Miracle-dz/UniFAR-FTUs huggingface dataset:
A 3D Mask Face Anti-Spoofing Database with Real World Variations

3D Mask face spoofing attack becomes new challenge and attracts more research interests in recent years. However, due to the deficiency number and limited variations of database, there are few methods be proposed to aim on it. Meanwhile, most of existing databases only concentrate on the anti-spoofing of different kinds of attacks and ignore the environmental changes in real world applications. In this paper, we build a new 3D mask anti-spoofing database with more variations to simulate the real world scenario. The proposed database contains 12 masks from two companies with different appearance quality. 7 Cameras from the stationary and mobile devices and 6 lighting settings that cover typical illumination conditions are also included. Therefore, each subject contains 42 (7 cameras * 6 lightings) genuine and 42 mask sequences and the total size is 1008 videos. Through the benchmark experiments, directions of the future study are pointed out. We plan to release the database as an platform to evaluate methods under different variations.
Transcatheter aortic valve implantation

[first paragraph of article] Aortic valve (AV) disease is a common condition with its prevalence, particularly aortic stenosis increasing exponentially with advancing age. A decade ago conventional aortic valve replacement (AVR) was the only treatment when medical management failed and symptoms developed. More than half of the patients potentially eligible for surgery have coexistent conditions making them unsuitable or very high-risk candidates. Balloon aortic valvuloplasty had too rapid a rate of restenosis to make it a viable long-term alternative . It was therefore occasionally used as a bridge or test to assess suitability for AVR in patients with severe but potentially reversible left ventricular (LV) dysfunction or comorbidities.
An Ant Colony heuristic for the Time Dependent Vehicle Routing Problem with Time Windows

This paper presents an Ant Colony heuristic for the Time Dependent Vehicle Routing Problem with Time Windows (TDVRPTW). The TDVRPTW involves finding the best routes for a fleet of vehicles that must deliver goods to a set of customers. Besides, the time window constraints of the customers must be respected and the fact that the travel time between to points depends on the time of departure has to be taken into account. The latter assumption is particularly important in an urban context where the traffic plays a significant role. The heuristic was enhanced through a local search with numerous neighborhood operators and an aggressive insertion heuristic relying on the minimum delay technique. The algorithm developed turned out to be competitive when tested with Solomon’s benchmark instances. Nomenclature n number of clients B big number κ number of available vehicles si service time of node i Ck capacity of vehicle k [ai,bi] time window of node i N {1.n}: clients di demand of node i D0 {1κ. 0}: origin deposits Tm end time of slice m DE {n+1. n+κ}: end deposits G (V, A) directed graph where V is the set of vertices and A the set of arcs. M {1.n}: time intervals ∆(i) forward star, sets of vertices j such that (i, j) ε A ∆(j) backward star, sets of vertices i such that (i, j) ε A
State space modelling and simulation lter methods

We model a time series yt, t = 1; :::; n, using a state space model. That is yt is conditionally independent given an unobserved su cient state t; which is itself assumed to be Markovian. The task will be to use simulation to estimate f( tjFt), t = 1; :::; n, where Ft is contemperaneously available information. We assume parametric forms for both the `measurement' density f(ytj t) and the `transition' density of the state f( t+1j t). The state evolution is initialized by some density f( 0). Filtering can be thought of as the repeated application of the iteration f( t+1jFt+1) / f(yt+1j t+1) Z f( t+1j t)dF ( tjFt): (1)
Delayed protection by ESAT-6–specific effector CD4+ T cells after airborne M. tuberculosis infection

