Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship between multiple forms of childhood maltreatment and adult mental health in community respondents: results from the adverse childhood experiences study.

OBJECTIVE This study examined the prevalence of a history of various combinations of childhood maltreatment types (physical abuse, sexual abuse, and witnessing of maternal battering) among adult members of a health maintenance organization (HMO) and explored the relationship with adult mental health of the combinations of types of childhood maltreatment and emotional abuse in the childhood family environment. METHOD A total of 8,667 adult members of an HMO completed measures of childhood exposure to family dysfunction, which included items on physical and sexual abuse, witnessing of maternal battering, and emotional abuse in the childhood family environment. The adults' current mental health was assessed by using the mental health scale of the Medical Outcomes Study 36-item Short-Form Health Survey. RESULTS The prevalences of sexual abuse, physical abuse, and witnessing of maternal violence were 21.6%, 20.6%, and 14.0%, respectively, when the maltreatment types were considered separately. Among respondents reporting any of the maltreatment types, 34.6% reported more than one type of maltreatment. Lower mean mental health scores were associated with higher numbers of abuse categories (mean=78.5, 75.5, 72.8, and 69.9 for respondents with no, one, two, and three abuse types, respectively). Both an emotionally abusive family environment and the interaction of an emotionally abusive family environment with the various maltreatment types had a significant effect on mental health scores. CONCLUSIONS Childhood physical and sexual abuse, as well as witnessing of maternal battering, were common among the adult members of an HMO in this study. Among those reporting any maltreatment, more than one-third had experienced more than one type of maltreatment. A dose-response relation was found between the number of types of maltreatment reported and mental health scores. In addition, an emotionally abusive family environment accentuated the decrements in mental health scores. Future research examining the effects of childhood maltreatment on adult mental health should include assessments of a wide range of abusive experiences, as well as the family atmosphere in which they occur.
A Modified Nested Sparse Grid Based Adaptive Stochastic Collocation Method for Statistical Static Timing Analysis

In this paper, we propose a Modified nested sparse grid based Adaptive Stochastic Collocation Method (MASCM) for block-based Statistical Static Timing Analysis (SSTA). The proposed MASCM employs an improved adaptive strategy derived from the existing Adaptive Stochastic Collocation Method (ASCM) to approximate the key operator MAX during timing analysis. In contrast to ASCM which uses non-nested sparse grid and tensor product quadratures to approximate the MAX operator for weakly and strongly nonlinear conditions respectively, MASCM proposes a modified nested sparse grid quadrature to approximate the MAX operator for both weakly and strongly nonlinear conditions. In the modified nested sparse grid quadrature, we firstly construct the second order quadrature points based on extended Gauss-Hermite quadrature and nested sparse grid technique, and then discard those quadrature points that do not contribute significantly to the computation accuracy to enhance the efficiency of the MAX approximation. Compared with the non-nested sparse grid quadrature, the proposed modified nested sparse grid quadrature not only employs much fewer collocation points, but also offers much higher accuracy. Compared with the tensor product quadrature, the modified nested sparse grid quadrature greatly reduced the computational cost, while still maintains sufficient accuracy for the MAX operator approximation. As a result, the proposed MASCM provides comparable accuracy while remarkably reduces the computational cost compared with ASCM. The numerical results show that with comparable accuracy MASCM has 50% reduction in run time compared with ASCM.
Data-Derived Non-Linear Mapping for Feature Extraction in HMM

Rather long temporal trajectory of critical band logarithmic power spectrum energy at a given frequency is used as an input feature vector in a MLP-based phoneme classi er, trained on a task-independent hand-labeled development data. Class-speci c log likelihood vectors from the individual sub-classi ers form input to a merging MLP classi er trained on the training data. Output of this merging classi er forms a feature vector for subsequent HMM ASR.
Association for Information Systems Year Information Search Process for a Well-Structured IS Problem : The Role of IS and Application Domain Knowledge

Prior research has shown that the effect of information systems (IS) domain knowledge and application domain knowledge on problem solving is contingent on task type (Khatri et al. 2006). We build on this study by engaging in an in-depth analysis of how both these types of knowledge influence one type of task referred to as “schema-based problem solving” task. Our theoretical analysis is based on the fact that conceptual schema understanding is a well-structured problem area and that, in such a setting, participants engage in depth-first rather than the breadth-first search that is evident in the more-frequently studied ill-structured problem areas. We used protocol analysis to explore the search process in the context of varying levels of both IS and application domain knowledge. We found that knowledge of the IS and application domains result in similar effects on the search process: both high IS knowledge and familiarity with the application domain result in deeper (more focused) search.
Risk sensitive stochastic control and differential games

