Min Intervals Research Articles

Intraoperative hyperthermia is associated with increased acute kidney injury following cytoreductive surgery and hyperthermic intraperitoneal chemotherapy: a retrospective cohort study

Background Acute kidney injury (AKI) is common after cytoreduction surgery and hyperthermic intraperitoneal chemotherapy (CRS-HIPEC) for peritoneal surface malignancies. Herein we analyzed the association between intraoperative hyperthermia and AKI following CRS-HIPEC. Methods In this retrospective cohort study, we collected baseline and perioperative data from patients who underwent CRS-HIPEC mainly for pseudomyxoma peritonei between 2014 and 2020. Nasopharyngeal temperature was recorded at 5-min intervals. The area above the threshold was calculated for intraoperative hyperthermia (>37.0 °C). AKI was diagnosed and classified according to the KDIGO creatinine criteria. A multivariable logistic regression model was established to assess the association between hyperthermia and AKI. Results A total of 480 patients were included in the analysis. Of these, 10.6% (51/480) developed AKI within 7 postoperative days. After correction for confounding factors, a larger area above the threshold of hyperthermia was significantly associated with an increased risk of AKI (odds ratio [OR] 1.36, 95% CI 1.14–1.63, p = 0.001). Among other factors, older age (OR 1.05, 95% CI 1.02–1.09, p = 0.002), postoperative hypotension requiring vasopressors (OR 2.09, 95% CI 1.02–4.27, p = 0.042), and intraperitoneal chemotherapy containing cisplatin (OR 2.75, 95% CI 1.20–6.33, p = 0.017) were also associated with an increased risk of AKI. Patients with AKI required longer mechanical ventilation, stayed longer in the intensive care unit and hospital, developed more complications, and required more intensive care unit readmission. Conclusions Among patients undergoing CRS-HIPEC, intraoperative hyperthermia was independently associated with a higher risk of AKI; this effect was additive to other risk factors including cisplatin-containing chemotherapy.

The immediate and lasting effects of imagery rescripting and their associations with imagery tendency in young adults with childhood maltreatment history: An ERP study.

The effectiveness of imagery rescripting (IR) in reducing psychological symptoms associated with aversive memories has been confirmed across various disorders. To better understand the neural mechanisms underlying IR, we assessed the immediate and lasting effects and their associations with imagery tendency by using unpleasant pictures depicting child maltreatment within a population with childhood maltreatment (CM) history. Participants (n = 68) were instructed to engage in two experimental phases while electroencephalogram was recorded. In the rescripting phase, participants viewed neutral or unpleasant pictures and then either imagined the same pictures or rescripted unpleasant ones to assess immediate effect. In the re-exposure phase, participants passively viewed all pictures without instruction to assess lasting effect. Participants rated their subjective valence and imagery vividness in the rescripting phase or intensity of negative feelings in the re-exposure phase. IR led to an attenuation of the late positive potential (LPP) amplitude in the late time window (2000-6000 ms at parietal-occipital electrodes) and a decrease in self-reported unpleasantness during the rescripting phase. After 5-min interval, unpleasant pictures with rescripted history elicited smaller LPP (400-1500 ms at centro-parietal electrodes) and negative feelings than those with imagery history in the re-exposure phase. The higher habitual use of imagery was associated with a greater reduction in late LPP during the rescripting phase and full-time range LPP during the re-exposure phase. The current findings suggest that IR has an immediate effect and a lasting effect on subjective and neural response in the CM population. Individuals with higher imagery tendency are likely to profit more from IR.

