Miracle-dz/UniFAR-FTUs huggingface dataset:
GENETICS Genome-Wide Linkage Analysis to Identify Chromosomal Regions Affecting Phenotypic Traits in the Chicken. I. Growth and Average Daily Gain1

A genome scan was used to detect chromosomal regions and QTL that control quantitative traits of economic importance in chickens. Two unique F2 crosses generated from a commercial broiler male line and 2 genetically distinct inbred lines (Leghorn and Fayoumi) were used to identify QTL affecting BW and daily average gain traits in chickens. Body weight at 2, 4, 6, and 8 wk was measured in the 2 F2 crosses. Birds were genotyped for 269 microsatellite markers across the entire genome. Linkage distance among microsatellite markers was estimated by the CRIMAP program. The program QTL Express was used for QTL detection. Significance levels were obtained using the permutation test. For the 8 traits, a total of 18 and 13 significant QTL were detected at a 1% chromosome-wise significance level, of which 17 and 10
Shared Interest: Measuring Human-AI Alignment to Identify Recurring Patterns in Model Behavior

Saliency methods — techniques to identify the importance of input features on a model’s output — are a common step in understanding neural network behavior. However, interpreting saliency requires tedious manual inspection to identify and aggregate patterns in model behavior, resulting in ad hoc or cherry-picked analysis. To address these concerns, we present Shared Interest: metrics for comparing model reasoning (via saliency) to human reasoning (via ground truth annotations). By providing quantitative descriptors, Shared Interest enables ranking, sorting, and aggregating inputs, thereby facilitating large-scale systematic analysis of model behavior. We use Shared Interest to identify eight recurring patterns in model behavior, such as cases where contextual features or a subset of ground truth features are most important to the model. Working with representative real-world users, we show how Shared Interest can be used to decide if a model is trustworthy, uncover issues missed in manual analyses, and enable interactive probing.
TRUST AND TRUSTWORTHINESS BETWEEN COOPERATORS AND NON-COOPERATIOS IN PUBLIC GOOD PROVISION: EVIDENCE FOR AN ARTEFACTUAL FIELD EXPERIMENT IN ETHIOPIA

The standard economic theory predicts that collective action problem arises because the selfish agents have no incentive to contribute to public goods. However, as revealed by numerous empirical and experimental findings, a substantial share of mankind is willing to contribute to public goods. Ostrom (2000) revised collective action theory predicts that as time passes with proper social norm (institutions) in place, and with information about the types of the agent provided, the share of cooperators in the population will increase, and selfish agents may even disappear from the population. Cooperative agents are trusted more, and hence agents are more likely to be willing to enter in mutually beneficial bilateral exchanges with cooperative agents than with selfish ones. I test this hypothesis in a setting that let participants who are members of collaborative forest management (CFM), and nonmembers (nonCFM) to play a trust game. Using this experiment, the findings of my study support the hypothesis that higher trust is placed on the cooperators than non-cooperators. Therefore, the cooperator type receives more money, but sends and returns less to non-cooperators which allow the cooperator type to receive consistently higher payoff.
The Preparation Method of a Flexible Tactile Sensors Array for Three-Dimensional Force Measurement

This paper described a process method of flexible three-dimensional force tactile sensor array that may install in the curved surface. First,the three-dimensional force tactile sensor array was made by MEMS technology.Second,many three-dimensional force tactile sensor unit separately was integrated on the flexible PCB by flip chip technology.This process has realized the interlink of the sensor and signal processing electric circuit unit,and flexibility of the sensor array(4×4). Uses the multichannel signal elects to pass to simplify the sensor array signal processing electric circuit.The test result indicated that,the flexible three-dimensional force tactile sensor array may bending strain above 90°,the detection of three dimensional force limit achieves 0.1 N.
Observational data from uncrewed systems over Southern Great Plains

