Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances in Imaging Techniques for Disease Monitoring of High Grade Gliomas during Immunotherapy

In general, high grade gliomas have a dismal prognosis. However, recent advances in disease classification, surgical treatment, and adjuvant therapy have increased the overall survival of this patient population. While a significant number of resources is used to improve treatment for high grade gliomas, there are few advancements in technology development towards an accurate non-invasive assessment of response to these therapeutic modalities. The advent of new treatment modalities and especially the increasing number of immunotherapy clinical trials for high grade gliomas necessitate the development of new approaches for accurate and timely assessment of treatment response in brain tumors. Conventional MRI assessment of response to immunotherapy is inadequate to guide treatment leading to a high number of surgical procedures for definitive assessment. In this review, we are outlining the evolution of imaging criteria as well as the advancements in imaging technology and computational analysis to address the challenges of disease monitoring in the setting of immunotherapy for high grade gliomas. We give particular emphasis on radiomics, a new field on image analysis that algorithmically assesses a large number of imaging features for an accurate diagnosis.
LANDSLIDE SUSCEPTIBILITY ASSESSMENT IN JIUZHAIGOU SCENIC AREA WITH GIS BASED ON CERTAINTY FACTOR AND LOGISTIC REGRESSION MODEL

Thousands of coseismic landslides were induced by the Jiuzhaigou MS7.0 earthquake on August 8th 2017, Sichuan, China. Thus, a tremendous volume of loose debris are extremely prone to convert into landslides and debris flow under rainfall. Therefore, it is necessary to conduct landslide susceptibility assessment in Jiuzhaigou Scenic area. Based on a large set of pre-and post-earthquake high-resolution satellite images and field investigation, a polygon-based interpretation of the coseismic landslides is carried out. In total, 1047 landslides are identified, covering an area of 3.88 km2. The relationship between the spatial distribution of landslides and its influencing factors is analyzed. Nine factors including tectonic, topographic, geological and other factors are selected to evaluate the landslide susceptibility by certainty factor model and logistic regression model, as well as coupled model. The result shows that slope, aspect, elevation and lithology are the main factors controlling the spatial distribution of landslides. The susceptibility of landslide is divided into low(60.72%), moderate(24.18%), high(9.89%) and extremely high areas(5.21%). The high and extremely high areas covering an area of 99 km2 including Tiger Lake and Panda Lake are distributed along the valleys. The assessment result of the coupled model is more reasonable than that of the single model and can be used as scientific reference for prevention of landslide hazard and segmented opening time of scenic area.
Characterization of a low-grade copper-sulphide ore to assess its suitability for in situ recovery

CSIRO Minerals is developing new technologies and approaches for the in situ recovery (ISR) of valuable metals. ISR provides opportunities to process small and/or deep deposits and could create additional revenue for conventional uneconomic mines. Unlike for conventional processing, no standard methodology exists for characterizing sample suitability for ISR. The authors are developing a workflow to understand sample and deposit amenability to ISR processing. A South Australian low-grade iron-oxide-copper-gold sulphide ore was studied. A total of 37 drill cores samples were obtained from the ore sample for detailed mineralogical and leaching characterization. A range of characterization techniques including chemical analysis, X-ray fluorescence mapping, quantitative evaluation of minerals by scanning electron microscopy, computed tomography scanning, and bulk- and micro-X-ray diffraction analyses were applied to understand the ore mineralogy. Leaching tests at 50 °C were performed on selected samples to understanding their leaching behaviour. Mineralogical characterization found that copper was present mostly as discrete secondary copper sulphides distributed in various areas and at various specimen depths, which, in theory should be readily available for leaching, provided sufficient solution access exists. Leaching results showed steady copper recovery under the conditions tested. This study provides insight into understanding the suitability of an ore for ISR processing.
Mathematical Analysis Model of Double-Stator Field Modulation HTS Machine Based on General Airgap Field Modulation Theory

