Miracle-dz/UniFAR-FTUs huggingface dataset:
Noninvasive Assessment of Photoreceptor Structure and Function in the Human Retina

NONINVASIVE ASSESSMENT OF PHOTORECEPTOR STRUCTURE AND FUNCTION IN THE HUMAN RETINA Robert F Cooper, B.S. Marquette University, 2015 The human photoreceptor mosaic underlies the first steps of vision; thus, even subtle defects in the mosaic can result in severe vision loss. The retina can be examined directly using clinical tools; however these devices lack the resolution necessary to visualize the photoreceptor mosaic. The primary limiting factor of these devices is the optical aberrations of the human eye. These aberrations are surmountable with the incorporation of adaptive optics (AO) to ophthalmoscopes, enabling imaging of the photoreceptor mosaic with cellular resolution. Despite the potential of AO imaging, much work remains before this technology can be translated to the clinic. Metrics used in the analysis of AO images are not standardized and are rarely subjected to validation, limiting the ability to reliably track structural changes in the photoreceptor mosaic geometry. Preceding the extraction of measurements, photoreceptors must be identified within the retinal image itself. This introduces error from both incorrectly identified cells and image distortion. We developed a novel method to extract measures of cell spacing from AO images that does not require identification of individual cells. In addition, we examined the sensitivity of various metrics in detecting changes in the mosaic and assessed the absolute accuracy of measurements made in the presence of image distortion. We also developed novel metrics for describing the mosaic, which may offer advantages over more traditional metrics of density and spacing. These studies provide a valuable basis for monitoring the photoreceptor mosaic longitudinally. As part of this work, we developed software (Mosaic Analytics) that can be used to standardize analytical efforts across different research groups. In addition, one of the more salient features of the appearance of individual cone photoreceptors is that they vary considerably in their reflectance. It has been proposed that this reflectance signal could be used as a surrogate measure of cone health. As a first step to understanding the cellular origin of these changes, we examined the reflectance properties of the rod photoreceptor mosaic. The observed variation in rod reflectivity over time suggests a common governing physiological process between rods and cones.
New murine model of alcoholic hepatitis in obesity-induced metabolic-associated fatty liver disease

Metabolic-associated fatty liver disease (MAFLD) and alcoholic hepatitis (AH) are among the most prevalent liver diseases worldwide, and their coexistence is common in clinical practice. However, currently established models of MAFLD-AH coexistence do not fully replicate their pathological characteristics and require sophisticated experimental techniques. Therefore, we aimed to develop an easily replicable model that mimics obesity-induced MAFLD-AH in patients. Our goal was to establish a murine model that replicates MAFLD and AH coexistence, resulting in significant liver injury and inflammation. To this end, we administered a single ethanol gavage dose to ob/ob mice on a chow diet. The administration of a single dose of ethanol led to elevated serum transaminase levels, increased liver steatosis, and apoptosis in ob/ob mice. Furthermore, ethanol binge caused a significant increase in oxidative stress in ob/ob mice, as measured via 4-hydroxynonenal. Importantly, the single dose of ethanol also markedly exacerbated liver neutrophil infiltration and upregulated the hepatic mRNA expression of several chemokines and neutrophil-related proteins, including Cxcl1, Cxcl2, and Lcn2. Whole-liver transcriptomic analysis revealed that ethanol-induced changes in gene expression profile shared similar features with AH and MAFLD. In ob/ob mice, a single dose of ethanol binge caused significant liver injury and neutrophil infiltration. This easy-to-replicate murine model successfully mimics the pathological and clinical features of patients with coexisting MAFLD and AH and closely resembles the transcriptional regulation seen in human disease.
Twenty-meter annual paddy rice area map for mainland Southeast Asia using Sentinel-1 synthetic-aperture-radar data

