Physiological Measures Research Articles

Measuring and Explaining Situational Fear of Crime: An Experimental Study Into the Effects of Disorder, Using Virtual Reality and Multimodal Measurement

Abstract The current study combines an experimental research design, Virtual Reality (VR) and multimodal (survey and physiological) measurements to measure and explain situational fear of crime. 159 participants completed our VR experiment in which we focused on the role of physical and social disorder in engendering situational fear of crime. Drawing on our survey measures, we find significant effects of disorder on a variety of outcome variables: situationally experienced safety, fear of theft, fear of verbal aggression, fear and physical aggression and fear of sexually transgressive behaviour. Most of our physiological measures rendered null findings. Hence, we also conclude that the results from our two data sources (survey measures vs. physiological measures) diverge in important ways.

Neurophysiological approaches to exploring emotional responses to cosmetics: a systematic review of the literature.

This systematic review explores the use of neurophysiological measurements to study emotional responses to cosmetic products. The aim is to evaluate existing literature on these measurements in cosmetics, identify the main findings, highlight methodological challenges, and propose new guidelines for future research. A systematic search focusing on neurophysiological measures to determine emotions induced by different cosmetic products was carried out in accordance with PRISMA guidelines. A total of 33 articles identified with the EBSCO database met the inclusion criteria. In all, 10 different measurement tools were used in these articles to assess the emotional effects of cosmetic products. This review emphasizes the complexity of interactions between cosmetics and emotional responses. It underscores the importance of future research with a more holistic approach that couples several physiological measurements. Among them, electrophysiological brain activity shows potential for enhancing understanding of emotional responses related to cosmetic products. Frontal asymmetry, particularly in the alpha frequency band, was often use and frequently linked to positive emotional states, although conflicting evidence exists. Additionally, cardiac activity, specifically the LF/HF ratio, emerges as a promising marker for differentiating between different cosmetic products. However, methodological heterogeneity, present challenges for replicability, generalizability, and complicate data interpretation.

Catching Mind Wandering With Pupillometry: Conceptual and Methodological Challenges.

Mind-wandering (MW) refers to the shift of attention away from an ongoing task and/or external environment towards mental contents (e.g., memories, prospective thoughts) unrelated to the task. Physiological measures (e.g., pupil size, EEG, and fMRI) have often been acquired as objective markers for MW states, which has greatly helped their study as well as triangulation with other measures. Pupillometry in particular has been used as a covert biomarker of MW because it is reliably modulated by several distinct processes spanning arousal, emotion, and attention, and it signals attentional lapses. Yet, coupling MW and the measurement of pupil size has led to seemingly contrasting results. We argue that, common to the studies reviewed here, one reason is resolving to the measurement of tonic pupil size, which reflects low-frequency, slow changes in one's physiological state, and thus implicitly assumes that MW is a static, long-lasting process. We then additionally focus on three major axes of variability in the reviewed studies: (i) the definition and measurement of MW; (ii) the impact of contextual aspects, such as task demands and individual arousal levels; (iii) the identification and tracking of MW in combination with pupillary measures. We provide an overview of these differences and put forward recommendations for using physiological measures-including, but not limited to, pupil size-in MW research effectively. In conclusion, pupillometry can be a very informative tool for MW research, provided that it is used with the due methodological caution.

A classification system for identifying persons with an unknown cardiovascular disease (CVD) status for a multiracial/ ethnic Caribbean population.

