Miracle-dz/UniFAR-FTUs huggingface dataset:
Managing Test Coverage Uncertainty due to Random Noise in Nano-CMOS: A Case-Study on an SRAM Array

Static random access memories (SRAM) are a major constituent in high performance microprocessors and systems-on-a-chip. With scaling of technology, manufacturing process variations in SRAMs are of significant concern. SRAM cells that are marginal due to process variations suffer from stability issues where random thermal noise and random telegraph noise (RTN) become determinant in memory state. This introduces uncertainty in testing, where passing a test does not necessarily mean that SRAM is good. A marginal cell may pass testing, but fail during operation. To address this problem, we introduce a new metric for probabilistic fault coverage. We present simulation methods for measuring such coverage and propose N-detect and multilevel wordline (WL) voltage techniques to increase the detection probability of marginal cells. We demonstrate the benefit of these testing approaches on a sample SRAM array, designed in 32 nm predictive technology models. To simulate marginal cells, we oversample the tail of the process variations distribution. Transient noise simulations show that thermal noise can lead to a fault coverage loss of 20% and RTN can lead to a maximum fault coverage loss of up to 75%. N-detect technique achieves close to a 100% fault coverage at n = 100 for thermal noise and n = 70 for RTN. Multilevel WL technique requires 20-30 mV boost in WL voltage during read test to achieve near ideal fault coverage at minimal yield loss. A combination of these techniques is shown to be effective in increasing fault coverage with a tradeoff between test time and yield loss.
Cooling Enhancement Using Inhomogeneous Thermoelectric Materials

The maximum cooling temperature of a thermoelectric refrigerator made of uniform bulk material is limited by its dimensionless figure-of-merit ZT. Cascaded stages are typically needed in order to obtain a higher cooling temperature. Multiple stage configurations have disadvantages of device complexity, and reduced efficiency due to the non-ideal heat spreading between different stages. In this paper, we prove that the maximum cooling temperature can be increased by using a single stage made of inhomogeneous material. This optimization is different from conventional graded materials where there is a large temperature gradient and local material properties are optimized in order to achieve the highest ZT at the local temperature under operation. The new optimization is attributed to the redistribution of the Joule heating and Peltier cooling profiles along the current and heat flow directions. The cooling efficiency can also be increased by a moderate amount. Numerical simulations are used to optimize the doping profile for a thermoelectric cooler based on single crystal silicon
‘I accept my son for who he is – he has incredible character and personality’: fathers’ positive experiences of parenting children with autism

Abstract Literature in the field of autism is largely deficit driven, with a focus on the inabilities of individuals and the negative experiences of families, often characterised by reductive assumptions and tragedy model interpretations. In addition, family-orientated research has generally overlooked the views and contribution of fathers of disabled children, with positive paternal narratives especially scarce. This study explored 198 father perspectives on perceived benefits of parenting their children with autism, gained in response to an open-ended question in an online survey. Key themes relate to appreciating children’s individual qualities, valuing the strong emotional bond, fathers’ own nurturing role and their associated personal development. Findings will be discussed in relation to models of childhood disability and fatherhood.
Predicting personal information behaviors with lifelog data

The research for monitoring and recognizing personal behaviors from various digital sensors has recently been doing in a variety of fields. We address this for “lifelog” - all of the digital information about personal daily life. The research typically focuses on collecting personal lifelog, managing huge amount of lifelog data, and recognizing activities and behavior patterns from them. The methods of extracting key features and characterizing patterns would be crucial for finding meaningful information from huge and complex lifelog data. The research is a significant challenge because individual's lifelog data would be useful to provide personal life services such as healthcare. In this paper, we propose the process for predicting personal future behavior by tracing back to the past experiences. The behavior prediction process is composed of five stages. Firstly, physical activities through various sensors are collected and then, major physical activities are extracted through feature selection. Secondly, behavioral context information such as location, time and object is annotated to each activity for recognizing the behavior states more exactly. Then all sequences of physical activities with contextual information are divided into each daily set. Thirdly, behavior patterns from them are extracted by analyzing key features. After that, all daily sequences are transferred as the set of semantic activities for presenting major behavior states. Fourthly, from the set of semantic activities, based on the behavior probability to be used for the behavior prediction in next step, a sequence tree is generated. Finally, the highest predicted activities can be shown in a user interface from the query based on `Time' or `Event'. In a user interface, the functions for retrieving past and current behaviors and searching the predicted behaviors will be provided by choosing specific point in time or the specific event. Currently we are building a system for processing the proposed behavior prediction.
Tools for Assessment of Intellectual Assets of Enterprise Based on Fuzzy Information

