Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotion regulation and psychological problems among Indian college youth

Background: Study of emotion regulation strategies used by youth becomes necessary in the background of the high prevalence of emotional disorders in this population. This study examined emotion regulation and psychological problems among college youth as well as the relationship between the two. Methodology: Four hundred and nineteen students, who were divided into two groups (older adolescents, aged 16-17 years - group 1, n = 217; young adults aged 18-25 years - group 2, n = 202) participated in this exploratory study. Results: Predominantly positive emotion regulation strategies were used by group 1 (positive refocusing, refocus on planning, and positive reappraisal, respectively). The sample as a whole used more positive strategies (positive refocusing: 82% and 64% and refocus on planning: 93% and 87% in groups 1 and 2, respectively). Significant correlations between emotion regulation strategies (CERQ) and psychological problems (YSR/YASR) were found, thereby indicating that negative emotion regulation strategies were associated with psychological problems and vice versa. Females were found to have more of anxiety problems as opposed to males with more of conduct problems. However with increase in age, increase in the percentage of psychological problems and usage of negative emotion regulation strategies was observed. Conclusion: The findings of the present study contribute to understanding the patterns of emotion regulation in various emotional disorders. Findings could also contribute to developing an intervention program to help students having difficulty in regulation of their emotions.
Approximating subdivision surfaces with Gregory patches for hardware tessellation

We present a new method for approximating subdivision surfaces with hardware accelerated parametric patches. Our method improves the memory bandwidth requirements for patch control points, translating into superior performance compared to existing methods. Our input is general, allowing for meshes that contain both quadrilateral and triangular faces in the input control mesh, as well as control meshes with boundary. We present two implementations of our scheme designed to run on Direct3D 11 class hardware equipped with a tessellator unit.
An Adaptive Image Enhancement Algorithm Based on Zone System

The main objective of image enhancement is to improve the visual quality of digital images that are captured under extremely low or non-uniform lighting conditions. We present an adaptive image enhancement algorithm based on Zone System. This study reveals hidden image details and increases the contrast of an image with low dynamic range. It is comprised two processes: adaptive luminance enhancement and adaptive contrast enhancement. The adaptive luminance enhancement algorithm is a global intensity transform function based on Zone System information. This process not only increases the luminance of darker pixels but also compresses the dynamic range of the image. The adaptive contrast enhancement adjusts the intensity of each pixel based on the discontinuities of the local luminance. It also improves the contrast of local region and reveals the details of image clearly. The proposed algorithm has good performance on enhancing contrast, preserving more detail of characteristics and sharpening edges of objects in experimental results. The performance with our proposed was better evaluation and comparison than other algorithms in the subjective and objective evaluation.
An Efficient Method for Incremental Mining of Share-Frequent Patterns

The share measure of item sets has been proposed to discover useful knowledge about numerical values associated with items in a transaction database. Therefore, share-frequent pattern mining problem becomes a very important research issue in data mining. However, the existing algorithms of share-frequent pattern mining are based on static databases. Moreover, they are not suitable for interactive mining. In this paper, we propose a novel tree structure IncrShrFP-Tree (Incremental Share-Frequent Pattern Tree) for incremental and interactive share-frequent pattern mining. It is effective for incremental and interactive mining to utilize the previous tree structure and to use the previous mining results when a database is updated or a minimum support threshold is changed. It needs maximum two database scans to calculate the resultant share-frequent patterns in incremental databases. Extensive performance analyses show that our method is very efficient for incremental and interactive share-frequent pattern mining.
OBSERVATION A New Mutation of the Gene , G 303 V , in Early-Onset Familial Progressive Supranuclear Palsy

P ROGRESSIVE SUPRANUCLEAR palsy (PSP) is usually sporadic, although some familial cases have been described. Mutations in the gene, encoding for the microtubuleassociated protein , have been mainly related to frontotemporal dementia with parkinsonism linked to chromosome 17 (FTDP-17). Frontotemporal dementia with parkinsonism linked to chromosome 17 is characterized by atypical parkinsonism or frontotemporal dementia. Typical cases of PSP and FTDP-17 can be differentiated by clinical symptoms because dementia appears early in FTDP-17 and late or in milder form in PSP. However, atypical familial PSP has also been related to gene mutations. We describe herein a family with clinicopathological features of PSP presenting a novel mutation in the gene, G303V. Analysis of brain proteins revealed hyperphosphorylation of and an increased 4 microtubule-binding repeat (4R)–3 microtubule-binding repeat (3R) ratio of isoforms. METHODS
Leakage Detection Via Model Based Method

