Large Complex Research Articles

Super-shear ruptures steered by pre-stress heterogeneities during the 2023 Kahramanmaraş earthquake doublet

The 2023 M7.8 and M7.5 earthquake doublet near Kahramanmaraş, Turkey, provides insight regarding how large earthquakes rupture complex faults. Here we determine the faults geometry using surface ruptures and Synthetic Aperture Radar measurements, and the rupture kinematics from the joint inversion of high-rate Global Navigation Satellite System (GNSS), strong-motion waveforms, and GNSS static displacement. The M7.8 event initiated on a splay fault and subsequently propagated along the main East Anatolian Fault with an average rupture velocity between 3.0 and 4.0 km/s. In contrast, the M7.5 event demonstrated a bilateral supershear rupture of about 5.0–6.0 km/s over an 80 km length. Despite varying strike and dip angles, the sub-faults involved in the mainshock are nearly optimally oriented relative to the local stress tensor. The second event ruptured a fault misaligned with respect to the regional stress, also hinting at the effect of local stress heterogeneity in addition to a possible free surface effect.

Quality and Efficiency of Coupled Iterative Coverage Path Planning for the Inspection of Large Complex 3D Structures

To enable unmanned aerial vehicles to generate coverage paths that balance inspection quality and efficiency when performing three-dimensional inspection tasks, we propose a quality and efficiency coupled iterative coverage path planning (QECI-CPP) method. First, starting from a cleaned and refined mesh model, this was segmented into narrow and normal spaces, each with distinct constraint settings. During the initialization phase of viewpoint generation, factors such as image resolution and orthogonality degree were considered to enhance the inspection quality along the path. Then, the optimization objective was designed to simultaneously consider inspection quality and efficiency, with the relative importance of these factors adjustable according to specific task requirements. Through iterative adjustments and optimizations, the coverage path was continuously refined. In numerical simulations, the proposed method was compared with three other classic methods, evaluated across five aspects: image resolution, orthogonality degree, path distance, computation time, and total path cost. The comparative simulation results show that the QECI-CPP achieves maximum image resolution and orthogonality degree while maintaining inspection efficiency within a moderate computation time, demonstrating the effectiveness of the proposed method. Additionally, the flexibility of the planned path is validated by adjusting the weight coefficient in the optimized objective function.

OOPS: Object-Oriented Polarization Software for analysis of fluorescence polarization microscopy images.

Most essential cellular functions are performed by proteins assembled into larger complexes. Fluorescence Polarization Microscopy (FPM) is a powerful technique that goes beyond traditional imaging methods by allowing researchers to measure not only the localization of proteins within cells, but also their orientation or alignment within complexes or cellular structures. FPM can be easily integrated into standard widefield microscopes with the addition of a polarization modulator. However, the extensive image processing and analysis required to interpret the data have limited its widespread adoption. To overcome these challenges and enhance accessibility, we introduce OOPS (Object-Oriented Polarization Software), a MATLAB package for object-based analysis of FPM data. By combining flexible image segmentation and novel object-based analyses with a high-throughput FPM processing pipeline, OOPS empowers researchers to simultaneously study molecular order and orientation in individual biological structures; conduct population assessments based on morphological features, intensity statistics, and FPM measurements; and create publication-quality visualizations, all within a user-friendly graphical interface. Here, we demonstrate the power and versatility of our approach by applying OOPS to punctate and filamentous structures.

