Miracle-dz/UniFAR-FTUs huggingface dataset:
Monetary Transmission via the Central Bank Balance Sheet

This paper estimates the effects of unconventional monetary policies on consumer as well as asset price inflation, economic activity and bank lending at the hand of a VAR analysis, covering episodes of balance sheet policies of 9 countries over the last 20 years. While recent episodes of unconventional monetary policies have been extensively analysed, this paper reduces deficiencies about long-run implications following central bank balance sheet policies in Scandinavian countries, Australia in the 1990s and Japan in the early 2000s. Results of this study are that balance sheet policies, in response to a collapse of asset price bubbles, can ensure a short run stabilisation of economic activity but are not able to lift the economy out of the ensuing deflationary slump alone. Additionally, they do not pose severe problems associated with inflation, as laid out in several theories such as the static monetarist interpretation of the quantity theory of money, or towards newly created asset price bubbles.
Image retrieval using NN based pre-classification and fuzzy relevance feedback

In this article, we have proposed an interactive image retrieval scheme using MPEG-7 visual features, Neural Network (NN)-based pre-classifier and fuzzy based feature evaluation scheme. The performance of the existing image retrieval systems is generally limited due to semantic gap, resulted due to the discrepancies between the computed low-level features and user's conception of an image. Partitioning the database by a NN-based pre-classifier, and using a fuzzy based feature evaluation scheme, the performance of the proposed scheme has been found to improved drastically by reducing the retrieval time and increasing the accuracy.
Violence by people discharged from acute psychiatric inpatient facilities and by others in the same neighborhoods.

BACKGROUND The public perception that mental disorder is strongly associated with violence drives both legal policy (eg, civil commitment) and social practice (eg, stigma) toward people with mental disorders. This study describes and characterizes the prevalence of community violence in a sample of people discharged from acute psychiatric facilities at 3 sites. At one site, a comparison group of other residents in the same neighborhoods was also assessed. METHODS We enrolled 1136 male and female patients with mental disorders between the ages of 18 and 40 years in a study that monitored violence to others every 10 weeks during their first year after discharge from the hospital. Patient self-reports were augmented by reports from collateral informants and by police and hospital records. The comparison group consisted of 519 people living in the neighborhoods in which the patients resided after hospital discharge. They were interviewed once about violence in the past 10 weeks. RESULTS There was no significant difference between the prevalence of violence by patients without symptoms of substance abuse and the prevalence of violence by others living in the same neighborhoods who were also without symptoms of substance abuse. Substance abuse symptoms significantly raised the rate of violence in both the patient and the comparison groups, and a higher portion of patients than of others in their neighborhoods reported symptoms of substance abuse. Violence in both patient and comparison groups was most frequently targeted at family members and friends, and most often took place at home. CONCLUSIONS "Discharged mental patients" do not form a homogeneous group in relation to violence in the community. The prevalence of community violence by people discharged from acute psychiatric facilities varies considerably according to diagnosis and, particularly, co-occurring substance abuse diagnosis or symptoms.
Bimanual shoulder flexion system with surface electromyography for hemiplegic patients after stroke: A preliminary study

A robot-assisted bimanual shoulder flexion rehabilitation system with surface electromyography (sEMG) for hemiplegic patients after stroke is presented as a preliminary study before clinical test. The assistive system driven by combination of bimanual mirror imaging motion and sEMG in order to induce continuous voluntary stimulation to muscle and nerve of the patients. In this paper, hardware design, controller with impedance compensation of actuator using disturbance observer (DOB) for back-drivable operation, and sEMG signal processing to obtain desired assistive torque are also reported. The performance of impedance compensation and assistive operation of the system with sEMG were verified by experiments with a healthy participant. This system is expected to help to recover functionality of neural/musculoskeletal system to hemiplegic patients.
Spectral Embedding of k-Cliques, Graph Partitioning and k-Means

We introduce and study a new notion of graph partitioning, intimately connected to spectral clustering and k-means clustering. Formally, given a graph G on n vertices, we ask to find a graph H that is the union of k cliques on n vertices, such that LG > λ LH where λ is maximized. Here LG and LH are the (normalized) Laplacians of the graphs G and H respectively. Informally, our graph partitioning objective asks for the optimal spectral simplification of a given graph as a disjoint union of k cliques. We justify this objective function in several ways. First and foremost, we show that a commonly used spectral clustering algorithm implicitly optimizes this objective function, up to a factor of O(k). Using this connection, we immediately get an O(k)-approximation algorithm to our new objective function by simply using the spectral clustering algorithm on G. Next, we demonstrate another application of our objective function: we use it as a means to proving that simple spectral clustering algorithms can solve some well-studied graph partitioning problems (such as partitioning into expanders). Additionally, we also show that (a relaxation of) this optimization problem naturally arises as the dual problem to the question of finding the worst-case integrality gap instance for the classical k-means SDP. Finally, owing to these close connection between some classical clustering techniques (such as k-means and spectral clustering), we argue that a more complete understanding of this optimization problem could lead to new algorithmic insights and techniques for the area of graph partitioning.
A Proposed Test Case Generation Technique Based on Activity Diagrams

