Agroforestry systems provide soil microorganisms with a rich variety of carbon sources and a relatively stable living environment. In this study, five planting systems were investigated; a pure poplar (Populus × euramericana ‘Nanlin 895’) plantation (P) system, a pure crop (wheat [Triticum aestivum L.] and soybean [Glycine max (Linn.) Merr.]) (WS) system, a poplar + wheat + soybean agroforestry (PWS) system, a poplar + potherb mustard (Brassica juncea var. multiceps) agroforestry (PP) system, and a poplar + native chicken agroforestry (PN) system. The Biolog EcoPlate method was used to determine the vertical and seasonal variations in soil microbial metabolic capacity. The average well color development, carbon source utilization ability, and microbial diversity index values were higher throughout the soil profile, and highly stable with seasonal changes in the PWS and PP agroforestry systems. Furthermore, the influence of the planting systems and seasonal changes on the metabolic activity of soil microorganisms decreased with an increase in soil depth. Overbreeding chickens in the forest reduced the metabolic activity of soil microorganisms. It was also found that plants influenced soil microbial metabolism through the available carbon source types. Therefore, agroforestry systems improved the metabolic potential of the soil microbial community. Our results demonstrated that soil microbial communities are affected by the planting system and soil depth. The findings enhance our understanding of the functional diversity of soil microorganisms in agroforestry systems.

Background It has been hypothesized that epigenomic modifications such as genomic methylation changes are an intermediate step linking environmental exposures with allergic disease development. Associations between individual DNA methylation CpG sites and allergic diseases have been reported, but they have not been assessed regarding their joint predictive capability. Methods Data were obtained from 240 children of the German LISA cohort. Blood-based DNA methylation was measured at six and ten years. Aeroallergen sensitization, at least RAST class 1, was measured in blood at six, ten and 15 years. We calculated six methylation risk scores (MRS) for allergy-related phenotypes based on available publications and assessed their performance both cross-sectionally and prospectively. Dose-response associations between aeroallergen sensitization and MRS, their correlation and mapping of common hits were evaluated. Results All six atopy-related MRS were highly correlated (r>0.86) and seven CpGs were included in more than one MRS. Cross-sectionally, we observed an 80% increased risk for aeroallergen sensitization at six years with an increased risk score by one standard deviation (best MRS: relative risk = 1.81, 95% confidence interval = [1.43; 2.27]). Significant associations were also seen at ten years and in prospective models, though the effect of the latter was attenuated when only including participants not sensitized at baseline. A clear dose-response relationship with RAST classes of aeroallergen sensitization could be established cross-sectionally, but not prospectively. Conclusion We found good classification and prediction capabilities of calculated allergy-related MRS, particularly cross-sectionally for the allergy prevalence, underlining the relevance of altered gene-regulation in allergic diseases.

The authors present an revolutionary study aiming to evaluate the effect of alterations in potassium concentrations in transfused packed red blood cells (PRBC) on neonate and infant potassium levels after congenital cardiac surgery. By establishing a strict protocol which restricts the rate of transfusion, the age of the transfused PRBC, and not transfusing a PRBC with a potassium level above 15 mmol/L, they accomplished to suggest a safe and easy way for preventing transfusion associated hyperkalemia.

Social media has been embraced by different people as a convenient and official medium of communication. People write messages and attach images and videos on Twitter, Facebook and other social media which they share. Social media therefore generates a lot of data that is rich in sentiments from these updates. Sentiment analysis has been used to determine opinions of clients, for instance, relating to a particular product or company. Knowledge based approach and Machine learning approach are among the strategies that have been used to analyze these sentiments. The performance of sentiment analysis is however distorted by noise, the curse of dimensionality, the data domains and size of data used for training and testing. This research aims at developing a model for sentiment analysis in which dimensionality reduction and the use of different parts of speech improves sentiment analysis performance. It uses natural language processing for filtering, storing and performing sentiment analysis on the data from social media. The model is tested using Naïve Bayes, Support Vector Machines and K-Nearest neighbor machine learning algorithms and its performance compared with that of two other Sentiment Analysis models. Experimental results show that the model improves sentiment analysis performance using machine learning techniques.

