Miracle-dz/UniFAR-FTUs huggingface dataset:
“Small Talk” : Young children in the general population as informants of their problem behavior

markdownabstract__Abstract__ Accurate diagnosis of young children’s problem behavior is of great importance for understanding the early development of psychopathology and for early and effective interventions. Children, even young children, may offer a valuable complement to information from the traditional adult informants. Yet, in the Netherlands, no validated instrument was available to systematically assess young children’s perspective on their feelings and behavior. To address this gap, the Berkeley Puppet Interview (BPI) was translated into Dutch and introduced in the Generation R Study, a large epidemiological study. The series of studies described in this thesis examined whether information about emotional, behavioral and peer relationship problems, obtained by the Dutch translation of the BPI, provides reliable, valid and valuable information that can be used in research settings. The studies also examined the value of young children’s reports if implemented along with other outcomes in a multi-informant approach.
International Capital Mobility and Current Account Targeting in Central and Eastern European Countries

The paper examines the degree of financial integration in five central and eastern European economies on the basis of saving-investment correlations. A comparison with eleven member states of the European monetary union shows that the countries under review have already reached a higher degree of integration in quantitative terms. Since this approach is sensitive to current account targeting policies, the paper uses econometric techniques to control for these kinds of policies revealing that the central and eastern European countries that suffered from current account crises in the past used policies to balance the current account.
Effects of hepatocyte growth factor on the expression of matrix metalloproteinases and their tissue inhibitors during the endometrial cancer invasion in a three‐dimensional coculture

Matrix metalloproteinase (MMP)-2 and -9 are secreted and translocated from endometrial stromal cells to HEC-1 A cells in a steroid-dependent manner. We investigated the paracrine effect of hepatocyte growth factor (HGF) on MMPs and metalloproteinase tissue inhibitor (TIMP) expression in stromal and endometrial cancer cells, and correlated with cancer cell invasiveness in three-dimensional (3D) coculture. The 3D coculture of endometrial stromal and cancer cell lines (HEC-1 A, HEC-IB, or KLE) were maintained in the presence or absence of HGF. The expression of MMP-2 and -9, MT1-MMP, TIMP-1 and -2 were examined by RT-PCR and zymography. Under the same conditions, invasion of the cancer cells was quantified by Boyden's chamber assay. HGF strongly induced MMP-9 mRNA expression in stromal cells, but had little effect on MMP-2 mRNA. MT1-MMP mRNA was detected only in KLE and stromal cells, which was also increased by HGF. TIMP-1 and -2 mRNAs was ubiquitous with no dependence on HGF. Zymographic analysis of MMPs showed that activation of MMP-2 and -9 was enhanced by HGF. A significant increase in invasion of all three cancer cells with HGF was observed. The effect of HGF on the invasiveness of 3D cocultured endometrial cancer cells and stromal cells appears to be due to induction of MMP-9 mRNA expression in stromal cells and /or increased activation of MMP-2 and MMP-9 by proteolytic digestion.
Significant reduction of BiFC non-specific assembly facilitates in planta assessment of heterotrimeric G-protein interactors

Protein networks and signaling cascades are key mechanisms for intra- and intercellular signal transduction. Identifying the interacting partners of a protein can provide vital clues regarding its physiological role. The bimolecular fluorescence complementation (BiFC) assay has become a routine tool for in vivo analysis of protein–protein interactions and their subcellular location. Although the BiFC system has improved since its inception, the available options for in planta analysis are still subject to very low signal-to-noise ratios, and a systematic comparison of BiFC confounding background signals has been lacking. Background signals can obscure weak interactions, provide false positives, and decrease confidence in true positives. To overcome these problems, we performed an extensive in planta analysis of published BiFC fragments used in metazoa and plants, and then developed an optimized single vector BiFC system which utilizes monomeric Venus (mVenus) split at residue 210, and contains an integrated mTurquoise2 marker to precisely identify transformed cells in order to distinguish true negatives. Here we provide our streamlined double ORF expression (pDOE) BiFC system, and show that our advance in BiFC methodology functions even with an internally fused mVenus210 fragment. We illustrate the efficacy of the system by providing direct visualization of Arabidopsis MLO1 interacting with a calmodulin-like (CML) protein, and by showing that heterotrimeric G-protein subunits Gα (GPA1) and Gβ (AGB1) interact in plant cells. We further demonstrate that GPA1 and AGB1 each physically interact with PLDα1 in planta, and that mutation of the so-called PLDα1 ‘DRY’ motif abolishes both of these interactions.
Estimating Bounds on Collisional Relaxation Rates of Spin-Polarized 87Rb Atoms at Ultracold Temperatures

