nils-herrmann/clean_scirepeval huggingface dataset:
Functional significance of the cortico–subthalamo–pallidal ‘hyperdirect’ pathway

How the motor-related cortical areas modulate the activity of the output nuclei of the basal ganglia is an important issue for understanding the mechanisms of motor control by the basal ganglia. The cortico-subthalamo-pallidal 'hyperdirect' pathway conveys powerful excitatory effects from the motor-related cortical areas to the globus pallidus, bypassing the striatum, with shorter conduction time than effects conveyed through the striatum. We emphasize the functional significance of the 'hyperdirect' pathway and propose a dynamic 'center-surround model' of basal ganglia function in the control of voluntary limb movements. When a voluntary movement is about to be initiated by cortical mechanisms, a corollary signal conveyed through the cortico-subthalamo-pallidal 'hyperdirect' pathway first inhibits large areas of the thalamus and cerebral cortex that are related to both the selected motor program and other competing programs. Then, another corollary signal through the cortico-striato-pallidal 'direct' pathway disinhibits their targets and releases only the selected motor program. Finally, the third corollary signal possibly through the cortico-striato-external pallido-subthalamo-internal pallidal 'indirect' pathway inhibits their targets extensively. Through this sequential information processing, only the selected motor program is initiated, executed and terminated at the selected timing, whereas other competing programs are canceled.
Concept definition for student profile forming

The paper presents possibilities and concepts of a university student professional profile forming with a possible implementation in form of a decision support system (DSS). Depending on the obligatory courses, requested by law or university standards, the general background of the profile is created. The variability of profile forming is assured by voluntary and partially voluntary choice of courses that students take each semester. The novelty of proposed concept lies in the possibilities to use various decision-making algorithms and methods for profile forming. The concept is based on empirical observations, theoretical assumptions, strongly on the theory of decision making and its properties.
When Cryptocurrencies Mine Their Own Business

Bitcoin and hundreds of other cryptocurrencies employ a consensus protocol called Nakamoto consensus which reward miners for maintaining a public blockchain. In this paper, we study the security of this protocol with respect to rational miners and show how a minority of the computation power can incentivize the rest of the network to accept a blockchain of the minority’s choice. By deviating from the mining protocol, a mining pool which controls at least 38.2% of the network’s total computational power can, with modest financial capacity, gain mining advantage over honest mining. Such an attack creates a longer valid blockchain by forking the honest blockchain, and the attacker’s blockchain need not disrupt any “legitimate” non-mining transactions present on the honest blockchain. By subverting the consensus protocol, the attacking pool can double-spend money or simply create a blockchain that pays mining rewards to the attacker’s pool. We show that our attacks are easy to encode in any Nakamoto-consensus-based cryptocurrency which supports a scripting language that is sufficiently expressive to encode its own mining puzzles.
Intelligent irrigation system — An IOT based approach

The Internet of Things (IOT) has been denoted as a new wave of information and communication technology (ICT) advancements. The IOT is a multidisciplinary concept that encompasses a wide range of several technologies, application domains, device capabilities, and operational strategies, etc. The ongoing IOT research activities are directed towards the definition and design of standards and open architectures which is still have the issues requiring a global consensus before the final deployment. This paper gives over view about IOT technologies and applications related to agriculture with comparison of other survey papers and proposed a novel irrigation management system. Our main objective of this work is to for Farming where various new technologies to yield higher growth of the crops and their water supply. Automated control features with latest electronic technology using microcontroller which turns the pumping motor ON and OFF on detecting the dampness content of the earth and GSM phone line is proposed after measuring the temperature, humidity, and soil moisture.
Targeted gene expression in dopamine and serotonin neurons of the mouse brain

We used a knock-in strategy to generate two lines of mice expressing Cre recombinase under the transcriptional control of the dopamine transporter promoter (DAT-cre mice) or the serotonin transporter promoter (SERT-cre mice). In DAT-cre mice, immunocytochemical staining of adult brains for the dopamine-synthetic enzyme tyrosine hydroxylase and for Cre recombinase revealed that virtually all dopaminergic neurons in the ventral midbrain expressed Cre. Crossing DAT-cre mice with ROSA26-stop-lacZ or ROSA26-stop-YFP reporter mice revealed a near perfect correlation between staining for tyrosine hydroxylase and beta-galactosidase or YFP. YFP-labeled fluorescent dopaminergic neurons could be readily identified in live slices. Crossing SERT-cre mice with the ROSA26-stop-lacZ or ROSA26-stop-YFP reporter mice similarly revealed a near perfect correlation between staining for serotonin-synthetic enzyme tryptophan hydroxylase and beta-galactosidase or YFP.  Cre expression in the thalamus and cortex was observed, reflecting the known pattern of transient SERT expression during early postnatal development. These findings suggest a general strategy of using neurotransmitter transporter promoters to drive selective Cre expression and thus control mutations in specific neurotransmitter systems. Crossed with fluorescent-gene reporters, this strategy tags neurons by neurotransmitter status, providing new tools for electrophysiology and imaging.
Is backhaul becoming a bottleneck for green wireless access networks?

