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With the development of human society, the balance between the minimum ecological instream flow requirement (MEIFR), which is an essential part of the ecological water demand in arid areas, and anthropogenic water depletion has received increasing attention. However, due to the lack of hydrological station data and river information on arid basins, previous researchers usually considered only the individual ecological water demand of rivers, lakes, or oases. To address this issue, a new method that combines river hydraulic parameters and the wet circumference obtained by an unmanned aerial vehicle (UAV) and remote sensing hydrological station (RSHS) technologies was applied to obtain the MEIFR and, then, systematically and quantitatively explore the balance from the perspective of the entire basin of Aiding Lake from 1990 to 2022, which is the lowest point of Chinese terrestrial territory. The results showed the following: (1) since 1990, the discharge of the seven rivers in the study area increased by 1–6%, and the MEIFR of these rivers increased by 15–100%; both quantities decreased by 3–5% from the upper to the lower reaches of the basin; (2) the surface area and water level of Aiding Lake decreased by 5% and 14%, respectively, but the MEIFR first decreased by 25% from 1990 to 2013 and, then, increased by 66.7% from 2013 to 2022; and (3) from 2011 to 2022, the MEIFR and anthropogenic water depletion exhibited a balance. Against the background of climate change, this research revealed that the MEIFR of the rivers in the Aiding Lake Basin have shown an upward trend over the past 30 years and quantitatively determined the above balance relationship and the period of its occurrence. This study supplied a method that could provide guidance for water resource management by decision-makers at a global level, thus helping achieve the sustainable development goals (SDGs). [ABSTRACT FROM AUTHOR]

Lactococcus garvieae (L. garvieae) is a pathogenic gram-positive, catalase-negative (GPCN) bacterium that causes bovine mastitis. A total of 49 L. garvieae isolates were identified from 1441 clinical mastitis (CM) samples. The pathogenic effects of L. garvieae were studied with two infection models: bovine mammary epithelial cells cultured in vitro and murine mammary infections in vivo. The overall farm prevalence was 15.5% (13/84 farms in 9/19 provinces) and sample prevalence was 3.40% (49/1441). Post-treatment somatic cell count (SCC) post L. garvieae infection was significantly higher than the other GPCN pathogens isolated, and the bacteriological cure fraction was 41.94% (13/31) after intramammary antibiotic treatment. All L. garvieae isolates were resistant to rifaximin, 12.24% of isolates were resistant to cephalexin, and 10.20% (5/49) were multidrug-resistant (MDR). The most prevalent virulence genes were Hemolysin 1 (hly1)(100%), Hemolysin 2 (hly2) (97.96%), NADH oxidase (NADHO) (100%), Superoxide dismutase (SOD) (100%), Adhesin Pav (Pav) (100%), Adhesin PsaA (PsaA) (100%), Enolase (eno) (100%), Adhesin cluster 1(AC1) (100%), Adhesin cluster 2 (AC2) (100%), and several exopolysaccharides. L. garvieae rapidly adhered to bovine mammary epithelial cells, resulting in an elevated lactate dehydrogenase release. Edema and congestion were observed in challenged murine mammary glands and bacteria were consistently isolated at 12, 24, 48, 72, and 120 h after infection. We concluded that L. garvieae had good adaptive ability in the bovine and murine mammary cells and tissue. Given the resistance profile, penicillin and ampicillin are potential treatments for CM cases caused by L. garvieae. [ABSTRACT FROM AUTHOR]

