Miracle-dz/UniFAR-FTUs huggingface dataset:
The retinoic acid receptor alpha (RARA) gene is not associated with myopia, hypermetropia, and ocular biometric measures

Purpose The Retinoic Acid Receptor Alpha (RARA) gene is a potential candidate gene for myopia due to its differential expression in animal models during experimentally induced myopia. To test for whether RARA is associated with myopia we have undertaken a case-control study assessing for associations between RARA and myopia, hypermetropia, and ocular biometric measures. Methods A total of 802 Anglo-Celtic individuals were genotyped. Five tag single nucleotide polymorphisms (tSNPs) in RARA with an r2 of 0.8 and a minor allele frequency greater than 5% were selected for genotyping. Genotype frequencies of these 5 tSNPs were compared between individuals with emmetropia and those with myopia or hypermetropia. A quantitative analysis was also performed to assess associations with ocular biometric measures including axial length, corneal curvature and anterior chamber depth. Results We did not identify any significant association between tSNPs in RARA with either myopia or hypermetropia as qualitative traits. Neither did we identify any significant associations of these tSNPs with the quantitative traits of axial length, corneal curvature and anterior chamber depth. Conclusions This is the first study to assess for associations between RARA and myopia, hypermetropia, and ocular biometric measures. Our findings suggest that variations in the nucleotide sequence of RARA are not associated with myopia, hypermetropia, or ocular biometric measures in our population.
Development of Loop-Mediated Isothermal Amplification Targeting 18S Ribosomal DNA for Rapid Detection of Azumiobodo hoyamushi (Kinetoplastea)

Ascidian soft tunic syndrome (AsSTS) caused by Azumiobodo hoyamushi (A. hoyamushi) is a serious aquaculture problem that results in mass mortality of ascidians. Accordingly, the early and accurate detection of A. hoyamushi would contribute substantially to disease management and prevention of transmission. Recently, the loop-mediated isothermal amplification (LAMP) method was adopted for clinical diagnosis of a range of infectious diseases. Here, the authors describe a rapid and efficient LAMP-based method targeting the 18S rDNA gene for detection of A. hoyamushi using ascidian DNA for the diagnosis of AsSTS. A. hoyamushi LAMP assay amplified the DNA of 0.01 parasites per reaction and detected A. hoyamushi in 10 ng of ascidian DNA. To validate A. hoyamushi 18S rDNA LAMP assays, AsSTS-suspected and non-diseased ascidians were examined by microscopy, PCR, and by using the LAMP assay. When PCR was used as a gold standard, the LAMP assay showed good agreement in terms of sensitivity, positive predictive value (PPV), and negative predictive value (NPV). In the present study, a LAMP assay based on directly heat-treated samples was found to be as efficient as DNA extraction using a commercial kit for detecting A. hoyamushi. Taken together, this study shows the devised A. hoyamushi LAMP assay could be used to diagnose AsSTS in a straightforward, sensitive, and specific manner, that it could be used for forecasting, surveillance, and quarantine of AsSTS.
Serotonin Receptor 2A/C Is Involved in Electroacupuncture Inhibition of Pain in an Osteoarthritis Rat Model

Osteoarthritis currently has no cure. Acupuncture can benefit patients with knee osteoarthritis by providing pain relief, improving joint function and serving as an effective complement to standard care. However, the underlying mechanisms of its effects are still not completely understood. The present study, an investigation of the effectiveness and mechanisms of electroacupuncture (EA) in attenuating osteoarthritis pain in a rat model, is focused on the involvement of 5-hydroxytryptamine 2A/C (5-HT2A/C) receptors, which play an important role in pain modulation at the spinal level. Osteoarthritis was induced under isoflurane anesthesia by a single intraarticular injection of monosodium iodoacetate (3 mg/50 μL/rat) into one hind leg of each rat. EA was given at acupoints GB 30 and ST 36 on days 1–4 after the injection. Vehicle or ketanserin, a 5-HT2A/C receptor antagonist, was given intraperitoneally (1 mg kg−1) or intrathecally (5 μg or 10 μg/10 μL), 30 min before each EA treatment. Assessment of weight-bearing difference between injected and uninjected hind legs was done on days 0, 1–4 and 7. Fos /serotonin and serotonin/Fluorogold double labeling were performed to determine EA activation of serotonergic neurons in the nucleus raphe magnus (NRM) that project to spinal cord. The results showed that EA significantly decreases weight-bearing difference compared to sham EA. Ketanserin pretreatment blocked the analgesic effect of EA but did not influence weight bearing in sham EA control rats. EA also activated serotonergic NRM neurons that project to the spinal cord. These data show that EA inhibits osteoarthritis-induced pain by enhancing spinal 5-HT2A/2C receptor activity.
Cooperative Adaptive Cruise Control: A Reinforcement Learning Approach

