Miracle-dz/UniFAR-FTUs huggingface dataset:
Physics-based seismic evaluation method: Evaluating possible seismic moment based on microseismic information due to fluid stimulation

ABSTRACTThe forecasting and risk assessment of induced seismicity associated with fluid injection have considerable importance for subsurface energy development. We have developed a seismic evaluation method called the possible seismic moment (PoSeMo) model to assess the potential seismic moment that could be released in the future based on current seismic activity. The PoSeMo model assumes the existence of a representative parameter that can describe the seismic characteristics of a given field. This parameter is defined as the seismic moment density, which quantifies the seismic moment able to be released per rock volume. The rock volume presumed to be in critical condition because of stimulation is defined as the stimulated rock volume. The current stimulation condition for the PoSeMo model can be estimated from the product of these two parameters. The difference between the output of the PoSeMo model and the observed cumulative seismic moment corresponds to the cumulative seismic moment that could be .
Optimization of Internet of Things Remote Desktop Protocol for Low-Bandwidth Environments Using Convolutional Neural Networks

This paper discusses optimizing desktop image quality and bandwidth consumption in remote IoT GUI desktop scenarios. Remote desktop tools, which are crucial for work efficiency, typically employ image compression techniques to manage bandwidth. Although JPEG is widely used for its efficiency in eliminating redundancy, it can introduce quality loss with increased compression. Recently, deep learning-based compression techniques have emerged, challenging traditional methods like JPEG. This study introduces an optimized RFB (Remote Frame Buffer) protocol based on a convolutional neural network (CNN) image compression algorithm, focusing on human visual perception in desktop image processing. The improved RFB protocol proposed in this paper, compared to the unoptimized RFB protocol, can save 30–80% of bandwidth consumption and enhances remote desktop image quality, as evidenced by improved PSNR and MS-SSIM values between the remote desktop image and the original image, thus providing superior desktop image transmission quality.
Gene editing improves endoplasmic reticulum-mitochondrial contacts and unfolded protein response in Friedreich’s ataxia iPSC-derived neurons

Friedreich ataxia (FRDA) is a multisystemic, autosomal recessive disorder caused by homozygous GAA expansion mutation in the first intron of frataxin (FXN) gene. FXN is a mitochondrial protein critical for iron-sulfur cluster biosynthesis and deficiency impairs mitochondrial electron transport chain functions and iron homeostasis within the organelle. Currently, there is no effective treatment for FRDA. We have previously demonstrated that single infusion of wild-type hematopoietic stem and progenitor cells (HSPCs) resulted in prevention of neurologic and cardiac complications of FRDA in YG8R mice, and rescue was mediated by FXN transfer from tissue engrafted, HSPC-derived microglia/macrophages to diseased neurons/myocytes. For a future clinical translation, we developed an autologous stem cell transplantation approach using CRISPR/Cas9 for the excision of the GAA repeats in FRDA patients’ CD34+ HSPCs; this strategy leading to increased FXN expression and improved mitochondrial functions. The aim of the current study is to validate the efficiency and safety of our gene editing approach in a disease-relevant model. We generated a cohort of FRDA patient-derived iPSCs and isogenic lines that were gene edited with our CRISPR/Cas9 approach. iPSC derived FRDA neurons displayed characteristic apoptotic and mitochondrial phenotype of the disease, such as non-homogenous microtubule staining in neurites, increased caspase-3 expression, mitochondrial superoxide levels, mitochondrial fragmentation, and partial degradation of the cristae compared to healthy controls. These defects were fully prevented in the gene edited neurons. RNASeq analysis of FRDA and gene edited neurons demonstrated striking improvement in gene clusters associated with endoplasmic reticulum (ER) stress in the isogenic lines. Gene edited neurons demonstrated improved ER-calcium release, normalization of ER stress response gene, XBP-1, and significantly increased ER-mitochondrial contacts that are critical for functional homeostasis of both organelles, as compared to FRDA neurons. Ultrastructural analysis for these contact sites displayed severe ER structural damage in FRDA neurons, that was undetected in gene edited neurons. Taken together, these results represent a novel finding for disease pathogenesis showing dramatic ER structural damage in FRDA, validate the efficacy profile of our FXN gene editing approach in a disease relevant model, and support our approach as an effective strategy for therapeutic intervention for Friedreich’s ataxia.
Gene Regulation and Mitochondrial Activity During White and Brown Adipogenesis Are Modulated by KDM5 Histone Demethylase