This article is dedicated to the application of mathematical tools of fuzzy logic theory for the financial assessment of intellectual assets. Intellectual capital (IC) represents a special kind of capital. Intellectual assets form a potential source of company’s value growth through the creation of new knowledge and its implementation in company’s activities. The basis of IC is formed by speculative and cogitative power of persons, together with such factors as consumer relations, business processes, databases, brands, and IT systems. IC components shaping and developing require investments. Results measurability has always been a major problem when making investment decisions in relation to IC. For companies’ financial managers, intellectual (intangible) assets are very often feebly measured up against financial results of the company. As the result of developing an analytical model, based on mathematical tools for fuzzy sets, fuzzy input information has been processed, and the results for making optimal investment decision have been obtained. The efficiency of the transfer to cloud-based computing is convincingly substantiated in the terms, interpretable by financial managers of a company.
Psychometric Properties of the Psychological Needs Satisfaction Frustration Scale (BPNFS) in Chilean University Students.

© Universidad San Ignacio de Loyola, Vicerrectorado de Investigación, 2018 Este artículo se distribuye bajo licencia CC BY-NC-ND 4.0 Internacional (http://creativecommons.org/licenses/by-nc-nd/4.0/). Del Valle, M. , Matos, L. , Diaz, A. , Pérez, M.V. & Vergara J. (2018). Propiedades psicométricas escala satisfacción y frustración necesidades psicológicas (ESFNPB) en universitarios chilenos. Propósitos y Representaciones, 6(1), 301-350. doi: http://dx.doi. org/10.20511/pyr2018.v6n1. 202 Artículo De InvestIgAcIón
Pattern Aware Cache Management for Efficient Subset Retrieving of Astronomical Image Data

FITS(Flexible Image Transport System) is the most widely used data format in astronomy. The size of one FITS file ranges from Megabytes(MB) to Gigabytes(GB), even to Terabytes(TB), and astronomers are among the first researchers to encounter Big Data. For most cases astronomers are only interested in certain small sub-area of time series image. However loading the whole raw FITS file from HDD(Hard Disk Drive) every time then cutting it for the target sub-area is both time consuming and I/O wasting, and there is no existing cache scheme optimized for the subset retrieval of FITS files. By recognizing the hot sub-areas according to the latest query history, loading and merging related sub-images via a coordinate-mapping algorithm, we proposed a Pattern-Aware(PA) cache management strategy to efficiently retrieve sub-image data from huge amounts of FITS files. Our novel method was compared with traditional LRU, LFU and LRFU strategies on full FITS files and sub-files respectively. The results show that our PA strategy can maintain a high hit ratio of 64.32%, and reduce the average response time by about 24% than the best of these traditional schemes. These results are achieved with a cache to raw requested data size ratio of 8.77%.
ROACH : Online Apprentice Critic Focused Crawling via CSS Cues and Reinforcement

The Internet today is replete with forum sites that in the context of the deep/dark web are used to sell illicit goods, and to deal in illegal activities including human trafficking (HT). Working on the DARPA MEMEX project, our team collaborated with law enforcement to perform bulk analysis and crawl these sites and in doing so found a number of challenges. Forum sites contained pages with many links and little content and the ads the rich source of content were hidden behind link-dense hubs. To identify important links that led to ads, crawlers had to take advantage of CSS visual cues. As forum sites changed often, training a model offline would not be sufficient.We address these issues by creating ROACH, or Reinforcement-based, Online, Apprentice-Critic based focused crawling approacH. ROACH provides an online, adaptive crawling mechanism that employs static subject matter expert knowledge, with online learning based on a simplified version of reinforcement learning with back propagation. We use the widely popular apprentice-critic framework for performing this capability. ROACH is independent of any crawler implementation. The approach is scalable and accurate and overall provides better link relevancy scores than two baseline approaches including Apache Nutch. We evaluate ROACH on a dataset collected in the human trafficking domain from the DARPA MEMEX effort.
Body Image among Students in Beijing : Impact of media , status , and health concerns

The importance of body image is increasing in China. Academic research and news media point to the rising desire for an ideal appearance, especially among young people in the country, in order to gain an advantage in society. This thesis was conducted to examine if university students at a high-ranking university in China were influenced by commercial ideals in the media to the same extent as young people in other settings in China have been shown to be in earlier research. This was done using a qualitative approach with a combination of in-depth interviews with students at Peking University and participant observation. The findings were interpreted through four different theoretical frameworks in order to analyze students’ perception of body image ideals shown in media, how these ideals are related to importance of status, as well as the implications they have for students’ mental and physical health. The study found that even for Peking University students, the necessity of possessing a favorable appearance cannot be neglected in order to enhance chances of future success. An ideal appearance was important for gaining status, and the quest for it had implications for students’ health.
J un 2 01 6 Convergence of the gradient method for ill-posed problems

