Miracle-dz/UniFAR-FTUs huggingface dataset:
An experimental study of Roman dropshaft hydraulics

In Roman aqueducts, series of vertical dropshafts were used to dissipate the kinetic energy of the flow: i.e., the dropshaft cascades. A re-analysis of Roman dropshaft hydraulics is conducted with physical model tests. Three basic flow patterns are observed. The results demonstrate that the vertical dropshafts could be very efficient energy dissipators and re-oxygenation structures, under appropriate flow conditions. The optimum operation of Roman dropshaft is discussed and an analytical model is developed to predict these conditions. Further the performances of aqueduct dropshafts are compared with modern dropshaft designs, and the operation of dropshaft cascades is discussed. Additional material is available upon request.
Cognition in patients treated with targeted therapy for chronic myeloid leukemia: a controlled comparison

Abstract This controlled comparison study evaluated objective and subjective cognitive function and their relationships with patient-reported symptoms (depression, fatigue, insomnia) in patients receiving tyrosine kinase inhibitors (TKIs) for chronic myeloid leukemia (CML) and non-cancer controls. Patients with CML in chronic phase treated with the same oral TKI for ≥6 months (n = 90) and non-cancer controls (n = 87) completed a neurocognitive battery and self-report measures. Patients demonstrated worse overall neuropsychological performance (p = .05) and verbal memory (p = .02) compared to controls. Patients were not more likely to meet criteria for impaired cognitive performance compared to controls (ps>.26). Patients reported worse subjective global and domain-specific cognitive complaints and less satisfaction with cognitive function compared to controls (ps < .05). Patients also reported greater fatigue and insomnia symptoms (ps < .001). In both groups, greater fatigue, insomnia, and depressive symptoms were associated with worse subjective cognition (ps < .01). Longitudinal studies are needed to examine changes in cognitive function in patients before and during TKI treatment.
The SSTeP-KiZ System—Secure Real-Time Communication Based on Open Web Standards for Multimodal Sensor-Assisted Tele-Psychotherapy

In this manuscript, we describe the soft- and hardware architecture as well as the implementation of a modern Internet of Medical Things (IoMT) system for sensor-assisted telepsychotherapy. It enables telepsychotherapy sessions in which the patient exercises therapy-relevant behaviors in their home environment under the remote supervision of the therapist. Wearable sensor information (electrocardiogram (ECG), movement sensors, and eye tracking) is streamed in real time to the therapist to deliver objective information about specific behavior-triggering situations and the stress level of the patients. We describe the IT infrastructure of the system which uses open standards such as WebRTC and OpenID Connect (OIDC). We also describe the system’s security concept, its container-based deployment, and demonstrate performance analyses. The system is used in the ongoing study SSTeP-KiZ (smart sensor technology in telepsychotherapy for children and adolescents with obsessive-compulsive disorder) and shows sufficient technical performance.
A Closer Look at the Kernels Generated by the Decision and Regression Tree Ensembles

Abstract Tree ensembles can be interpreted as implicit kernel generators, where the ensuing proximity matrix represents the data-driven tree ensemble kernel. Focus of our work is the utility of tree based ensembles as kernel generators that (in conjunction with a regularized linear model) enable kernel learning. We elucidate the performance of the tree based random forest (RF) and gradient boosted tree (GBT) kernels in a comprehensive simulation study comprising of continuous and binary targets. We show that for continuous targets (regression), this kernel learning approach is competitive to the respective tree ensemble in higher dimensional scenarios, particularly in cases with larger number of noisy features. For the binary target (classification), the tree ensemble based kernels and their respective ensembles exhibit comparable performance. We provide the results from several real life datasets for regression and classification relevant for biopharmaceutical and biomedical applications, that are in line with the simulations to show how these insights may be leveraged in practice. We discuss general applicability and extensions of the tree ensemble based kernels for survival targets and interpretable landmarking in classification and regression. Finally, we outline future research for kernel learning due to feature space partitionings.
Advanced lithography: wafer defect scattering analysis at DUV

Considerable effort is directed towards the development of next-generation lithography processes, addressing the need for transistor densification to meet Moore's Law. The aggressive design rule shrinkage requires very tight process windows and induces various types of pattern failure with lithography process variations. Since the lithography process is critical in the wafer fabrication process, the requirements for high sensitivity defect detection in the lithography process becomes tighter as design rules shrink. Analysis of the root cause of the defects and of their interaction with various light sources and optics systems configurations for wafer inspection is essential for understanding the detection limits and requirements from advanced inspection systems targeting future lithography inspection applications. In this work, we present an analysis of wafer defects light scattering and detection for a variety of 3xnm design rule resist structures with various polarizations and optics configurations, at the visible, at UV and at DUV wavelengths. The analysis indicates on the defect scattering and inspection performance trends for a variety of resist structures and defect types, and shows that control of the polarization of the optical inspection system is critical for enhanced scattering and detection sensitivity. The analysis is performed also for the 2xnm and 1xnm design rules showing the advantages of polarized DUV illumination over unpolarized and visible illumination.
Detecting the Phase of Marine Boundary Layer Clouds: Some Implications for Cloud Albedo

