Miracle-dz/UniFAR-FTUs huggingface dataset:
Attention Relational Network for Skeleton-Based Group Activity Recognition

Group activity recognition is a significant and challenging task in computer vision. The solution of group activity prediction can be classified with traditional hand-crafted features, RGB video features, and skeleton data-based deep learning architectures, such as Graph Convolutional Networks (GCNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory (LSTMs). However, they rarely explore pose information and rarely use relational networks to reason about group activity behavior. In this work, we leverage minimal prior knowledge about the skeleton information to reason about the interactions from group activity. The objective is to obtain discriminative representations and filter out some ambiguous actions to enhance the performance of group activity recognition. Our contribution is a proposed Attention Relation Network (ARN) that fuses the attention mechanisms and joint vector sequences into the relation network. The skeleton joints vector sequences are previously unexplored pose information and assign greater significance attributed to individuals who are more relevant for distinguishing the group activity behavior. First, our model focuses on the specified edge-level information (encompassing both edge and edge motion data) within the skeleton dataset, considering directionality, to analyze the spatiotemporal aspects of the action. Second, recognizing the inherent motion directionality, we establish diverse directions for skeleton edges and extract distinct motion features (including translation and rotation information) aligned with these various orientations, thereby augmenting the utilization of motion attributes related to the action. We also introduce a representation of human motion achieved by combining relational networks and examining their integrated characteristics. Extensive experiments were tested in the Hockey and UT-interaction datasets to evaluate our method, obtaining competitive performance to the state-of-the-art. Results demonstrate the modeling potential of a skeleton-based method for group activity recognition.
Design and Analysis of Electrical Characteristics of 14nm SOI-based Trigate Gaussian Channel Junctionless FinFET

Planar MOSFETs are reaching their physical limits. To overcome the limitations and improve channel gate control, FinFET technology, which uses many gate devices, is a superior choice while lowering the size of planar MOSFETs even further. In this paper, 14nm Silicon-On-Insulator-based Trigate Gaussian Channel Junctionless FinFET is presented. The gate length of 14nm is considered along with an Equivalent Oxide Thickness of 1nm, 5nm as fin width, and the work function of the gate metal is 4.75eV. The device architecture has a non-uniform doping profile (Gaussian distribution) across the fin’s thickness. It is devised to address the effects of Random Dopant Fluctuations such as channel mobility degradation in Junctionless FinFET based devices. The impact of fin height (Fh), gate dielectric and spacer dielectric on the Drain Induced Barrier Lowering, Subthreshold Swing, drain current of GC-JLFinFET is analyzed. The results show that the Ion=101. 5μA/μm and Ion/Ioff is 3.2×107 are obtained for the proposed device structure compared to the existing structure, which has Ion/Ioff of 1.1x107. Furthermore, the proposed design shows better efficiency in short channel characteristics, namely DIBL=25.3 mV/V, Subthreshold Swing=63.88 mV/dec and Transconductance =3.621×105 S/μm. Thus the Gaussian Channel-based FinFET architecture can provide optimum results for Junctionless-based FinFET devices.
Simulating the volatilization of solvents in unsaturated soils during laboratory and field infiltration experiments

This paper describes laboratory and field experiments which were conducted to study the dynamics of trichloroethylene (TCE) as it volatilized from contaminated groundwater and diffused in the presence of infiltrating water through the unsaturated soil zone to the land surface. The field experiments were conducted at the Picatinny Arsenal, which is part of the United States Geological Survey Toxic Substances Hydrology Program. In both laboratory and field settings the gas and water phase concentrations of TCE were not in equilibrium during infiltration. Gas-water mass transfer rate constants were calibrated to the experimental data using a model in which the water phase was treated as two phases: a mobile water phase and an immobile water phase. The mass transfer limitations of a volatile organic compound between the gas and liquid phases were described explicitly in the model. In the laboratory experiment the porous medium was nonsorbing, and water infiltration rates ranged from 0.076 to 0.28 cm h−1. In the field experiment the water infiltration rate was 0.34 cm h−1, and sorption onto the soil matrix was significant. The laboratory-calibrated gas-water mass transfer rate constant is 3.3×10−4 h−1 for an infiltration rate of 0.076 cm h−1 and 1.4×10−3 h−1 for an infiltration rate of 0.28 cm h−1. The overall mass transfer rate coefficients, incorporating the contribution of mass transfer between mobile and immobile water phases and the variation of interfacial area with moisture content, range from 3×10−4 h−1 to 1×10−2 h−1. A power law model relates the gas-water mass transfer rate constant to the infiltration rate and the fraction of the water phase which is mobile. It was found that the results from the laboratory experiments could not be extrapolated to the field. In order to simulate the field experiment the very slow desorption of TCE from the soil matrix was incorporated into the mathematical model. When desorption from the soil matrix was added to the model, the calibrated gas-water mass transfer rate constant is 2 orders of magnitude lower than that predicted using the power law model developed for the nonsorbing laboratory soil.
Body effect on inflow distortion in civil engine intake under crosswind condition