The need for classification systems for cardiovascular disease (CVD) that is population-specific is important towards understanding the clinical disease and diagnostics associated with the disease. This paper presents the form and validation results of this classification system. The survey data used was captured from 778 participants, 526 persons with no prior CVD, and 252 who reported prior CVD. Binomial logistic regression and Discriminant analysis were utilised to develop classification models. This classification system provided a general measure of severity of disease by utilising scores estimated from two algorithms developed from 13 routine physiologic measurements, along with demographic information of age and ethnicity, inter alia, and previous health status. For each model, specific score ranges were identified, which gave the best classification for those with a prior CVD incident (higher scores) and for others labelled as non-CVD (lower scores). The two classification models (Logistic Regression Model and Discriminant Analysis Model) developed had high area under the receiver-operating characteristic (AUROC) values (98% & 99%) and sensitivity (86 and 90%), which improved discrimination between Non-CVD and CVD participants and, more importantly, correctly classified a greater proportion of CVD participants. New to this type of research was the estimation and detailed evaluation of a range of scores, labelled non-differentiating, which fell in the middle of the spectrum and which contained the higher-end scores for the non-CVD individuals and the lower-end scores for CVD patients, all of whom were incorrectly classified, based on their prior history. The classification system of scores is able to differentiate the CVD status of individuals, with good predictability, and could assist physicians with recommending different treatment plans. The two models in this classification system each individually outperformed the three established models in terms of the strength of their correct classifications of individuals with or without prior reported CVD incidents. More importantly, they have smaller non-differentiating ranges than the three known models and, in that range, the two new models have lower CVD/non-CVD ratios suggesting they are more likely to misclassify non-CVD individuals compared to CVD patients, which is a more benign misclassification. Further, when used in combination, the two models increased the sensitivity, in classifying individuals of different ethnicities, beyond that of either one used independently or of any of the three standard European/North American models. These efforts will be instrumental in advancing personalised CVD management strategies and improving health outcomes across diverse populations.

Analysis of Mental Workload in Appropriate Technology (AT) for Agricultural Machinery Using Heart Rate Variability (HRV) Parameters

Appropriate Technology (AT) is designed to substitute manual work and to increase productivity for small-medium businesses. Due to its low-cost technology that affects its design quality, the acceptance of AT appears to be low. A guideline has yet to be available to determine AT's design quality. The purpose of this study was to explore the efficacy of physiological measures collected from a Heart Rate Monitor (HRM) in differentiating mental workload in using AT. If applicable, these measures can provide objective data for AT evaluation. Several parameters were collected from HRM, including frequency domain and time domain. Two ATs were used for evaluation that represented “good” and “poor” agricultural processing machines. Eleven participants were involved in this study in which they used both ATs. The result of this studyis the ratio of Low Frequency and High Frequency (LF/HF) parameter detects differences perceived by the participants. The increase in the LF/HF value from the Commercial Extruder to the Customized Extruder is directly proportional to the increase in mental workload, where the Commercial Extruder is defined as a “good” AT design, and the Customized Extruder as a “poor” AT design. Therefore, it can be concluded that designs with specific guidelines can reduce the mental workload perceived by operators.

Higher oxygen content and transport characterize high-altitude ethnic Tibetan women with the highest lifetime reproductive success

We chose the "natural laboratory" provided by high-altitude native ethnic Tibetan women who had completed childbearing to examine the hypothesis that multiple oxygen delivery traits were associated with lifetime reproductive success and had genomic associations. Four hundred seventeen (417) women aged 46 to 86 y residing at ≥3,500 m in Upper Mustang, Nepal, provided information on reproductive histories, sociocultural factors, physiological measurements, and DNA samples for this observational cohort study. Simultaneously assessing multiple traits identified combinations associated with lifetime reproductive success measured as the number of livebirths. Women with the most livebirths had distinctive hematological and cardiovascular traits. A hemoglobin concentration near the sample mode and a high percent of oxygen saturation of hemoglobin raised arterial oxygen concentration without risking elevated blood viscosity. We propose ongoing stabilizing selection on hemoglobin concentration because extreme values predicted fewer livebirths and directional selection favoring higher oxygen saturation because higher values had more predicted livebirths. EPAS1, an oxygen homeostasis locus with strong signals of positive natural selection and a high frequency of variants occurring only among populations indigenous to the Tibetan Plateau, associated with hemoglobin concentration. High blood flow into the lungs, wide left ventricles, and low hypoxic heart rate responses aided effective convective oxygen transport to tissues. Women with physiologies closer to unstressed, low altitude values had the highest lifetime reproductive success. This example of ethnic Tibetan women residing at high altitudes in Nepal links reproductive fitness with trait combinations increasing oxygen delivery under severe hypoxic stress and demonstrates ongoing natural selection.

