Miracle-dz/UniFAR-FTUs huggingface dataset:
Whole Exome Sequencing Study Suggests an Impact of FANCA, CDH1 and VEGFA Genes on Diffuse Gastric Cancer Development

Gastric cancer (GC) is one of the most common cancer types in the world with a high mortality rate. Hereditary predisposition for GC is not fully elucidated so far. The aim of this study was identification of possible new candidate genes, associated with the increased risk of gastric cancer development. Whole exome sequencing (WES) was performed on 18 DNA samples from adenocarcinoma specimens and non-tumor-bearing healthy stomach tissue from the same patient. Three pathogenic variants were identified: c.1320+1G>A in the CDH1 gene and c. 27_28insCCCAGCCCCAGCTACCA (p.Ala9fs) of the VEGFA gene were found only in the tumor tissue, whereas c.G1874C (p.Cys625Ser) in the FANCA gene was found in both the tumor and normal tissue. These changes were found only in patients with diffuse gastric cancer and were absent in the DNA of healthy donors.
Relaxation Theory of Thermal Conduction in Liquids

A linear relaxation equation for the heat flux in a fluid, proposed by Vernotte as a generalization of Fourier's law, is shown for liquids to be consistent with the assumption that thermal energy is carried by elastic waves of very high frequency which may be envisaged as being propagated in a continuum. The elastic constants and the velocity of the waves are obtained from the infinite frequency limits of viscoelastic equations, derived in earlier papers to describe the relaxation of compressional and shearing strains, and from these, the relaxation time and thermal conductivity are calculated for several nonassociated liquids with the aid of a theory of Debye. It is shown that the Vernotte equation may be viewed formally, from the point of view of irreversible thermodynamics, as a force‐flux equation linking two irreversible processes, and this interpretation makes it possible to calculate terms in the pressure and internal energy which are nonlinear in the temperature gradient.
A Hybrid Spiking Neural Network Reinforcement Learning Agent for Energy-Efficient Object Manipulation

Due to the wide spread of robotics technologies in everyday activities, from industrial automation to domestic assisted living applications, cutting-edge techniques such as deep reinforcement learning are intensively investigated with the aim to advance the technological robotics front. The mandatory limitation of power consumption remains an open challenge in contemporary robotics, especially in real-case applications. Spiking neural networks (SNN) constitute an ideal compromise as a strong computational tool with low-power capacities. This paper introduces a spiking neural network actor for a baseline robotic manipulation task using a dual-finger gripper. To achieve that, we used a hybrid deep deterministic policy gradient (DDPG) algorithm designed with a spiking actor and a deep critic network to train the robotic agent. Thus, the agent learns to obtain the optimal policies for the three main tasks of the robotic manipulation approach: target-object reach, grasp, and transfer. The proposed method has one of the main advantages that an SNN possesses, namely, its neuromorphic hardware implementation capacity that results in energy-efficient implementations. The latter accomplishment is highly demonstrated in the evaluation results of the SNN actor since the deep critic network was exploited only during training. Aiming to further display the capabilities of the introduced approach, we compare our model with the well-established DDPG algorithm.
Surface micromachined ultrasound transducers in CMOS technology

The paper presents a new technology for electrostatically driven ultrasound transducers, processed by only a few additional steps within a standard BiCMOS process. Measurements of the test structures showed good acoustic properties especially for application in fluids. The full integration with the electronic circuit allows the realization of a new generation of one- and two dimensional arrays for many different applications like low cost phased arrays or 2D arrays for specific medical applications like skin diagnosis.
The Art of Substrate-Integrated-Waveguide Power Dividers

Substrate-integrated-waveguide (SIW) technology can eliminate the limitations associated with conventional rectangular waveguides, i.e., bulky structures and production complexity at higher frequencies. Moreover, SIW technology replaces microstrip structures eliminating the drawback of excessive radiation leakage at higher frequencies. SIW power dividers are key elements in SIW antenna array synthesis. A SIW power divider’s design procedures are more complicated than conventional microstrip power dividers. However, no comprehensive review with design guidelines of substrate-integrated-waveguide (SIW) power dividers has been reported. In this paper, different types of SIW power dividers based on their configurations, functionality, and operating principles are analyzed and some recommendations are made for selection purposes. A comprehensive design guideline for SIW power dividers is given in this paper through a comparative study of T- and Y-type SIW junctions. These guidelines are based on key parameters, including insertion loss, isolation, co-phase bandwidth, return loss bandwidth, and phase balancing. This study provides valuable information for selecting and designing the best possible configuration of SIW power dividers for specific applications in microwave and millimeter-wave frequency ranges. A case study of a Ku-band SIW power divider is performed for a Ku-band soil moisture radiometer SIW antenna array.
A universal UHF near‐field RFID reader antenna with wide bandwidth and adjustable reading area

