Miracle-dz/UniFAR-FTUs huggingface dataset:
Relative Local Mean Classifier with Optimized Decision Rule

Local mean classifier can achieve good effect for many real problems and need not explicitly determine the prototypes beforehand. However, it still can not be comparable with human being in classification on the noisy, the sparse, and the high dimensional data. This paper proposes an new approach, called relative local mean classifier(RLMC), to overcome this problem by utilizing the perceptual relativity. It finds k nearest neighbors for the query sample from each class and then performs the relative transformation over all these nearest neighbors to build the relative space. Subsequently, each local center is computed in the relative space, which is then applied to perform the classification. Experimental results on both real and simulated data validate the proposed approach.
Remote Episodic Memory Deficits in Patients with Unilateral Temporal Lobe Epilepsy and Excisions

The nature of remote memory impairment in patients with medial temporal lobe damage is the subject of some debate. While some investigators have found that retrograde amnesia in such patients is temporally graded, with relative sparing of remote memories (Squire and Alvarez, 1995), others contend that impairment is of very long duration and that remote memories are not necessarily spared (Sanders and Warrington, 1971; Nadel and Moscovitch, 1997). In this study, remote memory was assessed in 25 patients with unilateral temporal lobe epilepsy and 22 non-neurologically impaired controls using the Autobiographical Memory Interview (Kopelman et al., 1989). Results indicate that patients have impaired personal episodic memory but intact personal semantic memory. The impairment extends even to the most remote time periods in early childhood, long before seizure onset in many patients. As well, patients awaiting temporal lobectomy for control of seizures perform as poorly as those who have already undergone resective surgery. These results support the hypothesis that temporal lobe damage or dysfunction, caused by recurrent seizures or surgical excision, results in extensive retrograde amnesia for personal episodic memories. Interestingly, patients with radiological evidence of hippocampal sclerosis were not significantly more impaired than those without obvious sclerosis. These results indicate that even minimal damage to medial temporal lobes results in significant impairment to autobiographical episodic memory. These findings are more compatible with a memory loss or retrieval deficit rather than a consolidation account of remote memory impairment.
Effect of Refrigeration Temperature, Sugar Concentrations and Different Chemicals Preservatives on the Storage Stability of Strawberry Juice

This research was carried out to investigate the effect of sugar concentrations, chemical preservatives, and refrigeration temperature (4-10C) on the physicochemical and sensory attributes of strawberry juice stored for one year. The samples were numbered as, TR24=Strawberry juice (7.5brix) no preservatives (control), TR25=Strawberry juice (7.5brix) with 0.1% sodium benzoate, TR26=Strawberry juice (7.5brix) with 0.1% potassium sorbate, TR27=Strawberry juice (7.5brix) with 0.05% sodium benzoate+0.05% potassium sorbate, TR28=Strawberry juice (20.5brix) no preservatives (control), TR29=Strawberry juice (20.5brix) with 0.1% sodium benzoate, TR30=Strawberry juice (20.5brix) with 0.1% potassium sorbate, TR31=Strawberry juice (20.5brix) with 0.05% sodium benzoate +0.05% potassium sorbate, TR32=Strawberry juice (30.5brix) no preservatives (control), TR33=Strawberry juice (30.5brix) with 0.1% sodium benzoate, TR34=Strawberry juice (30.5brix) with 0.1% potassium sorbate, TR35=Strawberry juice (30.5brix) with 0.05% sodium benzoate +0.05% potassium sorbate. Maximum increase in total soluble solids (TSS) content occurred in TR25 and TR26 (20.00%) while minimum increase was recorded in TR35 (6.55%) during storage. Maximum decrease in pH content occurred in TR24 (19.65%) followed by TR32 (16.30%) while minimum decrease was observed in TR35 (9.51%). Maximum increase in titratable acidity occurred in TR24 (145.92%) followed by TR32 (124.69%) while minimum increase occurred in TR35 (95.06%). Maximum ascorbic acid decreased in TR24 (88.81%) followed by TR32 (79.55%) while minimum decreased was observed in TR35 (64.53%) followed by TR33 (67.46%). Maximum increase in reducing sugar content was recorded in TR34 (30.70%) while minimum increase occurred in TR27 (19.65%). Maximum decrease in non reducing sugar occurred in TR32 (93.65%) followed by TR24 (83.09%) while minimum decrease occurred in TR27 (26.76%). Maximum decrease in color was recorded for TR24 (37.50%) followed by TR32 (31.25%). Flavor deterioration occurred in control samples and maximum decrease was observed in TR24 (87.50) followed by TR32 (62.50%) while concentrated samples showed less loss in flavor during storage. Comparatively better consistency was recorded by sweetened juice. After one year storage, the samples were acceptable to the consumer on the basis of color, flavor, consistency and overall acceptability. Among all the treatments TR24 and TR32 were rejected during storage while TR35 was found most effective followed by TR33 than other samples. Index Term-Strawberry juice, benzoate, sorbate, sucrose, refrigeration temperature.
Comparison of total energy expenditure between the farming season and off farming season and accuracy assessment of estimated energy requirement prediction equation of Korean farmers

