Miracle-dz/UniFAR-FTUs huggingface dataset:
Potential Geographic Range of the Endangered Reed Parrotbill Paradoxornis heudei under Climate Change

Simple Summary The phenomenon of global climate change can impact the geographic range and abundance of species, thereby heightening the vulnerability of rare species to extinction. The reed parrotbill (Paradoxornis heudei David, 1872) is endemic to central and eastern China and is considered a near-threatened species according to the International Union for Conservation of Nature (IUCN). This study shows that temperature annual range, annual precipitation, and isothermality were the principal climatic factors to limit the habitat suitability of P. heudei. Presently, the suitable habitat for P. heudei is predominantly found in the central–eastern and northeast plains of China, especially the eastern coastal area. P. heudei is sensitive to climate change. In the future, northeastern China may serve as a potential suitable habitat for P. heudei. Abstract The phenomenon of global climate change can impact the geographic range and biodiversity, thereby heightening the vulnerability of rare species to extinction. The reed parrotbill (Paradoxornis heudei David, 1872) is endemic to central and eastern China, it is mainly distributed in the middle and lower reaches of the Yangtze River Plain and the Northeast Plain. In this study, eight of ten algorithms of the species distribution model (SDM) were used to evaluate the impact of climate change on the potential distribution of P. heudei under current and future climate scenarios and to analyze the possible related climate factors. After checking the collected data, 97 occurrence records of P. heudei were used. The relative contribution rate shows that among the selected climatic variables, temperature annual range (bio7), annual precipitation (bio12), and isothermality (bio3) were the principal climatic factors to limit the habitat suitability of P. heudei. The suitable habitat for P. heudei is primarily concentrated in the central–eastern and northeast plains of China, particularly in the eastern coastal region, spanning a mere area of 57,841 km2. The habitat suitability of P. heudei under different representative concentration pathway (RCP) scenarios was predicted to be different under future climatic conditions, but all of them had a larger range than the current one. The species distribution range could expand by more than 100% on average compared with the current range under the four scenarios in 2050, while it could contract by approximately 30% on average relative to the 2050 range in 2070 under different climate change scenarios. In the future, northeastern China may serve as a potential suitable habitat for P. heudei. The changes in the spatial and temporal distributions of P. heudei’s range are of utmost importance in identifying high-priority conservation regions and devising effective management strategies for its preservation.
The Tortuosity Effect on the Thermal Conductivity of Si Nanowires

ABSTRACT The thermal conductivity of tortuous silicon nanowires with constant cross section at room temperature was investigated in use of full-spectrum Monte-Carlo simulations. Various geometric features that can be possibly used to describe the tortuosity of the nanowires were studied and their relationships with the thermal conductivity were explored. Comparison of simulation results with experimental data shows similar magnitudes and variation trend of the thermal conductivity against the nanowire hydraulic diameter. The more tortuous, the smaller the thermal conductivity is. Among all, data collapse is best when shown against the surface-to-volume ratio and the correlation length of the surface roughness does not affect the thermal conductivity at all. By taking the surface-to-volume ratio into account for the boundary scattering rate, which also depends on the phonon frequency indirectly through the phonon group velocity, we are able to obtain satisfactory predictions based on a linear spectral model, not only about the thermal conductivity but also about the spectral heat flux density distribution. The model also shows that the relative reduction caused by tortuosity decreases with increasing frequency. For highly tortuous nanowires of diameter 22 nm, simply increasing the tortuosity is sufficient to obtain simulated thermal conductivities that are smaller than the experimentally measured value.
A Model-Based Analysis-Design Approach for Virtual Binocular Vision System With Application to Vision-Based Tactile Sensors

