Miracle-dz/UniFAR-FTUs huggingface dataset:
Land Use Regulations, Housing Supply, and County Eviction Filings

The eviction crisis has attracted significant scholarly attention, but less is known about the links between evictions and policies that promote or impede housing supply. This research uses data from a large time-series, cross-sectional sample of U.S. counties to address this research gap. The results from several linear regression models suggest that restrictive land use regulations increase eviction filing rates, whereas elastic housing supply and inclusionary zoning reduce eviction filing rates. Controls for housing supply constraints also reduce the effect of median rents on eviction filings. Pro-renter state landlord–tenant laws have no effect on eviction filing rates.
Mise en correspondance de formes à niveaux de gris par palpage morphologique

In this paper, we introduce two new morphological transforms for pattern matching in gray scale images. They rely on a profiling approach and are defined in the context of mathematical morphology. The first transform allows to detect all occurrences of a single pattern in an image, which justifies the name SOMP (Single Object Matching using Probing). It is shown to have the properties of a metric and therefore returns a measure of similarity between the search image and the reference pattern. Other properties relative to noise and computation time are highlighted. The second transform MOMP (Multiple Objects Matching using Probing) offers the ability to locate all instances of multiple patterns. It is particularly suited to the detection of objects varying in size and with noisy distortion. Some results are presented for both transforms.
Wideband Blind Calibration for UCA OAM Communication System

This letter presents a wideband blind calibration method for uniform circular array (UCA) orbital angular momentum (OAM) systems without the prior knowledge of the positions and attitudes of the transmit and receive UCAs. The basic idea is to rewrite the maximum-likelihood estimation (MLE) for all parameters as an optimization problem over a Lie group which can represent the positions and attitudes of the UCAs. Then an accelerated Levenberg-Marquardt algorithm is implemented to solve this optimization problem by utilizing the sparsity in the iteration process. Simulation results show that the proposed wideband blind calibration method can estimate the gain/phase errors and the positions and attitudes of the transmit and receive UCAs simultaneously and improve the achievable spectral efficiency of the UCA OAM communication system efficiently.
Impact of Reliability Issues and Process Variability in Neuromorphic Circuits

Device reliability issues like BTI and HCI degrade the circuit performance over the device lifetime. The current work presents the degradation analysis of Axon Hillock (AH) and Simplified Leaky Integrate & Fire (SLIF) neuron circuits. The AH and SLIF circuits are implemented to generate spike output in two frequency ranges (KHz and MHz). We have analysed the impact of BTI, HCI and their combined effect on the circuit performance. Neuron circuits are characterized for their time-zero and aged performance by using spike frequency and spike output ON and OFF durations. 1000 Monte-Carlo (MC) simulations are performed to analyse the impact of time-zero process variability on the spike frequency.
Relationship Between Typical Defects of Power Cable Systems and the Harmonic Characteristics of Grounding Currents

Defects in the power cable system are common as a result of poor manufacturing, aging insulation, and poor installation workmanship. Continuous development of defects may result in cable heating, partial discharge, and even insulation breakdown, posing a serious threat to the stability and safety of the power system. In this paper, three common defects in power cable system were considered, including thermal aging, metal shield damage, and outer sheath damage. The ground current signal flowing through the insulation was recorded by a precision sampling resistor and a data acquisition system, while the voltage signal applied to the cable was simultaneously recorded by an oscilloscope. The FFT algorithm was improved by including window function and interpolation, and the improved FFT algorithm was then used to analyze the spectrum of the grounding current signal. The results show that the harmonic components of different defects are distributed differently, and the harmonic distribution also varies with the degree of defects.
A Low-Loss Reconfigurable Plasma Impedance Tuner for Real-Time, Frequency-Agile, High-Power RF Applications

Many frequency bands, previously allocated solely for radar, are being designated for sharing. Future radar transmitters must adaptively share the frequency spectrum with wireless communications, requiring high-power, high-speed reconfigurable circuits to maximize radar detection range upon changes in frequency and antenna impedance. This paper presents an octave (2–4 GHz) S-band reconfigurable impedance tuner with 35 W plasma switches connecting shunt inductors and capacitors to a series feedline. The tuner can be reoptimized to maximize output power in approximately 300 μs upon changes in operating frequency or antenna impedance. The tuner has a much lower average insertion loss (2.5 dB) and comparable optimization times when compared with the previous state-of-the-art octave S-band plasma tuner. The new design significantly reduces loss over its octave tuning range using shunt inductors and capacitors instead of open-circuited stubs.
Critical Review on Recent Advancement in Nanotechnology for Biomedical Application