Recently, improvements in sensing, communicating, and computing technologies have led to the development of driver-assistance systems (DASs). Such systems aim at helping drivers by either providing a warning to reduce crashes or doing some of the control tasks to relieve a driver from repetitive and boring tasks. Thus, for example, adaptive cruise control (ACC) aims at relieving a driver from manually adjusting his/her speed to maintain a constant speed or a safe distance from the vehicle in front of him/her. Currently, ACC can be improved through vehicle-to-vehicle communication, where the current speed and acceleration of a vehicle can be transmitted to the following vehicles by intervehicle communication. This way, vehicle-to-vehicle communication with ACC can be combined in one single system called cooperative adaptive cruise control (CACC). This paper investigates CACC by proposing a novel approach for the design of autonomous vehicle controllers based on modern machine-learning techniques. More specifically, this paper shows how a reinforcement-learning approach can be used to develop controllers for the secure longitudinal following of a front vehicle. This approach uses function approximation techniques along with gradient-descent learning algorithms as a means of directly modifying a control policy to optimize its performance. The experimental results, through simulation, show that this design approach can result in efficient behavior for CACC.
The real-time interactive 3-D-DVA for robust coronary MRA

A graphical user interface (GUI) has been developed which enables interactive feedback and control to the real-time diminishing variance algorithm (DVA). This interactivity allows the user to set scan parameters, view scan statistics, and view image updates during the course of the scan. In addition, the DVA has been extended to simultaneously reduce motion artifacts in three dimensions using three orthogonal navigators. Preliminary in vivo studies indicate that these improvements to the standard DVAI allow for significantly improved consistency and robustness in eliminating respiratory motion artifacts from MR images, particularly when imaging the coronary arteries.
Towards computational complexity certification for constrained MPC based on Lagrange Relaxation and the fast gradient method

This paper discusses the certification of Nesterov's fast gradient method for problems with a strongly convex quadratic objective and a feasible set given as the intersection of a parametrized affine set and a convex set. For this, we derive a lower iteration bound for the solution of the dual problem that is obtained from a partial Lagrange Relaxation and propose a new constant step-size rule that we prove to be optimal under mild assumptions. Finally, we apply the certification procedure to a constrained MPC problem and show that the new step-size rule improves performance significantly.
A novel voice signal discrimination algorithm and its application

A new algorithm which is capable of classifying voice signals recorded from subjects before and after the anesthetic procedure is presented. This new algorithm is based on Wavelet Packet Analysis (WPA) and Least Squares Support Vector Machines (LSSVM) and it combines the coefficients of WPA with other parameters, such as Spectral Centroid, Spectral roll-off point etc., as the feature vector. Experimental evaluation has shown that the proposed classification algorithm based on WPA and LSSVM is very effective as compared to the other two methods, and the total accuracy rate is over 85%.
Hierarchical Heuristic Search Techniques for Empire-based Games

