Miracle-dz/UniFAR-FTUs huggingface dataset:
HFE Genotypes in Decompensated Alcoholic Liver Disease: Phenotypic Expression and Comparison with Heavy Drinking and with Normal Controls

OBJECTIVES:Predisposition to alcoholic liver disease (ALD) may be partly genetic. Heterozygosity for the HFE mutations C282Y and/or H63D has been associated with more severe disease in several liver conditions. Studies in ALD have not used controls matched for alcohol consumption and results have been conflicting.METHODS:HFE genotyping was performed in two Caucasian heavy-drinking cohorts (>60 units/wk (M) or 40 units/wk (F) for >5 yr): (a) 254 patients with decompensated ALD (Child's grade B or C), (b) 130 controls with similar alcohol consumption but without liver disease. Results in males were also compared with those from another study of healthy male blood donors.RESULTS:(1) Genotype distributions for the C282Y and H63D mutations were similar in ALD patients, heavy-drinking controls, and healthy blood donors. (2) ALD patients with and without HFE mutations had similar disease severity, age at presentation, and alcohol consumption. (3) Increased serum ferritin and % transferrin saturation were seen in 63% and 29% of ALD patients, regardless of HFE genotype; the increased % transferrin saturation was due to reduced unsaturated iron binding capacity, rather than increased serum iron. (4) Stainable liver iron was present in 52% of patients; grade was greater in patients with two HFE mutations than in those with one or with none. (5) Only the two C282Y homozygote patients had substantial iron overload.CONCLUSIONS:Although serum iron abnormalities are common, C282Y and H63D mutation frequencies were not increased in heavy drinkers with decompensated liver disease. HFE mutations, although modestly influencing liver iron, do not predispose to clinically significant ALD.
Social Network Analyses of Patient-Healthcare Worker Interactions: Implications for Disease Transmission

Patients and healthcare workers (HCW) in healthcare settings represent a unique social network in which the risk of transmission of an infection is considered to be higher for both HCW and patients. Using data from existing clinical informatics resources, we constructed social networks of patient-HCW interactions in the emergency department of a tertiary care pediatric hospital. The structural properties of these networks were analyzed and compared to other well known networks. Patient-HCW networks do not demonstrate the classical power-law distribution of scale-free networks, thus indicating that they are different from social networks of individuals in a community. The clustering coefficient is larger as compared to a random network, indicating small world properties. The eigenvector centrality, used to identify the most important nodes, reveals HCW to be more connected than patients. These properties imply differences that must be taken into account when analyzing patient-HCW networks and planning interventions and mitigation strategies to prevent the spread of infectious diseases in healthcare settings.
Random walks driven by low moment measures

We study the decay of convolution powers of probability measures without second moment but satisfying some weaker finite moment condition. For any locally compact unimodular group G and any positive function ϱ:G→[0,+∞], we introduce a function ΦG,ϱ which describes the fastest possible decay of n↦ϕ(2n)(e) when ϕ is a symmetric continuous probability density such that ∫ϱϕ is finite. We estimate ΦG,ϱ for a variety of groups G and functions ϱ. When ϱ is of the form ϱ=ρ∘δ with ρ:[0,+∞)→[0,+∞), a fixed increasing function, and δ:G→[0,+∞), a natural word length measuring the distance to the identity element in G, ΦG,ϱ can be thought of as a group invariant.
A systematic search for near-infrared counterparts of nearby ultraluminous X-ray sources (II)

We present the results of our continued systematic search for near-infrared (NIR) candidate counterparts to ultraluminous X-ray sources (ULXs) within 10 Mpc. We observed 42 ULXs in 24 nearby galaxies and detected NIR candidate counterparts to 15 ULXs. Fourteen of these ULXs appear to have a single candidate counterpart in our images and the remaining ULX has two candidate counterparts. Seven ULXs have candidate counterparts with absolute magnitudes in the range between −9.26 and −11.18 mag, consistent with them being red supergiants (RSGs). The other eight ULXs have candidate counterparts with absolute magnitudes too bright to be a single stellar source. Some of these NIR sources show extended morphology or colours expected for active galactic nuclei (AGNs), strongly suggesting that they are likely stellar clusters or background galaxies. The RSG candidate counterparts form a valuable sample for follow-up spectroscopic observations to confirm their nature, with the ultimate goal of directly measuring the mass of the compact accretor that powers the ULX using binary Doppler shifts.
Sparse graph regularization for robust crop mapping using hyperspectral remotely sensed imagery: A case study in Heihe, Zhangye oasis

