Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward an Integrated Land–Ocean Surface Skin Temperature Analysis from the Variational Assimilation of Infrared Radiances

Abstract Geostationary Operational Environmental Satellite (GOES)-East and -West window channel radiances are directly assimilated using a 1D variational technique, providing surface skin temperature (Ts) estimates over all surface types (land, water, or ice) from a unique system. This is an important advantage over commonly used regression methods, such as split window. The physical nature of the method allows any combination of channels to be used, and adaptation to new sensors is straightforward. A full month (May 2001) of GOES-8 and -10 data is processed every 6 h; Ts estimates are obtained using radiances from imager channels 4 (11 μm) and 5 (12 μm). Imager channel 2 (3.9 μm) can also be used at night. Surface emissivity maps were constructed from available information based on surface type. The diurnal cycle is studied; its range is on the order of 0.7 K over the ocean. Over land, the diurnal range reaches 30 K for mountainous regions, such as the Rockies or Andes. A full GOES disk image can be proc.
Estimation of the ankle-joint space visibility in x-ray images using convolutional neural networks

For the X-ray image acquisition one of the most important factors for diagnostic quality is the patient position with respect to the X-ray tube and the detector. In case of orthopedic lateral ankle examinations, inaccurate positioning might lead to a covered joint space. This could make a reliable reading of the images impossible, which necessitates a retake. The presented approach estimates the joint space visibility of lateral ankle X-ray images. An annotation method for the joint space visibility is proposed which depends on the condyle alignment of the talus. A Convolutional Neural Network (CNN) was trained to estimate the joint space visibility. Additionally, the plausibility of the approach was confirmed by an experimental phantom setup. The estimations on a clinical dataset show that using the quality measure in regression space results in a sensitivity of 0.85 and a specificity of 0.91 for a clinically reasonable definition of image quality.
Uncovering Negative Interpretation Bias in Remitted/Recovered Depression with Laboratory Task

Objective: Research has demonstrated that individuals with a history of depression engage in complicated strategies (e.g., thought suppression) that may mask the possible existence of major depression. Increasing the mental strain, such as retrieving a six-digit number, may reveal depressive thinking in previously depressed individuals. This study examined the hypothesis that thought suppression could mask a cognitive vulnerability to depression and illustrated how cognitive tasks disrupt mind control. Method : This case-control study recruited 255 participants with a convenience sampling method conducted at the Razi Educational and Therapeutic Psychiatric Center (Tehran, Iran) in 2021. Participants were divided into five groups, then they were evaluated by a scrambled sentence test (SST) after random assignment to either mental load or no mental load conditions. The number of negative unscrambled statements was used as an index of negative interpretation bias. After gathering data, analysis of variance (ANOVA) for different group factors and conditions was carried out to test the main hypotheses. Results: The effect of the intervention provided to each group on the score of the Hamilton Depression Rating Scale (HRDS) was signiﬁcant (F (4, 208) = 511.77, P < 0.001). A significant correlation (r = 0.36, P < 0.01) was found between depression (HDRS) and negative interpretive bias (SST). Analysis of ANOVA has revealed a signiﬁcant effect on the group (F (4, 412) = 14.94, P < 0.001). The effect of the mental load was not signiﬁcant (F (4, 412) = 0.09, P = 0.75), but the group × load interaction was signiﬁcant (F (4, 412) = 5.03, P < 0.001). Post hoc test was used to draw multiple comparisons between the five groups. Conclusion: The results revealed that people who are vulnerable to depressive disorders are predominantly engaged in thought suppression, which can conceal their depressogenic thinking until cognitive requests consume their mind control efforts.
Speech compression scheme based on wavelet transform and vector quantization

