ahmedabdelwahed/Medical_papers_title_and_abstract_NLP_dataset huggingface dataset:
A novel visual tracking method using stochastic fractal search algorithm

Recently metaheuristic algorithms have attracted the attention of many researchers in various disciplines for their simplicity of application and their efficiency. Visual tracking is one of the most promising fields of application of these methods, and although many approaches have been proposed, their main disadvantage is the convergence at local minima which make them unable to find the exact position. To overcome this drawback, we propose to use an algorithm that provides an efficient exploration of the search space, which is stochastic fractal search (SFS) algorithm. SFS is used as a localization method, to find the most similar candidate to a previous defined template. Standard kernel-based spatial color histogram of the object bounding box, is evaluated in order to model the object appearance. Subsequently, Bhattacharyya distance is measured between the two histograms of the model and the candidate to define the fitness function, in which optimization is sought. To assess fairly the robustness of our approach, we have evaluated its performance on 20 video sequences from the OTB-100 sequences dataset and compared it to 11 other state-of-the-art trackers. Quantitative and qualitative evaluations on challenging situations provided satisfying results of SFS-based tracker compared to other state-of-the-art algorithms.
Phenotype-first hypotheses, spandrels and early metazoan evolution

Against the neo-Darwinian assumption that genetic factors are the principal source of variation upon which natural selection operates, a phenotype-first hypothesis strikes us as revolutionary because development would seem to constitute an independent source of variability. Richard Watson and his co-authors have argued that developmental memory constitutes one such variety of phenotypic variability. While this version of the phenotype-first hypothesis is especially well-suited for the late metazoan context, where animals have a sufficient history of selection from which to draw, appeals to developmental memory seem less plausible in the evolutionary context of the early metazoans. I provide an interpretation of Stuart Newman's account of deep metazoan phylogenesis that suggests that spandrels are, in addition to developmental memory, an important reservoir of phenotypic variability. I conclude by arguing that Gerd Müller's "side-effect hypothesis" is an illuminating generalization of the proposed non-Watsonian version of the phenotype-first hypothesis.
Differences in the cross-sectional area along the ankle tendons with both age and sex

Increasing age appears to influence several morphologic changes in major tendons. However, the effects of aging on the cross-sectional area (CSA) of different ankle tendons are much less understood. Furthermore, potential differences in specific tendon regions along the length of the tendons have not been investigated in detail. Sixty healthy adult participants categorized by age as young (n = 20; mean ± SD age = 22.5 ± 4.5 years), middle-age (n = 20; age = 40.6 ± 8. 0 years), or old (n = 20; age = 69.9 ± 9.1 years), from both sexes, were included. The tendon CSA of tibialis anterior (TA), tibialis posterior (TP), fibularis (FT), and Achilles (AT) was measured from T1-weighted 1.5 T MR images in incremental intervals of 10% along its length (from proximal insertion) and compared between different age groups and sexes. The mean CSA of the AT was greater in the middle-age group than both young and old participants (p < 0.01) and large effect sizes were observed for these differences (Cohen's d > 1). Furthermore, there was a significant difference in CSA in all three groups along the length of the different tendons. Region-specific differences between groups were observed in the distal portion (90% and 100% of the length), in which the FT presented greater CSA comparing middle-age to young and old (p < 0.05). In conclusion, (1) great magnitude of morpho-structural differences was discovered in the AT; (2) there are region-specific differences in the CSA of ankle tendons within the three groups and between them; and (3) there were no differences in tendon CSA between sexes.
Copper-catalyzed aerobic autoxidation of N-hydroxycarbamates probed by mass spectrometry

We present herein a mechanistic investigation by nanoelectrospray ionization mass spectrometry of copper-catalyzed aerobic oxidative processes involved in the N-nitrosocarbonyl aldol reaction of N-hydroxycarbamates. Protonated amine and copper as charge-tags aided the detection of reaction intermediates, which verified the enamine mechanism together with a competing enol process. Our experimental results reveal that the copper-catalyzed aerobic oxidation of N-hydroxycarbamates may proceed through an autoxidation catalytic mechanism in which a CbzNHO(.) radical abstracts a hydrogen from the bound N-hydroxycarbamate to release the nitroso intermediate through a bimolecular hydrogen-atom transfer. In this process, the chiral diamine also works as a ligand for copper to facilitate the aerobic oxidative step. The dual role of the chiral vicinal diamine as both an aminocatalyst and a bidentate ligand was finally uncovered.
Human ageing is associated with more rigid concept spaces