Acute tolerance to rocuronium -A case report-

Background: For most administration of a booster dose can result in a similar reaction to the initial dose. Of course, neuromuscular blocking agents (NMBAs) can produce a comparable reaction in the absence of specific pathophysiologic alterations. Case: An initial dose of 40 mg of rocuronium was given to a male patient (50 years old, height 168 cm, weight 54 kg, body mass index 19.13 kg/m2) for anesthesia. The onset time was usual, but the duration was brief. Two booster doses were administered at 20 min intervals, but recovery came quickly. So, acute tolerance was suspected. Muscle function was restored to greater than train-of-four ratio 0.75 while spontaneous aided breathing was maintained without the need of further NMBAs. Following the operation, sugammadex (1.85 mg/kg) was provided to prevent residual neuromuscular inhibition.Conclusions: Anesthetists must be able to suspect acute tolerance to NMBAs in patients with no unique medical history and have a plan to resolve it.

Physiological and perceptual demands of singles and doubles beach tennis in women of different competition levels

PurposeTo analyze and compare the physiological responses of women during singles and doubles beach tennis sessions.MethodsIn this crossover trial, twenty-two women with previous participation in amateur beach tennis tournaments randomly performed two experimental sessions: singles and doubles beach tennis. The routine for both sessions consisted of 10-min of seated rest, followed by 45-min of beach tennis and 30-min of post-exercise recovery. Participants were matched against opponents of the same competition level, defined according to their local beach tennis ranking (advanced or intermediate level). They warmed up with basic techniques for 5-min and played 3 matches lasting 12-min, interspersed with 2-min recovery intervals. Heart rate (HR), energy expenditure (EE), number of steps (STEPS), handgrip strength (HS), rating of perceived exertion (RPE), and enjoyment were assessed throughout the sessions. Generalized estimating equations were employed to examine the main effects between experimental sessions over the time and in relation to competition level.ResultsHRmean and HRmax (Δ: HRmean = 13 ± 3 bpm; HRmax = 11 ± 3 bpm) as well as EE and Steps (Δ: EE = 66 ± 22 kcal; RPE = 2 ± 0 A.U.; Steps = 250 ± 52 A.U.) were higher in singles than doubles (p < 0.05). The percentage of total time spent in the highest HR zone (91–100%HRmax) was significantly greater in singles than in doubles (39% ± 22% vs. 15% ± 18%; p < 0.05). Differences were found in the percentage of total time spent in each HR zone, recovery HR, and HS between competition levels (p < 0.05).ConclusionSingles beach tennis resulted in higher physiological demands than doubles in women, and players’ competition level partly affects the training responses.

Analysing Sector Safety Performance Based on Potential Conflicts: Complex Network Approach

This paper presents an in-depth analysis of Sector Safety Performance (SeSPe), focusing on potential conflicts within the Spanish Air Traffic Network. SeSPe serves as a comprehensive analysis for evaluating the safety levels of individual airspace sectors, taking into account both the frequency and severity of potential conflicts, along with their geospatial characteristics. Using Complex Network Theory, this study applies a novel methodology to four Madrid ACC sectors, analysing one month of flight track data. Multiple weighted spatial-temporal networks are built using 60 min intervals, allowing for the identification of critical nodes and the examination of interconnections and structural dynamics within the air traffic network. By incorporating temporal variations, the analysis uncovers evolving patterns. The research introduces an innovative approach for calculating potential conflicts by integrating radar data with airspace structure, thus offering a deeper understanding of sector risk profiles. The development of the SeSPe indicator, which combines historical safety data with topological features, enables a more informed and strategic evaluation of Air Traffic Management (ATM) system performance, ultimately contributing to safer and more efficient airspace operations.

