Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive spectrum segmentation Ramanujan decomposition and its application to gear fault diagnosis

Ramanujan Fourier mode decomposition (RFMD) is a novel non-stationary signal decomposition method, which can decompose a complex signal into several components and extract the periodic characteristics of the signal. However, the mode generation method adopted by RFMD does not consider the physical meaning of the component signal, which makes over-decomposition when dealing with real-life gear signals with complex modulation characteristics, thus destroying the integrity of the signal sideband, increasing the difficulty of subsequent analysis, and even losing key fault information. The iterative envelope-segmentation algorithm combines the modulation characteristics of the local fault gear signal and divides the original signal into a limited number of dominant frequency bands containing the modulation region in the Fourier spectrum, thereby ensuring that the obtained frequency bands contain rich fault information. Based on the above algorithm, a new adaptive decomposition method is proposed in this paper, which is adaptive spectrum segmentation Ramanujan decomposition (ASSRD). ASSRD uses fault envelope harmonic noise ratio as the index to evaluate the fault information content of component signals and uses it to assist the iterative envelope-segmentation algorithm to complete the adaptive segmentation of the Fourier spectrum. Finally, based on the segmentation result, the inverse RFT reconstruction of each frequency band is performed. Thus, the signal is decomposed into a finite number of component signals containing rich fault information. In addition, through the experiment on the gear simulation signal and the measured crack fault gear signal, the ASSRD method is compared with the original RFMD method and the existing ensemble empirical mode decomposition (EMD), variational mode decomposition, empirical wavelet transform, and singular spectrum decomposition method, verifying the feasibility and superiority of ASSRD in gear fault diagnosis. Besides, a comparative experiment based on compound faults diagnosis is carried out, in which ensemble EMD, Fourier decomposition method, empirical wavelet transform, and sparse decomposition are involved. The results show that the proposed method can extract the local fault information in the gear signal more effectively, and the performance is better than the comparison method.
Deep learning-based super-resolution holographic data storage

In this paper, we propose a super-resolution holographic data storage system based on deep learning. A low-pass filter was introduced into the Fourier plane to remove the high frequency. This produces a blurred intensity image of the reconstructed beam. A convolutional neural network is used to establish the relationship between the blurred intensity image and the data page. The encoded phase data page can be directly demodulated from a captured intensity image, which is a non-interferometric method without iterations. The function of the filter is to generate the blurred intensity image and to reduce the recording area to improve the recording intensity. Usually, the limit of the aperture is the Nyquist size. Here, by introducing embedded data on the phase data page, the aperture size of the recording can be reduced to smaller than the Nyquist size. A simulation experiment was established to verify the effectiveness of the proposed method.
RLPTO: A Reinforcement Learning-Based Performance-Time Optimized Task and Resource Scheduling Mechanism for Distributed Machine Learning

With the wide application of deep learning, the amount of data required to train deep learning models is becoming increasingly larger, resulting in an increased training time and higher requirements for computing resources. To improve the throughput of a distributed learning system, task scheduling and resource scheduling are required. This article proposes to combine ARIMA and GRU models to predict the future task volume. In terms of task scheduling, multi-priority task queues are used to divide tasks into different queues according to their priorities to ensure that high-priority tasks can be completed in advance. In terms of resource scheduling, the reinforcement learning method is adopted to manage limited computing resources. The reward function of reinforcement learning is constructed based on the resources occupied by the task, the training time, the accuracy of the model. When a distributed learning model tends to converge, the computing resources of the task are gradually reduced so that they can be allocated to other learning tasks. The results of experiments demonstrate that RLPTO tends to use more compu-ting nodes when facing tasks with large data scale and has good scalability. The distributed learning system reward experiment shows that RLPTO can make the computing cluster get the largest reward.
Compressive Sensing-Based Born Iterative Method for Tomographic Imaging

The problem of imaging nonweak scatterers in the compressive sensing (CS) framework, without recurring to the contrast-source formulation, is addressed by means of an innovative hybrid born iterative CS method (BI-CSM). Toward this end, the born iterative (BI) formulation of the nonlinear inverse scattering equations is adopted and a customized version of the CS-based inversion is implemented to retrieve the target contrast while estimating the electric field distribution without recurring to time-expensive full-wave simulations. The selected numerical and experimental results, drawn from a wide validation, are presented to illustrate the procedural steps of the BI-CSM and to assess, also comparatively, the features, the potentialities, and the limitations of the proposed inversion technique.
Characterisation of the chemical properties and behaviour of aerosols in the urban environment

