Miracle-dz/UniFAR-FTUs huggingface dataset:
DART: a fast and accurate RNA-seq mapper with a partitioning strategy

Abstract Motivation In recent years, the massively parallel cDNA sequencing (RNA-Seq) technologies have become a powerful tool to provide high resolution measurement of expression and high sensitivity in detecting low abundance transcripts. However, RNA-seq data requires a huge amount of computational efforts. The very fundamental and critical step is to align each sequence fragment against the reference genome. Various de novo spliced RNA aligners have been developed in recent years. Though these aligners can handle spliced alignment and detect splice junctions, some challenges still remain to be solved. With the advances in sequencing technologies and the ongoing collection of sequencing data in the ENCODE project, more efficient alignment algorithms are highly demanded. Most read mappers follow the conventional seed-and-extend strategy to deal with inexact matches for sequence alignment. However, the extension is much more time consuming than the seeding step. Results We proposed a novel RNA-seq de novo mapping algorithm, call DART, which adopts a partitioning strategy to avoid the extension step. The experiment results on synthetic datasets and real NGS datasets showed that DART is a highly efficient aligner that yields the highest or comparable sensitivity and accuracy compared to most state-of-the-art aligners, and more importantly, it spends the least amount of time among the selected aligners. Availability and implementation https://github.com/hsinnan75/DART Supplementary information Supplementary data are available at Bioinformatics online.
Influence of air-particle deposition protocols on the surface topography and adhesion of resin cement to zirconia

Abstract Objectives. This study evaluated the influence of air-particle abrasion protocols on the surface roughness (SR) of zirconia and the shear bond strength (SBS) of dual-polymerized resin cement to this ceramic. Materials and methods. Sintered zirconia blocks (n = 115) (Lava, 3M ESPE) were embedded in acrylic resin and polished. The specimens were divided according to the ‘particle type' (Al: 110 µm Al2O3; Si: 110 µm SiO2) and ‘pressure' factors (2.5 or 3.5 bar) (n = 3 per group): (a) Control (no air-abrasion); (b) Al2.5; (c) Si2.5; (d) Al3.5; (e) Si3.5. SR (Ra) was measured 3-times from each specimen after 20 s of air-abrasion (distance: 10 mm) using a digital optical profilometer. Surface topography was evaluated under SEM analyses. For the SBS test, ‘particle type', ‘pressure' and ‘thermocycling' (TC) factors were considered (n = 10; n = 10 per group): Control (no air-abrasion); Al2.5; Si2.5; Al3.5; Si3.5; ControlTC; Al2.5TC; Si2.5TC; Al3.5TC; Si3.5TC. After silane application, resin cement (Panavia F2.0) was bonded and polymerized. Specimens were thermocycled (6.000 cycles, 5–55°C) and subjected to SBS (1 mm/min). Data were analyzed using ANOVA, Tukey's and Dunnett tests (5%). Results. ‘Particle' (p = 0.0001) and ‘pressure' (p = 0.0001) factors significantly affected the SR. All protocols significantly increased the SR (Al2.5: 0.45 ± 0.02; Si2.5: 0.39 ± 0.01; Al3.5: 0.80 ± 0.01; Si3.5: 0.64 ± 0.01 µm) compared to the control group (0.16 ± 0.01 µm). For SBS, only ‘particle' factor significantly affected the results (p = 0.015). The SiO2 groups presented significantly higher SBS results than Al2O3 (Al2.5: 4.78 ± 1.86; Si2.5: 7.17 ± 2.62; Al3.5: 4.97 ± 3.74; Si3.5: 9.14 ± 4.09 MPa) and the control group (3.67 ± 3.0 MPa). All TC specimens presented spontaneous debondings. SEM analysis showed that Al2O3 created damage in zirconia in the form of grooves, different from those observed with SiO2 groups. Conclusions. Air-abrasion with 110 µm Al2O3 resulted in higher roughness, but air-abrasion protocols with SiO2 promoted better adhesion.
Hierarchically Organized Medial Frontal Cortex-Basal Ganglia Loops Selectively Control Task- and Response-Selection