Mycobacterium tuberculosis infection induces complex CD4 T cell responses that include T helper type 1 (Th1) cells and regulatory T cells. Although Th1 cells control infection, they are unable to fully eliminate M. tuberculosis, suggesting that Th1-mediated immunity is restrained from its full sterilizing potential. Investigation into T cell–mediated defense is hindered by difficulties in expanding M. tuberculosis–specific T cells. To circumvent this problem, we cloned CD4+ T cells from M. tuberculosis–infected B6 mice and generated transgenic mice expressing a T cell receptor specific for the immunodominant antigen early secreted antigenic target 6 (ESAT-6). Adoptively transferred naive ESAT-6–specific CD4+ T cells are activated in pulmonary lymph nodes between 7 and 10 d after aerosol infection and undergo robust expansion before trafficking to the lung. Adoptive transfer of activated ESAT-6–specific Th1 cells into naive recipients before aerosol M. tuberculosis infection dramatically enhances resistance, resulting in 100-fold fewer bacteria in infected lungs. However, despite large numbers of Th1 cells in the lungs of mice at the time of M. tuberculosis challenge, protection was not manifested until after 7 d following infection. Our results demonstrate that pathogen-specific Th1 cells can provide protection against inhaled M. tuberculosis, but only after the first week of infection.
A Preference Extraction Method Using Installed Applications and Their Descriptions

As personalization technologies are widely used, preference extraction is becoming important. In this work, we propose a preference extraction method on the basis of applications that are installed on a user's smart device. In this method, keywords are extracted from descriptions of the installed applications on an application market. Then, each keyword is scored by three scoring criteria: degree of characteristic of the keyword in the description, scarcity and usage time of the application. As a result, the user's preference is expressed in the form of a list of pairs of a word and its importance score. From the experimental result, we confirmed that the installed applications are useful as an information source for user preference extraction. We also examined the effectiveness of each of the scoring criteria. From the result, we found that the criterion that represents scarcity of the application is effective for users installing a large number of applications. On the other hand, the criterion that represents usage time of the application tends to be effective for users using their device for a long time.
Sex‐selective Predation by Threespine Sticklebacks on Sea Lice: A Novel Cleaning Behaviour

Cleaning interactions have been described in a wide range of fish species and other taxa. We observed a novel cleaning behaviour during a study of the transmission dynamics of sea lice (Lepeophtheirus salmonis) between juvenile pink salmon (Oncorhynchus gorbuscha) and threespine sticklebacks (Gasterosteus aculeatus) in the Broughton Archipelago, British Columbia, Canada. Experiments showed that sticklebacks significantly reduced the number of sea lice on individual juvenile salmon. Adult female lice were preferentially consumed by sticklebacks, and gravid female lice also experienced egg string cropping. Overall, 76% of gravid female lice experienced either consumption, egg string cropping, or both by sticklebacks. This preference by sticklebacks for female parasites may stem from female lice being larger than males and the added nutritional value of egg strings on gravid females. Cleaning by sticklebacks can potentially have an impact on sea louse populations on wild juvenile salmon.
Konrad-zuse-zentrum F ¨ Ur Informationstechnik Berlin Asymptotic Mesh Independence of Newton's Method Revisited Asymptotic Mesh Independence of Newton's Method Revisited *

The paper presents a new affine invariant theory on asymptotic mesh independence of Newton's method for discretized nonlinear operator equations. Compared to earlier attempts, the new approach is both much simpler and more intuitive from the algorithmic point of view. The theory is exemplified at collocation methods for ODE boundary value problems and at finite element methods for elliptic PDE problems. * Supported by the DFG Research Center " Mathematics for key technologies " (FZT 86) in Berlin.
SaaS and Integration Best Practices

The rising adoption of software-as-a-service (SaaS) applications by enterprise organizations has been driven by deep dissatisfaction with on-premise applications, which require organizations to purchase and deploy infrastructure, overstock on licenses, and pay for expensive resources for customizations, upgrades, and on-going maintenance. The large upfront investments combined with unpredictable costs and an immeasurable return on investment have prompted organizations to seek cheaper less-risky alternatives. Many have found that SaaS applications, which require minimal or no infrastructure and maintenance, can be deployed quickly and have a predictable cost model representing less risk and a faster return on investment. The new demand has led to rapid innovation in SaaS applications, SaaS platforms, third-party SaaS add-ons, and SaaS integration tools. However, enterprise organizations still have the burden of integrating these applications with their back-office systems and on-premise applications, without which the SaaS applications have little to no value. Complex enterprise integration requirements challenge even the best SaaS solution providers today; there are still limitations and pitfalls to be wary of. In this paper, we describe some SaaS integration best practices, present a case study, and highlight emerging integration technologies that can help ease the burden of integrating SaaS applications.
Mechanisms of white matter changes induced by meditation

