Miracle-dz/UniFAR-FTUs huggingface dataset:
Process and Temperature Compensation of CMOS Ring Oscillators

In order to compensate RO's process, temperature and voltage variations (PVT) several CMOS effects have been studied such as VT sensing and Zero Temperature Coefficient (ZTC). A single-ended RO topology was analysed taking into consideration theoretical studies, PVT behavior and sensitivity to control and supply voltage. The techniques used to obtain these characterizations helped to obtain, organize and classify data in a efficient and scalable manner. The modified false-position method was implemented to characterize the RO PVT behavior efficiently for a given target oscillation frequency, allowing to explore different RO's and specific transistor influence. For classification a coefficient of determination, pronounced R squared, was implemented allowing to know the goodness of fit of a line for instance RO's control voltage, and find straight, parallel and evenly spaced lines. Analysis of the supply and control voltage sensitivity to a variation was made allowing good error prediction and a clear way for correctly knowing how to compensate variations. An ideal topology was developed for matching two sets of those lines with similar features on different circuits, containing gain, offset and coefficient of temperature.The final topology includes two Bandgap voltage references, a simple VT extractor, a Differential Amplifier and a single-end RO.
Transfer Learning for Sentiment Analysis Using BERT Based Supervised Fine-Tuning

The growth of the Internet has expanded the amount of data expressed by users across multiple platforms. The availability of these different worldviews and individuals’ emotions empowers sentiment analysis. However, sentiment analysis becomes even more challenging due to a scarcity of standardized labeled data in the Bangla NLP domain. The majority of the existing Bangla research has relied on models of deep learning that significantly focus on context-independent word embeddings, such as Word2Vec, GloVe, and fastText, in which each word has a fixed representation irrespective of its context. Meanwhile, context-based pre-trained language models such as BERT have recently revolutionized the state of natural language processing. In this work, we utilized BERT’s transfer learning ability to a deep integrated model CNN-BiLSTM for enhanced performance of decision-making in sentiment analysis. In addition, we also introduced the ability of transfer learning to classical machine learning algorithms for the performance comparison of CNN-BiLSTM. Additionally, we explore various word embedding techniques, such as Word2Vec, GloVe, and fastText, and compare their performance to the BERT transfer learning strategy. As a result, we have shown a state-of-the-art binary classification performance for Bangla sentiment analysis that significantly outperforms all embedding and algorithms.
Photo-Crosslinked Hyaluronic Acid/Carboxymethyl Cellulose Composite Hydrogel as a Dural Substitute to Prevent Post-Surgical Adhesion

A dural substitute is frequently used to repair dura mater during neurosurgical procedures. Although autologous or commercially available dural substitutes matched most of the requirements; difficulties during dural repair, including insufficient space for suturing, insufficient mechanical strength, easy tear and cerebrospinal fluid leakage, represent major challenges. To meet this need, a photo-crosslinked hydrogel was developed as a dural substitute/anti-adhesion barrier in this study, which can show sol-to-gel phase transition in situ upon short-time exposure to visible light. For this purpose, hyaluronic acid (HA) and carboxymethyl cellulose (CMC), materials used in abdominal surgery for anti-adhesion purposes, were reacted separately with glycidyl methacrylate to form hyaluronic acid methacrylate (HAMA) and carboxymethyl cellulose methacrylate (CMCMA). The HA/CMC (HC) hydrogels with different HA compositions could be prepared by photo-crosslinking HAMA and CMCMA with a 400 nm light source using lithium phenyl-2,4,6-trimethylbenzoylphosphinate as a photo-initiator. From studies of physico-chemical and biological properties of HC composite hydrogels, they are bio-compatible, bio-degradable and mechanically robust, to be suitable as a dural substitute. By drastically reducing attachment and penetration of adhesion-forming fibroblasts in vitro, the HC hydrogel can also act as an anti-adhesion barrier to prevent adhesion formation after dural repair. From in vivo study in rabbits, the HC hydrogel can repair dural defects as well as protect the dura from post-operative adhesion, endorsing the possible application of this hydrogel as a novel dural substitute.
Representation and reward: the left-wing anti-globalization alliance, contributions, and the congress

Abstract Left-wing opposition to globalization lives, among voters and interest groups, both labor and progressive. But have left-wing opponents of trade successfully cultivated representation? Using the US Congress as a case, I show that two distinct groups of Democrats vote in characteristically progressive and protectionist ways on trade bills. These groups, especially progressives, are rewarded with excess campaign contributions from publicly anti-trade groups. A dyadic research design shows that interest group/representative relationships degrade noticeably when members of Congress vote for trade bills that interest groups have opposed. While recent events have highlighted business interests and right-wing economic populism, left-wing opposition to globalization remains a vibrant third face of contemporary domestic contestation over trade that will be especially important where populists fade.
Plants, soil properties and microbes directly and positively drive ecosystem multifunctionality in a plantation chronosequence