The new update in advancement in nanotechnology has engaged to develop a new nanomaterial with a different functional property. The morphology modification of nanoparticles has exhibited excellent physio-chemical properties such as high reactivity and absorption rate, photochemical and magnetic property, and larger surface area. Moreover, biomedical application of nanoparticles are yet a hard tool to use for therapeutic application owing to its limits such as Pitiable target specificity, bio-compatibility, low photostability, toxicity to organically, poor blood retention and cellular absorption. Therefore advancement in nanotechnology is required to overcome these defects. In this background, new nanomaterials are identified with suitable biological, chemical and physical properties, which suits the required demands of the application. In this mini-review, we have covered the recent focuses of nanomaterials for biomedical application.
Directionality and vector resonances of regular and chaotic dielectric microcavities

Directionality and Vector Resonances of Regular and Chaotic Dielectric Microcavities Harald Georg Leonhard Schwefel 2004 Dielectric microcavities/ microlasers are a key component for novel opto-electronic devices. We model such devices as a dielectric rod and analyze the vector waveequation for an infinite dielectric rod with arbitrary cross-section. Analytic results for the resonance condition and polarization properties are given for the cylinder. With the parabolic equation method we derive the resonance condition and the polarization properties for modes related to 2d stable periodic ray orbits. The polarization of hybrid emitting modes of cylindrical resonators is shown to be linear up to a polarization critical angle and elliptical beyond this angle, which always lies between the Brewster and the total-internal-reflection angles of the dielectric. Arbitrary cross-sections in general give rise to non-integrable ray dynamics. We review classical Hamiltonian dynamics and billiards and expand the theory to dielectric billiards. Analysis of periodic ray orbit bifurcations and unstable manifolds enables us to understand the emission directionality of differently deformed polymer microlasers. We report new experiments on the first whispering gallery laser from a resonator with a single reflection symmetry axis, and analyze a number of different Gallium Nitride resonators/ lasers. Directionality and Vector Resonances of Regular and Chaotic Dielectric Microcavities A Dissertation Presented to the Faculty of the Graduate School of Yale University in Candidacy for the Degree of Doctor of Philosophy by Harald Georg Leonhard Schwefel Dissertation Director: A. Douglas Stone
Maize Market Chain Analysis and the Determinants of Market Participation in the Gamo and Gofa Zones of Southern Ethiopia

The majority of farmers are producing maize in the Gamo and Gofa zones and they are not benefiting from it due to the marketing problem. Thus, this study was intended to analyze the maize market chain and determinants of market participation in the selected maize-producing districts of the Gamo and Gofa zones. To achieve this objective, multistage sampling techniques were followed to randomly select 151 sample respondents. The data were analyzed by using descriptive statistics, marketing margins, and the double hurdle model. The survey results revealed that approximately 35.88% of the maize from the total maize produced by the sampled farmers was marketed in the study area. The result indicates that among the five identified maize marketing channels, the largest volume of maize passed through channel V (producers, urban collectors, and consumers). In the marketing of maize, traders set the price due to poor market linkage and the low bargaining power of producers. The model regression result indicates that among the hypothesized factors, family size, allocated land size for maize, and market information have a significant effect on the quantity of maize market supply. Based on this finding, strengthening extension services through training and accessing inputs are recommended. Furthermore, market linkage through the cooperative establishment and the availability of market information by respective bodies is suggested.
Effect of Interlayer Shear to Graphene Resonators

Graphene nanostrips with single or a few layers can be made into bending resonators with extremely high sensitivity to environment changes. In this work we study the effect of interlayer shear on resonant frequencies f of graphene nanostrips, via both molecular dynamics (MD) simulation and elastic model analysis incorporating interlayer shear. Contrary to the classical thin beam theory prediction f~nl^-2 (l is beam length and n layer number), MD simulation results reveal very different dependences, f~l^-1.36 and f - fmono~(n-1)/n (fmono is frequency of the monolayer beam). Interlayer shear modulus of multilayer graphene strips is much smaller than their intralayer Young's modulus, and the weak interlayer interaction can not maintain the registry between the carbon atoms in adjacent layers. Large shear deformation occurs during vibration of multilayer graphene nano-strips. Therefore we propose a multi-beam shear model (MBSM) with the interlayer shear energy of multilayer graphene nano-strips taken into account. It makes predictions consistent excellently with direct MD simulations without any fitting parameter required. The results are of importance for various applications of multi-layer graphene nano-strips, such as in nano-electromechanical devices including resonators, sensors and actuators, where interlayer shear has apparent impacts to deformation, vibration, and energy dissipation processes.
Work-Related Smartphone Use at Night and Job Satisfaction: Testing a Moderated Mediation Model of Emotional Exhaustion and Organizational Dehumanization