Establishment of a rapid detection method for Mycoplasma pneumoniae based on RPA-CRISPR-Cas12a technology

Mycoplasma pneumoniae can cause respiratory infections and pneumonia, posing a serious threat to the health of children and adolescents. Early diagnosis of Mycoplasma pneumoniae infection is crucial for clinical treatment. Currently, diagnostic methods for Mycoplasma pneumoniae infection include pathogen detection, molecular biology techniques, and bacterial culture, all of which have certain limitations. Here, we developed a rapid, simple, and accurate detection method for Mycoplasma pneumoniae that does not rely on large equipment or complex operations. This technology combines the CRISPR-Cas12a system with recombinase polymerase amplification (RPA), allowing the detection results to be observed through fluorescence curves and immunochromatographic lateral flow strips.It has been validated that RPA-CRISPR/Cas12a fluorescence analysis and RPA-CRISPR/Cas12-immunochromatographic exhibit no cross-reactivity with other common pathogens, and The established detection limit was ascertained to be as low as 102 copies/µL.Additionally, 49 clinical samples were tested and compared with fluorescence quantitative polymerase chain reaction, demonstrating a sensitivity and specificity of 100%. This platform exhibits promising clinical performance and holds significant potential for clinical application, particularly in settings with limited resources, such as clinical care points or resource-constrained areas.

DISTRIBUTION OF THE THALLOID LIVERWORT GENUS MARCHANTIA (MARCHANTIACEAE) IN NORTH SUMATRA, INDONESIA

ARTICLE HIGLIGHTS- The survey method was successful in identifying the species Marchantia and mapping their distribution in North Sumatra- Eight taxa of Marchantia confirmed in North Sumatra, M. emarginata subsp. cuneiloba has the most widely distributed species. - Species distribution linked to environmental factors like elevation, humidity, rainfall, soil types, slope, solar intensity, and types of land coverABSTRACTMarchantia is one of the large genus complex thalloid liverworts (Marchantiophyta). The species of Marchantia has a wide distribution throughout the world, and occupies a variety of substrates. Studies on the presence and distribution of Marchantia species are still limited in North Sumatra. Therefore, the research was carried out to inventory the species of Marchantia and map their distribution in North Sumatra. Survey method was used to inventory the species of Marchantia, covering 9 locations, namely: Aek Nauli Forest, Bukit Barisan National Forest Park, Bukit Lawang, Resort Cinta Raja, Dolok Tinggi Raja Nature Reserve, Sibayak Mountain, Sicike-cike Natural Park, Silima-lima waterfall, and Taman Eden 100 Natural Park. Geographic Information System (GIS) was used to map the distribution of the species. The results showed that there were eight taxa of Marchantia confirmed in North Sumatra, namely, M. acaulis, M. emarginata subsp. emarginata, M. emarginata subsp. cuneiloba, M. geminata, M. paleacea subsp. paleacea, M. polymorpha, M. treubii, and Marchantia sp. The most widely distributed species of Marchantia is M. emarginata subsp. cuneiloba, found in 7 study locations. Species with the least distribution are M. treubii and Marchantia sp., each species found only in one location. Marchantia spp. in North Sumatra spread at an altitude of 77 to 1976 m alt, occupying habitats with 6 types of soil (orthic acrisol, humic andosol, humic acrisol, and humic cambisol), with rainfall of 1800-3600 mm/year. Marchantia species are found on sloping plains to steep, in various habitat, namely secondary forest, primary and secondary forest borders, dryland farming, primary and plantation borders, and plantations. The results of this study are important for the conservation of Marchantia spp. in North Sumatra considering the many benefits of the species.

Assessing the domain-based local pair natural orbital (DLPNO) approximation for non-covalent interactions in sizable supramolecular complexes.