We study the convergence of the gradient descent method for solving ill-posed problems where the solution is characterized as a global minimum of a differentiable functional in a Hilbert space. The classical least-squares functional for nonlinear operator equations is a special instance of this framework and the gradient method then reduces to Landweber iteration. The main result of this article is a proof of weak and strong convergence under new nonlinearity conditions that generalize the classical tangential cone conditions.
An Unsupervised Approach for Boundary Detection of Colored Natural Scenes

This work proposes a new unsupervised method for boundary detection in colored natural scenes, consisting of twostage sequential processes of integration. The first stage performs region extraction, where two different techniques measure the color-texture homogeneity in a region-growing method and they are combined by two different control algorithms. One control algorithm is based on a local property and the other is based on a global statistical property (the shape of the power spectrum of the image being analyzed). One homogeneity measure is the J-value and the second is a multifractal descriptor. In the second integration, edge information is extracted by a classical method, and integrated with region information. This process eliminates false boundaries in the region-map, guided by the edge-map, and reduces the noise in the edge-map as well, now guided by the region-map, thus taking advantage of their complementary nature. It integrates the two maps into a single final result, enhancing the coincident information of both maps. Each phase of integration improves, progressively, the detection of the boundaries. Experiments on a large dataset of natural color images BSDS suggest that the results for this approach proposed are closer to the human perception, quantitatively and qualitatively, than the individual methods. Keywords-boundary detection, multifractal measurement, J value, 1/f spectrum, region-growing, edge detection.
Ion trap mass spectrometry of surfactins produced by Bacillus subtilis SZMC 6179J reveals novel fragmentation features of cyclic lipopeptides.

RATIONALE Surfactins are mixtures of cyclic lipopeptides consisting of variants of a heptapeptide and a linked β-hydroxy fatty acid with various chain lengths of 13-15 carbon atoms. A lactone bridge between the β-hydroxy functional group of the fatty acid and the carboxy terminal functional component of the peptide chain form their cyclic structures. Such lipopeptides, produced mainly by Bacillus species, possess several remarkable biological effects such as antitumor and antimicrobial activities, some of which are highly promising for utilization in plant disease biocontrol. The strain Bacillus subtilis SZMC 6179J was previously shown to exert significant antifungal properties against various phytopathogenic filamentous fungi; therefore, we characterized the structural features of the surfactins produced by this strain in order to explore the origin of the observed antagonistic effects of this potential biocontrol organism. METHODS Bacillus subtilis SZMC 6179J was used to produce surfactins, which were characterized by high-performance liquid chromatography/electrospray ionisation ion trap mass spectrometry (HPLC/ESI-ITMS) techniques after precipitation and extraction steps. RESULTS The 26 isoforms separated and identified represent three types of known surfactin variants and a fourth, previously unknown group characterised by the replacement of the leucine residue by valine in position 2. The relative amounts of this newly identified surfactin group were below 1%, and their cyclic structures were closed by C13-C15 hydroxy fatty acids. The structural assessment of the isoforms by MS(2) measurements led to the characterisation and description of a new fragmentation mechanism of surfactins. CONCLUSIONS The detected new natural lipoheptapeptide compounds with modified structures have significant potential for biotechnological and biocontrol applications. The complementary ITMS(2) data as well as the described internal fragmentation mechanism obtained from the sodiated surfactin molecules may further facilitate the structural elucidation of cyclic lipopeptides in the future. Copyright © 2016 John Wiley & Sons, Ltd.
Potential biomarkers in psychiatry: focus on the cholesterol system

● Introduction ● Methods for proteomic analysis – Sample fractionation/biochemical fractionation – MS ● The cholesterol system – Cholesterol and apolipoproteins – Cholesterol – Apos – ApoE – ApoB – ApoA1 and ApoA4 ● The cholesterol system and specific disorders – Alzheimer's disease – Schizophrenia – Depression – Developmental disorders: ASDs ● Discussion – Proteomic considerations for analysis of Apos – Considering diet and lifestyle effects on the cholesterol system – Consequences of disturbed cholesterol and Apos in the CNS ● Conclusion
The Influence of Using Guided Questions Technique Towards Students’ Procedure Text Writing Ability