Abstract. Uncrewed Systems (UxS), including uncrewed aerial systems (UAS) and tethered balloon/kite systems (TBS), are significantly expanding observational capabilities in atmospheric science. Rapid adaptation of these platforms and the advancement of miniaturized instruments have resulted in an expanding number of datasets captured under various environmental conditions by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. In 2021, observational data collected using ARM UxS platforms, including seven TigerShark UAS flights and 133 tethered balloon system (TBS) flights, were archived by the ARM Data Center (https://adc.arm.gov/discovery/#/, last access: 11 February 2022) and made publicly available at no cost for all registered users (https://doi.org/10.5439/1846798) (Mei and Dexheimer, 2022). These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research. This paper describes the DOE UAS/TBS datasets, including information on the acquisition, collection, and quality control processes, and highlights the potential scientific contributions using UAS and TBS platforms.
Analysis of Method for TT&C Compatibility Test Between Ground Station with Satellite

There are three methods which are using in TTC compatibility test between ground station with satellite.They are the method using TTC equipments of satellite,the method using special TTC satellite simulator and using general TTC satellite simulator.The TTC compatibility test items between ground station and the geostationary communications satellite are introduced,and the composing,characters and test items of the three methods are also described.By a comparative analysis on the cost,development-time,authenticity and so on.A conclusion about the area where the three methods are appicable is drawn.
CONFETTI: Amplifying Concolic Guidance for Fuzzers

Fuzz testing (fuzzing) allows developers to detect bugs and vul-nerabilities in code by automatically generating defect-revealing inputs. Most fuzzers operate by generating inputs for applications and mutating the bytes of those inputs, guiding the fuzzing pro-cess with branch coverage feedback via instrumentation. Whitebox guidance (e.g., taint tracking or concolic execution) is sometimes in-tegrated with coverage-guided fuzzing to help cover tricky-to-reach branches that are guarded by complex conditions (so-called “magic values”). This integration typically takes the form of a targeted in-put mutation, e.g., placing particular byte values at a specific offset of some input in order to cover a branch. However, these dynamic analysis techniques are not perfect in practice, which can result in the loss of important relationships between input bytes and branch predicates, thus reducing the effective power of the technique. We introduce a new, surprisingly simple, but effective technique, global hinting, which allows the fuzzer to insert these interesting bytes not only at a targeted position, but in any position of any input. We implemented this idea in Java, creating Confetti, which uses both targeted and global hints for fuzzing. In an empirical com-parison with two baseline approaches, a state-of-the-art greybox Java fuzzer and a version of Confetti without global hinting, we found that Confetti covers more branches and finds 15 previously unreported bugs, including 9 that neither baseline could find. By conducting a post-mortem analysis of Confetti's execution, we determined that global hinting was at least as effective at revealing new coverage as traditional, targeted hinting.
A Deep Learning based Methodology for Information Extraction from Documents in Robotic Process Automation

In recent years, thanks to Optical Character Recognition techniques and technologies to deal with low scan quality and complex document structure, there has been a continuous evolution and automation of the digitization processes to allow Robotic Process Automation. In this paper we propose a methodology based both on deep learning algorithms (as generative adversarial network) and statistical tools (as the Hough transform) for the creation of a digitization system capable of managing critical issues, like low scan quality and complex structure of documents. The methodology is composed of 5 modules to manage the poor quality of scanned documents, identify the template and detect tables in documents, extract and organize the text into an easy-to-query schema and perform queries on it through search patterns. For each module diﬀerent state-of-the-art algorithms are compared and analyzed, with the aim of identifying the best solution to be adopted in an industrial environment. The implemented methodology is measured with respect to the business needs over real data by comparing the extracted information with the target value and shows performance of 90%, in terms of Gestalt Pattern Matching measure.
Stability issues in policy analysis

cu~(J·' DEPARTI-IENT OF AGRICULWRAL AND RESOURCE ECONO;VIIC~--l -DIVISION OF AGRICULWRE AND NA11JRAL RESOURCES ~IVERSITY OF CALIFORNIP< . J ~ . ,w Working Paper No. 458 STABILITY ISSUES IN POLICY ANALYSIS by Gordon C. Rausser GIANNINI FOUNDATION CO::- AGRICULTURAL ECONOMICs LIBRARY Uj~Y California Agricultural Experiment Station Giannini Foundation of Agricultural Economics January 1988
Integrating Architectures : Dovetailing Task Network and Cognitive Models