The virtual binocular vision system (VBVS) that consists of a single camera and multiple mirrors has been applied to the stereo vision. Several VBVS configurations have been proposed, showing the advantages, including the compact structure, simple calibration, and flexible adjustment. However, due to the high complexity of the optical system, a few researchers have studied the comprehensive analyzing and designing of the VBVS. To fill this gap, we propose a universal model and the design criteria and then construct a model-based analysis-design approach of the VBVS with mirrors. First, based on a novel understanding of the reflective optical system, the imaging cone model (ICM) is introduced to describe the geometry properties of an arbitrary VBVS completely, and the VBVS equations are constructed to calculate the imaging cones. Second, the equivalent descriptions of the design criteria are proposed as the expected field of view (FOV) and performances, deriving the analysis method of the VBVS. Then, the analysis method is combined with traversal calculation to establish a design process and its algorithm, which is applied to a novel vision-based tactile sensor with greatly improved design efficiency. Finally, we conduct the measurement of 3-D tactile information to demonstrate the performances of the designed sensors.
Shallow Sediment as a Phosphorus Reservoir in an Oligotrophic Lake

Lake sediment is an important reservoir for storage of phosphorus (P). Skaneateles Lake, a pristine oligotrophic, midsize lake in New York State, USA, is the primary unfiltered water source for the city of Syracuse and nearby communities. We conducted a lake‐wide survey of shallow sediments in Skaneateles Lake to inform understanding of the potential role of sediment in P storage and release into the water column. A total of 103 shallow samples of surface sediments were collected along 17 transects around the lake margin and analyzed for sediment and pore water elemental concentration, grain size, total organic carbon, nitrogen, carbonate content, stable isotopes of carbon, and mineral content. Reduction‐oxidation (redox) processes of Fe‐bound and Mn‐bound P appear to be a primary control of P storage and release. Sediment P concentrations are positively correlated with water depth and negatively correlated with Ca. Grain size and sediment P distributions around the lake are heterogeneous and patchy. Pore water concentrations reveal strong but variable partitioning of P, apparently controlled by sediment redox conditions. Pore water P concentrations (mean 90 μg L−1) are elevated compared with the oligotrophic water column (∼5 μg L−1) and may be an important source of nutrients to the water column of the lake.
The Burden of Cervical Conization in Privately Insured Young and Mid-Adult Women in the United States

In 2019, the United States (US) Advisory Committee on Immunization Practices (ACIP) recommended that healthcare providers engage in shared clinical decision making for adults aged 27–45 who may benefit from HPV vaccination. However, it is difficult to assess these benefits as there is a lack of data on HPV burden on young and mid-adult women. This analysis estimates the incidence of conization and the burden associated with treating pre-cancerous states related to HPV with a loop electrosurgical excision procedure (LEEP) or a cold knife conization (CKC) among commercially insured women aged 18–45. This retrospective cohort study used the IBM MarketScan commercial claims encounter database for women aged 18–45 treated with conization. We assessed the annual incidence of conization (2016–2019) and adjusted the two-year health care costs post-conization using a multivariable Generalized Linear Model (GLM)—accounting for follow-up time and other characteristics—stratified by the age groups, namely 18–26 and 27–45. The inclusion criteria were met by 6735 women, with a mean age of 33.9 years (SD = 6.2). Conization incidence was lowest for women aged 18–26 (41/100,000 to 62/100,000 women-years) and highest for women aged 31–35 (243/100,000 to 269/100,000). The GLM-adjusted, all-cause healthcare costs per patient per year were USD 7279 and USD 9249 in the 18–26 and 27–45 age groups, respectively. The adjusted costs for disease-specific care were USD 3609 and USD 4557 for women ages 18–26 and 27–45, respectively. The burden of conization and the associated costs were significant, indicating a potential healthcare benefit of HPV vaccination among young and middle-aged women.
E-Cigarette Vapour Alters High-Fat Diet-Induced Systemic Inflammatory Responses but Has No Effect on High-Fat Diet-Induced Changes in Gut Microbiota

