Miracle-dz/UniFAR-FTUs huggingface dataset:
Sentence Classifier for Helpdesk Emails

The rapid growth of online information has led to the increased need for methods to better organize such information. One common approach to handling such problem is the automated classification of documents into a predefined set of categories. This approach is generally referred to as text categorization (TC). Various TC methods have been imple-Most of these methods use low-level features, such as frequency of words in the documents, for classification tasks. Several studies have shown that high-level features, such as sentence types, can often be useful (McKnight and Srinivasan, 2003; Teufel and Moens, 2002). For example, an email can be assigned a priority based on the sentence types contained in that email, like task (" Send me the report as soon as possible ") or appointment (" We have decided to have a meeting at 3pm "). Other example include routing an email enquiry to an appropriate helpdesk operator based on the types of questions in the email enquiry. To obtain these high-level features, sentences in the texts will need to be classified. This project will investigate the methods to automatically classify sentences into a prede-fined set of sentence types. The outcome of this project will be a sentence classifier that aims to provide high-level features that can be used for further processing, for examples, in classification and summarization tasks. Email helpdesk will be used as the domain of the project due to its high volume of email enquiries. Further, if the sentence types can improve the automatic processing of some email enquiries, the overall productivity of the helpdesk can be improved. Sentence classification may appear fairly similar to TC. However, they differ in that sentence classification uses sentences as the unit of analysis, while TC uses documents as the unit of analysis. Most TC methods use only the words in the documents as features, discarding the ordering of the words. This creates a large feature vectors as there can be thousands or tens of thousands of words in a collection of documents. However, a particular document may contain only a small subset of all the words in the feature vectors. Thus, it is usually represented as a sparse data vector. As for sentence classification, the use of sentences as representation unit will lead to increased sparseness in an already sparse data vector (McKnight and Srinivasan, 2003). Therefore, using words-only approach to classify sentences is not likely to be as …
Weighted Graph Constraint and Group Centric Non-negative Matrix Factorization for gene-phenotype association prediction

Gene-phenotype association prediction can be applied to reveal the inherited basis of human diseases and help drug development. Gene-phenotype associations are related to complex biological process and influenced by various factors, such as relationship between phenotypes and that among genes. While due to sparseness of curated gene-phenotype associations, existing approaches are limited to prediction accuracy. In this paper, we propose a novel method by exploiting weighted graph constraint learned from hierarchical structures of phenotype data and group prior information among genes by inheriting advantages of Non-negative Matrix Factorization (NMF), called Weighted Graph Constraint and Group Centric Non-negative Matrix Factorization (GC2NMF). Specifically, firstly we introduce the depth of parent-child relationships between two adjacent phenotypes in hierarchal phenotypic data as weighted graph constraint for a better phenotype understanding. Secondly, we utilize intra-group correlation among genes in a gene group as group constraint for gene understanding. Such information provides us an intuitive priori that genes in a group probably result in similar phenotypes. The model allows not only to achieve a high prediction performance but also jointly to learn interpretable representation of genes and phenotypes to handle future biological analysis. Experimental results on biological gene-phenotype association datasets of mouse and human demonstrate that GC2NMF can obtain superior prediction accuracy and good understandability for biological explanation over other state-of-the-art methods.
Counting Maximal Distance-Independent Sets in Grid Graphs

Abstract Previous work on counting maximal independent sets for paths and certain 2-dimensional grids is extended in two directions: 3-dimensional grid graphs are included and, for some/any ℓ ∈ N, maximal distance-ℓ independent (or simply: maximal ℓ-independent) sets are counted for some grids. The transfer matrix method has been adapted and successfully applied
Association between thyroid dysfunction and venous thromboembolism in the elderly: a prospective cohort study

Essentials Subclinical thyroid dysfunction (SCTD) has been related to hypercoagulability. We studied its association with recurrent venous thromboembolism (rVTE). Subclinical hyperthyroidism, but not hypothyroidism, may be associated with lower rVTE risk. SCTD is not associated with mortality/differences in thrombophilic biomarkers.
in complex : the case of scientific collaboration.