In this study, water-soluble natural polysaccharides were extracted from the stems of Houttuynia cordata Thunb (HCPS). The optimization of the hot water extraction process using response surface methodology (RSM), and the extraction factors, were analyzed by multiple stepwise regression analysis and Pearson analysis. Then, the structural characterization and biological activity of the HCPS were investigated. The results indicated that the maximum extraction yield (2.43%) of the HCPS was obtained at the optimal condition (extraction temperature for 90 °C, extraction time for 5 h, solid-liquid ratio for 1:30 g/mL). The extraction temperature was determined to be the primary factor influencing the extraction yield. The HCPS molecules had an average molecular weight of 8.854 × 103 kDa and were primarily of mannose (Man), rhamnose (Rha), glucuronic acid (GlcA), galacturonic acid (GalA), glucose (Glc), and xylose (Xyl). In addition, the backbone of the HCPS might consist of →6)-α-d-Glcp-(1→ and →6)-β-d-GalpA-(1→. The HCPS had no triple-helix structure. The scanning electron microscopy (SEM) results showed that the HCPS presented a smooth and uniform appearance, and some sheet and chain structures existed. Moreover, the HCPS exhibited significant anti-oxidant activity and inhibited the activity of α-amylase and α-glucosidase. These findings showed that HCPS might be developed into a potential material for hypoglycemia, and provides a reference for the development of Houttuynia cordata polysaccharide applications in food. [ABSTRACT FROM AUTHOR]

With the standardization and commercialization of 5G, research on 6G technology has begun. In this paper, a new low-complexity soft-input–soft-output (SISO) adaptive detection algorithm for short CPM bursts is proposed for low-power, massive Internet of Things (IoT) connectivity in 6G. First, a time-invariant trellis is constructed on the basis of truncation in order to reduce the number of states. Then, adaptive channel estimators, recursive least squares (RLS), or least mean squares (LMS), are assigned to each hypothetical sequence by using the recursive structure of the trellis, and per-survivor processing (PSP) is used to improve the quality of channel estimation and reduce the number of searching paths. Then, the RLS adaptive symbol detector (RLS-ASD) and LMS adaptive symbol detector (LMS-ASD) could be acquired. Compared to using a least-squares estimator, the RLS-ASD avoids matrix inversion for the computation of branch metrics, while the LMS-ASD further reduces the steps in the RLS-ASD at the cost of performance. Lastly, a soft information iteration process is used to further improve performance via turbo equalization. Simulation results and analysis show that the RLS-ASD improves performance by about 1 dB compared to the state-of-the-art approach in time-variant environments while keeping a similar complexity. In addition, the LMS-ASD could further significantly reduce complexity with a power loss of approximately 1 dB. Thus, a flexible choice of detectors can achieve a trade-off of performance and complexity. [ABSTRACT FROM AUTHOR]

With the surge of Internet of Things (IoT) applications using unmanned aerial vehicles (UAVs), there is a huge demand for an excellent complexity/power efficiency trade-off and channel fading resistance at the physical layer. In this paper, we consider the blind equalization of short-continuous-phase-modulated (CPM) burst for UAV-aided IoT. To solve the problems of the high complexity and poor convergence of short-burst CPM blind equalization, a novel turbo blind equalization algorithm is proposed based on establishing a new expectation–maximization Viterbi (EMV) algorithm and turbo scheme. Firstly, a low complexity blind equalization algorithm is obtained by applying the soft-output Lazy Viterbi algorithm within the EM algorithm iteration. Furthermore, a set of initializers that achieves a high global convergence probability is designed by the blind channel-acquisition (BCA) method. Meanwhile, a soft information iterative process is used to improve the system performance. Finally, the convergence, bit error rate, and real-time performance of iterative detection can be further improved effectively by using improved exchange methods of extrinsic information and the stopping criterion. The analysis and simulation results show that the proposed algorithm achieves a good blind equalization performance and low complexity. [ABSTRACT FROM AUTHOR]