Work-related smartphone use at night has attracted substantial research attention. Surprisingly, its impact on employees’ job satisfaction is mixed. Based on the stressor–strain–outcome model, this study aims to examine whether emotional exhaustion mediates the relationship between work-related smartphone use at night and job satisfaction. Furthermore, the role of organizational dehumanization in moderating the relation between work-related smartphone use and emotional exhaustion, and the association between emotional exhaustion and job satisfaction, was examined. A total of 372 participants reported on two online surveys. Bivariate correlation results showed that work-related smartphone use was positively related to emotional exhaustion but there was no significant association between work-related smartphone use and job satisfaction. Moderated mediation analysis results suggested that organizational dehumanization (T1) did not interact with work-related smartphone use at night (T1) in predicting emotional exhaustion (T1). However, organizational dehumanization (T1) interacted with emotional exhaustion (T1) in predicting job satisfaction (T2), in which individuals who perceived higher organizational dehumanization reported lower job satisfaction under higher emotional exhaustion. The limitations and implications of this study are also discussed in this paper.
Numerical study of microwave impact on gas hydrate plugs in a pipeline

Purpose. Development of a technique for the numerical study on the decomposition of gas hydrate plugs in deep-water pipelines under microwave radiation using a coaxial source. Theoretical efficiency evaluation of using such an impact to unblock the pipelines. Methodology. Mathematical modeling and computational experiment. Findings. An original mathematical model is proposed to describe heat transfer processes during the decomposition of gas hydrates in a pipeline under the action of heat sources distributed over the volume. The non-stationary problem of heat transfer was considered in a one-dimensional formulation. An algorithm for numerical computation is proposed. A mathematical expression is obtained for distributed heat sources generated by the microwave radiation from a coaxially located SHF antenna. Parametric numerical studies on temperature fields and decomposition dynamics of a gas hydrate plug are performed for specified parameters of pipe and microwave radiation power. The boundaries of the decomposition area and the dynamics of change in this area are determined. The decomposition time of a gas hydrate plug with a diameter of 0.3 m was determined using a 300 W microwave source. The complete decomposition took approximately 40 hours. Originality. The task of thermal decomposition of a cylindrical gas hydrate plug in a pipeline due to microwave heating using a coaxial microwave power source has been considered for the first time. The process is viewed as a sequence of several stages: heating, heating and decomposition, decomposition after complete heating of the gas hydrate layer. To model the volumetric dissociation of gas hydrate, it was proposed to use special functions that characterize the amount of decomposed gas hydrate. The introduction of such functions makes it possible to construct an efficient computational algorithm taking into account the action of volumetric sources in the decomposition area. The known models mainly consider only surface thermal effect or microwave impact on gas hydrate in porous mediums. The presented model allows describing the decomposition during volumetric heating of a solid hydrate adequately. Practical value. Blocking plugs may occur due to hydrate formation when transporting gas through deep-water pipelines or through pipelines in cold environments. The elimination of such complications is a complex technical task. In particular, a special source of microwave radiation, which was proposed by the authors in previous works, can be used to unblock the pipeline. The device that makes the microwave radiation is located along the pipe axis. The results of this work allow us to evaluate the effectiveness of the microwave method for eliminating the gas hydrate plug. The mathematical model and computational method can be used in the development of appropriate technologies using a coaxial microwave heating source.
Low-Light Image Enhancement via Gradient Prior-Aided Network

Low-light images have low brightness and low contrast, which brings huge obstacles to the intelligent video surveillance system. The enhancement of low-light images must simultaneously consider the interference of factors such as brightness, contrast, artifacts, and noise. To this end, in this study, we propose a gradient prior-aided low-light enhancement network (GPANet). The main idea is to improve the network’s ability to extract edge features and remove unwanted noise by introducing first-order (i.e., Sobel Filter) and second-order gradient (i.e., Laplacian Filter) features. Unlike in previous methods, in the proposed study, we first extract the first-order and second-order gradient information of low-light images and concatenate them with low-light images for multi-view feature analysis in the multi-view fusion encoder (MFE). Then, we suggest the multi-branch topology module (MTM) to fuse and decompose the multi-view features. Finally, we reconstruct the multi-view features through multi-view decomposition decoders (MDDs, including three sub-decoders) to generate potentially normal-light images. The first- and second-order gradient decoders will provide the enhancement decoder with multi-scale gradient prior features. Furthermore, we suggest a residual network to speed up network convergence while ensuring stable enhancement performance. We conduct experiments on widely adopted datasets. The results demonstrate the advantages of our method compared to other methods from both qualitative and quantitative perspectives. The source code is available at https://github.com/LouisYuxuLu/GPANet.
Intrusion Detection using Dense Neural Network in Network System

