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A novel vernier effect filter is designed utilizing two cascaded Mach–Zehnder interferometers (MZIs). Integrating the filter into an erbium-doped fiber laser (EDFL), the tunability of laser wavelength is achieved. Each MZI comprises two sequentially interconnected 3 dB optical couplers (OCs), where the incoming light is initially split into two arms at the first OC and subsequently recombined at the second OC. Interference occurs due to the optical path difference between these two beams. Notably, the two MZIs exhibit closely matched free spectral ranges (FSRs), leading to the formation of a broadened envelope in the superimposed spectrum. By delicately adjusting the optical path difference between the two arms of one MZI, a little drift of the interference spectrum is induced. This small amount of drift, in turn, triggers a significant movement of the envelope, giving rise to the so-called vernier effect. Integrating the vernier effect filter into an EDFL, the wavelength of the fiber laser can be tuned from 1542.56 nm to 1556.62 nm, with a tuning range of 14.06 nm. Furthermore, by employing a high-precision stepper motor, a remarkable tuning accuracy of 0.01 nm is attainable. The side mode suppression ratio of all wavelengths is above 55 dB. In comparison to reported tunable fiber lasers utilizing MZI filters, the proposed fiber laser in this study offers enhanced precision and a more user-friendly tuning process. [ABSTRACT FROM AUTHOR]

Crop rotation increases crop yield, improves soil health, and reduces plant disease. However, few studies were conducted on the use of intensive cropping patterns to improve the microenvironment of saline soils. The present study thoroughly evaluated the impact of a three-year maize–peanut–millet crop rotation pattern on the crop yield. The rhizosphere soil of the crop was collected at maturity to assess the effects of crop rotation on the composition and function of microbial communities in different tillage layers (0–20 cm and 20–40 cm) of sandy saline–alkaline soils. After three years of crop rotation, the maize yield and economic benefits rose by an average of 32.07% and 22.25%, respectively, while output/input grew by 10.26%. The pH of the 0–40 cm tillage layer of saline–alkaline soils decreased by 2.36%, organic matter rose by 13.44%–15.84%, and soil-available nutrients of the 0–20 cm tillage layer increased by 11.94%–69.14%. As compared to continuous cropping, crop rotation boosted soil nitrogen and phosphorus metabolism capacity by 8.61%–88.65%. Enrichment of Actinobacteria and Basidiomycota increased crop yield. Crop rotation increases microbial community richness while decreasing diversity. The increase in abundance can diminish competitive relationships between species, boost synergistic capabilities, alter bacterial and fungal community structure, and enhance microbial community function, all of which elevate crop yields. The obtained insights can contribute to achieving optimal management of intensive cultivation patterns and green sustainable development. [ABSTRACT FROM AUTHOR]

Soil acidification is a global environmental problem with significant impacts on agricultural production, environmental protection, and ecosystem health. Soil acidification is widespread in China, affecting crop yields, agricultural product quality, and biodiversity. Since the 1980s, much work has been done on acidic soils in China, but it is controversial whether excessive nitrogen fertilizer application can lead to soil acidification mechanisms. To address the above issues, we conducted a meta-analysis of 115 published papers to integrate and analyze the effects of N fertilizer application on soil acidification and biological properties from 1980 to 2024. We also quantified the effect of nitrogen fertilization on soil acidification and biological changes under different climatic conditions. The results showed that under long-term application of nitrogen fertilizers in China from 1980 to 2024, soil pH decreased by an average of 15.27%, and the activities of soil urease, nitrate reductase, nitrite reductase, catalase, glutamate dehydrogenase, and glutamate synthetase decreased by an average of 9.82–22.37%. The soil microbial community richness (Chao1 index) increased by 6.53%, but the community diversity (Shannon index) decreased by 15.42%. Among the dominant soil microorganisms, the relative abundance of bacteria decreased by an average of 9.67–29.38% and the abundance of gene expression of nifH, amoA-AOA, amoA-AOB, and qnorB decreased by 9.92–19.83%. In addition, we found that the mean annual temperature and rainfall impacted soil acidification via their effect on soil microbial diversity and community composition. This study provides a scientific basis for an in-depth understanding of the spatial and temporal variation of soil acidification and biological properties in China. [ABSTRACT FROM AUTHOR]

Soil-borne diseases are exacerbated by continuous cropping and negatively impact maize health and yields. We conducted a long-term (11-year) field experiment in the black soil region of Northeast China to analyze the effects of different cropping systems on maize yield and rhizosphere soil fungal community structure and function. The experiment included three cropping systems: continuous maize cropping (CMC), maize–soybean rotation (MSR), and maize–soybean intercropping (MSI). MSI and MSR resulted in a 3.30–16.26% lower ear height coefficient and a 7.43–12.37% higher maize yield compared to CMC. The richness and diversity of rhizosphere soil fungi were 7.75–20.26% lower in MSI and MSR than in CMC. The relative abundances of Tausonia and Mortierella were associated with increased maize yield, whereas the relative abundance of Solicoccozyma was associated with decreased maize yield. MSI and MSR had higher proportions of wood saprotrophs and lower proportions of plant pathogens than CMC. Furthermore, our findings indicate that crop rotation is more effective than intercropping for enhancing maize yield and mitigating soil-borne diseases in the black soil zone of Northeast China. This study offers valuable insights for the development of sustainable agroecosystems. [ABSTRACT FROM AUTHOR]

Saline soils are characterized by organic matter and nutrient deficiencies, and their mineral fraction consists almost exclusively of fine sand particles, resulting in an unstable soil formation process. Due to the high amount of soluble salts in the soil, the osmotic pressure of the soil is elevated, restricting water absorption. This ultimately leads to the death of the plant and adversely impacts crop growth and yield. Incorporating Fe2+ can improve fertilizer utilization efficiency by reducing the oxidation of NH4+ to nitrogen (N2). However, reports on the usage of iron addition for the improvement of saline-alkali soils are scanty. This study conducted an outdoor simulation in pots to assess the soils of soybean crops during the podding stage. The effects of Fe2+ along with organic fertilizer or bio-C addition were elucidated on the composition and function of saline and alkaline microbial communities. The findings were correlated with soil environmental factors to analyze the dynamic changes in soil microbial communities. The soil pH decreased by 1.22–2.18% and SOM increased by 2.87–11.77% with organic fertilizer (OF) treatment. Compared to the ck treatment (control without iron supplementation), other treatments showed an average increase in abundance of dominant phylum by 8.25–11.23%, and an increase in the diversity and richness of the microbial community by 1.73–10.87%. The harmful bacteria in the Actinobacteriota, Chloroflexi, and Basidiomycota groups reduced by 57.83%, 74.29%, and 67.29%, and the beneficial bacteria in Ascomycota increased by 18.23–20.39%. Fe2+ combined with organic fertilizer or bio-C treatment could weaken the competitive relationship between the various bacterial lineages, enhance synergistic ability, favor the function and structure of the microbial community, and thus, improve the soil environment. Overall, the application of Fe2+ combined with organic fertilizers improved the saline-alkali soil, while the biochar (C) treatment mainly affected the soil nutrients. Through its detailed analysis, the study provides actionable insights for farmers to manage soil fertility in saline-alkaline soils, thereby overcoming the challenges of poor yields due to salinity stress. This will lead to resilient and sustainable farming systems, contributing to global food security. [ABSTRACT FROM AUTHOR]