The titular domain-based local pair natural orbital (DLPNO) approximation is the most widely used method for extending correlated wave function models to large molecular systems, yet its fidelity for intermolecular interaction energies in large supramolecular complexes has not been thoroughly vetted. Non-covalent interactions are sensitive to tails of the electron density and involve nonlocal dispersion that is discarded or approximated if the screening of pair natural orbitals (PNOs) is too aggressive. Meanwhile, the accuracy of the DLPNO approximation is known to deteriorate as molecular size increases. Here, we test the DLPNO approximation at the level of second-order Møller-Plesset perturbation theory (MP2) and coupled-cluster theory with singles, doubles, and perturbative triples [CCSD(T)] for a variety of large supramolecular complexes. DLPNO-MP2 interaction energies are within 3% of canonical values for small dimers with ≲10 heavy atoms, but for larger systems, the DLPNO approximation is often quite poor unless the results are extrapolated to the canonical limit where the threshold for discarding PNOs is taken to zero. Counterpoise correction proves to be essential in reducing errors with respect to canonical results. For a sequence of nanoscale graphene dimers up to (C96H24)2, extrapolated DLPNO-MP2 interaction energies agree with canonical values to within 1%, independent of system size, provided that the basis set does not contain diffuse functions; these cause the DLPNO approximation to behave erratically, such that results cannot be extrapolated in a meaningful way. DLPNO-CCSD(T) calculations are typically performed using looser PNO thresholds as compared to DLPNO-MP2, but this significantly impacts accuracy for large supramolecular complexes. Standard DLPNO-CCSD(T) settings afford errors of 2-6 kcal/mol for dimers involving coronene (C24H12) and circumcoronene (C54H18), even at the DLPNO-CCSD(T1) level.

Spatial variation, emissions, transport, and risk assessment of organophosphate esters in two large petrochemical complexes in southern China

Organophosphate esters (OPEs) serve as significant flame retardants and plasticizers in various petrochemical downstream products. The petrochemical industry could be a potential source of atmospheric OPEs, but their emissions from this industry are poorly understood. The present study revealed the spatial variation, emission, and atmospheric transport of traditional and novel OPEs (TOPEs and NOPEs, respectively) in atmospheric particulate matter (PM) across Hainan and Guangdong petrochemical complexes (HNPC and GDPC, respectively) in southern China. The total concentrations of TOPEs ranged from 232 to 46,002 pg/m3 and from 200 to 20,347 pg/m3 in the HNPC and GDPC, respectively, which were substantially higher than those of NOPEs (HNPC: 23.5−147 pg/m3, GDPC: 13.9−465 pg/m3). Enterprises involved in the production of downstream petrochemical products presented relatively high concentrations of OPEs, indicating evident emissions of these pollutants in the petrochemical industry. The correlations of PM-bound OPEs in the atmosphere are determined mainly by their coaddition to industrial products or their coexistence in technical mixtures. The annual emissions of TOPEs and NOPEs in the HNPC were 42.6 kg and 0.34 kg, respectively, and those in the GDPC were 116 kg and 1.85 kg, respectively. OPEs from the HNPC can reach Vietnam, Cambodia, and Guangxi Province, China, and those from the GDPC can reach Guangxi Province and Hunan Province via atmospheric transmission after 24 h of emission. The OPE concentrations reaching the receptor regions were generally less than 3.20 pg/m3. Risk assessment revealed that OPE inhalation exposure on two petrochemical complexes likely poses minor risks for people living in the study areas, but the risk resulting from two chlorinated OPEs should be noted since they are close to the threshold values. This study has implications for enhancing control measures for OPE emissions to reduce health risks related to the petrochemical industry.

