Miracle-dz/UniFAR-FTUs huggingface dataset:
Two-dimensional ferromagnetism with long-range interactions in the layered magnetic topological insulator MnBi2Te4.

MnBi2Te4(MBT) is a promising van der Waals layered antiferromagnetic (AF) topological insulator that combines a topologically non-trivial inverted Bi-Te band gap with ferromagnetic (FM) layers of Mn ions. We perform inelastic neutron scattering (INS) on co-aligned single crystals to study the magnetic interactions in MBT. Consistent with previous work, we find that the AF interlayer exchange coupling and uniaxial magnetic anisotropy have comparable strength, which supports metamagnetic transitions that allow access to different magnetic symmetries in applied fields. Modelling of the two-dimensional intralayer FM spin waves requires the introduction of long-range and competing Heisenberg FM and AF interactions, up to at least the seventh nearest-neighbor, and possess anomalous damping, especially near the Brillouin zone boundary. First-principles calculations of insulating MBT find that both interlayer and intralayer magnetic interactions are long-ranged. We discuss the potential roles that bulk $n$-type charger carriers and chemical disorder play in the magnetism of MBT.
X-ViT: High Performance Linear Vision Transformer without Softmax

Vision transformers have become one of the most important models for computer vision tasks. Although they outperform prior works, they require heavy computational resources on a scale that is quadratic to the number of tokens, $N$. This is a major drawback of the traditional self-attention (SA) algorithm. Here, we propose the X-ViT, ViT with a novel SA mechanism that has linear complexity. The main approach of this work is to eliminate nonlinearity from the original SA. We factorize the matrix multiplication of the SA mechanism without complicated linear approximation. By modifying only a few lines of code from the original SA, the proposed models outperform most transformer-based models on image classification and dense prediction tasks on most capacity regimes.
Clinical Study Gastric Cancer in Young Patients Manzoor

Aim.The aim of this study was to see the clinical, pathological, and demographic profile of young patients with stomach carcinoma besides association with p53. Patients and Methods. Prospective study of young patients with stomach carcinoma from January 2005 to December 2009. A total of 50 patients with age less than 40 years were studied. Results. Male female ratio was 1 : 1.08 in young patients and 2.5 : 1 in older patients. A positive family history of stomach cancer in the first degree relatives was present in 10% of young patients. Resection was possible only in 50% young patients. 26% young patients underwent only palliative gastrojejunostomy. The most common operation was lower partial gastrectomy in 68%. Amongst the intraoperative findings peritoneal metastasis was seen in 17.4% in young patients. 50% young patients presented in stage IV as per AJCC classification (P value .004; sig.). None of the patients presented as stage 1 disease in young group.Conclusion. Early detection of stomach carcinoma is very important in all patients but in young patients it is of paramount importance.
Penalty and related estimation strategies in the spatial error model

Spatial autoregressive models are powerful tools in the analysis of data sets from diverse scientific areas of research such as econometrics, plant species richness, cancer mortality rates, image processing, analysis of the functional Magnetic Resonance Imaging (fMRI) data, and many more. An important class in the host of spatial autoregressive models is the class of spatial error models in which spatially lagged error terms are assumed. In this paper, we propose efficient shrinkage and penalty estimators for the regression coefficients of the spatial error model. We carry out asymptotic as well as simulation analyses to illustrate the gain in efficiency achieved by these new estimators. Furthermore, we apply the new methodology to housing prices data and provide a bootstrap approach to compute prediction errors of the new estimators.
Heme oxygenase-1: a novel therapeutic target for gastrointestinal diseases

