Miracle-dz/UniFAR-FTUs huggingface dataset:
Phylogeographic structure of the dunes sagebrush lizard, an endemic habitat specialist

Phylogeographic divergence and population genetic diversity within species reflect the impacts of habitat connectivity, demographics, and landscape level processes in both the recent and distant past. Characterizing patterns of differentiation across the geographic range of a species provides insight on the roles of organismal and environmental traits, on evolutionary divergence, and future population persistence. This is particularly true of habitat specialists where habitat availability and resource dependence may result in pronounced genetic structure as well as increased population vulnerability. We use DNA sequence data as well as microsatellite genotypes to estimate range-wide phylogeographic divergence, historical population connectivity, and historical demographics in an endemic habitat specialist, the dunes sagebrush lizard (Sceloporus arenicolus). This species is found exclusively in dune blowouts and patches of open sand within the shinnery oak-sand dune ecosystem of southeastern New Mexico and adjacent Texas. We find evidence of phylogeographic structure consistent with breaks and constrictions in suitable habitat at the range-wide scale. In addition, we find support for a dynamic and variable evolutionary history across the range of S. arenicolus. Populations in the Monahans Sandhills have deeply divergent lineages consistent with long-term demographic stability. In contrast, populations in the Mescalero Sands are not highly differentiated, though we do find evidence of demographic expansion in some regions and relative demographic stability in others. Phylogeographic history and population genetic differentiation in this species has been shaped by the configuration of habitat patches within a geologically complex and historically dynamic landscape. Our findings identify regions as genetically distinctive conservation units as well as underscore the genetic and demographic history of different lineages of S. arenicolus.
A Chemosensory Protein BtabCSP11 Mediates Reproduction in Bemisia tabaci

The olfactory system serves a vital role in the evolution and survival of insects, being involved in behaviors such as host seeking, foraging, mating, and oviposition. Odorant-binding proteins (OBPs) and chemosensory proteins (CSPs) are involved in the olfactory recognition process. In this study, BtabCSP11, a CSP11 gene from the whitefly Bemisia tabaci, was cloned and characterized. The open reading frame of BtabCSP11 encodes 136 amino acids, with four highly conserved cysteine residues. The temporal and spatial expression profiles showed that BtabCSP11 was highly expressed in the abdomens of B. tabaci females. Dietary RNA interference (RNAi)-based functional analysis showed substantially reduced fecundity in parthenogenetically reproduced females, suggesting a potential role of BtabCSP11 in B. tabaci reproduction. These combined results expand the function of CSPs beyond chemosensation.
Scalability analysis of grammatical evolution based test data generation

Heuristic-based search techniques have been increasingly used to automate different aspects of software testing. Several studies suggest that variable interdependencies may exist in branching conditions of real-life programs, and these dependencies result in the need for highly precise data values (such as of the form i=j=k) for code coverage analysis. This requirement makes it very difficult for Genetic Algorithm (GA)-based approach to successfully search for the required test data from vast search spaces of real-life programs. Ariadne is the only Grammatical Evolution (GE)-based test data generation system, proposed to date, that uses grammars to exploit variable interdependencies to improve code coverage. Ariadne has been compared favourably to other well-known test data generation techniques in the literature; however, its scalability has not yet been tested for increasingly complex programs. This paper presents the results of a rigorous analysis performed to examine Ariadne's scalability. We also designed and employed a large set of highly scalable 18 benchmark programs for our experiments. Our results suggest that Ariadne is highly scalable as it exhibited 100% coverage across all the programs of increasing complexity with significantly smaller search costs than GA-based approaches, which failed even with huge search budgets.
An Emotional Agent for Moral Impairment Rehabilitation in TBI Patients

The ability to identify the emotions of others is a key component of what is known as social cognition. Narratives exploit this mechanism to create an emotional bond with the characters and to maintain the engagement of the audience throughout the story. In this paper, we illustrate a case study in emotion understanding in stories that exploits a computational agent to explore emotion impairment in a group of traumatic brain injured people. The study focuses on moral emotions, aiming to investigate the differences in moral functioning that characterize traumatic brain injured patients. After comparing the understanding of the moral and emotional facets of the agent's behavior in traumatic brain injured patients and in neurologically intact controls, slight–yet meaningful–differences were observed between the two groups. We describe the test methodology and results, highlighting their implications for the design of rehabilitation applications based on virtual agents.
Another difficulty of inverted triangular pareto fronts for decomposition-based multi-objective algorithms