We present quantum scattering calculations for the collisional relaxation rate coefficient of spin-polarized 87Rb(f = 2,m = 2) atoms, which determines the loss rate of cold Rb atoms from a magnetic trap. Unlike the lighter alkali atoms, spin-polarized 87Rb atoms can undergo dipolar relaxation due to both the normal spin-spin dipole interaction and a second-order spin-orbit interaction with distant electronic states of the dimer. We present ab initio calculations for the second-order spin-orbit terms for both Rb2 and Cs2. The corrections lead to a reduction in the relaxation rate for 87Rb. Our primary concern is to analyze the sensitivity of the 87Rb trap loss to the uncertainties in the ground state molecular potentials. Since the scattering length for the a3Σ+u state is already known, the major uncertainties are associated with the X1Σ+g potential. After testing the effect of systematically modifying the short-range form of the molecular potentials over a reasonable range, and introducing our best estimate of the second-order spin-orbit interaction, we estimate that in the low temperature limit the rate coefficient for loss of Rb atoms from the f = 2,m = 2 state is between 0.4 × 10−15 cm3/s and 2.4 × 10−15 cm3/s (where this number counts two atoms lost per collision). In a pure condensate the rate coefficient would be reduced by 1/2.
Male depression: expression and coping strategies

This study was designed to investigate how adult men think about, express, and cope with depression. Middle-aged men (n=79) and women (n=86) indicated on a Likert scale the de gree to which they engage in a number of behaviors and cogni tions when depressed; distinct sex patterns emerged, (^he findings suggest that for men, depression is a private expe rience which must be resolved as quickly and quietly as pos sible.3 Unwilling to label themselves 'depressed' men respond to depression by denying their feelings, avoiding their emo tions, and camouflaging their depression either by actively hiding their depressive affect, or by expressing depressive affect but not labelling it as.: When depressed, men seek to control their emotions while utilizing cognitive, instrumental, and action oriented strategies to either resolve external situational problems or to distract themselves from their depressive emotions. (For women, expression of depression appears to represent a viable strategy for coping with life events and releasing emotion. When depressed, women focus on their subjective experience of depression and express their depression both privately (crying) and publically (seeking help and support from others). Depression for women repre sents a state of 'being' rather than an external problem re-
Analysis of Time and Frequency Domain Features of Accelerometer Measurements

This paper addresses the signal processing aspect of wireless sensor networks. It analyzes several time and frequency domain features of measurements that are taken from 3D accelerometer sensors. The measurements represent various types of movements related to humans and cars. The aim is to obtain quantitative as well as qualitative comparisons concerning the expression power of these features in the presence of various sources of uncertainties (calibration, placement of sensors, and time synchronization). For the qualitative analysis, we define fuzzy sets and fuzzy membership functions for all the features. Particular attention is given to the analysis of the existence of correlation between measurements of different sensor nodes. We will demonstrate that correlation coefficients of both time and frequency domain features exhibit high degrees of uncertainties. On the other hand, short time Fourier transformations (STFT) of all types of movements prove to be agnostic of various forms of measurement and calibration errors. I. INTRODUCTION
Antibody-Dependent Cellular Cytotoxicity Mediated by Cetuximab against Lung Cancer Cell Lines

