Gait variability (GV) is a crucial measure of inconsistency of muscular activities or body seg-mental movements during repeated tasks. Hence, GV might serve as a relevant and sensitive measure to quantify adjustments of walking control. However, has not been clarified whether GV is associated with walking speed to exploit effective better coordination level. Fourteen male stu-dents (age 22.4 ± 2.7 years, body mass 74.9 ± 6.8 kg, body height 1.78 ± 0.05 m) took part in this study. After three days of walking 1 km each day at a self-selected speed (SS) on asphalt with Apple Watch S. 7 (AppleTM), the participants were randomly evaluated on a treadmill at three different walking speed intensities for 10 minutes each one, at SS-20% / SS+20% of SS, with 5 minutes of passive recovery in-between. Heart rate (HR) was monitored beat-to beat and nor-malized as HR%MAX, while the rate of perceived exertion (RPE) (CR-10) was asked after each trial. Kinematic analysis was performed assessing the Contact Time (CT), Swing Time (ST), Stride Length (SL), Stride Cycle (SC) and Gait Variability as Phase Coordination Index (PCI). RPE and HR increased with higher walking speed (P = 0.005 and P = 0.035, respectively). CT and SC decreased as the speed increased (P = 0.0001 and P = 0.013, respectively), while ST remained un-changed (P = 0.277). SL increased with higher walking speed (P = 0.0001). Conversely, PCI was 3.81 ± 0.88 % (high variability) at 3.96 ± 0.47 km·h-1, 2.64 ± 0.75 % (low variability) at SS (4.94 ± 0.58 km·h-1), 3.36 ± 1.09 % (high variability) at 5.94 ± 0.70 km·h-1 (P = 0.001). These results indi-cate that while the metabolic demand and kinematics variables changing linearly with increasing speed, the most effective GV was observed at SS. Therefore, SS could be a new methodological approach to choose the individual walking speed, normalize the speed intensity, and avoid a gait pattern alteration.

Quantitative analysis of human gait is critical for early discovery, progressive tracking, and rehabilitation of neurological and musculoskeletal disorders, such as Parkinson’s Disease, stroke, and Cerebral Palsy. Gait analysis typically involves estimating gait characteristics, such as spatio-temporal gait parameters and gait health indicators (e.g., step time, length, symmetry, and balance). Traditional methods of gait analysis involve the use of cameras, wearables, and force plates, but are limited in operational requirements when applied in daily life - such as direct line-of-sight, carrying devices, and dense deployment. This paper introduces a novel approach for gait analysis by passively sensing footstep-induced floor vibrations during walking using vibration sensors mounted on the floor surface. Our approach is non-intrusive, scalable, and perceived as more privacy-friendly, making it suitable for continuous gait health monitoring in daily life. We developed a floor vibration-based gait analysis framework to estimate various gait parameters that are used as standard metrics in medical practices, including temporal parameters (step, stride, stance, swing, double-support, single-support time) and spatial parameters (step length, width, angle, stride length), and extracts gait health indicators (cadence/walking speed, left-right symmetry, gait balance, initial contact types). The main challenge is that floor vibrations are distinct across different floor types. To address this challenge, our approach develops floor-adaptive algorithms to extract floor-specific features and is designed to be generalizable to various settings, including homes, hospitals, and eldercare facilities. We evaluate our approach through real-world walking experiments with 20 adults with 12,231 labeled gait cycles across concrete and wooden floors. Our results show 90.5% (RMSE 0.08s), 71.3% (RMSE 0.38m), and 92.3% (RMSPE 7.7%) accuracy in estimating temporal, spatial parameters, and gait health indicators, respectively.

The progress in markerless technologies is bringing clinicians tools to rapidly evaluate tests such as Timed Up and Go (TUG) without compromising the time of the assessment, yet it raises questions about the potential trade-off in accuracy compared to traditional marker-based systems, suggesting that the precision of these evaluations is not yet conclusively established. The OpenCap system is an easy tool to process 3D kinematics with two iPhone cameras placed in front of the subject. Previous research has primarily focused on walking and movement towards the cameras with the subject facing the cameras (WF) and thus has been unable to disentangle the differences in the movement directions. We have compared the OpenCap system with a standard marker-based system for both walking directions. In OpenCap, we found significantly worse results capturing walking facing away from the cameras (RW). Compared to the marker-based system, our findings indicate troubles measuring kinematic parameters but provide good accuracy in measuring spatial-temporal parameters. These insights pave the way for refining markerless assessment technologies, potentially enhancing their utility in clinical settings.

This review delves into the growing field of flexible and stretchable strain sensors utilized in human gait analysis, focusing on determining knee bending angle and muscle activities when a human subject walks. Recent advancements have enabled these sensors to accurately capture biomechanical parameters while accommodating the body's natural movements. We examine the principles underlying these sensors' design and fabrication techniques, emphasizing their flexibility, stretchability, and biocompatibility for seamless integration into wearable systems. Through critical evaluation of existing methodologies, we assess the reliability and validity of these sensors in quantifying gait parameters. Furthermore, we discuss this technology's clinical and research implications, highlighting its potential in personalized rehabilitation and sports performance optimization. We provide an overview of flexible strain sensors and their application for analyzing human walking gait, especially for observing walking gait in rehabilitation programs. First, we present the basic working principles of various flexible strain sensors. Second, by the application of flexible strain sensors as walking gait monitoring. Finally, current challenges and future opportunities in this research area are discussed. By synthesizing current knowledge and outlining future directions, this review aims to provide insights for researchers and practitioners seeking to leverage flexible and stretchable strain sensors for comprehensive human gait analysis.

The variability of ozone over Egypt has been studied in this work. Higher values of coefficient of variation (COV) at eight stations occur at winter while lowest values occur at summer. The COV is function of latitude in annual, winter and spring where it decreases gradually from the north to south of Egypt. The trend analysis of ozone over the eight stations indicates negative trends over northern stations for both annual and seasonal time series with the greatest one at winter. The horizontal distribution of ozone trend values is negative over all Egypt in winter while it positive over middle and south Egypt in the other seasons. The long-term variability of the behavior of the annual ozone shows positive trend values in ozone are the dominant features during the period 1979- 1989 at the most stations. Negative trend values in ozone are the dominant features during the period 1990- 2014 at all stations. The Mann–Kendall test confirms that there is an abrupt change towards decreasing of ozone occurs in 1981, 1984, 2012, 1999, 2000, 1998 and 2010, while a change towards increasing of ozone appears in 2006, 2014, 1993 and 1989.

Mobile health technologies enable continuous, quantitative assessment of mobility and gait in real-world environments, facilitating early diagnosis of gait disorders, disease progression monitoring, and prediction of adverse events like falls. Traditionally, mobile gait assessment predominantly relied on body-fixed sensors positioned at the feet or lower trunk. Here, we investigate the potential of an algorithm utilizing an ear-worn motion sensor for spatiotemporal segmentation of gait patterns. We collected 3D acceleration profiles from the ear-worn sensor during varied walking speeds in 53 healthy adults. Temporal convolutional networks were trained to detect stepping sequences and predict spatial relations between steps. The resulting algorithm, mEar, accurately detects initial and final ground contacts (F1 score of 99% and 91%, respectively). It enables determination of temporal and spatial gait cycle characteristics (among others stride time and stride length) with good to excellent validity at a precision sufficient to monitor clinically relevant changes in walking speed, stride-to-stride variability, and side asymmetry. This study highlights the ear as a viable site for monitoring gait and proposes its potential integration with in-ear vital sign monitoring. Such integration offers a practical approach to comprehensive health monitoring and telemedical applications, by integrating multiple sensors in a single anatomical location.

Techniques have been developed to determine whether a horse is in resting or running mode by measuring at least one of the following: the horse's body temperature, heart rate, oxygen saturation, and exercise level. However, the existing technology has not reached a level where a trainer can accurately assess a horse's running conditions, such as speed, acceleration, stride, limb rotation, ground impact, and frontal balance, during the training of racehorses. In addition, data is needed to quickly detect abnormalities during training and provide a basis for changing the intensity of training or deciding to give a rest to the horse. Devices that detect abnormalities in equine gait with high sensitivity will contribute to animal welfare and increase the athletic longevity of horses. This paper reports the development results of a new IoT device that acquires, processes, and analyzes information such as heart rate, position, speed, acceleration, pitch, stride, and ground contact during a training of racehorses. The purpose of this development is to provide an information on a novel processing system, device, method, and program that can analyze training condition of racehorses from multiple angles.

Channel bends are one of the most important characteristic features of natural streams. These bends often create the conditions for a hyporheic zone, which has been recognized as a critical component of stream ecosystems. The streambed vertical hydraulic conductivity (K_v), vertical hydraulic gradient (VHG) and Darcian flux (DF) in the hyporheic zone were estimated at 61 locations along a channel bend of the Beiluo River during July 2015 and January 2016. All the streambed attributes showed great spatial variability along the channel bend. Both upward fluxes and downward fluxes occurred during the two test periods, most of studied stream sections were controlled by downwelling, indicating stream water discharge into the subsurface. The average downward flux was higher at the downstream side than at the upstream side of the channel bend, especially in July 2015. The distribution of streambed sediment grain size has a significant influence on the variability of K_v; high percentages of silt and clay sediments generally lead to low K_v values. Higher K_v at the depositional left bank at the upstream site shifted toward the erosional right bank at the downstream site, with K_v values positively correlated with the water depth. This study suggested that the variabilities of K_v and VHG were influenced by the stream geomorphology and that the distribution of K_v was inversely related, to a certain extent, to the distribution of VHG across the channel bend. K_v and VHG were found to have opposite effects on the DF, and the close relationship between K_v and DF indicated that the water fluxes were mainly controlled by K_v.

Freezing of Gait (FoG) is a disabling motor complication in Parkinson’s disease (PD), affecting approximately 50% of advanced PD patients. It is characterized by sudden and transient inability to initiate or maintain walking, leading to falls and reduced quality of life. This study investigates the relationship between white matter integrity and step initiation impairments in FoG. Forty-three PD patients (26 with FoG) underwent diffusion-weighted imaging to assess white matter DTI metrics and kinematic analysis during step initiation tasks. Multiple regression analyses were conducted to explore the connection between white matter tract integrity and step initiation behavior. The multiple regression analysis shows that (1) Right Inferior Longitudinal Fasciculus RD explained 31% of APA duration’s variance; (2) Corpus Callosum Forceps Major explained 25% of the step length's variance. There was a positive correlation between the Right Inferior Longitudinal Fasciculus RD and APA duration and a negative correlation between Corpus Callosum Forceps Major RD and step length. The findings suggest that compromised white matter integrity in RILF and CC contributes to impaired motor control during step initiation in FoG. These regions are critical for inhibitory control and interhemispheric coordination, crucial for APA execution and step length regulation.

Veterinary science has benefitted from technological advancements in the past and will hopefully continue to do so, especially in the field of equine gait analysis. There is a need for rapid and easy to use technology that is accurate and portable, but at the same time is also readily interpretable. This manuscript presents two new approaches to equine gait analysis, both of which are commer-cial devices. The use of Acoustic MyoGraphy (AMG) has been proven in the field of muscle func-tion and performance as well as ligament health, but it can also provide details concerning gait when placed on the wall of the hoof of a horse. The TendibootTM system is a limb focused unit that can be easily attached, activated and used in a Veterinary clinic setting, rapidly providing gait details for equine diagnostic purposes. In conclusion this manuscript provides an insight into gait parameters from recent research trials that are novel and challenge current thinking.

The aim of this study was to examine the oxidation of human serum albumin (HSA) caused by oxidative stress after an exhaustive exercise such as ultra-marathon race. Thus, blood samples from 12 adult runners who underwent a 103 km mountain ultra-marathon race were collected pre- and 24, 48 and 72 h post race. HSA was partially purified using affinity chromatography and then was subjected to Western blot analysis for disulfide dimers determination, indicating oxidation. The results were correlated with those from a previous study in which the same samples were analyzed using different oxidative stress markers and a good correlation with protein carbonyls (PC) at all time points was observed. Moreover there was a significant correlation with static oxidation-reduction potential (sORP) at 24 h, and a negative correlation with capacity oxidation-reduction potential (cORP) at 24 and 48 h. In addition, an individual analysis of albumin dimers exhibited great inter-individual differences. This inter-individual variability in the oxidation of HSA may suggest different interventions (e.g. through diet) in order to confront the effects on athletes’ organism after a strenuous exercise. In conclusion, this study supported the importance of the assessment of albumin dimers as a predictive marker for exercise-induced oxidative stress.

The demonstration of compliance of rolling stock against disturbance limits for railway signaling, and in particular track circuits, is subject to a large deal of variability, caused by the diverse values of the electrical parameters of the railway line and resulting transfer functions, as well as operating conditions of rolling stock during tests. Instrumental uncertainty is evaluated with a Type B approach and shown to be much less than the experimental variability. Repeated test runs in acceleration, coasting, cruising, braking conditions are considered, deriving both max-hold (spread) and sample dispersion curves compared to the respective mean values (Type A approach to the evaluation of uncertainty). The major source of variability affecting a significant portion of the spectrum is caused by the superposed oscillations of the onboard LC filter, for which different choices of the transformation window duration are discussed. The test runs and the acquired data covered overall 1 day of tests along about 300 km of the Italian 3 kV DC railway network.

