Miracle-dz/UniFAR-FTUs huggingface dataset:
Break-Induced Replication and Genome Stability

Genetic instabilities, including mutations and chromosomal rearrangements, lead to cancer and other diseases in humans and play an important role in evolution. A frequent cause of genetic instabilities is double-strand DNA breaks (DSBs), which may arise from a wide range of exogeneous and endogeneous cellular factors. Although the repair of DSBs is required, some repair pathways are dangerous because they may destabilize the genome. One such pathway, break-induced replication (BIR), is the mechanism for repairing DSBs that possesses only one repairable end. This situation commonly arises as a result of eroded telomeres or collapsed replication forks. Although BIR plays a positive role in repairing DSBs, it can alternatively be a dangerous source of several types of genetic instabilities, including loss of heterozygosity, telomere maintenance in the absence of telomerase, and non-reciprocal translocations. Also, mutation rates in BIR are about 1000 times higher as compared to normal DNA replication. In addition, micro-homology-mediated BIR (MMBIR), which is a mechanism related to BIR, can generate copy-number variations (CNVs) as well as various complex chromosomal rearrangements. Overall, activation of BIR may contribute to genomic destabilization resulting in substantial biological consequences including those affecting human health.
Endogenous Interferon-β-Inducible Gene Expression and Interferon-β-Treatment Are Associated with Reduced T Cell Responses to Myelin Basic Protein in Multiple Sclerosis

Autoreactive CD4+ T-cells are considered to play a major role in the pathogenesis of multiple sclerosis. In experimental autoimmune encephalomyelitis, an animal model of multiple sclerosis, exogenous and endogenous type I interferons restrict disease severity. Recombinant interferon-β is used for treatment of multiple sclerosis, and some untreated multiple sclerosis patients have increased expression levels of type I interferon-inducible genes in immune cells. The role of endogenous type I interferons in multiple sclerosis is controversial: some studies found an association of high expression levels of interferon-β-inducible genes with an increased expression of interleukin-10 and a milder disease course in untreated multiple sclerosis patients, whereas other studies reported an association with a poor response to treatment with interferon-β. In the present study, we found that untreated multiple sclerosis patients with an increased expression of interferon-β-inducible genes in peripheral blood mononuclear cells and interferon-β-treated multiple sclerosis patients had decreased CD4+ T-cell reactivity to the autoantigen myelin basic protein ex vivo. Interferon-β-treated multiple sclerosis patients had increased IL10 and IL27 gene expression levels in monocytes in vivo. In vitro, neutralization of interleukin-10 and monocyte depletion increased CD4+ T-cell reactivity to myelin basic protein while interleukin-10, in the presence or absence of monocytes, inhibited CD4+ T-cell reactivity to myelin basic protein. Our findings suggest that spontaneous expression of interferon-β-inducible genes in peripheral blood mononuclear cells from untreated multiple sclerosis patients and treatment with interferon-β are associated with reduced myelin basic protein-induced T-cell responses. Reduced myelin basic protein-induced CD4+ T-cell autoreactivity in interferon-β-treated multiple sclerosis patients may be mediated by monocyte-derived interleukin-10.
A modeling technique for CMOS gates

In this paper, a modeling technique for CMOS gates, based on the reduction of each gate to an equivalent inverter, is presented. The proposed method can be incorporated in existing timing simulators in order to improve their accuracy. The conducting and parasitic behavior of parallel and serially connected transistors is accurately analyzed and an equivalent transistor is extracted for each case, taking into account the actual operating conditions of each device in the structure. The proposed model incorporates short-channel effects, the influence of body effect and is developed for nonzero transition time inputs. The exact time point when the gate starts conducting is efficiently calculated improving significantly the accuracy of the method. A mapping algorithm for reducing every possible input pattern of a gate to an equivalent signal is introduced and the "weight" of each transistor position in the gate structure is extracted. Complex gates are treated by first mapping every possible structure to a NAND/NOR gate and then by collapsing this gate to an equivalent inverter. Results are validated by comparisons to SPICE and ILLIADS2 for three submicron technologies.
Representing Clarification Dialogues in a Speaker/Hearer Model

This paper shows an extended Discourse Representation Theory (DRT) model which represents clarification dialogue and clarification dialogue acts and relates them to agents’ intentions. Agents’ intentions are linked to the dialogue acts associated with their utterances. The effect dialogue acts have on the speaker and the hearer is translated into an extended computational DRT model and linked to agents’ beliefs. These extensions to DRT allow the demonstration of problematic dialogues that require clarification, a topic neglected in DRT.
A Comparison of Information Concerning the Regression Parameter in The Accelerated Failure Time Model under Current Duration and Length Biased Sampling: Does it Pay to be Patient?