The rice–fish co-culture is an important model of carp farming in China; however, research on the dynamics and assembly of water bacterial communities in this system remains limited. Therefore, this study aimed to explore the dynamics and assembly of bacterial communities, as well as their correlation with environmental factors in paddy water. For these purposes, this study was divided into two groups: a rice–carp co-culture (WRC) group and a rice monoculture (WRM) group, with 20 rice fields in each group. After 60 days of farming, the concentrations of NH4+-N, NO2−-N, TN, and PO43− were significantly higher in the WRC group than those in the WRM group. Alpha diversity analysis showed that the Shannon index in the WRC group was significantly decreased compared with the WRM group. At the phylum level, the relative abundance of Actinobacteria significantly increased, while the relative abundance of Proteobacteria and Bacteroidetes significantly decreased in the paddy water of the WRC group. The neutral community model (NCM) indicated that a random process played a dominant role in the construction of bacterial communities in the two groups, and common carp cultivation increased migration rates, thereby affecting community assembly. The co-occurrence network displayed that common carp cultivation led to looser interactions between bacterial communities. In addition, the contents of nutrients significantly affected the abundance of bacteria in paddy water. In summary, carp cultivation decreased the diversity of bacteria and changed the relative abundance of dominant bacteria, thereby affecting the stability and assembly of bacterial communities. [ABSTRACT FROM AUTHOR]

Common carp (Cyprinus carpio) is a freshwater fish commonly farmed in rice fields, yet there were few studies on the intestinal functions and microbial community structure of common carp in the rice–carp co-culture system. Therefore, this study aimed to explore the effects of different stocking densities on the growth, antioxidant status, and intestinal bacterial composition of common carp in this system. This study was divided into three different stocking densities, including low density (LD, 10 fish, 52.9 g/m2), medium density (MD, 20 fish, 105.8 g/m2), and high density (HD, 30 fish, 158.7 g/m2), with a culturing period of 60 days. The results indicated that HD treatment inhibited the growth of common carp, as evidenced by the reduced final weight, WG, and SGR. In serum, the TG content in the HD group and the Cor content in the MD group were significantly increased. Meanwhile, HD treatment induced oxidative stress, manifesting specifically as increased SOD and CAT activities in the intestine or serum while reducing Gpx, GSH, and T-AOC in the serum. The 16S rDNA analysis indicated that the Simpson and Shannon indices of intestinal microbiota in the HD group were significantly higher than those in the LD group. At the phylum level, Proteobacteria, Cyanobacteria, and Firmicutes were dominant microbial communities in two groups. In addition, there was a significant difference between the two groups in the abundances of Actinobacterota and Bifidobacterium. Based on growth performances, biochemical indicators, and microbial diversity in rice–carp co-culture, low density (52.9 g/m2) may be more suitable in the rice–carp co-culture systems. In summary, this study contributes to a better understanding of common carp response to different stocking densities in the rice–carp co-culture system. [ABSTRACT FROM AUTHOR]

Cyprinus carpio is a significant freshwater species with substantial nutritional and economic value. Rice–carp co-culture represents one of its principal cultivation methods. However, in the system, the optimal farming density for carp and the impact of high stocking density on their muscle nutritional composition have yet to be explored. Thus, the objective of the current study was to investigate the influences of stocking density on the muscle nutrient profiles and metabolism of C. carpio in rice–fish co-culture systems. Common carp were cultured at three stocking densities, low density (LD), medium density (MD), and high density (HD), over a period of 60 days. Following this, comprehensive analyses incorporating physiological, biochemical, and multi-omics sequencing were conducted on the muscle tissue of C. carpio. The results demonstrated that HD treatment led to a reduction in the antioxidant capacity of C. carpio, while resulting in elevated levels of various fatty acids in muscle tissue, including saturated fatty acids (SFAs), omega-3 polyunsaturated fatty acids (n-3 PUFAs), and omega-6 polyunsaturated fatty acids (n-6 PUFAs). The metabolome analysis showed that HD treatment caused a marked reduction in 43 metabolites and a significant elevation in 30 metabolites, primarily linked to lipid and amino acid metabolism. Additionally, transcriptomic analysis revealed that the abnormalities in lipid metabolism induced by high-stocking-density treatment may be associated with significant alterations in the PPAR signaling pathway and adipokine signaling pathway. Overall, our findings indicate that in rice–fish co-culture systems, high stocking density disrupted the balance of antioxidant status and lipid metabolism in the muscles of C. carpio. [ABSTRACT FROM AUTHOR]

Currently, China's soybean self-sufficiency rate is only 15%, highlighting the soybean crisis and the supply chain risks that pose a major threat to China's food security. Thus, it has become imperative to step up efforts to boost soybean production capacity while promoting the green and sustainable development of regional farmland ecosystems. In this context, the present study comprehensively investigated the effects of intercropping and nitrogen application rate on soybean yield, as well as the changes in gradients generated by different levels of nitrogen application. Based on six consecutive years of maize–soybean intercropping planting patterns, the inter-root soils of soybeans were collected at the flowering stage and evaluated for soil nitrogen content, nitrogen-assimilating enzyme activities, and microbial community composition of soybean, which were correlated with yield, to clarify the main pathways and modes of intercropping effects. The N2 level (80 kg·ha−1) was favourable for higher yield. In comparison to monocropping, the intercropping reduced yield by 9.65–13.01%, photosynthetic characteristics by 1.33–7.31%, and plant nitrogen-assimilating enzyme activities by 8.08–32.01% at the same level of N application. Likewise, soil urease and catalase activities were reduced by 9.22 and 1.80%, while soil nitrogen content declined by an average of 6.38%. Gemmatimonas and Bradyrhizobium enrichment significantly increased soil nitrogen content, photosynthetic characteristics, and soybean yield, while it was reduced by Candidatus_Udaeobacter and Candidatus_Solibacte enrichment. The results of this study provide a theoretical basis for further optimising maize–soybean intercropping, which is crucial for enhancing the agricultural production structure and improving the overall soybean production capacity. [ABSTRACT FROM AUTHOR]

With mounting demand for high-quality agricultural products and the relentless exploitation of arable land resources, finding sustainable ways to safely cultivate food crops is becoming ever more important. Here, we investigated the effects of the integrated cropping technique "straw return + intercropping" on the soil aggregates as well as the microbial biomass carbon (MBC) content, enzyme activities and microbial diversity in soils of maize and soybean crops. Our results show that in comparison to straw removal and monoculture, straw return and intercropping increase the rhizosphere's MBC content (59.10%) of soil, along with urease (47.82%), sucrase (57.14%), catalase (16.14%) and acid phosphatase (40.66%) activities as well as the microbial diversity under maize and soybean. Under the same straw treatment, the yield of maize when intercropped surpassed that when grown in monoculture, with the land equivalent ratio of the intercropping treatment under straw return being highest. Overall, the intercropping of maize and soybean is beneficial for the healthy development of sustainable agriculture in the black soil region of northeast China, especially when combined with straw return to fields. [ABSTRACT FROM AUTHOR]

