Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling the Temporal Dynamics of Social Rating Networks Using Bidirectional Effects of Social Relations and Rating Patterns

In this paper we first observe and analyze the temporal behavior of users in a social rating network on expressing ratings and creating social relations. Then, we model the temporal dynamics of a SRN based on our observations and using bidirectional effects of ratings and social relationships. While existing models for other types of social networks have captured some of the factors, our model is the first one to represent all four factors, i.e. social relations-on-ratings (social influence), social relations-on-social relations (transitivity), ratings-on-social relations (selection), and ratings-on-ratings (correlational influence). We also model the strength of each effect throughout the evolution of a SRN. Using our model, we develop a generative model for SRNs. Such a model can serve as basis for several purposes, in particular link prediction, rating prediction and prediction of future community structures. Given the sensitive nature of social network data, there are only very few public social rating network datasets. This motivates the development of generative models to create such synthetic datasets for research purposes. Our experimental study on the Epinions dataset demonstrates that the proposed model produces social rating networks that agree with real world data on a comprehensive set of evaluation criteria much better than existing models.
Burnout, Social Support, and Job Satisfaction among Jordanian Mental Health Nurses

Burnout occurs in occupations, such as nursing, where a significant proportion of time is spent in close involvement with other people. Mental health nursing has been considered an area that is subjected to high levels of burnout. Burnout in mental health nursing affects both individuals and organizations. The purposes of this study were to measure the levels of burnout and identify the correlates of burnout among Jordanian mental health nurses. A descriptive correlational design was used to collect data from mental health nurses using the Maslach Burnout Inventory, Social Support Scale, Job Satisfaction Scale, and demographic and work-related variables through a self-reported questionnaire. The sample consisted of 181 mental health nurses recruited from all mental health settings in Jordan. Jordanian mental health nurses showed high levels of emotional exhaustion and moderate levels of depersonalization and personal accomplishment. Scores of job satisfaction and social support were slightly higher than the midrange. Significant correlations were found among burnout categories, job satisfaction, social support, and demographic and work-related variables. Predictor variables accounted for 32.7% of emotional exhaustion, 27.7% of depersonalization, and 16.8% of personal accomplishment. Results revealed that a comprehensive interventional approach aimed at minimizing the risk of burnout among mental health nurses is needed. Such an approach should involve interventions at both individual and organizational levels.
Diet Quality and Food Limitation Affect the Dynamics of Body Composition and Digestive Organs in a Migratory Songbird (Zonotrichia albicollis)

Migrating songbirds interrupt their feeding to fly between stopover sites that may vary appreciably in diet quality. We studied the effects of fasting and food restriction on body composition and digestive organs in a migratory songbird and how these effects interacted with diet quality to influence the rate of recovery of nutrient reserves. Food limitation caused white‐throated sparrows to reduce both lean and fat reserves, with about 20% of the decline in lean mass represented by a decline in stomach, small intestine, and liver. During refeeding on diets similar in nutrient composition to either grain or fruit, food‐limited grain‐fed birds ate 40% more than did control birds, and they regained body mass, with on average 60% of the increase in body mass composed of lean mass including digestive organs. In contrast, food‐limited fruit‐fed birds did not eat more than did control birds and did not regain body mass, suggesting that a digestive constraint limited their food intake. The interacting effects of food limitation and diet quality on the dynamics of body composition and digestive organs in sparrows suggest that the adequacy of the diet at stopover sites can directly influence the rate of recovery of body reserves in migrating songbirds and hence the pace of their migration.
Sublingual immunotherapy not effective in house dust mite–allergic children in primary care

To cite this article: de Bot CMA, Moed H, Berger MY, Röder E, Hop WCJ, de Groot H, de Jongste JC, van Wijk RG, Bindels PJE, van der Wouden JC. Sublingual immunotherapy not effective in house dust mite–allergic children in primary care. Pediatr Allergy Immunol 2011; Doi: 10.1111/j.1399‐3038.2011. 01219.x
Last Year of Life Study Cologne (LYOL-C): protocol for a cross-sectional mixed methods study to examine care trajectories and transitions in the last year of life until death

