banking. In conclusion, the authors have presented several suggestions for research studies, in time to come.
Exploring User Engagement in Museum Scenario with EEG—A Case Study in MAV Craftsmanship Museum in Valle d’Aosta Region, Italy

In the last decade, museums and exhibitions have benefited from the advances in Virtual Reality technologies to create complementary virtual elements to the traditional visit. The aim is to make the collections more engaging, interactive, comprehensible and accessible. Also, the studies regarding users’ and visitors’ engagement suggest that the real affective state cannot be fully assessed with self-assessment techniques and that other physiological techniques, such as EEG, should be adopted to gain a more unbiased and mature understanding of their feelings. With the aim of contributing to bridging this knowledge gap, this work proposes to adopt literature EEG-based indicators (valence, arousal, engagement) to analyze the affective state of 95 visitors interacting physically or virtually (in a VR environment) with five handicraft objects belonging to the permanent collection of the Museo dell’Artigianato Valdostano di Tradizione, which is a traditional craftsmanship museum in the Valle d’Aosta region. Extreme Gradient Boosting (XGBoost) was adopted to classify the obtained engagement measures, which were labeled according to questionnaire replies. EEG analysis played a fundamental role in understanding the cognitive and emotional processes underlying immersive experiences, highlighting the potential of VR technologies in enhancing participants’ cognitive engagement. The results indicate that EEG-based indicators have common trends with self-assessment, suggesting that their use as ‘the ground truth of emotion’ is a viable option.
Fusing LiDAR Data and Aerial Imagery for Building Detection Using a Vegetation-Mask-Based Connected Filter

Building detection is valuable for 3-D building reconstruction and urban management. In this letter, a vegetation mask-based connected filter (VMCF) algorithm is proposed to discriminate building regions from light detection and ranging (LiDAR) data using the following steps. First, digital surface model (DSM) data are obtained by the interpolation of a LiDAR point cloud, and a top-hat transform is introduced to remove outliers. Second, a vegetation mask is derived by using the entropy and normalized difference vegetation index extracted from the DSM and aerial imagery, respectively. Third, a stack of nested binary images is generated by slicing the DSM data into different levels, and in each level, the connected components are acquired by using vegetation-mask-based connected analysis. Finally, a tree structure is constructed using a max-tree algorithm, and then building regions are derived by analyzing the area difference of the corresponding nodes of the tree in adjacent levels. The proposed VMCF algorithm is validated using three test areas provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation. The experimental results show that building regions in the LiDAR data can be effectively detected by the proposed method, and the detection rates of three test areas are 89%, 91.8%, and 90.9%, respectively.
High-throughput mRNA sequencing of stromal cells from endometriomas and 1 endometrium

Tartu, Tartu, Estonia; 8 2 Competence Centre on Health Technologies, Tartu, Estonia; 9 3 Institute of Computer Science, University of Tartu, Tartu, Estonia; 10 4 Estonian Genome Center, University of Tartu, Tartu, Estonia; 11 5 Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia; 12 6 Tartu University Hospital’s Women’s Clinic, Tartu, Estonia; 13 7 Institute of Biomedicine and Translational Medicine, Department of Biomedicine, 14
Identifying Optimal Nanofluid Synthesis Conditions for Applications in Solar Thermal Concentrators

: For solar thermal applications, a novel idea is to employ directly radiation-absorbing working fluids to completely replace metallic receiver tubes. Advances in nanotechnology has enabled development of nanofluids, an optimized mix of nanoparticles (NPs) and a base fluid, which can absorb a large proportion of the solar spectrum. A nanofluid comprising of carbon NPs in ethylene glycol has been synthesized for solar thermal applications. The method of preparation and sonication conditions have been studied to evaluate their effect on nanofluid stability and its solar absorptivity. Nanofluid with a NP concentration of 40-300 mg/l was synthesized by adding a surfactant (Sodium dodecyl sulfate) and carbon NPs (<100 nm) in ethylene glycol followed by sonication for different durations (up to 60 min). Transmittance of the nanofluid was measured using UV-vis spectrophotometer after preparation and at pre-determined time intervals to evaluate the effect of sonication duration. Solar absorptivity of nanofluid was found to increase with increasing NP concentration. Sonication time of 60 min was found to be sufficient to form a uniform suspension with low transmittance (and therefore, high absorptivity). Continuous stirring maintained the nanofluid optical performance for longer durations with negligible changes in solar absorptivity. The optimal conditions for synthesizing a stable nanofluid for longer durations have been identified and are described here.
Socioeconomic inequalities in metabolic syndrome and its components in a sample of Iranian Kurdish adults

