Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship Between Psychosocial Distress in Pregnancy and Two Genes Associated With Human Social Interaction: A Pilot Study

Background Prenatal depression, anxiety, and stress (prenatal psychosocial distress) are common, and several environmental risk factors have been implicated in their development. Variation in genes, specifically single nucleotide polymorphisms (SNPs), may explain why some women develop maternal mental health concerns while others do not. Purpose The purpose of this pilot study was to determine the feasibility of completing SNP analyses using whole blood collected prenatally between 2008 and 2011. We examined the association between SNPs in two genes (FKBP5 and OXTR) among women with low and high prenatal psychosocial distress. Methods A subset (N = 50, 25 high and 25 low prenatal psychosocial distress) of participants was selected from the All Our Families pregnancy cohort. DNA was extracted from maternal blood and used for selected SNP analysis. Participants’ scores on the Edinburgh Prenatal Depression Scale, Spielberger State Anxiety Inventory, and Perceived Stress Scale were used along with demographic variables. Results Genotype distribution was not significantly different between the low and high prenatal psychosocial distress groups for either the FKBP5 or the OXTR SNP (p = .699 and p = .125). After controlling for maternal age and income, women with the GG genotype at the OXTR SNP (rs237885) were statistically less likely to be in the high prenatal psychosocial distress group (p = .037). Conclusion OXTR SNP rs237885, maternal age, and lower income were associated with prenatal psychosocial distress. This pilot study demonstrated the feasibility of continuing to a larger study that incorporates additional environmental and genetic information.
CTH10-2: On Orthogonal Space-Time Block Codes and Packings on the Grassmann Manifold

We show that orthogonal space-time block codes may be identified with packings on the Grassmann manifold. We describe a general criterion for packings on the Grassmann manifold that yield coherent space-time constellations with the same code properties that make orthogonal space-time block codes so favorable. As an example, we point out that the rate 3/4 orthogonal space-time block code motivates a packing on the Grassmann manifold that allows for a simplified maximum likelihood detection rule using the newly introduced framework. As a side product, this packing defines a noncoherent space-time constellation that may be regarded as a generalization of certain existing noncoherent space-time codes.
Ultrastructural analysis of the dynactin complex: an actin-related protein is a component of a filament that resembles F-actin

The dynactin complex visualized by deepetch electron microscopy appears as a short filament 37-nm in length, which resembles F-actin, plus a thinner, laterally oriented filament that terminates in two globular heads. The locations of several of the constituent polypeptides were identified on this structure by applying antibodies to decorate the dynactin complex before processing for electron microscopy. Antibodies to the actin-related protein Arp1 (previously referred to as actin- RPV), bound at various sites along the filament, demonstrating that this protein assembles in a polymer similar to conventional actin. Antibodies to the barbed-end actin-binding protein, capping protein, bound to one end of the filament. Thus, an actin-binding protein that binds conventional actin may also bind to Arp1 to regulate its polymerization. Antibodies to the 62-kD component of the dynactin complex also bound to one end of the filament. An antibody that binds the COOH-terminal region of the 160/150-kD dynactin polypeptides bound to the globular domains at the end of the thin lateral filament, suggesting that the dynactin polypeptide comprises at least part of the sidearm structure.
Symbolic systems Biology and PATHWAY LOGIC

Pathway Logic (PL) is an approach to modeling and analysis of biological processes based on rewriting logic. This chapter describes the use of PL to model signal transduction processes. It begins with a general discussion of Symbolic Systems Biology, followed by some background on rewriting logic and executable specifications. Finally, representation and analysis of a small model of Ras and Raf activation is presented in some detail.
Practical considerations in applying Σ-Δ modulation-based analog BIST to sampled-data systems

The analog built-in self-test (BIST) scheme, with stimulus generation and response extraction based on the /spl Sigma/-/spl Delta/ modulation, is proven to be quite effective for sampled-data systems. We show that the /spl Sigma/-/spl Delta/ modulators can be selected optimally for certain applications and functional tests. The criteria for valid tests are also derived. In particular, a valid frequency response test is determined by the frequency response observation range FROR/sub BIST/(z) of the BIST circuit. Given the transfer function H/sub CUT/(z) of the circuit under test, the requirement becomes FROR/sub BIST/(z)/spl Gt/|1/H/sub CUT/(z)|. Using the MOSIS 0.35-/spl mu/m CMOS process, we have implemented a test chip containing a Fleischer-Laker biquadratic low-pass filter as the circuit under test. An on-chip one-bit digital-to-analog converter provides the analog stimulus from a bit stream which is applied externally. For each test item, different bit streams, synthesized by first-, second-, and fourth-order /spl Sigma/-/spl Delta/ modulators that are programmed by software, are compared for performance. First- and second-order /spl Sigma/-/spl Delta/ modulators are implemented on the test chip as the candidates for the analog response extractor. The measurement results by single-tone tests and multitone tests validate the feasibility of the BIST scheme.
Correlated factors with filial piety expectations of older Koreans and Korean-Americans

