Miracle-dz/UniFAR-FTUs huggingface dataset:
Moonlight synchronous flights across three western palearctic swifts mirror size dependent prey preferences

Recent studies have suggested the presence of moonlight mediated behaviour in avian aerial insectivores, such as swifts. At the same time swift species also show differences in prey (size) preferences. Here, we use the combined analysis of state-of-the-art activity logger data across three swift species, the Common, Pallid and Alpine swifts, to quantify flight height and activity responses to crepuscular and nocturnal light conditions. Our results show a significant response in flight heights to moonlight illuminance for Common and Pallid swifts, while a moonlight driven response is absent in Alpine swifts. Swift flight responses followed the size dependent altitude gradient of their insect prey. We show a weak relationship between night-time illuminance driven responses and twilight ascending behaviour, suggesting a decoupling of both crepuscular and night-time behaviour. We suggest that swifts optimise their flight behaviour to adapt to favourable night-time light conditions, driven by light responsive and size-dependent vertical insect stratification and weather conditions.
Swi/Snf Chromatin Remodeling Regulates Transcriptional Interference and Gene Repression

Alternative transcription start sites can affect transcript isoform diversity and translation levels. In a recently described form of gene regulation, coordinated transcriptional and translational interference results in transcript isoform-dependent changes in protein expression. Specifically, a long undecoded transcript isoform (LUTI) is transcribed from a gene-distal promoter, interfering with expression of the gene-proximal promoter. While transcriptional and chromatin features associated with LUTI expression have been described, the mechanism underlying LUTI-based transcriptional interference is not well understood. Using an unbiased genetic approach followed by integrated genomic analysis, we uncovered that the Swi/Snf chromatin remodeling complex is required for co-transcriptional nucleosome remodeling that leads to LUTI-based repression. We identified genes with tandem promoters that rely on Swi/Snf function for transcriptional interference during protein folding stress, including LUTI-regulated genes. To our knowledge, this study is the first to observe Swi/Snf’s direct involvement in gene repression via a cis transcriptional interference mechanism.
Investigating Spatiotemporal Dynamics of Cortical Activity During Language Production in the Healthy and Lesioned Brain

Efficient language production requires rapid interactions between different brain areas. These interactions can be severely affected by brain lesions. However, the neurophysiological correlates of the spatiotemporal dynamics during language production are not well understood. The current pilot study explores differences in spatiotemporal cortical dynamics between five subjects with post-stroke aphasia and five control subjects. Electroencephalography was recorded during picture naming in both groups. Average-based analyses (event-related potential (ERP), frequency-specific Global Field Power (GFP)), reveal a strong synchronization of cortical oscillations, especially within the first 600ms post-stimulus, with a time shift between participants with aphasia and control subjects. ERPs and the corresponding brain microstates indicate coordinated brain activity alternating mainly between frontal and occipital zones. This behavior can be described as standing waves between two main sources. At the single-trial scale, traveling waves (TW) were identified from both phase and amplitude analyses. The spatiotemporal distribution of amplitude TW reveals subject-specific organization of several interconnected hubs. In patients with aphasia this spatial organization of TW reveals zones with no TW notably in the vicinity of stroke lesions. The present results provide important hints for the hypothesis that TW contribute to the synchronization and communication between different brain areas especially by interconnecting cortical hubs. Moreover, our findings show that cortical dynamics is affected by brain lesions. Contribution to the Field Spatiotemporal cortical dynamics of individual trials reveals the presence of phase and amplitude traveling waves. Exploration of traveling waves on the 2D cortical surface reveals the presence of interconnected epicenters or hubs in all subjects. The spatiotemporal distribution of traveling waves shows a higher density in the prefrontal area for people with aphasia than for healthy subjects. For subjects with aphasia, a sparser density of traveling waves is observed in the approximated lesion area. Event-related potential analyses reveal a consistent alternating activity between the frontal and occipital regions. Subjects with aphasia present a larger and/or delayed contribution in the delta range in the GFP patterns compared to control subjects.
Range correlation effects on phase noise spectra