TheSuperconducting (SC) machines have the merits of higher power and torque density due to the fact of higher electrical or magnetic loading. Especially, the field modulation SC machine (FMSCM) recently attracts more and more attention from scholars, since this kind of SC machines successfully overcome the drawbacks of the traditional SC synchronous machines, such as the rotating seal of the coolant and the electrical brush-slip-ring for current transfer. However, the research method of the FMSCM mainly adopts the finite element analysis (FEA). Although the FEA can provide accurate results, the time consumption is huge, particularly at the initial design of the large capacity FMSCM, the time cost will be unacceptable. Aiming at solving this problem, this paper attempts to establish the mathematical analysis model of a double-stator field modulation HTS machine (DSFM-SCM) using a new theory of electrical machine, i.e., general airgap field modulation theory, for the first time. Both the FEA and experiments are carried out on the DSFM-SCM, to verify the effectiveness of the proposed mathematical analysis model. Although there is discrepancy between the proposed analytical method and FEA, it can basically meet the requirement at the initial design, and sufficiently exhibit the modulation effect of geometric structure, reflecting the essential mechanism of the DSFM-SCM. In addition, it is worth noting that the establishment process of analytical model of the DSFM-SCM can provide reference for the other FMSCMs.
Low-Temperature Fabrication of Mesoporous Titania Thin Films

Mesoporous titania films are prepared via the polymer-template assisted sol-gel synthesis at low temperatures, using the titania precursor ethylene glycol-modified titanate (EGMT) and the diblock copolymer polystyrene-block-polyethyleneoxide (PS-b-PEO). UV-irradiation is chosen as a low temperature technique to remove the polymer template and thereby to obtain titania sponge-like nanostructures at processing temperatures below 100 °C. After different UV irradiation times, ranging for 0 h to 24 h, the surface and inner morphologies of the titania films are studied with scanning electron microscopy (SEM) and grazing incidence small-angle x-ray scattering (GISAXS), respectively. The evolution of the band gap energies is investigated using ultraviolet/visible (UV/Vis) spectroscopy. The findings reveal that 12 h UV-treatment is sufficient to remove the polymer template from the titania/PS-b-PEO composite films with a thickness of 80 nm, and the determined bad gap energies indicate an incomplete crystallization of the titania nanostructures.
Russia in the Post-Soviet Space: Dual Citizenship as a Foreign Policy Instrument

The spread of dual citizenship in the post-Soviet space is becoming one of the most important tools for ensuring Russia’s hegemony in the region. However, this phenomenon is often overlooked in foreign policy analysis. The study of changes in Russian legislation shows that over the past three years Russia has created a legal framework that would accelerate the spread of dual citizenship in Ukraine and potentially in Belarus, Kazakhstan, and Moldova. So, Moscow gets powerful leverage, but its use has so far run into both internal constraints and concerns within the Russian government structures and the resistance of neighboring independent states. Thus, a new research field is taking shape at the intersection of several disciplines—political science, international studies, and sociology.
Enhanced Boost Factor for Three-Level Quasi-Switched Boost T-Type Inverter

A new modulation strategy has been introduced in this paper in order to enhance the boost factor for the three-level quasi-switched boost T-type inverter (3L-qSBT2I). Under this approach, the component rating of power devices is significantly decreased. Moreover, the use of a larger boost factor produces a smaller shoot-through current. This benefit leads to reducing the conduction loss significantly. Furthermore, the neutral voltage unbalance is also considered. The duty cycle of two active switches of a quasi-switched boost (qSB) network is redetermined based on actual capacitor voltages to recovery balance condition. Noted that the boost factor will not be affected by the proposed capacitor voltage balance strategy. The proposed method is taken into account to be compared with other previous studies. The operation principle and overall control strategy for this configuration are also detailed. The simulation and experiment are implemented with the help of PSIM software and laboratory prototype to demonstrate the accuracy of this strategy.
Fuzzy Embedded Clustering Based on Bipartite Graph for Large-Scale Hyperspectral Image