— Software testing is an essential and integral part of the software development process. The testing effort is divided into three parts: test case generation, test execution, and test evaluation. Test case generation is the core of any testing process and automating it saves much time and effort as well as reduces the number of errors and faults. This paper proposes an automated approach for generating test cases from one of the most famed UML diagrams which is the activity diagram. The proposed model introduces an algorithm that automatically creates a table called Activity Dependency Table (ADT), and then uses it to create a directed graph called Activity Dependency Graph (ADG). The ADT is constructed in a detailed form that makes the generated ADG covers all the functionalities in the activity diagram. Finally the ADG with the ADT are used to generate the final test cases. The proposed model includes validation of the generated test cases during the generation process to ensure their coverage and efficiency. The generated test cases meet a hybrid coverage criterion in addition to their form which enables using them in system, regression as well as integration testing. The proposed model saves time and effort besides, increases the quality of generated test cases. The model is implemented on three different systems and evaluated to show its effectiveness.
A GPU-Based Solution to Fast Calculation of Betweenness Centrality on Large Weighted Networks

Recent decades have witnessed the tremendous development of network science, which indeed brings a new and insightful language to model real systems of different domains. Betweenness, a widely employed centrality in network science, is a decent proxy in investigating network loads and rankings. However, the extremely high computational cost greatly prevents its applying on large networks. Though several parallel algorithms have been presented to reduce its calculation cost on unweighted networks, a fast solution for weighted networks, which are in fact more ubiquitous than unweighted ones in reality, is still missing. In this study, we develop an efficient parallel GPU-based approach to boost the calculation of betweenness centrality on very large and weighted networks. Comprehensive and systematic evaluations on both synthetic and real-world networks demonstrate that our solution can arrive the performance of 30x to 150x speedup over the CPU implementation by integrating the work-efficient and warp-centric strategies. Our algorithm is completely open-sourced and free to the community and it is public available through this https URL. Considering the pervasive deployment and declining price of GPU on personal computers and servers, our solution will indeed offer unprecedented opportunities for exploring the betweenness related problems in network science.
Reliable metaphor analysis in organizational research: towards a dual dynamic approach

This paper is on metaphor in organizational research. First, we present a framework, proposed by Cornelissen et al. (2008), for organizing literature on metaphor and organization research. We argue that metaphors play a crucial role in conceptualizing and abstract concepts like ‘knowledge’ and ‘organization’. Second, we focus on metaphor from a linguistic point of view. We discuss the opportunities that arise from using the latest linguistic insights in identifying metaphor in discourse. Then, we come up with a research approach, based on the framework and the insights on metaphor from the field of linguistics. We propose that research on metaphor in organizational management should be based on a dual, dynamic approach, both projecting (deductive) and elicitating (inductive) metaphor.
Smart Tracker: Light Weight Infrastructure-less Assets Tracking solution for Ubiquitous Computing Environment

From container terminals, healthcare services, libraries to household, the role of Asset Tracking Applications has become indispensable. As the organizations grow, so do their volume of assets, soon it becomes very cumbersome to track these assets in real time and accurately prepare a financial report to avoid overbuys. Rapid development of Wireless Area Network and Radio Frequency transmitting active and passive devices like RFID tags have bolstered the deployment of Wireless Asset Tracking applications in all these disciplines. But apart from organizations where costly network infrastructures are in place to support such a reliable asset tracking task, the areas like ports, warehouses, truck stops, parks, mines, rescue spots still suffer from appropriate solutions that can cope with the adverse scenario of being devoid of infrastructure. Even high end Location Based Systems (LBS) like GPS are not scaled well in such situations. To meet these challenges, our approach presents a common platform that can locate different active and passive RF transmitting objects over the range of distances on small handheld devices. To effectively utilize the resources of the constrained handheld devices like PDA and cell phones, a light weight algorithm has been used. Our approach follows an extensible and modular architecture which offers applications from different platforms to customize and extend their functionalities. Smart Tracker has been implemented and evaluated with PDAs, RFID tags, WiFi sources for both indoor and outdoor applications.
Psychological characteristics of remedial teachers of different altruism levels