Introduction The last year of life constitutes a particularly vulnerable phase for patients, involving nearly all health and social care structures. Yet, little scientific evidence is available that provides insight into the trajectories including the number and types of care setting transitions, transitions into palliative care and the dying phase. Only few studies have focused on difficulties associated with having to move between health and social care settings in the last year of life, although patients face a significant risk of adverse events. The Last Year of Life Study Cologne (LYOL-C) aims to fill this gap. Methods and analysis LYOL-C is a mixed-methods study composed of four steps: (1) Claims data collected by the statutory health insurance funds of deceased persons will be analysed with regard to patient care trajectories, health service transitions and costs in the last year of life. (2) Patient trajectories and transitions in healthcare will additionally be reconstructed by analysing the retrospective accounts of bereaved relatives (n=400) using a culturally adapted version of the Views of Informal Carers—Evaluation of Services Short Form questionnaire and the Patient Assessment of Care for Chronic Conditions Short Form questionnaire adapted for relatives. (3) Qualitative interviews with bereaved relatives (n=40–60) will provide in-depth insight into reasons for transitions and effects on patients’ quality of life. (4) Focus groups (n=3–5) with Healthcare Professionals will be conducted to discuss challenges associated with transitions in the last year of life. Ethics and dissemination Ethical approval has been obtained from the Ethics Commission of the Faculty of Medicine of Cologne University (#17–188). Results will be submitted for publication in peer-reviewed journals and presented at national and international conferences. Trial registration number The study is registered in the German Clinical Trials Register (DRKS00011925) and in the Health Services Research Database (VfD_CoRe-Net_17_003806).
Realtime Reconstruction of an Animating Human Body from a Single Depth Camera

We present a method for realtime reconstruction of an animating human body,which produces a sequence of deforming meshes representing a given performance captured by a single commodity depth camera. We achieve realtime single-view mesh completion by enhancing the parameterized SCAPE model.Our method, which we call Realtime SCAPE, performs full-body reconstruction without the use of markers.In Realtime SCAPE, estimations of body shape parameters and pose parameters, needed for reconstruction, are decoupled. Intrinsic body shape is first precomputed for a given subject, by determining shape parameters with the aid of a body shape database. Subsequently, per-frame pose parameter estimation is performed by means of linear blending skinning (LBS); the problem is decomposed into separately finding skinning weights and transformations. The skinning weights are also determined offline from the body shape database,reducing online reconstruction to simply finding the transformations in LBS. Doing so is formulated as a linear variational problem;carefully designed constraints are used to impose temporal coherence and alleviate artifacts. Experiments demonstrate that our method can produce full-body mesh sequences with high fidelity.
Abnormal anterior cingulate cortical activity during emotional n-back task performance distinguishes bipolar from unipolar depressed females

Background Depression in the context of bipolar disorder (BDd) is often misdiagnosed as unipolar disorder depression (UDd) leading to poor clinical outcomes for many bipolar sufferers. We examined neural circuitry supporting emotion regulation in females with either BDd or UDd as a first stage toward identifying biomarkers that may differentiate BDd from UDd. Method Fifty-seven females aged 18–45 years participated in this study: 23 with UDd, 18 with bipolar disorder type I depression (BDId) and 16 healthy females. During 3-T functional magnetic resonance imaging (fMRI), the participants performed an emotional face n-back (EFNBACK) task, that is an n-back task with high (2-back) and low (0-back) memory load conditions flanked by two positive, negative or neutral face distracters. This paradigm examines executive control with emotional distracters–emotion regulation. Results High memory load with neutral face distracters elicited greater bilateral and left dorsal anterior midcingulate cortex (dAMCC) activity in UDd than in healthy and BDId females respectively, and greater bilateral putamen activity in both depressed groups versus healthy females. High memory load with happy face distracters elicited greater left putamen activity in UDd than in healthy females. Psychotropic medication was associated with greater putamen activity to these contrasts in UDd females. Conclusions During high memory load with neutral face distracters, elevated dAMCC activity in UDd suggests abnormal recruitment of attentional control circuitry to maintain task performance, whereas elevated putamen activity unrelated to psychotropic medication in BDId females may suggest an attentional bias toward ambiguous neutral face distracters. Differential patterns of functional abnormalities in neural circuitry supporting attentional control during emotion regulation, especially in the dAMCC, is a promising neuroimaging measure to distinguish UDd from BDId in females.
Clustering gene expression patterns of fly embryos

