Miracle-dz/UniFAR-FTUs huggingface dataset:
Lust for violence: Appetitive aggression as a fundamental part of human nature

Abstract Appetitive aggression describes a biologically-driven form of aggressive behaviour and violence characterized by positive affect. In contrast to reactive aggression, which has the function of resisting a threat, and reducing concomitant negative emotional arousal and anger, appetitive aggression underlies the pleasure of violence. A prototypical example is hunting, which can in turn transfer to the hunting of humans and can even result in bloodlust, and killing for its own sake. At the physiological level, this morally illicit pleasure is accompanied by an adrenalin surge, the release of cortisol and endorphins. In order to activate reward systems via appetitive aggression, their moral and cultural restraints need to be overridden. For example, armed groups work to dehumanize the enemy. Once initiated, a positive feedback loop is generated: As the individual commits more acts of violence with elements of positive affect, the tendency to commit them grows, and they begin to be perceived more positively. A latent passion for fighting and dominance can probably be evoked in almost all men and in some women. The cumulative outcome of whole groups, tribes, or communities enacting this aggression is war and destruction, to the point of trying to extinguish entire ethnic groups:“… and yes, human beings, hundreds of thousands of otherwise normal people, not professional killers, did it. ” (from “The Killers in Rwanda Speak” by Jean Hatzfeld, 2005). Thus, appetitive aggression, the disposition towards a lust for violence, is by no means a psychopathological anomaly but an intrinsic part of the human behavioural repertoire. Morality, culture and the state monopoly on violence constitute the guards that regulate aggression potential and to channel it into socially useful forms.
Temperament Moderates Associations between Young Children's Hostile Attributions and Aggressive Behavior.

This study examined the hypothesis that the association between hostile attributions and aggressive behavior with peers is moderated by children’s temperament among three samples of preschoolers. Hostile attributions were assessed through videotape-based and story-based laboratory procedures. Maternal ratings and laboratory-based assessment provided the measures of temperament, and children’s teachers completed ratings of aggression. Results revealed significant interaction terms between hostile attributions and temperament in the prediction of aggression. For children rated well or moderately skilled in selfregulation there was no association between hostile attributions and aggression. For children rated as poorly skilled in self-regulation making hostile attributions was significantly associated with aggression. This pattern of associations was particularly apparent for boys.
Profiling of differentially expressed genes in ectomycorrhizal fungus Pisolithus tinctorius responding to mycorrhiza helper Brevibacillus reuszeri MPt17

A cDNA library of the ectomycorrhizal (ECM) fungus Pisolithus tinctorius Pt2 after interaction with the mycorrhiza helper bacterium (MHB) Brevibacillus reuszeri MPt17 was constructed by suppression subtraction hybridization. Total RNA from B. reuszeri MPt17 exudates treated Pi. tinctorius Pt2 was used as a “tester” and total RNA from nonbacterial treated Pi. tinctorius Pt2 was used as a “driver. ” Among the differentially expressed sequences, a BLASTX in the NCBI non-redundant protein sequence database revealed that 75% of the non-redundant sequences (147 out of 196) were highly similar to known proteins (E-value < e−5). Twelve sequences were annotated as mycelium development function combining with a potential functional categories using gene ontology. Quantitative real-time PCR analysis showed that all of the 3 symbiosis regulated acidic polypeptide genes were all up-regulated in the MPt17-treated Pt2. These results provide evidence that the MHB B. reuszeri MPt17 could significantly change the expression of symbiosis-related genes and genes in mycelium development in ECM fungus, and also support the hypothesis that the MHB functions as helper though promotion on fungal mycelium.
N-Dimensional Binary Vector Spaces

Summary The binary set {0, 1} together with modulo-2 addition and multiplication is called a binary field, which is denoted by F2. The binary field F2 is defined in [1]. A vector space over F2 is called a binary vector space. The set of all binary vectors of length n forms an n-dimensional vector space Vn over F2. Binary fields and n-dimensional binary vector spaces play an important role in practical computer science, for example, coding theory [15] and cryptology. In cryptology, binary fields and n-dimensional binary vector spaces are very important in proving the security of cryptographic systems [13]. In this article we define the n-dimensional binary vector space Vn. Moreover, we formalize some facts about the n-dimensional binary vector space Vn.
Underpaid or Overpaid? Wage Analysis for Nurses Using Job and Worker Attributes

The nursing labor market presents an apparent puzzle. Hospitals report chronic shortages, yet standard wage analysis shows that nursing wages have increased over time and greatly exceed those received by other college-educated women. This paper addresses this puzzle. Data from the Current Population Survey (CPS) are matched with detailed job content descriptors from the Occupational Information Network (O*NET). Nursing jobs require higher levels of skills and more difficult working conditions than do jobs for other college educated workers. A standard CPS-only wage regression shows a registered nurse (RN) wage advantage of . 22 log points compared to a pooled male/female group of college-educated workers. Control for O*NET job attributes reduces the RN gap to . 08, while an arguably preferable nonparametric estimator produces a wage gap estimate close to zero. We conclude that nurses receive compensation close to long-run opportunity costs, narrowing if not resolving the RN wage-shortage puzzle.
The Strategy of Distributed Load Balancing Based on Hybrid Scheduling

