A multifaceted suite of metrics for comparative myoelectric prosthesis controller research.

Upper limb robotic (myoelectric) prostheses are technologically advanced, but challenging to use. In response, substantial research is being done to develop person-specific prosthesis controllers that can predict a user's intended movements. Most studies that test and compare new controllers rely on simple assessment measures such as task scores (e.g., number of objects moved across a barrier) or duration-based measures (e.g., overall task completion time). These assessment measures, however, fail to capture valuable details about: the quality of device arm movements; whether these movements match users' intentions; the timing of specific wrist and hand control functions; and users' opinions regarding overall device reliability and controller training requirements. In this work, we present a comprehensive and novel suite of myoelectric prosthesis control evaluation metrics that better facilitates analysis of device movement details-spanning measures of task performance, control characteristics, and user experience. As a case example of their use and research viability, we applied these metrics in real-time control experimentation. Here, eight participants without upper limb impairment compared device control offered by a deep learning-based controller (recurrent convolutional neural network-based classification with transfer learning, or RCNN-TL) to that of a commonly used controller (linear discriminant analysis, or LDA). The participants wore a simulated prosthesis and performed complex functional tasks across multiple limb positions. Analysis resulting from our suite of metrics identified 16 instances of a user-facing problem known as the "limb position effect". We determined that RCNN-TL performed the same as or significantly better than LDA in four such problem instances. We also confirmed that transfer learning can minimize user training burden. Overall, this study contributes a multifaceted new suite of control evaluation metrics, along with a guide to their application, for use in research and testing of myoelectric controllers today, and potentially for use in broader rehabilitation technologies of the future.

A Cluster Analysis of Neuropsychological Impairment in Borderline Personality Disorder: Identifying a Neurocognitive Subtype Linked to Attention Deficit Hyperactivity Disorder.

INTRODUCTION: Cognitive impairment associated with borderline personality disorder (BPD) has been consistently demonstrated. However, a specific neuropsychological profile has not yet been established for this disorder, maybe due to the heterogeneity of BPD. The aim of this work is the search for distinct neuropsychological subtypes among patients with BPD and for the association of neuropsychological subgroups with specific clinical characteristics. METHODOLOGY: One hundred fifteen patients with BPD diagnosis received an extensive neuropsychological evaluation assessing attentional, memory and executive functions indexes. For subtyping strategies, a cluster analysis of neuropsychological BPD distribution was performed. Central clinical dimensions of BPD were measured and analysed in relation with the obtained neuropsychological clusters. RESULTS: Two clusters were found: Cluster 1 showed a significantly lower score on the working memory index, and Cluster 2 had significantly worse overall executive performance, response inhibition and planning abilities. Patients in the neurocognitive Cluster 2 showed significantly higher clinical deficits of attention as measured with subscales of the CAARS attention deficit hyperactivity disorder (ADHD) index (F = 2.549, p < 0.005, d = 11.49). CONCLUSIONS: Two neuropsychological clusters of patients were found in the BPD sample: Cluster 1 patients showed greater impairment in working memory, while Cluster 2 patients had greater deficits of executive functioning, particularly for response inhibition and planning. In addition, BPD patients with greater executive deficits presented greater levels of ADHD clinical features. These findings might also facilitate earlier diagnosis of severe BPD patient profiles and to establish more personalized treatment based on neurocognitive stimulation.

Inertia suppresses signatures of activity of active Brownian particles in a harmonic potential.

A harmonically trapped active Brownian particle exhibits two types of positional distributions-one has a single peak and the other has a single well-that signify steady-state dynamics with low and high activity, respectively. Adding inertia to the translational motion preserves this strict classification of either single-peak or single-well densities but shifts the dividing boundary between the states in the parameter space. We characterize this shift for the dynamics in one spatial dimension using the static Fokker-Planck equation for the full joint distribution of the state space. We derive local results analytically with a perturbation method for a small rotational velocity and then extend them globally with a numerical approach.

