Absolute Loss Research Articles

Design and Experiment of Plate Taking Control System of Edible Sunflower (Edulis helianthus catino L.) Harvester

This study aims at the problems of high labor intensity, high cost and high loss rate of mechanical picking of seeds, low mechanization level and difficulty to guarantee the quality of picking plates in the process of picking edible sunflower. Based on the principle of manual plate taking, a plate taking control system for a sunflower harvesting table was designed. The principle of taking the plate of the edible sunflower harvesting table was analyzed. According to the actual operation requirements, the overall scheme of the sunflower plate control system is determined, and the control strategy of imitating artificial low-loss harvesting is designed. To reduce the grain loss in the process of taking the plate and improve the control accuracy of the system on the movement speed and displacement of the key components in the process of taking the plate, a trapezoidal acceleration and deceleration control algorithm is designed as the control algorithm of taking the plate. The working performance of the plate control system was verified with the absolute error, relative error and total loss rate of the harvest as objectives. Bench and field verification experiments were both carried out. The bench experiment showed that the speed error of the plate parts was not more than 0.028 m/s. In the bench experiments of the device, the maximum positioning error was 1.25 mm, the average relative error was only 0.94% and the grain loss rate was not more than 2.26%. Its result showed that the system algorithm was reliable, the positioning accuracy was high and the plate taking operation can be completed well. The field verification experiment showed that the forward speed of the unit was in the range of 0.4~0.8 m/s, and the total loss rate of harvest was less than 5%. When the forward speed is 0.6 m/s, the minimum harvest loss rate is 2.32%, which indicated the control system meets the requirements of sunflower harvesting operation.

Weight loss in adult male Wistar rats by Roux-en-Y gastric bypass is primarily explained by caloric intake reduction and presurgery body weight.

Diets varying in macronutrient composition, energy density, and/or palatability may cause differences in outcome of bariatric surgery. In the present study, rats feeding a healthy low-fat (LF) diet or an obesogenic high-fat/sucrose diet (HF/S) were either subjected to Roux-en-Y gastric bypass surgery (RYGB) or sham surgery, and weight loss trajectories and various energy balance parameters were assessed. Before RYGB, rats eating an HF/S (n = 14) diet increased body weight relative to rats eating an LF diet (n = 20; P < 0.01). After RYGB, absolute weight loss was larger in HF/S (n = 6) relative to LF feeding (n = 6) rats, and this was associated with reduced cumulative energy intake (EI; P < 0.05) and increased locomotor activity (LA; P < 0.05-0.001), finally leading to similar levels of reduced body fat content in HF/S and LF rats 3 wk after surgery. Regression analysis revealed that variation in RYGB-induced body weight loss was best explained by models including 1) postoperative cumulative EI and preoperative body weight (R2 = 0.87) and 2) postoperative cumulative EI and diet (R2 = 0.79), each without significant contribution of LA. Particularly rats on the LF diet became transiently more hypothermic and circadianally arrhythmic following RYGB (i.e., indicators of surgery-associated malaise) than HF/S feeding rats. Our data suggest that relative to feeding an LF diet, continued feeding an HF/S diet does not negatively impact recovery from RYGB surgery, yet it promotes RYGB-induced weight loss. The RYGB-induced weight loss is primarily explained by reduced cumulative EI and higher preoperative body weight, leading to comparably low levels of body fat content in HF/S and LF feeding rats.NEW & NOTEWORTHY Relative to feeding an LF diet, continued feeding an HF/S diet does not negatively impact recovery from RYGB surgery in rats. Relative to feeding an LF diet, continued feeding an HF/S diet promotes RYGB-induced weight loss. The RYGB-induced weight loss is primarily explained by reduced cumulative EI and higher preoperative body weight, leading to comparably low levels of body fat content in HF/S and LF feeding rats.

