Miracle-dz/UniFAR-FTUs huggingface dataset:
No-Hair Theorems in K-Essence Theories

We study the existence of black holes with a non-canonical scalar field as a matter source. We prove a simple no-hair theorem which rules out the existence of stationary, asymptotically flat black holes possessing scalar hair for a wide class of higher-derivative theories. In particular, we rule out the existence of such black holes in the ghost condensate model, and in large sectors of the dilatonic ghost condensate and DBI models.
Change-Point Analysis

Change-point analysis is a powerful new tool for determining whether a change has taken place. It is capable of detecting subtle changes missed by control charts. Further, it better characterizes the changes detected by providing confidence levels and confidence intervals. When collecting online data, a change-point analysis is not a replacement for control charting. But, because a change-point analysis can provide further information, the two methods can be used in a complementary fashion. When analyzing historical data, especially when dealing with large data sets, change-point analysis is preferable to control charting. A change-point analysis is more powerful, better characterizes the changes, controls the overall error rate, is robust to outliers, is more flexible and is simpler to use. This article describes how to perform a change-point analysis and demonstrates its capabilities through a number of examples.
Altered directional functional connectivity underlies post-stroke cognitive recovery

Abstract Cortical ischaemic strokes result in cognitive deficits depending on the area of the affected brain. However, we have demonstrated that difficulties with attention and processing speed can occur even with small subcortical infarcts. Symptoms appear independent of lesion location, suggesting they arise from generalized disruption of cognitive networks. Longitudinal studies evaluating directional measures of functional connectivity in this population are lacking. We evaluated six patients with minor stroke exhibiting cognitive impairment 6–8 weeks post-infarct and four age-similar controls. Resting-state magnetoencephalography data were collected. Clinical and imaging evaluations of both groups were repeated 6- and 12 months later. Network Localized Granger Causality was used to determine differences in directional connectivity between groups and across visits, which were correlated with clinical performance. Directional connectivity patterns remained stable across visits for controls. After the stroke, inter-hemispheric connectivity between the frontoparietal cortex and the non-frontoparietal cortex significantly increased between visits 1 and 2, corresponding to uniform improvement in reaction times and cognitive scores. Initially, the majority of functional links originated from non-frontal areas contralateral to the lesion, connecting to ipsilesional brain regions. By visit 2, inter-hemispheric connections, directed from the ipsilesional to the contralesional cortex significantly increased. At visit 3, patients demonstrating continued favourable cognitive recovery showed less reliance on these inter-hemispheric connections. These changes were not observed in those without continued improvement. Our findings provide supporting evidence that the neural basis of early post-stroke cognitive dysfunction occurs at the network level, and continued recovery correlates with the evolution of inter-hemispheric connectivity.
Information granularity of soft sets

Soft set theory, proposed by Molodtsov, has been regarded as an effective mathematical tool for dealing with uncertainties. This paper is devoted to the study of uncertainty measures of soft sets in the framework of granular computing. The similarity relation induced by a soft set is proposed and the related fuzzy granular structure is constructed. The notions of information granularity and information entropy of a soft set are introduced. Some formulas are presented to calculate them.
Enhanced piezoelectricity in plastically deformed nearly amorphous Bi12TiO20-BaTiO3 nanocomposites

Bulk Bi12TiO20-BaTiO3 (BTO-BT) nanocomposites are fabricated through the high-temperature interfacial reaction between nanometer-sized BaTiO3 particles and melting Bi12TiO20. Although the obtained BTO-BT nanocomposites are nearly amorphous and display very weak ferroelectricity, they exhibit relatively strong piezoelectricity without undergoing the electrical poling process. The volume fraction of crystalline Bi12TiO20 is reduced to less than 10%, and the piezoelectric constant d33 is enhanced to 13 pC/N. Only the presence of the macroscopic polar amorphous phases can explain this unusual thermal stable piezoelectricity. Combining the results from X-ray diffraction, Raman spectroscopy, and thermal annealing, it can be confirmed that the formation of macroscopic polar amorphous phases is closely related to the inhomogeneous plastic deformation of the amorphous Bi12TiO20 during the sintering process. These results highlight the key role of plastically deformed amorphous Bi12TiO20 in the Bi12TiO20-based pola.
Artificial Intelligence In