Comparison of Physiological Stress Indices in Anesthetized and Manually Restrained Leopard Sharks, Triakis semifasciata

Background: Leopard sharks (Triakis semifasciata) are abundant, coastal, eastern Pacific, mesopredatory sharks and are frequently managed in aquariums and zoos. Medical examinations are a routine part of good husbandry practices, but the handling protocols vary greatly between facilities. In this study, we compared the physiological stress responses of T. semifasciata associated with manual restraint and sedated handling under parallel holding and handling procedures in a 10 min interval. Methods: Blood was collected and analyzed for the hematocrit (Hct), lactate, glucose, beta-hydroxybutyrate (β-HB), pH, blood gasses, 1α-hydroxycorticosterone (1α-OHB), and corticosterone (B). Results: Overall, a minimal physiological stress response was observed in both groups. However, statistically significant increases in the PCO2, β-HB and lactate occurred, while the pHTC, SO2, and BE decreased over time in the manual-restraint group. In the sedated group, the B, PCO2, and lactate increased while the pHTC, SO2, and base excess (BE) decreased over time. When comparing treatments, the sedated group had a higher B and PCO2 TC and a lower pHTC, BE, and SO2 than the manual-restraint group at the second time point. Conclusions: This study indicates that manual restraint is comparable to the described sedation in T. semifasciata for minimally invasive procedures. The overall results show that this species had low physiological stress responses to both methods.

Ultrafast and Ultrasensitive Bacterial Detection in Biofluids: Leveraging Resazurin as a Visible and Fluorescent Spectroscopic Marker.

Here we report the application of chemometric analysis for modeling absorbance spectroscopy and fluorescence emission data from a resazurin-based assay targeting low-level bacterial detection in biofluids. Bacteria spiked samples were incubated with resazurin and absorbance and fluorescence data were collected at 30 min intervals. The absorbance data was subjected to Principal Component Analysis (PCA) and Partial Least Squares Regression (PLSR) and compared with the univariate fluorescence spectroscopy approach. The analysis demonstrated the multidimensional nature of the absorbance data, highlighting the appearance of the resorufin peak at the 2 h time point with a low bacterial inoculum of 0.01 CFU mL-1 across all the samples tested-water, urine and serum. The PLSR models supported the PCA data and exhibited strong predictive capabilities for water (RC2 = 0.937, RCV2 = 0.934), urine (RC2 = 0.899, RCV2 = 0.880) and serum (RC2 = 0.985, RCV2 = 0.967). Conversely, fluorescence is contingent upon resorufin existence, necessitating a prolonged waiting period postincubation with resazurin to verify the presence of bacteria, especially when contamination levels are low. Given the substantial global impact of bacteria-related infections, this method detects bacteria at low concentrations precisely and rapidly, improving efficiency and adaptability for point-of-care settings, promising swift diagnosis of bacterial infections, environmental monitoring, or food-quality control.

Feasibility and accuracy of pediatric core temperature measurement using an esophageal probe inserted through the gastric lumen of a second-generation supraglottic airway device: a prospective observational study

Background: Accurate core temperature measurement in children is crucial; however, measuring esophageal temperature (TE) using a supraglottic airway device (SAD) can be challenging. Second-generation SADs, which have a gastric channel, can measure TE, and reduce gastric air volume. This study aimed to compare TE, measured using a probe inserted through the SAD gastric channel, with tympanic membrane (TTM) and forehead (TZHF) temperatures, measured using a zero-heat-flux cutaneous thermometer, with rectal temperature (TR). Methods: Temperature was recorded at 10-min intervals from 10 min after probe insertion until completion of surgery. We performed an equivalence test to evaluate whether the TE, TTM, and TZHF were equivalent to TR, with a margin of 0.3°C. Additionally, intraclass correlation coefficients (ICC) were calculated to assess the reliability of TE and TR at each time point.Results: We included 41 patients in the final analysis. In all patients, the esophageal probe was successfully inserted through the gastric channel of the SAD. When assessing agreement with TR as a reference, TE demonstrated equivalent results at all time points (P < 0.001 at 0, 10, 20, 30, and 40-min intervals and P = 0.018 at the 50-min interval), except at the completion of surgery (P = 0.697). TE also demonstrated good reliability with TR as a reference throughout the surgery (ICC > 0.75).Conclusions: In children with SAD insertion, TE can be accurately and feasibly measured through the SAD’s gastric channel, making it suitable for routine application.

