Miracle-dz/UniFAR-FTUs huggingface dataset:
An Advancing Front Meshing Algorithm Using NURBS for Semiconductor Process Simulation

A surface extraction algorithm with NURBS has been developed for the mesh generation from the scattered data after a cell-based simulation. The triangulation of a surface is initiated with a step of describing the geometry along the polygonal boundary with multiple points. In this work, an NURBS surface can be generated with scattered data for each polygonal surface by employing a multilevel B-spline surface approximation. The NURBS mesh in accordance with our algorithm excellently represents the surface evolution of the topography on the wafer. A dynamically allocated topography model, so-called cell advancing model, is proposed to resolve an extensive memory requirement for the numerical simulation of a complicated structure on the wafer. A concave cylindrical DRAM cell capacitor was chosen to test the capability of our model. A set of capacitance present in the cell capacitor and interconnects was calculated with three-dimensional tetrahedral meshes generated from the NURBS surface on CRAY T3E supercomputer. A total of 5,475,600 (130 × 156 × 270) cells was employed for the simulation of semiconductor regions comprising four DRAM cell capacitors with a dimension of 1.3 μm × 1.56 μm × 2.7 μm. The size of the required memory is about 22 Mbytes and the simulation time is 64,082 seconds. The number of nodes for the FEM calculation was 70,078 with 395,064 tetrahedrons. key words: NURBS surface, mesh generation, advancing front,
A 1.4 GHz-2 GHz wideband CMOS class-E power amplifier delivering 23 dBm peak with 67% PAE

The design of CMOS power amplifiers (PA) is still a challenging issue. Efficiency is one of the key requirements, but it is usually obtained at the expense of large device stress. The latter can be reduced by introducing a cascode solution, which features an efficiency penalty due to dissipative mechanisms associated with MOS capacitive parasitics, overlooked up to date. A class-E PA is proposed which allows simultaneously high efficiency and reduced stress by means of an integrated inductor tuning out the parasitic. Prototypes, realized in a 0.13 /spl mu/m CMOS technology, demonstrate 67% PAE while delivering 23 dBm peak power at 1.7 GHz. PAE is still above 60% within the range 1.4-2 GHz.
Epitope Identification and Application for Diagnosis of Duck Tembusu Virus Infections in Ducks

Duck Tembusu virus (DTMUV) causes substantial egg drop disease. DTMUV was first identified in China and rapidly spread to Malaysia and Thailand. The antigenicity of the DTMUV E protein has not yet been characterized. Here, we investigated antigenic sites on the E protein using the non-neutralizing monoclonal antibodies (mAbs) 1F3 and 1A5. Two minimal epitopes were mapped to 221LD/NLPW225 and 87YAEYI91 by using phage display and mutagenesis. DTMUV-positive duck sera reacted with the epitopes, thus indicating the importance of the minimal amino acids of the epitopes for antibody-epitope binding. The performance of the dot blotting assay with the corresponding positive sera indicated that YAEYI was DTMUV type-specific, whereas 221LD/NLPW225 was a cross-reactive epitope for West Nile virus (WNV), dengue virus (DENV), and Japanese encephalitis virus (JEV) and corresponded to conserved and variable amino acid sequences among these strains. The structure model of the E protein revealed that YAEYI and LD/NLPW were located on domain (D) II, which confirmed that DII might contain a type-specific non-neutralizing epitope. The YAEYI epitope-based antigen demonstrated its diagnostic potential by reacting with high specificity to serum samples obtained from DTMUV-infected ducks. Based on these observations, a YAEYI-based serological test could be used for DTMUV surveillance and could differentiate DTMUV infections from JEV or WNV infections. These findings provide new insights into the organization of epitopes on flavivirus E proteins that might be valuable for the development of epitope-based serological diagnostic tests for DTMUV.
Comparative analysis of short-term variability of RR and QT intervals for the assessment of autonomic nerve activity