BACKGROUND/OBJECTIVES The purposes of this study were to compare total energy expenditure (including PAL and RMR) of Korean farmers between the farming season and off farming season and to assess the accuracy of estimated energy requirement (EER) prediction equation reported in KDRIs. SUBJECTS/METHODS Subjects were 72 Korean farmers (males 23, females 49) aged 30-64 years. Total energy expenditure was calculated by multiplying measured RMR by PAL. EER was calculated by using the prediction equation suggested in KDRIs 2010. RESULTS The physical activity level (PAL) was significantly higher (P < 0.05) in the farming season (male 1.77 ± 0.22, female 1.69 ± 0.24) than the off farming season (male 1.53 ± 0.32, female 1.52 ± 0.19). But resting metabolic rate was significantly higher (P < 0.05) in the off farming season (male 1,890 ± 233 kcal/day, female 1,446 ± 140 kcal/day) compared to the farming season (male 1,727 ± 163 kcal/day, female 1,356 ± 164 kcal/day). TEE (2,304 ± 497 kcal/day) of females was significantly higher in the farming season than that (2,183 ± 389 kcal/day) of the off farming season, but in males, there was no significant difference between two seasons in TEE. On the other hand, EER of male and female (2,825 ± 354 kcal/day and 2,115 ± 293 kcal/day) of the farming season was significantly higher (P < 0.05) than those (2,562 ± 339 kcal/day and 1,994 ± 224 kcal/day) of the off farming season. CONCLUSIONS This study indicates that there is a significant difference in PAL and TEE of farmers between farming and off farming seasons. And EER prediction equation proposed by KDRI 2010 underestimated TEE, thus EER prediction equation for farmers should be reviewed.
Chandra Discovery of a Tree in the X-Ray Forest toward PKS 2155–304: The Local Filament?

We present the first X-ray detection of resonant absorption from warm/hot local gas either in our Galaxy, or in the intergalactic space surrounding our Galaxy, along the line of sight toward the blazar PKS 2155-304. The Chandra HRCS/LETG spectrum of this z = 0.116 source clearly shows, at ≥5 σ level, unresolved (FWHM ≤ 800 km s-1 at a 2 σ confidence level) O VII Kα and Ne IX Kα resonant absorption lines at 21.603 and 13.448 Å (i.e., cz = 14 km s-1 in the rest frame, from the O VII Kα line). O VIII Kα and O VII Kβ from the same system are also detected at a lower significance level (i.e., ~3 σ), while upper limits are set on O VIII Kβ, Ne X Kα, and Ne IX Kβ. The Far Ultraviolet Spectroscopic Explorer spectrum of this source shows complex O VI 2s→2p absorption at the same redshift as the X-ray system, made by at least two components: one relatively narrow (FWHM = 106 ± 9 km s-1) and slightly redshifted (cz = 36 ± 6 km s-1), and one broader (FWHM = 158 ± 26 km s-1) and blueshifted (cz = -135 ± 14 km s-1). We demonstrate that the physical states of the UV and X-ray absorbers are hard to reconcile with a single, purely collisionally ionized, equilibrium plasma. We propose instead that the X-ray and at least the broader and blueshifted UV absorber are produced in a low-density intergalactic plasma, collapsing toward our Galaxy, consistent with the predictions of a warm-hot intergalactic medium from numerical simulations. We find that any reasonable solution requires overabundance of Ne compared to O by a factor of ~2, with respect to the solar value. We propose several scenarios to account for this observation.
3D Reconstruction of Simple Objects from A Single View Silhouette Image

