Miracle-dz/UniFAR-FTUs huggingface dataset:
Piece-wise analytic trajectory computation for polytopic switching between stable affine systems

Our problem is to compute trajectories of a hybrid system that switches between stable affine ODEs, with switching triggered by hyperplane crossings. Instead of integrating over relatively short time steps, we propose to analytically calculate the affine ODE trajectories between switching times. Our algorithm computes the switching times themselves by Chebyshev interpolation of the analytic trajectory pieces, and polynomial root finding. We shrink the interpolation time intervals using bounds on the times needed by the affine ODE trajectories to enter certain Lyapunov sub-level sets. Based on the Chebfun package, we give a MATLAB implementation of our algorithm. We find that this implementation simulates Relay feedback systems as accurately and sometimes faster than conventional algorithms.
Video Dehazing using LMNN with respect to Augmented MRF

The presence of haze within the atmospheric medium degrades the quality of videos captured by camera sensors. The expulsion of haze, referred to as dehazing, is typically performed subject to the physical degradation display, that involves an explanation of an ill-posed inverse drawback. A few efforts have been made for image dehazing, whereas, video dehazing still remains an unexplored area of research. This paper proposes an approach for video dehazing combining the concepts of single image dehazing, optical stream estimation and Markov Random Field (MRF). The proposed method enhances the temporal and spatial coherence of the hazy video. Assuming that the dark channel of the haze-free picture is zero, we acquire the raw transmission map. In the proposed approach, we focus on the raw transmission map obtained from the dark channel prior using guided filter. We assess the forward and reverse optical streams between the neighboring frames to locate individual pixels using Linear Discriminant Analysis. The color of the haze-free pixels in the frames is approximated by a few hundred discrete colors, which generate a fixed cluster in space and the directions of the pixel. The pixels at a given cluster are spread and can be determined by analyzing the forward and in reverse optical frames to predict its value after haze removal. Largest Margin Nearest Neighbor (LMNN) algorithm is applied to get the smooth transmission map of the foggy frames of the video to approximate the pixel value in the RGB space. The stream fields are utilized in an augmented MRF model on the transmission guide obtained to enhance the temporal and the spatial coherence of the transmission. The proposed method is compared against the state-of-the-art on both real and synthetic videos to preserve the information optimally.
Visual Attention toward Human Face Recognizing for Autism Spectrum Disorder and Normal Developing Children: An Eye Tracking Study

The paper discusses an eye tracking analysis study to let us understand the visual behavior and pattern of Normal Developing children and Autistic children while viewing human face stimulus. An eye tracking experiment consists of displaying different images with human face embedded in different locations (left, center and right) and the eye tracker captured and tracked the child's eye gaze movements, then analyzed to identify where specifically in the stimulus is the child looking at. The finding indicates a significant difference was found between the two groups viewing patterns and behavior when they presented with a scene that have human face. The study also reveals that large percentage of Autistic participants expressed minimum interest and time looking at face area, evident by significant time spent fixations on non-face regions, comparing to the normal developing children. The results can be used to improve the life style of other children who have a risk to develop Autism as well as discover earlier signs of ASD.
Algorithm 1004

Iterated-integral signatures and log signatures are sequences calculated from a path that characterizes its shape. They originate from the work of K. T. Chen and have become important through Terry Lyons’s theory of differential equations driven by rough paths, which is an important developing area of stochastic analysis. They have applications in statistics and machine learning, where there can be a need to calculate finite parts of them quickly for many paths. We introduce the signature and the most basic information (displacement and signed areas) that it contains. We present algorithms for efficiently calculating these signatures. For log signatures this requires consideration of the structure of free Lie algebras. We benchmark the performance of the algorithms. The methods are implemented in C++ and released as a Python extension package, which also supports differentiation. In combination with a machine learning library (Tensorflow, PyTorch, or Theano), this allows end-to-end learning of neural networks involving signatures.
Improving Online Peer Assessment Engagement: Interaction between Signature Forms and Rubric

