Miracle-dz/UniFAR-FTUs huggingface dataset:
Retrieval Term Prediction Using Deep Belief Networks

This paper presents a method to predict retrieval terms from relevant/surrounding words or descriptive texts in Japanese by using deep belief networks (DBN), one of two typical types of deep learning. To determine the effectiveness of using DBN for this task, we tested it along with baseline methods using examplebased approaches and conventional machine learning methods, i.e., multi-layer perceptron (MLP) and support vector machines (SVM), for comparison. The data for training and testing were obtained from the Web in manual and automatic manners. Automatically created pseudo data was also used. A grid search was adopted for obtaining the optimal hyperparameters of these machine learning methods by performing cross-validation on training data. Experimental results showed that (1) using DBN has far higher prediction precisions than using baseline methods and higher prediction precisions than using either MLP or SVM; (2) adding automatically gathered data and pseudo data to the manually gathered data as training data is an effective measure for further improving the prediction precisions; and (3) DBN is able to deal with noisier training data than MLP, i.e., the prediction precision of DBN can be improved by adding noisy training data, but that of MLP cannot be.
Early adversity, personal resources, body dissatisfaction, and disordered eating.

OBJECTIVE Early adverse experiences have been associated with disordered eating, but the mechanisms underlying that association are not well understood. The purpose of this study is to test a structural equation model in which early adversity is associated with disordered eating via intrapersonal resources, interpersonal resources, and body dissatisfaction. METHOD Female university students (n = 748) completed a series of questionnaires online, including measures of early adverse experiences, intrapersonal resources (self-esteem and personal growth initiative), interpersonal resources (gratitude and social support), body dissatisfaction, and disordered eating and exercising to lose weight. RESULTS Structural equation modeling indicated that early adverse experiences were negatively associated with interpersonal and intrapersonal resources. Intrapersonal resources were negatively associated with body dissatisfaction, whereas interpersonal resources were positively associated with body dissatisfaction (although negative bivariate correlations in this latter case suggest possible suppression effects). Finally, body dissatisfaction was associated with a range of disordered eating behaviors and exercise. DISCUSSION Early adverse experiences are important to consider in models of disordered eating. The results of this study highlight potential points of early prevention efforts, such as improving personal resources for those who experience early adversity, to help reduce the risk of body dissatisfaction and disordered eating in young women.
A Hardware Virtualization Based Component Sandboxing Architecture

Modern applications comprise multiplecomponents, such as browser plug-ins, often of unknownprovenance and quality. Statistics show that failure of suchcomponents accounts for a high percentage of softwarefaults. Enabling isolation of such fine-grained componentsis therefore necessary to increase the robustness andresilience of security-critical and safety-critical computersystems. In this paper, we evaluate whether such fine-grainedcomponents can be sandboxed through the use of thehardware virtualization support available in modern Inteland AMD processors. We compare the performance andfunctionality of such an approach to two previous softwarebased approaches. The results demonstrate that hardwareisolation minimizes the difficulties encountered withsoftware based approaches, while also reducing the size ofthe trusted computing base, thus increasing confidence inthe solution’s correctness. We also show that our relativelysimple implementation has equivalent run-timeperformance, with overheads of less than 34%, does notrequire custom tool chains and provides enhancedfunctionality over software-only approaches, confirmingthat hardware virtualization technology is a viablemechanism for fine-grained component isolation.
Decision-Making Trial and Evaluation Laboratory

The aim of this study is introducing a technique to illuminate composite issue, aspects or system factors, the complicated problems need to be structured with graphical illustration and analyzed casual interdependence and influences throughout the organization. Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology is proposed to for researching and solving complex and intertwined problem groups because of its capability in verifying interdependence between variables and try to improve them by offering a specific chart to reflect interrelationships between variables. In this technique experts plays complementary and approval role in all steps and sections. , key factors will be clarified by using the direct-influenced matrix and then it specifies priorities of each factor. The end product of the DEMATEL process is a visual demonstration-the Impact-Relations Map (IRM)-by which respondents organize their own actions in the world. First In this study, DEMATEL methodology in explained and then kind of different problems which can be solved by DEMATEL, will discussed and finally the method of DEMATEL is detailed completely.
Dendritic sodium spikes are required for long-term potentiation at distal synapses on hippocampal pyramidal neurons

