Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Genomics Uncovers Unique Gene Turnover and Evolutionary Rates in a Gene Family Involved in the Detection of Insect Cuticular Pheromones

Chemoreception is an essential process for the survival and reproduction of animals. Many of the proteins responsible for recognizing and transmitting chemical stimuli in insects are encoded by genes that are members of moderately sized multigene families. The members of the CheB family are specialized in gustatory-mediated detection of long-chain hydrocarbon pheromones in Drosophila melanogaster and play a central role in triggering and modulating mating behavior in this species. Here, we present a comprehensive comparative genomic analysis of the CheB family across 12 species of the Drosophila genus. We have identified a total of 102 new CheB genes in the genomes of these species, including a functionally divergent member previously uncharacterized in D. melanogaster. We found that, despite its relatively small repertory size, the CheB family has undergone multiple gain and loss events and various episodes of diversifying selection during the divergence of the surveyed species. Present estimates of gene turnover and coding sequence substitution rates show that this family is evolving faster than any known Drosophila chemosensory family. To date, only other insect gustatory-related genes among these families had shown evolutionary dynamics close to those observed in CheBs. Our findings reveal the high adaptive potential of molecular components of the gustatory system in insects and anticipate a key role of genes involved in this sensory modality in species adaptation and diversification.
Effects of prolonged drought on the anatomy of sun and shade needles in young Norway spruce trees

Abstract Predicted increases in the frequency and duration of drought are expected to negatively affect tree vitality, but we know little about how water shortage will influence needle anatomy and thereby the trees’ photosynthetic and hydraulic capacity. In this study, we evaluated anatomical changes in sun and shade needles of 20‐year‐old Norway spruce trees exposed to artificial drought stress. Canopy position was found to be important for needle structure, as sun needles had significantly higher values than shade needles for all anatomical traits (i.e., cross‐sectional needle area, number of tracheids in needle, needle hydraulic conductivity, and tracheid lumen area), except proportion of xylem area per cross‐sectional needle area. In sun needles, drought reduced all trait values by 10–40%, whereas in shade needles, only tracheid maximum diameter was reduced by drought. Due to the relatively weaker response of shade needles than sun needles in drought‐stressed trees, the difference between the two needle types was reduced by 25% in the drought‐stressed trees compared to the control trees. The observed changes in needle anatomy provide new understanding of how Norway spruce adapts to drought stress and may improve predictions of how forests will respond to global climate change.
ANNOT: Automated Electricity Data Annotation Using Wireless Sensor Networks

Recent advances in low-power wireless networking have enabled remote and nonintrusive access to households' electric meter readings, allowing direct real-time feedback on electricity consumption to home owners and energy providers. Fine-grained electricity billing based on appliance power load monitoring has been investigated for more than two decades, but has not yet witnessed wide commercial acceptance. In this paper, we argue that the required human supervision for profiling and calibrating appliance load monitoring systems is a key reason preventing large-scale commercial roll-outs. We propose ANNOT, a system to automate electricity data annotation leveraging cheap wireless sensor nodes. Characteristic sensory stimuli captured by sensor nodes placed next to appliances are translated into appliance operating state and correlated to the electricity data, autonomously generating the annotation of electricity data with appliance activity. The system is able to facilitate the acquisition of appliance signatures, training data and validate the monitoring output. We validate the concept by integrating the automated annotation system to the RECAP appliance load monitoring system.
Enhanced Sensitivity of Gas Sensor Based on Poly(3-hexylthiophene) Thin-Film Transistors for Disease Diagnosis and Environment Monitoring

Electronic devices based on organic thin-film transistors (OTFT) have the potential to supply the demand for portable and low-cost gadgets, mainly as sensors for in situ disease diagnosis and environment monitoring. For that reason, poly(3-hexylthiophene) (P3HT) as the active layer in the widely-used bottom-gate/bottom-contact OTFT structure was deposited over highly-doped silicon substrates covered with thermally-grown oxide to detect vapor-phase compounds. A ten-fold organochloride and ammonia sensitivity compared to bare sensors corroborated the application of this semiconducting polymer in sensors. Furthermore, P3HT TFTs presented approximately three-order higher normalized sensitivity than any chemical sensor addressed herein. The results demonstrate that while TFTs respond linearly at the lowest concentration values herein, chemical sensors present such an operating regime mostly above 2000 ppm. Simultaneous alteration of charge carrier mobility and threshold voltage is responsible for pushing the detection limit down to units of ppm of ammonia, as well as tens of ppm of alcohol or ketones. Nevertheless, P3HT transistors and chemical sensors could compose an electronic nose operated at room temperature for a wide range concentration evaluation (1–10,000 ppm) of gaseous analytes. Targeted analytes include not only biomarkers for diseases, such as uremia, cirrhosis, lung cancer and diabetes, but also gases for environment monitoring in food, cosmetic and microelectronics industries.
“WHAT ARE WE THINKING?” VERSUS “WHAT ARE THEY THINKING?”:SOCIAL CATEGORIZATION ANDTHE INTRACULTURAL ADVANTAGE IN MENTAL STATE DECODING