The friendship paradox states that your friends have on average more friends than you have. Does the paradox ‘‘hold’’ for other individual characteristics like income or happiness? To address this question, we generalize the friendship paradox for arbitrary node characteristics in complex networks. By analyzing two coauthorship networks of Physical Review journals and Google Scholar profiles, we find that the generalized friendship paradox (GFP) holds at the individual and network levels for various characteristics, including the number of coauthors, the number of citations, and the number of publications. The origin of the GFP is shown to be rooted in positive correlations between degree and characteristics. As a fruitful application of the GFP, we suggest effective and efficient sampling methods for identifying high characteristic nodes in large-scale networks. Our study on the GFP can shed lights on understanding the interplay between network structure and node characteristics in complex networks.
Preferential Glutathione Conjugation of a Reverse Diol Epoxide Compared with a Bay Region Diol Epoxide of Benzo[a]pyrene in Human Hepatocytes

Many studies have examined the relationship between polymorphisms in glutathione S-transferase genes and cancer in people exposed to polycyclic aromatic hydrocarbons (PAH) such as benzo[a]pyrene (BaP), but the results to date have been modest. Missing from these studies has been an exploration of the formation of the appropriate glutathione conjugates in humans. We incubated human hepatocytes from 10 donors with racemic anti-BaP-7,8-diol-9,10-epoxide (BPDE), believed to be a major ultimate carcinogen of BaP, or with the noncarcinogenic reverse diol epoxide, racemic anti-BaP-9,10-diol-7,8-epoxide (rev-BPDE). Incubations were carried out for 12 or 24 h. We used high-performance liquid chromatography-electrospray ionization-tandem mass spectrometry-selected reaction monitoring at m/z 464 → m/z 317 to analyze the incubation mixtures for the mercapturic acid products that would result from glutathione conjugation. The standard mercapturic acids were synthesized by reaction of BPDE or rev-BPDE with N-acetylcysteine. We obtained convincing evidence in human hepatocytes for mercapturic acid formation from rev-BPDE in all 10 samples, in amounts up to 17 pmol/ml. However, we could detect mercapturic acids from BPDE in only 1 of 10 samples (0.05 pmol/ml). Taken together with our similar previous results of analyses of phenanthrene metabolites in human hepatocytes and human urine, the results of this study indicate that conjugation of BPDE with glutathione is a minor pathway in humans, indicating that glutathione S-transferase genotyping is not an effective method for assessing risk of PAH-induced cancer in humans, at least with respect to the diol epoxide pathway of PAH carcinogenesis.
Axonal Kv7.2/7.3 channels

