bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of tectonically enhanced radon in fault zones by quantification of the radon activity index
Authors: Benà Eleonora , Ciotoli Giancarlo , Ruggiero Livio , Coletti Chiara , Bossew Peter , Massironi Matteo , Mazzoli Claudio , Mair Volkmar , Morelli Corrado , Galgaro Antonio , Morozzi Pietro , Tositti Laura , Sassi Raffaele 
Published: December 2022

AbstractThis work highlights the importance of the Geogenic Radon Potential (GRP) component originated by degassing processes in fault zones. This Tectonically Enhanced Radon (TER) can increase radon concentration in soil gas and the inflow of radon in the buildings (Indoor Radon Concentrations, IRC). Although tectonically related radon enhancement is known in areas characterised by active faults, few studies have investigated radon migration processes in non-active fault zones. The Pusteria Valley (Bolzano, north-eastern Italy) represents an ideal geological setting to study the role of a non-seismic fault system in enhancing the geogenic radon. Here, most of the municipalities are characterised by high IRC. We performed soil gas surveys in three of these municipalities located along a wide section of the non-seismic Pusteria fault system characterised by a dense network of faults and fractures. Results highlight the presence of high Rn concentrations (up to 800 kBq·m−3) with anisotropic spatial patterns oriented along the main strike of the fault system. We calculated a Radon Activity Index (RAI) along north–south profiles across the Pusteria fault system and found that TER is linked to high fault geochemical activities. This evidence confirms that TER constitutes a significant component of GRP also along non-seismic faults.
Opportunistic screening for osteoporosis using hydroxyapatite measurements of the vertebral by thorax dual-energy spectral CT in postmenopausal females
Authors: Deng Lei , Yao Yue , Shang A.-Li , Du Tongtong , Zhang Jingbin , Yang Quanxin , Li Jianying , Wang Qian , Li Xiaohui 
Published: December 2022

AbstractThe purpose of this study was to evaluate the feasibility of opportunistic screening for osteoporosis in postmenopausal females using the dual-energy CT(DECT)-derived hydroxyapatite (HAP) concentration and CT value of L1-vertebra. 239 consecutive postmenopausal female patients were enrolled and underwent both chest DECT and Dual energy X-ray absorptiometry (DXA). According to the T-score of the 1st lumbar vertebra on DXA, patients were divided into the osteoporosis group (T $$\le$$
≤
− 2.5, n = 112) and non-osteoporosis group (T $$>$$
>
− 2.5, n = 127). The HAP values of the 1st lumbar vertebra were measured from the coronal-view HAP(Fat)-based material decomposition(MD) images, and CT values were measured on the 75 keV monochromatic image. The cutoff values of using HAP and CT value for diagnosing osteoporosis were obtained by drawing receiver operating characteristic (ROC) curves. Both HAP and CT value of the 1st lumbar vertebra had moderate-high correlation with bone-mineral-density measurement on DXA (HAP, r = 0.614; CT value, r = 0.625; all p < 0.01). The area-under-the-curve (AUC), sensitivity, specificity, PPV and NPV for diagnosing osteoporosis was 0.754, 0.714, 0.693, 0.68 and 0.752 using HAP (cutoff value: 142.05 mg/cm3) and 0.766, 0.741, 0.7, 0.685 and 0.754 using CT value (cutoff value: 132HU), respectively. HAP measurements on HAP(Fat)-based MD images in DECT could provide reasonably accurate BMD quantification for diagnosing osteoporosis in postmenopausal females. DECT prescribed for lung cancer screening could also provide opportunistic screening for osteoporosis, extending the clinical application of DECT without additional radiation to patients.
Design and control of a robotic system with legs, wheels, and a reconfigurable arm
Authors: Ye Linqi , Liu Houde , Wang Xueqian , Liang Bin , Yuan Bo 
Published: December 2022

