Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Type and Severity of Intimate Partner Violence on Women’s Health and Service Use

Intimate partner violence (IPV) has major affects on women’s wellbeing. There has been limited investigation of the association between type and severity of IPV and health outcomes. This article describes socio-demographic characteristics, experiences of abuse, health, safety, and use of services in women enrolled in the Women’s Evaluation of Abuse and Violence Care (WEAVE) project. We explored associations between type and severity of abuse and women’s health, quality of life, and help seeking. Women (aged 16–50 years) attending 52 Australian general practices, reporting fear of partners in last 12 months were mailed a survey between June 2008 and May 2010. Response rate was 70.5% (272/386). In the last 12 months, one third (33.0%) experienced Severe Combined Abuse, 26.2% Physical and Emotional Abuse, 26.6% Emotional Abuse and/or Harassment only, 2.7% Physical Abuse only and 12.4% scored negative on the Composite Abuse Scale. A total of 31.6% of participants reported poor or fair health and 67.9% poor social support. In the last year, one third had seen a psychologist (36.6%) or had 5 or more general practitioner visits (34.3%); 14.7% contacted IPV services; and 24.4% had made a safety plan. Compared to other abuse groups, women with Severe Combined Abuse had poor quality of life and mental health, despite using more medications, counseling, and IPV services and were more likely to have days out of role because of emotional issues. In summary, women who were fearful of partners in the last year, have poor mental health and quality of life, attend health care services frequently, and domestic violence services infrequently. Those women experiencing severe combined physical, emotional, and sexual abuse have poorer quality of life and mental health than women experiencing other abuse types. Health practitioners should take a history of type and severity of abuse for women with mental health issues to assist access to appropriate specialist support.
ExRank: An Exploratory Ranking Interface

Even with simple everyday tasks like online shopping or choosing a restaurant, users are easily overwhelmed with the large number of choices available today, each with a large number of inter-related attributes. We present ExRank, an interactive interface for exploring data that helps users understand the relationship between attribute values and find interesting items in the dataset. Based on a kNN graph and a PageRank algorithm, ExRank suggests which attributes the user should look at, and how expressed choices in particular attributes affect the distribution of values in other attributes for candidate objects. It solves the problem of empty result by showing similar items and when there are too many results, it ranks the data for the user. This demo consists of 1) the description of the software architecture and the user interface 2) the logic and reason behind our solution and 3) a list of demonstration scenarios for showing to the audience.
Clinical significance of subcortical vascular disease in patients with mild cognitive impairment

Patients with mild cognitive impairment (MCI) typically present with memory complaints. Some of these patients have subcortical vascular disease on computed tomography (CT) scan, namely white matter changes and lacunar infarcts, however it is not known whether these findings are associated with more pronounced cognitive deficits. In the present study we compare demographic, clinical and neuropsychological characteristics of MCI patients according to the presence or the absence of subcortical vascular disease. Forty consecutive patients with memory complaints, at least one neuropsychological memory test below 1 SD the normal for age and education, and maintained activities of daily living, were included. Patients with dementia, history of stroke or transient ischemic attack, or other brain disorders, were excluded. Twenty‐five (62.5%) patients with MCI had no ischemic lesions on CT scan, and 15 (37.5%) were found to have subcortical vascular changes. MCI patients with subcortical vascular changes were older (77.1 ± 6.8 vs. 70.8 ± 7.5 years old), and more often males. The number of vascular risk factors, the frequency of neurological signs, the Hachinski score and the neuropsychological tests scores were not significantly different. The presence of subcortical vascular disease on CT scan is frequent in older patients with MCI, but does not appear to be associated with the severity of cognitive deficits.
Diagnosis of primary aldosteronism: value of different screening parameters and influence of antihypertensive medication.

