Miracle-dz/UniFAR-FTUs huggingface dataset:
UV-B Signaling Pathways with Different Fluence-Rate Response Profiles Are Distinguished in Mature Arabidopsis Leaf Tissue by Requirement for UVR8, HY5, and HYH1[W][OA]

UV-B signaling is an important but poorly understood aspect of light responsiveness in plants. Arabidopsis (Arabidopsis thaliana) UV RESISTANCE LOCUS8 (UVR8) is a recently identified UV-B-specific signaling component that regulates UV-protective responses. Using the uvr8 mutant, we defined genetically distinct UVR8-dependent and UVR8-independent pathways that stimulate different sets of genes in mature Arabidopsis leaf tissue. Both pathways operate at 1 μmol m−2 s−1 UV-B and above, but the UVR8-dependent pathway is able to stimulate UV-protective genes even in response to 0.1 μmol m−2 s−1 UV-B. Both pathways function in mutants lacking phytochromes, cryptochromes, or phototropins. Genes encoding the ELONGATED HYPOCOTYL5 (HY5) and HY5 HOMOLOG (HYH) transcription factors are induced at low UV-B fluence rates (0.1 μmol m−2 s−1). Experiments with hy5 and hyh mutants reveal that both these factors mediate responses of the UVR8-dependent pathway, acting with partial or complete redundancy to stimulate expression of particular genes. Furthermore, evidence is presented that all UVR8 pathway genes are likely to be regulated by HY5/HYH and that these transcription factors do not mediate UV-B responses independent of UVR8. Finally, we highlight the functions of HY5 and HYH in UV protection and show that HY5 plays the more critical role. This research provides evidence that, in UV-B signaling, UVR8, HY5, and HYH act together in a photoregulatory pathway and demonstrates a new role for HYH in UV-B responses.
The University as Center and Periphery

This article1 concerns complexities and dilemmas in higher education. It is specifically concerned with the relationship between universities in the industrialized countries and those in the Third World. An effort is made to understand how universities located in countries at very different levels of economic and technological development relate to one another in an international knowledge system. Universities function in several different contexts at the same time. They are rooted in their own cultures and are affected by national realities. They are also parts of an international knowledge system. They are producers and disseminators of knowledge in their own nations, playing increasingly important roles in technologically developing societies. They also interact with institutions and ideas from abroad, because knowledge has no national boundaries.
Managing the 802.11 Energy/Performance Tradeoff with Machine Learning

This paper addresses the problem of managing the tradeoff between energy consumption and performance in wireless devices implementing the IEEE 802.11 standard [1]. To save energy, the 802.11 specification proposes a power-saving mode (PSM), where a device can sleep to save energy, periodically waking up to receive packets from a neighbor (e.g., an access point) that may have buffered packets for the sleeping device. Previous work has shown that a fixed polling time for waking up degrades the performance of Web transfers [2], because network activity is bursty and time-varying. We apply a new online machine learning algorithm to this problem and show, using ns-2 simulation and trace analysis, that it is able to adapt well to network activity. The learning process makes no assumptions about the underlying network activity being stationary or even Markov. Our learning power-saving algorithm, LPSM, guides the learning using a “loss function” that combines the increased latency from potentially sleeping too long and the wasted use of energy in waking up too soon. In our ns-2 simulations, LPSM saved 7%-20% more energy than 802.11 in powersaving mode, with an associated increase in average latency by a factor of 1.02, and not more than 1.2. LPSM is straightforward to implement within the 802.11 PSM framework.
A system for creating virtual reality content from make-believe games

Pretend play is a storytelling technique, naturally used from very young ages, which relies on object substitution to represent the characters of the imagined story. We propose a system which assists the storyteller by generating a virtualized story from a recorded dialogue performed with 3D printed figurines. We capture the gestures and facial expressions of the storyteller using Kinect cameras and IMU sensors and transfer them to their virtual counterparts in the story-world. As a proof-of-concept, we demonstrate our system with an improvised story involving a prince and a witch, which was successfully recorded and transferred into 3D animation.
Interference Pricing for SINR-Based Random Access Game

