Miracle-dz/UniFAR-FTUs huggingface dataset:
Proof of all-order finiteness for planar beta-deformed Yang-Mills

We study a marginal deformation of N = 4 Yang–Mills, with a real deformation parameter β. This β-deformed model has only N = 1 supersymmetry and a U(1)×U(1) flavor symmetry. The introduction of a new superspace ⋆-product allows us to formulate the theory in N = 4 light-cone superspace, despite the fact that it has only N = 1 supersymmetry. We show that this deformed theory is conformally invariant, in the planar approximation, by proving that its Green functions are ultra-violet finite to all orders in perturbation theory.
Relationship Between Drusen Height and OCT Biomarkers of Atrophy in Non-Neovascular AMD

Purpose To determine if increasing drusen height correlates with predictive optical coherence tomography (OCT) biomarkers of atrophy. Methods Retrospective cross-sectional study that enrolled patients with drusen associated with intermediate AMD. Macular drusen were classified as small, intermediate, large, or very large based on OCT quartile measurement of height. Drusen diameter was also tabulated. The presence and localization of the OCT biomarkers of atrophy were assessed: disruption of the external limiting membrane and ellipsoid zone, intraretinal hyper-reflective foci, RPE disruption, choroidal hypertransmission, and presence of hyporeflective cores. Predictive OCT biomarkers of atrophy were correlated with drusen height. Results A total of 155 eyes from 104 patients met the inclusion and exclusion criteria. The mean age was 75.7 ± 8.7 years, and patients were predominantly female (74.0%). The mean visual acuity was logMAR 0.2 ± 0.2 (Snellen equivalent 20/32). The average drusen height was 134.6 ± 107.5 µm and the greatest horizontal diameter was 970.7 ± 867.4 µm. Disruption of the external limiting membrane and ellipsoid zone, RPE thickening or thinning, intraretinal hyper-reflective foci, choroidal hypertransmission, and presence of hyporeflective cores (P < 0.05) were more common in eyes with large drusen and very large drusen versus small or intermediate drusen. All biomarkers were positively correlated with drusen height. OCT biomarkers of atrophy were predominantly located at the apex of the drusen. Conclusions Predictive OCT biomarkers of atrophy, specifically signs of RPE breakdown and disruption, occur more commonly in large or very large drusen, especially in drusen with greater height and separation of the RPE from the underlying choroid.
On the origin of central abundance drops in the intracluster medium of galaxy groups and clusters

A central drop of ICM Fe abundance has been observed in several cool-core clusters. It has been proposed that this abundance drop may be due, at least partially, to the depletion of Fe into dust grains in the central, high-density regions. According to this scenario, noble gas elements such as Ar and Ne are not expected to be depleted into dust, and therefore should not show any drop, but follow the general increase of metal abundance toward the center. In this work, we test this scenario by measuring with {\sl Chandra} data the radial profiles of Ar and Ne in a sample of 12 groups and clusters where a central drop in Fe abundance has been detected. We confirm the presence of the Fe drop in 10 out of 12 clusters at more than 2$\sigma$ c.l. , and 4 Ar drops with similar significance. We also find 4 Ne drops, with the caveat that Ne abundance measurement from CCD spectra suffers from systematics not completely under control. Our results are consistent with an abundance drop common to the three elements. When comparing the profiles, we find that, on average, the abundance profiles of Ar and Ne are significantly higher than Fe and steeper toward the center, while they all gradually become consistent with solar composition at $r\geq 0. 05r_{500}$. We also check that Si and S profiles are mostly consistent with Fe. This result confirms a scenario in which some fraction of Fe is depleted into dust grains in the inner regions, although the global central abundance drop is mostly due to mechanical processes, like the displacement of metal-rich ICM from the very center to larger radii by AGN-driven feedback. Finally, we report the detection of an Fe drop in the cluster MACSJ1423.8+2404 at $z=0.543$, showing that this feature appears early on in cool-core clusters.
A comparison between the hourly autoscaled and manually scaled characteristics from the Chilton ionosonde from 1996 to 2004