Mobile operators are facing an exponential traffic growth due to the proliferation of portable devices that require a high-capacity connectivity. This, in turn, leads to a tremendous increase of the energy consumption of wireless access networks. A promising solution to this problem is the concept of heterogeneous networks, which is based on the dense deployment of low-cost and low-power base stations, in addition to the traditional macro cells. However, in such a scenario the energy consumed by the backhaul, which aggregates the traffic from each base station towards the metro/core segment, becomes significant and may limit the advantages of heterogeneous network deployments. This paper aims at assessing the impact of backhaul on the energy consumption of wireless access networks, taking into consideration different data traffic requirements (i.e., from todays to 2020 traffic levels). Three backhaul architectures combining different technologies (i.e., copper, fiber, and microwave) are considered. Results show that backhaul can amount to up to 50% of the power consumption of a wireless access network. On the other hand, hybrid backhaul architectures that combines fiber and microwave performs relatively well in scenarios where the wireless network is characterized by a high small-base-stations penetration rate.
Does sexual selection explain human sex differences in aggression?

I argue that the magnitude and nature of sex differences in aggression, their development, causation, and variability, can be better explained by sexual selection than by the alternative biosocial version of social role theory. Thus, sex differences in physical aggression increase with the degree of risk, occur early in life, peak in young adulthood, and are likely to be mediated by greater male impulsiveness, and greater female fear of physical danger. Male variability in physical aggression is consistent with an alternative life history perspective, and context-dependent variability with responses to reproductive competition, although some variability follows the internal and external influences of social roles. Other sex differences, in variance in reproductive output, threat displays, size and strength, maturation rates, and mortality and conception rates, all indicate that male aggression is part of a sexually selected adaptive complex. Physical aggression between partners can be explained using different evolutionary principles, arising from the conflicts of interest between males and females entering a reproductive alliance, combined with variability following differences in societal gender roles. In this case, social roles are particularly important since they enable both the relatively equality in physical aggression between partners from Western nations, and the considerable cross-national variability, to be explained.
What you ask is what you get: Understanding architecturally significant functional requirements

Software architects are responsible for designing an architectural solution that satisfies the functional and non-functional requirements of the system to the fullest extent possible. However, the details they need to make informed architectural decisions are often missing from the requirements specification. An earlier study we conducted indicated that architects intuitively recognize architecturally significant requirements in a project, and often seek out relevant stakeholders in order to ask Probing Questions (PQs) that help them acquire the information they need. This paper presents results from a qualitative interview study aimed at identifying architecturally significant functional requirements' categories from various business domains, exploring relevant PQs for each category, and then grouping PQs by type. Using interview data from 14 software architects in three countries, we identified 15 categories of architecturally significant functional requirements and 6 types of PQs. We found that the domain knowledge of the architect and her experience influence the choice of PQs significantly. A preliminary quantitative evaluation of the results against real-life software requirements specification documents indicated that software specifications in our sample largely do not contain the crucial architectural differentiators that may impact architectural choices and that PQs are a necessary mechanism to unearth them. Further, our findings provide the initial list of PQs which could be used to prompt business analysts to elicit architecturally significant functional requirements that the architects need.
Combining Independent Modules to Solve Multiple-choice Synonym and Analogy Problems

Existing statistical approaches to natural language problems are very coarse approximations to the true complexity of language processing. As such, no single technique will be best for all problem instances. Many researchers are examining ensemble methods that combine the output of successful, separately developed modules to create more accurate solutions. This paper examines three merging rules for combining probability distributions: the well known mixture rule, the logarithmic rule, and a novel product rule. These rules were applied with state-of-the-art results to two problems commonly used to assess human mastery of lexical semantics—synonym questions and analogy questions. All three merging rules result in ensembles that are more accurate than any of their component modules. The differences among the three rules are not statistically significant, but it is suggestive that the popular mixture rule is not the best rule for either of the two problems.
Encoding color information for visual tracking: Algorithms and benchmark