Optimal Instruments for Measurement of Dietary Intake, Physical Activity, and Sleep Among Adults in Population-Based Studies: Report of a National Heart, Lung, and Blood Institute Workshop.

The National Heart, Lung, and Blood Institute convened a virtual workshop in September 2022 to discuss "Optimal Instruments for Measurement of Diet, Physical Activity, and Sleep." This report summarizes the proceedings, identifying current research gaps and future directions for measuring different lifestyle behaviors in adult population-based studies. Key discussions centered on integrating report-based methods, like questionnaires, with device-based assessments, including wearables and physiological measures such as biomarkers and omics to enhance self-reported metrics and better understand the underlying biologic mechanisms of chronic diseases. Emphasis was placed on the need for data harmonization, including the adoption of standard terminology, reproducible metrics, and accessible raw data, to enhance the analysis through artificial intelligence and machine learning techniques. The workshop highlighted the importance of standardizing procedures for integrated behavioral phenotypes using time-series data. These efforts aim to refine data accuracy and comparability across studies and populations, thereby advancing our understanding of lifestyle behaviors and their impact on chronic disease outcomes over the life course.

Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations.

Psychiatric disorders are complex and influenced by both genetic and environmental factors. However, studying the full spectrum of these disorders is hindered by practical limitations on measuring human behavior. This highlights the need for novel technologies that can measure behavioral changes at an intermediate level between diagnosis and genotype. Wearable devices are a promising tool in precision medicine, since they can record physiological measurements over time in response to environmental stimuli and do so at low cost and minimal invasiveness. Here we analyzed wearable and genetic data from a cohort of the Adolescent Brain Cognitive Development study. We generated >250 wearable-derived features and used them as intermediate phenotypes in an interpretable AI modeling framework to assign risk scores and classify adolescents with psychiatric disorders. Our model identifies key physiological processes and leverages their temporal patterns to achieve a higher performance than has been previously possible. To investigate how these physiological processes relate to the underlying genetic architecture of psychiatric disorders, we also utilized these intermediate phenotypes in univariate and multivariate GWAS. We identified a total of 29 significant genetic loci and 52 psychiatric-associated genes, including ELFN1 and ADORA3. These results show that wearable-derived continuous features enable a more precise representation of psychiatric disorders and exhibit greater detection power compared to categorical diagnostic labels. In summary, we demonstrate how consumer wearable technology can facilitate dimensional approaches in precision psychiatry and uncover etiological linkages between behavior and genetics.

In vivo imaging of the human brain with the Iseult 11.7-T MRI scanner.

The understanding of the human brain is one of the main scientific challenges of the twenty-first century. In the early 2000s, the French Atomic Energy Commission launched a program to conceive and build a human magnetic resonance imaging scanner operating at 11.7 T. We have now acquired human brain images in vivo at such a magnetic field. We deployed parallel transmission tools to mitigate the radiofrequency field inhomogeneity problem and tame the specific absorption rate. The safety of human imaging at such high field strength was demonstrated using physiological, vestibular, behavioral and genotoxicity measurements on the imaged volunteers. Our technology yields T2 and T2*-weighted images reaching mesoscale resolutions within short acquisition times and with a high signal and contrast-to-noise ratio.

EzySCR: A free and easy tool for scoring event-related skin conductance responses in the first, second, and third interval latency windows.

Skin conductance is a commonly used physiological measure during psychology experiments, such as during fear conditioning. Methods for scoring skin conductance responses (SCRs) are highly heterogeneous, though most researchers agree that manually inspected scores provide the highest quality data when compared to most available fully automated scoring methods. However, manual scoring is extremely time-consuming. We developed a semi-automated scoring program that reduces the time required to process SCR data at a level of quality akin to manual scoring. In contrast to all previous scoring programs, our program enables scoring of first interval response (FIR), second interval response (SIR), and third interval response (TIR) SCRs. Using interclass correlation coefficients (ICCs), Bland-Altman plots and Pareto analysis, we show here that our method is highly reliable and produces data that are almost identical to data that are manually scored and scored using LEDALAB. This software is very easy to use and is freely available to download and modify. We expect that this software will be helpful in reducing the time required to produce high quality FIR, SIR, and TIR skin conductance data for psychology researchers around the world.