ABSTRACT Changing filial piety expectations have been examined from the viewpoint of younger generations. However, research on older adults’ perspective of this cultural phenomenon is virtually absent from the empirical literature. In an effort to address the changing family life circumstances of Korean and Korean-American families, this study explores older adults’ filial expectations from their own children and correlated factors associated with the expectation. The cross-sectional survey study with 449 older adults found that the majority of respondents still believe that adult children should assume responsibility for the care of their parents. Several factors such as age, education, income, living arrangements, self-rated health, year of immigration, and social support were significantly correlated with filial expectations among older Korean-Americans. Only satisfaction with social support received from family and friends was significantly related to older Koreans’ expectations. Implications for social work practice are discussed and further research directions are suggested.
Intrusion and Fault Tolerance in Heterogeneous Wireless Sensor Networks Using Weighted voting Method

A wireless sensor network (WSN) is a large collection sensor node with limited memory, battery and processing capacity. Due to this limited resources the energy conservation plays important role in wireless sensor networks. We formulate optimization problem for dynamically determining the best redundancy level to apply to multipath routing for intrusion tolerance so that query success probability maximized while prolonging system useful lifetime. In redundancy management “packet dropping” and “Bad mouthing” are the major problems in managing the redundancy. In order sort out these problems we plan to propose “weighted voting” based trust management method is used to achieve best energy efficiency. The main function of weighted voting method is to find the trust/reputation of neighbor nodes.
Angular momentum transport and dynamo-effect in stratified, weakly magnetic disks

The magnetic shear instability is reviewed numerically in the local box approximation for a Kepler disk. Special emphasis is laid on the relation between the viscosity–alpha and dynamo–alpha in case a mean magnetic field is generated. Self-sustaining ‘turbulence’ is initiated by the instability which acts simultaneously as dynamo and efficient outward transporter for angular momentum. The Shakura-Sunyaev parameterαSS is estimated to≈ 1.5 · 10−2 for an adiabatic disk model, and the contribution from the Maxwell stress dominates over that of the Reynolds stress by a factor of 4. In case of stress-free, normalB vertical boundary conditions, a non-zero mean magnetic field mainly oriented in azimuthal direction is generated. This mean field turns out timedependent in a quasi-periodic manner. Box resonance oscillations in the horizontal velocities for a limited time lead to an enhanced, violently fluctuating Reynolds stress associated with a reduced magnetic activity. The resulting (dynamo-) α-effect is negative in the upper disk plane and positive in the lower disk plane, it is small and highly noisy.
Methods for Classification of Input Stimuli for Single Trial EEG

In this paper we describe pattern recognition techniques to classify single trial electroencephalogram (EEG) data to one of two stimulus classes (face or car) which have been presented as an image with phase incoherent noise to a human observer. We investigate methods to determine the optimal time and sensor windows, compare classification results across a variety of current classification methods, explore classification accuracy using the time-frequency spectrogram, and develop a modification of Adaboost [9] to automatically select highly discriminable regions in the input feature space. Results identifying the best channels and time windows for support vector machine (SVM) and Boosting methods are given. Performance in terms of area under the receiver operating characteristic (ROC) curve (Az) is used to compare classifier to human performance. SVM’s give the best result for a long time window (200 samples starting at sample 110): 0.71 Az compared to 0.81 Az for the human observer.
Service Agents for Calendar Exchange

With the emerging use of electronic calendars services on the Internet the users are constantly increasing the number of calendar platforms they use and the need to have them synchronized in one place is increasing. In this paper we discuss the evolution of the electronic services for calendars, and give overview of the APIs they use, along with protocols and interfaces to these services. We introduce an idea to create Calendar Service Agent as a software agent in order to exchange, modify and synchronize information about events from different calendar platforms. The solution is explained by protocols and patterns, as well as the structure and architecture, and platforms included.
Practical Bayesian support vector regression for financial time series prediction and market condition change detection