A set of uniformly sampled weight vectors from a unit simplex has been frequently used in decomposition-based multi-objective algorithms. The number of the generated weight vectors is controlled by a user-defined parameter H. In the literature, good results are often reported on test problems with triangular Pareto fronts since the shape of the Pareto fronts is consistent with the distribution of the weight vectors. However, when a problem has an inverted triangular Pareto front, well-distributed solutions over the entire Pareto front are not obtained due to the inconsistency between the Pareto front shape and the weight vector distribution. In this paper, we demonstrate that the specification of H has an unexpected large effect on the performance of decomposition-based multi-objective algorithms when the test problems have inverted triangular Pareto fronts. We clearly explain why their performance is sensitive to the specification of H in an unexpected manner (e.g., H = 3 is bad but H = 4 is good for three-objective problems whereas H = 3 is good but H = 4 is bad for four-objective problems). After these discussions, we suggest a simple weight vector specification method for inverted triangular Pareto fronts.
Carrier-based Aircraft Detection on Flight Deck of Aircraft Carrier with Simulated 3-D Model by Deep Neural Network

Military aircraft detection is always a challenging problem in the development of defence technology since World War II (WWII). The target is usually captured by electromagnetic wave reflection, which is accomplished by radar and CCD camera. The existed studies in this field mainly focused on aircraft detection in airbase or airports so far. It is noteworthy that the aircraft carrier is also an essential vector for the military aircraft, which is more challenging for aircraft detection, especially in the complex sea condition. This paper proposed a novel method of carrier-based aircraft detection on the flight deck of an aircraft carrier with simulated 3-D model. We construct a Parallel Convolutional Neural Network (PCNN) to train the simulated 3-D model dataset, which is also used for the final detection process. Finally, we apply the generalized deep convolutional neural network to detect the real reconnaissance images of the aircraft carrier with carrier-based aircraft on the flight deck. Experiments result show that the proposed method achieves an average detection accuracy of 99.92% in the real reconnaissance images, which contributes to the surveillance and early warning of the actual naval warfare.
Investigation of Electrically Evoked Auditory Brainstem Responses to Multi-Pulse Stimulation of High Frequency in Cochlear Implant Users

We investigated the effects of electric multi-pulse stimulation on electrically evoked auditory brainstem responses (eABRs). Multi-pulses with a high burst rate of 10,000 pps were assembled from pulses of 45-μs phase duration. Conditions of 1, 2, 4, 8, and 16 pulses were investigated. Psychophysical thresholds (THRs) and most comfortable levels (MCLs) in multi-pulse conditions were measured. Psychophysical temporal integration functions (slopes of THRs/MCLs as a function of number of pulses) were −1.30 and −0.93 dB/doubling of the number of pulses, which correspond to the doubling of pulse duration. A total of 15 eABR conditions with different numbers of pulses and amplitudes were measured. The morphology of eABRs to multi-pulse stimuli did not differ from those to conventional single pulses. eABR wave eV amplitudes and latencies were analyzed extensively. At a fixed stimulation amplitude, an increasing number of pulses caused increasing wave eV amplitudes up to a certain, subject-dependent number of pulses. Then, amplitudes either saturated or even decreased. This contradicted the conventional amplitude growth functions and also contradicted psychophysical results. We showed that destructive interference could be a possible reason for such a finding, where peaks and troughs of responses to the first pulses were suppressed by those of successive pulses in the train. This study provides data on psychophysical THRs and MCLs and corresponding eABR responses for stimulation with single-pulse and multi-pulse stimuli with increasing duration. Therefore, it provides insights how pulse trains integrate at the level of the brainstem.
Computational prediction of drug response in short QT syndrome type 1 based on measurements of compound effect in stem cell-derived cardiomyocytes