While recent deep neural networks have achieved promising results for 3D reconstruction from a single-view image, these rely on the availability of RGB textures in images and extra information as supervision. In this work, we propose novel stacked hierarchical networks and an end to end training strategy to tackle a more challenging task for the first time, 3D reconstruction from a single-view 2D silhouette image. We demonstrate that our model is able to conduct 3D reconstruction from a single-view silhouette image both qualitatively and quantitatively. Evaluation is performed using Shapenet for the single-view reconstruction and results are presented in comparison with a single network, to highlight the improvements obtained with the proposed stacked networks and the end to end training strategy. Furthermore, 3D re- construction in forms of IoU is compared with the state of art 3D reconstruction from a single-view RGB image, and the proposed model achieves higher IoU than the state of art of reconstruction from a single view RGB image.
Survey in sentiment, polarity and function analysis of citation

In this paper we proposed a survey in sentiment, polarity and function analysis of citations. This is an interesting area that has had an increased development in recent years but still has plenty of room for growth and further research. The amount of scientific information in the web makes it necessary innovate the analysis of the influence of the work of peers and leaders in the scientific community. We present an overview of general concepts, review contributions to the solution of related problems such as context identification, function and polarity classification, identify some trends and suggest possible future research directions.
Framework and Bio-Mechanical Model for a Per-Operative Image-Guided Neuronavigator Including 'Brain-Shift' Compensation

In this paper we present a methodology to adress the problem of brain tissue deformation referred to as "brainshift". This deformation occurs throughout a neurosurgery intervention and strongly alters the accuracy of the neuronavigation systems used to date in clinical routine which rely solely on preoperative patient imaging to locate the surgical target, such as a tumour or a functional area. After a general description of the framework of our intraoperative image-guided system, we propose a biomechanical model of the brain which can take into account interactively such deformations as well as surgical procedures that modify the brain structure, like tumour or tissue resection.
Dynamically dysfunctional protein interactions in the development of Alzheimer's disease

Alzheimer's disease usually causes dementia in the old people and the symptom progression of the disease phenotype displays certain patterns. One possible reason is that the nerve cells in the brains of the patients degenerate at different stages. Here, we analyze the dynamics of disease progression based on its biomolecular network. We develop a novel computational method to integrate an ensemble protein network and the hippocampal gene expression data. Specifically, we construct the induced dynamical pathways which present particular characteristics at different disease stages from the control to disease samples. Based on the network-based method, we reveal that the active pathways tend to be more complicated during the development of disease. Also we find that the disease proteins performing important functions are always located in the cooperations of the identified pathways. These results also demonstrate that the network-based analysis can provide knowledge and evidences on the dynamics and pathological pathways of the complex Alzheimer's disease.
Human Ability to Scale and Discriminate Forces Typical of Those Occurring during Grasp and Manipulation

