Miracle-dz/UniFAR-FTUs huggingface dataset:
Distinct Seasonality in Aerosol Responses to Emission Control Over Northern China

Despite intensive research exploring how aerosols respond to emission control over Northern China, efforts mostly focus on the environmental benefit, especially in winter. Here we found that unlike the most substantial PM2.5 concentration reduction in winter, aerosol optical depth (AOD) declines more than 2 times faster in summer, causing an increase in aerosol radiative effects of 1.2 (5.7)Wm−2 on all‐sky (clear‐sky) conditions over 2013–2019 and largely shaping the climate impact. Low‐level aerosols are shown to be the prime contributor under the synergetic effects of aerosol composition and ambient relative humidity (RH). The dominance of the highly hygroscopic sulfate combined with high RH enables a strong extinction efficiency of the reduced summertime aerosols, while the insignificant AOD decline in wintertime result from the dominance of organic aerosols with weak hygroscopicity, and is further offset by the increased frequencies of extremely high RH. We show the environmental and climatic responses of aerosols to emission control exhibit distinctively different seasonality.
A Purity Criterion for Pairs of Linear Transformations

In connection with the study of perturbation methods for differential eigenvalue problems, Aronszajn put forth a theory of systems (X, Y; A, B) consisting of a pair of linear transformations A, B:X → Y (see [1]; cf. also [2]). Here X and Y are complex vector spaces, possibly of infinite dimension. The algebraic aspects of this theory, where no restrictions of topological nature are imposed, where developed in [3] and [5]. We hasten to point out that the category of C 2-systems (definition in § 1) in which this algebraic investigation takes place is equivalent to the category of all right modules over the ring of matrices of the form
Design of a Dual-Band Metasurface Cross-Polarization Converter for Cancer Detection in the Terahertz Band

We present the design of a metasurface-based, cross-polarization converter as a sensor for label-free detection of cancerous cells in the terahertz (THz) band. The device is designed to work on the principle of refractive index (RI) sensing wherein the frequency shift of the maximum polarization conversion peak in the presence of the target analyte is measured. This shift is proportional to the RI difference between healthy and cancerous cells thereby enabling classification with high sensitivity. Our metasurface is designed to support two resonances which significantly reduces the measurement errors, thereby increasing the detection accuracy. We report sensitivities of 155 and 350 GHz/RIU at the first and second resonant frequencies, respectively. The proposed structure is simulated using a finite element method (FEM) and validated with an equivalent circuit model.
Continuous Stereo Matching using Local Expansion Moves

We present an accurate and efficient stereo matching method using local expansion moves, a new move making scheme using graph cuts. The local expansion moves are presented as many alpha-expansions defined for small grid regions. The local expansion moves extend the traditional expansion moves by two ways: localization and spatial propagation. By localization, we use different candidate alpha-labels according to the locations of local alpha-expansions. By spatial propagation, we design our local alpha-expansions to propagate currently assigned labels for nearby regions. With this localization and spatial propagation, our method can efficiently infer Markov random field models with a huge or continuous label space using a randomized search scheme. Our local expansion move method has several advantages over previous approaches that are based on fusion moves or belief propagation; it produces submodular moves deriving a subproblem optimality; it helps find good, smooth, piecewise linear disparity maps; it is suitable for parallelization; it can use cost-volume filtering techniques for accelerating the matching cost computations. Our method is evaluated using the Middlebury stereo benchmark and shown to have the best performance in sub-pixel accuracy.
The Involvement of Neutrophil in the Immune Dysfunction Associated with BVDV Infection

Bovine viral diarrhea virus (BVDV) induces immune dysfunction that often results in a secondary bacterial infection in the infected animals. The underlying mechanism of BVDV-induced immune dysfunction is not well understood. The role of BVDV-infected macrophage-secreted factors was investigated. BVDV-infected monocyte-derived macrophage (MDM) supernatants down-regulated the expression of neutrophil L-selectin and CD18. Regardless of the biotype, phagocytic activity and oxidative burst were downregulated by BVDV-infected MDM supernatants. However, only supernatants from cytopathic (cp) BVDV down-regulated nitric oxide production and neutrophil extracellular traps (NET) induction. Our data suggested that BVDV-induced macrophage-secreted factors caused immune dysfunction in neutrophils. Unlike lymphocyte depletion, the negative impact on neutrophils seems to be specific to cp BVDV biotype. Interestingly the majority of modified live BVDV vaccines are based on cp strain of BVDV.
Compensation of Hot Carrier Degradation Enabled by Forward Back Bias in π-GAA-π MOSFET