OBJECTIVES The worldwide incidence of metabolic syndrome (MetS) has increased in recent decades. In this study, we investigated the socioeconomic inequalities associated with MetS and its components in a sample of the Iranian Kurdish population. METHODS We used data from 3,996 participants, aged 35 years to 70 years, from the baseline phase of the Dehgolan Prospective Cohort Study (February 2018 to March 2019). The concentration index and concentration curve were used to measure inequality and the Blinder-Oaxaca decomposition method was used to examine the contribution of various determinants to the observed socioeconomic inequality in MetS and its components. RESULTS The prevalence of MetS was 34.44% (95% confidence interval [CI], 32.97 to 35.93). The prevalence of MetS was 26.18% for those in the highest socioeconomic status (SES), compared with 40.51% for participants in the lowest SES. There was a significant negative concentration index for MetS (C=-0.13; 95% CI, -0.16 to -0.09), indicating a concentration of MetS among participants with a lower SES. The most prevalent component was abdominal obesity (59.14%) with a significant negative concentration index (C=-0.21; 95% CI, -0.25 to -0.18). According to decomposition analysis, age, gender, and education were the highest contributing factors to inequality in MetS and its components. CONCLUSIONS This study showed socioeconomic inequality in MetS. People with a low SES were more likely to have MetS. Therefore, policymakers and health managers need to develop appropriate strategies to reduce these inequalities in MetS across age groups, genders, and education levels, especially among women and the elderly.
Chapter 2 An Overview of the Synthesis of Nanomaterials

Nanomaterials have distinguished themselves as an outstanding class of materials with at least one dimension falling between 1 and 100 nm. The logical design of nanoparticles allows exceptionally high surface area. It is possible to create nanomaterials with exceptional magnetic, electrical, mechanical, optical, and catalytic capabilities that differ significantly from their bulk counterparts. By carefully regulating the size, shape, synthesis conditions, and appropriate functionalization, the properties of nanomaterials can be tailored to meet specific needs. This chapter highlights the particular characteristics of nanomaterials. We specifically outline and define terminologies associated with nanomaterials. The discussion covers a range of nanomaterial synthesis techniques, including top-down and bottom-up methods.
Palatability of glyphosate in ants: a field experiment reveals broad acceptance of 1 highly polluted solutions in a Mediterranean ant 2

22 23 Glyphosate is a systemic herbicide still used in many countries, though there are several known 24 detrimental effects on animals. Previous studies concerning its effects on social insects are 25 available, but they are primarily focused on honeybees; little is known about the interactions of this 26 compound with ants. Here, we assessed whether different concentrations of glyphosate can be 27 perceived by ant workers and to what extent. As a model species, we used the Mediterranean ant 28 Crematogaster scutellaris , commonly found in agroecosystems. We performed 3,000 individual 29 tests of acceptance using ten different solutions of various concentrations of the herbicide. Half of 30 the solutions contained added sucrose in order to test the possible masking effect of the sugar taste 31 on glyphosate. We used comparable glyphosate concentrations to those previously used in other 32
Survival Analysis and Contributing Factors among PCR-Confirmed Adult Inpatients during the Endemic Phase of COVID-19

In May 2023, the global health emergency status of COVID-19 concluded, marking the onset of an endemic era. This study assessed survival rates among PCR-confirmed adult inpatients during this phase and determined contributing factors. Employing a survival analysis approach, this investigation utilized a nationwide Mexican cohort encompassing 152 adult inpatients. Survival rates were computed using the Kaplan–Meier method, and a proportional Cox model identified mortality risk factors. Survival rates remained above 65% on day 14 after admission. Vaccination status, including the number of doses administered, was not significantly associated with fatal outcomes. Chronic kidney disease or a history of immunosuppression (due to any cause) increased mortality risk. Our findings underscore the persistent severity of COVID-19 beyond the global health emergency, emphasizing the necessity for tailored interventions for vulnerable patients.
Does Monetary Policy Affect the Central Bank's Role in Bank Supervision?

This paper examines whether monetary policy responsibilities alter the central bank's role as a bank supervisor. The analysis focuses on the U.S., where the FED shares supervisory duties with two other federal agencies, namely the OCC and the FDIC. Among these three institutions, the FED is the only one responsible for monetary policy. Hence, using banks supervised by the FDIC and the OCC as a control group, the FED's supervisory behavior is compared with the other two agencies. The comparison is made using a new panel dataset that includes all insured commercial and savings banks in the U.S., and all formal regulatory actions issued against these institutions during the period 1990:I- 1998:IV. The results suggest that the FED's monetary policy duties do alter its role in bank supervision: indicators of monetary policy affect the supervisory actions of the FED, but do not affect the actions of the other two agencies. However, the scenario in which the FED uses bank supervision to reinforce the objectives of monetary policy is rejected.