Adaptive behavior requires context-sensitive configuration of task-sets that specify time-varying stimulus–response mappings. Intriguingly, response time costs associated with changing task-sets and motor responses are known to be strongly interactive: switch costs at the task level are small in the presence of a response-switch but large when accompanied by a response-repetition, and vice versa for response-switch costs. The reasons behind this well known interdependence between task- and response-level control processes are currently not well understood. Here, we formalized and tested a model assuming a hierarchical organization of superordinate task-set and subordinate response-set selection processes to account for this effect. The model was found to successfully explain the full range of behavioral task- and response-switch costs across first and second order trial transitions. Using functional magnetic resonance imaging (fMRI) in healthy humans, we then characterized the neural circuitry mediating these effects. We found that presupplementary motor area (preSMA) activity tracked task-set control costs, SMA activity tracked response-set control costs, and basal ganglia (BG) activity mirrored the interaction between task- and response-set regulation processes that characterized participants' response times. A subsequent fMRI-guided transcranial magnetic stimulation experiment confirmed dissociable roles of the preSMA and SMA in determining response costs. Together, these data provide evidence for a hierarchical organization of posterior medial frontal cortex and its interaction with the BG, where a superordinate preSMA-BG loop establishes task-set selection, which imposes a (unidirectional) constraint on a subordinate SMA-BG loop that determines response-selection, resulting in the characteristic interdependence in task- and response-switch costs in behavior. SIGNIFICANCE STATEMENT The ability to use context-sensitive task-sets to guide our responses is central to human adaptive behavior. Task and response selection are strongly interactive: it is more difficult to repeat a response in the context of a changing task-set, and vice versa. However, the neurocognitive architecture giving rise to this interdependence is currently not understood. Here we use modeling, neuroimaging, and noninvasive neurostimulation to show that this phenomenon derives from a hierarchical organization of posterior medial frontal cortex and its interaction with the basal ganglia, where a more anterior corticostriatal loop establishes task-set selection, which constrains a more posterior loop responsible for response-selection. These data provide a neural explanation for a key behavioral signature of human cognitive control.
Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis

Distance metric learning (DML), which learns a distance metric from labeled "similar" and "dissimilar" data pairs, is widely utilized. Recently, several works investigate orthogonality-promoting regularization (OPR), which encourages the projection vectors in DML to be close to being orthogonal, to achieve three effects: (1) high balancedness -- achieving comparable performance on both frequent and infrequent classes; (2) high compactness -- using a small number of projection vectors to achieve a "good" metric; (3) good generalizability -- alleviating overfitting to training data. While showing promising results, these approaches suffer three problems. First, they involve solving non-convex optimization problems where achieving the global optimal is NP-hard. Second, it lacks a theoretical understanding why OPR can lead to balancedness. Third, the current generalization error analysis of OPR is not directly on the regularizer. In this paper, we address these three issues by (1) seeking convex relaxations of the original nonconvex problems so that the global optimal is guaranteed to be achievable; (2) providing a formal analysis on OPR's capability of promoting balancedness; (3) providing a theoretical analysis that directly reveals the relationship between OPR and generalization performance. Experiments on various datasets demonstrate that our convex methods are more effective in promoting balancedness, compactness, and generalization, and are computationally more efficient, compared with the nonconvex methods.
Learning to Race Through Coordinate Descent Bayesian Optimisation

In the automation of many kinds of processes, the observable outcome can often be described as the combined effect of an entire sequence of actions, or controls, applied throughout the process execution. In these cases, strategies to optimise control policies for individual stages of the process are not applicable, and instead the whole policy needs to be optimised at once. On the other hand, the cost to evaluate the policy's performance might also be high, being desirable that a solution can be found with as few interactions as possible with the real system. We consider the problem of optimising control policies to allow a robot to complete a given race track within a minimum amount of time. We assume that the robot has no prior information about the track or its own dynamical model, just an initial valid driving example. Localisation is only applied to monitor the robot and to provide an indication of its position along the track's centre axis. With that in mind, we propose a method for finding a policy that minimises the time per lap while keeping the vehicle on the track using a Bayesian optimisation (BO) approach over a reproducing kernel Hilbert space. We apply an algorithm to search more efficiently over high-dimensional policy-parameter spaces with BO, by iterating over each dimension individually, in a sequential coordinate descent-like scheme. Experiments demonstrate the performance of the algorithm against other methods in a simulated car racing environment.
Research on a novel magnetic-catalytic sensing material on CMOS-MEMS gas sensor

