Miracle-dz/UniFAR-FTUs huggingface dataset:
Brittle-Ductile Transition in Laser 3 D Printing of Fe-Based Bulk Metallic Glass Composites

The effects of the α-Fe phase on mechanical properties and cracking of laser 3D printing Fe-based bulk metallic glass composites were investigated. The elastic recovery and plasticity index were characterized by nanoindentation. As the volume fraction of the α-Fe phase increases from 23.66% to 52.38%, the elastic modulus of printed samples suddenly drops. The samples exhibit a lower deformation resistance, and the plasticity index increases gradually. When the volume fraction of the α-Fe phase is 67.84%, the interaction between the α-Fe phase and matrix phase is smaller during expansion shrinkage. As a result, cracking is easy to initiate, which leads to the highest crack rate of the printed sample. However, as the volume fraction of the α-Fe phase increases to 83.31%, the hard brittle phase was sandwiched between the α-Fe phases similar to the finger structure plays key role in the plastic deformation. The plastic deformation releases large amounts of stress concentrated at the boundary and suppresses crack formation.
QUASI-OPPOSITIONAL SYMBIOTIC ORGANISMS SEARCH ALGORITHM FOR DIFFERENT ECONOMIC LOAD DISPATCH PROBLEMS

In this paper, an effective meta-heuristic technique called Quasi-Oppositional Symbiotic Organisms Search is applied for solving non-convex economic dispatch problems. Symbiotic Organisms Search is a soft computing technique, inspired by organisms in the ecosystem. This technique is implemented for improving the solution quality in minimum time. In order to improve convergence rate, quasi-reflected numbers are used here instead of pseudo-random numbers. Different equality and inequality constraints such as transmission loss, load demand, prohibited operating zone, generator operating limits and boundary of ramp rate are considered here. Presence of multiple fuels and valve point are also considered in some cases. This algorithm is applied to four different test systems. Simulation results are compared with many recently developed optimization techniques to show the superiority and consistency of this method. Simulation results also show that the computational efficiency of this algorithm is much better than the other meta-heuristic methods available in the literature.
Investigation of Electromagnetic Angle Sensor Integrated in FR4-Based Scanning Micromirror

This paper performs a detailed investigation on the electromagnetic angle sensor integrated in the flame retardant 4 (FR4)-based scanning micromirror. An accurate theoretical model is presented, especially considering the coupling effect between the driving and sensing coils. Experimental results agree well with the theoretical results, and show a sensitivity of 55.0 mVp/° and a high signal-to-noise ratio (SNR) of 71.9 dB. Moreover, the linearity of the angle sensor can still reach 0.9995, though it is affected slightly by the coupling effect. Finally, the sensor’s good feasibility for feedback control has been further verified through a simple closed-loop control circuit. The micromirror operated with closed-loop control possesses better long-term stability and temperature stability than that operated without closed-loop control.
Firm ownership and board characteristics: Do they matter for corporate social responsibility disclosure of Indian companies?

Purpose – This paper aims to examine whether the extent and type of corporate social responsibility (CSR) disclosures made by Indian public listed companies are associated with firm ownership and board characteristics. Design/methodology/approach – Data analysis is based on the top 100 companies listed on the Bombay Stock Exchange (2007-2011) using a 17-item CSR disclosure measure. Findings – The extent of CSR disclosure is positively associated with foreign ownership, government ownership and board independence and negatively associated with CEO duality. Promoter ownership has a negligible effect on the extent of CSR disclosure. In terms of the type of CSR disclosure, community information increases with government ownership and board independence, while environmental information expands with foreign ownership and board independence. Information on employees/human resources has a positive association with foreign ownership but decreases with CEO duality. The amount of product and services information inc.
Net National Product as a Welfare Indicator

The question of whether changes in net national product (NNP) will measure changes in welfare is investigated in this paper. M. Weitzman (1976) demonstrated that, under specific conditions, NNP is proportional to discounted consumption. The result requires NNP to be measured in current prices in utility units. Changes in real NNP measured using given prices from a base year will not represent a complete account of welfare changes. Copyright 1994 by The editors of the Scandinavian Journal of Economics.
G R ] 2 0 M ar 2 01 7 Automorphisms and endomorphisms of lacunary hyperbolic groups

In this article we study automorphisms and endomorphisms of lacunary hyperbolic groups. We prove that every lacunary hyperbolic group is Hopfian, answering a question by Henry Wilton. In addition, we show that if a lacunary hyperbolic group has the fixed point property for actions on R-trees, then it is co-Hopfian and its outer automorphism group is locally finite. We also construct lacunary hyperbolic groups whose automorphism group is infinite, locally finite, and contains any locally finite group given in advance.
The Matter Bounce Alternative to Inflationary Cosmology