In order to explore the influence of signature form and rubric on the online peer assessment's engagement, this paper designed a two-factor mixed experiment of 2 (anonymous, real name) × 2 (with rubric, no-rubric) with 379 students from C College as the research object. The statistical analysis was carried out from the three dimensions of behavioral engagement, cognitive engagement and emotional engagement of learners participating in peer assessment. The study found learner's behavioral engagement in the real-name form is higher than the anonymous, and has nothing to do with whether or not to provide the rubric. However, in anonymous situation, the online peer assessment's cognitive engagement and emotional engagement with rubric are significantly higher than without the rubric. Therefore, it is recommended that teaching practitioners provide rubric when using anonymous peer assessment, but other relevant measures should be taken to improve learners' behavioral engagement.
Functional and diffusion MRI reveal the functional and structural basis of infants’ noxious-evoked brain activity

Understanding the neurophysiology underlying pain perception in infants is central to improving early life pain management. In this multimodal MRI study, we use resting-state functional and white matter diffusion MRI to investigate individual variability in infants’ noxious-evoked brain activity. In an 18-infant nociception-paradigm dataset, we show it is possible to predict infants’ cerebral haemodynamic responses to experimental noxious stimulation using their resting-state activity across nine networks from a separate stimulus-free scan. In an independent 215-infant Developing Human Connectome Project dataset, we use this resting-state-based prediction model to generate noxious responses. We identify a significant correlation between these predicted noxious responses and infants’ white matter mean diffusivity, and this relationship is subsequently confirmed within our nociception-paradigm dataset. These findings reveal that a newborn infant’s pain-related brain activity is tightly coupled to both their spontaneous resting-state activity and underlying white matter microstructure. This work provides proof-of-concept that knowledge of an infant’s functional and structural brain architecture could be used to predict pain responses, informing infant pain management strategies and facilitating evidence-based personalisation of care.
Review Article: Sensory Characteristics of Probiotic Cheese

Abstract: Cheese has a good potential for delivery of probiotic microorganisms into the human intestine. In addition, the very wide variety of cheese types all over the world, consumption of cheese by almost everybody, as well as the high nutritional value of cheese constitute growing market for probiotic cheese. Probiotic microorganisms must survive in food products above a standard level until the time of consumption without adversely changing their sensory attributes. Since probiotic microorganisms could affect the flavor, texture, and appearance of dairy products, the sensory attributes of these products have been the subject of numerous studies. This article reviews the sensory characteristics of cheese as affected by probiotic microorganisms.
Feeding strategy of the Deepwater Goby, Chasar bathybius, in the Southern Caspian Sea (Osteichthyes: Gobiidae)

Eleven animal taxa were identified as prey of the Deepwater Goby, Chasar bathybius (Kessler, 1877), by analysing stomach contents: these were some species of Gobiidae, Clupeidae, Atherina boyeri, Carassius gibelio, Liza sp. , Cardium sp. , and Rhithropanopeus sp. With a frequency of 66%, Neogobius fluviatilis was the most prevalent food item, and was the dominant prey taxon in all seasons and age groups. C. bathybius exhibited a specialist feeding strategy on this fish and the other prey types. The dietary breadth is highest in spring according to the Shannon index.
An Efficient Indoor Wi-Fi Positioning Method Using Virtual Location of AP

