Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of landscape features influencing gene flow: How useful are habitat selection models?

Understanding how dispersal patterns are influenced by landscape heterogeneity is critical for modeling species connectivity. Resource selection function (RSF) models are increasingly used in landscape genetics approaches. However, because the ecological factors that drive habitat selection may be different from those influencing dispersal and gene flow, it is important to consider explicit assumptions and spatial scales of measurement. We calculated pairwise genetic distance among 301 Dall's sheep (Ovis dalli dalli) in southcentral Alaska using an intensive noninvasive sampling effort and 15 microsatellite loci. We used multiple regression of distance matrices to assess the correlation of pairwise genetic distance and landscape resistance derived from an RSF, and combinations of landscape features hypothesized to influence dispersal. Dall's sheep gene flow was positively correlated with steep slopes, moderate peak normalized difference vegetation indices (NDVI), and open land cover. Whereas RSF covariates were significant in predicting genetic distance, the RSF model itself was not significantly correlated with Dall's sheep gene flow, suggesting that certain habitat features important during summer (rugged terrain, mid‐range elevation) were not influential to effective dispersal. This work underscores that consideration of both habitat selection and landscape genetics models may be useful in developing management strategies to both meet the immediate survival of a species and allow for long‐term genetic connectivity.
NEW PHYSICS EFFECTS IN THE FLAVOR-CHANGING NEUTRAL COUPLINGS OF THE TOP QUARK

We survey the flavor-changing neutral couplings (FCNC) of the top quark predicted by some extensions of the Standard Model: THDM, SUSY, Left–Right symmetric, TC2, 331, and models with extra quarks. Since the expected sensitivity of the LHC and ILC for the tcV (V = γ, g, Z) and tcH couplings is of order of a few percent, we emphasize the importance of any new physics effect that gives a prediction for these FCNC couplings within this limit. We also review the constraints imposed on these couplings from low-energy precision measurements.
Parent-reported Language and Communication Skills at One and Two Years of Age in Relation to Otitis Media in the First Two Years of Life

Objective. As part of a study of possible effects of early life otitis media on children's development, we attempted to determine whether levels of language and communication skills at 1 and 2 years of age are associated with the cumulative duration of middle ear effusion (MEE) in the first 2 years of life. Methods. Subjects (N = 2156) were followed at one of eight study sites in the Pittsburgh area. Middle ear status was monitored closely throughout the first 2 years of life. For each child, the cumulative percentage of days with MEE was estimated based on diagnoses at visits and interpolations for intervals between visits. For each child also, 1 or both parents completed the MacArthur Communicative Development Inventory–Words and Gestures (CDI–WG) when the child was 1 year of age and the MacArthur Communicative Development Inventory–Words and Sentences (CDI–WS) when the child was 2 years of age. Results. Unadjusted correlations between scores on the CDI–WG and percentage of days with MEE in the first year of life were close to zero, and there were no statistically significant negative correlations. Unadjusted correlations between scores on the CDI–WS and the cumulative percentage of days with MEE in year 2 and in years 1 and 2 combined were generally negative and statistically significant, but the magnitudes of those correlations were no higher than 0.09. After adjustment for sociodemographic variables, only the Vocabulary Production Scale of the CDI–WS remained correlated significantly with the percentage of days with MEE, and the percentage of days with MEE accounted for only a negligible percentage of the variance in scores on this scale. Conclusions. In this diverse sample of children, parent-reported levels of language skills at 1 and 2 years of age were correlated negligibly with the cumulative percentage of days with MEE in the children's first and second years of life. otitis media, otitis media with effusion, language, communication.
Mismatch and blunt to protruding-end joining by DNA ligases.

A nuclear DNA ligase activity from immature chicken erythrocytes, and to a lesser extent T4-induced DNA ligase, can join cohesive-ends (3 and 5-nucleotides long) having one of the mismatches, A/A, T/T, C/C, G/G, at the middle position. The rate of ligation depends on the length and stability of the mispaired intermediate (G/G, T/T greater than A/A, C/C). When the non-complementary overhanging-ends are short (i.e. 1-nucleotide) both ligases catalyze the joining of the single-stranded protruding-end with a blunt-end. This reaction occurs at low but significant rates compared to blunt-end ligation. The chicken ligase has lower flush-end joining activity than T4 DNA ligase, but it is more permissive since it joins C/C or A/A mismatched-ends, whereas the prokaryotic ligase does not. Possible biological implications of the reactions are discussed. We have also found that BstEII easily cleaves at sites harboring a C/C or a G/G mismatch at the center of its recognition sequence, whereas AvaII (T/T or A/A), HinfI (G/G) and DdeI (G/G) do not.
Image Segmentation – A State-Of-Art Survey for Prediction