Aiming at the problem of huge energy consumption in the Fog Wireless Access Networks (F-RANs), the resource allocation scheme of the F-RAN architecture under the cooperation of renewable energy is studied in this paper. Firstly, the transmission model and Energy Harvesting (EH) model are established, the solar energy harvester is installed on each Fog Access Point (F-AP), and each F-AP is connected to the smart grid. Secondly, the optimization problem is established according to the constraints of Signal to Noise Ratio (SNR), available bandwidth and energy harvesting, so as to maximize the average throughput of F-RAN architecture with hybrid energy sources. Finally, the dynamic power allocation scheme in the network is studied by using Q-learning and Deep Q Network (DQN) respectively. Simulation results show that the proposed two algorithms can improve the average throughput of the whole network compared with other traditional algorithms.

Endometriosis constitutes a benign condition, occurring in 10-12% of menstruating women. Bowel involvement is estimated to occur in 5-12% with the rectosigmoid region involved in up to 90% of these cases. We present the case of a 45-year-old Caucasian female patient with rectosigmoid endometriosis.

Abstract Development of serious complications after COVID-19 infection can occur even in very young patients without any comorbidities. Appropriate, non-aggressive ventilation and adequate treatment is essential for COVID-19 convalescents and may prevent them from aggravating surgical procedures.

Taste is one of the most basic and important sensations that is able to monitor the food quality and avoid intake of potential danger materials. Whether as an inevitable symptom of aging or a complication of cancer treatment, taste loss so seriously affects the patient’s life quality. Taste bud organoids provide a great convenience for the research of taste functions and the underlying mechanisms due to their characteristics of availability, strong maneuverability, and high similarity to the in-vivo taste buds. This review gives a systemic and comprehensive introduction to the preparation and application of taste bud organoids towards chemical sensing mechanisms. For the first, the basic structure and function of taste buds in biomedicine will be brief introduced. Then, the currently available approaches for the preparation of taste bud organoids are summarized and discussed, which are mainly divided into two categories, i.e. stem/progenitor cell-derived approach and tissue-derived approach. For the next, different applications of taste bud organoids in biomedicine are outlined based on their central roles such as disease modeling, biological sensing, gene regulation, and signal transduction. Finally, the current challenges, future development trends and prospects of research in taste bud organoids are proposed and discussed.

This work analyzes the existence of solution and approximate controllability for higher order non-linear fractional integro-differential systems with Riemann-Liouville derivatives in Banach spaces. Firstly, the definition of mild solution for the system is derived. Then a set of sufficient conditions for the existence of mild solution and approximate controllability of the system is obtained. The discussions are based on fixed point approach, and the theory of convolution and fractional resolvent. To illustrate the feasibility of developed theory, an example is given.

DNA metabarcoding has been widely used to access and monitor species. However, several challenges remain open for its mainstream application in ecological studies, particularly when dealing with a quantitative approach. In a from the Cover article in this issue of Molecular Ecology, Cédric et al. (2021) report species-level ichthyoplankton dynamics for 97 fish species from two Amazon river basins using a clever quantitative metabarcoding approach employing a probe capture method. They clearly show that most species spawned during the rainy season when the floods started, but interestingly, species from the same genus reproduced in distinct periods (i.e., inverse phenology). Opportunistically, Cédric et al. (2021) reported that during an intense hydrological anomaly, several species had a sharp reduction in spawning activity, demonstrating a quick response to environmental cues. This is an interesting result since the speed at which fish species can react to environmental changes, during the spawning period, is largely unknown. Thus, this study brings remarkable insights into basic life history information that is imperative for proposing strategies that could lead to a realistic framework for sustainable fisheries management practices and conservation, fundamental for an under-studied and threatened realm, such as the Amazon River basin.