The effect of body on the inlet aerodynamic performance of distortion under crosswind condition for a high pass ratio turbofan engine was investigated. The work is carried out by using computational fluid dynamics on civil nacelle and body. The investigation suggests that: due to the shelter of the body, the inlet distortion on the windward side and leeward side is very different under crosswind conditions. The nacelle on the windward side mainly takes in air from the side while the engine on the leeward side takes in air from above and below. The existence of body makes it easier to produce fuselage vortex and tail vortex near the nacelle. The body has an adverse impact on the intake of the engine on the leeward side and improves the requirement of the crosswind resistance of the upper section of the nacelle.
Climate Shocks Cash Crops and Resilience: Evidence from Colonial Tropical Africa

A rapidly growing body of research examines how weather variability, anomalies and shocks influence economic and societal outcomes. This study investigates the effects of weather shocks on African smallholder farmers in British colonial Africa and intervenes in the debate on the mediating effect of cash crops on resilience to shocks. We employ a dual research strategy, involving both qualitative and econometric analysis. We analyse original primary evidence retrieved from annual administrative records and construct a panel dataset of 151 districts across West, South-central and East Africa in the Interwar Era (1920-1939). Our findings are twofold. First, we qualitatively expose a range of mechanisms leading from drought and excessive rainfall to harvest failure and social upheaval. We then test the link econometrically and find a robust U-shaped relation between rainfall deviation and social upheaval, proxied by annual imprisonment. Second, we review a long-standing and unsettled debate on the impact of cash crop cultivation on farmers’ resilience to environmental shocks and find that cash crop districts experienced lower levels of social tension and distress in years of extreme rainfall variability.
Pliocene stable isotope stratigraphy of site 846

Oxygen and carbon isotope ratios were measured in benthic foraminifers from the entire Pliocene and latest Miocene sections of Site 846, a 180-m section, at a sampling interval of 10 cm. This provides a temporal resolution of about 2500 yr. The documented continuity of the record is excellent. Using the time scale that was developed on the basis of orbital tuning of GRAPE density records, we observed a fairly constant phase relationship between δ 18 θ and variations in the obliquity of EaruYs rotational axis. A new numbering scheme for Pliocene isotope stages is proposed. This high-resolution δ 18 θ record clarifies several interesting aspects of late Neogene climatic evolution, including a "glacial" event that may have caused the final Messinian desiccation of the Mediterranean Sea; one or more "interglacial" events that might have caused refilling of the Mediterranean; a well-resolved couplet of glacial events at about the age of the Sidujfall Subchron; interglacial extremes in the early part of the Gauss that could have resulted from either significant deglaciation on Antarctica or from warming of deep water; and a gradual ramp of increasingly extreme "glacial" events, starting at about the Kaena Subchron and culminating with δ 18 θ stage 100 in the earliest Matuyama.
Least-squares Gaussian Beam Migration

We present a theory of Least-Squares Gaussian Beam Migration (LSGBM), which uses Gaussian beam propagator as the kernel of linearized forward modeling (demigration) and migration. Gaussian beam demigration relies on the calculation of the Green functions by a Gaussian-beam summation for the downward and upward wavefields. Actually, the adjoint operator of Gaussian beam demigration accounts for prestack depth migration by the cross-correlation imaging condition, and in the migration process, seismic traces are calculated one by one for each shot. Application of Gaussian beam demigration/migration algorithms to the least-squares migration scheme can optimally estimate a subsurface reflectivity. The proposed LSGBM is illustrated with a recorded data generated by Gaussian beam demigration for the Marmousi2 model. Numerical results show that LSGBM, compared to migration (adjoint) with Gaussian beams, produces images with more balanced amplitude, higher resolution and even fewer artifacts.
Polyphase deformation and evidence for transpressive tectonics in the Kimbi area, northwestern Cameroon Pan-African fold belt