AbstractUnmanned robotic systems are expected to liberate people from heavy, monotonous, and dangerous work. However, it is still difficult for robots to work in complicated environments and handle diverse tasks. To this end, a robotic system with four legs, four wheels, and a reconfigurable arm is designed. Special attention has been given to making the robot compact, agile, and versatile. Firstly, by using separate wheels and legs, it removes the coupling in the traditional wheeled–legged system and guarantees highly efficient locomotion in both the wheeled and legged modes. Secondly, a leg–arm reconfiguration design is adopted to extend the manipulation capability of the system, which not only reduces the total weight but also allows for dexterous manipulation and multi‐limb cooperation. Thirdly, a multi‐task control strategy based on variable configurations is proposed for the system, which greatly enhances the adaptability of the robot to complicated environments. Experimental results are given, which validate the effectiveness of the system in mobility and operation capability.
Improving multispectral pedestrian detection with scale‐aware permutation attention and adjacent feature aggregation
Authors: Zuo Xin , Wang Zhi , Shen Jifeng , Yang Wankou 
Published: December 2022

AbstractHigh quality feature fusion module is one of the key components for multispectral pedestrian detection system in challenging situations, such as large‐scale variance and occlusion. Although attention mechanism is one of the most effective ways for feature refining, the correlation between attention and scales in feature pyramid still remains unknown. Therefore, a scale‐aware permutated attention module is proposed to enhance features of objects with different scales adaptively in the feature pyramid. Specifically, four different local and global attention sub‐modules are investigated to refine feature maps with different permutations in the Feature Pyramid Networks, improving the quality of the feature fusion. Besides, to address the high miss‐rate issue for small‐sized pedestrians, an adjacent‐branch feature aggregation module is proposed to aggregate features across different scales, taking both semantic context and spatial resolution into consideration. Both modules can benefit from each other with significant performance improvement in terms of efficiency and accuracy, when equipped with the dual‐branch CenterNet detection framework. Experiments on the KAIST and FLIR datasets demonstrate its superior performance compared with other state‐of‐the‐arts.
Signal demodulator based on in‐phase and quadrature interference‐robust feature
Authors: Deng Wen , Cai Xin , Wang Xiang , Huang Zhitao 
Published: December 2022

AbstractThis letter examines the issue of mitigating strong co‐channel interference in communication systems is addressed. Unlike conventional model‐based methods, a novel data‐driven scheme is proposed. A recurrent neural network is trained to directly demodulate the desired signal under strong co‐channel interference. Instead of inputting the original received signal, in‐phase and quadrature interference‐robust features are extracted through preprocess. The recurrent neural network is then trained offline to implement sequence labelling, with the interference‐robust feature sequences and known code sequences of the desired signal as inputs and ground‐truth labels. Meanwhile, a guard zone is introduced when loading the interference‐robust feature sequences to enable better contextual information exploitation by the recurrent neural network demodulator. Online tests validated the low bit error rate of the recurrent neural network demodulator, under strong co‐channel interference. Moreover, the proposed scheme outperformed existing model‐based and data‐driven interference mitigation schemes in terms of the bit error rate, especially in low signal‐to‐interference ratio region. Inspiringly, the proposed data‐driven scheme generalized well to varied unseen test conditions.
Litz wire loss performance and optimization for cryogenic windings
Authors: Manolopoulos Charalampos D. , Iacchetti Matteo F. , Smith Alexander C. , Miller Paul , Husband Mark 
Published: December 2022

AbstractLitz wires operating in a cryogenic environment can potentially improve both the efficiency and power density of electrical machines and passive components. However, due to the low resistivity and high magnetic fields, eddy‐current losses may become significant in cryogenically cooled windings, especially in airgap winding arrangements or in the case of significant slot leakage fields, unless the litz wire parameters are carefully chosen. A framework for litz wire loss performance optimization and experimental characterisation at cryogenic temperatures is provided. An optimum operating temperature for minimum loss is derived based on analytical expressions, which highlights the role of litz wire parameters, current density and external field. The proximity loss model, used to calculate the optimum operating temperature, is validated experimentally. Two test rigs with different magnetic cores were designed and built. Copper and aluminium litz wires with a strand diameter down to 0.1 mm were tested in a liquid nitrogen bath with a uniform harmonic external magnetic field up to 0.5 T peak and a frequency up to 1 kHz. Measurements show good agreement with the theoretical results and confirm that the proposed model can be confidently used during the preliminary design of cryogenic windings.
Improvement of breakdown and flashover properties against thermal aging of oil paper insulation through addition of TiO2 nanoparticles
Authors: Huang Meng , Li Sai , Zhang Lei , Yao Yuanxin , Lv Yuzhen , Chen Xin , Pang Wenli 
Published: December 2022