In 1859, Charles Darwin proposed that species are not fundamentally different from subspecies or the varieties from which they evolve. A century later, Dobzhansky (1958) suggested that many such lineages are ephemeral and are likely to revert differentiation through introgression (Fig. 1A); only a few evolve complete reproductive isolation and persist in sympatry. In this issue of Molecular Ecology, Bouzid et al. (2021) show how new analytical methods, when applied to genome data, allow us to more precisely determine whether or not species formation follows the paths outlined by Darwin and Dobzhansky (Fig. 1B). The authors study the diversification of the lizard Sceloporus occidentalis, finding a continuum of genetic interactions between the preservation of genetic identity to genetic merger, analogous to what is exemplified by ring species. In doing so, they teach us two tales on species formation: that lineages are fractal byproducts of evolutionary processes such as genetic drift and selection, and that lineages are often ephemeral and do not always progress into species. Studying ephemeral lineages like those in S. occidentalis allows us to capture divergence at its earliest stages, and potentially to determine the factors that allow lineages to remain distinct despite pervasive gene flow. These lineages thus serve as a natural laboratory to address long standing hypotheses on species formation.

•A 28-month retrospective review from February 2019 to April 2021 of penetrating neck injuries (PNIs) at our trauma centre revealed a 48% (n=25 to n=37) increase in PNIs ‘post-lockdown’ (lockdown date = 23rd March 2020). •The aetiology of PNI changed over time, with an increase in the proportion of Deliberate Self Harm’ (DSH) cases from 1/3 to 2/3rds of case (n=9 to n=25), an overall 177.8% increase ‘post-lockdown’. An increase in mortality was also seen with no deaths ‘pre-lockdown’, and 3 deaths ‘post-lockdown’. •‘Accidental Injuries’ (AI) increased from 4% to 10% of cases (n=1 to n=4) post lockdown, with ‘grievous bodily harm (GBH) reducing from half to 1/5th of all cases (n=13 to n=8), and ‘domestic violence’ from 8% of cases to no cases post lockdown (DV) ‘post lockdown’. •‘Pre-lockdown’ 10% of DSH patients (n=1) were noted to have a prior mental health diagnosis or psychiatric care, ‘post-lockdown’ this increased to 61.5% (n=16) of DSH patients. •Data from our tertiary trauma centre in London has shown a change in aetiology, psychiatric co-morbidity and number of PNIs pre and post lockdown.

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This study investigates the impacts of climate change on the hydrology and soil thermal regime of ten sub-arctic watersheds (northern Manitoba, Canada) using the Variable Infiltration Capacity (VIC) model. We utilize statistically downscaled and bias-corrected forcing datasets based on 17 general circulation model (GCM) - representative concentration pathways (RCP) scenarios from phase 5 of the Coupled Model Intercomparison Project (CMIP5) to run the VIC model for three 30-year periods: a historical baseline (1981–2010), and future projections (2021–2050: 2030s and 2041–2070: 2050s), under representative concentration pathways (RCPs) 4.5 and 8.5. The CMIP5 Multi-Model Ensemble (MME) mean-based VIC simulations indicate a 15–20% increase and 10% decrease in the projected annual precipitation and snowfall, respectively over the southern portion of the basin and >20% rainfall increase over the higher latitudes of the domain by the 2050s. Snow accumulation is projected to decline across all sub-basins, particularly in the lower latitudes. Projected uncertainties in major water balance components (i.e., evapotranspiration, surface runoff, and streamflow) are more substantial in the wetland and lake-dominated Grass and Gunisao watersheds than their eight counterparts. Future warming increases soil temperatures >2.5°C by the 2050s, resulting in 40–50% more baseflow. Further analyses of soil temperature trends at three different depths show the most pronounced warming in the top soil layer (1.6°C 30-year-1 in the 2050s), whereas baseflow increases substantially by 19.7% and 46.3% during the 2030s and 2050s, respectively. These results provide crucial information on the potential future impacts of warming soil temperatures on the hydrology of sub-arctic watersheds in north-central Canada and similar hydro-climatic regimes.

We introduce and study in a general setting the concept of homogeneity of an operator and, in particular, the notion of homogeneity of an integral operator. In the latter case, homogeneous kernels of such operators are also studied. The concept of homogeneity is associated with transformations of a measure - measure dilations, which are most natural in the context of our general research scheme. For the study of integral operators, the notions of weak and strong homogeneity of the kernel are introduced. The weak case is proved to generate a homogeneous operator in the sense of our definition, while the stronger condition corresponds to the most relevant specific examples - classes of homogeneous integral operators on various metric spaces, and allows us to obtain an explicit general form for the kernels of such operators. The examples given in the article - various specific cases - illustrate general statements and results given in the paper and at the same time are of interest in their own way.