Diagnostic accuracy of ePOS score in predicting DNR labeling after ICU admission: A prospective observational study (ePOS-DNR).

Background: Resuscitation can sometimes be futile and making a do-not-resuscitate (DNR) decision is in the best interest of the patient. The electronic poor outcome screening (ePOS) score was developed to predict 6-month poor outcomes of critically ill patients. We explored the diagnostic accuracy of the ePOS score in predicting DNR decisions in the intensive care unit (ICU). Methods: This study was conducted at the ICU of a tertiary referral hospital in Saudi Arabia between March and May 2023. Prospectively, we calculated ePOS scores for all eligible consecutive admissions after 48 h in the ICU and recorded the DNR orders. The ability of the score to predict DNR was explored using logistic regression. Youden's ideal cut-off value was calculated using the DeLong method, and different diagnostic accuracy measures were generated with corresponding 95 % confidence intervals (CIs). Results: We enrolled 857 patients, 125 received a DNR order and 732 did not. The average ePOS score of DNR and non-DNR patients was 28.2±10.7 and 15.2±9.7, respectively. ePOS score, as a predictor of DNR order, had an area under receiver operator characteristic (AUROC) curve of 81.8 % (95% CI: 79.0 to 84.3, P <0.001). Youden's ideal cut-off value >17 was associated with a sensitivity of 87.2 (95% CI: 80.0 to 92.5, P <0.001), specificity of 63.9 (95% CI: 60.3 to 67.4, P <0.001), positive predictive value of 29.2 (95% CI: 24.6 to 33.8, P <0.001), negative predictive value of 96.7 (95% CI: 95.1 to 98.3, P <0.001), and diagnostic odds ratio 12.1 (95% CI: 7.0 to 20.8, P <0.001). Conclusions: In this study, the ePOS score performed well as a diagnostic test for patients who will be labeled as DNR during their ICU stay. A cut-off score >17 may help guide clinical decisions to withhold or commence resuscitative measures.

Study of High-Transverse-Momentum Higgs Boson Production in Association with a Vector Boson in the qqbb Final State with the ATLAS Detector.

This Letter presents the first study of Higgs boson production in association with a vector boson (V=W or Z) in the fully hadronic qqbb final state using data recorded by the ATLAS detector at the LHC in proton-proton collisions at sqrt[s]=13 TeV and corresponding to an integrated luminosity of 137 fb^{-1}. The vector bosons and Higgs bosons are each reconstructed as large-radius jets and tagged using jet substructure techniques. Dedicated tagging algorithms exploiting b-tagging properties are used to identify jets consistent with Higgs bosons decaying into bb[over ¯]. Dominant backgrounds from multijet production are determined directly from the data, and a likelihood fit to the jet mass distribution of Higgs boson candidates is used to extract the number of signal events. The VH production cross section is measured inclusively and differentially in several ranges of Higgs boson transverse momentum: 250-450, 450-650, and greater than 650 GeV. The inclusive signal yield relative to the standard model expectation is observed to be µ=1.4_{-0.9}^{+1.0} and the corresponding cross section is 3.1±1.3(stat)_{-1.4}^{+1.8}(syst) pb.