Hyperspectral image (HSI) clustering has been widely used in the field of remote sensing. However, most traditional clustering algorithms are not suitable for dealing with large-scale HSI due to their low clustering performance and high computational complexity. In this letter, we propose a novel fuzzy clustering algorithm, called fuzzy embedded clustering based on the bipartite graph (FECBG), to efficiently deal with large-scale HSI clustering problems. First, we propose the FECBG method that incorporates fuzzy clustering with the nonnegative regularization term based on the bipartite graph into a unified model, which has good clustering performance and reduces the sensitivity of fuzzy clustering to the initial cluster centers. Second, we adopt the fast spectral embedded method to obtain the low-dimensional representation of HSI data, to reduce the computational complexity. At last, we add the nonnegative regularization term based on the bipartite graph to fuzzy clustering, to constrain the solution space of the fuzzy membership matrix. Experimental results on several HSI data sets have demonstrated the efficiency and effectiveness of the proposed FECBG algorithm.
Automatic image quality tuning framework for optimization of ISP parameters based on multi-stage optimization approach

Image signal processors (ISP) plays a significant role in camera systems by converting the RAW image from image sensor to a processed image. In order to achieve best image quality, the ISP parameters have to be configured in an iterative manner for various lighting conditions and scenarios, which is carried out by a camera tuning engineer. Usually, the manual tuning process takes up to several weeks to months due to huge number of ISP parameters to be optimized and the iterations involved to achieve good image quality. In this paper, we present a novel approach to automatically tune ISP parameters based on a multi-stage multi-criteria optimization approach using Non sorted Genetic algorithm (NSGA-II) for achieving objective and subjective image quality. In this approach, we focus on important blocks in ISP such as noise reduction, sharpness and tone mapping for human vision use-cases for camera systems widely used for smart phones or smart home IoT devices. The experiments for validating our approach are carried out under different scenarios using Qualcomm’s Spectra 380 ISP simulator and OV13880 sensor and the performance of automatic tuned IQ is compared with manual tuned IQ and some of the previous works done for automatically tuning ISP parameters. With the automatic ISP tuning approach, we verify the significant performance improvement in terms of IQ metrics and time consumed for the tuning process when compared to manual tuning approach.
Evidence for New Enantiospecific Interaction Force in Chiral Biomolecules

Enantiospecific biorecognition interactions are key to many biological events. Commonly, bio-affinity values, measured in these processes, are higher than those calculated by available methods. We report here the first direct measurement of the interaction force between right and left handed helical polyalanine peptides using atomic force microscope (AFM) and calculations based on a simple theoretical model. A force difference of 60pN between same and opposite enantiomer interactions is measured. Additional measurements show spin dependency and fast decay of the interaction term, consistent with spin exchange interactions. This short range enantiospecific interaction term is especially relevant in crowded biological systems. The results shed light on the importance of spin and exchange interactions in biological processes, providing explanation to the discrepancies between past calculations and experiments.
Contributing Roles of Depression, Anxiety, and Impulsivity Dimensions in Eating Behaviors Styles in Obese Individuals Seeking Bariatric Surgery

BackgroundEven if bariatric surgery appears as the most effective therapeutic approach, it is not equally successful across individuals suffering from obesity. Among the factors that influence postsurgical outcomes, eating behaviors are known to play a key role in relapses. The aim of our study was to assess eating behaviors styles and several modulating psychopathological factors in patients suffering from obesity.MethodsPatients seeking bariatric surgery (N = 127) completed a set of standardized tools assessing eating behaviors (DEBQ), psychiatric comorbid conditions (MINI), mood (BDI-13, STAI), and impulsivity (UPPS-P). ResultsWe found significant correlations between DEBQ Emotional Eating (EmoE) and depression, state and trait anxiety and all dimensions of impulsivity. Significant correlations also occurred between DEBQ External Eating (ExtE) and depression, state and trait anxiety and UPPS-P positive urgency, lack of perseverance and sensation seeking. Regression analyses showed female gender, trait anxiety, and lack of perseverance as explanatory factors in EmoE, and depression severity score and positive urgency in ExtE.ConclusionsEmoE might be a means of dealing with negative emotions and/or intrusive thoughts, while ExtE may result from a mechanism associated with depression. These results may help to improve patients’ outcome by defining specific therapeutic targets in psychological interventions.
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge

Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems, as underground settings present key challenges that can render robot autonomy hard to achieve. This problem has motivated the DARPA Subterranean Challenge, where teams of robots search for objects of interest in various underground environments. In response, we present the CERBERUS system-of-systems, as a unified strategy for subterranean exploration using legged and flying robots. Our proposed approach relies on ANYmal quadraped as primary robots, exploiting their endurance and ability to traverse challenging terrain. For aerial robots, we use both conventional and collision-tolerant multirotors to explore spaces too narrow or otherwise unreachable by ground systems. Anticipating degraded sensing conditions, we developed a complementary multimodal sensor-fusion approach, utilizing camera, LiDAR, and inertial data for resilient robot pose estimation. Individual robot pose estimates are refined by a centralized multi-robot map-optimization approach to improve the reported location accuracy of detected objects of interest in the DARPA-defined coordinate frame. Furthermore, a unified exploration path-planning policy is presented to facilitate the autonomous operation of both legged and aerial robots in complex underground networks. Finally, to enable communication among team agents and the base station, CERBERUS utilizes a ground rover with a high-gain antenna and an optical fiber connection to the base station and wireless “breadcrumb” nodes deployed by the legged robots. We report results from the CERBERUS system-of-systems deployment at the DARPA Subterranean Challenge’s Tunnel and Urban Circuit events, along with the current limitations and the lessons learned for the benefit of the community.
Quality analysis in the service sector of an electricity generating company according to Servqual’s model

— Measuring the quality of service levels in self-service, rural and urban emergency services, as well as the wait time for a possible customer until connection offered by an electricity company continues as an objective, based on the perspective proposed by Parasuraman et al. (1985). In order to detect the sources of problems in service quality and seek improvement, this model is based on the principle of comparison between the perceived service and the expected service, considering that the expectations of customers is strongly influenced by their personal needs.The survey had participation from 2450 customers distributed in the 98 neighborhoods of the municipality, which were already familiar with the services provided, since, in the state of Paraná, this company is currently the only electricity utility servicio, Confianza y Seguridad. La valoración de la calidad percibida de estos servicios se consideró media para prácticamente todas las dimensiones. Este estudio también presenta una comparativa entre las diez dimensiones evaluadas y el método de los principales componentes del análisis factorial, responsable de extraer cinco nuevas dimensiones: Confianza en la empresa, Flexibilidad en la prestación del servicio, Facilidad de autoservicio, Seguridad y Velocidad. Y aunque estas nuevas dimensiones han reducido significativamente el número inicial de variables analizadas, no hubo pérdida en relación a la importancia de los servicios prestados por la empresa.
Evaluation of Single-Frequency Precise Point Positioning Performance Based on SPARTN Corrections Provided by the SAPCORDA SAPA Service

Fields of high-precision positioning applications are growing fast across the mass market worldwide. Accordingly, the industry is focusing on developing methods of applying State-Space Representation (SSR) corrections on low-cost GNSS receivers. Among SSR correction types, this paper analyzes Safe Position Augmentation for Real Time Navigation (SPARTN) messages being offered by the SAfe and Precise CORrection DAta (SAPCORDA) company and validates positioning algorithms based on them. The first part of this paper introduces the SPARTN format in detail. Then, procedures on how to apply Basic-Precision Atmosphere Correction (BPAC) and High-Precision Atmosphere Correction (HPAC) messages are described. BPAC and HPAC messages are used for correcting satellite clock errors, satellite orbit errors, satellite signal biases and also ionospheric and tropospheric delays. Accuracies of positioning algorithms utilizing SPARTN messages were validated with two types of positioning strategies: Code-PPP using GPS pseudorange measurements and PPP-RTK including carrier phase measurements. In these performance checkups, only single-frequency measurements have been used and integer ambiguities were estimated as float numbers instead of fixed integers. The result shows that, with BPAC and HPAC corrections, the horizontal accuracy is 46% and 63% higher, respectively, compared to that obtained without application of SPARTN corrections. Also, the average horizontal and vertical RMSE values with HPAC are 17 cm and 27 cm, respectively.
On Improving Sine Sweep Impulse Response Measurments through Adaptive Filtering