Using diffusion tensor imaging, several recent studies have shown that training results in changes in white matter efficiency as measured by fractional anisotropy (FA). In our work, we found that a form of mindfulness meditation, integrative body–mind training (IBMT), improved FA in areas surrounding the anterior cingulate cortex after 4-wk training more than controls given relaxation training. Reductions in radial diffusivity (RD) have been interpreted as improved myelin but reductions in axial diffusivity (AD) involve other mechanisms, such as axonal density. We now report that after 4-wk training with IBMT, both RD and AD decrease accompanied by increased FA, indicating improved efficiency of white matter involves increased myelin as well as other axonal changes. However, 2-wk IBMT reduced AD, but not RD or FA, and improved moods. Our results demonstrate the time-course of white matter neuroplasticity in short-term meditation. This dynamic pattern of white matter change involving the anterior cingulate cortex, a part of the brain network related to self-regulation, could provide a means for intervention to improve or prevent mental disorders.
UHF-RFID tag antenna using diamond structure and rectangular loop

This paper proposes the UHF RFID tag antenna design for operation of the frequency band 920–925 MHz corresponding to the standard of UHF RFID in Thailand. The tag antenna fabrication from the thin FR4 substrate (εr = 4.3) with the thickness of substrate of 0.25 mm. The pattern of the tag antenna is omni-directional one. The tag antenna design is used rectangular loop matching technique for matching between the tag antennas with IC chip with the impedance of 21.29-j191.7 Ω at the frequency of 922.5 MHz that is the center frequency. The meander line structure can be decrease the size of tag antenna to compact size.
Enhancing Science Teaching Through Effective Multisensory Integration Approach

Sensory integration takes place in the central nervous system where complex interactions such as co-ordination, attention, arousal levels, autonomic functioning, emotions, memory and higher level cognitive functions are carried out. Sensory integration gets information through the senses, puts it together with prior knowledge, information and memories already stored in the brain to make a meaningful response. Multi-sensory learning, as the name implies, is the process of learning a new subject matter through the use of two or more senses. This may include combining visual, auditory, tactile or kinaesthetic, olfactory and gustatory sensation. By activating brain regions associated with touch, flavour, audition and vision, they indicate a direct relationship between perceptual knowledge and sensory brain mechanisms. The present research study to find out effectiveness of Multisensory Integration Approach to Enhancing Achievement on Science among IX Standard Students reveals that activating appropriate processes through Multisensory Integration Approach plays a vital role in improving achievement in science. Further it is observed that the Multisensory Integration Approach expands the learning schema, since the learner is able to activate appropriate sensory integration. This contributes to meaningful and joyful learning. This facilitates the teacher’s task of enabling the students to apply Multisensory Integration Model on enhancing learning.
SYNCHROTRON-LOSS SPECTRAL BREAKS IN PULSAR-WIND NEBULAE AND EXTRAGALACTIC JETS

Flows of synchrotron-emitting material can be found in several astrophysical contexts, including extragalactic jets and pulsar-wind nebulae (PWNe). For X-ray synchrotron emission, flow times are often longer than electron radiative lifetimes, so the effective source size at a given X-ray energy is the distance electrons radiating at that energy can convect before they burn off. Since synchrotron losses vary strongly with electron energy, the source size drops with increasing X-ray energy, resulting in a steepening of the synchrotron spectrum. For homogeneous sources, this burnoff produces the well known result of a steepening by 0.5 in the source's integrated spectral index. However, for inhomogeneous sources, different amounts of steepening are possible. I exhibit a simple phenomenological picture of an outflow of relativistic electrons with bulk nonrelativistic flow speed, with transverse flow-tube radius, magnetic field strength, matter density, and flow velocity all varying as different powers of distance from the injection point. For such a picture, I calculate the value of the spectral index above the break as a function of the power-law indices, and show the possible range of steepenings. I show that these simple calculations are confirmed by full integrations of source luminosity, which also include the spectral “bump” below the break from the accumulation of electrons formerly at higher energies. In many cases, extragalactic jets show X-ray synchrotron emission steeper by more than 0.5 than the radio emission; the same phenomenon is exhibited by many PWNe. It is possible that source inhomogeneities are responsible in at least some cases, so that the amount of spectral steepening becomes a diagnostic for source dynamical or geometrical properties.
Goal-Directed Learning: A Decision-Theoretic Model for Deciding What to Learn Next

