Miracle-dz/UniFAR-FTUs huggingface dataset:
DIRECT SOLUTION OF THE POISSON EQUATION FOR BIOMOLECULES OF ARBITRARY SHAPE, POLARIZABILITY DENSITY, AND CHARGE DISTRIBUTION

Classical electrostatics has been used with considerable success to explain the dielectric, optical, and energetic properties of molecular systems. Three general approaches have been used for problems where polarizability effects are important. I n the first, the molecule and its environment are represented by dielectric media that may contain embedded charges or dipoles. Polarization of the dielectric by a field corresponds to the nuclear and electronic displacements. ’-* I n the second, the diffuse polarizability of the electron cloud is replaced by a set of point polarizabilities, usually situated at atomic centers. The throughspace interactions of the induced point dipoles then explain the molecular properties3 I n the third, the bonds of a molecule are assigned polarizability tensors that are often assumed additive for the purpose of predicting molecular properties. I t is somewhat surprising that this approach has been found useful, since it neglects the important through-space interaction^. ^ I n spite of important successes, there are some serious limitations. Solutions by the first method have been achieved only for simple shapes and uniform dielectric constants. The second method becomes uncertain when the diffuse charge distributions overlap significantly, or when there is significant delocalization of charge. as in double bonds. The classical approach would be expected to apply more rigorously to larger systems such as proteins. However, considerable success has also been achieved at the atomic level, where the neglect of dynamic and quantum effects may be expected to cause errors. The problem of colliding rare gas atoms in an electric field has recently been treated with considerable success by the classical electrostatic f o r m a l i ~ m , ~ and quantum corrections have been considered.6 While a general examination of the validity and limits of the classical model a t the atomic level would be of interest, it is the purpose of the present paper to show that it is now possible to obtain more general solutions by the first method described above. Over the last ten to fifteen years, structural engineers have developed a new technique, the finite element method, for obtaining solutions to partial differential equations with general boundary conditions, material properties, and source distribution. ’The method first came to my attention two years ago. ’ I n the following sections, the Poisson equation will be solved for two types of
A Novel Graph-Based Framework for Classifying Urban Functional Zones with Multisource Data and Human Mobility Patterns

Recent research has shown the advantages of incorporating multisource geospatial data into the classification of urban functional zones (UFZs), particularly remote sensing and social sensing data. However, the effects of combining datasets of varying quality have not been thoroughly analyzed. In addition, human mobility patterns from social sensing data, which capture signals of human activities, are often represented by origin-destination pairs, thus ignoring spatial relationships between UFZs embedded in mobility trajectories. To address the aforementioned issues, this study proposed a graph-based UFZ classification framework that fuses semantic features from high spatial resolution (HSR) remote sensing images, points of interest, and GPS trajectory data. The framework involves three main steps: (1) High-level scene information in HSR remote sensing imageries was extracted through deep neural networks, and multisource semantic embeddings were constructed based on physical features and social sensing features from multiple geospatial data sources; (2) UFZ mobility graph was constructed by spatially joining trajectory information with UFZs to construct topological connections between functional parcel segments; and (3) UFZ segments and multisource semantic features were transformed into nodes and embeddings in the mobility graphs, and subsequently graph-based models were adopted to identify UFZs. The proposed framework was tested on Zhuhai and Singapore datasets. Results indicated that it outperformed traditional classification methods with an overall accuracy of 76.7% and 84.5% for Zhuhai and Singapore datasets, respectively. The proposed framework contributes to literature in heterogeneous data fusion and is generalizable to other UFZ classification scenarios where human mobility patterns play a role.
An SOI-MEMS Acoustic Sensor Based on Optical Grating Interferometer

Capacitive microelectromechanical system (MEMS) microphone in a small package encounters performance limits associated with damping in the air gap between diaphragm and backplate. In this work, we explored an optical-readout technique by fabrication of an optical interferometric acoustic sensor. The designed sensor chip forms a grating interferometer by a diffraction grating integrated backplate and a pressure-sensitive diaphragm. A scalar diffraction theory and a finite-element method have been applied to optimize the sensor parameters. The sensor device was fabricated on a silicon-on-insulator (SOI) wafer using complementary metal–oxide–semiconductor (CMOS) compatible processes. The performance of the sensor was studied using an acoustic testing system. The sensor demonstrates a good linear relationship with applied sound pressure. The frequency response is relatively consistent with a commercial reference microphone for audible range. The signal-to-noise ratio (SNR) of the sensor is about 43 dB at a frequency of 1 kHz. The proposed design shows good potential for high-performance acoustic sensors.
Automatic Generation and Detection Method of LCD Samples Based on Deep Learning