A universal ultrahigh‐frequency (UHF) near‐field radio‐frequency identification (RFID) reader antenna with wide bandwidth and adjustable reading area is proposed in this letter. The antenna consists of an inverting power splitter base on double‐sided parallel stripline and adjustable traveling‐wave near‐field radiation units, which consists of two symmetrical meander microstrips and a complementary open resonant ring loaded on the ground plane. A design example with three radiation units is simulated, fabricated, and tested for verification. The result indicates that the proposed antenna has the 10‐dB impedance bandwidth of 128%, which completely covers the universal UHF RFID band from 840 to 960 MHz. The 100% read–write rate is achieved within the read–write distance of 10 mm according to the reading test. The reading area of 731 × 120 mm2 can be obtained for increasing the number of radiation units to 10. Moreover, the antenna features low far‐field gain, low‐cost, strong and uniform magnetic field distribution. Therefore, the proposed antenna and design method have good application prospects in the Internet of Things.
Estimating the subgrid variance of saturation, and its parametrization for use in a gcm cloud scheme

The prediction of cloud fraction and condensate in the unified weather forecasting/climate prediction model of the UK Meteorological Office, and many other general‐circulation models, depends upon a probability distribution of a saturation variable in a grid box. A method of estimating the width of the probability distribution of the saturation variable on the scales of one grid box of the climate configuration (2.5° latitude × 3.75° longitude) has been created, using analyses from the global weather forecasting configuration (0.55° latitude × 0.833° longitude). This width was found to be potentially very variable in time at many locations, therefore the use of climatological values was inappropriate. A parametrization was created to predict the width of the probability distribution of the saturation variable for use in the climate model. the concept of this empirical parametrization was based upon a scaling relationship often observed, and which is present in the global analyses. This new statistically based parametrization replaced the standard approximation used in the Hadley Centre climate model, and significantly reduced the model's biases concerning water vapour, temperature and cloud amount in the upper troposphere.
Using UAV-Based Photogrammetry Coupled with In Situ Fieldwork and U-Pb Geochronology to Decipher Multi-Phase Deformation Processes: A Case Study from Sarclet, Inner Moray Firth Basin, UK

Constraining the age of formation and repeated movements along fault arrays in superimposed rift basins helps us to better unravel the kinematic history as well as the role of inherited structures in basin evolution. The Inner Moray Firth Basin (IMFB, western North Sea) overlies rocks of the Caledonian basement, the pre-existing Devonian–Carboniferous Orcadian Basin, and a regionally developed Permo–Triassic North Sea basin system. IMFB rifting occurred mainly in the Upper Jurassic–Lower Cretaceous. The rift basin then experienced further regional tilting, uplift and fault reactivation during the Cenozoic. The Devonian successions exposed onshore along the northwestern coast of IMFB and the southeastern onshore exposures of the Orcadian Basin at Sarclet preserve a variety of fault orientations and structures. Their timing and relationship to the structural development of the wider Orcadian and IMFB are poorly understood. In this study, drone airborne optical images are used to create high-resolution 3D digital outcrops. Analyses of these images are then coupled with detailed field observations and U-Pb geochronology of syn-faulting mineralised veins in order to constrain the orientations and absolute timing of fault populations and decipher the kinematic history of the area. In addition, the findings help to better identify deformation structures associated with earlier basin-forming events. This holistic approach helped identify and characterise multiple deformation events, including the Late Carboniferous inversion of Devonian rifting structures, Permian minor fracturing, Late Jurassic–Early Cretaceous rifting and Cenozoic reactivation and local inversion. We were also able to isolate characteristic structures, fault kinematics, fault rock developments and associated mineralisation types related to these events
Classroom Community and Time: Comparing Student Perceptions in Traditional vs. Accelerated Online Courses

Online educators regularly experiment with ways to create a sense of classroom community in the online courses they design and teach. They do this in part to battle feelings of isolation and loneliness but also to align with prevailing theories of learning (e.g., social constructivism) as well as to mimic idealized in-person face-to-face learning experiences. However, little is known about how well a sense of community is developed in accelerated online courses. Given this, we investigated students’ perceptions of classroom community in traditional length online courses (e.g., 15-week courses) and accelerated online courses (e.g., 7-week courses) taught by the same instructors. The results showed that there was not a statistically significant difference in students’ perceptions of classroom community between the 15-week and 7-week courses. Students in this study rated the accelerated 7-week courses as having a higher sense of classroom community. In this paper, we present the results of our inquiry. We conclude with the implications of our research on research and practice.
Transportation of measure, Young diagrams and random matrices