In this research, a novel magnetic catalyzed SnO<sub>2</sub> with Mn<sub>3</sub>O<sub>4</sub> of CMOS-MEMS gas sensor is firstly proposed. Beyond the conventional heating methods to obtain high chemical reaction rate, the sensitivity of gas sensors can be enhanced by using our proposed magnetic catalysis technique at ultra-low power consumption. Fabrication of sensor structure is realized by the standard 0. 35μm CMOS process and MEMS post process. Preparing for the magnetic sensing material, the solution of SnCl<sub>4(aq)</sub> with powder of Mn<sub>3</sub>O<sub>4</sub> and the precursor is mixed to obtain sol-gel solution. Measurement of gas concentration of monoxide is arranged in the gas chamber with solenoidal coils using magnetic material, SnO<sub>2</sub>-Mn<sub>3</sub>O<sub>4</sub> coated onto a CMOS-MEMS gas sensor with donut-shaped stacked electrodes by horizontal magnetic field to facilitate sensitivity. Based on our mature CMOS-MEMS gas sensor structure and developed magnetic-catalytic sensing mechanism, the enhancement of sensitivity with SnO<sub>2</sub>-Mn<sub>3</sub>O<sub>4</sub> is investigated and formulated with the Gibbs free energy and the Eyric equation. According to a careful investigation of the measurement results, the sensitivity of proposed CO gas sensor reaches 1.87%/ppm under the 6 Gauss. Moreover, the sensitivity of the novel material SnO<sub>2</sub>-Mn<sub>3</sub>O<sub>4</sub> is better than our previous research with sensing material SnO<sub>2</sub>-Fe<sub>3</sub>O<sub>4</sub>. This research shows a highly practical application to CMOS gas sensor with a widespread magnetic-catalytic mechanism and sol-gel solution.
Becoming a CPA —How to Attract University Students to the Accounting Profession Using Theory of Planned Behavior?

The purpose of this study is to determine the relative importance of factors that attract university students to the accounting profession in Lebanon using Theory of Planned Behavior. The significance of this study is based on the previous research which has shown that “intrinsic factors” (attitude toward the behavior) and “parental influence” (subjective norms) are significant predictors of career choice of accounting students. Using a very large judgmental sample from business students focusing on accounting, the researchers in this study constructed a reliable and valid instrument having one item measuring intention to pursue accounting career in Lebanon, four items measuring self efficacy, another four items measuring social influence (subjective norms) and five items measuring attitude and behavioral beliefs. The multiple regression analysis retained “Subjective Norms” in the model and removed “Beliefs and Attitude towards Accountant and CPA”, “Self Efficacy”, and “Perceived Behavioral Control”. The current study showed that path analysis was not an acceptable fit of data. All predictors (paths) except the direct effect between “Subjective Norms” and “intention to pursue accounting career in Lebanon” should be deleted from the model. Findings of this study support that Hypothesis 1—Subjective Norms (perceived social pressure to become or not become CPA) will be a significant positive predictor of intention to Pursue a CPA Career. Furthermore, the current study provided implications for policy making and for further research.
Light-Trapping and Electrical Transport in Randomly Rough Thin-Film Solar Cells

In this work, we use a rigorous electro-optical model to study silicon solar cells with random textures. First, we calculate the efficiency limits of silicon solar cells by considering a p-n junction and solving the driftdiffusion equations as a function of the cell thickness, assuming the Lambertian light trapping. Second, we aim to design realistic solar cells to get as close as possible to the efficiency limits. We use an efficient numerical model, which allows us to study a wide range of the absorber thickness and material parameters. We theoretically demonstrate how to simultaneously increase short-circuit current and improve open-circuit voltage by, respectively, texturing the front surface and decreasing the absorber thickness.
Machine Vision and Applications Automatic Free Parking Space Detection by Using Motion Stereo-based 3d Reconstruction