Image Segmentation is a technique that partitioned the input image into prerequisite semantic unique regions. Segmentation should stop as object of interest in an application is isolated. The ultimate goal is to make the image more simplified one and that to get more meaningful to analyze. Number of segmentation techniques are available but none of them satisfy the global properties and thus remain challenge for researcher. Many computer applications like Object Recognition, Automatic pictorial Pattern Recognition, Automatic Traffic control are based on this analysis. As per need of an application segmentation techniques can be selected . This survey addressed various segmentation techniques, discussed fundamental methodologies , and issues related with specific techniques. It discussed its limitations and probable solution to recover it. It also include discussion on segmentation technique based on graph partitioning which would be helpful to add intelligence for prediction. Concept of Ontology is introduced in short as technical bridge in between segmentation and image prediction.
1 Differential Dynamic Programming Approach for Robust-optimal Low-thrust Trajectory Design Considering Uncertainy

This study proposes a fast computation technique to solve robust optimal control based on two techniques: Robust Dynamic Programming [1] and Differential Dynamic Programming [2] to design a low-thrust robust optimal trajectory considering uncertainty to minimize the worst-case objective function. In recent years, low-thrust propulsion systems have been increasingly used in the interplanetary missions, because these systems have high specific impulse and can achieve large delta-V to travel far from the Earth. Due to this background, various low-thrust trajectory design methods have been developed [3]. These methods assume that the spacecraft is perfectly guided to the predesigned trajectory as planned; however, the assumption is violated in realistic operation because of various uncertainties including missed-thrust [4] (i.e. contingent coasting period due to temporary operational troubles). Because the low-thrust propulsion systems require long-time operation to achieve a certain delta-V in exchange for high specific impulse and the spacecraft always have the risk to enter the safe mode that the propulsion system is not operated, the occurrence of missed-thrust, or uncertainty, caused by operational anomaly is inevitable. Therefore, the low-thrust trajectory for actual mission must improve robustness against the uncertainties. To improve robustness of low-thrust trajectory, we conventionally impose forced coast period [4], where we force coast periods during long thrusting periods (e.g. 4 days every 6 months), and duty cycle [4] on the trajectory, where the duty cycle is defined to be the rate of time available for low-thrust propulsion system thrusting at the maximum achievable throttle level in planned thrusting period. The experienced specialists have empirically determined the forced coast period and the duty cycle on a regular basis all along the trajectory; however this empirical method does not give robust optimal solution. Robust optimal solution is the optimal solution within the solutions that have certain robustness, and it is obtained by minimizing the worst-case objective function. In other words, the conventional solution is unnecessarily too conservative and it has room for improving the optimality, shown in Fig.1. Most of the previous works to design robust low-thrust trajectory considering uncertainty (especially missed-thrust) have been based on sampling methods (i.e. MonteCarlo method)[4][5]; however it is not only a large burden on the computation because of large number of samples but also difficult to treat infeasible solutions in optimization. To overcome this difficulty, Olympio[6] has suggest the sophisticated method by two-stage stochastic programming with indirect method; however this method is only focused on one temporary engine failure (because of twostage) that is not proved as the worst case. Therefore, we need to invent an innovative Fig. 1 Comparison of robust optimal solution and conventional solution with respect to robustness and optimality
Evolution of trading rules for the FX market or How to make money out of GP

In this work we apply genetic programming [1] to the discovery of pro table trading rules for the foreign exchange market. Technical trading rules are quite commonly used by traders in the capital markets [2], and have been under much discussion, since their use contradicts the commonly accepted e cient market hypothesis (e.g., [3]). In the academic literature, technical analysis has often been dismissed as futile, but a number of recent more careful statistical studies have shown
Accurate off-line phase classification for HW/SW co-designed processors

Evaluation techniques in microprocessor design are mostly based on simulating selected application's samples using a cycle-accurate simulator. These samples usually correspond to different phases of the application stream. To identify these phases, relevant high-level application statistics are collected and clustered using a process named "Off-Line Phase Classification". The purpose of phase classification is to reduce the number of samples that need to be simulated with the minimum loss in accuracy (compared to simulating the complete set of samples). Unfortunately, when directly applied to HW/SW co-designed processors the traditional phase classifications do not provide a good trade-off between accuracy and the number of samples. As an example, according to our experimental results, to achieve a 4% error (compared to simulating all the samples) one needs to simulate 2.5X more samples for the case of HW/SW co-designed processors compared to what is necessary for HW-only processors. In this paper, we propose a novel off-line phase classification scheme called TOL Description Vector (TDV), which is suitable for HW/SW co-designed processors. TDV targets at estimating the TOL particularities and on average gives significantly better accuracy than traditional phase classification for any number of selected samples. For instance, TDV reaches the average error of 3% with 3X less samples than traditional classification. These benefits apply for different TOL and microarchitecture configurations.
Journal of Work and Organizational Psychology Original the Work Design Questionnaire: Spanish Version and Validation Validación Espã Nola Del Work Design Questionnaire