The theory of transportation of mesure for general cost functions is used to obtain a novel logarithmic Sobolev inequality for measures on phase spaces of high dimension and hence a concentration of measure inequality. The are applications to Plancherel measure associated with the symmetric group, the distribution of Young diagrams partitioning N as N tends to infinity and to the mean field theory of random matrices. For the portential Gamma (N+1), the generalized orthogonal ensemble and its empirical eigenvalue distribution satisfy a Gaussian concentration of measure phenomenon. Hence the empirical eigenvalue distribution converges weakly almost surely as the matix size increases; the limiting density is given by the derivative of the Vershik probability density.
Proxy‐Model Comparison for the Eocene‐Oligocene Transition in Southern High Latitudes

The Eocene‐Oligocene transition (EOT) marks the shift from greenhouse to icehouse conditions at 34 Ma, when a permanent ice sheet developed on Antarctica. Climate modeling studies have recently assessed the drivers of the transition globally. Here we revisit those experiments for a detailed study of the southern high latitudes in comparison to the growing number of mean annual sea surface temperature (SST) and mean air temperature (MAT) proxy reconstructions, allowing us to assess proxy‐model temperature agreement and refine estimates for the magnitude of the pCO2 forcing of the EOT. We compile and update published proxy temperature records on and around Antarctica for the late Eocene (38–34 Ma) and early Oligocene (34–30 Ma). Compiled SST proxies cool by up to 3°C and MAT by up to 4°C between the timeslices. Proxy data were compared to previous climate model simulations representing pre‐ and post‐EOT, typically forced with a halving of pCO2. We scaled the model outputs to identify the magnitude of pCO2 change needed to drive a commensurate change in temperature to best fit the temperature proxies. The multi‐model ensemble needs a 30 or 33% decrease in pCO2, to best fit MAT or SST proxies respectively. These proxy‐model intercomparisons identify declining pCO2 as the primary forcing of EOT cooling, with a magnitude (200 or 243 ppmv) approaching that of the pCO2 proxies (150 ppmv). However individual model estimates span a decrease of 66–375 ppmv, thus proxy‐model uncertainties are dominated by model divergence.
Security Interval Type-2 Fuzzy Sliding Mode Control Under Multistrategy Injection Attack: Design, Analysis, and Optimization

This article considers the security sliding mode control problem for interval type-2 (IT2) fuzzy systems, where the sensor–controller channel may be subject to the false data injection (FDI) attack with a multistrategy attack model. The different attack patterns at each instant are described via a random categorical distribution. It is noted that the injected false data may result in the system state to exceed the modeling domain. In order to handle the above phenomenon, a reconstruction method of the controller's membership functions (MFs) is proposed via analyzing the variation range of the attacked state, and then, a feasible IT2 fuzzy sliding mode security controller is designed. The explicit relation between the raw state signal and attacked state is established, based on which stability conditions dependent on the regional boundaries of MFs are obtained for the input-to-state stability in probability of the closed-loop system. Meanwhile, a framework of security performance optimization is established via searching a desirable sliding matrix, which may be solved via the particle swarm optimization algorithm. Furthermore, the proposed security control scheme is extended to imperfectly matched MFs case, where the controller does not demand the same fuzzy rules as the controlled fuzzy system. Finally, the simulation verification is carried out via numerical and practical examples.
On first-order algorithms for l1/nuclear norm minimization

In the past decade, problems related to l1/nuclear norm minimization have attracted much attention in the signal processing, machine learning and optimization communities. In this paper, devoted to l1/nuclear norm minimization as ‘optimization beasts’, we give a detailed description of two attractive first-order optimization techniques for solving problems of this type. The first one, aimed primarily at lasso-type problems, comprises fast gradient methods applied to composite minimization formulations. The second approach, aimed at Dantzig-selector-type problems, utilizes saddle-point first-order algorithms and reformulation of the problem of interest as a generalized bilinear saddle-point problem. For both approaches, we give complete and detailed complexity analyses and discuss the application domains.
Universal resistivity-strain dependence of carbon nanotube/polymer composites

The resistivity response upon stretching of a carbon nanotube/thermoplastic elastomer composite fabricated by a solution process with good nanotube dispersion and low percolation threshold $({p}_{c}\ensuremath{\sim}0.35\phantom{\rule{0.3em}{0ex}}\mathrm{wt}\phantom{\rule{0.2em}{0ex}}%)$ is reported. The relationship between resistivity and strain (deformation) shows an exponential relationship with universal, nanotube concentration-independent behavior. The temperature dependence of the resistivity is described by the fluctuation induced tunneling model. The experimental resistivity-strain dependence greater than 5% strain is interpreted in terms of this model by consideration of the gap-width modulation of tunnel junctions. Percolation theory applied to the conductive nanotube network indicates that for less than 5% strain, deformation of the conductive network is the controlling mechanism for changes in resistivity.
Effects of haptic imagery on purchase intention