The majority of social communication is conveyed through nonverbal behavior. Accordingly, nonverbal sensitivity is necessary for smooth communication and social adaptability. Interestingly, basic emotion perception has largely been shown to be universal across cultures, though small intracultural advantages have also been documented. Two theories may help explain these advantages. First, nonverbal behavior may carry with it cultural dialects, or small, physical differences in the expression of emotions and mental states that vary from one culture to the next that, coupled with culturally defined perceptual attunements to such features, may facilitate accurate decoding of sameversus other-culture members. Second, social categorization, the tendency to allocate more attentional resources to the processing of ingroup targets than to outgroup targets, may influence the ability to properly process emotional or mental state expressions. The present studies examine the latter route. It was found that, under certain conditions, the relative speed of categorization of a target as an outgroup versus an ingroup member was predictive of an ingroup advantage in mental state decoding. Methodological constraints and potential implications of this effect are discussed.
Gana: A novel low-cost conflict-free NoC architecture

Similar to off-chip networks, current NoC architectures are based on the store and forward of uncoordinated end-to-end packet transmissions through autonomous buffered routers. However, the monolithic nature and the small physical dimensions of on chip networks open up the opportunity for much more tightly controlled architectures. We present GANA, a new Global Arbiter NoC Architecture. In GANA, the transmission of end-to-end data is timed by a global arbiter in a way that avoids any queuing in the network. The arbitration takes into account the complete transfer of the end-to-end packets through the entire network path, avoiding any intermediate queuing and hop-by-hop packet arbitration. Consequently, buffers and arbiters are no longer required in the routers, resulting in smaller area and low power consumption. It is demonstrated through detailed design and synthesis that the additional area of the central arbiter and the control path are negligible in comparison to the provided area saving. For example, an 8× 8 GANA consumes only 16% of the area of an equivalent autonomous NoC while providing a better end-to-end throughput. The end-to-end performance of GANA at high network loads is typically much better than in a distributed-control NOC, because resource contention and queuing in the network are avoided. This comes at the cost of a few percentage increase in latency at light loads due to the additional arbitration phase. GANA architecture combines the inherent benefits of a network (parallelism and spatial reuse of links) with the inherent benefits of high integration (global view of the system state, central control, and synchronization). The scalability of GANA is evaluated analytically, showing that it can be superior to fully-distributed networks in systems up to a size of about 100 modules manufactured in 45nm technology, which can be used today as well as in the foreseeable future.
Inferential Theory for Factor Models of Large Dimensions

This paper develops an inferential theory for factor models of large dimensions. The principal components estimator is considered because it is easy to compute and is asymptotically equivalent to the maximum likelihood estimator (if normality is assumed). We derive the rate of convergence and the limiting distributions of the estimated factors, factor loadings, and common components. The theory is developed within the framework of large cross sections ("N") and a large time dimension ("T"), to which classical factor analysis does not apply.We show that the estimated common components are asymptotically normal with a convergence rate equal to the minimum of the square roots of "N" and "T". The estimated factors and their loadings are generally normal, although not always so. The convergence rate of the estimated factors and factor loadings can be faster than that of the estimated common components. These results are obtained under general conditions that allow for correlations and heteroskedasticities in both dimensions. Stronger results are obtained when the idiosyncratic errors are serially uncorrelated and homoskedastic. A necessary and sufficient condition for consistency is derived for large "N" but fixed "T". Copyright The Econometric Society 2003.
The Effects of Organizational Citizenship Behaviors on Enterprise Resource Planning System in Telecommunication Company of Iran

