Miracle-dz/UniFAR-FTUs huggingface dataset:
Human-to-Animal Similarity and Participant Mood Influence Punishment Recommendations for Animal Abusers

Studies of observer responses to human-to-human abuse have found that both an observer's mood and the similarity of the victim to the observer affect the observer's desire to help the victim and punish the offender. The present study examined the extent to which similarity and mood also shape observer responses to human-to-animal abuse.We first manipulated participants' mood by giving non-contingent feedback on a hidden word task (positive, negative, or no feedback). Participants then read a scenario describing an instance of animal abuse (using four different specific kinds of animals and six general species categories). Results showed that participants in a better mood recommended harsher punishment for the offender.They also recommended harsher punishment for the abuse of animals more similar to humans. Similarity and mood interacted on fine recommendationsmdash;better mood accentuated the similarity effect. Empathy for an animal positively correlated with punishment recommendations for the offender. The study discusses directions for future research and theory development.
The evolution of phenotypic plasticity when environments fluctuate in time and space

Most studies have explored the evolution of plasticity when the environment, and there-fore the optimal trait, varies in time or space. When the environment varies in time and space we show that genetic adaptation to temporal fluctuations depends on the between-generation autocorrelation in the environment in exactly the same way that genetic adaptation to spatial fluctuations depends on the probability of philopatry. This is because both measure the correlation in parent-offspring environments and therefore the effectiveness of a genetic response to selection. If the capacity to genetically respond to selection is stronger in one dimension (e.g. space) then plasticity mainly evolves in response to fluctuations in the other dimension (e.g. time). If the relationship between the environments of development and selection are the same in time and space then the evolved plastic response to temporal fluctuations is useful in a spatial context and genetic differentiation in space is reduced. However, if the relationship between the environments of development and selection are different then the optimal level of plasticity is different in the two dimensions. In this case the plastic response that evolves to cope with temporal fluctuations may actually be maladaptive in space. This can result in the evolution of hyperplasticity or negative plasticity, the effects of which are mitigated by spatial genetic differentiation. However, genetic differentiation acts in opposition to plasticity resulting in counter-gradient variation. These results highlight the difficulty of making space-for-time substitutions in empirical work but identify the key parameters which need to be measured in order to test whether space-for-time substitutions are likely to be valid.
Non-engineered and Engineered Adult Neurogenesis in Mammalian Brains

Adult neurogenesis has been extensively studied in rodent animals, with distinct niches found in the hippocampus and subventricular zone (SVZ). In non-human primates and human postmortem samples, there has been heated debate regarding adult neurogenesis, but it is largely agreed that the rate of adult neurogenesis is much reduced comparing to rodents. The limited adult neurogenesis may partly explain why human brains do not have self-repair capability after injury or disease. A new technology called “in vivo cell conversion” has been invented to convert brain internal glial cells in the injury areas directly into functional new neurons to replenish the lost neurons. Because glial cells are abundant throughout the brain and spinal cord, such engineered glia-to-neuron conversion technology can be applied throughout the central nervous system (CNS) to regenerate new neurons. Thus, compared to cell transplantation or the non-engineered adult neurogenesis, in vivo engineered neuroregeneration technology can provide a large number of functional new neurons in situ to repair damaged brain and spinal cord.
A general framework for discrete variable representation basis sets

A framework for discrete variable representation (DVR) basis sets is developed that is suitable for multidimensional generalizations. Those generalizations will be presented in future publications. The new axiomatization of the DVR construction places projection operators in a central role and integrates semiclassical and phase space concepts into the basic framework. Rates of convergence of basis set expansions are emphasized, and it is shown that the DVR method gives exponential convergence, assuming conditions of analyticity and boundary conditions are met. A discussion of nonorthogonal generalizations of DVR functions is presented, in which it is shown that projected δ-functions and interpolating functions form a biorthogonal basis. It is also shown that one of the generalized DVR proposals due to Szalay [J. Chem. Phys. 105, 6940 (1996)] gives exponential convergence.
REL-AT: A relational-attentional account of consciousness

In this paper I will try to show that (i) consciousness makes a difference to human behaviour; (ii) the main difference it makes, is to provide us with the sense of self; (iii) this sense of self is produced because consciousness allows us to relate ourselves to other entities, and therefore to understand what kinds of relations exist between us and them; (iv) the basic mechanism that allows us to relate ourselves to other entities, place things in relation to each other, and more in general have conscious experiences, is represented by variations in the state of nervous energy elicited by the use of attention; by attentional acting, we produce conscious experiences in the form of either a constraint or a freedom (to act in general). Finally I will show that the principal means by which variations in the state of nervous energy are used to put things in relation, is that of serving as a basis for the construction of possible orders (such as space and time).
Decomposition of juvenile-sized remains: a macro- and microscopic perspective