This paper describes our efforts to develop the Human Behavior Architecture (HBA), an integration of task network and cognitive modeling tools. We begin by describing the two component modeling tools we have integrated: C3TRACE, a task network modeling tool and the ACT-R cognitive architecture. Next, we describe the current state of the integration, highlighting practical aspects. We then turn to a discussion of conceptual issues that have surfaced as we put integration into practice. Finally, we discuss the benefit we see in this integration.
Applications of adaptive variable step-size algorithm in turbulence observation system

In turbulence observation system, noise signal is random and difficult to identify, which will pollute the real signal and affect the quality of the data. To eliminate the noise signal, the article puts forward a kind of adaptive variable step-size de-noising algorithm. Firstly, raw data is changed into corresponding physical parameters, and spectral analysis is used to analyze the relationship among these parameters, and then, according to the correlation to construct the variable step-size de-noising algorithm, and through error to adjust shape of the step size factor to control the optimal weight coefficient. Finally, simulation and observation data is used to verify the effectiveness of the algorithm, and Goodman’s filter algorithm is compared with the algorithm. The results show that the algorithm has higher precision and the noise is effectively reduced. c ©2016 All rights reserved.
Coupling streaming AI and HPC ensembles to achieve 100–1000× faster biomolecular simulations

Machine learning (ML)-based steering can improve the performance of ensemble-based simulations by allowing for online selection of more scientifically meaningful computations. We present DeepDriveMD, a framework for ML-driven steering of scientific simulations that we have used to achieve orders-of-magnitude improvements in molecular dynamics (MD) performance via effective coupling of ML and HPC on large parallel computers. We discuss the design of DeepDriveMD and characterize its performance. We demonstrate that DeepDriveMD can achieve between 100-1000× acceleration for protein folding simulations relative to other methods, as measured by the amount of simulated time performed, while covering the same conformational landscape as quantified by the states sampled during a simulation. Experiments are performed on leadership-class platforms on up to 1020 nodes. The results establish DeepDriveMD as a high-performance framework for ML-driven HPC simulation scenarios, that supports diverse MD simulation and ML back-ends, and which enables new scientific insights by improving the length and time scales accessible with current computing capacity.
A Monte Carlo Method for Evaluating Empirical Gyrochronology Models and Its Application to Wide Binary Benchmarks

Accurate stellar ages are essential for our understanding of the star formation history of the Milky Way and Galactic chemical evolution, as well as to constrain exoplanet formation models. Gyrochronology, a relationship between stellar rotation and age, appears to offer a reliable age indicator for main-sequence (MS) stars over the mass range of approximately 0.6–1.3 M ⊙. Those stars lose their angular momentum due to magnetic braking and as a result their rotation speeds decrease with age. Although current gyrochronology relations have been fairly well tested for young MS stars with masses greater than 1 M ⊙, primarily in young open clusters, insufficient tests exist for older and lower mass MS stars. Binary stars offer the potential to expand and fill in the range of ages and metallicity over which gyrochronology can be empirically tested. In this paper, we demonstrate a Monte Carlo approach to evaluate gyrochronology models using binary stars. As examples, we used five previously published wide binary pairs. We also demonstrate a Monte Carlo approach to assess the precision and accuracy of ages derived from each gyrochronology model. For the traditional Skumanich models, the age uncertainties are σ age/age = 15%–20% for stars with B − V = 0.65 and σ age/age = 5%–10% for stars with B − V = 1.5 and rotation period P ≤ 20 days.
Theory of defect-mediated morphogenesis