Protein-protein interaction is one of the ways viruses interact with their hosts. Therefore, identifying protein interactions between viruses and hosts helps explain how virus proteins work, how they replicate, and how they cause disease. SARS-CoV-2 is a new type of virus that emerged from the coronavirus family in 2019 and caused a worldwide pandemic. Detection of human proteins interacting with this novel virus strain plays an important role in monitoring the cellular process of virus-associated infection. Within the scope of the study, a natural language processing-based collective learning method is proposed for the prediction of potential SARS-CoV-2-human PPIs. Protein language models were obtained with the prediction-based word2Vec and doc2Vec embedding methods and the frequency-based tf-idf method. Known interactions were represented by proposed language models and traditional feature extraction methods (conjoint triad and repeat pattern), and their performances were compared. The interaction data were trained with support vector machine, artificial neural network (ANN), k-nearest neighbor (KNN), naive Bayes (NB), decision tree (DT), and ensemble algorithms. Experimental results show that protein language models are a promising protein representation method for protein-protein interaction prediction. The term frequency-inverse document frequency-based language model performed the SARS-CoV-2 protein-protein interaction estimation with an error of 1.4%. Additionally, the decisions of high-performing learning models for different feature extraction methods were combined with a collective voting approach to make new interaction predictions. For 10,000 human proteins, 285 new potential interactions were predicted, with models combining decisions.
Improving Performance of Kernel Principal Component Analysis Using Combination Kernel Functions

In the paper, the formation conditions and the characteristics of kernel functions are researched and analysed which are used in kernel principal component analysis algorithm. Kernel principal component analysis algorithm is a new statistic signal processing technique which can extract nonlinear features of images. Kernel functions are key elements for improving it's performance. A new kernel function-combination kernel function is proposed. The new kernel function combines a local kernel function with a global kernel function. The local kernel is conditionally positive definite kernel which can extract local features of images. The global kernel function is polynomial kernel function which can extract global features of images. So the new kernel function can extract not only local features but also global features of images. The new kernel function is applied in kernel principal component analysis for extracting features of images. The test images are MNIST handwriting digits and ORL face database. Features of images are extracting by kernel principal component analysis firstly. Then performing classification by using linear support vector machines, the effect of the new kernel and that of other kernel on kernel principal component analysis are compared. The experiment results indicate the new kernel function certainly improves the performance of kernel principal component analysis.
Factors Affecting Customers' Satisfaction on Public Service Quality at the Social Insurance Agency of Lao Cai Province, Vietnam

Applying the servqual model (Parasuraman et al., 1988), in this study, the authors proposed a model to assess customer satisfaction with the quality of public services at the insurance agency in Lao Cai province, Vietnam. The study used a combination of qualitative and quantitative research methods. The research model is tested with the survey data of customers participating in using public services at the social insurance agency of Lao Cai province. The results of the regression anal ysis show that the five factors affecting customer satisfaction with the quality of public services at the social insurance agency are arranged in order of decreasing importance as follows: responsiveness, service capacity, empathy, reliability, and tangible means.
A Laboratory Experiment on the Dynamics of the Land and Sea Breeze

Abstract The land and sea breeze (LSB) circulation was simulated in a laboratory using a temperature controlled water tank. Flow visualization by tellurium and phenolphthalein and velocity measurement by laser-Doppler velocimeter were carried out in addition to temperature measurements. from similarity considerations, the simulated flow pattern was shown to have good correspondence with that in the atmosphere. It was shown that the overall features of the LSB flow pattern consist of a closed circulating motion caused by the periodically changing horizontal temperature difference between the land and the sea, and several kinds of small-scale motions induced by the periodic variation of the land surface temperature itself. The most important small-scale motion is the cellular convection which occurs all over the land surface due to unsteady heating from below in the morning calm. Other small-scale motions such as longitudinal vortex rows which are formed inland throughout the sea breeze layer, and gravity c.
Composing meanings as programs