The purpose of this study is to validate the Spanish version of the Work Design Questionnaire (WDQ; Morgeson & Humphrey, 2006). Employees from three Colombian samples completed the questionnaire (N = 831). Confirmatory factor analyses revealed a 21-factor structure (␹ 2 /df ratio = 2.40, SRMR = .06, RMSEA = .04, CFI = .90) with adequate levels of convergent and discriminant validity. Additional support for construct validity was found from significant differences among different occupational groups (professional and nonprofessional, health-focused, commercial, and manufacturing workers). Furthermore, knowledge, social, and work context characteristics showed incremental validity over task characteristics on job satisfaction and perceived performance. Possible interpretations of these relationships are offered. It is concluded that the study provides evidence for the validity of a Spanish version of the scale, and presents further support for the generalization of the 21-factor structure of work design characteristics in different cultural settings. been a demand, from both scientists and practitioners, to have a valid and reliable instrument assessing work characteristics in organizational settings. During the last 30 years questionnaires such as the 1985) have been developed to assess work design characteristics ; however, these instruments generally have suffered from two
Substrate coupling modeling in integrated circuits using analytical Green's function

The aim of this paper is the development of two different analytical Green's functions for the modeling of the substrate electrical coupling in integrated circuits. The first procedure solves directly the Poisson's equation of the substrate as a two-layer problem using the adequate boundary conditions. An accurate and stable expression is obtained which is compared to other numerical methods. The second one is an heuristic approach that divides the actual substrate in two single one-layer substrates; although the accuracy is reduced, the computation of the coupling is faster. Both models are applied to the computation of the capacitance between two contact patches.
Gaze-Based Onlooker Integration: Exploring the In-Between of Active Player and Passive Spectator in Co-Located Gaming

In co-located gaming, a player is often watched by another person who has no direct interaction with the game. For such a potential onlooker, the game setting is mainly experienced with ones eyes by looking at what happens on the screen. An integration of an onlooker's gaze into the game could potentially improve the game experience of player and onlooker. In this paper we report a study based on an interaction concept that uses the gaze of a second observing person during a co-located gaming situation as an input modality to assist the player. Our study investigates the effects of different levels of gaze-based onlooker integration and their influence on the player's and the onlooker's experience. With our research we want to address the "in-between" design space of being an active player or a passive spectator. Our findings show that gaze-based onlooker integration can address this "in-between", and change the game experience for both player and onlooker for the better.
Context browser: ontology based navigation in information spaces

For people working in knowledge intensive organisations, information about specific projects, documents, etc. are important for performing an ordinary workday. Different kinds of problems, large or small, complex or simple, continually arise and need to be dealt with. Finding information or people with specific knowledge to solve the problem may be of crucial importance. Today, a number of technologies exist facilitating this, but they are either not sophisticated enough, i.e., not providing results detailed enough, or too complicated to prepare for, e.g., tagging large amounts of information. As an alternative, we propose using ontologies to facilitate free-text searches. From an ontology, a menu-like interface can be automatically generated. Such a menu can replace searching with navigation. To demonstrate our ideas, we present Context Browser, a tool providing ontology based navigation in structured and unstructured information spaces.
Addressing barriers to implementing inclusive education in the Pacific

ABSTRACT Countries of the Pacific region are currently undergoing significant reforms. While disability inclusive education has been identified as a regional priority by all member nations, implementing inclusive education in the countries of the region can be quite challenging as many barriers continue to hamper the progress of the countries. Unless the barriers are identified and systematically addressed, it is unlikely that the countries will be able to implement a robust and holistic inclusive education strategy. In this paper, we present possible ways in which the countries of the Pacific could make significant progress in implementing a sustainable inclusive education strategy. We used a collaborative approach of co-examining potential barriers that are likely to impede the growth of countries in implementing a comprehensive inclusive education plan of action. We then identified possible strategies that are likely to result in an improved and perhaps more culturally responsive implementation of inclusive education in the Pacific. The most significant barriers identified by the members included: inadequate teacher preparation, stigma and negative attitudes towards people with disabilities, and limited engagement with the local leaders and key stakeholders. Possible strategies for addressing the barriers are outlined and discussed with possible implications for local, regional, and international researchers and policy makers.
Reinforcement learning approach to generate goal-directed locomotion of a snake-like robot with screw-drive units

