Miracle-dz/UniFAR-FTUs huggingface dataset:
How Much Does This Tick You Off? Online Rejection and Criticism Lead to Negative Affect and Retaliatory Aggression

A three-condition (rejection, criticism, control) single-factor experiment (N = 77) on a mock social-networking site similar to Facebook reveals that even a slight rejection – not being allowed to join groups on the site – lead to increases in self-reported negative affect and retaliation against the site and the rejecting groups compared to a control. Subjects who were accepted into the groups but then criticized experienced the same increases in negative affect and retaliatory aggression, as those who were not allowed to join. In addition, men showed heightened retaliatory aggression compared to women and responded differently to criticism than women. However, no significant effects were found by condition in regard to arousal, physiologically measured affect, attempts to restore relational value, triggered displaced aggression, or feelings associated with ostracism. Findings suggest that while rejection and criticism cause emotional pain, they do not hurt as much as ostracism. Results are discussed in relation to the belongingness hypothesis, sociometer theory, the ostracism model, and face theory. Gender differences are explored using social cognitive theory.
Manifold Regularization for Kernelized LSTD

Policy evaluation or value function or Q-function approximation is a key procedure in reinforcement learning (RL). It is a necessary component of policy iteration and can be used for variance reduction in policy gradient methods. Therefore its quality has a significant impact on most RL algorithms. Motivated by manifold regularized learning, we propose a novel kernelized policy evaluation method that takes advantage of the intrinsic geometry of the state space learned from data, in order to achieve better sample efficiency and higher accuracy in Q-function approximation. Applying the proposed method in the Least-Squares Policy Iteration (LSPI) framework, we observe superior performance compared to widely used parametric basis functions on two standard benchmarks in terms of policy quality.
Labor induction failure prediction using Gabor filterbanks and center symmetric local binary patterns

Labor induction is defined as the artificial stimulation of uterine contractions aimed to induce vaginal birth. Occurring in about 20% of pregnancies labor induction has become one the most commonly practiced procedures in obstetrics. One of the risk related to labor induction is cesarean section which accounts about 20% of the inductions. A requirement for a successful labor is a ripe cervix (soft and distensible). Microestructural changes occurring in the cervix during the ripening process, will affect the interaction between cervical tissues and sound waves during ultrasound transvaginal scanning and will be perceived as gray level intensity variations in the echographic image. A non-invasive method using image processing of ultrasound images may help in predicting the outcome of labor induction. In this paper a set of echography images from labor induction patients is analyzed using a multiscale methodology based on Center Symmetric Local Binary Patterns and Gabor filters. Results show that it is feasible to predict the outcome of a labor induction procedure using this method with a good accuracy.
Secondary Electron Trajectories in Scanning Tunneling Microscopy

The recently developed technique Scanning Tunneling Microscopy in the Field Emission regime (STM FE) is based on the Russell Young's topografiner technology [1]. The set-up is a no contacting device consisting of a sharp tip approached vertically to a conducting surface at variable distances and biased with a small voltage with respect to the surface (Figure 1). The system builds a junction across which electrons can be transferred from the tip apex to the surface by direct quantum mechanical tunneling if the distance is in the sub nanometer region. In this case the surface topography can be imaged with atomic spatial resolution using the STM technique. In the STM FE mode, the distance between tip and collector is increased and the current is dominated by electrons emitted from the tip into the vacuum region via electric field assisted tunneling. In the experiment, secondary electrons carrying chemical and magnetic information are produced via diverse mechanisms on the surface of the sample and form a cloud in the vicinity around the interaction region in a macroscopic environment. Some of them are attracted by an electric potential to the entrance of a lens system designed for focusing the electrons into a counter and a Mott detector. The imaging of the sample with a resolution in the nanoscale depends on the amount of secondary electrons that effectively reach the detectors. We use COMSOL Multiphysics® to optimize the electrostatic and geometric parameters by calculating the trajectories of the secondary electrons from the sample to the final position on the detectors. The set of results achieved on the physical characterization of the instrument refers to a situation where a nanoscale quantum process, comprising field emission, secondary electron production and electron transport in the presence of strongest electric fields is shown to couple efficiently to a macroscopic environment. An accurate modeling of this multiscale process requires the solution of the Laplace and movement equations in two separate subsystems with different space scales. In the first component, the system consists of a tungsten tip in front of a silicon surface in a subspace of some hundreds of nanometers [2]. In the second component, the geometry is generated by importing a simplified version of the CAD-construction files of the instrument (in a scale of centimeters) (Figure 2). In both cases the electrostatic problem is solved using the AC/DC Module and the trajectories of the electrons are calculated with the Particle Tracing Module. For coupling the two simulations, in analogy to the model "Syngas Combustion in a Round-Jet Burner" (Model Library), the final positions and velocities on the walls of the first Component are used as initial values in the second Component (Figure 3). Most of the calculations are performed on a cluster. First results shown that only a few electrons can escape from the interaction region if their energies are about 70 eV. From the escaped electrons, a 10% can reach the Mott detector (Figure 4).
Personality factors at the base of sustainable behavior: A first approach across two universities