Support vector regression (SVR) has long been proven to be a successful tool to predict financial time series. The core idea of this study is to outline an automated framework for achieving a faster and easier parameter selection process, and at the same time, generating useful prediction uncertainty estimates in order to effectively tackle flexible real-world financial time series prediction problems. A Bayesian approach to SVR is discussed, and implemented. It is found that the direct implementation of the probabilistic framework of Gao et al. returns unsatisfactory results in our experiments. A novel enhancement is proposed by adding a new kernel scaling parameter to overcome the difficulties encountered. In addition, the multi-armed bandit Bayesian optimization technique is applied to automate the parameter selection process. Our framework is then tested on financial time series of various asset classes (i.e. equity index, credit default swaps spread, bond yields, and commodity futures) to ensure its flexibility. It is shown that the generalization performance of this parameter selection process can reach or sometimes surpass the computationally expensive cross-validation procedure. An adaptive calibration process is also described to allow practical use of the prediction uncertainty estimates to assess the quality of predictions. It is shown that the machine-learning approach discussed in this study can be developed as a very useful pricing tool, and potentially a market condition change detector. A further extension is possible by taking the prediction uncertainties into consideration when building a financial portfolio.
A Posterior Distribution for Anti-Spam Bayesian Statistical Model

This paper deals with Bayesian models applied to anti-spam. In our previous work involved in mathematically modeling the behavior of spam, we worked on defining the priors distributions that summarize the behavior of spam. In this paper, taking into account certain priors distributions and we define the posterior distributions that summarize the probability that a received message is spam. These laws a priori and a posteriori certainly help improve the spam detection and increase the reliability decision.
Part 2: Preparing Entry-Level Occupational and Physical Therapy Students to Promote Healthy Lifestyles Emphasizing Healthy Eating with Individuals with Disabilities

Rehabilitation professionals including occupational therapists (OT) and physical therapists (PT) are increasingly called upon to incorporate health promotion of lifestyle behaviors including physical activity and healthy eating into routine clinical care. While OTs and PTs may be comfortable promoting activity-related behaviors, many are less comfortable with nutrition behaviors. To address entry-level OT and PT students’ perceived discomfort with discussing diet-related behaviors, faculty developed a healthy eating module for students to use during a community-based service learning program. The purpose of this paper is to describe the formative evaluation process of developing the healthy eating module, and to discuss results of a pilot trial of this module. The formative assessment of the healthy eating module consisted of four steps: focus groups with students, key informant interviews with community partners, expert panel round table, and expert panel review of materials. Students (n=117) completed questionnaires at the end of the service learning program to assess how much they used the new resources, and how useful they found the resources. The final healthy eating module consisted of an on-line training session and a healthy eating toolkit, including resources for assessments, treatment activities and additional nutrition information. Mann-Whitney U tests indicated that students who reported high use of materials found the resources significantly more helpful than those students who reported low use (p
Weighted finite-state transducer approach to German compound words reconstruction for Speech Recognition

An approach is proposed for German Large Vocabulary Speech Recognition, dealing with the problem of compound words, based on unsupervised word decomposition for German words and a probabilistic method for combining the words using finite state transducers. The basic idea of the method is to train n-gram language model on the texts where compound words are substituted by their parts plus concatenation symbol. Thus, the context information is taken into account for the compound words and is used in the process of recombination to find most probable variant for recognition result. The advantage of this approach is the improvement of the word recognition accuracy and a more precise recombination of compound words.
Balanced Dopamine Is Critical for Pattern Completion during Associative Memory Recall

Pattern completion, the ability to retrieve complete memories initiated by partial cues, is a critical feature of the memory process. However, little is known regarding the molecular and cellular mechanisms underlying this process. To study the role of dopamine in memory recall, we have analyzed dopamine transporter heterozygous knockout mice (DAT+/−), and found that while these mice possess normal learning, consolidation, and memory recall under full cue conditions, they exhibit specific deficits in pattern completion under partial cue condition. This form of memory recall deficit in the dopamine transporter heterozygous knockout mice can be reversed by a low dose of the dopamine antagonist haloperidol, further confirming that the inability to retrieve memory patterns is a result of dopamine imbalance. Therefore, our results reveal that a delicate control of the brain's dopamine level is critical for pattern completion during associative memory recall.
Human megakaryocytes. V. Changes in the phenotypic profile of differentiating megakaryocytes

