Miracle-dz/UniFAR-FTUs huggingface dataset:
1 End-to-end crypto works . Now what ?

The disconnect between the research community and the practice of voting is stark. We now have a vari­ ety of techniques that can provably catch tabulation errors, verifying that votes are recorded as they were cast and tabulated as they were recorded. The mathematics are sound. Prototype systems have been im­ plemented [10, 5] and in some cases field tested [1]. Despite this, none of the major vendors of voting technologies have made any moves toward adopting e2e techniques in their systems. None of the standards organizations or regulatory bodies have moved toward requiring these technologies. The best we have is the EAC’s “innovation class” that at least allows these things. This paper attempts to address the question of what’s missing. There are several possible reasons that we might consider.
Adaptive Filters Employing Partial

{ In some adaptive ltering applications, the least-mean-square (LMS) algorithm may be too computationally-and memory-intensive to implement. In this paper , we analyze two adaptive algorithms that update only a portion of the coeecients of the adaptive lter per iteration. These algorithms use decimated versions of the error and regressor signals, respectively. Simulations verify the accuracy of the analyses, and the robustness of the algorithms is also explored.
The feminisation of migration and the migrants VET policy neglects: the case of skilled women secondary migrants in Australia

There is increasingly scholarship on gender and migration, yet the international migration of highly skilled women is still somewhat under-researched. This article focuses on this neglected area in the context of Australia’s discretionary inward migration policies to solve skills shortages. The article draws on empirical research using a qualitative case-study approach with in-depth narrative interviews to explore understandings of the experience of highly skilled female secondary migrants. The findings resonate with a growing body of work in North America, Europe and the UK. Applying a gendered and intersectional analysis to the case of Australia with its complex mix of skilled migrants from predominantly English speaking countries, as well as many countries in the Asia-Pacific region and Africa, reveals a more nuanced understanding of the temporality and gendered and racialised ways in which the processes of career disruption, deskilling, intensification of domestic responsibilities and re-feminisation of health and human service work play out through tensions between migration and education policies.
The Impact of the European Union Regional Policy on Sub-National Mobilisation in a Unitary State: The Case of Estonia

The discussion of multilevel governance and sub-national mobilisation, because of its potential for circumventing national governments policy, has become a critical case for those concerned with the political and institutional consequences of European integration. The debate of mult-level governance and sub-national mobilisation has almost exclusively been discussed in relation to Europeanisation and more precisely in the context of EU regional policy. However, in each country the roles, functions and financial structures of sub-national administration are different – so is the impact of EU legislation at the local level. Evidence so far indicates that regional mobilisation does not empower regional and local governments in general, but only select subset of them. In order to conceptualise more the impact of the EU on decentralisation and devolution of political systems due to the attention given to the sub-national level by the Commission (especially by including the principle of partnership to the SF legislation as well as setting up the Committee of the Regions) a great deal more casestudy testing needs to be carried out before multi-level government can be adopted as a general account of how EU operates. Therefore, the purpose of the paper is to explore the overall sub-national mobilisation in a small unitary new Member State Estonia due to Europeanisation through EU regional policy. As there is no regional level in Estonia, local governments remain in the centre of the study and the main research question explores to what extent has impact of the EU empowered Estonian sub-national level and why this kind of mobilisation has happened? The results of the study give ground to the analysis of the possible wider applicability of these manifestations to wider set of countries with similar territorial and political structures.
Multi-Scale Approaches to the MediaEval 2015 "Emotion in Music" Task

The goal of the “Emotion in Music” task in MediaEval 2015 is to automatically estimate the emotions expressed by music (in terms of Arousal and Valence) in a time-continuous fashion. In this paper, considering the high context correlation among the music feature sequence, we study several multiscale approaches at different levels, including acoustic feature learning with Deep Brief Networks (DBNs) followed a modified Autoencoder (AE), bi-directional Long-Short Term Memory Recurrent Neural Networks (BLSTM-RNNs) based multi-scale regression fusion with Extreme Learning Machine (ELM), and hierarchical prediction with Support Vector Regression (SVR). The evaluation performances of all runs submitted are significantly better than the baseline provided by the organizers, illustrating the effectiveness of the proposed approaches.
An Empirical Model of Cultural Factors on Trust in Automation