A strategy of distributed load balancing based on hybrid scheduling (LBHS) is proposed in this paper. This method is a hybrid scheduling strategy, which is based on the static allocation, and used dynamic scheduling system with the amply consideration of all the factors in the process of load balancing. This method can improve the utilization of the processor. The method is tested in the land surface disaster and ecology model. The result indicates that the strategy could improve the performance of parallel computing effectively, especially in the case that the size and data of the task is partially mastered beforehand.
Gain and Q Bounds for Coupled TM-TE Modes

The possibility of minimizing the bound on the Q of an antenna by resonating TM modes with TE modes has been described in many papers. Other papers have dealt with maximizing the gain by combining these modes in an optimum manner. However, there are fundamental relations for the phasing of the two modes which prevents minimum Q and maximum gain from being realized simultaneously. These phase restrictions have been neglected in some papers, leading to the presentation of incorrect results. This paper explores the relationships between phase, gain, bandwidth, and the Q lower bound, particularly for electrically-small antennas.
Amitriptyline Therapy in Chronic Pain

Rodent evidence has confirmed the analgesic effect of tricyclic antidepressants in the treatment of chronic pain, which amitriptyline is rigorously verified. The analgesic effect of amitriptyline, whose mechanisms are complex and unclear, is different from its antidepressant effect. This article reviewed the mechanisms behind amitriptyline’s analgesic properties to further understanding of this drug. Additionally, this article reviewed the clinical evidence of the effectiveness of amitriptyline therapy in treatment of chronic pain to offer guidance for future clinical practice.
A Comprehensive Linkage Map of the Dog Genome

We have leveraged the reference sequence of a boxer to construct the first complete linkage map for the domestic dog. The new map improves access to the dog's unique biology, from human disease counterparts to fascinating evolutionary adaptations. The map was constructed with ∼3000 microsatellite markers developed from the reference sequence. Familial resources afforded 450 mostly phase-known meioses for map assembly. The genotype data supported a framework map with ∼1500 loci. An additional ∼1500 markers served as map validators, contributing modestly to estimates of recombination rate but supporting the framework content. Data from ∼22,000 SNPs informing on a subset of meioses supported map integrity. The sex-averaged map extended 21 M and revealed marked region- and sex-specific differences in recombination rate. The map will enable empiric coverage estimates and multipoint linkage analysis. Knowledge of the variation in recombination rate will also inform on genomewide patterns of linkage disequilibrium (LD), and thus benefit association, selective sweep, and phylogenetic mapping approaches. The computational and wet-bench strategies can be applied to the reference genome of any nonmodel organism to assemble a de novo linkage map.
Does a Peer Recommender Foster Students' Engagement in MOOCs?

Overall the social capital of MOOCs is under-exploited. For most students in MOOCs, autonomous learning often means learning alone. Students interested in adding a social dimension to their learning can browse discussion threads, join social medias and may decide to message other students… but usually in a random way. This common isolation might be a contributing factor on student attrition rate and on their general learning experience. To foster learners' persistence in MOOCs, we propose to enhance the MOOC experience with a recommender which provides each student with an individual list of rich-potential contacts, created in real-time on the basis of their own profile and activities. This paper describes a controlled study conducted from Sept. to Nov. 2015 during a MOOC on Project Management. A recommender panel was integrated to the users' interface and allowed to manage contacts, send them an instant message or consult their profile. The population (N = 8,673) was randomly split into 2 parts: a control group, without any recommendations, and an experimental group in which students could choose to activate and use the recommender. After having demonstrated that these populations were similar up to the activation of the recommender, we evaluate the effect of the recommender on the basis of four pillars of learners' persistence: attendance, completion, success and participation. Results suggest that the recommender improved all these four factors: students were much more likely to persist and engage in the MOOC if they received recommendations than if they did not.
Optimization of the structure of bilayer organic solar cells based on light intensity distribution and quantity of effective excitons

The light intensity distribution inside organic solar cells is described by optical propagation matrix and the quantity of effective excitons is defined in this paper. The quantity of effective excitons describes the total intensity near the donor/acceptor interface, which can contribute to the generation of holes and electrons. The optimum structure then can be obtained by maximizing this parameter. In this paper, CuPc/C60 structure is taken as an example. It is found the optimum structure is CuPc(15nm)/C60(40nm). The verification experiments are established and only 5nm error appears in the thickness of CuPc.
Models and thresholds for random constraint satisfaction problems