Short QT (SQT) syndrome is a genetic cardiac disorder characterized by an abbreviated QT interval of the patient’s electrocardiogram. The syndrome is associated with increased risk of arrhythmia and sudden cardiac death and can arise from a number of ion channel mutations. Cardiomyocytes derived from induced pluripotent stem cells generated from SQT patients (SQT hiPSC-CMs) provide promising platforms for testing pharmacological treatments directly in human cardiac cells exhibiting mutations specific for the syndrome. However, a difficulty is posed by the relative immaturity of hiPSC-CMs, with the possibility that drug effects observed in SQT hiPSC-CMs could be very different from the corresponding drug effect in vivo. In this paper, we apply a multistep computational procedure for translating measured drug effects from these cells to human QT response. This process first detects drug effects on individual ion channels based on measurements of SQT hiPSC-CMs and then uses these results to estimate the drug effects on ventricular action potentials and QT intervals of adult SQT patients. We find that the procedure is able to identify IC50 values in line with measured values for the four drugs quinidine, ivabradine, ajmaline and mexiletine. In addition, the predicted effect of quinidine on the adult QT interval is in good agreement with measured effects of quinidine for adult patients. Consequently, the computational procedure appears to be a useful tool for helping predicting adult drug responses from pure in vitro measurements of patient derived cell lines. Author summary A number of cardiac disorders originate from genetic mutations affecting the function of ion channels populating the membrane of cardiomyocytes. One example is short QT syndrome, associated with increased risk of arrhythmias and sudden cardiac death. Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs) provide a promising platform for testing potential pharmacological treatments for such disorders, as human cardiomyocytes exhibiting specific mutations can be generated and exposed to drugs in vitro. However, the electrophysiological properties of hiPSC-CMs differ significantly from those of adult native cardiomyocytes. Therefore, drug effects observed for hiPSC-CMs could possibly be very different from corresponding drug effects for adult cells in vivo. In this study, we apply a computational framework for translating drug effects observed for hiPSC-CMs derived from a short QT patient to drug effects for adult short QT cardiomyocytes. For one of the considered drugs, the effect on adult QT intervals has been measured and these measurements turn out to be in good agreement with the response estimated by the computational procedure. Thus, the computational framework shows promise for being a useful tool for predicting adult drug responses from measurements of hiPSC-CMs, allowing earlier identification of compounds to accurately treat cardiac diseases.
Trauma or Drama: A Predictive Processing Perspective on the Continuum of Stress

The notion of psychological trauma has been liberally used both in clinical literature and general discourse. However, no consensus exists on its exact meaning and definition. Whereas traditionally trauma has been mostly associated with criterion A of acute and posttraumatic stress disorders (PTSDs) as defined in the Diagnostic and Statistical Manual of Mental Disorders, many researchers find this definition too constraining and not accounting for the complexity and many aspects of trauma. This touched off a quest for a broader more accommodating trauma concept, and a dimensional view of trauma with PTSD as its extreme manifestation has been suggested. The dimensional view also has its detractors arguing that “conceptual bracket creep” may undermine the category’s utility. Both categorical and dimensional views mostly rely on trauma’s clinical phenomenology and lack a unified theoretical basis. In an attempt to reconcile this contradiction, a hybrid categorical–dimensional model of trauma based on the general theory of stress has been recently proposed (Krupnik, 2019). Herein, I explore the categorical boundary of the trauma concept, as posited by the model, within the predictive processing framework (PPF). I integrate the PPF view with the theory of stress. In conclusion, I briefly discuss how the proposed model of trauma may guide clinical practice.
An Automatic Extraction Method of Coronary Arteries Centerline Based on Cellular Automata