Optimization and validation of the DESIGNER preprocessing pipeline for clinical diffusion MRI in white matter aging

Abstract Various diffusion MRI (dMRI) preprocessing pipelines are currently available to yield more accurate diffusion parameters. Here, we evaluated accuracy and robustness of the optimized Diffusion parameter EStImation with Gibbs and NoisE Removal (DESIGNER) pipeline in a large clinical dMRI dataset and using ground-truth phantoms. DESIGNER, a preprocessing pipeline targeting various imaging artifacts in diffusion MRI data, has been modified to improve denoising and target Gibbs ringing for partial Fourier acquisitions. We compared the revised DESIGNER (Dv2) (including denoising, Gibbs removal, correction for motion, echo planar imaging (EPI) distortion, and eddy currents) against the original DESIGNER (Dv1) pipeline, minimal preprocessing (including correction for motion, EPI distortion, and eddy currents only), and no preprocessing on a large clinical dMRI dataset of 524 control subjects with ages between 25 and 75 years old. We evaluated the effect of specific processing steps on age correlations in white matter with diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) metrics. We also evaluated the added effect of minimal Gaussian smoothing to deal with noise and to reduce outliers in parameter maps compared to DESIGNER-v2’s noise removal method. Moreover, Dv2’s updated noise and Gibbs removal methods were assessed using a ground truth dMRI phantom to evaluate accuracy. Results show age correlations of DTI and DKI metrics in white matter were affected by the preprocessing pipeline, causing systematic differences in absolute parameter values and loss or gain of statistical significance. Both in clinical dMRI and ground-truth phantoms, Dv2 pipeline resulted in the smallest number of outlier voxels and improved accuracy in DTI and DKI metrics as noise was reduced and Gibbs removal was improved. Thus, DESIGNER-v2 provides more accurate and robust DTI and DKI parameter maps by targeting common artifacts present in dMRI data acquired in clinical settings, as compared to no preprocessing or minimal preprocessing.

Design and validation of novel maize grain cleaning loss detection system based on classification models of particle time-domain signals

Quantitative evaluation of grain cleaning loss is a central concern in maize intelligent direct harvesting. This study integrates particle time-domain signals with machine learning models to develop a novel grain cleaning loss detection system and create modular embedded companion software. Specifically, collisional time-domain signals of grains and impurities with varying mass gradients are captured, and abnormal data are eliminated utilizing the Mahalanobis Distance (MD) algorithm. Signal classification models incorporating diverse preprocessing methods are trained using Naive Bayes (NB) and Support Vector Machine (SVM) algorithms. Model performance is evaluated through internal leave-one-out-cross-validation (LOOCV) and external validation sets. The best classification model is integrated into the grain loss detection software, and bench tests verify real-time cleaning loss rates for detection systems. Results demonstrate that the SVM model with Savitzky-Golay (S-G) smoothing + Second-Order Derivative (SOD) preprocessing achieves the highest predictive accuracy, with 97.44 % and 96.15 % in training and validation sets, respectively. When the feeding rate of maize mixtures is 5 kg/s, absolute grain loss rates for three measurements are 1.62 %, 1.72 % and 1.86 %, respectively. Compared to traditional loss detection systems with multifunctional circuits, the novel loss detection system enhances the average accuracy of grain loss rate by 6.54, 6.82 and 8.93 percentage points. Hence, the proposed method and apparatus can be applied to detect grain cleaning loss quantitatively.

O255: Is a low calorie "liver shrinking" diet predictive of long term weight loss and metabolic improvement after sleeve gastrectomy?

Abstract Introduction Limited evidence exists regarding pre-operative “liver shrinking” diet, but a two-week period of low calorie diet (LCD) is mandated before bariatric surgery, with weight outcomes rarely measured. Longer periods of LCD can ameliorate obesity, diabetes and metabolic-associated-fatty-liver disease (MAFLD). Primary aim to determine if response to LCD is predictive of long-term weight loss. Secondary aim to determine if alteration in liver function, and MAFLD, correlate with weight change after diet/ in follow up. Methodology Patients undergoing sleeve gastrectomy recruited and weight, blood plasma and 16S rRNA faecal microbiome profile recorded at baseline, following two-week LCD and at six-months, with liver biopsy at surgery (6). Results First nine patients had median baseline BMI 47.3kg/m2, and 34.7 kg/m2 at 6-months (-12.3kg/m2). Median excess weight loss was 8.6% (6.35kg) after LCD and 47.57% (34.65kg) at 6-months. Spearman’s Rank Correlation was weakly positive (0.5) for absolute weight loss between LCD and follow up, and was 0.25 using excess weight loss (non-significant). Change in liver function and MAFLD grade did not correlate with weight loss following LCD and at 6-months. Conclusions Weight loss response to LCD correlated poorly with long-term weight loss (analysing by absolute/ excess weight). Liver health and MAFLD did not predict 6-month weight loss. A dramatic response to LCD may not manifest in longer term metabolic improvement after surgery. We will also report on faecal microbiome; it appears more complex mechanisms underpin weight change and response to dietary manipulation in the surgical cohort than can be extrapolated from population studies.