Dendritic integration of synaptic inputs mediates rapid neural computation as well as longer-lasting plasticity. Several channel types can mediate dendritically initiated spikes (dSpikes), which may impact information processing and storage across multiple timescales; however, the roles of different channels in the rapid vs long-term effects of dSpikes are unknown. We show here that dSpikes mediated by Nav channels (blocked by a low concentration of TTX) are required for long-term potentiation (LTP) in the distal apical dendrites of hippocampal pyramidal neurons. Furthermore, imaging, simulations, and buffering experiments all support a model whereby fast Nav channel-mediated dSpikes (Na-dSpikes) contribute to LTP induction by promoting large, transient, localized increases in intracellular calcium concentration near the calcium-conducting pores of NMDAR and L-type Cav channels. Thus, in addition to contributing to rapid neural processing, Na-dSpikes are likely to contribute to memory formation via their role in long-lasting synaptic plasticity. DOI: http://dx.doi. org/10.7554/eLife.06414. 001
An Assessment of the Use of Technology in the Direct Selling Industry

Although research exists on the use of technology in sales, very little addresses the adoption, use, and success of technology in the direct selling industry. In response to this dearth of knowledge, we conducted an exploratory study to examine how direct sellers use technology to link the firm to its customers and its sales force, as well as how technology is used to facilitate interactions between the sales force and customers. In an industry that has historically differentiated itself by face to-face, personal relationships, we explore the possibly new direct selling environment brought on by the technology revolution. Through in-depth, open-ended interviews, we provide the groundwork for understanding how direct selling firms use technology to develop a competitive advantage while still maintaining strong personal relationships with consumers.
Tumor Size and Computed Tomography Attenuation of Pulmonary Pure Ground-Glass Nodules Are Useful for Predicting Pathological Invasiveness

Objectives Pulmonary ground-glass nodules (GGNs) are occasionally diagnosed as invasive adenocarcinomas. This study aimed to evaluate the clinicopathological features of patients with pulmonary GGNs to identify factors predictive of pathological invasion. Methods We retrospectively evaluated 101 pulmonary GGNs resected between July 2006 and November 2013 and pathologically classified them as adenocarcinoma in situ (AIS; n = 47), minimally invasive adenocarcinoma (MIA; n = 30), or invasive adenocarcinoma (I-ADC; n = 24). The age, sex, smoking history, tumor size, and computed tomography (CT) attenuation of the 3 groups were compared. Receiver operating characteristic (ROC) curve analyses were performed to identify factors that could predict the presence of pathologically invasive adenocarcinomas. Results Tumor size was significantly larger in the MIA and I-ADC groups than in the AIS group. CT attenuation was significantly greater in the I-ADC group than in the AIS and MIA groups. In ROC curve analyses, the sensitivity and specificity of tumor size (cutoff, 11 mm) were 95.8% and 46.8%, respectively, and those for CT attenuation (cutoff, −680 HU) were 95.8% and 35.1%, respectively; the areas under the curve (AUC) were 0.75 and 0.77, respectively. A combination of tumor size and CT attenuation (cutoffs of 11 mm and −680 HU for tumor size and CT attenuation, respectively) yielded in a sensitivity and specificity of 91.7% and 71.4%, respectively, with an AUC of 0.82. Conclusions Tumor size and CT attenuation were predictive factors of pathological invasiveness for pulmonary GGNs. Use of a combination of tumor size and CT attenuation facilitated more accurate prediction of invasive adenocarcinoma than the use of these factors independently.
The Linkages between Energy Efficiency and Security of Energy Supply in Europe

It can be argued that one way to reduce the dependence from external energy sources, is simply to reduce the demand for energy. Energy savings may thus be considered a policy priority when concerns for energy security are particularly strong. Drawing on an original econometric approach, we check whether policies and measures that affect indicators of energy efficiency performance have an analogous effect on security of supply indicators, both at the whole economy level and within the main sectors of energy use in the EU 15 countries and Norway. Our analyses show that the indicators studied are affected by a number of policies and measures; however very few of them seem able to tackle effectively and simultaneously, energy efficiency, carbon efficiency and energy security. The main lesson to be drawn from this analysis is therefore that there is a number of energy efficiency policies in the EU that do work, but there is no silver bullet able to successfully address different policy objectives. Taking a more general perspective, what seems to work is the policy mix rather than this or that policy in insulation.
Political Prediction Markets : Can we use them to predict election outcomes ?