Purpose: Epidermal growth factor receptor (EGFR) is commonly overexpressed in lung cancer. Cetuximab is a chimeric mouse-human antibody targeted against EGFR. Compared with its inhibitory properties, its immunologic mechanisms have not been well studied. In this study, we investigated the antibody-dependent cellular cytotoxicity (ADCC) activity of cetuximab against lung cancer cell lines. Experimental Design: We studied the correlation between EGFR expression in lung cancer cell lines and the ADCC activity of cetuximab as well as the influence of interleukin-2 and chemotherapy on the ADCC activity. EGFR expression was measured by a quantitative flow cytometric analysis and immunohistochemistry. The ADCC activity was assessed by a 4-h 51Cr release assay. Peripheral blood mononuclear cells, purified T cells, natural killer (NK) cells, and monocytes from healthy donors or lung cancer patients were used as effector cells. Results: Fresh peripheral blood mononuclear cells exhibited cetuximab-mediated ADCC activity against lung cancer cell lines at a low concentration of cetuximab (0.25 μg/mL). A logarithmic correlation was observed between the number of EGFRs and ADCC activity. Even low EGFR expression, which was weakly detectable by immunohistochemistry, was sufficient for maximum ADCC activity, and further increases in EGFR expression on the target cells had no further effect on the ADCC activity. In addition, ADCC activity was enhanced by interleukin-2 mainly through activation of NK cells and was less susceptible to immunosuppression by chemotherapy than NK activity in lung cancer patients. Conclusions: These observations suggest the importance of ADCC activity as an immunologic mechanism of cetuximab in biological therapy for lung cancer patients.
Multi-criterion mining algorithm for efficient Home Energy Management System

This paper presents new multi-criterion mining algorithm, which as a module of the Home Energy Management System (HEMS) can identify the operating states of a combination of controllable appliances. There is a close interaction between HEMS and this algorithm. The new incoming samples, collected by HEMS, are associated with appropriate cluster using the mining algorithm. This information is submitted back to HEMS which appropriately controls the appliances by switching them on/off. The strength of our mining algorithm is the combined usage of geometrical and statistical approach to the data clustering. The criteria that embody the geometrical approach include: identification of corresponding min-max parallelepipeds, embodying the new instance by the neighboring parallelepipeds and minimum distance criterion. Box-dimension with its definition as a measure of self-similarity is used as a statistical approach criterion. As a result from the testing of these criteria, we have achieved time optimization and improved accuracy, due to reducing of the number of potential clusters (reducing the number of testing instances but not excluding them for further analysis) without reducing the dimensionality of the clustering problem. The successful identification of the operating states of the appliances, done with our continuously learning algorithm, enables HEMS to improve energy efficiency and cost savings.
Firma : Disk-Based Foundations for Trusted Operating Systems

Secure boot mechanisms aim to provide guarantees of integrity of a system as it loads. It ensures that if a system is running, all of its process will satisfy integrity verification requirements. While secure boot has been available for a long time, it is not available in commodity systems due to the high cost of secure hardware. In this paper, we describe Firma, an architecture that provides secure boot functionality based on a storage root of trust. Unlike previous secure boot mechanisms, use of the disk can protect data secrecy by only releasing data to systems trusted not to leak data, while also providing data integrity through release to high integrity systems. We implement a prototype of Firma and show how it may be used to provide a trusted virtual machine monitor (TVMM) capable of supporting strong security guarantees for running VMs. Only minimal administration is required, and we detail the tasks necessary to support the architecture, showing new systems can be configured with a small number of automated steps. Our evaluation shows that Firma requires additional overhead of just over 1 second for the boot process.
On Relaxing and Steady State Genetic Methods for Satellite Imaging Scheduling

Satellite imaging scheduling problem with energy and memory limit belongs to NP-hard problems. As the mathematical programming model is built, a Lagrangian relaxation method can provide tight upper bound, using a max-weighted path algorithm in the constraint graph and a sub-gradient optimizing method to explore the minimum upper bound. Then, permutation based stochastic local search algorithms are used to optimize imaging scheduling results. Finally, the testing results demonstrate the efficiency of these methods.
Diabetes and glucose disturbances in patients with psychosis in Sweden