Heme oxygenase-1 (HO-1) is the rate-limiting enzyme in the catabolism of heme, followed by production of biliverdin, free iron and carbon monoxide (CO). HO-1 is a stress-responsive protein induced by various oxidative agents. Recent studies demonstrate that the expression of HO-1 in response to different inflammatory mediators may contribute to the resolution of inflammation and has protective effects in several organs against oxidative injury. Although the mechanism underlying the anti-inflammatory actions of HO-1 remains poorly defined, both CO and biliverdin/bilirubin have been implicated in this response. In the gastrointestinal tract, HO-1 is shown to be transcriptionally induced in response to oxidative stress, preconditioning and acute inflammation. Recent studies suggest that the induction of HO-1 expression plays a critical protective role in intestinal damage models induced by ischemia-reperfusion, indomethacin, lipopolysaccharide-associated sepsis, trinitrobenzene sulfonic acid, and dextran sulfate sodium, indicating that activation of HO-1 may act as an endogenous defensive mechanism to reduce inflammation and tissue injury in the gastrointestinal tract. In addition, CO derived from HO-1 is shown to be involved in the regulation in gastro-intestinal motility. These in vitro and in vivo data suggest that HO-1 may be a novel therapeutic target in patients with gastrointestinal diseases.
Energy-based stabilisation and H∞ robust stabilisation of stochastic non-linear systems

This study proposes a constructive stabilisation and H ∞ robust controller design method for stochastic non-linear systems from a novel dissipation analysis and energy point of view. First, the authors propose a sufficient condition for the dissipation of stochastic Hamiltonian systems and discuss the energy property of the systems, which will be used for the stability analysis and feedback controller design. Then, the authors show that the system is (asymptotically) stable in probability if it is (strictly) dissipative. By completing the Hamiltonian realisation of the stochastic non-linear systems, a feedback controller is proposed to stabilise the system under the condition of dissipation and zero state detectability. For stochastic non-linear systems subjected to external disturbances, an energy-based H ∞ controller was proposed by choosing the Hamiltonian function to construct a solution of Hamiltonian–Jacobi inequality. Finally, the effectiveness of the proposed method was illustrated via the inverted pendulum systems.
Improving Target-driven Visual Navigation with Attention on 3D Spatial Relationships

Embodied artificial intelligence (AI) tasks shift from tasks focusing on internet images to active settings involving embodied agents that perceive and act within 3D environments. In this paper, we investigate the target-driven visual navigation using deep reinforcement learning (DRL) in 3D indoor scenes, whose navigation task aims to train an agent that can intelligently make a series of decisions to arrive at a pre-specified target location from any possible starting positions only based on egocentric views. However, most navigation methods currently struggle against several challenging problems, such as data efficiency, automatic obstacle avoidance, and generalization. Generalization problem means that agent does not have the ability to transfer navigation skills learned from previous experience to unseen targets and scenes. To address these issues, we incorporate two designs into classic DRL framework: attention on 3D knowledge graph (KG) and target skill extension (TSE) module. On the one hand, our proposed method combines visual features and 3D spatial representations to learn navigation policy. On the other hand, TSE module is used to generate sub-targets which allow agent to learn from failures. Specifically, our 3D spatial relationships are encoded through recently popular graph convolutional network (GCN). Considering the real world settings, our work also considers open action and adds actionable targets into conventional navigation situations. Those more difficult settings are applied to test whether DRL agent really understand its task, navigating environment, and can carry out reasoning. Our experiments, performed in the AI2-THOR, show that our model outperforms the baselines in both SR and SPL metrics, and improves generalization ability across targets and scenes.
The physical processes causing nocturnal rainfall over northwest Australia and their representation in high‐ and low‐resolution models with parametrized convection

