Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictors of psychosis risk and neurocognitive deficits

Psychotic disorders usually become evident during adolescence and early adulthood and are commonly preceded by psychosis risk states. Young people at risk for developing psychosis may already have cognitive deficits. This research examined factors associated with psychosis risk and adverse cognitive performance, particularly in those at risk for developing psychosis. We aimed to characterise genetic risk factors for psychosis risk and adverse cognitive performance. Additionally, early and later biological risk markers for adverse cognitive performance and psychosis risk were explored. Two longitudinal birth cohorts, the Northern Finland Birth Cohort 1986 (NFBC 1986, n=6,985 at 16 years) and Avon Longitudinal Study of Parents and Children (ALSPAC, n=5,217 at 17 years), two NFBC 1986 sub-studies, the Oulu Brain and Mind 1 (n=182 for these analyses) and Oulu Brain and Mind 2 (n=471 for these analyses) studies, and two Irish case control studies, the Adolescent Brain Development (n=212) and Challenging Times (n=211) studies, were utilised. Predictors of interest were selected Single Nucleotide Polymorphisms (SNPs at COMT, BDNF and DRD2), prenatal exposure to maternal cigarette smoking (PEMCS) and adolescent metabolic measures. Though not directly associated with psychotic experiences, the COMT-Val158Met Val-Val genotype interacted with experience of childhood trauma to predict more psychotic experiences. Two DRD2 SNPs were associated with poorer cognitive performance, though only in those with risk for psychotic disorders. PEMCS was associated with adult vocabulary and matrix reasoning performance in males, though not in males with adolescent psychotic experiences. Adolescent academic performance, but not psychotic experiences, were associated with metabolic measures, especially with ratios of omega-3 to total fatty acids. These findings impact on prevention strategies for long-term adverse outcomes. Some risk factors differ for those with psychotic experiences compared to the general population, while others do not. SNPs at COMT and DRD2 may be more relevant in those with psychotic experiences. Interventions targeting these groups may be particularly beneficial. Smoking in pregnancy, however, is harmful to male cognitive performance across the population, suggesting elimination of this risk is more broadly relevant. Fatty acid-related metabolic measures may mark risk for cognitive deficits or may represent a developmental feature that is potentially open to intervention.
The In Vivo Therapeutic Efficacy of the Oncolytic Adenovirus Delta24-RGD Is Mediated by Tumor-Specific Immunity

The oncolytic adenovirus Delta24-RGD represents a new promising therapeutic agent for patients with a malignant glioma and is currently under investigation in clinical phase I/II trials. Earlier preclinical studies showed that Delta24-RGD is able to effectively lyse tumor cells, yielding promising results in various immune-deficient glioma models. However, the role of the immune response in oncolytic adenovirus therapy for glioma has never been explored. To this end, we assessed Delta24-RGD treatment in an immune-competent orthotopic mouse model for glioma and evaluated immune responses against tumor and virus. Delta24-RGD treatment led to long-term survival in 50% of mice and this effect was completely lost upon administration of the immunosuppressive agent dexamethasone. Delta24-RGD enhanced intra-tumoral infiltration of F4/80+ macrophages, CD4+ and CD8+ T-cells, and increased the local production of pro-inflammatory cytokines and chemokines. In treated mice, T cell responses were directed to the virus as well as to the tumor cells, which was reflected in the presence of protective immunological memory in mice that underwent tumor rechallenge. Together, these data provide evidence that the immune system plays a vital role in the therapeutic efficacy of oncolytic adenovirus therapy of glioma, and may provide angles to future improvements on Delta24-RGD therapy.
GARBAGE COLLECTION FOR THE DELFT JAVA PROCESSOR