Neurons target high densities of fast voltage-gated Na+ (Nav) and K+ (Kv) channels to their axonal initial segment (AISs) and nodes of Ranvier, subcellular domains governing the initiation and conduction of fast action potentials, respectively. Kv1 and Kv3 channels open rapidly to repolarize the action potential. In contrast, Kv7 channels, underlying the M-current (or IM), 1 are characterized by slow activation and de-activation kinetics leading to outward K+ flow lasting for many milliseconds after the action potential, providing an ionic mechanism for adjusting the action potential firing rates. A decade of work, including immunohistochemical, cell biological, and electrophysiological studies using somatic recordings, have provided evidence that the slow-gating Kv7 channels are also partners with Nav channels at the AISs and nodes. In vertebrates, the Kv7 channel subfamily consists of five subunits (Kv7.1 – 7.5). Neuronal Kv7.2 subunits are expressed either as homotetramers or as heterotetramers with Kv7.3 subunits. Kv7.2 and Kv7.3 share a conserved domain in the C-terminus for binding to Ankyrin G, thus increasing surface expression of Kv7.2 and Kv7.3 to the AIS and nodes of Ranvier. Despite a wealth of studies focusing on their modulation and pathogenic mutations, the precise gating kinetics of Kv7.2/7.3 channels in the central nervous system axonal domains where they are natively expressed remained unknown (but see). Here, we summarize key findings from a recent study, in which we directly measured for the first time the neocortical axonal M-current with patch-clamp recording. In myelinated axons, the known potassium currents activated in the same voltage range as IM are limited to AIS and juxtaparanodal Kv1 and nodal Kv3 subfamily channels, both of which can be selectively blocked by 4-aminopyridine (4-AP). Under these conditions, activation and deactivation voltage-clamp step protocols could be used across a large voltage range (–120 mV to +45 mV), allowing a complete examination of whole-axon currents evoked at the cut-end of myelinated axons. The outward K+ currents were activated with a time constant (τ) of ~40 ms (at –40 mV) and a Boltzmann fit to the normalized conductance revealed a halfmaximum activation at –34 mV together with a slope factor of 8.6 mV. Consistent with the presumed role of Kv7.2/7.3 channels, the outward currents were blocked with the Kv7 selective blocker XE-991 (ref.). Different stoichiometric combinations of Kv7.2 – 7.5 subunits have been reported to generate functionally diverse M-currents. The various Kv7 channels differ in sensitivity to block by extracellular tetraethyl ammonium chloride (TEA), allowing this compound to be used to determine the subunit composition of the axonal, 4-AP insensitive and XE-991 sensitive current. The fit with a singlepower Hill equation showed that the IC50 for TEA block was approximately 3 mM, indicating that the axonal channels were formed by heteromeric assembly of Kv7.2 and Kv7.3 subunits. This observation was in good agreement with the confocal Axonal Kv7.2/7.3 channels
Using Pivots to Speed-Up k-Medoids Clustering

Clustering is a key technique within the KDD process, with k-means, and the more general k-medoids, being well-known incremental partition-based clustering algorithms. A fundamental issue within this class of algorithms is to find an initial set of medians (or medoids) that improves the efficiency of the algorithms (e.g., accelerating its convergence to a solution), at the same time that it improves its effectiveness (e.g., finding more meaningful clusters). Thus, in this article we aim at providing a technique that, given a set of elements, quickly finds a very small number of elements as medoid candidates for this set, allowing to improve both the efficiency and effectiveness of existing clustering algorithms. We target the class of k-medoids algorithms in general, and propose a technique that selects a well-positioned subset of central elements to serve as the initial set of medoids for the clustering process. Our technique leads to a substantially smaller amount of distance calculations, thus improving the algorithm's efficiency when compared to existing methods, without sacrificing effectiveness. A salient feature of our proposed technique is that it is not a new k-medoid clustering algorithm per se, rather, it can be used in conjunction with any existing clustering algorithm that is based on the k-medoid paradigm. Experimental results, using both synthetic and real datasets, confirm the efficiency, effectiveness and scalability of the proposed technique.
IRS-2 G1057D polymorphism in Turkish patients with colorectal cancer

Introduction Gene polymorphisms have a broad range of analysis, but are of particular use in molecular medicine due to their potential in revealing the genetic tendency in diseases such as cancer, heart attack etc. These studies basically depend on mutations that can be detected by proper techniques. The genes coding the insulin receptor substrate (IRS) proteins are among the most widely analysed polymorphisms in various cancer types, in which a G1057D mutation is seen. Aim To determine the risk of colon cancer by analysing the IRS-2 gene polymorphism in Turkish patients. Material and methods A total of 161 newly diagnosed colorectal cancer patients were analysed and compared to 197 unrelated healthy controls. A polymerase chain reaction-based restriction fragment length polymorphism method was carried out. Results No differences were observed between the patient and control groups for both allele and genotype frequencies of the IRS-2 G1057D gene. Conclusions Our results demonstrated that IRS-2 G1057D polymorphism is not associated with colorectal cancer in the Turkish population. This research is a preliminary and original study in Turkish patients with colorectal cancer. It also provides population-level genetic data on IRS-2 in the Turkish population. Further studies should be performed on larger number of patients and controls for more reliable results about the genetic tendency in colorectal cancer in Turkey. The study is a collaborative work of different universities and scientists.
An evaluation of the response to Poole's algorithm education programme by aged care facility staff.