We introduce a class of models for random Constraint Satisfaction Problems. This class includes and generalizes many previously studied models. We characterize those models from our class which exhibit thresholds for satisfiability in the sense that the limiting probability of satisfiability changes significantly as the number of constraints increases. We also discuss models which exhibit sharp thresholds in the sense that the limiting probability jumps from 0 to 1 suddenly.
Altered Fatty Acid, Cholesterol and Na+/K+ ATPase Activity in Erythrocyte Membrane of Rheumatoid Arthritis Patients

Abstract Rheumatoid Arthritis, Cholesterol, Eicosapentaenoic Acid. Na+/K+ ATPase, Erythrocyte Membrane Rheumatoid arthritis (RA) is a chronic inflamatory disease whose cause remains obscure. Blood from 15 R A patients and controls was taken and their ghosts separated. The ghosts were analysed for cholesterol content, Na+/K+ ATPase activity and eicosapentaenoic acid. The cholesterol content in the ghosts of RA patients was significantly lower as compared with the set of controls. There was a major difference in the activity of Na+/K+ ATPase between the two groups with RA patients showing significantly elevatad activity. The ghosts of the RA patients exhibited major abnormality in the polyunsaturated fatty acids of phospholipids with the level of eicosapentaenoic acid (ω-3, 20:5) being significantly reduced.
Large Wireless Ad Hoc Network Clustering with End-to-End QoS Constraints Using Multiobjective Particle Swarm Optimization

—To scale for large ad hoc networks containing hundreds or even thousands of subnets, the networks must be hierarchically organized by partitioning them into clusters or domains. Many researchers have proposed partitioning of large networks into clusters, but this requires specifying cluster size bound. Graph Partitioning (GP) algorithms search for min-cut that balances the number of nodes in each partition. The limitations of GP algorithms are that they cannot be optimized for end-to-end performance requirements or take into account the characteristics of network topology. We propose a clustering algorithm based on the concept of Multiobjective Particle Swarm Optimization (MOPSO). Our algorithm minimizes the sum of the total hop count in each cluster and minimizes the edge-cut weight between clusters. Further, our algorithm provides quality of service (QoS) by taking into account end-to-end performance requirements. We find that minimizing the sum of the cluster hop count results in a balanced and bounded cluster size. For a given number of clusters, our clustering algorithm creates clusters with sizes closer to average size and avoids isolated nodes. In our study, the terms domain, cluster, and partition are used interchangeably.
A Quirky Little Higgs Model

We consider an extra dimensional model where the quadratically divergent top loop contribution to the Higgs mass is cancelled by an uncolored heavy ``top quirk" charged under a different SU(3) gauge group. The cancellation is enforced by bulk gauge symmetries. Thus we have an unusual type of little Higgs model which has some quirky signatures. The top partner in this model could be identified at the Large Hadron Collider due to macroscopic strings that connect quirk and anti-quirks. The model can undergo radiative electroweak symmetry breaking and is consistent with precision electroweak measurements.
Multiple Model-Based Reinforcement Learning

We propose a modular reinforcement learning architecture for nonlinear, nonstationary control tasks, which we call multiple model-based reinforcement learning (MMRL). The basic idea is to decompose a complex task into multiple domains in space and time based on the predictability of the environmental dynamics. The system is composed of multiple modules, each of which consists of a state prediction model and a reinforcement learning controller. The responsibility signal, which is given by the softmax function of the prediction errors, is used to weight the outputs of multiple modules, as well as to gate the learning of the prediction models and the reinforcement learning controllers. We formulate MMRL for both discrete-time, finite-state case and continuous-time, continuous-state case. The performance of MMRL was demonstrated for discrete case in a nonstationary hunting task in a grid world and for continuous case in a nonlinear, nonstationary control task of swinging up a pendulum with variable physical parameters.
A Mechanism Design for Privacy-Preserving Computation on Shared Data

In times of surveillance and data retention, sharing information often comes together with privacy concerns. However, information sharing has benefits, e.g. sharing log files for including the knowledge gained from a broader view for security analysis, or sharing healthcare data for the use in studies for improving medical treatments. We present an information sharing framework design that meets both privacy and utility requirements of the information sharing parties. We utilize homomorphic encryption and show how it can be used for offline data analysis.
The vegetative state

#### Summary points The vegetative state may develop suddenly (as a consequence of traumatic or non-traumatic brain injury, such as hypoxia or anoxia; infection; or haemorrhage) or gradually (in the course of a neurodegenerative disorder, such as Alzheimer’s disease). Although uncommon, the condition is perplexing because there is an apparent dissociation between the two cardinal elements of consciousness: awareness and wakefulness.1 Patients in a vegetative state appear to be awake but lack any sign of awareness of themselves or their environment.w1 Large retrospective clinical audits have shown that as many as 40% of patients with a diagnosis of vegetative state may in fact retain some level of consciousness. Misdiagnosis has many implications for a patient’s care—such as day to day management, access to early interventions, and quality of life—and has ethical and legal ramifications pertaining to decisions on the discontinuation of life supporting …
A 283 GHz low power heterodyne receiver with on-chip local oscillator in 65 nm CMOS process