Background: The gut microbiome, which can be altered by different diets or smoking, has been implicated in the pathogenesis of lung conditions. E-cigarette vaping is now recognised to have detrimental health effects, with several of these being similar to cigarette smoking. However, whether e-cigarettes can alter high-fat diet (HFD)-induced systemic effects and gut microbiota is unknown. In this study, we investigated the effects of HFD in the absence/presence of e-cigarette exposure on systemic inflammation, lipid metabolic markers, and the gut microbiome. Methods: Mice were fed a HFD (or chow) in the absence/presence of e-vapour exposure (±nicotine) and serum inflammation, lipid levels, and microbial diversity were assessed. Results: HFD increased the circulating levels of both triglycerides and non-esterified fatty acids, which were significantly reduced by e-vapour exposure in HFD-fed mice. Serum TNF-α was increased by HFD consumption or e-vapour. HFD had a significant effect on microbial diversity, but there were no additional effects of e-vapour exposure. Conclusions: This study highlights both similarities and differences in how the body responds to e-cigarette vapours, and it is therefore likely that the long-term sequelae of e-cigarette vapour exposure/vaping might not involve the significant alteration of the gut microbiome.
Neural-Network-Assisted Packet Accelerators for Internet of Things Network Systems

Major device nodes within the Internet of Things (IoT) system collects and store information in bit forms of 0’s and 1’s regardless of its repetition. The nodes do not possess the capability of processing redundant data information except for outright rejection/replacement of packets of similar sizes. This becomes a research problem since high volumes of packet redundancy are prevalent owing to repetitive information. Many optimal solutions have been provided to reprocess redundant packets and to store them in edge server for accessibility by other connected IoT systems and networks servers. To do so, major IoT platforms implements tier-based network layers which primarily aid seamless communication among nodes. These network layers perform near-similar tasks of guaranteeing packet sensing and exchange although at often-higher energy requirement. To mitigate the energy concerns, packets are clustered and compressed, allowing exchange of essential information only. But the approach continues to present heavy packet-losses and/or redundancies. In this article, two-tier layered network—where packet exchange is conducted at the top layer in order to lower energy consumption and promote system-reliability is investigated. All packets are first segregated into multiple clusters using the Voronoi cell-based correlation cluster formation (VC3F) technique. Cluster heads (CHs) are identified by their multipath (M-Score) value, thus, assuming sole responsibility of redundant packet removal within each cluster. The redundant packets are then moved to the edge-tier layer using optimized multiobjective flower pollination (MO-FPO) routing, and finally processed using hybrid models of novel fast-fully connected neural network (F2CNN) accelerator and Lempel–Ziv–Welch (LZW) data compression. The F2CNN and LZW models are harmonized to further collectively explore potential benefits of both models. These benefits include the neural capability to work on the sensitivity level of the packets determined by the packet classification and validation approaches. The system is evaluated with detailed experimental investigations where higher system throughput, packet delivery ratio (PDR), end-to-end delay, and system reliability are corroborated.
Machine reasoning for segmentation of the kidneys on CT images: improving CNN performance by incorporating anatomical knowledge in post-processing

Purpose: Convolutional Neural Networks (CNN) are frequently used for organ segmentation in medical imaging. Many CNNs, however, struggle for acceptance into clinical practice because of mis-segmentations that are obvious to radiologists or other experts. We propose using a Cognitive AI framework that applies anatomical knowledge and machine reasoning to check and improve CNN segmentations and avoid obvious mis-segmentations. Methods: We used the open-source SimpleMind framework that allows post-processing and machine reasoning to be applied to CNN segmentation results. Within this framework, a 3D-UNet CNN was trained on 212 contrast-enhanced kidney CT scans. From an anatomical knowledge base, SimpleMind derived the following Cognitive AI post-processing steps: (1) identification of the abdomen, (2) segmentation of the spine by searching for bone in the posterior region of the abdomen, (3) CNN output separation into right and left kidneys using the spine as reference, (4) refinement of individual kidney segmentations using thresholds of volume, HU, and voxel count, which are designed to eliminate disconnected false positives, (5) morphological opening to reduce connected false positives bordering the kidneys’ segmentations. On a test set of 53 scans, using reference annotations, Dice Coefficient (DC), Hausdorff Distance (HD) and Average Symmetric Surface Distances (ASSD) were computed and compared for the CNN and post-processed outputs. Results: Post-processing with Cognitive AI reduced the kidney segmentation HD from 46.4±55.8 mm to 30.7±17.6 mm, with the decrease in variance being statistically significant (p = 0.0296). DC and ASSD metrics were also improved. Conclusions: This initial work demonstrates that the incorporation of anatomical knowledge using Cognitive AI techniques can improve the segmentation accuracy of CNNs. The CNN provides very good overall kidney segmentation performance, and in cases where segmentation errors occur the post processing was able to improve performance.
Investigating the role of plurilingual pre-service language teachers’ psychological landscape in their learning-to-teach process