Wemodel semantic interpretation operationally : constituents interact as their combination in discourse evolves from state to state. The states are recursive data structures and evolve from step to step by context-sensitive rewriting. These notions of context and order let us explain inverse-scope quantifiers and their polarity sensitivity as metalinguistic quotation of the wider scope.
Mathematisches Forschungsinstitut Oberwolfach Report No . 12 / 2009 Mini-Workshop : Numerical Upscaling for Flow Problems : Theory and Applications

The objective of this workshop was to bring together researchers working in multiscale simulations with emphasis on multigrid methods and multiscale finite element methods, aiming at chieving of better understanding and synergy between these methods. The goal of multiscale finite element methods, as upscaling methods, is to compute coarse scale solutions of the underlying equations as accurately as possible. On the other hand, multigrid methods attempt to solve fine-scale equations rapidly using a hierarchy of coarse spaces. Multigrid methods need “good” coarse scale spaces for their efficiency. The discussions of this workshop partly focused on approximation properties of coarse scale spaces and multigrid convergence. Some other presentations were on upscaling, domain decomposition methods and nonlinear multiscale methods. Some researchers discussed applications of these methods to reservoir simulations, as well as to simulations of filtration, insulating materials, and turbulence Mathematics Subject Classification (2000): 65N99, 65N55, 65N52, 65N30, 65N06, 65M60, 65M55,
The optimum design of the baffle of R-C system

Based on the graphing method, the constraint condition of the lengths and diameters of the baffles in the R C system is deduced, and the optimization method is used to determine the lengths and diameters of the baffes It overcomes the shortcomings of the graphing method, and it can be finished simultaneously with the optical design in order to obtain the optimum structural design of R C system
Intraseasonal Sea Ice Concentration Variability Over the Weddell Sea During Austral Autumn

The sea ice concentration (SIC) over the Weddell Sea displays obvious intraseasonal variability during austral autumn with a dominant frequency of 5–20 days. The intraseasonal SIC variability is manifested as development of sea ice anomalies from the northeastern Antarctic Peninsula toward the central Weddell Sea. Rossby wave train associated with the internal atmospheric variability featuring circumglobal zonal wavenumber 4 pattern induces the development of anomalous surface winds and sea ice drifting, leading to the SIC anomalies directly. The thermodynamical processes associated with the intraseasonal SIC variability include the air temperature, the moisturizing of the lower troposphere, the latent and sensible heating, and the downwelling longwave radiation, which contribute to the variation of the local greenhouse effect over the Weddell Sea, and thus lead to the sea ice variation. The investigation of the intraseasonal SIC variability helps the understanding of sea‐ice‐atmosphere interaction over the Antarctic region.
Graph Cut Based Image Segmentation in Fluorescence Microscopy

