Miracle-dz/UniFAR-FTUs huggingface dataset:
Modulation of mutagenesis in eukaryotes by DNA replication fork dynamics and quality of nucleotide pools

The rate of mutations in eukaryotes depends on a plethora of factors and is not immediately derived from the fidelity of DNA polymerases (Pols). Replication of chromosomes containing the anti‐parallel strands of duplex DNA occurs through the copying of leading and lagging strand templates by a trio of Pols α, δ and ϵ, with the assistance of Pol ζ and Y‐family Pols at difficult DNA template structures or sites of DNA damage. The parameters of the synthesis at a given location are dictated by the quality and quantity of nucleotides in the pools, replication fork architecture, transcription status, regulation of Pol switches, and structure of chromatin. The result of these transactions is a subject of survey and editing by DNA repair. Environ. Mol. Mutagen. , 2012. © 2012 Wiley Periodicals, Inc.
Type I Collagen α1 Sp1 Polymorphism and the Risk of Cruciate Ligament Ruptures or Shoulder Dislocations

Background Cruciate ligament ruptures and shoulder dislocations are often caused by trauma, but predisposing intrinsic factors might also influence the risk. These injuries are more common in those with a previously injured sibling, an observation that might indicate a genetic predisposition. It is well known that polymorphisms in the collagen I gene are associated not only with osteoporosis and osteoporotic fracture risk, but also with osteoarthritis. Hypothesis Because collagen I is abundant in ligaments and tendons, the authors hypothesized that collagen I α1 Sp1 polymorphism also was related to the occurrence of cruciate ligament ruptures and shoulder dislocations. Study Design Case-control study; Level of evidence, 3. Methods A total of 358 patients and 325 randomly selected population-based female controls were included in the study. Of the cases, 233 had a cruciate ligament rupture and 126 had had a shoulder dislocation. Age-adjusted odds ratios (ORs) with 95% confidence intervals (CIs) estimated by unconditional logistic regression were used as measures of association. Results Compared with the homozygous SS category, the heterozygous participants displayed a similar risk (OR, 1.06; 95% CI, 0.76–1.49), whereas the ss genotype was underrepresented in the injured population compared with the controls (OR, 0.15; 95% CI, 0.03–0.68). This latter estimate was similar for both cruciate ligament ruptures and shoulder dislocations, and was furthermore not modified by general joint laxity. Conclusion The authors found a substantially decreased risk of these injuries associated with collagen type I α1 Sp1 polymorphism. The study might encourage other investigators to consider further research in the area of genes and soft tissue injuries.
An algorithm for modularity analysis of directed and weighted biological networks based on edge-betweenness centrality

MOTIVATION Modularity analysis is a powerful tool for studying the design of biological networks, offering potential clues for relating the biochemical function(s) of a network with the 'wiring' of its components. Relatively little work has been done to examine whether the modularity of a network depends on the physiological perturbations that influence its biochemical state. Here, we present a novel modularity analysis algorithm based on edge-betweenness centrality, which facilitates the use of directional information and measurable biochemical data.
NBTI degradation and its impact for analog circuit reliability

A methodology to quantify the degradation at circuit level due to negative bias temperature instability (NBTI) has been proposed in this work. Using this approach, a variety of analog/mixed-signal circuits are simulated, and their degradation is analyzed. It has been shown that the degradation in circuit performance is mainly dependent on the circuit configuration and its application rather than the absolute value of degradation at the device level. In circuits such as digital-to-analog converters, NBTI can pose a serious reliability concern, as even a small variation in bias currents can cause significant gain errors.
On the Representation and Combination of Evidence in Instance-Based Learning

In instance-based learning the classification of a novel instance relies upon experience given in the form of similar instances whose labels are already known. Each of these instances can hence be seen as an individual piece of evidence. In this paper, we elaborate on issues concerning the representation and combination of such pieces of evidence. Particularly, we argue that the information provided by similar instances must not be considered as independent. We propose a new inference principle that derives an evidence function specifying the available evidence in favor of each potential label. This principle, which is built upon a probabilistic (random field) model, takes interdependencies between stored instances into account and suggests a generalization of weighted nearest neighbor estimation.
Primary Carcinoid Tumor of the Skull Base: Case Report and Review of the Literature

We present an unusual case of primary intracranial carcinoid tumor of the skull base centered at the level of the foramen jugulare, which was proven with surgical biopsy and later with Somatostatin receptor nuclear medicine scan. We present the salient magnetic resonance imaging features of this rare tumor, describe their characteristic nuclear medicine findings, and briefly review the literature.
Autonomous vehicle detection system using visible and infrared camera