Digital gait monitoring is increasingly used to assess locomotion and fall risk. The aim of this work is analyzing the changes in the foot-floor contact sequences of Parkinson’s Disease (PD) patients in the year following the implant for deep brain stimulation (DBS). During their best-ON condition, 30 PD patients underwent gait analysis at baseline (T0), at 3 months (T1), and 12 months (T2) after the DBS neurosurgery for bilateral high-frequency subthalamic nucleus stimulation. Thirty age-matched controls underwent gait analysis once. Each subject was equipped with bilateral foot-switches and a 5-minute walk was recorded, including both straight-line and turnings. The walking speed, turning time, stride time variability, percentage of atypical gait cycles, stance, swing, and double support duration were estimated. Overall, the gait performance of PD patients improved after DBS, as also confirmed by the decrease in the UPDRS-III score from 19.4±1.8 to 10.2±1.0 points (T0 vs. T2) (p < 0.001). In particular, the percentage change of atypical gait cycles of PD more affected side decreased at T1 (Straigh-line: -72%; Turnings: -43%) and at T2 (Straigh-line: -54%; Turnings: -20%). The percentage of atypical gait cycles proved an informative digital biomarker for quantifying PD gait changes after DBS, both in straight-line paths and turnings.

State-of-the-art augmented-reality (AR) glasses record their position and orientation in space, enabling measurements and analyses of clinical gait-and-balance tests. This study’s objective was to evaluate concurrent validity and test-retest reliability for common clinical gait-and-balance tests in people with Parkinson’s disease: the Five Times Sit-To-Stand (FTSTS) and Timed Up-and-Go (TUG) tests. Position and orientation data was collected in 22 participants with Parkinson's disease using HoloLens 2 and Magic Leap 2 AR glasses, from which test-completion durations and durations of distinct sub-parts (e.g., sit-to-stand, turning) were derived and compared to reference systems and over test repetitions. Regarding concurrent validity, for both tests an excellent between-systems agreement was found for position and orientation time series and test-completion durations. Between-systems agreement for FTSTS (sub-)durations were all excellent, while TUG turning sub-durations were excellent (turn 1) and moderate (turn 2). Regarding test-retest reliability, the within-system test-retest variation in test-completion times and sub-durations was always much greater than the between-systems variation, implying that these (sub-)durations may be derived interchangeably from AR and reference-system data. In conclusion, AR data are of sufficient quality to evaluate gait and balance in people with Parkinson's disease, with valid quantification of test-completion durations and sub-durations of distinct FTSTS and TUG sub-parts.

Freezing of gait (FOG), a debilitating symptom of Parkinson’s disease (PD), can be safely studied using the stepping in place (SIP) task. However, clinical, visual identification of FOG during SIP is subjective and time consuming, and automatic FOG detection during SIP currently requires measuring center of pressure on dual force plates. This study examines whether FOG elicited during SIP in 10 individuals with PD could be reliably detected using kinematic data measured from wearable inertial measurement unit sensors (IMUs). A general, logistic regression model (AUC = 0.81) determined that three gait parameters together were overall the most robust predictors of FOG during SIP: arrhythmicity, swing time coefficient of variation, and swing angular range. Participant-specific models revealed varying sets of gait parameters that best predicted FOG for each participant, highlighting variable FOG behaviors, and demonstrated equal or better performance for 6 out of the 10 participants, suggesting the opportunity for model personalization. The results of this study demonstrated that gait parameters measured from wearable IMUs reliably detected FOG during SIP, and the general and participant-specific gait parameters allude to variable FOG behaviors that could inform more personalized approaches for treatment of FOG and gait impairment in PD.

The role of natural factors mainly solar eleven-year cycle variability, and volcanic eruptions on two major modes of climate variability the North Atlantic Oscillation (NAO) and El Niño Southern Oscillation (ENSO) are studied for around last 150 years period. The NAO is the primary factor to regulate Central England Temperature (CET) during winter throughout the period, though NAO is impacted differently by other factors in various time periods. Solar variability indicates a strong positive influence on NAO during 1978-1997, though suggests opposite in earlier period. Solar NAO lag relationship is also shown sensitive to the chosen times of reference and thus points towards the previously proposed mechanism/ relationship related to the sun and NAO. The ENSO is influenced strongly by solar variability and volcanic eruptions in certain periods. This study observes a strong negative association between the sun and ENSO before the 1950s, which is even opposite during the second half of 20th century. The period 1978-1997, when two strong eruptions coincided with active years of strong solar cycles, the ENSO, and volcano suggested a stronger association, and we discussed the important role played by ENSO. That period showed warming in central tropical Pacific while cooling in the North Atlantic with reference to the later period (1999-2017) and also from chosen earlier period. Here we show that the mean atmospheric state is important for understanding the connection between solar variability, the NAO and ENSO and associated mechanism. It presents a critical analysis to improve knowledge about major modes of variability and their role in climate. We also discussed the importance of detecting the robust signal of natural variability, mainly the sun.

The construction industry is a key driver of environmental change due to its extensive ‎use of resources and high levels of emissions, thus placing a significant burden on global ‎efforts towards sustainable development targets. A large portion of the environmental ‎footprint of buildings results from the energy required to sustain indoor comfort levels. ‎Therefore, enhancing the energy efficiency of existing buildings becomes critical in ‎reducing their environmental impact. This study examines the influence of increasing ‎thermal performance with the aim of reducing heating ‎demand. Thus, numerical modelling tools and different energy performance assessment meth-odologies have been used. ‎Specifically, it evaluates two existing residential buildings in Romania and compares ‎heating demand predictions using PHPP and Mc001-2022 methodologies across various ‎climatic data sets and case studies. The results reveal significant variability in heating ‎demand predictions, emphasizing the importance of methodological choice and climatic ‎data. The ‎study highlights that both PHPP and Mc001-2022 methodologies yield varying results ‎depending on the specific conditions and characteristics of each building. This variation in results underscores ‎the necessity for a nuanced and context-specific approach to energy performance ‎assessment, in-corporating multiple energy efficiency measures tailored to the unique ‎features of each building.

Introduction: Low back pain (LBP) is the leading cause of lost productivity, absenteeism, disability, and early retirement worldwide. LBP treatment should be comprehensive, including prevention, education, diagnosis, and various treatment methods. Treatment can be divided into pharmacological and non-pharmacological. The role of physiotherapy in the comprehensive treatment of LBP is very important. Elastic therapeutic tape, also called kinesiology tape or therapeutic kinesiology tape, has been used for about 50 years. Purpose: The aim of this study was to evaluate the effectiveness of Kinesio taping in patients suffering from (LBP) and its possible effect on the swing of the center of pressure (COP), balance, gait, improvement of coordination, and pain reduction. Material and methods: A total of 60 patients aged 20 to 83 years (54% women) were examined, all of whom met the inclusion and exclusion criteria. In the experimental group, in addition to comprehensive rehabilitation, kinesiotaping of the L1-L5 spine was used. The control group underwent balance control training. The research tools used included the Bohannon single-leg standing test, the FAC scale - Functional Ambulatory Category, the Podsiadlo and Richardson Standing and Walking Test - Timed Up and Go (TUG), lumbar spine mobility assessment, Lasegue's sign and examination of neurological deficit symptoms. and self-assessment of pain using the Visual Analogue Scale (VAS). Results: Kinesio taping has a statistically significant effect on postural control, balance, gait, coordination, and pain. The main parameter with a statistically significant effect on the effects of Kinesio taping was age (below 55 years), which was also observed in the control group. Conclusions: Kinesio taping is an effective method in the treatment of LBP. It improves postural control, balance, gait, coordination, and pain.

Most research on colostrum quality and colostrum management focuses on maternal IgG transfer to the newborn calf. However, in addition to being a source of antibodies, colostrum has other components that influence passive immune transfer, nutrition, gut maturation, and thermoregulation. In this review, the constituents in the bovine colostrum, as well as their variation, are explored and it is discussed the biological role of colostrum on the newborn calf. Protein is the nutrient in higher concentration and fat is the nutrient with the most variation. There is a pronounced amplitude in the total solids content of colostrum, but the average concentration does not vary much between studies (24.7%). Bovine colostrum major components can vary with several factors, such as the region, season, breed, dry period length, and nutritional aspects of the dam. Bioactive components, cells, and microbiome variability are less understood, besides IgG. Regardless, they play crucial distinct roles in the physiological development of the newborn. However, a multi-interactive effect between these components, cells, and microorganisms is more likely to occur. Recently researched components in colostrum like miRNA, nucleo(t)sides, the milk fat globule membrane, oligosaccharides, minor proteins, and the microbiome are examples of promising interest areas of study.

Several plant species produce mixtures of odorous and volatile compounds known as essential oils (EOs). These mixtures play important roles in nature and have been utilized by man for pharmaceutical and agrochemical purposes. There are more than 3000 EOs reported in the literature with approximately 300 having commercial use, including the oils from Eucalyptus species. Such oils are rich in monoterpenes and have found applications as pharmaceuticals, agrochemicals, food flavorants and in the perfume industry. Such applications are related to their diverse biological and organoleptic properties. In view of their importance, we review in this article up to date information concerning chemical composition and biological activities of essential oils from different species of Eucalyptus. Among the 900 species and subspecies of the Eucalyptus genus¸ we examined 68 species. The studies associated with these species were conducted in 27 countries. We have focused on the antimicrobial, acaricide, insecticide and herbicide activities, hoping that such information will contribute in the advances of the research in this field. It is also intended that the information herein described can be useful in the rationalization of the use of Eucalyptus EOs as components for new pharmaceutical and agrochemical applications as well as food preservatives and flavorants.

Background: Anxiety disorders can be both an independent risk factor of many somatic conditions and the cause of complications of various organic disorders leading to poor prognosis. Objectives: The purpose of this study is to compare the heart rate variability (HRV) recorded both during the day and at night in patients with anxiety disorders and healthy individuals. Methods: The study was conducted on fifty consecutive outpatients with anxiety disorders who participated in intensive group psychotherapy. The diagnosis was made according to DSM-IV-TR criteria using the PSE-10 questionnaire. Out of 50 patients under study, 17 were diagnosed with panic disorder (PD) and 21 with generalized anxiety disorder (GAD). The control group consisted of 40 healthy people. The resulting three groups were compared in terms of circadian HRV using the Oxford Medilog Suprima Holter System. Results: The HRV analysis showed the nocturnal falls in the time and frequency parameters related to parasympathetic activity (rMSSD, pNN50, HF). The most unfavourable alterations were observed in the PD group, which comprised the disappearance of day vs. night amplitude of the majority of HRV parameters. Hence, the PD group was particularly susceptible to the arrhythmic events. It was noticeable that nocturnal vagotonia in the PD group was significantly lower as compared with the GAD and control group. Conclusions: The innovative aspect of the present study was to find a distinct profile of HRV with regard to the types of anxiety disorders because of the existing considerable differences between the nature of PD and GAD.

Background: This study aimed to investigate how external perturbations caused by the treadmill belt's acceleration (Acc) and deceleration (Dec) during the Initial Contact (Initial), Mid Stance (Mid) and Pre-Swing (ToeOff) phase affect gait regularity in young adults. Methods: Twenty-one healthy young females walked on a treadmill in a virtual environment (Grail, Motek), where four unexpected perturbations were applied to the left belt at Initial, Mid, and ToeOff. Sample Entropy (SampEn) was calculated for the center of mass (CoM) displacements, for six perturbation scenarios in three directions: anterior-posterior (AP), medial-lateral (ML), and vertical (vert), with SampEn vector lengths (m) ranging from 2 to 10. Results: The CoM displacement exhibited its highest regularity (low SampEn values) in the AP and vert-directions during Dec_ToeOff, across all m values. Similarly, this pattern was observed in the ML-direction, but exclusively for m = 2 and 4. The least regular CoM trajectories (high SampEn values) were for Dec_Mid in the AP-direction, across all m values. This trend persisted in the ML-direction, only for m = 2 and 4. However, the most irregular CoM displacements in the ML-direction occurred during Dec_ToeOff for the remaining m values. Vertical CoM displacements exhibited the highest irregularities during Dec_Initial for m ≥ 4. Conclusions: Evaluating the regularity of CoM displacements using SampEn can be a useful tool for assessing how gait perturbations are handled.

The paper presents an innovative hexapod walking robot built with 3-UPU parallel mechanism. In the robot, the parallel mechanism is used as both an actuator to generate walking and also a connecting body to connect two groups of three legs, thus enables the robot to walk with simple gait by very few motors. In the paper, the forward and inverse kinematics solutions are obtained. The workspace of the parallel mechanism is analyzed using limit boundary search method. The walking stability of the robot is analyzed, which yields the robot’s maximum step length. The gait planning of the hexapod walking robot is studied for walking on both flat and uneven terrains. The new robot, combining the advantages of parallel robot and walking robot, has a large carrying capacity, strong passing ability, flexible turning ability, and simple gait control for its deployment for uneven terrain.

Sarcoglycanopathies are among the most frequent and severe autosomal recessive forms of limb-girdle muscular dystrophies /LGMD/ with childhood onset. Mutations in , , and sarcoglycan genes lead to various kinds of LGMD. We present the clinical variability of LGMD 2C/R5 among a genetically homogeneous group of 56 patients, belonging to 35 pedigrees. Molecular genetic analysis showed thаt all 57 patients were homozygous for C283Y variant. The muscles of the pelvic girdle and the trunk were early and more severely affected, followed by the the shoulder girdle. Macroglossia, hypertrophy of the calves, scapular winging and lumbar hyperlordosis were common in the ambulatory phase. A great variability in the clinical presentation of LGMD 2C/R5 was observed both intra and interfamilial, despite the same underlying molecular defect. Females demonstrated a relatively milder clinical course, compared to males. Mean CK levels were 20 times above normal values. Muscle CT of MRI showed earlier and more severe involvement of the flexor proximal limb muscles in comparison to the extensor ones.