The Delft Java Processor (DJP) is a hardware approach aiming at accelerating bytecode execution. One of the critical tasks in a JVM that could benefit from hardware support is garbage collection. To efficiently perform garbage collection in the DJP we have to better understand the general garbage collection related issues in real life situations. In this respect we provide in this paper a study of the dynamic allocation behavior of Java programs based on the SPECjvm98 benchmark suite. Age, size and type distribution of Java objects are presented and interpreted from the general point of view of garbage collection, together with other garbage collection related measurements. Thus we can identify the features of an efficient DJP dedicated garbage collector and propose supporting architectural extension(s) in the DJP. The study confirms the weak generational hypothesis according to which objects are most likely to die very young, suggesting that a collector with two generations could improve garbage collection performance with corresponding hardware support. To fully take advantage of the generational hypothesis efficient hardware-implemented write barriers are needed. Hardware support is also recommended for describing the dynamic layout of the stack (stack pointer map) for accurate garbage collection.
Observation of Single Top-Quark Production

We report observation of the electroweak production of single top quarks in ppbar collisions at sqrt(s) = 1.96 TeV based on 2.3 fb^-1 of data collected by the D0 detector at the Fermilab Tevatron Collider. Using events containing an isolated electron or muon and missing transverse energy, together with jets originating from the fragmentation of b quarks, we measure a cross section of sigma(ppbar ->tb + X, tqb + X) = 3.94 +- 0.88 pb. The probability to measure a cross section at this value or higher in the absence of signal is 2.5 x 10^-7, corresponding to a 5.0 standard deviation significance for the observation.
A yeast replicative helicase, Dna2 helicase, interacts with yeast FEN-1 nuclease in carrying out its essential function

We have recently described a new helicase, the Dna2 helicase, that is essential for yeast DNA replication. We now show that the yeast FEN-1 (yFEN-1) nuclease interacts genetically and biochemically with Dna2 helicase. FEN-1 is implicated in DNA replication and repair in yeast, and the mammalian homolog of yFEN-1 (DNase IV, FEN-1, or MF1) participates in Okazaki fragment maturation. Overproduction of yFEN-1, encoded by RAD27/RTH1, suppresses the temperature-sensitive growth of dna2-1 mutants. Overproduction of Dna2 suppresses the rad27/rth1 delta temperature-sensitive growth defect. dna2-1 rad27/rth1 delta double mutants are inviable, indicating that the mutations are synthetically lethal. The genetic interactions are likely due to direct physical interaction between the two proteins, since both epitope-tagged yFEN-1 and endogenous yFEN-1 coimmunopurify with tagged Dna2. The simplest interpretation of these data is that one of the roles of Dna2 helicase is associated with processing of Okazaki fragments.
PolSAR image speckle reduction based on sparse representation and structure characteristics

This paper presents a novel speckle reduction algorithm based on sparse representation and structure characteristics of PolSAR image. First, each pixel in original image is classified into bright point or line targets, dark point or line targets and others to form a classification map. Second, sparse decomposition and reconstruction is performed on PolSAR image by OMP and K-SVD methods to filter speckle. Finally, the blurred point and line targets in filtered image are enhanced with the classification map. Experimental results with the data of Hayward area from AIRSAR system show that the proposed method is effective both on speckle reduction and scattering characteristics preservation.
Green Cooperative Spectrum Sensing and Scheduling in Heterogeneous Cognitive Radio Networks

In this paper, we consider heterogeneous cognitive radio networks (CRNs) comprising primary channels (PCs) with heterogeneous characteristics and secondary users (SUs) with various sensing and reporting qualities for different PCs. We first define the opportunity as the achievable total data rate and its cost as the energy consumption caused from sensing, reporting, and channel switching operations and formulate a joint spectrum discovery and energy efficiency objective to minimize the energy spent per unit of data rate. Then, a mixed integer nonlinear programming problem is formulated to determine: 1) the optimal subset of PCs to be scheduled for sensing; 2) the SU assignment set for each scheduled PC; and 3) sensing durations and detection thresholds of each SU on PCs it is assigned to sense. Thereafter, an equivalent convex framework is developed for specific instances of the above combinatorial problem. For comparison, optimal detection and sensing thresholds are also derived analytically under the homogeneity assumption. Based on these, a prioritized ordering heuristic is developed to order channels under the spectrum, energy, and spectrum-energy limited regimes. After that, a scheduling and assignment heuristic is proposed and is shown to perform very close to the exhaustive optimal solution. Finally, the behavior of the CRN is numerically analyzed under these regimes with respect to different numbers of SUs, PCs, and sensing qualities.
Classification of processed hazelnuts with computer vision