Sine sweeps proves to be a reliable tool for measuring impulse responses even in noisy conditions or by using loudspeakers which are not linear. In this paper we present some results regarding an enhanced sine sweep method, used for impulse response measurement, based on the use of adaptive filtering. Using MATLAB, the conditions of a real case scenario impulse response measurement are simulated in order to quantify the performances of the proposed method by using as reference the performances of the classical sine sweep method.
Fabrication and Characterization of Double-Walled Microsphere as a Drug Delivery System for Stroke Treatment

i Résumé . iii Statement of originality . iv Statement of contribution . v Acknowledgements . vi List of Abbreviations. x List of Figures . xii List of Tables . xiv 1.Introduction . 1 2. Literature Review . 3 2.1 Stroke . 3 2.1.1 Approaches to overcome stroke . 4 2.1.1. 1 Treatments for ischemic stroke . 4 2.1.1.2 Treatments for hemorrhagic stroke . 5 2.1.1.3 Stem cell therapy . 6 2.1.2 Decompressive Craniectomy (DC) . 10 2.2 Protective layers of the brain . 11 2.3 Duraplasty . 12 2.4 Hydrogels . 13 2.4. 1 Post-stroke treatment using hydrogels . 14
Enhanced biodegradation of sugarcane bagasse by co-culture of Clostridium thermocellum and Thermoanaerobacterium aotearoense supplemented with CaCO3

The pretreated sugarcane bagasse (SCB) could be directly degraded by a designed co-culture system with Clostridium thermocellum and Thermoanaerobacterium aotearoense for biological hydrogen and ethanol production, and the production was remarkably improved by CaCO3 supplementation. Here, the effects of CaCO3 concentration (10~100 mM) on the production of hydrogen and ethanol were investigated. Under the optimal CaCO3 concentration of 40 mM, the hydrogen production reached 87.56±4.08 mmol/L from 2% pretreated SCB with a yield of 4.38 mmol H2/g SCB, an 88.62% increase over the culture without added CaCO3 (46.42±1.22mmol/L, 2.32 mmol H2/g SCB). Additionally, the maximum ethanol concentration reached 10.60±0.81 mM, a 192.82% increase over the control (3.62±0.14 mM). The stimulatory effect of CaCO3 on biodegradation of SCB was primarily ascribed to the buffering capacity of CO32-. This study developed a novel strategy to improve SCB biodegradation for biofuel production.
Transfer Learning with Style Transfer between the Photorealistic and Artistic Domain

Transfer Learning is an important strategy in Computer Vision to tackle problems in the face of limited training data. However, this strategy still heavily depends on the amount of availabl data, which is a challenge for small heritage institutions. This paper investigates various ways of enrichingsmaller digital heritage collections to boost the performance of deep learningmodels, using the identification of musical instruments as a case study. We apply traditional data augmentation techniques as well as the use of an external, photorealistic collection, distorted by Style Transfer. Style Transfer techniques are capable of artistically stylizing images, reusing the style from any other given image. Hence, collections can be easily augmented with artificially generated images. We introduce the distinction between inner and outer style transfer and show that artificially augmented images in both scenarios consistently improve classification results, on top of traditional data augmentation techniques. However, and counter-intuitively, such artificially generated artistic depictions of works are surprisingly hard to classify. In addition, we discuss an example of negative transfer within the non-photorealistic domain.