Noise aware content-noise complementary GAN with local and global discrimination for low-dose CT denoising

In response to rising concerns over radiation exposure in computed tomography (CT) imaging, effective denoising methods for low-dose CT (LDCT) images are crucial. In recent years, the use of deep learning techniques especially generative adversarial networks (GANs) significantly enhanced the efficiency of LDCT denoising methods, surpassing traditional methods. However, GAN-based denoising methods often face challenges in preserving structural consistency and fine details. This study introduces a novel GAN framework with three accretions to enhance the effectiveness of LDCT denoising. Firstly, our generator is designed to leverage a complementary learning scheme between image noise and image content via two distinct paths. One path focuses on exploring the anatomical information of the image, while the second path is dedicated to learning the noise pattern. This complementary learning scheme provides stable noise cancellation while preserving the maximum structural information of the image. Subsequently, we propose a novel noise-conscious mean absolute error loss to address the challenge posed by the non-stationary characteristic of CT noise. In contrast to conventional MAE loss, this loss attentively prioritizes the different parts of the image based on the local distribution of noise in that region. We also incorporate a gradient-domain loss into the loss function, which inspires the generator to preserve precise image details through explicit guidance. Finally, this study adopted a U-Net-based design for the discriminator to better regularize the model by discriminating between the clean image and the denoised image at both global and local levels. The merit of this discriminator is that it can better adapt to the non-stationary environment of GAN training and guide the generator to produce denoised images that are locally and globally consistent. Our thorough experiments using abdominal CT and lung CT datasets demonstrate the superior performance of our approach compared to state-of-the-art methods.

Cost-effectiveness of teduglutide in adult patients with short bowel syndrome – a European socioeconomic perspective

BackgroundShort bowel syndrome with intestinal failure (SBS-IF) is a rare but devastating medical condition. An absolute loss of bowel length forces the patients into parenteral support dependency and a variety of medical sequelae, resulting in increased morbidity and mortality. Interdisciplinary treatment may include therapy with the effective but expensive intestinotrophic peptide teduglutide. ObjectivesA time-discrete Markov model was developed to simulate the treatment effect [lifetime costs, quality-adjusted life years (QALYs), and life years (LYs)] of teduglutide plus best supportive care compared with best supportive care alone in patients with SBS-IF. MethodsThe health status of the model was structured around the number of days on PS. Clinical data from 3 data sets were used: 1) an Austrian observational study (base case), 2) pooled observational cohort studies, and 3) a prospective study of teduglutide effectiveness in parenteral nutrition-dependent short bowel syndrome subjects. Direct and indirect costs were derived from published sources. QALYs, LYs, and costs were discounted (3% per annum). ResultsUnder the base case assumption, teduglutide is associated with costs of 2,296,311 € per patient and 10.78 QALYs (13.74 LYs) over a lifetime horizon. No teduglutide is associated with 1,236,816 € and 2.24 QALYs (8.57 LYs). The incremental cost-utility ratio (ICUR) amounts to 123,945 €. In case of the pooled clinical data set, the ICUR increases to 184,961 €. If clinical data based on the study of teduglutide effectiveness in parenteral nutrition-dependent short bowel syndrome subjects were used, the ICUR increased to 235,612 €. ConclusionsTeduglutide in treating patients with SBS-IF meets the traditional cost-effectiveness criteria from a European societal perspective. Nevertheless, the varying concentrations of teduglutide efficacy leave a degree of uncertainty in the calculations.

