Miracle-dz/UniFAR-FTUs huggingface dataset:
Panoptic Segmentation Meets Remote Sensing

Panoptic segmentation combines instance and semantic predictions, allowing the detection of countable objects and different backgrounds simultaneously. Effectively approaching panoptic segmentation in remotely sensed data is very promising since it provides a complete classification, especially in areas with many elements as the urban setting. However, some difficulties have prevented the growth of this task: (a) it is very laborious to label large images with many classes, (b) there is no software for generating DL samples in the panoptic segmentation format, (c) remote sensing images are often very large requiring methods for selecting and generating samples, and (d) most available software is not friendly to remote sensing data formats (e.g., TIFF). Thus, this study aims to increase the operability of panoptic segmentation in remote sensing by providing: (1) a pipeline for generating panoptic segmentation datasets, (2) software to create deep learning samples in the Common Objects in Context (COCO) annotation format automatically, (3) a novel dataset, (4) leverage the Detectron2 software for compatibility with remote sensing data, and (5) evaluate this task on the urban setting. The proposed pipeline considers three inputs (original image, semantic image, and panoptic image), and our software uses these inputs alongside point shapefiles to automatically generate samples in the COCO annotation format. We generated 3400 samples with 512 × 512 pixel dimensions and evaluated the dataset using Panoptic-FPN. Besides, the metric analysis considered semantic, instance, and panoptic metrics, obtaining 93.865 mean intersection over union (mIoU), 47.691 Average (AP) Precision, and 64.979 Panoptic Quality (PQ). Our study presents the first effective pipeline for generating panoptic segmentation data for remote sensing targets.
Graph Modularity: Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Neural Networks

There are good arguments to support the claim that feature representations eventually transition from general to speciﬁc in deep neural networks (DNNs), but this transition remains relatively underexplored. In this work, we move a tiny step towards understanding the transition of feature representations. We ﬁrst characterize this transition by analyzing the class separation in intermediate layers, and next model the process of class separation as community evolution in dynamic graphs. Then, we introduce modularity, a common metric in graph theory, to quantify the evolution of communities. We ﬁnd that modularity tends to rise as the layer goes deeper, but descends or reaches a plateau at particular layers. Through an asymptotic analysis, we show that modularity can provide quantitative analysis of the transition of the feature representations. With the insight on feature representations, we demonstrate that modularity can also be used to identify and locate redundant layers in DNNs, which provides theoretical guidance for layer pruning. Based on this inspiring ﬁnding, we propose a layer-wise pruning method based on modularity. Further experiments show that our method can prune redundant layers with minimal impact on performance. The codes are available at https://github.com/yaolu-zjut/ Dynamic-Graphs-Construction .
PT-VTON: an Image-Based Virtual Try-On Network with Progressive Pose Attention Transfer

The virtual try-on system has gained great attention due to its potential to give customers a realistic, personalized product presentation in virtualized settings. In this paper, we present PT-VTON, a novel pose-transfer-based framework for cloth transfer that enables virtual try-on with arbitrary poses. PT-VTON can be applied to the fashion industry within minimal modification of existing systems while satisfying the overall visual fashionability and detailed fabric appearance requirements. It enables efficient clothes transferring between model and user images with arbitrary pose and body shape. We implement a prototype of PT-VTON and demonstrate that our system can match or surpass many other approaches when facing a drastic variation of poses by preserving detailed human and fabric characteristic appearances. PT-VTON is shown to outperform alternative approaches both on machine-based quantitative metrics and qualitative results.
Stabilization of the epitaxial rhombohedral ferroelectric phase in 
ZrO2
 by surface energy