Trust is conceived to be an important factor mediating an individual’s reliance on automation. Studies have shown individual and cultural differences as well as tasking context significantly affect an individual’s development of trust behaviors. This paper reports preliminary progress in developing a psychometrically grounded subjective measure of trust in automation. A total of 110 items from 8 existing instruments were considered for inclusion in this instrument using Amazon Mechanical Turk to supply samples. Exploratory factor analysis was performed to determine the dimensionality of the data, with 42 items selected for continued refinement. Our proposed model comprises 3 main constructs (performance expectancy, process transparency, and purpose influence) along with 3 types of moderators (cultural-technological contexts, individual, and cultural differences).
Localization method for low power consumption systems

Locating nodes is a fundamental problem in wireless networks with hundreds of devices deployed in a wide area. This is especially relevant for mobile nodes. Wireless sensor nodes are usually powered by small batteries, solar panels or piezoelectric generators, so that, and consequently, power consumption is the main constraint to deal with. But classic localization techniques do not consider the problem of energy consumption as a key point. This paper presents a novel low power and range-free localization technique based on distributed fuzzy logic and cooperative processing among a set of fixed nodes and its neighbours. This feature permits better accuracy with less power consumption than most relevant localization techniques
Finding Median Point-Set Using Earth Mover's Distance

In this paper, we study a prototype learning problem, called Median Point-Set, whose objective is to construct a prototype for a set of given point-sets so as to minimize the total Earth Mover's Distances (EMD) between the prototype and the point-sets, where EMD between two point-sets is measured under affine transformation. For this problem, we present the first purely geometric approach. Comparing to existing graph-based approaches (e.g., median graph, shock graph), our approach has several unique advantages: (1) No encoding and decoding procedures are needed to map between objects and graphs, and therefore avoid errors caused by information losing during the mappings; (2) Staying only in the geometric domain makes our approach computationally more efficient and robust to noise. We evaluate the performance of our technique for prototype reconstruction on a random dataset and a benchmark dataset, handwriting Chinese characters. Experiments suggest that our technique considerably outperforms the existing graph-based methods.
Face Recognition Using 3-D Models: Pose and Illumination

Unconstrained illumination and pose variation lead to significant variation in the photographs of faces and constitute a major hurdle preventing the widespread use of face recognition systems. The challenge is to generalize from a limited number of images of an individual to a broad range of conditions. Recently, advances in modeling the effects of illumination and pose have been accomplished using three-dimensional (3-D) shape information coupled with reflectance models. Notable developments in understanding the effects of illumination include the nonexistence of illumination invariants, a characterization of the set of images of objects in fixed pose under variable illumination (the illumination cone), and the introduction of spherical harmonics and low-dimensional linear subspaces for modeling illumination. To generalize to novel conditions, either multiple images must be available to reconstruct 3-D shape or, if only a single image is accessible, prior information about the 3-D shape and appearance of faces in general must be used. The 3-D Morphable Model was introduced as a generative model to predict the appearances of an individual while using a statistical prior on shape and texture allowing its parameters to be estimated from single image. Based on these new understandings, face recognition algorithms have been developed to address the joint challenges of pose and lighting. In this paper, we review these developments and provide a brief survey of the resulting face recognition algorithms and their performance
Consideration of manufacturing data to apply machine learning methods for predictive manufacturing

According to the recent development of internet of things and big data, the serious tries of implementing smart factory have been increased. To realize the smart factory, firstly predictive manufacturing system should be implemented. As a first step of predictive manufacturing, this paper focuses on solving the simple but time consuming and high cost task in the predictive manner. The target problem of this paper is predicting CNC tool wear compensation offset using machine learning methods based on the data. To apply machine learning methods, we should understand the characteristics of the data and find the most suitable method according to the data characteristics. Thus, this paper discusses the characteristics of manufacturing data and compares various cases of applying machine learning methods.
International Sport Federations in the World City Network

In this article, we analyze the transnational urban geographies produced by international sport federations (ISFs) through their global, regional, and national headquarter locations. Data on the global urban presence of 35 major ISFs are examined through connectivity analysis and principal component analysis. The connectivity analysis reveals the relative dominance of cities in Europe and Pacific Asia, whereby Seoul, Tokyo, Kuala Lumpur, Cairo, and Lausanne stand out. The principal component analysis reveals the main subnetworks produced through ISF location decisions, which includes inter alia a “winter sports subnetwork” centered on Ankara, Belgrade, Helsinki, and Stockholm; an “Olympic subnetwork” centered on Lausanne; and a decentered subnetwork with truly “global sports. ”
Archetypes of Inter-firm Relations in the Implementation of Management Innovation: A Set-theoretic Study in China’s Biopharmaceutical Industry