OBJECTIVE The aim of this study was to investigate the utility of different screening techniques for primary aldosteronism (PA), including serum aldosterone (SA), plasma renin activity (PRA) and the SA/PRA ratio in hypertensive patients of a tertiary-care centre. Furthermore, the influence of antihypertensive medication on SA and the SA/PRA ratio were studied. DESIGN Clinical records of 425 hypertensive patients who had SA and PRA measurements over a 27-month period were analysed retrospectively. Eighty patients were excluded from further analysis because of incomplete data. The remaining 345 patients were classified into the following groups: patients with essential hypertension (EH) (n=260, 75.4%), patients with PA (n=49, 14.2%) and patients with secondary hypertension other than PA (n=36, 10.4%). Diagnosis of PA was made in accordance with established laboratory criteria (including measurements of SA, PRA, urinary excretion of aldosterone and metabolites, imaging techniques and response to treatment). RESULTS Although mean serum potassium values were significantly lower (P<0.001) in the PA group compared with the EH group, 61% of PA subjects were normokalaemic (3.4-5.2 mmol/l). The SA/PRA ratio alone identified 94% of the patients with PA, but was false positive in 30% of the patients with EH. The SA/PRA ratio together with SA>150 g/ml increased the diagnostic accuracy, led to the correct identification of 84% of the patients with PA, and decreased the false-positive rate to 3%. A multivariate binary logistic regression analysis based on SA and PRA was performed, which identified PA with 90% sensitivity and 91% accuracy. The SA(2)/PRA or the SA(3)/PRA ratio was found useful for simplification of the regression analysis. Antihypertensive medication influenced SA, PRA and the SA/PRA ratio only in EH patients. In EH patients taking beta-adrenoceptor antagonists PRA tended to be lower, leading to a significantly higher SA/PRA ratio and therefore increasing the false-negative rate. CONCLUSION To reduce false-positive results in screening for PA, and thereby avoid unnecessary and cost-intensive diagnostic procedures, SA should be taken into account in addition to the SA/PRA ratio as a second screening criterion. Alternatively, the SA(2)/PRA or the SA(3)/PRA ratio is more accurate screening tests than the SA/PRA ratio. Beta-blockers should be avoided whilst screening for PA.
The TELRI tool catalogue: structure and prospects

In the scope of the TELRI concerted action a working group is investigating the formation of a tool catalogue and repository. The idea is similar to that of the ACL Natural Language Software Registry, but the contents should be mostly limited to corpus processing tools available free of cost for research use. The catalogue should also offer a help-line for installing and using the software. The paper reports on the setup of this catalogue, and concentrates on the technical issues involved in its creation, storage and display. This involves the form interface on the Web, the XML DocBook encoding, and the XSL stylesheets used to present the catalogue either on the Web or in print. The paper lists the current entries in the catalogue and discusses plans for their expansion and maintenance.
Melanie: multi-level modeling and ontology engineering environment

Multi-level modeling based on deep instantiation has attracted growing interest over the last few years as a better way of creating and organizing models capturing problem domains featuring more than one classification level. However, until recently the approach has lacked practical tool support. This work introduces Melanie, a new MultiLevel Modeling and Ontology Engineering Environment, that has been specifically developed to support multi-level modeling as well as other important new modeling use cases such as unified exploratory / constructive modeling, symbiotic domain-specific / general purpose languages and interactive (meta)modeling. This work briefly explains the motivations and goals behind Melanie and provides a short overview of its features and architecture.
Gene Silencing in Androgen-Responsive Prostate Cancer Cells from the Tissue-Specific Prostate-Specific Antigen Promoter

The success of gene therapy using a RNA interference approach relies on small interfering RNA (siRNA) expression from a highly tissue-specific RNA polymerase II promoter rather than from ubiquitous RNA polymerase III. Accordingly, we have developed a prostate-specific vector that expresses siRNAs from the human prostate-specific antigen promoter, a RNA polymerase II promoter. Our data demonstrate androgen-dependent and tissue-specific siRNA-mediated gene silencing in the androgen-responsive prostate cancer cell line, LNCaP. The biological significance was evidenced by altered apoptotic activity through the inhibition of the apoptosis-related regulatory gene. These results demonstrate that siRNA-mediated gene silencing from a tissue-specific RNA polymerase II promoter could be a potential tool for tissue-specific gene therapy.
An Environment Model for N onstationary Reinforcement Learning

Reinforcement learning in nonstationary environments is generally regarded as an important and yet difficult problem. This paper partially addresses the problem by formalizing a subclass of nonsta-tionary environments. The environment model, called hidden-mode Markov decision process (HM-MDP), assumes that environmental changes are always confined to a small number of hidden modes. A mode basically indexes a Markov decision process (MDP) and evolves with time according to a Markov chain. While HM-MDP is a special case of partially observable Markov decision processes (POMDP), modeling an HM-MDP environment via the more general POMDP model unnecessarily increases the problem complexity. A variant of the Baum-Welch algorithm is developed for model learning requiring less data and time.
An Experience with Ontology-based Agent Clustering

This article presents a structure of multiple shared ontologies to integrate heterogeneous sources. This specific structure is intended to be easy to implement to maintain and to scale, and also close to the human model of conceptualisation. The structure has been investigate in a small scale experiment set in the domain of the international coffee preparation. The experiment has also addressed, an identification of the different types of heterogeneity that can affect the resources.
Research on public-key digital watermarking system

