Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling and Implementation of Threshold Logic Circuits and Architectures

Threshold logic has long been studied as a means of achieving higher performance and lower power dissipation, providing improvements by condensing simple logic gates into more complex primitives, effectively reducing gate count, pipeline depth, and number of interconnects. This work proposes a new physical implementation of threshold logic, the threshold logic latch (TLL), which overcomes the difficulties observed in previous work, particularly with respect to gate reliability in the presence of noise and process variations. Simple but effective models were created to assess the delay, power, and noise margin of TLL gates for the purpose of determining the physical parameters and assignment of input signals that achieves the lowest delay subject to constraints on power and reliability. From these models, an optimized library of standard TLL cells was developed to supplement a commercial library of static CMOS gates. The new cells were then demonstrated on a number of automatically synthesized, placed, and routed designs. A two-stage 2’s complement integer multiplier designed with CMOS and TLL gates utilized 19.5% less area, 28.0% less active power, and 61.5% less leakage power than an equivalent design with the same performance using only static CMOS gates. Additionally, a two-stage 32-instruction 4way issue queue designed with CMOS and TLL gates utilized 30.6% less area, 31.0% less active power, and 58.9% less leakage power than an equivalent design with the same performance using only static CMOS gates.
Learning from the experiments of others-Simultaneous search and coordination in R & D and diffusion processes

In this paper we are studying a multiple player two-armed bandit model with two risky arms in discrete time. Players have to find the superior arm and can learn from others’ history of choices and successes. In equilibrium, there is no conflict between individual and social rationality. If agents depart from perfect rationality and use count heuristics, they can benefit from coordination (or centralization) of search activities. We test the conjecture that agents gain from coordination with a between-subject design in two treatments. In the experiments we find no gains from coordination. Instead, we find less severe deviations from the equilibrium strategy in the non-coordinated treatment.
Recommender Systems using Collaborative Filtering

With the vast amount of data that the world has nowadays, institutions are looking for more and more accurate ways of using this data. Companies like Amazon use their huge amounts of data to give recommendations for users. Based on similarities among items, systems can give predictions for a new items rating. Recommender systems use the user, item, and ratings information to predict how other users will like a particular item. Recommender systems are now pervasive and seek to make prot out of cus- tomers or successfully meet their needs. However, to reach this goal, systems need to parse a lot of data and collect information, sometimes from dierent resources, and predict how the user will like the product or item. The computation power needed is considerable. Also, companies try to avoid ooding customer mailboxes with hundreds of products each morning, thus they are looking for one email or text that will make the customer look and act. The motivation for this project comes from the eagerness to get a deep un- derstanding of recommender systems. One of the goals set for this project was to apply machine learning dynamically and to verify the results. Thus, a large dataset is used to test the algorithm and to compare each algorithm in terms of error rate. In this project, a website has been developed that uses dierent techniques for recommendations namely User-based Collaborative Filtering, Item-Based Collab- orative Filtering and Model Based Collaborative Filtering. Every technique has its way of predicting the user rating for a new item based on existing users data. To evaluate each method, I have used Movie Lens, an external data set of users, items, and ratings, and calculated the error rate using Mean Absolute Error Rate (MAE) and Root Mean Squared Error (RMSE)
Translation into Portuguese , Cultural Adaptation and Validation of the Rosenberg Self-esteem Scale Gal Moreira Dini

The authors had as obJectives: to translate into Portuguese) culturally adapt and validate the Rosenberg self-esteem scale to be used in a population which will be submitted to plastic surgery. Conclusion: The Portuguese version of the Rosenberg Self-Esteem scale (UNIFESP-EPMjRosenberg) proved reliable and valid and can be used as an instrument to measure the self-esteem of patients who will be undergoing cosmetic surgery
Working Paper Welfare Implication of India-ASEAN FTA : An Analysis using GTAP Model Biswajit