The structures of the Pan-African fold belt in North-western Cameroon (Kimbi area) are the result of a succession of several events. Petrographic description and detailed kinematical analysis of the various structures with emphasis on superposed folds discovered in the metamorphic and plutonic complex of Kimbi area provided detailed information on the structures and the relative timing of deformation, which are as follows: (1) an early Pan-African stage (D1) of tangential movement immediately followed by (2) two stages (D2 and D3). D2phase is heterogeneous simple shear in dextral transpressive context. D3tectonic phase, also marked by dextral transpressional movements, is the phase of superposed folding with a NNE-SSW kinematics direction. D2 and D3 are associated with medium-grade amphibolites facies metamorphism. (3) A brittle stage (D4) responsible for the emplacement of granitic veins, faults and joints. The similarities of these last phases with the central Cameroon shear-zone suggest that the D3 and D4 stage are controlled by transcurrents tectonics. Transpressive tectonic seem to be the main deformation style in major shear zones of Central Africa and NE Brazil. Key words: Transpressive tectonic, Pan-African, tangential movement, transcurrent tectonics, Cameroon.
Level merging attention based on dense network for remote sensing image scene classification

In the intelligent extraction of high-resolution remote sensing images, the scene classification of remote sensing images has great application prospects in many application fields. In past research, convolutional neural networks have shown great potential, and the introduction of the attention mechanism can further improve the feature representation ability in CNNs-based models. This letter proposes a new network architecture for remote sensing image scene classification. By introducing two attention mechanisms with different structures at different operation levels, the attention mechanism is merged at the level, and the performance of the basic network structure is effectively improved by using the new network architecture constructed. The overall accuracy show that the two attention structures can enhance the feature extraction effect overall and the details effectively. Experimental results on two public datasets, UC Merced and NWPU-RESISC45, show that the proposed model outperforms the current state-of-the-art methods in classification accuracy.
Finite Element and Fluid-Structure Interaction Modeling of a Balloon Catheter

Intervention treatments for aortic stenosis strongly rely on the use of a medical balloon catheter which is utilized for dilating the narrowed aortic valve or the deployment of the implanted devices. However, the complete inflation of the balloon will block the blood outflow and cause instability. This paper demonstrates a computational analysis method to examine the influence of the amount of balloon inflation volume on balloon movement within a pulsating fluid environment. A tri-folded typical shape of the balloon model was inflated by pressurization. The balloon’s front projection area changes during both simulation and experiment were recorded. To address the interaction between the balloon model with varying inflation levels and the introduction of fluid into the arched aorta, a Fluid-Structure Interaction (FSI) model was developed. Compared with the experimental data, the front projection area in the simulation showed a similar increment, which can be used to validate the balloon model. For FSI simulation, the balloon catheter’s maximum displacement rises with the inflation level, with a slight rise at about 10 ml and a substantial rise at 20 ml volume. This work showed a significant advancement in the ability to replicate balloon movement during valvuloplasty using an FSI model.
Motivational Interviewing Effect on Medication Adherence and Other Outcomes in People with Schizophrenia (PwS): A Review

Adherence will have an impact on therapy because schizophrenia is a chronic mental disorder that requires long-term treatment. One strategy to improve adherence to medications is motivational interviewing (MI), although more study is needed to see how well it works and whether it has any other effects on schizophrenia. The study aimed to assess the effectiveness of motivational interviews in improving adherence to medications and other positive impacts on PwS. A literature review using PubMed, Science Direct, Springerlink, and google scholar databases from 2010-2023 focused on keywords adherence, schizophrenia, and motivational interviewing. The results showed that MI has inconsistencies in their effect on improving medication adherence in PwS, but some studies found evidence of an association between MI and other outcomes, such as improvement in psychotic symptoms and decreased hospitalisation rates. Differences in patient characteristics and MI interventions in each study, the to perform MI techniques, and the trusting relationship built by the counsellor with the patient will affect the impact of MI on adherence. MI showed inconsistencies in improving medication adherence in people with schizophrenia. Several factors will affect the effectiveness of MI. However, MI also has the potential to improve psychosis symptoms and reduce hospitalisation rates, although more research is needed.
Improved normal distribution function for skin specular reflection rendering based on GGX distribution

With the development of subsurface scattering technology in recent years, skin rendering has also increased realism. However, as an important part of skin rendering, specular rendering now mostly still uses the K/S model based on Beckmann’s normal distribution function, which makes skin specular reflection always too concentrated, reducing the realism of rendering. To solve this problem, this paper proposes an improved normal distribution function: GGX-Improved based on the GGX normal distribution function. By introducing a parameter K into the GGX normal distribution function, it can realize the adjustment of the tail length of the K/S model specular reflection while ensuring the shape invariance, to make the skin specular reflection softer and more natural, which enhances the realism of the skin rendering.
A Reliable Position Estimation Methodology Based on Multi-Source Information for Intelligent Vehicles in Unknown Environment