Human megakaryocytes were studied for phenotypic changes occurring throughout differentiation using a panel of monoclonal antibodies raised against marrow megakaryocytes and blood platelets. 11 monoclonal antibody preparations were selected for restricted specificity against megakaryocytes and/or platelets after screening by immunofluorescence, complement-mediated cytolysis, and solid phase enzyme-linked immunosorbent assay. The expression of the cellular epitopes recognized by these reagents enabled the identification of three levels of megakaryocyte maturation characterized by distinct immunologic phenotypes. Based upon their reactivities against megakaryocytic cells at different ontogenetic levels, monoclonal antibodies were operationally categorized into three groups. Group A consisted of six different monoclonal antibodies that recognized antigens on the colony- forming unit-megakaryocyte (CFU-Mk), in vitro grown colony megakaryocytes, and early immature marrow megakaryocytes, only, and did not detect their respective epitopes on either mature megakaryocytes or platelets. A monoclonal antibody categorized in group B detected a cell antigen expressed by megakaryocytic cells at all maturational levels, but which is lost or suppressed during terminal differentiation and is not expressed on blood platelets. Group C included four different monoclonal antibodies raised against platelets that recognized antigenic determinants expressed on the CFU-Mk, colony megakaryocytes, early and mature megakaryocytes, and platelets. Three group C monoclonal antibodies (PC-1, PC-3, and PC-4) were specific for platelet glycoprotein IIb/IIIa. Additionally, group C monoclonal antibody PC-2 was unique in that it showed partial reactivity against the clonable progenitor for the erythroid series (BFU-E). Recognition of discrete phenotypic changes in differentiating megakaryocytes will enable multiparameter analyses of these cells as well as the study of factors regulating the dynamics of megakaryocytopoiesis in health and disease.
Physical Fitness Assessment Using Supervised SOM Classification Based on BMI of College Students, Northern China

The physical fitness of college students in northern China, was systermetic evaluated with classified data by supervised SOM , then differences of classified data were validated with ANOVA. The relative importance of all physique indicators in each classified data were evaluated by PCA. BMI was considered as the supervised parameter in SOM analysis due to the reasonable and prevalent parameter reflecting health of physical health. The results were as follows: (1) The supervised SOM provided the intuitive and visual characteristics of classification for physical fitness data as well as the emphasis on BMI; (2) The differences of the classifications coupled with emphasized BMI were validated by ANOVA, and the relative importance indicators were pointed by PCA for each classification. Physique indicator showed heterogeneity in different classifications. Height and Pulup were relative important for male students, but Weight for female students; (3) the methods presented here were universally applicable, and the better performance could be promoted with much more data inputs. The results and the relevant methods of the study are valuable for deepening our understanding of BMI effects on physical fitness and can be used to develop a practical strategy for effective physical activities.
Unconscious Relational Self 1 The Unconscious Relational Self

Electronic mail may be sent via the Internet to sma1@nyu.edu. Unconscious Relational Self 2 T he Unconscious Relational Self T he notion that previous knowledge is brought to bear in extracting and constructing meaning is fundamental in social cognition. This process can be understood in terms of mental representations of self and of others, representations that give both idiosyncratic and shared meaning to experience, and reflect not only what is personal but what is interpersonal. T he self, experienced in relation to others, involves what is individual and what is social in the self. T he self and on self-regulation can be seen in terms of an interpersonal social-cognitive theory of the relational self that draws on personality and clinical theory as well (Andersen & Chen, in press). It assumes that significant others play a critical role in both self-definition and self-regulation. In short, each individual has an overall repertoire of selves, each of which stems from a relationship with a significant other, and this overall repertoire of selves is a repository for, and later, a source of, the interpersonal patterns that characterize the individual. Each self is keyed to a mental representation of a significant other. When activated, significant-other representations and aspects of the self linked to them imbue experience with different meaning, depending on their content and the context in which they are used. People may then have nearly as many selves as they have significant interpersonal relationships (Sullivan, 1953; see also Kelly, 1955), providing for both contextual variability and the longstanding representations as a chronic influence. We assess idiosyncratic knowledge representations in memory and track their influence on affect and motivation. We also examine how self-regulatory processes further modulate these responses. Our
Region Based Image Indexing and Retrieval Inspired by Text Search

In this paper we present an approach for image similarity search that takes inspiration from text retrieval. Images are indexed using visual terms chosen from a visual lexicon. Each visual term represents a typology of visual regions, according to various criteria. The visual lexicon is obtained by analyzing a training set of images, to infer which are the relevant typology of visual regions. We have defined a weighting and matching schema that are able respectively to associate visual terms with images and to compare images by means of the associated terms. We show that the proposed approach do not lose performance, in terms of effectiveness, with respect to other methods existing in literature, and at the same time offers higher performance, in terms of efficiency, given the possibility of using inverted files to support similarity searching. The proposed techniques were implemented in a running prototype.