Understanding novel neuromodulation pathways in tDCS: brain stem recordings in rats during trigeminal nerve direct current stimulation

tDCS is widely assumed to cause neuromodulation via the electric field in the cortex acting directly on cortical neurons. However, recent evidence suggests that tDCS may indirectly influence brain activity through cranial nerve pathways, notably the trigeminal nerve, but these neuromodulatory pathways remain unexplored. To investigate the first stages in this potential pathway we developed an animal model to study the effect of trigeminal nerve direct current stimulation (TN-DCS) on neuronal activity in the principal sensory nucleus (NVsnpr) and the mesencephalic nucleus of the trigeminal nerve (MeV). We conducted experiments on twenty-four male Sprague Dawley rats (n = 10 NVsnpr, n = 10 MeV during anodic stimulation, and n = 4 MeV during cathodic stimulation). DC stimulation, ranging from 0.5 to 3 mA, targeted the trigeminal nerve’s marginal branch. Concurrently, single-unit electrophysiological recordings were obtained using a 32-channel silicon probe, encompassing three 1-min intervals: pre, during, and post-stimulation. Xylocaine trigeminal nerve blockage served as a control. TN-DCS increased neuronal spiking activity in both NVsnpr and MeV, returning to baseline during the post-stimulation phase. The 3 mA DC stimulation of the blocked trigeminal nerve failed to induce increased spiking activity in the trigeminal nuclei. These findings provide empirical support for trigeminal nuclei modulation via TN-DCS, suggesting the cranial nerve pathways could play a role in mediating the tDCS effects in humans.

Integrating Thermal Infrared Imaging and Weather Data for Short-Term Prediction of Building Envelope Thermal Appearance

This study presents a novel deep-learning framework for predicting the thermal appearance of building envelopes under varying weather conditions based on a new dataset collected using a thermal infrared camera at 10 min intervals over a one-and-a-half-year period. Unlike existing studies that rely on simulated data or physical models that do not always accurately reflect the complex heat transfer processes in real buildings, we have collected a large dataset showing how a building behaves under different climatic conditions. We propose a novel deep-learning approach that integrates weather data and thermal imagery to predict the temperature distribution on the building façade for the next 24 and 48 h. The model uses a state-of-the-art recurrent neural network architecture, PredRNN V2, with an action conditioning mechanism to incorporate weather forecasting data into the prediction process. We evaluate this approach in terms of average accuracy, prediction accuracy in specific regions, and visual-perceptual performance of the images. The proposed framework achieves a prediction accuracy of 1.5 °C (root mean square error—RMSE) for the 24 h prediction and 2.04 °C (RMSE) for the 48 h prediction, outperforming baseline models in terms of temperature prediction accuracy and structural similarity of the predicted images.

Prediction of Carbon Dioxide Concentrations in Strawberry Greenhouse by Using Time Series Models

Carbon dioxide (CO2) concentrations play an important role in plant production, as they have a direct impact on both plant growth and yield. Therefore, the objectives of this study were to predict CO2 concentrations in the greenhouse by applying time series models using five datasets. To estimate the CO2 concentrations, this study was conducted over a four-month period from 1 December 2023 to 31 March 2024, in a strawberry-cultivating greenhouse. Fifteen sensors (MCH-383SD, Lutron, Taiwan) were installed inside the greenhouse to measure CO2 concentration at 1-min intervals. Finally, the dataset was transformed into intervals of 1, 5, 10, 30, and 60 min. The time-series data were analyzed using the autoregressive integrated moving average (ARIMA) and the Prophet Forecasting Model (PFM), with performance assessed through root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). The evaluation indicated that the best model performance was achieved with data collected at 1-min intervals, while model performance declined with longer intervals, with the lowest performance observed at 60-min intervals. Specifically, the ARIMA model outperformed across all data collection intervals while comparing with the PFM. The ARIMA model, with data collected at 1-min intervals, achieved an R2 of 0.928, RMSE of 7.359, and MAE of 2.832. However, both ARIMA and PFM exhibited poorer performances as the interval of data collection increased, with the lowest performance at 60-min intervals where ARIMA had an R2 of 0.762, RMSE of 19.469, and MAE of 11.48. This research underscores the importance of frequent data collection for precise environmental control in greenhouse agriculture, emphasizing the critical role of short-interval data collection for accurate predictive modeling.

