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Background: Intersegmental coordination between thigh, shank, and foot plays a crucial role in human gait, facilitating stable and efficient human walking. Limb elevation angles during the gait cycle form a planar manifold describes the by the planar covariation law, a recognized fundamental aspect of human locomotion., Research Question: How does the walking speed, age, BMI, and height, affect the size and orientation of the intersegmental coordination manifold and covariation plane?, Methods: This study introduces novel metrics for quantifying intersegmental coordination, including the mean radius of the manifold, rotation of the manifold about the origin, and the orientation of the plane with respect to the coordinate planes. A statistical investigation is conducted on a publicly available human walking dataset for subjects aged 19-67 years, walking at speeds between 0.18 and 2.3 m s -1 to determine correlations of the proposed quantities. We used two sample t-test and ANOVA to find statistical significance of changes in the metrics with respect to gender and walking speed, respectively. Regression analysis was used to establish relationships between the introduced metrics and walking speed., Results: High correlations are observed between walking speed and the computed metrics, highlighting the sensitivity of these metrics to gait characteristics. Conversely, negligible correlations are found for demographic parameters like age, body mass index (BMI), and height. Male and female groups exhibit no practically significant differences in any of the considered metrics. Additionally, metrics tend to increase in magnitude as walking speed increases., Significance: This study contributes numerical metrics to characterize ISC of lower limbs with respect to walking speed along with regression models to estimate these metrics and related kinematic quantities. These findings hold significance for enhancing clinical gait analysis, generating optimal walking trajectories for assistive devices, prosthetics, or rehabilitation, aiming to replicate natural gaits and improve the functionality of biomechanical devices., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Declarations of interest None. Conflict of Interest Statement The authors declare no conflicts of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Intersegmental coordination (ISC) of lower limbs and planar covariation law (PCL) are important phenomena observed in biomechanics of human walking and other activities. Gait perturbations tend to cause deviation from the expected ISC pattern thus violating PCL. We used a data set of seven subjects, who experienced unexpected slips, to investigate and characterize the evolution of ISC during slip recoveries and falls. We have analyzed and presented the development of ISC patterns, encompassing the step preceding the slip initiation and duration of slip until it stops. The results show that the ISC patterns during slip recovery deviate considerably from the normal walking patterns. A newly proposed Euclidian distance-based metric (EDM) was used to quantify the deviation from the normal walking ISC pattern during four slip recoveries and three falls evaluated at gait events such as slip start, foot strike, and peak height of the swing foot. The timing of gait events after slip, pattern of EDM, placement of the feet after slip and temporal patterns of each limb angle have been presented. This initial investigation provides insight into the ISC during slip recovery which highlights the human natural recovery trajectories during such perturbations. The observed patterns of the ISC trajectories during slip can be used for the design of human-inspired controllers for exoskeleton devices that can provide external assistance to human subjects during balance recovery., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Wastewater-based epidemiology has shown to be a promising and innovative approach to measure a wide variety of illicit drugs that are consumed in the communities. In the same way as for illicit drugs, wastewater-based epidemiology is a promising approach to understand the prevalence of viruses in a community-level. The ongoing coronavirus disease 2019 (COVID-19) pandemic created an unprecedented burden on public health and diagnostic laboratories all over the world because of the need for massive laboratory testing. Many studies have shown the applicability of a centralized wastewater-based epidemiology (WBE) approach, where samples are collected at WWTPs. A more recent concept is a decentralized approach for WBE where samples are collected at different points of the sewer system and at polluted water bodies. The second being particularly important in countries where there are insufficient connections from houses to municipal sewage pipelines and thus untreated wastewater is discharged directly in environmental waters. A decentralized approach can be used to focus the value of diagnostic tests in what we call targeted-WBE, by monitoring wastewater in parts of the population where an outbreak is likely to happen, such as student dorms, retirement homes and hospitals. A combination of centralized and decentralized WBE should be considered for an affordable, sustainable, and successful WBE implementation in high-, middle- and low-income countries., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)

Low-friction foot/ground contacts present a particular challenge for stable bipedal walkers. The slippage of the stance foot introduces complexity in robot dynamics and the general locomotion stability results cannot be applied directly. We relax the commonly used assumption of nonslip contact between the walker foot and the ground and examine bipedal dynamics under foot slip. Using a two-mass linear inverted pendulum model, we introduce the concept of balance recoverability and use it to quantify the balanced or fall-prone walking gaits. Balance recoverability also serves as the basis for the design of the balance recovery controller. We design the within- or multi-step recovery controller to assist the walker to avoid fall. The controller performance is validated through simulation results and robustness is demonstrated in the presence of measurement noises as well as variations of foot/ground friction conditions. In addition, the proposed methods and models are used to analyze the data from human walking experiments. The multiple subject experiments validate and illustrate the balance recoverability concept and analyses., (Copyright © 2022 by ASME.)