AbstractTiO2 nanoparticles can improve the electrical performance of oil paper insulation. In this study, 10 nm TiO2 nanoparticles were prepared and dispersed into transformer oil, and then immerse pressboards in it to obtain nanofluid impregnated pressboards (NP). Its thermal aging was accelerated together with the reference sample at 130°C for 36 days. Analyzing the acid value in the oil, polymerization degree, surface topography, AC breakdown strength, surface flashover characteristics and surface potential decay characteristics. It was observed that TiO2 nanoparticles can reduce the acid value and improve AC breakdown strength of oil. However, the degree of polymerization and surface appearance of NP and oil impregnated pressboards (OP) during thermal aging did not differ significantly. During the aging process, the energy level of pressboard surface traps shifted first towards the shallow and then gradually towards the deep. During all the aging stages, the surface flashover voltage of NP was always higher or close to that of OP. The mechanism of TiO2 nanoparticles improving the breakdown and surface flashover characteristics of oil–paper insulation during thermal aging is discussed from the perspective of water molecules and aging by‐products adsorption and introduction of shallow traps by nanoparticles.
Diabetes prediction using machine learning and explainable AI techniques
Authors: Tasin Isfafuzzaman , Nabil Tansin Ullah , Islam Sanjida , Khan Riasat 
Published: December 2022

AbstractGlobally, diabetes affects 537 million people, making it the deadliest and the most common non‐communicable disease. Many factors can cause a person to get affected by diabetes, like excessive body weight, abnormal cholesterol level, family history, physical inactivity, bad food habit etc. Increased urination is one of the most common symptoms of this disease. People with diabetes for a long time can get several complications like heart disorder, kidney disease, nerve damage, diabetic retinopathy etc. But its risk can be reduced if it is predicted early. In this paper, an automatic diabetes prediction system has been developed using a private dataset of female patients in Bangladesh and various machine learning techniques. The authors used the Pima Indian diabetes dataset and collected additional samples from 203 individuals from a local textile factory in Bangladesh. Feature selection algorithm mutual information has been applied in this work. A semi‐supervised model with extreme gradient boosting has been utilized to predict the insulin features of the private dataset. SMOTE and ADASYN approaches have been employed to manage the class imbalance problem. The authors used machine learning classification methods, that is, decision tree, SVM, Random Forest, Logistic Regression, KNN, and various ensemble techniques, to determine which algorithm produces the best prediction results. After training on and testing all the classification models, the proposed system provided the best result in the XGBoost classifier with the ADASYN approach with 81% accuracy, 0.81 F1 coefficient and AUC of 0.84. Furthermore, the domain adaptation method has been implemented to demonstrate the versatility of the proposed system. The explainable AI approach with LIME and SHAP frameworks is implemented to understand how the model predicts the final results. Finally, a website framework and an Android smartphone application have been developed to input various features and predict diabetes instantaneously. The private dataset of female Bangladeshi patients and programming codes are available at the following link: https://github.com/tansin-nabil/Diabetes-Prediction-Using-Machine-Learning.
Single‐phase common ground type 5L inverter with reduced capacitor voltage stress for photovoltaic applications
Authors: Pandurangan Gopinath Narayanan , Krishnasamy Vijayakumar , Ali Jagabar Sathik Mohamed , Mahmood Farhad Muhsin , Almakhles Dhafer 
Published: December 2022