Innovation research increasingly focuses on understanding why and how firms implement new management practices, processes or structures. Emerging in the shadow of research on technological innovation, growing evidence points towards the inter-firm relation as an important locus of innovation. Yet although organizational theory suggests discrete alternative inter-firm coordination mechanisms, the literature on management innovation has thus far treated the inter-firm relation as one broad mode of organizing. This study takes a configurational perspective to identify archetypes of inter-firm relations leading to the implementation of management innovation. Using fuzzy set Qualitative Comparative Analysis (fsQCA) to analyse 56 firm partnerships in China’s biopharmaceutical industry, the empirical evidence identifies four such discrete inter-firm archetypes: organic coalitions, bureaucratic foundations, coalitions of intense interdependency and reciprocal foundations. The results suggest that the type of interdependency, rather than the coordination mechanisms governing inter-firm relations, leads to the implementation of management innovation.
Aldose Reductase Inhibitor Fidarestat as a Promising Drug Targeting Autophagy in Colorectal Carcinoma: a Pilot Study.

BACKGROUND Colorectal cancer (CRC) is a leading cause of morbidity and mortality worldwide. Targeting autophagic cell death is emerging as a novel strategy in cancer chemotherapy. Aldose reductase (AR) catalyzes the rate limiting step of the polyol pathway of glucose metabolism; besides reducing glucose to sorbitol, AR reduces lipid peroxidation-derived aldehydes and their glutathione conjugates. A complex interplay between autophagic cell death and/or survival may in turn govern tumor metastasis. This exploratory study aimed to investigate the potential role of AR inhibition using a novel inhibitor Fidarestat in the regulation of autophagy in CRC cells. MATERIALS AND METHODS For glucose depletion (GD), HT-29 and SW480 CRC cells were rinsed with glucose-free RPMI-1640, followed by incubation in GD medium+/-Fidarestat (10μM). Proteins were extracted by a RIPA-method followed by Western blotting (35-50 μg of protein; n=3). RESULTS Autophagic regulatory markers, primarily, microtubule associated protein light chain (LC) 3, autophagy-related gene (ATG) 5, ATG 7 and Beclin-1 were expressed in CRC cells; glyceraldehyde-3 phosphate dehydrogenase (GAPDH) was used as an internal reference. LC3 II (14 kDa) expression was relatively high compared to LC3A/B I levels in both CRC cell lines, suggesting occurrence of autophagy. Expression of non-autophagic markers, high mobility group box (HMG)-1 and Bcl-2, was comparatively low. CONCLUSIONS GD+/-ARI induced autophagy in HT-29 and SW-480 cells, thereby implicating Fidarestat as a promising therapeutic agent for colorectal cancer; future studies with more potent ARIs are warranted to fully dissect the molecular regulatory networks for autophagy in colorectal carcinoma.
Towards Automatic and Lightweight Detection and Classification of Malicious Web Contents

Malicious webpages are today one of the most prevalent threats in the Internet security landscape. To understand such problem, there has been several efforts of analysis, classification, and labeling of malicious webpages, ranging from the simple static techniques to the more elaborate dynamic techniques. Building on such efforts, this work summarizes our work in the design and evaluation of a system that utilizes machine learning techniques over network metadata to identify malicious webpages and classify them into broader classes of vulnerabilities. The system uses easy to interpret features, utilizes uniquely acquired dynamic network artifacts, and known labels for rendered webpages in a sandboxed environment. We report on the success (and failure) of our system, and the way forward by suggesting open directions for practical malicious web contents classification.
The global methane cycle: recent advances in understanding the microbial processes involved.

The global budget of atmospheric CH4 , which is on the order of 500-600 Tg CH4 per year, is mainly the result of environmental microbial processes, such as archaeal methanogenesis in wetlands, rice fields, ruminant and termite digestive systems and of microbial methane oxidation under anoxic and oxic conditions. This review highlights recent progress in the research of anaerobic CH4 oxidation, of CH4 production in the plant rhizosphere, of CH4 serving as substrate for the aquatic trophic food chain and the discovery of novel aerobic methanotrophs. It also emphasizes progress and deficiencies in our knowledge of microbial utilization of low atmospheric CH4 concentrations in soil, CH4 production in the plant canopy, intestinal methanogenesis and CH4 production in pelagic water.
Combined administration of antibodies to human interleukin 8 and epidermal growth factor receptor results in increased antimetastatic effects on human breast carcinoma xenografts.