Improper manual material handling (MMH) techniques are shown to lead to low back pain, the most common work-related musculoskeletal disorder. Due to the complex nature and variability of MMH and obtrusiveness and subjectiveness of existing hazard analysis methods, providing systematic, continuous, and automated risk assessment is challenging. We present a machine learning algorithm to detect and classify MMH tasks using minimally-intrusive instrumented insoles and chest-mounted accelerometers. Six participants performed standing, walking, lifting/lowering, carrying, side-to-side load transferring (i.e., 5.7 kg and 12.5 kg), and pushing/pulling. Lifting and carrying loads as well as hazardous behaviors (i.e., stooping, overextending and jerky lifting) were detected with 85.3%/81.5% average accuracies with/without chest accelerometer. The proposed system allows for continuous exposure assessment during MMH and provides objective data for use with analytical risk assessment models that can be used to increase workplace safety through exposure estimation., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

We present two frameworks for design optimization of a multi-chamber pneumatic-driven soft actuator to optimize its mechanical performance. The design goal is to achieve maximal horizontal motion of the top surface of the actuator with a minimum effect on its vertical motion. The parametric shape and layout of air chambers are optimized individually with the firefly algorithm and a deep reinforcement learning approach using both a model-based formulation and finite element analysis. The presented modeling approach extends the analytical formulations for tapered and thickened cantilever beams connected in a structure with virtual spring elements. The deep reinforcement learning-based approach is combined with both the model- and finite element-based environments to fully explore the design space and for comparison and cross-validation purposes. The two-chamber soft actuator was specifically designed to be integrated as a modular element into a soft robotic pad system used for pressure injury prevention, where local control of planar displacements can be advantageous to mitigate the risk of pressure injuries and blisters by minimizing shear forces at the skin-pad contact. A comparison of the results shows that designs achieved using the deep reinforcement based approach best decouples the horizontal and vertical motions, while producing the necessary displacement for the intended application. The results from optimizations were compared computationally and experimentally to the empirically obtained design in the existing literature to validate the optimized design and methodology., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Raeisinezhad, Pagliocca, Koohbor and Trkov.)

Previous studies on SARS-CoV and MERS-CoV reported the detection of viral RNA in the stool of both symptomatic and asymptomatic individuals. These clinical observations suggest that municipal and hospital wastewater from affected communities may contain SARS-CoV-2 RNA. Recent studies have also reported the presence of SARS-CoV-2 RNA in human feces. Wastewater-based epidemiology (WBE) is a promising approach to understand the prevalence of viruses in a given catchment population, as wastewater contains viruses from symptomatic and asymptomatic individuals. The current study reports the first detection of SARS-CoV-2 RNA in untreated wastewater in Slovenia. Two sizes of centrifugal filters were tested: 30 kDa and 10 kDA AMICON® Ultra-15 Centrifugal Filters, where 10 kDA resulted in a higher concentration factor and higher recovery efficiency. The results in hospital wastewater show that WBE can be used for monitoring COVID -19 and could be applied in municipal wastewater treatment plants as a potential complementary tool for public health monitoring at population level., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Several sports-related injuries and orthopedic treatments need the necessity of corrective shoes that can assuage the excessive pressure on sensitive locations of the foot. In the present work, we study the mechanical and energy absorption characteristics of density-graded foams designed for shoe midsoles. The stress-strain responses of polyurea foams with relative densities (nominal density of foam divided by the density of water) of 0.095, 0.23, and 0.35 are obtained experimentally and used as input to a semi-analytical model. Using this model, three-layered foam laminates with various gradients are designed and characterized in terms of their weight, strength, and energy absorption properties. We show that, in comparison with monolithic foams, significant improvement in strength and energy absorption performance can be achieved through density gradation. Our findings also suggest that there is not a single gradient that offers a superior combination of strength, energy absorption, and weight. Rather, an optimal gradient depends on the plantar location and pressure. Depending on the magnitude of the local plantar pressure, density gradients that lead to the highest specific energy absorption are identified for normal walking and running conditions., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Shoe-floor interactions play a crucial role in determining the possibility of potential slip and fall during human walking. Biomechanical and tribological parameters influence the friction characteristics between the shoe sole and the floor and the existing work mainly focus on experimental studies. In this paper, we present modeling, analysis, and experiments to understand slip and force distributions between the shoe sole and floor surface during human walking. We present results for both soft and hard sole material. The computational approaches for slip and friction force distributions are presented using a spring-beam networks model. The model predictions match the experimentally observed sole deformations with large soft sole deformation at the beginning and the end stages of the stance, which indicates the increased risk for slip. The experiments confirm that both the previously reported required coefficient of friction (RCOF) and the deformation measurements in this study can be used to predict slip occurrence. Moreover, the deformation and force distribution results reported in this study provide further understanding and knowledge of slip initiation and termination under various biomechanical conditions.