One of the most important skills in English is writing. It is often considered as the most difficult skill by the students. This problem was also faced by the students of the eleventh grade of SMA Tamansiswa Teluk Betung Bandar Lampung. To overcome that problem, the teachers should provide Some appropriate techniques. One of the techniques is Guided Questions. The objective of this research is to know whether there is significant influence of using Guided Questions toward students’ procedure text writing ability or not. The design of this research was post test only design. The population of this research was the students of SMA Tamansiswa Teluk Betung Bandar Lampung at the eleventh grade. The writer chose the sample randomly by using cluster random sampling technique. The writer used Guided Questions in Experimental class as a treatment and lecturing technique in control class. In collecting the data, the writer used instrument in written form. The instrument was used for the post test. The writer did the post test to find out the students’ procedure text writing ability after conducting the treatment. After giving the post test, the writer analyzed the data by using independent sample ttest. It was found out that result of Sig (Pvalue) = 0.000 < α = 0.05. It means that Ho is rejected and Ha is accepted. To sum up, the use of Guided Questions toward students’ procedure text writing ability had significant influence. The conclusion of this research is Guided Questions is effective to be used toward students’ procedure text writing ability
Is the association of breastfeeding with child obesity explained by infant weight change?

OBJECTIVE Breastfeeding and infant weight change are both associated with adiposity. We examined the extent to which infant weight change mediates the association between breastfeeding and adiposity at age 3 years. METHODS We studied 884 children in a prospective cohort study. We determined breastfeeding status in the first 6 months. Our primary outcomes at 3 years were body mass index (BMI) z score and the sum of subscapular and triceps skinfold thicknesses (SS + TR); we also assessed obesity. We defined infant weight change as change in weight-for-age z score between birth and 6 months. We performed multivariable regression analyses. RESULTS At age 6 months, 25.0% of infants were fully breastfed. At age 3 years, mean (standard deviation) BMI z score was 0.45 (1.03). In linear regression analyses adjusted for mother's educational level, race/ethnicity, smoking, BMI, pregnancy weight gain and birth weight (adjusted for gestational age), the BMI z score of fully breastfed children was 0.17 (95% CI: -0.43, 0.09) units lower than never breastfed children. After additional adjustment for infant weight change, the estimate was attenuated (-0.03, 95% CI: -0.27, 0.20). Adjustment for infant weight change only modestly attenuated estimates for SS + TR (from -1.48 mm [95% CI: -2.52, -0.44] to -1.16 mm [95% CI: -2.18, -0.14]), and for the odds of being obese (from 0.21 [95% CI: 0.07, 0.68] to 0.29 [95% CI: 0.08, 1.05]). CONCLUSION Infant weight change between birth and 6 months mediates associations of breastfeeding with BMI, but only partially with indicators of child adiposity.
Genome Sequences of Mycobacteriophages Jane and Sneeze, New Members of Cluster G

ABSTRACT Jane and Sneeze are newly isolated phages of Mycobacterium smegmatis mc2155 from Hillsborough, NJ, and Palo Verde, Costa Rica, respectively. Both are cluster G, subcluster G1 mycobacteriophages. Notable nucleotide differences exist between genomes in the right half, including the presence of mycobacteriophage mobile element 1 (MPME1) in Jane.
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We present a software toolkit called SLMotion which provides a framework for automatic and semiautomatic analysis, feature extraction and annotation of individual sign language videos, and which can easily be adapted to batch processing of entire sign language corpora. The program follows a modular design, and exposes a Numpy-compatible Python application programming interface that makes it easy and convenient to extend its functionality through scripting. The program includes support for exporting the annotations in ELAN format. The program is released as free software, and is available for GNU/Linux and MacOS platforms.
Towards Secure Interoperability between Heterogeneous Blockchains using Smart Contracts

Achieving data confidentiality and privacy while maintaining secure access is essential in various fields, including in the medical sector. Implementing a blockchain-based technology to secure sensitive data ensures that the users own their data and have control over who can access it. While blockchain technology is still in its infancy, it is the cutting-edge of research in many industries and institutions. The decentralized nature of blockchain technology and the presence of smart contracts in Ethereum are two major features that can be utilized to create a novel data sharing and access system that is secure, flexible, and more reliable. In this paper, we investigate the use of smart contracts between heterogeneous blockchains for the purpose of achieving secure interoperability for data sharing and access control. As a proof of concept, we propose and implement a record management system for healthcare data, where access to healthcare providers’ databases is managed through a private blockchain, only available to healthcare providers, and patients access their medical records through a public blockchain. Additionally, we develop a set of smart contracts for each blockchain to control access, manage storage, and enable interoperability between the two blockchains. Keywords—Blockchain; Ethereum; smart contract