ABSTRACT This cross-national study investigates the role of the plurilingual identity and the psychological landscape, i.e. the psychological disposition of pre-service language teachers in their learning-to-teach process. Thirty multilingual pre-service teachers from Israel and Austria participated in the study (15 from each country). Data sources included language portraits and in-depth semi-structured interviews. Drawing on ecological perspectives, data were analysed qualitatively utilising content analysis. Predominant themes were identified suggesting that pre-service teachers’ plurilingual identity is closely intertwined with their psychological landscape, influencing a wide array of professional development dimensions of their learning-to-teach process.
Doxorubicin-Induced Cardiotoxicity in Adult Male Albino Rats and the Ameliorative Effects of Achillea Fragrantissima Crude Extract, Its Combined Ethyl Acetate/n. Butanol Fraction, and Vitamin E

Doxorubicin (DOX) is a potent chemotherapeutic agent. Unfortunately, due to the incidence of dose-dependent cardiotoxicity, its clinical usage is hampered. Natural products are gaining popularity as a means of preventing DOX-induced cardiotoxicity. In the present study, we investigated the cardiotoxic effects of DOX and assessed the potential ameliorative effects of Achillea fragrantissima extract, its combined ethyl acetate/ n . butanol (EtOAc-Bu) fraction
Factors Influencing Follicular Output Rate and Follicle-to-Oocyte Index in POSEIDON-Defined Low-Prognosis Women in Vietnam: A Cross-Sectional Study

Objective This study aimed to identify the factors that influence follicular output rate (FORT) and follicle-to-oocyte index (FOI) among infertile Vietnamese women, as described by the Poseidon classification of poor responders. Methods This cross-sectional analysis includes women who received IVF/ICSI treatment at Hue University Hospital, Vietnam, between January 2017 and December 2019. The study population was divided into four groups: Group 1 (age < 35, AFC ≥ 5 and AMH ≥ 1.2 ng/mL, number of oocytes retrieved in the previous cycle ≤ 9), group 2 (age ≥ 35; AFC ≥ 5 and AMH ≥ 1.2 ng/mL, number of oocytes retrieved in the previous cycle ≤ 9), group 3 (age < 35; AFC < 5 and/or AMH < 1.2 ng/mL) and group 4 (age ≥ 35; AFC < 5 and/or AMH < 1.2 ng/mL). All of the patients underwent controlled ovarian stimulation utilizing GnRH antagonist. Results A total of 243 cases were recruited into groups 1 (n = 44), 2 (n = 33), 3 (n = 54), and 4 (n = 112). There were statistically significant differences between the four groups in terms of age, infertility type, menstrual cycle, body mass index (BMI) and waist-hip ratio (WHR), endocrine tests, and total retrieved oocytes (p 0.05). The average number of oocytes per participant was 7.27, with the highest number occurring in group 1 (10.77) and the lowest occurring in group 4 (5.59). There was a relationship between FORT and BMI (ß: −0.146, p=0.039), FSH starting dose (ß: 0.146, p=0.030), and AMH (ß:0.166, p=0.015). No statistically significant correlation was detected between FOI and other variables. Conclusion The starting dose of FSH for ovarian stimulation and AMH concentration were positively associated with FORT in individuals with a poor prognosis, whereas BMI was negatively correlated with FORT; No other parameters were found to correlate with FOI.
Barrett's lesion detection using a minimal integer-based neural network for embedded systems integration