Antibiotics have always appeared miraculous, saving innumerable lives. However, the unwise use of antimicrobial drugs has led to the appearance of resistant bacteria. The purpose of this study was to evaluate antimicrobial resistance in Escherichia coli (n =160) isolated from food of animal origin. The focus was on E. coli -producing extended-spectrum β-lactamases. E. coli was chosen because it is a part of the normal microbiota in mammals and can enter the food chain during slaughtering and food manipulation. Subsequently, its resistance genes can be transferred to pathogenic bacteria and human microbiota. Phenotypic and genotypic analyses of selected antimicrobial resistances were carried out together with a molecular analysis of virulence genes. E. coli isolates from food of animal origin were compared with clinical E. coli strains isolated from the human intestinal tract. Extended-spectrum β-lactamase-producing E. coli isolates were found in 9.4% of food isolates and in 1.8% of intestinal isolates. Phylogenetically, the majority of food (86.3%) and intestinal E. coli (58.1%) isolates were found to belong to the commensal phylogenetic groups A and B1. The distribution of 4 of 14 analyzed virulence factors was similar in the food and intestinal isolates. Strains isolated from food in Slovenia harbored resistance genes and virulence factors, which can constitute a problem for food safety if not handled properly.

Background: Twenty-five percent to 50% of acute gastroenteritis (AGE) cases remain etiologically undiagnosed. Our main aim was to determine the most appropriate list of enteric pathogens to be included in the daily diagnostics scheme of AGE, ensuring the lowest possible diagnostic gap., Methods: Two hundred ninety seven children ≤6 years of age, admitted to hospital in Slovenia, October 2011 to October 2012, with AGE, and 88 ≤6 years old healthy children were included in the study. A broad spectrum of enteric pathogens was targeted with molecular methods, including 8 viruses, 6 bacteria and 2 parasites., Results: At least one enteric pathogen was detected in 91.2% of cases with AGE and 27.3% of controls. Viruses were the most prevalent (82.5% and 15.9%), followed by bacteria (27.3% and 10.2%) and parasites (3.0% and 1.1%) in cases and controls, respectively. A high proportion (41.8%) of mixed infections was observed in the cases. For cases with undetermined etiology (8.8%), stool samples were analyzed with next generation sequencing, and a potential viral pathogen was detected in 17 additional samples (5.8%)., Conclusions: Our study suggests that tests for rotaviruses, noroviruses genogroup II, adenoviruses 40/41, astroviruses, Campylobacter spp. and Salmonella sp. should be included in the initial diagnostic algorithm, which revealed the etiology in 83.5% of children tested. The use of molecular methods in diagnostics of gastroenteritis is preferable because of their high sensitivity, specificity, fast performance and the possibility of establishing the concentration of the target. The latter may be valuable for assessing the clinical significance of the detected enteric, particularly viral pathogens.

Campylobacteriosis is the leading zoonosis in the European Union with the majority of cases attributed to Campylobacter jejuni. Although the disease is usually self-limiting, some severe cases need to be treated with antibiotics, primarily macrolides and quinolones. However, the resistance to the latter is reaching alarming levels in most of the EU countries. To shed light on the expansion of antibiotic resistance in central Europe, we have investigated genetic similarity across 178 ciprofloxacin-resistant C. jejuni mostly isolated in Slovenia, Austria and Germany. We performed comparative genetic similarity analyses using allelic types of seven multilocus sequence typing housekeeping genes, and single nucleotide polymorphisms of a quinolone resistance determining region located within the DNA gyrase subunit A gene. This analysis revealed high genetic similarity of isolates from clonal complex ST-21 that carry gyrA allelic type 1 in all three of these central-European countries, suggesting these ciprofloxacin resistant isolates arose from a recent common ancestor and are spread clonally.