Abstract There is currently a dearth of research investigating the progression and rate of decomposition for juvenile remains. It is thought that juveniles and infants decompose at an increased rate relative to adults due simply to body mass and that skeletal preservation is commonly dependent on intrinsic levels of bone mineral density (BMD). This study investigates the environmental variables important in driving juvenile decomposition as well as examining if currently accepted methodology for quantifying adult decomposition can be applied to juvenile remains. Furthermore, histological analysis is undertaken to test the Histological Index (HI) as a semi-quantitative indicator of decomposition. Thirty-five Sus scrofa ranging between 1.8 and 22.7 kg were deposited to simulate body mass of human infant and juvenile remains. Pigs were deposited every season over two years in the southeastern US with five depositional types: bagged, blanket wrapped, and surface control foetal remains, surface, and buried juvenile remains. Remains were scored quantitatively throughout soft tissue decomposition. Following study completion and skeletonization, a femur was selected from each set of remains for histological analysis. Thick sections were assessed under standard brightfield light and scored using Oxford Histological Index (OHI). Results indicate that seasonal variation is an important factor to consider even when using a standardized time variable such as accumulated degree days (ADD), particularly variation in soil moisture. Soil moisture was a consistent significant variable in the mixed effects model. The pattern of decomposition using total body score (TBS) was similar to that observed by others prior to log transformation with a rapid incline early in decomposition with levelling off. The correlation between time in days, ADD, and TBS was not as strong as those previously reported (R2 = 0.317 and 0.499, respectively) suggesting that TBS as it is currently formulated cannot be directly applied to juvenile remains. Finally, the OHI model performed moderately well, but was variable even within seasons across multiple years.
Nutritional status of Korean elderly with dementia in a long-term care facility in Hongseong

BACKGROUND/OBJECTIVES This study investigated nutritional status of the elderly with dementia in a care facility with the aim of improving the meal quality of the facility. SUBJECTS/METHODS Data were collected from 30 dementia patients aged more than 65 years in a long-term care facility in Hongseong. The data were obtained from questionnaires and medical records. The food intake data was obtained using food photographs and the nutrient intakes were calculated using the CAN-Pro 5.0. The data were compared with the dietary reference intakes for Koreans (KDRIs). The nutrient density, diet quality such as nutrient adequacy ratio (NAR), mean adequacy ratio (MAR), and index of nutritional quality (INQ), as well as dietary diversity score (DDS) were evaluated. The data were analyzed using SPSS statistical programs. RESULTS The average daily energy intakes for men and women were much lower than the estimated energy requirements of the KDRIs. The average intakes of energy and most nutrients in the general diet group were significantly higher than those of the other two groups. Significant differences in diet quality and diet diversity were observed according to the meal type groups. The NARs of some minerals (calcium, iron, and zinc) and vitamins (vitamin B6 and folic acid) were less than 0.5 in all study groups. The NARs of protein, iron and MAR of the general diet group were significantly higher than those of the liquid diet group. The DDS scores of meats, fruits and diary food group were very low in all meal type groups, meaning that the diet qualities of the study subjects were not appropriate in all meal type groups. CONCLUSIONS The food intakes of the study groups showed some limitations by a direct comparison with KDRIs because of the very low physical activities of the study subjects. The diet quality and diet diversity indices suggest the need for improvements in the nutritional quality in all types of diet. Overall, new intervention strategies targeting facility residents with dementia in Korea are needed as soon as possible.
Robustness of a biomolecular oscillator to pulse perturbations

Biomolecular oscillators can function robustly in the presence of environmental perturbations, which can either be static or dynamic. While the effect of different circuit parameters and mechanisms on the robustness to steady perturbations has been investigated, the scenario for dynamic perturbations is relatively unclear. To address this, the authors use a benchmark three protein oscillator design – the repressilator – and investigate its robustness to pulse perturbations, computationally as well as use analytical tools of Floquet theory. They found that the metric provided by direct computations of the time it takes for the oscillator to settle after pulse perturbation is applied, correlates well with the metric provided by Floquet theory. They investigated the parametric dependence of the Floquet metric, finding that the parameters that increase the effective delay enhance robustness to pulse perturbation. They found that the structural changes such as increasing the number of proteins in a ring oscillator as well as adding positive feedback, both of which increase effective delay, facilitates such robustness. These results highlight such design principles, especially the role of delay, for designing an oscillator that is robust to pulse perturbation.
Upper extremity health profile in Turkish overhead throwing athletes: the effect of current level of play, sports participation, sports type, and previous injury