Objective The objectives of this study were to (1) analyze the prevalence of diabetes, prediabetes, and antidiabetic medication in patients with psychosis compared with control subjects and (2) determine what factors in patients with psychosis were associated with antidiabetic medication. Method We studied 977 patients with psychosis recruited from outpatient clinics in Stockholm County, Sweden, and they were compared with 3908 non-psychotic control subjects for fasting plasma glucose levels; prevalence of diabetes, prediabetes, antidiabetic treatment, and tobacco use; and blood pressure, weight, height, and waist circumference. Group differences were evaluated with analysis of variance and χ2 test, and factors associated with antidiabetic treatment were evaluated with logistic regression. Results Diabetes was observed in 94 (10%) patients with psychosis, 2.7 times the prevalence observed in control subjects. Among patients with psychosis, 87 (10%) had prediabetes (fasting glucose, 6.1–6.9 mmol/L) compared with 149 (3.8%) control subjects. Most patients with psychosis (77%) who had prediabetes fulfilled criteria for metabolic syndrome. In patients with psychosis, both lipid-lowering medication and fasting glucose were significantly associated with antidiabetic treatment. There was no significant relation between antidiabetic treatment and lifestyle factors such as smoking or degree of psychiatric illness. Conclusions The high prevalence of impaired fasting glucose and metabolic syndrome in patients with psychosis warrants further clinical research in preventing or delaying the onset of diabetes in these patients by pharmacotherapy and/or lifestyle intervention.
The Ribosome Scanning Model for Translation Initiation: Implications for Gene Prediction and Full-Length cDNA Detection

Biological signals, such as the start of protein translation in eukaryotic mRNA, are stretches of nucleotides recognized by cellular machinery. There are a variety of techniques for modeling and identifying them. Most of these techniques either assume that the base pairs at each position of the signal are independently distributed, or they allow for limited dependencies among different positions. In previous work, we provided a statistical model that generalizes earlier methods and captures all significant high-order dependencies among different base positions. In this paper, we use a set of experimentally verified translation initiation (TI) sites (provided by Amos Bairoch) from eukaryotic sequences to train a range of methods, and then compare these methods. None of the methods is effective in predicting TI sites. We take advantage of the ribosome scanning model (Cigan et al., 1988) to significantly improve the prediction accuracy for full-length mRNAs. The ribosome scanning model suggests scanning from the 5' end of the capped mRNA and initiating translation at the first AUG in good context. This reduces the search space dramatically and accounts for its effectiveness. The success of this approach illustrates how biological ideas can illuminate and help solve challenging problems in computational biology.
Estimation of crowd density using multi-local features and regression

Crowd analysis is an important issue in intelligent visual surveillance systems. In this paper, a tracking-free solution to crowd density estimation is presented. The method consists of four steps: each motion parts are first extracted from video frames through motion segmentation; then eight kinds of low-level image features including blob area, Harris corner, KLT feature points, contour number, contour perimeter, ratio of perimeter to area, edge and fractal dimension are calculated; to eliminate the errors introduced by perspective effect and occlusion, both geometric correction and overlapping compensation through proper weight assignments are performed; finally, multiple regression model is used to estimate pedestrian numbers. Various experiments are performed on three video data sets and the encouraging results show that the proposed algorithm not only can perform crowd density estimation correctly but can operate in real-time.
Diet-induced obesity impairs muscle satellite cell activation and muscle repair through alterations in hepatocyte growth factor signaling