Most monitoring ionosonde stations now rely on automatic processing rather than manual processing to provide ionospheric characteristics. A systematic assessment was made of the quality of all the key ionospheric characteristics scaled automatically from hourly ionograms from the midlatitude Chilton ionosonde in the United Kingdom, by comparing them with the definitive values produced by manual scaling. The data for the study were a nearly continuous series of hourly values covering the majority of solar cycle 23 from 1996 to the end of 2004. This period includes solar maximum and minimum conditions and quiet and disturbed intervals, and the investigation is the first comprehensive examination of the performance of automatic scaling without any data preselection over such an extended period. The accuracy of autoscaled values during storm periods was examined against the global storm index Dst for the whole 9‐year data set. Geomagnetic conditions were found to have only a small effect on autoscaling performance, with the most important identifiable cause of error being the truncation of automatic layer traces due to broadcast interference. Overall, the performance of the autoscaling algorithms was found to be acceptable, with the characteristics foF2, h′E, M(3000)F2, and MUF(3000)F2 within defined error bounds for more than 90% of the time and all characteristics within these bounds more than 80% of the time.
Detectability of High-Redshift Elliptical Galaxies in the Hubble Deep Field

Relatively few intensively star-forming galaxies at redshifts of z>2.5 have been found in the Hubble Deep Field (HDF). This has been interpreted to imply a low space density of elliptical galaxies at high z, possibly due to a late (z<2.5) epoch of formation or to dust obscuration of the ellipticals that are forming at z~3. I use Hubble Space Telescope UV (~2300 Å) images of 25 local early-type galaxies to investigate a third option, that ellipticals formed at z>4.5 and were fading passively by 2<z<4.5. Present-day early-type galaxies are faint and centrally concentrated in the UV. If elliptical galaxies formed their stars in a short burst at z>4.5 and have faded passively to their present brightnesses at UV wavelengths, they would generally be below the HDF detection limits in any of its bands at z>2.5. Quiescent z~3 ellipticals, if they exist, should turn up in sufficiently deep IR images.
The other blue: Role of sky in the perception of nature

Nature is frequently operationalized as greenery or water to estimate the restorativeness of the environment. Pursuing a deeper understanding of the connection between representation of naturalness and its relationship with restoration, we conducted an experiment aimed to investigate if the sky is perceived as an element of nature. The main goal of this study was to understand how the composition of the environment guides people’s selection of sky as nature in an explicit task. Moreover, we investigated how the amount of visible sky determines this relationship. One hundred five participants participated in a novel explicit judgment task conducted online. In this task, we prepared a set of images trimmed out of 360-degree high dynamic range images. The images were classified according to two primary independent variables representing type of environment (four levels: Nature, Some Nature, Some Urban and Urban) and horizon level (three levels: Low, Medium and High). Each participant was asked to select, by clicking on the image, what they consider as “nature. ” In addition, they were asked to judge images on five visual analogue scales: emotional response, aesthetic preference, feeling of familiarity, the openness of the space and naturalness. For analysis, images were segmented into 11 semantic categories (e.g., trees, sky, and water) with each pixel being assigned one semantic label. Our results show that, sky is associated with selections of nature in a specific pattern. The relationship is dependent on the particular set of conditions that are present in the environment (i.e., weather, season of the year) rather than the type of the environment (urban, nature). The availability of sky on the image affects the selection of other nature labels with selections more likely when only a small amount of sky was available. Furthermore, we found that the amount of sky had a significant positive association with the naturalness rating of the whole image, but the effect was small. Our results also indicate that subjective selections of sky predict the naturalness better than trees and water. On the other hand, objective presence of trees and water has a stronger positive association with naturalness while objective presence of sky is positively associated with naturalness. The results show that, relative to its availability sky is considered as nature.
Review and assessment of interpolatory model order reduction methods for frequency response structural dynamics and acoustics problems