Abstract. Over 90 % of the world's rice is produced in the Asia–Pacific region. Synthetic-aperture radar (SAR) enables all-day and all-weather observations of rice distribution in tropical and subtropical regions. The complexity of rice cultivation patterns in tropical and subtropical regions makes it difficult to construct a representative data-relevant rice crop model, increasing the difficulty in extracting rice distributions from SAR data. To address this problem, a rice area mapping method for large regional tropical or subtropical areas based on time-series Sentinel-1 SAR data is proposed in this study. Based on the analysis of rice backscattering characteristics in mainland Southeast Asia, the combination of spatiotemporal statistical features with good generalization ability was selected and then input into the U-Net semantic segmentation model, combined with WorldCover data to reduce false alarms, finally the 20 m resolution rice area map of five countries in mainland Southeast Asia in 2019 was obtained. The proposed method achieved an accuracy of 92.20 % on the validation sample set, and the good agreement was obtained when comparing our rice area map with statistical data and other rice area maps at the national and provincial levels. The maximum coefficient of determination R2 was 0.93 at the national level and 0.97 at the provincial level. These results demonstrate the advantages of the proposed method in rice area mapping with complex cropping patterns and the reliability of the generated rice area maps. The 20 m annual paddy rice area map for mainland Southeast Asia is available at https://doi.org/10.5281/zenodo.7315076 (Sun et al., 2022b).
The Effect of Genotyping on the Number of Pharmacotherapeutic Gene–Drug Interventions in Chronic Kidney Disease Patients

Patients with chronic kidney disease (CKD) stage 3–5 are polypharmacy patients. Many of these drugs are metabolized by cytochrome P450 (CYP450) and CYP450. Genetic polymorphism is well known to result in altered drug metabolism capacity. This study determined the added value of pharmacogenetic testing to the routine medication evaluation in polypharmacy patients with CKD. In adult outpatient polypharmacy patients with CKD3-5 disease, a pharmacogenetic profile was determined. Then, automated medication surveillance for gene–drug interactions was performed based on the pharmacogenetic profile and the patients’ current prescriptions. Of all identified gene–drug interactions, the hospital pharmacist and the treating nephrologist together assessed clinical relevance and necessity of a pharmacotherapeutic intervention. The primary endpoint of the study was the total number of applied pharmacotherapeutic interventions based on a relevant gene–drug interaction. A total of 61 patients were enrolled in the study. Medication surveillance resulted in a total of 66 gene–drug interactions, of which 26 (39%) were considered clinically relevant. This resulted in 26 applied pharmacotherapeutic interventions in 20 patients. Systematic pharmacogenetic testing enables pharmacotherapeutic interventions based on relevant gene–drug interactions. This study showed that pharmacogenetic testing adds to routine medication evaluation and could lead to optimized pharmacotherapy in CKD patients.
A defense of QUD reasons contextualism

In this article, we defend the semantic theory, Question Under Discussion (QUD) Contextualism about Reasons that we develop in our monograph Semantics for Reasons against a series of objections that focus on whether our semantics can deliver predictions for some common examples, how we defend the semantic theory, and how we assess it compared to its competitors
Semi-parametric efficiency bounds and efficient estimation for high-dimensional models

Asymptotic lower bounds for estimation play a fundamental role in assessing the quality of statistical procedures. In this paper we consider the possibility of establishing semi-parametric efficiency bounds for high-dimensional models and construction of estimators reaching these bounds. We propose a local uniform asymptotic unbiasedness assumption for high-dimensional models and derive explicit lower bounds on the variance of any asymptotically unbiased estimator. We show that an estimator obtained by de-sparsifying (or de-biasing) an $\ell_1$-penalized M-estimator is asymptotically unbiased and achieves the lower bound on the variance: thus it is asymptotically efficient. In particular, we consider the linear regression model, Gaussian graphical models and Gaussian sequence models under mild conditions. Furthermore, motivated by the results of Le Cam on local asymptotic normality, we show that the de-sparsified estimator converges to the limiting normal distribution with zero mean and the smallest possible variance not only pointwise, but locally uniformly in the underlying parameter. This is achieved by deriving an extension of Le Cam's Lemma to the high-dimensional setting.
Limit theorems for Markov-modulated and reflected diffusion processes