Purpose – The purpose of this paper is to examine the effects of organizational citizenship behavior on enterprise resource planning system in Telecommunication Company of Iran. Design/methodology/approach – The papers develops a research model based on current literature and then test this model in Telecommunication Company. Statistics society consists of 202 experts include personnel affairs and welfare and domestic payments department, deputy of personnel affair, and department of organization and methods. The sample size provided based on "CohanMorganKorjsay" is 202 persons which has been determined with descriptive methods. To analyze the statistical data, descriptive statistics techniques (including: mean, standard deviation) and inferential (Kolmogorov-Smirnov's Test, Structural Equation Modeling) have been used. Findings – The results indicate that we found that there are positive effects between organizational citizenship behavior and enterprise resource planning system. Research limitations/implications – This study could benefit from a large sample from public sector and replication in more organizations. Practical implications – The paper offers practical suggestions to the public sector and management in general on how to manage the organizational citizenship behavior effects on enterprise resource planning system. Originality/value – This paper has tried to provide an inclusive understanding about the effects of organizational citizenship behavior on enterprise resource planning system in Telecommunication Company of Iran. Since there was a lack of such research in an Iranian context, this paper can provide theoretical basis for future researches as well as practical implications for managers and the professionals. Keyword: Organizational Citizenship Behavior, Enterprise Resource Planning, Iran.
General relativistic magnetohydrodynamic simulations of monopole magnetospheres of black holes

ABSTRACT In this paper we report the results of the ﬁrst ever time-dependent general rela-tivistic magnetohydrodynamic simulations of the magnetically dominated monopolemagnetospheres of black holes. It is found that the numerical solution evolves towardsa stable steady-state solution which is very close to the corresponding force-free solu-tion found by Blandford and Znajek. Contrary to the recent claims, the particle inertiadoes not become dynamically important near the event horizon and the force-free ap-proximation provides a proper framework for magnetically dominated magnetospheresof black holes. For the ﬁrst time, our numerical simulations show the development ofan ultra-relativistic particle wind from a rotating black hole. However, the ﬂow re-mains Poynting dominated all the way up to the fast critical point. This suggests thatthe details of the so-called “astrophysical load”, where the electromagnetic energy istransferred to particles, may have no eﬀect on the eﬃciency of the Blandford-Znajekmechanism.Key words: black hole physics – magnetic ﬁelds – methods:numerical.
Attitudinal Model for Technology Acceptance : A Study of Self-Service Technologies in Banks

Introduction The concept of Technology Acceptance has been taken from the studies on attitude formation towards technology and its acceptance. Technology acceptance means how users come to accept and use a technology. There are a number of factors on which use of a new technology by any user depends. Based on research on information Technology (IT) acceptance, many such models have been studied which propose different factors of acceptance determinants. Present study reviews Acceptance literature and based on this Attitudinal Model for Technology Acceptance: A Study of Self-Service Technologies in Banks
Community Detection in Networks using Graph Distance

The study of networks has received increased attention recently not only from the social sciences and statistics but also from physicists, computer scientists and mathematicians. One of the principal problem in networks is community detection. Many algorithms have been proposed for community finding but most of them do not have have theoretical guarantee for sparse networks and networks close to the phase transition boundary proposed by physicists. There are some exceptions but all have some incomplete theoretical basis. Here we propose an algorithm based on the graph distance of vertices in the network. We give theoretical guarantees that our method works in identifying communities for block models and can be extended for degree-corrected block models and block models with the number of communities growing with number of vertices. Despite favorable simulation results, we are not yet able to conclude that our method is satisfactory for worst possible case. We illustrate on a network of political blogs, Facebook networks and some other networks.
Random disease on the square grid

We introduce some generalizations of a nice combinatorial problem, the central notion of which is the so-called Disease Process. Let us color independently each square of an n×n chessboard black with a probability p(n), this is a random initial configuration of our process. Then we have a deterministic painting or expansion rule, and the question is the behaviour of the disease process determined by this rule of spreading. In particular, how large p(n) must be for painting the whole chessboard black? The main result of this paper is the almost exact determination of the threshold function in the fundamental case of this Random Disease Problem. Further investigations are involved about the general randomized and deterministic cases.
On using the auditory image model and invariant-integration for noise robust automatic speech recognition

Commonly used feature extraction methods for automatic speech recognition (ASR) incorporate only rudimentary psychoacoustic findings. Several works showed that a physiologically closer auditory processing during the feature extraction stage can enhance the robustness of an ASR system in noisy environments. The “auditory image model” (AIM) is such a more sophisticated computational model. In this work we show how invariant integration can be applied in the feature space given by the AIM, and we analyze the performance of the resulting features under noisy conditions on the Aurora-2 task. Furthermore, we show that previously presented features based on power-normalization and invariant integration benefit from the AIM-based integration features when the feature vectors are combined with each other.
Nonparametric Estimation of Regression Functions in the Presence of Irrelevant Regressors