This paper describes a theory called Goal-Directed Learning (gdl) that uses the principle of decision theory to choose learning tasks. The expected utility of being able to predict various features of the environment is computed and those with highest expected utility can be used as learning goals, which an agent's inductive mechanism should form theories to predict. We present a general decision-theoretic formula for the utility of learning goals, formalizing the concept that the best learning goals are those which, if learned, would maximize the agent's expected utility. The performance element of pagoda (Probabilistic Autonomous GOal-Directed Agent), an autonomous agent design presented in 4], is described, and a formula is given for computing the utility of learning goals in pagoda.
D2D caching vs. small cell caching: Where to cache content in a wireless network?

Proximity-based content caching and distribution in wireless networks has been identified as a promising traffic offloading solution for improving the capacity and the quality of experience (QoE) by exploiting content popularity and spatiotemporal request correlation. In this paper, we address the following question: where should popular content be cached in a wireless network? For that, we model a wireless cellular network using stochastic geometry and analyze the performance of two network architectures, namely caching at the mobile device allowing device-to-device (D2D) connectivity and local caching at the radio access network edge (small cells). We provide analytical and numerical results to compare their performance in terms of the cache hit probability, the density of cache-served requests and average power consumption. Our results reveal that the performance of cache-enabled networks with either D2D caching or small cell caching heavily depends on the user density and the content popularity distribution.
Makespan Minimization with Machine Availability Constraints

We investigate the problems of scheduling n jobs to m = m 1 + m 2 identical machines where m 1 machines are always available, m 2 machines have some specified unavailable intervals. The objective is to minimize the makespan. We assume that if a job is interrupted by the unavailable interval, it can be resumed after the machine becomes available. We show that if at least one machine is always available, i.e. m 1 > 0, then the PTAS for Multiple Subset Sum problem given by Kellerer [3] can be applied to get a PTAS; otherwise, m = m 2 , every machine has some unavailable intervals, we show that if (m *** 1) machines each of which has unavailable intervals with total length bounded by *** (n ) ·P sum /m where P sum is the total processing time of all jobs and *** (n ) can be any non-negative function, we can develop a (1 + *** (n ) + *** ) ***approximation algorithm for any constant 0 < *** < 1; finally we show that there does not exist any polynomial time (1 + *** (n ) *** o (1)) ***approximation unless P=NP.
Systemic FasL and TRAIL Neutralisation Reduce Leishmaniasis Induced Skin Ulceration

Cutaneous leishmaniasis (CL) is caused by Leishmania infection of dermal macrophages and is associated with chronic inflammation of the skin. L. aethiopica infection displays two clinical manifestations, firstly ulcerative disease, correlated to a relatively low parasite load in the skin, and secondly non-ulcerative disease in which massive parasite infiltration of the dermis occurs in the absence of ulceration of epidermis. Skin ulceration is linked to a vigorous local inflammatory response within the skin towards infected macrophages. Fas ligand (FasL) and Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) expressing cells are present in dermis in ulcerative CL and both death ligands cause apoptosis of keratinocytes in the context of Leishmania infection. In the present report we show a differential expression of FasL and TRAIL in ulcerative and non-ulcerative disease caused by L. aethiopica. In vitro experiments confirmed direct FasL- and TRAIL-induced killing of human keratinocytes in the context of Leishmania-induced inflammatory microenvironment. Systemic neutralisation of FasL and TRAIL reduced ulceration in a model of murine Leishmania infection with no effect on parasitic loads or dissemination. Interestingly, FasL neutralisation reduced neutrophil infiltration into the skin during established infection, suggesting an additional proinflammatory role of FasL in addition to direct keratinocyte killing in the context of parasite-induced skin inflammation. FasL signalling resulting in recruitment of activated neutrophils into dermis may lead to destruction of the basal membrane and thus allow direct FasL mediated killing of exposed keratinocytes in vivo. Based on our results we suggest that therapeutic inhibition of FasL and TRAIL could limit skin pathology during CL.
A COMPARATIVE STUDY OF DETERMINISTIC AND STOCHASTIC OPTIMIZATION METHODS FOR INTEGRATED DESIGN OF PROCESSES