Влияние теплового стресса на оплодотворяемость и многоплодие свиноматок

Abstract. The study of the effect of heat stress on the reproductive parameters of pigs is an urgent problem all over the world. Knowing the degree of influence of heat stress on pigs of different breeds will allow you to choose economically sound solutions to this problem in specific conditions. The propose is to study the effect of heat stress on some indicators of reproduction of sows of different breeds (large white, landrace, duroc, MAXGRO). Methods. The study was conducted on a large pig breeding complex. The material for the analysis was data on changes in air temperature in the breeding farm in the period from June to August (13 weeks) and data on the fertilization and duration of pregnancy of sows fertilized during this period and the size of the offspring obtained from them. Scientific novelty. For the first time, a comparative analysis of the effect of heat stress on fertilization, duration of pregnancy and the size of the offspring of sows of four breeds – large white, landrace, duroc, MAXGRO – was carried out on a wide population of pigs. Different sensitivity of sows to heat stress was revealed. Results. From the 4th to the 6th week of the experiment, the sows were in a state of increasing heat stress – the average daily temperature during this period increased to 27.68 ± 1.36 °C. The negative effect of hyperthermia on fertilization was recorded with a delay of 1–3 weeks, depending on the breed. The most sensitive to heat stress were sows of the duroc breed – fertilization decreased by 25.00 % compared to the pre-stress period, the least – sows of the large white breed – fertilization decreased by 9.82 %. The duration of pregnancy was not affected by heat stress. As well as fertilization, heat stress had a negative effect on the size of the litter. The most sensitive were sows of duroc and MAXGRO breeds – the litter size decreased by 3.77 and 3.61 heads compared to the pre-stress period, the least – sows of the large white breed, the size of the litter decreased by 0.38 heads. duroc sows are the most sensitive to heat stress, then, according to sensitivity reduction, MAXGRO, landrace and large white.

Recovering 3D salt dome by gravity data inversion using ResU-Net++

In geophysical research, gravity-based inversion is essential for identifying geologic anomalies, mapping rock structures, and extracting resources such as oil and minerals. However, traditional gravity inversion methods face challenges, such as the volumetric effects of gravity fields and the management of large complex matrices. Unsupervised learning techniques often struggle with overfitting and interpreting gravity data. This study explores the application of various U-Net-based network architectures in gravity inversion, each offering distinct challenges and advantages. Nested U-Net, although effective, requires a high parameter count, leading to extended training periods. The recurrent residual U-Net’s implicit attention mechanism restricts its dynamic adaptability, whereas the attention U-Net’s lack of residual connections raises concerns about gradient issues. This research comprehensively analyzes the training processes, core functionalities, and module distribution of these networks, including the residual U-Net++. Our synthetic studies compare these networks with traditional focused regularized gravity inversion for reconstructing density anomalies. The results demonstrate that the nested U-Net closely approximates the actual model despite some redundancy. The recurrent residual U-Net indicates an improved alignment with minimal redundancies, and the attention U-Net is effective in density prediction but encounters difficulties in areas of low density. Notably, the residual U-Net++ excels in inversion modeling, achieving the lowest misfit percentage and accurately replicating density values. In practical applications, the residual U-Net++ impressively reconstructs the F2 salt diapir in the Nordkapp Basin with well-defined boundaries that closely match seismic data interpretations. These results underscore the capabilities of the residual U-Net++ in geophysical data analysis, structural reconstruction, and inversion, demonstrating its effectiveness in simulated settings and real-world scenarios.

Sub‐6 GHz plane wave generator design for automotive antenna over‐the‐air testing

AbstractAutomotive antennas are gaining importance due to their increasingly important role for autonomous driving with the development of the Internet of Vehicles. However, over‐the‐air testing on automotive antennas is difficult owing to its large volume and complex body structure. Plane wave generators can approximate uniform plane waves in the near field of the device under test, which can greatly reduce the measurement distance and thereby decreasing the cost compared with direct far‐field solutions. This letter designs three plane wave generators for three quiet zone sizes selected according to the vehicle structure at 5.9 GHz, achieving quiet zone sizes of 1.45 m m, 2.9m m, and 3.9 m m, respectively. Within the three quiet zones, amplitude deviations of 0.82, 0.34, and 0.34 dB and phase deviations of , and are realized, respectively, according to the numerical simulations. Uncertainty analysis is further implemented to investigate the robustness of the designed PWGs proposed in this letter.

Microbes as marine habitat formers and ecosystem engineers.