Frequency sweeps in structural dynamics, acoustics, and vibro‐acoustics require evaluating frequency response functions for a large number of frequencies. The brute force approach for performing these sweeps leads to the solution of a large number of large‐scale systems of equations. Several methods have been developed for alleviating this computational burden by approximating the frequency response functions. Among these, interpolatory model order reduction methods are perhaps the most successful. This paper reviews this family of approximation methods with particular attention to their applicability to specific classes of frequency response problems and their performance. It also includes novel aspects pertaining to the iterative solution of large‐scale systems of equations in the context of model order reduction and frequency sweeps. All reviewed computational methods are illustrated with realistic, large‐scale structural dynamic, acoustic, and vibro‐acoustic analyses in wide frequency bands. These highlight both the potential of these methods for reducing CPU time and their limitations. Copyright © 2012 John Wiley & Sons, Ltd.
An analysis of sexual dimorphism in the tumor microenvironment of colorectal cancer

Women with colorectal cancer (CRC) have survival advantages over men, yet the underlying mechanisms are unclear. T cell infiltration within the CRC tumor microenvironment (TME) correlates strongly with survival. We hypothesized that women with CRC have increased T cell infiltration and differential gene expression in the TME compared to men. Tissue microarrays comprising primary tumor, tumor infiltrated lymph nodes, and uninvolved colon were created from CRC patients. Proportions of CD4 positive (CD4+) and CD8 positive (CD8+) T cells were identified using immunohistochemistry. TME immune- and cancer-related genetic expression from primary and metastatic CRC tumor were also evaluated via the NanoStringIO360 panel and The Cancer Genome Atlas Project database. CD4+ was higher in tumor samples from women compared to men (22.04% vs. 10.26%, p=0.002) and also in lymph node samples (39.54% vs. 8.56%, p=0.001). CD8+ was increased in uninvolved colon from women compared to men (59.40% vs. 43.61%, p=0.015), and in stage I/II tumors compared to III/IV in all patients (37.01% vs. 23.91%, p=0.009). Top CD8+ tertile patients survived longer compared to the bottom (43.9 months vs. 25.3 months, p=0.007). Differential gene expression was observed in pathways related to Treg function, T cell activity, and T cell exhaustion, amongst several others, in women compared to men. Thus, significant sexual dimorphism exists in the TME that could contribute to survival advantages observed in female patients with CRC.
Cyber-Espionage Malware Attacks Detection and Analysis: A Case Study

ABSTRACT Malware attacks for electronic espionage and intelligence focus on gathering or destroying the information, documents, system infrastructure, and applications without the consent of the victim. Recent studies in this field concentrate on theoretical assessments, and a limited number of studies have been carried out about its application dimension. Therefore, in this study, the detection and analysis of a real malware attack against a public institution for cyber-espionage and intelligence purposes are investigated in detail. The selected samples were analyzed by the malware named “Injector.exe” which is recently popular in attacking. We also introduce an analysis method based on the attack techniques and characteristics of the selected sample. Finally, we explain that the traces of the attacker can be monitored through the analysis method of the “Injector.exe” which is examined by using the fast and effective technique.
An Examination of the Factors Affecting the Adoption of Cloud Enterprise Resource Planning Systems in Egyptian Companies

 Abstract— Enterprise resource planning (ERP) is an integrated system that helps companies in managing their resources. There are two types of ERP systems, the traditional ERP systems, and the cloud ERP systems. Cloud ERP systems were introduced after the development of cloud computing technology. This research aims to identify the factors that affect the adoption of cloud ERP in Egyptian companies. Moreover, the aim of our study is to provide guidance to Egyptian companies in the cloud ERP adoption decision and to participate in increasing the number of the cloud ERP studies that are conducted in the Middle East and in developing countries. There are many factors influencing the adoption of cloud ERP in Egyptian organizations which are discussed and explained in the research. Those factors are examined through combining the Diffusion of Innovation theory (DOI) and technology-organization-environment framework (TOE). Data were collected through a survey that was developed using constructs from the existing studies of cloud computing and cloud ERP technologies and was then modified to fit our research. The analysis of the data was based on Structural Equation Modeling (SEM) using Smart PLS software that was used for the empirical analysis of the research model.
Potassium limitation of forest productivity – Part 1: A mechanistic model simulating the effects of potassium availability on canopy carbon and water fluxes in tropical eucalypt stands