In this paper, we study the problem of random access with interference pricing in wireless ad hoc networks using non-cooperative game theory. While most of the previous works in random access games are based on the protocol model, we analyze the game under the more accurate signal-to-interference-plus-noise-ratio (SINR) model. First, under the setting with fixed interference linear pricing, we characterize the existence of the Nash equilibrium (NE) in the random access game. In particular, when the utility functions of all the players satisfy a risk aversion condition, we show that the game is a S-modular game and characterize the convergence of the strategy profile to the NE. Then, under the setting with adaptive interference linear pricing, we propose an iterative algorithm that aims to solve the network utility maximization (NUM) problem. Convergence of the solution to a Karush-Kuhn-Tucker (KKT) point of the NUM problem is studied. It can be shown that the solution obtained under the protocol model may result in starvation for some users due to the inaccurate interference pricing. Simulation results show that our proposed algorithm based on the SINR model achieves a higher average utility than the algorithm based on the protocol model and a carrier sense multiple access (CSMA) scheme implemented in a slotted time system.
Poor Long-Term Blood Pressure Control After Intracerebral Hemorrhage

Background and Purpose— Hypertension is the most important risk factor associated with intracerebral hemorrhage. We explored racial differences in blood pressure (BP) control after intracerebral hemorrhage and assessed predictors of BP control at presentation, 30 days, and 1 year in a prospective cohort study. Methods— Subjects with spontaneous intracerebral hemorrhage were identified from the DiffErenCes in the Imaging of Primary Hemorrhage based on Ethnicity or Race (DECIPHER) Project. BP was compared by race at each time point. Multivariable linear regression was used to determine predictors of presenting mean arterial pressure, and longitudinal linear regression was used to assess predictors of mean arterial pressure at follow-up. Results— A total of 162 patients were included (mean age, 59 years; 53% male; 77% black). Mean arterial pressure at presentation was 9.6 mm Hg higher in blacks than whites despite adjustment for confounders (P=0.065). Fewer than 20% of patients had normal BP (<120/80 mm Hg) at 30 days or 1 year. Although there was no difference at 30 days (P=0.331), blacks were more likely than whites to have Stage I/II hypertension at 1 year (P=0.036). Factors associated with lower mean arterial pressure at follow-up in multivariable analysis were being married at baseline (P=0.032) and living in a facility (versus personal residence) at the time of BP measurement (P=0.023). Conclusions— Long-term BP control is inadequate in patients after intracerebral hemorrhage, particularly in blacks. Further studies are needed to understand the role of social support and barriers to control to identify optimal approaches to improve BP in this high-risk population.
Robust variable length data classification with extended sequential fuzzy indexing tables

Recurrent Neural Networks are widely used tools for the classification of variable length data. However, their training is generally a very time-consuming task, especially for problems with high dimensions. The classification method proposed in this paper aims to provide a fast and simple alternative. Extended Sequential Fuzzy Indexing Tables are following the principle behind lookup table classifiers in that they realize an input-output association by mapping the problem space using arrays. The proposed network achieves this by breaking the multi-dimensional problem space down to a sequence of combinations, resulting in a flexible architecture that can work well with varying length data.
Theory in North American Information Systems Research: A Culturomic Analysis