Despite their small individual size, marine prokaryotic and eukaryotic microbes can form large 3D structures and complex habitats. These habitats contribute to seafloor heterogeneity, facilitating colonization by animals and protists. They also provide food and refuge for a variety of species and promote novel ecological interactions. Here we illustrate the role of microbes as ecosystem engineers and propose a classification based on five types of habitat: microbial mats, microbial forests, microbial-mineralized habitats, microbial outcrops and microbial nodules. We also describe the metabolic processes of microbial habitat formers and their ecological roles, highlighting current gaps in knowledge. Their biogeography indicates that these habitats are widespread in all oceans and are continuously being discovered across latitudes and depths. These habitats are also expected to expand under future global change owing to their ability to exploit extreme environmental conditions. Given their high ecological relevance and their role in supporting endemic species and high biodiversity levels, microbial habitats should be included in future spatial planning, conservation and management measures.

A single-domain antibody library based on a stability-engineered human VH3 scaffold

Using conventional immunoglobulin G (IgG) molecules as therapeutic agents presents several well-known disadvantages owing to their large size and structural complexity, negatively impacting development and production efficiency. Single-domain antibodies (sdAbs) are the smallest functional antibody format (~ 15 kDa) and represent a viable alternative to IgG in many applications. However, unlike natural single-domain antibodies, such as camelid VHH, the variable domains of conventional antibodies show poor physicochemical properties when expressed as sdAbs. This report identified stable sdAb variants of human VH3-23 from a framework region 2-randomized human VH library by phage display selection under thermal challenge. Synthetic complementarity determining region diversity was introduced to one of the selected variants with high thermal stability, expression level, and monomeric content to construct a human VH sdAb library. The library was validated by panning against a panel of antigens, and target-specific binders were identified and characterized for their affinity and biophysical properties. The results of this study suggest that a synthetic sdAb library based on a stability-engineered human VH scaffold could be a facile source of high-quality sdAb for many practical applications.

The DUF579 proteins GhIRX15s regulate cotton fiber development by interacting with proteins involved in xylan synthesis

Cotton provides the most abundant natural fiber for the textile industry. The mature cotton fiber largely consists of secondary cell walls with the highest proportion of cellulose and a small amount of hemicellulose and lignin. To dissect the roles of hemicellulosic polysaccharides during fiber development, four IRREGULAR XYLEM 15 (IRX15) genes, GhIRX15-1/-2/-3/-4, were functionally characterized in cotton. These genes encode DUF579 domain-containing proteins, which are homologs of AtIRX15 involved in xylan biosynthesis. The four GhIRX15 genes were predominantly expressed during fiber secondary wall thickening, and the encoded proteins were localized to the Golgi apparatus. Each GhIRX15 gene could restore the xylan deficient phenotype in the Arabidopsis irx15irx15l double mutant. Silencing of GhIRX15s in cotton resulted in shorter mature fibers with a thinner cell wall and reduced cellulose content as compared to the wild type. Intriguingly, GhIRX15-2 and GhIRX15-4 formed homodimers and heterodimers. In addition, the GhIRX15s showed physical interaction with glycosyltransferases GhGT43C, GhGT47A and GhGT47B, which are responsible for synthesis of the xylan backbone and reducing end sequence. Moreover, the GhIRX15s can form heterocomplexes with enzymes involved in xylan modification and side chain synthesis, such as GhGUX1/2, GhGXM1/2 and GhTBL1. These findings suggest that GhIRX15s participate in fiber xylan biosynthesis and modulate fiber development via forming large multiprotein complexes.

“Architecture, construction system and functioning of the roman saltworks of O Areal (Vigo-Galicia-Spain). A reference in the investigation of salt production in the roman world”

These Roman saltworks are located in the city of Vigo, in the northwest of the Iberian Peninsula, and they were part of a large industrial complex, dedicated to the production of sauces and salted fish. To this day, they are the best-preserved solar evaporation marine saltworks evidences in the Roman world, making it possible to know the entire production cycleBased on ceramic contexts and C14 data, we have concluded a period of use around the 1st-3rd c. AD, which falls completely within what is known as the Warm Roman Period.The architecture of the salt complex is articulated through different types of ponds, of various dimensions and construction characteristics. They use different materials for their construction: stone, ceramics, silt, clay, wood or sand. Its characteristics and dimensions are in accordance with its function within the salt production cycle: decanters, evaporators and crystallizers. Other architectural elements complete the ensemble and help to understand its functioning in detail.Knowledge of the architecture, constructive techniques and morphology of these saltworks has made it possible to identify others even when excavated on small surfaces, thanks to the archaeological indicators that the study of these salt pans allows us to define.