Political prediction markets such as INTRADE, in which people trade stocks based on their belief about the outcome of the election or political event, offer a unique opportunity to use market behavior to predict the outcome of political events. This paper provides a two-fold contribution to the literature. First, we analyze 457 political prediction markets contracts in terms of the accuracy of their predictions at various time intervals and high-level categorizations. Second, we attempt to forecast the outcome of political prediction markets using a standard feedforward/backpropagation neural network trained on the time history of contract prices. We find that we can out perform the market predictions by between 1% 4% percent during times earlier than half-way to contract expiry. This suggests the market is not the most efficient aggregation of the likelihood of a future political event at these short times.
Detection and location of interturn short circuits in the stator windings of operating motors

One major cause of motor failures is breakdown of the turn insulation leading to puncture of the groundwall. Early detection of interturn shorts during motor operation would eliminate consequential damage to adjacent coils and the stator core reducing repair costs and motor outage time. In addition to the benefits gained from early detection of turn insulation breakdown, significant advantages would accrue by locating the faulted coil within the stator winding. Fault location would not only increase the speed of the repair, but would also permit more optimal scheduling of the repair outage. This work was successful in practically implementing a theory to predict changes in the axial leakage flux resulting from stator winding interturn shorts and in developing an algorithm to locate the position of the faulted coil. An experimental setup consisting of a 200 hp motor loaded by a generator was used to validate this theory. Suitable transducers were developed and installed on this motor. Measurement using this experimental configuration clearly validated the theoretical model. On the basis of this experimental work an instrument to continuously monitor for shorted turns is under development. >
Self-configuration for surveillance sensor network

This paper describes an autonomous monitoring system to supervise environmental parameters such as temperature, humidity, poisonous gases or smoke concentration, etc. This system is designed as a set of sensor nodes connected via a wireless network. The feature of this system is its ability to autonomously configure the network structure and synchronize data between nodes. This allows the network to be fault-tolerant. Each sensor node consists of three layers. The bottom layer includes a 5 to 12 volts battery and a stabilizer. The middle level consists of an 8-bit microcontroller, LCD (Liquid Crystal Display), SD (Secure Digital) card reader, and a set of sensors. The top level includes RF (Radio Frequency) communication module and GPS (Global Positioning System) module. Each sensor node is able to work as a standalone unit and as a part of a sensor network. The experimental works were performed for ensuring worth using in real time.
MAC protocols based on busy duration for underwater acoustic networks

Long propagation delay and low bit rate of underwater acoustic networks (UANs) make these systems fundamentally different from the radio networks. Especially, high propagation delay of acoustic waves makes UANs low efficiency and poor performance. In this paper, we investigate how UANs' throughput may be enhanced via medium access control (MAC) techniques and propose two new MAC protocols called handshaking with busy duration (HDSK-BD) and Aloha with busy duration (Aloha-BD), which takes advantage of long propagation delay in underwater channel by achieving busy durations of other nodes. Simulation tests on OPNET radio modeler show that two schemes proposed have better performance.
Inflation Convergence within the European Union: A Panel Data Analysis

This paper investigates the question of whether there exists evidence in support of inflation convergence within the European Union. The analysis also focuses on whether the Exchange Rate Mechanism (ERM) helped to accelerate inflation convergence in its member countries. The results of this paper are supportive of convergence. The countries which continuously participated in the narrow ERM bands show a dramatically higher convergence rate during the period following establishment of the mechanism.
The Relationship Between Military Expenditure and Economic Growth in Four Asian Countries

In this study, we use the ARDL bounds testing procedure suggested by Pesaran (2001) and modified version of the Granger causality test proposed by Toda and Yamamoto (1995) to test the robustness of the causality effect between military expenditure and economic growth in 4 Asian countries, two industrial countries (South Korea and Malaysia), and others are developing countries (Iran and Saudi Arabia), from 1988 to 2006 years, data series obtained from word development indicator (WDI). With respect to that military expenditure can affect economic growth so increase in GDP can increase or decrease military expenditure, too. We investigate the causality relationship between military expenditure and economic growth because the purpose of military expenditures is to provide national security. The results show that Iran and Saudi Arabia don’t have any causality relationship between military expenditure and economic growth. The results of South Korea show a unidirectional relationship from LGDP (Logarithm of real GDP) and LGDPK (logarithm of real GDP per capita) to military expenditure, and in Malaysia there is unidirectional relationship from LGDPK to military expenditure. The comparison of these results, we can say that developing countries don’t have meaningful relationship between military expenditure and economic growth, but we can find unidirectional or bidirectional relationship between military expenditure and economic growth in industrial countries.
An Advantage for Active versus Passive Aperture-Viewing in Visual Object Recognition