Vývoj v moderni eře molekularni a buněcne biologie je hnaný ohromným technologickým pokrokem několika poslednich dekad. Nove nastroje jako fluorescencni mikroskopy s vysokým rozlisenim spolecně s vývojem fluorescencnich sond umožňuji biologům pozorovat buněcne komponenty vcetně proteinů, chromosomů nebo dokonce jednotlivých genů a studovat dynamiku rozlicných biologických procesů na mikroskopicke urovni. Avsak rucni zpracovani rozsahlých datových souborů ziskaných v těchto experimentech je těžkopadne a nachylne k chybam a vytvaři proto přirozenou poptavku po spolehlivých kvantitativnich metodach založených na rychlých a robustnich automatických nebo alespoň castecně automatických algoritmech pro zpracovani obrazu, ktere umožni ziskat nezkreslene výsledky. Jednim z klicových kroků ve zpracovani biomedicinskeho obrazu je segmentace, jejiž cilem je nalezeni studovaných objektů v obraze. Předni roli v soucasnem výzkumu segmentace hraji sofistikovane a matematicky dobře podložene metody založene na minimalizaci energie. Mezi těmito metodami je velmi popularni přistup využivajici hledani řezů ve specialně zkonstruovanem grafu, zejmena z důvodů efektivniho výpoctu, numericke stability, schopnosti zahrnout do výpoctu visualni a kontextovou informaci, globalně optimalni řeseni, neomezene topologicke vlastnosti a snadne zobecněni do vyssich dimenzi. Přestože metody založene na grafových řezech byly v minulosti prezentovany na siroke skale dat, vcetně biomedicinských, obrazkům, se kterými se setkavame ve fluorescencni mikroskopii se nevěnovala zvlastni pozornost. Hlavnim přinosem teto prace je zaměřit se na specifika dat pořizených na fluorescencnich mikroskopech (zejmena obrazky buněk a buněcných jader) jako jsou nizký kontrast, rozmazani, anizotropni rozliseni, nehomogenni obarveni nebo dotýkajici se objekty a navrhnout vhodne a efektivni algoritmy pro segmentaci a sledovani založene na řezech v grafu. Tato prace se sklada ze tři hlavnich temat. V prvni casti se zabývame aproximaci Euklidovske a Riemannovske metriky pomoci grafových řezů a odvodime aproximacni metodu, ktera ma několik přiznivých vlastnosti v porovnani s existujicimi přistupy. Ve druhe casti uvedeme dva segmentacni algoritmy využivajici navrhnutou aproximaci. Prvni metoda je založena na popularnim Chan-Vese funkcionalu a přinasi vylepseni zejmena v oblasti robustnosti, rychlosti, paměťove narocnosti a kvalitě nalezených řeseni. Druha metoda je novým přistupem k segmentaci dotýkajicich se buněcných jader. V posledni casti prace integrujeme do grafových řezů omezeni pro zachovavani topologie objektů a ukažeme, jak lze tuto modifikaci zkombinovat se segmentaci pomoci Chan-Vese funkcionalu a ziskat rychlou metodu pro sledovani pohybu buněk.
Running head: TACTILE LOCALISATION ON THE FOREARM More than skin-deep: Integration of skin-based and musculo-skeletal reference frames in localisation of touch

If you believe this document infringes copyright then please contact the KAR admin team with the take-down information provided at http://kar.kent. ac.uk/contact.html Citation for published version Sadibolova, Renata and Tamè, Luigi and Longo, Matthew R. (2018) More than skin-deep: Integration of skin-based and musculoskeletal reference frames in localization of touch. Journal of Experimental Psychology: Human Perception and Performance, 44 (11). pp. 1672-1682. ISSN 0096-1523.
Metabolic performance of black soldier fly larvae during entomoremediation of brewery waste

This study aims to evaluate the metabolic performance, in terms of specific rates of growth and feed assimilation, as well as the cost of growth and maintenance of black soldier fly larvae, BSF, Hermetia illucens on brewery waste, a potential worldwide available resource for industrial scale insect production. Brewery waste lacks starch and thus has a nutritional profile substantially different from chicken feed, which is a well‐established and excellent starchy food source for BSF larvae. It is therefore interesting to gain insight into how BSF larvae perform on brewery waste. Larvae of the BSF were reared on chicken feed, on brewery waste and on mixtures of the two. Measurements of the weight of the larvae and their respiratory CO2 production were used to estimate metabolic performance on daily basis. The BSF larvae grew on all the substrates. They reached the highest weight on chicken feed, but their specific growth and feed assimilation rates were highest on the mixed substrates, in which the larvae also reached their maximal weight in the shortest time. Substrate‐dependent costs of growth were not observed while maintenance rates tended to be only slightly lower on the mixed substrates. Overall, the BSF larvae converted the low‐starch brewery waste and the starchy chicken feed into larval biomass about equally efficiently, although brewery waste led to smaller larvae and mixing of the two substrates enhanced feed assimilation and growth. Brewery waste seems thus a suitable resource for BSF larvae, comparable with chicken feed, with respect to their metabolic performance.
Conditional Covariance-Based Nonparametric Multidimensionality Assessment