Berberine, a natural alkaloid found abundantly in various medicinal plants, exhibits antioxidative, anti-inflammatory, and lipid metabolism-regulatory properties. Nonetheless, its protective effects and the molecular mechanisms underlying liver injury in fish have not been fully elucidated. The aims of this study were to investigate the antioxidative, anti-inflammatory, and lipid metabolism-regulating effects of berberine against high-fat diet (HFD)-induced liver damage and to clarify the underlying molecular mechanisms. Tilapia were fed diets containing two doses of berberine (50 and 100 mg/kg diet) alongside high fat for 60 days. The results showed that berberine treatments (50 and/or 100 mg/kg) significantly reduced elevated aminotransferases, triglycerides (TG), total cholesterol (TC), and low-density lipoprotein cholesterol (LDL-c) in the plasma. In the liver, berberine treatments significantly increased the expression of peroxisome proliferator-activated receptor α (pparα) and carnitine palmitoyltransferase 1 (cpt-1) genes, leading to a reduction in lipid accumulation. Meanwhile, berberine treatment suppressed lipid peroxidation formation and enhanced antioxidant capacity. Berberine upregulated the mRNA levels of erythroid 2-related factor 2 (nrf2) and its downstream genes including heme oxygenase 1 (ho-1) and glutathione-S-transferase (gstα). Additionally, berberine attenuated the inflammation by inhibiting the expression of toll-like receptor 2 (tlr2), myeloid differential protein-88 (myd88), relb, and inflammatory cytokines such as interleukin-1β (il-1β), tumor necrosis factor-α (tnf-α), and il-8. In summary, this study suggested that berberine offers protection against HFD-induced liver damage in tilapia via regulating lipid metabolism, antioxidant status, and immune response. This protective effect may be attributed to the modulation of the Nrf2, TLR2/MyD88/NF-κB, and PPARα signaling pathways. [ABSTRACT FROM AUTHOR]

Simple Summary: Procambarus clarkii, an important freshwater species in China, is predominantly cultivated in an integrated rice–crayfish co-culture system. However, potential regional differences in the quality of P. clarkii have been scarcely reported. Therefore, the aim of this study was to assess the regional differences of P. clarkii through analyzing gut microbiota composition in specimens from ten major producing areas in China. Microbial sequencing analysis demonstrated that P. clarkii across various regions exhibit distinct microbial diversity and composition. These data would contribute to the assessment of the quality of P. clarkii aquaculture. The aim of this study was to assess the regional differences of Procambarus clarkii through analyzing gut microbiota in specimens from different areas in China. The P. clarkii were collected from ten integrated rice–crayfish farming systems locating across ten major producing areas as follows: Feixi (FX), Suqian (SQ), Yangzhou (YZ), Xuyi (XY), Qianjiang (QJ), Jianli (JL), Honghu (HH), Yueyang (YY), Changsha (CS), and Nanxian (NX). The composition of gut microbiota was assessed by analyzing 16S rRNA sequences. The PCoA results indicated significant differences in microbial community composition among the ten areas (R = 0.999, p = 0.001). The intestinal microbial diversity in P. clarkii cultured in rice fields from YY and CS exceeded that of other regions, with NX displaying the least diversity. At the phylum level, Proteobacteria were most abundant in HH, while Firmicutes showed increased relative abundances in FX and SQ, contrasted by lower relative abundances of Bacteroidetes in these areas. At the genus level, Ralstonia, Amedibacillus, Bacteroides, Anaerorhabdus, and Dysgonomonas were the dominant bacteria. The bacterial co-occurrence networks analysis revealed that the community structures in locations FX, SQ, XY, HH, and NX were comparatively simplistic, whereas those in the YZ, QJ, JL, YY, and CS regions displayed as more complex. In summary, the diversity and relative abundance of intestinal bacteria exhibits regional variability. These findings can offer theoretical data for evaluating the quality of P. clarkii aquaculture. [ABSTRACT FROM AUTHOR]

Ocean salinity is a pivotal aspect of the ocean dynamic environment. Spaceborne L-band radiometers, like SMOS, Aquarius, and SMAP, offer a comprehensive approach to mapping out large-scale ocean salinity patterns. As China prepares for the launch of the Chinese Ocean Salinity and Soil Moisture Mission (COSM), it is essential to delve into the intricacies of radio frequency interference (RFI) detection, localization, and mitigation. The L-band, in particular, is highly susceptible to RFI. COSM will carry not one but two advanced instruments: a 2-D L-band aperture synthesis microwave radiometer (LASMR) and a 1-D L-C-K band microwave imager combined active and passive (MICAP). This article delves into the current state of RFI research, particularly in recent years, and introduces a fusion method that integrates MICAP and LASMR for more accurate RFI detection, localization, and mitigation. This fusion method relies on an algorithm that constructs localization and intensity objective functions based on the principle of least squares. By optimizing these functions, we can pinpoint the precise location and intensity of RFI. The resulting minimum mitigation residual offers a blueprint for achieving optimal RFI detection, localization, and mitigation. The experimental results, achieved in a controlled anechoic chamber, confirm that this fusion method—when weighted by variance—boosts detection accuracy, refines localization precision, and minimizes residual mitigation errors compared with standalone MICAP or LASMR techniques. [ABSTRACT FROM AUTHOR]

To investigate the mechanisms behind the effect of ultrasonic vibration on the plastic deformation of materials, the flow stress model of Cr4Mo4V was established according to the dislocation dynamics and thermal activation theory, which considers the effect of dislocation density evolution on plastic deformation under ultrasonic vibration conditions. The effect of amplitude and strain rate on the flow stress was analyzed by fitting the stress-strain data obtained from an ultrasonic vibration-assisted tensile (UVAT) single-factor test. To investigate the influence of strain rate and vibration duration on the acoustic effect, comparative tests with and without vibration were performed for various strain rates. The results showed that the flow stress decreased significantly in the tensile test with ultrasound compared to the test without ultrasound, and the degree of reduction increased with increasing amplitude. In addition, the nonlinear relationship between the acoustic softening effect and the strain rate was analyzed. The result demonstrates that the dislocation density absorbs the ultrasonic vibration energy, which results in slip and proliferation. Macroscopically, due to a greater susceptibility to plastic deformation, the dislocation density shows residual hardening at the end of the ultrasound. Finally, the average absolute relative error (AARE) between predicted flow stresses and experimental results under three ultrasonic conditions using the developed model were 4.49%, 1.27%, and 5.64%, which proved the validity of the model. [ABSTRACT FROM AUTHOR]

Determining the dynamic processes of the subsurface ocean is a critical yet formidable undertaking given the sparse measurement resources available presently. In this study, using the light gradient boosting machine algorithm (LightGBM), we report for the first time a machine learning strategy for retrieving subsurface velocities at 1000 dbar depth in the Southern Ocean from information derived from satellite observations. Argo velocity measurements are used in the training and validation of the LightGBM model. The results show that reconstructed subsurface velocity agrees better with Argo velocity than reanalysis datasets. In particular, the subsurface velocity estimates have a correlation coefficient of 0.78 and an RMSE of 4.09 cm/s, which is much better than the ECCO estimates, GODAS estimates, GLORYS12V1 estimates, and Ora-S5 estimates. The LightGBM model has a higher skill in the reconstruction of subsurface velocity than the random forest and the linear regressor models. The estimated subsurface velocity exhibits a statistically significant increase at 1000 dbar since the 1990s, providing new evidence for the deep acceleration of mean circulation in the Southern Ocean. This study demonstrates the great potential and advantages of statistical methods for subsurface velocity modeling and oceanic dynamical information retrieval. [ABSTRACT FROM AUTHOR]