In this research, a novel sparse graph regularization (SGR) method was presented, aiming at robust crop mapping using hyperspectral imagery with very few in situ data. The core of SGR lies in propagating labels from known data to unknown, which is triggered by: 1) the fraction matrix generated for the large unknown data by using an effective sparse representation algorithm with respect to the few training data serving as the dictionary; 2) the prediction function estimated for the few training data by formulating a regularization model based on sparse graph. Then, the labels of large unknown data can be obtained by maximizing the posterior probability distribution based on the two ingredients. The study area is located at Zhangye oasis in the middle reaches of Heihe watershed, Gansu, China, where eight crop types were mapped with Compact Airborne Spectrographic Imager (CASI) and Shortwave Infrared Airborne Spectrogrpahic Imager (SASI) hyperspectral data. Experimental results demonstrate that the proposed method significantly outperforms other classifiers, with an overall accuracy of 87.43% and a kappa value of 0.827 (5 labeled samples per class), which are respectively, 9%-30% and 0.1-0.3 higher than other counterparts.
Orientation of vascular cell divisions in Arabidopsis

Orientation of cell division is essential for plant development as the direction of growth is determined by the direction of cell expansion and orientation of cell division. We have demonstrated that cell division orientation in vascular tissue is regulated by the interactions between a receptor kinase (PXY) expressed in dividing cells and its peptide ligand (CLE41) that is localized to adjacent phloem cells. Given that other receptor kinases have been identified as orienting the cell division plane in several developmental processes, we suggest that localized signaling from adjacent cells may be a general mechanism for defining the plane of cell division.
Environment for Telehealth Applications on Top of BDI4JADE

Patients using telehealth systems have different needs and hence their treatments must differ accordingly. Different compositions of smart home sensors, telehealth devices, and services are used depending on the needs of the individual. This paper presents an open and flexible infrastructure implemented as an agent-based environment to handle the problem of seamless integration between the technologies used in telehealth deployments. The environment uses an ontology to facilitate semantic interoperability. Data providers are easily and transparently wrapped in JADE gateway agents, committed to the ontology, to integrate to the infrastructure.
System floorplanning optimization

Notebook and Laptop Original Equipment Manufacturers (OEMs) place great emphasis on creating unique system designs to differentiate themselves in the mobile market. These systems are developed from the `outside in' with the focus on how the system is perceived by the end-user. As a consequence, very little consideration is given to the interconnections or power of the devices within the system with a mentality of `just make it fit'. In this paper we discuss the challenges of Notebook system design and the steps by which system floor-planning tools and algorithms can be used to provide an automated method to optimize this process to ensure all required components most optimally fit inside the Notebook system.
Techniques for cold-starting context-aware mobile recommender systems for tourism

Novel research works in recommender systems have illustrated the benefits of exploiting contextual information, such as the time and location of a suggested place of interest, in order to better predict the user ratings and produce more relevant recommendations. But, when deploying a context-aware system one must put in place techniques for operating in the cold-start phase, i.e., when no or few ratings are available for the items listed in the system catalogue and it is therefore hard to predict the missing ratings and compose relevant recommendations. This problem has not been directly tackled in previous research. Hence, in order to address it, we have designed and implemented several novel algorithmic components and interface elements in a fully operational points of interest (POI) mobile recommender system (STS). In particular, in this article we illustrate the benefits brought by using the user personality and active learning techniques. We have developed two extended versions of the matrix factorisationalgorithmtoidentifywhatitemstheuserscouldandshouldrateandtocomposepersonalisedrecommendations.While context-aware recommender systems have been mostly evaluated offline, a testing scenario that suffers from many limitations, in our analysis we evaluate the proposed system in live user studies where the graphical user interface and the full interaction design play a major role. We have measured the system effectiveness in terms of several metrics such as: the quality and quantity of acquired ratings-in-context, the recommendation accuracy (MAE), the system precision, the perceived recommendation quality, the user choice satisfaction, and the system usability. The obtained results confirm that the proposed techniques can effectively overcome the identified cold-start problem.
An Extension of Tomlinson-Harashima Precoding for Downlink Multi-User MIMO Systems

Non-linear precoding (NLP) for downlink multi-user multiple-input multiple-output (DL-MU-MIMO) trans- mission is receiving much attention as a promising technology to achieve high capacity within the limited bandwidths available to radio access systems. In order to minimize the required transmission power for DL-MU- MIMO and achieve high spectrum efficiency, Vector Perturbation (VP) was proposed as an optimal NLP scheme. Unfortunately, the original VP suffers from significant computation complexity in searching the optimal perturbation vector due to the infinite number of perturbation vector candidates. To achieve the complexity reduction with the transmission performance near to that of Sphere Encoding VP (SE-VP), several recent studies have investigated various efficient NLP schemes based on Tomlinson-Harashima precoding (THP) approach that applies successive pre-cancellation of inter-user interference (IUI) and offsets the transmission vector based on the modulo operation. This paper investigates transmission performance improvement of Lattice Reduction Aided THP (LRA THP), called Extended LRA THP, where the modulo operation is substituted by seaching perturbation vector and subtracting this perturbation vector from the transmit signal vector. This paper proposes an extension of LRA THP with Minimum Mean Square Error based successive IUI pre-cancellation called Extended LRA MMSE-THP as a novel NLP scheme. Computer simulations quantitatively clarify that our proposed Extended LRA MMSE-THP achieves better transmission performance than the conventional NLP techniques while decreasing the number of searches required to determine the optimal perturbation vector.
Preparation and characterization of superparamagnetic magnetite (Fe3O4) nanoparticles: A short review