River discharge is an important hydrological parameter of river water resources. Especially in small- and medium-scale rivers, data deficiency is the biggest problem for studies of river discharge. In recent years, remote sensing has become a rapid and convenient method to estimate river discharge. However, remote sensing images still have some difficulty generating continuous long-term river discharge. To address this problem, we developed a new method coupling the remote sensing hydrology station method (RSHS) with statistical regression downscaling, using data from optical satellites (Landsat-8, Sentinel-2), radar satellites (Sentinel-1), and un-manned aerial vehicles (UAVs). We applied this method to monitor monthly river discharge for small- and medium-scale rivers from 2016 to 2020 on Yunnan-Guizhou Plateau and evaluated the accuracy of the results. The results show that (1) by applying the newly constructed method, the water body continuity index obtained by Landsat-8 increased by 7% and the average river length percentage in the channel reached 90.7%, a 40% increase; (2) there were only 10 river flow data points, on average, in the 5-year period obtained before this method was applied; after this method was applied, more than 50 river flow data points could be obtained, on average, extending the quantity of data fivefold; in addition, improper extreme values could also be avoided; (3) with better continuity of water body distribution, the images provided steadier river widths. The relative error of daily flow estimation from Landsat-8 images was reduced by 60% and the mean percentage error was reduced by one-fourth. The relative error of the multisource remote sensing composited flow was reduced by 37% with a reduction in the mean percentage error of over a half; (4) in addition, we found that when the threshold difference between water bodies and land in remote sensing images is more than 0.2, the impact of water body recognition error on flow accuracy can be ignored. This method helps to overcome the absence of remote sensing methods for the long-term estimation of flow series in small- and medium-scale rivers, improves the accuracy of remote sensing methods for calculating flow, and provides ideas for regional water resource management and utilization. [ABSTRACT FROM AUTHOR]

Infection with the epidemic virulent strain of Streptococcus suis serotype 2 (SS2) can cause septicemia in swine and humans, leading to pneumonia, meningitis and even cytokine storm of Streptococcal toxic shock-like syndrome. Despite some progress concerning the contribution of bacterial adhesion, biofilm, toxicity and stress response to the SS2 systemic infection, the precise mechanism underlying bacterial survival and growth within the host bloodstream remains elusive. Here, we reported the SS2 virulent strains with a more than 20 kb endoSS-related insertion region that showed significantly higher proliferative ability in swine serum than low-virulent strains. Further study identified a complete N-glycans degradation system encoded within this insertion region, and found that both GH92 and EndoSS contribute to bacterial virulence, but that only DndoSS was required for optimal growth of SS2 in host serum. The supplement of hydrolyzed high-mannose-containing glycoprotein by GH92 and EndoSS could completely restore the growth deficiency of endoSS deletion mutant in swine serum. EndoSS only hydrolyzed a part of the model glycoprotein RNase B with high-mannose N-linked glycoforms into a low molecular weight form, and the solo activity of GH92 could not show any changes comparing with the blank control in SDS-PAGE gel. However, complete hydrolyzation was observed under the co-incubation of EndoSS and GH92, suggesting GH92 may degrade the high-mannose arms of N-glycans to generate a substrate for EndoSS. In summary, these findings provide compelling evidences that EndoSS-related N-glycans degradation system may enable SS2 to adapt to host serum-specific availability of carbon sources from glycoforms, and be required for optimal colonization and full virulence during systemic infection. [ABSTRACT FROM AUTHOR]

Recently, bovine enterovirus (BEV) has caused several respiratory and gastrointestinal diseases outbreaks in cattle. Monitoring the epidemiological and pathogenic characteristics of this virus is crucial to controlling its spread. We isolated a BEV strain with typical cytopathic effects from the faeces of cows with significant diarrhoeal symptoms in China and observed the viral particles within 20-30 nm through transmission electron microscopy. Then, we designated this strain as HB19-1 in this study. The multistep growth curves showed that the virus propagated well in the MDBK cells. Molecular genetic analysis of VP1 indicated that HB19-1 belonged to the BEV-F1 group. Although the challenged ICR mice did not exhibit typical disease symptoms in animal infection assay, we observed significant pathological damage in the lungs, intestines, and muscle tissues. In summary, we isolated a BEV strain HB19-1 causing severe diarrhoea in cattle and proposed reinforcing the epidemiological surveillance of this virus.