Forward back biasing (FBB) technique is considered as a potential solution for aging compensation in silicon on insulator (SOI) MOSFET. However, traditional SOI devices under FBB would suffer from extra off-state leakage current <inline-formula> <tex-math notation="LaTeX">$(I_{\mathrm{ off}})$ </tex-math></inline-formula> and undesirable static power consumption. In this work, we studied the hot carrier degradation and FBB compensation in <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula>-GAA-<inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula> MOSFET. With the unique hybrid gate structure, the performance degradation is found to be less severe than pure <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula> gate device; and moreover it can be partially recovered by FBB without the sacrifice of <inline-formula> <tex-math notation="LaTeX">$I_{\mathrm{ off}}$ </tex-math></inline-formula>. The presence of <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula> gates offer the back gate tunability that is not provided by pure GAA gate; while the GAA gate component can effectively prevent the impact of FBB from affecting the surface potential. Our findings in <inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula>-GAA-<inline-formula> <tex-math notation="LaTeX">$\pi $ </tex-math></inline-formula> hybrid gate MOSFETs would be beneficial for device reliability improvement.
Multifractal spectrum features based classification method for aircraft

The multifractal spectrum characteristics of aircraft echoes from low-resolution radars offer a fine description of dynamic characteristics which induce the echo structure; therefore they can provide a new way for aircraft target classification and recognition with low-resolution radars. On basis of introducing the elementary theory of multifractal, the paper analyzed the multifractal spectrum characteristics of aircraft echoes along with the extraction method of their multifractal spectrum features by means of the multifractal analysis of measures, and proposed the classification method for different types of aircraft targets from the viewpoint of pattern classification. The results of classification experiments with real recorded echo data showed the multifractal-spectrum-feature-based classification method can classify different types of aircraft effectively, thus. the defined characteristic parameters could be used as effective features for aircraft target classification.
A STRATEGY TO ACCELERATE THE NUMERICAL INTEGRATION IN THE DYNAMIC SIMULATION OF MULTIBODY SYSTEMS

This paper presents a multi-index variable time step method for the integration of the equations of motion of constrained multibody systems in descriptor form. The basis of the method is the augmented Lagrangian formulation with projections in index-3 and index-1. The method takes advantage of the better performance of the index-3 formulation for large time steps and of the stability of the index-1 for low time steps, and automatically switches from one method to the other depending on the required accuracy and values of the time step. The variable time stepping is accomplished through the use of an integral of motion, which in the case of conservative systems becomes the total energy. The error introduced by the numerical integrator in the integral of motion during consecutive time steps provides a good measure of the local integration error, and permits a simple and reliable strategy for varying the time step. Overall, the method is efficient and powerful; it is suitable for stiff and non-stiff systems, robust for all time step sizes, and it works for singular configurations, redundant constraints and topology changes. Also, the constraints in positions, velocities and accelerations are satisfied during the simulation process. The method is robust in the sense that becomes more accurate as the time step size decreases.
A Survey on IOT Based Air Pollution Monitoring System

Poor air quality is the fundamental problem that both advanced and emerging nations must cope with. Health problems have been becoming worse more quickly, mainly in urban regions of emerging nations where modernization and a rise in the number of cars lead to the emission of various gaseous pollutants. In addition to more serious illnesses including bronchitis, heart problems, influenza, pulmonary, and respiratory problems, pollution can also cause temporary anaphylactic reactions like throat, vision, and nostril discomfort. So, there is a necessity to control air pollution. In order to take necessary actions monitoring the air quality is major task. Conventional systems are expensive and the data is not accurate. IOT (Internet of Things) is currently becoming more and more popular, and standards are about to follow. Before suggesting a solution to deliver ambiance surveillance at a reduced cost and size, the objective of this study is to analyse the existing research on IOT-based environmental monitoring.
Impact of socialization on the possibility to conduct behavioral tests in sheep

The aim of the study was to assess the impact of socialization with humans on the possibility to conduct tests evaluating problem-solving in sheep. The research included 30 Świniarka sheep aged from 2 to 8 years. The sheep were kept in the barn-pasture system. The observations included three trials carried out on three consecutive days for each sheep. The behavior of the sheep, i.e. exploration and approach to equipment elements of the test arena, was analyzed. The experiment was conducted on groups of sheep with low (G1) and high (G2) levels of socialization. The study showed that the test environment was challenging for the G1 sheep, so they were unable to complete the task successfully.
Hybrid deep neural network for automatic detection of COVID‐19 using chest x‐ray images

The 2019 coronavirus (COVID‐19), started in China, spreads rapidly around the entire world. In automated medical imagery diagnostic technique, due to presence of noise in medical images and use of single pre‐trained model on low quality images, the existing deep network models cannot provide the optimal results with better accuracy. Hence, hybrid deep learning model of Xception model & Resnet50V2 model is proposed in this paper. This study suggests classifying X‐ray images into three categories namely, normal, bacterial/viral infections and Covid positive. It utilizes CLAHE & BM3D techniques to improve visual clarity and reduce noise. Transfer learning method with variety of pre‐trained models such as ResNet‐50, Inception V3, VGG‐16, VGG‐19, ResNet50V2, and Xception are used for better feature extraction and Chest X‐ray image classification. The overfitting issue were resolved using K‐fold cross validation. The proposed hybrid deep learning model results high accuracy of 97.8% which is better than existing techniques.
State-of-the-Art Passive Beam-Steering Antenna Technologies: Challenges and Capabilities