Real-Time Indoor Environmental Quality (IEQ) Monitoring Using an IoT-Based Wireless Sensing Network

In recent years, our time spent indoors has risen to around 90% and to maintain an occupant’s comfort and well-being, Indoor Environmental Quality (IEQ) is monitored. Concerned with inhabitant’s satisfaction and health, the adoption of smart solutions for IEQ monitoring and improvement has expanded. The solution this study explores is an occupant-centric approach involving the implementation of an Internet of Things (IoT) IEQ sensing network in a prominent office skyscraper in Hong Kong. Over the course of 15 months, real-time IEQ data were collected from 12 locations within the building. The data were collected at 1-min time intervals and consisted of readings of indoor air temperature, radiant temperature, relative humidity, air velocity, carbon dioxide (CO2), particulate matter (PM10 and PM2.5), horizontal illuminance levels, and sound pressure levels, which served as the basis of the assessment made about the qualities of thermal comfort, indoor air quality (IAQ), aural comfort, and visual comfort. Compared to traditional periodic surveys, this IoT-based sensing network captured instantaneous environmental variations, providing valuable insights into the indoor environment’s spatial characterization and temporal dynamics. This smart solution also assisted facility management in terms of identifying sources of discomfort and developing effective mitigation strategies accordingly. This study presents an occupant-centric approach to improve occupant comfort and energy efficiency within office buildings. By customizing the built environment to enhance occupants’ well-being, comfort, and productivity, an emphasis is placed on a more personalized and occupant-focused design strategy. This approach integrates technical design with human experience, highlighting the importance of real-time physical and subjective surveys for achieving optimal results.

A Case Study on the Integration of Remote Sensing for Predicting Complicated Forest Fire Spread

Forest fires can occur suddenly and have significant environmental, economic, and social consequences. The timely and accurate evaluation and prediction of their progression, particularly the spread speed in difficult-to-access areas, are essential for emergency management departments to proactively implement prevention strategies and extinguish fires using scientific methods. This paper provides an analysis of models for predicting forest fire spread in China and globally. Incorporating remote sensing (RS) technology and forest fire science as the theoretical foundation, and utilizing the Wang Zhengfei forest fire spread model (1983), which is noted for its broad adaptability in China as the technical framework, this study constructs a forest fire spread model based on remote sensing interpretation. The model improves the existing model by adding elevation an factor and optimizes the method for acquiring certain parameters. By considering regional landforms (ridge lines, valley lines, and slopes) and vegetation coverage, this paper establishes three-dimensional visual interpretation markers for identifying hotspots; the orientation of the hotspots can be identified to simulate the spread of the fire uphill, downhill, in the direction of the wind, left-level slope, and right-level slope. Then, the data of Sentinel-2 and DEM were used to invert the fuel humidity and slope of pixels in the fire line areas. The statistical inversion data from pixels, which replaced fixed-point values in traditional models, were utilized for predicting forest fire spread speed. In this paper, the model was applied to the case of a forest fire in Mianning County, Sichuan Province, China, and verified using high-time-resolution Himawari-8 data, Gaofen-4 data, and historical data. The results demonstrate that the direction and maximum speed of fire spread for the fire lines in Baifen Mountai, Jiaguer Villageand, Muchanggou, Xujiabaozi, and Zhaizigou are uphill, 16.5 m/min; wind direction, 17.32 m/min; wind direction, 1.59 m/min; and wind direction, 5.67 m/min. The differences are mainly due to the locations of the fire lines, moisture content of combustibles, and maximum slopes being different. Across the entire fire line area, the average rate of increase in the area of open flames within one hour was 3.257 hm2/10 min (square hectares per 10 min), closely matching the average increase rate (3.297 hm2/10 min) monitored by the Himawari-8 satellite in 10 min intervals. In contrast, conventional fixed-point fire spread models predicted an average rate of increase of 3.5637 hm2/10 min, which shows a larger discrepancy compared to the Himawari-8 satellite monitoring results. Moreover, when compared to the fire spot monitoring results from the Gaofen-4 satellite taken 54 min after the initial location of the fire line, the predictions from the RS-enabled fire spread model, which integrates remote sensing interpretations, closely matched the actual observed fire boundaries. Although the predictions from the RS-enabled fire spread model and the traditional model both align with historical data in terms of the overall fire development trends, the RS-enabled model exhibits higher reliability and can provide more accurate information for forest fire emergency departments, enabling effective pre-emptive measures and scientific firefighting strategies.

