Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution of the Mechanical Properties of a Tropical Soil Stabilized with Lime and Ash of Rice Rind

The ash of rice rind is a pozzolanic material that reacts with the calcium hydroxide (Ca (OH)2) forming bonding composites, when finely worn out and in water presence. Considering this behavior, the objective of the present work was to evaluate the potential use of this residue in the enrichment of the content of pozzolanic materials of a tropical soil stabilized with a commercial hydrated lime. The laboratory testing program incorporated unconfined compression strength tests performed on the soil and on its mixtures with contents of 8% of lime enriched with 5 and 10% of ash of rice rind in relation to the soil dry mass. The results of the testing program supported that the use of the residue was effective in increasing the degree of reactivity of the soil that was also directly related with the increase in the ash content and the period of cure of the mixtures.
Microwave Diagnosis of Bronchopulmonary Diseases Using Tightly Coupled Dipole Array Elements

This article discusses the feasibility of applying tightly coupled dipole array (TCDA) elements as antenna-applicators for bronchopulmonary diseases diagnosing using a method based on the analysis of microwave signals transmitted through the human chest. The antenna array element is designed to effectively transmit microwave signals deep into the body, minimizing reflection losses from tissues and the influence of the environment on the matching characteristics of the antenna-applicator. Numerical analysis of the TCDA element applicability was carried out in 3D electromagnetic simulation software ANSYS HFSS using a chest model in the frequency range from 1 to 2 GHz. During the simulation a radiofrequency scan of a part of the chest model was performed to obtain the distributions of the amplitude and phase of the transmission coefficient which are criteria for diagnosis.
A laminin 511 matrix is regulated by TAZ and functions as the ligand for the alpha6Bbeta1 integrin to sustain breast cancer stem cells

Repository Citation Chang C, Goel HL, Gao H, Pursell BM, Shultz LD, Greiner DL, Ingerpuu S, Patarroyo M, Cao S, Lim E, Mao J, McKee KK, Yurchenco PD, Mercurio AM. (2015). A laminin 511 matrix is regulated by TAZ and functions as the ligand for the alpha6Bbeta1 integrin to sustain breast cancer stem cells. Molecular, Cell and Cancer Biology Publications. https://doi.org/10.1101/gad.253682. 114. Retrieved from https://escholarship.umassmed. edu/mccb_pubs/22
DC Biased Field Plate RESURF for Further RDSON Reduction of LDMOS Transistors

A new RESURF variant concept termed DC Biased Field Plate RESURF (BFP-RESURF) is proposed and studied through TCAD simulation in this work. The new LDMOS device structure features multiple field plates over the drift region that are biased at constant voltages. Significant reduction of ${\mathrm {R}}_{{\mathrm {DSON}}}$ can be achieved by a more ideal electric field profile and an accumulation channel induced by the BFPs. Simulation study indicates that the new BFP-LDMOS offers a specific ${\mathrm {R}}_{{\mathrm {DSON}}}$ of 58 m$\Omega$. m${\mathrm {}}m ^{2}$ comparing to 91 m$\Omega$. m${\mathrm {m}}^{2}$ of the conventional LDMOS, a 1.6X reduction at a BV of 100V. The concept could be further extended to a wider range of BV ratings, the ${\mathrm {R}}_{{\mathrm {DSON}}}$ benefit becomes more pronounced as BV goes higher. The switching performance shows no obvious difference between the BFP and standard LDMOS. The BFP-RESURF concept is completely compatible with conventional BCDMOS processes and scalable over a wide range of voltage ratings.
Sorting Overlapping Spikes Based on Log-Mel Spectrogram and Convolutional Neural Networks

Sorting overlapping spikes is a key problem in spike classification. The overlapping spikes not only affect the accuracy of spike classification, but also interfere with correct information decoding. The template matching method is the main method to distinguish overlapping spikes, and its accuracy is also better than other methods. However, with the increase of collected data, the traditional template matching method consumes a lot of time and manpower to distinguish overlapping spikes. Therefore, this paper proposes a new method based on template to automatically distinguish overlapping spikes using Log-Mel spectrogram and convolution neural network (Mel_CNN). Firstly, make overlapping spike templates according to the existing spike categories. Secondly, use the spike and overlapping spike templates to train Mel_CNN. Finally, test the trained network with real spike and overlapping spike, The trained network can not only classify spikes into correct categories, but also identify overlapping spikes. The Mel_CNN method proposed in this paper not only outperforms the traditional template matching method in time, but also shows that the average accuracy of Mel_CNN method can reach 95.74%, so the method can effectively distinguish overlapping spikes. And validating the model with different metrics, the results are stable on datasets with different noise levels, suggesting out model has a strong robustness.
Influencia de la radiación solar en el proceso de degradación y fragmentación post-pequeña Edad del Hielo del glaciar de la Madaleta (Pirineo Central Español)