The authors address the problem of characterizing the effects of range correlation and local oscillator phase noise on the intermediate frequency spectrum of a coherent, continuous wave or pulsed Doppler radar. Since the phase noise is a stochastic process, the problem is defined in a stochastic processes context and a reasonable set of assumptions are imposed to produce a general, straight forward and easily understood solution. The solution clearly indicates how the natural spectrum of the scatterer, the phase noise spectrum, and range correlation combine to produce the intermediate frequency spectrum. A specific example is provided for the case of a continuous wave radar.
Hyper-hemispheric lens distortion model for 3D-imaging SPAD-array-based applications

Panoramic omnidirectional lenses have the typical draw-back effect to obscure the frontal view, producing the classic "donut-shape" image in the focal plane. We realized a panoramic lens in which the frontal field is make available to be imaged in the focal plane together with the panoramic field, producing a FoV of 360° in azimuth and 270° in elevation; it have then the capabilities of a fish eye plus those of a panoramic lens: we call it hyper-hemispheric lens. We built and test an all-spherical hyper-hemispheric lens. The all-spherical configuration suffer for the typical issues of all ultra wide angle lenses: there is a large distortion at high view angles. The fundamental origin of the optical problems resides on the fact that chief rays angles on the object side are not preserved passing through the optics preceding the aperture stop (fore-optics). This effect produce an image distortion on the focal plane, with the focal length changing along the elevation angles. Moreover, the entrance pupil is shifting at large angle, where the paraxial approximation is not more valid, and tracing the rays appropriately require some effort to the optical designer. It has to be noted here as the distortion is not a source-point-aberrations: it is present also in well corrected optical lenses. Image distortion may be partially corrected using aspheric surface. We describe here how we correct it for our original hyper-hemispheric lens by designing an aspheric surface within the optical train and optimized for a Single Photon Avalanche Diode (SPAD) array-based imaging applications.
Jumps in financial modelling: pitting the Black-Scholes model refinement programme against the Mandelbrot programme

This paper gives an overview of the financial modelling of discontinuities in the behaviour of stock market prices. I adopt an epistemological perspective to present to the two main competitors for this stake: Mandelbrot's programme and the non-stable Levy processes based approach. I explain this contest using the De Bruin's notions of refinement programme, over-mathematisation and model-tinkering: I argue that the non-stable Levy based approach of discontinuities can be viewed as a " Black-Scholes model refinement programme " (BSMRP) in the De Bruin's sense, launched against the radical view of Mandelbrot. I use Sato's classification to contrast the two competitors. Next I present the two strands of research from an historical perspective between 1960 and 2000. Mandelbrot's initial model based on alpha-stable motions initiated huge controversies in the finance field and failed to fully describe the observed behaviour of returns due to the stronger fractal hypothesis. The mixed jump-diffusion non fractal processes began in the 1970s, followed after two decades by infinite activity processes in the 1990s. At the end, the time-change representation of the 2000s seems to unify the two competitors.
Recent results from prototypes of the Fluorescence detector Array of Single-pixel Telescopes (FAST) in both hemispheres

The origin and nature of ultrahigh-energy cosmic rays (UHECRs) are of uppermost importance in astroparticle physics. Motivated by the need for an unprecedented aperture for further advancements, the Fluorescence detector Array of Single-pixel Telescopes (FAST) is a prospective next-generation, ground-based UHECR observatory that aims to cover an enormous area by deploying a large array of low-cost fluorescence telescopes. The full-scale FAST prototype consists of four 20 cm photomultiplier tubes at the focus of a segmented mirror 1.6 m in diameter. Three FAST prototypes have been installed at the Telescope Array Experiment in Utah, USA, and two prototypes at the Pierre Auger Observatory in Mendoza, Argentina, commencing remote observation of UHECRs in both hemispheres. We report on recent results of the full-scale FAST prototypes operated in both hemispheres, including telescope calibrations, atmospheric monitoring, ongoing electronics upgrades, development of sophisticated reconstruction methods and UHECR detections.
THE STOCHASTIC OBSERVABILITY AND THE ESTIMATES WITHOUT THE KNOWLEDGE OF INITIAL VALUES FOR THE CONTINUOUS TIME SYSTEM