Longitudinal observations are sometimes costly or not available. Cross sectional sampling can be an alternative. Observations are drawn then at a specific point in time from a population of durations whose distributions satisfy a {\em core model}. Subsequently, one has a choice. One may process the data immediately, obtaining so called current duration data. Or one waits until the sampled durations are known completely obtaining the full durations via length biased sampling. We compare the Fisher information for the Euclidean parameter corresponding to an Accelerated Failure Time core model when the observations are obtained by either current duration or length biased sampling.
Comparative subthreshold analysis for channel thickness variation on sub-100 nm Double Gate with Single-Gate HEMT

In recent years, double gate high electron mobility transistor (DGHEMT) have been introduced to provide better immunity to short channel effects which are inescapable with downscaling of the single gate devices due to fundamental limit on gate-to-channel thickness. Furthermore, in sub 100 nm regime, for lower device aspect ratio, channel thickness also becomes an important parameter affecting the device performance due to oncoming of short channel effects. In this paper, the effect of channel thickness in sub 100 nm DGHEMT and SGHEMT devices under OFF conditions has been studied using ATLAS device simulator. The analysis provides a valuable insight into the subthreshold behavior and presents a comparative picture of the two types of devices.
Improving the Performance of Topic Tracking System by Ensemble

The aim of topic tracking is to monitor the stream of news stories to find additional stories on a topic that was identified by several sample stories. In this paper, we adopt majority voting to ensemble several topic tracking systems. The experiment results on TDT3 corpus show that our ensemble topic tracking system performs better than each individual topic tracking system, and that the performance of topic tracking system could be improved by ensemble technology.
Collision prediction system for external airbag using an interacting multiple model estimation with multirate Kalman filter

External airbag installed in vehicle can protect pedestrians and reduce injuries in the event of a crash. In this paper, a collision prediction system for external airbag using an interacting multiple model is proposed to detect a collision and inflates quickly enough to cushion the impact. The system includes two different models, constant velocity and constant acceleration, in order to estimate a distance between ego vehicle and front object. The integration of two models gives optimized object state estimation with low cost laser scanner and reduces the root mean squares error.
Pyrosequencing Analysis of APC Methylation Level in Human Prostate Tissues: A Molecular Marker for Prostate Cancer

Purpose Epigenetic alterations such as abnormal DNA methylation are associated with many human cancers. Differences in methylation patterns between neoplastic and normal cells can be used to detect cancer. The aim of the present study was to evaluate the effectiveness of detecting Adenomatous polyposis coli (APC) hypermethylation by quantitative pyrosequencing for discriminating between normal and prostate cancer (PCa) cells and for predicting tumor behaviors. Materials and Methods A total of 218 human prostate tissues obtained from our institute were assessed: 106 specimens of benign prostatic hyperplasia (BPH) and 112 specimens of PCa. The methylation status of APC was analyzed by quantitative pyrosequencing. The association between the APC methylation level and clinicopathological parameters was explored. Results The level of APC methylation was significantly higher in PCa specimens than in BPH specimens (33.3%±20.7% vs. 1.3%±1.8%, p<0.001). The sensitivity and specificity of APC methylation status in discriminating between PCa and BPH reached 89.3% and 98.1%, respectively. Similar results were obtained after stratification by stage, Gleason score, and prostate-specific antigen level. The APC methylation level correlated positively with Gleason score (p trend=0.016). There was no association between the APC methylation level and the PSA level or staging. Conclusions Our results demonstrate that APC methylation is associated with PCa and its aggressive tumor features.
Flavor Perception in Human Infants: Development and Functional Significance

Background: Foods people consume impact on their health in many ways. In particular, excess intake of salty, sweet and fatty foods and inadequate intake of fruits and vegetables have been related to many diseases including diabetes, hypertension, cardiovascular disease and some cancers. The flavor of a food determines its acceptability and modulates intake. It is thus critical to understand the factors that influence flavor preferences in humans. Aim: To outline several of the important factors that shape flavor preferences in humans. Methods: We review a series of studies, mainly from our laboratories, on the important role of early experiences with flavors on subsequent flavor preference and food intake. Results and Conclusions: Some taste preferences and aversions (e.g. liking for sweet, salty and umami; disliking for bitter) are innately organized, although early experiences can modify their expression. In utero events may impact on later taste and flavor preferences and modulate intake of nutrients. Both before and after birth, humans are exposed to a bewildering variety of flavors that influence subsequent liking and choice. Fetuses are exposed to flavors in amniotic fluid modulating preferences later in life and flavor learning continues after birth. Experience with flavors that are bitter, sour or have umami characteristics, as well as volatile flavors such as carrot and garlic, occurs through flavorings in breast milk, infant formula and early foods. These early experiences mold long-term food and flavor preferences which can impact upon later health.
Algorithmic analysis on a class of Boolean equations