This study examines rare examples of marine boundary layer clouds that show a sharp transition from supercooled to glaciated phase without other significant changes in appearance. We used the Cloud‐Aerosol Lidar with Orthogonal Polarization's (CALIOP) cloud phase detection algorithm and cloud top height to identify these cases. Measurements by CALIOP were co‐located with those by the Moderate Resolution Imaging Spectroradiometer (MODIS) to determine spectral changes in reflected and emitted radiation along the glaciated to supercooled transition path. In every case, the MODIS 8.5–11 µm brightness temperature difference abruptly changed from positive to negative, with a relatively constant cloud top temperature. No change was seen in visible reflectivity, and only weak changes were detected in shortwave infrared reflectivity. These glaciated‐to‐supercooled transitions were incorrectly classified with the MODIS cloud phase classification algorithm. We show that, for boundary layer clouds, it is possible to improve the (passive) remote sensing of the cloud phase using only a single spectral difference in brightness temperature. Using this approach, we closely match CALIOP's climatological distributions of the cloud phase. Our work also indicates that a sudden change in the boundary layer cloud thermodynamic phase from supercooled to glaciated is not accompanied by a shift in shortwave albedo.
Prevention of Overweight and Obesity at Global Levels in Particular to Gastronomic Opportunities

With the advent of the Coronavirus and in addition to many factors, stress also appears to be more pronounced in people's lives. In addition, in a life full of constraints, the weight gain is also a function of time spent at home. A stressful life-style and home-spend time affects not only the mental but also physical health. Therefore, a number of chronic diseases have manifested, of which the appearance of abnormal weight gain is increasing. Obesity and overweight once considered the problem of high-income nations but now increasing in low- and middle-income countries, particularly in urban areas. The prevalence of obesity nearly tripled between 1975 and 2016. It is estimated that over 340 million children and adolescents aged 5-19 were overweight or obese in 2016. Obesity rates in adults were found highest in several countries including Mexico, USA, New Zealand and others. In India, the prevalence of obesity is estimated around 40%. The common health consequences of overweight and obesity are cardiovascular disease, diabetes mellitus, osteoarthritis, and cancer. The manuscript, therefore, first summarizes the nutritional suggestions for the prevention and treatment of overweight and obesity. Then it helps in practical implementation by presenting the possibilities offered by gastronomy. In doing so, we present foods that, with their energy and macronutrient content, greatly help to protect against overweight and obesity. Their other useful active ingredient contents are also important in achieving the normal body weight and optimizing energy levels. It is advised that an increased intake of energy-dense foods that are very rich in fats and sugars must be avoided by everyone. Further, the importance of daily regular physical activities should be highlighted in order to prevent overweight and obesity.
Clinical Utility of Human Papillomavirus Circulating Tumour DNA in Human Papillomavirus-positive Head and Neck Squamous Cell Carcinomas

Human papillomavirus (HPV)-associated head and neck squamous cell carcinomas (HNSCCs) are a subtype of virally driven tumours with favourable responses to definitive therapy. However, disease relapse or progression is clinically challenging due to limited effective treatment options. Circulating tumour DNA (ctDNA) technology has emerged in the past decade, and it remains an active area of research in head and neck cancers. A variety of assays for the analysis of HPV ctDNA in patients with HPV-positive HNSCC have been developed and studied, though standardization in HPV ctDNA testing has yet to be established. Studies show promise in HPV ctDNA as a prognostic biomarker and predictor of treatment response and risk for recurrence. Growing evidence suggests that absolute HPV ctDNA quantification, as well as dynamic changes in HPV ctDNA concentration, can potentially inform outcomes and guide decisions about therapy. The aim of this article is to review the clinical utility of HPV ctDNA as a biomarker in HNSCC.
Investigation of Behavioral Characteristic Parameters Intended for Emotional State Classification

In the present, we can use more than 200 different methods and algorithms for automatic recognition systems, the basis of which is the recognition of a face in an image, subsequent extraction of areas of interest and classification of individual parameters using neural networks or other classifications. Currently, one of the most discussed research topics connecting the fields of psychology and artificial intelligence is the classification of emotions from behavioral characteristics. We created the Emotnizer application for collecting and processing behavioral characteristics. The input characteristics record 24 different ways of user behavior when working with a mouse and keyboard, e.g., when rewriting text (determining the method of clicking / key pressing speed, cursor changes, errors in the text, etc.). In the article, we analyze the obtained parameters using the decision tree method and find out whether it is possible to successfully classify the emotional state using these parameters. We found that for the successful classification of emotional states using behavioral characteristics, it is appropriate to classify mainly emotional states with a high value of valence and arousal.
DARN: Distance Attention Residual Network for Lightweight Remote-Sensing Image Superresolution