The purpose of this study is to investigate the behavior of autonomic nervous system (ANS), reflected by short-term variability (STV), in the hemodialysis patients with high risk for cardiac arrhythmias and sudden cardiac death. Comparison was performed with normal people. The data were provided by THEW (database ESRD and Normal). STV of RR intervals (STVRR) and QT intervals (STVQT) as well as the ratio of them (STVQT/RR) were calculated using 30 consecutive beats. Two resting episodes lasting 1 h were selected in each Holter record, one by day, the other at night. For each 1 h interval series, a sliding window with width of 30 beats was implemented and indexes of each sliding window within the episode were averaged as the feature indexes (MSTVRR, MSTVQT and MSTVQT/RR) of this episode. Results showed that MSTVRR in ESRD was much lower than that in Normal. Though the level of MSTVQT/RR by day was comparable in these two groups, there existed significantly increased MSTVQT/RR at night in ESRD. The decreased heart rate variability (HRV) and increased MSTVQT/RR at night suggest the sympathetic overactivity in ESRD. Comparative analysis of HRV and QT variability using Holter data might be a potential approach to get information of ANS modulation.
Incremental Line-based 3D Reconstruction using Geometric Constraints

Generating accurate 3D models for man-made environments can be a challenging task due to the presence of texture-less objects or wiry structures. Since traditional point-based 3D reconstruction approaches may fail to integrate these structures into the resulting point cloud, a different feature representation is necessary. We present a novel approach which uses point features for camera estimation and additional line segments for 3D reconstruction. To avoid appearance-based line matching, we use purely geometric constraints for hypothesis generation and verification. Therefore, the proposed method is able to reconstruct both wiry structures as well as solid objects. The algorithm is designed to generate incremental results using online Structure-from-Motion and linebased 3D modelling in parallel. We show that the proposed method outperforms previous descriptor-less line matching approaches in terms of run-time while delivering accurate
Mild Salt Stress Conditions Induce Different Responses in Root Hydraulic Conductivity of Phaseolus vulgaris Over-Time

Plants respond to salinity by altering their physiological parameters in order to maintain their water balance. The reduction in root hydraulic conductivity is one of the first responses of plants to the presence of salt in order to minimize water stress. Although its regulation has been commonly attributed to aquaporins activity, osmotic adjustment and the toxic effect of Na+ and Cl− have also a main role in the whole process. We studied the effects of 30 mM NaCl on Phaseolus vulgaris plants after 9 days and found different responses in root hydraulic conductivity over-time. An initial and final reduction of root hydraulic conductivity, stomatal conductance, and leaf water potential in response to NaCl was attributed to an initial osmotic shock after 1 day of treatment, and to the initial symptoms of salt accumulation within the plant tissues after 9 days of treatment. After 6 days of NaCl treatment, the increase in root hydraulic conductivity to the levels of control plants was accompanied by an increase in root fructose content, and with the intracellular localization of root plasma membrane aquaporins (PIP) to cortex cells close to the epidermis and to cells surrounding xylem vessels. Thus, the different responses of bean plants to mild salt stress over time may be connected with root fructose accumulation, and intracellular localization of PIP aquaporins.
ANALYSIS OF LOAD BALANCERS IN CLOUD COMPUTING

Cloud Computing is high utility software having the ability to change the IT software industry and making the software even more attractive. It has also changed the way IT companies used to buy and design hardware. The elasticity of resources without paying a premium for large scale is unprecedented in the history of IT industry. The increase in web traffic and different services are increasing day by day making load balancing a big research topic. Cloud computing is a new technology which uses virtual machine instead of physical machine to host, store and network the different components. Load balancers are used for assigning load to different virtual machines in such a way that none of the nodes gets loaded heavily or lightly. The load balancing needs to be done properly because failure in any one of the node can lead to unavailability of data.
Using Wi-Fi Signal Strength to Localize in Wireless Sensor Networks

