Miracle-dz/UniFAR-FTUs huggingface dataset:
Behavior Analysis of Si Etching Process with HF/HNO3 Mixture in Single-Spin Wafer Process

The HF/HNO3 mixture Si etching process is widely used to remove stress and damaged layers after Si wafer back grinding. Although there have been many reports on the dip process, there have been few detailed reports on the single-spin process. In a single spin process, Si etch rate distributions largely differ with different HF/HNO3 concentrations. On the other hand, thermal SiO2 etch rate distributions are similar even with different HF/HNO3 concentrations. In this work, we analyzed Si surfaces with XPS (X-ray Photoelectron Spectroscopy) after processing various HF/HNO3 mixture concentrations. SiOx stays steady in any wafer position and HNO3 concentration, whereas SiO2 thickens depending on HNO3 concentration at the center. We assumed that Si etch rate distributions were caused by HF or HNO3 consumption and confirmed this assumption was correct in a wafer center SiN cover experiment.
Joint Social, Energy and Transfer Rate to Select Cluster Heads in D2D Multicast Communication

Content sharing among users through Device-to-Device (D2D) multicast communication is an attractive solution to offload the mobile traffic. To achieve stable and effective sharing of content among nearby users, how to select D2D multicast cluster heads (DMCHs) is important. In this paper, a D2D multicast cluster head selection strategy based on Chinese Restaurant Process (CRP) is proposed. Firstly, in order to establish stable D2D multicast links, some requesting users (RUs) are classified as D2D multicast users (DMUs) taking account of their mobility. Secondly, to help the base station (BS) distributing data to DMUs effectively, DMCHs are selected from DMUs jointly considering DMUs' social attributes, available energy of their devices and the transfer rate from the BS to DMUs. At last, simulation results show that the proposed strategy can not only improve throughput, but also reduce the energy consumption and the transmission delay.
Development of Idea Generation Consistent Support System That Includes Suggestive Functions for Preparing Concreteness of Idea Labels and Island Names

In recent years, networking has spread substantially owing to the rapid developments made in Information & Communication Technology (ICT). It has also become easy to share highly contextual data and information, including ideas, among people. On the other hand, there exists information that cannot be expressed in words (tacit knowledge) and useful knowledge or know-how that is not shared well in an organization. The idea generation method enables the expression of explicit knowledge, which enables the expression of tacit knowledge by words, and can utilize explicit knowledge as know-how in organizations. We propose an idea generation consistent support system, GUNGEN-Web II. This system has suggestion functions for a concrete idea label and a concrete island name. The suggestion functions convey an idea and the island name to other participants more precisely. This system also has an illustration support function and a document support function. In this study, we aimed to improve the quality of the sentence obtained using the KJ method. We compared the results of our proposed systems with conventional GUNGEN-Web by conducting experiments. The results are as follows: The evaluation of the sentence of GUNGEN-Web II was significantly different to those obtained using the conventional GUNGEN-Web. key words: KJ method, groupware, framework level, Web base system
Study on Probability Estimation of Haze in Beijing Based Logistic Regression Model

The Logistic Regression Model of two categories is used to explore the relationship between haze and season, various meteorological factors such as air pressure, temperature, relative humidity, precipitation, wind direction and so on. Among all the factors, the relative humidity is best related to haze and season is in the second place. The odds of haze in winter are 17.87 times bigger than that in summer, 3.99 times bigger than that in spring. The odds of haze would increase by 48 percent averagely when the relative humidity increase by 10 percent.
Multiscale network analysis through tail-greedy bottom-up approximation, with applications in neuroscience

We propose the TGUH (Tail-Greedy Unbalanced Haar) transform for networks, which results in an orthonormal, adaptive decomposition of the network adjacency matrix into Haar-wavelet like components. The ‘tail-greediness’ of the algorithm — indicating multiple greedy steps are taken in a single pass through the data — enables both fast computation and consistent estimation of network signals. We focus on development of our multiscale network decomposition and a corresponding method for network signal denoising. Moreover, we establish consistency of our resulting denoising methodology, present numerical simulations illustrating compression, and illustrate through application to signals on diffusion tensor imaging (DTI) networks.
Leveraging Semantic Transformation to Investigate Password Habits and Their Causes

It is no secret that users have difficulty choosing and remembering strong passwords, especially when asked to choose different passwords across different accounts. While research has shed light on password weaknesses and reuse, less is known about user motivations for following bad password practices. Understanding these motivations can help us design better interventions that work with the habits of users and not against them. We present a comprehensive user study in which we both collect and analyze users' real passwords and the reasoning behind their password habits. This enables us to contrast the users' actual behaviors with their intentions. We find that user intent often mismatches practice, and that this, coupled with some misconceptions and convenience, fosters bad password habits. Our work is the first to show the discrepancy between user intent and practice when creating passwords, and to investigate how users trade off security for memorability.
The signal code structure selection in the communication channels in the wireless sensor networks