Grain quality, cooking quality and nutritional quality traits are some of the major attributes that enhance uptake and utilisation of improved cowpea varieties. Therefore, there is need for a better understanding of the genetic variation and inter-relationships among these quality traits in cowpea to integrate them in cowpea breeding programs. The study was conducted to determine genetic variability among 306 cowpea genotypes for grain quality, cooking quality and nutritional quality traits and to understand the interrelationships among these traits for exploitation in breeding programs. The results showed highly significant differences (P

Abstract: Congenital hyperinsulinism (CHI) is a rare disorder of glucose metabolism and is the most common cause of severe and persistent hypoglycemia (hyperinsulinemic hypoglycemia, HH) in the neonatal period and childhood. Most cases are caused by mutations in the ABCC8 and KCNJ11 genes that encode the ATP-sensitive potassium channel (KATP). We present the correlation between genetic heterogeneity and the variable phenotype in patients with early-onset hyperinsulinemic hypoglycemia caused by ABCC8 gene mutations. In the first patients, which presented persistent severe hypoglycemia since the first day of life, molecular genetic testing revealed the presence of a homozygous mutation in the ABCC8 gene [deletion in the ABCC8 gene c.(2390+1_2391-1)_(3329+1_3330- 1)del] correlated with a diffuse form of hyperinsulinism (the parents being healthy heterozygous carriers). In the second patient, the onset was on the third day of life with severe hypoglycemia, and genetic testing identified a heterozygous mutation in the ABCC8 gene c.1792C&gt;T (p.Arg598*) inherited on the paternal line, which led to the diagnosis of focal form of hyperinsulinism. To locate the focal lesions, (18)F-DOPA (3,4-dihydroxy-6-[18F]fluoro-L-phenylalanine) PET/CT was recommended (an investigation that cannot be carried out in the country), but the parents refused to carry out the investigation abroad. In this case, early surgical treatment could have been curative. In addition, the second child also presented secondary adrenal insufficiency requiring replacement therapy. At the same time, she developed early recurrent seizures that required antiepileptic treatment. We emphasize the importance and of molecular genetic testing for diagnosis, management and genetic counseling in patients with HH.

This study investigates the collapse of the medial longitudinal arch (MLA) as a risk factor for medial tibial stress syndrome (MTSS), hypothesizing that overuse of extrinsic foot muscles to prevent MLA collapse can lead to disability. Twenty healthy adults (39 feet) with a foot posture index score below 6 and no recent lower extremity orthopedic history participated. Ultrasonog-raphy measured foot muscle cross-sectional areas, while three-dimensional motion analysis us-ing VICON assessed foot kinematics during gait, focusing on navicular height at initial contact (ICNH) and dynamic navicular drop (DND) during the stance phase. Hierarchical cluster analy-sis based on ICNH and DND compared muscle cross-sectional areas between clusters using ANOVA or Kruskal–Wallis test. The analysis indicated that ICNH was lower in clusters 1 and 3 than in cluster 2, and DND was smaller in clusters 1 and 2 than in cluster 3. Although there was no significant difference in muscle cross-sectional area between the clusters, the flexor hallucis longus tended to be thicker in cluster 1 than in cluster 3 (p = 0.051). The findings suggest that the flexor hallucis longus may help prevent MLA compression during loading, indicating that over-use of extrinsic foot muscles may contribute to MTSS development.

Total hip arthroplasty (THA) is a preferred treatment for primary osteoarthritis (OA) or secondary due to developmental hip dysplasia (DDH). Gait analysis is considered a golden standard for evaluating post-arthroplasty walking patterns. This study compared post-THA spatiotemporal gait parameters (SGPs) between OA and DDH patients and explored correlations with demographic and clinical variables. Thirty patients (15 per group) were recorded during gait, and their SGPs were analyzed. Functionality was evaluated with the Oxford Hip Score (OHS). The OA patients were significantly older than DDH (pr< 0.51, all p< 0.05). The preoperative gait alterations associated with OA or DDH were improved to similar levels in both groups after THA. Post-arthroplasty SGPs and OHS correlations indicate limitations in certain activities. These find-ings must be correlated with kinetic gait analysis data to fully evaluate gait and functionality dif-ferences among patient groups.

Intermittent religious fasting increases a risk of hypo- and hyperglycemia in individuals with diabetes, but its impact in those without diabetes is poorly investigated. The study aim was to examine the effects of religious Bahá'í fasting (BF) on glycemic control and variability and compare these effects with time-restricted eating (TRE). In a three-arm randomized controlled trial, 16 subjects without diabetes were assigned to a BF, 16:8 TRE or control group. Continuous glucose monitoring and food intake documentation was conducted before and during the 19 days of intervention, and 24-hour mean glucose, glycemic variability indices, and glucotypes were assessed. BF and TRE groups, but not the control group, markedly reduced the daily eating window while maintaining macronutrient composition. Only the BF group decreased caloric intake (-677.8 ± 357.6 kcal, p=0.013), body weight (-1.92 ± 0.95 kg, p=0.011) and BMI (-0.65 ± 0.28 kg, p=0.006). Higher maximum glucose values were observed during BF in the within-group (+1.41 ± 1.04, p=0.039) and between-group comparison (BF vs. Control: p= 0.010 and TRE vs. BF: p= 0.022). However, there were no alterations of 24-hour mean glucose, intra- and inter-day glycemic variability indices, or glucotypes in any group. Proportions of time above and below range (70-180mg/dl) and HbA1c values remained unchanged. BF and TRE do not exhibit negative effects on glycemic control and variability in subjects without diabetes.

This paper pioneers a novel exploration of environmental impacts in livestock farming, with a focus on pig farming's intersection with climate change and sustainability. It emphasizes the transformative potential of data-driven Artificial Intelligence (AI) methodologies, specifically the Internet of Things (IoT) and multimodal data analysis, in promoting equitable and sustainable food systems. The study observes five pigs, aged 86 to 108 days, using a tripartite sensor that records heart rate, respiration rate, and accelerometer data. The unique experimental design alternates between periods of isolation during feeding and subsequent pairing, enabling the investigation of stress-induced changes. Key inquiries include discerning patterns in heart rate data during isolation versus paired settings, fluctuations in respiration rates, and behavioral shifts induced by isolation or pairing. The study also explores potential detection of gait abnormalities, correlations between pigs' age and their gait or activity patterns, and the evolution of pigs' walking abilities with age. The paper scrutinizes accelerometer data to detect activity changes when pigs are paired, potentially indicating increased stress or aggression. It also examines the adaptation of pigs to alternating isolation and pairing over time, and how their heart rate, respiration rate, and activity data reflect this process. The study considers other significant variables, such as time of day and isolation duration, affecting the pigs' physiological parameters. Sensor data is further utilized to identify behavioral patterns during periods of feeding, isolation, or pairing. In conclusion, this study harnesses IoT and multimodal data analysis in a groundbreaking approach to pig welfare research. It underscores the compelling potential of technology to inform about overall pig welfare, particularly stress levels and gait quality, and the power of data-driven insights in fostering equitable, healthy, and environmentally conscious livestock production systems.

Brucellosis is a multi-system infectious disease that exhibits with various manifestations and complications. Neurobrucellosis is a rare but serious presentation of brucellosis that can be discovered in every stages of the disease. Laboratory tests and physical examination and patient history are generally the basis for diagnosing the disease. It has both insidious and prolonged clinical course of the disease and long-term therapies. Also the most common pattern of exhibition is subacute or chronic. We reported a case of young female who had history of painless weakness in the right lower limb (proximal and distal) that started gradually and had progressed over the time, and after a month she felt weakness in the left lower limb with the same pattern. Lumbosacral Magnetic resonance imaging (MRI) with and without contrast was shown evidence of enhancement thickening of caudal equina ventral roots. Brucella antigen titer was positive, the result was 1/160. And other clinical tests were normal. Patient treated with Intravenous injection (IV) Rifampicin and Intravenous Cotrimoxazole. patient was discharged with good health and continuinng all two medications for 5 months. The descision was taken to report this case as a result of entire respond in patient’s illness after a enduring disease. Neurobrucellosis is a treatable disease in which it would be better to consider a high indication of suspicion. Due to if ignored, it may cause significant morbidity and mortality.

To maintain a healthy lifestyle, adults rely on their ability to walk while simultaneously managing multiple tasks that challenge their coordination. This study investigates the impact of cognitive dual-task on lower limb muscle activities in 21 healthy young adults during both gait initiation and steady-state gait. We utilized wireless electromyography sensors to measure muscle activities, along with a 3D motion capture system and force plates to detect the phases of gait initiation and steady-state gait. Participants were asked to walk at their self-selected pace, and we compared single-task and dual-task conditions. We analyzed mean muscle activation and co-contraction in the biceps femoris, vastus lateralis, gastrocnemius, and tibialis anterior muscles. The findings revealed that during gait initiation with the dual-task condition, there was a decrease in mean muscle activation and an increase in mean muscle c-contraction between the swing and stance limb compared to the single-task condition. In steady-state gait, there was also a decrease in mean muscle activation in the dual-task condition compared to the single-task condition. When participants performed dual-task activities during gait initiation, early indicators of reduced balance capability were observed. Additionally, during dual-task steady-state gait, knee stabilizer muscles exhibited signs of altered activation, contributing to balance instability.

Background : The quantification of electromyographic activity using surface electrodes is inval-uable for understanding gait disorders in patients with central nervous system lesions. We propose to evaluate a commercially available low-cost system compared to a reference system in partic-ipants with stroke-related movement disorders in functional situations. Methods : Three hemiparetic participants performed three functional tasks: two treadmill walks at different speeds and a sit-to-stand test. The vastus lateralis and gastrocnemius medialis muscles were equipped with two EMG sensors. The comparison between the two EMG systems was based on 883 identified cycles. Spearman’s correlation coefficients (SC), linear correlation coefficients (LCC), and cross-correlation coefficients (CCC) were calculated. Results : The main results indicate good to very good similarity of the EMG signals collected from the two tested sEMG systems. In the comfortable walking condition, an SC of 0.894±0.091 and an LCC of 0.909±0.094 were noted. In the fast walking condition, an SC of 0.918±0.064 and an LCC of 0.935±0.056 were observed. For the 1-minute sit-to-stand test an SC of 0.880±0.058 and an LCC of 0.881±0.065 were noted. Conclusions : This study demonstrates good to very good similarity between the two sEMG systems, enabling the analysis of muscle activity during functional tasks.

The deterioration of gait can be used as a biomarker for ageing and neurological diseases. Continuous gait monitoring and analysis are essential for early deficit detection and personalized rehabilitation. The use of mobile and wearable inertial sensor systems for gait monitoring and analysis have been well explored with promising results in the literature. However, most of these studies focus on the technologies for gait characteristic assessment, few of them have considered the data acquisition bandwidth of the sensing system. Inadequate sampling frequency will sacrifice signal fidelity, thus leading to an inaccurate estimation especially for spatial gait parameters. In this work, we developed an inertial sensor based in-shoe gait analysis system for real-time gait monitoring and investigated the optimal sampling frequency to capture all the information on walking patterns. An exploratory validation study was performed using an optical motion capture system on four healthy adult subjects, where each person underwent five walking sessions, giving a total of 20 sessions. Percentage mean absolute errors (MAE%) obtained in stride time, stride length, stride velocity, and cadence while walking were 1.19%, 1.68%, 2.08%, and 1.23%, respectively. In addition, an eigen-analysis based graphical descriptor from raw gait cycle signals was proposed as a new gait metric that can be quantified by principal component analysis to differentiate gait patterns, which has great potential to be used as a powerful analytical tool for gait disorder diagnostics.

Coronaviruses are a large family of diverse enveloped RNA viruses found in numerous animal species. They are well-known for their ability to cross species barriers and have been transmitted from bats or intermediate hosts to humans on several occasions. Four of the seven human coronaviruses (hCoVs) are responsible for approximately 20% of common colds (hCoV-229E, -NL63, -OC43, -HKU1). Two others (SARS-CoV-1 and MERS-CoV) cause severe and frequently lethal respiratory syndromes but have only spread to very limited extents in human populations. In contrast, SARS-CoV-2, while exhibiting intermediate pathogenicity, has a profound impact on public health due to its enormous spread. In this review, we discuss which initial features of the SARS-CoV-2 Spike protein and subsequent adaptations to the new human host may have helped this pathogen to cause the COVID-19 pandemic. Our focus is on host forces driving changes in the Spike protein and their consequences for virus infectivity, pathogenicity, immune evasion and resistance to preventive or therapeutic agents. In addition, we discuss the significance and perspectives of broad-spectrum therapeutics and vaccines.

(1) Background: Heart rate variability (HRV) has emerged as a potential prognostic tool in cardiovascular diseases, offering individualized insights into autonomic nervous system activity. However, real-time HRV data during the acute phase of STEMI, particularly during percutaneous coronary intervention (PCI), was not previously explored. (2) Methods: This single-center, observational cohort study included 104 STEMI patients undergoing primary percutaneous coronary intervention (PCI). HRV parameters were measured using a wearable device (CE marked) during PCI, capturing dynamic responses. The association between HRV parameters and adverse outcomes, including in-hospital mortality and major adverse cardiovascular events (MACE), were assessed. (3) Results: HRV parameters significantly decreased after myocardial revascularization, particularly SDNN, RMSSD, pNN50, HF, SD1, and SD2/SD1 ratio. Significant associations were found between reduced SD2/SD1 ratio, approximate entropy, and adverse outcomes, including increased in-hospital mortality and MACE. The SD2/SD1 ratio was significantly lower in patients who died during the hospital stay (p = 0.008) compared to survivors. Approximate entropy was also significantly lower in deceased patients (p = 0.019). (4) Conclusions: Real-time HRV monitoring using wearable technology offers valuable data regarding dynamic physiological changes during primary PCI. The integration of HRV into routine clinical practice, facilitated by wearable devices, could improve the risk stratification and event prediction in STEMI patients.

