were used to construct the MIMO antenna system for Wibro service. To obtain high isolation between antenna #2 and antenna #3, a hairpin resonator was added between the two antenna elements. The total size of the proposed multiantenna is 40 mm  7 mm  5 mm. The designed multiantenna has measured peak gains of 3.8 dBi at the WCDMA lower band, 1.4 dBi at the WCDMA higher band, 1.2 dBi for antenna #2, and À0.95 dBi for antenna #3 in the Wibro band. The isolation (S 32 ) in the Wibro band is lower than À17 dB.Although the two MIMO antenna elements have different directivities, their radiation patterns resemble each other. Further research will examine the following: (1) gain enhancement at the WCDMA higher band (Rx band) and the Wibro band and (2) equalization of the performance of Wibro MIMO antenna elements. ABSTRACT: In this article, a novel and compact hairpin bandpass filter (BPF) using defected ground structure (DGS) is discussed. By placing a novel cascaded z-slot DGS at the location of the input and output port, the first spurious passband can be rejected. The elaborate analysis of the z-slot DGS has been given. The equivalent circuit of the z-slot and how the dimension affects the frequency response are presented. In addition, as the DGS is etched on the backside of the substrate, no extra size is added to the final layout. The experimental results demonstrate that this filter has low insertion loss, small size, and with a rejection level of more than 35 dB for the first spurious passband. The measured results of the proposed BPFs are in good agreement with the simulated ones.

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Background: Lactic acidosis is the most common cause of anion gap metabolic acidosis in the intensive care unit (ICU), associated with poor outcomes including mortality. We sought to compare machine learning (ML) approaches versus logistic regression analysis for prediction of mortality in lactic acidosis patients admitted to the ICU. Methods: We used the Medical Information Mart for Intensive Care (MIMIC-III) database to identify ICU adult patients with lactic acidosis (serum lactate ≥4 mmol/L). The outcome of interest was hospital mortality. We developed prediction models using four ML approaches consisting of random forest (RF), decision tree (DT), extreme gradient boosting (XGBoost), artificial neural network (ANN), and statistical modeling with forward stepwise logistic regression using the testing dataset. We then assessed model performance using area under the receiver operating characteristic curve (AUROC), accuracy, precision, error rate, Matthews correlation coefficient (MCC), F1 score, and assessed model calibration using the Brier score, in the independent testing dataset. Results: Of 1919 lactic acidosis ICU patients, 1535 and 384 were included in the training and testing dataset, respectively. Hospital mortality was 30%. RF had the highest AUROC at 0.83, followed by logistic regression 0.81, XGBoost 0.81, ANN 0.79, and DT 0.71. In addition, RF also had the highest accuracy (0.79), MCC (0.45), F1 score (0.56), and lowest error rate (21.4%). The RF model was the most well-calibrated. The Brier score for RF, DT, XGBoost, ANN, and multivariable logistic regression was 0.15, 0.19, 0.18, 0.19, and 0.16, respectively. The RF model outperformed multivariable logistic regression model, SOFA score (AUROC 0.74), SAP II score (AUROC 0.77), and Charlson score (AUROC 0.69). Conclusion: The ML prediction model using RF algorithm provided the highest predictive performance for hospital mortality among ICU patient with lactic acidosis.

Aggression in correctional and psychiatric settings is relatively common and has a negative effect on physical and mental health both among inmates/clients and staff, as well as organizational‐level functioning. The aim of the present study was to critically review the evidence on the effectiveness of nutritional supplements in reducing aggression and violence to contribute to a better understanding of options available for managing aggressive behaviors in adults. The EMBASE, MEDLINE, PsycINFO, Cochrane Library, and PubMed databases were searched for effectiveness studies published in English anytime up until March 2020. Study quality was assessed using the Mixed Methods Appraisal Tool. Altogether, 14 studies met inclusion criteria; 2 investigated micronutrients, 10 examined macronutrients, while further 2 examined a combination of micro and macronutrients. Out of the 14 studies, 5 reported a beneficial effect of nutritional supplementation (omega‐3 fatty acids, vitamins/minerals, S‐adenosyl‐l‐methionine, or tryptophan). Five studies did not report a significant beneficial effect of nutritional supplementation (omega‐3 fatty acids, folic acid, tryptophan, broad range supplement containing vitamins and fatty acids, and fatty acids in augmentation with valproic acid), while four studies reported mixed effects (on l‐tryptophan, broad‐range micronutrient formula, folic acid, and omega‐3 fatty acids). The results overall indicated that research in this area is in its infancy: very few studies examined the same composition of nutritional supplementation and when they did so the results were contradictory. The methodological shortcoming of existing studies and directions for future research are discussed to facilitate high‐quality research in this evolving area of nutritional psychiatry.

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Background: There have been concerns regarding increased perioperative mortality, length of hospital stay, and rates of graft loss in kidney transplant recipients with functional limitations. The application of machine learning consensus clustering approach may provide a novel understanding of unique phenotypes of functionally limited kidney transplant recipients with distinct outcomes in order to identify strategies to improve outcomes. Methods: Consensus cluster analysis was performed based on recipient-, donor-, and transplant-related characteristics in 3205 functionally limited kidney transplant recipients (Karnofsky Performance Scale (KPS) < 40% at transplant) in the OPTN/UNOS database from 2010 to 2019. Each cluster’s key characteristics were identified using the standardized mean difference. Posttransplant outcomes, including death-censored graft failure, patient death, and acute allograft rejection were compared among the clusters Results: Consensus cluster analysis identified two distinct clusters that best represented the clinical characteristics of kidney transplant recipients with limited functional status prior to transplant. Cluster 1 patients were older in age and were more likely to receive deceased donor kidney transplant with a higher number of HLA mismatches. In contrast, cluster 2 patients were younger, had shorter dialysis duration, were more likely to be retransplants, and were more likely to receive living donor kidney transplants from HLA mismatched donors. As such, cluster 2 recipients had a higher PRA, less cold ischemia time, and lower proportion of machine-perfused kidneys. Despite having a low KPS, 5-year patient survival was 79.1 and 83.9% for clusters 1 and 2; 5-year death-censored graft survival was 86.9 and 91.9%. Cluster 1 had lower death-censored graft survival and patient survival but higher acute rejection, compared to cluster 2. Conclusion: Our study used an unsupervised machine learning approach to characterize kidney transplant recipients with limited functional status into two clinically distinct clusters with differing posttransplant outcomes.