The application of single-image superresolution (SISR) in remote sensing is of great significance. Although the state-of-the-art convolution neural network (CNN)-based SISR methods have achieved excellent results, the large model and slow speed make it difficult to deploy in real remote sensing tasks. In this article, we propose a compact and efficient distance attention residual network (DARN) to achieve a better compromise between model accuracy and complexity. The distance attention residual connection block (DARCB), the core component of the DARN, uses multistage feature aggregation to learn more accurate feature representations. The main branch of the DARCB adopts a shallow residual block (SRB) to flexibly learn residual information to ensure the robustness of the model. We also propose a distance attention block (DAB) as a bridge between the main branch and the branch of the DARCB; the DAB can effectively alleviate the loss of detail features in the deep CNN extraction process. Experimental results on two remote sensing and five super-resolution benchmark datasets demonstrate that the DARN achieves a better compromise than existing methods in terms of performance and model complexity. In addition, the DARN achieves the optimal solution compared with the state-of-the-art lightweight remote sensing SISR method in terms of parameter amount, computation amount, and inference speed. Our code will be available at https://github.com/candygogogogo/DARN.
Processing near-infrared imagery of hypersonic space shuttle reentries

High-resolution, calibrated, near-infrared imagery of the Space Shuttle during reentry has been obtained by a US Navy NP-3D Orion aircraft as part of NASA's HYTHIRM (Hypersonic Thermodynamic InfraRed Measurements) project. The long-range optical sensor package is called Cast Glance. Three sets of imagery have been processed thus far: 1) STS- 119 when Shuttle Discovery was at 52 km away at Mach 8.4, 2) STS-125 when Shuttle Atlantis was 71 km away at Mach 14.3, and 3) STS-128 when Shuttle Discovery was at 80 km away at Mach 14.7. The challenges presented in processing a manually-tracked high-angular rate, air-to-air image data collection include management of significant frame-to-frame motions, motion-induced blurring, changing orientations and ranges, daylight conditions, and sky backgrounds (including some cirrus clouds). This paper describes processing the imagery to estimate Shuttle surface temperatures. Our goal is to reduce the detrimental effects due to motions (sensor and Shuttle), vibration, and atmospherics for image quality improvement, without compromising the quantitative integrity of the data, especially local intensity variations. Our approach is to select and utilize only the highest quality images, register many cotemporal image frames to a single image frame, and then add the registered frames to improve image quality and reduce noise. These registered and averaged intensity images are converted to temperatures on the Shuttle's windward surface using a series of steps starting with preflight calibration data. Comparisons with thermocouples at different points along the space Shuttle and between the three reentries will be shown.
In Skeletal Muscle Fibers, Protein Kinase Subunit CSNK2A1/CK2α Is Required for Proper Muscle Homeostasis and Structure and Function of Neuromuscular Junctions

CSNK2 tetrameric holoenzyme is composed of two subunits with catalytic activity (CSNK2A1 and/or CSNK2A2) and two regulatory subunits (CSNK2B) and is involved in skeletal muscle homeostasis. Up-to-date, constitutive Csnk2a2 knockout mice demonstrated mild regenerative impairments in skeletal muscles, while conditional Csnk2b mice were linked to muscle weakness, impaired neuromuscular transmission, and metabolic and autophagic compromises. Here, for the first time, skeletal muscle-specific conditional Csnk2a1 mice were generated and characterized. The ablation of Csnk2a1 expression was ensured using a human skeletal actin-driven Cre reporter. In comparison with control mice, first, conditional knockout of CSNK2A1 resulted in age-dependent reduced grip strength. Muscle weakness was accompanied by impaired neuromuscular transmission. Second, the protein amount of other CSNK2 subunits was aberrantly changed. Third, the number of central nuclei in muscle fibers indicative of regeneration increased. Fourth, oxidative metabolism was impaired, reflected by an increase in cytochrome oxidase and accumulation of mitochondrial enzyme activity underneath the sarcolemma. Fifth, autophagic processes were stimulated. Sixth, NMJs were fragmented and accompanied by increased synaptic gene expression levels. Altogether, knockout of Csnk2a1 or Csnk2b results in diverse impairments of skeletal muscle biology.
Lattice Boltzmann simulation of nucleate pool boiling in saturated liquid