Towards liquid EPR dosimetry using nitroxides in aqueous solution.

Objective. Water-equivalent dosimeters are desirable for dosimetry in radiotherapy. The present work investigates basic characteristics of novel aqueous detector materials and presents a signal loss approach for electron paramagnetic resonance (EPR) dosimetry.Approach. The proposed principle is based on the radiation dose dependent annihilation of EPR active nitroxides (NO·) in aqueous solutions. Stable nitroxide radicals (3-Maleimido-2,2,5,5-tetramethyl-1-pyrrolidinyloxy (MmP), 3-Carbamoyl-2,2,5,5-tetramethyl-1-pyrrolidinyloxy (CmP)) in aqueous solutions containing dimethyl sulfoxide (DMSO) as an additive were filled in glass capillaries for irradiation and EPR readout. Radiation doses ranging from 1 to 64 Gy were applied with a clinical 6 MV flattening filter free photon beam. EPR readout was then performed with a X-band benchtop spectrometer. The dose response, temporal stability and reproducibility of the samples' EPR signal amplitudes as well as the influence of the nitroxide concentration between 10 and 160μM on the absolute signal loss were investigated using MmP. CmP was used to examine the dependence of the dose response on DMSO concentration between 0 and 10 vol%. An indirect effect model was fitted to the experimental data assuming irradiation induced radical reactions as the underlying mechanism.Main results. For an initial MmP concentration of 20μM, absolute EPR signal loss is linear up to a dose of 16 Gy with a yield G(-NO·) of approximately 0.4μmol J-1. Within five weeks upon sample irradiation to doses between 0 and 32 Gy relative EPR signal fluctuations were on average (126 readouts) below 1% (1σ). For c(MmP) ≥ 20μM, absolute signal loss is only weakly dependent on c(MmP), whereas it increases strongly with increasing c(DMSO) in the range 0-5 vol%. An indirect effect model is applicable to describe the reaction mechanism resulting in the observed dose response curve.Significance. Liquids consisting of nitroxides in aqueous solution and small amounts of DMSO (2 vol%) show promising basic characteristics for application as water-equivalent EPR dosimeter materials in radiotherapy. The EPR signal loss is based on an indirect effect mediated by diffusing radicals originating from the radiolysis of the water/DMSO mixture.

Efficacy and safety of tirzepatide, GLP-1 receptor agonists, and other weight loss drugs in overweight and obesity: a network meta-analysis.

This network meta-analysis evaluates the efficacy and safety of tirzepatide compared to glucagon-like peptide-1 receptor agonists (GLP-1 RA) and other weight loss drugs in the treatment of overweight and obesity. MEDLINE, Embase, and Cochrane CENTRAL were searched for randomized controlled trials on tirzepatide, GLP-1 RA, and weight loss drugs approved by the US Food and Drug Administration. A network meta-analysis was performed, drawing direct and indirect comparisons between treatment groups. Network diagrams and surface under the cumulative ranking curve analysis were performed for primary (≥5%, ≥10%, ≥15%, absolute weight loss) and secondary outcomes and adverse effects. Thirty-one randomized controlled trials, involving more than 35,000 patients, were included in this study. Tirzepatide 15 mg ranked in the top three across weight-related parameters, glycemic profile (glycated hemoglobin), lipid parameters (total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides), and blood pressure. Tirzepatide 15 mg had the highest efficacy compared with placebo for achieving ≥15% weight loss (risk ratio 10.24, 95% CI: 6.42-16.34). As compared to placebo, tirzepatide and GLP-1 RA across all doses had significant increases in gastrointestinal adverse effects. The superiority of tirzepatide and GLP-1 RA in inducing weight loss and their ability to target multiple metabolic parameters render them promising candidates in the treatment of patients with overweight and obesity.