The goal of this study is to assess the importance of short-wave solar radiation in the ice wastage processes observed in the Maladeta Glacier since the last Little Ice Age maximum till today. The reconstruction of that evo- lution was made using different graphic documents (iconography, topographic maps, aerial photographs, terrestrial photographs) that showed the condition of the glacier in several moments of its recent history. The solar radiation values have been obtained by using the Solar Analyst software (an ArcView GIS extension), which calculates estimations of direct, diffuse and global radiation for each cell of a Digital Elevation Model and for selected periods
ACE: An Analog Cell Emulator for Dependability Study of NAND Flash Memory

Reliability is one of the primary concerns in modern SSD designs. Despite the benefits of high performance, low power consumption, and increased density, the vendors struggle with the reliability of user data due to various sources of analog noise. There were consorted efforts and studies to improve the reliability issues in SSDs, but we still need experimenting tools that present analog states of errors. To address this issue, we propose a novel NAND flash memory emulator, called ACE (Analog Cell Emulator), that uses threshold voltages for dependability studies. The proposed emulator maintains data as analog values through threshold voltage modeling, enabling emulation of endurance, retention, and disturbance errors of flash memory. To reduce the emulation overhead, metadata in a cell, page, and block are managed separately, and emulation is performed while reading rather than periodic error emulation. We evaluate the accuracy of ACE by comparing its signal with that of actual devices, with the results indicating that the signal differences are up to 4.3%. Additionally, we analyze two reliability enhancement techniques, ECC (Error Correction Code) and read-retry, using ACE with adjusted reference voltages. This analysis, which could not be feasible with existing emulators, demonstrates the advantages of the proposed analog emulator.
P-Q Control of Microgrid with Energy Storage Using Adaptive Controller

This paper introduces an adaptive active and reactive power control for inverter-based Battery Energy Storage System (BESS) with other Distributed Generators (DGs) of Microgrid (MG). The adaptive P-Q controller utilizes the advantages of Genetic Algorithm (GA) Optimizer and Artificial Neural Network (ANN) which resulted in a very efficient technique. The system is modeled in grid-connected mode to control active and reactive power exported and imported from the grid. Different scenarios were implemented under critical load levels and the proposed adaptive control technique exhibits excellent performance in supporting the load with the required power and sustain grid voltage requirement.
Analisa Penerapan Algoritma Brute Force Dalam Pencocokan String

Kebutuhan untuk menemukan informasi yang berguna dan cepat dalam suatu data yang besar sangat dibutuhkan. Karena kompleksitas data yang begitu banyak maka diperlukan suatu metode atau cara untuk dapat mencari suatu informasi yang diperlukan. Untuk melakukan pencarian sebuah data atau informasi tidak terlepas dari pencocokan string dimana dari hasil pencocokan inilah akan ditemukan pola kalimat yang dicari. Dalam penelitian ini membahas tentang penerapan algoritma brute force dalam melakukan pencocokan sebuah string. Algoritma ini melakukan pencocokan string dengan menggeser satu persatu pattern dan menyesuaikannya dengan teks hingga antara pattern dan teks memiliki pola yang sama. Hasil analisis dari penelitian ini berupa uji coba pencocokan string dengan algoritma brute force dengan studi kasus menggunakan mesin pencarian (search engine) dengan bahasa pemrograman PHP untuk pencocokan string
Soil biodiversity

Auteurs : VINCENT Quentin, Docteur en écotoxicologie et écologie des sols, Directeur Scientifique et Technique et co-fondateur de Sol & co. Vandoeuvre-Lès-Nancy. AUCLERC Apolline, Maître de Conférences, Université de Lorraine /ENSAIA, Laboratoire Sols et Environnement, Vandoeuvre-Lès-Nancy. LEYVAL Corinne, Directrice de Recherche au CNRS, Laboratoire Interdisciplinaire des Environnements Continentaux (LIEC UMR 7360 CNRS UL), Vandoeuvre-Lès-Nancy.
Understanding news: the impact of media literacy education on teenagers’ news literacy

Media literacy education is presented as an answer to the increasing demand for active citizenship in democratic societies. Consequently, educational programmes that empower teenagers to deal with the opportunities and risks that media pose are developing fast. Against this background, a number of secondary schools in The Netherlands started specific media literacy programmes, but it is unexplored to what extent these programmes are effective in promoting news media literacy among teenagers. To investigate this, a survey was conducted to measure news media literacy levels among more than 1,300 students that did or did not participate in a media literacy programme. Results show that media literacy programmes promote teenagers’ news media literacy to a certain ex - tent. However, the contribution of media literacy programmes to news literacy is small. Moreover, findings show that the level of news media literacy was moderate, and that educational level and age were stronger predictors of the student’s level of news media literacy than media literacy education itself. There is thus room for improvement with regard to delivering (news) media literacy education across school levels in the Netherlands.
Empirical likelihood confidence intervals under imputation for missing survey data from stratified simple random sampling