In this paper we apply a policy improvement algorithm called Policy Improvement with Path Integrals (PI2) to generate goal-directed locomotion of a complex snake-like robot with screw-drive units. PI2 is numerically simple and has an ability to deal with high dimensional systems. Here, this approach is used to find proper locomotion control parameters, like joint angles and screw-drive velocities, of the robot. The learning process was achieved using a simulated robot and the learned parameters were successfully transferred to the real one. As a result the robot can locomote toward a given goal.
An optimization model for metabolic pathways

MOTIVATION Different mathematical methods have emerged in the post-genomic era to determine metabolic pathways. These methods can be divided into stoichiometric methods and path finding methods. In this paper we detail a novel optimization model, based upon integer linear programming, to determine metabolic pathways. Our model links reaction stoichiometry with path finding in a single approach. We test the ability of our model to determine 40 annotated Escherichia coli metabolic pathways. We show that our model is able to determine 36 of these 40 pathways in a computationally effective manner.
Outage performance analysis of dual-hop AF relaying system with underlay spectrum sharing

In this paper, we investigate the outage performance of underlay cognitive dual-hop relaying systems under the effect of using statistical instead of instantaneous information of the interference links (from the secondary source and relay to the primary user) and the first relaying link (from the secondary source to relay) to calculate transmit power and amplifying gain for secondary network. We derive the closed-form of outage probability expression for some considered cases and validate them through simulation results. It is numerically demonstrated that using instantaneous information of the first relaying link for calculating the amplifying gain plays a vital role while using interference link statistical information does not strongly affect the system performance. Furthermore, this work shows that the fixed gain specified by averaging the individual random components of the variable gain is not applicable in underlay cognitive dual-hop relaying systems.
An Effective Method of Discovering Target Groups on Social Networking Sites

With the popularity of social networking sites (SNS) in this era of Web 2.0, increasingly more users are contributing their opinions about products and organizations. These online comments often have direct influence on consumers’ buying decisions and the public’s impressions of enterprises. As a result, enterprises have begun to use SNS to conduct targeted marking and reputation management. As indicated from recent marketing research, the joint influence power of a small group of active users could have considerable impact on consumers’ buying decisions and the public’s perception of the enterprises. To help enterprises conduct cost-effective targeted marketing and reputation management, this paper illustrates a novel methodology that can effectively discover the most influential users from SNS. In particular, the general methodology of mining the influence network from SNS and the computational models of mathematical programming for discovering the user groups with the maximal joint influence power are proposed. The empirical evaluation with real data extracted from SNS shows that the proposed method can effectively identify the most influential groups when compared to the benchmark methods. This study opens the door to effectively conducting targeted marketing and enterprise reputation management on SNS.
Optimum Copper Stabilizer Thickness for Symmetric Tape Round (STAR) REBCO Wires With Superior Mechanical Properties for Accelerator Magnet Applications

Symmetric Tape Round (STAR) wires are only 1.6–1.9 mm in diameter and are made by winding 2.5-mm-wide REBCO tapes on an AWG 18 (1.02-mm diameter) copper wire former. Such ultra-small diameter wires are possible by the use of symmetric tapes where the REBCO film is positioned at the geometric center, close to the neutral axis. Such symmetric tape architecture is achieved by a strategic selection of the thickness of the copper stabilizer to match the thickness of the Hastelloy substrate. The substrate itself is made thin, to enable good tolerance to bend strain. The optimized STAR wire architecture is found to be mechanically robust and retain nearly 98% of its critical current of over 500 A at 77 K, self-field even when bent to a small radius of 15 mm. The superior bend strain tolerance of STAR REBCO wires make them suitable for use in canted cosine theta coils for future compact accelerator magnet applications.
Research and Application of Data Mining in Traditional Chinese Medical Clinic Diagnosis

In this paper, a new data-mining algorithm based on Bayesian network was proposed and applied in traditional Chinese medical clinical diagnosis for coronary heart disease (CHD). With the relative factors of the differentiation for traditional Chinese medical symptoms the gain information algorithm is used to select the attributes of the differentiation. The experiment with the data from the database of electronic patient cases shows that the Bayesian algorithm has good classification capability in traditional Chinese medical clinical diagnosis