The authors of this paper studied psychological characteristics of remedial teachers with different altruism levels. Altruism is a motive to render assistance to anyone not consciously related to one’s own selÞ sh interests. Subjectively it manifests itself in sympathy, being oriented towards helping others. Altruism is opposed to selÞ shness, which is incompatible with disinterested concern for the welfare of others and willingness to sacriÞ ce personal interests for them. The main driving force behind altruistic behaviour is a drive to improve the situation of others rather than expecting some reward. In psychology, altruism is considered as a system of personality value priorities in which interests of another person or social community are a central motive and a moral evaluation criterion.
Circulating transferrin receptor assay--coming of age.

Transferrin receptors are transmembrane proteins present on the surface of most cells. Under normal circumstances, the iron required for cellular metabolism is acquired via transferrin receptors. Several recent reviews detail the methods of iron acquisition, the intracellular throughput of transferrin receptors, and the controlling mechanisms in the cell‘s quest to acquire and store iron (1)(2)(3). The cells of different organ systems show considerable differences in the concentration of cellular transferrin receptor, the highest concentrations being found in cells of organs with the highest iron requirements, such as the erythroid bone marrow and placenta (4). The concentration of cell surface transferrin receptor is carefully regulated by transferrin receptor mRNA according to the internal iron content of the cell and its individual iron requirements. Iron-deficient cells contain increased numbers of receptor, while receptor numbers are downregulated in iron-replete cells (4)(5). Transferrin receptor was identified in serum (6) after investigators recognized that the molecule was secreted into culture media in reticulocyte and erythroleukemia cell models (7)(8), and the concentrations of secreted receptor were found to correlate with the total receptor content of the cells. Subsequent studies showed that serum concentrations of transferrin receptor increase in iron-deficiency anemia, making it a useful marker in the diagnosis of microcytic anemias (9). Circulating transferrin receptor is a truncated form of tissue receptor (10), produced by proteolytic cleavage of cellular receptor, and for the most part circulates attached to transferrin (11)(12). The reference interval for concentration of circulating receptor varies between different assay systems, depending on the choice of calibrators. In this issue of Clinical Chemistry , the transferrin receptor assay recently approved by the US Food and Drug Administration is described by Allen et al. (13). The calibrators used in this enzyme immunoassay system are …
A novel Q-learning algorithm with function approximation for constrained Markov decision processes

We present a novel multi-timescale Q-learning algorithm for average cost control in a Markov decision process subject to multiple inequality constraints. We formulate a relaxed version of this problem through the Lagrange multiplier method. Our algorithm is different from Q-learning in that it updates two parameters - a Q-value parameter and a policy parameter. The Q-value parameter is updated on a slower time scale as compared to the policy parameter. Whereas Q-learning with function approximation can diverge in some cases, our algorithm is seen to be convergent as a result of the aforementioned timescale separation. We show the results of experiments on a problem of constrained routing in a multistage queueing network. Our algorithm is seen to exhibit good performance and the various inequality constraints are seen to be satisfied upon convergence of the algorithm.
Integration Calculation, Community and Cues: Public Opinion on European

This article summarizes and extends the main lines of theorizing on public opinion on European integration. We test theories of economic calculus and communal identity in a multi-level analysis of Eurobarometer data. Both economic calculus and communal identity are influential, but the latter is stronger than the former. We theorize how the political consequences of identity are contested and shaped – that is to say, politically cued – in national contexts. The more national elites are divided, the more citizens are cued to oppose European integration, and this effect is particularly pronounced among citizens who see themselves as exclusively national. A model that synthesizes economic, identity, and cue theory explains around one-quarter of variation at the individual level and the bulk of variation at the national
Negotiation for Meaning and Peer Assistance in Second Language Classrooms