Today's, blanched or roasted hazelnuts are widely used in chocolate and biscuits industry. Partly skin removed hazelnuts kernels are caused to deterioration in flavor and taste of the chocolate. Many of chocolate and biscuits cooperation in Turkey are using traditional manual selection methods. However, manual selection has high error rate, time consuming and costly. In this study, the partly skin removed hazelnut kernel, skin removed and rotten hazelnuts kernels which are obtained from processed kernels are classified by using computer vision approach. In the proposed study, the processed hazelnut kernels are classified with 93.57% classification accuracy rate.
Ad-hoc Security Associations for Wireless Devices

of Master's thesis Abstract: A conversation secured with a session key is referred to as security association. In ad-hoc scenarios without key management infrastructure, key agreement is a challenging task. The challenge becomes even greater, when the association must be built among a group of devices. Several techniques to create an association between a pair of devices using human assisted out-of-band channels have been proposed in the recent years. These protocols can be divided into two groups, the methods based on a shared secret passkey and the methods based on comparing data on the devices. In this thesis, a survey of these technologies is given. First, the basic ideas behind authenticated key exchange methods are discussed followed by a survey of theoretical protocols and some recent industry implementations of such protocols. The protocols are studied based on a literary survey. A natural question is how to extend these pair-wise protocols to handle also the multiparty case. In this thesis, two new key management protocols for a group of devices are presented and their security properties analyzed. Also practical procedures for managing group associations based on numeric comparison or shared passkey are discussed. Preface First of all, I would like to thank my supervisor, Professor Kaisa Nyberg for taking me as a research assistant and providing interesting topic to work with. Further, I am deeply indebted to her for her support during the process of writing this thesis. I would also like to thank Professor N. Asokan for his contribution to the paper this thesis is based on. Finally, I would like to express my gratitude to the Laboratory for Theoretical Computer Science for providing an excellent environment to work on this thesis.
Objective Study of Sensor Relevance for Automatic Cough Detection

The development of a system for the automatic, objective, and reliable detection of cough events is a need underlined by the medical literature for years. The benefit of such a tool is clear as it would allow the assessment of pathology severity in chronic cough diseases. Even though some approaches have recently reported solutions achieving this task with a relative success, there is still no standardization about the method to adopt or the sensors to use. The goal of this paper is to study objectively the performance of several sensors for cough detection: ECG, thermistor, chest belt, accelerometer, contact, and audio microphones. Experiments are carried out on a database of 32 healthy subjects producing, in a confined room and in three situations, voluntary cough at various volumes as well as other event categories which can possibly lead to some detection errors: background noise, forced expiration, throat clearing, speech, and laugh. The relevance of each sensor is evaluated at three stages: mutual information conveyed by the features, ability to discriminate at the frame level cough from these latter other sources of ambiguity, and ability to detect cough events. In this latter experiment, with both an averaged sensitivity and specificity of about 94.5%, the proposed approach is shown to clearly outperform the commercial Karmelsonix system which achieved a specificity of 95.3% and a sensitivity of 64.9%.
Title Markov Weight Fields for face sketch synthesis