Effectively obtaining the centerline of the coronary arteries is very important to the clinical medical diagnosis. Cellular automata are extensively used to find fine solutions in many complex hard. However, it has the problem of large amount of computation. In this paper, we propose an automatic extraction method of coronary centerline based on cellular automata. Different from the existing methods, the distance from boundary field is used to extract the centerline of the coronary arteries roughly, which can place the candidate voxel at the center of the coronary arteries and reduce the size of the data. Furthermore, the centerlines of the coronary arteries are extracted accurately by using cellular automata to find the shortest path. The proposed method can extract the centerlines of each branch of the coronary arteries simultaneously from a single source to multiple destinations. Furthermore, compared to the method in Ref [10], our proposed method works well, especially in the case of large vessel curvature, the voxels at the extracted centerline are relatively centered. In the last, quantitative evaluation is conducted on the coronary arteries and the results show that the proposed method achieves a smaller deviation distance.
Lipase From Rhizomucor miehei Immobilized on Magnetic Nanoparticles: Performance in Fatty Acid Ethyl Ester (FAEE) Optimized Production by the Taguchi Method

In this communication, it was evaluated the production of fatty acid ethyl ester (FAAE) from the free fatty acids of babassu oil catalyzed by lipase from Rhizomucor miehei (RML) immobilized on magnetic nanoparticles (MNP) coated with 3-aminopropyltriethoxysilane (APTES), Fe3O4@APTES-RML or RML-MNP for short. MNPs were prepared by co-precipitation coated with 3-aminopropyltriethoxysilane and used as a support to immobilize RML (immobilization yield: 94.7 ± 1.0%; biocatalyst activity: 341.3 ± 1.2 Up–NPB/g), which were also activated with glutaraldehyde and then used to immobilize RML (immobilization yield: 91.9 ± 0.2%; biocatalyst activity: 199.6 ± 3.5 Up–NPB/g). RML-MNP was characterized by X-Ray Powder Diffraction (XRPD), Fourier Transform-Infrared (FTIR) spectroscopy and Scanning Electron Microscope (SEM), proving the incorporation and immobilization of RML on the APTES matrix. In addition, the immobilized biocatalyst presented at 60°C a half-life 16–19 times greater than that of the soluble lipase in the pH range 5–10. RML and RML-MNP showed higher activity at pH 7; the immobilized enzyme was more active than the free enzyme in the pH range (5–10) analyzed. For the production of fatty acid ethyl ester, under optimal conditions [40°C, 6 h, 1:1 (FFAs/alcohol)] determined by the Taguchi method, it was possible to obtain conversion of 81.7 ± 0.7% using 5% of RML-MNP.
Data-driven point sampling with blue-noise properties for triangular meshes

In this paper, we present a novel data-driven schema for generating stochastically distributed points with blue-noise properties on triangle meshes. We propose a pre-processing method to generate triangles with different features and sample each of them uniformly. Subsequently, we utilize the k-nearest neighbors (k-NN) regression to train the features and the pre-sampled points of these triangles. For the inference of new meshes, we generate a point set with the Poisson distribution and minimal distance constraint based on the pre-sampled points of new meshes inferred by the trained model. The result of k-fold cross-validation shows that the trained model shows high-quality results dues to its small MSE. The frequency analysis shows that the sampled points on new meshes have blue-noise characterization. We also apply the trained model to sample the surfaces of 3D models. Result analysis shows that the proposed approach gives better performance than the state-of-art computational geometry methods.
Early cardiac inflammation as a driver of murine model of Arrhythmogenic Cardiomyopathy

The study of a desmoglein 2 murine model of arrhythmogenic cardiomyopathy revealed cardiac inflammation as a key early event leading to fibrosis. Arrhythmogenic Cardiomyopathy (AC) is an inherited heart muscle disorder leading to ventricular arrhythmias and heart failure due to abnormalities in the cardiac desmosome. We examined how loss of desmoglein 2 (Dsg2) in the young murine heart leads to development of AC. Cardiomyocyte apoptosis was an early cellular phenotype and RNA-Seq analysis revealed early activation of inflammatory-associated pathways in Dsg2 null (Dsg2−/−) hearts at postnatal day 14 (Two weeks) that were absent in the fibrotic heart of adult mice (Ten weeks). This included upregulation of iRhom2/ADAM17 and its associated pro-inflammatory cytokines and receptors such as TNFα, IL6R and IL-6. Furthermore, genes linked to specific macrophage populations were upregulated. This suggests cardiomyocyte stress triggers an early immune response to clear apoptotic cells allowing tissue remodelling later on in the fibrotic heart. Our analysis at different disease stages implicate inflammation related to loss of desmoglein 2 as a major mechanism for disease progression.
Defoliation and Fruit Removal Effects on Papaya Fruit Production, Sugar Accumulation, and Sucrose Metabolism