The theoretical framework on the cognitive information processing holds that mental processes such as formation of beliefs, attitudes, or perceptions are impossible to directly observe and measure. This condition is resolved by implementing questionnaires integrated with hypothetical variables which can measure individual responses as real entities. Hypothetical variables related to individual personality features in this study were ascription of responsibility, universal values, personal skills, and awareness of consequences. Universal values discern on inherent conflicts among peoples motivational goals. Personal skills are concerned with the capacity to understand the intentions of others and oneself. Ascription of responsibility and awareness of consequences explain peoples desire to take action. The four factors are statistically highly related and proved explaining the construct of sustainable behavior (SB) (Juarez-Najera, 2009). SB as is defined in this work is an effective disposition to act. It was tested by applying a 67-issue questionnaire among 106 participants, 69 Mexicans from the Universidad Autonoma Metropolitana, Azcapotzalco campus and 37 Germans from Leuphana Universitaet Lueneburg, Institut fur Umweltkommunication. SB was validated by means of an exploratory principal component analysis (PCA) which searches a factor structure underlying the hypothetical variables. To this end, this paper presents a pattern of the first components found by the PCA and the representative relations of the personality factors which explains sustainable behavior across participants in higher education institutions from two countries with vastly different cultures and economies. Ascription of responsibility appears as the main personal factor.
Beta/Gamma Oscillations and Event-Related Potentials Indicate Aberrant Multisensory Processing in Schizophrenia

Recent behavioral and neuroimaging studies have suggested multisensory processing deficits in patients with schizophrenia (SCZ). Thus far, the neural mechanisms underlying these deficits are not well understood. Previous studies with unisensory stimulation have shown altered neural oscillations in SCZ. As such, altered oscillations could contribute to aberrant multisensory processing in this patient group. To test this assumption, we conducted an electroencephalography (EEG) study in 15 SCZ and 15 control participants in whom we examined neural oscillations and event-related potentials (ERPs) in the sound-induced flash illusion (SIFI). In the SIFI multiple auditory stimuli that are presented alongside a single visual stimulus can induce the illusory percept of multiple visual stimuli. In SCZ and control participants we compared ERPs and neural oscillations between trials that induced an illusion and trials that did not induce an illusion. On the behavioral level, SCZ (55.7%) and control participants (55.4%) did not significantly differ in illusion rates. The analysis of ERPs revealed diminished amplitudes and altered multisensory processing in SCZ compared to controls around 135 ms after stimulus onset. Moreover, the analysis of neural oscillations revealed altered 25–35 Hz power after 100 to 150 ms over occipital scalp for SCZ compared to controls. Our findings extend previous observations of aberrant neural oscillations in unisensory perception paradigms. They suggest that altered ERPs and altered occipital beta/gamma band power reflect aberrant multisensory processing in SCZ.
Diacylglycerol Lipase α Knockout Mice Demonstrate Metabolic and Behavioral Phenotypes Similar to Those of Cannabinoid Receptor 1 Knockout Mice