The diurnal cycle of precipitation in the Tropics is represented poorly in general circulation models (GCMs), which is primarily attributed to the representation of moist convection. Nonetheless, in areas where precipitation is driven by the diurnal cycle in the synoptic‐scale flow, GCMs may represent that circulation–rainfall relationship well. Over northwest Australia there is a tendency for precipitation to peak overnight where the diurnal cycle of the heat low circulation leads to the development of strong convergence after local sunset. In order to assess the heat low–precipitation relationship in more detail, a case‐study approach is used to investigate the actual ‘weather’ that is responsible for night‐time precipitation. The study shows that, where there is sufficient moisture, precipitation typically forms along convergence zones that coincide with boundaries between relatively moist and dry air masses (termed a ‘dryline’). A convergence line detection algorithm is then used to identify the fraction of observed nocturnal rainfall that is associated with any convergence zones. The same evaluation is then undertaken for a relatively high‐resolution (MetUM) and low‐resolution (ACCESS1.0) GCM, which simulate rainfall‐generation processes similar to the observations. Finally, the convergence line detection/precipitation algorithm is run on other GCM data (from CMIP5) to see whether the same processes occur despite different model configurations (i.e. physics), which appears to be the case.
High-performance FeSe0.5Te0.5 thin films fabricated on less-well-textured flexible coated conductor templates

We report on the transport properties of FeSe0.5Te0. 5 (FST) thin films fabricated on less-well-textured flexible coated conductor templates with LaMnO3 (LMO) as buffer layers using pulsed laser deposition. The LMO buffer layers exhibit large in-plane misalignment of ∼7.72°, which is unfavorable for cuprate-coated conductors due to the high grain boundaries. The FST thin films show a superconducting transition temperature of 16.8 K, higher than that of bulk materials due to the compressive strain between LMO and FST. Atomic force microscopy observations reveal that island-like features appear at the surfaces of both LMO and FST, confirming the island growth mode. A self-field transport critical-current density of up to 0.43 MA cm−2 at 4.2 K has been observed in FST thin films, which is much higher than that in powder-in-tube processed FST tapes. The films are capable of carrying current densities of over 105 A cm−2 in the whole applied magnetic field up to 9 T, showing great potential for high-field applications. The results indicate that, for FST, highly textured metal tapes are not needed to produce coated conductors with high performance, which is of great advantage over cuprate-coated conductors.
Pixel-Pair Occlusion Relationship Map (P2ORM): Formulation, Inference & Application Supplementary Material

In this supplementary material, we provide: A.1. ROC-like curves showing our significant and systematic outperformance; A.2. The detailed architecture of our network for occlusion relation estimation; A.3. An ablation study on domain adaptation for training with synthetic images; A.4. An ablation study about the impact of ground truth quality A.5. An adaption of ground truth generation with noised geometry information B.1. Detailed quantitative results on the application to depth map refinement; B.2. An ablation study regarding variants for depth map refinement; C. Illustration of occlusion relationship annotations in our generated datasets.
Quality of working life and turnover intention in information technology work

High turnover has been a major issue in information technology (IT) organizations. A conceptual model to explain turnover was developed and tested in two national samples of IT and IT manufacturing work. The model postulates that quality of working life mediates the relations between job/organizational characteristics and turnover intention. The American sample consisted of 624 IT employees of five IT organizations. The Austrian sample consisted of 677 employees from an international IT production company (IT manufacturing work). A similar questionnaire was used in both studies. The model was tested with path analysis. A core model with main pathways between job demands and supervisory support to emotional exhaustion, and between emotional exhaustion and job satisfaction to turnover intention was confirmed in the national samples and in subsamples of demographics and job types. © 2008 Wiley Periodicals, Inc.
Towards Positive Education: A Mindful School Model

In a world of increasing emphasis on well-being, positive education, articulated as the teaching of skills of wellbeing alongside academic ones, can be a vehicle for educating both the mind and heart. The Singapore education system is moving towards a future curricula, C2015, fostering student-centric and values-driven education. This demands continued engagement of the whole-child through a co-constructive journey, a school ecosystem that encompasses total curricula and whole-school approach, and a future-oriented perspective with multiple pathways of excellence. Mindfulness is a crucial lever for enacting qualitative transformation by enabling individuals and systems to be skilful architects of internal and external changes. It confers clarity, autonomy, and congruence that motivates, calibrates, and informs action. This paper delineates a whole-school approach to cultivating dispositional mindfulness through teaching, embedding and living it. An exposition of mindful schools is given, including but not limited to mindful teaching, learning, structures, and relationships. These mindful components interact to form a collective greater than its summation, instilling a culture and climate that can be self-sustaining. Ultimately, mindful schools can serve as the foundation for positive educational curricula (e.g. character strengths, resilience, motivation), furnishing a pathway towards student flourishing.
Results about fractional derivatives of Zeta functions