Amac: Bu calismanin amaci Turk bas ustu firlatma sporcularinda ust ekstremite saglik profili uzerine oyun seviyesi, spora katilim, spor dali ve yaralanma hikayesinin etkisini arastirmakti. Yontem: Calismaya 134 bas ustu firlatma sporcusu dahil edildi. Ust ekstremite agri varligi ve siddeti, ozur seviyesi ve fonksiyonel aktivite duzeyi Kol, Omuz ve El Sorunlari Anketi (DASH) ve Amerikan Omuz ve Dirsek Cerrahlari Degerlendirme Formu (ASES) kullanilarak degerlendirildi. Bulgular: Katilimcilarin % 41,8’inde ust ekstremite sorunlari gozlendi. Oyun seviyesine ve onceki yaralanma hikayesine gore gruplara ayrilan bireyler karsilastirildiginda DASH ve ASES skorlarinda farkliliklar gozlendi (p 0,05). Sonuc: Bas ustu firlatma sporcularinda ust ekstremite problemleri yuksek oranda gozlenmektedir. Bu calisma Turk bas ustu firlatma sporcularinda ust ekstremite saglik profilini belirlemis ve boylelikle sporla iliskili ust ekstremite yaralanmalarinin onlenmesi acisindan bilgi saglamistir.
A Random Subspace Technique That Is Resistant to a Limited Number of Features Corrupted by an Adversary

In this paper, we consider batch supervised learning where an adversary is allowed to corrupt instances with arbitrarily large noise. The adversary is allowed to corrupt any $l$ features in each instance and the adversary can change their values in any way. This noise is introduced on test instances and the algorithm receives no label feedback for these instances. We provide several subspace voting techniques that can be used to transform existing algorithms and prove data-dependent performance bounds in this setting. The key insight to our results is that we set our parameters so that a significant fraction of the voting hypotheses do not contain corrupt features and, for many real world problems, these uncorrupt hypotheses are sufficient to achieve high accuracy. We empirically validate our approach on several datasets including three new datasets that deal with side channel electromagnetic information.
Deep Learning Segmentation and 3D Reconstruction of Road Markings Using Multiview Aerial Imagery

The 3D information of road infrastructures is growing in importance with the development of autonomous driving. In this context, the exact 2D position of road markings as well as height information play an important role in, e.g., lane-accurate self-localization of autonomous vehicles. In this paper, the overall task is divided into an automatic segmentation followed by a refined 3D reconstruction. For the segmentation task, we applied a wavelet-enhanced fully convolutional network on multiview high-resolution aerial imagery. Based on the resulting 2D segments in the original images, we propose a successive workflow for the 3D reconstruction of road markings based on a least-squares line-fitting in multiview imagery. The 3D reconstruction exploits the line character of road markings with the aim to optimize the best 3D line location by minimizing the distance from its back projection to the detected 2D line in all the covering images. Results showed an improved IoU of the automatic road marking segmentation by exploiting the multiview character of the aerial images and a more accurate 3D reconstruction of the road surface compared to the semiglobal matching (SGM) algorithm. Further, the approach avoids the matching problem in non-textured image parts and is not limited to lines of finite length. In this paper, the approach is presented and validated on several aerial image data sets covering different scenarios like motorways and urban regions.
Perfect reconstruction of sparse signals with piecewise continuous nonconvex penalties and nonconvexity control

We consider a reconstruction problem of sparse signals from a smaller number of measurements than the dimension formulated as a minimization problem of nonconvex sparse penalties: smoothly clipped absolute deviations and minimax concave penalties. The nonconvexity of these penalties is controlled by nonconvexity parameters, and the ℓ 1 penalty is contained as a limit with respect to these parameters. The analytically-derived reconstruction limit overcomes that of the ℓ 1 limit and is also expected to overcome the algorithmic limit of the Bayes-optimal setting when the nonconvexity parameters have suitable values. However, for small nonconvexity parameters, where the reconstruction of the relatively dense signals is theoretically expected, the algorithm known as approximate message passing (AMP), which is closely related to the analysis, cannot achieve perfect reconstruction leading to a gap from the analysis. Using the theory of state evolution, it is clarified that this gap can be understood on the basis of the shrinkage in the basin of attraction to the perfect reconstruction and also the divergent behavior of AMP in some regions. A part of the gap is mitigated by controlling the shapes of nonconvex penalties to guide the AMP trajectory to the basin of the attraction.
Walking with adaptive augmented reality workspaces: design and usage patterns