While color information is known to provide rich discriminative clues for visual inference, most modern visual trackers limit themselves to the grayscale realm. Despite recent efforts to integrate color in tracking, there is a lack of comprehensive understanding of the role color information can play. In this paper, we attack this problem by conducting a systematic study from both the algorithm and benchmark perspectives. On the algorithm side, we comprehensively encode 10 chromatic models into 16 carefully selected state-of-the-art visual trackers. On the benchmark side, we compile a large set of 128 color sequences with ground truth and challenge factor annotations (e.g., occlusion). A thorough evaluation is conducted by running all the color-encoded trackers, together with two recently proposed color trackers. A further validation is conducted on an RGBD tracking benchmark. The results clearly show the benefit of encoding color information for tracking. We also perform detailed analysis on several issues, including the behavior of various combinations between color model and visual tracker, the degree of difficulty of each sequence for tracking, and how different challenge factors affect the tracking performance. We expect the study to provide the guidance, motivation, and benchmark for future work on encoding color in visual tracking.
Measurement properties of Skindex-16: a brief quality-of-life measure for patients with skin diseases.

An accurate, sensitive, but brief quality-of-life outcomes measure is needed for studies of dermatologic care.



To construct a single-page version of Skindex (a dermatologic quality-of-life instrument) that would have two new features compared with the current 29-item version: (1) fewer items to which a majority of patients choose the same response, and (2) measurement of bother rather than frequency of patient experiences.



Random samples of patients waiting for dermatology appointments in clinics of Veterans Affairs hospitals and in private dermatology practices completed questionnaires; 692 patients responded to the parent instrument and 541 additional patients responded to the brief version. Reproducibility, internal consistency reliability, validity, and responsiveness of the brief version of Skindex were determined.



For 16 items of the current 29-item version (55%), more than 50% of patients responded "Never." After an explicit process of item analysis and elimination, a single-page 16-item version was composed that asks patients about bother from their experiences; responses are reported as three scales, Symptoms, Emotions, and Functioning. For 6 items of the 16-item version (38%), more than 50% of patients responded "Never." Scale scores were reproducible after 72 hours (r = 0.88-0.90) and were internally reliable (Cronbach's alpha = 0.86-0.93). The instrument demonstrated both content and construct validity: Most patients' responses to an open-ended question about their skin disease was addressed by the items; patients with inflammatory dermatoses had higher scores than those with isolated lesions; and in an exploratory principal axes factor analysis with an oblique rotation, 74% of the common variance was explained by three factors that correlated with the a priori scales. Mean scale scores stayed the same or changed in the expected direction in patients who reported that their skin was the same or had improved.



This brief single-page version of Skindex accurately and sensitively measures how much patients are bothered by their skin conditions.
AquaOptical: A lightweight device for high-rate long-range underwater point-to-point communication

This paper describes AquaOptical, an underwater optical communication system. Three optical modems have been developed: a long range system, a short range system, and a hybrid. We describe their hardware and software architectures and highlight trade-offs. We present pool and ocean experiments with each system. In clear water AquaOptical was tested to achieve a data rate of 1.2Mbit/sec at distances up to 30m. The system was not tested beyond 30m. In water with visibility estimated at 3m AquaOptical achieved communication at data rates of 0.6Mbit/sec at distances up to 9m.
Predicting Scene Parsing and Motion Dynamics in the Future

The ability of predicting the future is important for intelligent systems, e.g. autonomous vehicles and robots to plan early and make decisions accordingly. Future scene parsing and optical flow estimation are two key tasks that help agents better understand their environments as the former provides dense semantic information, i.e. what objects will be present and where they will appear, while the latter provides dense motion information, i.e. how the objects will move. In this paper, we propose a novel model to simultaneously predict scene parsing and optical flow in unobserved future video frames. To our best knowledge, this is the first attempt in jointly predicting scene parsing and motion dynamics. In particular, scene parsing enables structured motion prediction by decomposing optical flow into different groups while optical flow estimation brings reliable pixel-wise correspondence to scene parsing. By exploiting this mutually beneficial relationship, our model shows significantly better parsing and motion prediction results when compared to well-established baselines and individual prediction models on the large-scale Cityscapes dataset. In addition, we also demonstrate that our model can be used to predict the steering angle of the vehicles, which further verifies the ability of our model to learn latent representations of scene dynamics.
Influences of diet and the gut microbiome on epigenetic modulation in cancer and other diseases