Perhaps the most important function in all mathematics is the Riemann Zeta function. For almost 150 years Mathematicians have tried to understand the behavior of the function’s complex zeros. Our main aim is to investigate properties of the Riemann Zeta Function and Hurwitz Zeta Functions, which generalize the Riemann Zeta Function. The main goal of this work is to approach this problem from a traditional and computational approach. We aim to investigate derivatives of Zeta functions by exploring the behavior of its fractional derivatives and its derivatives, which has not been sufficiently examined yet.
Annoyance due to air pollution in Europe.

BACKGROUND Annoyance due to air pollution is a subjective score of air quality, which has been incorporated into the National Environmental monitoring of some countries. The objectives of this study are to describe the variations in annoyance due to air pollution in Europe and its individual and environmental determinants. METHODS This study took place in the context of the European Community Respiratory Health Survey II (ECRHS II) that was conducted during 1999-2001. It included 25 centres in 12 countries and 7867 randomly selected adults from the general population. Annoyance due to air pollution was self-reported on an 11-point scale. Annual mean mass concentration of fine particles (PM(2.5)) and its sulphur (S) content were measured in 21 centres as a surrogate of urban air pollution. RESULTS Forty-three per cent of participants reported moderate annoyance (1-5 on the scale) and 14% high annoyance (> or =6) with large differences across centres (2-40% of high annoyance). Participants in the Northern European countries reported less annoyance. Female gender, nocturnal dyspnoea, phlegm and rhinitis, self-reported car and heavy vehicle traffic in front of the home, high education, non-smoking and exposure to environmental tobacco smoke were associated with higher annoyance levels. At the centre level, adjusted means of annoyance scores were moderately associated with sulphur urban levels (slope 1.43 microg m(-3), standard error 0.40, r = 0.61). CONCLUSIONS Annoyance due to air pollution is frequent in Europe. Individuals' annoyance may be a useful measure of perceived ambient quality and could be considered a complementary tool for health surveillance.
Assessment of model fit via network comparison methods based on subgraph counts

While the number of network comparison methods is increasing, benchmarking of these methods is still in its infancy. The lack of understanding of complex dependencies among network characteristics makes it difﬁcult to fully understand the meaning of the different network comparison methodologies and the relations between them. In this paper we use a Monte Carlo framework as a way to address three general questions about the network comparison methods based on subgraph counts: (1) Can the methods differentiate between networks generated from different network generation mechanisms? (2) Are the number of nodes, or average degree, confounding factors for the comparison of networks? (3) Do all methods reach the same conclusions? Wefurtheruse the Monte Carlo framework to test the ﬁt of ER, Chung-Lu and a duplication divergence model to the protein-protein interaction networks of Yeast, Fly, Worm, Human, E. Coli, ﬁve herpes virus networks and ﬁve social networks. In contrast to previous claims in the literature, we show that the large protein-protein interaction networks are not well modelled by the Chung-Lu model according to any of our tested methods. We ﬁnd that network comparison statistics are not completely invariant to changes in the number of nodes and edges. Some methods focus on ﬁne grain similarities, such as GCD, while other methods, such as Netdis, can capture the similarities of networks despite them having different numbers of nodes and edges.
BASIC SCIENCE REVIEW