Doped HfO 2 and HfO 2 -ZrO 2 compounds are gaining significant interest thanks to their ferroelectric properties in ultrathin films. Here, we show that ZrO 2 could be a new playground for doping and strain engineering to increase the thickness in epitaxial thin films. Based on surface energy considerations supported by ab initio calculations, we find that pure ZrO 2 exhibits a ferroelectric rhombohedral phase (r-phase, with R3m space group) more stable than for the HZO and pure HfO 2 cases. In particular, for a thickness up to 37 nm we experimentally evidence a single (111)-oriented r-phase in ZrO 2 films deposited on La 2/3 Sr 1/3 MnO 3 -buffered DyScO 3 (110) substrate. The formation of this r-phase is discussed and compared between HfO 2 , ZrO 2 and HZO, highlighting the role of surface energy.
ChebLieNet: Invariant Spectral Graph NNs Turned Equivariant by Riemannian Geometry on Lie Groups

We introduce ChebLieNet, a group-equivariant method on (anisotropic) manifolds. Surfing on the success of graph- and group-based neural networks, we take advantage of the recent developments in the geometric deep learning field to derive a new approach to exploit any anisotropies in data. Via discrete approximations of Lie groups, we develop a graph neural network made of anisotropic convolutional layers (Chebyshev convolutions), spatial pooling and unpooling layers, and global pooling layers. Group equivariance is achieved via equivariant and invariant operators on graphs with anisotropic left-invariant Riemannian distance-based affinities encoded on the edges. Thanks to its simple form, the Riemannian metric can model any anisotropies, both in the spatial and orientation domains. This control on anisotropies of the Riemannian metrics allows to balance equivariance (anisotropic metric) against invariance (isotropic metric) of the graph convolution layers. Hence we open the doors to a better understanding of anisotropic properties. Furthermore, we empirically prove the existence of (data-dependent) sweet spots for anisotropic parameters on CIFAR10. This crucial result is evidence of the benefice we could get by exploiting anisotropic properties in data. We also evaluate the scalability of this approach on STL10 (image data) and ClimateNet (spherical data), showing its remarkable adaptability to diverse tasks.
Scrutinizing the Debye plasma model: Rydberg excitons unravel the properties of low-density plasmas in semiconductors

For low-density plasmas, the classical limit described by the Debye-Hückel theory is still considered as an appropriate description even though a clear experimental proof of this paradigm is lacking due to the problems in determining the plasma-induced shift of single-particle energies in atomic systems. We show that Rydberg excitons in states with a high principal quantum number are highly sensitive probes for their surrounding making it possible to unravel accurately the basic properties of low-density non-degenerate electron-hole plasmas. To this end, we accurately measure the parameters of Rydberg excitons such as energies and linewidths in absorption spectra of bulk cuprous oxide crystals in which a tailored electron-hole plasma has been generated optically. Since from the absorption spectra exciton energies, as well as the shift of the single-particle energies given by the band edge, can be directly derived, the measurements allow us to determine the plasma density and temperature independently, which has been a notoriously hard problem in semiconductor physics. Our analysis shows unambiguously that the impact of the plasma cannot be described by the classical Debye model, but requires a quantum many-body theory, not only for the semiconductor plasma investigated here, but in general. Furthermore, it reveals a new exciton scattering mechanism with coupled plasmon-phonon modes becoming important even at very low plasma densities.
Data-Based Models for Hurricane Evolution Prediction: A Deep Learning Approach

Fast and accurate prediction of hurricane evolution from genesis onwards is needed to reduce loss of life and enhance community resilience. In this work, a novel model development methodology for predicting storm trajectory is proposed based on two classes of Recurrent Neural Networks (RNNs). The RNN models are trained on input features available in or derived from the HURDAT2 North Atlantic hurricane database maintained by the National Hurricane Center (NHC). The models use probabilities of storms passing through any location, computed from historical data. A detailed analysis of model forecasting error shows that Many-To-One prediction models are less accurate than Many-To-Many models owing to compounded error accumulation, with the exception of $6-hr$ predictions, for which the two types of model perform comparably. Application to 75 or more test storms in the North Atlantic basin showed that, for short-term forecasting up to 12 hours, the Many-to-Many RNN storm trajectory prediction models presented herein are significantly faster than ensemble models used by the NHC, while leading to errors of comparable magnitude.
Detection of novel paramyxoviruses in Chaerephon bat species in Nigeria and phylogenetics of paramyxoviruses co‐evolution with bats in Africa