Tunable fiber lasers have the advantages of good beam quality, high integration, and adjustable output wavelength, and they are widely used in fields such as optical fiber communication and optical fiber sensing. The fiber filter is one of the key components of tunable fiber lasers. Among the various filters currently used, multimode interference filters have the advantages of simple structure, convenient implementation, flexible tuning methods, and convenient spectral range design. The structures of multimode interference filters based on multimode fibers, no-core fibers, multi-core fibers, tapered fibers, and other special fibers are introduced in this paper. The working principles and tuning methods are analyzed and the research progress of tunable fiber lasers based on these filters is summarized. Finally, the development trend of tunable fiber lasers based on multimode interference filters is discussed. The rapid development and applications of multimode interference filters can help improve the performance of continuous and pulse lasers as well as promote the practicality of tunable fiber lasers. [ABSTRACT FROM AUTHOR]

An interference filter is designed by cascading two Mach-Zehnder interferometers (MZIs), which is then utilized in the construction of a wavelength interval adjustable dual-wavelength Erbium-doped fiber laser (EDFL). Each MZI consists of two 3 dB optical couplers (OCs) connected in series. The input light is split into two arms at the first OC and recombined at the second OC. The first MZI (MZI 1) has a smaller free spectral range (FSR) and is used for selecting the output wavelength of the laser. The second MZI (MZI 2) has a larger FSR and forms an envelope structure on the comb-like spectrum of MZI 1. By adjusting the optical path difference between the two arms of MZI 2, the FSR of the envelope can be changed, thereby altering the interval of the output wavelengths. The implemented filter is inserted into the EDFL to achieve stable dual-wavelength output. By stretching one arm of MZI 2, the interval of the dual-wavelength can be adjusted from 4.64 to 13.94 nm, with the side-mode suppression ratio of over 44 dB for all wavelengths. [ABSTRACT FROM AUTHOR]

The SSS (sea surface salinity) is an important factor affecting global climate changes, sea dynamic environments, global water cycles, marine ecological environments, and ocean carbon cycles. Satellite remote sensing is a practical way to observe SSS from space, and the key to retrieving SSS satellite products is to establish an accurate sea surface brightness temperature forward model. However, the calculation results of different forward models, which are composed of different relative permittivity models and SSR (sea surface roughness) brightness temperature increment models, are different, and the impact of this calculation difference has exceeded the accuracy requirement of the SSS inversion, and the existing SSR brightness temperature increment models, which primarily include empirical models and theoretical models, cannot match all the relative permittivity models. In order to address this problem, this paper proposes a universal DNN (deep neural network) model architecture and corresponding training scheme, and provides different SSR brightness temperature increment models for different relative permittivity models utilizing DNN based on offshore experiment data, and compares them with the existing models. The results show that the DNN models perform significantly better than the existing models, and that their calculation accuracy is close to the detection accuracy of a radiometer. Therefore, this study effectively solves the problem of SSR brightness temperature correction under different relative permittivity models, and provides a theoretical support for high-precision SSS inversion research. [ABSTRACT FROM AUTHOR]

The timely and accurate mapping of crops over large areas is essential for alleviating food crises and formulating agricultural policies. However, most existing classical crop mapping methods usually require the whole-year historical time-series data that cannot respond quickly to the current planting information, let alone for future prediction. To address this issue, we propose a novel spatial–temporal feature and deep integration strategy for crop growth pattern prediction and early mapping (STPM). Specifically, the STPM first learns crop spatial–temporal evolving patterns from historical data to generate future remote sensing images based on the current observations. Then, a robust crop type recognition model is applied by combining the current early data with the predicted images for early crop mapping. Compared to existing spatial–temporal prediction models, our proposed model integrates local, global, and temporal multi-modal features comprehensively. Not only does it achieve the capability to predict longer sequence lengths (exceeding 100 days), but it also demonstrates a significant improvement in prediction accuracy for each time step. In addition, this paper analyses the impact of feature dimensionality and initial data length on prediction and early crop mapping accuracy, demonstrating the necessity of multi-modal feature fusion for spatial–temporal prediction of high-resolution remote sensing data and the benefits of longer initial time-series (i.e., longer crop planting time) for crop identification. In general, our method has the potential to carry out early crop mapping on a large scale and provide information to formulate changes in agricultural conditions promptly. [ABSTRACT FROM AUTHOR]

Rotation and fertilization are important methods used to improve crop yield. In particular, crop rotation is an effective means of enhancing ecosystem diversity; however, there exist relatively few studies regarding the effects of long-term maize–soybean rotation and fertilization on soil microbial communities. To further understand the changes in soil microbial community structure under long-term maize–soybean rotation and fertilization, we used a 9-year-old experimental site with maize–soybean rotation as the research object and soybean continuous cropping as a control. We explored the growth effects of soybean and the changes in soil microbial communities under the soybean–maize rotation system and fertilization treatments by analyzing the physicochemical properties of the soil, crop agronomic traits, yield, and changes in soil microbial community structure. The results show that, in comparison with soybean continuous cropping, the yield of soybeans was increased by 12.11% and 21.42% under maize–soybean rotation with different fertilization treatments, respectively. Additionally, there was a significant increase in the agronomic effects of nitrogen following rotation combined with fertilization. Moreover, the soil pH, SOM, and nutrient status were also improved. Bryobacter, Gemmatimonas, and Rhodanobacter were the dominant bacteria. Rotation treatment increased the relative abundance of Bryobacter and Rhodanobacter, and fertilization treatment increased the relative abundance of Gemmatimonas. Rotation also increased the stability of the bacterial community structure and strengthened the symbiotic relationship between species. The prediction of nitrogen-related functional genes indicates that rotation increased soil ammonification and nitrification. Heterocephalacria and Mrakia were the dominant fungal genera under crop rotation. The abundance of Saccharomyces Mrakia was significantly positively correlated with ammonium nitrogen levels and crop yield. Crop rotation increased the abundance of Saccharomyces Mrakia and reduced the abundance of Fusarium, but fertilization increased the abundance of Fusarium. Functional gene prediction also indicates that the relative abundance of plant pathogens was significantly reduced. This study provides a theoretical basis for soil microbial diversity and ecosystem service function in long-term soybean–maize rotation. [ABSTRACT FROM AUTHOR]

Multi-core fibers have been widely used for vector-bending sensing due to their off-axis distributed cores. In contrast to vector-bending sensors based on Bragg gratings, fiber Fabry–Perot (F–P) interferometers are more advantageous due to their ease of fabrication and potential for introducing the Vernier effect to further improve sensitivity. We propose and experimentally demonstrate a cascaded Fabry–Perot (F–P) cavity vector bending sensor. From the experimental results, the sensor has a strong bending dependence with a maximum sensitivity of 123.12 pm/m−1, and the curvature magnitude and direction can be reconstructed from the tilted wavelength shift of the asymmetric fiber-core F–P cavities. [ABSTRACT FROM AUTHOR]

The snow temperature above the ice sheet is one of the basic characteristic parameters of the ice sheet, which plays an important role in the study of the global climate. Because infrared and microwaves with different frequencies have different penetration depths in snow, it is possible to retrieve the snow temperature profiles by combining microwave and infrared brightness temperatures. This paper proposes a conjoint inversion algorithm to retrieve snow temperature profiles by combining multi-frequency microwave brightness temperature (BT) with infrared BT, in which different weight functions of microwave BT at different frequencies are adopted, and the atmosphere influence has also been corrected. The snow temperature profile data are retrieved based on AMSR2 microwave BT data and MODIS infrared BT data in 2017 and 2018, which are evaluated by comparing with the measured snow temperature at Dome-C station. The results confirm that the inverted snow temperature profiles are consistent with the field observation data from the Dome-C station. Multi-frequency microwave brightness temperature can be used to invert the snow temperature profiles; however, the inverted snow surface temperature is more accurate by combining the infrared BT with the microwave BT in the conjoint inversion algorithm. [ABSTRACT FROM AUTHOR]