In this paper we shall give a necessary and sufficient condition for the stochastic observability of the continuous-time linear stochastic systems. This condition is reduced to that of the complete observability, when the original system degenerates into the deterministic one. The estimates without the knowledge of initial values for the states as well as for the initial value are also considered in this paper, when the system is stochastically observable.
Understanding cardiac senescence one cell type at a time

Cellular senescence, a hallmark of aging, is defined as a state of stress-induced proliferative arrest while maintaining viability and metabolic activity [1,2] . Senescence was first characterized in vitro by Leonard Hayflick in WI-38 lung fibroblasts after replicative exhaustion and critical telomere shortening [3] . Eventually, senescence was observed in multiple cell types including those of cardiovascular origin (cardiomyocytes, cardiac fibroblasts, endothelial cells, etc.), and in multiple contexts [4] . For example, acute senescence was found to be critical for embryogenesis, injury response, and wound healing [2] , whereas chronic senescence, while initially tumor suppressive, appeared to be associated with a decline in tissue function and even tumor promotion in aging [5] . Acute cellular senescence plays an important physiological role in cardiac development and regeneration, while senescent cells accumulate in the heart with age, leading to an age-related decline in cardiac function [1,4] . Accordingly, recent studies have linked cellular senescence and the associated release of inflammatory components to cardiac pathologies. However, the exact role of senescent cells in these diseases is unclear, and in some cases, both adverse and beneficial effects have been reported. Therefore, a more complete understanding of cellular senescence promises new insights into disease pathophysiology and will provide new avenues for disease prevention and treatment.
Correlation between Economic Development and Regime Types

Democracy is considered by many to be the ultimate form of government. This paper tries to identify the effects of choosing certain regime types over others on the economic development of that society. Through careful review of several scholars’ works on this topic, this study finds that several key factors, such as how long has the newly created democracy existed, how well democratic institutions are established (free and fair elections, control over economy, rule of law etc.). Simply transitioning into a democracy does not guarantee economic growth, but maturing as a democracy does. This study seeks to provide a meaningful discussion and help its audience understand the more specific details of each type of regime, thus allowing for a closer examination of the debate of democracy versus autocracy. Through this paper, readers will be able to understand what makes a mature democracy, and how does a mature democracy help economic development.
Affine Principal-Component-Based Term Structure Model

We present an affine multifactor Gaussian term structure model, where we let factors be principal components of yields. Taking forward the affine-yield idea presented in Duffie and Kan (1996) we derive general expressions for the coefficients of a multidimensional affine Gaussian stochastic process given an exogenous matrix of loadings of selected yields on the state variables.
THE IMPACT OF DATA SECURITY ON THE INTENTION OF VIETNAMESE CONSUMERS TO USE E-WALLETS

E-wallets are used as a form of payment that brings many benefits to users. This article studies the impact of data security on consumer intentions to use e-wallets in the rapidly growing economy of Vietnam. The data consist of 236 observations from a survey of consumers in Vietnam. Covariance-based structural equation modeling (CB-SEM) was employed to test the proposed hypotheses. Research results show that security trust has the greatest impact on the intention to use e-wallets, followed by perceived privacy risk, social influence, and information sensitivity. The study also reveals the role of privacy policies and security concerns in consumer intentions to use e-wallets. Based on the research results, the study provides recommendations for consumers, e-wallet providers, and governmental agencies to increase awareness of and responsibility for information security among the consumers who use e-wallets.
Metabolic Disturbance of High-Saturated Fatty Acid Diet in Cognitive Preservation