Wireless sensor network (WSN) is widely used in many applications such as localization and real-time tracking system. Previous researches commonly suffer the line-of-sight (LOS) problem and dependence on contrast of the background light intensity. Location Fingerprinting (LF) method uses a training dataset of received signal strength (RSS) at different location to track the target. The drawbacks of LF method are needed to have extensive training dataset surveying and highly affected by the changing of internal building infrastructure. In this paper, a sensor-based LF method will be implemented to replace extensive site-surveying. Using a Kalman Filter tracks multiple points to characterize a trajectory. Our experimental result shows that the effectiveness of our method leads to have more accurate and effective tracking system.
Effects of fatigue and surface instability on neuromuscular performance during jumping

It has previously been shown that fatigue and unstable surfaces affect jump performance. However, the combination thereof is unresolved. Thus, the purpose of this study was to examine the effects of fatigue and surface instability on jump performance and leg muscle activity. Twenty elite volleyball players (18 ± 2 years) performed repetitive vertical double‐leg box jumps until failure. Before and after a fatigue protocol, jump performance (i.e., jump height) and electromyographic activity of selected lower limb muscles were recorded during drop jumps (DJs) and countermovement jumps (CMJs) on a force plate on stable and unstable surfaces (i.e., balance pad on top of force plate). Jump performance (3–7%; P < 0.05; 1.14 ≤ d ≤ 2.82), and muscle activity (2–27%; P < 0.05; 0.59 ≤ d ≤ 3.13) were lower following fatigue during DJs and CMJs, and on unstable compared with stable surfaces during DJs only (jump performance: 8%; P < 0.01; d = 1.90; muscle activity: 9–25%; P < 0.05; 1.08 ≤ d ≤ 2.54). No statistically significant interactions of fatigue by surface condition were observed. Our findings revealed that fatigue impairs neuromuscular performance during DJs and CMJs in elite volleyball players, whereas surface instability affects neuromuscular DJ performance only. Absent fatigue × surface interactions indicate that fatigue‐induced changes in jump performance are similar on stable and unstable surfaces in jump‐trained athletes.
Home and School Environmental Influences on Adolescents’ Sociopolitical Group Participation: Implications for Increasing Youth Involvement

The potential benefits associated with sociopolitical group involvement for participating youth have been well documented in the existing literature. Yet, little is known about what motivates voluntary participation in such programs among youth. The purpose of this study is to explore what environmental factors influence youth civic engagement through participation in sociopolitical groups (e.g., service-learning or community service programs). To do this, several independent variables captured in The Commission on Youth Voting and Civic Knowledge Youth Post Election Survey 2012 dataset and the respondents’ reported participation in social or political groups while in high school were observed. Binary and ordinal logistic regression modeling were used to analyze the data. The results indicate that several factors in the home and school environment are related to an increased probability of youth joining a sociopolitical group at school, away from school, or both. These findings suggest that the messages crafted to encourage youth participation in sociopolitical groups should account for the demographic (i.e., racial, gender, and cultural) and experiential (i.e., civics education quality) differences present within the target population.
The system performance of wireless CSMA/CA protocol with capture effect

This work presents a deterministic channel that rules according to inverse α power propagation law. The proposed channel model allows us to derive the lower bound and upper bound of packet's capture probability in Rayleigh fading and shadowing cellular mobile system. According to these capture probabilities, we analyze the system performance in the case of finite stations and finite communicated coverage of a base station. We also adopted a dynamic backoff window size to discuss the robustness of IEEE 802.11 draft standard. Some suggestions and conclusions from numerical results are given to establish the more strong CSMA/CA protocol.
On the Analysis of Diseases and Their Related Geographical Data