This paper presents a model based approach for real time leakage detection in a nonlinear multi tank flow rig. A state space model of the process was derived based on the expansion of the nonlinear function into a Taylor's series about the operating point and the retention of only the linear term. The model based approach performs consistency checks of the process against the state space model of the process. Using fault detection technique, leakage indicating signals were generated. False detection due to uncertainty as a result of using the linearised reference mathematical model and sensor noise can be avoided by referring to real time measurement data recorded when system is operating normally. This method has been implemented in real time and results show promising potentials.
Multi-mode wide-band 130 nm CMOS WLAN and GSM/UMTS

This paper presents a fully integrated VCO covering the requirements of four cellular phone standards GSM, DCS, PCS and UMTS as well as WLAN 802.11 a/b/g. The frequency range from 3.42 GHz up to 11.45 GHz is managed with an innovative differential switchable inductor architecture. In addition a switched capacitor array and varactors are applied for precise tuning of all necessary frequency bands. The circuit is fabricated in a 130 nm CMOS process and housed into a VQFN 48 plastic package together with a proper direct conversion Rx-frontend solution for the cellular modes. The VCO has been measured and draws less than 13 mA at a supply voltage of 1.5 V whereas the VCO core needs only 2 mA. The evaluation of the VCO was done on a FR4 board.
Denoising and signal detection for pulse position modulation 60 GHz impulse radio based on sparse representation

A 60 GHz Impulse Radio (IR) communications system has a simple architecture and operates at low power levels, thus it is a promising technology for future very high speed wireless networks. A signal detection method with noise suppression based on sparse signal representation is proposed in this paper. Because of the low duty cycle and spike-like characteristics of 60 GHz IR signals, an overcomplete dictionary is employed. Guidelines to construct this dictionary for signals on AWGN channels are presented. Results show that the noise can be significantly reduced and the PPM IR signals can be detected directly with the proposed method.
The Neuronal-Specific SGK1.1 (SGK1_v2) Kinase as a Transcriptional Modulator of BAG4, Brox, and PPP1CB Genes Expression

The Serum- and Glucocorticoid-induced Kinase 1, SGK1, exhibits a broad range of cellular functions that include regulation of the number of ion channels in plasma membrane and modulation of signaling pathways of cell survival. This diversity of functions is made possible by various regulatory processes acting upon the SGK1 gene, giving rise to various isoforms: SGK1_v1–5, each with distinct properties and distinct aminotermini that serve to target proteins to different subcellular compartments. Among cellular effects of SGK1 expression is to indirectly modulate gene transcription by phosphorylating transcriptional factors of the FOXO family. Here we examined if SGK1.1 (SGK1_v2; NM_001143676), which associates primarily to the plasma membrane, is also able to regulate gene expression. Using a differential gene expression approach we identified six genes upregulated by SGK1.1 in HeLa cells. Further analysis of transcript and protein levels validated two genes: BCL2-associated athanogene 4 (BAG-4) and Brox. The results indicate that SGK1.1 regulates gene transcription upon a different set of genes some of which participate in cell survival pathways (BAG-4) and others in intracellular vesicular traffic (Brox).
Coupling of surface pCO2 and dissolved oxygen in the northern South China Sea: Impacts of contrasting coastal processes

Abstract. We examined the relationship between CO2 partial pressure (pCO2) and dissolved oxygen (DO) based on a cruise conducted in July 2004 to the northern South China Sea (111°–118° E 18°–23° N), spanning from estuarine plume, coastal upwelling and deep basin areas. Distinct relationships between pCO2 and DO saturation were identified in different regimes. In coastal upwelling areas and the Pearl River estuary, biological drawdown of pCO2 and production of O2 were simultaneously observed. The two properties were coupled with each other primarily via photosynthesis and respiration. The stoichiometric relationship of the two properties however, was quite different in these two environments due to different values of the Revelle factor. In the offshore areas, apart from the estuary and upwelling, the dynamics of pCO2 and DO were mainly influenced by air-sea exchange during water mixing. Given the fact that air-sea re-equilibration of O2 is much faster than that of CO2, the observed pCO2-DO relationship deviated from that of the theoretical prediction based on the Redfield relationship in the offshore areas. Although this study is subject to the limited temporal and spatial coverage of sampling, we have demonstrated a simple procedure to evaluate the community metabolic status based on a combination of high-resolution surface pCO2 and DO measurements, which may have applicability in many coastal systems with a large gradient of changes in their physical and biogeochemical conditions.
Analytical Data Mining for Stream Data Analysis

The main idea behind this research relies on analytical data mining functions to handle data streams. Given the characteristics of the data stream, the new methods and techniques for stream data analysis must conduct advanced analysis and data mining over fast and large data streams to capture the trends, patterns and exceptions. Besides, much of such data resides at rather low level of abstraction, whereas most analysts are interested in dynamic changes at relatively high levels of abstractions. Furthermore, recently studies are heading to combine ideas of cube-based algorithms with data mining functions to reveal exceptional and trend patterns over data streams. Thus, this work intends to provide new methods for effective and efficient analytical data mining over data streams.
Proxies: design principles for robust object-oriented intercession APIs