When the deep learning method is applied to the detection of microscopic defects with uneven brightness on the low-contrast LCD surface, due to the imbalance between the positive samples and negative samples when training the deep learning method, we propose a method to automatically generate samples based on a deep generative network model. First, a small number of defect samples are generated through a generative adversarial network to generate an expanded sample data set, and then the samples in these data sets are manually marked to highlight the defect parts, and the mask of the defect image is obtained for Mask R-CNN detection. The experimental results confirm that LCD image samples can be automatically generated by the proposed method, and the experiments on Mask R-CNN also confirm the effectiveness of our proposed method.
Is the Distribution of Mass within Spiral Galaxies a Function of Galaxy Environment

On a obtenu les courbes de rotation de 20 galaxies spirales connues pour leur appartenance a de grands amas. Les types Sa, Sb et Sc sont egalement representes dans les echantillons du champ et des amas. Mais les galaxies des amas ont des courbes de rotation dont l'allure est differente et partant des distributions de la masse de forme differente. Il semble donc que l'allure de la distribution de la masse d'une galaxie spirale soit plus une fonction de l'environnement que du type de Hubble
Practical building of subjective covariance structures for large complicated systems

Summary. In many practical problems it is necessary to specify prior beliefs about large numbers of related quantities. In Bayes linear systems this consists of specifying means, variances and covariances. Likewise standard probabilistic Bayesian approaches often lead to prior representations involving systems of Gaussian unknowns which require similar moment specifications. In practice, the specification of such collections of beliefs may seem daunting to non-specialists if no help or guidance is given. However, such assistance can be provided through the use of structured graphical models and some simple devices to make the task manageable. These ideas are illustrated by some practical examples. In particular, a computer system, designed for sales forecasting in supply chain management, is described. This system includes a graphical interface for building and editing belief specifications.
Diagnostic Ability of Endoscopic Ultrasound-Guided Tissue Acquisition Using 19-Gauge Fine-Needle Biopsy Needle for Abdominal Lesions

Attempts at performing endoscopic ultrasound-guided tissue acquisition (EUS-TA) with a 19G needle are increasing because histological diagnosis and comprehensive genomic profiling are a necessity. However, the diagnostic ability of the 19G fine-needle biopsy (FNB) needle, especially the third-generation FNB needle, is unclear and has been retrospectively reviewed. The 19G TopGain needle was used in 147 patients and 160 lesions between September 2020 and December 2021. The technical success rate of the biopsies was 99.4% (159/160). The early adverse event rate was 4.1% (6/147), and moderate or severe adverse event rate occurrence was 2.0% (3/147). The sensitivity, specificity, and accuracy of the 19G TopGain needle for 157 lesions with a confirmed diagnosis were 96.7%, 100%, and 96.8%, respectively. Rescue EUS-TA using the 19G TopGain needle was performed for nine lesions, and a successful diagnosis was made in six of these lesions (66.7%). The diagnostic ability of EUS-TA using the third-generation 19G TopGain needle was favorable. However, the use of 19G FNB needles may increase adverse events. Therefore, EUS-TA with a 19G FNB needle is mainly indicated in lesions where comprehensive genomic profiling may be necessary or the diagnosis could not be determined via EUS-TA using the 22G needle.
Deep machine learning in bridge structures durability analysis

According to Eurocode 0 structural durability is next to ultimate and serviceability one of the basic criteria in the structural design process. This article discusses the subject of concrete cracks observation in bridge structures, as one of the factors determining their durability. The durability of bridge structures is important due to both social, economic aspects and also the defense aspects of countries. Cracking of the reinforced concrete structures is a natural effect in concrete. The aim in the design and construction of structures is not to prevent the formation of cracks, but to limit their width to acceptable values. At the same time, there is a need for structure tests that allow for non-contact, fast measurements and algorithms that allow for efficient analysis of large amounts of measurement data. Deep machine learning algorithms can be used here. They can be used to analyse data which are acquired by means of photogrammetric methods (especially helpful during construction to inventory concealed works). Moreover, they can also be applied to standard data acquisition methods, consisting in photographing objects damage during works acceptance or periodic inspections. This paper discusses the application of deep machine learning to assess the condition of bridge structures based on photographs of object damage. The use of this method makes it possible to observe the rate and extent of damage development. Consequently, this method makes it possible to predict the development of damage in time and space in order to prevent failures and take structures out of service.
Analytical investigation of the flattening effect: The reactive power balance rule

McIntyre et al. [J. Acoust. Soc. Am. 74, 1325–1345 (1983)], through comprehensive time‐domain analyses of the bowed string mechanisms and various numerical simulations, have first pointed out that the hysteretical character of the sticking–slipping process necessarily induces, under certain end conditions, a flattening effect (the note plays flat as the bow pressure exceeds a given level). Taking advantage of a frequency‐domain analysis, it is demonstrated that the area of the hysteresis cycle has an analytical relation to various physical parameters of the bowed string, leading to the concept of reactive power. The flattening effect appears as a consequence of this relation. Another possible consequence is the observed dependence of the spectrum and intensity of the string vibration on the bow pressing force. Based on realistic assumptions, an algorithm is proposed to connect the flattening effect or the intensity variations to the physical characteristics of the string. Finally, the variations of the fl.
Loudness, Sound Pressure, and Subglottal Pressure in Speech