The welfare effect under GTAP model computes a money metric equivalent of the utility change. This is calculated by measuring ‘equivalent variation’ (EV) which summarizes the regional welfare changes resulting from any policy shock and is given in dollar values (US $ million). In GTAP, this money metric change is broken down into different components, each of which relates to a quantity change interacting with a distortion in the model. Considering the welfare decomposition effect under multiple regions as proposed by Huff & Hurtel (2001), the current study gives an insight into the sources of welfare gain under various simulations describing stages of India-ASEAN FTA. ASEAN is so far the biggest bloc with which India has an operational FTA. Almost 9% of India’s trade is with ASEAN as a group. In this context, the paper makes an attempt to assess the welfare implication of this agreement considering various implementation stages. It has been noticed that relatively bigger ASEAN members will derive more benefits in terms of welfare growth. India will have higher benefits only when the agreement gets fully implemented. ASEAN members will gain from higher ‘terms of trade’ effect while India’s gain mainly will be from the resource reallocation and change in domestic production activities reflected through ‘allocative efficiency’. However, the overall gain gets dampened due to the presence of negative ‘terms of trade’ in India’s welfare equation. India’s import demand of several intermediate as well as final goods will remain high and ASEAN will have advantage to supply these at a higher price yet lower than average prevailing import price in India which will lead to negative ‘terms of trade’ effect for India. The value of ‘allocative efficiency’ for India increases significantly once there is full liberalization. With full liberalization India extends tariff concessions for large number of products which are otherwise included in its negative list and not allowed any concessions. This adds to allocative efficiencyfirstly due to removal of protection from several inefficient production processes and second due to increased import taxes contributed by increased imports of many of the products otherwise featuring in the country’s negative list. Once we incorporate imperfect competition and presence of increasing return to scale in selected sectors in India, ‘scale economy’ effect, ‘profit shifting’, and various tax contributions will lead to more welfare gain in India. This indicates that with the presence of imperfect competition, profit shifting will allow India to invest in capital goods and technology leading to high ‘scale effect’ and thereby to increase exports further to ASEAN. The study brings up a very crucial issue that the gain from FTA with ASEAN hinges on India’s big firm’s ability to reduce average cost bringing better technology and quality inputs. This will improve production system in India which in turn will further boost the export sector. JEL Classification: F12, F13, F14, F15, C68, D58
vidence of sympatric speciation of elderberry carlaviruses

Five new carlaviruses infecting elderberry were characterized and tentatively named as elderberry virus A–E (ElVA–ElVE). Their genome organization is similar to that of other carlaviruses with size ranging from 8540 to 8628 nucleotides, excluding the polyadenylated tails. ElVA, ElVB and ElVD share a common ancestor as do ElVC and ElVE, indicating that speciation may be sympatric with all viruses having emerged in elderberry. Analyses of the carlavirus conserved domains indicate that the 2-oxoglutarate
Development of NanoSatellite OrigamiSat-1 with Highly Functional Deployable Membrane

This paper discusses a design of a 3U CubeSat, which will demonstrate an advanced membrane space structure in orbit. The objective of the CubeSat development is the establishment of research /development hub which enables the realization of innovative space deployable structures. The 3U CubeSat is designed as a pilot project to achieve the objective. This paper describes the CubeSat missions derived from the bigger development objective, and explains the system design of the CubeSat.
Studying Collaborative Learning Using Name Networks

This article reports on efforts to gain greater insight into the operation of LIS e-learning communities, by applying automated text-mining techniques to text-based communication to identify, describe and evaluate underlying social networks within such communities. More specifically, the article presents a new, content-based method for automated discovery of social networks from threaded discussions called name networks. This new method has been incorporated into an online tool called Internet Community Text Analyzer (ICTA) and is available at http://textanalytics.net. The proposed method is evaluated in the context of six online classes. The results suggest that the name network method is a viable alternative to costly and time-consuming collection of social network data using surveys. The study also demonstrates how name networks can be used to evaluate online classes.
EU Grant Agreement number : 290529 Project acronym : ANTICORRP Project title : Anti-Corruption Policies Revisited Work Package : WP 7 , Individual values and motivations to engage against corruption Title of deliverable : part of D 7

The information and views set out in this publication are those of the author(s) only and do not reflect any collective opinion of the ANTICORRP consortium, nor do they reflect the official opinion of the European Commission. Neither the European Commission nor any person acting on behalf of the European Commission is responsible for the use which might be made of the following information Project co-funded by the European Commission within the Seventh Framework Programme Dissemination Level
USING EVIDENCE-BASED KNOWLEDGE TO CREATE AN OFFENDER THROUGHCARE SYSTEM