Prevalence-induced concept change describes a cognitive mechanism by which someone's definition of a concept shifts as the prevalence of instances of that concept changes. While this phenomenon has been established in young adults, it is unclear how it affects older adults. In this study, we explore how prevalence-induced concept change affects older adults' lower-level, perceptual, and higher-order, ethical judgements. We find that older adults are less sensitive to prevalence-induced concept change than younger adults across both domains. Using computational modeling, we demonstrate that these age-related changes in judgements reflect more cautious and deliberate responding in older adults. Based on these findings, we argue that while overly cautious responding by older adults may be maladaptive in some cognitive domains, in the case of prevalence-induced concept change, it might be protective against biased judgements.
Cationic Modified PVA Hydrogels Provide Low Friction and Excellent Mechanical Properties for Potential Cartilage and Orthopedic Applications

Poly(vinyl alcohol) (PVA) hydrogel is a promising candidate for articular cartilage repair yet restrained by its mechanical strength and tribological property. Current work reports a newly designed PVA-based hydrogel modified by glycerol (g), bacterial cellulose (BC), and a cationic polymer poly (diallyl dimethylammonium chloride) (PDMDAAC), which is a novel cationic strengthening choice. The resultant PVA-g-BC-PDMDAAC hydrogel proves the effectiveness of this modification scheme, with a confined compressive modulus of 19.56 MPa and a friction coefficient of 0.057 at a joint-equivalent load and low sliding speed. The water content, swelling property, and creep behavior of this hydrogel are also within a cartilage-mimetic range. The properties of PVA-based hydrogels before PDMDAAC addition are likewise studied as a cross-reference. Besides, PDMDAAC-modified PVA hydrogel realizes ideal mechanical and lubrication properties with a relatively low PVA concentration (10 wt.%) and facile fabrication process, which lays a foundation for mass production and marketization in the future.
Sequential Subspace Clustering via Temporal Smoothness for Sequential Data Segmentation

This paper develops a novel sequential subspace clustering method for sequential data. Inspired by the state-of-the- art methods, ordered subspace clustering, and temporal subspace clustering, we design a novel local temporal regularization term based on the concept of temporal predictability. Through minimizing the short-term variance on historical data, it can recover the temporal smoothness relationships in sequential data. Moreover, we claim that the local temporal regularization is more important than the global structural regularization for a specific task, such as sequential subspace clustering, which leads to a concise minimization objective function. To solve the bi-convex objective function, a simple and efficient optimization algorithm based on the alternate convex search method is devised to jointly learn the coding matrix and the dictionary. Furthermore, five baseline methods are also devised for comparison with our proposed method from different aspects. Extensive experimental results and comparisons with the state-of-the-art methods on three data sets demonstrate the effectiveness of the proposed temporal smoothness sequential subspace clustering method for sequential data.
Developments in xEVs charging infrastructure and energy management system for smart microgrids including xEVs

The swiftly growing structure of urbanization and smart cities facilitating the transportation era at peak. Thus, the rising pattern of conventional automobiles leading to the high contribution of greenhouse gas (GHG) emission. To mitigate the hazardous profile of GHG emissions, the electric vehicles (xEVs) as the part of smart cities, are gaining immense consideration. However, the unscheduled EVs connectivity with conventional grid system leading unreliable and interrupted power supply, which may lead to the grid failure. In such state of affairs (i.e. GHG emission and rising power demand), the smart microgrids including Renewable Energy Sources (RESs) based charging infrastructure are becoming the most viable paradigm. In this paper, two most emerging technologies belonging to smart cities i.e. xEVs and RESs based smart Microgrid has been covered. The xEVs part of the presented manuscript discusses the detailed study of rising advancement in xEVs charging infrastructure, enhancement in international standards for proper xEVs deployment, and state of art in the xEVs application such as the vehicle to grid (V2G) and vehicle to home (V2H). The second part of the presented work elaborates the state of art in research of smart microgrids energy management system (EMS) including xEVs to enhance the reliability of charging infrastructure.
Coordination of Pnictogenylboranes Towards Tl(I) Salts and a Tl- Mediated P-P Coupling