5-year follow-up of the randomised Diabetes Remission Clinical Trial (DiRECT) of continued support for weight loss maintenance in the UK: an extension study

In DiRECT, a randomised controlled effectiveness trial, weight management intervention after 2 years resulted in mean weight loss of 7·6 kg, with 36% of participants in remission of type 2 diabetes. Of 36 in the intervention group who maintained over 10 kg weight loss at 2 years, 29 (81%) were in remission. Continued low-intensity dietary support was then offered up to 5 years from baseline to intervention participants, aiming to maintain weight loss and gain clinical benefits. This extension study was designed to provide observed outcomes at 5 years. The DiRECT trial took place in primary care practices in the UK. Participants were individuals aged 20-65 years who had less than 6 years' duration of type 2 diabetes, a BMI greater than 27 kg/m2, and were not on insulin. The intervention consisted of withdrawal of antidiabetic and antihypertensive drugs, total diet replacement (825-853 kcal per day formula diet for 12-20 weeks), stepped food reintroduction (2-8 weeks), and then structured support for weight-loss maintenance. After sharing the 2-year results with all participants, UK National Health Service data were collected annually until year 5 from remaining intervention participants who received low-intensity dietary support, intervention withdrawals, and the original randomly allocated groups. The primary outcome was remission of type 2 diabetes; having established in the DiRECT trial that sustained weight loss was the dominant driver of remission, this was assumed for the Extension study. The trial is registered with the ISRCTN registry, number 03267836. Between July 25, 2014, and Aug 5, 2016, 149 participants were randomly assigned to the intervention group and 149 were assigned to the control group in the original DiRECT study. After 2 years, all intervention participants still in the trial (101 [68%] of 149) were approached to receive low-intensity support for a further 3 years. 95 (94%) of 101 were able to continue and consented and were allocated to the DiRECT extension group. 54 participants were allocated to the non-extension group, where intervention was withdrawn. At 5 years, DiRECT extension participants (n=85) lost an average of 6·1 kg, with 11 (13%) of 85 in remission. Compared with the non-extension group, DiRECT extension participants had more visits with HbA1c <48 mmol/mol (<6·5%; 36% vs 17%, p=0·0004), without glucose-lowering medication (62% vs 30%, p<0·0001), and in remission (34% vs 12%, p<0·0001). Original control participants (n=149) had mean weight loss 4·6 kg (n=82), and 5 (5%) of 93 were in remission. Compared with control participants, original intervention participants had more visits with weight more than 5% below baseline (61% vs 29%, p<0·0001), HbA1c below 48 mmol/mol (29% vs 15%, p=0·0002), without antidiabetic medication (51% vs 16%, p<0·0001), and in remission (27% vs 4%, p<0·0001). Of those in remission at year 2, 26% remained in remission at 5 years. Serious adverse events in the original intervention group (4·8 events per 100 patient-years) were under half those in the control group (10·2 per 100 patient-years, p=0·0080). The extended DiRECT intervention was associated with greater aggregated and absolute weight loss, and suggested improved health status over 5 years. Diabetes UK.

Personalization of treatment based on obesity phenotypes

Introduction:&#x0D; Obesity is a significant clinical problem worldwide. The disease exhibits remarkable heterogeneity, leading to diverse pathogenesis among individuals. Despite a growing selection of weight-reducing medications and increased awareness of the importance of a healthy lifestyle, the effectiveness of obesity therapy often remains insufficient. This raises the question of whether tailoring obesity pharmacotherapy to specific phenotypes and individual patient characteristics results in improved treatment outcomes.&#x0D; Objective:&#x0D; To review literature on the effectiveness of obesity treatment based on the personalization of pharmacotherapy according to its underlying causes.&#x0D; Current Knowledge:&#x0D; Currently, the early outcome of weight loss is closely linked to the long-term effectiveness of obesity pharmacotherapy. However, due to the diversity of obesity pathogenesis, it is not helpful in selecting therapy at the initiation of treatment. Specific characteristics are sought to indicate the appropriate drug during therapy planning.&#x0D; In a U.S. study (Acosta et al., 2021) results showed that phenotype-guided obesity pharmacotherapy resulted in clinically more significant absolute weight loss than in the non-phenotyped group.&#x0D; Other studies demonstrated that for very rare types of obesity dependent on specific genetic mutations, targeted treatment addressing these defects yielded the best therapeutic outcomes (recombinant human leptin therapy for patients with leptin gene mutation – Farooqi et al., 2002; setmelanotide therapy for individuals with proopiomelanocortin deficiency – Clément et al., 2020).&#x0D; The impact of specific gene variants on therapeutic response should also be considered, leading to variability in treatment effects for different patients using the same drug.&#x0D; Conclusion:&#x0D; The concept of basing therapy on obesity phenotypes may currently serve as a guide for treatment selection, although it still requires confirmation in randomized clinical trials.&#x0D;