Atmospheric aerosols have adverse effects on human health, air quality, and visibility and frequently result in severe pollution events, particularly in urban areas. However, the sources of aerosols and the processes governing their behaviour in the atmosphere, including those which lead to high concentrations, are not well understood thus limit our ability to accurately assess and forecast air quality.Presented here are the first long-term chemical composition measurements from an urban environment using an Aerodyne compact Time-of-Flight Aerosol Mass Spectrometer (cToF-AMS). Organic aerosols (OA) were observed to account for a significant fraction (44%) of the total non-refractory submicron mass during 2012 at the urban background site in North Kensington, London, followed by nitrate (28%), sulphate (14%), ammonium (13%), and chloride (1%). The sources and components of OA were determined using Positive Matrix Factorisation (PMF) and attributed as hydrocarbon-like OA (HOA), cooking OA (COA), solid fuel OA (SFOA), type 1 oxygenated OA (OOA1), and type 2 oxygenated OA (OOA2), where HOA, COA, and SFOA were observed to be of equal importance across the year. The concentration of secondary OA increased during the summer yet the extent of oxidation, as defined by the oxygen content, showed no variability during the year.The main factors governing the diurnal, monthly, and seasonal trends observed in all organic and inorganic species were meteorological conditions, specific nature of the sources, and availability of precursors. Regional and transboundary pollution influenced total aerosol concentrations and high concentration events were observed to be governed by different factors depending on season. High-Resolution ToF-AMS measurements were used to further probe OA behaviour, where two SFOA factors were derived from PMF analysis in winter, which likely represent differences in burn conditions. In the summer an OA factor was identified, likely of primary origin, which was observed to be strongly associated with organic nitrates and anthropogenic emissions.This work uses instruments and techniques that have not previously been used in this way in an urban environment, where the results further the understanding of the chemical components of urban aerosols. Aerosol sources are likely to change in the future with increases in solid fuel burning as vehicular emissions decrease, with significant implications on air quality and health. Thus it is important to understand aerosol sources and behaviour in order to develop effective pollution abatement strategies.
A Distinct Microglial Cell Population Expressing Both CD86 and CD206 Constitutes a Dominant Type and Executes Phagocytosis in Two Mouse Models of Retinal Degeneration

Microglial cells are the key regulators of inflammation during retinal degeneration (RD) and are conventionally classified as M1 or M2. However, whether the M1/M2 classification exactly reflects the functional classification of microglial cells in the retina remains debatable. We examined the spatiotemporal changes of microglial cells in the blue-LED and NaIO3-induced RD mice models using M1/M2 markers and functional genes. TUNEL assay was performed to detect photoreceptor cell death, and microglial cells were labeled with anti-IBA1, P2RY12, CD86, and CD206 antibodies. FACS was used to isolate microglial cells with anti-CD206 and CD86 antibodies, and qRT-PCR was performed to evaluate Il-10, Il-6, Trem-2, Apoe, and Lyz2 expression. TUNEL-positive cells were detected in the outer nuclear layer (ONL) from 24 h to 72 h post-RD induction. At 24 h, P2RY12 was decreased and CD86 was increased, and CD86/CD206 double-labeled cells occupied the dominant population at 72 h. And CD86/CD206 double-labeled cells showed a significant increase in Apoe, Trem2, and Lyz2 levels but not in those of Il-6 and Il-10. Our results demonstrate that microglial cells in active RD cannot be classified as M1 or M2, and the majority of microglia express both CD86 and CD206, which are involved in phagocytosis rather than inflammation.
Advancements in Nanoparticle Deposition Techniques for Diverse Substrates: A Review

Nanoparticle deposition on various substrates has gained significant attention due to the potential applications of nanoparticles in various fields. This review paper comprehensively analyzes different nanoparticle deposition techniques on ceramic, polymeric, and metallic substrates. The deposition techniques covered include electron gun evaporation, physical vapor deposition, plasma enriched chemical vapor deposition (PECVD), electrochemical deposition, chemical vapor deposition, electrophoretic deposition, laser metal deposition, and atomic layer deposition (ALD), thermophoretic deposition, supercritical deposition, spin coating, and dip coating. Additionally, the sustainability aspects of these deposition techniques are discussed, along with their potential applications in anti-icing, antibacterial power, and filtration systems. Finally, the review explores the importance of deposition purities in achieving optimal nanomaterial performance. This comprehensive review aims to provide valuable insights into state-of-the-art techniques and applications in the field of nanomaterial deposition.
Analiza możliwości wykorzystania zasobów wód podziemnych na podstawie numerycznych modeli wybranych struktur wodonośnych rejonu Wrocławia