Chinese fir (Cunninghamia lanceolata) is the main plantation species in the subtropical region of China. However, the shift in ecosystem multifunctionality with stand development remains largely unexplored for these plantations. This study used a chronosequence to investigate the variations of ecosystem multifunctionality by employing individual functions and identified its driving factors in Chinese fir plantations. The findings provide strong evidence that the individual functions of carbon stocks, water regulation and wood production increased with stand ages, but the tradeoff of individual functions did not significantly increase ecosystem multifunctionality. Soil microbial parameters (the abundances of bacteria, fungi and actinomycete), soil properties (soil moisture, total carbon and total nitrogen), and plant parameters (the shrub layer cover and total understory cover) exhibited positive correlations with ecosystem multifunctionality. The structural equation model revealed that plants, soil properties and microbes pathways explained 83% of the total variance in ecosystem multifunctionality. Results showed that plants, soil microbes and properties directly and significantly affected ecosystem multifunctionality with path coefficients of 0.404, 0.487 and 0.334, respectively. Soil microbes were identified as the top direct predictor for ecosystem multifunctionality, while plant and soil properties had strong direct and positive effects on ecosystem multifunctionality. These results verified that soil microbes, plants and soil properties directly and positively regulated ecosystem multifunctionality. Our findings demonstrate that ecosystem multifunctionality should be considered as a comprehensive ecological indicator for ecosystem services and functions, and sustainable plantation management. This study highlights the importance of conserving soil microbes for maintaining multifunctionality in Chinese fir plantations.
Handbook of Offshore Oil and Gas Operations

Description: Handbook of Offshore Oil and Gas Operations is an authoritative source providing extensive up-to-date coverage of the technology used in the exploration, drilling, production, and operations in an offshore setting. Offshore oil and gas activity is growing at an expansive rate and this must-have training guide covers the full spectrum including geology, types of platforms, exploration methods, production and enhanced recovery methods, pipelines, and envinronmental managment and impact, specifically worldwide advances in study, control, and prevention of the industry's impact on the marine environment and its living resources. In addition, this book provides a go-to glossary for quick reference. Handbook of Offshore Oil and Gas Operations empowers oil and gas engineers and managers to understand and capture on one of the fastest growing markets in the energy sector today. Quickly become familiar with the oil and gas offshore industry, including deepwater operations Understand the full spectrum of the business, including environmental impacts and future challenges Gain knowledge and exposure on critical standards and real-world case studies
You process content and I process context: Cross-platform divergence of retweetability between Twitter and Weibo

RESUME Artiklen undersoger forskelle i brugeres retweeting-adfaerd pa tvaers af platformene Twitter og Sina Weibo. Med en heuristisk-analytisk informationsbehandlingsmodel for retweeting, som udspringer af dual-proces-teori, rationaliserer denne undersogelse sammenligningen af brugeradfaerden for de to platforme pa basis af bruger-centrerede tvaerkulturelle kognitive forskelle. Resultaterne viser, at nar der traeffes beslutninger om, hvorvidt et indlaeg skal retweetes, er brugere pa Twitter mere tilbojelige til at anvende en analytisk strategi baseret pa informationsbehandling af indholdsfaktorer i sammenligning med brugere pa Weibo, der er mere tilbojelige til at benytte en heuristisk strategi baseret pa informationsbehandling af kontekstuelle faktorer. ABSTRACT This article examines the cross-platform divergence between Twitter and Sina Weibo in users’ retweeting behaviors. With a heuristic-analytic information-processing model of retweeting proposed on the basis of dual-process theory, this study rationalizes the cross-platform comparison by introducing user-centered cross-cultural cognitive differences. Results show that when making decisions about whether to retweet a post, users on Twitter are more likely to use an analytic strategy based on information processing of content factors compared to users on Weibo, who are more likely to adopt a heuristic strategy based on information processing of contextual factors.
APPLICATION OF MACHINE LEARNING FOR OBJECT DETECTION IN OBLIQUE AERIAL IMAGES

Abstract. At the time of continuous development of all technologies, deep machine learning (more precisely, convolutional neural networks), which is one of the branches of artificial intelligence (AI), has found wide application in many fields, including photogrammetry and remote sensing. One of the areas where a lot of research is conducted using these methods is the recognition of objects in aerial and satellite imagery. Through the application of deep learning algorithms and neural networks, it is possible to automate labour-intensive processes. However, while object detection in images using machine learning is popular for natural scenes and in recent years also for nadir aerial and satellite imagery, for aerial oblique imagery at the moment of this research there were relatively few publications on the subject. The challengeable task in object detection is the time-consuming generation of training datasets when access is limited or non-existent. This study proposed the methodology to automate this process with use of existing resources for transferring of references to new databases for training models for detect objects on aerial oblique images. The object detection was performed using the YOLOv3 neural network. Experiment results tested on two datasets have shown that the proposed method could realize the task of object detection in oblique aerial images.
3D DIGITIZATION OF TRANSPARENT AND GLASS SURFACES: STATE OF THE ART AND ANALYSIS OF SOME METHODS