We give a concise introduction to risk sensitive control of Markov diffusion processes and related two-controller, zero-sum differential games. The method of dynamic programming for the risk sensitive control problem leads to a nonlinear partial differential equation of HamiltonJacobi-Bellman type. In the totally risk sensitive limit, this becomes the Isaacs equation for the differential game. There is another interpretation of the differential game using the Maslov idempotent probability calculus. We call this a max-plus stochastic control problem. These risk sensitive control/differential game methods are applied to problems of importance sampling for Markov diffusions.
Please Scroll down for Article Journal of Clinical and Experimental Neuropsychology Serial Position Effects in Mild Cognitive Impairment

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Linking species diversity to the functioning of ecosystems: on the importance of environmental context

There is currently much interest in understanding how loss of biodiversity might alter ecological processes vital to the functioning of ecosystems. Unfortunately, ecologists have reached little consensus regarding the importance of species diversity to ecosystem functioning because empirical studies have not demonstrated any consistent relationship between the number of species in a system and the rates of ecological processes. We present the results of a simple model that suggests there may be no single, generalizable relationship between species diversity and the productivity of an ecosystem because the relative contributions of species to productivity change with environmental context. The model determined productivity for landscapes varying in species diversity (the number of species in the colonist pool), spatial heterogeneity (the number of habitat types composing the landscape), and disturbance regimes (+/− a non-selective mortality). Linear regressions were used to relate species diversity and productivity for each of the environmental contexts. Disturbance changed the form of the diversity/productivity relationship by reducing the slope (i.e. the change in productivity per species added to the colonist pool), but spatial heterogeneity increased or decreased this slope depending on the particular habitat types composing the landscape. The cause of the diversity/productivity relationship also changed with environmental context. The amount of variation in productivity explained by species diversity always increased with spatial heterogeneity, while the amount of variation explained by species composition (i.e. the particular species composing the colonist pool) tended to increase with disturbance. These results lead us to conclude that the form and cause of the relationship between species diversity and productivity may be highly dynamic-changing over both time and space. Because the trends resulted from well-known mechanisms by which environmental variation alters the absolute and relative abundances of taxa, we suspect this conclusion may be applicable to many different systems.
How Nonconsumption Shapes Desire

How does nonconsumption shape desire? The proposed model suggests that desire depends on the length of nonconsumption of a good and the presence of salient alternatives, and that desire is at least partially constructed. In the absence of salient alternatives, a longer nonconsumption period results in stronger desire for the unconsumed good. However, in the presence of salient alternatives, individuals infer that they have developed new tastes, and thus a longer nonconsumption period results in a weaker desire for the unconsumed good. Five studies support this model across nonconsumption of various goods: food from home when attending college (study 1); chametz food during the Passover holiday (study 2); social media (i.e., abstaining from Facebook; study 3); and cultural foods (i.e., forgoing Japanese food, study 4; and Thai food, study 5). We discuss implications of our findings for when and how the experience of desire is constructed and situationally determined.
Democratic Voting and Social Exclusion

This paper explores the political determinants of societies' tolerance for social exclusion on the basis of ethnicity, religion, or race. We develop a political-economic model of social exclusion with three main features. First, each individual living in this society must submit a political proposals regarding the extent to which society must tolerance social exclusion. Second, depending on the realized degree of society's tolerance for social exclusion, each population group comprising the society must decide on how much resources to expend in order to exclude rival groups from, or include its members in, the public allocation of education resources. Third, allocation of resources to participation in the exclusion contest trades off private investment in child's human capital. To the extent that population size is, at least initially, the only source of asymmetry between rival groups, our analysis suggests that the introduction of democratic voting may not be sufficient to save small, but visible, minorities from social exclusion. Only where this asymmetric is moderate, can the introduction of democratic voting suffice to eliminate social exclusion.
The impacts of exchange rate volatility on vegetable trade flows