Accurate position is important for intelligent vehicles especially in unknown environments without prior information. Light Detection and Ranging (LiDAR) has shown great potential in the application of intelligent vehicles, especially when satellites fail. However, the following should be considered to further improve its positioning performance. Firstly, the LiDAR positioning accuracy is influenced by the initial iteration value. Secondly, the cumulative error of LiDAR positioning cannot be ignored due to its incremental positioning method. To circumvent aforementioned problems, a reliable position estimation methodology based on multi-source information is proposed. Initially, a deep neural network based on multi view features multi-head self-attention fusion is designed to estimate the relative heading value to offer initial value for LiDAR positioning. Then, the cooperative positioning multilayer perceptron (CPMLP) is proposed to obtain reliable cooperative position observation just by one road side unit to suppress the cumulative error especially in the environment without prior information. Lastly, the probabilistic graphical model is used to fuse multi-source information. Extensive dataset and real experiments show the effectiveness of our methodology.
Late Quaternary palaeoenvironmental reconstructions from a permafrost sequence (North Siberian Lowland, SE Taymyr Peninsula)—a multidisciplinary case study

A Late Quaternary permafrost profile from the Labaz Lake area (Taymyr Peninsula, Central Siberia) has been investigated using analyses of diatoms, pollen, sedimentology and geochemistry. A sedimentation gap for the termination of the Pleistocene and the start of lacustrine sedimentation in the Boreal can be inferred. At that time shallow‐lake conditions prevailed and a connection to the Labaz Lake is probable. The diatom data provide indications for the assessment of the Holocene environmental development of the study site in more detail. The most favourable climatic conditions and comparatively higher water level stands are inferred for the early Atlantic. Towards the end of this period the gradual transition to a wetland with poor‐fen character took place. Within the Subboreal there was a short episode with mild climate conditions. At that time the last trees occurred in the Labaz Lake area and somewhat higher water level stands were likely. The Subatlantic climate deterioration led to further drying up of the wetland along with a lowering of water pH and permafrost aggradation. The transition from a locality with low‐centre to one with high‐centre polygons is still underway.
Self-Powered ε-GaO Schottky Photodiode Array Featuring High External Quantum Efficiency Toward Solar-Blind UV Imaging

In this work, a Ga2O3-based Schottky photodiode array is fabricated and discussed, towards solar-blind UV image sensing application. The Ga2O3 thin film was prepared by metalorganic chemical vapor deposition, and the array was constructed via UV photolithography technique. Excited by 254 nm solar-blind UV light, the photodiode unit has responsivity, external quantum efficiency, and specific detectivity of 35.1 A/W, <inline-formula> <tex-math notation="LaTeX">$1.7\times 10 ^{4}$ </tex-math></inline-formula>% and <inline-formula> <tex-math notation="LaTeX">$1.6\times 10 ^{14}$ </tex-math></inline-formula> Jones at −10 V; and of 0.17 A/W, 83% and <inline-formula> <tex-math notation="LaTeX">$1.94\times 10 ^{13}$ </tex-math></inline-formula> Jones at 0 V. This indicates that it is a self-powered photodetector with high photo-response. The high external quantum efficiency at 0 V suggest a high-efficient photon-electron conversion efficiency. In addition, the multi-pixels photodiode array exhibited low current deviation of 6.5% towards high-resolution and low chromatic aberration image sensing.
Generalized Analysis of Systems Based on Two Nonlinear Resonators

Circuits containing two nonlinear resonators have been recently proposed for a variety of applications, such as nonlinear isolators, robust wireless power transfer, and sensors. However, their simulation is difficult due to the presence of hysteresis phenomena, associated with turning points in the solution curve, and even disconnected curves, as will be shown in this work. Here, we will present a general analysis methodology, compatible with commercial harmonic balance (HB) and able to provide all the coexisting periodic solutions. It is based on the use of two auxiliary generators (AGs), one per nonlinear resonator. The first AG acts like an independent source and controls the second one, which also depends on the input source, unlike a previously presented formulation. This extra dependence enables a systematic and broad-scope application but demands a conceptually different analysis strategy, presented in this work. Besides its numerical capabilities (in combination with HB), the new formulation will provide insight into the complex behavior of systems composed by two nonlinear resonators. It will be illustrated through its application to a Lorentzian–Fano nonlinear isolator and a system for robust near-field wireless power transfer, in which the new formulation particularizes to the previous one.