A comparison of objective priors for Cronbach’s coefficient alpha using a balanced random effects model

. In this article, the reference and probability matching priors for Cronbach’s alpha will be derived. The performance of these two priors will be compared to that of the well-known Jeffreys prior and a divergence prior. Cronbach’s alpha is a measure used to assess the reliability of a set of test items. A simulation study will be considered to compare the performance of the priors, where the coverage rates, average interval lengths, and standard deviations of the interval lengths will be computed. A second simulation study will be considered where the mean relative error will be compared for the various priors using three different loss functions. The following loss functions will be considered, Squared error loss, Absolute error loss, and Linex loss. An illustrative example will also be considered. Throughout the article, the random effects approach will be used.

Predicting Soil Quality Index with a Deep Regression Approach

ABSTRACT The detection, preservation and enhancement of soil quality is essential for ecosystem managers to offer the appropriate support after discovering factors that are linked to soil’s functional capability. In this study, soil quality indicators were combined to establish a soil quality index (SQI) by conducting an efficiency analysis for using Convolutional Neural Network (CNN), Gradient Boosting Methods (GBM) and Decision Tree (DT) approaches. For this purpose, soil’s intrinsic parameters, namely indicators, are utilized in case of fitting a deeper regression model. The experiments were carried out with analysis results of 545 soil samples obtained from previously studies conducted on different areas such as watershed, delta, pasture and farmland. The performance of each model is validated by the reported data. Compared to gradient boosting models, the proposed CNN model with mean absolute loss function achieves a lower error rate of 2.71 in Mean Absolute Percentage Error (MAPE) and best average correlation coefficient 0.90 in R2, which proves generalizability of CNN based regression. The findings show that CNNs may be utilized as an effective tool as giving a better prediction accuracy level and reliability in terms the establishing correlations and providing a conceptual framework for modeling of soil quality.

Attenuation correction and truncation completion for breast PET/MR imaging using deep learning.

Objective. Simultaneous PET/MR scanners combine the high sensitivity of MR imaging with the functional imaging of PET. However, attenuation correction of breast PET/MR imaging is technically challenging. The purpose of this study is to establish a robust attenuation correction algorithm for breast PET/MR images that relies on deep learning (DL) to recreate the missing portions of the patient's anatomy (truncation completion), as well as to provide bone information for attenuation correction from only the PET data.Approach. Data acquired from 23 female subjects with invasive breast cancer scanned with18F-fluorodeoxyglucose PET/CT and PET/MR localized to the breast region were used for this study. Three DL models, U-Net with mean absolute error loss (DLMAE) model, U-Net with mean squared error loss (DLMSE) model, and U-Net with perceptual loss (DLPerceptual) model, were trained to predict synthetic CT images (sCT) for PET attenuation correction (AC) given non-attenuation corrected (NAC) PETPET/MRimages as inputs. The DL and Dixon-based sCT reconstructed PET images were compared against those reconstructed from CT images by calculating the percent error of the standardized uptake value (SUV) and conducting Wilcoxon signed rank statistical tests.Main results. sCT images from the DLMAEmodel, the DLMSEmodel, and the DLPerceptualmodel were similar in mean absolute error (MAE), peak-signal-to-noise ratio, and normalized cross-correlation. No significant difference in SUV was found between the PET images reconstructed using the DLMSEand DLPerceptualsCTs compared to the reference CT for AC in all tissue regions. All DL methods performed better than the Dixon-based method according to SUV analysis.Significance. A 3D U-Net with MSE or perceptual loss model can be implemented into a reconstruction workflow, and the derived sCT images allow successful truncation completion and attenuation correction for breast PET/MR images.