This paper presents a vision-based vehicle detection system in the infrared (IR) and vision system using an effective feature extraction and algorithm. This system follows two steps: Hypothesis Generation (HG) method and Hypothesis Verification (HV) method. In HG method, vertical and horizontal edges are used. To extract these edges effectively a neighborhood gradient prediction(NGP) edge detection is used. With these extracted edges, the vehicle location candidates are generated. This step reduces the computational time in comparison with exhaustive search method. In HV method, the effective feature extraction such as HOG and GABOR feature are used. A support vector machine (SVM) for classification is also used. This step verifies if the vehicle candidates are vehicle or not. The test image is obtained by a monocular IR camera and visible camera attached on moving vehicle. In vision image, NGP method is compared with SOBEL method. In IR image, HOG feature is compared with GABOR feature.
Continuously motor-synchronized ride-through capability for matrix-converter adjustable-speed drives

The ride-through capability of adjustable-speed drives has become an important issue due to its direct impact on production and revenue losses. Moreover, different industrial surveys have shown that voltage sags are the main cause of converter tripping. Disturbances such as swells, distortion, and impulses were found far less common and did not cause any tripping nor production losses. Matrix-converter (MC) drives are also prone to voltage sags, furthermore the lack of the DC-link capacitor renders them somehow more vulnerable. This paper presents a ride-through strategy for MC adjustable-speed drives. The strategy is based on the reduced speed/load approach for conventional drives and is capable of enforcing constant volts/hertz operation regardless of the supply voltage conditions by first regulating the modulation index of the matrix converter, which counteracts the supply voltage drop, and second by reducing the speed reference if required. This reduction seeks to maintain the maximum torque capability of the drive and not to reduce the motor load as in conventional drives. Hence, the proposed strategy is suitable for both variable and constant torque loads. Moreover, the converter never loses synchronization with the motor, so it is capable of immediate acceleration to its former speed after the disturbance disappears. The proposed strategy was experimentally verified under typical industry disturbances using a TMS320C32 DSP based system. Particularly, three-phase and single-phase sags varying from 10% to 60% were tested. Results obtained showed the effectiveness of the proposed strategy for MC adjustable-speed drives.
On the Finite Element Method with Riesz Bases and Its Applications to Some Partial Differential Equations

In this paper, we will find the numerical solution of partial differential equations by using the finite element method with Riesz bases that are elevated from ortho normal bases. Especially for the two-dimensional cases, we also propose another way to solve a matrix-valued equation (Lyapunov equation). Moreover, we give the precise inverse formula for symmetric block tridiagonal Toeplitz matrices. To conclude, we present some numerical results that show the usefulness of the elevated bases.
YCZ-18 Is a New Brassinosteroid Biosynthesis Inhibitor

Plant hormone brassinosteroids (BRs) are a group of polyhydroxylated steroids that play critical roles in regulating broad aspects of plant growth and development. The structural diversity of BRs is generated by the action of several groups of P450s. Brassinazole is a specific inhibitor of C-22 hydroxylase (CYP90B1) in BR biosynthesis, and the application use of brassinazole has emerged as an effective way of complementing BR-deficient mutants to elucidate the functions of BRs. In this article, we report a new triazole-type BR biosynthesis inhibitor, YCZ-18. Quantitative analysis the endogenous levels of BRs in Arabidopsis indicated that YCZ-18 significantly decreased the BR contents in plant tissues. Assessment of the binding affinity of YCZ-18to purified recombinant CYP90D1 indicated that YCZ-18 induced a typical type II binding spectrum with a Kd value of approximately 0.79 μM. Analysis of the mechanisms underlying the dwarf phenotype associated with YCZ-18 treatment of Arabidopsis indicated that the chemically induced dwarf phenotype was caused by a failure of cell elongation. Moreover, dissecting the effect of YCZ-18 on the induction or down regulation of genes responsive to BRs indicated that YCZ-18 regulated the expression of genes responsible for BRs deficiency in Arabidopsis. These findings indicate that YCZ-18 is a potent BR biosynthesis inhibitor and has a new target site, C23-hydroxylation in BR biosynthesis. Application of YCZ-18 will be a good starting point for further elucidation of the detailed mechanism of BR biosynthesis and its regulation.
Efficient ID-based Broadcast Threshold Decryption in Ad Hoc Network

In this paper, we construct an efficient ID-based broadcast threshold decryption scheme in mobile ad hoc network. Our scheme allows a sending node to efficiently broadcast an encrypted message to many dynamic groups in such a way that only the groups meeting the minimal size requirement (number of nodes that is within the range of the group) can read the message. Moreover, we analyze the security and discuss how to improve the security of the scheme. Finally, we evaluate our scheme's performance
Framework for Modeling Partial Conceptual Autonomy of Adaptive and Communicating Agents