In this paper we consider a nonparametric regression model that admits a mix of continuous and discrete regressors, some of which may in fact be redundant (that is, irrelevant). We show that, asymptotically, a data-driven least squares cross-validation method can remove irrelevant regressors. Simulations reveal that this automatic dimensionality reduction feature is very effective in finite-sample settings.
Facebook to facilitate instructor roles in course-related online interaction: a pilot study

The popularity of Facebook as the most used platform among university youth made it an acceptable platform for professional purposes. The use of Facebook for educational purpose is becoming more accepted to facilitate and ease online interaction with the learning participants. The purpose of this study is to investigate students’ expectations towards the instructor role in learning interaction through Facebook and its correlation with students’ academic performance. Quantitative data was collected from the respondents through survey method of data collection. The findings of the study reveal that students have positive expectations of instructor role on Facebook interaction. Additionally, the findings reveal that there are a correlation between instructor role of facilitating discourse and direct instruction with students’ academic performance.
Understanding Socialization Efficacy and Loneliness of Baby Boomers through Facebook

Understanding Socialization Efficacy and Loneliness of Baby Boomers through Facebook by Lindsay E. Ballinger MS, Walden University, 2015 MA, Texas Wesleyan University, 2007 BA, University of Texas at Dallas, 2004 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Psychology Walden University February 2018 Abstract Baby boomers are the largest age cohort in the United States, making up approximately 20% of the population. This cohort is faced with global problems that contribute to perceived loneliness and a lack of socialization. Additionally, baby boomers have an increased online presence on Facebook (FB), yet little is known about this age group and FB use. This research study addressed this issue with an examination of the relationshipsBaby boomers are the largest age cohort in the United States, making up approximately 20% of the population. This cohort is faced with global problems that contribute to perceived loneliness and a lack of socialization. Additionally, baby boomers have an increased online presence on Facebook (FB), yet little is known about this age group and FB use. This research study addressed this issue with an examination of the relationships between overall perceived loneliness, socialization efficacy, and FB use. The theoretical framework that guided this study was Bandura’s social learning theory, which was used to examine the effects of social reinforcement. Participants, those born between 1946 and 1964, (n = 97) were asked to share 2 months of FB activity, including the number of FB friends, number of postings, types of postings, quotes included, status updates, articles reposted, and whether friends were tagged in their posts. The FB variables were correlated with perceived loneliness, as measured by the Revised UCLA Loneliness Scale, and socialization efficacy, as measured by the Social Skill Scale, through a stepwise multiple regression analysis. The findings did not yield any statistically significant relationships between the FB variables and loneliness or socialization efficacy among baby boomers. These findings imply that other factors not studied here are promoting the increase in baby boomer FB use. The social change implications include mental health clinicians having a deeper knowledge base of baby boomers’ FB use and an accurate portrayal of this cohort for increased treatment effectiveness, as baby boomers are portrayed as being lonely, isolated, and technologically challenged, which was not empirically supported in this study. Understanding Socialization Efficacy and Loneliness of Baby Boomers through Facebook by Lindsay E. Ballinger MS, Walden University, 2015 MA, Texas Wesleyan University, 2007 BA, University of Texas at Dallas, 2004 Doctoral Study Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Psychology
Distributed resolution of network congestion and potential deadlock using reservation-based scheduling

Efficient and reliable communication is essential for achieving high performance in a networked computing environment. Finite network resources bring about unavoidable competition among in-flight network packets, resulting in network congestion and, possibly, deadlock. Many techniques have been proposed to improve network performance by efficiently handling network congestion and potential deadlock. However, none of them provide an efficient way of accelerating the movement of network packets in congestion toward their destinations. In this paper, we propose a new mechanism for detecting and resolving network congestion and potential deadlocks. The proposed mechanism is based on efficiently tracking paths of congestion and increasing the scheduling priority of packets along those paths. This acts to throttle other packets trying to enter those congested regions - in effect, locking out packets from congested regions until congestion has had the opportunity to disperse. Simulation results show that the proposed technique effectively disperses network congestion and is also applicable in helping to resolve potential deadlock.