The spatio-temporal patterning of gene expression in early embryos is an important source of information for understanding the functions of genes involved in development. Most analyses to date rely on biologists' visual inspection of microscope images, which for large-scale datasets becomes impractical and subjective. In this paper, we introduce a new method for clustering 2D images of gene expression patterns in Drosophila melanogaster (fruit fly) embryos. These patterns, typically generated from in situ hybridization of mRNA probes, reveal when, where and how abundantly a target gene is expressed. Our method involves two steps. First, we use an eigen-embryo model to reduce noise and generate feature vectors that form a better basis for capturing the salient aspects of quantized embryo images. Second, we cluster these feature vectors by an efficient minimum-spanning-tree partition algorithm. We investigate this approach on fly embryo datasets that span the entire course of embryogenesis. The experimental results show that our clustering algorithm produces superior pattern clusters. We also find previously unobserved clusters of genes that share biologically interesting patterns of gene-expression
Title Epigenetic inactivation of miR-9 family microRNAs in chronic lymphocytic leukemia-- implications on constitutive activation of NF κ B pathway

Background: The miR-9 family microRNAs have been identified as a tumor suppressor miRNA in cancers. We postulated that miR-9-1, miR-9-2 and miR-9-3 might be inactivated by DNA hypermethylation in chronic lymphocytic leukemia (CLL). Methods: Methylation of miR-9-1, miR-9-2 and miR-9-3 was studied in eight normal controls including normal bone marrow, buffy coat, and CD19-sorted peripheral blood B-cells from healthy individuals, seven CLL cell lines, and seventy-eight diagnostic CLL samples by methylation-specific polymerase chain reaction. Results: The promoters of miR-9-3 and miR-9-1 were both unmethylated in normal controls, but methylated in five (71.4%) and one of seven CLL cell lines respectively. However, miR-9-2 promoter was methylated in normal controls including CD19 + ve B-cells, hence suggestive of a tissue-specific but not tumor-specific methylation, and thus not further studied. Different MSP statuses of miR-9-3, including complete methylation, partial methylation, and complete unmethylation, were verified by quantitative bisulfite methylation analysis. 5-Aza-2′-deoxycytidine treatment resulted in miR-9-3 promoter demethylation and re-expression of pri-miR-9-3 in I83-E95 and WAC3CD5+ cells, which were homozygously methylated for miR-9-3. Moreover, overexpression of miR-9 led to suppressed cell proliferation and enhanced apoptosis together with downregulation of NFκB1 in I83-E95 cells, supporting a tumor suppressor role of miR-9-3 in CLL. In primary CLL samples, miR-9-3 was detected in 17% and miR-9-1 methylation in none of the patients at diagnosis. Moreover, miR-9-3 methylation was associated with advanced Rai stage (≥ stage 2) (P = 0.04). Conclusions: Of the miR-9 family, miR-9-3 is a tumor suppressor miRNA relatively frequently methylated, and hence silenced in CLL; whereas miR-9-1 methylation is rare in CLL. The role of miR-9-3 methylation in the constitutive activation of NFκB signaling pathway in CLL warrants further study.
Optimal design of Fresnel lens for a reading light system with multiple light sources using three-layered hierarchical genetic algorithm