A new coding method of speech compression which is based on Wavelet Transform and Vector Quantization(VQ), is developed and studied in this paper. Firstly the speech is processed with Wavelet Transform or Wavelet PacketTransform, then VQ is used to compress the coefficients of Wavelet Transform. The entropy coding is also used todecrease the bit rate. The experimental results demonstrate that the speech signal sampled by 8 kHz sampling rateand 8 bit quantization, so that 64 kbit/s bit rate, can be compressed to 6 kbit/s ~ 8 kbit/s, and still have good speechquality. The low--delay is another advantage for this method, which is only 8 ms.
On the Complexity of Literary and Popular Fiction

Research findings in cognitive literary studies show that lifetime exposure to literary versus popular fiction has a differential association with social cognition processes such as psychological essentialism, attributional complexity, and, particularly, with Theory of Mind. Experimental findings further show that brief exposure to literary, but not popular fiction, boosts performance on Theory of Mind. These results are interpreted as stemming from the greater complexity of the characters and plots of literary fiction; a claim that is consistent with evidence that readers view literary fiction characters as more complex than popular fiction characters. Here we focus on style, and test whether said differential complexity finds a parallel in the language of these two types of fiction. Results of Natural Language Processing analyses on a corpus of literary and popular fiction texts confirm that literary fiction has greater lexical and syntax complexity than popular fiction.
Central bank coordinated policies and bank market power: an insight from the African context

Abstract The paper examines the impact of central bank regulatory policies on market power in Africa. The study presents a representative sample of 52 African economies over the period 2006–2020. The study shows that the individual regulatory policies of the central bank (i.e. monetary and macro-prudential policies) enhance banks’ market power. Also, it reveals that central bank regulatory policies are better coordinated, as complements, in achieving greater market power of banks in countries with strong central bank independence (CBI) framework. However, the coordinated policies are substitutes in determining bank’s market power in countries with weak CBI framework. The policy implication is that the right policy mix of coordinated central bank regulatory policy framework is important in determining an optimal outcome of bank’s market power in both an inclusive central bank (monetary-prudential) policy targeting economies and an independent policy targeting economies.
An Implementable Augmented Lagrange Method for Variational Inequality with Constraints

An augmented Lagrange method is constructed to solve variational inequality with constraints and the global convergence theorem is demonstrated.The augmented Lagrange method and the semismooth inexact Newton method are used to solve the inner problems.Numerical results for four examples are reported to verify the effectiveness of the augmented Lagrange function method for obtaining approximate solutions.
Analyzing components of a transformer under different dataset scales in 3D prostate CT segmentation

Literature on medical imaging segmentation claims that hybrid UNet models containing both Transformer and convolutional blocks perform better than purely convolutional UNet models. This recently touted success of hybrid Transformers warrants an investigation into which of its components contribute to its performance. Also, previous work has a limitation of analysis only at fixed dataset scales as well as unfair comparisons with other models where parameter counts are not equivalent. Here, we investigate the performance of a hybrid Transformer network i.e. the nnFormer for organ segmentation in prostate CT scans. We do this in context of replacing its various components and by constructing learning curves by plotting model performance at different dataset scales. To compare with literature, the first experiment replaces all the shifted-window(swin) Transformer blocks of the nnFormer with convolutions. Results show that the convolution prevails as the data scale increases. In the second experiment, to reduce complexity, the self-attention mechanism within the swin-Transformer block is replaced with an similar albeit simpler spatial mixing operation i.e. max-pooling. We observe improved performance for max-pooling in smaller dataset scales, indicating that the window-based Transformer may not be the best choice in both small and larger dataset scales. Finally, since convolution has an inherent local inductive bias of positional information, we conduct a third experiment to imbibe such a property to the Transformer by exploring two kinds of positional encodings. The results show that there are insignificant improvements after adding positional encoding, indicating the hybrid swin-Transformers deficiency in capturing positional information given our dataset at its various scales. Through this work, we hope to motivate the community to use learning curves under fair experimental settings to evaluate the efficacy of newer architectures like Transformers for their medical imaging tasks. Code is available on https://github.com/prerakmody/ window-transformer-prostate-segmentation.
Design of a Compact Ultra-Wideband Microstrip Bandpass Filter