An Network Intrusion Detection System can be perceived as a device, either software or hardware which is utilized to screen the organization for suspicious action or policy violation. In this era of digitization where everyone is using computers for all types of communications- personal, political, financial, etc., it becomes necessary to ensure that the medium of the communication is secure or not. Because nowadays every small scale enterprise, big companies, even personal households are having their own server. The new technologies are based on the concept of networking. So, an intrusion in such networks can cause bid risks like data breach financial risk or malfunctioning of the devices connected in that network. It might be possible for small networks to be checked manually because the total connection in such networks is less, but when it comes to the big networks where a lot of connections are sending and receiving requests, it is near to impossible for someone to check all the connections manually. In this paper dense neural network are used for detecting the network intrusion and NSL-KDD dataset are used to test the model. The proposed model achieved 98.29% accuracy.
A Fast Moving Object Detection Technique using QR Decomposition based TV Regularized RPCA Framework

Moving Object Detection (MOD) is one of the prominent application in the field of computer vision. This paper contributes towards designing a fast and accurate MOD technique for real time applications by addressing the issues like dynamic background, illumination changes, occlusion, camera jitter, moving shadows, etc. The brilliance of the proposed method is confined in the effective utilization of QR decomposition and $l_{2,1}$-norm minimization in the well-known Robust Principal Component Analysis (RPCA) framework. The $l_{2,1}$ norm is robust to outliers and exploits the low rankness of the background component. While the use of $l_{1}$-norm enhances the sparsity in the foreground part. Moreover, Total Variation(TV) regularization technique helps in retaining the details about the edges. Experimental result shows the supremacy of the proposed method w.r. t. the state of the art methods in terms of computational complexity and F-measure score.
Contemporary Approach for Simulation and Computation of Fluid Flows in Centrifugal Hydromachines

The article describes various aspects of mathematical modeling of fluid flows, both in general and with reference to hydraulic machinery. The article reviews historical development of corresponding methods of mathematical modeling. Implementation of these aspects in modern commercial CFD software tools is described together with advantages and disadvantages of implemented methods. The conclusion is drawn concerning possibilities of computation of fluid flows nowadays.
Sensory Processing Sensitivity and Reactivity to Daily Events

Sensory processing sensitivity is an individual difference that captures the extent to which people show heightened emotional reactivity to, and increased cognitive processing of, their environment. Although central to its definition, there has been no research examining whether highly sensitive individuals display stronger reactivity to naturally occurring negative and positive events in everyday life. We addressed this gap by carrying out a 21-day online diary study with 239 participants, varying in sensory processing sensitivity, who reported their daily life-satisfaction, affective experiences, and self-esteem along with appraisals of the most negative and positive events of the day. Multilevel analyses demonstrated that individuals higher in sensory processing sensitivity showed greater reactivity to more subjectively intense negative events, but no difference in their reactivity to positive events. These findings provide initial insights into how sensory processing sensitivity manifests in daily emotional reactivity with greater reactivity to negative events in our study.
COVID-19 Vaccine Literacy, Attitudes, and Vaccination Intention Against COVID-19 Among Thai Older Adults

Introduction Unvaccinated older adults with COVID-19 are at higher risk for severe illness and complications compared with those have been vaccinated. Vaccine literacy and attitudes are important factors that enhance healthy behaviors and choices, including vaccination intention. Objective To explore vaccine literacy, attitudes, and vaccination intention toward COVID-19 among Thai older adults and examine associations between vaccine literacy, attitudes, and vaccination intention. Methods This study used a cross-sectional online design. We surveyed 408 older adults who met our inclusion criteria. Participants were recruited online via social media and websites. The survey covered demographic data, vaccine literacy, attitudes, and intention to get the COVID-19 vaccine. Results COVID-19 vaccination intention among Thai older adults was high (81.3%). Females and those aged 60–69 years had higher COVID-19 vaccine literacy scores than males (t = −2.120, p < 0.05) and those aged ≥70 years (t = 2.438, p < 0.05). Participants with postgraduate education and those who were health professionals scored higher for vaccine literacy than less educated (t = −3.501, p < 0.01) and non-health professional (t = 5.437, p < 0.001) participants. Those with an adequate income or that had been vaccinated against COVID-19 scored significantly higher for vaccine literacy and attitudes toward the COVID-19 vaccine than participants with an inadequate income (t = 4.626, p < 0.001) or that had not been vaccinated (t = 2.842, p < 0.01). Vaccine literacy (r = 0.219, p < 0.001) and attitudes (r = 0.459, p < 0.001) were significantly associated with vaccination intention. Conclusion COVID-19 vaccine literacy and attitudes are significant factors related to vaccination intention. Health professionals could play an important role in enhancing vaccine literacy among older adults. Positive attitudes and COVID-19 vaccine literacy may enhance vaccination uptake in older adults.