No Effect of Intermittent Palm or Sole Cooling on Acute Training Volume during Resistance Exercise in Physically Active Adults: A Summary of Protocols.

Intermittent palm (PC) and sole cooling (SC) are proposed ergogenic methods for enhancing exercise performance during high-intensity and fatiguing conditions. However, findings in the literature regarding its positive effect remain inconclusive. This study aimed at investigating the effects of intermittent PC and SC compared to no cooling (NC) on acute training volume during resistance exercise, particularly focusing on the total number of repetitions (TR) performed. Three separate randomized crossover protocols, incorporating commonly practiced resistance exercises (Protocol 1: pullups; Protocol 2: pushups; Protocol 3: leg extensions), were conducted, enrolling healthy, physically active adults (overall sample: n = 41 (12 female), age: 23.9 ± 4.0 years (mean ± SD), height: 174.4 ± 9.5 cm, body mass: 69.3 ± 12.4 kg). During Protocol 3, tympanic temperature (TT), rate of perceived exertion (RPE), and electromyography (EMG) of quadriceps muscles were additionally assessed for SC. PC resulted in less TR compared to NC in Protocol 1 (p < 0.001). Protocol 2 and 3 did not reveal significant ergogenic benefits of PC or SC compared to NC (p > 0.05). Furthermore, SC had no effect on TT, RPE, or EMG amplitudes (all p > 0.05). The inconsistent findings suggest that intermittent PC and SC might have limited effectiveness in enhancing training volume during resistance exercise in physically active adults. Future research should examine various resistance training protocols under controlled conditions, and incorporate comprehensive physiological measurements to elucidate the potential benefits and mechanisms of intermittent cooling in resistance exercise contexts.

Violations of Musical Expectations and Emotion

This study investigates the possibility of a relationship between types of violations of musical expectations and perceived emotions. A natural consequence of listening to music is the development of musical expectations, or rhythmic, harmonic, and structural anticipations of what the listener expects to hear. Existing research in psychology and neuroscience demonstrates that violation of these musical expectations has significant physiological and emotional effects on the listener. Through a survey format, participants were asked to evaluate their experience listening to twelve excerpts by providing written responses and completing two rating scales. This allowed for a qualitative and quantitative evaluation of emotion in contrast to physiological measures used in other studies. Nonparametric tests showed statistically significant differences between ranked mean ratings according to type of violation. Thus, this study provides evidence supporting the existence of a relationship between types of violations of musical expectation and perceived emotions in listeners. Further research is suggested for clarification of this relationship and its possible applications in musical compositions.

Neurophysiological Approach for Psychological Safety: Enhancing Mental Health in Human–Robot Collaboration in Smart Manufacturing Setups Using Neuroimaging

Human–robot collaboration (HRC) has become increasingly prevalent due to innovative advancements in the automation industry, especially in manufacturing setups. Although HRC increases productivity and efficacy, it exposes human workers to psychological stress while interfacing with collaborative robotic systems as robots may not provide visual or auditory cues. It is crucial to comprehend how HRC impacts mental stress in order to enhance occupational safety and well-being. Though academics and industrial interest in HRC is expanding, safety and mental stress problems are still not adequately studied. In particular, human coworkers’ cognitive strain during HRC has not been explored well, although being fundamental to sustaining a secure and constructive workplace environment. This study, therefore, aims to monitor the mental stress of factory workers during HRC using behavioural, physiological and subjective measures. Physiological measures, being objective and more authentic, have the potential to replace conventional measures i.e., behavioural and subjective measures, if they demonstrate a good correlation with traditional measures. Two neuroimaging modalities including electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have been used as physiological measures to track neuronal and hemodynamic activity of the brain, respectively. Here, the correlation between physiological data and behavioural and subjective measurements has been ascertained through the implementation of seven different machine learning algorithms. The results imply that the EEG and fNIRS features combined produced the best results for most of the targets. For subjective measures being the target, linear regression has outperformed all other models, whereas tree and ensemble performed the best for predicting the behavioural measures. The outcomes indicate that physiological measures have the potential to be more informative and often substitute other skewed metrics.