Electronic medical records (EMRs) store data related to patients information enrolled during their stay in health structures. Data stored into EMRs span from data crawled from biological laboratories to textual description of diseases and diagnostic device results (e.g., biomedical images). Each EMR is related to a diagnosis related group (DRG) record. A DRG record is a record associated with a citizen that has been cured in a hospital. It contains a code, called major diagnostic category (MDC), which summarizes the treated disease and allows to reimburse costs related to patient treatments during his staying in health structures. DRGs are used for administrative process (e.g., costs and reimbursement management) as well as disease monitoring. Associating diagnostic codes with external information (such as environmental and geographical data) and with information filtered from EMRs (e.g., biological results or analytes values) can be useful to monitor citizens wellness status. We propose a methodology to analyze such data based on a multistep process. First, we cross reference data by using a semantics-based clustering procedure, extract information from EMRs, and then, cluster them by looking for similar patterns of diseases. Then, biological records in each disease cluster are analyzed to evaluate intracluster similarity by selecting analytes typologies and values. Finally, biological data is related to diagnosis codes and geometrically projected in areas of interest in order to map calculated outlier patients. We applied the methodology on two case studies: 1) diagnosis codes and biochemical analytes of 20 000 biological analyses about hospitalized patients during one observation year and 2) the correlation between cardiovascular diseases and water quality in a southern Italian region. Preliminary findings show the effectiveness of our method.
Practising Physical Activity Following Weight-Loss Surgery: The Significance of Joy, Satisfaction, and Well-Being

Abstract While health care professionals advise those who have undergone weight loss surgery (WLS) to increase their levels of physical activity, research suggests that often this is not achieved. This paper explores the experiences of ten Norwegian women as they engaged in physical activity several years after weight loss surgery (WLS). In contrast to the existing literature, which explores physical activity post-WLS largely in terms of quantitative data and measurable outcomes, the present study sought to explore women’s lived experiences of physical activity, including the meanings they ascribed to different forms of activity and how such meanings changed over time. The research participants, all of whom had undergone WLS more than five years earlier, described (during individual interviews) the meanings they attached to becoming physically active, as well as the different activities and movement practices they engaged in, from interval training to mountain hiking and yoga. For all the women, maintaining and increasing their level of physical activity was challenging. On the one hand, engaging in exercise after weight loss improved their sense of joy and well-being and expanded their opportunities to move and act. On the other hand, during physical activity they needed to be constantly alert to symptoms of post-surgical side-effects, including variable energy levels, digestive problems and acute illness episodes. As the women explored their new capacities, it seemed to be important for them to explore various forms of physical activity in order to find the form of exercise which best suited them or which they most enjoyed. In some cases, they constructed new meanings around activities which, prior to surgery, had seemed onerous and bereft of pleasure. We argue that such insights will benefit health professionals who provide advice on physical activity at different post-surgical stages, sometimes to persons seriously concerned about regaining weight.
Fine-tuning HMMS for nonverbal vocalizations in spontaneous speech: A multicorpus perspective

Phenomena like filled pauses, laughter, breathing, hesitation, etc. play significant role in everyday human-to-human conversation and have a significant influence on speech recognition accuracy [1]. Because of their nature (e. g. long duration), they should be modeled with different number of emitting states and Gaussian mixtures. In this paper we address this question and try to determine the most suitable method for finding these parameters: we provide an examination of two methods for optimization of hidden Markov model (HMM) configurations for better classification and recognition of nonverbal vocalizations within speech. Experiments were conducted on three conversational databases: TUM AVIC, Verbmobil, and SmartKom. These experiments show that with HMMs configurations tailored to a particular database we can achieve 1-3% improvement in speech recognition accuracy with comparison to a baseline topology. An in-depth analysis of discussed methods is provided.
Theme-Based Query Expansion by Mining Log Data