During an interdisciplinary study of the mire “Pod Małym Śnieżnikiem”, a very old specimen of the Norway spruce (Picea abies L.) was encountered. The aim of the present work was to perform a detailed examination of this tree, to compare it to other spruce trees on the mire, and to provide support for establishing protection for this tree stand. Tree-ring cores were sampled at 1.3 m above ground using Pressler borer, in two field campaigns: in June and July 2023, the latter campaign aiming to find the oldest trees. A total of 46 trees were sampled, yielding 84 measuring radii. Tree ring widths were measured down to 0.01 mm under a stereomicroscope. The oldest sampled tree yielded a total of 370 tree rings in the two radii, representing the period 1653–2022. The average tree ring width for TM15 equals 0.33 mm/year, and shows low values (on average 0.19 mm/year) for the period 1742–1943, i.e., during the Little Ice Age cooling. TM15 does not stand out from other trees from the population with respect to height or trunk diameter. A comparison of the age of this tree to the oldest spruce trees in Poland indicates that it is one of the longest living specimens of this species. Considering the natural character of the stand, the remaining flora and the peat-forming processes taking place within the mire “Pod Małym Śnieżnikiem”, we argue that the mire should become protected by the law as soon as possible in order to preserve this valuable high-mountain habitat.

Immersive virtual reality has the potential to motivate and challenge patients that need and want to relearn movements in the process of (neuro-)rehabilitation. The aims of this study were to evaluate the feasibility and users’ acceptance of an innovative immersive virtual reality system (head-mounted display) used in combination with robot assisted gait training in subjects suffering from neurological diseases. Fifteen participants tested a single session of immersive virtual reality by means of head-mounted display during a Lokomat gait session. Training parameters and safety indicators were collected and the acceptance was investigated among the participants and the therapists. The results suggest that the immersive virtual reality system is feasible with respect to safety and tolerance. Furthermore, the very positive overall acceptance of the system suggests that it has potential to be included in a robot assisted gait training session by means of Lokomat. Taken together, this study demonstrates the feasibility and acceptance of an innovative immersive virtual reality system in combination with a robot assisted gait training in subjects suffering from stroke and spinal cord injury, as well as their therapists.

Solar and wind resources available for power generation are subject to variability due to meteorological factors. Here, we use a new global climate reanalysis product, Version 2 of the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA-2), to quantify interannual variability of monthly-mean solar and wind resource from 1980 to 2016 at a resolution of about 0.5 degrees. We find an average coefficient of variation (CV) of 11% for monthly-mean solar radiation and 8% for windspeed. Mean CVs were about 25% greater over ocean than over land, and, for land areas, were greatest at high latitude. The correlation between solar and wind anomalies was near zero in the global mean, but markedly positive or negative in some regions. Both wind and solar variability were correlated with values of climate modes such as the Southern Oscillation Index and Arctic Oscillation, with correlations in the Northern Hemisphere generally stronger during winter. We conclude that reanalysis solar and wind fields could be helpful in assessing variability in power generation due to interannual fluctuations in the wind and solar resource. Skillful prediction of these fluctuations seems to be possible, particularly for certain regions and seasons, given persistence or predictability of climate modes with which these fluctuations are associated.

When limited area models of the hydrodynamics of the atmosphere and of the ocean are 1 run over an extended time, variability unrelated to external "drivers" emerge - this variability is 2 colloquially named "hydrodynamical noise" or just "noise". This article summarises what we have 3 learned in the past few years about the properties of such noise, and the implications for numerical 4 experimentation and analysis. The presence of this noise can be identified easily in ensembles of 5 numerical simulations, and it turns out that the intensity of the noise is closely linked to the scale- 6 dependent "memory". At the system level, this "memory" term as given by Hasselmann’s Stochastic 7 Climate model plays a key role. In the case of marginal seas, the process of baroclinic instability 8 modulated by tides and the formation of seasonal thermoclines are significant aspects. Some more 9 general aspects are discussed, such as the applicability of the Stochastic Climate model to systems 10 outside of atmospheric and oceanic dynamics, the irreversibility of tipping points and the challenges 11 of detecting changes beyond a noise level and of the attribution of causes of change.

Stumbling during gait is commonly encountered in patients who suffer from mild to serious walking problems, e.g. after stroke, in osteoarthritis, or amputees using a lower leg prosthesis. Instead of self-reporting, an objective assessment of the amount of stumbles in daily life would inform clinicians more accurately and enable the evaluation of treatments that aim to achive a safer walking pattern. An easy to use wearable might fullfill this need. The goal of the present study was to investigate whether a single inertial measurement unit (IMU) placed at the shank and machine learning algorithms could be used to detect and classify stumbling events in a dataset comprising of a wide variety of daily movements. Ten healthy test subjects were deliberately tripped by an unexpected and unseen obstacle while walking on a treadmill. The subjects stumbled a total of 276 times, both using an elevating recovery strategy and a lowering recovery strategy. Subjects also performed multiple Activities of Daily Living. During data processing, an event-defined window segmentation technique was used to trace high peaks in acceleration which could potentially be stumbles. In the reduced dataset, time windows were labelled with the aid of video annotation. Subsequently, discriminative features were extracted and fed to train seven different types of machine learning algorithms. Trained machine learning algorithms were validated using leave-one-subject-out cross-validation. Support Vector Machine (SVM) algorithms were most succesful, and could detect and classify stumbles with 100% sensitivity, 100% specificity and, 96.7% accuracy, in the independent testing dataset. The SVM algorithms were implemented in a user-friendly, freely available, stumble detection app named Stumblemeter. This work shows that stumble detection and classification based on SVMs is accurate and ready to apply in clinical practise.

The question whether a given set of test items can be considered “identical” is often addressed in terms of the homogeneity of the test material from which said items were taken. However, for some types of matrices – in particular, for matrices consisting of minute separate particles, only some of which carry the analyte under consideration – even in the case of homogenous test material, an irreducible source of variability between test items may remain: the fundamental variability. In this paper, the concept of fundamental variability is explained, and procedures for reducing and characterizing it are described.

We discuss what we believe could be an improvement in future discussions of the ever-changing brain. We do so by distinguishing different types of brain variability and outlining methods suitable to analyse them. We argue that, when studying brain and behaviour data, classical methods such as regression analysis and more advanced approaches both aim to decompose the total variance into sensible variance components. In parallel, we argue that a distinction needs to be made between innate and acquired brain variability. For varying high-dimensional brain data, we present methods useful to extract their low-dimensional representations. Finally, to trace potential causes and predict plausible consequences of brain variability, we discuss how to combine statistical principles and neurobiological insights to make associative, explanatory, predictive, and causal enquires; but cautions are needed to raise association- or prediction-based neurobiological findings to causal claims.

Rainfall variability has resulted in extreme events like devastating floods and droughts which is the main cause of human vulnerability to precipitation in West Africa. Attempts have been made by previous studies to understand rainfall variability over Ghana but these have mostly focused on the major rainy season of April-July, leaving a gap in our understanding of the variability in the September-November season which is a very important aspect of the Ghanaian climate system. The current study seeks to close this knowledge gap by employing statistical tools to quantify variabilities in rainfall amounts, rain days, and extreme precipitation indices in the minor rainfall season over Ghana. We find extremely high variability in rainfall with a Coefficient of variation (CV) between 25.3% and 70.8%, and moderate to high variability in rain days (CV=14.0% - 48.8%). Rainfall amount was found to be higher over the middle sector (262.7 mm – 400.2 mm) but lowest over the east coast (125.2 mm – 181.8 mm). Analysis of the second rainfall season using the Mankandell Test presents a non-significant trend of rainfall amount and extreme indices (R10, R20, R99p, and R99p) for many places in southern Ghana. Rainfall Anomaly Indices show that the middle sector recorded above normal precipitation which is the opposite for areas in the transition zone. The result of this work provides a good understanding of rainfall in the minor rainfall season and may be used for planning purposes.

This article shortly introduces Gaussian processes as a new approach for modelling time series in the field of blazar physics. In the second part of the paper, recent results from an application of GP modelling to the multi-wavelength light curves of the blazar PKS 1502+106 are discussed.

Abrus precatorius is a medicinal herb originated from Southeast Asia and native to India. The Hindustani centre of origin was found to possess lot of variability especially with respect to seed color. However, no previous researchers have focused on studying the variability by including the entire variability of the region. A total of 99 accessions were analyzed for its biochemical components like moisture content, total phenols, antioxidants, ash content, protein content, total monomeric anthocyanin and flavonols. Principal component analysis (PCA) shown that first three components viz., seed color, phenols and antioxidants are major principal components that contribute to 80.86% of total variability in the germplasm. The dendrogram constructed based on the biochemical data and by using the software Darwin version 6.0. formed three main clusters i.e. cluster 1, cluster 2 and cluster 3 which contain 55 accessions, 40 accessions and 1 accession respectively. Seed color was found to be the main criteria based on which the Abrus accessions were grouped. Accessions from different clusters also differ for their mean phytochemical constituents. Germplasm curators / plant breeders can select such elite genotypes and utilize them in crop improvement programmes.

Cassava brown streak disease (CBSD) threatens cassava production in sub-Saharan Africa despite the availability of resistant varieties since extreme environmental factors weakens plant defenses hence reduce CBSD resistance. This study examined the inheritance of CBSD in cassava populations, assessed genetic variability and identified superior sources of resistance through F1, S1 and half-sib offspring of populations derived from resistant sources. The offsprings underwent field evaluation at two distinct sites from 2019 to 2021, and the symptoms free genotypes were analyzed using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Resistance to CBSD was categorized as most resistant, resistant, most tolerant and tolerant based on symptoms and virus titer. The findings of the study indicate that the resistance to Cassava Brown Streak Disease (CBSD) is highly influenced by genotypes, F1/S1 types, and environmental conditions. The analysis of combining abilities revealed significant general combining abilities (GCA) for CBSD, cassava mosaic disease (CMD), and traits associated with yield. The heritability estimates for resistance to CBSD varied between 43.4% to 63.2% for foliar symptoms and 14.6% to 57.9% for root necrosis across locations. The inheritance pattern involved a combination of additive and recessive genes and selfed (S1) populations displayed stronger and effective resistance to the disease. There was a high prevalence of cassava brown streak virus (CBSV) and a low prevalence of Ugandan cassava brown streak virus (UCBSV). Four genotypes were identified to be highly resistant to Cassava Brown Streak Disease (CBSD) that could be used as key sources of resistance to CBSD.

About 70% of children and adolescents with cerebral palsy experience gait impairments which affect their autonomy and well-being. Robotic-assisted gait training using the Lokomat is particu-larly promising for rehabilitation as it provides a standardized environment favoring the massive repetition of the movement, in which physical demands are low on the therapist and high training loads can be achieved. As no guidelines exist regarding training protocols and Lokomat settings, the goal of this study was to review the literature on Lokomat-assisted gait therapy and possibly make training recommendations. The twelve studies reviewed reported both positive and null effects of Lokomat training on gait. Half of the studies combined Lokomat with other types of training and only five used a control intervention to assess its benefit. Overall, training was administered 1-5 times per week for 20-60 minutes, over 1-12 weeks. Although Lokomat settings were not always described, progressively decreasing body-weight support and guidance, while increasing treadmill speed appear to be prioritized. The variety of training protocols and settings used did not allow pooling of the studies to assess effects of interventions on gait parameters in children and adoles-cents with cerebral palsy. This review highlights the need for homogenization of interventions so that clear guidelines can emerge and be applied in rehabilitation centers.

Antibiotic resistance is a persistent and growing concern. Our objective was to analyze antibiotic prescribing in the United States (US) in the Medical Expenditure Panel System (MEPS) and to Medicaid patients. We obtained total MEPS prescriptions for eight antibiotics from 2013 to 2020. We extracted prescribing rates per 1,000 Medicaid enrollees for two years, 2018 and 2019, for four broad spectrum (azithromycin, ciprofloxacin, levofloxacin, and moxifloxacin) and four narrow spectrum (amoxicillin, cephalexin, doxycycline, and trimethoprim/sulfamethoxazole) antibiotics. Antibiotics in MEPS decreased from 2013 to 2020 by -38.7% with a larger decline for broad (-53.7%) than narrow (-23.5%) spectrum. Antibiotic prescriptions in Medicaid decreased by -6.7%. Amoxicillin was the predominant antibiotic followed by azithromycin, cephalexin, trimethoprim/sulfamethoxazole, doxycycline, ciprofloxacin, levofloxacin, and moxifloxacin. Substantial geographic variation in antibiotic prescribing existed with 2.8-fold between the highest (Kentucky = 855/1,000) and lowest (Oregon = 299) states. The South prescribed 52.2% more antibiotics (580/1,000) than the West (381/1,000). There were significant correlations across states in antibiotic prescribing. This study identified sizable disparities by geography in prescribing rates of eight antibiotics with over three-fold state level differences. Areas with high antibiotic prescribing rates, particularly for outpatients, may benefit from stewardship programs to reduce potentially unnecessary prescribing.