Trade flows of commodities are generally affected by the principles of comparative advantage in a free trade. However, trade flows might be enhanced or distorted not only by various government interventions, but also by exchange rate fluctuations among others. This study applies a commodity-specific gravity model to selected vegetable trade flows among Organization for Economic Co-operation and Development (OECD) countries to determine the effects of exchange rate uncertainty on the trade flows. Using the data from 1996 to 2002, the results show that, while the exchange rate uncertainty significantly reduces trade in the majority of commodity flows, there is evidence that both short- and long-term volatility have positive effect on trade flows of specific commodities. This study also tests the regional preferential trade agreements such as the North American Free Trade Agreement (NAFTA), the Asia-Pacific Economic Cooperation (APEC) and the EU, and their different effects on commodities.
An intelligent control system using an efficient License Plate Location and Recognition Approach

This paper presents a real-time and robust method for license plate location and recognition. After adjusting the image intensity values, an optimal adaptive threshold is found to detect car edges and then the algorithm uses morphological operators to make candidate regions. Features of each region are to be extracted in order to correctly differentiate the license plate regions from other candidates. It was done by analysis of percentage of Rectangularity of plate. Using color filter makes the algorithm more robust on license plate localization (LPL). The algorithm can efficiently determine and adjust the plate rotation in skewed images. The Binary unit uses Otsu method to find the optimal adaptive threshold corresponding to the intensity of image. To segment the characters of the license plate, a segmentation algorithm based on the profile is proposed. In the following, an optical character recognition (OCR) engine has then been proposed. The OCR engine includes characters dilation, resizing input vector of Artificial Neural Network (ANN). To recognize the characters on the plates, Multi layer Perceptron (MLP) has been used and compared with Hopfield, Linear Vector Quantization (LVQ) and Redial Basis Function (RBF). The results show that MLP outperforms. According to the results, the performance of the proposed system is better even in case of low-quality images or images with illumination effects and noise. Saeed Rastegar, Reza Ghaderi, Gholamreza Ardeshipr & Nima Asadi International Journal of Image Processing (IJIP) Volume(3), Issue(5) 253
Impact of Transmit Power Control and Receiver Association on Interweave Network Interference

Erroneous beacon detection by interweave secondary nodes generates interference on the primary system. This paper analyzes how the aggregate interference behaves when secondary nodes use transmit power control and receiver association schemes. For this purpose, secondary transmitter nodes and receiver nodes are assumed to be distributed over a circular region and over the entire 2-D plane respectively. Two independent Poisson point processes model these distributions. We propose a receiver association scheme where each secondary transmitter attempts to connect to the closest available receiver. If it is not available, the transmitter attempts to connect with the next closest. This process continues until the M-th closest receivers are scanned. If no receiver is available, the transmitter remains silent. Moreover, a per-user transmit power control scheme is considered in which the transmit power is based on the distance between the transmitter and the associated receiver subject to a cut-off power level. All links are assumed to undergo path-loss and Rayleigh fading. The exact moment generating function (MGF) of the aggregate interference, the outage probability of the primary system, and the average probability of concurrent transmission are derived. Validated by simulations, our results show how the aggregate interference is affected by secondary power thresholds, receiver densities, and availability of the secondary receiver.
Extracting knowledge from association relationships to build navigational models

We analyze how the semantics of association relationships in OO conceptual modeling can help to build navigational models for Web applications. The work has been developed in the context of OOWS (a model-driven development method for building Web applications). We study some structural and behavioral properties of those conceptual abstractions in order to extract knowledge to be applied in the construction of navigational models. From this study, a set of design rules has been obtained. These rules help the modeler to build navigational models in a systematic way. The results of this work have improved the modeling and code generation processes introduced by OOWS.
A bulk micromachined distributed digital phase shifter for microwave phased array applications

A novel distributed digital MEMS (micro-electro-mechanical system) microwave phase shifter, fabricated with bulk Si micromachining techniques, is presented. Using a distributed nonlinear transmission line technique, with single crystal silicon based multilayer microbridge structures as loading varactors, this phase shifter delivers true time delay and wideband performance. A micromachining process flow, combining anodic bonding and single crystal silicon etching with heavy boron doping, was developed to fabricate the movable Si-based microbridges over a coplanar waveguide (CPW). An electrostatic voltage, applied between the Si layer of the microbridges (varactors) and CPW ground plane, pulls down the microbridges, effecting a phase shift varying linearly with. frequency. The principle, process and RF performance characterization are described. The actuated phase shifter has achieved 90.2/spl deg/ phase shift at 20.5 GHz, with good reflection loss (-12 dB) in the frequency range of 5-20.5 GHz. The insertion loss is a little high, 3.87 dB, however, due to the lossy substrate of Pyrex 7740 glass and the thin metalization of the CPW.
Image Optimization and Prediction