Magnetic magnetite (Fe3O4) nanoparticles have attracted a great deal of attention in both fundamental research and practical applications over the past decades. Down to the nanoscale, superparamagnetic Fe3O4 nanoparticles with only a single magnetic domain exhibit high magnetic susceptibility, which provides a stronger and faster magnetic response. Their superparamagnetic properties together with other intrinsic properties such as low toxicity, high surface area-to-volume ratio and simple separation methodology, making them ideal for environmental remediation, biomedical, and agricultural applications. This review discusses three conventional wet chemical methods, including chemical co-precipitation, sol-gel synthesis and thermal decomposition for the preparation of superparamagnetic Fe3O4 nanoparticles with controlled size and magnetic properties. Nowadays, with the growing research interest in Fe3O4 nanoparticles, there is a great amount of researches reported on efficient routes to prepare size-controlled magnetic nanoparticles. Thus, this review is designed to report the recent information from synthesis to the characterization of Fe3O4 nanoparticles as well as the discussion of future perspective in this research area.
Comparison of AVPU Scale and the Glasgow Coma Scale Score in Assessing Encephalitis in Children

Vietnam is a developing country with tropical climate where infectious diseases, especially encephalitis are common. Every year, in National Hospital of Pediatrics from 200 to 300 encephalitis patients are hospitalized due to encephalitis. A rapid assessment of consciousness level in encephalitis is of importance in treatment and prognosis for patients. Two scales are usually used in assessment of consciousness level, The Alert Verbal Painful Unresponsiveness (AVPU) scale and the Glasgow Coma Scale (GCS). The GCS score is one of the most commonly used methods. AVPU scale is a simple method for assessment of consciousness. We conducted this study to determine how the AVPU responsive scale corresponds with the GCS in children who have encephalitis.
HonIDS: enhancing honeypot system with intrusion detection models

Honeypots are highly valued for their detective function. However, suitable detection models use in honeypot system have not been fully explored. We present HonIDS, a honeypot system for detecting malicious hosts and intruders in local network. HonIDS is characterized by its layered structure and is enhanced by two detection models: TFRPP (times, frequency, range, port risk, average payload length) model and Bayes model. The basic idea of these models is that although it is hard to directly judge whether one interaction with the honeypots is an attack or malicious activity, it is possible to identify intruders by analyzing the plentiful and global events of honeypots in a given period of time. The TFRPP model gives the honeypot system the ability to assess different risks, by assigning dubiety scores to the hosts who visited honeypots. The Bayes detection model can detect some main types of attacks by classification. The results of our evaluation experiments indicate that TFRPP model and Bayes model are effective and suitable for honeypot system
Biological Actions of Artemisinin: Insights from Medicinal Chemistry Studies

Artemisinins have become essential antimalarial drugs for increasingly widespread drug-resistant malaria strains. Although tremendous efforts have been devoted to decipher how this class of molecules works, their exact antimalarial mechanism is still an enigma. Several hypotheses have been proposed to explain their actions, including alkylation of heme by carbon-centered free radicals, interference with proteins such as the sarcoplasmic/endoplasmic calcium ATPase (SERCA), as well as damaging of normal mitochondrial functions. Besides artemisinins, other endoperoxides with various backbones have also been synthesized, some of which showed comparable or even higher antimalarial effects. It is noteworthy that among these artemisinin derivatives, some enantiomers displayed similar in vitro malaria killing efficacy. In this article, the proposed mechanisms of action of artemisinins are reviewed in light of medicinal chemistry findings characterized by efficacy-structure studies, with the hope of gaining more insight into how these potent drugs work.
A Classifier-CMAC Neural Network Model for Web Mining

The rapid growth of Web has made it a huge source of information which will make the availability of data easier and more efficient if its content is well organized. Automatic classification of Web pages is one of the major methods in the Web content mining (WCM) which can be of great value in the development and maintenance of Web directories. Based on the analysis done, CMAC neural network showed faster learning in high dimensional problems, but considering the heavy data on the Web, the main challenge in Web page classification is how to deal with high dimensional feature space which increase the memory required by CMAC neural network. In the present paper a classifier-CMAC neural network model is proposed for use in content based Web page classification which requires less memory. The results reveal that the proposed model is more useful than any other algorithms.
Fra‐1/AP‐1 Impairs Inflammatory Responses and Chondrogenesis in Fracture Healing