Computer games have long been a fruitful and challenging area for the application of AI technologies. The empire-based strategy game is one genre that presents unique challenges to the implementation of an AI-based player due to the extremely large search space. Consequently, a majority of AI systems utilize ad hoc strategies such as hand-built finite state automata. While practical, this approach limits the computer player to the strategies designed by the programmer. A more flexible approach allows the computer to adaptively search for promising moves. This paper proposes a hierarchical architecture that breaks the problem space into manageable units. Through aggressive pruning strategies heuristic search may be employed across the hierarchical levels. The new search space examines approximately (nm) states for m moves, n pieces, and a search depth of d. In comparison, full search requires the examination of approximately (m) states. This technique was implemented on a simple empire-style game that generated expected results
Entry of Amphotropic Murine Leukemia Virus Is Influenced by Residues in the Putative Second Extracellular Domain of Its Receptor, Pit2

ABSTRACT Human cells express distinct but related receptors for the gibbon ape leukemia virus (GALV) and the amphotropic murine leukemia virus (A-MuLV), termed Pit1 and Pit2, respectively. Pit1 is not able to function as a receptor for A-MuLV infection, while Pit2 does not confer susceptibility to GALV. Previous studies of chimeric receptors constructed by interchanging regions of Pit1 and Pit2 failed to clarify the determinants unique to Pit2 which correlate with A-MuLV receptor function. In order to identify which regions of Pit2 are involved in A-MuLV receptor function, we exchanged the putative second and third extracellular domains of Pit1, either individually or together, with the corresponding regions of Pit2. Our functional characterization of these receptors indicates a role for the putative second extracellular domain (domain II) in A-MuLV infection. We further investigated the influence of domain II with respect to A-MuLV receptor function by performing site-specific mutagenesis within this region of Pit2. Many of the mutations had little or no effect on receptor function. However, the substitution of serine for methionine at position 138 (S138M) in a Pit1 chimera containing domain II of Pit2 resulted in a 1,000-fold reduction in A-MuLV receptor function. Additional mutations made within domain II of the nonfunctional S138M mutant restored receptor function to nearly wild-type efficiency. The high degree of tolerance for mutations as well as the compensatory effect of particular substitutions observed within domain II suggests that an element of secondary structure within this region plays a critical role in the interaction of the receptor with A-MuLV.
Integration as a general boundary condition on retrieval-induced forgetting

When people form connections between several memories that share a common retrieval cue, the tendency for those memories to interfere with one another during later retrieval attempts is often eliminated. Three experiments examined whether forming such connections might also protect memories from retrieval-induced forgetting, the phenomenon in which retrieving some associates of a cue leads to the suppression of others that interfere during retrieval (M. C. Anderson, E. L. Bjork, & R. A. Bjork, 1994). All 3 experiments found that instructing subjects to interrelate category exemplars during an initial study phase reduced retrieval-induced forgetting. Postexperimental questionnaires indicated that even when people were not instructed to interrelate exemplars, they often did so spontaneously and that this spontaneous integration also protected people from impairment. These findings, together with others obtained in different experimental settings, suggest that complex knowledge structures composed of highly interconnected components may be especially resistant to retrieval-induced forgetting.
Culture and gender differences in the self-esteem of college students: A four-country comparison

The responses of 268 Hong Kong and 399 Nigerian first or second year social science undergraduate university students to the Personal and Academic Self-Concept Inventory were compared to previously reported findings with similar groups of American and Nepalese students. Country x Gender analyses indicated clear, statistically significant main and interaction effects which varied according to the area of self-esteem under investigation. Support was found for the tendency found in research with secondary school students for subjects from non-Western cultures to report higher academic but lower non-academic self-esteem than their Western peers. However, the gender differences did not generalize across cultures.
Cell Growth Defect Factor1/CHAPERONE-LIKE PROTEIN OF POR1 Plays a Role in Stabilization of Light-Dependent Protochlorophyllide Oxidoreductase in Nicotiana benthamiana and Arabidopsis[C][W]