Since its inception, North American information systems (IS) research has relied on a broad and varied collection of theories. The core of this theoretical landscape is an important determinant of the IS research community’s identity, and, as such, researchers have discussed it extensively in recent years. Nevertheless, we know few concrete facts about the composition, consistency, or evolution of this theoretical core over time. Using a set of 318 theories in conjunction with n-gram analyses, we address these issues empirically by computationally analyzing the complete text of every research paper published in three leading North American IS journals over a 24-year period. In examining these 2,215 papers and more than 3.54 billion n-gram records, we identify the theories that constitute the overall core of North American IS research and provide insights into the evolution of that core. We further identify and quantify the nature of theoretical pluralism in North American IS research and examine the evolution of the theoretical density of IS research studies over time. Finally, our results shed light on the patterns of theory co-occurrence in North American IS research studies and demonstrate how such information can facilitate increasingly imperative efforts aimed at theory consolidation and generalization.
Transmission of chosen transform coefficients of normalized cardiac beats for compression

A new technique for ECG compression is presented. Each delineated ECG beat is period normalized by multirate processing and then amplitude normalized. The discrete wavelet transform (DWT), based on Daubechies-4 basis functions is applied on these normalized beats, after shifting each of them to the origin. The concatenation of the ordered DWT coefficients of these beats is a near-cyclostationary signal. An algorithm is proposed to select a set of common positions of the significant coefficients to be retained from each beat. Linear prediction is then applied to predict only these DWT coefficients of the current beat from the corresponding coefficients of a certain number of previous beats. Transmitting only the residuals of selected coefficients improves the compression. A significant advantage of this technique is that the maximum reconstruction error in any cycle does not occur in the diagnostically crucial QRS region, while achieving a compression of about 15:1 and a normalized root mean square error of about 10%.
Exposure to pulsed high‐frequency electromagnetic field during waking affects human sleep EEG

The aim of the study was to investigate whether the electro-magnetic field (EMF) emitted by digital radiotelephone handsets affects brain physiology. Healthy, young male subjects were exposed for 30 min to EMF (900 MHz; spatial peak specific absorption rate 1 W/kg) during the waking period preceding sleep. Compared with the control condition with sham exposure, spectral power of the EEG in non-rapid eye movement sleep was increased. The maximum rise occurred in the 9.75–11.25 Hz and 12.5–13.25 Hz band during the initial part of sleep. These changes correspond to those obtained in a previous study where EMF was intermittently applied during sleep. Unilateral exposure induced no hemispheric asymmetry of EEG power. The present results demonstrate that exposure during waking modifies the EEG during subsequent sleep. Thus the changes of brain function induced by pulsed high-frequency EMF outlast the exposure period.
Calibration of the L-MEB Model for Croplands in HiWATER Using PLMR Observation

The Soil Moisture and Ocean Salinity (SMOS) mission was initiated in 2009 with the goal of acquiring global soil moisture data over land using multi-angular L-band radiometric measurements. Specifically, surface soil moisture was estimated using the L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer model. This study evaluated the applicability of this model to the Heihe River Basin in Northern China for specific underlying surfaces by simulating brightness temperature (BT) with the L-MEB model. To analyze the influence of a ground sampling strategy on the simulations, two resampling methods based on ground observations were compared. In the first method, the simulated BT of each point observation was initially acquired. The simulations were then resampled at a 1 km resolution. The other method was based on gridded data with a resolution of 1 km averaged from point observations, such as soil moisture, soil temperature, and soil texture. The simulated BTs at a 1 km resolution were then obtained using the L-MEB model. Because of the large variability in soil moisture, the resampling method based on gridded data was used in the simulation. The simulated BTs based on the calibrated parameters were validated using airborne L-band data from the Polarimetric L-band Multibeam Radiometer (PLMR) acquired during the HiWATER project. The root mean square errors (RMSEs) between the simulated results and the PLMR data were 6 to 7 K for V-polarization and 3 to 5 K for H-polarization at different angles. These results demonstrate that the model effectively represents agricultural land surfaces, and this study will serve as a reference for applying the L-MEB model in arid regions and for selecting a ground sampling strategy.
Kimlik ile Yaşam Doyumu Arasındaki İlişkide Yakınlık ve Akademik Başarının Aracı Rolü