A compact ultra-wideband bandpass filter based on a multilayer printed circuit board (MPCB) structure is proposed in this paper. RO4450F prepreg is used to bond three RO4350B dielectric substrates with different thicknesses in the MPCB structure. The upper surfaces of the three dielectric substrates are respectively provided with copper-coated structures with different patterns. The blind holes and the defected ground structure (DGS) are added to the MPCB of an ultra-wideband bandpass filter. Two groups of loaded quarter-wavelength terminal-open stubs introduce two transmission zeros, which improves the roll-off rates and stopband characteristics, while simple DGS composed of rectangular slots introduces two resonance points in the passband to improve the return loss. Simulation and measurement are consistent. The insertion loss at the center frequency of 12.795 GHz is 0.58 dB and the fractional bandwidth of 3 dB is 40.33% from 10.215 GHz to 15.375 GHz. This bandpass filter can be widely used in wireless and satellite communication.
Morphological analysis of ankle shorts bones of children with cerebral palsy: a comparative study

Cerebral palsy is a common physical disability in childhood that results in aberrant movement and postural patterns. To better understand the pathology and improve the rehabilitation of patients, this article comparatively studies the ankle short bones morphology with one of the state-of-the-art tools, ShapeWorks, and a deformation-based method. Experiments on a clinical dataset reveal calcaneus and talus deformity patterns, providing a guideline for clinical decisions.
Non-verbal predicates and predicate movement in Hungarian

It is argued that Hungarian copular clauses have a uniform base-generated structure, where the copula has a Small Clause complement and the predicate of the SC forms a complex predicate with the copula. Existential and locative sentences have the same underlying structure, however, their surface word order is different and there is no complex predicate formation. Predicative adpositional phrases (PPs) also form complex predicates with verbs other than the copula. It is shown that particles are part of the extended projection of PPs, which contain projections for place and path denoting postpositions and a functional projection for articles. Particle movement to the preverbal position is therefore one of the instances of a predicative PP forming a complex predicate with the verb. Resultative and depictive secondary predicates and predicative complements of consider-type verbs are also Non-verbal predicates and predicate movement in Hungarian
Radiolabeled Chalcone Derivatives as Potential Radiotracers for β-Amyloid Plaques Imaging

Natural products often provide a pool of pharmacologically relevant precursors for the development of various drug-related molecules. In this review, the research performed on some radiolabeled chalcone derivatives characterized by the presence of the α-β unsaturated carbonyl functional group as potential radiotracers for the imaging of β-amyloids plaques will be summarized. Chalcones’ structural modifications and chemical approaches which allow their radiolabeling with the most common SPECT (Single Photon Emission Computed Tomography) and PET (Positron Emission Tomography) radionuclides will be described, as well as the state of the art regarding their in vitro binding affinity and in vivo biodistribution and pharmacokinetics in preclinical studies. Moreover, an explanation of the rationale behind their potential utilization as probes for Alzheimer’s disease in nuclear medicine applications will be provided.
Longitudinal Critical Current Profiles in Coated Conductors Examined by Transport and Magnetization Measurements

Critical current (<italic>I<sub>c</sub></italic>) variations along the coated conductor (CC) have a significant impact on the conductor stability and quench behavior. In the direct current (DC) transport case, localized <italic>I<sub>c</sub></italic> minimum can lead to the formation of a region with a higher electric field. Joule heating in such a region can disable the operational functionality of the device. Then a sufficiently detailed knowledge of the longitudinal profile of the conductor <italic>I<sub>c</sub></italic> is in the first place necessary in assessing the conductor eligibility for a specific application. In the second place, it serves to design appropriate electro-thermal stabilization, securing an effective operation, and reducing the probability of conductor degradation during the quench. We report on the experimental investigation of longitudinal <italic>I<sub>c</sub></italic> homogeneity of <italic>CC</italic> observed by means of transport and magnetization measurements. Basic information is the CC data from the producer on <italic>I<sub>c</sub></italic> profiles obtained with ∼1-milimeter spatial resolution by Tapestar<sup>TM</sup> XL. We compare it with the result obtained by multi-channel DC transport measurement with 3-millimeter spatial resolution between neighboring contacts on a multiprobe device. Then the whole sample is characterized by a complex AC susceptibility experiment. We analyze possible causes of observed discrepancies between respective methods and discuss the relevance of various techniques for the determination of longitudinal <italic>I<sub>c</sub></italic> profiles in commercial CC.
Comparison of Acute Arterial Responses Following a Rescue Simulation and Maximal Exercise in Professional Firefighters