An interference filter is designed by fusing a segment of multi-core fiber (MCF) between two segments of multimode fibers (MMFs), which is then spliced between two segments of single mode fibers (SMFs). The light is split into the cladding and different cores of the MCF through the first segment of MMF, which is then coupled back into the core of SMF by the second segment of MMF. When the lengths of MCF are selected to be 4 mm and 10 mm, the 3 dB bandwidths of the filters around 1060 nm are 8.40 nm and 4.84 nm, respectively. Applying these filters in an Yb-doped fiber laser mode-locked by nonlinear polarization rotation, stable pulses have been obtained. Compared with the reported interference filters, the filter proposed in this paper has the advantages of simple fabrication process, compact structure and high environmental stability. [ABSTRACT FROM AUTHOR]

In this paper, a low-loss 90°-bending design in femtosecond laser-induced double-line waveguides is theoretically proposed and experimentally demonstrated. The bending is realized based on the total internal reflection of a corner mirror (made by precise diamond blade dicing) located at the intersection of a pair of waveguides perpendicular to each other. The waveguide bending performance was birefringence free, with the insertion loss of each bending below 0.8 dB. This method provides great flexibility and has great potential for the design of integrated photonics based on femtosecond laser-inscribed crystalline materials. [ABSTRACT FROM AUTHOR]

The effective use of nutrient-rich crop straw is an important way to use resources efficiently and to sustain agricultural development. This meta-analysis study collected and analyzed the data of 6788 observations published in 238 peer-reviewed papers to investigate differences in soil C-N fractions and yields of paddy soils under different straw-return amounts. This large dataset was also used to quantify the degree of influence of factors such as climate characteristics, soil properties, N fertilizer application rates, straw-rotting agent addition, rice varieties, and straw return methods. The results showed that straw return amounts improved soil alkaline-hydrolysable N (7%), total N (10%), organic C (11%), the C:N ratio (8%), rice N accumulation (12%), and overall yield (18%). The most significant effect was in northeast China fields for total soil nitrogen (TN) content and yield with increases of 13% and 22%, respectively. We also found more effective N utilization and a greater rice yield when 220–260 kg ha−1 N fertilizer was applied with 20–30 kg ha−1 straw-rotting agent with the total amount of straw return. These findings have important implications for choosing appropriate conditions and field management practices and to improve rice yield in China. [ABSTRACT FROM AUTHOR]

Continuous casting is a dominant steelmaking process due to its steady-state nature, enhanced yield of steel production, and low consumption of energy and manpower. However, the production of defect-free cast products is still a big challenge, as the internal defects, including macro-segregation of alloying elements, cracks, and pores, can be easily formed during the solidification process, which seriously deteriorates the microstructure and mechanical properties of the cast products. Therefore, this paper puts forward the common solutions to overcome these problematic issues. The reduction technology can effectively improve the center segregation of the billet, bloom, and slab. The history of the development of the reduction technology is summarized and classified according to the variations in research trend. Furthermore, the basic principles and parameters of reduction technology are described to implement them in the actual production process. This paper compares the similarities and differences between soft reduction (SR) and heavy reduction (HR) technologies with a particular focus on the theoretical research of HR technology and further elaborates the key parameter and equipment problems during implementation of HR. Moreover, this paper also considers the HR technology adopted by Baosteel as a case study, which helped to put forward some viewpoints for the future development of reduction technology. [ABSTRACT FROM AUTHOR]

Diagnostic blood cell counting is of limited use in monitoring a minimal number of leukaemia cells, warranting further research to develop more sensitive and reliable techniques to identify leukaemia cells in circulation. In this work, a hemin–graphene nanocomposite-based aptasensor was developed for ultrasensitive colorimetric detection of leukaemia cells (CEM) using magnetic enrichment. Hemin-conjugated graphene oxide nanocomposites (HGNs) were prepared by hydrazine reduction using graphene oxide nanosheets and hemins. Hence, the prepared HGNs become able to absorb single-stranded DNA and acquire peroxidase-like activity. The aptamer sgc8c, which recognizes a specific target on leukaemia cells, was absorbed onto HGNs to capture the target CEM cancer cells. The captured target cells that associated with the HGNs were then concentrated and separated by magnetic beads (MBs) coated with sgc8c aptamers, forming a HGN–cell–MB sandwich structure. These sandwich structures can be quantified via an oxidation reaction catalysed by HGNs. By utilizing dual signal amplification effects generated by magnetic enrichment and the improved peroxidase activity of HGNs, the biosensor allowed for highly sensitive detection of 10 to 105 CEM cells with an ultra-low limit of detection (LOD) of 10 cells under optimal conditions. It is expected that the proposed aptasensor can be further employed in monitoring the minimal residual disease during the treatment of leukaemia. [ABSTRACT FROM AUTHOR]

The accuracy with which a neural network interprets a point cloud depends on the quality of the features expressed by the network. Addressing this issue, we propose a multi-level feature extraction layer (MFEL) which collects local contextual feature and global information by modeling point clouds at different levels. The MFEL is mainly composed of three independent modules, including the aggregated GAPLayer, the spatial position perceptron, and the RBFLayer, which learn point cloud features from three different scales. The aggregated GAPLayer aggregates the geometry features of neighboring points in a local coordinate system to centroid by graph convolution. Then, the spatial position perceptron independently learns the position features of each point in the world coordinate system. Finally, the RBFLayer aggregates points into pointsets according to the correlation between features, and extracts features from the pointset scale through the quantization layer. Based on the MFEL, an end-to-end classification and segmentation network, namely the MFNet and MFNet-S, is proposed. In the proposed network, the channel-attention mechanism is employed to better aggregate multi-level features. We conduct classification and semantic segmentation experiments on four standard datasets. The results show that the proposed method outperforms the compared methods on the multiple datasets, resulting in 93.1% classification accuracy in ModelNet40. Furthermore, the mIoU of part semantic segmentation in ShapeNet is 85.4%, and the mIoU for semantic segmentation in S3DIS and Semantic3D is 62.9% and 71.9%, respectively. [ABSTRACT FROM AUTHOR]

Duchenne muscular dystrophy is an X-linked disease afflicting 1 in 3500 males that is characterized by muscle weakness and wasting during early childhood, and loss of ambulation and death by early adulthood. Chronic inflammation due to myofiber instability leads to fibrosis, which is a primary cause of loss of ambulation and cardiorespiratory insufficiency. Current standard of care focuses on reducing inflammation with corticosteroids, which have serious adverse effects. It is imperative to identify alternate immunosuppressants as treatments to reduce fibrosis and mortality. Serp-1, a Myxoma virus-derived 55 kDa secreted glycoprotein, has proven efficacy in a range of animal models of acute inflammation, and its safety and efficacy has been shown in a clinical trial. In this initial study, we examined whether pegylated Serp-1 (PEGSerp-1) treatment would ameliorate chronic inflammation in a mouse model for Duchenne muscular dystrophy. Our data revealed a significant reduction in diaphragm fibrosis and increased myofiber diameter, and significantly decreased pro-inflammatory M1 macrophage infiltration. The M2a macrophage and overall T cell populations showed no change. These data demonstrate that treatment with this new class of poxvirus-derived immune-modulating serpin has potential as a therapeutic approach designed to ameliorate DMD pathology and facilitate muscle regeneration. [ABSTRACT FROM AUTHOR]