Bu calismanin temel amaci kimlik statulerinin universite ogrencilerinin yakinlik doyumu, akademik basari puanlari ve yasam doyumlarini yordama gucunun ideolojik ve kisilerarasi alanlar ayristirilarak incelenmesi, cinsiyete gore farkliliklar olup olmadiginin belirlenmesi ve kimlik statuleri ile yasam doyumu arasindaki iliskide yakinlik doyumu ve akademik basarinin araci rolunun test edilmesidir. Bu amacla 490 kiz ve 183 erkek olmak uzere toplam 673 ogrenciden Genisletilmis Objektif Ego Kimlik Statuleri Olcegi, Cok Boyutlu Iliski Olcegi ve Yasam Doyumu Olcegi kullanilarak veri toplanmistir. Yapilan regresyon analizleri, yakinlik doyumunun kisilerarasi moratoryum, kisilerarasi daginik ve kisilerarasi basari statuleri tarafindan, akademik basari puanlarinin ideolojik basari ve kisilerarasi moratoryum tarafindan, yasam doyumunun ise ideolojik moratoryum, ideolojik basari, kisilerarasi bagimli ve kisilerarasi moratoryum statuleri tarafindan yordandigini gostermektedir. Bulgular ayni zamanda, yakinlik doyumunun yasam doyumu ile ideolojik alanda bagimli ve moratoryum, kisilerarasi alanda ise moratoryum arasindaki iliskide araci rolu bulundugunu ortaya koymustur. Son olarak, elde edilen iliskiler kiz ve erkek ogrenciler icin bazi farkliliklar gostermektedir.
Online survey for collective clustering of computer generated architectural floor plans

The aim of this study is to understand what are the collective actions of architecture practitioners when grouping floor plan designs. The understanding of how professionals and students solve this complex problem may help to develop specific programmes for the teaching of architecture. In addition, the findings of this study can help in the development of query mechanisms for database retrieval of floor plans and the implementation of clustering mechanisms to aggregate floor plans resulting from generative design methods. The study aims to capture how practitioners define similarity between floor plans from a pool of available designs. A hybrid evolutionary strategy is used, which takes into account the building's functional program to generate alternative floor plan designs. The first step of this methodology consisted in an online survey to gather information on how the respondents would perform a clustering task. Online surveys have been used in several applications and are a method of data collection that conveys several advantages. When properly developed and implemented, a survey portrays the characteristics of large groups of respondents on a specific topic and allows assessing its representation. Several types of surveys are available; e.g. questionnaire and interview formats, phone survey, and online surveys, which can be coupled with inference engines that act and direct the survey according to respondents' answers. In the present study, the survey was posed as an online exercise in which respondents had to perform a pre-defined task, which makes it similar to running an experiment in an online environment. The experiment aimed to understand the perception and criteria of the target population to perform the clustering task by comparing the results with the respondents' answers to a questionnaire presented at the end of the exercise.
Experience of women in the postoperative period of bariatric surgery: a phenomenological study

Aim: understand the experience of women in the postoperative period of bariatric surgery. Method: qualitative study based on Social Phenomenology of Alfred Schutz. The study included eight women, whose testimonies were obtained in the period October-December 2012 through interviews with open questions. Results: The category "Rescue of everyday activities" reveals that surgery allowed the control of chronic diseases associated with obesity, autonomy for self-care and daily activities, the rescue of self-esteem and social inclusion. The category "Challenges" shows that women live with the need to adopt healthy eating habits that can enable the achievement and maintenance of the desired weight. Conclusion: Although this study evidences a gain in quality of life of the "bariatriczied" woman, it also underscores the need for a shared and longitudinal care with this clientele by a multidisciplinary team, due to the chronic nature of obesity.
GRACE and GEORGE: Autonomous Robots for the AAAI Robot Challenge

Abstract : In an attempt to solve as much of the AAAI Robot Challenge as possible, five research institutions representing academia, industry and government, integrated their research on a pair of robots named GRACE and GEORGE. This paper describes the second year effort by the GRACE team, the various techniques each participant brought to GRACE, and the integration effort itself.
Navigating new norms of involved fatherhood: Employment, gender attitudes, and father involvement in American families