Randomised controlled trial comparing different intersession intervals of intermittent theta burst delivered to the dorsal medial prefrontal cortex

BackgroundIntermittent theta burst stimulation (iTBS) is a form of repetitive transcranial magnetic stimulation (rTMS) that can be administered in a fraction of the time of standard rTMS. Applying multiple daily...

Habitual water intake impacted the body composition of young male athletes in free-living conditions: a cross-sectional study.

The study aimed to explore the associations between water intake and body composition and differences of body composition in different water itake and hydration statuses among young male athletes. A cross-sectional study was conducted among 111 young male athletes in Beijing, China. Total drinking fluids (TDF) and water from food were assessed using a 7-day, 24-h fluid intake record questionnaire and the duplicate portion method, respectively. The osmolality of 24-hour urine and blood samples was tested. Body composition was measured using a bioelectrical impedance analyzer twice at 5-min intervals. Participants were divided into two groups based on the recommendations of total water intake (TWI) and TDF in China, as well as into three groups based on 24-h urine osmolality. Pearson's correlation coefficients were calculated to determine the relationship between water intake and body composition. Chi-square tests and Student's t-tests were used to compare differences. A total of 109 participants completed the study. TDF (r = 0.230, p = 0.016; r = 0.234, p = 0.014; r = 0.242, p = 0.011) and TWI (r = 0.275, p = 0.004; r = 0.243, p = 0.011; r = 0.243, p = 0.011) were positively correlated with total body water (TBW), intracellular water (ICW), and extracellular water (ECW). TBW/body weight (BW) was positively associated with TDF percentage of BW (TDF/BW) (r = 0.267, p = 0.005), water from food percentage of BW (r = 0.217, p = 0.024), and TWI percentage of BW (TWI/BW) (r = 0.316, p = 0.001). Participants who met the TDF recommendation of China had 1.3 kg higher skeletal muscle mass (SMM), 0.9 kg higher ICW, and 0.5% higher TBW/BW than those who did not (all p < 0.05), with fat-free mass (FFM) and TBW being higher (p = 0.051; p = 0.050). Those who met the TWI recommendation of China had 1.3 kg higher SMM, 2.4 kg higher FFM, 1.1 kg higher ICW, 0.6 kg higher ECW, and 1.7 kg higher TBW than their counterparts (all p < 0.05). Moderate associations were found between water intake and body composition. No significant differences were observed among participants in three hydration statuses (all p > 0.05). Participants who met the TWI or TDF recommendations had better body composition distribution than their counterparts. Thus, habitual water intake, not hydration status, affects body composition among athletes in free-living conditions.