Queries committed to the search engines are usually short. They usually contain insufficient information to the IR system. Previous research has proposed the utilization of query expansion to deal with this problem. However, expansion terms are usually determined on term co-occurrences within documents. Sometimes the expansion terms don't represent the user's real intent. In this study, we propose a novel method for query expansion based on mining the user's intent through the click-through data. The users log builds the bridge between the queries and the user's intent. The experimental results show that the theme-based query expansion method can produce much better results than the classical search method.
Comparison of absolute and relative strategies to encode sensorimotor transformations in tool-use

We explore different strategies to overcome the problem of sensorimotor transformation that babies face during development, especially in the case of tool-use. From a developmental perspective, we investigate a model based on absolute coordinate frames of reference, and another one based on relative coordinate frames of reference. In a situation of sensorimotor learning and of adaptation to tool-use, we perform a computer simulation of a 4 degrees of freedom robot. We show that the relative coordinate strategy is the most rapid and robust to re-adapt the neural code.
ORIGAMI - Folded Plate Structures, Architecture

This research proposes new methods to generate rapidly complex folded plate structures that can be built with cross laminated timber panels. Composition and dimensions of these panels as well as the possibility to mill them by Computer Numerically Controlled machines, show a great potential for surface structures. The aim of this research is to reveal this potential in the domain of folded plate structures. An interdisciplinary team investigates architectural, structural and mathematical aspects of folded plate structures built from cross laminated timber panels. The main concern of the architectural part is the form finding process witch is inspired by Origami, the Japanese art of paper folding. Based on a simple technique, Origami gives birth to an astonishing formal richness and variability. Complex geometries are generated in an economic way and this research aims at transposing these principles to construction with timber panels.
Trading Cores for Memory Bandwidth in Real-Time Systems

Federated scheduling has been proposed for parallel tasks. In this scheduling scheme, each parallel task is a assigned a private set of cores whereas sequential tasks share the remaining set of cores. Since parallel tasks are assigned dedicated cores, they receive no interference from other tasks. However, multicore processors are commonly built with shared main memory. The memory bandwidth is limited and therefore subject to contention. Consequently, parallel tasks can interfere with each other through the shared main memory. In this paper, we propose a novel method that is memory-aware when assigning cores to tasks. Our experimental results show a significant advantage of our method with respect to memory- oblivious methods.
Update and repair of a roadmap after model error discovery

Roadmaps, generated by pre-processing of the known environment, have been a popular approach to robot motion planning. Generally designed for static environments, roadmaps are often invalidated by any anomaly between the real world and the model of the environment. We investigate the effect on roadmaps when sensor information indicates such an error and describe an algorithm which, by performing further pre-processing on the known environment, generates a mapping between points in the workspace and the road map. Used during on-line planning the mapping enables a valid, although not necessarily connected, roadmap to be maintained if such an error is discovered. We then present a divide and conquer algorithm which uses guided random motion to attempt to reconnect paths affected by the error. This is the first step towards a global planner that could be used in evolving environments.
Knowledge Reengineering and Reusing Based on Ontology in Online Organizational Discussion

Hall for Workshop of Metasynthetic Engineering (HWME), a newly burgeoning GDSS based on web, supplies an organizational decision situations supported by online resources (analysis and computing tools, information from web, etc.) and aims at making decision on problems related to Open Complex Giant Systems(OCGS). This paper focuses on the knowledge reengineering and reusing in online organizational discussion in HWME To facilitate knowledge reengineering knowledge ontologies based on roles and functions in online organizational discussion is analyzed deeply. Then, a new method of knowledge reengineering and reusing based on roles and functions in online organizational discussion is proposed. To illustrate the structure of ontologies, we give a suppositional example of macroeconomics forecasting designed by economists.
Modules as gradually-typed objects

Grace is a gradually typed, object-oriented language for use in education. Grace needs a module system for several reasons: to teach students about modular program design, to organise large programs, especially its self-hosted implementation, and to provide access to resources defined in other languages. Grace uses its basic organising construct, objects, to provide modules, and is then able to use its gradual structural typing to obtain a number of interesting features without any additional mechanisms.