Background In the traditional division of labor, men were expected to provide for their families economically as breadwinners, while women’s primary responsibility was the care of children and the home. However, in recent decades, gender roles have shifted toward greater overlap of roles: women have entered the paid labor force in record numbers, while new norms of fatherhood now emphasize men’s involvement with their children in addition to their traditional role of financial provider (Furstenberg 1988; Gerson 1993; Townsend 2002; Lamb and Tamis-Lemonda 2004). While much scholarly and popular interest has focused on how women have adapted to their new roles in this gender revolution, much less work has focused on men’s experiences (Gerson 1993). And, in fact, many men may face great tension and conflict in attempting to fulfill their roles as both provider and involved father. The primary tension in the “new father” role lies in the conflict of time and place: while the “new father” role requires spending time with children, the provider and good worker roles require a commitment to spending time on the job (Kaufman and Uhlenberg 2000; Townsend 2002). How do men navigate these contradictory roles? To what extent does employment impact men’s involvement with their children? Are men with more egalitarian attitudes trading off longer work hours for more time—or more “quality” time—with their children? This study examines these questions using data from the 1997 and 2002 waves of the Child Development Supplement to the Panel Study of Income Dynamics (PSID-CDS). These data offer rich measures of father involvement, employment, and gender attitudes. In addition, the longitudinal nature of the data offers a unique opportunity to address the endogeneity of decisions about work and family life.
Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing

A key input to the call center staffing process is a forecast for the number of calls arriving. Density forecasts of arrival rates are needed for analytical call center models, which assume Poisson arrivals with a stochastic arrival rate. Density forecasts of call volumes can be used in simulation models and are also important for the analysis of outsourcing contracts. A forecasting method, which has previously shown strong potential, is Holt--Winters exponential smoothing adapted for modeling the intraday and intraweek cycles in intraday data. To enable density forecasting of the arrival volume and rate, we develop a Poisson count model, with gamma distributed arrival rate, which captures the essential features of this exponential smoothing method. The apparent stationary level in our data leads us to develop versions of the new model for series with stationary levels. We evaluate forecast accuracy up to two weeks ahead using data from three organizations. We find that the stationary level models improve prediction beyond approximately two days ahead, and that these models perform well in comparison with sophisticated benchmarks. This is confirmed by the results of a call center simulation model, which demonstrates the use of arrival rate density forecasting to support staffing decisions. This paper was accepted by Yossi Aviv, operations management.
Recognition of Implicit Rules on the Simulation Game BARNGA:Towards Development of Social Agent

We developed anOnline BARNNGA, which is social simulation game towards development of social agent. We observe human’s social skills of leaning to implicit understanding. This game based onBARNGA whose purpose is experience to explore factors related to communication problems in intercultural situations with cards game: trick taking game. In BARNGA, differences of a game’s rule represent cultural difference. Likewise, implicit rules can represent likely differences of a game’s rule. Then we observe behavior of players on the game and analyze social skills.
Data-driven augmented reality display and operations for UAV ground stations

The commonly used 2D Display is limited in aiding operators to control unmanned aerial vehicles (UAVs) within complex environments, due to its weak immersion. This paper proposes a data-driven 3D augmented reality approach. Pre-known data and experience can be integrated into to constructing a 3D virtual scenario. Furthermore, the on-board sensor data is continuously updated to this scenario during the task process. Under such circumstance, the static scenario and dynamic data are fused together by using the UAV's position and orientation. Task-associated information, e.g. route points and flying status, is simultaneously imported into the scenario to augment the virtual reality and to support the operator as well. Eventually, the AR ground station prototype is designed and implemented. Experimental results of quad rotors demonstrate that the developed system is feasible and effective to strengthen immersion with the virtual reality glasses.