AIM To evaluate the response of residential aged care facility staff to the education programme--Poole's Algorithm: Nursing management of disturbed behaviour in aged care facilities. DESIGN Descriptive study, aged care setting. METHOD Following offers to all facilities in a large area health service, 104 senior staff took the opportunity to participate in train-the-trainer programs and then returned pre and post knowledge evaluation questionnaires for 190 of their own staff that they had trained, using the program, over a three month period. Thirty six of those trainers then shared their views of the usability and effectiveness of the program in focus group interviews. RESULTS The questionnaire analysis showed statistically significant improvements in overall knowledge for the trainers with 19.2% correct answers pre education and 91.3% correct afterwards, a difference of 71.1%. Overall, the staff trained by the trainers improved from 12.6% correct to 59.5% post education, a difference of 46.8%. In particular, the trainers' recognition of delirium as a cause for disturbed behaviour improved from 39.4% to 97.15% and the staff from 24.7% to 75.2%. CONCLUSIONS Concern was raised about the poor understanding of mental health problems such as personality and anxiety disorders. Analysis and coding of the focus group transcriptions showed improvements in attitudes and practice. Recommendations are made for the instigation of ongoing train-the-trainer sessions using this program and the replication of this study in the acute and community sectors.
Signaling trouble in robot-to-group interaction.emerging visitor dynamics with a museum guide robot.

Once a museum guide robot is deployed in the real world, it is faced with the difficulty to deal with user utterances within a noisy environment. We present explorative analysis of the ways in which visitors signal trouble on a multimodal level when they have difficulties in understanding the robot. Such moments of trouble are investigated in the context of robot-to-group situations. Analysis will give insights into the visitors conduct at moments of trouble in robot-to-single-user and robot-to-group interactions. In a limited data set, we found that members of a group show internal gaze coordination between each other when trouble occurs due to the robot's inadequate behavior. Implications will be drawn for further developing the interactional capabilities of an autonomous robot system to be attentive and responsive to the users' needs.
An E-TSPC Divide-by-2 Circuit With Forward Body Biasing in 0.25 $\mu$ m CMOS

A forward body biasing (FBB) technique is employed by an extended true-single-phase-clock (E-TSPC) divide-by-2 circuit in 0.25 mu m CMOS for an efficient on-chip control of power and speed. By applying the forward body bias voltage of 0.4 V, the maximum operating frequency is improved by 78% while the current dissipation is increased only by 21%. As a result, the divider figure-of-merit is improved by 46%. The phase noise however is not significantly affected by the forward body biasing. We believe that the FBB technique can be an efficient means for on-chip scaling of speed and power in E-TSPC RF frequency divider circuits.
Hospital cost differences and payment by results

Street and Maynard (2007) argue the case for refining the system of payment by results currently being introduced for English hospitals. On the basis of international experience, they recommend, among other things, moving away from setting prices equal to average cost towards setting them equal to best practice costs, adjusting them for quality and using them to signal what activities are desirable. They also discuss how to control total expenditure for primary care trusts (PCTs) under payment by results and question the merits of extending payment by results to mental health services, ambulances, community services, and long-term conditions, ‘where it is difficult to describe patient care requirements and cost variations may be high’ (p. 9).
RESULTS The cis Elements of the miR 398 Promoter Are Essential for Response to Copper Deficiency In Arabidopsis

Expression of miR398 is induced in response to copper deficiency and is involved in the degradation of mRNAs encoding copper/zinc superoxide dismutase in Arabidopsis thaliana. We found that SPL7 (for SQUAMOSA promoter binding protein– like7) is essential for this response of miR398. SPL7 is homologous to Copper response regulator1, the transcription factor that is required for switching between plastocyanin and cytochrome c6 in response to copper deficiency in Chlamydomonas reinhardtii. SPL7 bound directly to GTAC motifs in the miR398 promoter in vitro, and these motifs were essential and sufficient for the response to copper deficiency in vivo. SPL7 is also required for the expression of multiple microRNAs, miR397, miR408, and miR857, involved in copper homeostasis and of genes encoding several copper transporters and a copper chaperone, indicating its central role in response to copper deficiency. Consistent with this idea, the growth of spl7 plants was severely impaired under low-copper conditions.
Massive MIMO versus small-cell systems: Spectral and energy efficiency comparison