This paper investigates the value of language classroom negotiation of meaning from both cognitive and sociocultural perspectives. According to Long (1985, 1996) comprehensible input gained through interactional adjustments such as negotiating meaning and modifying output is central to second language acquisition, and much research has been undertaken to discover which classroom activities give learners the greatest benefit from this type of interaction (Pica 1994). This paper discusses the measures typically used to identify negotiated interaction and proposes that more rigorous definitions need to be employed to separate signals of communication problems from signals of interest and encouragement. In the study reported for this paper, learners were recorded during an interactive classroom task, and the incidence of negotiation moves (learners’ clarification requests, comprehension and confirmation checks) was calculated by counting only those instances where communication problems were clearly signalled. The quantitative results show that the incidence of negotiating meaning was very low. A qualitative analysis of the data subsequently investigated what was going on in the long stretches of interaction that lacked any signs of meaning negotiation. A picture emerges of learners actively assisting each other to transact the task through co-construction and prompting. Learners expressed interest and encouragement while seeking and providing assistance and initiating self-repair of their own utterances, all in the absence of communication breakdowns. Obtaining completely comprehensible input appeared to be of lower priority than maintaining a supportive and friendly discourse. Negotiation is one of a range of conversational processes that facilitate SLA as learners work to understand and express meaning in the L2.
Novel Colors Correction Approaches for Natural Scenes and Skin Detection Techniques

— Color detection in visible spectrum is a very challenging task as the color in an image is sensitive to various factors such as sensor characteristics, illumination, optics, and ethnicity. Many researchers emphasis that there is a relationship between surface colors and illumination which is closely related problem of color constancy. For skin color detection methods, color correction stage should applied first to get better classification rate. In order to map the observed color to the correct one under some canonical illumination, prior to applying skin detection technique, common and popular solutions of illumination adaptation approaches are investigated and compared like the gray world approach, the white patch, stretch, and neural network approaches. In this paper, three new approaches have been introduced to correct the color of the image that suffers from color unbalancing. The purpose of these approaches is to correct the color natural scene and also to be used to prepare the image prior to applying skin detection technique. The first introduced color correction approach is Modified Grey World (MGW) that uses a reference value calculated using the means of RGB color components. The second approach is MGWWP to use the new MGW approach followed by white patch approach. Also, some other new approaches to solve color constancy problem are proposed during experimental tests. In this paper also, a new approach named Illumination Reflection Problem Solution (IRPSS) has been proposed to correct the skin color in the image that suffers from illumination reflection problem. Some of the skin color detection techniques are investigated and tested to show their results. The proposed IRPS approach succeeded to correct color of 95% of affected pixels from illumination reflection problem .
Application of renal-rotation techniques in retroperitoneoscopic partial nephrectomy

Retroperitoneoscopic partial nephrectomy (RPN) is one of the standard methods for treating T1-stage renal carcinoma, which has a narrow operational space and a difficult surgical procedure. The aim of this study was to examine the safety and feasibility of renal-rotation techniques in RPN. Between April 2012 and June 2014, the renal-rotation technique in RPN was performed in 22 male and 16 female patients, aged between 31 and 75 years (mean, 52 years), with stage T1N0M0 renal-cell carcinoma. In 29 cases the tumor was located at the ventral side of the kidney, including 22 cases at the renal hilum, and in nine cases the tumor was located at the inferior pole of the kidney. The tumor size was between 1.5 and 4.6 cm (mean, 2.8 cm). The results showed that, in all 38 cases, the procedure was successfully accomplished without conversion to open surgery. There were no intraoperative complications and only three cases of postoperative complications. The surgery duration was between 45 and 116 min (mean, 59 min); blood loss was between 10 and 120 ml (mean, 40 ml) and no patients required a blood transfusion. The average kidney ischemia time was 21 min (range, 15–38 min). No patients had local recurrence or metastasis after follow-up of between one and 26 months. In conclusion, the application of the renal-rotation technique in RPN for tumors located at the ventral side, renal hilum or at the inferior pole of the kidney is safe and feasible and worth wider clinical application.
Exploiting Symmetries for Optimal Integrated Code Generation

High quality code generation for irregular architectures, such as Digital Signal Processors, is a complex task, as it requires a fully integrated approach that simultaneously deals with the most important tasks of instruction selection, register allocation and instruction scheduling. We show how a fully integrated approach for optimal code generation based on dynamic programming can benefit from exploiting symmetry properties of dependence graphs that decrease the combinatorial explosion of the solution space. We identify conditions when it suffices to explore only one of multiple possible branches that would lead to equivalent results with respect to code quality.
When to Accentuate the Negative: The Effects of Perceived Efficacy and Message Framing on Intentions to Perform a Health-Related Behavior

The authors explore the relationship between perceived efficacy, depth of processing, and message framing. They conduct two experiments on varying health-related issues: sexually transmitted disease and skin cancer. In both studies, the authors demonstrate that a low efficacy condition (i.e., when it is uncertain that following the recommendations will lead to the desired outcome) motivates more in-depth processing. They then show that when subjects process in-depth, negative frames are more persuasive than positive ones. In contrast, a high efficacy condition generates less effortful message processing in which positive and negative frames are equally persuasive.