Abstract Body fat accumulation differs between males and females and is influenced by both gonadal sex (ovaries vs testes) and chromosomal sex (XX vs XY). We previously showed that an X chromosome gene, Kdm5c, is expressed at higher levels in females compared to males and correlates with adiposity in mice and humans. Kdm5c encodes a KDM5 histone demethylase that regulates gene expression by modulating histone methylation at gene promoters and enhancers. Here, we use chemical inhibition and genetic knockdown to identify a role for KDM5 activity during early stages of white and brown preadipocyte differentiation, with specific effects on white adipocyte clonal expansion, and white and brown adipocyte gene expression and mitochondrial activity. In white adipogenesis, KDM5 activity modulates H3K4 histone methylation at the Dlk1 gene promoter to repress gene expression and promote progression from preadipocytes to mature adipocytes. In brown adipogenesis, KDM5 activity modulates H3K4 methylation and gene expression of Ucp1, which is required for thermogenesis. Unbiased transcriptome analysis revealed that KDM5 activity regulates genes associated with cell cycle regulation and mitochondrial function, and this was confirmed by functional analyses of cell proliferation and cellular bioenergetics. Using genetic knockdown, we demonstrate that KDM5C is the likely KDM5 family member that is responsible for regulation of white and brown preadipocyte programming. Given that KDM5C levels are higher in females compared to males, our findings suggest that sex differences in white and brown preadipocyte gene regulation may contribute to sex differences in adipose tissue function.
An appraisal of traditional knowledge of plant poisoning of livestock and its validation through acute toxicity assay in rats

Background: Kashmir Himalaya hosts the most diverse and rich flora in the world, which serves as grazing land for millions of small ruminants in the area. While most plant species are beneficial, some can be poisonous, causing economic losses and animal health issues for livestock. Consequently, this study is the first comprehensive report on the traditional phyto-toxicological knowledge in District Muzaffarabad and the assessment of its authenticity through experimental studies in rats. Methods: The data regarding traditional knowledge was gathered from 70 key respondents through semi-structured interviews, which was quantitatively analyzed and authenticated through plant extract testing on Wistar female rats and comparison with published resources. Results: A total of 46 poisonous plant species belonging to 23 families and 38 genera were reported to be poisonous in the study area. Results revealed that leaves were the most toxic plant parts (24 species, 52.1%), followed by the whole plant (18 species, 39.1%), stem (17 species, 36.9%), and seeds (10 species, 21.7%). At the organ level, liver as most susceptible affected by 13 species (28.2%), followed by the gastrointestinal tract (15 species, 32.6%), nervous system (13 species, 8.2%), dermis (8 species, 17.3%), renal (7 species, 15.2%), respiratory (4 species, 8.7%), cardiovascular system (3 species, 6.5%), and reproductive system (2 species, 4.3%). The poisonous plant species with high Relative frequency citation (RFC) and fidelity level (FL) were Nerium oleander (RFC, 0.6; FL, 100), Lantana camara (RFC, 0.6; FL, 100), and Ricinus communis (RFC, 0.6; FL, 100). Experimental assessment of acute toxicity assay in rats revealed that Nerium oleander was the most toxic plant with LD50 of (4,000 mg/kg), trailed by Ricinus communis (4,200 mg/kg), L. camara (4,500 mg/kg), and Datura stramonium (4,700 mg/kg); however, other plants showed moderate to mild toxicity. The major clinical observations were anorexia, piloerection, dyspnea, salivation, tachypnea, constipation, diarrhea, tremor, itchiness, and dullness. Conclusion: This study showed that numerous poisonous plants pose a significant risk to the livestock industry within Himalayan territory, leading to substantial economic losses. Consequently, it is of utmost importance to conduct further comprehensive studies on the phytotoxicity of plants.
Precision Agriculture Applied to Harvesting Operations through the Exploitation of Numerical Simulation

When it comes to harvesting operations, precision agriculture needs to consider both combine harvester technology and the precise execution of the process to eliminate harvest losses and minimize out-of-work time. This work aims to propose a complete control framework defined by a two-layer-based algorithm and a simulation environment suitable for quantitative harvest loss, time, and consumption analyses. In detail, the path-planning layer shows suitable harvesting techniques considering field boundaries and irregularities, while the path-tracking layer presents a vision-guided Stanley Lateral Controller. In order to validate the developed control framework, challenging driving scenarios were created using IPG-CarMaker software to emulate wheat harvesting operations. Results showed the effectiveness of the designed controller to follow the reference trajectory under regular field conditions with zero harvest waste and minimum out-of-work time. Whereas, in presence of harsh road irregularities, the reference trajectory should be re-planned by either selecting an alternative harvesting method or overlapping the harvester header by some distance to avoid missing crops. Quantitative and qualitative comparisons between the two harvesting techniques as well as a relationship between the level of irregularities and the required overlap will be presented. Eventually, a Driver-in-the-loop (DIL) framework is proposed as a methodology to compare human and autonomous driving.
Is it possible to identify physical-motor profiles of preschool children on their association with selected biosocial factors?