II. BATTLE TO REDUCE RECIDIVISM A. Continuing Efforts to Reduce Crime and Reoffending Despite achieving a 2-year recidivism rate of 26.7% in 2010, there was still much that could be done to further reduce recidivism rates. In the ongoing efforts to reduce crime, the Singapore government explored a number of measures. These included upstream crime prevention measures, further law enforcement strategies, enhanced community engagement strategies and the use of offender rehabilitation. The recommendations from several recent government initiated Inter-Ministry Committees, set up to address matters relating to reducing crime and offending, involve SPS as a key player in the overall strategies to reduce offending. The success of the Prison Service in maintaining security while establishing evidenceinformed rehabilitation system brought confidence in the ability to reap further recidivism benefits for the future.
N o 3 COOPERATION AND COLLECTIVE PERFORMANCE IN LABOR NEGOTIATIONS :   THE ROLE OF THE NEGOTIATOR ’ S MOTIVATION

Understanding the factors that determine the process and results of labor negotiations is very important for the performance of organizations. This need has recently become stronger because of the issues that organizations face today. Nowadays they operate in complex situations involving major transformations imposed by globalization, digital technology and the rise of artificial intelligence as well as by the individualization of the relationships between unions and employers. In this context, labor negotiation can play a major role by becoming the means of federating all the different elements of the organization to contribute to these transformations. Like all negotiations, labor negotiation is a complex interaction between the different parties involved whose result depends on many factors. Whether it occurs in the public or the private sector, this specific type of negotiation takes place in highly normative organizational contexts. In this normative context, the legal aspect of labor negotiations has for a long time been dominant, particularly in France (Lichtenberger, 2013). However, this legal approach has also acted as a brake on taking into consideration various other approaches that can teach us a lot about the process and the behavioral practices that will best facilitate labor negotiators. Among these, the psychosocial approach, widespread in North America where the culture of labor negotiation is not limited to the search for a compromise but includes the behavioral dimension of the negotiation (bargaining), opens new perspectives towards understanding the conduct of this kind of social interaction. This is the approach that we have adopted in the present study, whose objective is to explore the psychosocial processes operating in labor negotiators, particularly the negotiator’s motivation as to the desired result. We will show that the results of labor negotiations can vary in accordance with the negotiator’s subjective perceptions and motivations. It thus becomes essential for workers’ and employers’ representatives to understand these subjective factors in order to better comprehend and conduct the negotiations in which they are involved.
Employment protection legislation : a critical review of the literature 4 th May 2001

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Governance of collaborative projects organized as communities Completed Research

Collaborative projects organized as communities have a significant participation of volunteers and are formed by individuals geographically distributed, interconnected through a technology platform in a work of mutual interest, creating and freely sharing knowledge-based products. Despite several researches on the subject, community projects still lack a better understanding of how they govern their actions to achieve collective results. This paper aims at understanding these projects and their aspects of governance by comparing them with traditional organizations. Although it is possible to distinguish community arrangements from other types, especially in terms of their structural and control aspects, the key factor not always considered in such differentiation refers to the potential impact of maturity of projects on its governance. As a consequence, it is believed that as community projects develop, even though they may retain characteristics of community models, their mode of operation is close to that of traditional organizations.
The g c-cytokine regulated transcription factor , STAT 5 , increases HIV-1 production in primary CD 4 T cells

Although HIV-1 (HIV) replicates poorly in non-dividing CD4 lymphocytes, resting T cells contribute to the latent reservoir. The gc-related cytokines reverse this block to HIV infection; however, the molecular mechanisms controlling this process are not understood. We asked whether the gc-cytokine regulated transcription factor, signal transducer and activator of transcription 5 (STAT5), activates HIV transcription. We identified three regions in the long terminal repeat (LTR) as close matches to the STAT5 consensus-binding site and show that STAT5 binds the LTR during HIV infection. Expression of Janus kinase 3 (JAK3) or STAT5 in primary human CD4 T cells activated LTR transcription, while transactivationincompetent dominant-negative STAT5 inhibited JAK3-induced LTR activity and infection of activated HIV-producing CD4 T-cells. In addition, overexpression of STAT5 increased virus production in unstimulated primary T cells – both the number of p24+ cells and their level of p24 production – suggesting that STAT5 promotes a permissive state for HIV infection. These data may have implications for regulation of latency and therapeutic strategies for control of HIV disease. D 2005 Elsevier Inc. All rights reserved.
RUPTURE MODEL OF THE TAURAMENA EARTHQUAKE ( COLOMBIA JAN . 19 / 95 )