Wi-Fi fingerprinting has been widely used for indoor localization because of its good cost-effectiveness. However, it suffers from relatively low localization accuracy and robustness owing to the signal fluctuations. Virtual Access Points (VAP) can effectively reduce the impact of signal fluctuation problem in Wi-Fi fingerprinting. Current techniques normally use the Log-Normal Shadowing Model to estimate the virtual location of the access point. This would lead to inaccurate location estimation due to the signal attenuation factor in the model, which is difficult to be determined. To overcome this challenge, in this study, we propose a novel approach to calculating the virtual location of the access points by using the Apollonius Circle theory, specifically the distance ratio, which can eliminate the attenuation parameter term in the original model. This is based on the assumption that neighboring locations share the same attenuation parameter corresponding to the signal attenuation caused by obstacles. We evaluated the proposed method in a laboratory building with three different kinds of scenes and 1194 test points in total. The experimental results show that the proposed approach can improve the accuracy and robustness of the Wi-Fi fingerprinting techniques and achieve state-of-art performance.
GENETIC AND NON-GENETIC FACTORS AFFECTING MORTALITY IN LORI-BAKHTIARI LAMBS

Data and pedigree information for Lori-Bakhtiari sheep used in this study were 6,239 records of lamb mortality from 246 sires and 1,721 dams, collected from 1989 through 2007 from a Lori-Bakhtiari flock at Shooli station in Shahrekord. The traits investigated were cumulative lamb mortality from birth up to 7 days, up to 14 days, up to 21 days, and up to 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 and 12 months of age. The models included fixed factors that had significant effects and random direct genetic, maternal genetic and maternal permanent environmental effects. Variance components were estimated using the restricted maximum likelihood procedure applying three animal models with and without maternal and common environmental effects. The overall mean of cumulative lamb mortality rate was 22.95% from birth to 1 year of age, while the overall mortality rate up to 3 and from 3 to 6 months of age was 6.14% and 12.76%, respectively. The mortality rate after 6 months of age declined as the lambs grew older. The age of dam had no important effect on lamb mortality. The type of birth was more important during the preweaning period than at later ages, and lamb mortality rate was higher in twins. The year of birth, month of birth and sex of lamb significantly (p≤0.01) affected the cumulative lamb mortality rate at all ages. The least square mean of mortality during the final one-third of the lambing period was higher than the first and middle one-third of the lambing period. Male lambs were found to be at a higher risk of mortality than females. Birth weight of the lamb had a highly significant (p≤0.01) effect on lamb mortality at all ages as a quadratic regression. Direct and maternal heritability estimates of lamb mortality ranged from 0.01 to 0.13 and 0.01 to 0.05, respectively. Direct heritability increased with age of lamb, while maternal effects (genetic and common environmental) were important in the preweaning period. These results indicate that lamb mortality can be reduced first through farm management practices and secondly by genetic selection. Both animal and maternal effects should be considered in breeding programmes for reducing lamb mortality at preweaning.
Differential NO3 - dependent patterns of NO3 - uptake in Pinus pinaster, Rhizopogon roseolus and their ectomycorrhizal association.

• A different NO3 - dependent pattern of NO3 - uptake at low [NO3 - ] (0-0.1 mM) is shown in Pinus pinaster and in the ectomycorrhizal fungus Rhizopogon roseolus. In ectomycorrhizal symbiosis, the fungal pattern is pre-eminent. • Net NO3 - uptake rates were deduced in plant and fungus from solution depletion measurements. Net NO3 - fluxes were estimated at the surface of mycorrhizal and nonmycorrhizal short roots, using NO3 - selective microelectrodes. • In NO3 - starved seedlings, maximum NO3 - uptake rates were reached after 3 d of incubation in 0.05 mM NO3 - . In R. roseolus mycelia, NO3 - uptake rates did not change after withdrawing NO3 - for up to 7 d, or after adding NO3 - for 3 d. Net NO3 - fluxes in nonmycorrhizal short roots were increased twofold by a 3-d exposure to NO3 - whereas in ectomycorrhiza they were similar irrespective of the NO3 - pretreatment, but always higher than the fluxes measured in nonmycorrhizal roots. • Ectomycorrhiza have a greater capacity to use NO3 - than nonmycorrhizal short roots, whatever the NO3 - concentration in the solution. This may give mycorrhizal plants a greater ability to use fluctuating concentrations of NO3 - in the soil solution.
Importance of albumen during embryonic development in avian species, with emphasis on domestic chicken