Objective To investigate the epidemiological changes in extended-spectrum β-lactamase-producing Enterobacteriaceae (ESBL-E) vaginal colonization in high-risk pregnant women and identify independent risk factors. Further, the differences in perinatal outcomes according to maternal ESBL-E vaginal colonization were analyzed. Design Retrospective cohort study. Setting Republic of Korea Population 1,460 women admitted to our high-risk pregnancy unit between 14+0 and 35+6 gestational weeks. Methods The study period was divided into periods 1 (January 2010 to July 2015) and 2 (August 2015 to December 2020). The main outcomes were analyzed according to each period and ESBL-E vaginal colonization. Main Outcome Measures ESBL-E vaginal colonization rate, risk factors for ESBL-E vaginal colonization, and perinatal outcomes. Results The ESBL-E vaginal colonization rate was higher in period 2, which was attributed to a significantly higher proportion of ESBL-producing Escherichia coli. Cerclage (odds ratio [OR]: 3.248; 95% confidence interval [CI]: 1.744–6.049) and prior antibiotic treatment (OR: 3.044; 95% CI: 1.713–5.410) were found as independent risk factors for ESBL-E vaginal colonization. Earlier gestational age at delivery, and higher proven early-onset neonatal sepsis (EONS) rate were observed in the ESBL-E-positive group. Conclusions The ESBL-E vaginal colonization rate in high-risk pregnant patients has increased over the past decade, and the independent risk factors for colonization are cerclage and prior antibiotic treatment. Additionally, maternal ESBL-E vaginal colonization is associated with higher proven EONS rates. Funding This study received no funding. Keywords Extended-spectrum β-lactamase, Enterobacteriaceae, vaginal colonization, antibiotics use, cerclage, neonatal sepsis

The objective of this paper is to develop a modified strain gradient beam constraint model (MSGBCM) to improve modeling accuracy of small-scale compliant mechanisms. First, a simple nano/micro flexure beam under the effect of end loads is considered. The virtual work principle is employed to formulate the load-displacement behavior of the system based on the modified strain gradient theory. It is observed that as the size of the structure becomes smaller, the elements of the elastic stiffness and load stiffening matrices severely deviate from their corresponded values in the beam constraint model (BCM). Then, a closed-form expression is proposed for the nonlinear strain energy of the nano/micro flexure beams in terms of their tip displacements. This energy expression is then utilized to model load-displacement relationship of micron/submicron size parallelogram (P) flexures. Moreover, analytical formulas are derived for the axial, transverse and rotational stiffnesses of P-flexures. The most important observation is that the axial stiffness loss of small-scale P-flexures resulted from the movement of the stage in the transverse direction, may be seriously overestimated by the BCM. The MSGBCM developed in this paper can be easily extended for investigating static and dynamic behavior of more complex micron and submicron size flexure units.

1. The foraging and nesting performance of bees can provide important information on bee health and is of interest for risk and impact assessment of environmental stressors. While radio-frequency identification (RFID) technology is an efficient tool increasingly used for the collection of behavioral data in social bee species such as honey bees, behavioral studies on solitary bees still largely depend on direct observations, which is very time-consuming. 2. Here, we present a novel automated methodological approach of individually and simultaneously tracking and analyzing foraging and nesting behavior of numerous cavity-nesting solitary bees. The approach consists of monitoring nesting units by video recording and automated analysis of videos by a machine learning based software. This Bee Tracker software consists of four trained deep learning networks to detect bees that enter or leave their nest and to recognize individual IDs on the bees’ thorax as well as the IDs of their nests according to their positions in the nesting unit. 3. The software is able to identify each nest of each individual nesting bee, which permits to measure individual-based measures of reproductive success. Moreover, the software quantifies the number of cavities a female enters until it finds its nest as a proxy of nest recognition, and it provides information on the number and duration of foraging trips. By training the software on 8 videos recording 24 nesting females per video, the software achieved a precision of 96% correct measurements of these parameters. 4. The software could be adapted to various experimental setups by training it to an according set of videos. The presented method allows to efficiently collect large amounts of data on cavity-nesting solitary bee species and represents a promising new tool for the monitoring and assessment of behavior and reproductive success under laboratory, semi-field and field conditions.