Proxies are a powerful approach to implement meta-objects in object-oriented languages without having to resort to metacircular interpretation. We introduce such a meta-level API based on proxies for Javascript. We simultaneously introduce a set of design principles that characterize such APIs in general, and compare similar APIs of other languages in terms of these principles. We highlight how principled proxy-based APIs improve code robustness by avoiding interference between base and meta-level code that occur in more common reflective intercession mechanisms.
Flexible Transfer Functions with Ontogenic Neural Networks

Transfer functions play a very important role in learning process of neural systems. This paper presents new functions which are more flexible than other functions commonly used in artificial neural networks. The latest improvement added is the ability to rotate the contours of constant values of transfer functions in multidimensional spaces with only N − 1 adaptive parameters. Rotation using full covariance matrices requires N parameters. These functions have biases and slopes separable in each dimension for each neuron, completely independent in multi-dimensional spaces. Therefore they are dimensionally separable — each dimension may be excluded independently at any time. As the neural network model for testing the performance of these new transfer functions the Incremental Network (IncNet) was chosen. These networks are similar to radial basis function (RBF) networks and resource allocating networks. The architecture of IncNet is the same as the architecture of RBF networks, but the structure (the number of hidden nodes) changes during the learning process according to certain statistical criterion that controls growth and pruning of network connections. Preliminary results show superior performance of the new transfer functions comparing with gaussian functions often used by RBF networks and other models.
Recognizing Human Emotional State Based on the 2D-FrFT and FLDA

Computer recognition of human emotional states is an important component for efficient human-computer interaction. In this paper we explore an approach for recognition of human emotion from the visual information. We perform feature selection by using The Two Dimensions Fractional Fourier Transform. As a generalization of Fourier transform, the Two Dimensions Fractional Fourier Transform (2D-FrFT) contains simultaneity the time-frequency information of the signal, and is considered as a new tool for time-frequency analysis, especially in the area of image recognition. In this paper we use the amplitude of the 2D-FrFT of an image as the feature of the images to train the FLDA multiclassifier for human emotion recognition. Simulation result shows that this method of the features extraction and classifier has high recognition rate.
Greedy routing performance analysis of network embedded in Hyperbolic and Euclidean Space

In a network, routing is the fundamental task. The routing has large overhead, due to which it is bottleneck to the performance and scalability of the network. The networks implementing Geographic Routing protocols are highly scalable as these allow stateless routing. The inconsistency between the two topologies, the actual network topology and modelled network topology degrades the performance of the network. The performance of the network increases if the networks are embedded in Hyperbolic Space rather than Euclidean Space. In this paper, we evaluate the performance of greedy routing in networks embedded in Hyperbolic Space and Euclidean Space. The evaluation is done on success percentage and hop stretch metrics.
NII-UIT at MediaEval 2014 Violent Scenes Detection Affect Task

Violent scene detection (VSD) is a challenging problem because of the heterogeneous content, large variations in video quality, and semantic meaning of the concepts. The Violent Scenes Detection Task of MediaEval [1] provides a common dataset and evaluation protocol thus enables a fair comparison of methods. In this paper, we describe our VSD system used in MediaEval 2014 and brieﬂy discuss the performance results obtained in main subjective tasks. In this year, we focus on improving the trajectory-based motion features that have been proven eﬀective in previous year’s evaluation. Besides that, we also adopt SIFT-based and audio features as in last year’s system. We combined these features using late fusion. Our results show that the trajectory-based motion features still have very competitive performance and the combination with still image features and audio features can improve overall performance.
Multi-dimensional Fault Diagnosis Using a Subspace Approach

Fault detection and process monitoring using principal component analysis (PCA) have been studied intensively and applied to industrial processes. PCA is used to deene an orthogonal partition of the measurement space into two orthogonal subspaces: a principal component sub-space (PCS), and a residual subspace (RS). In this paper, each process fault is also described by a subspace and the fundamental issues of fault detectability, reconstructabil-ity, identiiability and isolatability are analyzed. Based on the fault subspace, fault magnitude and the PCS, necessary and suucient conditions are provided to determine if the faults from a simulated process are detectable, recon-structable, identiiable and isolatable.
Application of the central composite design to optimize the preparation of novel micelles of harmine