Depending on the bird species, about 33-86% of the egg content consists of albumen. In eggs from domestic fowl, albumen contains about 10.5% protein and 88.5% of water and may be regarded as the main water source for the developing embryo. Besides carbohydrates, lipids, and inorganic ions, over 90% of the solids in the albumen are proteins. Several factors are known to influence the amount and composition of the albumen: egg weight, age and genetics of the parent flock, amount and quality of the feed provided, environmental factors (e.g. temperature, light), position in laying sequence, and also storage conditions of eggs prior to incubation. The albumen content of an egg plays an important role during embryonic development. Not only for formation of sub-embryonic fluid, but albumen proteins are known to flow into the amniotic cavity, the yolk sac and finally the digestive tract of the embryo and are used as the main source of proteins for tissue synthesis. Partial removal of albumen had negative consequences on chick weight at hatch, reduced the amount of amniotic and allantoic fluid and may reduce the water content of the chick and the residual yolk. Replacing the removed albumen with saline, however, reduced the residual yolk weight without differences in water content, suggesting increased uptake and utilisation of yolk, possibly as a compensation for the removed albumen proteins. In addition to reduced chick weight at hatch, some authors report an asymmetric growth restriction where nutrients are diverted away from non-vital organs in favour of brain and heart, with a relative ‘sparing’ of these latter two organs. Partial albumen removal led to a reduced whole-body protein synthesis, similar to eggs containing naturally less albumen. Importantly, several studies reported some long-term effects of albumen removal on growth, indicating that prenatal environment will have life-long consequences.
Bacterial diversity in the foreland of the Tianshan No. 1 glacier, China

There is compelling evidence that glaciers are retreating in many mountainous areas of the world due to global warming. With this glacier retreat, new habitats are being exposed that are colonized by microorganisms whose diversity and function are less well studied. Here, we characterized bacterial diversity along the chronosequences of the glacier No. 1 foreland that follows glacier retreat. An average of 10 000 sequences was obtained from each sample by 454 pyrosequencing. Using non-parametric and rarefaction estimated analysis, we found bacterial phylotype richness was high. The bacterial species turnover rate was especially high between sites exposed for 6 and 10 yr. Pyrosequencing showed tremendous bacterial diversity, among which the Acidobacteria, Actinobacteria, Bacteroidetes and Proteobacteria were found to be present at larger numbers at the study area. Meanwhile, the proportion of Bacteroidetes and Proteobacteria decreased and the proportion of Acidobacteria increased along the chronosequences. Some known functional bacterial genera were also detected and the sulfur- and sulfate-reducing bacteria were present in a lower proportion of sequences. These findings suggest that high-throughput pyrosequencing can comprehensively detect bacteria in the foreland, including rare groups, and give a deeper understanding of the bacterial community structure and variation along the chronosequences.
Representing Complex Evolving Spatial Networks: Geographic Network Automata

Many real-world spatial systems can be conceptualized as networks. In these conceptualizations, nodes and links represent system components and their interactions, respectively. Traditional network analysis applies graph theory measures to static network datasets. However, recent interest lies in the representation and analysis of evolving networks. Existing network automata approaches simulate evolving network structures, but do not consider the representation of evolving networks embedded in geographic space nor integrating actual geospatial data. Therefore, the objective of this study is to integrate network automata with geographic information systems (GIS) to develop a novel modelling framework, Geographic Network Automata (GNA), for representing and analyzing complex dynamic spatial systems as evolving geospatial networks. The GNA framework is implemented and presented for two case studies including a spatial network representation of (1) Conway’s Game of Life model and (2) Schelling’s model of segregation. The simulated evolving spatial network structures are measured using graph theory. Obtained results demonstrate that the integration of concepts from geographic information science, complex systems, and network theory offers new means to represent and analyze complex spatial systems. The presented GNA modelling framework is both general and flexible, useful for modelling a variety of real geospatial phenomena and characterizing and exploring network structure, dynamics, and evolution of real spatial systems. The proposed GNA modelling framework fits within the larger framework of geographic automata systems (GAS) alongside cellular automata and agent-based modelling.
Horizontal Gene Transfer: A Universal Phenomenon