A Fully integrated 283 GHz heterodyne receiver in 65 nm CMOS process is presented in this paper. The circuit includes a resistive differential mixer, an intermediate frequency amplifier and a 282 GHz subharmonic injection locked oscillator. The on-chip oscillator generates a 94 GHz fundamental tone but exploits a 282 GHz third harmonic. An injection signal of 47 GHz (one sixth of the RF frequency) is used to lock the oscillator on a reference. The receiver measured conversion gain is -6 dB for a DC power consumption of 97.6 mW. Simulated noise figure is 38 dB. The chip size is 820 μm × 780 μm including matching networks and DC/RF pads.
JECB: a join-extension, code-based approach to OLTP data partitioning

Scaling complex transactional workloads in parallel and distributed systems is a challenging problem. When transactions span data partitions that reside in different nodes, significant overheads emerge that limit the throughput of these systems. In this paper, we present a low-overhead data partitioning approach, termed JECB, that can reduce the number of distributed transactions in complex database workloads such as TPC-E. The proposed approach analyzes the transaction source code of the given workload and the database schema to find a good partitioning solution. JECB leverages partitioning by key-foreign key relationships to automatically identify the best way to partition tables using attributes from tables. We experimentally compare our approach with the state of the art data-partitioning techniques and show that over the benchmarks considered, JECB provides better partitioning solutions with significantly less overhead.
A new multi-agent reinforcement learning algorithm and its application in wastewater reclamation by IBAC reactor

In multi-agent systems, joint-action must be employed to achieve cooperation because the evaluation to the behavior of an agent often depends on the other agents' behaviors. However, joint-action reinforcement learning suffers the slow convergence rate because of the enormous learning space produced by joint-action. In this article, a prediction-based reinforcement learning algorithm is presented for multi-agent cooperation tasks, which demands all agents to learn predicting the probabilities of actions that other agents may execute. An Immobilized Biological Activated Carbon (IBAC) reactor is run to test the efficacy of the new algorithm, and the result shows that the new algorithm can achieve high biodegradation efficiency much faster than the primitive reinforcement learning algorithm.
Expression and Modulation of an NADPH Oxidase in Mammalian Astrocytes

Amyloid β peptides generate oxidative stress in hippocampal astrocytes through a mechanism sensitive to inhibitors of the NADPH oxidase [diphenylene iodonium (DPI) and apocynin]. Seeking evidence for the expression and function of the enzyme in primary hippocampal astrocytes, we confirmed the expression of the subunits of the phagocyte NADPH oxidase by Western blot analysis and by immunofluorescence and coexpression with the astrocyte-specific marker glial fibrillary acidic protein both in cultures and in vivo. Functional assays using lucigenin luminescence, dihydroethidine, or dicarboxyfluorescein fluorescence to measure the production of reactive oxygen species (ROS) demonstrated DPI and apocynin-sensitive ROS generation in response to the phorbol ester PMA and to raised [Ca2+]c after application of ionomycin or P2u receptor activation. Stimulation by PMA but not Ca2+ was inhibited by the protein kinase C (PKC) inhibitors staurosporine and hispidin. Responses were absent in transgenic mice lacking gp91phox. Expression of gp91phox and p67phox was increased in reactive astrocytes, which showed increased rates of both resting and stimulated ROS generation. NADPH oxidase activity was modulated by intracellular pH, suppressed by intracellular alkalinization, and enhanced by acidification. The protonophore carbonyl cyanide p-trifluoromethoxyphenylhydrazone suppressed basal ROS generation but markedly increased PMA-stimulated ROS generation. This was independent of mitochondrial ROS production, because it was unaffected by mitochondrial depolarization with rotenone and oligomycin. Thus, the NADPH oxidase is expressed in astrocytes and is functional, activated by PKC and intracellular calcium, modulated by pHi, and upregulated by astrocyte activation. The astrocytic NADPH oxidase is likely to play important roles in CNS physiology and pathology.
The stability of delays BAM neural networks with Variable-time and poisson arrival impulses

In this paper, we consider the globally stability of BAM neural networks with time delays and Random Variable-time Impulses (RVI). RVI denotes the impulses occurring follow Poisson Arrival in time, instead of fixed instants. Under this assumption, the time interval between two successive impulses follows exponential distribution with arrival rate. By simulation, we found that the system will be more stability as the arrival rate gets smaller. Numerical examples are also given to illustrate the effective of our results.