Early separation of mother and offspring remains common in the beef cattle industry, despite several reported animal health and welfare concerns related to this practice. Public and research interest in extending the cow-calf contact period in the dairy industry is increasing. However, few published works have described weaning as a behavioural process as it occurs naturally between cows and calves towards full nutritional independence, perhaps due to this commonly practiced early separation of cow and calf. Understanding the role of domestic cow and calf behaviours towards weaning will support management of weaning in a way which is better aligned with the natural process. We aimed to 1) identify and describe suckling and cow-calf behaviour around suckling in beef cattle (Aberdeen Angus (AA), AA – White Park crosses), and 2) ascertain how the identified behaviours changed as weaning progressed. To inform our first aim, one herd of 73 AA – White Park cows and their current and past offspring was observed from October to November 2017. The herd was managed as a single group, in an extensive outdoor natural weaning system with calves left with their mothers. To inform our second aim, sixteen cow-calf dyads (mean calf age 9.9 months, range 7-11; mean parity 1.7, range 1-6) within the larger herd of 73 were observed during suckling from first light until darkness once per week for five weeks. During the behaviour identification, thirty behaviours performed by the cow, calf, or dyad were identified by focal sampling. An ethogram containing these behaviours was created, and the progression of each behaviour was tracked over time by scanning the herd until a suckling dyad was observed and subsequently carrying out focal sampling of that dyad (January – February 2018). These behaviours were grouped into seven behavioural categories for further analysis (informing aim 2); cow walk, cow still, cow move, cow stationary movement, kick calf, calf seeking, and calf move. Each of these categories were included in univariate two-level models as dependent variables. Each category was the dependent variable in two models, where the independent variables were either ‘days until calving’ or ‘days since calving’. The independent variables were selected to represent 1) weaning being driven by offspring maturity and 2) weaning being driven by gestational state of the dam. We found that behaviours related to the cow terminating the suckling bout increased and behaviours linked to the calf terminating suckling decreased as time passed from the previous until the next calving. We also found an increase in “kick calf” behaviour as the birth date of the next calf approached, and that the duration of cow’s stationary behaviour during suckling bouts increased and duration of cow’s and calf’s mobile behaviour decreased as time passed from the previous calving. Overall, few empirical works have explored the natural weaning process in domestic cattle, despite large interest in increased cow-calf contact within the cattle industry. This study presents an investigation of these behaviours as a basis for future research and application. • Natural weaning in domestic cattle is not fully described as calves are often removed early • We aimed to identify unmanaged, natural suckling and weaning behaviours and describe changes over time • Thirty behaviours performed by the cow, calf or dyad were identified • Behaviours where the cow terminated suckling increased over time • Behaviours where the calf terminated suckling decreased over time

Characterization of human-animal interactions among pet owners in Mexico from a One Health perspective: A cross-sectional study.

Potential of fish skin gelatin for dough rheology and quality optimization of extruded gluten-free noodles

The monitoring of one's own learning progress is a key process in models of self-regulated learning and a key predictor of self-regulated learning and academic success. Judgments of learning (JOLs) are an established measure for assessing people's monitoring of learning and have been found to predict learners' subsequent performance as well as effort regulation. However, most studies have been conducted in laboratory settings, involving relatively artificial learning materials and low-stakes tests. We evaluate the predictive validity of JOLs for learning performance and effort regulation in an ecologically valid learning environment by requesting aggregate JOLs in an intelligent tutoring system. 90 German university students used an intelligent tutoring system that provided practice exercises for self-regulated preparation for a statistics exam over the course of a semester. Aggregate JOLs for each chapter of the statistics course were assessed once per week (279 assessments in total). Dependent variables were learning performance as well as absolute and relative learning effort for each chapter, derived from the intelligent tutoring system's log files. JOLs significantly predicted learning performance ( β = 0.20, p < .001) and effort regulation ( β absolute = −0.12, p < .001, β relative = −0.07, p = .002). The present research demonstrates that JOLs have predictive power in real-world learning. It thus bridges the gap between experimental cognitive research and applied educational research on metamemory and self-regulation. • Judgments of learning (JOLs) are predictions of one's own future performance. • Little is known about JOL accuracy in ecologically valid learning environments. • We examined JOL accuracy in an intelligent tutoring system used for exam preparation. • JOLs predicted effort regulation and performance during exam preparation.