Great progress has been made in face sketch synthesis in recent years. State-of-the-art methods commonly apply a Markov Random Fields (MRF) model to select local sketch patches from a set of training data. Such methods, however, have two major drawbacks. Firstly, the MRF model used cannot synthesize new sketch patches. Secondly, the optimization problem in solving the MRF is NP-hard. In this paper, we propose a novel Markov Weight Fields (MWF) model that is capable of synthesizing new sketch patches. We formulate our model into a convex quadratic programming (QP) problem to which the optimal solution is guaranteed. Based on the Markov property of our model, we further propose a cascade decomposition method (CDM) for solving such a large scale QP problem efficiently. Experimental results on the CUHK face sketch database and celebrity photos show that our model outperforms the common MRF model used in other state-of-the-art methods.
The Roles of Path-based and Distributional Information in Recognizing Lexical Semantic Relations

Recognizing various semantic relations between terms is cr ucial for many NLP tasks. While path-based and distributional information sources are con sidered complementary, the strong results the latter showed on recent datasets suggested that th e former’s contribution might have become obsolete. We follow the recent success of an integrat ed neural method for hypernymy detection (Shwartz et al., 2016) and extend it to recognize m ultiple relations. We demonstrate that these two information sources are indeed complementar y, and analyze the contributions of each source.
Dynamic Promotional Resource Allocation for Segment Specific and Spectrum Effect of Promotion for a Product Line Incorporating Repeat Purchase Behavior

Promotion is an essential element in the marketing mix. It is used by businesses to inform, influence and persuade customers to adopt the products and services they offer. Without promotion, business would be stagnant and lack substantial growth because the brands would have low visibility in the market. Moreover, today’s vast and assorted markets comprise of customers with different needs and varied behavior. So it is rarely possible for companies to satisfy all customers by treating them alike. Thus there arises a need to divide the market into segments having customers with similar traits/characteristics. After identifying appropriate market segments, firms can design differentiated promotional campaigns for each segment. At the same time there can be a mass market promotional campaign that reaches different segments with a fixed spectrum. Also since promotional effort resources are limited, one must use them judiciously. In this paper, we formulate mathematical programming problem under repeat purchase scenario, which optimally allocates mass promotional effort resources and differentiated promotional effort resources across the segments dynamically in order to maximize the overall sales obtained from multiple products of a product line under budgetary and minimum sales aspiration level constraint on each product under consideration in each segment. The planning horizon is divided into multi periods, the adoption pattern of each product in each segment is observed in every subinterval and accordingly promotional effort allocations are determined for the next period till we reach the end of planning period. The optimization model has been further extended to incorporate minimum aspiration level constraints on total sales for each product under consideration from all the segments taken together. The non linear programming problem so formulated is solved using differential evolution approach. A numerical example has been discussed to illustrate applicability of the model.
Grass, scrub, trees and random forest

Habitat classification is important for monitoring the environment and biodiversity. Currently, this is done manually by human surveyors, a laborious, expensive and subjective process. We have developed a new computer habitat classification method based on automatically tagging geo-referenced ground photographs. In this paper, we present a geo-referenced habitat image database containing over 400 high-resolution ground photographs that have been manually annotated by experts based on a hierarchical habitat classification scheme widely used by ecologists. This will be the first publicly available image database specifically designed for the development of multimedia analysis techniques for ecological (habitat classification) applications. We formulate photograph-based habitat classification as an automatic image tagging problem and we have developed a novel random-forest based method for annotating an image with the habitat categories it contains. We have also developed an efficient and fast random-projection based technique for constructing the random forest. We present experimental results to show that ground-taken photographs are a potential source of information that can be exploited in automatic habitat classification and that our approach is able to classify with a reasonable degree of confidence three of the main habitat classes: Woodland and Scrub, Grassland and Marsh and Miscellaneous.
A New Localization Algorithm of Mobile Phone for Outdoor Emergency Rescue

In outdoor emergency rescue, it is of utmost importance to acquire the location of trapped people, the more quickly and precisely the location can be determined, the more chance can be saved for the victims. Taking a mobile phone of trapped people as a localization carrier, this work proposes a Remote Emergency Localization (REL) algorithm to calculate the location of mobile phone based on Portable Base Station (PBS). The performance of REL approach is evaluated by simulation, the results show REL is efficient for outdoor emergency rescue.
Hermaphroditic, demasculinized frogs after exposure to the herbicide atrazine at low ecologically relevant doses