According to the weak local independence approach to defining dimensionality, the fundamental quantities for determining a test's dimensional structure are the co variances of item-pair responses conditioned on exam inee trait level. This paper describes three dimensionality assessment procedures-HCA/CCPROX, DIMTEST, and DETECT—that use estimates of these con ditional covariances. All three procedures are nonpara metric ; that is, they do not depend on the functional form of the item response functions. These procedures are applied to a dimensionality study of the LSAT, which illustrates the capacity of the approaches to assess the lack of unidimensionality, identify groups of items manifesting approximate simple structure, determine the number of dominant dimensions, and measure the amount of multidimensionality.
A Systematic Overview of Underwater Wireless Sensor Networks: Applications, Challenge and Research Perspectives

Underwater Wireless Sensor Networks (UWSNs) are becoming increasingly popular in marine applications due to advances in wireless and microelectronics technology. However, UWSNs present challenges in processing, energy, and memory storage due to the use of acoustic waves for communication, which results in long delays, significant power consumption, limited bandwidth, and packet loss. This paper provides a comprehensive review of the latest advancements in UWSNs, including essential services, common platforms, critical elements, and components such as localization algorithms, communication, synchronization, security, mobility, and applications. Despite significant progress, reliable and flexible solutions are needed to meet the evolving requirements of UWSNs. The purpose of this paper is to provide a framework for future research in the field of UWSNs by examining recent advancements, establishing a standard platform and service criteria, using a taxonomy to determine critical elements, and emphasizing important unresolved issues.
A new time-domain approach to the analysis of scattering problems

A new approach to the time-domain analysis of scattering problems is presented. In this approach, the Kirchhoff-type formulas are interpreted as explicit Dirichlet boundary conditions that can be posed on any artificial boundary that encloses a scattering object. These boundary conditions are updated as computations proceed. The physical foundation for this approach is the retardation phenomena. First- and second-order formulations of this approach are discussed and some preliminary numerical results are reported.
Sensitivity of January Climate Response to the Magnitude and Position of Equatorial Pacific Sea Surface Temperature Anomalies

Abstract We present here the results of two categories of equatorial Pacific sea surface temperature (SST) anomaly experiments using the NCAR Community Climate Model in the perpetual-January mode. Each experiment consists of an ensemble of eight independent realizations of 90 days duration. Anomaly fields are derived by subtracting the ensemble-average fields in the control experiment from the ensemble-average fields in an experiment with an SST anomaly present. In the first category of experiments (1W, 2W, 3W) we examine the response in the tropics and midlatitudes to a change in the amplitude of an SST anomaly of fixed shape and position. This SST anomaly produces an equatorial Pacific precipitation anomaly just east of the dateline. We show that the most significant feature of the midiatitude response is a feature resembling the teleconnection pattern known as the Pacific/North American (PNA) pattern. The amplitude of this response becomes insensitive to an increase in the tropical precipitation anomal.
Interestingness of stereoscopic images

The added value of stereoscopy is an important factor for stereoscopic product development and content production. Previous studies have shown that 'image quality' does not encompass the added value of stereoscopy, and thus the attributes naturalness and viewing experience have been used to evaluate stereoscopic content. The objective of this study was to explore what the added value of stereoscopy may consist of and what are the content properties that contribute to the magnitude of the added value. The hypothesis was that interestingness is a significant component of the added value. A subjective study was conducted where the participants evaluated three attributes of the stimuli in the consumer photography domain: viewing experience, naturalness of depth and interestingness. In addition to the no-reference direct scaling method a novel method, the recalled attention map, was introduced and used to study attention in stereoscopic images. In the second part of our study, we use eye tracking to compare the salient regions in monoscopic and stereoscopic conditions. We conclude from the subjective results that viewing experience and naturalness of depth do not cover the entire added value of stereoscopy, and that interestingness brings a new dimension into the added value research. The eye tracking data analysis revealed that the fixation maps are more consistent between participants in stereoscopic viewing than in monoscopic viewing and from this we conclude that stereoscopic imagery is more effective in directing the viewer's attention.