In this work, an embroidered textile moisture sensor is presented. The sensor is based on a capacitive interdigitated structure embroidered on a cotton substrate with an embroidery conductor yarn composed by 99% pure silver plated nylon yarn 140/17 dtex. In order to evaluate the sensor sensitivity, the impedance of the sensor has been measured by means of a LCR meter from 20 Hz to 20 kHz on a climatic chamber with a sweep of the relative humidity from 25% to 65% at 20 ºC. The experimental results show a clear and controllable dependence of the sensor impedance with the relative humidity. Moreover, the reproducibility of the sensor performance subject to the manufacturing process variability and washing process is also evaluated. The results show that the manufacturing variability introduce a moisture measurement error up to 4%. The washing process impact on the sensor behavior after applying the first washing cycle implies a sensitivity reduction higher than 14%. Despite these effect, the textile sensor keeps its functionality and can be reused in standard conditions. Therefore, these properties point out the usefulness of the proposed sensor to develop wearable applications on health and fitness scope including the user needs to have a life cycle longer than one-time use

In Shark Bay, a large hypersaline bay in Western Australia, longitudinal density gradients force gravitational circulation that is important for Bay-ocean exchange. Observations of vertical stratification and velocity are presented, confirming a steady near-bed dense water outflow from Shark Bay’s northern Geographe Channel that persisted through all stages of the tide. Outflow velocities were 2–3 times stronger than the outflows recorded previously in Naturaliste Channel (in the west) and were more resistant to breakdown by tidal mixing. Estimates of turbulent kinetic energy production derived from ADCP data using the variance method showed a more complex structure in Geographe Channel, due to shear associated with the stratified conditions, with peak levels of turbulence occurring during reversal of tidal flows. For both channels the main source of turbulence was tidal flow along the seabed, with the bottom current speed cubed, |U_b³|, providing a reasonable proxy for tidal mixing and prediction of dense water outflows from Shark Bay the majority of the time. Orientation and deeper water of Geographe Channel along the main axis of the longitudinal density gradient provided an explanation for the predominant outflow from the Bay’s northern entrance. These density-driven currents could potentially influence recruitment of commercially fished scallops and prawns through dispersal and flushing of larvae.

Ankle sprains are the most frequently occurring musculoskeletal injuries among recreational athletes. Ankle support through bandages following the initial orthotic treatment might be beneficial for rehabilitation purposes. Since hardly any study has investigated the impact of bandages in the acute phase of ankle sprains, our study examined the immediate effects of wearing an ankle bandage on fine coordination, proprioception, and motor performance in subjects five weeks after an acute ankle injury. In total, 70 subjects with acute unilateral supination trauma were tested. All subjects completed several rating questionnaires and biomechanical investigations, including a fine coordination and proprioception test, single leg stances, the Y-Balance test and gait analysis. All biomechanical investigations were conducted for the subject's injured leg with and without a bandage (MalleoTrain® Bauerfeind AG) and the healthy leg. Subjects reported moderate to strong improvements in ankle stability and pain when wearing the bandage. Wearing the bandage significantly normalized subjects’ single leg stance performance, as well as the stance phase duration, and the vertical ground reaction forces during walking. However, the bandage did not have a clear effect on fine coordination and proprioception. Wearing a bandage in the acute phase of an ankle sprain may immediately improve motor performance, including standing and walking.

Background: Gait analysis systems offer invaluable insights for rehabilitation, yet their expense limits clinician access. We developed GAITWell®, a low-cost modular system for capturing spatiotemporal gait variables, and evaluated its measurement properties. Methods: The GAITWell® uses discreet binary sensors on interconnected boards to collect gait data, which is then analyzed using the DBSCAN algorithm on the Cartesian points from sensor outputs. Reliability was assessed using ICC2,1, standard error of the mean (SEM) and Bland-Altman plots. Validity was determined by comparing GAITWell® with the Qualisys Pro-Reflex system. Results: Participated 38 healthy adults, with an average age of 33.2 years (SD 13.0). Correlations between GAITWell® and the Qualisys system ranged from moderate to very high for most gait variables, with the exception of stride length, which demonstrated a low but significant correlation (r = .360, p &lt; .05). The ICC2,1 indicated moderate to good agreement for most gait variables. Stance and double support times, cadence, and base of support exhibited poor reliability, characterized by larger SEM and limits of agreement. Conclusions: Our findings indicate that the GAITWell® system is a promising tool for gait analysis. Future research will enhance sensor accuracy and refine algorithms to improve reliability.

In recent years, both domestic and international research on quadruped robots has advanced towards high dynamics and agility, with a focus on high-speed locomotion as a representative motion in high-dynamic activities. Quadruped animals like cheetahs exhibit high-speed running capabilities, attributed to the indispensable role played by their flexible spines during the flight phase motion. This paper establishes dynamic models of quadruped robots with different degrees of spine flexibility, providing a parameterized description of the flight phase motion for both rigid trunks and flexible spine quadruped robots. By setting different initial values for the spine joint and calculating the flight phase results for both types of robots at various initial velocities, the study compares and analyzes the impact of a flexible spine on the flight phase motion of quadruped robots. Through comparative experiments, the research aims to validate the influence of a flexible spine during the flight phase motion, providing insights into how spine flexibility affects the flight phase motion of quadruped robots.

This study examines the effects and durability of postural exercise on gait kinematics in people with intellectual and developmental disabilities (IDD). Thirty-four men with mild IDD were assigned to either the training group (n = 19) or the control group (n = 15). The TG performed the intervention over 8 weeks, 3 days/week, 1 h/day. The results indicated that the intervention program had a significant effect on some variables of gait. Also, in the TG between post-test and follow-up, there was no significant difference, which indicated that gait variables were maintained by the TG one month after the end of the program. This study provides evidence that postural exercises can be used as an effective intervention for improving gait in individuals with IDD.

Freezing of Gait (FOG) is an impairment that affects the majority of patients in the advanced stages of Parkinson’s Disease (PD). FOG can lead to sudden falls and injuries, negatively impacting the quality of life for the patients and their families. Rhythmic Auditory Stimulation (RAS) can be used to help patients recover from FOG and resume normal gait. RAS might be ineffective due to the latency between the start of a FOG event, it’s detection and initialization of RAS. We propose a system capable of both FOG prediction and detection using signals from tri-axial accelerometer sensors that will be useful in initializing RAS with minimal latency. We compared the performance of several time frequency analysis techniques, including moving windows extracted from the signals, handcrafted features, Recurrence Plots (RP), Short Time Fourier Transform (STFT), Discreet Wavelet Transform (DWT) and Pseudo Wigner Ville Distribution (PWVD) with Deep Learning (DL) based Long Short Term Memory (LSTM) and Convolutional Neural Networks (CNN). We also propose three Ensemble Network Architectures that combine all the time frequency representations and DL architectures. Experimental results show that our ensemble architectures significantly improve the performance compared with existing techniques. We also present the results of applying our method trained on publicly available dataset to data collected from patients using wearable sensors in collaboration with A.T. Still University.

We present a study of the radio variability of bright, $S_{1.4}\geq100$ mJy, high-redshift quasars at $z\geq3$ on timescales up to 30--40 years. The study involved simultaneous RATAN-600 measurements at frequencies of 2.3, 4.7, 8.2, 11.2, and 22.3 GHz in 2017--2020. In addition, data from the literature were used. We have found that the variability index $V_S$ of the quasars ranges from 0.02 to 0.96, with about half of the objects in the sample showing a variability index in the range of 0.25--0.50, which is comparable to that of the blazars at lower redshifts. The distribution of $V_S$ at 22.3 GHz is significantly different from that at 2.3--11.2 GHz, which may be attributed to the fact that a compact AGN core dominates at the source's rest frame frequencies greater than 45 GHz, leading to higher variability indices obtained at 22.3 GHz (the $V_S$ distribution peaks around 0.4) compared to the lower frequencies (the $V_S$ distribution peaks around 0.1--0.2). Several source groups with distinctive variability characteristics were found using cluster analysis of quasars. We propose 7 new candidates for gigahertz peaked-spectrum (GPS) sources and 5 new megahertz peaked-spectrum (MPS) sources based on their spectrum shape and variability features. Only 6 out of 23 sources previously reported as GPS demonstrate a low variability level typical of classical GPS sources ($V_{S} < 0.25$) at 4.7--22.3~GHz. When excluding the highly variable peaked-spectrum blazars, we expect no more than 20\% of the sources in the sample to be GPS candidates and no more than 10\% to be MPS candidates.

We present a method to study the interannual variability of the annual cycle. The method consists of first determining the amplitude and phase of segments of 12 monthly means at all spatial points, resulting in one complex number per grid point and per year. The complex fields, once per year, are then subject to a complex EOF (CEOF) analysis. We consider as an example the barotropic stream function in the South China Sea as simulated with an ocean general circulation model across 6 decades of years, driven my realistic (NCEP) weather forcing. We find 3 to 4 to “significant” CEOFs, which account for about 53 to 62% of variance. These CEOFs go with large-scale patterns. Their time coefficients are mostly stationary, but point to some inhomogeneities related to instationarities in the forcing. In particular, the simulation since 1950-1958 deviates from the remainder of the simulation. The first CEOF describes variations in the center of the South China Sea. Its principal component describes a systematic, albeit noisy shift by almost 180o from 1960 to about the year 2000. When overlaid the long-term mean annual mean, the overall change consists of an amplification of the annual cycle in the 1960s and 1990s, whereas In the 1970s, the amplitude was reduced. Phase shifts in the anomaly (given by the CEOFs) have a small effect, because of the dominance of the mean annual cycle. These variations are not related to ENSO variability but may origin in variations of the Southeast monsoon. The second EOF represents strong changes, both in terms of intensity and phase, in the Luzon strait.

The way in which a person walks, known as human gait, is a significant indicator of overall health and well-being. Abnormalities in gait can indicate the presence of metabolic disorders, such as diabetes or obesity. However, detecting these disorders can be challenging using traditional methods, which often involve subjective assessments or invasive procedures. In this study, a novel methodology known as Criticality Analysis (CA) was proposed for the detection and monitoring of human gait in people with metabolic disorders taking part in an intervention to increase activity and reduce weight. The CA approach utilised inertial measurement unit gait data, alongside clinical health measures. This allows for the control of nonlinear growth in the system, resulting in lower dimensional, nonlinear, free-scale, stable, controlled, and organised trajectories. These trajectories were then analysed using a Support Vector Machine (SVM) algorithm, which is well-suited for this task due to its ability to handle nonlinear and dynamic data. The combination of the CA approach and the SVM algorithm demonstrated high accuracy and non-invasiveness in detecting metabolic disorders, yielding an average accuracy within the range of 78.2% to 90%. Additionally, the classification technique accuracy, at a group level was observed to reduce during period of the intervention (e.g., from week 2 to week 3) alongside changes in fitness and health, which indicates the potential of using the approach to measure and monitor biological systems. As such, this novel methodology has the potential to be a valuable tool for healthcare professionals in detecting and monitoring metabolic disorders, as well as other unknown diseases associated with the human biological system.

Understanding the motor patterns underlying the movement of people with Parkinson's disease (PD) is fundamental to the effective targeting of non-pharmacological therapies. This study aims to analyze the gait pattern in relation to the evolutionary stage between I-II and III-IV according to the Hoehn and Yahr scale (H&amp;Y) in people affected by PD. The study was conducted with the participation of 37 PD patients, with a mean age of 70.09±9.53 years, and of whom 48.64% were women. The inclusion criteria were: 1. To be diagnosed with PD; 2. To be in an evolutionary stage of the disease of between I and IV and; 3. To be able to walk independently and without any assistance. Kinematic and spatial-temporal parameters of the gait were analyzed. The results show differences in speed of movement, cadence, stride length, support duration, swing duration, step width, walking cycle duration and double support time between the stages analyzed. These results confirm the differences in PD gait pattern between stages I-II and III-IV. Different behaviors of the same variable were recorded depending on whether the right or left sides were affected by PD.

Motor functions are deteriorated by aging. Some conditions may magnify this deterioration. To examine whether hemodialysis (HD) process would negatively impact gait and balance beyond diabetes condition among mid-age adults (48-64 years) and older adults (65+ years). One hundred and ninety-six subjects (age=66.2±9.1 years, body-mass-index=30.1±6.4 kg/m², female=56%) in 5 groups were recruited: mid-age adults with diabetes undergoing HD (Mid-age HD+, n=38) and without HD (Mid-age HD-, n=40); older adults with diabetes undergoing HD (Older HD+, n=36) and without HD (Older HD-, n=37); and non-diabetic older adults (Older DM-, n=45). Gait parameters (stride velocity, stride length, gait cycle time, and double support) and balance parameters (ankle, hip, and center of mass sways) were quantified using validated wearable platforms. Groups with diabetes had overall poorer gait and balance compared to the non-diabetic group (p<0.050). Among people with diabetes, the HD+ had significantly worsened gait and balance when comparing to the HD- (Cohen’s effect size d=0.63-2.32, p<0.050). Between-group difference was more pronounced among older adults with the largest effect size observed for stride length (d=2.32, p<0.001). Results suggested that deterioration in gait speed among the HD+ was correlated with age (r=-0.440, p<0.001), while this correlation was diminished among the HD-. Interestingly, results also suggested that poor gait in the Older HD- related to poor balance, while no correlation was observed between poor balance and poor gait among the Older HD+. Using objective assessments, results confirmed that the presence of diabetes can deteriorate gait and balance, and this deterioration can be magnified by HD process. Among non-HD people with diabetes, poor static balance described poor gait. However, among people with diabetes undergoing HD, age was a dominate factor describing poor gait irrespective of static balance. Results also suggested feasibility of using wearable platforms to quantify motor performance during routine dialysis clinic visits. These objective assessments may assist in identifying early deterioration in motor function, which in turn may promote timely intervention.