This article reviews the latest developments of beam steering antennas that are entirely passive to realize interference-free, power-efficient, and highly secured end-to-end wireless communication. We briefly introduce metamaterials and metasurfaces, a timely advanced topic in electromagnetics (EM) and optics. Mathematical formulas associated with the design of beam steering metasurfaces have been numerically explained. In addition, reflect and transmit array antennas are also discussed for an in-depth understanding of beam scanning principles in elevation and azimuth planes. We then provide intuitive design examples and discuss three broad classes of the latest beam scanning antenna systems, namely 1) Reflectarrays (RAs); 2) Transmitarrays (TAs); and 3) Near-Field Meta-Steering (NFMS) antennas that are available in up-to-date literature. The third category’s unprecedented scanning performance and aesthetically compact size are elucidated compared to previous antenna systems, such as reflector dishes or large phased arrays. Alongside the working principles, the trade-offs for the scanning techniques, operation, and physical size of each antenna type are also discussed. Towards the end, an evaluative conclusion with a comparative discussion on the beam-steering antenna systems is provided. Future research directions considering mass-market demands are also indicated.
The Mathematical Model and the Optimal Solution of Emergency Evacuation Problem in Densely Populated Places

The principal contradiction in the process of crowd dispersal is analyzed and a nonlinear programming model is set up based on the analog map of audience seats and the evacuation routes distribution in densely populated places,also focusing on the main problem of the formulation on emergency evacuation program.After changed it into integer Linear Programming, the solution is got using Branch and bound method with the lingo software.The optimal solution of the model provides basis for setting up emergency evacuation program of simple layout venue.
A Novel Liquid Water Content Retrieval Method Based on Mass Absorption for Single-Wavelength Cloud Radar

Low-level clouds (LLCs), mainly composed of liquid water droplets, cool the climate system by strongly reflecting solar radiation back to space and thus play an important role in the Earth energy budget. However, the LLC properties and their radiative effects are poorly represented in climate models, leading to the largest source of uncertainty in climate prediction. Liquid water content (LWC) is a key property of LLC determining cloud extinction characteristics and is a fundamental parameter in the radiative transfer model. To improve the understanding of LWC properties, algorithms have been proposed to retrieve LWC based on millimeter-wavelength radar. However, the traditional retrieval relies on preconstructed empirical relationship between reflectivity and LWC and has noticeable limitations. In particular, the retrieval uncertainty is strongly dependent on the assumed particle size distribution, the existence of drizzle particle, and on the accuracy of reflectivity measurement. In this study, we develop a new self-consistent algorithm to retrieve LWC by constraining radar reflectivity factor and attenuation in the whole liquid cloud layer. A relationship between the radar measured reflectivity, LWC, and intrinsic reflectivity is first constructed based on the radiative transfer theory under the Rayleigh scattering regime. A nonlinear least-square regression technique is then applied to derive the optimal parameters in the retrieval equations to obtain the LWC. Comparison with the microwave radiometer (MWR) derived liquid water path (LWP) indicates that our proposed method retrieves more accurate LWC products than that from the traditional empirical algorithms.
Effluent water quality prediction method based on no-inflected point neural network

In practice, the effluent quality is the most important indicator to measure the performance of wastewater treatment. However, most existing sensing technology are difficult to maintain the real-time accurate of online monitoring. In his paper, a novel no-inflection point neural network (NI-BP) with adaptive learning rate is proposed for wastewater quality indicators prediction. The proposed algorithm updates the weight parameters by an adaptive learning rate method when some inflection points are detected, it can increase the weight iteration step size and make the network converge quickly. In the simulation examples, the data from Benchmark simulation model NO.1 (BSM1) are used to demonstrate the effectiveness of the proposed method. The results show that the proposed NI-BP can significantly accelerate the model training efficiency and the prediction accuracy, simultaneously.
Existence of global solutions of initial value problem for nonlinear integro -differential equations of mixed type in Banach spaces

In this paper,by the use of a new comparsion result and Mnch fixed point theorem, the existence of global solutions of initial value problem for nonlinear integro differential equations of mixed type in Banach spaces is investigated.As an application of our result,the existence of global solutions for two classes of third order mixed boundary value problem is obtained.
A Study About the Impact of Rewards on Student's Engagement with the Flipped Classroom Methodology