Missing observations due to non‐response are commonly encountered in data collected from sample surveys. The focus of this article is on item non‐response which is often handled by filling in (or imputing) missing values using the observed responses (donors). Random imputation (single or fractional) is used within homogeneous imputation classes that are formed on the basis of categorical auxiliary variables observed on all the sampled units. A uniform response rate within classes is assumed, but that rate is allowed to vary across classes. We construct confidence intervals (CIs) for a population parameter that is defined as the solution to a smooth estimating equation with data collected using stratified simple random sampling. The imputation classes are assumed to be formed across strata. Fractional imputation with a fixed number of random draws is used to obtain an imputed estimating function. An empirical likelihood inference method under the fractional imputation is proposed and its asymptotic properties are derived. Two asymptotically correct bootstrap methods are developed for constructing the desired CIs. In a simulation study, the proposed bootstrap methods are shown to outperform traditional bootstrap methods and some non‐bootstrap competitors under various simulation settings. The Canadian Journal of Statistics 47: 281–301; 2019 © 2019 Statistical Society of Canada
Making the Impossible Possible: Leading Extraordinary Performance: The Rocky Flats Story

The most contaminated nuclear plant in the country, Rocky Flats was an environmental disaster and the site of rampant worker unrest. Although estimates projected that cleaning up and closing the facility would take seventy years and $36 billion, something stunning happened. The project was completed sixty years ahead of schedule and $30 billion under budget and is now on its way to becoming a wildlife refuge. In Making the Impossible Possible, Kim Cameron and Marc Lavine explain how this remarkable feat was achieved--and how breakthrough levels of performance can be achieved by any organization. After analyzing numerous firsthand accounts and public records, Cameron and Lavine realized that the leaders of the Rocky Flats cleanup took a distinctive "abundance approach" to the task. These leaders focused on identifying and building on sources of strength, resilience, and vitality rather than simply solving problems and overcoming difficulties. The result was extraordinary positive deviance: outcomes far exceeding normal expectations. For the first time, Cameron and Lavine identify the specific leadership roles and key enablers--levers, techniques, and practices--involved in implementing this innovative approach. This fascinating and thoroughly researched case study concludes by revealing ten leadership principles ultimately responsible for the Rocky Flats turnaround, providing a complete guide for any organization wanting to better understand and apply the lessons of this incredible success.
Overview of the Style Change Detection Task at PAN 2020

The goal of style change detection is to identify text positions within a multi-author document at which the author switches. Detecting these positions is a crucial part of processing multi-author documents for purposes of author-ship identiﬁcation. In this year’s PAN style change detection task, we asked the participants to answer the following questions for a given document: (1) Given a document, was it written by multiple authors? (2) For each pair of consecutive paragraphs in a given document, is there a style change between these para-graphs? The task is performed and evaluated on two datasets compiled from an English Q&A platform, which differ in their topical breadth (i.e., the number of different topics that are covered in the documents contained). The paper in hand introduces style change detection as a task and its underlying dataset, surveys the participants’ submissions, and analyzes their performance.
Global Journal of Foreign Language Teaching

It is difficult to describe cross-linguistic influence; however, it has been a contentious phenomenon for a long time. Whenever the speaker of a language becomes bilingual, the first language will subtly affect the new one, even if it is not used much. This is how first language influence begins since the majority of Arab English as a foreign language (EFL) learners suffer from this problem. This current research aims to study the negative influence of the native language (Arabic) on utilising the English passive voice. In this article, we aim to discover the levels of Arab EFL learners’ knowledge of the passive voice, as well as to examine the percentage of interlingual and intralingual errors. This study applies a quantitative method. Forty-six participants, who are Arab EFL learners studying at the Universiti Malaysia Pahang, engaged in the task of answering a grammar test. To conclude, the results show that Arab students have a high rate of L1 transfer on the English passive voice, and their levels of knowledge of passive voice are identified. The researchers recommend mixed methods for further research in order to provide a wider understanding about this issue.
UvA-DARE ( Digital Academic Repository ) Which dressing do donor site wounds need ? : study protocol for a randomized controlled trial