AbstractIn recent years, common ground (CG)‐type transformerless (TL) inverters have been paid more attention. However, the existing topologies have more voltage stress on either switch or on capacitor voltage or in both. This article proposes a novel five‐level TL inverter topology with a CG type and a voltage stress reduction on power components. The proposed topology offers less component count and a simple structure. Here, the quasi‐soft charging (QSC) technique is proposed to minimize the high charging current during the capacitor charge. Since the proposed topology is the family of switched capacitors (SC), the determination of SC and QSC is presented. A detailed comparison of the proposed topology with other recent five‐level topologies is presented, and the proposed topology's advantage is highlighted. Further, the performance of the proposed topology is verified in simulation software and verified in a scale‐down hardware setup developed for 400 W. The various experimental results are presented to ensure the feasibility of the proposed topology.
An experimental realization of improved grid integrated multilevel inverter based PV systems with MPPT
Authors: Priyadarshi Neeraj , Bhaskar Mahajan Sagar , Hussien Mohamed G. , Khan Baseem , Hassan Abd El‐Wahab 
Published: December 2022

AbstractThis research work explains a sliding mode controller‐based multilevel inverter for grid integrated photovoltaic power structure. A gravitational search algorithm based on maximum power point tracking has also been discussed for optimal photovoltaic power achievement. Moreover, a two‐stage cascaded interleaved boost converter has been employed, which provides minimised voltage/current ripple, higher current/power density, better efficacy, faster response, and reduced electromagnetic interference as major benefits. The multilevel inverter's proposed constant frequency‐based sliding mode controller provides better transient responses, high photovoltaic power tracking, and good robust behaviour under changing operating conditions. The proposed sliding mode controller has a fixed frequency operation and has low reactivity to parameter divergence. The proposed multilevel diode clamped inverter for grid integrated photovoltaic system provides a reduced number of components and a power rating. The gravitational search algorithm‐based swarm technique as a maximum power point tracking provides high convergence velocity, better accuracy, and good local search capability. The experimentation was carried out to implement control algorithms using the dSPACE platform. The designed multilevel inverter system with proposed control provides average 89.2% inverter efficiency under variation of sun insolations.
The outburst of the changing-look AGN IRAS 23226-3843 in 2019
Authors: Kollatschny W. , Grupe D. , Parker M. L. , Ochmann M. W. , Schartel N. , Romero-Colmenero E. , Winkler H. , Komossa S. , Famula P. , Probst M. A. , Santos-Lleo M. 
Published: December 2022

Aims. IRAS 23226-3843 has previously been classified as a changing-look active galactic nucleus (AGN) based on observations taken in the 1990s in comparison to X-ray data (Swift, XMM-Newton, and NuSTAR) and optical spectra taken after a very strong X-ray decline in 2017. In 2019, Swift observations revealed a strong rebrightening in X-ray and UV fluxes. We aimed to study this outburst in greater detail.
Methods. We took follow-up Swift, XMM-Newton, and NuSTAR observations of IRAS 23226-3843 together with optical spectra (SALT and SAAO 1.9 m telescope) from 2019 until 2021.
Results. IRAS 23226-3843 showed a strong X-ray and optical outburst in 2019. It varied in the X-ray continuum by a factor of 5 and in the optical continuum by a factor of 1.6 within two months. This corresponds to a factor of 3 after correction for the host galaxy contribution. The Balmer and Fe II emission-line intensities showed comparable variability amplitudes during the outburst in 2019. The Hα emission-line profiles of IRAS 23226-3843 changed from a blue-peaked profile in the years 1997 and 1999 to a broad double-peaked profile in 2017 and 2019. However, there were no major profile variations in the extremely broad double-peaked profiles despite the strong intensity variations in 2019. One year after the outburst, IRAS 23226-3843 changed its optical spectral type and became a Seyfert type 2 object in 2020. Blue outflow components are present in the optical Balmer lines and in the Fe band in the X-rays. A deep broadband XMM-Newton/NuSTAR spectrum was taken during IRAS 23226-3843’s maximum state in 2019. This spectrum is qualitatively very similar to a spectrum taken in 2017, but by a factor of 10 higher. The soft X-ray band appears featureless. The soft excess is well modeled with a Comptonization model. A broadband fit with a power-law continuum, Comptonized soft excess, and Galactic absorption gives a good fit to the combined EPIC-pn and NuSTAR spectrum. In addition, we see a complex and broadened Fe K emission-line profile in the X-rays. The changing-look character in IRAS 23226-3843 is most probably caused by changes in the accretion rate – based on the short-term variations on timescales of weeks to months.
Clouds form on the hot Saturn JWST ERO target WASP-96b
Authors: Samra D. , Helling Ch. , Chubb K. L. , Min M. , Carone L. , Schneider A. D. 
Published: December 2022