Image Processing, Optimization and Prediction of an Image play a key role in Computer Science. Image processing provides a way to analyze and identify an image . Many areas like medical image processing, Satellite images, natural images and artificial images requires lots of analysis and research on optimization. In Image Optimization and Prediction we are combining the features of Query Optimization, Image Processing and Prediction . Image optimization is used in Pattern analysis, object recognition, in medical Image processing to predict the type of diseases, in satellite images for predicting weather forecast, availability of water or mineral etc. Image Processing, Optimization and analysis is a wide open area for research . Lots of research has been conducted in the area of Image analysis and many techniques are available for image analysis but, a single technique is not yet identified for image analysis and prediction . our research is focused on identifying a global technique for image analysis and Prediction.
Survey on Host and Network Based Intrusion Detection System

------------------------------------------------------------------- ABSTRACT --------------------------------------------------------------- With invent of new technologies and devices, Intrusion has become an area of concern because of security issues, in the ever growing area of cyber-attack. An intrusion detection system (IDS) is defined as a device or software application which monitors system or network activities for malicious activities or policy violations. It produces reports to a management station [1]. In this paper we are mainly focused on different IDS concepts based on Host and Network systems.
Analysis and evaluation of a lossless turn-on snubber

A lossless turn-on snubber was studied analytically, by simulation and experimentally. Limits were found for the proper operation of the snubber and are expressed as permissible duty cycle as a function of input current. It was found that a modified version of the snubber, which includes a tapped main inductor, improves the performance by allowing a wider operational range. The experimental results confirm the theoretical analysis. A reduction of power losses of about 19 W was observed when the snubber was implemented in a 1 kW boost power converter.
Demand Estimation in the Presence of Revenue Management

Yield management has become a standard tool in several industries to increase the profits of firms facing demand uncertainty or consumers heterogeneity. But this technique also raises econometric problems in the estimation of demand models. Quantity-based management, in particular, is the source of both an endogeneity and a right-censoring problem. Disposing of macro data only and ignoring these issues leads to an aggregation bias. We develop a structural model of demand in the presence of quantity-based management. We show that the price elasticity is identified in this model provided that (i) we observe two subpopulations that face different prices but are not separated in the yield management policy, (ii) the highest prices and quantities sold at these prices are observed, (iii) the highest prices vary with time or across markets. We apply our method to the French railroad industry, using disaggregated data on trips between Paris and big cities on the period 2007-2009. Our estimates of the price-elasticity are consistent with a rather responsive demand, from 1.7 to 2 in economy class and from 1.3 to 1.5 in business class.
Discontinuation and reinitiation patterns of osteoporosis treatment among commercially insured postmenopausal women

Objective Poor adherence to chronic medications is common and compromises medication effectiveness. We sought to describe longitudinal patterns of osteoporosis medication use. Study design This was a retrospective observational cohort study using 2005–2009 data from a large, commercially insured population. Methods Patients were women aged ≥55 years initiating osteoporosis therapy who had a ≥12-month (baseline) period with no osteoporosis therapy claims preceding initiation, and ≥24 months follow-up after therapy initiation. Discontinuation was defined as a gap >60 days (varied in sensitivity analyses) in prescription claims. Reinitiation was defined as a prescription claim for the same or different osteoporosis therapy following the therapy gap. Discontinuation and reinitiation patterns were described using Kaplan–Meier analysis. Multivariable Cox regression assessed the impact of baseline factors on reinitiation. Results Of the 92,839 patients, 45%, 58%, and 70% discontinued therapy at 6, 12, and 24 months, respectively, following initiation. Of the discontinuers, 46% reinitiated therapy, with the majority doing so within 6 months of discontinuation. Women were less likely to reinitiate therapy if they were older (P < 0.0001) or were hospitalized during baseline (P = 0.0007). Women who discontinued treatment early (<6 months) following initiation were less likely to reinitiate (P < 0.0001) and remained on therapy for shorter periods following reinitiation. Depending on the available observation time, the median time on therapy following reinitiation was 58–193 days. Study findings did not change appreciably in sensitivity analyses. Conclusion Many patients stop and restart treatment for osteoporosis. A better understanding of determinants of treatment stopping and restarting could inform adherence improvement efforts.