Abstract The COVID‑19 pandemic has increased the popularity of online shopping, and companies are looking for ways to provide consumers with experiences that online shopping cannot provide, such as touching products and imagining them in use. In this context, the importance of haptic imagery of products showcased online is increasing. This study replicated and extended Peck et al.’s (2013, Journal of Consumer Psychology, 23, 189–196) finding that physical control and psychological ownership mediate the influence of haptic imagery on purchase intention. This study showed that imagining touching a product increased purchase intention through the mediation of physical control and psychological ownership compared with not imagining, conceptually replicating Peck et al.’s study. This study also examined the moderating effect of product involvement and showed that there was no moderator role of product involvement. The findings would have a practical application in marketing, such as encouraging consumers to imagine touching the product.
Surface-Emitted Terahertz-Wave Difference-Frequency Generation in Periodically Poled Lithium Niobate Ridge-Type Waveguide

We demonstrated surface-emitted terahertz (THz)-wave difference-frequency generation from a periodically poled magnesium-oxide-doped lithium niobate (PPMgLN) ridge-type optical waveguide. The periodic structure in the direction of propagation of the incident laser light was sufficient for surface emission because the incident laser light was confined within a waveguide. Tunable THz waves were generated at around 1 and 1.5 THz using two ridge-type PPMgLN waveguides. The generated THz wavelengths were determined under the quasi-phase matching condition.
Changepoint detection in daily precipitation data

This paper introduces a method to identify an undocumented changepoint time in a daily precipitation series. A two‐state Markov chain is used to induce dependence in the precipitation amounts; our dynamics allow for seasonality in the daily observations, a structure inherent to many nonequatorial region series. No current precipitation changepoint techniques exist that consider day‐to‐day dependencies, the zero support set aspect (the fact that most measurements are zero), and the periodic dynamics of the problem. The test statistic is constructed by applying cumulative sum methods to a strategically devised set of one‐step‐ahead prediction residuals. The methods are robust to distributional assumptions, requiring only seasonal mean and transition probability estimators. Simulations are presented that demonstrate the efficacy of the methods; application to two daily precipitation series is made. Copyright © 2012 John Wiley & Sons, Ltd.
Experimental Investigation of the Differences Between Reynolds-Averaged and Favre-Averaged Velocity in Supersonic Jets

Abstract Recent advancement in the molecular Rayleigh scattering based technique allowed for simultaneous measurement of velocity and density fluctuations with high sampling rates. The technique was used to investigate unheated high subsonic and supersonic fully expanded free jets in the Mach number range of 0.8 to 1.8. The difference between the Favre averaged and Reynolds averaged axial velocity and axial component of the turbulent kinetic energy is found to be small. Estimates based on the Morkovin’s ‘Strong Reynolds Analogy’ were found to provide lower values of turbulent density fluctuations than the measured data. I. Introduction Reynolds averaging involves dividing a fluid flow parameter w into a time-averaged w , and a fluctuating w′ part: ∫→ ∞= + ′ = T0Tw dtT1w (1) (t) w w (t), w Lim In the Favre-averaging process a density-weighted filtering is used to calculate time average w~ and the remaining fluctuating part w′′: ∫→ ∞= + ′′ = T0T ρw dtT1Limρ1w(t) w~ w (t), w~ (2) where ρ denotes air density. As there is no mass flux across the Favre-averaged streamline, the use of the Favre-averaged variables makes the governing equations for the mean density, mean velocity and the mean enthalpy more compact. In compressible flow, such simplifications are unattainable by the Reynolds averaging process. Experimental data, such as those measured by Particle image Velocimetry and the present Rayleigh scattering technique, however, produce Reynolds averaged quantities. The differences between the two averages for parameters such as the axial velocity u and the turbulent kinetic energy become a concern whenever computational results are to be compared against experimental data.
On the S-approximation of the Earth's gravity field: regional version

The S-approximation method proposed by Stepanova [Inv. Probl. Sci. Eng. 16 (5) (2008), pp. 547–566] is applied for solving interpretation problems when the sphericity of the Earth is taken into account. A new method of finding stable approximate solutions of linear algebraic equation systems is described.
Modifying the t test for assessing the correlation between two spatial processes

Clifford, Richardson, and Hm they require the estimation of an effective sample size that takes into account the spatial structure of both processes. Clifford et al. developed their method on the basis of an approximation of the variance of the sample correlation coefficient and assessed it by Monte Carlo simulations for lattice and non-lattice networks of moderate to large size. In the present paper, the variance of the sample covariance is computed for a finite number of locations, under the multinormality assumption, and the mathematical derivation of the definition of effective sample size is given. The theoretically expected number of degrees of freedom for the modified t test with renewed modifications is compared with that computed on the basis of equation (2.9) of Clifford et al. (1989). The largest differences are observed for small numbers of locations and high autocorrelation, in particular when the latter is present with opposite sign in the two processes. Basic references that were missing in Clifford et al. (1989) are given and inherent ambiguities are discussed.