We develop a framework for discussing the degree of conceptual autonomy of natural and artificial agents. We claim that aspects related to learning and communication necessitate adaptive agents that are partially autonomous. We demonstrate how partial conceptual autonomy can be obtained through a self-organization process. The input for the agents consists of perceptions of the environment, expressions communicated by other agents as well as the recognized identities of other agents.
‘It's vocabulary’/‘it's gender’: learner awareness and incidental learning

Research has shown that second language (L2) learners that become aware of linguistic features during grammar-based tasks are better able to process these features on a posttest compared to learners that do not focus on these features. However, much L2 input does not come in the form of grammar-based tasks. This study investigates whether learners who become aware of French grammatical gender during a meaning-based task are better able to process these forms than learners whose experience with the same task does not lead to awareness of the feature. Thirty-six Anglophones with low-level French were exposed to reliable noun-ending clues to grammatical gender whilst completing a crossword task. A think-aloud protocol and two probe questions measured awareness. A pre- to posttest design measured accuracy with French nouns ending in eau (e.g. le cadeau). The results revealed no advantage for learners who became aware of the noun-ending clues during exposure: all learners improved in their ability to judge the gender of words encountered during the task (item learning) but none were able to extend this new knowledge to novel items (system learning). The interpretation of the findings considers the choice of linguistic feature, the role of awareness in item learning and the learning conditions that might be necessary for awareness of form to occur during meaning-based exposure.
GSM BASED REMOTE PATIENT MONITORING SYSTEM

This paper presents the methodology for monitoring patients remotely using GSM network & Very large scale integration (VLSI) technique. Patient monitoring systems consist of equipment, devices and supplies that measure, display and record human physiological characteristics, including blood pressure, body temperature, heart activity, various bodily substances (e.g. cholesterol, glucose, etc.), pulse rate, respiration rate and other health-related criteria. A patient monitoring system for providing continuous monitoring of a patient includes a data acquisition and processing module receiving physiological data from the patient This unit may be inserted in a bedside display unit to display the physiological condition of the patient. The major reason for the development of the said system is to reduce the product size , power consumption & cost of the system. The remote monitoring & control of the physiological parameters can be obtained by interfacing GSM mobile unit with the patient monitoring system. The system architecture is described. Patient monitoring systems measure physiological characteristics either continuously or at regular intervals over time. The embedded system is developed using iibero IDE. An application of this method in Biomedical includes better accuracy, design security, productivity, speed and flexibility.
Blinded by Emotion: Target Misses Follow Attention Capture by Arousing Distractors in RSVP

Participants are usually able to search rapid serial visual presentation (RSVP) streams and report a single target, given that RSVP distractors do not typically deplete attention required for target identification. Here, participants performed single target search, but the target was preceded by a to-be-ignored distractor varying in valence and arousal. When the critical distractor was a sexual word, lower target accuracy was observed, particularly at short distractor-target stimulus onset asynchronies, even when participants were shown the critical distractors beforehand and told to ignore them. No reduction in target accuracy was evidenced when the critical distractor was negative, positive, threatening, or emotionally neutral. Target accuracy was predicted by participants' arousal ratings to the critical distractor words and by their memory for them, but not by their valence ratings. Memory for critical distractors mediated the relationship between arousal and target accuracy. The results provide evidence that arousing sexual words involuntarily capture attention and enter awareness at the expense of goal-driven targets, at least in the context of laboratory experiments performed by young university participants for whom sexual material might have high impact and relevance.
3D MIMO-OFDM Channel Estimation

In this paper bandwidth efficient pilot design for a MIMO-OFDM downlink is addressed. By exploiting the spatial correlation of signals originating from neighboring transmit antennas, the principle of pilot aided channel estimation (PACE) by two-dimensional (2D) interpolation in time and frequency is extended to the spatial domain; giving rise to three-dimensional (3D) PACE. By invoking the multi-dimensional sampling theorem conditions for regular pilot patterns to attain minimum overhead are derived. Provided sufficient spatial correlation 3D-PACE reduces pilot overhead by 50% compared to conventional 2D-PACE. Unfortunately, spatial correlation may not be universally available: while for outdoor macro-cells, where transmit antennas are typically mounted above rooftop, the assumption of spatially correlated channels is justified, in indoor deployments where spatial correlation tends to be low, spatial interpolation may not be feasible. On the other hand, in indoor environments cell sizes together with mobile velocities are substantially smaller, giving rise to lower Doppler and channel delay spreads. We show that a sophisticated pilot design is able to retain the low pilot overhead of 3D-PACE by exploiting these heterogeneous correlation properties, in the way that high spatial correlation compensates for low correlation in time and/or frequency, and vice versa.
Real Time Congestion Management in Power Systems Considering Quasi-Dynamic Thermal Rating and Congestion Clearing Time