A bouncing cosmology with an initial matter-dominated phase of contraction during which scales which are currently probed with cosmological observations exit the Hubble radius provides a mechanism alternative to inflation for producing a nearly scale-invariant spectrum of cosmological perturbations. In this review article I first discuss the evolution of cosmological fluctuations in the matter bounce scenario, and then discuss various attempts at realizing such a scenario. Observational signatures which will allow the matter bounce to be distinguished from the inflationary paradigm are also discussed.
Lessons from a Community Health Worker Home-visiting Program to Reduce Infant Mortality Among Black Mothers in Ohio

The Ohio Infant Mortality Reduction Initiative (OIMRI) aims to reduce infant mortality rates among black infants in Ohio by employing community health workers (CHWs) to conduct home visits. At these home visits, CHW activities include: refer-ring mothers to health and social services, educating mothers, giving mothers needed supplies, and providing social support. This study uses participant self-report data collected by CHWs from 2010 to 2015 and interviews with county-level program managers from 14 counties in Ohio. Program data and interviews were used to describe ways clients were recruited, client gestational age at enrollment and start of prenatal care, number of prenatal care visits, ways that OIMRI helps facilitate prenatal care, and barriers to staying in the program. Findings indicate that the earlier participants were recruited into OIMRI, the more prenatal care visits they attended, which may relate to whether barriers like transportation and poor/inconsistent housing were addressed. Programs like OIMRI may help reduce risk factors for infant mortality by improving the uptake of prenatal care.
Willingness of Online Panelists to Perform Additional Tasks

People’s willingness to share data with researchers is the fundamental raw material for most social science research. So far, survey researchers have mainly asked respondents to share data in the form of answers to survey questions but there is a growing interest in using alternative sources of data. Less is known about people’s willingness to share these other kinds of data. In this study, we aim to: 1) provide information about the willingness of people to share different types of data; 2) explore the reasons for their acceptance or refusal, and 3) try to determine which variables affect the willingness to perform these additional tasks. We use data from a survey implemented in 2016 in Spain, in which around 1,400 panelists of the Netquest online access panel were asked about their hypothetical willingness to share different types of data: passive measurement on devices they already use; wearing special devices to passively monitor activity; providing them with measurement devices and then having them self-report the results; providing physical specimens or bodily fluids (e.g. saliva); others. Open questions were used to follow up on the reasons for acceptance or refusal in the case of the use of a tracker. Our results suggest that the acceptance level is quite low in general, but there are large differences across tasks and respondents. The main reasons justifying both acceptance and refusal are related to privacy, security and trust. Our regression models also suggest that we can identify factors associated with such willingness.
Si-to-Si wafer bonding using evaporated glass

Anodic bonding of Si to Si four inch wafers using evaporated glass was performed in air at temperatures ranging from 300/spl deg/C to 450/spl deg/C. Although annealing of Si/glass structures around 340/spl deg/C for 15 minutes eliminates stress, the bonded wafer pairs exhibit compressive stress. Pull testing revealed maximum bond strengths greater than 50 N/mm/sup 2/ and an average bond strength of 30 N/mm/sup 2/. The bond strength is independent of both the bonding temperature and the feature size. We observed no fracture at the actual bond interface.
The Gdap 1 knockout mouse mechanistically links redox control to Charcot – Marie – Tooth disease

1 Institute of Molecular Health Sciences, Cell Biology, Department of Biology, ETH Zurich, Swiss Federal Institute of Technology, Switzerland, ETH-Hönggerberg, 8093 Zürich, Switzerland 2 Department of Sleep Medicine and Neuromuscular Disorders, University of Münster, 48149 Münster, Albert-Schwitzer-Campus, Germany 3 Division of Neuroanatomy and Behaviour, Institute of Anatomy, University of Zurich, Winterthurerstrasse 190, 8057 Zürich, Switzerland 4 Hunter James Kelly Research Institute, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY 14203, USA 5 Department of Neurology, University of Würzburg, 97080 Würzburg, Germany
A conceptual model of a single-event gate-rupture in power MOSFETs

Proposes a physical model of hole-collection following a heavy-ion strike to explain the development of oxide fields sufficient to cause single-event gate rupture (SEGR) in power MOSFETs. It is found that the size of the maximum field and the time at which it is attained are strongly affected by the hole mobility. Oxide fields larger than the intrinsic breakdown strength of the oxide can arise from the holes collecting at the interface and their image charge in the gate electrode. These high fields persist for times of the order of picoseconds. It is not known how long these fields must persist to initiate SEGR. >
Collecting Image Datasets with a Quadcopter