A healthy skeletal muscle mass is essential in attenuating the complications of obesity. Importantly, healthy muscle function is maintained through adequate repair following overuse and injury. The purpose of this study was to investigate the impact of diet‐induced obesity (DIO) on skeletal muscle repair and the functionality of the muscle satellite cell (SC) population. Male C57BL/6J mice were fed a standard chow or high‐fat diet (60% kcal fat; DIO) for 8 weeks. Muscles from DIO mice subjected to cardiotoxin injury displayed attenuated muscle regeneration, as indicated by prolonged necrosis, delayed expression of MyoD and Myogenin, elevated collagen content, and persistent embryonic myosin heavy chain expression. While no significant differences in SC content were observed, SCs from DIO muscles did not activate normally nor did they respond to exogenous hepatocyte growth factor (HGF) despite similar receptor (cMet) density. Furthermore, HGF release from crushed muscle was significantly less than that from muscles of chow fed mice. This study demonstrates that deficits in muscle repair are present in DIO, and the impairments in the functionality of the muscle SC population as a result of altered HGF/c‐met signaling are contributors to the delayed regeneration.
Identity-Based Proxy-Oriented Data Uploading and Remote Data Integrity Checking in Public Cloud

More and more clients would like to store their data to public cloud servers (PCSs) along with the rapid development of cloud computing. New security problems have to be solved in order to help more clients process their data in public cloud. When the client is restricted to access PCS, he will delegate its proxy to process his data and upload them. On the other hand, remote data integrity checking is also an important security problem in public cloud storage. It makes the clients check whether their outsourced data are kept intact without downloading the whole data. From the security problems, we propose a novel proxy-oriented data uploading and remote data integrity checking model in identity-based public key cryptography: identity-based proxy-oriented data uploading and remote data integrity checking in public cloud (ID-PUIC). We give the formal definition, system model, and security model. Then, a concrete ID-PUIC protocol is designed using the bilinear pairings. The proposed ID-PUIC protocol is provably secure based on the hardness of computational Diffie-Hellman problem. Our ID-PUIC protocol is also efficient and flexible. Based on the original client's authorization, the proposed ID-PUIC protocol can realize private remote data integrity checking, delegated remote data integrity checking, and public remote data integrity checking.
A practical network coding and routing scheme based on maximum flow combination

Network coding is a novel field of information theory and coding theory. It is a breakthrough over the traditional store‐and‐forward routing methods by allowing coding of two or more packets together. From an information flow aspect, multiple flows could be overlapped in a routing scheme. Hence the theoretical upper bound of multicast capacity could be achieved by network coding. In this project, a complete routing and coding scheme is constructed to realize the maximum multicast transportation task. In order to implement the scheme, the paths of multiple max‐flows are determined. Edges are divided into overlapped and normal type based on the merged max‐flows. The transmitting data are represented using packets in a specific format. Multicast, forward and coding operations are defined to transmit data at the nodes. The nodes are classified according to the type of operation. A dynamic coding and routing algorithm is proposed to route packets gradually from source node to destinations in topological sorting order by the three operations on the path of merged max‐flows. We show that the use of simple XOR operations can satisfy most of the network topologies. The running time of the algorithm presented here is less than 1 second for most of the benchmark and random datasets. Copyright © 2012 John Wiley & Sons, Ltd.
Mechanical Load Fault Detection in Induction Motors by Stator Current Time-Frequency Analysis

This paper examines the detection of mechanical faults in induction motors by an original use of stator current time-frequency analysis. Mechanical faults lead generally to periodic load torque oscillations. The influence of the torque oscillations on the induction motor stator current is studied using an analytical approach. The mechanical fault results in a sinusoidal phase modulation of the stator current, which is equivalent to a time-varying frequency. Based on these assumptions, several signal processing methods suitable for stator current signature analysis are discussed: classical spectral analysis, instantaneous frequency estimation, and the Wigner distribution. Experimental and simulation results validate the theoretical approach in steady-state operating conditions
Studying Human Neurodegenerative Diseases in Flies and Worms

Invertebrate models of several human neurodegenerative diseases have recently been described. These models faithfully replicate key neuropathological features of the human disorders. Because the basic cell biology of the nervous system is very similar in vertebrates and invertebrates, the sophisticated and rapid genetic analysis feasible in Drosophila and C. elegans promises significant insight into human neurodegenerative syndromes. In addition, the short lifespan, small size, and ease of culturing make worms and flies ideal for drug testing.