The algorithm of the signal code structure selection is proposed. The structure is optimum for the minimum criterion of the erroneous message transfer probability method under the conditions of the concentrated interferences in the channel and equipment signal distortions. The branch-and-bound method is realized. The effectiveness of this algorithm in computational complexity reduction in comparison with the methods of sequential sorting is shown for the parameters specific values of the distorted signal and interference.
Cellular Regulation of Amyloid Formation in Aging and Disease

As the population is aging, the incidence of age-related neurodegenerative diseases, such as Alzheimer and Parkinson disease, is growing. The pathology of neurodegenerative diseases is characterized by the presence of protein aggregates of disease specific proteins in the brain of patients. Under certain conditions these disease proteins can undergo structural rearrangements resulting in misfolded proteins that can lead to the formation of aggregates with a fibrillar amyloid-like structure. Cells have different mechanisms to deal with this protein aggregation, where the molecular chaperone machinery constitutes the first line of defense against misfolded proteins. Proteins that cannot be refolded are subjected to degradation and compartmentalization processes. Amyloid formation has traditionally been described as responsible for the proteotoxicity associated with different neurodegenerative disorders. Several mechanisms have been suggested to explain such toxicity, including the sequestration of key proteins and the overload of the protein quality control system. Here, we review different aspects of the involvement of amyloid-forming proteins in disease, mechanisms of toxicity, structural features, and biological functions of amyloids, as well as the cellular mechanisms that modulate and regulate protein aggregation, including the presence of enhancers and suppressors of aggregation, and how aging impacts the functioning of these mechanisms, with special attention to the molecular chaperones.
Predictive Validity of the Aviation Lights Test for Testing Pilots With Color Vision Deficiencies

Abstract : The color filters of the Farnsworth Lantern (FALANT) were changed to meet the Federal Aviation Administration s signal color specifications, thereby creating a job-sample color vision test called the Aviation Lights Test (ALT) that is used for secondary screening of air traffic control specialist applicants in the terminal option. The purpose of this experiment was two-fold: to determine whether the ALT could be used in place of the FALANT for testing pilots and whether the altered filters in the ALT (primarily, a more highly saturated red) improved its predictive validity with the criterion instrument called the signal light gun (SLG). The SLG is used by air traffic controllers to communicate with pilots in aircraft experiencing radio failure within the airport terminal area. Method. Participants were 145 individuals with moderate to strong red-green color vision deficiency, 10 individuals with minimal color vision anomalies, and 227 individuals with normal color vision, as classified by a Nagel anomaloscope. Participants identified 3 series of 9 pairs of colored lights of the FALANT and the ALT. A subset of 82 participants also identified the color-coded signals of the signal light gun test (SLGT). Results. The frequency of confusing white and green lights was similar for all tests; however, as predicted, errors involving red targets were reduced for the color deficient sample for the ALT relative to the FALANT. Compared with the FALANT, the use of signal colors in the ALT had little effect on cross-tabulated pass/fail outcomes with the SLGT, K(82)= . 70 and . 675. Conclusions. Results suggest that if the ALT is administered and scored with procedures identical to the FALANT, the incidence of passes and failures for pilots with color vision deficiencies will be essentially the same for the two tests.
Toxicity of multi-walled carbon nanotubes, graphene oxide, and reduced graphene oxide to zebrafish embryos.

OBJECTIVE This study was aimed to investigate the toxic effects of 3 nanomaterials, i.e. multi-walled carbon nanotubes (MWCNTs), graphene oxide (GO), and reduced graphene oxide (RGO), on zebrafish embryos. METHODS The 2-h post-fertilization (hpf) zebrafish embryos were exposed to MWCNTs, GO, and RGO at different concentrations (1, 5, 10, 50, 100 mg/L) for 96 h. Afterwards, the effects of the 3 nanomateria on spontaneous movement, heart rate, hatching rate, length of larvae, mortality, and malformations ls were evaluated. RESULTS Statistical analysis indicated that RGO significantly inhibited the hatching of zebrafish embryos. Furthermore, RGO and MWCNTs decreased the length of the hatched larvae at 96 hpf. No obvious morphological malformation or mortality was observed in the zebrafish embryos after exposure to the three nanomaterials. CONCLUSION MWCNTs, GO, and RGO were all toxic to zebrafish embryos to influence embryos hatching and larvae length. Although no obvious morphological malformation and mortality were observed in exposed zebrafish embryos, further studies on the toxicity of the three nanomaterials are still needed.
Forecasting Monthly Electricity Demands by Wavelet Neuro-Fuzzy System Optimized by Heuristic Algorithms

