The connection between international trade and food systems (un)sustainability is both contentious and critical for policy work supporting progress towards achieving the twin goals of hunger alleviation and dietary health while improving the overall sustainability of development. We characterize the food system using a set of metrics based upon the EAT-Lancet commission dietary guidelines for both over- and under-consumption of different foods to assess country-level dietary health and sustainability in tandem. Using a partial equilibrium model of agricultural production and trade, we then project the functioning of the global agricultural system to 2050 and calculate the metrics for that year. For most regions we find increased overconsumption above the expert-defined healthy and sustainable diet thresholds, with more limited progress towards closing dietary health and sustainability gaps where they currently exist. Trade influences this dynamic into the future under certain socioeconomic conditions, and we find that under a “business as usual” trade environment, future agricultural import profiles continue to be misaligned with dietary health and sustainability outcomes, suggesting the potential for early intervention in trade policy as a means to positively influence food system outcomes.Large-scale and long-period metabolomics study is more susceptible to various sources of systematic errors, resulting in nonreproducibility and poor data quality. A reliable and robust batch correction method removes unwanted systematic variations and improves the statistical power of metabolomics data, which undeniably becomes an important issue for the quality control of metabolomics. This study proposed a novel data normalization and integration method, Norm ISWSVR. It is a two-step approach via combining the best-performance internal standard correction with support vector regression normalization, comprehensively removing the systematic and random errors and matrix effects. This method was investigated in three untargeted lipidomics or metabolomics datasets, and the performance was further evaluated systematically in comparison with that of 11 other normalization methods. As a result, Norm ISWSVR decreased the data’s median cross-validated relative standard deviation (cvRSD), increased the correlation between QCs, improved the classification accuracy of biomarkers, and was well-compatible with quantitative data. More importantly, Norm ISWSVR also allows a low frequency of QCs, which could significantly decrease the burden of a large-scale experiment. Correspondingly, Norm ISWSVR favorably improves the data quality of large-scale metabolomics data.Rice (Oryza sativa L.) is a staple food of Madagascar, where per capita rice consumption is among the highest worldwide. Rice in Madagascar is mainly grown on smallholder farms on soils with low fertility and in the absence of external inputs such as mineral fertilizers. Consequently, rice productivity remains low and the gap between rice production and consumption is widening at the national level. This study evaluates genetic resources imported from the IRRI rice gene bank to identify potential donors and loci associated with low soil fertility tolerance (LFT) that could be utilized in improving rice yield under local cultivation conditions. Accessions were grown on-farm without fertilizer inputs in the central highlands of Madagascar. A Genome-wide association study (GWAS) identified quantitative trait loci (QTL) for total panicle weight per plant, straw weight, total plant biomass, heading date and plant height. We detected loci at locations of known major genes for heading date (hd1) and plant height (sd1), confirming the validity of GWAS procedures. Two QTLs for total panicle weight were detected on chromosomes 5 (qLFT5) and 11 (qLFT11) and superior panicle weight was conferred by minor alleles. Further phenotyping under P and N deficiency suggested qLFT11 to be related to preferential resource allocation to root growth under nutrient deficiency. A donor (IRIS 313-11949) carrying both minor advantageous alleles was identified and crossed to a local variety (X265) lacking these alleles to initiate variety development through a combination of marker-assisted selection with selection on-farm in the target environment rather than on-station as typically practiced.Posttraumatic Stress Disorder (PTSD) is a psychiatric condition affecting nearly a quarter of the United States war veterans who return from war zones. Treatment for PTSD typically consists of a combination of in-session therapy and medication. However; patients often experience their most severe PTSD symptoms outside of therapy sessions. Mobile health applications may address this gap, but their effectiveness is limited by the current gap in continuous monitoring and detection capabilities enabling timely intervention. The goal of this article is to develop a novel method to detect hyperarousal events using physiological and activity-based machine learning algorithms. Physiological data including heart rate and body acceleration as well as self-reported hyperarousal events were collected using a tool developed for commercial off-the-shelf wearable devices from 99 United States veterans diagnosed with PTSD over several days. The data were used to develop four machine learning algorithms Random Forest, Support Vector Machine, Logistic Regression and XGBoost. The XGBoost model had the best performance in detecting onset of PTSD symptoms with over 83% accuracy and an AUC of 0.70. buy RK-33 Post-hoc SHapley Additive exPlanations (SHAP) additive explanation analysis showed that algorithm predictions were correlated with average heart rate, minimum heart rate and average body acceleration. Findings show promise in detecting onset of PTSD symptoms which could be the basis for developing remote and continuous monitoring systems for PTSD. Such systems may address a vital gap in just-in-time interventions for PTSD self-management outside of scheduled clinical appointments.A Pd(II)-catalyzed synthesis of furopyridines has been developed from β-ketodinitriles and alkynes via an unusual N-H/C annulation. The participation of both the nitrile groups and the concurrent construction of furan and pyridine rings through the formation of C-C, C═C, C-O, C-N, and C═N bonds are the important features. The synthetic applicability is further demonstrated through a series of postsynthetic alterations.