In aperture viewing the field-of-view is restricted, such that only a small part of an image is visible, enforcing serial exploration of different regions of an object in order to successfully recognise it. Previous studies have used either active control or passive observation of the viewing aperture, but have not contrasted the two modes. Active viewing has previously been shown to confer an advantage in visual object recognition. We displayed objects through a small moveable aperture and tested whether people's ability to identify the images as familiar or novel objects was influenced by how the window location was controlled. Participants recognised objects faster when they actively controlled the window using their finger on a touch-screen, as opposed to passively observing the moving window. There was no difference between passively viewing again one's own window movement as generated in a previous block of trials versus viewing window movements that had been generated by other participants. These results contrast with those from comparable studies of haptic object recognition, which have found a benefit for passive over active stimulus exploration, but accord with findings of an advantage of active viewing in visual object recognition.
Evaluating the Impact of Transmission Power on QoS in Wireless Mesh Networks

Wireless interference is a natural problem of single radio Wireless Mesh Networks (WMN) that operate on a shared medium. Noise induced by simultaneously sending nodes within the same transmission range leads to less throughput and a higher latency. These are critical for the overall quality of a network and regulate the level of achieved QoS. Reducing the transmission power implies less interference on the medium, but also less robust links. Therefore finding an optimal transmission power level may be one solution to increase the efficiency of single radio WMN. We analyze the impact of transmission power control (TPC) on wireless interference within a real testbed environment, and show that transmission power control leads to a better throughput and latency.
RISING WAGE DISPERSION ACROSS AMERICAN MANUFACTURING

2 We use data from the manuscript censuses of manufacturing for 1850, 1860, 1870, and 1880 to study the dispersion of average monthly wages across establishments. We find a marked increased in wage inequality over the period, an increase that cannot be explained by biases in the data or changes in census enumeration procedures. Based on log wage regressions on establishment characteristics (for example, size, capital intensity, use of steam power, and so on) we compute a decomposition of the change in wage inequality between 1850 and 1880. The decomposition reveals that changes in “wage structure” – the regression coefficients and the standard error of the residuals – largely offset each: changes in the coefficients produced a reduction in wage inequality, while residual inequality increased. Most of the rise in wage inequality can be attributed to an increased concentration of employment in large establishments, which paid relatively low wages. We present indirect evidence that the negative effect of size on wages reflected differences in skill composition: workforces in large establishments were less skilled than in small establishments. Jeremy Atack Department of Economics Vanderbilt University Nashville TN 37235 and NBER jeremy.atack@vanderbilt.edu Fred Bateman Department of Economics Terry College of Business University of Georgia Athens GA 30602 bateman@terry.uga. edu Robert A. Margo The Jerome Levy Economics Institute of Bard College Blithewood Annandale-on-Hudson NY 12504-5000 and NBER margo@levy.org
Light deflection in perturbed Friedmann universes.

A new formula for light deflection is derived using only physically observable concepts. The general result is specialized to cosmological perturbation theory and expressed in terms of gauge-invariant perturbation variables. The resulting scalar, vector and tensor equations are supplemented by simple examples for illustration. The gravity wave example may be of more than academic interest and even represent a new way to detect gravitational waves.
Obesity and Metabolic Syndrome in Korea

In Korea, a person with a body mass index (BMI) ≥25 kg/m2 is considered obese, and a person with a BMI ≥30 kg/m2 is classified as severely obese. Central obesity is defined as a waist circumference ≥90 cm for Korean men and ≥85 cm for Korean women. Recent epidemiologic data show that the prevalence of severe obesity and metabolic syndrome is steadily increasing. These epidemics increased morbidity and mortality of type 2 diabetes, cardiovascular diseases, and obesity-related cancers such as breast, colorectal, and other cancers in Korea. Decreased physical activity, increased fat and alcohol consumption, heavy smoking, and stress/depressed mood are the primary modifiable life-style risk factors for Koreans. Recently, public health interventions to encourage life-style changes have shown promising results in reducing the prevalence of severe obesity and metabolic syndrome.
Integrating machine learning in embedded sensor systems for Internet-of-Things applications

Interpreting sensor data in Internet-of-Things applications is a challenging problem particularly in embedded systems. We consider sensor data analytics where machine learning algorithms can be fully implemented on an embedded processor/sensor board. We develop an efficient real-time realization of a Gaussian mixture model (GMM) for execution on the NXP FRDM-K64F embedded sensor board. We demonstrate the design of a customized program and data structure that generates real-time sensor features, and we show details and training/classification results for select IoT applications. The integrated hardware/software system enables real-time data analytics and continuous training and re-training of the machine learning (ML) algorithm. The real-time ML platform can accommodate several applications with lower sensor data traffic.