Honeycomb composites (HCs) are diversely employed in aerospace, national defense and other fields owing to their remarkable spatial geometry and excellent mechanical properties. Their complex hexagonal cell structure and heterogeneous material properties cause major problems when implementing high-quality processing. Surface defects generated by processing will reduce the capability and service lifespan of the honeycomb sandwich structure. Therefore, the high quality of HCs is a topic of close attention for researchers. In this paper, the consequences of different cutting parameters of rotary ultrasonic machining (RUM) on surface quality with an ultrasonic circular knife (UCK) were studied through multiple groups of single-factor and orthogonal experiments with two-factors/four-levels and one-factor/three-levels. The single factor experiment was used to explain the effect that the degree of cutting parameters has on surface quality, and the orthogonal experiments were applied to explain the interaction between the processing parameters and the influence law of each factor on surface quality. Therefore, the reasonable cutting parameters of HCs were determined through experimental results to provide guidance for the realization of the precise and efficient machining of HCs. This study can provide a basis for the subsequent comprehensive consideration of various factors to achieve high-quality machining of HCs. [ABSTRACT FROM AUTHOR]

Immune cell invasion after the transplantation of solid organs is directed by chemokines binding to glycosaminoglycans (GAGs), creating gradients that guide immune cell infiltration. Renal transplant is the preferred treatment for end stage renal failure, but organ supply is limited and allografts are often injured during transport, surgery or by cytokine storm in deceased donors. While treatment for adaptive immune responses during rejection is excellent, treatment for early inflammatory damage is less effective. Viruses have developed highly active chemokine inhibitors as a means to evade host responses. The myxoma virus-derived M-T7 protein blocks chemokine: GAG binding. We have investigated M-T7 and also antisense (ASO) as pre-treatments to modify chemokine: GAG interactions to reduce donor organ damage. Immediate pre-treatment of donor kidneys with M-T7 to block chemokine: GAG binding significantly reduced the inflammation and scarring in subcapsular and subcutaneous allografts. Antisense to N-deacetylase N-sulfotransferase1 (ASONdst1) that modifies heparan sulfate, was less effective with immediate pre-treatment, but reduced scarring and C4d staining with donor pre-treatment for 7 days before transplantation. Grafts with conditional Ndst1 deficiency had reduced inflammation. Local inhibition of chemokine: GAG binding in donor organs immediately prior to transplant provides a new approach to reduce transplant damage and graft loss. [ABSTRACT FROM AUTHOR]

Pedestrian navigation systems could serve as a good supplement for other navigation methods or for extending navigation into areas where other navigation systems are invalid. Due to the accumulation of inertial sensing errors, foot-mounted inertial-sensor-based pedestrian navigation systems (PNSs) suffer from drift, especially heading drift. To mitigate heading drift, considering the complexity of human motion and the environment, we introduce a novel hybrid framework that integrates a foot-state classifier that triggers the zero-velocity update (ZUPT) algorithm, zero-angular-rate update (ZARU) algorithm, and a state lock, a magnetic disturbance detector, a human-motion-classifier-aided adaptive fusion module (AFM) that outputs an adaptive heading error measurement by fusing heuristic and magnetic algorithms rather than simply switching them, and an error-state Kalman filter (ESKF) that estimates the optimal systematic error. The validation datasets include a Vicon loop dataset that spans 324.3 m in a single room for approximately 300 s and challenging walking datasets that cover large indoor and outdoor environments with a total distance of 12.98 km. A total of five different frameworks with different heading drift correction methods, including the proposed framework, were validated on these datasets, which demonstrated that our proposed ZUPT–ZARU–AFM–ESKF-aided PNS outperforms other frameworks and clearly mitigates heading drift. [ABSTRACT FROM AUTHOR]

Extracting buildings from high-resolution remote sensing images is essential for many geospatial applications, such as building change detection, urban planning, and disaster emergency assessment. Due to the diversity of geometric shapes and the blurring of boundaries among buildings, it is still a challenging task to accurately generate building footprints from the complex scenes of remote sensing images. The rapid development of convolutional neural networks is presenting both new opportunities and challenges with respect to the extraction of buildings from high-resolution remote sensing images. To capture multilevel contextual information, most deep learning methods extract buildings by integrating multilevel features. However, the differential responses between such multilevel features are often ignored, leading to blurred contours in the extraction results. In this study, we propose an end-to-end multitask building extraction method to address these issues; this approach utilizes the rich contextual features of remote sensing images to assist with building segmentation while ensuring that the shape of the extraction results is preserved. By combining boundary classification and boundary distance regression, clear contour and distance transformation maps are generated to further improve the accuracy of building extraction. Subsequently, multiple refinement modules are used to refine each part of the network to minimize the loss of image feature information. Experimental comparisons conducted on the SpaceNet and Massachusetts building datasets show that the proposed method outperforms other deep learning methods in terms of building extraction results. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer metastasis to the lung represents the second most common site of metastasis, and a major challenge for clinical treatment of cancer, however, armed oncolytic viruses (Ovs) systemically delivered by carrier leukocytes represents a new treatment strategy. To study PBMC delivery of oncolytic myxoma virus armed with murine LIGHT (vMyx-mLIGHT), we exploited a later-stage syngeneic murine lung metastatic osteosarcoma model. Our results show that PBMC-delivered vMyx-mLIGHT is an effective treatment for even later-stage disease in vivo and offered superior tumor cell cytotoxicity in vitro. Taken together, vMyx-mLIGHT/PBMC therapy offers great promise to treat lung metastatic cancers. Cancers that metastasize to the lungs represent a major challenge in both basic and clinical cancer research. Oncolytic viruses are newly emerging options but successful delivery and choice of appropriate therapeutic armings are two critical issues. Using an immunocompetent murine K7M2-luc lung metastases model, the efficacy of MYXV armed with murine LIGHT (TNFSF14/CD258) expressed under virus-specific early/late promoter was tested in an advanced later-stage disease K7M2-luc model. Results in this model show that mLIGHT-armed MYXV, delivered systemically using ex vivo pre-loaded PBMCs as carrier cells, reduced tumor burden and increased median survival time. In vitro, when comparing direct infection of K7M2-luc cancer cells with free MYXV vs. PBMC-loaded virus, vMyx-mLIGHT/PBMCs also demonstrated greater cytotoxic capacity against the K7M2 cancer cell targets. In vivo, systemically delivered vMyx-mLIGHT/PBMCs increased viral reporter transgene expression levels both in the periphery and in lung tumors compared to unarmed MYXV, in a tumor- and transgene-dependent fashion. We conclude that vMyx-mLIGHT, especially when delivered using PBMC carrier cells, represents a new potential therapeutic strategy for solid cancers that metastasize to the lung. [ABSTRACT FROM AUTHOR]

In this paper, we propose a deep learning framework, namely AFGL-Net to achieve building façade parsing, i.e., obtaining the semantics of small components of building façade, such as windows and doors. To this end, we present an autoencoder embedding position and direction encoding for local feature encoding. The autoencoder enhances the local feature aggregation and augments the representation of skeleton features of windows and doors. We also integrate the Transformer into AFGL-Net to infer the geometric shapes and structural arrangements of façade components and capture the global contextual features. These global features can help recognize inapparent windows/doors from the façade points corrupted with noise, outliers, occlusions, and irregularities. The attention-based feature fusion mechanism is finally employed to obtain more informative features by simultaneously considering local geometric details and the global contexts. The proposed AFGL-Net is comprehensively evaluated on Dublin and RueMonge2014 benchmarks, achieving 67.02% and 59.80% mIoU, respectively. We also demonstrate the superiority of the proposed AFGL-Net by comparing with the state-of-the-art methods and various ablation studies. [ABSTRACT FROM AUTHOR]