When humans manipulate objects, the sensorimotor system coordinates three-dimensional forces to optimize and maintain grasp stability. To do this, the CNS requires precise information about the magnitude and direction of load force (tangential to skin surface) plus feedback about grip force (normal to skin). Previous studies have shown that there is rapid, precise coordination between grip and load forces that deteriorates with digital nerve block. Obviously, mechanoreceptive afferents innervating fingerpad skin contribute essential information. We quantify human capacity to scale tangential and normal forces using only cutaneous information. Our paradigm simulated natural manipulations (a force tangential to the skin superimposed on an indenting force normal to the skin). Precisely controlled forces were applied by a custom-built stimulator to an immobilized fingerpad. Using magnitude estimation, subjects (n = 8) scaled the magnitude of tangential force (0.25–2.8 N) in two experiments (normal force, 2.5 and 4 N, respectively). Performance was unaffected by normal force magnitude and tangential force direction. Moreover, when both normal (2–4 N) and tangential forces were varied in a randomized-block factorial design, the relationship between applied and perceived tangential force remained near linear, with a minor but statistically significant nonlinearity. Our subjects could also discriminate small differences in tangential force, and this was the case for two different reference stimuli. In both cases, the Weber fraction was 0.16. Finally, scaling functions for magnitude estimates of normal force (1–5 N) were also approximately linear. These data show that the cutaneous afferents provide a wealth of precise information about both normal and tangential force.
Population genetics of the roan antelope (Hippotragus equinus) with suggestions for conservation

The roan antelope (Hippotragus equinus) is the second largest African antelope, distributed throughout the continent in sub‐Saharan savannah habitat. Mitochondrial DNA (mtDNA) control region sequencing (401 bp, n = 137) and microsatellite genotyping (eight loci, n = 137) were used to quantify the genetic variability within and among 18 populations of this species. The within‐population diversity was low to moderate with an average mtDNA nucleotide diversity of 1.9% and average expected heterozygosity with the microsatellites of 46%, but significant differences were found among populations with both the mtDNA and microsatellite data. Different levels of genetic resolution were found using the two marker sets, but both lent strong support for the separation of West African populations (samples from Benin, Senegal and Ghana) from the remainder of the populations studied across the African continent. Mismatch distribution analyses revealed possible past refugia for roan in the west and east of Africa. The West African populations could be recognized together as an evolutionarily significant unit (ESU), referable to the subspecies H. e. koba. Samples from the rest of the continent constituted a geographically more diverse assemblage with genetic associations not strictly corresponding to the other recognized subspecies.
Alternate Equivalent Substitutes : Recognition of Synonyms Using Word Vectors

The task of computationally learning the linguistic application of a word requires a robust analysis of both the word’s semantic presence and its independent characteristics. Word vectors are learned, functional representation of words which can then be analyzed for linguistic regularities. We examine whether the synonyms of a word can be recognized from their word vectors by training a neural network on a large corpus of text, then implementing k-means clustering to check whether synonyms have a statistically significant word vector similarity. We illustrate the output using a simplified version of the vectors generated by principal component analysis. Results suggest that increasing vector length, which improves syntactic and semantic accuracy when performing comparisons of words, negatively correlates with synonym recognition.
Semi‐Uniform Adaptive Patch Tessellation

We present an adaptive tessellation scheme for surfaces consisting of parametric patches. The resulting tessellations are topologically uniform, yet consistent and watertight across boundaries of patches with different tessellation levels. Our scheme is simple to implement, requires little memory and is well suited for instancing, a feature available on current Graphical Processing Units that allows a substantial performance increase. We describe how the scheme can be implemented efficiently and give performance benchmarks comparing it to some other approaches.
A Knowledge Engineering Method for Track Initiation in Complex Conditions

In a complex environment radar plot is often changing dramatically, non-uniform, discontinuous, uncertain and containing lots of false alarms. It is difficult for tracking system to form tracks in such complex environment. Traditional track formation methods can not accurately determine the size of track initiation gate and select specific initiation criteria. In this paper, an intelligent information processing method is proposed to solve track initiation in complex environments. The track initiation is considered as a progress of plot identification, classification and fuzzy information processing. According to the integration and fusion of neural network (NN), fuzzy reasoning (FR) and expert system (ES) technology, an intellectualized track initiation knowledge reasoning system is constructed which can realize structural, functional, algorithmic and hierarchical complementation. Further more the adaptive robust learning algorithm and the weighted synthesis reasoning algorithm are used in this system. Real data experiment shows that the proposed knowledge engineering method can effectively solve track initiation problem in complex conditions.
A compact AWPC antenna for DOA estimation