Bat paramyxoviruses (PmV) are a diverse group of viruses and include zoonotic viruses such as henipaviruses. Members of this group in other continents have been associated with severe respiratory and neurological infections in animals and humans. Furthermore, despite the richness of diverse bat species that can transmit this virus in African countries like Nigeria, there is very scanty information as to the presence and co‐evolution of paramyxoviruses in bats. There is a need for continuous surveillance of zoonotic viruses and their biological reservoirs as this will help in the prevention and management of pathogens' spillovers. This study detected novel paramyxoviruses in Chaerephon nigeriae bat species found in Badagry, Lagos. Phylogenetic analyses of paramyxovirus sequences' co‐evolution with frugivorous and insectivorous bats circulating in African countries were also performed using sequences of African origin available in the Database of Bat‐Associated Viruses (DBatVir: http://www.mgc.ac.cn/DBatVir/). Oral swabs (n = 18) and blood samples (n = 32) were collected from C. nigeriae bats in Badagry, Lagos. The L gene of bat paramyxovirus was detected in all oral swabs using PCR techniques. Six of the amplicons were successfully sequenced. Estimated phylogenies placed the sequences in close relationship with those isolated from insectivorous bats. Phylogenetic analyses of previously sequenced isolates in the African region showed the likelihood of different co‐evolution mechanisms of paramyxoviruses with frugivorous bats compared with insectivorous bats. This may be due to codon usage bias of the L gene. Spatial distribution of paramyxoviruses in African countries showed limited ongoing surveillance of this virus in the continent, especially in southern and northern countries. Extensive surveillance of paramyxoviruses with possible zoonotic potentials among bat species in the continent is recommended. This will provide further insights into co‐evolution as well as prevent possible spillover into the human population.
Transcatheter Aortic Valve Implantation: The Evolving Role of the Radiologist in 2021

Abstract Background Transcatheter aortic valve implantation (TAVI) has gained worldwide acceptance and implementation as an alternative therapeutic option in patients with severe aortic valve stenosis unable to safely undergo surgical aortic valve replacement. This transformative technique places the radiologist in a key position in the pre-procedural assessment of potential candidates for this technique, delivering key anatomical information necessary for patient eligibility and procedural safety. Recent trials also provide encouraging results to potentially extend the indication to patients with safer risk profiles. Method The review is based on a PubMed literature search using the search terms “transcatheter heart valve”, “TAVI”, “TAVR”, “CT”, “imaging”, “MR” over a period from 2010–2020, combined with personal comments based on the author’s experience. Results and Conclusion CT plays a prominent role in the pre-procedural workup, delivering as a true 3D imaging modality optimal visualization of the complex anatomy of the aortic root with simultaneous evaluation of the patency of the different access routes. As such, the contribution of CT is key for the determination of patient eligibility and procedural safety. This input is supplementary to the contributions of other imaging modalities and forms an important element in the discussions of the Heart Valve Team. Knowledge of the procedure and its characteristics is necessary in order to provide a comprehensive and complete report. While the role of CT in the pre-procedural evaluation is well established, the contribution of CT and MR and the clinical significance of their findings in the routine follow-up after the intervention are less clear and currently the subject of intense investigation. Important issues remain, including the occurrence and significance of subclinical leaflet thrombosis, prosthetic heart valve endocarditis, and long-term structural valve degeneration. Key Points: CT plays a crucial role in evaluating transcatheter heart valve candidates Evaluation must include the dimensions of the aortic root and access paths The exact post-procedural role of CT and MRI has not yet been determined. Citation Format Salgado R, El Addouli H, Budde RP. Transcatheter Aortic Valve Implantation: The Evolving Role of the Radiologist in 2021. Fortschr Röntgenstr 2021; 193: 1411 – 1425
Electrophysiological evidence of enhanced early attentional bias toward sexual images in individuals with tendencies toward cybersex addiction