Electricity load forecasting plays a paramount role in capacity planning, scheduling, and the operation of power systems. Reliable and accurate planning and prediction of electricity load are therefore vital. In this study, a novel approach for forecasting monthly electricity demands by wavelet transform and a neuro-fuzzy system is proposed. Firstly, the most appropriate inputs are selected and a dataset is constructed. Then, Haar wavelet transform is utilized to decompose the load data and eliminate noise. In the model, a hierarchical adaptive neuro-fuzzy inference system (HANFIS) is suggested to solve the curse-of-dimensionality problem. Several heuristic algorithms including Gravitational Search Algorithm (GSA), Cuckoo Optimization Algorithm (COA), and Cuckoo Search (CS) are utilized to optimize the clustering parameters which help form the rule base, and adaptive neuro-fuzzy inference system (ANFIS) optimize the parameters in the antecedent and consequent parts of each sub-model. The proposed approach was applied to forecast the electricity load of Hanoi, Vietnam. The constructed models have shown high forecasting performances based on the performance indices calculated. The results demonstrate the validity of the approach. The obtained results were also compared with those of several other well-known methods including autoregressive integrated moving average (ARIMA) and multiple linear regression (MLR). In our study, the wavelet CS-HANFIS model outperformed the others and provided more accurate forecasting.
The Formation of Training and Occupational Safety Conditions as a Factor in the Creation of a Favorable Image of an Educational Organization

Intensive competition between educational organizations implies a shift in the perspective of studies aimed at investigating the creation of a favorable image of an educational organization from the external environment to the internal potential of higher educational institutions in the context of formation of optimal conditions for the training and occupational safety of employees and students. Therefore, the purpose of this study is to explore the system of occupational safety and training in Russian State Social University (RSSU) according to the following blocks: personnel, research and development, and infrastructure. Interviews, questionnaire surveys, and overt observations were used to determine the opinions of teachers (n=35) and students (n=140) in regards to the social and occupational phenomena related to the problem of creation of favorable labor and training conditions. The paper reveals the preferences of teachers and students in regards to the optimization of the RSSU image policy, formulates a strategic forecast of the optimization of training and occupational safety conditions, and gives recommendations regarding the creation of a favorable image of the RSSU.
Provider-Side VoD Content Delivery Using OpenFlow Multicast

IP based multicast is considered as the most efficient way to deliver data to multiple receivers at the same time with preserving high throughput, and hence, most of the IPTV system exploits IP based multicast protocol to deliver content especially between Super head end often called root node and Regional Head end called local nodes. With this protocol, the data transmission paths are determined by multicast tree which is constructed and maintained by each network router in distributed manner. Since each network router has no holistic network view and it is not aware of the entire network status, even though some local nodes encounter a drastic packet loss due to the network congestion, the multicast tree will still be maintained, and this in turn causes waste of network resources. OpenFlow is one of the enabling technologies to manage and control a network in a centralized and programmable manner by considering the current network status. Therefore, in this paper we take advantage of OpenFlow and propose a resource efficient “Provider-Side VoD Content Delivery method using OpenFlow multicast feature in IPTV network.
Effects of dietary assessment methods on assessing risk of nutrient intake adequacy at the population level: from theory to practice

The present study evaluated how applying different dietary methods affects risk assessment of inadequate intakes at the population level. A pooled analysis was conducted using data from two Spanish regional representative surveys both applying similar methodology with a total sample of 2615 individuals aged 12–80. Diet was assessed in the entire sample applying data from one 24 h recall (24HR), a mean of two non-consecutive 24HR, both crude and adjusted for intraindividual variability, and a FFQ. Intakes of vitamins A, C, E, thiamin, riboflavin, niacin, vitamin B6, vitamin B12, Fe, Mg, P and Zn were compared to the average nutrient requirement (ANR or estimated average requirement) in the entire sample and also excluding under-reporters applying the ANR cut-point method (and the probability approach for Fe). Higher percentages of intakes below the ANR were seen for 1–24HR and the mean of 2–24HR, except for nutrients with the highest rates of inadequacy (vitamins A, E, folate and Mg). For these micronutrients, higher percentages of inadequacy were obtained by adjusted 24HR data and the lowest with FFQ. For the remaining nutrients, adjusted data gave the lowest inadequacy percentages. The best concordance was seen between 2–24HR and 1–24HR as well as for adjusted 24HR, with the least observed between FFQ and the other methods. Exclusion of under-reporters considerably reduced inadequacy in both daily methods and FFQ. Crude daily data gave higher estimates of inadequate intakes than adjusted data or FFQ. Reproducibility of daily methods was also reasonably good. Results may differ depending on the micronutrient thus impeding reaching conclusions/recommendations common for all micronutrients.
Towards using musculoskeletal models for intelligent control of physically assistive robots