PURPOSE Current antibody-based immunotherapeutic approaches under evaluation for breast carcinoma are limited in target scope. For example, administration of the human epidermal growth factor receptor (EGFR) antibody, alone or in combination with a chemotherapeutic drug, is thought to primarily inhibit tumor cell proliferation. The aim of this study was to assess the effects of a combined blockade designed to inhibit tumor growth by inhibition of proliferation rate and the proinflammatory effects of interleukin (IL) 8. EXPERIMENTAL DESIGN A human breast carcinoma cell line that produces high levels of IL-8 was injected s.c. into severe combined immunodeficient mice. IL-8 has been reported to augment the progression of some human tumors; thus, we used a human IL-8 antibody, ABXIL8, in combination with anti-EGFR, ABXEGFR, to inhibit the metastasis of MDA231 tumors. RESULTS Whereas anti-IL-8 alone had no appreciable antimetastatic effect, the combination of ABXIL8 significantly enhanced the antitumor effects of ABXEGFR, resulting in greater survival of SCID tumor-bearing mice. This effect on survival was correlated with decreased metastatic spread and decreased tumor size in mice receiving both antibodies. Intriguingly, in vitro studies indicate that this antibody combination markedly inhibited matrix metalloproteinase activity associated with MDA-231 cells to a greater degree than either antibody alone. CONCLUSION Combined administration of these two human antibodies using growth factor blockade in conjunction with chemokine blockade may thus provide a more effective approach for treatment of metastatic human breast carcinoma.
The role of sociocultural context for culture competence and depressive symptoms among ethnic minority youths in junior high school

The aim of the study was to examine whether school sociocultural context affects culture competence and its relationship to depressive symptoms. As part of the Youth, Culture and Competence study conducted in the Norwegian Institute of Public Health, questionnaire data was collected from 373 immigrant students in two junior high schools within Oslo. The school contexts were represented in terms of proportion of ethnic minority students, 90% versus 60% referred to as the concentrated and balanced context, respectively. Results showed a relatively low level of depressive symptoms and high level of ethnic and host culture competence regardless of context. Ethnic culture competence showed an inverse relationship to depression in both contexts. Host culture competence was also negatively correlated with depression, but only in the balanced context. In the concentrated context this correlation was unsubstantial. Thus, the sociocultural context was found to moderate this correlation.
A novel murine model of rhinoscleroma identifies Mikulicz cells, the disease signature, as IL-10 dependent derivatives of inflammatory monocytes

Rhinoscleroma is a human specific chronic disease characterized by the formation of granuloma in the airways, caused by the bacterium Klebsiella pneumoniae subspecies rhinoscleromatis, a species very closely related to K. pneumoniae subspecies pneumoniae. It is characterized by the appearance of specific foamy macrophages called Mikulicz cells. However, very little is known about the pathophysiological processes underlying rhinoscleroma. Herein, we characterized a murine model recapitulating the formation of Mikulicz cells in lungs and identified them as atypical inflammatory monocytes specifically recruited from the bone marrow upon K. rhinoscleromatis infection in a CCR2‐independent manner. While K. pneumoniae and K. rhinoscleromatis infections induced a classical inflammatory reaction, K. rhinoscleromatis infection was characterized by a strong production of IL‐10 concomitant to the appearance of Mikulicz cells. Strikingly, in the absence of IL‐10, very few Mikulicz cells were observed, confirming a crucial role of IL‐10 in the establishment of a proper environment leading to the maturation of these atypical monocytes. This is the first characterization of the environment leading to Mikulicz cells maturation and their identification as inflammatory monocytes.
GENDER, CLASS, AND SOCIAL MOVEMENT OUTCOMES

Animal rights organizations in the United States are predominantly female and middle class. What are the implications of the composition of these groups for animal rights activists' abilities to achieve their goals? In this article, the author examines the role of class and gender in the outcomes of an anti-hunting campaign and an anti-circus campaign waged by one animal rights organization in the Seattle area. The article shows that hunters make classed and gendered attributions about the activists, whereas circus patrons do not view activists in terms of these statuses and end up taking their demands more seriously. It is suggested that an “identity interaction” between the activists' class and gender identity and that of their targets helps to explain these different reactions. The analysis also highlights the role of emotion in social movements, especially the ways in which targets perceive and react to activists' emotional displays.