Head and neck cancers are heavily infiltrated by immune cells, the significance of which is complex. The natural immune response against head and neck tumors, including antihuman papillomavirus (HPV) T cells, and humoral responses has been clearly documented. However, during the course of tumor progression, co-option of the immune system by tumor cells for their own advantage and increased resistance of tumor cells to immune attack also occur. Inflammation and immune subversion to support angiogenesis are key factors promoting tumor growth. Only a better understanding of this tumor–host interaction will permit a rational design of new immunotherapeutic approaches combining immunostimulation with drugs endowed with the ability to counteract immunoevasion mechanisms. VC 2010 Wiley Periodicals, Inc. Head Neck 32: 946–958, 2010
Electron-impact ionization of W25+

Electron-impact ionization cross sections for the ground level of the W25+ ion have been investigated by performing level-to-level calculations and using the Dirac–Fock–Slater method in the single-configuration approach. The main attention has been focused on the influence of the increasing principal and orbital quantum numbers on the excitation-autoionization (EA) process and its contribution to the total ionization cross sections. The obtained results demonstrate that excitations to the high-nl shells ( n ≥ 9 ) increase cross sections of the indirect ionization process by about 60% compared to the excitations to the lower shells ( n ≤ 8 ). It was established that excitations to the shells with the orbital quantum number l = 4 give the greatest contribution to EA. Maxwellian rate coefficients derived from the cross sections for the ground state are compared with the previously obtained values from the configuration-average distorted-wave (CADW) approximation. The rate coefficients for direct ionization (DI) are smaller than the corresponding CADW values, while the EA rate coefficients are larger than the ones from the CADW calculations. The total DI+EA rate coefficients are about 20% larger than the CADW rate coefficients.
Hydrodynamics of water-worked and screeded gravel beds: A comparative study

The turbulence characteristics within flows over water-worked gravel beds (WGBs) and screeded gravel beds (SGBs) were examined by measuring the instantaneous flow velocity field using a two-dimensional particle image velocimetry system. To compare the responses of a WGB and an SGB to velocity and various turbulence characteristics, the flow Froude number was kept identical for both the beds that remained immobile. The roughness structures of both the beds were measured using a laser scanner. The results showed that the bed surface roughness was higher in the WGB than in the SGB. However, the longest axis of the gravels of WGBs was oriented streamwise owing to the action of water work, but the gravels of SGBs were randomly poised. The distribution of bed roughness fluctuations was negatively skewed in the WGB and positively skewed in the SGB. Double averaging methodology was applied to analyze the flow parameters. In this paper, the vertical profiles of the double-averaged streamwise velocity and the turbulence parameters, specifically the spatially averaged (SA) Reynolds shear and normal stresses, form-induced shear and normal stresses, turbulent kinetic energy (TKE) and form-induced TKE fluxes, quadrant analysis of SA Reynolds shear stress, etc., are presented and analyzed critically by focusing on comparisons between a WGB and an SGB. A comparative study reveals that in the near-bed flow zone, the SGB underestimates the turbulence parameters compared to the WGB. Therefore, in order to represent the prototypical flow in laboratory, the experiments should be performed in a WGB.The turbulence characteristics within flows over water-worked gravel beds (WGBs) and screeded gravel beds (SGBs) were examined by measuring the instantaneous flow velocity field using a two-dimensional particle image velocimetry system. To compare the responses of a WGB and an SGB to velocity and various turbulence characteristics, the flow Froude number was kept identical for both the beds that remained immobile. The roughness structures of both the beds were measured using a laser scanner. The results showed that the bed surface roughness was higher in the WGB than in the SGB. However, the longest axis of the gravels of WGBs was oriented streamwise owing to the action of water work, but the gravels of SGBs were randomly poised. The distribution of bed roughness fluctuations was negatively skewed in the WGB and positively skewed in the SGB. Double averaging methodology was applied to analyze the flow parameters. In this paper, the vertical profiles of the double-averaged streamwise velocity and the turbu.