THE USE OF POTENTIAL GROUNDWATER RESOURCES FROM NUMERICAL MODELS OF SELECTED HYDROGEOLOGICAL STRUCTURES NEAR WROCŁAW Abstract. The aim of the research was to evaluate capability of giving furtherance to the water supply system in the Wroclaw agglomeration from groundwater reservoirs. They focused on MGWBs in the vicinity of the city. Numerical model calculations prove that groundwater resources of Cenozoic structures are appropriate for localising large intakes to significantly support the Wroclaw water supply system. Disposal groundwater resources in the study areas were evaluated at ~170 000 m 3 /d. Apart from indicating the groundwater resources in the MGWB 322 and the formally cancelled MGWB 321-E, it was also shown the possibility of extraction of 15 000 m 3 /d from the Bogdaszowice structure included in the MGWB 319. Recharge from infiltration was evaluated at 3.0 l/s km 2 .
A Survey of Latest Wi-Fi Assisted Indoor Positioning on Different Principles

As the location-based service (LBS) plays an increasingly important role in real life, the topic of positioning attracts more and more attention. Under different environments and principles, researchers have proposed a series of positioning schemes and implemented many positioning systems. With widely deployed networks and massive devices, wireless fidelity (Wi-Fi) technology is promising in the field of indoor positioning. In this paper, we survey the authoritative or latest positioning schemes for Wi-Fi-assisted indoor positioning. To this end, we describe the problem and corresponding applications, as well as an overview of the alternative methods. Then, we classify and analyze Wi-Fi-assisted indoor positioning schemes in detail, as well as review related work. Furthermore, we point out open challenges and forecast promising directions for future work.
Nutritional Composition and Anti-Type 2 Diabetes Mellitus Potential of Femur Bone Extracts from Bovine, Chicken, Sheep, and Goat: Phytochemical and In Vivo Studies

Nutritional deficits in one’s diet have been established as the key risk factor for T2DM in recent years. Nutritional therapy has been demonstrated to be useful in treating T2DM. The current study was carried out to assess the nutritional composition of bovine (12 months), chicken (4 months), sheep (13 months), and goat (9 months) femur bone extracts, as well as their potential therapeutic effects on T2DM regression in a Wistar albino rat model (500 mg/kg b.wt.). The proximate composition of the different extracts, their fatty acid composition, their amino acids, and their mineral contents were identified. In vivo data indicated considerably improved T2DM rats, as seen by lower serum levels of TL, TG, TC, ALT, AST, ALP, bilirubin, creatinine, urea, IL-6, TNF-α, sICAM-1, sVCAM-1, and MDA. Low levels of HDL-C, GSH, and total proteins were restored during this study. Histological investigations of liver and pancreatic tissue revealed that the distribution of collagen fibers was nearly normal. The bovine extract, on the other hand, was the most active, followed by the sheep, goat, and finally chicken extract. This research could result in the creation of a simple, noninvasive, low-cost, and reliable method for T2DM control, paving the way for potential early therapeutic applications in T2DM control.
The efficacy and safety of oral antibiotic treatment in patients with chronic low back pain and Modic changes: A systematic review and meta‐analysis

Abstract Background This systematic review and meta‐analysis aimed to summarize evidence regarding the effectiveness and safety of oral antibiotic intervention for chronic low back pain (CLBP) patients with/without type‐1 Modic changes (MC1). Methods AMED, CINAHL, Cochrane Library, Embase, and Medline were searched from inception to March 3, 2023. Randomized controlled trials (RCTs) or non‐RCTs that investigated the effectiveness or safety of oral antibiotics in treating CLBP patients were eligible for inclusion. Two independent reviewers screened abstracts, full‐text articles, and extracted data. The methodological quality of each included article were evaluated by RoB2 and NIH quality assessment tools. The quality of evidence was appraised by GRADE. Meta‐analyses were performed, where applicable. A subgroup analysis was conducted to evaluate the RCTs and case series separately, and to evaluate the effect of removing a low‐quality RCT. Results Three RCTs and four case series were included. All Amoxicillin‐clavulanate/Amoxicillin treatments lasted for approximately 3 months. Moderate‐ and low‐quality evidence suggested that antibiotic was significantly better than placebo in improving disability and quality of life in CLBP patients with MC1 at 12‐month follow‐up, respectively. Low‐quality evidence from meta‐analyses of RCTs showed that oral antibiotic was significantly better than placebo in improving pain and disability in CLBP patients with MC1 immediately post‐treatment. Very low‐quality evidence from the case series suggested that oral Amoxicillin‐clavulanate significantly improved LBP/leg pain, and LBP‐related disability. Conversely, low‐quality evidence found that oral Amoxicillin alone was not significantly better than placebo in improving global perceived health in patients with CLBP at the 12‐month follow‐up. Additionally, oral antibiotic users had significantly more adverse effects than placebo users. Conclusions Although oral antibiotics were statistically superior to placebo in reducing LBP‐related disability in patients with CLBP and concomitant MC1, its clinical significance remains uncertain. Future large‐scale high‐quality RCTs are warranted to validate the effectiveness of antibiotics in individuals with CLBP.
Interacciones tróficas entre dos especies simpátricas de hormigas cortadoras y el ensamble de plantas en el Monte central