Digital watermarks are signals embedded in multimedia data to allow copyright enforcement or to distinguish copies of the document and it's still a novel study area. While a public-key watermarking system allows two parties who have never met or exchanged a secret to send hidden messages over a public channel so that an adversary cannot even detect that these hidden messages are being send, and in copyright protection, everybody who owns the public key can detect and verify the authenticity of watermarking information but can't alternate or remove it. In this work, we propose a public-key watermarking method, where combined a public/private key cryptographic method with a digital watermarking technique together, which is suitable for protection of the copyright as a fragile watermarking method. The embedding method based on wavelet transform and RSA encryption algorithm. The use of a public/private key cryptographic system guarantees anybody with the public-key can detect the embedding information. So it can be used for copyright protection of DVD system and other digital works.
A Query-Based Summarizer based on the Context

: Summarization condenses a document or multiple documents into a smaller version by preserving the information content and its meaning. It is very difficult to summarize large documents manually. Many summarizers have been developed to capture the content of the document. Existing models use similarity between the sentences to extract the most salient features. The techniques do not depend on the context of the document. A context sensitive model based on association of the terms is introduced. The resulting index weights are used to calculate sentence similarity.
A time-motion analysis of Paralympic football for athletes with cerebral palsy

To investigate the soccer match-play work of players with cerebral palsy, 40 elite players were monitored for cardiovascular and locomotive demands of tournament match play. Using global positioning satellite and heart rate monitors, total distance travelled, distance travelled at high intensity and very high intensity (m); frequency of high intensity and very high intensity activity; heart rate. Disability classes C5/6, C7 and C8 were compared. The results showed C8 players covered the greatest distance. Frequency, contribution and maximum speed of high intensity and very high intensity activity was greater in C8. There was a progressive decline in distances covered in all classes across match quarters. C8 spent more time above 85% HRmax. No differences were observed between C5/6 and C7 classes. In conclusion, C8 players most notably perform best in very high intensity activity associated with game-defining moments. C5/6 and C7 players performed equitably. This study is the first to provide an insight for practitioners and coaches interested in the work rates in soccer for athletes with cerebral palsy.
A Novel Segmentation Approach for Modeling of Radiated Emission and Immunity Test Setups

A novel procedure is developed to simulate radiated emission (RE) and immunity scenarios using a common approach for electronic control unit with complex wiring harness and terminations. This is possible by applying Huygens principle and Reciprocity theorem to the problem. A segmented approach is proposed to split the device under test into multiple segments, which converts the radiation problem to circuit simulation, in addition to reducing the requirement of computing resources. The proposed method is validated using measurements and also full-wave three-dimensional simulations for both RE and immunity test setups.
State-space black-box model identification of a voltage-source converter with LCL filter

The paper proposes a multivariable identification method to identify the discrete state-space model of a grid-connected voltage-source converter and LCL filter. The method is based in one of the so-called subspace identification methods: the N4SID method. That kind of methods are based on the QR and the Singular Values decompositions and works with black-box state-space model structures, which mean particularly flexibility in the choice of the model representation. The so obtained discrete state-space model of the converter could be used to design directly the control of the system using advanced control techniques as robust control, optimal control, etc.
Annotation guided local similarity search in multiple sequences and its application to mitochondrial genomes

Given a set of nucleotide sequences and corresponding gene annotations which might contain a moderate number of errors we consider the problem to identify common substrings occurring in homologous genes and to identify putative errors in the given annotations. The problem is solved by identifying nodes in a suffix tree that contains all substrings occurring in the data set. Due to the large size of the targeted data set our approach employs a truncated version of suffix trees. The approach is successfully applied to the mitochondrial nucleotide sequences and the corresponding annotations available in RefSeq for more than 2000 metazoan species. We demonstrate that the approach finds appropriate subsequences despite of errors in the given annotations. Moreover, it identifies several hundred errors within the RefSeq annotations.
Mining consumer's opinion target based on translation model and word representation

In recent years, the E-commercial plays an important role in people's daily life. When on the Internet, people often buy commodities from Taobao, Tmall and make comments on them, the comments of the goods may have closely connections with commercial value, which often reflect what's the consumers really care when they choose one piece of good among thousands of other similar ones. How to mining these aspects which the consumers really concern is a problem left unsolved. As a potential effective solution to construct structured information for people's preference, Information Extraction(IE) has attracted more and more scholar's attention. A meaningful research area is Opinion Target Extraction(OTE). This paper proposed a system using translation model as well as word representation method to obtain user's interests on dataset in Chinese. To release the word segmentation error, a finely generated system with new Chinese word detection module is proposed. The experiments on two corpus subjected on digital product verify the effective of our method.
Arrestin Serves as a Molecular Switch, Linking Endogenous α2-Adrenergic Receptor to SRC-dependent, but Not SRC-independent, ERK Activation*