Efficacy and safety of aldafermin in non-alcoholic steatohepatitis: A systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Non-alcoholic steatohepatitis (NASH) is an advanced subtype of non-alcoholic fatty liver disease (NAFLD). NASH prevalence is increasing exponentially and carries a high risk for disease progression, cirrhosis, and liver-related mortality. Aldafermin, a fibroblast growth factor 19 (FGF19) analog, is one of the evolving therapeutic agents with the potential to regulate multiple pathways involved in the pathogenesis of NASH. We aimed to investigate the efficacy and safety of aldafermin in patients with NASH. METHODS: PubMed, Scopus, Cochrane Library, and Web of Science were searched till November 2023 to identify eligible randomized controlled trials (RCTs). Continuous data were pooled as mean difference (MD), while dichotomous data were pooled as risk ratios (RR) with a 95 % confidence interval. A subgroup meta-analysis was conducted to evaluate the efficacy of the two doses (1 mg and 3 mg) of aldafermin. RESULTS: Four RCTs with a total of 491 patients were included. Aldafermin showed a dose-dependent improvement in the ≥30 % reduction in the liver fat content (RR: 2.16, 95 % CI [1.41 to 3.32]) and (RR: 5.00, 95 % CI [1.34 to 18.64]), alanine aminotransferase levels (MD: -19.79, 95 % CI [-30.28 to -9.3]) and (MD: -21.91, 95 % CI [-29.62 to -14.21]), aspartate aminotransferase levels (MD: -11.79, 95 % CI [-18.06 to -5.51]) and (MD: -13.9, 95 % CI [-18.59 to -9.21]), and enhanced liver fibrosis score (ELF) (MD: -0.13, 95 % CI [-0.29 to 0.02]) and (MD: -0.33, 95 % CI [-0.50 to -0.17]), in the 1 mg and 3 mg subgroups respectively. No significant differences were detected in the aldafermin group regarding histologic endpoints, lipid profile, metabolic parameters, and overall adverse effects, except for the increased occurrence of diarrhea in the aldafermin 3 mg subgroup. CONCLUSION: Aldafermin is a promising well-tolerated therapeutic agent for NASH with evidence supporting its ability to reduce liver fat content, fibrosis serum biomarkers, and liver enzymes. However, its effectiveness in improving histologic fibrosis, while showing numerical trends, still lacks statistical significance. Larger and longer NASH trials are warranted to enhance the robustness of the evidence.

Association between frailty, long-term mortality and functional outcomes for older adults undergoing emergency laparotomy.

BACKGROUND: An increasing number of older patients are undergoing emergency laparotomy (EL). Frailty is thought to contribute to adverse outcomes in this group. The best method to assess frailty and impacts on long-term mortality and other important functional outcomes for older EL patients have not been fully explored. METHODS: A prospective multicenter study of older EL patients was conducted across four hospital sites in New Zealand from August 2017 to September 2022. The Clinical Frailty Scale (CFS) was used to measure frailty-defined as a CFS of ≥5. Primary outcomes were 30-day and one-year mortality. Secondary outcomes were postoperative morbidity, admission for rehabilitation, and increased care level on discharge. A multivariate logistic regression analysis was conducted, adjusting for age, sex, and ethnicity. RESULTS: A total of 629 participants were included. Frailty prevalence was 14.6%. Frail participants demonstrated higher 30-day and 1-year mortality-20.7% and 39.1%. Following adjustment, frailty was directly associated with a significantly increased risk of short- and long-term mortality (30-day aRR 2.6, 95% CI 1.5, 4.3, p = <0.001, 1-year aRR 2.0, 95% CI 1.5, 2.8, p < 0.001). Frailty was correlated with a 2-fold increased risk of admission for rehabilitation and propensity of being discharged to an increased level of care, complications, and readmission within 30 days. CONCLUSION: Frailty was associated with increased risk of postoperative mortality up to 1-year and other functional outcomes for older patients undergoing EL. Identification of frailty in older EL patients aids in patient-centered decision-making, which may lead to improvement in outcomes.

What is the impact of Kinesio taping on anterior cruciate ligament reconstruction: a systematic review and meta-analysis.