Sesame (Sesamum indicum), a highly valued oilseed, faces challenges in cultivation, especially in regions susceptible to environmental stressors. This study investigates the interactive effects of salinity and temperature on sesame seed germination. Two cultivars, Darab 1 and Oltan, were subjected to various salinity levels (-3 to -12 bars) and temperatures (15°C, 20°C, and 25°C). Results revealed that at 15°C, salinity levels beyond -3 bars significantly reduced germination, while at 25°C, 40% and 62% germination rates were recorded even at -12 bars for Darab 1 and Oltan, respectively. The study highlights the importance of temperature in mitigating the inhibitory effects of salinity on germination. Germination speed exhibited a decline with increasing salinity, particularly at lower temperatures. Shoot and root lengths and dry weights decreased with rising salinity, but Oltan demonstrated greater tolerance than Darab 1. The research emphasises the species-specific nature of temperature-salinity interactions and the intraspecific variability among sesame cultivars. Notably, Oltan, adapted to arid regions with elevated temperatures, displayed increased tolerance to salinity stress. The findings contribute to understanding sesame's resilience to environmental stressors, aiding in developing resilient cultivars for challenging agricultural landscapes. Overall, temperature is pivotal in influencing sesame seed germination and early seedling growth under salinity stress, offering insights for optimised cultivation practices.

Following the central dogma of molecular biology, gene expression variability can aid in predicting and explaining the wide variety of protein products, functions, and, ultimately, variability in phenotypes. There is currently overlapping terminology used to describe the types of variability in gene expression profiles, and overlooking these nuances can misrepresent important biological information. Here, we describe transcriptional diversity as quantifying transcriptional changes as a measure of the variability in 1) the total expression of all genes or a gene across samples (transcriptome diversity) or 2) the isoform-specific expression of a given gene (isoform diversity). We first overview modulators and quantification of gene expression variability. Then, we discuss the role alternative splicing plays in driving transcript isoform expression variability and how isoform diversity can be quantified. Additionally, we overview computational resources for calculating transcriptome and isoform diversity for short- and long-read sequencing data. Finally, we discuss future applications of transcriptional diversity. This review provides a comprehensive overview of how gene expression variability arises, and how measuring it determines a more complete picture of heterogeneity across proteins, cells, tissues, organisms, and species

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) challenges include understanding what triggered SARS-CoV-2 emergence, how this RNA virus is evolving or how the genomic variability may impact the primary structure of proteins that are targets for vaccine. We analyzed 19471 SARS-CoV-2 genomes and 199,984 spike glycoprotein sequences available at the GISAID database from all over the world and 3335 genomes of other Coronoviridae family members available at Genbank, collecting SARS-CoV-2 high-quality genomes and distinct Coronoviridae family genomes. Here, we identify a SARS-CoV-2 emerging cluster containing 13 closely related genomes isolated from bat and pangolin that showed evidence of recombination, which may have contributed to the emergence of SARS-CoV-2. The analyzed SARS-CoV-2 genomes presented 9632 single nucleotide polymorphisms (SNPs) corresponding to a variant density of 0.3 over the genome, and a clear geographic distribution. SNPs are unevenly distributed throughout the genome and hotspots for mutations were found for the spike gene and ORF 1ab. We describe a set of predicted spike protein epitopes whose variability is negligible. All predicted epitopes for the structural E, M and N proteins are highly conserved. This result favors the continuous efficacy of the available vaccines.

Dengue hemorrhagic fever is an arboviral infectious disease that has occurred frequently as an extraordinary event due to its fast spread and lethal potential in Indonesia. The vector Aedes aegypti is sensitive to climate variability. This study determines the relationship between climate variability and dengue hemorrhagic fever in Surabaya, East Java, Indonesia from 2009 to 2017. This study used the monthly dengue hemorrhagic fever incidence obtained from the Surabaya Health Office and the monthly climate variability parameters (average temperature, rainfall, humidity) obtained from the Indonesian Agency for Meteorology, Climatology and Geophysics and website www.worldweatheronline.com. Data analysis was done using One-Sample Kolmogorov Smirnov Test and Spearman non-parametric correlation test. The results showed a correlation between all three climate variability parameters with dengue hemorrhagic fever incidence (average temperature p<0.05, r=-0.603; rainfall p<0.05, r=0.407; humidity p<0.05, r=0.7). Average temperature is negatively correlated to dengue hemorrhagic fever incidence, while rainfall and humidity are positively correlated to dengue hemorrhagic fever incidence. This study shows preliminary evidence on the correlation of climate variability and dengue hemorrhagic fever in Surabaya, East Java, Indonesia.

Dengue hemorrhagic fever is an arboviral infectious disease that has occurred frequently as an extraordinary event due to its fast spread and lethal potential in Indonesia. The vector Aedes aegypti is sensitive to climate variability. This study determines the relationship between climate variability and dengue hemorrhagic fever in Surabaya, East Java, Indonesia from 2009 to 2017. This study used the monthly dengue hemorrhagic fever incidence obtained from the Surabaya Health Office and the monthly climate variability parameters (average temperature, rainfall, humidity) obtained from the Indonesian Agency for Meteorology, Climatology and Geophysics and website www.worldweatheronline.com. Data analysis was done using One-Sample Kolmogorov Smirnov Test and Spearman non-parametric correlation test. The results showed a correlation between all three climate variability parameters with dengue hemorrhagic fever incidence (average temperature p<0.05, r=-0.603; rainfall p<0.05, r=0.407; humidity p<0.05, r=0.7). Average temperature is negatively correlated to dengue hemorrhagic fever incidence, while rainfall and humidity are positively correlated to dengue hemorrhagic fever incidence. This study shows preliminary evidence on the correlation of climate variability and dengue hemorrhagic fever in Surabaya, East Java, Indonesia.

Background Some patients with mild cognitive impairment (MCI) experience gait disturbances. However, there are few reports on the relationship between gait disturbance and cognitive function in patients with MCI. Therefore, we investigated the neural correlates of gait characteristics related to cognitive dysfunction. Methods Eighty patients diagnosed with MCI from three dementia centres in Gangwon-do, Korea were recruited for this study. We defined MCI as a Clinical Dementia Rating global score of 0.5 or higher, with a memory domain score of 0.5 or greater. The patients were classified as having either early or late MCI based on their Mini Mental Status Examination z-scores. Multiple logistic regression analysis was performed to examine the association between the gait characteristics and cognitive impairment. Analyses included variables such as age, sex, years of education, number of comorbidities, body mass index and height. Results Gait velocity, step count, step length, heel-to-heel base support, swing and stance phase duration, and support time were associated with cognitive function. A decrease in gray matter volume in the right pericalcarine area was associated with gait characteristics related to cognitive dysfunction. An increase in the curvature of gray matter in the right entorhinal, right lateral orbitofrontal, right cuneus, and right and left pars opercularis areas was also associated with gait characteristics related to cognitive dysfunction. Conclusion Since gait impairment is an important factor in determining activities of daily living in patients with mild cognitive impairment, the evaluation of gait and cognitive functions in patients with mild cognitive impairment is important.

AYUMI EYE is an accelerometer-based gait analysis device that measures the 3D accelerations of the human trunk. This study investigated the measurement accuracy of the AYUMI EYE as hardware as well as the accuracy of the gait cycle extraction program via simultaneous measurements using AYUMI EYE, a ground reaction force (GRF), and an optical motion capture system called VICON. The study was conducted with four healthy individuals as participants. The gait data were obtained by simulating four different patterns for three trials each: normal walking, anterior-tilt walking, hemiplegic walking, and shuffling walking. The AYUMI EYE and VICON showed good agreement for both the acceleration and displacement data. The durations of subsequent stride cycles calculated using the AYUMI EYE and GRF were in good agreement based on the calculated cross-correlation coefficients (CCs) with an r value of 0.896 and p-value less than 0.05, and their accuracies for these results were sufficient.

Studies on the gait's parameters have been identified on the patients population. Most researchers confirm that the patients walk differently than normal people and they may have a risk for falls. Consistent finding and description of gender, age, and body mass index differences in gait studies is rare in healthy subjects. A cross-sectional study with forty-five young adult (F = 20, M = 25) was conducted. Stadiometer and Physilog 4 inertial sensors were used for data collection. A gait analyser 5.2 software (GaitUp, S.A. Lausanne, Switzerland) was used to determine spatiotemporal parameters. No statistically significant differences were found in any bilateral foot gait parameters with respect to gender, age, and body mass index. Females are found with higher total double support and cadence than males. Cadence also increases with age. Obese people showed lower gait speed, cadence, and total double support. These findings may be beneficial to those who have abnormal gait pattern due to age, body mass index differences, decreased muscle strength, spasticity, and joint mobility. This important informations should be considered to rehabilitate patients with abnormal gait patterns to controlling dynamic balance and riks to falling.

Running on a non-motorized, curved-deck treadmill is thought to improve gait mechanics. It is not known, though, if the change in gait carries over to running on a motorized treadmill or level ground. To determine the effect of running on a curved non-motorized treadmill (CNT) on gait characteristics measured during a subsequent bout of running on a traditional motorized treadmill (TMT). Sixteen healthy college-aged participants, age (mean±SD) 20.4±1.6 years volunteered to have their gait analyzed while running on a TMT and CNT. After familiarization and warm-up on both treadmills, each subject completed five, 4-minute bouts of running alternating between traditional motorized and curved non-motorized treadmills: TMT-1, CNT-1, TMT-2, CNT-2, and TMT-3. Variables of interest included step length (m), stride length (m), imbalance score (%), and step angle (°) and were measured using Optogait gait analysis equipment. Differences in gait char acteristics among TMT-1, TMT-2, and TMT-3 can be attributed to running on the CNT. The results show that running on a CNT resulted in significant changes in gait characteristics. These findings suggest that running on a CNT can significantly alter gait characteristics may result in improvements in running gait that persist to subsequent running on a TMT.

Variability is the predisposition of phenomena to assume different values over time. Variability is higher when the differences of cases from each other are larger or diverge from a specific value, such as arithmetic mean. This study focuses on the variability of research topics within and between research fields to explain, whenever possible, how the variability shapes the structure and dynamics of technological trajectories. Analysis of variability here applies the entropy and variance decomposition on main research fields in quantum technologies. Empirical evidence shows that variability in research topics is inversely proportional to the age of research fields. Inductive implications are that higher variability in research topics of recent scientific fields is due to uncertain dynamics that generates a heterogeneity of different technological trajectories some of them can growth and develop towards fruitful directions others can be dismissed. Hence the variability seems to be one of the drivers that shapes technological evolution and can provide policy and managerial implications to improve the scientific and technological forecasting that may support appropriate decisions of R&D investments towards promising research fields and technologies.

A proposed interpretation of the characteristics and causes of the variation in science dynamics for technological evolution is described. The theoretical approach focuses on variability in research topics that guide scientific and technological evolution. Statistical method verifies the proposed approach by applying entropy, measures of dispersion and variance decomposition. The statistical evidence, using data of four main research fields in quantum technologies, suggests the following empirical properties: a) the growth of heterogeneity in research topics is inversely proportional to the age of research fields: recent research fields have a higher variability between topics with uncertainty in evolutionary dynamics, whereas older research fields have a lower variability and more concentration in specific research topics with stable evolution towards clear directions; b) the nature of research fields has a systematic effects in variability guiding the evolution of technologies. The theoretical approach and findings clarify main characteristics and causes of the evolution of science and technologies considering the underlying homogeneity or heterogeneity in research topics, providing main implications to improve the scientific and technological forecasting that may support appropriate R&amp;D investments towards promising research fields and technologies

The purpose of this scoping review was to examine the literature on the use of anti-gravity treadmill and its effects on lower limb motor functions in children and adolescents with locomotor impairments. Four databases (MEDLINE, CINAHL, Embase, Web of Science) were searched for articles from inception to August 2021. Inclusion criteria were: (1) experimental or quasi-experimental studies using the anti-gravity training as the primary intervention; (2) studies conducted in paediatricpediatric participants; (3) articles reporting outcomes related to the lower limb functions; and (4) studies published in French or English. Fifteen articles were included in the review. Studies included children and adolescents aged 4–18 years with locomotor impairments. The intervention duration was ranged from 2 and to 12 weeks, with 2-5 sessions per week. Included studies showed reported that anti-gravity training induces improvements in muscle strength, balance, spatiotemporal gait parameters, and walking endurance in children with locomotor impairments. This review provides relevant information about the modalities, outcomes and limits associated with the anti-gravity training protocol reported in the literature. Overall, the anti-gravity treadmill training could be viewed as a valuable training modality for children with cerebral palsy. However, more precise, and comprehensive description of anti-gravity rehabilitation protocols would be useful.

Background and Objectives: Sports medicine, orthopaedic and rehabilitation physicians use gait analysis and goniometry to evaluate and diagnose patients with neuro-musculo-skeletal diseases. Goniometry is a measuring method that shows the joint’s range of motion. Three-dimensional goniometry has been used in order to assess the patients in a kinematic manner, but they are not affordable, so, phone apps come handy to any orthopaedic or rehabilitation physician so we can have a clear image of the progress made by the patient after the rehabilitation program or should something happen and the patient cannot come to the facility, such as the Covid-19 pandemic, when some orthopaedic and most of the rehabilitation facilities have been temporarily closed. Midstance has been chosen as the moment of the gait evaluation in this paper since it has an important role in stability. The objective of this paper is to figure out if the measurements taken during midstance at the knee joint of the subjects can be statistically significant and used during usual examinations. Materials and Methods: Four groups of subjects: patients suffering from hip, knee, hip and knee osteoarthritis and a control group volunteered their participation, being asked to normally walk while their gait was recorded and uploaded into Angles App – a phone based videogoniometer. Results: Patients suffering from hip osteoarthritis have a higher knee angle on the right side than the ones suffering from knee osteoarthritis, hip and knee osteoarthritis and the control group. Female patients suffering from hip osteoarthritis also presented a more flexed knee than the ones suffering from knee osteoarthritis and the ones in the control group, the knee flexion presenting itself as a compensation mechanism. Conclusion: Video goniometry can help us make an orthopaedic, rehabilitation or neurology database for each assessment with constant updates of the evolution of the osteoarthritis patient’s treatment.