Abstract. The extent of the potassium (K) limitation of forest productivity is probably more widespread than previously thought, and K limitation could influence the response of forests to future global changes. To understand the effects of K limitation on forest primary production, we have developed the first ecophysiological model simulating the K cycle and its interactions with the carbon (C) and water cycles. We focused on the limitation of the gross primary productivity (GPP) by K availability in tropical eucalypt plantations in Brazil. We used results from stand-scale fertilisation experiments as well as C flux measurements in two tropical eucalypt plantations to parameterise the model. The model was parameterised for fertilised conditions and then used to test for the effects of contrasting additions of K fertiliser. Simulations showed that K deficiency limits GPP by more than 50 % during a 6-year rotation, a value in agreement with estimations in K-limited eucalypt stands. Simulations showed a decrease of modelled canopy transpiration of around 50 % and a decrease in modelled water-use efficiency WUEGPP of 10 %. Through a sensitivity analysis, we used the model to identify the most critical processes to consider when studying K limitation of GPP. The inputs of K to the stands, such as the atmospheric deposition and weathering fluxes, and the regulation of the cycle of K within the ecosystem were critical for the response of the system to K deficiency. Litter leaching processes were of lower importance, since residence time of K in litter was low. The new forest K-cycle model developed in the present study includes multiple K processes interacting with the carbon and water cycles, and strong feedbacks on GPP were outlined. This is a first step in identifying the source or sink limitation of forest growth by K.
Author Responses Addressing Review from Referee #1 for “Transfer learning for landslide susceptibility modelling using domain adaptation and case-based reasoning”

Thank you for giving me the opportunity to revise the manuscript entitled “Transfer learning for landslide susceptibility modelling using domain adaptation and case-based reasoning” by Zhihao Wang and his/her colleagues that was submitted to “Geoscientific Model Development”. The manuscript used transfer-learning strategies to landslide susceptibility assessment (LAS) for 10 different cases in Austria, Ecuador, and Italy. Application of various learning based algorithms are interesting topics in LSA, but regarding the existed literatures needs to be polished properly.
Two Transitions in the Damping of a Unitary Fermi Gas

We measure the temperature dependence of the radial breathing mode in an optically trapped, strongly-interacting Fermi gas of $^6$Li, just above the center of a broad Feshbach resonance. The frequency remains close to the unitary hydrodynamic value, while the damping rate reveals transitions at two well-separated temperatures, consistent with the existence of atom pairs above a superfluid transition.
Frequency Jump at Low Energies

One or more radio-frequency jumps are usually necessary for realizing a >= 100 AMeV/u proton or ion driver linac. Typically, such jumps happen in the range of \b{eta} = 0.2-0.6 between the resonator structures fitting to this \b{eta}-range, e.g. DTL, HWR, CCL or elliptical cavities. We propose to perform the first frequency jump already at low energies (\b{eta} <= 0.1) between two RFQ accelerators, which can bring some unique advantages. First studies have been performed and the results proved that this idea is feasible and promising. Many efforts have been and are being made to address the most critical issue for the jumps i.e. the beam matching at the transition.
Fusing Panoptic Segmentation and Geometry Information for Robust Visual SLAM in Dynamic Environments

Mobile robots need reliable maps for autonomous operation. Traditional SLAM systems, which are mainly developed for static scenes, often fail in dynamic environments with moving objects present in the scene. Learning based dynamic SLAM systems often suffer from insufficient or inaccurate identification of feature points. This paper proposes a novel real-time RGB-D SLAM system, which is targeted for dynamic environments, can further enhance feature detection and dynamic removal. This is done by fusing panoptic segmentation and geometry information. The system includes four components: dynamic segmentation that reduces the impact of moving objects, pose estimation with dynamic object removal, panoptic mapping, and loop closing. The pose estimation uses coarse-to-fine dynamic/static classification to further reduce the impact of unknown moving objects. Extensive evaluations demonstrate that our system can achieve robust performance in complex dynamic environments.
Penetration State Identification from Stereo Image Pair of Weld Pool in GMAW Process by Deep Learning