PURPOSE: As a therapeutic intervention for several musculoskeletal illnesses, the benefits and effectiveness of Kinesio taping (KT) are currently unclear. This systematic review and meta-analysis's (MA) goal is to evaluate the effectiveness of KT for anterior cruciate ligament (ACL) reconstruction and its impact on clinical outcomes. METHODS: A comprehensive search of online databases was done to discover relevant studies. Inclusion criteria included controlled or randomized clinical trials that were published in English. Changes in pain, flexion strength, and extension strength were among the outcomes of interest. RevMan 5.4 was used to extract and analyze data. RESULTS: After satisfying the inclusion requirements, five studies were included in the MA. Pooled analysis showed that, in comparison with the intervention group, the control group had a statistically significant improvement in flexion strength (Standardized mean difference (SMD) = 0.44, 95% Confidence interval (CI) [0.01, 0.87], p = 0.04). Extension strength and pain, however, did not significantly differ between the intervention and control groups (SMD = 30, 95% CI [- 0.12, 0.72], p = 0.16), (SMD = 0.26, 95% CI [- 0.14, 0.66], p = 0.20), respectively. CONCLUSIONS: This analysis suggests limited to no benefits of KA post-ACL reconstruction. While the control group surprisingly showed better improvement in flexion strength, no significant differences were found in extension strength and pain. Further rigorous trials are needed to confirm its utility in rehabilitation.

Measurement of the Centrality Dependence of the Dijet Yield in p+Pb Collisions at sqrt[s_{NN}]=8.16 TeV with the ATLAS Detector.

ATLAS measured the centrality dependence of the dijet yield using 165 nb^{-1} of p+Pb data collected at sqrt[s_{NN}]=8.16 TeV in 2016. The event centrality, which reflects the p+Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R_{CP}, is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R_{CP} shows a scaling with the Bjorken x of the parton originating from the proton, x_{p}, while no such trend is observed as a function of x_{Pb}. This analysis provides unique input to understanding the role of small proton spatial configurations in p+Pb collisions by covering parton momentum fractions from the valence region down to x_{p}∼10^{-3} and x_{Pb}∼4×10^{-4}.

Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at sqrt[s]=13 TeV with the ATLAS Detector.

Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140 fb^{-1} of pp collisions at sqrt[s]=13 TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton (e,µ), photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions.

Changes in food preferences and ingestive behaviors after glucagon-like peptide-1 analog treatment: techniques and opportunities.

BACKGROUND: Glucagon-like peptide-1 (GLP-1) analogs are approved for the treatment of obesity in adults and adolescents. Reports have emerged that the weight loss effect of these medications may be related to changes in food preferences and ingestive behaviors following the treatment. Understanding the mechanisms which impact ingestive behavior could expand opportunities to develop more refined and personalized treatment options for obesity. METHODS: Recent studies investigating the relationship between GLP-1 analogs and ingestive behaviors were retrieved from PubMed using the search terms: "obesity," "food preference," "taste," "ingestive behavior," "weight loss medication," "anti-obesity medication," "GLP-1 analog," "tirzepatide," "liraglutide," "semaglutide." Measurement tools were studied to compare variables used to assess food intake behavior. The main outcomes from each study were analyzed to evaluate the current standing and future directions of appetitive, ingestive, and consummatory behaviors and their association with GLP-1 analogs. RESULTS: Thus far, studies have primarily explored the weight loss phase and report decreased short-term appetite and food intake upon treatment. However, research during the weight maintenance phase and objective measurements of food intake are notably sparse. Additionally, verbal reports have been primarily used to examine food intake, which can be susceptible to subjectivity. CONCLUSIONS: Elucidating the relationship between GLP-1 analogs and ingestive behavior could reveal additional parameters which contribute to their anti-obesity effects. To better understand these mechanisms, it is imperative to consider objective measurements of food intake in future studies. Several measurement tools have been adapted to measure variables of food behavior in humans, and each must be carefully considered with their strengths and limitations to develop optimal investigations.

Climate change and geopolitical conflicts: The role of ESG readiness.

This study examines the relationship between climate change vulnerability and geopolitical risk using data on 42 countries from 1995 to 2021. Utilising two distinct indices, the climate vulnerability index (CVI) and the country-specific geopolitical risk (CGPR) indices, we find that countries with high vulnerability to climate change are more likely to experience geopolitical conflicts. Further analysis reveals that country-level overall economic, social, and governance (ESG) readiness significantly mitigates this detrimental effect. This moderation is mainly attributed to the social and governance readiness measures. Additional tests indicate that the mitigating role of ESG is more pronounced for countries with high institutional governance. These results remain resilient through a set of endogeneity tests using matched samples of countries generated through propensity score matching (PSM) estimation. Our findings suggest that addressing climate vulnerability is crucial to promoting global peace and geopolitical stability.