Abstract Background and aims Attentional bias is a key factor in addictive behavior maintenance. However, whether attentional bias has a similar effect on cybersex addiction is unclear. We investigated differences in the attentional processing of sexually explicit images between individuals with high tendencies toward cybersex addiction (TCA) versus low tendencies using behavioral and electrophysiological indices. Methods Twenty-eight individuals with high TCA and 29 with low TCA performed an addiction Stroop task comprising sexual and neutral images in colored frames. Participants were asked to respond to the frame color and not the image contents, and behavioral and event-related potentials were recorded. Results Behaviorally, an addiction Stroop interference effect was found in the high TCA group, as shown by the longer reaction times to judge the frame colors of sexual images. Electrophysiologically, a P200 (150–220 ms) enhancement was present in response to sexual images compared with neutral ones, which was absent in the low TCA group. The event-related potential correlates with the addiction Stroop interference effect, indicating that the attentional bias underlying the addiction Stroop interference operates at an automatic level. A general, sexually related bias was found in the late positive potential (300–700 ms) amplitude, although between-group differences were insignificant. Discussion and conclusions These findings indicate that sexual stimuli grab the attentional resources of individuals with high TCA at early automatic stages of attentional processing. Increased cue reactivity to sexual stimuli may contribute to pornographic consumption and play a crucial role in sustaining problematic excessive use of online pornography.
Effect of a community‐based child health counselling intervention on health‐seeking behaviours, complementary feeding and nutritional condition among children aged 6–23 months in rural China: A pre‐ and post‐comparison study

Abstract In China, the prevalence of undernutrition among children under 5 years of age has declined significantly during recent decades. However, noticeable gaps exist between rural and urban areas. Since 2012, a government‐funded nutrition programme, Ying Yang Bao (YYB; soybean powder‐based iron‐rich supplement) programme, has been implemented in poor rural areas to decrease the risk of developing anaemia among children aged 6–23 months, but there are still inadequate health care awareness, feeding knowledge and skills among caregivers. From June 2018 to December 2020, a child health counselling intervention was delivered through a home visit based on the YYB programme in Liangshan. Child health messages were given by trained village child health assistants while distributing YYB. Surveys were conducted before and after the intervention to analyse changes in child health check‐up frequency, complementary feeding practice and prevalence of undernutrition. After the intervention, the proportion of children who had regular health check‐ups, who were vaccinated and who met the minimum YYB consumption significantly increased from 26.0%, 81.6%, and 67.8% to 59.7%, 95.0%, and 79.2%. Increased rates of IYCF indicators (introduction of solid, semisolid, or soft foods, minimum dietary diversity and consumption of iron‐rich or iron‐fortified foods) were observed after the intervention. The prevalence of stunting, underweight, wasting, and anaemia significantly decreased from 26.3% to 10.8%, 13.4% to 8.7%, 14.0% to 10.5%, and 52.1% to 43.9%. This intervention can be well integrated into the YYB programme with less additional resources. Children in resource‐limited areas will benefit more from a comprehensive nutritional package, including food supplements and child health education.
Understanding the Determinants of Gambling-Related Intimate Partner Violence: Perspectives From Women Who Gamble

Rates of intimate partner violence (IPV) victimization are higher among women with a gambling problem. However, women's experiences of this violence, from a gendered perspective, have not been examined. Based on interviews with 24 women, this study explored how problem gambling contributes to IPV against women across three levels of influence. Findings reveal that problem gambling did not directly cause IPV, but interacts where gendered drivers and reinforcers are present to exacerbate this violence. Reducing violence against women with a gambling problem requires a coordinated, integrated multidisciplinary approach targeting different levels of influence.
BUILDING SATISFACTION - USING THERMAL MODELLING TO IDENTIFY AREAS OF BUILDING USE FOCUS FOR POST OCCUPANCY EVALUATION