Bleaching efficacy, decomposition rate and pH of experimental bleaching gels incorporating bioactive materials

Aim: To evaluate the bleaching efficacy, decomposition rate, and pH of experimental gels containing 35% hydrogen peroxide (HP) and different concentrations of 45S5-bioglass (BG) or Biosilicate® (BS). Methods: Bovine enamel/dentin blocks (n=10) were allocated into the groups HP_BG or HP_BS (2.5, 5, 7.5 and 10 wt%) and HP (35% HP – positive control). The blocks were submitted to three sessions of 40 min and 7-day intervals. During the interval, the blocks were kept in artificial saliva at 37ºC. Color change (ΔE00) and whiteness index change (ΔWID) were determined after staining with black tea (T1) and 24 h after the 3rd bleaching session (T2). HP decomposition rate (%) and pH were evaluated for 40 min. Two-way ANOVA and Tukey analyzed ΔE00 and ΔWID data, while the Kruskal-Wallis test determined the decomposition rate and pH of the gels. Results: There were no differences in ΔE00 and ΔWID among the experimental bleaching gels containing BG or BS and 35% HP (p &gt; 0.05), but BG and BS gels displayed lower HP concentration than 35% HP, regardless of the bioactive material concentration (p &lt; 0.05). The experimental BG and BS gels exhibited alkaline pH (ranging from 9.28 to 9.82), which was higher than that of 35% HP (p &lt; 0.05). But regardless of the gel, all kept the pH values stable for 40 min. Conclusion: The experimental gels containing BG and BS did not hamper the 35% HP bleaching efficacy. Moreover, BG or BS gels decreased the hydrogen peroxide concentration and exhibited alkaline pH values.

Autonomic regulation in athletic horses repetitively participating in two novice jumping classes on consecutive days.

Animal welfare is of great concern in equestrian sports and has been evaluated in athletic horses competing at different levels. However, the impact of consecutive days of jumping competition and the extent of resultant stress responses remains unclear. To address this point, the present study compared the changes in stress response via heart rate variability (HRV) in horses participating in two national jumping events on consecutive days. The study involved six experienced horses equipped with heart rate monitoring devices. HRV variables were measured before, during, and after jumping at 10-min intervals for 60 min on each competition day. Multiple HRV variables decreased to varying degrees on both days from warm-up until 30 min post-jumping. Meanwhile, the mean heart rate increased during jumping and returned to normal levels at 50 min post-jumping on the first day (for all intervals, p < 0.05-0.001), while it remained elevated beyond 60 min post-jumping on the second day (for all intervals, p < 0.01-0.001). Additionally, maximum heart rate and respiratory rate were higher on the second day than in the first round during the warm-up phase (p < 0.05 for both variables). The proportion of the HRV low-frequency band was higher during riding on the second day (p < 0.05), while the proportion of the high-frequency band was reduced during warm-up on the first day (p < 0.05) and during course riding on the second (p < 0.01). Meanwhile, the sympathetic nervous system index took longer to return to baseline on the second day than on the first. These results suggest that autonomic regulation differed in horses between jumping rounds on two consecutive days, with horses experiencing higher sympathetic activity and potentially increased stress in the second round. This information is important for riders, highlighting the need to be mindful of potential stress that could, at least in part, impact the welfare of horses participating in the same jumping competition on consecutive days.

The higher oxygen consumption during multiple short intervals is sex-independent and not influenced by skeletal muscle characteristics in well-trained cyclists.