Biosocial factors play a crucial role in the physical-motor development (PMD) of children during the preschool age. The present study aims to identify physical-motor profiles throughout preschool age (3–6 years) and explore associations between profiles and selected biosocial factors such as age, sex, prematurity, weight, height, BMI, and participation in extracurricular physical activities. Data from 412 typically developing children (46.6% girls and 53.4% boys), aged 35–71 months (M = 51.21, SD = 10.47) was collected using the Psychomotor Activities Checklist and specifically the scale of Psycho-Motor Aspects. Cluster analysis made it possible to define four different childhood PMD profiles. High PMD; High PMD except left laterality; medium-low PMD; and low PMD. High PMD profile includes older children, with anthropometric measurements closer to the WHO recommendations, fewer preterm children, and greater participation in extracurricular physical activities. Low PMD profile includes younger children, with weight slightly above and height slightly below the WHO recommendations and low participation in extracurricular physical activities. This study allows us to identify specific trends that may be decisive for the motor development of children throughout preschool age, highlighting selected biological variables and participation in extracurricular physical activities.
THE MAPPING OF THE AGRICULTURAL INNOVATION SYSTEM IN NICARAGUA

The paper report an innovation study done by CATIE/CINET joint research collaboration about the agricultural innovations system in Nicaragua. By utilizing the notion of knowledge and information management among the actors and sector involved it was generated learning capability analysis that allows mapping the actual configuration of the agricultural innovation system. The mapping and discussion about the features of the strategic alliances need to conform an agricultural innovation systems are underlined and policy recommendations are established.
Leveraging Deep Learning for High-Resolution Optical Satellite Imagery From Low-Cost Small Satellite Platforms

The expansion of small satellite networks in earth's orbit has resulted in a plethora of earth optical imagery available to the civil, defense, and commercial sectors. Small satellites (less than 1000 kg in mass) and their constellations can be delivered rapidly and at low cost and are more difficult to target by adversaries—a key consideration in the defense industry. Yet, small satellite size constraints often result in reduced payload capacity, reduced power capacity, or loss of redundancy. Traditionally, the cost of an optical telescope on board a satellite scales at roughly the square of the aperture, meaning that it costs four times as much to double the resolution of the imaging hardware. However, deep learning has shown considerable success in the areas of super-resolution and enhancing the pixel resolution of optical imagery. These deep learning methods have the potential to provide optical resolution capabilities rivaling larger satellites and their telescopes, while maintaining the benefits of small satellites—smaller physical size (which lowers launch vehicle costs and provides a basis for large constellations), reduced manufacturing time, and lower manufacturing costs. By providing low-cost small satellite platforms with the same capabilities as larger satellites, the cost for high-resolution in-orbit optical imagery is reduced alongside time to orbit. In this work, we detail a deep-learning-based approach, which improves optical satellite imagery to five times the original pixel-based resolution without the need or expense of increasing the capabilities of the imager through larger telescope apertures. The approach—demonstrated on Terran Orbital's GEOStare SV2 mission imagery—is generally applicable to any optical satellite image and is agnostic to the mission, satellite manufacturer, optical payload specifications, or data source. This capability provides a basis for small satellite missions and constellations—and their optical payloads—to rival the native hardware-based resolutions available through larger satellites with wider telescope apertures at a significantly reduced cost.
Genome-Wide Analysis of the Lateral Organ Boundaries Domain (LBD) Gene Family in Sweet Potato (Ipomoea batatas)

The LBD family is a plant-specific transcription factor family that plays an important role in a variety of biological processes. However, the function of IbLBD genes in sweet potato remains unclear. In this study, we identified a total of 53 IbLBD genes in sweet potato. Genetic structure showed that most of the IbLBD genes contained only two exons. Following the phylogenetic investigation, the IbLBD gene family was separated into Class I (45 members) and Class II (8) members. Both classes of proteins contained relatively conservative Motif1 and Motif2 domains. The chromosomal locations, gene duplications, promoters, PPI network, and GO annotation of the sweet potato LBD genes were also investigated. Furthermore, gene expression profiling and real-time quantitative PCR analysis showed that the expression of 12 IbLBD genes altered in six separate tissues and under various abiotic stresses. The IbLBD genes belonging to Class I were mostly expressed in the primary root, the pencil root, and the leaves of sweet potatoes, while the genes belonging to Class II were primarily expressed in the various sweet potato roots. The IbLBD genes belonging to Class I were mostly expressed in the primary root, the pencil root, and the leaves of sweet potatoes, while the genes belonging to Class II were primarily expressed in the fibrous root, pencil root, and tuber root.
A Novel High Sensitivity Fiber SPR Sensor for the Specific Detection of Baohuoside-I