After creating >4,650 knockouts (KOs) of independent mouse genes, we screened them by high-throughput phenotyping and found that cannabinoid receptor 1 (Cnr1) KO mice had the same lean phenotype published by others. We asked if our KOs of DAG lipase α or β (Dagla or Daglb), which catalyze biosynthesis of the endocannabinoid (EC) 2-arachidonoylglycerol (2-AG), or Napepld, which catalyzes biosynthesis of the EC anandamide, shared the lean phenotype of Cnr1 KO mice. We found that Dagla KO mice, but not Daglb or Napepld KO mice, were among the leanest of 3651 chow-fed KO lines screened. In confirmatory studies, chow- or high fat diet-fed Dagla and Cnr1 KO mice were leaner than wild-type (WT) littermates; when data from multiple cohorts of adult mice were combined, body fat was 47 and 45% lower in Dagla and Cnr1 KO mice, respectively, relative to WT values. By contrast, neither Daglb nor Napepld KO mice were lean. Weanling Dagla KO mice ate less than WT mice and had body weight (BW) similar to pair-fed WT mice, and adult Dagla KO mice had normal activity and VO2 levels, similar to Cnr1 KO mice. Our Dagla and Cnr1 KO mice also had low fasting insulin, triglyceride, and total cholesterol levels, and after glucose challenge had normal glucose but very low insulin levels. Dagla and Cnr1 KO mice also showed similar responses to a battery of behavioral tests. These data suggest: (1) the lean phenotype of young Dagla and Cnr1 KO mice is mainly due to hypophagia; (2) in pathways where ECs signal through Cnr1 to regulate food intake and other metabolic and behavioral phenotypes observed in Cnr1 KO mice, Dagla alone provides the 2-AG that serves as the EC signal; and (3) small molecule Dagla inhibitors with a pharmacokinetic profile similar to that of Cnr1 inverse agonists are likely to mirror the ability of these Cnr1 inverse agonists to lower BW and improve glycemic control in obese patients with type 2 diabetes, but may also induce undesirable neuropsychiatric side-effects.
Relaxin favors the development of activated human T cells into Th1‐like effectors

Differentiation of naive CD4+ helper T (Th) cells into Th1 or Th2 effectors, as characterized by their opposite pattern of cytokine production, can be influenced by several factors, including hormones. In this study, we demonstrate that porcine relaxin, at concentrations ranging from 10–10, to 10–6M, favors the in vitro development of human antigen‐specific T cells into Th1‐like effectors and enhances both IFN‐γ mRNA expression and IFN‐γ production by established human T cell clones. The promoting effect of relaxin on the development of IFN‐γ‐producing cells was not due to a relaxin‐induced release of IL‐12 and/or IFN‐α by antigen‐presenting cells. These results suggest that relaxin may contribute to the regulation of the immune homeostasis during pregnancy and may also play some role in counteracting Th2‐dominated disorders.
Nonprofits, Crowd-Out, and Credit Constraints

We introduce a model of an infinitely-lived nonprofit organization facing donor crowd-out by government grants and credit constraints. The nonprofit chooses the optimal allocation of resources over time between providing service and fund-raising activities. We show that the response of fund-raising expenditures to grants not only hinges on the effect of grants on the productivity of fund-raising as in static models, but depends critically on the timing of grants and credit market access. When nonprofits face credit constraints, increases in future grants lead to reductions in fund-raising because nonprofits reallocate resources over time. In previous nonprofit theories of crowd-out, a negative relationship between grants and fund-raising expenditures follows from an assumption that the marginal productivity of fund-raising expenditures decreases with government grants. In contrast we provide robust empirical evidence that government grants increase the marginal productivity of fund-raising, which is inconsistent with the key assumption of those theories. Moreover, we provide strong evidence of intertemporal resource allocation with limited credit access as predicted in our theoretical model. We discuss why the distinction matters for policies supporting nonprofit public good provision.
Low duty-cycle UWB communications design for body area network