It has been suggested that time spent at a high fraction of maximal oxygen consumption (% O2max) plays a decisive role for adaptations to interval training. However, previous studies examining how interval sessions should be designed to achieve a high % O2max have exclusively been performed in males. The present study compared the % O2max attained during three different 6×8 min interval protocols, in female (n=11; O2max, 62.5 (6.4)mL·min-1·kg-1) and male (n=8; O2max, 81.0 (5.2)mL·min-1·kg-1) cyclists. Mean power output during work intervals were identical across the three interval protocols, corresponding to the cyclist's 40 min maximal effort (PO40min): (1) 30 s intervals at 118% of PO40min interspersed with 15 s active recovery at 60% (30/15), (2) constant pace at 100% of PO40min (CON), and (3) altering between 60 s intervals at 110% and 60 s at 90% of PO40min (60/60). Additionally, the study explored whether the m. vastus lateralis characteristics of the cyclists (fiber type proportion, capillarization, and citrate synthase activity) were associated with the % O2max attained during the interval sessions. Overall, mean % O2max and time ≥90% of O2max were higher during 30/15 compared to CON (86.7 (10.1)% and 1123 (787) s versus 85.0 (10.4)% and 879 (779) s, respectively; both p≤0.01) and 60/60 (85.6 (10.0)% and 917 (745) s, respectively; both p≤0.05), while no difference was observed between 60/60 and CON (both p≥0.36). During interval sessions, % O2max and time ≥90% of O2max did not differ between sexes. Skeletal muscle characteristics were not related to % O2maxduring interval sessions. In conclusion, well-trained cyclists demonstratehighest % O2max during 30/15, irrespective of sex and skeletal muscle characteristics.

Wind power prediction based on deep learning models: The case of Adama wind farm

Wind is a renewable energy source that is used to generate electricity. Wind power is one of the suitable solutions for global warming since it is free from pollution, doesn't cause greenhouse effects, and it is a natural source of energy. However, Wind power generation highly depends on weather conditions. It is very difficult to easily predict the amount of power generated from wind at a particular instant in time. Adama wind power farm is one of the wind farms in Ethiopia. There is no accurate and reliable forecasting model for the Adama wind farm that enables the forecasting of the power generated from the farm. The main objective of this research is to develop a wind power forecasting model for the Adama wind farm using deep learning techniques. Forecasting of wind power generation capacity involves appropriate modeling techniques that use past wind power generation data. The experiments have been conducted using Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (Bi-LSTM) and Gated Recurrent Unit (GRU). To achieve the highest forecasting accuracy, four years of data (from 2016 to 2019), with 5-min intervals, have been collected with a total of 163,802 rows. For hyperparameter optimization grid search and random search techniques have been utilized. The performances of the proposed deep learning models were investigated error metrics, including Mean Absolute Errors (MAE) and the Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE) and R squared (R2). Bi-LSTM outperforms the other two algorithms, scoring 0.644, 0.388, 0.769 and 0.978 MAE, MAPE, RMSE and R2 values respectively. Such wind power forecasting helps energy planners and regional power providers to compute power production and energy generated from other sources.

Using open-path dual-comb spectroscopy to monitor methane emissions from simulated grazing cattle

Abstract. Accurate whole-farm or herd-level measurements of livestock methane emissions are necessary for anthropogenic greenhouse gas inventories and to evaluate mitigation strategies. A controlled methane (CH4) release experiment was performed to determine if dual-comb spectroscopy (DCS) can detect CH4 concentration enhancements produced by a typical herd of beef cattle in an extensive grazing system. Open-path DCS was used to measure downwind and upwind CH4 concentrations from 10 point sources of methane simulating cattle emissions. The CH4 mole fractions and wind velocity data were used to calculate CH4 flux using an inverse dispersion model, and the simulated fluxes were then compared to the actual CH4 release rate. For a source located 60 m from the downwind path, the DCS system detected 10 nmol mol−1 CH4 horizontal concentration gradient above the atmospheric background concentration with a precision of 6 nmol mol−1 in 15 min interval. A CH4 release of 3970 g d−1 was performed, resulting in an average concentration enhancement of 24 nmol mol−1 of CH4. The calculated CH4 flux was 4002 g d−1, showing good agreement with the actual CH4 release rate. Periodically altering the downwind path, which may be needed to track moving cattle, did not adversely affect the ability of the instruments to determine the CH4 flux. These results give us confidence that CH4 flux can be determined by grazing cattle with low disturbance and direct field-scale measurements.