Aging continues to be the main cause of the development of Alzheimer’s, although it has been described that certain chronic inflammatory pathologies can negatively influence the progress of dementia, including obesity and hyperlipidemia. In this sense, previous studies have shown a relationship between low-density lipoprotein receptor (LDLR) and the amyloid-beta (Aβ) binding activity, one of the main neuropathological features of Alzheimer’s disease (AD). LDLR is involved in several processes, including lipid transport, regulation of inflammatory response and lipid metabolism. From this perspective, LDLR−/− mice are a widely accepted animal model for the study of pathologies associated with alterations in lipid metabolism, such as familial hypercholesterolemia, cardiovascular diseases, metabolic syndrome, or early cognitive decline. In this context, we induced hyperlipidemia in LDLR−/− mice after feeding with a high-saturated fatty acid diet (HFD) for 44 weeks. LDLR−/−-HFD mice exhibited obesity, hypertriglyceridemia, higher glucose levels, and early hepatic steatosis. In addition, HFD increased plasmatic APOE and ubiquitin 60S levels. These proteins are related to neuronal integrity and health maintenance. In agreement, we detected mild cognitive dysfunctions in mice fed with HFD, whereas LDLR−/−-HFD mice showed a more severe and evident affectation. Our data suggest central nervous system dysfunction is associated with a well-established metabolic syndrome. As a late consequence, metabolic syndrome boots many behavioral and pathological alterations recognized in dementia, supporting that the control of metabolic parameters could improve cognitive preservation and prognosis.
Precipitation Nowcasting with Three-Dimensional Space–Time Extrapolation of Dense and Frequent Phased-Array Weather Radar Observations

AbstractThe phased-array weather radar (PAWR) is a new-generation weather radar that can make a 100-m-resolution three-dimensional (3D) volume scan every 30 s for 100 vertical levels, producing ~100 times more data than the conventional parabolic-antenna radar with a volume scan typically made every 5 min for 15 scan levels. This study takes advantage of orders of magnitude more rapid and dense observations by PAWR and explores high-precision nowcasting of 3D evolution at 1–10-km scales up to several minutes, which are compared with conventional horizontal two-dimensional (2D) nowcasting typically at O(100) km scales up to 1–6 h. A new 3D precipitation extrapolation system was designed to enhance a conventional algorithm for dense and rapid PAWR volume scans. Experiments show that the 3D extrapolation successfully captured vertical motions of convective precipitation cores and outperformed 2D nowcasting with both simulated and real PAWR data.
ESTIMASI CONFIDENCE INTERVAL BOOTSTRAP UNTUK ANALISIS DATA SAMPEL TERBATAS

Dalam analisis data seringkali peneliti ingin mengetahui karakteristik data penelitian seperti jenis distribusi, mean, median atau varians data. Kendala dalam menentukan karakteristik data biasanya ketika data yang tersedia di lapangan sedikit, sehingga tidak cukup untuk dilakukan analisis secara parametrik. Tulisan ini membahas estimasi confidence interval (CI) dengan menggunakan bootstrap untuk estimasi nilai parameter mean, median, dan varians data juga dalam menentukan kecocokan distribusi (goodness of fit) data. Tiga metoda CI bootstrap yaitu percentile CI, standard normal CI, dan bias-corrected percentile CI digunakan dan dibandingkan untuk mengetahui perbedaan nilai estimasi parameternya. Metoda bootstrap parametrik digunakan untuk menentukan estimasi parameter CI data berdistribusi Eksponensial, Gamma, Log-Normal, dan Weibull yang akan digunakan untuk mengetahui distribusi data yang cocok. Langkah-langkah estimasi CI dan kecocokan model distribusi dibuat, selanjutnya digunakan dalam menganalisis data waktu kerusakan mesin untuk sampel yang kecil. Hasil menunjukkan bahwa estimasi CI bootstrap dengan ketiga metoda memberikan nilai yang relatif sama, dilihat dari batas bawah dan batas atas yang dihasilkan, maupun selisih interval yang kurang dari 5%, selain itu dapat juga ditentukan pemilihan distribusi yang terbaik dengan melihat nilai MSE (mean square error) terkecil, sehingga dapat ditentukan estimasi CI parameter bootstrap untuk distribusi tersebut.
The level of aquatic yeast as a possible indicator of microbiological quality of urban recreational water reservoirs

ABSTRACT Sanitary indicators standardly used in water quality monitoring refer to fecal microorganisms or cyanobacterial toxins, but at present they do not include fungi, despite the fact that many fungi can pose potential health hazards. The aim of study was a quantitative and qualitative assessment of yeast in waters of urban artificial recreational reservoirs in relation to microbiological and sanitary cleanliness indicators and to demonstrate that yeast could be an indicator of anthropogenic pollution. In total, 18 species of yeast were isolated, including 13 classified as clinically relevant. Tested reservoirs exceeded the standards of sanitary indicators acceptable for bathing water. Since isolated yeasts are associated with living organisms, their presence in the water of urban recreational reservoirs may be a public health concern. Therefore, a mycological analysis should be incorporated into standard water quality assessment procedures. The results obtained are very promising, but further research is still needed.
A Hybrid Multimodal Emotion Recognition Framework for UX Evaluation Using Generalized Mixture Functions