Although general object detection models exist, it is important to train mobile robots to detect and recognize specific objects that are unique to an environment. Transfer learning can be used to reduce the amount of new images required to learn the new object instances by leveraging more general existing models. This paper describes our user interface for collecting custom image datasets with a quadcopter and performing object instance labeling and annotation semi-autonomously. Collecting images with marked objects is a time consuming process and usually done under heavy human supervision. We evaluated our dataset by detecting the annotated objects in the real-time quadcopter video feed.
An overview of recent graph partitioning algorithms

Distributed Graph Databases DGDB became increasingly important in many area , particularly in social networks. The DGDB systems require a good graph partitioner for an efficient distribution of graph data. The graph partitioner, aims to produce a balanced partitions while minimizing the communication cost between machines. Moreover, the graph partitioning method for graph databases should be distributed and also incremental to cope up with graph changes. There are several graph partitioning algorithms. In this work, we have classified them into three categories such as : static methods for offline partitioning, streaming method for dynamic graphs and OLTP methods for Online and Transactional DGDB. Then we have organized a comparative study between the different graph partitioning methods. We have concluded that, the partitioners used by such DGDB are not favorable, because according to our study, there are certain algorithms that outperform them.
Fine-Grained Sentiment Analysis of Restaurant Customer Reviews in Chinese Language

Chinese language processing is a challenging topic in the well-developed area of sentiment analysis. In this project we implement 3 types of 4-class classification models (SVM, XGBoost, LSTM) for the fine-grained, or aspect-level sentiment analysis of restaurant customer reviews in Chinese language. There are 20 aspects for classification, each representing one type of target information in the reviews. We separately train one model for each element. The overall results of the models on the 20 aspects shows that XGBoost has the best performance, based on the average accuracy, weighted F1 score, and efficiency.
Application-aware IPv6 Networking (APN6) Encapsulation

Application-aware IPv6 Networking (APN6) framework makes use of IPv6 encapsulation in order to convey the application-aware information along with the data packet to the network so to facilitate the service deployment and SLA guarantee. This document defines the encodings of the application characteristic information, for the APN6 framework, that can be exchanged between an application and the network infrastructure through the use of IPv6 extension headers.
Audit Market Concentration in Turkey : An Empirical Study of the Relationship between the Audit Firm Characteristics

The aim of this study is to analyze the characteristics of the auditing firms operating in Turkey and analyze the relationship between the firm characteristics. In this study, using data obtained from the 2014 transparency reports of audit firms operating in Turkey, the following variables were analyzed with correlation analysis method; • The number of partners of the audit firm • The number of audited companies • Total income of audit firm • The number of auditors in the firm • The percent of income from financial statement audits • The number of junior auditors in the firm • The percent of income from tax audits • Duration of the training at firm There were 80 audit firms which must have published a transparency report in 2014. This study was performed by benefitting from 80 transparency reports published by the said 80 audit firms.
Sistem pendingin konvensional berdasarkan kompresi uap memiliki koefisien kinerja (COP) yang tinggi. Namun terdapat kekurangan sistem pendingin kompresi uap saat ini masih menggunakan refrigeran yang memiliki efek merugikan pada lingkungan. Untuk itu dilakukan penelitian mesin penyimpan buah dan

Conventional cooling systems based on vapor compression have a high coefficient of performance (COP). However shortage of vapor compression cooling systems still using refrigerants that have detrimental effects on the environment. For that purpose, the research of fruit and vegetable storage machine using thermoelectric system TEC1-12706 with temperature control system using arduino. In this study the temperature in the cabin can be stable at 15° C and still feasible for use as a storage of fruits and vegetables.
Stability Analysis of Magnetised Neutron Stars - A Semi-analytic Approach

We implement a semi-analytic approach for stability analysis, addressing the ongoing uncertainty about stability and structure of neutron star magnetic fields. Applying the energy variational principle, a model system is displaced from its equilibrium state. The related energy density variation is set up analytically, whereas its volume integration is carried out numerically. This facilitates the consideration of more realistic neutron star characteristics within the model compared to analytical treatments. At the same time, our method retains the possibility to yield general information about neutron star magnetic field and composition structures that are likely to be stable. In contrast to numerical studies, classes of parametrized systems can be studied at once, finally constraining realistic configurations for interior neutron star magnetic fields. We apply the stability analysis scheme on polytropic and non-barotropic neutron stars with toroidal, poloidal and mixed fields testing their stability in a Newtonian framework. Furthermore, we provide the analytical scheme for dropping the Cowling approximation in an axisymmetric system and investigate its impact. Our results confirm the instability of simple magnetised neutron star models as well as a stabilisation tendency in the case of mixed fields and stratification. These findings agree with analytical studies whose spectrum of model systems we extend by lifting former simplifications.
Explicating "Implicit Interaction": An Examination of the Concept and Challenges for Research