ABSTRACT According to the scientific literature, it is reasonable to consider that lateral transfer of genes is an usual mechanism of adaptation of the biological organisms to environmental stresses. Furthermore, from bacteria to cultured human cells, including fungi and plants, a large diversity of horizontal gene transfers—natural or artificial, experimental or deduced from sequence analysis—have been described. Therefore, the uncharacterized biodiversity—particularly in microbiology—associated with the universality of the horizontal gene transfer phenomenon leads to the consideration that dissemination of DNA from Genetically Modified Organisms (GMO) in biological environments, including food and soil, is uncontrolled and predictable.
Machine Learning for Gully Feature Extraction Based on a Pan-Sharpened Multispectral Image: Multiclass vs. Binary Approach

Gullies reduce both the quality and quantity of productive land, posing a serious threat to sustainable agriculture, hence, food security. Machine Learning (ML) algorithms are essential tools in the identification of gullies and can assist in strategic decision-making relevant to soil conservation. Nevertheless, accurate identification of gullies is a function of the selected ML algorithms, the image and number of classes used, i.e., binary (two classes) and multiclass. We applied Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and Random Forest (RF) on a Systeme Pour l’Observation de la Terre (SPOT-7) image to extract gullies and investigated whether the multiclass (m) approach can offer better classification accuracy than the binary (b) approach. Using repeated k-fold cross-validation, we generated 36 models. Our findings revealed that, of these models, both RFb (98.70%) and SVMm (98.01%) outperformed the LDA in terms of overall accuracy (OA). However, the LDAb (99.51%) recorded the highest producer’s accuracy (PA) but had low corresponding user’s accuracy (UA) with 18.5%. The binary approach was generally better than the multiclass approach; however, on class level, the multiclass approach outperformed the binary approach in gully identification. Despite low spectral resolution, the pan-sharpened SPOT-7 product successfully identified gullies. The proposed methodology is relatively simple, but practically sound, and can be used to monitor gullies within and beyond the study region.
Cloning, functional expression, and characterization of an edema-producing Asp-49 phospholipase A2 from Trimeresurus mucrosquamatus

The snake-bite of Trimeresurus mucrosquamatus can cause severe edema and result in complications. Snake venom phospholipase A2s are the major components responsible for causing edema. Therefore, understanding the edema-producing mechanism induced by the venom of T. mucrosquamatus can be important in treating the edema. In order to study the edema-producing effect, a venom Asp-49 phospholipase A2 (TMV-D49-PLA2) was cloned, sequenced, and functionally expressed in Escherichia coli. This expressed venom protein demonstrated specific phospholipase activities both in the digestion of lecithin in vitro and in inducing edema in rats in vivo. Therefore, the cloning and functional expression of the recombinant edema-producing protein are critical steps and should allow further characterization of the functional motifs responsible for both the edema-inducing activity and the development of therapeutic antiserum against the edema effect of the snake venom proteins.
A vegetation survey of the Tsitsikamma Coastal National Park

Sampling plots (5 m x 10 m in fynbos, 10 m x 10 m in forest) were analysed in the littoral, coastal escarpment, and north and south facing inland escarp- ment zones of 17 transect sites along the length of the Tsitsikamma Coastal National Park. Cover- abundance values were estimated for each species in the sampling plots. A detrended correspondence analysis (using CANOCO) and a two way indicator species analysis (TWINSPAN) were carried out on these data to determine the communities sampled. The vegetation of the park was classified into an Afromontane Forest, a Littoral Herbland and two Mesic Mountain Fynbos Communities. The distribution and extent of these communities were determined and their conservation discussed.