Low duty-cycle (LDC) algorithm is interference mitigation technique, which can reduce the average interference to the existing radio systems by lowering pulse repetition interval or pulse occupation time. Moreover, LDC algorithm is also low power consumption by using lowering pulse repetition interval or pulse occupation time. Thus, in order to design a novel ultra wideband (UWB) system for body area network (BAN) application in the low data low power regime, it is necessary to pay special attentions in the energy requirements and the risk factor for tissue heating (damage) of UWB systems from theoretical and practical viewpoints. In this paper, the coexistence environment between low data rate UWB system such as wireless sensor network including BAN and the existing wideband system using OFDM is considered. In order to analyze the interference mitigation capability of LDC algorithm with impulse based UWB (LDC-UWB) system, the frame error rate (FER) of wideband OFDM system is examined for two types of LDC-UWB system: binary pole signals and mono pole signals. We present that LDC algorithm is an efficient interference mitigation technique for low data rate UWB communication for BAN via computer simulations regardless of definitions of transmitted energy of UWB communication system, and also that the binary pole signal is suitable for LDC-UWB system to mitigate interference to the other radio systems. We further investigate the adequate duty-cycle of LDC-UWB system for each definition of transmitted power of UWB communication.
Greater Transportation Energy and GHG Offsets from Bioelectricity Than Ethanol

Future Fuels In the scramble to develop more environmentally friendly transportation methods, a wide range of questions must be answered, including how automobiles may best be powered. Biomass might be an important source for that power, either to generate electricity for electric vehicles, or to make ethanol for combustion vehicles. Campbell et al. (p. 1055; published online 7 May; see the Policy Forum by Ohlrogge et al.) examined each approach's demands on land-use, using a lifecycle assessment model, for a range of energy feedstocks, conversion methods, and vehicle types. In nearly all cases, bioelectricity would have a significantly higher net transportation efficiency per area of land used than bioethanol, owing to the greater efficiency of electric engines. Furthermore, bioelectricity would result in a smaller CO2 burden. Thus, bioelectricity could represent an important bridge to more advanced transportation technologies with less environmental impact. Electric vehicles powered by electricity made from biofuels are more efficient than vehicles fueled by bioethanol. The quantity of land available to grow biofuel crops without affecting food prices or greenhouse gas (GHG) emissions from land conversion is limited. Therefore, bioenergy should maximize land-use efficiency when addressing transportation and climate change goals. Biomass could power either internal combustion or electric vehicles, but the relative land-use efficiency of these two energy pathways is not well quantified. Here, we show that bioelectricity outperforms ethanol across a range of feedstocks, conversion technologies, and vehicle classes. Bioelectricity produces an average of 81% more transportation kilometers and 108% more emissions offsets per unit area of cropland than does cellulosic ethanol. These results suggest that alternative bioenergy pathways have large differences in how efficiently they use the available land to achieve transportation and climate goals.
A comparative analysis of weighted and unweighted power grid networks

This paper focuses on identification of vulnerable lines and nodes of the power grid (PG) network whose removal disrupt on its operational capability. Here the topological parameters are derived from CN theory, and these are used to identify the most important elements i.e., lines and nodes of the PGs. Based on this concept, the number of attack strategies are illustrated and also applied to different IEEE bus networks, e.g., IEEE 39 and 300 buses. We show that in case of electrical PG network, weights are related to electric concepts, and that can enhance the representation of the PG. This work identifies the vulnerable lines and nodes of both weighted and unweighted networks, and quantify the results by applying the concept to real AC power flow model. We conclude that a weighted network analysis can give a better vulnerability assessment than that of an unweighted network.
Transcriptomic Signature of the SHATTERPROOF2 Expression Domain Reveals the Meristematic Nature of Arabidopsis Gynoecial Medial Domain1[OPEN]

