Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Scale Based Approach for Denoising Real-World Noisy Image Using Curvelet Thresholding: Scope and Beyond

Na $\ddot {i}$ ve simulated additive white Gaussian noise (AWGN) may not fully characterize the complexity of real world noisy images. Owing to optimal sparsity in image representation, we propose a curvelet based model for denoising real-world RGB images. Initially, the image is decomposed in three curvelet scales, namely: the approximation scale (that retains low-frequency information), the coarser scale and the finest scale (that preserves high-frequency components). Coefficients in the approximation and finest scale are estimated using NLM filter, while a scale dependent threshold is adopted for signal estimation in the coarser scale. The reconstructed image in spatial domain is further processed using Guided Image Filter (GIF) to suppress the ringing artifacts due to curvelet thresholding. The proposed approach known as CTuNLM method is extended for color image denoising using uncorrelated YUV color space. Extensive experiments on multi-channel real noisy images are conducted in comparison with eight sate-of-the-art methods. With four encouraging qualitative and quantitative measures including PSNR and SSIM, we found that CTuNLM method achieves better denoising performance in terms of noise reduction and detail preservation. We further examined the potential of proposed approach by focusing only on the Finest scale curvelet Coefficients (FC). Features like small details, edges and textures always add up to improve the overall denoising performance, while minimizing spurious details. We studied “The Curious Case of the Finest Scale” and constructed “Deep Curvelet-Net”: an encoder-decoder-based CNN architecture, as a pilot work. The encoder uses multiscale spatial characteristics from noisy FC, while the decoder processes de-noised FC under the supervision of encoder’s multiscale spatial attention map. The “Deep Curvelet-Net” links encoder multiscale feature modeling with decoder spatial attention supervision to learn the most essential features for denoising. The CNN-based architecture only estimates FC, while all other CTuNLM stages are left unchanged to produce the denoised output. Results presented in this article validated the design of proposed CNN architecture in curvelet domain and motivated us to search beyond classical thresholding and/or filtering approaches.
Partition-Global Dual-Layer Collaborative Voltage Control Strategy for Active Distribution Network With High Proportion of Renewable Energy

With the integration of highly penetrative distributed photovoltaics into the distribution network, the imbalance between PV generation and load power becomes increasingly apparent, resulting in significant voltage security and stability issues in the distribution network. To overcome the limitations of traditional global voltage control and regional voltage cooperative control, a novel two-layer coordinated voltage control strategy, combining regional control and global control, is proposed for active distribution networks. Firstly, an adaptive partitioning of the active distribution network is achieved, without predefining the number of partitions, using the modular function gain change indicator and the Fast Unfolding algorithm. This adaptive partitioning ensures optimal regional control. Secondly, based on the voltage-power sensitivity principle, the reactive power control margin of PV sources is prioritized for regional-level reactive power control at critical nodes experiencing voltage violations. If the reactive power control margin within the region is insufficient, a combination of global-level reactive power control and active power control is employed. Lastly, simulation analysis is discussed by the IEEE 141-node traditional distribution network to confirm the effectiveness of the proposed method. Results demonstrate its ability to reduce the duration of voltage regulation and overcome the limitations of coordinated control range. The proposed method maximizes the utilization of the reactive power control margin of PV sources and significantly enhances PV penetration levels.
Walking around the preferred speed: examination of metabolic, perceptual, spatiotemporal and stability parameters

Walking is the most accessible and common type of physical activity. Exercising at one’s self-selected intensity could provide long-term benefits as compared to following prescribed intensities. The aim of this study was to simultaneously examine metabolic, perceptual, spatiotemporal and stability parameters at an absolute 3 km·h−1 speed range around the individual preferred walking speed (PWS). Thirty-four young sedentary adults (18 women) volunteered to walk at seven speeds relative to their PWS in 3-min trials interspaced with 3-min rest intervals. Results indicated a significant main effect of speed on all studied variables. While metabolic, perceptual and spatiotemporal values were sensitive to the smallest change in speed (i.e., 0.5 km·h−1), a significant increase in the rate of carbohydrate oxidation and decrease in %fat oxidation were only observed at speeds above PWS. Results also revealed significantly higher coefficients of variation for stride characteristics at speeds below PWS only. Moreover, analyses of best fit models showed a quadratic relationship between most variables and speed, with the exceptions of metabolic cost of transport, rating of perceived exertion and stride duration that changed exponentially with speed. PWS coincided with optimized mechanical efficiency, fuel oxidation and gait stability. This indicated that walking below PWS decreased both mechanical efficiency and stability of gait, while walking above PWS increased carbohydrate oxidation. Those factors seem to play an important role as determinants of PWS. We suggest that walking at PWS may provide benefits in terms of fat oxidation while optimizing gait stability.
Recurrent atrial fibrillation episodes related to monosodium glutamate (MSG) - a case report