In a smart power system, smart measurement infrastructure brings so many advantages in monitoring and control of the power system. This paper proposes an optimal real time transmission congestion management algorithm in a competitive electricity market based on real time measurements in a smart power system. Instead of static and fix thermal rates, quasi-dynamic thermal rates of transmission lines are calculated and used to solve the real time congestion management optimization problem. The optimization problem includes an optimal generation rescheduling and load shedding scheme to minimize the congestion management costs in a specific time interval. This time interval is introduced and defined as congestion clearing time in this paper. Furthermore, in the proposed algorithm, the congestion clearing time is divided into few subsequent subintervals aimed at considering loads and power system variations during rescheduling procedure. The proposed method could be used by system operators (SOs) to adapt the real time congestion management procedure with regard to the power system loads and generations, or system configuration variations during rescheduling and load shedding process. Numerical results obtained from running the algorithm on the modified IEEE 30-bus test system and the transmission network of Esfahan Regional Power Network (ERPN), as a real size power system, demonstrate convincingly the ability of the proposed algorithm in the congestion management cost and load shedding reduction, while it increases the power system security margin in intensive congestion cases significantly.
A Polymorphism (rs1801018, Thr7Thr) of BCL2 is Associated with Papillary Thyroid Cancer in Korean Population

Objectives Among the apoptosis signals, B-cell CLL/lymphoma 2 (BCL2) is a well-known regulator of apoptosis with anti-apoptotic properties. We investigated here whether single nucleotide polymorphisms (SNPs) of the BCL2 were associated with host susceptibility of papillary thyroid cancer (PTC) occurrence and clinicopathologic parameters. Methods Ninety-two PTC patients and 222 control subjects were recruited. One promoter SNP (rs2279115, -938A/C) and one synonymous SNP (rs1801018, Thr7Thr) in the BCL2 gene were selected and genotyped using direct sequencing. Multiple logistic regression models were performed to evaluate odds ratios, 95% confidence intervals, and P-values. Results rs1801018 of the BCL2 gene was not associated with the development of PTC. In the clinicopathologic features, rs1801018 SNP was associated with the number and location. The G allele frequency of rs1801018 in PTC patients with multifocality (13.3%) was about four-fold higher than that in PTC patients with unifocality (3.4%). The G allele frequency of rs1801018 in PTC patients with both lobes (15.4%) was increased by about five-fold, compared to PTC patients with one lobe (3.2%). Conclusion The results suggest that synonymous SNP rs1801018 and the G allele of the BCL2 gene may be associated with the multifocality and bilaterality of PTC in Korean population.
ADAPTIVE CACHE REPLACEMENT POLICY (ACRP): A DYNAMIC REPLACEMENT POLICY FOR CACHE MANAGEMENT

The discovery of memory access time as one of the major design issues in the processor has increased effort in the development of different cache replacement policies to manage what to be the content of caches in both uniprocessor and multiprocessor. This is to improve the overall performance of the processor. Most time the potential benefits of these policies are not instantaneous due to the varying nature of the workloads. Therefore, it is difficult to identify which particular policy to apply during cache’s content replacement. In this paper, an adaptive replacement technique using the minimum threshold value of the improvement factor of cache, which was analytically obtained, is proposed in order to explore the combine merits of fundamental replacement policies and strikes a minimum balance with their demerits. ACRP approach uses the threshold values of improvement factor obtained from the analytic modeling to determine when the current replacement policy’s performance becomes or getting worse, the ACRP switches to another replacement policy from the pool of replacement policy. Specifically, the ACRP approach solves the problem associated with wrong usage of replacement policy and reduces processor cache miss rate caused by wrong evictions.
Log-Linear Mixture Models for Patch-Based Object Recognition

In this work, we present a new log-linear model for object recognition in images using local features. Object recognition is a building block for applications in many fields of image understanding. To recognise objects in images, commonly local features and statistical models are used in a Bayesian framework. Based on an approach that uses Gaussian mixtures to model object appearance we present a fully discriminative model using log-linear mixtures. The proposed model has the advantage over previous models that it requires less parameters, can be trained efficiently and allows for fusion of arbitrary information cues. We also propose extensions to our model that allow for incorporating spatial information and we propose and evaluate different techniques for efficient and reliable training of the model parameters. Furthermore, we evaluate the impact of different local descriptors and how they can be combined into a single system. The the performance of our model is measured on two standard object recognition datasets. We evaluate the impact of different model and feature extraction parameters and incrementally improve the performance of the proposed system to achieve state-of-the-art results on these datasets.