Characterization of the SUF FeS cluster synthesis machinery in the amitochondriate eukaryote Monocercomonoides exilis

Monocercomonoides exilis is the first known amitochondriate eukaryote. Loss of mitochondria in M.exilis ocurred after the replacement of the essential mitochondrial iron-sulfur cluster (ISC) assembly machinery by a unique, bacteria-derived, cytosolic SUF system. It has been hypothesized that the MeSuf pathway, in cooperation with proteins of the cytosolic iron-sulfur protein assembly (CIA) system, is responsible for the biogenesis of FeS clusters in M.exilis, yet biochemical evidence is pending. Here, we address the M.exilis MeSuf system and show that SUF genes, individually or in tandem, support the loading of iron-sulfur (FeS) clusters into the reporter protein IscR in Escherichia coli. The Suf proteins MeSufB, MeSufC, and MeSufDSU interact invivo with one another and with Suf proteins of E.coli. Invitro, the M.exilis Suf proteins form large complexes of varying composition and hence may function as a dynamic biosynthetic system in the protist. The putative FeS cluster scaffold MeSufB-MeSufC (MeSufBC) forms multiple oligomeric complexes, some of which bind FeS clusters and form selectively only in the presence of adenosine nucleotides. The multi-domain fusion protein MeSufDSU binds a PLP cofactor and can form higher-order complexes with MeSufB and MeSufC. Our work demonstrates the biochemical property of M. exilis Suf proteins to act as a functional FeS cluster assembly system and provides insights into the molecular mechanism of this unique eukaryotic SUF system.

Superinfection of endometriosis presenting as a complex pelvic mass.

SynopsisA patient presented with a large complex pelvic mass, presumed an ovarian carcinoma. She underwent surgical management. Histopathology report revealed chronic superinfection of endometriosis.

Automatic response framework for large complex natural gas pipeline operation optimization based on data-mechanism hybrid-driven

In recent years, the scale of gas transmission networks has been continuously expanding, and the operational conditions are becoming increasingly complex. This poses higher requirements for the centralized control of the pipeline network operation. Relying solely on the experience of scheduling personnel may not comprehensively address the operational issues within the network. There is an urgent need for efficient automatic response methods (ARM) to assist in formulating operation schemes and ensuring the safe and stable operation of the pipeline network. Therefore, this paper proposes an automatic response framework of large complex natural gas pipeline operation optimization based on data-mechanism coupling to provide operation schemes that ensure safety, stability, and economic benefits. First, two ARM is proposed, namely the Data-Based ARM using operation scheme database, and the Opti-Model ARM based on optimization modeling. Subsequently, the rapid response features of Data-Based ARM and the optimal response characteristics of Opti-Model ARM are combined to establish the Integrated ARM. Finally, these three ARMs are compared and analyzed through a regional natural gas pipeline network in China. The result indicates that the Data-Based ARM can quickly produce a variety of matched solutions but cannot ensure economic optimality. Response solutions obtained through Opti-Model ARM reduce the compressor energy costs by 4.6–10.8 % compared to on-site operational schemes, but they take longer in response time. In contrast, the economic attributes of solutions derived from the Integrated ARM are on par with Opti-Model ARM, but with a 58.7 % improvement in response speed. The proposed Integrated ARM can swiftly and accurately offer economically viable operation schemes tailored to the varying needs of pipeline operators, which can help to address the energy demand challenges of the future, fostering sustainable development.