With the increasing number of robots being developed to physically assist humans in tasks such as rehabilitation and assistive living, more intelligent and personalized control systems are desired. In this paper we propose the use of a musculoskeletal model to estimate the strength of the user, from which information can be utilized to improve control schemes in which robots physically assist humans. An optimization model is developed utilizing a musculoskeletal model to estimate human strength in a specified dynamic state. Results of this optimization as well as methods of using it to observe muscle-based weaknesses in task space are presented. Lastly potential methods and problems in incorporating this model into a robot control system are discussed.
Improving the interface adherence at sealings in solid oxide cell stacks

Thermal cycling of planar solid oxide cell (SOC) stacks can lead to failure due to thermal stresses arising from differences in thermal expansion of the stack’s materials. The interfaces between the cell, interconnect, and sealing are particularly critical. Hence, understanding possible failure mechanisms at the interfaces and developing robust sealing concepts are important for stack reliability. In this work, the mechanical performance of interfaces in the sealing region of SOC stacks is studied. Joints comprising Crofer22APU (preoxidized or coated with MnCo_2O_4 or Al_2O_3) are sealed using V11 glass. The fracture energy of the joints is measured, and the fractured interfaces are analyzed using microscopy. The results show that choosing the right coating solution would increase the fracture energy of the sealing area by more than 70%. We demonstrate that the test methodology could also be used to test the adhesion of thin coatings on metallic substrates.
Modelling Effects Of Particle Size And Pipe Gradient On Sand Transport In Multiphase Pipes

Multiphase flow is important in many industrial processes such as sand transport in multiphase pipeline during petroleum production process. The interactions of sand and liquid exhibit complex flow characteristics including undesired deposition of sand in pipe. This study presents a three-dimensional (3D) computational fluid dynamics (CFD) modelling of horizontal and V-inclined multiphase pipe flow of liquid and sand for predicting sand transport flow regimes and minimum sand transport velocity (MTV) using the two-fluid Eulerian–granular modelling approach. This work presents precisely selected closure models which account for stresses due to kinetic and collisional interparticle interactions based on the kinetic theory of granular flow and frictional stress due to inter-particle interaction in stationary sand bed regime by the addition of solid friction pressure models. The simulations were performed for particle size ranging from 38 to 255 μm and 0.1 m diameter horizontal and V-inclined pipes in order to investigate the effect of particle size and pipe gradient on sand transport. The present study shows that particle size and pipe gradient have significant effect on liquid turbulence intensity and sand concentration distribution in pipeline. The predicted results show sand accumulates in the dip of the V-pipe which increases with increase in pipe gradient. The sand deposition varies in the V-pipe due to the pipe orientation, with a lower deposition at the pipe outlet when compared with the horizontal pipe flow at the same flow velocity and particle size. The predicted results show good agreement with experimental data obtained from literature for horizontal pipe flow.
Mobile Application Based Translation of Sign Language to Text Description in Kannada Language

Sign language is a main mode of communication for vocally disabled. This language use set of representation which is finger sign, expression or mixture of both to express their information among others. This system presents a novel approach for mobile application based translation of sign action analysis, recognition and generating a text description in Kannada language. Where it uses two important steps training and testing. In training set of 50 different domains of video samples are collected, each domain contains 5 samples and assign a class of words to each video sample and it will be store in database. Where in testing test sample under goes preprocessing using median filter, canny operator for edge detection, HOG for feature extraction. SVM takes input as a HOG features and predict the class label based on trained SVM model. Finally the text description will be generated in Kannada language. The average computation time is minimum and with acceptable recognition rate and validate the performance efficiency over the conventional model.
Fractional nonlinear synergetic control for DC-link voltage regulator of three phase inverter grid-tied PV system

The paper proposes a Fractional Nonlinear Synergetic Controller for three phase grid Photovoltaic (PV) system to regulate the dc-link capacitor voltage and ensure fast transient response, low dc link voltage fluctuation and low Total Harmonic Distortion (THD) in the current injected to the grid even under irradiance change. A comparison between the proposed controller with Nonlinear Synergetic and Sliding Mode control (SMC) using MATLAB/SIMULINK has been done to validate the proposed controller. The simulation results show the advantage of the proposed one over the other available controllers.
Additive Manufacturing in Civil Engineering

Research in additive manufacturing is going on since last three [1,2] decades. Researchers have been developed different materials [3], tool path [4] and methods of AM. Initially, AM was used for fabrication of prototypes [5-10], but now functional machine parts [11,12] are also produced. Due to its ability to process different kinds of materials AM is now utilized in various other sectors like food printing, chocolate printing, glass and ceramic printing, bio printing , scaffold fabrication [7,13-17], etc. In the modern era of industrializations, there is need to fabricate custom design products of the short life cycle to transform the traditional design of products. Designers have the potential to design new products which are aesthetically and functionally better than existing one. However, some time subtractive manufacturing techniques were not able to fabricate part of complex geometry, which was a major gap between design and manufacturing conceptualization.