Efficient procedures for satisfiability verification are foundations of numerical simulation and algorithmic analysis of NP-complete problems. Previous researches in this direction include well-known Davis-Putnam-Logemann-Loveland (DPLL) and leaf removal procedures. In this paper, we propose a new procedure called Leaf-removal Gaussian Elimination procedure (LGC) to verify the satisfiability of a class of NP-complete problems. This novel procedure is much simpler and faster than the original DPLL procedure. We also provide estimation of the phase transition point based on this procedure. Numerical experiments are conducted for Boolean equations systems with different parameters and the results verify the validity and efficiency of our novel techniques.
Nominalization in Titles : A Way to Extract Document Details

Titles of documents are the first information a reader gets from their content. In our efforts to obtain more information about document content, we came across nominalizations in titles that provides a means to identify specific content level as suggested by the verb they are derived from. The way these nominals are identified and extracted is discussed as well as the method applied to recover their implicit information. Related to this phenomenon, the use of present participle is also illustrated regarding similar verbs, and also extracted. Several patterns emerged revealing content in both cases. The information gathered is expressed in a structured representation complementing additional details assessed by different means, and later used for information retrieval purpose.
In-car interaction using search-based user interfaces

Increasing functionality, growing media volumes and dynamic data in today's in-vehicle information systems bear new challenges for user interaction design. Traditional hierarchical and menu-based interaction can only provide limited support while new search-based approaches are promising. In this work we assess different search techniques and search-based user interfaces. In particular we compare free search across all data items with categorized search. Our experiments with functional prototypes show that free search is more efficient and easier to use than searching within categories. Tests in a driving simulator show promising results regarding safety and workload. Means for alphanumeric input appear to be essential for an efficient and safe search interaction while driving.
Analisis Sistem Informasi Aplikasi Online Kartu Kredit Menggunakan Metode SERVQUAL

Kemudahan, efisiensi, ketepatan, kecepatan, simple serta flexibilitas menjadi pertimbangan para pelaku kegiatan untuk menggunakan kartu kredit diera globalisasi saat ini. Ada beberapa cara yang bisa dilakukan untuk pengajuan kartu kredit seperti melalui direct selling, telemarketing dan aplikasi online. Dari ketiga cara tersebut aplikasi online menjadi salah satu cara yang paling mudah dalam pengajuan aplikasi kartu kredit Kunci permasalahan pada penelitian ini yakni terkait dengan kualitas layanan yang diberikan apakah cukup memberikan pemahaman terhadap calon customer sehingga terjadi peningkatan dalam kartu kredit di ANZ Bank serta layanan seperti apa yang diharapkan oleh customer. Metode penelitian yang digunakan adalah metode deskriptif analis dengan pengumpulan data dilakukan dengan menyebarkan kuesioner kepada 150 responden, metode pengambilan sampel menggunakan metode servqual, skala likert, SEM amos 18. Berdasarkan analisis yang telah dilakukan didapatkan bahwa kualitas layanan Aplikasi Online seperti tampilan, pelayanan marketing, tarif, teknologi yang digunakan pada aplikasi online sangat mempengaruhi kepuasan customer yang berdampak pada peningkatan customer kartu kredit ANZ.
The cystic fibrosis transmembrane conductance regulator (CFTR) inhibits ENaC through an increase in the intracellular Cl− concentration

Activation of the CFTR Cl− channel inhibits epithelial Na+ channels (ENaC), according to studies on epithelial cells and overexpressing recombinant cells. Here we demonstrate that ENaC is inhibited during stimulation of the cystic fibrosis transmembrance conductance regulator (CFTR) in Xenopus oocytes, independent of the experimental set‐up and the magnitude of the whole‐cell current. Inhibition of ENaC is augmented at higher CFTR Cl− currents. Similar to CFTR, ClC‐0 Cl− currents also inhibit ENaC, as well as high extracellular Na+ and Cl−in partially permeabilized oocytes. Thus, inhibition of ENaC is not specific to CFTR and seems to be mediated by Cl−.
Attitudes to science : part of the puzzle to improve educational achievement?