A typical Fresnel lens is not suitable to a reading light system with multiple light sources since it is designed in such a way that each groove is at a slightly different angle from the next but with the same focal length. Therefore, a Fresnel lens with suitably designed groove angles is needed for this kind of light system. In this paper, a more efficient three-layered Hierarchical Genetic Algorithm (3LHGA) is proposed to find an optimal set of groove angles for a designed Fresnel lens to optimize both the illuminace and uniformity for a reading light system with multiple light sources. The groove angles of a designed Fresnel lens are directly derived from a Fresnel lens database by two layers of control genes in the proposed 3LHGA. The proposed 3LHGA not only makes it possible to evolve a lot of groove angles as parametric genes but also further improve the performance of a Fresnel lens and increase the speed of evolution. From the simulation results we can demonstrate that the designed Fresnel lens indeed offers improvement of light-guiding performance for a multiple-LED reading light system.
Identifying Compromised Accounts on Social Media Using Statistical Text Analysis

Compromised social media accounts are legitimate user accounts that have been hijacked by a third (malicious) party and can cause various kinds of damage. Early detection of such compromised accounts is very important in order to control the damage. In this work we propose a novel general framework for discovering compromised accounts by utilizing statistical text analysis. The framework is built on the observation that users will use language that is measurably different from the language that a hacker (or spammer) would use, when the account is compromised. We use the framework to develop specific algorithms based on language modeling and use the similarity of language models of users and spammers as features in a supervised learning setup to identify compromised accounts. Evaluation results on a large Twitter corpus of over 129 million tweets show promising results of the proposed approach.
Mixed-Norm Regularization for Brain Decoding

This work investigates the use of mixed-norm regularization for sensor selection in event-related potential (ERP) based brain-computer interfaces (BCI). The classification problem is cast as a discriminative optimization framework where sensor selection is induced through the use of mixed-norms. This framework is extended to the multitask learning situation where several similar classification tasks related to different subjects are learned simultaneously. In this case, multitask learning helps in leveraging data scarcity issue yielding to more robust classifiers. For this purpose, we have introduced a regularizer that induces both sensor selection and classifier similarities. The different regularization approaches are compared on three ERP datasets showing the interest of mixed-norm regularization in terms of sensor selection. The multitask approaches are evaluated when a small number of learning examples are available yielding to significant performance improvements especially for subjects performing poorly.
A Multi-task Selected Learning Approach for Solving New Type 3D Bin Packing Problem

This paper studies a new type of 3D bin packing problem (BPP), in which a number of cuboid-shaped items must be put into a bin one by one orthogonally. The objective is to find a way to place these items that can minimize the surface area of the bin. This problem is based on the fact that there is no fixed-sized bin in many real business scenarios and the cost of a bin is proportional to its surface area. Based on previous research on 3D BPP, the surface area is determined by the sequence, spatial locations and orientations of items. It is a new NP-hard combinatorial optimization problem on unfixed-sized bin packing, for which we propose a multi-task framework based on Selected Learning, generating the sequence and orientations of items packed into the bin simultaneously. During training steps, Selected Learning chooses one of loss functions derived from Deep Reinforcement Learning and Supervised Learning corresponding to the training procedure. Numerical results show that the method proposed significantly outperforms Lego baselines by a substantial gain of 7.52%. Moreover, we produce large scale 3D Bin Packing order data set for studying bin packing problems and will release it to the research community.
Indexing the fully evolvement of spatiotemporal objects

This paper proposes a novel economic and efficient framework of indexing spatiotemporal objects based on compressed B+-trees. Our new index technique can compress data records in leaves and in turn reduce index size to improve update and query efficiencies. The contribution of our framework is threefold. First, the proposed index structures are more succinct to resident in the main memory. Second, sufficient data with high similarity inside all indexing pages for the high retrieval quality of cache fetches are attainable. Third, in addition to process multi-dimensional spatial information, our framework is typically appropriate to model the valid- and transaction-time of a fact. We present the index efficiency analyses and experimental results which show that our technique outperforms others.
Learning Topics and Positions from Debatepedia