Efficacy and Safety of Lotilaner Ophthalmic Solution 0.25% in the Treatment of Demodex Blepharitis: A Systematic Review and Meta-Analysis.

PURPOSE: To evaluate the safety and efficacy of Lotilaner ophthalmic solution 0.25% in the treatment of demodex blepharitis. METHODS: PubMed, Web of Science, Scopus, and Embase databases were searched. RCTs comparing lotilaner with placebo or any other standard treatments were included. Outcomes of mean collarette grade (MCG), mite density (Md), meaningful collarette reduction (MCR), mite eradication (ME), were pooled as mean difference (MD), and the outcomes of erythema cure (EC), collarette cure (CC) adverse events (AE) as risk ratio (RR) with their 95% confidence interval (CI) between the two groups from baseline to the endpoint. Review Manager (Version 5.4.1) software was used to conduct all statistical analyses. RESULTS: Four RCTs (947 patients) were included in this study. The overall effect favored the lotilaner group in terms of mean collarette grade upper lid (MD -0.99, 95% CI [-1.26, -0.72]), MCG lower lid (MD -0.57, 95% CI [-1.03, -0.11]), Md (MD -1.13, 95% CI [-1.47, -0.79]), MCR (MD 2.07, 95% CI [2.27, 3.21]), ME (MD 3.46, 95% CI [2.96, 4.04]). EC (RR 3.16, 95% CI [2.18 to 4.59]) and CC (RR 4.17, 95% CI [2.97 to 5.85]). No significant difference between the two groups in terms of AE (RR 1.25, 95% CI [0.75 to 2.06]). However, these findings are limited by significant heterogeneity in some of the reported outcomes. CONCLUSIONS: Our findings show that lotilaner might effectively treat Demodex blepharitis. However, further RCTs with larger and more diverse populations are needed to confirm these findings as some outcomes show significant heterogeneity.

Observation of WZγ Production in pp Collisions at sqrt[s]=13 TeV with the ATLAS Detector.

This Letter reports the observation of WZγ production and a measurement of its cross section using 140.1±1.2 fb^{-1} of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. The WZγ production cross section, with both the W and Z bosons decaying leptonically, pp→WZγ→ℓ^{'}^{±}νℓ^{+}ℓ^{-}γ (ℓ^{(^{'})}=e, µ), is measured in a fiducial phase-space region defined such that the leptons and the photon have high transverse momentum and the photon is isolated. The cross section is found to be 2.01±0.30(stat)±0.16(syst) fb. The corresponding standard model predicted cross section calculated at next-to-leading order in perturbative quantum chromodynamics and at leading order in the electroweak coupling constant is 1.50±0.06 fb. The observed significance of the WZγ signal is 6.3σ, compared with an expected significance of 5.0σ.

The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs).

Pediatric tumors of the central nervous system are the most common cause of cancer-related death in children. The five-year survival rate for high-grade gliomas in children is less than 20%. Due to their rarity, the diagnosis of these entities is often delayed, their treatment is mainly based on historic treatment concepts, and clinical trials require multi-institutional collaborations. The MICCAI Brain Tumor Segmentation (BraTS) Challenge is a landmark community benchmark event with a successful history of 12 years of resource creation for the segmentation and analysis of adult glioma. Here we present the CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge, which represents the first BraTS challenge focused on pediatric brain tumors with data acquired across multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. The BraTS-PEDs 2023 challenge focuses on benchmarking the development of volumentric segmentation algorithms for pediatric brain glioma through standardized quantitative performance evaluation metrics utilized across the BraTS 2023 cluster of challenges. Models gaining knowledge from the BraTS-PEDs multi-parametric structural MRI (mpMRI) training data will be evaluated on separate validation and unseen test mpMRI dataof high-grade pediatric glioma. The CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs 2023 challenge brings together clinicians and AI/imaging scientists to lead to faster development of automated segmentation techniques that could benefit clinical trials, and ultimately the care of children with brain tumors.