Atrazine is the most commonly used herbicide in the U.S. and probably the world. It can be present at several parts per million in agricultural runoff and can reach 40 parts per billion (ppb) in precipitation. We examined the effects of atrazine on sexual development in African clawed frogs (Xenopus laevis). Larvae were exposed to atrazine (0.01–200 ppb) by immersion throughout larval development, and we examined gonadal histology and laryngeal size at metamorphosis. Atrazine (≥0.1 ppb) induced hermaphroditism and demasculinized the larynges of exposed males (≥1.0 ppb). In addition, we examined plasma testosterone levels in sexually mature males. Male X. laevis suffered a 10-fold decrease in testosterone levels when exposed to 25 ppb atrazine. We hypothesize that atrazine induces aromatase and promotes the conversion of testosterone to estrogen. This disruption in steroidogenesis likely explains the demasculinization of the male larynx and the production of hermaphrodites. The effective levels reported in the current study are realistic exposures that suggest that other amphibian species exposed to atrazine in the wild could be at risk of impaired sexual development. This widespread compound and other environmental endocrine disruptors may be a factor in global amphibian declines.
Effects of Listening Comprehension Anxiety from Saudi EFL Learners’ Perspectives

Anxiety has been an important topic of discussion in foreign language learning. Listening comprehension anxiety can have negative effects on learners’ performance. Therefore, this paper aims at exploring the effects of listening comprehension anxiety on Saudi English as a Foreign Language (EFL) learners at Majmaah University, Saudi Arabia. This qualitative case study research design involves 15 participants. The findings show that the learners experienced high level of listening comprehension anxiety in their listening classes. Three main themes emerged from the interview data in relation to the effects of listening comprehension anxiety from the learners’ perspectives: 1) personal effect: losing concentration, feeling depressed and avoiding listening skill classes, 2) social effect: isolating oneself from others and showing bad behavior, and 3) academic effect: getting low performance and achievement.
EAR RECOGNITION AND OCCLUSION

Personal identification using 2D ear images still has many problems such as occlusion mostly caused by hair, earrings, and clothes. To avoid this problem, we propose to divide the ear image into non-overlapping equal divisions and identify persons through these non -occluded parts separately and then combine outputs of the classification of these parts in abstract, rank, and measurement level fusion. Experimental results show that the increasing of recognition rate through combining small parts of non -occluded divisions of ear image.
GENDER, POWER AND SEXUAL VIOLENCE: A COMMENTARY ON "YOU ARE NOT YOUR OWN:" RAPE, SEXUAL ASSAULT, AND CONSENT IN EVANGELICAL CHRISTIAN DATING BOOKS

In this commentary on “You Are Not Your Own:” Rape, Sexual Assault, and Consent in Evangelical Christian Dating Books (Moon, 2014; see this present issue of JISS), we invite a feminist extension of the author’s primary argument that religious institutions are vital sites for investigating the reproduction and maintenance of sexist attitudes. We critically analyze the findings introduced in this study and discuss the contributions of this work to continued research on social justice issues and examinations of sex, gender and sexuality as they relate to the circulation of power at institutional and individual levels in society. In her work Moon (2014) calls attention to multiple ways in which traditional religious discourse, specifically Evangelical Christian discourse, contributes to the perpetuation of rape myths. The focus on language as a cultural system for communication and meaning making analyzes the construction of gender with regard to sexual scripts and gender role expectations. In this research, the author conducts a textual analysis of selected dating books that offer perspectives on relationships, connection and intimacy from a religious perspective. The conclusion of this study suggests that while rape myths may not be directly or explicitly condoned within the religious dating literature reviewed, the prominence of discursively limiting sexual scripts operate at individual and institutional levels with significant consequences on cultural definitions, recognition and perpetuation of sexual domination and violence.