Inflammation inevitably follows injury of various tissues, including bone. Transgenic overexpression of Fra‐1, a component of the transcription factor activator protein‐1 (AP‐1), in various tissues progressively and globally enhances bone formation, but little is known about the possible effects of Fra‐1/AP‐1 on fracture healing. We created a transverse fracture of the mouse tibial diaphysis and examined fracture healing radiologically, histologically, and immunologically. Strikingly, fracture union was delayed even though the bone formation rate in callus was higher in Fra‐1 transgenic (Tg) mice. In these mice, chondrogenesis around the fracture site was impaired, resulting in accumulation of fibrous tissue, which interferes with the formation of a bony bridge across the callus. Curiously, immediately after fracture, induction of the inflammatory mediators TNF‐α, interleukin (IL)‐6, and Cox‐2 was significantly suppressed in Fra‐1 Tg mice followed, by the reduced expression of Sox‐9 and BMP‐2. Because serum prostaglandin E2 (PGE2) levels were dramatically low in these mice, we administered PGE2 to the fracture site using a slow‐release carrier. The accumulation of fibrous tissue in Fra‐1 Tg mice was significantly reduced by PGE2 administration, and chondrogenesis near the fracture site was partially restored. These data suggest that the Fra‐1‐containing transcription factor AP‐1 inhibits fracture‐induced endochondral ossification and bony bridge formation presumably through suppression of inflammation‐induced chondrogenesis.
Cash Trade Within the Magic Circle: Free-to-Play Game Challenges and Massively Multiplayer Online Game Player Responses

Cash trades for virtual items in game worlds are now a recognized part of the “free game” business model, but perhaps at the expense of players’ senses of immersion, fairness, and fun. We review several perspectives related to Huizinga’s [8] “magic circle” concept in order to establish an analytical framework, then discuss player opinions in support of or opposed to free games, based on data collected from various sources. Our hope is that this study will be useful for those researchers who are monitoring the rapidly changing line separating game worlds and the physical world. Author Keywords free-to-play game model, magic circle, MMOGs, cash trade for virtual goods.
On the Trade-Off of Accuracy and Computational Complexity for Classifying Normal and Abnormal ECG in Remote CVD Monitoring Systems

Remote cardiovascular disease monitoring systems are characterised from a limited number of available leads and limited processing capabilities. In this paper, we investigate the trade-off between accuracy and computational complexity in order to derive the best strategy for classifying the ECG signal into normal or abnormal in such systems, with the spectral energy contained in the constituent waves of the ECG signal, as the primary feature for classification. Five established classifiers are considered and through exhaustive simulations the maximum accuracy is derived for each classifier. Based on 104 ECG records, we present a systematic analysis of the tradeoff between computational complexity and accuracy, which allow us to deduce the best classification strategy considering only a small number of available leads.
The Dynamics of IT Workaround Practices - A Theoretical Concept and an Empirical Assessment

An interesting phenomenon that has received limited attention in the extant literature is that of IT workaround practices. Based on Ashby's Law of Requisite Variety, workarounds were found to be used to accomplish the basic task of matching unmatched variety in the system. The Interaction Effectiveness (IE) ratio of 1.4 was used as a baseline to uncover potential sources of workarounds. The Echo method was used to collect data from 42 users in a high-technology company (HTC). Enablers of and barriers to workaround practices were divided into four main categories - flexibility, reliability, ease of use, and coordination - whereas workarounds were divided into three categories - using other tools, seeking help, and accepting. The results of the case study indicate that "reliability" is the dominant category for both helpful and non-helpful incidents, whereas "coordination" was the least significant. Of the workaround mechanisms, "using other tools" was the most significant category for all users. The findings suggest cycles of continuous improvement to the IE ratio to alleviate the need for workarounds, but a more fundamental issue concerning the source of workaround behaviors is a function of misfits between input variety by users and variety handling capabilities of the system.
Nanostructured Composites based on interpenetrated polymer networks

Using an interpenetrating polymer networks (IPN) principle in production of composite materials provides an unique possibility to regulate their both microand nanostructures and properties. By changing the IPN formation conditions (as a result of polymerization and ratio of components, temperature, pressure, catalyst content, introduction of filler and or ionic group) one may obtain the material with desirable properties. Different types of IPN are prepared by using traditional polymers: polyurethanes, including nonisocyanate polyurethanes, epoxies and acrylates; nonorganic filler scan be used as the cluster system. The article discusses their basic synthesis methods for IPNs their principal features and characteristics.