In this thesis, asymptotic properties of two variants of one-dimensional diffusion processes, which are Markov-modulated and reflected Ornstein-Uhlenbeck processes, are studied. Besides the random term of the Brownian motion, the Markov-modulated diffusion process evolves in an extra random environment, namely the finite-state Markov chain. The reflected Ornstein-Uhlenbeck process behaves as an Ornstein-Uhlenbeck process which has instantaneous reflection at boundaries. They are widely used in modeling due to above mentioned their distinctive features and great analytical tractability. We obtain four limit theorems from the perspectives of weak convergence and large deviations. Firstly, we prove weak convergence of a sequence of Markov-modulated diffusion processes with rapid switching to an ordinary diffusion process by verifying its tightness property. Secondly, a sample-path large deviations principle for the coupling of the Markov-modulated diffusion process with small noise and the occupation measure of the rapid switching Markov chain is obtained. The large deviations principles for each individual term are derived by the contraction principle. Those results reveal interesting behavior of Markov-modulated diffusion process when the modulating Markov chain switches fast. Thirdly, transient asymptotics of large deviations type are acquired for reflected and doubly reflected Ornstein-Uhlenbeck processes. Fourthly, we prove central limit theorems and functional central limit theorems for the centered and scaled loss and idle processes of doubly reflected Ornstein-Uhlenbeck processes.
Mattic epipedon fragmentation strengthened the soil infiltration capacity of a hillside alpine meadow on the Qinghai‐Tibetan Plateau

Degradation of hillside alpine meadow ecosystems is a widespread problem that usually results in the fragmentation of the mattic epipedon (ME). The mattic epipedon plays a well‐known role in the hydrological cycle of alpine ecosystems due to its high water‐holding capacity. However, little is known about how ME fragmentation alters soil infiltrability—a key soil property that influences runoff and erosion processes as well as soil moisture dynamics. To address this issue, we contrasted the infiltration rates and soil and plant characteristics of preserved meadow patches (with full ME) and patches at two stages of ME fragmentation, namely, half ME and without ME. Our results showed that mattic epipedon fragmentation reduced aboveground plant biomass (mainly of sedges) by 58.6–65.6 g m−2 and root biomass by 5,643–10,054 g m−2. Soil compressive strength (11.6 kg cm−2) and total soil porosity (52%) of fragmented meadow patches without ME were significantly lower than in those with half (17.9 cm−2 and 62%, respectively) or full ME (31.7 cm−2 and 62.5%, respectively). In contrast, non‐capillary porosity and aggregate stability slightly increased with fragmentation and were highest at patches without ME. Importantly, soil infiltration rates in hillside alpine meadows greatly increased as a result of mattic epipedon fragmentation. Initial infiltration rates were approximately 10 and 20 times higher at patches with half ME and without ME (177 mm h−1 and 326 mm h−1, respectively) than at patches with the full ME (17 mm h−1). Moreover, steady‐state infiltration rates were approximately 6 and 9 times higher at patches with half ME and without ME (60 mm h−1 and 88 mm h−1, respectively) than at patches with the full ME (17 mm h−1). Overall, mattic epipedon fragmentation improved soil infiltrability by changing the soil and plant characteristics. These findings suggest that mattic epipedon fragmentation will lower runoff maintenance and have drastic effects on the water provisioning function of hillside alpine meadows on the Qinghai‐Tibetan Plateau.
From Physiology to Pathology: The Role of Mitochondria in Acute Kidney Injuries and Chronic Kidney Diseases

Background: Renal diseases remain an increasing public health issue affecting millions of people. The kidney is a highly energetic organ that is rich in mitochondria. Numerous studies have demonstrated the important role of mitochondria in maintaining normal kidney function and in the pathogenesis of various renal diseases, including acute kidney injuries (AKIs) and chronic kidney diseases (CKDs). Summary: Under physiological conditions, fine-tuning mitochondrial energy balance, mitochondrial dynamics (fission and fusion processes), mitophagy, and biogenesis maintain mitochondrial fitness. While under AKI and CKD conditions, disruption of mitochondrial energy metabolism leads to increased oxidative stress. In addition, mitochondrial dynamics shift to excessive mitochondrial fission, mitochondrial autophagy is impaired, and mitochondrial biogenesis is also compromised. These mitochondrial injuries regulate renal cellular functions either directly or indirectly. Mitochondria-targeted approaches, containing genetic (microRNAs) and pharmaceutical methods (mitochondria-targeting antioxidants, mitochondrial permeability pore inhibitors, mitochondrial fission inhibitors, and biogenesis activators), are emerging as important therapeutic strategies for AKIs and CKDs. Key Messages: Mitochondria play a critical role in the pathogenesis of AKIs and CKDs. This review provides an updated overview of mitochondrial homeostasis under physiological conditions and the involvement of mitochondrial dysfunction in renal diseases. Finally, we summarize the current status of mitochondria-targeted strategies in attenuating renal diseases.
Population Dynamics of Bithynia Tentaculata