Embedded processing architectures are often integrated into devices to develop novel functions in a cost-effective medical system. In order to integrate neural networks in medical equipment, these models require specialized optimizations for preparing their integration in a high-efficiency and power-constrained environment. In this paper, we research the feasibility of quantized networks with limited memory for the detection of Barrett’s neoplasia. An Efficientnet-lite1+Deeplabv3 architecture is proposed, which is trained using a quantizationaware training scheme, in order to achieve an 8-bit integer-based model. The performance of the quantized model is comparable with float32 precision models. We show that the quantized model with only 5-MB memory is capable of reaching the same performance scores with 95% Area Under the Curve (AUC), compared to a fullprecision U-Net architecture, which is 10× larger. We have also optimized the segmentation head for efficiency and reduced the output to a resolution of 32×32 pixels. The results show that this resolution captures sufficient segmentation detail to reach a DICE score of 66.51%, which is comparable to the full floating-point model. The proposed lightweight approach also makes the model quite energy-efficient, since it can be real-time executed on a 2-Watt Coral Edge TPU. The obtained low power consumption of the lightweight Barrett’s esophagus neoplasia detection and segmentation system enables the direct integration into standard endoscopic equipment.
Image Deblurring Based on Non-Local Total Variation and Global Non-Zero Local Rank Penalty

The imaging and analysis module is an important part of automobile application system in the future, and clear images provide a reliable guarantee for the intelligent control system. However, due to the existing problems of imaging equipment hardware, the obtained images appear blurring. Therefore, in order to restore the clean images from the blur ones and bring convenience to the subsequent processing, this paper proposes an image deblurring method based on non-local total variation and global non-zero local rank penalty. The non-local total variation model is mainly used to restore the texture details of image, and the non-zero local rank penalty is mainly used to sharp the edge of the image. The proposed deblurring method in this paper has achieved better results on simulated images and real blurred image than other methods.
Pseudo-turbulent gas-phase velocity fluctuations in homogeneous gas–solid flow: fixed particle assemblies and freely evolving suspensions

Gas-phase velocity fluctuations due to mean slip velocity between the gas and solid phases are quantified using particle-resolved direct numerical simulation. These fluctuations are termed pseudo-turbulent because they arise from the interaction of particles with the mean slip even in ‘laminar’ gas–solid flows. The contribution of turbulent and pseudo-turbulent fluctuations to the level of gas-phase velocity fluctuations is quantified in initially ‘laminar’ and turbulent flow past fixed random particle assemblies of monodisperse spheres. The pseudo-turbulent kinetic energy $k^{(f)}$ in steady flow is then characterized as a function of solid volume fraction ${\it\phi}$ and the Reynolds number based on the mean slip velocity $\mathit{Re}_{m}$ . Anisotropy in the Reynolds stress is quantified by decomposing it into isotropic and deviatoric parts, and its dependence on ${\it\phi}$ and $Re_{m}$ is explained. An algebraic stress model is proposed that captures the dependence of the Reynolds stress on ${\it\phi}$ and $Re_{m}$ . Gas-phase velocity fluctuations in freely evolving suspensions undergoing elastic and inelastic particle collisions are also quantified. The flow corresponds to homogeneous gas–solid systems, with high solid-to-gas density ratio and particle diameter greater than dissipative length scales. It is found that for the parameter values considered here, the level of pseudo-turbulence differs by only 15 % from the values for equivalent fixed beds. The principle of conservation of interphase turbulent kinetic energy transfer is validated by quantifying the interphase transfer terms in the evolution equations of kinetic energy for the gas-phase and solid-phase fluctuating velocity. It is found that the collisional dissipation is negligible compared with the viscous dissipation for the cases considered in this study where the freely evolving suspensions attain a steady state starting from an initial condition where the particles are at rest.