Context. WASP-96b is a hot Saturn exoplanet, with an equilibrium temperature of ≈1300 K. This is well within the regime of thermo-dynamically expected extensive cloud formation. Prior observations with Hubble/WFC3, Spitzer/IRAC, and VLT/FORS2 have been combined into a single spectrum for which retrievals suggest a cold but cloud-free atmosphere. Recently, the planet was observed with the James Webb Space Telescope (JWST) as part of the Early Release Observations (ERO).
Aims. The formation of clouds in the atmosphere of exoplanet WASP-96b is explored.
Methods. One-dimensional profiles were extracted from the 3D GCM expeRT/MITgcm results and used as input for a kinetic, non-equilibrium model to study the formation of mineral cloud particles of mixed composition. The ARCiS retrieval framework was applied to the pre-JWST WASP-96b transit spectrum to investigate the apparent contradiction between cloudy models and assumed cloud-free transit spectrum.
Results. Clouds are predicted to be ubiquitous throughout the atmosphere of WASP-96b. Silicate materials contribute between 40% and 90% cloud particle volume, which means that metal oxides also contribute with up to 40% cloud particle volume in the low-pressure regimes that affect spectra. We explore how these cloudy models match currently available transit spectra. Reduced vertical mixing acts to settle clouds to deeper in the atmosphere, and an increased cloud particle porosity reduces the opacity of clouds in the near-IR and optical region. These two effects allow for clearer molecular features to be observed while still allowing clouds to be in the atmosphere.
Conclusions. The atmosphere of WASP-96b is unlikely to be cloud free. Retrievals of HST, Spitzer, and VLT spectra also show that multiple cloudy solutions reproduce the data. JWST observations will be affected by clouds, where the cloud top pressure varies by an order of magnitude within even the NIRISS wavelength range. The long-wavelength end of NIRSpec and the short-wavelength end of MIRI may probe atmospheric asymmetries between the limbs of the terminator on WASP-96b.
Diagnostik von Nierenerkrankungen bei Europäischen Landschildkröten (Testudo spp.)
Authors: Lehmann Verena , Kölle Petra 
Published: December 2022

ZusammenfassungDie Diagnostik einer Nierenerkrankung bei Landschildkröten ist nur anhand der klinischen Allgemeinuntersuchung durch die Ausbildung von unspezifischen Krankheitssymptomen nur sehr eingeschränkt möglich und es bedarf umfangreicher zusätzlicher Untersuchungen, um die Diagnose abzusichern. Neben Blut- und Urinuntersuchung eignen sich bildgebende Verfahren wie Röntgen, Computertomographie und MRT zur Darstellung des Skelett- und Organsystems, während im Rahmen einer endoskopischen Untersuchung zusätzlich Proben entnommen werden können. Es zeigen sich artspezifisch deutliche Unterschiede in Bezug auf die Referenzwerte der Laborparameter, die teils erheblich durch Umwelteinflüsse, die Jahreszeiten oder auch das Geschlecht beeinflusst werden. Auch lässt sich feststellen, dass beispielsweise Nierenerkrankungen bei in Menschenobhut gehaltenen Landschildkröten bei Diagnosestellung meist sehr weit fortgeschrittenen sind, da diese Tiere, wie Reptilien generell, erst sehr spät im Krankheitsverlauf klinische Symptome zeigen. Jährliche Kontrollen bei einem auf Reptilien spezialisierten Tierarzt können dazu beitragen, Erkrankungen frühzeitig zu erkennen.