The coordination chemistry of only Lewis-base (LB)-stabilized pnictogenylboranes EH2 BH2 ⋅NMe3 (E=P, As) towards Tl(I) salts has been studied. The reaction of Tl[BArCl ] (BArCl =[B(3,5-C6 H3 Cl2 )4 ]- ) with the corresponding pnictogenylborane results in the formation of [Tl(EH2 BH2 ⋅NMe3 )][BArCl ] (1 a: E=P; 1 b: E=As). Whereas the Tl ion in 1 a/b is monocoordinated, the exchange of the weakly coordinating anion (WCA) in the Tl(I) salt leads to the formation of a trigonal pyramidal coordination mode at the Tl atom by coordination of three equivalents of EH2 BH2 ⋅ NMe3 in [Tl(EH2 BH2 ⋅ NMe3 )3 ][WCA] (2 a: E=P, WCA=TEFCl ; 2 b: E=As, WCA=TEF) (TEF=[Al{OC(CF3 )3 }4 ]- , TEFCl =[Al{(OC(CF3 )2 (CCl3 )}4 ]- ). Furthermore, by using two equivalents of PH2 BH2 ⋅NMe3 , a Tl(I)-mediated P-P coupling takes place in CH2 Cl2 as solvent resulting in [Me3 N⋅BH2 PH2 PHBH2 ⋅NMe3 ][WCA] (WCA=TEF, 3 a; BArCl , 3 b; TEFCl , 3 c). In contrast, for the arsenic derivatives 1 b and 2 b, no coupling reaction is observed. The underlying chemical processes are elucidated by quantum chemical computations.
Biodegradable Redox-Responsive AIEgen-Based-Covalent Organic Framework Nanocarriers for Long-Term Treatment of Myocardial Ischemia/Reperfusion Injury

Timely restoration of blood supply after myocardial ischemia is imperative for the treatment of acute myocardial infarction but causes additional myocardial ischemia/reperfusion (MI/R) injury, which has not been hitherto effectively targeted by interventions for MI/R injury. Hence, the development of advanced nanomedicine that can reduce apoptosis of cardiomyocytes while protecting against MI/R in vivo is of utmost importance. Herein, a redox-responsive and emissive TPE-ss covalent organic framework (COF) nanocarrier by integrating aggregation-induced emission luminogens and redox-responsive disulfide motifs into the COF skeleton is developed. TPE-ss COF allows for efficient loading and delivery of matrine, a renowned anti-cryptosporidial drug, which significantly reduces MI/R-induced functional deterioration and cardiomyocyte injury when injected through the tail vein into MI/R models at 5 min after 30 min of ischemia. Moreover, TPE-ss COF@Matrine shows a drastic reduction in cardiomyocyte apoptosis and improvements in cardiac function and survival rate. The effect of the TPE-ss COF carrier is further elucidated by enhanced cardiomyocyte viability and triphenyltetrazolium chloride staining in vitro. This work demonstrates the cardioprotective effect of TPE-ss COFs for MI/R injury, which unleashes the immense potential of using COFs as smart drug carriers for the peri-reperfusion treatment of ischemic heart disease with low cost, high stability, and single postoperative intervention.
Ranavirus infection-induced avoidance behaviour in wood frog juveniles: do amphibians socially distance?