Abstract This paper focuses on the application of stochastic (genetic algorithms, simulated annealing) and deterministic (sequential quadratic programming) optimization methods for the Integrated Design of processes considering dynamical non-linear models. Moreover, a hybrid methodology that combines both types of methods is proposed, showing an improvement on performance. Controllability indexes such as disturbance sensitivity gains, the H∞ norm, and the ISE were considered to obtain optimum disturbance rejection. In order to illustrate and validate our proposal, an activated sludge process with PI schemes is taken. The problem is stated as a multiobjective non-linear optimization problem with non-linear constraints. The application of the mentioned strategies is discussed. The results are encouraging for future application of these techniques to solve synthesis MINLP problems.
Adaptive Load Distribution in Strong Dynamic Heterogeneous Systems

This paper presents a dynamic load distribution strategy adapting the conditions of dynamic heterogeneous systems at runtime. Workload which is dynamically generated by any processor will be distributed over the system. The goal of this receiver-initiated approach is choosing the slowes t processing element with the highest communication speed as a candidate for load distribution. Decisions from which processor workload will be migrated are totally based on the system's parameters (processor speed and communication speed) evaluated during runtime. The presented load distribution algorithm was evaluated on a parallel implementation of the concurrent logic language Flat Concurrent Prolog (FCP) which runs on heterogeneous workstation clusters using PVM (Parallel Virtual Machine [7]). The presented algorithm shows good improvements for this application. The average runtime of an applicationcan drasti cally be reduced because of the selection of a suitable node.
The mill load modeling of combined grinding system based on RBF neural networks

In order to get the mill load modeling of combined grinding system in normal working condition, this paper proposes a method based on the RBF neural network. The neural network uses three kinds of kernel functions that are Gauss kernel function, multiquadric kernel function and inverse multinuclear kernel function. Using the gradient descent method trains the neural network. With the comparison of three neural network's fitting error, I've come to the conclusion that the RBF neural network based on Gauss function is more accurate.
The Effects of L1 and L2 Hypertext Glosses on Reading Comprehension and Vocabulary Retention among Thai Secondary School Students

This study investigates the effects of first language (L1) and second language (L2) hypertext glosses on reading comprehension (RC), immediate vocabulary recognition (IVR), and delayed vocabulary retention (DVR). A group of 83 secondary school low-achieving students (10 grade) were assigned to read glossed texts, L1 and L2 hypertext glosses. This study may help teachers create glossed texts to improve students’ incidental vocabulary learning and it can contribute to the raising of students’ attitudes towards learning English with encouraging and interesting vocabulary learning conditions. A repeated measure t-test design (without control group) was employed. The results indicated that the effects between the L1 and L2 glosses were significantly different. The paired sample t-test revealed that the L1 gloss scores were significantly higher than the L2 gloss scores regarding RC (p = .014), IVR (p = .000) and DVR (p = .000). The pedagogical implications suggest that reading with the assistance of glosses can be successfully integrated into a real classroom setting to improve low-achieving students' vocabulary knowledge in an English as a Foreign Language (EFL) context. It is recommended that future studies use L1 written story retelling/recall techniques to collect the reading comprehension and vocabulary retention data as choices offer random guesses to the participants.