Cardiac disease is largely believed to be a gift of modern sedentary life style and junk foods. Yet often the clinicians fail to find the etiologic factors in many of the patients. This case report is about recurrent episodes of atrial fibrillation in a physician. Careful history revealed the relationship of having ingested Chinese food before every episode of the atrial fibrillation. Aspartame and flavor enhancer monosodium glutamate have been considered as the food ingredients that may cause such arrythmias. The patient had to be treated aggressively with drugs and even cardiac cryoablation of four pulmonary veins and radiofrequency ablation of right atrium. Key words: Monosodium glutamate (MSG); Exocitotoxins; Cardiac arrhythmias; Atrial fibrillation Citation: Purvez A, Valentine CM, Monfredi OJ, Engel GD. Recurrent atrial fibrillation episodes related to monosodium glutamate (MSG) - a case report. Anaesth. pain intensive care 2023;27(4):613−615. DOI: 10.35975/apic.v27i4. 2273 Received: June 29, 2023; Reviewed: July 4, 2023; Accepted: July 4, 2023
Joint DOA Estimation and Dereverberation Based on Multi-Channel Linear Prediction Filtering and Azimuth Sparsity

Source localization in reverberant environments has been a prominent research topic in the past two decades. In this paper, instead of the commonly employed time-frequency (TF) bin based methods which rely on empirically selected threshold values, we leverage the microphone array signal model comprising an early reverberant component and a late reverberant component, to propose a novel method for the source localization problem in reverberant environments. Our proposed criterion involves the joint removal of the late reverberant component using the multi-channel linear prediction (MCLP) filter, while estimating the directions of arrival (DOAs) of the actual sources using the early component signals. By applying the azimuth sparsity constraint, the true DOA can be estimated with high resolution and free from the interference of the early reflections. To solve the proposed criterion, DOAs, source signals, and MCLP filter coefficients are estimated by alternative iterations. Additionally, we present a source localization criterion specifically designed for the single source scenario as a special case of the multiple sources scenario. Finally, a source number estimation method and a postprocessing procedure are discussed for searching the global solutions to our proposed criteria. Evaluations with both simulated and realistic data demonstrate the advantages of our proposed methods over the baseline methods.
A Review of Current Approaches in the Pretreatment of Bone for Radiocarbon Dating by AMS

Although the reliability of 14C dates of bone has increased greatly since AMS methods permitted better pretreatment on smaller samples, most old, badly contaminated or severely weathered bone still give serious problems. Several groups have recently proposed improvements to sample purification methods, often supported by a number of 14C measurements. We present here an overview of these improvements. The issue is complicated by the following: 1. Different problems are presented depending on age, preservation and degree of contamination of bone. 2. Methods may or may not be developed with routine application in mind. 3. Determining the conditions for which any method can be regarded as reliable is not at all straightforward.
Dupilumab Efficacy on Asthma Functional, Inflammatory, and Patient-Reported Outcomes across Different Disease Phenotypes and Severity: A Real-Life Perspective

Dupilumab is currently approved for the treatment of Type 2 severe asthma and chronic rhinosinusitis with nasal polyps (CRSwNP). Few studies have specifically reported on dupilumab efficacy on asthma outcomes as a primary objective in a real-life setting, in patients with and without CRSwNP. Our study aimed to explore the efficacy of dupilumab on functional, inflammatory, and patient-reported outcomes in asthma patients across different disease phenotypes and severity, including mild-to-moderate asthma coexisting with CRSwNP. Data from 3, 6, and 12 months follow-up were analyzed. Asthma (FEV1%, Tiffeneau%, ACT, FeNO, oral steroid use, exacerbation rate, and blood eosinophilia) and polyposis (SNOT22, VAS, NPS) outcomes showed a rapid (3 months) and sustained (6 and 12 months) significant change from baseline, despite most of the patients achieving oral steroid withdrawal. According to the sensitivity analysis, the improvement was not conditioned by either the presence of polyposis or severity of asthma at baseline. Of note, even in the case of milder asthma forms, a significant further improvement was recorded during dupilumab treatment course. Our report provides short-, medium-, and long-term follow-up data on asthma outcomes across different diseases phenotypes and severity, contributing to the real-world evidence related to dupilumab efficacy on upper and lower airways T2 inflammation.
Mood and microbes: a comprehensive review of intestinal microbiota’s impact on depression