Growing experimental evidence indicates that topological defects could serve as organizing centers in the morphogenesis of tissues. Here, we provide a quantitative explanation for this phenomenon, rooted in the buckling theory of deformable active polar liquid crystals. Using a combination of linear stability analysis and computational fluid dynamics, we demonstrate that active layers, such as confined cell monolayers, are unstable to the formation of protrusions in the presence of disclinations. The instability originates from an interplay between the focusing of the elastic forces, mediated by defects, and the renormalization of the system’s surface tension by the active flow. The posttransitional regime is also characterized by several complex morphodynamical processes, such as oscillatory deformations, droplet nucleation, and active turbulence. Our findings offer an explanation of recent observations on tissue morphogenesis and shed light on the dynamics of active surfaces in general.
Models for the investigation of the results of MHD mode active control in RFX-mod

In this Ph.D. thesis we report the work performed at Consorzio RFX1 in Padua, where a large RFP device is set to study magnetically confined plasmas for thermonuclear fusion. Particular configurations of magnetic fields permit this confinement. The tokamak is been the most successful concept of toroidal machine, but alternative concepts, like reversed field pinch (RFP) and stellarator, have been developed for a commercial application (fusion power plant). All the present experiments are inductive and pulsed. ITER2 machine will work stationary and will demonstrate the scientific and practical feasibility of thermonuclear fusion. To reach this goal many questions have to be solved: the in-depth comprehension of transport mechanism for to achieve the better plasma confinement, equilibrium and stability; the crucial topic of magnetohydrodynamics (MHD) instability control (or mode control); the development of right materials for the first wall; the utilization of superconductive magnets; the problem of the plasma impurities, due to the plasma-wall interaction. Linear MHD is a fundamental model in plasma physics and in fusion research, providing basic ideas about the system stability, the dominant modes and their spatial structure. However, strong non-linear effects are also at work and the most important is the so-called dynamo effect : the RFP configuration is sustained in a steady state by the generation of a plasma selfinduced electric field. This dynamo electric field originated, in turn, from the non-linear coupling between magnetic and velocity fluctuations. There are also other interesting phenomena linked to the mode couplings. In all these cases, their exploration and the investigation of their mechanisms is an important issue in order to understand the nature of the RFP sustainment. In the last decade, several experiments carried out and theoretical studies indicate that MHD instabilities can be stabilized by active feedback. In this work we consider feedback systems for the RFP, using a reasonably realistic geometrical description of the coils. RFX is acronym for Reversed Field eXperiment. The acronym means trail or path, the way in latin. ITER is for International Tokamak Experimental Reactor.
Evaluating the population-level effects of overdose prevention sites and supervised consumption sites in British Columbia, Canada: Controlled interrupted time series

Background On 14 April 2016, British Columbia’s Provincial Medical Health Officer declared the overdose crisis a public health emergency, sanctioning the implementation of new overdose prevention sites (OPS) and supervised consumption sites (SCS) across the province. Methods We used the BC Centre for Disease Control’s Provincial Overdose Cohort of all overdose events between 1 January 2015 and 31 December 2017 to evaluate the population-level effects of OPSs and SCSs on acute health service use and mortality. We matched local health areas (LHA) that implemented any site with propensity score matched controls and conducted controlled interrupted time series analysis. Results During the study period, twenty-five OPSs and SCSs opened across fourteen of British Columbia’s 89 LHAs. Results from analysis of LHAs with matched controls (i.e. excluding Vancouver DTES) were mixed. Significant declines in reported overdose events, paramedic attendance, and emergency department visits were observed. However, there were no changes to trends in monthly hospitalization or mortality rates. Extensive sensitivity analyses found these results persisted. Conclusions We found OPSs and SCSs reduce opioid-related paramedic attendance and emergency department visit rates but no evidence that they reduce local hospitalization or mortality rates.
The Last Domicile of the Iceman from Hauslabjoch: A Geochemical Approach Using Sr, C and O Isotopes and Trace Element Signatures