Development of a Nomogram for Predicting ICU Readmission.

Background This study aims to develop and validate a comprehensive prediction model for ICU readmissions. Readmission following ICU discharge is associated with adverse outcomes such as increased mortality, prolonged hospital stays, and elevated healthcare costs. Consequently, predicting and preventing readmissions is crucial. Previous models for predicting ICU readmissions were primarily based on physiological indices; however, these indices fail to capture the complete nature of treatment or patient conditions beyond physiological measures, thereby limiting the accuracy of these predictions. Methodology A total of 1,400 patients who had an unplanned ICU admission at Sapporo Medical University Hospital from January 2015 to October 2022 were included; a single regression analysis was performed using unplanned ICU readmission as the dependent variable. After performing a single regression analysis, logistic regression analysis using the stepwise method was performed using variables with significant differences, and a predictive nomogram was created using the variables that remained in the final model. To internally validate the predictive nomogram model, nonparametric bootstrapping (1,000 replications) was performed on the original model. Results Of the 1,400 patients who had an unplanned admission to the ICU, 114 (8.1%) were readmitted to the ICU unplanned. Seven main variables (Sequential Organ Failure Assessment score, respiratory rate, Glasgow Coma Scale, sleep disturbance, Continuous Kidney Replacement Therapy, presence of tracheal suctioning, and Oxygen Saturation) were selected to be associated with ICU readmission. The evaluation of the models showed excellent discrimination with an area under the receiver operating characteristic of 0.805 (original model) and 0.796 (bootstrap model). Calibration plots also confirmed good agreement between observed and predicted reentry. Conclusions This new predictive model is more accurate than previous models because it includes physiological indicators as well as other patient conditions and procedures needed and is expected to be used in clinical practice. In particular, the inclusion of new factors, such as sleep disturbance and the need for tracheal suctioning, enabled a more comprehensive patient assessment. The use of this predictive nomogram as a criterion for discharging ICU patients may prevent unplanned ICU readmission.

Associations Between Sleep Disorders and Treatment Response in Service Members With Post-traumatic Stress Symptoms: A Secondary Outcome Analysis

ABSTRACT Introduction Compared with the civilian population, a higher rate of reported sleep apnea exists among military service members resulting in inadequate sleep. Those who experience chronic sleep deprivation may suffer from debilitating problems that may compromise military mission readiness and unit safety. The purpose of the study on which this secondary outcome analysis was based was to evaluate the effect of manual standardized stress acupuncture as an adjunct therapy to an abbreviated form of cognitive behavioral therapy for insomnia for sleep disturbances in post-deployment service members. The aim of this secondary outcome analysis was 2-fold: (1) to assess the relationship between sleep disorder symptoms and post-traumatic stress symptoms (PSS) and (2) to determine if the presence of sleep disorder symptoms influenced the effects of acupuncture and cognitive behavioral therapy as compared to cognitive behavior therapy only on PSS) in post-deployment military service members. Materials and Methods The study was a 2-arm, single-center, randomized controlled trial approved by the Naval Medical Center San Diego and the Vanderbilt University Institutional Review Board. It was conducted at the U.S. Naval Hospital in Okinawa, Japan. Participants were active duty service members from all military branches who were stationed in Okinawa. Two measures were used to analyze the data: the Global Sleep Assessment Questionnaire (GSAQ) and the Post-traumatic Stress Disorder Checklist. A Pearson correlation coefficient was calculated to determine the relationship between sleep disorder symptoms (i.e., 11 pre-intervention GSAQ symptoms) and PSS treatment outcomes (i.e., PCL and PTSD clusters). Results Results indicated associations between the GSAQ components and PCL total and PTSD cluster scores. Findings showed that the presence of sleep disorder symptoms influenced PSS treatment response in post-deployment military service members. Conclusions Results from this secondary outcome analysis showed associations between GSAQ components (i.e., excessive daytime sleepiness, working conditions causing inadequate sleep, involuntary movements in sleep, and sadness or anxiousness) and PCL total and PTSD cluster scores (i.e., avoidance, negative cognition and mood, avoidance, and hyperarousal). Furthermore, sleep disorder symptoms such as having stressful working conditions (e.g., shift work), probable obstructive sleep apnea, insomnia, anxiety, and depression influenced PSS treatment responses. This study provided information on the major contribution of sleep disorder symptoms in the treatment of PSS through self-report. Future researchers should consider the use of physiologic measures to further understand the mechanisms of how sleep disorder symptoms affect treatment responses in service members with PSS. Implications for this study may assist clinicians in determining effective PSS treatments for those with OSA and insomnia.