Antennas without phase center (AWPC) have been used for Direction-of-Arrival estimation. However, these structures, being symmetric, always face the whole-space ambiguity problem. This paper proposes a new asymmetric AWPC structure for DOA estimation that is able to resolve the ambiguity in the whole space. In addition, the structure is optimized in such a way that it is compact and isotropic. Simulated results indicate the effectiveness of the proposed structure.
A new vehicle detection method

This paper presents a new vehicle detection method from images acquired by cameras embedded in a moving vehicle. Given the sequence of images, the proposed algorithms should detect out all cars in realtime. Related to the driving direction, the cars can be classified into two types. Cars drive in the same direction as the intelligent vehicle (IV) and cars drive in the opposite direction. Due to the distinct features of these two types, we suggest to achieve this method in two main steps. The first one detects all obstacles from images using the so-called association combined with corner detector. The second step is applied to validate each vehicle using AdaBoost classifier. The new method has been applied to different images data and the experimental results validate the efficacy of our method.
The Shape of Things to Come: Inspiration in the Organizational Sciences

Moments of inspiration are powerful in that they give us a renewed sense of energy and purpose. They also orient us to move in directions that we never thought possible. Most of the research in the organizational sciences has focused on inspiration as a leadership process in which a leader inspires followers by engaging in inspirational behaviors. This simplification leads to interpretation of inspiration as a one dimensional construct placed exclusively inside the leadership development literature. However, research in psychology shows that inspiration may be a multi-dimensional construct as well as a construct applicable outside of leader-follower relationships. The purpose of this paper is to introduce and operationally define inspiration, to introduce an initial nomological network of inspiration in a work context, and to provide future research directions that will enhance our understanding of the complexity of the construct.
Stitching line and deformation propagation for seamless image stitching

This paper presents an approach to determine the optimal stitching line and propagate deformation in irregular overlap for image stitching. First, determine the optimal stitching line that has the lowest cost of some candidate lines in the irregular region; second, detect and match the features in the neighborhood of the optimal stitching line and calculate deformation vectors; finally, spread the deformation vectors to the whole of image region by Poisson equation and constitute the image gradient field that can reconstruct seamless mosaic. This method has no limitation to the shape of the overlapping area so can reduce the juncture of structure and color in the stitching images. Compared with other methods this method can achieve better visual results both in structure and color.
A Three-level Architecture for Model-free Detection and Tracking of Independently Moving Objects

We present a three–level architecture for detection and tracking of independently moving objects (IMOs) in sequences recorded from a moving vehicle. At the first stage, image pixels with an optical flow that is not entirely induced by the car’s motion are detected by combining dense optical flow, egomotion extracted from this optical flow, and dense stereo. These pixels are segmented and an attention mechanism is used to process them at finer resolution at the second level making use of sparse 2D and 3D edge descriptors. Based on the rich and precise information on the second level, the full rigid motion for the environment and for each IMO is computed. This motion information is then used for tracking, filtering and the building of a 3D model of the street structure as well as the IMO. This multi-level architecture allows us to combine the strength of both dense and sparse processing methods in terms of precision and computational complexity, and to dedicate more processing capacity to the important parts of the scene (the IMOs).
Neural modeling of dynamic systems with nonmeasurable state variables

The paper studies the ability possessed by recurrent neural networks to model dynamic systems when some relevant state variables are not measurable. Neural architectures based on virtual states-which naturally arise from a space state representation-are introduced and compared with the more traditional neural output error ones. Despite the evident potential model ability possessed by virtual state architectures we experimented that their performances strongly depend on the training efficiency. A novel validation criterion for neural output error architectures is suggested which allows to assess the neural network not only in terms of its approximation accuracy but also with respect to stability issues.