The Tauramena Earthquake occurred in Colombia in the eastern border of the North Andes, on the 19 of January of 1995 (ML=6.5), causing a considerable damage and several life losses. This paper summarizes the source rupture characteristics of that earthquake, obtained by performing a multitime window linear source inversion, using strong motion and teleseismic broadband data. The aftershock distribution of the earthquake shows two perpendicular fault planes, one corresponding to the mainshock, dipping to the northwest with a reverse fault mechanism, and the other corresponding to a big aftershock and dipping to the southeast. The slip distribution of the mainshock shows the existence of three asperities. The slip on the fault plane showed a strong change in orientation during the rupture specially for the region corresponding to the main asperities, suggesting a low level of initial shear stress. The final slip vector on the fault plane showed a large rotation in space, which could be explained by the presence of a strong barrier located besides the southern edge of the fault plane.
Rough Set Theory : A Mathematical Tools can be Utilized in Fault Detection

With the flourish of the research field in cloud computing, high performance computer (HPC) and cluster computer are being used more and more widely due to its powerful computing capacity. Nowadays, a high performance computer used to perform scientific computing usually contains thousand of computing nodes or even more [9, 13]. The increasing number of compute nodes caused another problem: difficulty of administrating and managing all those nodes efficiently. Errors in software and hardware are ongoing facts that accompanies system running [16]. Traditionally, system administrator monitors system logs generated by each node to find those errors. How to extract useful information from huge amount of system logs to distinguish normal nodes from sick ones becomes a tough problem and many studies have been conducted in this field [21,31,32]. As a kind of new soft computing method, rough set theory can discover connotative knowledge and reveal the underlying rules among data through processing and analyzing various imprecise, inconsistent, imperfect data effectively. This project is trying to probe the effectiveness of applying rough set theory on cluster system log analysis in a parallel pattern, which is closed to studies in [1, 26].
Layered neural net design through decision trees

A multiple-layer artificial network (ANN) structure is capable of implementing arbitrary input-output mappings. Similarly, hierarchical classifiers, more commonly known as decision trees, possess the capabilities of generating arbitrarily complex decision boundaries in an n-dimensional space. Given a decision tree, it is possible to restructure it as a multilayered neural network. It is shown how this mapping of decision trees into a multilayer neural network structure can be exploited for the systematic design of a class of layered neural networks, called entropy nets, that have far fewer connections. <<ETX>>
A neural network isolated word recognition system for moderate sized databases

A neural net-based isolated word recognition system that was tested on a moderate sized database is presented. The system includes an acoustic preprocessor, feature maps and single layer feedforward networks which are used for classification of the input from the preprocessor. The feature maps are trained using the K-means algorithm. The single layer feedforward networks are trained using the backpropagation algorithm. Several methods are studied to partition a moderate sized database into smaller groups, so as to obtain high speaker dependent recognition rates. <<ETX>>
Long non-coding RNA SPRY 4-IT 1 as a common molecular marker for clinicopathological features and prognosis : a meta-analysis

Long non-coding RNA (lncRNA) SPRY4-IT1 has been reported to be aberrantly expressed in various cancers and correlated with progression. We conducted a meta-analysis to further investigate its prognostic potential in malignant tumors. Relevant literature was searched in several electronic databases using combinations of keywords relating to SPRY4-IT1 and cancer. The pooled hazard ratios (HRs) or odds ratios (OR) with a 95% confidence interval (95% CI) were used to evaluate its prognostic value. Quality assessment of the included studies was performed by the Newcastle-Ottawa Scale. 12 studies with a total of 1261 participants were included in the current meta-analysis. The results revealed a significant association between elevated SPRY4-IT1 expression with poor overall survival (OS) in 10 types of cancers (HR=2.26, 95% CI=1.44-3.54, P=0.0004). Additionally, elevated SPRY4IT1 expression was also correlated with lymph node metastasis (LNM) (OR=2.57, 95% CI=1.18-5.64, P=0.02) and tumor-node-metastasis (TNM) stage (OR=2.61, 95% CI=1.15-5.89, P=0.02). In the subgroup analysis, we found that increased SPRY4-IT1 expression was an unfavorable prognostic factor for patient OS indigestive system cancers (OR=1.92, 95% CI=1.12-3.30, P=0.02). This meta-analysis indicated that elevated SPRY4-IT1 expression may serve as a potential novel biomarker for LNM, TNM stage and OS in different types of cancer.