Three experiments using one speaker and 30 listeners provided correlated data on subglottal pressure, average volume velocity through the glottis, fundamental frequency, effective sound pressure in front of the speaker, and judgments of loudness. Experiment 1: In 12 repetitions each of bee, bay, bar, bore, and boo spoken at various loudnesses, it was found that in the middle range (subglottal pressure) ∝ (effective sound pressure)0.6; and the level of the vowel in bar was about 5 dB greater than in bee or boo produced with the same subglottal pressure. Experiment 2: In 32 repetitions of the vowel /ɑ/ uttered at various loudnesses with the pitch uncontrolled, it was found that an increase of subglottal pressure of about 6.5 cm aq accompanied an increase in frequency of half an octave; and to a first approximation (rate of flow) ∝ (subglottal pressure). It follows that (rate of work done on the air) ∝ (subglottal pressure)2 ∝ (effective sound pressure)1.2. The exponent 1.2 compares well with the exponent 1.
Testing of Coulomb-Volkov functions

A time-dependent generalization of the Siegert theorem is applied to test the accuracy of the Coulomb-Volkov functions (CVFs) widely used for the description of electron motion in a laser field combined with the Coulomb field of the atomic core. Free-free transitions in the case of arbitrary elliptic polarization of the electromagnetic field are investigated. It is shown that the ratio between the strength of the light wave electric field and its frequency (in atomic units) has crucial importance for estimation of the CVF accuracy.
Body Mass Index and Waist Circumference as Determinants of Hemostatic Factors in Participants of a Population-Based Study

Background: In contrast to studies in patients, an association between obesity and blood coagulation factors has not been established in the population. If confirmed it could become a target for primary prevention. Objective: To investigate the relationship between Body Mass Index (BMI) and waist circumference (WC) with plasma concentrations of antithrombin III, D-dimers, fibrinogen D, protein S, factor VIII, activated partial thromboplastin time (aPTT), quick value, and international normalized ratio (INR) in the general population. Materials and Methods: Participants of the Cooperative Health Research in the Region of Augsburg (KORA) S4 study who took part in the KORA Fit follow-up (2018–2019, aged 54–74 years) examination were eligible. Citrate plasma samples were collected in fasted participants. After the exclusion of participants with anticoagulative treatment, 776 participants (420 women and 356 men) with analytic data on hemostatic factors were included in the present analysis. Linear regression models were used to explore the association between BMI or WC with hemostatic markers, adjusted for sex, age, alcohol consumption, education, smoking status, and physical activity. In a second model, additional adjustments were made for the prevalence of stroke, hypertension, myocardial infarction, serum non-HDL cholesterol, and serum triglycerides. Results: In the multivariable models (with or without health conditions), significant positive associations with BMI were obtained for plasma concentrations of D-dimers, factor VIII, fibrinogen D, protein S, and quick value, while INR and antithrombin III were inversely associated. Similar to BMI, WC was significantly associated with all hemostatic factors, except for aPTT. Conclusion: In this population-based study, both increasing BMI and WC affect the blood coagulation system. Thus, modification of a prothrombotic coagulation profile emerged as a potential target for primary prevention in obese subjects.
Application of Compact Folded-Arms Square Open-Loop Resonator to Bandpass Filter Design

Folded-arms square open-loop resonator (FASOLR) is a variant of the conventional microstrip square open-loop resonator (SOLR) that facilitates further device size miniaturization by having the two arms of the conventional SOLR folded inwards. This paper highlights the benefits of this brand of compact SOLR by implementing a five-pole Chebyshev bandpass filter (BPF) using compact FASOLR. The test BPF is presented, with centre frequency of 2.2 GHz, fractional bandwidth of 10%, passband ripple of 0.04321 dB, and return loss of 20 dB. The design is implemented on a Rogers RT/Duroid 6010LM substrate with a dielectric constant of 10.7 and thickness of 1.27 mm. The filter device is manufactured and characterised, with the experimentation results being used to justify the simulation results. The presented measurement and electromagnetic (EM) simulation results demonstrate a good match. The EM simulation responses achieve a minimum insertion loss of 0.8 dB and a very good channel return loss of 22.6 dB. The measurement results, on the other hand, show a minimum insertion loss of 0.9 dB and a return loss of better than 19.2 dB. The filter component has a footprint of 36.08 mm by 6.74 mm (that is, 0.26 λg × 0.05 λg), with λg indicating the guided wavelength for the 50 Ohm microstrip line impedance at the centre frequency of the proposed fifth-order bandpass filter.
Vortex ring breakdown induced by topographic forcing