Dynamics of snail populations are analyzed both qualitatively and quantitatively. Starting from the concrete measured data in the form of tables, the modelling logistic-type equations have been determined at first. These are then examined as deterministic and random dynamical systemsundervariousconstraints. Finally,theresultsobtainedfromsuch a mathematical analysis are interpreted in biological terms.
Especificação e Verificação Formal de Sistemas Distribuídos

Neste artigo utilizamos uma linguagem visual de especificação formal, chamada Gramáticas de Grafos Baseadas em Objetos (GGBO), para especificar sistemas distribuídos. A GGBO é comparada com a linguagem PROMELA (a PROcess MEta LAnguage), usada como entrada pelo verificador de modelos SPIN. Com base nesta comparação, define-se um mapeamento de GGBO para PROMELA. É visto como especificar e verificar propriedades sobre os modelos mapeados para PROMELA. Um algoritmo de eleição em anel é utilizado, no decorrer do artigo, para ilustrar a GGBO, a tradução e a verificação de propriedades.
Serological Cross-Reaction between Six Thiadiazine by Indirect ELISA Test and Their Antimicrobial Activity

Malaria is a parasitic infection caused by a protozoon of the genus Plasmodium, transmitted to humans by female biting mosquitoes of the genus Anopheles. Chloroquine and its derivates have caused the parasite to develop drug resistance in endemic areas. For this reason, new anti-malarial drugs as treatments are crucial. This work aimed to evaluate the humoral response. with hyper-immune sera, of mice immunized with six derivatives of tetrahydro-(2H)-1,3,5-thiadiazine-2-thione (bis-THTT) by indirect ELISA test. The cross-reactivity between the compounds as antigens and their microbial activity on Gram-positive and Gram-negative bacteria was evaluated. The results of the humoral evaluation by indirect ELISA show that three bis-THTTs react with almost all of the above. Besides, three compounds used as antigens stimulate the BALB/c mice’s immune system. The best combination of two antigens as a combined therapy displays similar absorbances between the antigens in the mixture, showing similar recognition by antibodies and their compounds. In addition, our results showed that different bis-THTT presented antimicrobial activity on Gram-positive bacteria, mainly on Staphylococcus aureus strains, and no inhibitory activity was observed on the Gram-negative bacteria tested.
Simulation of Inelastic Scattering in Molecular Junctions: Application to Inelastic Electron Tunneling Spectroscopy and Dissipation Effects

In this paper we investigate inelastic processes inside molecular junctions, comprising two electrodes, metallic or semiconducting, connected by a molecular bridge. Inelastic events are fundamental not only because they define the concept of dissipation and resistance at the nanoscale, but also because inelastic scattering can be used directly as probes to investigate characteristics of molecular junctions, such as the geometry of the molecular moiety. We present a non-equilibrium Green's function method (NEGF) which includes inelastic correction in the weak coupling between electrons and nuclei. The method includes also a formalism to include the relaxation of molecular vibrations into the contacts. The application of the formalism is in two directions: investigating Inelastic Electron Tunneling Spectroscopy and its selection rules and dissipation in fullerene on metallic and semiconductor surfaces in a STM setup.
Fifteen-Year Nationwide Trend in Antiplatelet Treatment among Drug-Eluting Stent Recipients in Korea: Many Patients Receive Very Prolonged Dual-Antiplatelet Treatment, and Newer Drugs Are Replacing the Older Ones