This paper proposes a free parking space detection system by using motion stereo-based 3D reconstruction. An image sequence is acquired with a single rearview fisheye camera and the view behind the automobile is three-dimensionally reconstructed by using point correspondences. Metric information is recovered from the camera height ratio and free parking spaces are detected by estimating the positions of adjacent vehicles. Since adjacent vehicles are usually located near the epipole, their structures are seriously degraded. To solve this problem, we select point correspondences by using a de-rotation-based method and mosaic 3D structures by estimating a similarity transformation. Unlike in previous work, our system proposes an efficient way of locating free parking spaces in 3D point clouds. Odometry is not used because its accuracy depends largely on road conditions. In the experiments, the system was tested in 154 different parking situations and its success rate was 90% (139 successes in 154 cases). The detection accuracy was evaluated by using ground truth data that was acquired with a laser scanner.
Heteroblastic Development and Shade‐avoidance in Response to Blue and Red Light Signals in Acacia implexa

Information from blue (400–500 nm) and red (660–730 nm) wavelengths is used by plants to determine proximity of neighbors or actual shading. Plants undergo trait changes in order to out‐compete neighbors or accommodate shading. Heteroblasty, the dramatic shift from one leaf type to another during juvenility, can be influenced by the light environment although it is unknown whether cues from blue or red (or both) are driving the developmental process. Seedlings of three populations of Acacia implexa (Mimosaceae) collected from low, medium and high rainfall habitats were grown in a factorial design of high/low blue and red light to determine how light signals affect heteroblasty and patterns of biomass allocation. Low blue light significantly delayed heteroblasty in the low rainfall population and low red light significantly delayed in the low and high rainfall populations. Low blue light increased stem elongation and decreased root biomass whereas low red light induced a strong shade‐avoidance response. These results were consistent across populations although the low rainfall population showed greater trait variability in response to red light signals. We conclude that red light conveys a greater information signal than blue light that affects heteroblasty and seedling development in A. implexa.
Measuring productivity in agile software development process: a scoping study

An agile software development process is often claimed to increase productivity. However, productivity measurement in agile software development is little researched. Measures are not explicitly defined nor commonly agreed upon. In this paper, we highlight the agile productivity measures reported in literature by means of a research method called scoping study. We were able to identify 12 papers reporting the productivity measures in agile software development processes. We found that finding, understanding and putting into use agile productivity definitions is not an easy task. From the perspective of common roles in agile software development process and existing knowledge workers’ productivity dimensions, we also emphasize that none of the productivity measures satisfy these fully. We recommend that future effort should be focused on defining agile productivity in measurable, practicable and meaningful form.
To control or to be controlled? From health locus of control to morphine control during patient-controlled analgesia.

We postulated that patients with an internal locus of control, i.e. those who like to control their health problems themselves, would adapt more adequately to the 'patient-controlled analgesia' technique as compared to patients with an external health locus of control, who do not believe in their own control. Since contradicting studies have been published on this matter, we investigated relations between the demand for analgesics, perceived pain in the postoperative phase, and the health locus of control in the postoperative context of cardiac surgery. Findings demonstrate distinct utilization patterns between subjects with internal or external locus of control concerning total morphine consumption, number of unsatisfied demands and reduction of perceived pain.
Single Stage Prediction with Online Reviews for Mobile App Development and Management

Mobile apps are one of the building blocks of the mobile digital economy. A differentiating feature of mobile apps to traditional enterprise software is online reviews, which are available on app marketplaces and represent a valuable source of consumer feedback on the app. We create a supervised topic modeling approach for app developers to use mobile reviews as useful sources of quality and customer feedback, thereby complementing traditional software testing. The approach is based on a constrained matrix factorization that leverages the relationship between term frequency and a given response variable in addition to co-occurrences between terms to recover topics that are both predictive of consumer sentiment and useful for understanding the underlying textual themes. The factorization can provide guidance on a single app's performance as well as systematically compare different apps over time for benchmarking of features and consumer sentiment. We apply our approach using a dataset of over 81,000 mobile reviews over several years for the two of the most reviewed online travel agent apps from the iOS and Google Play marketplaces.
Treatment Effect Analyses through Orthogonality Conditions Implied by a Fuzzy Regression Discontinuity Design, with Two Empirical Studies1