The dependence of the output pulse characteristics of a Mamyshev fiber oscillator on cavity parameters is investigated in detail. We analyze the change in pulse spectrum bandwidth, pulse duration, dechirped pulse duration and chirp with the change in fiber group velocity dispersion, fiber nonlinearity, gain, and filters by putting forward a numerical model. In particular, as one of the most important components, the effect of filters bandwidth and the central wavelength interval between them is discussed. The passive fibers are classified into two kinds according to their locations in the cavity, which are the one before the gain fiber and the one after the gain fiber. Numerical simulation results show that a wide spectrum can be obtained by increasing the nonlinearity of the second passive fiber, while the change in nonlinearity of the first passive fiber has a weak effect on spectrum broadening. A wide spectrum could also be obtained by increasing the nonlinearity or the small-signal gain coefficient of the gain fiber. A Yb-doped Mamyshev fiber oscillator is demonstrated. The results show the increase in pump power, which agrees reasonably well with the numerical simulation results. [ABSTRACT FROM AUTHOR]

Point cloud registration is the foundation and key step for many vital applications, such as digital city, autonomous driving, passive positioning, and navigation. The difference of spatial objects and the structure complexity of object surfaces are the main challenges for the registration problem. In this paper, we propose a graph attention capsule model (named as GACM) for the efficient registration of terrestrial laser scanning (TLS) point cloud in the urban scene, which fuses graph attention convolution and a three-dimensional (3D) capsule network to extract local point cloud features and obtain 3D feature descriptors. These descriptors can take into account the differences of spatial structure and point density in objects and make the spatial features of ground objects more prominent. During the training progress, we used both matched points and non-matched points to train the model. In the test process of the registration, the points in the neighborhood of each keypoint were sent to the trained network, in order to obtain feature descriptors and calculate the rotation and translation matrix after constructing a K-dimensional (KD) tree and random sample consensus (RANSAC) algorithm. Experiments show that the proposed method achieves more efficient registration results and higher robustness than other frontier registration methods in the pairwise registration of point clouds. [ABSTRACT FROM AUTHOR]

To determine the effects of a gradual temperature decrease on reactor performance and the microbial community, four fixed-bed reactors that were packed with a biofilm carrier were operated for 217 days. The temperature of the reactors was decreased from 30 °C to 3 °C. The reactors initially soured at 3 °C and recovered when they were returned to 4 °C, as indicated by the stabilization of biogas production, methane production, VFA concentration, pH, and the COD removal rate. Our results also revealed that methanomicrobiales were the dominant methanogen, the concentration of the 16S rRNA gene in the carbon-fiber carrier sludge exceeded the same gene concentration in the deposited sludge, and that the carbon-fiber carrier played an important role in methanomicrobiale colonization at low temperatures. We suggest that 4 °C is the low-temperature threshold for optimal reactor performance. [ABSTRACT FROM AUTHOR]

High purity titanium (Ti) thin strip was prepared by rolling with large deformation and was characterized by the means of Transmission Electron Microscopy (TEM), selected area diffraction (SAED) pattern, high-resolution (HRTEM) analysis, as well as Transmission Kikuchi Diffraction (TKD). It is found that there are face-centered cubic (FCC) Ti laths formed within the matrix of hexagonal close packing (HCP) Ti. This shows that the HCP-FCC phase transition occurred during the rolling, and a specific orientation relationship (OR) between HCP phase and FCC phase obeys 〈0001〉α//〈001〉FCC and {10 1 ¯ 0}α//{110}FCC. The ORs of HCP-FCC phase transition are deeply studied by TKD pole figure and phase transformation matrix. It is found that the derived results via pole figure and transformation matrix are equivalent, and are consistent with TEM-SAED analysis results, which proves that these two methods can effectively characterize the ORs of HCP-FCC phase transition and predict possible FCC phase variants. [ABSTRACT FROM AUTHOR]

This paper adopts the method of steel tube wall thickness and strength reduction to simulate corrosion damage. The numerical model of the square concrete-filled steel tube long column (SCFST-LC) under eccentric compression after acid rain corrosion is established in the finite element software, ABAQUS. The reliability and accuracy of the model are verified by comparing it with published relevant experimental results. The failure mode, load-deformation curve, and ultimate compressive load were analysed. Following that, the impacts of section size, yield strength of the steel tube, axial compressive strength of concrete, steel ratio, slenderness ratio, and load eccentricity on its ultimate compressive load are comprehensively investigated. The results demonstrate that the ultimate compressive load of the SCFST-LC decreases significantly with the increase in corrosion rate. The corrosion rate increases from 10 to 40%, and the ultimate bearing capacity decreases by 37.6%. Its ultimate bearing capacity can be enhanced due to the increase in section size, material strength, and steel ratio. In contrast, the ascending slenderness ratio and load eccentricity has harmful effects on the ultimate compressive load of the specimens. Finally, a simplified formula for the axial compressive load of the SCFST-LC under eccentric compression after acid rain corrosion is proposed. The calculation accuracy is high and the deviation of the results is basically within 15%, which is in good agreement with the numerical simulation results. [ABSTRACT FROM AUTHOR]

Complex dermal wounds represent major medical and financial burdens, especially in the context of comorbidities such as diabetes, infection and advanced age. New approaches to accelerate and improve, or "fine tune" the healing process, so as to improve the quality of cutaneous wound healing and management, are the focus of intense investigation. Here, we investigate the topical application of a recombinant immune modulating protein which inhibits the interactions of chemokines with glycosaminoglycans, reducing damaging or excess inflammation responses in a splinted full-thickness excisional wound model in mice. M-T7 is a 37 kDa-secreted, virus-derived glycoprotein that has demonstrated therapeutic efficacy in numerous animal models of inflammatory immunopathology. Topical treatment with recombinant M-T7 significantly accelerated wound healing when compared to saline treatment alone. Healed wounds exhibited properties of improved tissue remodeling, as determined by collagen maturation. M-T7 treatment accelerated the rate of peri-wound angiogenesis in the healing wounds with increased levels of TNF, VEGF and CD31. The immune cell response after M-T7 treatment was associated with a retention of CCL2 levels, and increased abundances of arginase-1-expressing M2 macrophages and CD4 T cells. Thus, topical treatment with recombinant M-T7 promotes a pro-resolution environment in healing wounds, and has potential as a novel treatment approach for cutaneous tissue repair. [ABSTRACT FROM AUTHOR]

Spinal cord injury (SCI) initiates a severe, destructive inflammation with pro-inflammatory, CD68+/CD163−, phagocytic macrophages infiltrating the area of necrosis and hemorrhage by day 3 and persisting for the next 16 weeks. Inhibition of macrophage infiltration of the site of necrosis that is converted into a cavity of injury (COI) during the first week post-SCI, should limit inflammatory damage, shorten its duration and result in neuroprotection. By sustained subdural infusion we administered Serp-1, a Myxoma virus-derived immunomodulatory protein previously shown to improve neurologic deficits and inhibit macrophage infiltration in the COI in rats with the balloon crush SCI. Firstly, in a 7 day long study, we determined that the optimal dose for macrophage inhibition was 0.2 mg/week. Then, we demonstrated that a continuous subdural infusion of Serp-1 for 8 weeks resulted in consistently accelerated lowering of pro-inflammatory macrophages in the COI and in their almost complete elimination similar to that previously observed at 16 weeks in untreated SCI rats. The macrophage count in the COI is a quantitative test directly related to the severity of destructive inflammation initiated by the SCI. This test has consistently demonstrated anti-inflammatory effect of Serp-1 interpreted as neuroprotection, the first and necessary step in a therapeutic strategy in neurotrauma. [ABSTRACT FROM AUTHOR]