This work describes an incremental design of a course that implements the flipped classroom methodology. The last phase of this implementation was to include rewards based on self-evaluation tests that would impact the students' grades. This should foster students' engagement with the learning methodology. In this work, a deep analysis of the impact of the reward is performed. The analysis of the use of the out-class materials shows that the students' pace does not correspond to the flipped classroom methodology. The students' behaviour is more focused on achieving rewards rather than preparing in-class activities with out-class materials. It is hypothesized that, the main reasons for these behaviours could be that, on the one hand, since the reward is considered by students as another item of the course grade, they work to get the reward. On the other hand, students do not want to change their study methodology because getting involved in the flipped methodology requires from them a significant effort.
The role of phonology-to-orthography consistency in predicting the degree of pupil dilation induced in processing reduced and unreduced speech

Abstract The relationship between the ways in which words are pronounced and spelled has been shown to affect spoken word processing, and a consistent relationship between pronunciation and spelling has been reported as a possible cause of unreduced pronunciations being easier to process than reduced counterparts although reduced pronunciations occur more frequently. In the present study, we investigate the effect of pronunciation-to-spelling consistency for reduced and unreduced pronunciations in L1 and L2 listeners of a logographic language. More precisely, we compare L1 and L2 Japanese listeners to probe whether they use orthographic information differently when processing reduced and unreduced speech. Using pupillometry, the current study provides evidence that extends the hypothesis about the role of orthography in the processing of reduced speech. Orthographic realization matters in processing for L1 and L2 advanced listeners. More specifically, how consistent the orthographic realization is with its phonological form (phonology-to-orthography consistency) modulates the extent to which reduced pronunciation induces additional processing costs. The results are further discussed in terms of their implications for how listeners process reduced speech and the role of the orthographic form in speech processing.
Molecular gas content in typical L* galaxies at z ∼ 1.5 − 3

Abstract To extend the molecular gas measurements to typical L* star-forming galaxies (SFGs) at z ∼ 1.5 − 3, we have observed CO emission for five strongly-lensed galaxies selected from the Herschel Lensing Survey. The combined sample of our L* SFGs with CO-detected SFGs at z >1 from the literature shows a large spread in star formation efficiency (SFE). We find that this spread in SFE is due to variations of several physical parameters, primarily the specific star formation rate, but also stellar mass and redshift. An increase of the molecular gas fraction (fgas) is observed from z ∼ 0.2 to z ∼ 1.2, followed by a quasi non-evolution toward higher redshifts, as found in earlier studies. We provide the first measure of fgas of z >1 SFGs at the low-stellar mass end between 109.4 < M∗/M⊙ < 109.9, which shows a clear fgas upturn.
Interféromètre optique à faible cohérence couplé aux microrésonateurs optiques en polymère : nouveau protocole de biodétection.

This paper presents a low coherence interferometer as a new interrogation technique of micro-resonator for biological molecules sensing. The spatial responses obtained with PS-OLCI setup are used to evaluate relevant parameters of micro-resonator design like coupling coefficient which allows to discern different coupling configurations. This setup, which is able to provide almost simultaneously the transverse magnetic and electric responses was used to evaluate the spectral performances of micro-resonator. The best performances were obtained on a polymeric racetrack micro-resonator when immersed in deionized water. This micro-resonator displays at 1 527.7 nm a Q factor higher than 38 000 and a finesse of 21. The association of the interferometric set-up and a polymer micro-resonator was allowed the detection of the concentration of glucose in deionized water lower than 5 μg·mL−1 for homogeneous sensing and the surface density of TAMRA Cadaverin lower than 4 ag·mm−2 for surface sensing.
Rebranding Samosir Island As City of Foreign Tourists

Tourism contributes greatly to a developing country as one of the driving sectors of the economy. The government and the management of tourist destinations must consistently improve the quality of tourism in terms of destinations, industries, institutions, and marketing because of the scope of tourism and the movement of millions of people on indirect tourist trips. So far, foreign tourists have become familiar with tourist destinations in Bali and Lombok. However, many tourist destinations in Indonesia have not been maximally introduced, like Samosir Island at Lake Toba Region. In 2016, the Government of Indonesia envisioned making Toba become the Monaco of Asia. This article examines the factors affecting how long visitors from other countries remain when vacationing in Samosir, a popular international travel destination in Indonesia. Using 100 hundred samples of international travelers' empirical modeling is carried out using a quantitative approach through Ordinary Least Squares (OLS) and descriptive analysis. The quality of the accommodations, infrastructure, and rising travel costs contribute to longer travel time for tourists. Although it does not considerably shorten the length of stay in Samosir, rising vacation expenditures in other locations are a bonus for adventurous foreign tourists in Indonesia. Although the appeal of nature and its peace appeal to visitors from abroad, income levels do not greatly raise demand for international visitors to Samosir. As an effort, brand management is needed to improve the image of Samosir Island as the city of foreign tourists in Indonesia.