One control challenge in prosthetic legs is seamless transition from one gait mode to another. User intent recognition (UIR) is a high-level controller that tells a low-level controller to switch to the identified activity mode, depending on the user’s intent and environment. We propose a new framework to design an optimal UIR system with simultaneous maximum performance and parsimony for gait mode recognition. We use multi-objective optimization (MOO) to find an optimal feature subset that creates a trade-off between these two conflicting objectives. The main contribution of this paper is two-fold: (1) a new gradient-based multi-objective feature selection (GMOFS) method for optimal UIR design; and (2) the application of advanced evolutionary MOO methods for UIR. GMOFS is an embedded method that simultaneously performs feature selection and classification by incorporating an elastic net in multilayer perceptron neural network training. Experimental data are collected from six subjects, including three able-bodied subjects and three transfemoral amputees. We implement GMOFS and four variants of multi-objective biogeography-based optimization (MOBBO) for optimal feature subset selection, and we compare their performances using normalized hypervolume and relative coverage. GMOFS demonstrates competitive performance compared to the four MOBBO methods. We achieve a mean classification accuracy of 97.14% ± 1.51% and 98.45% ± 1.22% with the optimal selected subset for able-bodied and amputee subjects, respectively, while using only 23% of the available features. Results thus indicate the potential of advanced optimization methods to simultaneously achieve accurate, reliable, and compact UIR for locomotion mode detection of lower-limb amputees with prostheses.

Gait abnormalities are one of the distinguishing symptoms of patients with Parkinson's disease (PD) that contribute to fall risk. Our study compares the gait parameters of people with PD when they walk through a predefined course without assistance, with a conventional walker, and with a motorized walker under different speed cues. Six PD subjects were recruited at the New York Institute of Technology College of Osteopathic Medicine to participate in this study. Spatial posture and gait data of the test subjects were collected via a VICON motion capture system. We developed a framework to process and extract gait features and applied statistical analysis on these features to examine the significance of the findings. The results showed that motorized walkers with haptic cues significantly improved gait symmetry of PD subjects. Specifically, the asymmetry index of the gait cycle time was reduced from 6.7% when walking without assistance to 0.56% and below when using a walker. Furthermore, the double support time of a gait cycle was reduced by 4.88% compared to walking without assistance.

People with diabetic foot frequently exhibit poor gait and balance. However, there is no review to inform digital biomarkers of poor gait and balance related to diabetic foot, measurable by wearables outside traditional gait laboratories. Such information could assist in designing remote patient monitoring platform to track changes in gait and balance dysfunction among people with diabetic foot for timely referral and intervention. Accordingly, we conducted a web-based review using PubMed. Our search was limited to human subjects and English-written papers published in peer-reviewed journals. We identified 20 papers in this review. We found preliminary evidence of digital biomarkers of gait and balance dysfunction in people with diabetic foot, measured by wearables, such as slow gait speed, large gait variability, unstable gait initiation, and large body sway. However, due to heterogeneities in included papers in terms of study design, movement tasks, and small sample size, more studies are recommended to confirm this preliminary evidence. Additionally, based on our review, we recommend establishing appropriate strategies to successfully implement wearable-based assessment into clinical practice for diabetic foot care.

Human footprint is having a unique set of ridges unmatched by any other human being, and therefore it can be used in different identity documents for example birth certificate, Indian biometric identification system AADHAR card, driving license, PAN card, and passport. There are many instances of the crime scene where an accused must walk around and left the footwear impressions as well as barefoot prints and therefore it is very crucial to recovering the footprints to identify the criminals. Footprint-based biometric is a considerably newer technique for personal identification. Fingerprints, retina, iris and face recognition are the methods most useful for attendance record of the person. This time world is facing the problem of global terrorism. It is challenging to identify the terrorist because they are living as regular as the citizens do. Their soft target includes the industries of special interests such as defense, silicon and nanotechnology chip manufacturing units, pharmacy sectors. They pretend themselves as religious persons, so temples and other holy places, even in markets is in their targets. These are the places where one can obtain their footprints easily. The gait itself is sufficient to predict the behaviour of the suspects. The present research is driven to identify the usefulness of footprint and gait as an alternative to personal identification.

The purpose of this study is to analyze the causes of cost variation in natural disaster prevention projects (NDPP) in Gyeongsangbuk-do and to develop effective cost and risk management strategies. The study collected data by conducting an online survey of 244 stakeholders. Binary logistic regression was used to analyze the impact of various variables on cost deviation, in-cluding project management risk (PMR), project costing and execution risk (PCER), project exe-cution strategy risk (PESR), construction project risk (CPR), project cost and schedule risk (PCSR), project management challenges (PMC), and construction project subcontractor and safety man-agement (CPSSM). The results showed that PMR (OR=3.744, 95% C.I. [1.657, 8.457]), PCER (OR=5.068, 95% C.I. [2.236, 11.484]), PESR (OR=3.447, 95% C.I. [1. 853, 6.413]), CPR (OR=2.292, 95% C.I. [1.020, 5.151]), PCSR (OR=4.817, 95% C.I. [2.250, 10.317]), PMC (OR=2.954, 95% C.I. [1.452, 6. 013]), and CPSSM (OR=2.419, 95% C.I. [1.297, 4.515]) had statistically significant effects on cost deviation. In particular, PMR, PCER, and PESR were identified as the main causes, and the effects of additional factors such as CPSSM were also important. The developed predictive model plays an important role in helping stakeholders of NDPP to manage risks in advance and take appro-priate preventive measures to ensure the success of the project. This study empirically supports the theoretical hypotheses of previous studies and provides a clear understanding of the causes of cost deviation in NDPP, which provides important insights for strategic decision-making and provides a new perspective on risk management.

The mass composition of Particulate Matter (PM) with an aerodynamic diameter of 2.5 microns (PM2.5) in San Joaquin Valley (SJV) is dominated by ammonium nitrate (NH4NO3) which is a secondary pollutant. The goal of this research was the investigation of the relationship between emissions, meteorology and PM2.5 concentrations in Fresno for the winter season. It was found that the location of sites near emission sources such as freeways compared with residential sites strongly affected measured PM2.5 concentrations. It was found that although long-term trends showed declines in both emissions and PM2.5 concentrations there was substantial variability between the years in the PM2.5/emissions relationship. Much of the yearly variation in the relationship between emissions and PM2.5 concentrations can be attributed to yearly variations in weather, such as atmospheric stability, precipitation frequency and average wind speed. There are moderate correlations between PM2.5 concentrations and temperature differences between nearby surface stations at varying elevations which explains some of the daily and seasonal variation in PM2.5. Occurrence of precipitation was related to low PM¬2.5 although the higher wind speeds and lower atmospheric stability associated with precipitation likely explain some of the low PM2.5 as well as washout of PM.

Forest healing effects are increasingly valued for their contribution to human psychological and physiological health, motivating further advances aimed at improving the knowledge of the relevant forest resources. Biogenic volatile organic compounds, emitted by the plants and accumulating in the forest atmosphere, are essential contributors to the forest healing effects, and represent the focus of this study. Using a photoionization detector, we investigated the high frequency variability, in time and space, of the concentration of total volatile organic compounds, on a hilly site, as well as along forest paths and long hiking trails on Italian northern Apennines. The scale of concentration variability was found to be comparable to absolute concentration levels, within time scales of less than one hour, and spatial scales of several hundred meters. During daylight hours, the concentration peaked from noon to early afternoon, followed by early morning, with lowest levels in late afternoon. Based on a conceptual model, these results were related to meteorological variables, including the atmospheric vertical stability profile. Moreover, preliminary evidence pointed to higher concentration of volatile organic compounds in forests dominated by conifer trees, in comparison with pure beech forests.

The use of machine learning techniques in predictive health care is on the rise with minimal data used for training machine-learning models to derive high accuracy predictions. In this paper, we propose such a system, which utilizes Heart Rate Variability (HRV) as features for training machine learning models. This paper further benchmarks the usefulness of HRV as features calculated from basic heart-rate data using a window shifting method. The benchmarking has been conducted using different machine-learning classifiers such as artificial neural network, decision tree, k-nearest neighbour and naive bays classifier. Empirical results using MIT-BIH Arrhythmia database shows that the proposed system can be used for highly efficient predictability of abnormality in heartbeat data series.

Human adaptive responses to climate change occur at the local level, where climatic variability is experienced. Therefore analyzing vulnerability at the local level is important in planning effective adaptation options in a semi-arid environment. This study was conducted to assess vulnerability of Maasai pastoralist communities in Kajiado County, Kenya to climate change by generating vulnerability index for the communities. Data was collected using questionnaires that were administered to 305 households in the five different administrative wards (Oloosirkon/Sholinke, Kitengela, Kapetui North, Kenyawa-Poka and Ilmaroro) in Kajiado East. Vulnerability was measured as the net effect of adaptive capacity, sensitivity and exposure to climate change. Principal Component Analysis (PCA) was used to assign weights to the vulnerability indicators used for the study and also to calculate the household vulnerability index. A vulnerability map was produced using the GIS software package ArcGIS 10.2. Results showed that gender of household head, age of household head, educational level, access to extension agents, herd size, livestock diversity and access to credit facility influenced vulnerability of the Maasai pastoralists to climate change in Kajiado East. The result showed that the most vulnerable communities with the highest negative vulnerability index value are Ilpolosat (-2.31), Oloosirikon (-2.22), Lenihani (-2.05), Konza (-1.81) and Oloshaiki (-1.53). The communities with the highest positive vulnerability index values were Kekayaya (4.02), Kepiro (3.47), Omoyi (2.81), Esilanke (2.23), Kisaju (2.16) and Olmerui (2.15). We conclude that provision of basic amenities such as good roads and electricity; access to extension agents, access to credit facilities and herd mobility will reduce vulnerability of Maasai pastoralists in Kajiado east to climate change and variability.

Gait is a basic cognitive propositive action that has been shown to be altered in late stages of neurodegenerative dementias. Nevertheless, alterations are less clear in mild forms of dementia, and the potential use of gait analysis as a biomarker of initial cognitive decline has hitherto mostly been neglected. We here report the results of a study of gait kinematic time series for two groups of patients (Mild Cognitive Impairment and mild Alzheimer's disease) and a group of matched control subjects. Two metrics based on permutation patterns are considered, respectively measuring the complexity and irreversibility of the time series. Results indicate that kinematic disorganisation is present at early phases of cognitive impairment; in addition, they depict a rich scenario, in which some joint movements display an increased complexity and irreversibility, while others a marked decrease. Beyond their potential use as biomarkers, complexity and irreversibility metrics can open a new door towards the understanding of the role of the nervous system in gait, as well as its adaptation and compensatory mechanisms.

Background: This systematic review aimed to provide a comprehensive overview of the effects of Functional Electrical Stimulation (FES) on gait characteristics in healthy individuals. Methods: Six electronic databases (PubMed, Embase, Epistemonikos, PEDro, COCHRANE Library, Scopus) were searched for studies evaluating the effects of FES on spatiotemporal, kinematic and kinetic gait parameters in healthy individuals. Two examiners evaluated the eligibility and quality of included studies using the PEDro scale. Results: A total of 15 studies met the inclusion criteria. Findings from the literature reveal that FES can be used to modify lower-limb joint kinematics, i.e., to increase or reduce the range of motion of hip, knee and ankle joints. In addition, FES can be used to alter kinetics parameters, including ground reaction forces, center of pressure trajectory, or knee joint reaction force. As a consequence of these kinetics and kinematics changes, FES can lead to changes in spatiotemporal gait parameters, such as gait speed, step cadence, and stance duration. Conclusion: The findings of this review improve our understanding of the effects of FES on gait biomechanics in healthy individuals, and highlight the potential of this technology as a training or assistive solution for improving gait performance in this population.

Formula feeding, as an alternative to breastfeeding, offers benefits such as convenience and consistent nutrition. Among the drawbacks of formula feeding, however, is potential dilution or concentration errors in the of formula during preparation that may lead to infant health issues. The present study aimed to investigate the accuracy of caregiver measurements as they prepared infant formula under multiple conditions, compared with manufacturer specifications. A diverse sample of caregivers (N = 84) participated in this cross-over experimental study. Participants hand-scooped infant formula powder and poured water to prepare 4oz and 7oz feedings, using both a standardized set of infant formula products and participants’ own products. Linear mixed effects models were used to estimate fixed effects of target amount (4oz versus 7oz) and products (participant versus researcher) on mean absolute percent error (MAPE) of measurement. Across all conditions MAPE was significantly greater for measuring powder than for water (9.0% vs. 4.4%; p&lt;0.001) with a combined powder and water MAPE at 13.0%. Greater measurement error was associated with the odd-sized 7oz preparation and participants’ own products. We observed considerable variability and substantial error during infant formula preparation, particularly for hand-scooping of powder, which tended toward higher values than the theoretical gold standard.