The term implicit interaction is often used to denote interactions that differ from traditional purposeful and attention demanding ways of interacting with computers. However, there is a lack of agreement about the term's precise meaning. This paper develops implicit interaction further as an analytic concept and identifies the methodological challenges related to HCI's particular design orientation. We first review meanings of implicit as unintentional, attentional background, unawareness, unconsciousness and implicature, and compare them in regards to the entity they qualify, the design motivation they emphasize and their constructive validity for what makes good interaction. We then demonstrate how the methodological challenges can be addressed with greater precision by using an updated, intentionality-based definition that specifies an input-effect relationship as the entity of implicit. We conclude by identifying a number of new considerations for design and evaluation, and by reflecting on the concepts of user and system agency in HCI.
PREDIABETES AND THE NEED FOR CARDIOVASCULAR RISK ASSESSMENT IN AVIATION

ABSTRACT Obesity, the disease of the twenty-first century, has a range of serious consequences to health. These are related in part to abnormal glucose levels, resulting in inflammatory and atherogenic response, hypertension and abnormal lipid profile. This increases the risk of cardiovascular disease significantly besides developing diabetes later. Hyperglycaemia is diagnosed with impaired fasting glucose and/or impaired glucose tolerance or elevated glycated haemoglobin (HbA1c). The Royal Australian College of General Practitioners (RACGP) guidelines for diagnosis using oral glucose tolerance test (or HbA1c) recognise the importance of extending diagnosis beyond simply identifying diabetes. This is relevant in view of the risk of composite cardiovascular events, coronary heart disease, stroke, and all-cause mortality associated with abnormal blood glucose. Since the pilot population mirrors this morbidity, the aviation regulator has an obligation to consider the impact in terms of aviation safety. Furthermore, although primary care literature predominantly focusses on the importance of diagnosing diabetes, from a regulator’s perspective there are incapacitation risks originating outside that narrow diagnosis. They arise once the control of glucose has begun to deteriorate. This article considers the regulatory importance of pilots and controllers who present with hyperglycaemia, or what is sometimes termed “prediabetes”. This includes the evidence for the risk assessment to help minimise the likelihood of an adverse event due to atherosclerotic cardiovascular disease among those holding aviation medical certificates, in turn promoting aviation safety.
Fluctuation relations for equilibrium states with broken discrete symmetries

Relationships are obtained expressing the breaking of spin-reversal symmetry by an external magnetic field in Gibbsian canonical equilibrium states of spin systems under specific assumptions. These relationships include an exact fluctuation relation for the probability distribution of the magnetization, as well as a relation between the standard thermodynamic entropy, an associated spin-reversed entropy or coentropy, and the product of the average magnetization with the external field, as a non-negative Kullback–Leibler divergence. These symmetry relations are applied to the model of noninteracting spins, the 1D and 2D Ising models, and the Curie–Weiss model, all in an external magnetic field. The results are drawn by analogy with similar relations obtained in the context of nonequilibrium physics.
Chapter 1 Hierarchical Nanostructures of Titanium Dioxide : Synthesis and Applications

This chapter covers different routes of preparation of hierarchical nanostructures (HNS) of titanium dioxide. Keeping the interest in developing modern and sustainable methods of materials chemistry, this chapter focuses on synthesis routes for TiO 2 HNSs reported by researchers from all over the world. The chapter includes the details of chemical reactions taking place during the synthesis and the effects of various process parameters like: type of surfactants, organic/inorganic titanium salts, temperature and pressure on products. The obtained TiO 2 HNSs from different synthesis routes are subsequently compared in terms of their morphology, crystallite size, surface area, particle size and phase. The merits and demerits of all synthesis techniques are also added for comprehensive information. At the end, various applications of HNSs are discussed and their performance is analyzed with respect to the morphologies obtained from different synthesis techniques.
Object-Based Convolutional Neural Networks for Cloud and Snow Detection in High-Resolution Multispectral Imagers

Cloud and snow detection is one of the most significant tasks for remote sensing image processing. However, it is a challenging task to distinguish between clouds and snow in high-resolution multispectral images due to their similar spectral distributions. The shortwave infrared band (SWIR, e.g., Sentinel-2A 1.55–1.75 µm band) is widely applied to the detection of snow and clouds. However, high-resolution multispectral images have a lack of SWIR, and such traditional methods are no longer practical. To solve this problem, a novel convolutional neural network (CNN) to classify cloud and snow on an object level is proposed in this paper. Specifically, a novel CNN structure capable of learning cloud and snow multiscale semantic features from high-resolution multispectral imagery is presented. In order to solve the shortcoming of “salt-and-pepper” in pixel level predictions, we extend a simple linear iterative clustering algorithm for segmenting high-resolution multispectral images and generating superpixels. Results demonstrated that the new proposed method can with better precision separate the cloud and snow in the high-resolution image, and results are more accurate and robust compared to the other methods.