Our previous studies have demonstrated that neither receptor endocytosis nor arrestin is required for ERK activation by the α2-adrenergic receptor (Wang, Q., Zhao, J., Brady, A. E., Feng, J., Allen, P. B., Lefkowitz, R. J., Greengard, P., and Limbird, L. E. (2004) Science 304, 1940–1944). The present studies address whether arrestin plays a role in determining the route of α2AR-evoked ERK signaling activation, taking advantage of endogenous expression of the α2AAR subtype in mouse embryonic fibroblasts (MEFs) and the availability of MEFs without arrestin expression (derived from Arr2,3–/– mice). Our data demonstrate that the endogenous α2AAR evokes ERK phosphorylation through both a Src-dependent and a Src-independent pathway, both of which are G protein dependent and converge on the Ras-Raf-MEK pathway. Arrestin is essential to recruit Src to this process, as α2AAR-mediated ERK signaling in Arr2,3–/– MEFs does not involve Src. Stimulation of α2AAR enhances arrestin-Src interaction and promotes activation of Src. α2 agonists have similar potencies in stimulating Src-dependent and Src-independent ERK phosphorylation in wild-type and Arr2,3–/– cells, respectively. However, Src-independent α2AAR-mediated ERK stimulation has both a longer duration of activation and a more rapid translocation of pERK into the nucleus when compared with Src-dependent activation. These data not only affirm the role of arrestin as an escort for signaling molecules such as Src family kinases but also demonstrate the impact of arrestin-dependent modulation on both the temporal and spatial properties of ERK activation.
Distributed Wireless Sensor Network Localization Via Sequential Greedy Optimization Algorithm

Node localization is essential to most applications of wireless sensor networks (WSNs). In this paper, we consider both range-based node localization and range-free node localization with uncertainties in range measurements, radio range, and anchor positions. First, a greedy optimization algorithm, named sequential greedy optimization (SGO) algorithm, is presented, which is more suitable for distributed optimization in networks than the classical nonlinear Gauss-Seidel algorithm. Then a unified optimization framework is proposed for both range-based localization and range-free localization, and two convex localization formulations are obtained based on semidefinite programming (SDP) relaxation techniques. By applying the SGO algorithm to the edge-based SDP relaxation formulation, we propose a second-order cone programming (SOCP)-based distributed node localization algorithm. Two distributed refinement algorithms are also proposed by using the SGO algorithm to nonconvex localization formulations. The proposed localization algorithms all can be implemented partially asynchronously in networks. Finally, extensive simulations are conducted to demonstrate the efficiency and accuracy of the proposed distributed localization algorithms.
Depth Filters Containing Diatomite Achieve More Efficient Particle Retention than Filters Solely Containing Cellulose Fibers

The clarification of biological feed stocks during the production of biopharmaceutical proteins is challenging when large quantities of particles must be removed, e.g., when processing crude plant extracts. Single-use depth filters are often preferred for clarification because they are simple to integrate and have a good safety profile. However, the combination of filter layers must be optimized in terms of nominal retention ratings to account for the unique particle size distribution in each feed stock. We have recently shown that predictive models can facilitate filter screening and the selection of appropriate filter layers. Here we expand our previous study by testing several filters with different retention ratings. The filters typically contain diatomite to facilitate the removal of fine particles. However, diatomite can interfere with the recovery of large biopharmaceutical molecules such as virus-like particles and aggregated proteins. Therefore, we also tested filtration devices composed solely of cellulose fibers and cohesive resin. The capacities of both filter types varied from 10 to 50 L m−2 when challenged with tobacco leaf extracts, but the filtrate turbidity was ~500-fold lower (~3.5 NTU) when diatomite filters were used. We also tested pre–coat filtration with dispersed diatomite, which achieved capacities of up to 120 L m−2 with turbidities of ~100 NTU using bulk plant extracts, and in contrast to the other depth filters did not require an upstream bag filter. Single pre-coat filtration devices can thus replace combinations of bag and depth filters to simplify the processing of plant extracts, potentially saving on time, labor and consumables. The protein concentrations of TSP, DsRed and antibody 2G12 were not affected by pre-coat filtration, indicating its general applicability during the manufacture of plant-derived biopharmaceutical proteins.
Geotag-based travel route recommendation featuring seasonal and temporal popularity

In this paper, a geotag-based travel route recommendation algorithm that considers the seasonal and temporal popularity is presented. Travel routes are extracted from geotags attached to Flickr images. Then, landmarks/routes that become particularly popular at a specific time range in a typical season are extracted. By using the Bayes' theory, the transition probability matrix is efficiently calculated. Experiments were conducted using 21 famous sightseeing cities/places in the world. The results have shown that the recommendation accuracy can be improved by 0.9% - 10.3% on average. The proposed algorithm can also be incoorporated into the state-of-the-art algorithms, having a potential for further recommendation accuracy improvement.