Transcriptional profiles of spatially and temporally restricted cell populations from the Arabidopsis gynoecium reveals the meristematic nature of the gynoecial medial domain. Plant meristems, like animal stem cell niches, maintain a pool of multipotent, undifferentiated cells that divide and differentiate to give rise to organs. In Arabidopsis (Arabidopsis thaliana), the carpel margin meristem is a vital meristematic structure that generates ovules from the medial domain of the gynoecium, the female floral reproductive structure. The molecular mechanisms that specify this meristematic region and regulate its organogenic potential are poorly understood. Here, we present a novel approach to analyze the transcriptional signature of the medial domain of the Arabidopsis gynoecium, highlighting the developmental stages that immediately proceed ovule initiation, the earliest stages of seed development. Using a floral synchronization system and a SHATTERPROOF2 (SHP2) domain-specific reporter, paired with FACS and RNA sequencing, we assayed the transcriptome of the gynoecial medial domain with temporal and spatial precision. This analysis reveals a set of genes that are differentially expressed within the SHP2 expression domain, including genes that have been shown previously to function during the development of medial domain-derived structures, including the ovules, thus validating our approach. Global analyses of the transcriptomic data set indicate a similarity of the pSHP2-expressing cell population to previously characterized meristematic domains, further supporting the meristematic nature of this gynoecial tissue. Our method identifies additional genes including novel isoforms, cis-natural antisense transcripts, and a previously unrecognized member of the REPRODUCTIVE MERISTEM family of transcriptional regulators that are potential novel regulators of medial domain development. This data set provides genome-wide transcriptional insight into the development of the carpel margin meristem in Arabidopsis.
Approximating Handwritten Curve by Using Progressive-Iterative Approximation

In this paper, a given handwritten curve will be approximately converted into a Bezier curve. First, a number of sampled points on the given curve are systematically chosen to guarantee that the Bezier curve can be adequately modeled without the loss of curve characteristics. These points are considered to be the Bezier control points. The Progressive-Iterative Approximation (PIA) is then adopted to construct the interpolating curve. Employing PIA algorithm, Bernstein polynomials are selected to be a blending function of PIA so that this interpolating curve will develop a Bezier curve. This technique will avoid the ill-conditioned circumstance because of using Newton/Lagrange polynomials in curve fitting.
Regional changes in cerebral extracellular glucose and lactate concentrations following severe cortical impact injury and secondary ischemia in rats.

Traumatic brain injury (TBI) causes the brain to be more susceptible to secondary insults, and the occurrence of a secondary insult after trauma increases the damage that develops in the brain. To study the synergistic effect of trauma and ischemia on brain energy metabolites, regional changes in the extracellular concentrations of glucose and lactate following a severe cortical impact injury were measured employing a microdialysis technique. Three microdialysis probes were placed in center of the impact site, in an area adjacent to the impact site, and in the contralateral parietal cortex, and perfused with artificial cerebrospinal fluid (CSF) at 2 microl/min. Rats were assigned to one of the following experimental groups (n = 7 per group): (1) combined impact injury and secondary insult, (2) impact injury with sham secondary insult, (3) sham impact with secondary insult, or (4) sham impact and sham secondary insult. The impact injury was produced with a pneumatic impactor (5 m/sec, 3-mm deformation). One hour following the impact injury, a secondary insult was produced by bilateral carotid occlusion for 1 h. The impact injury resulted in a three- to fivefold global increase in dialysate lactate concentrations, with a corresponding fall in dialysate glucose concentration by 50% compared to no change in lactate or glucose concentrations in sham-injured animals (p < .0001 for both lactate and glucose). The secondary insult resulted in a second increase in dialysate lactate and decrease in dialysate glucose concentration that was significantly greater in the animals that had suffered the impact injury than in the sham-injured animals. Ischemia and traumatic injury have synergistic effects on lactate accumulation and on glucose depletion in the brain that probably reflects persisting ischemia, but may also indicate mitochondrial abnormalities and inhibition of oxidative metabolism.