The 3D shape and oscillation of weld pool surface contain abundant significant information related to the welding penetration state, which provides clues to control the welding process. In this paper, a biprism stereo vision system based on a single camera was established to sense the 3D surface of weld pool under different penetration states during the pulsed gas metal arc welding process with a V shape groove. We utilize Pyramid Stereo Matching Network to calculate a high-quality disparity map for weld pool image pair, which fuses features from different levels to improve the disparity estimation accuracy in high light and textureless regions. The disparity map contains two and three dimensions information directly related to the penetration state. Then the disparity maps were input into the Residual Neural Network to extract deeper-level features for training and testing. In our experiments, the welding penetration states were classified as four classes, i.e. partial penetration, full penetration, over penetration and burn through. Testing experiments demonstrated 99.7% as the penetration state identification accuracy.
Deterministic Bandwidth-Based Packet-Level Traffic Splitting for Datacenter Networks

Traffic splitting is to distribute traffic over multiple paths so as to better utilize link bandwidth and avoid potential link congestion. Many traffic splitting schemes have been proposed for datacenter networks, which provide different levels of splitting granularity. This paper proposes a packet-level traffic splitting scheme, which provides the most fine-grained link utilization as it lays out a forwarding path for each individual packet. The proposed scheme mitigates possible packet reordering problem by equalizing the build-ups of packet queues in all switches as the path layout utilizes links in proportional to the associated exploitable link bandwidth. The result is a packet dispatching rule designated to each switch. We implemented the rules using P4 (Programming Protocol-Independent Packet Processors) switches and conducted experiments to measure the performance. Experimental results show that the proposed scheme provides higher goodput compared with another packet-level traffic splitting scheme which dispatches packets randomly among all links.
Blackstart and Restoration of 100% Renewable Power Systems with Grid Forming Converters

Blackstart (BS) is one of the most challenging processes in power system operations planning. The availability of resources, determining the order of element energization while adhering to the grid's operational constraints, makes this problem extremely complex. This task can become even more daunting in the future, where the majority of the available generation will be converter-based. In this work, we demonstrate the energization process of the IEEE 14-bus system with 100% renewable penetration, by utilizing grid-forming converter-enabled PhotoVoltaic (PV) plants. This work demonstrates a BS sequence, driven by grid-forming enabled PV plants in a network comprised of passive/motor loads and a grid-following plant. The utilized system is implemented in PSCAD. The focus of this work is to highlight the most impactful steps of this process and demonstrate that the utilized controls keep the system within acceptable operational bounds. In addition, the impact of droop control tuning on synchronization and frequency response is discussed and finally, the transient stability and voltage ride-through capability of the system following a severe fault is presented.
Dynamics Modeling and Verification of Parallel Extensible Soft Robot Based on Cosserat Rod Theory

Soft robots show important application prospects because of their infinite degree of freedom, flexibility and dexterity, among which parallel extensible soft robots can elongate and bend at the same time, and are capable of crawling, grasping and manipulation. However, the constraints between pneumatic soft actuators (PSAs) and the coupling of elongation and bending make it harder to build dynamic model than fixed-length soft robots. In this paper, we propose a dynamic modeling method capable of describing soft robots that can elongate and bend at the same time. First, we give the characteristics of parallel extensible soft robot. Then we deduce the dynamic model of PSA. By developing the interactive constraint topological structure (ICTS), we further deduce the complete dynamic model of parallel extensible soft robot. Finally, we carry out simulation experiments and it proves that the established model can well describe the multi-degree-of- freedom motion and the constraint relations of parallel PSAs.