Native Proteomics by Capillary Zone Electrophoresis-Mass Spectrometry.

Native proteomics measures endogenous proteoforms and protein complexes under a near physiological condition using native mass spectrometry (nMS) coupled with liquid-phase separations. Native proteomics should provide the most accurate bird's-eye view of proteome dynamics within cells, which is fundamental for understanding almost all biological processes. nMS has been widely employed to characterize well-purified protein complexes. However, there are only very few trials of utilizing nMS to measure proteoforms and protein complexes in a complex sample (i.e., a whole cell lysate). Here, we pioneer the native proteomics measurement of large proteoforms or protein complexes up to 400 kDa from a complex proteome via online coupling of native capillary zone electrophoresis (nCZE) to an ultra-high mass range (UHMR) Orbitrap mass spectrometer. The nCZE-MS technique enabled the measurement of a 115-kDa standard protein complex while consuming only about 0.1 ng of protein material. nCZE-MS analysis of an E . coli cell lysate detected 72 proteoforms or protein complexes in a mass range of 30-400 kDa in a single run while consuming only 50-ng protein material. The mass distribution of detected proteoforms or protein complexes agreed well with that from mass photometry measurement. This work represents a technical breakthrough in native proteomics for measuring complex proteomes.

Preparation of Dendrobium officinale Polysaccharide by Lactic Acid Bacterium Fermentation and Its Protective Mechanism against Alcoholic Liver Damage in Mice.

Dendrobium officinale polysaccharide (DP) was prepared with lactic acid bacterium fermentation to overcome the large molecular weight and complex structure of traditional DP for improving its functional activity and application range in this work. The structure was analyzed, and then the functional activity was evaluated using a mouse model of alcoholic liver damage. The monosaccharide compositions were composed of four monosaccharides: arabinose (0.13%), galactose (0.50%), glucose (24.38%), and mannose (74.98%) with a molecular weight of 2.13 kDa. The connection types of glycosidic bonds in fermented D. officinale (KFDP) were →4)-β-D-Manp(1→, →4)-β-Glcp(1→, β-D-Manp(1→, and β-D-Glcp(1→. KFDP exhibited an excellent protective effect on alcoholic-induced liver damage at a dose of 80 mg/kg compared with polysaccharide separated and purified from D. officinale without fermentation (KDP), which increased the activity of GSH, GSH-Px, and GR and decreased the content of MDA, AST, T-AOC, and ALT, as well as regulated the level of IL-6, TNF-α, and IL-1β to maintain the normal functional structure of hepatocytes and retard the apoptosis rate of hepatocytes. The results proved that fermentation degradation is beneficial to improving the biological activity of polysaccharides. The potential mechanism of KFDP in protecting alcoholic liver damage was inhibiting the expression of miRNA-150-5p and targeting to promote the expression of Pik3r1. This study provides an important basis for the development of functional foods.

Hyperspectral Image Analysis Using Cloud-Based Support Vector Machines

Hyperspectral image processing techniques involve time-consuming calculations due to the large volume and complexity of the data. Indeed, hyperspectral scenes contain a wealth of spatial and spectral information thanks to the hundreds of narrow and continuous bands collected across the electromagnetic spectrum. Predictive models, particularly supervised machine learning classifiers, take advantage of this information to predict the pixel categories of images through a training set of real observations. Most notably, the Support Vector Machine (SVM) has demonstrate impressive accuracy results for image classification. Notwithstanding the performance offered by SVMs, dealing with such a large volume of data is computationally challenging. In this paper, a scalable and high-performance cloud-based approach for distributed training of SVM is proposed. The proposal address the overwhelming amount of remote sensing (RS) data information through a parallel training allocation. The implementation is performed over a memory-efficient Apache Spark distributed environment. Experiments are performed on a benchmark of real hyperspectral scenes to show the robustness of the proposal. Obtained results demonstrate efficient classification whilst optimising data processing in terms of training times.