Protochlorophyllide oxidoreductase (POR), which catalyzes the protochlorophyllide reduction step in the chlorophyll biosynthetic pathway, is activated by light, and its substrate and product are photosensitizers. This work reports that CHAPERONE-LIKE PROTEIN OF POR1 interacts with POR isoforms in chloroplast membranes and protects POR proteins from photooxidative damage with its chaperone activity. Angiosperms require light for chlorophyll biosynthesis because one reaction in the pathway, the reduction of protochlorophyllide (Pchlide) to chlorophyllide, is catalyzed by the light-dependent protochlorophyllide oxidoreductase (POR). Here, we report that Cell growth defect factor1 (Cdf1), renamed here as CHAPERONE-LIKE PROTEIN OF POR1 (CPP1), an essential protein for chloroplast development, plays a role in the regulation of POR stability and function. Cdf1/CPP1 contains a J-like domain and three transmembrane domains, is localized in the thylakoid and envelope membranes, and interacts with POR isoforms in chloroplasts. CPP1 can stabilize POR proteins with its holdase chaperone activity. CPP1 deficiency results in diminished POR protein accumulation and defective chlorophyll synthesis, leading to photobleaching and growth inhibition of plants under light conditions. CPP1 depletion also causes reduced POR accumulation in etioplasts of dark-grown plants and as a result impairs the formation of prolamellar bodies, which subsequently affects chloroplast biogenesis upon illumination. Furthermore, in cyanobacteria, the CPP1 homolog critically regulates POR accumulation and chlorophyll synthesis under high-light conditions, in which the dark-operative Pchlide oxidoreductase is repressed by its oxygen sensitivity. These findings and the ubiquitous presence of CPP1 in oxygenic photosynthetic organisms suggest the conserved nature of CPP1 function in the regulation of POR.
Condensation-based multi-person tracking using an online SVM approach

We propose a multi-person tracking framework using only one single camera in this paper. We utilize particle filter as the tracking framework and train a SVM classifier by reliable examples extracted from associated detections without occlusion. Based on the results of data association, we integrate the target's velocity into weights calculation to handle object occlusion assuming that fast-moving target is not likely to change directions abruptly because of inertia. In addition, we design a new data association method whose affinity measure is computed by the classifier score judged on candidate image patch, the distance and size similarity of two rectangles. The experiments reveal that our method obtains a better performance compared with other state-of-the-art algorithms for PETS'09 videos S2 L1.
Television violence and aggression: A genotype-environment correlation and interaction theory

A study of siblings was run to obtain data on the relationships between aggression, the viewing and enjoyment of television (TV) violence, and the personality traits of extraversion, neuroticism, and psychoticism. The results failed to support the theory of a causal effect of the amount of viewing of TV violence on aggression. The correlations between siblings for aggression were very low, indicating an absence of shared family environmental effects including the amount of family viewing of TV violence; and there were no within-family correlations between the amount of viewing of TV violence and aggression, suggesting the absence of a causal relationship. It was proposed that a genotype-environment correlation and interaction theory would be more consistent with the data. The theory would posit genotypic differences in psychoticism generating differences in aggression and the enjoyment of TV violence, which could augment aggression.
Molecular Pathways Molecular Pathways : HER 3 Targeted Therapy

The HER family of receptor tyrosine kinases, including EGF receptor (EGFR), HER2, HER3, and HER4, transduce growth-promoting signals in response to ligand binding to their extracellular domains (ECD). This family is deregulated in numerous cancers, withmutations in EGFR andHER2 often serving as "driver" events to activate key growth factor signaling pathways such as the RAS-ERK and PI3K-AKT pathways. Less attention has been paid to the oncogenic functions ofHER3 due to its lack of intrinsic kinase activity. Recent work, however, has placed HER3 in the spotlight as a key signaling hub in several clinical contexts. First, HER3 has been shown to play a major role inmediating resistance to HER2 and phosphoinositide 3-kinase (PI3K) pathway-directed therapies due to its feedback regulation via AKT signaling. Second, activating mutations in HER3 have been identified in multiple cancer types, including gastric, colon, bladder, and non–small cell lung cancers. As a result, HER3 is now being examined as a direct therapeutic target. In the absence of a strong enzymatic activity to target, the focus has been on strategies to prevent HER3 activation including blocking its most relevant dimerization partner’s kinase activity (erlotinib, gefitinib, and lapatinib), blocking its most relevant dimerization partner’s ability to dimerize with HER3 (trastuzumab and pertuzumab), and directly targeting the HER3 ECD (MM-121, U3-1287, and LJM716). Although drugs targeting EGFR andHER2 have proven effective even as single agents, the preclinical and clinical data on the antibodies directly targeting HER3 suggest more limited potential for single-agent activity. Possible reasons for this include the lack of a suitable biomarker for activatedHER3, the lack of potency of the antibodies, and the lack of relevance of HER3 for growth of some of the cancer types analyzed. Nevertheless, clear improvements in activity are being observed for many of these compounds when they are given in combination. In this snapshot, we will highlight the basis for HER3 activation in cancer, the different pharmacologic strategies being used, and opportunities for further development. Clin Cancer Res; 20(6);
Effects of early dark energy on strong cluster lensing