In this paper, we study the downlink performance of two important 5G network architectures, i.e. massive multiple-input multiple-output (M-MIMO) and small-cell densification. We propose a comparative modeling for the two systems, where the user and antenna/base station (BS) locations are distributed according to Poisson point processes (PPPs). We then study the SIR distribution and the outage rate of each network. By comparing these results, we observe that for user-average spectral efficiency, small-cell densification is favorable in crowded areas with moderate to high user density and M-MIMO with low user density. However, small-cell systems outperform M-MIMO in all cases when the performance metric is the energy efficiency. The results of this paper are useful for the optimal design of practical 5G networks.
Drug Resistance and Virological Failure among HIV-Infected Patients after a Decade of Antiretroviral Treatment Expansion in Eight Provinces of China

Background China’s National Free Antiretroviral Treatment Program (NFATP) has substantially increased the survival rate since 2002. However, the emergence of HIV drug resistance (HIVDR) limits the durability and effectiveness of antiretroviral treatment (ART) in at risk patients. Method A cross-sectional survey was conducted among patients having received a median of 13.9 months of ART in eight provinces in China. Demographic and clinical information was collected, and venous blood was sampled for CD4 cell counts, measurement of the HIV viral load (VL), and HIV drug resistance (HIVDR) genotyping. Possible risk factors for HIVDR were analyzed by the logistic regression model. Results The study included 765 patients. Among them, 65 patients (8.5%) had virological failure (VLF) defined as ≥1,000 copies/ml. Among the individuals with VLF, 64 were successful genotyped, and of these, 33 had one or more HIVDR mutations. The prevalence of HIVDR mutations among patients receiving first-line ART was 4.3% (33/765). All of the patients with HIVDR mutations were resistant to non-nucleoside transcriptase inhibitors, 81.8% were resistant to nucleoside reverse transcriptase inhibitors, and only 3% had mutations that caused resistance to protease inhibitors. Having lower ratios of drug intake in the past month and dwelling in two southwestern provinces were factors independently associated with the emergence of HIVDR. Conclusion Most patients receiving first-line ART treatment achieved sound virological and immunological outcomes. However, poor adherence is still a key problem, which has led to the high rate of HIVDR. It was notable that the proportion of drug resistance widely varied among the provinces. More studies are needed to focus on adherence.
The chemokine interleukin‐8 acutely reduces Ca2+ currents in identified cholinergic septal neurons expressing CXCR1 and CXCR2 receptor mRNAs

The chemokine IL‐8 is known to be synthesized by glial cells in the brain. It has traditionally been shown to have an important role in neuroinflammation but recent evidence indicates that it may also be involved in rapid signaling in neurons. We investigated how IL‐8 participates in rapid neuronal signaling by using a combination of whole‐cell recording and single‐cell RT‐PCR on dissociated rat septal neurons. We show that IL‐8 can acutely reduce Ca2+ currents in septal neurons, an effect that was concentration‐dependent, involved the closure of L‐ and N‐type Ca2+ channels, and the activation of Giα1 and/or Giα2 subtype(s) of G‐proteins. Analysis of the mRNAs from the recorded neurons revealed that the latter were all cholinergic in nature. Moreover, we found that all cholinergic neurons that responded to IL‐8, expressed mRNAs for either one or both IL‐8 receptors CXCR1 and CXCR2. This is the first report of a chemokine that modulates ion channels in neurons via G‐proteins, and the first demonstration that mRNAs for CXCR1 are expressed in the brain. Our results suggest that IL‐8 release by glial cells in vivo may activate CXCR1 and CXCR2 receptors on cholinergic septal neurons and acutely modulate their excitability by closing calcium channels.