Depression is considered a multifaceted and intricate mental disorder of growing concern due to its significant impact on global health issues. The human gut microbiota, also known as the “second brain,” has an important role in the CNS by regulating it through chemical, immunological, hormonal, and neurological processes. Various studies have found a significant bidirectional link between the brain and the gut, emphasizing the onset of depression therapies. The biological and molecular processes underlying depression and microbiota are required, as the bidirectional association may represent a novel study. However, profound insights into the stratification and diversity of the gut microbiota are still uncommon. This article investigates the emerging evidence of a bacterial relationship between the gut and the brain’s neurological system and its potential pathogenicity and relevance. The interplay of microbiota, immune system, nervous system neurotransmitter synthesis, and neuroplasticity transitions is also widely studied. The consequences of stress, dietary fibers, probiotics, prebiotics, and antibiotics on the GB axis are being studied. Multiple studies revealed the processes underlying this axis and led to the development of effective microbiota-based drugs for both prevention and treatment. Therefore, the results support the hypothesis that gut microbiota influences depression and provide a promising area of research for an improved knowledge of the etiology of the disease and future therapies.
04. Global warming, body size and conservation in a Qinghai-Tibet Plateau lizard

Global mean temperatures have increased by 0.3–0.6°C since the late 19th century, affecting the physiology, distributions, phenology and adaptations of plants and animals. In the Qinghai-Tibet Plateau, average annual temperatures increased by an average of 0.25°C per decade from the 1970s to the 1990s, and by an average of 0.34°C per decade thereafter. Using museum collections from the 1950s to the 2000s and published references, we tested the hypothesis that body size of the toad-headed lizard Phrynocephalus vlangalii in the Qinghai-Tibet Plateau declined between 1954 and 2008 as a response to global warming. However, body size of males and females did not vary significantly between 1954 and 2008, probably due to the reciprocity between higher food availability and earlier age at sexual maturity. We suggest that human activity might result in declining population sizes in the future despite the lack of an apparent current response to changing climates.
Multi-attribute decision-making method based on Taylor expansion

Determining attribute weights is an indispensable step in multi-attribute decision-making problems, and it is also a top priority in the study of multi-attribute decision-making problems. Existing methods for determining attribute weights do not completely and effectively reflect the decision-maker’s dependency preferences, which will result in unreasonable ranking results for decision-makers. To solve this problem, this article proposes a feature-weighted multi-attribute decision-making method based on Taylor expansion. The method uses the natural base and the eigenvalues of the matrix to construct the feature-weighted coefficients and weights; normalizes all the feature vectors of the matrix; and constructs a new weight vector. Combined with the example to analyze and verify, the method makes reasonable use of all decision information, which saves the decision time of decision-makers.
Urban vs. rural: colorectal cancer survival and prognostic disparities from 2000 to 2019

This study aimed to analyze the differences in colorectal cancer (CRC) survival between urban and rural areas over the past 20 years, as well as investigate potential prognostic factors for CRC survival in both populations. Using registry data from Surveillance, Epidemiology, and End Results (SEER) from 2000 to 2019, 463,827 CRC cases were identified, with 85.8% in urban and 14.2% in rural areas. The mortality of CRC surpassed its survival rate by the sixth year after diagnosis in urban areas and the fifth year in rural areas. Furthermore, the 5-year overall survival (OS) of CRC increased by 2.9–4.3 percentage points in urban and 0.6–1.5 percentage points in rural areas over the past two decades. Multivariable Cox regression models identified independent prognostic factors for OS and disease-specific survival (DSS) of CRC in urban and rural areas, including age over 40, Black ethnicity, and tumor size greater than 5 cm. In addition, household income below $75,000 was found to be an independent prognostic factor for OS and DSS of CRC in urban areas, while income below $55,000 was a significant factor for rural areas. In conclusion, this study found a notable difference in CRC survival between rural and urban areas. Independent prognostic factors shared among both rural and urban areas include age, tumor size, and race, while household income seem to be area-specific predictive variables. Collaboration between healthcare providers, patients, and communities to improve awareness and early detection of CRC may help to further advance survival rates.
Drought Policy And Politics In India The Need For A Long Term Perspective

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Cairo's contested garbage : sustainable solid waste management and the zabaleen's right to the city

FAHMI, Wael. SUTTON, Keith. Cairo's contested garbage : sustainable solid waste management and the zabaleen's right to the city. in Sustainability, 2010, 2, 1765-1783 Over the decades, the Zabaleen, the traditional waste collectors of Cairo, have created what is arguably one of the world’s most efficient and sustainable resource-recovery and waste-recycling systems. Yet the continuation of this intricate relationship between community, environment and livelihood is jeopardized by the offi.
Microbial Pathway Thermodynamics: Stoichiometric Models Unveil Anabolic and Catabolic Processes