This study proposes a new estimator for estimating a treatment effect in one particular fuzzy regression discontinuity (RD) setting, in which the treatment effect is homogeneous on the support of an assignment variable and the treatment assignment is exogenous conditional on that assignment variable. The estimator is constructed using orthogonality conditions and can be easily implemented by an instrumental variable (IV) estimation procedure. We use Monte Carlo experiments to show that the proposed estimator can substantially reduce the bias in estimating the treatment effect caused by misspecifying the regression model of the observed outcome. We also use two empirical studies to demonstrate the advantages of our proposed estimator over alternative estimators. Furthermore, we use the first empirical study to highlight a connection between our proposed estimator and propensity-score matching estimators. The second empirical study emphasizes that the proposed estimator can work in a fuzzy RD setting where the cutoff point is either unknown or not exactly known.
Association between MRI-derived hepatic fat fraction and blood pressure in participants without history of cardiovascular disease

Objectives: We assessed whether liver fat content, as determined by MRI, correlates with blood pressure (BP), a major vascular risk factor, in individuals from the general population without history of stroke and coronary or peripheral artery disease. Methods: Cross-sectional data from 384 participants (161 women; aged 39–73 years) of a MRI substudy of the KORA FF4 survey were used. Hepatic fat fraction (HFF) was measured in the left and right lobe of the liver using single voxel multiecho 1H-spectroscopy and at the level of the portal vein using a multiecho Dixon-sequence. Associations of HFF with SBP and DBP as well as hypertension were assessed by right censored normal regression (accounting for antihypertensive treatment) and by logistic regression, respectively. Results: High levels of HFF measured on the level of the portal vein (90th percentile, 21.8%), compared with low HFF levels (10th percentile, 1.7%), were associated with higher SBP (131 vs. 122 mmHg; overall P = 0.001), higher DBP (82 vs. 76 mmHg, P < 0.001) and with higher odds of hypertension [odds ratio (OR) = 2.16, P = 0.025]. A level of 5.13% (54th percentile) was identified as optimal HFF cut-off for the prediction of hypertension (OR = 2.00, P = 0.015). Alcohol consumption emerged as an effect modifier for the association between HFF and hypertension (nonalcohol drinker: OR = 3.76, P = 0.025; alcohol drinker: OR = 1.59, P = 0.165). Conclusion: MRI-derived subclinical HFF is associated with SBP and DBP as well as with hypertension in participants from the general population without history of cardiovascular disease.
Developing a contrast agent for the in vivo detection of apoptosis

ii Acknowledgments . iii Table of Contents . iv List of Figures . vii List of Abbreviations . viii Chapter 1 . 1 1 Introduction . 1 1.1 Apoptosis . 1 1.1.1 Overview of Programmed Cell Death . 1 1.1.2 Caspases: The Mediators of Apoptosis . 2 1.1.3 Molecular Signaling Pathways of Apoptosis . 3 1.1.3.1 Extrinsic Pathway . 3 1.1.3.2 Intrinsic Pathway . 4 1.1.3.3 Execution Pathway . 5 1.1. 4 Morphological and Biochemical Hallmarks of Apoptosis . 6 1.1. 5 Differentiating Apoptosis from Necrosis . 7 1.1. 6 Apoptosis in Physiology and Pathology . 8 1.1. 6.1 Apoptosis and Neurodegenerative Disease . 10 1.2 Models of Apoptosis . 11 1.2.1 Inducing Apoptosis in Cell Culture . 11 1.2.2 Mouse Models of Apoptosis . 12 1.2.2.1 Fas-Mediated Hepatic Apoptosis . 12 1.2.2. 2 Treatment of Tumor Models with Anticancer Drugs . 12 1.2.2.3 Cerebral Stroke Model . 13 1.2.2.4 1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine Mouse Model of Parkinson's Disease . 13 1.3 Methods for Detecting Apoptosis in Vitro . 14 1.3.1 Cytomorphological Detection . 15