The Prevalence of Hypohydration in School-Sponsored Athletes Across and Within Practice Sessions

Hydration status monitoring through weight charts can help active individuals maintain optimal fluid balance and prevent health/performance impairments. This study aimed to determine the prevalence of athletes above an acute hypohydration threshold (within practices), a chronic hypohydration threshold (across practices), and the prevalence of athletes below the acute hypohydration threshold and above the chronic hypohydration threshold simultaneously (e.g., undetected chronic hypohydration). Second, involvement of baseline hydration verification (BV; with/without), sex, and competition level (high school, college/university) with acute hypohydration, chronic hypohydration, and undetected chronic hypohydration were also examined. Undetected chronic hypohydration was prevalent across sexes (6.4 ± 16.7% males; 1.4 ± 5.8% females) and competition levels (6.5 ± 16.4% high school; 5.4 ± 15.6% college/university). No significant differences existed across BV status for average acute hypohydration (with BV = 0.8; without BV = 0.8) or chronic hypohydation (with BV = 0.7; without BV = 0.8). All three calculations, absolute body mass loss, acute hypohydration, and chronic hypohydration, should be utilized to determine the prevalence of hypohydration, and they should also be used to assist athletic trainers while making clinical decisions regarding appropriate rehydration interventions.

Gutta-percha dissolving ability of Citrus limetta, essential oils and a customized emulsion: An in vitro study

Aim: This study aims to evaluate the GP dissolving property of ethanolic extract of sweet lime peel (Citrus limetta), peppermint oil, cedarwood oil, and an emulsion (equal volumes of ethanolic extract of sweet lime peel, peppermint, and cedarwood oils) compared to xylene and chloroform (CHCl3). Methods: Equal weight of GP were divided into 7 groups and immersed for 5 min and 10 min in the test and control groups. Distilled water was used as a negative control. Absolute weight loss (WL) was calculated. Results: Data were analyzed using Kruskal–Wallis test followed by Dunn’s pairwise comparison with a significance value of P ≤ 0.05. The median WL of GP in the solvents shows a significant difference at 5 min (P = 0.001) and 10 min (P = 0.000). After 5 min, the order of WL was highest in sweet lime peel extract, CHCl3, and emulsion followed by xylene and peppermint oil. After 10 min, the highest WL was seen in emulsion, CHCl3 followed by sweet lime peel and peppermint oil. Cedarwood oil had no GP solvent effect at both time intervals. Conclusion: Sweet lime peel extract, emulsion, and peppermint oil showed a significant GP dissolving effect at 5 and 10 min and were comparable to CHCl3. Cedarwood oil showed no GP dissolving effect.

Bariatric arterial embolization in patients with body mass index ranging from 25 to 40 kg/m2: A systematic review & meta-analysis.

The present review sought to evaluate by meta-analysis the efficacy of bariatric arterial embolization (BAE) in promoting weight loss in patients with body mass index (BMI) ranging from 25-40 kg/m2. This study was performed and reported according to Preferred Reporting Items for Systematic reviews and Meta-analysis guidelines. A systematic literature search of MEDLINE, Embase Google Scholar, and World Health Organization Library database was done for studies evaluating BAE for promoting weight loss in patients with BMI ranging from 25-40 kg/ m2 published up to March 10, 2021. Primary outcome measure included weight loss after the embolisation procedure. Three single-arm studies comprising of a total of 28 patients (BMI: 25- 40 kg/m2) were found eligible for meta-analysis. All patients underwent embolization with either Embosphere microspheres or PVA particles. The predominant artery embolised was left gastric artery (in all patients). Additional arteries embolised included gastroepiploic artery (8 patients), or accessory left gastric artery (1 patient), or short gastric artery (1 patient). Pooled absolute mean weight loss was 7.854 kg (95% CI: 6.103-9.605). No significant statistical heterogeneity was detected (I2=51.75%, P=0.126) among pooled studies. In conclusion, limited single-arm studies report BAE as an effective, and relatively safe procedure for promoting weight loss in patients with BMI ranging from 25-40 kg/m2, although the number of patients included is very small. Initial results of BAE in promoting weight loss are promising with no major/severe complications reported; however, long term follow-up is required to see the sustainability of the effects.