Enhancing the applicability of Spirulina platensis in food systems: the role of double coated encapsulation.

Mediating effect of dyadic coping on the relationship between patient empowerment and quality of life in acute ischemic stroke patients and their spouses.

The emergence of Automated Vehicles (AVs) will result in mixed traffic with Human-Driven Vehicles (HDVs), creating a complex traffic environment. While literature supports the effect of AVs on human driving behavior, the influence of different AV driving styles in this context remains largely unexplored. This study investigated interactions between HDVs and AVs varying in driving style (cautious vs. aggressive) and appearance (recognizable vs. unrecognizable) at Market Penetration Rates (MPR) of 0% to 75% in 25% increments within a highway context. Car-following behavior of 160 participants (56 females, age range 19-65) in a driving simulator experiment was analyzed using average time headway (THW) and standard deviation of relative speed (SDRS) as key metrics. Linear Mixed Models (LMMs) and Structural Equation Modelling (SEM) were applied. Results showed that compared to the baseline (no AVs), drivers' THW decreased when interacting with aggressive AVs by 11.1%, 8.6%, and 13.2% at MPRs of 25%, 50%, and 75%, respectively. Interactions with cautious AVs led to even larger reductions in THW by about 9.9%, 16.6%, and 17.3% at the same MPRs. SDRS improved across MPRs by 4.5%, 5.2%, and 6.2%, independent of AV driving style or appearance. SEM analysis indicated that AV driving style moderated relationships between independent, mediating, and dependent variables, while drivers' perceived stress and comfort mediated effects of AVs, trust propensity, and recognizability on THW and SDRS. These findings provide insights into human responses to AV behavior, highlighting implications for traffic flow and safety to ensure smoother and safer human-AV interactions.

Investigating student teachers' perceptions of authentic assessment: The influence of gender, field of study, and institutional context.

Weight's effect on impact acceleration in time and frequency domain in recreational runners.

Despite the availability of diagnostic tools and effective treatments for osteoporosis (OP), many women do not receive adequate care. This study seeks to explore the diagnosis and treatment gaps for OP among postmenopausal women. This cross-sectional study was conducted among Iranian women aged 50 and older selected through simple random sampling. The dependent variables were diagnosis gap and treatment gap of osteoporosis. Covariates included demographic, socioeconomic, clinical, and FRAX-related factors. After FRAX screening, participants completed a structured questionnaire. Multiple logistic regression was performed, and model selection was conducted using a backward stepwise method. Model performance was assessed using goodness-of-fit tests and AUC. Analyses were performed in Stata 14. A total of 998 women (mean age 64.6 ± 10.4 years) were included in this study. Of these, 346/998 (34.67%) were classified as being at high risk of fragility fractures based on FRAX. Among the 346 high-risk women, the osteoporosis diagnosis gap was 237/346 (68.49%), and the overall treatment gap was 248/346 (71.67%). Of 109 women diagnosed with osteoporosis and considered at high risk for fragility fractures, 11/109 (10.09%) remained untreated. Elementary education (OR = 4.80, 95% CI: 1.65-13.99, P = 0.004) and awareness of osteoporosis and its complications (OR = 6.03, 95% CI: 3.38-10.73, P < 0.001) were associated with higher odds of osteoporosis diagnosis, whereas rural residence (OR = 0.52, 95% CI: 0.30-0.91, P = 0.022) was associated with lower odds of being undiagnosed, indicating a protective effect against the diagnosis gap. No other variables, including age, BMI, and comorbidities, were significant. No predictors were associated with the treatment gap. The model showed good fit (AUC = 0.78, Hosmer-Lemeshow P = 0.45) and no multicollinearity was detected. Significant gaps exist in the diagnosis and treatment of osteoporosis among Iranian women aged 50 years and older, with diagnosis and treatment gaps of 68.49% and 71.67%, respectively. Addressing these gaps requires strategies to increase patient and provider awareness, enhance primary care screening, facilitate BMD referrals, and reduce barriers to care, particularly in rural areas.