Abstract. In the field of industrial metrology, there is a rising need for 3D information at a very high resolution for micro-measurements and quality control of transparent objects such as glass bottles (beer, wine, cola, cosmetics, etc.). However, such objects are particularly challenging for optical-based 3D reconstruction methods and systems such as photogrammetry, photometric stereo, structured light scanning, laser scanning, typically resulting in poor metrological performances. Indeed, these methods require the surface of the object to diffusely reflect the incoming light, which is not the case with the glass material where refraction and absorption phenomena do not permit their use. Over the years, various methods have been investigated and developed to avoid the coating (or powdering) treatment often used to make transparent objects opaque and diffusely reflecting. Most of the approaches require either some a priori knowledge of the transparent object or assumptions about how light interacts with the surface. This paper provides a general overview of state-of-the-art 3D digitization methods for optically non-cooperative surfaces featuring absorption, scattering, and refraction. The paper reviews research works summarizing them into four categories including shape-from-X, direct ray measurements, hybrid, and learning-based approaches. Moreover, we provided some 3D results to better highlight the advantages and disadvantages of each method in practice when dealing with transparent objects.
Systematic Surveillance of Rickettsial Diseases in 27 Hospitals from 26 Provinces throughout Vietnam

In Vietnam, the public health burden of rickettsial infections continues to be underestimated due to knowledge gaps in the epidemiology of these diseases. We conducted a systematic study among 27 hospitals from 26 provinces in eight ecological regions throughout Vietnam to investigate the prevalence, distribution, and clinical characteristics of rickettsial diseases. We recruited 1834 patients in the study from April 2018 to October 2019. The findings showed that rickettsial diseases were common among undifferentiated febrile patients, with 564 (30.8%) patients positive by qPCR for scrub typhus, murine typhus or spotted fever. Scrub typhus (484, 85.8%) was the most common rickettsial disease, followed by murine typhus (67, 11.9%) and spotted fever (10, 1.8%). Rickettsial diseases were widely distributed in all regions of Vietnam and presented with nonspecific clinical manifestations.
The Upper and Lower Body Aerobic Fitness of Semi-elite Rugby League Players

Objectives: The aim of this study was to measure the upper and lower body aerobic capacity of semi-elite Rugby League (RL) players. Methods: Twenty-two semi-elite RL players and 24 physically active but untrained men completed a maximal oxygen consumption test (VO2 max test) on a treadmill and electronic arm ergometer in a randomized order. Percent body fat was calculated from the sum of six skinfolds. Results: Lower and upper body absolute (P=0.03 and P=0.02 respectively) but not relative VO2 max was higher in the RL group compared to the control group. Upper body peak power (P=0.001), ventilation (P=0.05) and lactate concentration (P=0.03) were higher in the RL group compared to the control group. Maximum heart rate was lower during arm ergometry for both groups (P ≤ 0.001) compared to predicted and treadmill values. Conclusions: The results show that while semi-elite RL players have above average lower body aerobic capacity their upper body aerobic capacity is not well developed and similar to untrained men. Coaches and players need to implement separate and dedicated training programs to enhance the development of the upper body aerobic system in RL players. Upper body training should be based on maximal heart rate values achieved during upper body maximal testing.
Offer structure and design of the menu in hospitality industry

Purpose – Proper structure of menus, number of meals, information about the food and complete design to a large extent affect the selection of dishes by the customer and the entire business. This paper should show all the elements of relevance for structuring and designing of menus such as: balance, variety, composition, description, the accuracy of the menu, marking of menu, specification of items and sizes, then paper, font, colour, as important for the sale of food, in accordance with the theme of the restaurant. Methodology – The survey was conducted by direct and indirect collection of written bids (menus) in a la carte restaurants for food and drink throughout the Autonomous Province of Vojvodina (northern part of the R. Serbia). Collection was followed by systematization of data obtained by examining the sampled specimens according to the established methodology. The data were analyzed with descriptive statistics and presented graphically in this paper. Findings – The Research has shown that catering facilities do not have properly structured and designed menus, which is in line with all the theoretical principles and previously conducted researches in this field. Contribution – The data provide a general overview of the situation in the hospitality industry of Vojvodina and guidance on ways of elimination of all irregularities and an improvement of menu appeal for the guest. Proper structuring of menus, giving the required food information and design of menus can be critical in business of restaurants, and how to eliminate them will be shown in the paper.
Utilizing Structural Equation Modeling–Artificial Neural Network Hybrid Approach in Determining Factors Affecting Perceived Usability of Mobile Mental Health Application in the Philippines