We explore Debatepedia, a communityauthored encyclopedia of sociopolitical debates, as evidence for inferring a lowdimensional, human-interpretable representation in the domain of issues and positions. We introduce a generative model positing latent topics and cross-cutting positions that gives special treatment to person mentions and opinion words. We evaluate the resulting representation’s usefulness in attaching opinionated documents to arguments and its consistency with human judgments about positions.
Attachment of oligonucleotide probes to polymer biochips and its application for the detection of point mutations

This dissertation is on the fabrication of polymer-based microfluidic arrays for the detection of genetic mutations. Poly(methyl methacrylate) (PMMA) was chosen as one of the polymer substrate materials due to its low background levels, low adsorption of biomolecules, and low assembly temperatures. The surface modification of polymer substrates for covalent attachment of oligonucleotide probes, the construction of fluidic channels/arrays, and hybridization kinetics in coupled microfluidic channels and arrays will be covered. As an example of the application, point mutation detection using immobilized arrays constructed in microfluidic devices will be demonstrated. The PMMA surface was derivatized with N-lithioethylenediamine solution to introduce amine groups, which were utilized for the covalent immobilization of terminal amino modified oligonucleotide probes via the homo-bi-functional linker molecule. The coupling bonds formed were stable enough to withstand multiple denaturation/rehybridization cycles. To overcome the drawbacks associated with conventional 2-D flat microarrays, such as long hybridization times and large sample consumption, oligonucleotide arrays were constructed into the microfluidic channels hot embossed into PMMA substrate. With the use of these fluidic channels, we observed increased hybridization kinetics as compared to that on the flat arrays. Another benefit is that the channel-attached oligonucleotide probes allowed the detection of target concentrations down to pM levels. Specially designed oligonucleotide probes, which had similar melting temperatures, were printed in microfluidic channels. Low-abundant point mutations in K-ras genes were successfully detected by using a ligase detection reaction (LDR) combined with the microfluidic hybridization. Near-IR laser-induced fluorescence was used for the detection of surface conducted bioanalytical reactions and high detection sensitivity was obtained.
Activated ezrin controls MISP levels to ensure correct NuMA polarization and spindle orientation

ABSTRACT Correct spindle orientation is achieved through signaling pathways that provide a molecular link between the cell cortex and spindle microtubules in an F-actin-dependent manner. A conserved cortical protein complex, composed of LGN (also known as GPSM2), NuMA (also known as NUMA1) and dynein–dynactin, plays a key role in establishing proper spindle orientation. It has also been shown that the actin-binding protein MISP and the ERM family, which are activated by lymphocyte-oriented kinase (LOK, also known as STK10) and Ste20-like kinase (SLK) (hereafter, SLK/LOK) in mitosis, regulate spindle orientation. Here, we report that MISP functions downstream of the ERM family member ezrin and upstream of NuMA to allow optimal spindle positioning. We show that MISP directly interacts with ezrin and that SLK/LOK-activated ezrin ensures appropriate cortical MISP levels in mitosis by competing with MISP for actin-binding sites at the cell cortex. Furthermore, we found that regulation of the correct cortical MISP levels, by preventing its excessive accumulation, is essential for crescent-like polarized NuMA localization at the cortex and, as a consequence, leads to highly dynamic astral microtubules. Our results uncover how appropriate MISP levels at the cortex are required for proper NuMA polarization and, therefore, an optimal placement of the mitotic spindle within the cell. This article has an associated First Person interview with the first author of the paper. Summary: Activated ezrin controls cortical MISP levels, which are necessary for proper NuMA polarization at the cortex and, hence, precise spindle orientation.