Safety and Efficacy of 12-Month Intra-gastric Balloon-Series of over 1100 Patients.

Intra-gastric balloons (IGB) are a mainstay of endoscopic treatment of overweight and obesity. In recent years, an IGB which can remain in situ for 12 months has been developed. The current study aimed to analyse the safety and efficacy of this 12-month IGB. Consecutive patients receiving the Orbera 365TM IGB (Apollo Endosurgery, TX, USA) between September 2017 and August 2021 were included in a prospective database. Patients received regular follow-up consultations followed by endoscopic removal at 12 months. Demographic data along with weight loss data were collected. All adverse events were recorded. In total, 1149 patients were included in the study. A majority of the patients were female (87.13%). Median body mass index (BMI) prior to insertion was 36.30 kg/m2 (IQR 32.60-40.00 kg/m2). Median absolute weight loss for all patients was 11.36 kg (IQR 6.70-16.82 kg). There was ongoing sustained weight loss until device removal at week 52. For patients with a weight recording at point of IGB removal, median weight loss was greater (15.88 kg, IQR 10.43-21.72) with percentage total body weight loss of 15.38% (IQR 10.99-21.77) and excess weight loss of 53.99% (IQR 32.44-76.30). Increased patient engagement with post-procedural follow-up was associated with increased weight loss (p<0.001). There were 60 total complications (5.22%). Fifty patients required balloon removal due to intolerance. There were eight cases of balloon rupture. There were only two severe complications (0.17%). The current study has confirmed safety of this IGB at 12 months with adverse events comparable to published literature. Weight loss increased up until the point of removal at 12 months.

Prediction of erosive wear – A novel mathematical model

Several authors in past idealized erodent particles by assuming of spherical shapes. In reality, particles predominantly have irregular and angular shapes. The present study evolved a novel mechanistic mathematical model for prediction of solid particle erosive wear assuming the angular particles of square pyramidal shapes. The proposed model predicts the absolute volume loss as a cumulative contribution of deformation damage and cutting removal. It includes the effect of velocity, impingement angle, mass, abrasiveness factor of striking particles and the properties of target material. It can be effectively used for prediction of erosive wear for jet type of fluid flow.

Association between management practices and estimated mastitis incidence and milk losses on robotic dairy farms.

This study aims to describe the relation between farm-level management factors and estimated farm-level mastitis incidence and milk loss traits (MIMLT) at dairy farms with automated milking systems. In this observational study, 43 commercial dairy farms in Belgium and the Netherlands were included and 148 'management and udder health related variables' were obtained during a farm visit through a farm audit and survey. The MIMLT were estimated from milk yield data. Quarter-level milk yield perturbations that were caused by presumable mastitis cases (PMC) were selected based on quarter-level milk yield and electrical conductivity. On average, 57.6±5.4% of the identified milk yield perturbations complied with our criteria. From these PMC, 3 farm-level MIMLT were calculated over a one-year period around the farm visit date: (1) the 'average number of PMC per cow per year', (2) the 'absolute milk loss per cow per day', calculated as the farm-level sum of all milk losses during PMC in one year, divided by the average number of lactating cows and the number of days, and (3) the 'relative milk loss', calculated as the farm-level sum of milk losses during PMC in one year, divided by the estimated total production in the absence of PMC. The 'average number of PMC per cow per year' was on average 1.81±0.47. The PMC caused an average milk loss of 0.77±0.26kg per lactating cow per day, which corresponded to an average production loss of 2.38±0.82% of the expected production in the absence of PMC. We performed a principal component regression (PCR) analysis to link the 3 MIMLT to the 'management and udder health related variables', whilst reducing the multicollinearity and the number of dimensions. The first principal component was mainly related to 'milking system brand, maintenance and settings'. The second component mainly linked to average productivity and somatic cell counts, whereas the third component mainly contained variables linked with mastitis management, treatment, and biosecurity. The 3 PCR models had R² ranging from 0.46 (for absolute milk loss per cow per day) to 0.57 (for relative milk loss). For all models, the second PC had the largest effect size. This analysis raises awareness of the impact of management factors on a factual basis and provides handles to take management actions to improve udder health.