Hosts may limit exposure to pathogens through changes in behaviour, such as avoiding infected individuals or contaminated areas. Here, we tested for a behavioural response to ranavirus infection in juvenile wood frogs (Rana sylvatica) because the majority of dispersal between populations occurs during this life stage. We hypothesized that if infections are transmissible and detectable at this life stage, then susceptibles would display avoidance behaviours when introduced to an infected conspecific. Despite no apparent signs of infection, we observed a greater distance between susceptible-infected pairs, compared to pairs of either two infected or two susceptible animals. Further, distances between susceptible-infected pairs were positively related to the infection intensity of the focal exposed frog, suggesting the cue to avoid infected conspecifics may become more detectable with more intense infections. Although we did not quantify whether the transmission was affected by their distancing, our findings suggest that juvenile frogs have the potential to reduce terrestrial transmission of ranaviruses through avoidance behaviours.
Formulating Spatially Varying Performance in the Statistical Fusion Framework

To date, label fusion methods have primarily relied either on global [e. g., simultaneous truth and performance level estimation (STAPLE), globally weighted vote] or voxelwise (e. g., locally weighted vote) performance models. Optimality of the statistical fusion framework hinges upon the validity of the stochastic model of how a rater errs (i.e., the labeling process model). Hitherto, approaches have tended to focus on the extremes of potential models. Herein, we propose an extension to the STAPLE approach to seamlessly account for spatially varying performance by extending the performance level parameters to account for a smooth, voxelwise performance level field that is unique to each rater. This approach, Spatial STAPLE, provides significant improvements over state-of-the-art label fusion algorithms in both simulated and empirical data sets.
Skin lightness affects ultraviolet A-induced oxidative stress: Evaluation using ultraweak photon emission measurement

The human skin is usually exposed to ultraviolet A (UVA) in the sunlight and experiences oxidative stress associated with skin disorders and aging. Although oxidative stress caused by UVA exposure is assumed to be dependent on skin colour, few studies have demonstrated this dependency. We investigated the effects of skin colour on UVA-induced oxidative stress using ultraweak photon emission (UPE) generated from the skin during oxidation processes. The UPE intensities of skin samples were detected using a photomultiplier tube every second without any labelling. We irradiated skin tissue of different colours with UVA and measured UPE over time. UVA-induced UPE could be detected from immediately after irradiation to 2 h after irradiation, indicating persistent oxidative stress. Skin lightness (L*) positively correlates with UPE intensity. Lighter-coloured skin exhibited more UVA-induced UPE, indicating higher oxidative stress. Additionally, oxidative stress persisted significantly more in lighter skin compared with darker skin. Skin tissues exhibited pigment darkening after UVA irradiation. Our results suggest that skin lightness affects oxidative stress induced by UV irradiation. Our study demonstrated the relationship between skin lightness and UVA-induced oxidative stress for the first time and offers new photodermatological insights into the human skin.
ART 2 - an unsupervised neural network for PD pattern recognition and classification

This paper introduces a method of classifying partial discharges of unknown origin. The innovative trend of using Artificial Neural Network (ANN) towards classification of Partial Discharge (PD) patterns is cogent and discernible. The Adaptive Resonance Theory (ART), a type of neural network which is suitable for PD pattern recognition is explained here. To ensure the suitability and reliability of chosen network for PD pattern recognition, the network is tested with the well known Iris plant database and alphabet character for recognition & classification. Further more the network is trained with various combinations of (phi-q-n distributions of PD patterns and tested. It is shown that the ART 2 network is able to classify the PD patterns. The paper ends with analyzing the efficacy of multifarious features selected in the measurement space. Also the validation of input features is done using 'Hold-One-Out' method and partial set training technique (C) 2005 Elsevier Ltd. All rights reserved.
A 30.1 mW/mu m(2) SiGe:C HBT Featuring an Implanted Collector in a 55-nm CMOS Node

This letter deals with the load-pull measurements at 94 GHz of 450 GHz Si/SiGe f(T) HBTs. On the one hand the technological modifications performed to improve large signal performances are presented and on the other hand, load-pullmeasurements are presented after having describing the measurement setup. A state-of-the-art 30.1 mW / mu m(2) Si/SiGe HBT is demonstrated thanks to a layout optimization.
Scatter Component Analysis: A Unified Framework for Domain Adaptation and Domain Generalization