The biotechnological exploitation of microorganisms enables the use of metabolism for the production of economically valuable substances, such as drugs or food. It is, thus, unsurprising that the investigation of microbial metabolism and its regulation has been an active research field for many decades. As a result, several theories and techniques were developed that allow for the prediction of metabolic fluxes and yields as biotechnologically relevant output parameters. One important approach is to derive macrochemical equations that describe the overall metabolic conversion of an organism and basically treat microbial metabolism as a black box. The opposite approach is to include all known metabolic reactions of an organism to assemble a genome-scale metabolic model. Interestingly, both approaches are rather successful at characterizing and predicting the expected product yield. Over the years, macrochemical equations especially have been extensively characterized in terms of their thermodynamic properties. However, a common challenge when characterizing microbial metabolism by a single equation is to split this equation into two, describing the two modes of metabolism, anabolism and catabolism. Here, we present strategies to systematically identify separate equations for anabolism and catabolism. Based on metabolic models, we systematically identify all theoretically possible catabolic routes and determine their thermodynamic efficiency. We then show how anabolic routes can be derived, and we use these to approximate biomass yield. Finally, we challenge the view of metabolism as a linear energy converter, in which the free energy gradient of catabolism drives the anabolic reactions.
Alteration of functional connectivity network in population of objectively-defined subtle cognitive decline

Abstract The objectively-defined subtle cognitive decline individuals had higher progression rates of cognitive decline and pathological deposition than healthy elderly, indicating a higher risk of progressing to Alzheimer’s disease. However, little is known about the brain functional alterations during this stage. Thus, we aimed to investigate the functional network patterns in objectively-defined subtle cognitive decline cohort. Forty-two cognitive normal, 29 objectively-defined subtle cognitive decline and 55 mild cognitive impairment subjects were included based on neuropsychological measures from the Alzheimer’s disease Neuroimaging Initiative dataset. Thirty cognitive normal, 22 objectively-defined subtle cognitive declines and 48 mild cognitive impairment had longitudinal MRI data. The degree centrality and eigenvector centrality for each participant were calculated by using resting-state functional MRI. For cross-sectional data, analysis of covariance was performed to detect between-group differences in degree centrality and eigenvector centrality after controlling age, sex and education. For longitudinal data, repeated measurement analysis of covariance was used for comparing the alterations during follow-up period among three groups. In order to classify the clinical significance, we correlated degree centrality and eigenvector centrality values to Alzheimer’s disease biomarkers and cognitive function. The results of analysis of covariance showed significant between-group differences in eigenvector centrality and degree centrality in left superior temporal gyrus and left precuneus, respectively. Across groups, the eigenvector centrality value of left superior temporal gyrus was positively related to recognition scores in auditory verbal learning test, whereas the degree centrality value of left precuneus was positively associated with mini-mental state examination total score. For longitudinal data, the results of repeated measurement analysis of covariance indicated objectively-defined subtle cognitive decline group had the highest declined rate of both eigenvector centrality and degree centrality values than other groups. Our study showed an increased brain functional connectivity in objectively-defined subtle cognitive decline individuals at both local and global level, which were associated with Alzheimer’s disease pathology and neuropsychological assessment. Moreover, we also observed a faster declined rate of functional network matrix in objectively-defined subtle cognitive decline individuals during the follow-ups.
Phytoplankton Species Richness along Coastal and Estuarine Salinity Continua

The high number of freshwater species at low salinity and the correspondingly high number of marine species at high salinity enveloping a conspicuous richness minimum at intermediate salinities has shaped our basic understanding of biodiversity along a coastal salinity gradient for almost 80 years. Visualized as the Remane curve, this iconic concept was originally based on sedentary macroinvertebrates in the Baltic Sea. To what extent the concept can be generalized, particularly to free-drifting organisms, is currently debated. Here we use approximately 16,000 phytoplankton samples from two large coastal ecosystems—the Baltic Sea and Chesapeake Bay—to analyze the relationship between salinity and phytoplankton species richness. Alpha diversity showed a consistent variation along the salinity gradient, with a minimum at mesohaline salinities of around 7–9. Rarefied species pools at narrow salinity intervals also showed reduced diversity at intermediate salinities, surrounded by high richness toward both ends of the gradient. The cumulative likelihood of species presence validated the minimum at intermediate salinities. Community composition changed abruptly at the α diversity minimum in the Baltic Sea, while it changed gradually along the salinity gradient in Chesapeake Bay. We conclude that the Remane concept is in every respect valid for phytoplankton.