Rectal predominance and annular wall thickening: Abdominal computed tomography and clinical characteristics of colorectal cancer in a resource-limited setting.

Alcohol misuse and negative emotion processing in neurotypical drinkers: Sex differences in behavioral and neural markers.

Background: Since their introduction in professional football, penalty shoot-outs represent key moments in matches. Motor imagery (MI) can improve soccer performance, but different MI modalities can be used to mentally simulate motor actions. This study aimed to evaluate whether the MI modality used by the players would influence their penalty shoot-out performance. Methods: Twenty youth skilled football players from the Elite Center of the French Regions of America (CERFA) voluntarily participated in this experiment (Mage ​= ​16.4 years). After an assessment of their MI ability, the participants completed 4 counterbalanced experimental sessions spread over 4 weeks, each including the completion of 5 penalty shoot-outs. The sessions consisted of a control condition (count-down and actual execution) and 3 MI conditions during which the players had to mentally imagine themselves performing a penalty shoot-out according to one of the MI modalities: Internal Visual Imagery (IVI), External Visual Imagery (EVI), or Kinesthetic Imagery (KI), before kicking. Number of goals scored, shooting accuracy and ball speed were measured and served as dependent variables. Results: The soccer players benefited from MI. Indeed, in both the IVI and KI conditions, their performances were significantly higher than in the no-MI (i.e., control) condition with respect to the total number of goals scored and shooting accuracy variables. Conclusions: Practically, we suggest skilled football players imagine, from an internal perspective, taking a successful penalty kick before shooting.

Comment on "Inter-examiner and inter-day reliability of dynamic tibiofemoral movements measurement using motion capture during walking and jumping tasks".

Green innovation pathways and sustainable development performance in China’s logistics industry: an integration of TOE framework and resource orchestration theory

Understanding what determines blood flow in the circulation is central to haemodynamic management in anaesthesia and critical care. Traditional teaching emphasises pressure-based concepts, such as preload; afterload; central venous pressure; and venous return curves. However, these frameworks generate confusion about causality and control. Interpreting pressure variables as drivers of flow has contributed to inconsistent physiological reasoning and potentially harmful treatment. This narrative review re-examines how blood flow is generated and regulated, integrating classical physiology with contemporary mechanisms and provides a coherent clinical framework. We performed a search of MEDLINE and Embase with key terms, supplemented by citation tracking. We also included seminal physiological studies. The reviewed literature showed that blood flow is constrained by energy supply from the heart and pressure established by vascular volume, elastance and the impedance of the inflow pathway to the heart. Mean systemic pressure reflects potential energy stored within the compliant venous system but does not drive flow. Right atrial pressure and preload are dependent variables that report the equilibrium between venous return and cardiac function, but do not control flow. Starling's mechanism provides passive mechanical matching of inflow to outflow but does not regulate cardiac output actively. Resistance-based interpretations alone fail to account for the influence of compliance, impedance and pulsatility. Misinterpretation of graphical and algebraic representations, particularly venous return curves, has obscured these relationships. We describe a unified physiological framework in which the heart supplies energy, vascular properties define what flow is possible, and pressures reflect system state rather than driving forces. This model reconciles historically opposing paradigms and clarifies the limits of pressure-targeted resuscitation. Clinically, it promotes assessing flow responsiveness and cardiac reserve over static pressure targets, and provides a mechanistic basis for contemporary shock management, thus avoiding interventions that increase congestion without improving perfusion.