Cardiovascular events are the leading cause of on-duty deaths among firefighters. Screening firefighters for risk of sudden cardiac event is a critical element of a comprehensive medical program. Although intense physical exertion has been shown to trigger sudden cardiac events in the general population, it is unclear how hemodynamic responses following clinical exercise testing compare to that of performing firefighting tasks in personal protective equipment. Therefore, the purpose of this study was to compare hemodynamic responses following rescue simulation (RS) and maximal exercise in firefighters. This was a cross-over repeated measures study. Thirty-eight professional firefighters (31.8 ± 5.2 yr; VO2peak: 57.9 mL/kg/min) completed a maximal aerobic exercise test (MAET) and an RS. Pulse wave velocity (PWV), pulse pressure (PP), and brachial and central mean arterial pressure (MAP) were measured before and 5 and 15 min post-exercise. The findings indicated that femoral PWV decreased after MAET and RS at both time points (p < 0.005). No significant differences were found in aortic and carotid PWV over time or between conditions (p ≥ 0.05). Significant increases in brachial and central PP and MAP were noted 5 min post-MAET and RS (p = 0.004). In conclusion, the present study demonstrated that peripheral arterial stiffness (AS) decreased in firefighters following both conditions, with no differences in central AS. Our findings provide valuable information on hemodynamic responses similar between RS and MAET, and are important for controlling CVD risk and the AS response.
Asymmetric Information and Receiving Investor Outcomes in the Block Market for Corporate Bonds

We examine two decades of block trading in corporate bonds to test theoretical predictions on receiving investors to whom the dealer distributes the block. Receiving investors lose on average from participating as a counterparty in the block trade. Nevertheless, participation is often optimal, even when asymmetric information is elevated (e.g., the block initiator is informed or in opaque markets), as receiver losses are smaller than initiating a similar-size trade. Across various settings that reduce asymmetric information, we show a substantial transfer in profits from the dealer to receiving investors. We exploit variations in trade reporting rules of maximum stipulated delay, showing that receiving investors obtain better terms on offsetting trades that occur after disclosure of the block trade. Our study adds nuance to existing evidence that customers benefit from transparency and helps explain the appeal of the block market for receiving investors. --------------------------------------------------------------------------------------------------------------------* None of the authors received financial support specific to this project. Kumar thanks Larry Harris, Ananth Madhavan and members of the FIMSAC transparency sub-committee. Jacobsen has no conflicts of interest to report. Venkataraman is a visiting economist at FINRA’s Office of Chief Economist and acknowledges financial support for other projects. Southern Methodist University. Email: staceyj@mail.cox. smu.edu and kumar@mail.cox. smu.edu. Asymmetric Information and Receiving Investor Outcomes in the Block Market for Corporate Bonds
Forward-backward: a new method for computing low-grazing angle scattering

A new technique called "forward-backward," has been developed for solving the magnetic field integral equation (MFIE) for perfectly conducting azimuthally homogeneous surfaces, including cases where the incident radiation has a lowgrazing angle. The technique involves splitting both the surface current and the MFIE into two pieces; one representing primarily forwardly scattered energy and one representing primarily backwardly scattered energy. Each of the new integral equations can be solved by an iterative stepping procedure. The technique is applied to two sample problems–the classic Sommerfeld wedge and a peaked surface consisting of two filtered exponentials. The obtained solutions are shown to be accurate for each of these problems.
Foreign emissions exacerbate PM2.5 pollution in China through nitrate chemistry