Remote physiological signal recovery with efficient spatio-temporal modeling.

Contactless physiological signal measurement has great applications in various fields, such as affective computing and health monitoring. Physiological measurements based on remote photoplethysmography (rPPG) are realized by capturing the weak periodic color changes. The changes are caused by the variation in the light absorption of skin surface during systole and diastole stages of a functioning heart. This measurement mode has advantages of contactless measurement, simple operation, low cost, etc. In recent years, several deep learning-based rPPG measurement methods have been proposed. However, the features learned by deep learning models are vulnerable to motion and illumination artefacts, and are unable to fully exploit the intrinsic temporal characteristics of the rPPG. This paper presents an efficient spatiotemporal modeling-based rPPG recovery method for physiological signal measurements. First, two modules are utilized in the rPPG task: 1) 3D central difference convolution for temporal context modeling with enhanced representation and generalization capacity, and 2) Huber loss for robust intensity-level rPPG recovery. Second, a dual branch structure for both motion and appearance modeling and a soft attention mask are adapted to take full advantage of the central difference convolution. Third, a multi-task setting for joint cardiac and respiratory signals measurements is introduced to benefit from the internal relevance between two physiological signals. Last, extensive experiments performed on three public databases show that the proposed method outperforms prior state-of-the-art methods with the Pearson's correlation coefficient higher than 0.96 on all three datasets. The generalization ability of the proposed method is also evaluated by cross-database and video compression experiments. The effectiveness and necessity of each module are confirmed by ablation studies.

Exploring the Role of Action Mechanics in Game-Based Stress Recovery

Digital games can provide effective recovery from stress, with players turning to a variety of genres-including those with game mechanics that can be considered stressors themselves, i.e., action mechanics. We examine whether action mechanics undermine or facilitate game-based recovery by exposing participants (n=60) to a stress induction, and then having them play a roguelike game in one of three conditions: Combat-Required, Combat-Optional, and Combat-Free. We assess experience through self-report and observed physiological responses. Our findings suggest that gameplay-irrespective of action mechanic intensity-supports the recovery process through the pathways of experienced psychological detachment, control, dominance, and pleasure. Additionally, action mechanics were perceived by participants as particularly promising for mastery recovery experiences-but undermine the recovery pathways of relaxation, as corroborated by experienced arousal and subjective stress. Physiological measures corroborate subjective self-report. We contend that video games featuring action mechanics represent a promising strategy for stress recovery, and may be particularly beneficial in the re-assertion of mastery.