Drug-eluting stent (DES) recipients require 6–12 months of dual antiplatelet treatment (DAPT) and long-term aspirin mono-antiplatelet treatment (MAPT). Given the diversity of contemporary antiplatelet agents, antiplatelet treatment (APT) selection is becoming more complicated. We evaluated 15-year APT trends based on nationwide prescription data of 79,654 patients who underwent percutaneous coronary intervention (PCI) using DESs from 2002 to 2018 in Korea. DAPT (80.7%) was the most preferred initial APT post-PCI. Many DES recipients received prolonged DAPT (post-PCI 3 years: 41.0%; 10 years: 27.7%). There was a noticeable delay in DAPT-to-MAPT conversion from the mid to late 2000s (after the late-stent thrombosis concerns of first-generation DESs raised); the conversion after that was similar during the 2010s, occurring most robustly at 12–18 months post-PCI. Clopidogrel had long and increasingly been used for MAPT, surpassing aspirin. The recent increase in newer P2Y12 inhibitor prescriptions was noted. The patients treated with newer P2Y12 inhibitors were more likely younger men and presented with acute myocardial infarction. Real-world APT is evolving, and guideline–practice gaps exist. Further studies exploring the impact of diverse APT strategies on patient outcomes are expected to provide insights into optimal APT that can sophisticatedly balance the ischemic and bleeding risks.
Pre‐Buried ETL with Bottom‐Up Strategy Toward Flexible Perovskite Solar Cells with Efficiency Over 23%

With rapid development of photovoltaic technology, flexible perovskite solar cells (f‐PSCs) have attracted much attention for their light weight, high flexibility and portability. However, the power conversion efficiency (PCE) achieved so far is not yet comparable to that of rigid devices. This is mainly due to the great challenge of depositing homogeneous and high‐quality perovskite films on flexible substrate. In this study, the pre‐buried 3‐aminopropionic acid hydroiodide (3AAH) additives into the electron transport layer (ETL) and modified the ETL/perovskite (PVK) interface by a bottom‐up strategy. 3AAH treatment induced a templated perovskite grain growth and improved the quality of the ETL. By this, the residual stresses generated in PVK during the annealing‐cooling process are released and converted into micro‐compressive stresses. As a result, the defect density of f‐PSCs with pre‐buried 3AAH is reduced and the photovoltaic performance is greatly improved, reaching an exceptional PCE of 23.36%. This strategy provides a new idea to bridge the gap between flexible and rigid devices.
Application of low-dimension hyper-plane in anomaly detection of hyperspectral image

A nomaly detection plays an important role in hyperspectral military application field,because it can detect the objects whose spectra are different from their surroundings under the conditions of no spectral libraries and atmospheric correction.While the statistic characteristics of hyperspectral image are complicated,some errors exit on the statistic model and parameters estimation so that the anomaly detection methods based on statistic could not acquire the ideal results.From the view of struction of data set,a new approach of anomaly detection based on high dimensionality space hyper-plane in hyperspectral image was presented.Starting from Linear Mixture Modal(LMM),the geometric distribution characteristic of hyper-plane was used to detect image anomaly,which was based on the geometric distribution characteristic of image' s data sets in high dimensionality space.The approach is practical for it doesn' t need multivariate statistic model.Simulation and real datum verify the validity of the approach.
Emergent Visual Sensors for Autonomous Vehicles

For vehicles to navigate autonomously, they need to perceive and understand their immediate surroundings. Currently, cameras are the preferred sensors, due to their high performance and relatively low-cost compared with other sensors like LiDARs and Radars. However, their performance is limited by inherent imaging constraints, a standard RGB camera may perform poorly in extreme conditions, including low illumination, high contrast, bad weather (e.g. fog, rain, snow, etc.), glare, etc. Further, when using monocular cameras, it is more challenging to determine spatial distances than when using active range sensors such as LiDARs or Radars. Over the past years, novel image sensors, namely, infrared cameras, range-gated cameras, polarization cameras, and event cameras, have demonstrated strong potential. Some of them could be game-changers for future autonomous vehicles, they are the result of progress in sensor technology and the development of the accompanying perception algorithms. This paper presents in a systematic manner their principles, comparative advantages, data processing algorithms, and related applications. The purpose is to provide practitioners with an in-depth overview of novel sensing technologies that can contribute to the safe deployment of autonomous vehicles.