A growing number of studies focus on methods to estimate and analyze the functional connectome of the human brain. Graph theoretical measures are commonly employed to interpret and synthesize complex network-related information. While resting state functional MRI (rsfMRI) is often employed in this context, is known to exhibit poor reproducibility, a key factor which is commonly neglected in typical cohort studies using connectomics-related measures as biomarkers. We aimed to fill this gap by analyzing and comparing inter- and intra- subject variability of connectivity matrices as well as graph-theoretical measures in a large (n=1003) database of young healthy subjects which underwent four consecutive rsfMRI sessions. We analyzed both directed (Granger Causality and Transfer Entropy) and undirected (Pearson Correlation and Partial Correlation) time-series association measures and related global and local graph-theoretical measures. While matrix weights exhibit a higher reproducibility in undirected as opposed to directed methods, this difference disappears when looking at global graph metrics and, in turn, exhibits strong regional dependence in local graphs metrics. Our results warrant caution in the interpretation of connectivity studies, and serve as a benchmark for future investigations by providing quantitative estimates for the inter- and intra- subject variabilities in both directed and undirected connectomic measures.

With the continual global increase of PV power systems and the inherent weather-induced volatility of their power output, understanding the underlying variability of solar radiation in both space and time is important for the planning and reliable operation of future power grids. This paper concisely reviews recent advances in the characterization of irradiance variability with an emphasis on small spatial and temporal scales (respectively less than about 10\,km and 1\,min), for which comprehensive data sets are time consuming and expensive to collect, and although needed have not been available until recently. Special attention is given to studies dealing with the quantification of variability using such unique data, the analysis and modeling of spatial smoothing, and the evaluation of temporal averaging.

In the last century, statistical process control has been considered a successful methodology for monitoring the variability and stability of a process over time. The analysis of variability using functional data analysis has become widespread during the early years of the 21st century. The present study proposes the implementation of a hybrid methodology called functional process control based on the functional data analysis methodology and combines its advantages with those of statistical process control, in order to provide a tool for detecting functional deviations. The phases are: (1) stabilization of processes through the identification and elimination of special causes of functional variability; (2) improvement of the process to be controlled by minimizing the common causes of functional variability; and (3) monitoring of the processes to ensure the maintenance or addition of further improvements.

GDF5 gene is involved in the development of skeletal elements, synovial joint formation, tendons, ligaments, and cartilage. Several polymorphisms are present within the gene and two of them, rs143384 and 143383, have been reported as correlated with osteoarticular disease or muscle flexibility. The aim of this research is to verify if the worldwide distribution among human populations of rs143384 polymorphism has been shaped by selective pressure, or if it’s the result of random genetic drift events. Ninety-four individuals of both sexes, 18-28 years old, from Sardinia were analyzed. We observed the following genotype frequencies: 28.72% of homozygotes AA, 13.83% of homozygotes GG, and 57.45% of heterozygotes AG. Allele frequencies were 0.574 for allele A and 0.426 for alle G. Relationships between populations were verified by Multidimensional Scaling (MDS). Our data show: i) a clear heterogeneity within the African populations; ii) a strong differentiation between Africans and the other populations: iii) the Sardinian population is placed withing the European cluster. To reveal possible traces of selective pressure, Population Branch Statistic (PBS) was calculated; both SNPs rs143384 and 143383 have low PBS values, suggesting that there are no signals of selective pressure in those areas of the gene.

The operating room in a cardiothoracic surgical case is a complex environment, with multiple handoffs often required by staffing changes, and can be variable from program to program. This study was done to characterize what types of practitioners provide anesthesia during cardiac operations to determine the variability in this aspect of care. A survey was sent out via a list serve of members of the cardiac surgical team. Responses from 40 programs from a variety of countries showed variability across every dimension requested of the cardiac anesthesia team. Given that anesthesia is proven to have influence on the outcome of cardiac procedures, this study indicates the opportunity to further study how this variability influences outcomes, and to identify best practices.

The key towards a sustainable future is the reduction of mankind’s impact on natural systems via the development of new technologies and the improvement of source apportionment. Though days, years and seasons are arbitrarily set, their mechanisms are based on natural cycles driven by Earth’s orbital periods. This is not the case for weeks, which are a pure anthropic category and are known from literature to influence emission cycles. For the first time since it started data gathering operations, CO (carbon monoxide), CO₂ (carbon dioxide), CH₄ (methane) and eBC (equivalent black carbon) values detected by the Lamezia Terme WMO/GAW station in Calabria, Southern Italy have been evaluated via a two-pronged approach accounting for weekly variations in absolute concentrations, as well as the number of hourly averages exceeding select thresholds. The analyses were performed on seven continuous years of measurements, from 2016 to 2022. Moreso, the two results have been combined into a new parameter: the hereby defined WDWO (Weighed Distribution of Weekly Outbreaks) normalizes weekly trends of CO, CO₂, CH₄ and eBC on an absolute scale as percentages, with the scope of providing regulators and researchers alike with a new tool meant to better evaluate anthropogenic pollution and mitigate its effects.

Background: The prevalence of falls among the older population underscores the imperative of comprehending human adaptations to gait perturbations. Dual-belt treadmills offer a controlled setting for such investigations. The purpose of this study was to examine the effect of acceleration of one belt of the treadmill during three different phases of the gait cycle on kinematic and kinetic parameters and relate these changes to unperturbed gait. Methods: Twenty-one healthy young females walked on a treadmill in a virtual environment, in which five unexpected perturbations were applied to the left belt at the Initial Contact (IC), Mid Stance (MS), and Pre-Swing (PS) phase of the gait cycle. Data from the undisturbed gait and the first disturbance of each trial were extracted for analysis. Results: All perturbations significantly affected the gait pattern, mainly by decreasing the knee extension angle. The perturbation in the IC phase had the most significant effect, resulting in a 248.48% increase in knee flexion torque. The perturbation in the MS phase mainly affected plantar flexion torque, increasing it by 118.18%, while perturbation in the PS phase primarily increased the hip extension torque by 73.02%. Conclusions: The presence of perturbations in the IC and PC phases caused the most aggressive and significant changes in gait parameters.

In this analysis, we assess the performance of GSMaP-GNRT6 data in capturing precipitation climatology and climate variability across China from 2001 to 2020. The evaluation involves comparing four precipitation indices of accumulated precipitation, the number of rainy days, rainstorm days, and precipitation maximum with the daily precipitation data from 2419 stations in China. The findings reveal that the GSMaP data effectively captures the overall spatial distribution of annual, summer, and monthly precipitation. However, it exhibits minor limitations in accurately depicting the spatial distribution of the number of rainy days from July to September and the precipitation maximum during wintertime in eastern China. While the GSMaP data depicts a coherent annual cycle consistent with the station observations, a general underestimation is observed. Notably, the GSMaP data presents a much smoother annual cycle in precipitation maximum. Regarding accumulated precipitation, the number of rainstorm days, and precipitation maximum, the GSMaP data shows an almost consistent interannual variation and increasing trends, aligning with station observations. However, it is noteworthy that the magnitude of the increasing trend based on the GSMaP data is greater, especially entering the early 21st century. Conversely, a significant discrepancy in the annual variation and an almost opposite changing trend are noticed in the number of rainy days between the GSMaP data and station observations.

The factors influencing hepatitis E virus (HEV) circulation remain largely unexplored. We investigated HEV seroprevalence in humans and the prevalence of infection in farm pigs and rabbits in different regions of the Russian Federation, as well as the genetic diversity and population dynamics of HEV. Anti-HEV IgG antibody detection rates in the general population increase significantly with age, from 1.5% in children and adolescents under 20 years old to 4.8% in adults aged between 20 and 59 years old, to 16.7% in people aged 60 years and older. HEV seroprevalence varies between regions, with the highest rate observed in Belgorod Region (16.4% compared with the national average of 4.6%), which also has the country’s highest pig population. When compared with the archival data, both increases and declines in HEV seroprevalence have been observed within the last 10 years, depending on the study region. Virus shedding has been detected in 19 out of the 21 pig farms surveyed. On one farm, circulation of the same viral strain for five years was documented. All human and animal strains belonged to the HEV-3 genotype, with its clade 2 sequences being predominant in pigs. Sequences from patients, pigs, and sewage from pig farms clustered together, suggesting a zoonotic infection in humans and possible environmental contamination. The HEV-3 population size predicted using SkyGrid reconstruction demonstrated exponential growth in the 1970s–1990s, with a subsequent decline followed by a short rise around the year 2010, the pattern being similar to the dynamics of the pig population in the country. The HEV-3 reproduction number (Re) predicted using Birth-Death Skyline analysis has fluctuated around 1 over the past 20 years in Russia, but is 10 times higher in Belgorod Region. In conclusion, HEV-3 circulation varies both geographically and temporally, even within a single country. The possible factors contributing to this variability are largely related to the circulation of the virus among farm pigs.

The COLOSS research association has been assessing honey bee colony losses, associated risk factors and management, focusing on Western countries but with a progressive international expansion. Here, we report the first survey on the loss rates of colonies in 2022/23 in Ethiopia using COLOSS monitoring survey tools. A face-to-face interview questionnaire survey was conducted on 64 beekeepers selected from Oromia and Tigray regions. This covered 1,713 honey bee colonies distributed in 68 apiaries. The percentages of colonies lost were significantly different between Oromia (24.1%) and Tigray (66.4%) regions. Colony losses were attributed as unsolvable queen problems (8% in Oromia; 10% in Tigray), natural disaster (32%; 82%), and empty hives or dead colonies (60%; 8%). The loss rate was significantly affected by queen replacement (p

While researchers have made notable progress in bio-inspired swimming robot development, a persistent challenge lies in creating propulsive gaits tailored to these robotic systems. The California sea lion achieves its robust swimming abilities through a careful coordination of foreflippers and body segments. In this paper, reinforcement learning (RL) was used to develop a novel sea lion foreflipper gait for a bio-robotic swimmer using a numerically modelled computational representation of the robot. This model integration enabled reinforcement learning to develop desired swimming gaits in the challenging underwater domain. The novel RL gait outperformed the characteristic sea lion foreflipper gait in the simulated underwater domain. When applied to the real-world robot, the RL constructed novel gait performed as well or better than the characteristic sea lion gait in many factors. This work shows the potential for using complimentary bio-robotic and numerical models with reinforcement learning to enable the development of effective gaits and maneuvers for underwater swimming vehicles.

Adults with obesity experience high rates of disability and rapid functional decline. Identifying movement dysfunction early can direct intervention and disrupt disability development, however subtle changes in movement are difficult to detect with the naked eye. This study evaluated how a portable, inertial measurement unit (IMU)-based motion capture system compares to a laboratory-based optokinetic motion capture (OMC) system for evaluating gait kinematics in adults with obesity. Ten adults with obesity performed overground walking while equipped with the OMC and IMU systems. Fifteen gait cycles for each participant were extracted for 150 total cycles analyzed. Kinematics were compared between OMC and IMU across the gait cycles (coefficient of multiple correlations), at clinically significant time points (interclass correlations), and over clinically relevant ranges (Bland Altman plots). Sagittal plane kinematics were most similar between systems, especially at the knee. Sagittal plane joint angles at clinically meaningful timepoints were poorly associated except for ankle dorsiflexion at heel strike (ρ=0.38) and minimum angle (ρ=0.83). Most motions had more than 5° difference between systems across the range of angles measured. IMU-based motion capture shows promise for detecting subtle gait changes in adults with obesity. However, more work is needed before this method can replace traditional OMC.

The purpose of the present study was to investigate the effect of the laterally moving tactile stimuli to the sole on the anticipatory postural adjustment (APA) of the gait initiation. Thirteen healthy males participated in this study. A sound cue was provided at the beginning of each trial. The moving tactile stimuli were delivered to the sole after the start cue. The loci of the tactile stimuli moved from the left to right most side of the sole, and then moved from the right to left most side of that in a stimuli cycle. The duration of one stimuli cycle was 960 ms, and this cycle repeated 16 times in a trial. The participants made three steps forward from quiet stance at the participants' preferred time after the start cue. The APA did not onset at the specific direction or phase of the moving tactile stimuli, indicating that they did not use the stimuli as a trigger for initiating the gait. The moving tactile stimuli decreased the amplitude and increased the duration of the APA. The moving tactile stimuli increased the time between the APA onset and toe-off of the initial support leg, indicating that they moved slower when initiating gait during the moving tactile stimuli. Those findings are explained by the view that suppression of the APA induced by the moving tactile stimuli to the sole is caused by the decrease in the velocity of the gait initiation, and the slower velocity of the gait initiation is caused by masking tactile sensation of the sole.

Hippotherapy is a popular rehabilitation method for children with cerebral palsy (CP), which is done by riding an actual horse or a horse riding simulator (HRS) device. Riding a real horse is more expensive than using an HRS device due to its high maintenance cost. However, most HRS devices commonly sold in the market are designed as exercise devices, not rehabilitation devices. Most of them are designed to simulate a horse's walk, trot, canter, or gallop gait at various speeds. Hippotherapy aims to improve the walking ability of CP patients. Therefore, the device should aim to replicate the walking gait of a healthy human, the end goal of hippotherapy. This problem motivates us to design and build a specialized HRS device replicating the walking gait of a healthy human that is suitable for hippotherapy, which is achievable by simulating a horse walking gait with several adjustments. We first studied and observed the walking gait cycle of a horse, then analyzed and derived a formulation of it. We then continue by designing an HRS device using a single electrical rotational motor and mechanical means to replicate the walking gait of a horse, then tune it to an extent to replicate a human walking gait. To measure the performance of our design, we compare the gait of the user when riding our device versus walking.