Abstract We present Sr, C and O isotope ratios and quantitative ratios of trace element ratios in the rib and the femur of the Tyrolean Iceman “Otzi”. The results from the rib and the femur are compared with those obtained from pre-industrial historic human skull bone fragments collected in the late 19th century from charnel houses located on different geological backgrounds throughout North and South Tyrol. Comparison of strontium isotope data from the bone fragments locates the Iceman's domicile, during the last 5 to 10 years of his life, to the crystalline part of the Central Alps. Statistical analysis of the trace element ratios, together with oxygen isotope results, suggests that the Iceman probably spent most of his last years in southern elevated part of the Otztal. However, the results from Iceman only represent those from a single individual and are not a representative average of a group. It cannot therefore be established with absolute certainty that the original trace element signatures were conserved, especially during the first stage of mummification. Our conclusions should therefore be regarded as tentative, but nevertheless the best possible indication his domicile, and a stimulus for further research.
Sustained chemogenetic activation of locus coeruleus norepinephrine neurons promotes dopaminergic neuron survival in synucleinopathy

Dopaminergic neuron degeneration in the midbrain plays a pivotal role in motor symptoms associated with Parkinson’s disease. However, non-motor symptoms of Parkinson’s disease and post-mortem histopathology confirm dysfunction in other brain areas, including the locus coeruleus and its associated neurotransmitter norepinephrine. Here, we investigate the role of central norepinephrine-producing neurons in Parkinson’s disease by chronically stimulating catecholaminergic neurons in the locus coeruleus using chemogenetic manipulation. We show that norepinephrine neurons send complex axonal projections to the dopaminergic neurons in the substantia nigra, confirming physical communication between these regions. Furthermore, we demonstrate that increased activity of norepinephrine neurons is protective against dopaminergic neuronal depletion in human α-syn A53T missense mutation over-expressing mice and prevents motor dysfunction in these mice. Remarkably, elevated norepinephrine neurons action fails to alleviate α-synuclein aggregation and microgliosis in the substantia nigra suggesting the presence of an alternate neuroprotective mechanism. The beneficial effects of high norepinephrine neuron activity might be attributed to the action of norepinephrine on dopaminergic neurons, as recombinant norepinephrine treatment increased primary dopaminergic neuron cultures survival and neurite sprouting. Collectively, our results suggest a neuroprotective mechanism where noradrenergic neurons activity preserves the integrity of dopaminergic neurons, which prevents synucleinopathy-dependent loss of these cells.
Experimental Studies on the Effect of Gamibaegi-eum

Objective : This study was undertaken to determine whether Gamibaegi-eum (BGU) in vitro and in vivo exerts a beneficial effect against cell injury induced by reactive oxygen species (ROS) in the human intestine. Methods : Effects of BGU in vitro on cell injury were examined using Caco-2 cells, cultured human intestinal cell line. Exposure of cells to H2O2 induced increases in the loss of cell viability in a time and dose-dependent fashion. Results : BGU prevented H2O2-induced cell death and its effect was dose-dependent over a concentration range of 0.051%. H2O2-induced cell death was prevented by catalase, the hydrogen peroxide scavenger enzyme, and deferoxamine, the iron chelator. However, the potent antioxidant DPPD did not affect H2O2-induced cell death. H2O2 increased lipid peroxidation, which was inhibited by BGU and DPPD. H2O2 caused DNA damage in a dose-dependent manner, which was prevented by BGU, catalase, and deferoxamine, but not DPPD. BGU restored ATP depletion induced by H2O2. BGU inhibited generation of superoxide and H2O2 and scavenged directly H2O2. Oral administration of mepirizole in vivo at a dose of 200mg/kg resulted in ulcer lesions in the stomach and the proximal duodenum. Pretreatment of BGU(0.1%/kg, orally) and catalase (800Units/kg, i.v.) significantly decreased the size of ulcers. Mepirizole increased lipid peroxidation in the mucosa of the duodenum, suggesting an involvement of ROS. Pretreatment of BGU and catalase significantly inhibited lipid peroxidation induced by mepirizole. Morphological studies showed that mepirizole treatment causes duodenal injury and its effect is prevented by BGU. Conclusion : These results indicate that BGU exerts a protective effect against cell injury in vitro and in vivo through antioxidant action. The present study suggests that BGU may play a therapeutic role in the treatment of human gastrointestinal diseases mediated by ROS.