This paper examines the relationship between attitudes to learning science and science achievement in South Africa. TIMSS 2011 science achievement data and science attitudinal indices of enjoyment, valuing science and self-confidence in ability to learn science, are used to examine this. All three indices were found to contribute significantly to the science performance of Grade 9 learners. The findings highlight the need to focus on the non-cognitive aspects in educational interventions in order to improve science achievement in the country.
Mobile Services for Group Decision Support

In this paper we study a new role for smart mobile devices: their potential assistance in group-based decision making. Assuming that smart devices implement wireless short range scanning technology, they have the capacity to scan other devices and by doing so, group members can exchange information and decision preferences with other group members. We introduce four mobile services that exploit this technology for the purpose of group decision making: information gathering, information matching, preference gathering, and preference matching. The paper continues by outlining to what extent these services will have value for specific types of group tasks. We conclude that information gathering and matching are appropriate for simple tasks and problem tasks, and preference gathering and matching are appropriate for judgement tasks and “fuzzy” tasks.
microRNAs in axon guidance

Brain wiring is a highly intricate process in which trillions of neuronal connections are established. Its initial phase is particularly crucial in establishing the general framework of neuronal circuits. During this early step, differentiating neurons extend axons, which reach their target by navigating through a complex environment with extreme precision. Research in the past 20 years has unraveled a vast and complex array of chemotropic cues that guide the leading tip of axons, the growth cone, throughout its journey. Tight regulation of these cues, and of their receptors and signaling pathways, is necessary for the high degree of accuracy required during circuit formation. However, little is known about the nature of regulatory molecules or mechanisms fine-tuning axonal cue response. Here we review recent, and somewhat fragmented, research on the possibility that microRNAs (miRNAs) could be key fine-tuning regulatory molecules in axon guidance. miRNAs appear to shape long-range axon guidance, fasciculation and targeting. We also present several lines of evidence suggesting that miRNAs could have a compartmentalized and differential action at the cell soma, and within axons and growth cones.
Revisiting the stability of computing the roots of a quadratic polynomial

We show in this paper that the roots x1 and x2 of a scalar quadratic polynomial ax 2 +bx+c = 0 with real or complex coecients a, b c can be computed in a elementwise mixed stable manner, measured in a relative sense. We also show that this is a stronger property than norm-wise backward stability, but weaker than element-wise backward stability. We nally show that there does not exist any method that can compute the roots in an element-wise backward stable sense, which is also illustrated by some numerical experiments.
USING DOUBLE KEYS HASHING FOR EFFICIENT STRING SEARCHING PROBLEM

String matching also referred to as string searching algorithm, is a class of string algorithms that try to find a place where one or several strings (patterns) are found within a larger string or text. Hashing is any welldefined procedure or mathematical function that converts a large, possibly variable-sized amount of data into a small sized-datum, usually a single integer that may serve as an index to an array. It’s also mathematical process that converts a message (document) into a unique "message digest" that represents the original message. A hash function will not produce the same message digest from two different inputs.
Iterative-Mapping PHD filter for extended targets tracking

A novel Iterative-Mapping algorithm is proposed to alleviate the computation intractable measurement partition problem in a Probability Hypothesis Density tracking filter for extended targets. The iterative mapping procedure is based on the assumption that the target centroids can be estimated as the conditional expectation of measurements. Using sequential Monte Carlo method, this algorithm iteratively maps the target states and measurement sources each other. It can be applied to track multiple extended targets. Simulation results demonstrate superior performance of this proposed method over traditional extended target PHD filter with partition.
Perfect Packings in Quasirandom Hypergraphs II

For each of the notions of hypergraph quasirandomness that have been studied, we identify a large class of hypergraphs F so that every quasirandom hypergraph H admits a perfect F-packing. An informal statement of a special case of our general result for 3-uniform hypergraphs is as follows. Fix an integer r ⩾ 4 and 0 < p < 1. Suppose that H is an n-vertex triple system with r|n and the following two properties: • for every graph G with V(G) = V(H), at least p proportion of the triangles in G are also edges of H, • for every vertex x of H, the link graph of x is a quasirandom graph with density at least p. Then H has a perfect Kr (3)-packing. Moreover, we show that neither of the hypotheses above can be weakened, so in this sense our result is tight. A similar conclusion for this special case can be proved by Keevash's Hypergraph Blow-up Lemma, with a slightly stronger hypothesis on H.
A Data Science Model for Big Data Analytics of Frequent Patterns

Frequent pattern mining is an important data mining task. Since its introduction, it has drawn attention from many researchers. Consequently, many frequent pattern mining algorithms have been proposed, which include level-wise Apriori-based algorithms, tree-based algorithms, and hyperlinked array structure based algorithms. While these algorithms are popular and benefit from a few advantages, they also suffer from some disadvantages. In the current era of big data, a wide variety of high volumes of valuable data of different veracities can be easily collected and generated at a high velocity. These big data lead to additional challenges for frequent pattern mining. In this paper, we present a data science model for big data analytics of frequent patterns with MapReduce. We evaluated our model by using social networks, which are good examples of big data. Evaluation results show the efficiency and practicality of our data science model in mining and analyzing big data for the discovery of interesting frequent patterns from various real-life applications including social network analysis.