The impact of chronic kidney disease (CKD) is unevenly distributed across socio-demographic groups in England, contributing to disparities in healthcare access and outcomes. This study presents a baseline assessment of equity in renal care pathways across England, utilising health equity audit methodology, to facilitate future comparisons assessing intervention impact. This study used a retrospective, observational design. Data from three routinely available sources of healthcare activity data; CVDPREVENT, the Secondary Uses Service, and the UK Renal Registry (UKRR) were analysed to evaluate disparities in access to renal care pathways. More than twenty different dependent variables were analysed, by age, sex, ethnicity, socioeconomic status, and geography. We calculated the proportion of patients or rates per population for each category of explanatory variables. The baseline equity assessment highlighted substantial disparities in access to kidney care across primary, secondary, and specialised services. Findings showed that; older adults faced lower access to transplants and peritoneal dialysis, while younger adults, particularly young men, were less likely to attend outpatient appointments. Socio-economic inequalities were evident, with patients from deprived areas having higher rates of late presentation and non-attendance, alongside reduced access to transplants and peritoneal dialysis. Asian patients demonstrated higher testing rates, whereas Black patients experienced higher non-attendance rates and lower transplant access. The study highlights the utility of the health equity audit for identifying inequities and provides a replicable methodology for local systems. Addressing these findings requires targeted interventions and systemic changes to reduce avoidable inequities and improve healthcare outcomes for all patients with CKD.

Measurement error is an unavoidable feature of experimental data collection. It is common in mathematical biology to consider measurement error in the dependent variable. However, less attention has been given to errors in the independent variable. This work is focussed on the effects of independent variable measurement error in the biological sciences and the available statistical methods to account for these errors when performing parameter inference. Through a series of synthetic data studies, the effects of various error models are investigated, with a particular focus given to error in the time a measurement is taken. Across many scenarios, parameter inference proves robust to these errors, even without directly accounting for them. However, we find some systems, such as oscillating systems, are particularly susceptible to these errors and parameter estimates become biased. To aid researchers in the biological sciences, we review some statistical methods to correct for measurement error. We assess the applicability of these methods in a biological context by considering data availability and necessary assumptions for the methods. We find measurement error can have non-trivial and counter-intuitive effects on parameter inference and suggest assessing the available data should be an integral step in the modelling workflow. This allows researchers to identify when the integration of statistical methods to correct for measurement error are warranted.

Ending the HIV epidemic in the U.S. requires access to comprehensive care. Traditional measures of service access have focused on distance and time. This study used the enhanced two-step floating catchment area (E2SFCA) method to measure geospatial accessibility and its association with HIV care continuum outcomes. Data from South Carolina's 2020 enhanced HIV/AIDS reporting system (eHARS) were used to calculate aggregated county-level percentage linkage to care (LTC), retention in care (RIC), and viral suppression (VS) among adult people living with HIV (PLWH). E2SFCA was used to measure geospatial accessibility, using the 60-min index as the threshold. County-level mean percentage of dependent variables and covariates were calculated. A linear regression model (LRM) was used to evaluate the association between accessibility index and LTC, RIC, and VS after adjusting for covariates. Accessibility index ranged from 17.9 to 198 across the 46 counties (mean = 67.5, SD = 36.5). Counties with better accessibility were more likely to have a higher percentage of LTC (β = 5.07, 95% CI = 0.83, 9.31) but a lower percentage of VS (β = -2.85, 95% CI= -4.60, -1.10). The negative association between accessibility index and VS was moderated by the percentage of household without vehicle ownership (β = 2.00, 95% CI = 0.02, 4.00). No association was found between the accessibility index and RIC. Counties with lower uninsured rates (β= -3.11, 95% CI= -5.35, -0.87) had higher % LTC. Suboptimal geographic accessibility to HIV care is an important structural barrier in South Carolina. Targeted policies and interventions are needed to address this challenge.

Are risky driving, health behaviors, and cardiometabolic risk interrelated? Findings from the cooper center longitudinal study.