Background: Donor site wounds after split-skin grafting are rather ‘standard’ wounds. At present, lots of dressings and topical agents for donor site wounds are commercially available. This causes large variation in the local care of these wounds, while the optimum ‘standard’ dressing for local wound care is unclear. This protocol describes a trial in which we investigate the effectiveness of various treatment options for these donor site wounds. Methods: A 14-center, six-armed randomized clinical trial is being carried out in the Netherlands. An a-priori power analysis and an anticipated dropout rate of 15% indicates that 50 patients per group are necessary, totaling 300 patients, to be able to detect a 25% quicker mean time to complete wound healing. Randomization has been computerized to ensure allocation concealment. Adult patients who need a split-skin grafting operation for any reason, leaving a donor site wound of at least 10 cm are included and receive one of the following dressings: hydrocolloid, alginate, film, hydrofiber, silicone dressing, or paraffin gauze. No combinations of products from other intervention groups in this trial are allowed. Optimum application and changes of these dressings are pursued according to the protocol as supplied by the dressing manufacturers. Primary outcomes are days to complete wound healing and pain (using a Visual Analogue Scale). Secondary outcomes are adverse effects, scarring, patient satisfaction, and costs. Outcome assessors unaware of the treatment allocation will assess whether or not an outcome has occurred. Results will be analyzed according to the intention to treat principle. The first patient was randomized October 1, 2009. Discussion: This study will provide comprehensive data on the effectiveness of different treatment options for donor site wounds. The dressing(s) that will prevail in effectiveness, satisfaction and costs will be promoted among clinicians dealing with such patients. Thus, we aim to contribute a well-designed trial, relevant to all clinicians involved in the care for donor site wounds, which will help enhance uniformity and quality of care for these patients. Trial registration: http://www.trialregister. nl, NTR1849. Date registered: June 9, 2009
Analytical and numerical analyses of an unconfined aquifer test considering unsaturated zone characteristics

A 7‐d, constant rate aquifer test conducted by University of Waterloo researchers at Canadian Forces Base Borden in Ontario, Canada, is useful for advancing understanding of fluid flow processes in response to pumping from an unconfined aquifer. Measured data include not only drawdown in the saturated zone but also volumetric soil moisture measured at various times and distances from the pumped well. Analytical analyses were conducted with the model published in 2001 by Moench and colleagues, which allows for gradual drainage but does not include unsaturated zone characteristics, and the model published in 2006 by Mathias and Butler, which assumes that moisture retention and relative hydraulic conductivity (RHC) in the unsaturated zone are exponential functions of pressure head. Parameters estimated with either model yield good matches between measured and simulated drawdowns in piezometers. Numerical analyses were conducted with two versions of VS2DT: one that uses traditional Brooks and Corey functional relations and one that uses a RHC function introduced in 2001 by Assouline that includes an additional parameter that accounts for soil structure and texture. The analytical model of Mathias and Butler and numerical model of VS2DT with the Assouline model both show that the RHC function must contain a fitting parameter that is different from that used in the moisture retention function. Results show the influence of field‐scale heterogeneity and suggest that the RHC at the Borden site declines more rapidly with elevation above the top of the capillary fringe than would be expected if the parameters were to reflect local‐ or core‐scale soil structure and texture.
Brightness Temperatures From Very Lossy Medium With Near-Field Bistatic Transmission Coefficients

The scattering fields from a very lossy medium with a flat interface are computed by using a finite-difference time-domain method. Near-field bistatic transmission coefficients (BTCs) are proposed, and the Planck’s law is extended to nondispersive lossy medium to compute the brightness temperatures from the lossy medium. The reciprocity relation on BTCs is utilized to reduce the computational load. The efficacy of the proposed method is verified by comparing the simulation results with the literature.
Lowering the Pre-training Tax for Gradient-based Subset Training: A Lightweight Distributed Pre-Training Toolkit

Training data and model sizes are increasing exponentially. One way to reduce training time and resources is to train with a carefully selected sub-set of the full dataset. Prior work uses the gradient signals obtained during a warm-up or “pre-training” phase over the full dataset, for determining the core subset; if the pre-training phase is too small, the gradients obtained are chaotic and unreliable. As a result, the pre-training phase itself incurs significant time/resource overhead, and prior work has not gone beyond hyperparam-eter search to reduce pre-training time. Our work explicitly aims to reduce this pre-training tax in gradient-based subset training. We develop a principled, scalable approach for pre-training in a distributed setup. Our approach is lightweight and minimizes communication between distributed worker nodes. It is the first to utilize the concept of model-soup based distributed training at initialization . The key idea is to minimally train an ensemble of models on small, disjointed sub-sets of the data; we further employ data-driven sparsity and data augmentation for local worker training to boost ensemble diversity. The centralized model, obtained at the end of pre-training by merging the per-worker models, is found to offer stabilized gradient signals to select subsets, on which the main model is further trained. We have validated the effectiveness of our method through extensive experiments on CIFAR-10/100, and ImageNet, using ResNet and WideResNet models. For example, our approach is shown to achieve 15.4 × pre-training speedup and 2.8 × end-to-end speedup on CIFAR10 and ResNet18 without loss of accuracy. The code is at https: //github.com/moonbucks/LiPT.git .