Mobile augmented reality may eventually replace our smartphones as the primary way of accessing information on the go. However, current interfaces provide little support to walking and to the variety of actions we perform in the real world. To achieve its full potential, augmented reality interfaces must support the fluid way we move and interact in the physical world. We explored how different adaptation strategies can contribute towards this goal. We evaluated design alternatives through contextual studies and identified the key interaction patterns that interfaces for walking should support. We also identified desirable properties of adaptation-based interface techniques, which can be used to guide the design of the next-generation walking-centered augmented reality workspaces.
Non-Parametric Cell-Based Photometric Proxies for Galaxy Morphology: Methodology and Application to the Morphologically-Defined Star Formation -- Stellar Mass Relation of Spiral Galaxies in the Local Universe

We present a non-parametric cell-based method of selecting highly pure and largely complete samples of spiral galaxies using photometric and structural parameters as provided by standard photometric pipelines and simple shape fitting algorithms. The performance of the method is quantified for different parameter combinations, using purely human-based classifications as a benchmark. The discretization of the parameter space allows a markedly superior selection than commonly used proxies relying on a fixed curve or surface of separation. Moreover, we find structural parameters derived using passbands longwards of the g band and linked to older stellar populations, especially the stellar mass surface density μ* and the r-band effective radius re, to perform at least equally well as parameters more traditionally linked to the identification of spirals by means of their young stellar populations, e.g. UV/optical colours. In particular, the distinct bimodality in the parameter μ*, consistent with expectations of different evolutionary paths for spirals and ellipticals, represents an often overlooked yet powerful parameter in differentiating between spiral and non-spiral/elliptical galaxies. We use the cell-based method for the optical parameter set including re in combination with the Sersic index n and the i-band magnitude to investigate the intrinsic specific star formation rate-stellar mass relation (Φ*-M*) for a morphologically defined volume-limited sample of local Universe spiral galaxies. The relation is found to be well described by Φ* α M-0.5 * over the range of 109.5 ≤ M* ≤ 1011M⊙ with a mean interquartile range of 0.4 dex. This is somewhat steeper than previous determinations based on colour-selected samples of starforming galaxies, primarily due to the inclusion in the sample of red quiescent discs. © 2013 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.
Air Quality Measurement Based on Double-Channel Convolutional Neural Network Ensemble Learning

Environmental air quality affects people’s lives and has a profound guiding significance for the development of social activities. At present, environmental air quality measurement mainly adopts the method that setting air quality detectors at specific monitoring points in cities with fix-time sampling and slow analysis, which is severely restricted by the time and location. To address this problem, recognizing air quality with mobile cameras is a natural idea. Some air quality measurement algorithms related to deep learning mostly adopt a single convolutional neural network to directly train the whole image, which will ignore the difference of each part of the image. In this paper, in order to learn the combined feature extracted from different parts of the environmental image, we propose the double-channel weighted convolutional network (DCWCN) ensemble learning algorithm. This mainly includes two aspects: ensemble learning of DCWCN and self-learning weighted feature fusion. Firstly, we construct a double-channel convolutional neural network, which uses each channel to train different parts of the environment images for feature extraction. Secondly, we propose a feature weights self-learning method, which weights and concatenates the extracted feature vectors to measure the air quality. Moreover, we build an environmental image dataset with random sampling time and locations to evaluate our method. The experiments show that our method can achieve over 87% accuracy on the newly built dataset. At the same time, through comparative experiments, we proved that the proposed method achieves considerable improvement in terms of performance compared with existing CNN based methods.
CSR CONTRIBUTION TO SUSTAINABLE DEVELOPMENT IN THE ENERGETIC SECTOR

The paper presents the necessity of developing and applying social, environmental and economical commune standards in order to improve inter-operability and development of commune understanding frameworks. The energetic industry become more and more interested to contribute in a constructive measure at studying and resolving important social and environmental problems provoked by its activities and to encourage the dialogue with the stakeholders, which have increased expectations. Notable progresses were realized at international level regarding increasing the quantity and quality of realized stakeholders consultations, increasing transparency and public awareness having as purpose integrating sustainability in its practices. The paper also studies the financial and economic crises impact on social responsibility practices and relationships between business and society.