Reservoir heterogeneity is a key geological problem that restricts oil and gas exploration and development of clastic rocks from the early to late stages. Existing reservoir heterogeneity modeling methods such as multiple-point geostatistics (MPS) can accurately model the two-dimensional anisotropic structures of reservoir lithofacies. However, three-dimensional training images are required to construct three-dimensional reservoir lithofacies anisotropic structures models, and the method to use reservoir heterogeneity model of fewer-dimensional to obtain a three-dimensional model has become a much-focused research topic. In this study, the outcrops of the second member of Qingshuihe Formation (K1q2) in the northwestern margin of the Junggar Basin, which are lower cretaceous rocks, were the research target. The three-dimensional reservoir heterogeneity model of the K1q2 outcrop was established based on the unmanned aerial vehicle (UAV) digital outcrops model and MPS techniques, and the "sequential two-dimensional conditioning data" (s2Dcd) method was modified based on a sensitivity parameter analysis. Results of the parametric sensitivity analysis revealed that the isotropic multigrid simulations demonstrate poor performance because of the lack of three-dimensional training images, conditioning data that are horizontally discrete and vertically continuous, and distribution of lithofacies that are characterized by large horizontal continuities and small thicknesses. The reservoir lithofacies anisotropic structure reconstructions performed well with anisotropic multigrids. The simulation sequence of two-dimensional surfaces for generating the three-dimensional anisotropic structure of reservoir lithofacies models should be reasonably planned according to the actual geological data and limited hard data. In additional to this, the conditional probability density function of each two-dimensional training image should be fully utilized. The simulation results using only one two-dimensional section will have several types of noises, which is not consistent with the actual geological background. The anisotropic multigrid simulations and two-dimensional training image simulation sequence, proposed in this paper as "cross mesh, refinement step by step", effectively reduced the noise generated, made full use of the information from the two-dimensional training image, and reconstructed the three-dimensional reservoir lithofacies anisotropic structures models, thus conforming to the actual geological conditions. [ABSTRACT FROM AUTHOR]

Spinal cord injury (SCI) results in massive secondary damage characterized by a prolonged inflammation with phagocytic macrophage invasion and tissue destruction. In prior work, sustained subdural infusion of anti-inflammatory compounds reduced neurological deficits and reduced pro-inflammatory cell invasion at the site of injury leading to improved outcomes. We hypothesized that implantation of a hydrogel loaded with an immune modulating biologic drug, Serp-1, for sustained delivery after crush-induced SCI would have an effective anti-inflammatory and neuroprotective effect. Rats with dorsal column SCI crush injury, implanted with physical chitosan-collagen hydrogels (CCH) had severe granulomatous infiltration at the site of the dorsal column injury, which accumulated excess edema at 28 days post-surgery. More pronounced neuroprotective changes were observed with high dose (100 µg/50 µL) Serp-1 CCH implanted rats, but not with low dose (10 µg/50 µL) Serp-1 CCH. Rats treated with Serp-1 CCH implants also had improved motor function up to 20 days with recovery of neurological deficits attributed to inhibition of inflammation-associated tissue damage. In contrast, prolonged low dose Serp-1 infusion with chitosan did not improve recovery. Intralesional implantation of hydrogel for sustained delivery of the Serp-1 immune modulating biologic offers a neuroprotective treatment of acute SCI. [ABSTRACT FROM AUTHOR]

Viruses are widely used as a platform for the production of therapeutics. Vaccines containing live, dead and components of viruses, gene therapy vectors and oncolytic viruses are key examples of clinically-approved therapeutic uses for viruses. Despite this, the use of virus-derived proteins as natural sources for immune modulators remains in the early stages of development. Viruses have evolved complex, highly effective approaches for immune evasion. Originally developed for protection against host immune responses, viral immune-modulating proteins are extraordinarily potent, often functioning at picomolar concentrations. These complex viral intracellular parasites have "performed the R&D", developing highly effective immune evasive strategies over millions of years. These proteins provide a new and natural source for immune-modulating therapeutics, similar in many ways to penicillin being developed from mold or streptokinase from bacteria. Virus-derived serine proteinase inhibitors (serpins), chemokine modulating proteins, complement control, inflammasome inhibition, growth factors (e.g., viral vascular endothelial growth factor) and cytokine mimics (e.g., viral interleukin 10) and/or inhibitors (e.g., tumor necrosis factor) have now been identified that target central immunological response pathways. We review here current development of virus-derived immune-modulating biologics with efficacy demonstrated in pre-clinical or clinical studies, focusing on pox and herpesviruses-derived immune-modulating therapeutics. [ABSTRACT FROM AUTHOR]

Numerous treatments have been developed to promote wound healing based on current understandings of the healing process. Hemorrhaging, clotting, and associated inflammation regulate early wound healing. We investigated treatment with a virus-derived immune modulating serine protease inhibitor (SERPIN), Serp-1, which inhibits thrombolytic proteases and inflammation, in a mouse excisional wound model. Saline or recombinant Serp-1 were applied directly to wounds as single doses of 1 μg or 2 µg or as two 1 µg boluses. A chitosan-collagen hydrogel was also tested for Serp-1 delivery. Wound size was measured daily for 15 days and scarring assessed by Masson's trichrome, Herovici's staining, and immune cell dynamics and angiogenesis by immunohistochemistry. Serp-1 treatment significantly accelerated wound healing, but was blocked by urokinase-type plasminogen activator (uPAR) antibody. Repeated dosing at a lower concentration was more effective than single high-dose serpin. A single application of Serp-1-loaded chitosan-collagen hydrogel was as effective as repeated aqueous Serp-1 dosing. Serp-1 treatment of wounds increased arginase-1-expressing M2-polarized macrophage counts and periwound angiogenesis in the wound bed. Collagen staining also demonstrated that Serp-1 improves collagen maturation and organization at the wound site. Serp-1 has potential as a safe and effective immune modulating treatment that targets thrombolytic proteases, accelerating healing and reducing scar in deep cutaneous wounds. [ABSTRACT FROM AUTHOR]

Panoramic images have a wide range of applications in many fields with their ability to perceive all-round information. Object detection based on panoramic images has certain advantages in terms of environment perception due to the characteristics of panoramic images, e.g., lager perspective. In recent years, deep learning methods have achieved remarkable results in image classification and object detection. Their performance depends on the large amount of training data. Therefore, a good training dataset is a prerequisite for the methods to achieve better recognition results. Then, we construct a benchmark named Pano-RSOD for panoramic road scene object detection. Pano-RSOD contains vehicles, pedestrians, traffic signs and guiding arrows. The objects of Pano-RSOD are labelled by bounding boxes in the images. Different from traditional object detection datasets, Pano-RSOD contains more objects in a panoramic image, and the high-resolution images have 360-degree environmental perception, more annotations, more small objects and diverse road scenes. The state-of-the-art deep learning algorithms are trained on Pano-RSOD for object detection, which demonstrates that Pano-RSOD is a useful benchmark, and it provides a better panoramic image training dataset for object detection tasks, especially for small and deformed objects. [ABSTRACT FROM AUTHOR]