Investigating the Impact of Garden Plant Smellscapes on Human Well-Being: A Case Study of Pine Forests

The smellscape of garden plants plays a crucial role in promoting human well-being. Despite this, empirical data on the specific effects of distinct stimulation methods on public health remain insufficient. The objective of this research is to investigate the influence of three distinct sensory modalities, olfactory, visual, and their combined effect, on both physiological and psychological reactions to a pine forest’s smellscape. A sample of 95 college students was selected, with data collected through both physiological and psychological measurements. The analysis focused on variables such as blood pressure (BP), pulse rate (P), pulse pressure (PP), skin conductance (SC), brainwave patterns (α, β), the odor emotion semantic differential (SD), and the State Anxiety Inventory (S-AI) scale. The results reveal that in the pine forest aroma environment, the central nervous system shows a compromise effect during olfactory–visual interaction, with greater autonomic nervous system (ANS) activation compared with either stimulus alone, suggesting cumulative effects. Psychologically, the influence of olfactory interaction on anxiety fell between that of visual and olfactory stimulation. Participants consistently reported that the combination of both the sight and scent of a pine forest was the most invigorating. Furthermore, research revealed that combining olfactory and visual stimuli led to a more profound amplification of positive environmental perceptions compared with when each sense was engaged individually. These findings lay the groundwork for understanding how garden plant aromas contribute to human well-being.

Effect of acute supplementation of hibiscus-ginger drink on university athletes’ aerobic power and blood lactate

Background: Sport training places significant demand on athletes, motivating them to seek strategies to enhance performance and maintain competitiveness. The use of ergogenic aids has become prevalent in sport, although not without potential risks. Hibiscus-ginger juice, rich in vitamins and minerals, has been suggested to improve metabolism, aid in post-exercise recovery, reduce inflammation, and enhance athletic performance. Aims: This study aimed to investigate the effect of hibiscus ginger juice supplementation on aerobic power and blood lactate levels in athletes. Methods: A pretest-posttest experimental design was employed, involving 28 university athletes aged 20 – 37 years. Participants were randomly assigned to a treatment group receiving 500 mL of hibiscus-ginger juice daily after training for 24 days, or a control group. Physiological measures of blood lactate levels and aerobic power were assessed on three separate occasions during the study period. Results: Mixed model ANOVA showed no significant differences in blood lactate levels (p = .502) or aerobic power (p = .117). Daily consumption of 500 mL of hibiscus-ginger juice for 24 days did not significantly alter aerobic power or blood lactate levels of athletes. Conclusion: The findings suggest that consuming hibiscus-ginger juice may not provide a performance advantage for athletes compared to those who do not. Keywords: Acute supplementation, aerobic power, blood lactate level, hibiscus-ginger juice, university athletes.

Vegetation Growth and Physiological Adaptation of Pioneer Plants on Mobile Sand Dunes

The Hunshandake Sandy Land is one of the largest sandy areas in China and the closest source of sand dust to the Beijing and Tianjing areas. Sand fixation by vegetation is considered the most efficient strategy for sand control and sustainable development, so clarifying the vegetation coverage and plant adaptation characteristics in the Hunshandake Sandy Land is helpful in guiding restoration and improving local sustainability. Here, we investigated the vegetation growth on the mobile sand dunes in the Hunshandake Sandy Land and specified the photosynthesis and stomatal characteristics of the pioneer plants for sand fixation. The vegetation survey showed that the windward slopes of the mobile sand dunes had far lower plant coverage (6.3%) and plant biodiversity (two species m−2) than the leeward ones (41.0% and eight species m−2, respectively). Elymus sibiricus L. and Agriophyllum squarrosum (L.) Moq. were the only two sand-fixing pioneer plants that grew on both the windward and leeward slopes of the mobile sand dunes and had higher plant heights, greater abundance, and more biomass than other plants. Physiological measurements revealed that Elymus sibiricus L. and Agriophyllum squarrosum (L.) Moq. also had higher photosynthetic rates, transpiration rates, and water use efficiency. In addition, the stomata density (151–197 number mm−2), length (18–29 μm), and area index (13–19%) of these two pioneer species were smaller than those of the common grassland species in Inner Mongolia, suggesting that they were better adapted to the dry habitat of the mobile sand dunes. These findings not only help in understanding the adaptive strategies of pioneer plants on mobile sand dunes, but also provide practical guidance for sand dune restoration and the sustainable development of local areas. Pioneer sand-fixing plant species that are well adapted to sand dunes can be used for sowing or aerial seeding in sand fixation during ecosystem restoration.