Abstract. Fine particulate matter (PM2.5) pollution is a severe problem in China. Research on the sources of Chinese PM2.5 pollution has focused on the contributions of China's domestic emissions. However, the impact of foreign anthropogenic emissions has typically been simplified or neglected, partly due to the perception that the short lifetime of PM2.5 (a few days) does not allow long-distance transport. Here we explore the role of foreign anthropogenic emissions in Chinese PM2.5 pollution in 2015 using the GEOS-Chem chemical transport model. We validate the model simulations with a comprehensive set of observations of PM2.5 and its composition, including sulfate, nitrate, ammonium, black carbon, and primary organic aerosols, over China and its surrounding regions. We find that 8 % of PM2.5 (5 µg m−3) and 19 % of nitrate (2.6 µg m−3) over eastern China in 2015 was contributed by foreign anthropogenic emissions. The contributions were the highest in January (6.9 µg m−3 PM2.5, with 68 % nitrate) and the lowest in July (2.7 µg m−3 PM2.5, with 11 % nitrate). Yet, only 30 % of such foreign contributions in January were through direct atmospheric transport. The majority (70 %) were instead through chemical interactions between foreign-transported aerosol precursors and China's domestic emissions of pollutants. Specifically, the transport of non-methane volatile organic compounds (NMVOCs) from foreign countries enhanced the atmospheric oxidizing capacity and facilitated the oxidation of Chinese nitrogen oxides (NOx) to form nitric acid (HNO3) over eastern China. The abundance of Chinese ammonia (NH3) further partitioned nearly all HNO3 gas to particulate nitrate, leading to considerable foreign contributions of nitrate and PM2.5 to eastern China. Over southwestern China, foreign anthropogenic emissions contributed 4.9 µg m−3 PM2.5 concentrations (18 % of total PM2.5 mass) to Yunnan Province, with 37 % as organics and 27 % as sulfate. Our findings suggest that foreign anthropogenic emissions play an important role in Chinese PM2.5 pollution because of direct aerosol transport and, more importantly, chemical interactions between transported pollutants and China's local emissions. Thus, foreign emission reductions will be very beneficial for improving Chinese air quality.
Joint Separation and Localization of Moving Sound Sources Based on Neural Full-Rank Spatial Covariance Analysis

This paper presents an unsupervised multichannel method that can separate moving sound sources based on an amortized variational inference (AVI) of joint separation and localization. A recently proposed blind source separation (BSS) method called neural full-rank spatial covariance analysis (FCA) trains a neural separation model based on a nonlinear generative model of multichannel mixtures and can precisely separate unseen mixture signals. This method, however, assumes that the sound sources hardly move, and thus its performance is easily degraded by the source movements. In this paper, we solve this problem by introducing time-varying spatial covariance matrices and directions of arrival of sources into the nonlinear generative model of the neural FCA. This generative model is used for training a neural network to jointly separate and localize moving sources by using only multichannel mixture signals and array geometries. The training objective is derived as a lower bound on the log-marginal posterior probability in the framework of AVI. Experimental results obtained with mixture signals of moving sources show that our method outperformed an existing joint separation and localization method and standard BSS methods.
Accuracy Problems of Numerical Calculation of Fractional Order Derivatives and Integrals Applying the Riemann-Liouville/Caputo Formulas

Abstract In the paper there are presented and evaluated for effectiveness three methods of accuracy increase of fractional order derivatives and integrals computations for application with the Riemann-Liouville/Caputo formulas. They are based on the ideas of either transforming difficult integrand in the formulas to high-accuracy computations requirements of a applied method of numerical integration or adapting a numerical method of integration to handle with high-accuracy a difficult feature in the integrand. Additional accuracy gain is obtained by incorporating increased precision into computations. The actual accuracy improvement by applying presented methods is compared with the capabilities of wide range of available methods of integration.