Epigenetic modulation of gene activity occurs in response to non-genetic factors such as body weight status, physical activity, dietary factors, and environmental toxins. In addition, each of these factors is thought to affect and be affected by the gut microbiome. A primary mechanism that links these various factors together in mediating control of gene expression is the production of metabolites that serve as critical cofactors and allosteric regulators of epigenetic processes. Here, we review the involvement of the gut microbiota and its interactions with dietary factors, many of which have known cellular bioactivity, focusing on particular epigenetic processes affected and the influence they have on human health and disease, particularly cancer and response to treatment. Advances in DNA sequencing have expanded the capacity for studying the microbiome. Combining this with rapidly improving techniques to measure the metabolome provides opportunities to understand complex relationships that may underlie the development and progression of cancer as well as treatment-related sequelae. Given broad reaching and fundamental biology, both at the cellular and organismal levels, we propose that interactive research programs, which utilize a wide range of mutually informative experimental model systems—each one optimally suited for answering particular questions—provide the best path forward for breaking ground on new knowledge and ultimately understanding the epigenetic significance of the gut microbiome and its response to dietary factors in cancer prevention and therapy.
Reproduction and spawning behavior of the climbing perch Anabas testudineus (Perciformes, Anabantidae) in an aquarium

Results of study of the spawning and reproductive behavior of the climbing perch Anabas testudineus in an aquarium are presented. Main specific features of reproduction of this species are revealed. In the performed experiments, climbing perches did not build a nest, did not prepare a spawning substrate, and did not show any forms of parental care. The pre-spawning and spawning behavior of the climbing perch is described, and fecundity and gonadosomatic index are determined. It is shown that intermittent spawning is typical of these fish. Mating system of the climbing perch is either polygamy or promiscuity. Sexual dimorphism in the climbing perch was not found. The eggs of the climbing perch have positive buoyancy and belong to the really pelagic type, which is rare for freshwater fish. Infanticide is a common phenomenon for the climbing perch. Breeding of the given species under aquarium conditions can be exercised without artificial hormonal stimulation, at different sex ratio, and under conditions of stocking density considerably exceeding standard aquacultural recommendations. The main specific features of reproduction of the climbing perch are discussed in relation to evolution of parental care in labyrinth fishes.
Multiple-model adaptive estimation using a residual correlation Kalman filter bank

A multiple model adaptive estimator (MMAE) [1, 2, 6, 8, 9, 11] consists of a bank of parallel Kalman filters, each with a different model, and a hypothesis testing algorithm as shown in Fig. 1. Each of the internal models of the Kalman filters can be represented by a discrete value of a parameter vector (ak; k= 1,2 ,K). The Kalman filters are provided a measurement vector (z) and the input vector (u), and produce a state estimate (x̂k) and a residual (rk). The hypothesis testing algorithm uses the residuals to compute conditional probabilities (pk) of the various hypotheses that are modeled in the Kalman filters, conditioned on the history of measurements received up to that time, and to compute an estimate of the true parameter vector (â). The conventional MMAE computes conditional probabilities (pk) in a manner that exploits three of four characteristics of Kalman filter residuals that are based on a correctly modeled hypothesis—that they should be Gaussian, zero-mean, and of computable covariance—but does not exploit the fact that they should also be white. The algorithm developed herein addresses this directly, yielding a complement to the conventional MMAE. One application of MMAE is flight control sensor/actuator failure detection and identification, where each Kalman filter has a different failure status model (ak) that it uses to form the state estimate (x̂k) and the residual (rk). The hypothesis testing algorithm assigns conditional probabilities (pk) to each of the hypotheses that were used to form the Kalman filter models. These conditional probabilities indicate the relative correctness of the various filter models, and can be used to select the best estimate of the true system failure status, weight the individual state estimates appropriately, and form a probability-weighted average state estimate (x̂MMAE). A primary objection to implementing an MMAE-based (or other) failure detection algorithm is the need to dither the system constantly to enhance failure identifiability. The MMAE compares the magnitudes of the residuals (appropriately scaled to account for various uncertainties and noises) from the various filters and chooses the hypothesis that corresponds to the residual that has a history of having smallest (scaled) magnitude. Large residuals must be produced by the filters with models that are incorrect to be able to discount these incorrect hypotheses. The residual is the difference between the measurement of the system output and the filter’s prediction of what that measurement should be, based on the filter-assumed system model. Therefore, to produce the needed large residuals in the incorrect filters, we need to produce a history of sufficiently large system outputs, so we need to dither the system constantly and thereby