A thermal lattice Boltzmann method (LBM) for two-phase fluid flows in nucleate pool boiling process is proposed. In the present method, a new function for heat transfer is introduced to the isothermal LBM for two-phase immiscible fluids with large density differences. The calculated temperature is substituted into the pressure tensor, which is used for the calculation of an order parameter representing two phases so that bubbles can be formed by nucleate boiling. By using this method, two-dimensional simulations of nucleate pool boiling by a heat source on a solid wall are carried out with the boundary condition for a constant heat flux. The flow characteristics and temperature distribution in the nucleate pool boiling process are obtained. It is seen that a bubble nucleation is formed at first and then the bubble grows and leaves the wall, finally going up with deformation by the buoyant effect. In addition, the effects of the gravity and the surface wettability on the bubble diameter at departure are numerically investigated. The calculated results are in qualitative agreement with other theoretical predictions with available experimental data.
Phonon Raman spectroscopy of nanocrystalline multinary chalcogenides as a probe of complex lattice structures

Ternary (I–III–VI) and quaternary (I–II–IV–VI) metal-chalcogenides like CuInS2 or Cu2ZnSn(S,Se)4 are among the materials currently most intensively investigated for various applications in the area of alternative energy conversion and light-emitting devices. They promise more sustainable and affordable solutions to numerous applications, compared to more developed and well understood II–VI and III–V semiconductors. Potentially superior properties are based on an unprecedented tolerance of these compounds to non-stoichiometric compositions and polymorphism. However, if not properly controlled, these merits lead to undesirable coexistence of different compounds in a single polycrystalline lattice and huge concentrations of point defects, becoming an immense hurdle on the way toward real-life applications. Raman spectroscopy of phonons has become one of the most powerful tools of structural diagnostics and probing physical properties of bulk and microcrystalline I–III–VI and I–II–IV–VI compounds. The recent explosive growth of the number of reports on fabrication and characterization of nanostructures of these compounds must be pointed out as well as the steady use of Raman spectroscopy for their characterization. Interpretation of the vibrational spectra of these compound nanocrystals (NCs) and conclusions about their structure can be complicated compared to bulk counterparts because of size and surface effects as well as emergence of new structural polymorphs that are not realizable in the bulk. This review attempts to summarize the present knowledge in the field of I–III–VI and I–II–IV–VI NCs regarding their phonon spectra and capabilities of Raman and IR spectroscopies in the structural characterizations of these promising families of compounds.
Molecular mechanism of QH-BJ drug pair in the treatment of systemic lupus erythematosus based on network pharmacology and molecular docking

To analyze the molecular mechanism of Qinghao-Biejia (QH-BJ) drug pair in the treatment of systemic lupus erythematosus (SLE) based on the method of network pharmacology and molecular docking technology. The components and related targets of QH-BJ drug pair, as well as SLE-related targets, were obtained. Intersection targets of QH-BJ drug pair and SLE were screened to construct the protein–protein interaction network, conduct gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, and establish the component-target-pathway network. The core active components and core targets of QH-BJ drug pair for the treatment of SLE were selected, and molecular docking was carried out between the ligand components and the receptor target proteins. The core active components of QH-BJ drug pair for the treatment of SLE are luteolin, quercetin, and kaempferol; the core targets are PTGS2, HSP90AA1, RELA, MAPK1, MAPK14, AKT1, JUN, TNF, TP53. The ligand components can spontaneously bind to the receptor target proteins. Besides, QH-BJ drug pair is likely to act on PI3K/Akt signal pathway, interleukin-17 signal pathway, and TNF signal pathway in the treatment of SLE. The study indicates that QH-BJ drug pair might play a role in the treatment of SLE through multi-components, multi-targets, and multi-pathways.
Sparse Gabor wavelets by local operations

Efficient sparse coding of overcomplete transforms remains still an open problem. Different methods have been proposed in the literature, but most of them are limited by a heavy computational cost and by difficulties to find the optimal solutions. We propose here an algorithm suitable for Gabor wavelets and based on biological models. It is composed by local operations between neighboring transform coefficients and achieves a sparse representation with a relatively low computational cost. Used with a chain coder, this sparse Gabor wavelet transform is suitable for image compression but is also of interest also for other applications, in particular for edge and contour extraction and image denoising.
Mitochondrial genome characterization and phylogeny of Wallacea dactyliferae Maulik 1919 (Coleoptera: Chrysomelidae) from China

Abstract Wallacea dactyliferae Maulik 1919 (Coleoptera: Chrysomelidae) has been reported as a new invasive palm pest in Asia recently. So far, a total of 29 species have been reported in Wallacea. In the present study, the whole mitochondrial genome of W. dactyliferae was identified for the first time (also for the first species of Wallacea) by using high throughput sequencing systems. The entire genome is 16,243 bp in length (ACCN: OK513040) consisting of 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes, and an A + T-rich region. Phylogenetic analysis revealed that insects from the same subfamily were clustered together, with W. dactyliferae being clustered together with other Cassidinae species. This study can provide essential DNA molecular data for further phylogenetic and evolutionary analyses for Chrysomelidae family of the Coleoptera order.