Fiber SPR sensors can be used for rapid detection of active ingredients in traditional Chinese medicine. To achieve micro-detection of specific active ingredients in traditional Chinese medicine, its further development requires significantly improving sensitivity and achieving specific detection. In this article, we proposed and demonstrated a new type of highly sensitive and specific detection fiber SPR sensor, which employed a graded index multimode fiber as the sensing fiber. Due to the self-focusing effect of the graded index multimode fiber, the mode number of transmission light in the sensing area is significantly reduced. By using an eccentric core fiber to inject light and controlling the depth of the flat bottom groove made on the graded index multimode fiber to control the incident angle of light, the sensitivity of the fiber SPR sensor is greatly improved. By modifying the Retinoid X Receptor <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula> (RXR<inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>) protein on the surface of sensing gold film, the specific recognition of the active ingredient Baohuoside I in traditional Chinese medicine Epimedium has been achieved. According to the experiment, the sensor has a detection sensitivity of 0.66 nm/(<inline-formula> <tex-math notation="LaTeX">$\mu \text{g}$ </tex-math></inline-formula>/ml) and a LOD of <inline-formula> <tex-math notation="LaTeX">$0.15 ~\mu \text{g}$ </tex-math></inline-formula>/ml. At a concentration of <inline-formula> <tex-math notation="LaTeX">$100 ~\mu \text{g}$ </tex-math></inline-formula>/ml, the wavelength shift of Baohuoside I or a mixed solution containing Baohuoside I is higher than 60 nm, while the wavelength shift of other components is lower than 10 nm. The new sensor proposed in this article has a stable structure, high sensitivity, and specific recognition ability, providing a new solution for the highly sensitive detection of specific active ingredients in traditional Chinese medicine using fiber SPR sensors.
Recent Advances in Low-Dimensional Metal Oxides via Sol-Gel Method for Gas Detection

Low-dimensional metal oxides have drawn significant attention across various scientific domains due to their multifaceted applications, particularly in the field of environment monitoring. Their popularity is attributed to a constellation of unique properties, including their high surface area, robust chemical stability, and remarkable electrical conductivity, among others, which allow them to be a good candidate for detecting CO, CO2, H2, NH3, NO2, CH4, H2S, and volatile organic compound gases. In recent years, the Sol-Gel method has emerged as a powerful and versatile technique for the controlled synthesis of low-dimensional metal oxide materials with diverse morphologies tailored for gas sensing applications. This review delves into the manifold facets of the Sol-Gel processing of metal oxides and reports their derived morphologies and remarkable gas-sensing properties. We comprehensively examine the synthesis conditions and critical parameters governing the formation of distinct morphologies, including nanoparticles, nanowires, nanorods, and hierarchical nanostructures. Furthermore, we provide insights into the fundamental principles underpinning the gas-sensing mechanisms of these materials. Notably, we assess the influence of morphology on gas-sensing performance, highlighting the pivotal role it plays in achieving exceptional sensitivity, selectivity, and response kinetics. Additionally, we highlight the impact of doping and composite formation on improving the sensitivity of pure metal oxides and reducing their operation temperature. A discussion of recent advances and emerging trends in the field is also presented, shedding light on the potential of Sol-Gel-derived nanostructures to revolutionize the landscape of gas sensing technologies.
Distributed Primal-Dual Proximal Algorithms for Convex Optimization Involving Three Composite Functions

This article develops a novel distributed primal-dua l proximal algorithm (PDPA-Dist) and its corresponding randomized version (Rand-PDPA-Dist) for solving convex optimization problems. The local objective consists of a smooth function and two possibly nonsmooth ones, with one involving a linear mapping. At each iteration, PDPA-Dist allows each agent to perform local computations by communicating with its neighbors, while Rand-PDPA-Dist is executed with a randomly and independently activated subset of agents. The proposed algorithms recover new distributed extensions of known centralized algorithms and existing distributed schemes, depending on certain special setups. Both PDPA-Dist and Rand-PDPA-Dist achieve exact linear convergence rates provided that local objective functions satisfy piecewise linear-quadratic or certain quadratic growth conditions. Finally, the performance and effectiveness of the proposed algorithms are demonstrated by resolving a distributed model predictive control (DMPC) problem.