Multimodal emotion recognition has gained much traction in the field of affective computing, human–computer interaction (HCI), artificial intelligence (AI), and user experience (UX). There is growing demand to automate analysis of user emotion towards HCI, AI, and UX evaluation applications for providing affective services. Emotions are increasingly being used, obtained through the videos, audio, text or physiological signals. This has led to process emotions from multiple modalities, usually combined through ensemble-based systems with static weights. Due to numerous limitations like missing modality data, inter-class variations, and intra-class similarities, an effective weighting scheme is thus required to improve the aforementioned discrimination between modalities. This article takes into account the importance of difference between multiple modalities and assigns dynamic weights to them by adapting a more efficient combination process with the application of generalized mixture (GM) functions. Therefore, we present a hybrid multimodal emotion recognition (H-MMER) framework using multi-view learning approach for unimodal emotion recognition and introducing multimodal feature fusion level, and decision level fusion using GM functions. In an experimental study, we evaluated the ability of our proposed framework to model a set of four different emotional states (Happiness, Neutral, Sadness, and Anger) and found that most of them can be modeled well with significantly high accuracy using GM functions. The experiment shows that the proposed framework can model emotional states with an average accuracy of 98.19% and indicates significant gain in terms of performance in contrast to traditional approaches. The overall evaluation results indicate that we can identify emotional states with high accuracy and increase the robustness of an emotion classification system required for UX measurement.
Method to Change the Through-Hole Structure to Broaden Grounded Coplanar Waveguide Bandwidth

A grounded coplanar waveguide (GCPW), as a millimeter wave special transmission line, can be used to calibrate broadband oscilloscope probes. A method to change the through-hole structure to widen the GCPW is investigated in this paper. The effect of the through-hole array on the band-width of the GCPW is investigated and verified using COMSOL Multiphysics simulation software. Finally, the S-parameters of the fabricated GCPWs are measured by a vector network analyzer, and the results show that they have an insertion loss > −3 dB and return loss < −10 dB in the frequency range of DC to 60 GHz, which satisfies the design requirements.
Semi-global output regulation for discrete-time singular linear systems with input saturation via composite nonlinear feedback control

The semi-global output regulation problem of multi-variable discrete-time singular linear systems with input saturation is investigated in this paper. A composite nonlinear feedback control law is constructed by using a low gain feedback technique for semi-global stabilisation of discrete-time singular linear systems with input saturation. The sufficient solvability conditions of the semi-global output regulation problem by composite nonlinear feedback control are established. When the composite nonlinear feedback control law is reduced to a linear control law, the solvability conditions are an exact discrete-time counterpart of the semi-global output regulation problem of continuous-time singular linear systems. With the extra control freedom of the nonlinear part in the composite nonlinear feedback control law, the transient performance of the closed-loop system can be improved by carefully choosing the linear feedback gain and the nonlinear feedback gain. The design procedure of the composite nonlinear feedback control law and the improvement of the transient performance are illustrated by a numerical example.
Lotfi A. Zadeh

퍼지 논리는 1965년 Zadeh[13]에 의하여 소개된 이후 꾸준히 확장, 발전하였다. 퍼지 논리와 관련된 수학사 및 수학교육 논문[1, 2, 3, 4, 5, 7]들이 많이 발표 되었지만 정작 퍼지 논리의 창시자인 Zadeh에 대한 연구 논문은 아직까지 나오지 않았다. 본 논문에서는 Zadeh의 생애와 업적을 알아보고 이를 통해 우리가 배워야 할 점들에 대해 논의한다. 또한 이가 논리, 다가 논리, 퍼지 논리, 직관주의 논리 및 직관적 퍼지 집합을 비교, 분석해보고 직관적 퍼지 집합에서 ‘직관적(intuitionistic)’이라는 용어의 부적절성에 대해 논의한다.