This paper addresses classification tasks on a particular target domain in which labeled training data are only available from source domains different from (but related to) the target. Two closely related frameworks, domain adaptation and domain generalization, are concerned with such tasks, where the only difference between those frameworks is the availability of the unlabeled target data: domain adaptation can leverage unlabeled target information, while domain generalization cannot. We propose Scatter Component Analyis (SCA), a fast representation learning algorithm that can be applied to both domain adaptation and domain generalization. SCA is based on a simple geometrical measure, i.e., scatter, which operates on reproducing kernel Hilbert space. SCA finds a representation that trades between maximizing the separability of classes, minimizing the mismatch between domains, and maximizing the separability of data; each of which is quantified through scatter. The optimization problem of SCA can be reduced to a generalized eigenvalue problem, which results in a fast and exact solution. Comprehensive experiments on benchmark cross-domain object recognition datasets verify that SCA performs much faster than several state-of-the-art algorithms and also provides state-ofthe- art classification accuracy in both domain adaptation and domain generalization. We also show that scatter can be used to establish a theoretical generalization bound in the case of domain adaptation.
Robust occlusion-aware part-based visual tracking with object scale adaptation

Visual tracking is still a challenging task as the objects suffer significant appearance changes, fast motion, and serious occlusion. In this paper, we propose an occlusion-aware part-based tracker for robust visual tracking. We first present a novel occlusion-aware part-based model based on correlation filters to integrate the global model and part-based model adaptively. It can effectively employ both the global and local information to improve the robustness of the tracker. Then we propose an integral pipeline aiming to the long-term tracking under the correlation filters, which achieves the state-of-the-art performance. In this tracking pipeline, we adopt separate translation and scale estimation. For translation estimation, we exploit and jointly learn the hierarchical features of deep Convolutional Neural Networks (CNNs) to locate the target center accurately. Then we learn an independent scale correlation filter to handle the scale variation. This design realizes scale adaptation of the target preferably, and reduces computational complexity efficiently. We further ameliorate the model update method by introducing the original reliable information. It greatly alleviates the error accumulation of the incorrect information and efficiently achieves long-term tracking. Extensive experimental results on several different challenging benchmark datasets show that our proposed tracker achieves outstanding performance against the state-of-the-art methods. (C) 2018 Elsevier Ltd. All rights reserved.
Position sensors based on the delay line principle

A position sensor is presented based on the magnetostrictive delay line (MDL) principle. The sensor is accompanied by its electronic circuitry and packaging. We present and analyze the sensor principle, electronics, calibration procedure as well as its evaluation with respect to the state of the art, showing its advantages and applications. (C) 2003 Elsevier B.V All rights reserved.
Gray whale density during seismic surveys near their Sakhalin feeding ground

Oil and gas development off northeastern Sakhalin Island, Russia, has exposed the western gray whale population on their summer-fall foraging grounds to a range of anthropogenic activities, such as pile driving, dredging, pipeline installation, and seismic surveys. In 2015, the number of seismic surveys within a feeding season surpassed the level of the number and duration of previous seismic survey activities known to have occurred close to the gray whales' feeding ground, with the potential to cause disturbance to their feeding activity. To examine the extent that gray whales were potentially avoiding areas when exposed to seismic and vessel sounds, shore-based teams monitored the abundance and distribution of gray whales from 13 stations that encompassed the known nearshore feeding area. Gray whale density was examined in relation to natural (spatial, temporal, and prey energy) and anthropogenic (cumulative sound exposure from vessel and seismic sounds) explanatory variables using Generalized Additive Models (GAM). Distance from shore, water depth, date, and northing explained a significant amount of variation in gray whale densities. Prey energy from crustaceans, specifically amphipods, isopods, and cumaceans also significantly influenced gray whale densities in the nearshore feeding area. Increasing cumulative exposure to vessel and seismic sounds resulted in both a short- and longer-term decline in gray whale density in an area. This study provides further insights about western gray whale responses to anthropogenic activity in proximity to and within the nearshore feeding area. As the frequency of seismic surveys and other non-oil and gas anthropogenic activity are expected to increase off Sakhalin Island, it is critical to continue to monitor and assess potential impacts on this endangered population of gray whales.