Assessing the ecological and health risks associated with heavy metal pollution levels in sediments of Big Giftun and Abu Minqar Islands, East Hurghada, Red Sea, Egypt.

This study assessed pollution levels, ecological and health risk, and spatial distribution of eight heavy metals in sediments of Big Giftun and Abu Minqar Islands, Red Sea, Egypt. Iron (Fe) and manganese (Mn) had the highest contents in both island sediments, while cobalt (Co) in Big Giftun and cadmium (Cd) in Abu Mingar had the lowest values. The obtained PCA data exhibited positively significant loadings of Cd, Co, copper (Cu), nickel (Ni), and zinc (Zn) with 51.03 % of data variance in Big Giftun, and lead (Pb), Cu, Mn, Ni, Zn, and Fe (37.7 %) in Abu Minqar sediments. The contamination factor (CF) showed low contamination for all metals, except cadmium; Cd (moderate). The geo-accumulation index (Igeo) values showed uncontaminated (Cd, Co), moderately (Cu), extremely contaminated (Fe, Mn) (Igeo > 5) in Big Giftun, and uncontaminated (Cd), moderately to strongly contaminated (Cu, Ni), and extremely contaminated (Fe, Mn, and Zn) in Abu Minqar sediments. The pollution load index (PLI) values indicated baseline level of contamination (PLI <1), and degree of contamination (DC) indicated low degree of contamination (DC < n) in all sediments. Nemerow pollution index (NPI) showed unpolluted sediments in Abu Minqar (NPI ≤1) and slight pollution (1 < NPI ≤2) in Big Giftun. Cd showed moderate potential ecological risk (40 ≤ Eri < 80) in Big Giftun sediments. Potential ecological risk index (PERI) indicated low risk sediments (PERI <150). Mean effects range median quotient (MERMQ) indicated low-priority risk of toxicity (MERMQ ≤0.1), and toxic risk index (TRI) showed no toxic risk in all sediments (TRI <5). The modified hazard quotient (mHQ) indicated very low severity of contamination (mHQ <0.5). The hazard quotient (HQ) levels of all metals were below the safe value (HQ <1). The hazard index (HI) levels indicated that no chronic risks occur (HI <1). The total cancer risk (TCR) for all metals were below the safe level (1 × 10-4) of the United States Environmental Protection Agency (U.S. EPA) guidelines.

Characterizing Air Medical Transport Experiences in Emergency Medicine Residency Training Programs.

OBJECTIVE: Air medical transportation (AMT) of patients plays a critical role in the prehospital care of the ill patient. Despite its importance, there is no requirement in emergency medicine training programs to have direct experience or education on the topic, and data detailing current AMT experiences across programs are limited. METHODS: A survey detailing program characteristics, AMT experience characteristics, and curriculum factors relating to AMT experience was sent to all 275 credentialed emergency medicine residency training programs in the United States. Our outcomes were to describe the characteristics of AMT and non-AMT programs (proportions) and to evaluate associations (odds ratios with 95% confidence intervals) between program characteristics and 1) AMT experience opportunity and 2) level of resident participation among AMT programs. RESULTS: Two hundred (73%) programs responded, with 135 of 200 (68%) offering some type of AMT experience. The majority of programs offering AMT were 3 years (113 [84%]), university based (63 [47%]), and located in small urban areas (57 [42%]). When AMT was offered, most programs reported that the overall resident participation was low (≤ 20%). Programs that did not offer shift reduction or additional pay for participation in AMT were significantly more likely to have low participation than those with incentives (odds ratio = 4.8; 95% confidence interval, 1.8-15.3). Around one third of AMT experiences allowed for direct patient care. Less than half of the responding programs reported a dedicated AMT curriculum. CONCLUSION: The majority of emergency medicine residency training programs offer an AMT experience, but this experience is highly variable, and overall participation by residents is low. Given the importance of AMT in the care of emergency patients, standardization and increased access to AMT experience and education should be considered by emergency medicine training programs moving forward.