Lactose–palmitoyl–trimethyl–chitosan (Lac-TPCS), a novel amphipathic self-assembled polymer, was synthesized for administration of insoluble drugs to reduce their adverse effects. The central composite design was used to study the preparation technique of harmine (HM)-loaded self-assembled micelles based on Lac-TPCS (Lac-TPCS/HM). Three preparation methods and single factors were screened, including solvent type, HM amount, hydration volume, and temperature. The optimal preparation technique was identified after investigating the influence of two independent factors, namely, HM amount and hydration volume, on four indexes, ie, encapsulation efficiency (EE), drug-loading amount (LD), particle size, and polydispersity index (PDI). Analysis of variance showed a high coefficient of determination of 0.916 to 0.994, thus ensuring a satisfactory adjustment of the predicted prescription. The maximum predicted values of the optimal prescription were 91.62%, 14.20%, 183.3 nm, and 0.214 for EE, LD, size, and PDI, respectively, when HM amount was 1.8 mg and hydration volume was 9.6 mL. HM-loaded micelles were successfully characterized by Fourier-transform infrared spectroscopy, differential scanning calorimetry, X-ray diffraction, and a fluorescence-quenching experiment. Sustained release of Lac-TPCS/HM reached 65.3% in 72 hours at pH 7.4, while free HM released about 99.7% under the same conditions.
MetroBuzz: Interactive 3D visualization of spatiotemporal data

The rapidly increasing use of mobile devices for sensing applications, and the growing amount of simulated data generated from simulation tools such as agent-based transport simulations results in massive spatiotemporal datasets. Therefore, the demand for applications to manage and to visualize this data effectively in an interactive and easily understandable way increases quickly. Spatiotemporal visualization has long been recognized as being able to provide a suitable solution for creating such applications. However it remains a challenging task to combine such a visualization with interactive operation. In this paper, we describe MetroBuzz, a prototype system designed for visualizing large amounts of spatiotemporal data, and for interacting with the dataset in a way that is both interesting from a scientific viewpoint as well as for a broader non-expert audience. At its core, MetroBuzz generalizes activities in urban networks, specified as origin-destination trip information in terms of series of line segments in 3D space. These 3D elements are stored in a spatial index that allows quick retrieval of relevant data. Based on this, we implemented interactive tools to define queries on the spatial index in an intuitive manner. We show how such tools can be applied in the case of large transport simulation datasets.
Translation Quality Assessment. Strategies, Parametres and Procedures

L'evaluation de la qualite de la traduction a souvent fait les frais de jugements impressionnistes et souvent paradoxaux s'appuyant sur une esthetique bien vague. Cette etude cherche a construire un modele empirique d'evaluation de la qualite qui s'appuie sur des parametres objectifs de typologie textuelle, de correspondance formelle, de coherence thematique, de cohesion referentielle, d'equivalence pragmatique et de proprietes lexicosyntactiques. La verification de la viabilite de ce modele eclectique passe par son application a l'analyse textuelle d'un texte evocateur (une publicite) avec pour but de faire ressortir les points convergents et divergents.
Model-Free 3D Reconstruction of Weld Joint Using Laser Scanning

This article presents a novel utilization of the concept of entropy in information theory to model-free 3D reconstruction of weld joint in presence of noise. We show that our formulation attains its global minimum at the upper edge of this joint. This property significantly simplifies the extraction of this welding joint. Furthermore, we present an approach to compute the volume of this extracted space to facilitate the monitoring of the progress of the welding task. Moreover, we provide a preliminary analysis of the effect of variation of the noise on the extraction process of this space to realize the impact of this noise on the computation of its area and volume.
Spectral diffusion map approach for structural health monitoring of wind turbine blades

In this paper, we develop data-driven method for the diagnosis of damage in mechanical structures using an array of distributed sensors. The proposed approach relies on comparing intrinsic geometry of data sets corresponding to the undamage and damage state of the system. We use spectral diffusion map approach for identifying the intrinsic geometry of the data set. In particular, time series data from distributed sensors is used for the construction of diffusion map. The low dimensional embedding of the data set corresponding to different damage level is done using singular value decomposition of the diffusion map to identify the intrinsic geometry. We construct appropriate metric in diffusion space to compare the different data set corresponding to different damage cases. The application of this approach is demonstrated for damage diagnosis of wind turbine blades. Our simulation results show that the proposed diffusion map-based metric is not only able to distinguish the damage from undamage system state, but can also determine the extent and the location of the damage.
From Solitary to the Streets: The Effect of Restrictive Housing on Recidivism

ABSTRACT Restrictive housing is sometimes required for the sake of safety and institutional order. However, many observers have argued that this practice is inhumane and leaves inmates at a greater risk of recidivism. This study empirically examined the effect of restrictive housing on recidivism using a cohort of released state prisoners. The results revealed that time spent in restrictive housing increased the risk of supervision revocations up to two years after release, but did not significantly increase the likelihood of rearrest or re-conviction. Thus, rule-breaking behaviors appear to continue into the community, but not necessarily continued criminal offending.