Detailed measurements of the vortex breakdown within a strongly forced impinging jet are presented, with the goal of studying the effects of a small topographic disturbance on the breakdown and turbulence structure. This work is related to an ongoing effort to understand the dynamics of sediment suspension within a landing rotorcraft where a mobile boundary is subject to rapid erosion and deposition. The current work compares the results of a uniform surface to that of a small radial fence placed upstream of the vortex impingement location. The result is a dramatic increase in the coherence of the three-dimensional looping exhibited by the secondary vortex, leading to a more organized and strongly perturbed mean flow. Specifically, a triple decomposition of the velocity fluctuations indicates a very intense periodic stress in the vicinity of the impingement site, followed by a significant decay. Conversely, the random component of the fluctuating stresses gradually increases to modest levels as the coherent contributions decrease, eventually becoming greater than the coherent stress. The fence produces a bifurcation in the flow through the perturbation of the secondary vortex, which in turn creates a high-and low-speed streak on either side of the fence. The subsequent dynamics leads to increased fluctuating stress in the high-speed region, and a dramatically lower stress in the low-speed region, favoring preferential erosion on either side of the topographic disturbance.
Optimisation of Raman spectral processing for classification of radiotherapeutic toxicity

Severe radiation toxicity can continue years after the completion of radiotherapy for prostate cancer patients. Currently, it is impossible to predict before treatment which patients will experience these long-term side effects. New approaches based on vibrational spectroscopy have advantages over lymphocyte and genomic assays in terms of minimal sample preparation, speed and cost. A high throughput method has been developed to measure Raman spectra from liquid plasma in a cover glass bottomed 96 well plate. However, the Raman spectra can show contributions from glass and water. The current study aims to optimise pre-processing steps to improve classification performance.
Pointwise in frequency performance weight optimization in µ‐synthesis

A conceptually different approach to the µ‐synthesis robust performance problem is proposed in this article. The optimization problem posed maximizes the performance weights with respect to a suitable cost function that captures the desired closed‐loop performance. This maximization of performance weights is limited by the fact that there must exist some internally stabilizing controller that guarantees robust performance with respect to these maximized weights. Thus, performance weights and a controller that achieves an optimized level of robust performance are synthesized together by one algorithm in a systematic way. The designer is only required to specify the plant set and an optimization directionality. This directionality only appears in the cost function and reflects the desired closed‐loop properties in particular frequency regions. It is pointed out that choosing this directionality is much easier than choosing the performance weights directly. Correspondingly, this approach greatly simplifies the often long and tedious process of designing ‘good’ performance weights directly and gives an indication of what is the achievable performance. A pointwise in frequency solution to the posed optimization problem is also developed in this article. Copyright © 2005 John Wiley & Sons, Ltd.
Review on Hydrogel-Based Flexible Supercapacitors for Wearable Applications

Smart hydrogels with high electrical conductivity, which can be a real source of power while also collecting and storing the diverse sources of energy with ultrahigh stretchability, strong self-healability, low-temperature tolerance, and excellent mechanical properties, are great value for tailored wearable cloths. Considerable effort has been dedicated in both scientific and technological developments of electroconductive hydrogels for supercapacitor applications in the past few decades. The key to realize those functionalities depends on the processing of hydrogels with desirable electrochemical properties. The various hydrogel materials with such properties are now emerging and investigated by various scholars. The last decade has witnessed the development of high-performance supercapacitors using hydrogels. Here, in this review, the current status of different hydrogels for the production of flexible supercapacitors has been discussed. The electrochemical properties such as capacitance, energy density and cycling ability has been given attention. Diverse hydrogels, with their composites such as carbon-based hydrogels, cellulose-based hydrogels, conductive-polymer-based hydrogels and other hydrogels with excellent electromechanical properties are summarized. One could argue that hydrogels have played a central, starring role for the assembly of flexible supercapacitors for energy storage applications. This work stresses the importance of producing flexible supercapacitors for wearable clothing applications and the current challenges of hydrogel-based supercapacitors. The results of the review depicted that hydrogels are the next materials for the production of the flexible supercapacitor in a more sustainable way.
A Tapering Method in the Construction of Covariance Regularization

Estimation of Population covariance matrix from samples is important in a wide range of areas of statistical analysis. In the estimation, the sample covariance matrix, which is the most natural and standard estimator, often performs badly. With the collection of large high-dimensional data in scientific investigation, the related covariance matrix becomes complicated to deal with. Therefore, for the convenience in computing and analyzing, we need to simplify the covariance matrix. This method is referred as regularization. In this paper, we will consider a proof for a construction of covariance regularization by tapering.