A novel weighted family of probability distributions with applications to world natural gas, oil, and gold reserves.

Recent innovations have focused on the creation of new families that extend well-known distributions while providing a huge amount of practical flexibility for data modeling. Weighted distributions offer an effective approach for addressing model building and data interpretation problems. The main objective of this work is to provide a novel family based on a weighted generator called the length-biased truncated Lomax-generated (LBTLo-G) family. Discussions are held about the characteristics of the LBTLo-G family, including expressions for the probability density function, moments, and incomplete moments. In addition, different measures of uncertainty are determined. We provide four new sub-distributions and investigated their functionalities. Subsequently, a statistical analysis is given. The LBTLo-G family's parameter estimation is carried out using the maximum likelihood technique on the basis of full and censored samples. Simulation research is conducted to determine the parameters of the LBTLo Weibull (LBTLoW) distribution. Four genuine data sets are considered to illustrate the fitting behavior of the LBTLoW distribution. In each case, the application outcomes demonstrate that the LBTLoW distribution can, in fact, fit the data more accurately than other rival distributions.

A Case Series in Position-Aware Myoelectric Prosthesis Control Using Recurrent Convolutional Neural Network Classification with Transfer Learning.

Position-aware myoelectric prosthesis controllers require long, data-intensive training routines. Transfer Learning (TL) might reduce training burden. A TL model can be pre-trained using forearm muscle signal data from many individuals to become the starting point for a new user. A recurrent convolutional neural network (RCNN)-based classifier has already been shown to benefit from TL in offline analysis (95% accuracy). The present real-time study tested whether an RCNN-based classification controller with TL (RCNN-TL) could reduce training burden, offer improved device control (per functional task performance metrics), and mitigate what is known as the "limb position effect". 27 participants without amputation were recruited. 19 participants performed wrist/hand movements across multiple limb positions, with resulting forearm muscle signal data used to pre-train RCNN-TL. 8 other participants donned a simulated prosthesis, retrained (calibrated) and tested RCNN-TL, plus trained and tested a conventional linear discriminant analysis classification controller (LDA-Baseline). Results confirmed that TL reduces user training burden. RCNN-TL yielded improved task performance durations over LDA-Baseline (in specific Grasp and Release phases), yet other metrics worsened. Overall, this work contributes training condition factors necessary for TL success, identifies metrics needed for comprehensive control analysis, and contributes insights towards improved position-aware control.

Practical prototype for energy management system in smart microgrid considering uncertainties and energy theft.

The conventional electrical grid faces significant issues, which this paper aims to address one of most of them using a proposed prototype of a smart microgrid energy management system. In addition to relying too heavily on fossil fuels, electricity theft is another great issue. The proposed energy management system can simultaneously detect electricity theft and implement demand response tactics by employing time-of-use pricing principles and comparing real electricity consumption with grid data. The system uses the Al-Biruni earth radius (BER) optimization algorithm to make smart choices about how to distribute the load, intending to reduce energy consumption and costs without sacrificing comfort. As a bonus, it considers limitations imposed by battery charging/discharging and decentralized power generation. Incorporating sensors and SCADA-based monitoring, the system provides accurate measurement and management of energy usage through load monitoring and control. An intuitive mobile app also helps consumers connect, allowing for more active participation and better control over energy use. Extensive field testing of the prototype shows that by moving loads from peak period to another off-peak period, electricity expenditures can be reduced by up to 48.45%. The energy theft value was calculated to be 1199 W, proving that the system's theft detection model was effective.