Papaya (Carica papaya L.) source size and sink strength were modified by a single defoliation or continual defoliation and fruit thinning. Fruit set, development, weight, total sugar (sum of sucrose, fructose, and glucose), sucrose phosphate synthase (SPS), sucrose synthase (SS), and acid invertase (AI) enzyme activities in response to defoliation and fruit thinning were determined. The effects of defoliation and fruit thinning varied with weather conditions, plant growth conditions, and cultivar. Removal of 75% of the leaves significantly reduced new flower production and fruit set, and decreased ripe fruit total soluble solids (TSS), while 50% defoliation did not reduce new fruit set or ripe fruit TSS. When eve ry third leaf from the oldest leaf was not removed, the number of new flowers was reduced by 47% more than when the same number of leaves was removed from the oldest to younger leaves. Continual removal of old leaves reduced new fruit set, fruit weight, and TSS in the 168 day experimental period. Fruit thinning increased new fruit set and ripe fruit TSS. Larger fruit size, faster fruit development, lower respiration rate, and higher sugar contents and AI activity were observed in immature (young) fruit when old fruit were removed. AI activity was reduced during early fruit development and increased again in mature fruit in plants subjected to defoliation, and suggested a role for AI in mature fruit sugar accumulation, while SS activity declined significantly in fruit 154 and 175 days after anthesis and in mature fruit when plants were subjected to continual defoliation. SPS activity was not affected significantly by defoliation or fruit thinning. Source-sink balance was critical for papaya fruit set, development, and sugar accumulation and each mature leaf was able to provide photoassimilate for about three fruit.
Invasion dynamics of Cytisus scoparius: a matrix model approach.

It is at the level of population dynamics that an invasion either fails or succeeds. By elucidating patterns of variation in population growth rates or demographic rates, it is possible to forge a connection between quantitative field data and theoretical ideas about invasiveness, invasibility, and rates of spread. Demographic models also provide a tool to guide control strategies for invasive pests. Here I report the results of a demographic study of Cytisus scoparius, an exotic shrub on the west coast of North America. I used matrix population models to describe demographic patterns in six populations (three in prairies and three in urban fields) and across advancing stages of invasion. At the edge of the invading front, all populations showed finite rates of increase (λ) >1; however, prairie populations were increasing much more rapidly than urban ones. While many individual vital rates differed between prairie and urban populations, Life Table Response Analysis revealed that seedling establishment mad.
HLH-30 dependent rewiring of metabolism during starvation in C. elegans

One of the most fundamental challenges for all living organisms is to sense and respond to alternating nutritional conditions in order to adapt their metabolism and physiology to promote survival and achieve balanced growth. Here, we applied metabolomics and lipidomics to examine temporal regulation of metabolism during starvation in wildtype Caenorhabditis elegans and in animals lacking the transcription factor HLH-30. Our findings show for the first time that starvation alters the abundance of hundreds of metabolites and lipid species in a temporal- and HLH-30-dependent manner. We demonstrate that premature death of hlh-30 animals under starvation can be prevented by supplementation of exogenous fatty acids, and that HLH-30 is required for complete oxidation of long-chain fatty acids. We further show that RNAi-mediated knockdown of the gene encoding carnitine palmitoyl transferase I (cpt-1) only impairs survival of wildtype animals and not of hlh-30 animals. Strikingly, we also find that compromised generation of peroxisomes by prx-5 knockdown renders hlh-30 animals hypersensitive to starvation, which cannot be rescued by supplementation of exogenous fatty acids. Collectively, our observations show that mitochondrial functions are compromised in hlh-30 animals and that hlh-30 animals rewire their metabolism to largely depend on functional peroxisomes during starvation, underlining the importance of metabolic plasticity to maintain survival.