Buildings do not perform as modelled. There are many reasons for this, for example change of scope, functions, assumptions, weather, user behaviour and so forth. This paper investigates the latter. It turns the use of Post Occupancy Evaluation (POE) around and asks: what is the impact of people on building performance? Based on IES modelling, the researchers identified those areas of performance that were sensitive to user behaviour and used the process of post occupancy evaluation to observe this as well as the standard elements related to user satisfaction. Using a small City of Melbourne community building, we report on the difference between expected and actual performance and report on the importance of user behaviour. We also present this novel approach to designing a POE.
A comprehensive review on mutan (a mixed linkage of α-1-3 and α-1-6 glucans) from bacterial sources

ABSTRACT Mutan is an extracellular sticky polymer having α-1-3 and α-1-6 glycosidic linkages with a large diversity in molecular weights and structures depending on the source. These compounds are reported to be highly thermostable and also have potential physiochemical and biological applications. The main aim of this review is to provide an overview of glucosyltransferases and their role in mutan synthesis. The production strategies and structural properties of bacterial mutans are discussed with a goal to improve production efficiency. The physicochemical features, chemical modifications, potential industrial applications and future prospects are also discussed. According to data, mutan and its derivatives will play a larger role in medicinal sectors and as thermoplastics in the near future. Abbreviations: ABTS: 2,2ʹ-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid; BHI: Brain heart infusion broth; 13C (HSQC) NMR: Heteronuclear Single Quantum Coherence NMR; CBMs: Carbohydrate binding modules; DPPH: 2,2-diphenyl-1-picrylhydrazyl; FTIR: Fourier-transform infrared spectroscopy; GC–MS: Gas chromatography-mass spectrometry; GPC: Gel permeation chromatography; Gtfs: Glucosyltransferases; 1H (DQF-COSY): Double-quantum filtered correlation spectroscopy; HPAEC-PAD: High-performance anion exchange chromatography with pulsed amperometric detection; HPLC: High performance liquid chromatography; HPSEC-RI: High-performance size exclusive chromatography coupled with refractive index; HPSEC-MALLS: High-performance size exclusive chromatography with multi-angle laser light scattering detection; MALDI-TOF: Matrix-Assisted Laser Desorption/Ionization-Time of Flight mass spectrometry; Mw : Weight-average molecular weight; MWD: Molecular weight distribution; NMR: Nuclear magnetic resonance spectroscopy; TEM: Transmission electron microscopy; THB: Todd Hewitt Broth; TTY: Tryticase tryptose yeast extract broth.
Serum folate levels in children on long-term anti-seizure medication in a Nigerian tertiary center—Implications for practice and public health

Background: Epilepsy is the most common childhood neurological disorder in Nigeria. Treatment of epilepsy is long-term and sometimes lifelong with anti-seizure medications. There are conflicting reports on the effect of anti-seizure medications on serum folate. There is therefore a need to determine the effect of a commonly used anti-seizure medication's on serum folate levels of children. This would provide an evidence-based consideration for folic acid supplementation in children on anti-seizure medication as has been suggested by some studies. Study objectives: To determine whether serum folate levels were lower in children taking long-term carbamazepine or sodium valproate, compared to a control group. Methods: Serum folic acid levels were measured from well-nourished children between the ages of 1–17 years on carbamazepine and sodium valproate monotherapy and their age/sex-matched controls, using spectrophotometry. Results: The mean serum folate levels of patients on carbamazepine (43) and sodium valproate (22) were 0.032 mg/l ± 0.009 and 0.028 mg/l ± 0.008, respectively. The mean folate levels of the controls were 0.046 mg/l ± 0.03 (p = 0 001). No statistically significant difference was observed between the serum folate levels of children on the two anti-seizure medications, that is, carbamazepine and valproate. Conclusion: The children on treatment with carbamazepine and sodium valproate for more than 6 months had statistically significantly lower serum levels of folic acid compared to the standard reference range and controls. The serum folate levels of children on carbamazepine were not statistically different from those on sodium valproate.