Aunque la disponibilidad de agua es considerada el principal factor que regula a las comunidades de plantas en los ecosistemas aridos, las interacciones con los herbivoros tambien pueden jugar un rol importante. En ecosistemas neotropicales, el gremio de los herbivoros se caracteriza por la ausencia de grandes ungulados y la presencia destacada de las hormigas cortadoras. Estas hormigas pueden interactuar de diversas maneras con la comunidad de plantas, generando cambios en su dinamica y composicion. El objetivo de este trabajo fue analizar los efectos reciprocos entre las plantas y las hormigas cortadoras en el Monte central, y en particular las posibles consecuencias de la accion de las hormigas sobre la estructura y la dinamica de las comunidades de plantas. Para ello se estudiaron diferentes aspectos de la ecologia trofica de Acromyrmex lobicornis y Acromyrmex striatus. Ambas especies forrajean activamente desde la primavera hasta el otono, pero A. lobicornis es mayoritariamente nocturna y A. striatus es exclusivamente diurna. En general, A. lobicornis forrajea a temperaturas menores que A. striatus sin superponerse en sus temperaturas de forrajeo optimo, lo cual podria deberse a que las especies tienen distintos rangos de tolerancia a la temperatura o a que presentan cierto grado de evitacion. Ambas muestran una dieta generalista y oportunista, cosechando un alto porcentaje de las especies de plantas disponibles en su entorno. La composicion de su dieta y su grado de selectividad depende principalmente de las variaciones estacionales e interanuales en la disponibilidad de los recursos. A nivel de colonia, A. lobicornis cosecha mucho mas material vegetal que A. striatus, aunque esta diferencia no se observa a nivel poblacional ya que las colonias de A. striatus son mucho mas abundantes. Cada especie llega a cosechar 70–72 Kg/ha·ano, o, entre ambas, el ~20% de la productividad primaria en el area de estudio. Estas hormigas tambien cosechan una gran cantidad de frutos y pueden actuar como dispersoras de semillas. En el caso del arbusto Condalia microphylla, no solo depositan las semillas lejos de la planta madre y en micrositios favorables sino que, ademas, estas semillas dispersadas tienen mayor capacidad de germinacion que las que no fueron manipuladas por las hormigas. Este estudio muestra que en estos ecosistemas deserticos las interacciones entre las hormigas cortadoras y las plantas son frecuentes e intensas, y pueden jugar un rol importante en la dinamica de las comunidades de plantas.
Variable Switching Frequency Techniques for Power Converters: Review and Future Trends

Variable-frequency (VF) techniques have been widely applied in the fields of power electronics and motor drives. Based on the categories of frequency variables, the VF techniques can be typically classified into three perspectives: variable drive speed frequency, variable switching frequency (VSF), and variable sampling frequency. The speed frequency is related to the motor speed/torque control and has already been well summarized. VSF techniques for power converters can also be leveraged in isolated/nonisolated topologies to improve the performances in the aspects of switching loss reduction, power transfer optimization, optimal voltage/current control, and electromagnetic interference noise reduction. The corresponding works on VSF techniques lack systematic study and review. This article studies the VSF techniques based on the methodologies and application purposes. The detailed classification and analysis for VSF techniques are derived according to the existing publications. The typical analyzed techniques have been compared and validated experimentally in this article to show the effectiveness. Also, the inspirations and future trends are studied and summarized.
A Dietary Source of High Level of Fluoroquinolone Tolerance in mcr-Carrying Gram-Negative Bacteria

The emergence of antibiotic tolerance, characterized by the prolonged survival of bacteria following antibiotic exposure, in natural bacterial populations, especially in pathogens carrying antibiotic resistance genes, has been an increasing threat to public health. However, the major causes contributing to the formation of antibiotic tolerance and underlying molecular mechanisms are yet poorly understood. Herein, we show that potassium sorbate (PS), a widely used food additive, triggers a high level of fluoroquinolone tolerance in bacteria carrying mobile colistin resistance gene mcr. Mechanistic studies demonstrate that PS treatment results in the accumulation of intracellular fumarate, which activates bacterial two-component system and decreases the expression level of outer membrane protein OmpF, thereby reducing the uptake of ciprofloxacin. In addition, the supplementation of PS inhibits aerobic respiration, reduces reactive oxygen species production and alleviates DNA damage caused by bactericidal antibiotics. Furthermore, we demonstrate that succinate, an intermediate product of the tricarboxylic acid cycle, overcomes PS-mediated ciprofloxacin tolerance. In multiple animal models, ciprofloxacin treatment displays failure outcomes in PS preadministrated animals, including comparable survival and bacterial loads with the vehicle group. Taken together, our works offer novel mechanistic insights into the development of antibiotic tolerance and uncover potential risks associated with PS use.