Mental health problems have emerged as one of the biggest problems in the world and one of the countries that has been seen to be highly impacted is the Philippines. Despite the increasing number of mentally ill Filipinos, it is one of the most neglected problems in the country. The purpose of this study was to determine the factors affecting the perceived usability of mobile mental health applications. A total of 251 respondents voluntarily participated in the online survey we conducted. A structural equation modeling and artificial neural network hybrid was applied to determine the perceived usability (PRU) such as the social influence (SI), service awareness (SA), technology self-efficacy (SE), perceived usefulness (PU), perceived ease of use (PEOU), convenience (CO), voluntariness (VO), user resistance (UR), intention to use (IU), and actual use (AU). Results indicate that VO had the highest score of importance, followed by CO, PEOU, SA, SE, SI, IU, PU, and ASU. Having the mobile application available and accessible made the users perceive it as highly beneficial and advantageous. This would lead to the continuous usage and patronage of the application. This result highlights the insignificance of UR. This study was the first study that considered the evaluation of mobile mental health applications. This study can be beneficial to people who have mental health disorders and symptoms, even to health government agencies. Finally, the results of this study could be applied and extended among other health-related mobile applications worldwide.
League of Legends: An Application of Classification Algorithms to Verify the Prediction Importance of Main In-Game Variables

League of Legends is currently one of the most popular video games with a competitive scene involving regional and international tournaments. In this paper, we predict the result of competitive matches using information about games played between the years 2016 and 2020 in the most well-known regional and international leagues, such as the Brazilian League of Legends Championship and League of Legends Pro League. We used several different approaches to train our models based on different variable categories. First, we used economic variables registered in the first 10 and 15 minutes of each match. Then we considered variables that change only from the beginning to the end of the game and do not suffer interference before and after the game. The accuracy of classifiers such as KNearest Neighbors, Random Forest, and Decision Tree varied from 68.33% to 85.17%, depending on which variables were used to train the models.
Design Charts for Estimating Face Stand-Up Time in Soft Ground Tunnelling; TBM DiGs 2016, International Conference on Tunnel Boring Machines in Difficult Grounds; TBM DiGs 2016, International Conference on Tunnel Boring Machines in Difficult Grounds

ABSTRACT: Under unstable face conditions, inspections and maintenance work in the working chamber of EPBs or slurry shields have to be carried out under compressed air conditions. As hyperbaric interventions generally present operational disadvantages, the question often arises as to whether the face may be stable at least for the limited period of an intervention. In fact, if the ground exhibits a medium or low permeability, then the face – even if unstable in the long-term – may be stable for a practically significant period of time. Estimations of the stand-time of the face (i.e. the time lapsing from the beginning of the standstill until collapse) are thus important for assessing the feasibility of atmospheric interventions in the working chamber. Short-term stability can be traced back to excavation-induced negative excess pore pressures. Stability deteriorates over time due to excess pore pressure dissipation during the consolidation process. Instability occurs earlier or later depending on the permeability of the ground. In an on-going research project, the phenomenon of delayed failure was investigated in laboratory tests under controlled conditions; the experimental results can be reasonably reproduced using hydraulic-mechanical coupled spatial FEM analyses. Based upon a suite of such analyses, dimensionless design charts were worked out, which allow the stand-up time of a tunnel face to be estimated for a wide range of ground parameters and overburdens of between one and four tunnel diameters.
The Analysis of Cones within the Tianwen-1 Landing Area

On 15 May 2021, the Zhurong rover of China’s first Mars mission, Tianwen-1 (TW-1), successfully landed in southern Utopia Planitia on Mars. Various landforms were present in the landing area, and this area recorded a complex geological history. Cones are one of the typical landforms in the landing area and Utopia Planitia, and they have a great significance to the local geological processes due to the diversity of their origins. Using High-Resolution Imaging Camera (HiRIC) images collected by the TW-1 orbiter, we identified a total of 272 well-preserved circular cones in the landing area. Detailed surveys of their spatial distribution, morphological characteristics, and morphometric parameters were conducted. A preliminary analysis of the surface characteristics of these cones also provides additional information to strengthen our understanding of them. The results of the high-resolution topographic analysis show that the cone heights are in the range of 10.5–90.8 m and their basal diameters range from 178.9–1206.6 m. We compared the morphometric parameters of the cones in the landing area with terrestrial and Martian analogous features and found that our measured cones are consistent with the ranges of mud volcanoes and also a small subset of igneous origin cones. However, the result of spatial analysis is more favorable to mud volcanoes, and the lower thermal inertia of the cones in the landing area compared to their surrounding materials is also a typical characteristic of mud volcanoes. Based on current evidence and analysis, we favor interpreting the cones in the TW-1 landing area as mud volcanoes.