To analyze the cause of prolonged recovery from general anesthesia with remimazolam.

We studied 65 patients under general anesthesia with remimazolam. According to time to extubation, patients were divided into short period (SP) (n = 34, < 15 min) and long period (LP) (n = 31, ≥ 15 min) groups. Variables affecting time to extubation such as age, sex, height, body weight, body mass index (BMI), plasma albumin concentration, ASA class, duration of surgery, and total duration of general anesthesia, and total dose of remimazolam were compared between SP and LP groups. At the end of remimazolam infusion and upon extubation, predictive remimazolam concentrations were calculated using pharmacokinetic/pharmacodynamic three compartment modeling.

LP group showed significantly higher BMI, older age, and lower plasma albumin concentration compared with those of SP group. Logistic regression analysis showed that the probability of time to extubation of ≥ 15 min was higher in patients with BMI greater than 22.0 kg/m2 (AUC 0.668, 95% CI 0.533‒0.803), ages older than 79.0 years (AUC 0.662, 95% CI 0.526‒0.798), and plasma albumin concentrations lower than 3.60 g/dl (AUC 0.720, 95% CI 0.593‒0.847). LP group showed significantly lower predicted remimazolam concentration than SP group upon extubation despite no difference in concentration between both groups at the end of infusion. Pharmacological analysis estimates that LP group is more sensitive to remimazolam than SP group through amplified responses.

Lower remimazolam doses should be considered for the overweight patients, elderly, and those with lower plasma albumin concentration.

Lower remimazolam doses should be considered for the overweight patients, elderly, and those with lower plasma albumin concentration.The NBA has undergone formative changes since commissioner David Stern began his tenure. Stern has endeavored to make the NBA a consumer-friendly and marketable league by implementing sanctions on physical violence. This study takes a closer look at Stern’s efforts by examining the interplay between two forms of violence in NBA basketball players on the court “old fashioned” physical violence (PV) and symbolic violence (SV). Of the 117 NBA finals broadcast for twenty years from 1998 to 2018, a stratified random sample (36 games or 30.8%) of the violations and commentators’ comments were coded, providing a wide perspective on forms of violence over time. The findings reveal that although the number of PV incidents decreased, SV increased starting in 2014, to the extent that SV incidents were more frequent than PV. A thematic analysis of the commentators’ remarks associated with these incidents showed that they support and encourage PV, whereas SV tends to be perceived as harmless and therefore permissible to ignore. Unlike PV, SV is not perceived to be as worthy of media coverage. The relative lack of commentator interest is indicative of the lack of “glamour” of SV in the NBA league. It is suggested that since viewers of professional sports often emulate the players, the increase of SV within the NBA is likely to be mirrored in fans in their everyday lives and in amateur basketball players. Although the rise in SV causes fewer physical injuries in professional basketball players, it nevertheless can cause psychological harm.Phytoremediation is a potentially cost-effective and environmentally friendly remediation method for environmental pollution. However, the safe treatment and resource utilization of harvested biomass has become a limitation in practical applications. To address this, a novel manganese-carbon-based single-atom catalyst (SAC) method has been developed based on the pyrolysis of a manganese hyperaccumulator, Phytolacca americana. In this method, manganese atoms are dispersed atomically in the carbon matrix and coordinate with N atoms to form a Mn-N4 structure. The SAC developed exhibited a high photooxidation efficiency and excellent stability during the degradation of a common organic pollutant, rhodamine B. The Mn-N4 site was the active center in the transformation of photoelectrons via the transfer of photoelectrons between adsorbed O2 and Mn to produce reactive oxygen species, identified by in situ X-ray absorption fine structure spectroscopy and density functional theory calculations. This work demonstrates an approach that increases potential utilization of biomass during phytoremediation and provides a promising design strategy to synthesize cost-effective SACs for environmental applications.

Respiratory sounds have been recognized as a possible indicator of behavior and health. Computer analysis of these sounds can indicate characteristic sound changes caused by COVID-19 and can be used for diagnostics of this illness.

The aim of the study is to develop 2 fast, remote computer-assisted diagnostic methods for specific acoustic phenomena associated with COVID-19 based on analysis of respiratory sounds.

Fast Fourier transform (FFT) was applied for computer analysis of respiratory sound recordings produced by hospital doctors near the mouths of 14 patients with COVID-19 (aged 18-80 years) and 17 healthy volunteers (aged 5-48 years). Recordings for 30 patients and 26 healthy persons (aged 11-67 years, 34, 60%, women), who agreed to be tested at home, were made by the individuals themselves using a mobile telephone; the records were passed for analysis using WhatsApp. For hospitalized patients, the illness was diagnosed using a set of medical methods; for outpatients, polymerase chain reaction (PCR) was used.