We use the semi-analytic method developed earlier for computing strong-lensing optical depths to study the statistics of gravitational arcs in four dark-energy cosmologies. Specifically, we focus on models with early dark energy and compare them to more conventional models. Merger trees are constructed for the cluster population because strong cluster lensing is amplified by factors of two to three during mergers. We find that the optical depth for gravitational arcs in the early dark-energy models is increased by up to a factor of ∼3 compared to the other models because of the modified dynamics of cluster formation. In particular, the probability of gravitational arcs in high-redshift clusters is considerably increased, which may offer an explanation for the unexpectedly high lensing efficiency of distant clusters.
An optimized design of bi-directional dual active bridge converter for low voltage battery charger

This paper proposes an optimized design of dual active bridge (DAB) converter for low voltage charger. Among various bi-directional DC/DC converters, DAB converter is a high efficiency buck and boost bi-directional DC-DC converter isolated by a high frequency transformer. Battery voltage varies according to the charging status of the battery and the parameters of the DC/DC converter are the same regardless of the battery voltage. When the battery voltage is high, the soft switching (ZVS) region is reduced compared to the low battery voltage. In this paper, variable switching frequency is adopted in order to maximize soft-switching (ZVS) region at the high battery voltage. The same power can be obtained at the same duty regardless of the battery voltage using the variable switching frequency. The proposed method is applied to a 5kW prototype dual active bridge converter, and the experimental results are analyzed and verified.
Closed-Form Optimal Updates in Transform Learning

I. TRANSFORM LEARNING While the idea of learning a synthesis [1] or analysis [2], [3] dictionary for sparse signal representation has received recent attention, these formulations are typically non-convex and NP-hard, and the approximate algorithms are still computationally expensive. In this work, we focus instead on the learning of square sparsifying transforms W ∈ Rn×n, and develop efficient algorithms. The classical transform model for signal y is Wy = x+ e, where W ∈ Rm×n is a sparsifying transform, x is sparse, and e is a small transform domain residual [4]. The transform model is more general than both the analysis and noisy signal analysis models [4]. Moreover, transform sparse coding is easy and exact, involving thresholding Wy [4]. Importantly, the transform model holds well for natural images. Given a matrix Y ∈ Rn×N , whose columns represent training signals, the following formulation learns an orthonormal transform.
Narrative dependency and the false belief task in autism

Several studies have used a cognitive approach to teaching people with autism to pass false belief tasks with a broader aim of developing theory of mind abilities. However, these tasks have certain executive features that may influence performance on the tasks and the potential for generalization. The study examines the influence of narrative support and language level on the ability of children with autism to pass tests of false belief and control tasks of “false photo”. Thirty-four children with ASD, with a range of age and ability, were shown six video-recorded false belief stories and six matched false photo stories, half narrated and half not. Results showed that the children performed similarly on the tasks overall in narrated and unnarrated conditions. However, the narrative support aided responses to the control questions, highlighting the executive load in these tasks. Results showed a significant effect of verbal age on the children's performance on both sets of tasks.