Search Results (660)

Pitaya (Selenicereus undatus) is a long-day climbing cactus that blooms in waves mostly on 1-year old, succulent leafless shoots called cladodes. Nonetheless, pitaya can also bloom on new-year growth if the buds of the cladodes are mature enough and competent for flower induction. Here, we tested, during two consecutive years, whether early pruning could have a positive effect on promoting more flowering waves, better fruiting, and heavier yield of ‘Korean White’ pitaya cultivated in unheated greenhouses of Southeastern Spain. The results show that pruning in January instead of March did not consistently modify the reproductive behavior of ‘Korean White’ pitaya in our conditions. Therefore, no significant effects on the number of blooming waves, flowering intensity, fruit set, quality or yield were observed. The only positive effect, not always significant, was an increase in fruit size that led to better fruit distribution into commercial categories in one out of the two experimental seasons. The lack of effect of early pruning was attributed to the prevalent low temperatures during winter in Spain. The results, however, suggest it is worthwhile exploring whether greenhouse heating with temperatures above pitaya’s base temperature may have the desired effects on increasing blooming waves. The profitability of this practice have to be carefully assessed. Full article

The somatic cell count (SCC) and differential somatic cell count (DSCC) are proxies for the udder health of dairy cattle, regarded as the criterion of mastitis identification with healthy, suspicious mastitis, mastitis, and chronic/persistent mastitis. However, SCC and DSCC are tested using flow cytometry, which is expensive and time-consuming, particularly for DSCC analysis. Mid-infrared spectroscopy (MIR) enables qualitative and quantitative analysis of milk constituents with great advantages, being cheap, non-destructive, fast, and high-throughput. The objective of this study is to develop a dairy cattle udder health status diagnostic model of MIR. Data on milk composition, SCC, DSCC, and MIR from 2288 milk samples collected in dairy farms were analyzed using the CombiFoss 7 DC instrument (FOSS, Hilleroed, Denmark). Three MIR spectral preprocessing methods, six modeling algorithms, and three different sets of MIR spectral data were employed in various combinations to develop several diagnostic models for mastitis of dairy cattle. The MIR diagnostic model of effectively identifying the healthy and mastitis cattle was developed using a spectral preprocessing method of difference (DIFF), a modeling algorithm of Random Forest (RF), and 1060 wavenumbers, abbreviated as “DIFF-RF-1060 wavenumbers”, and the AUC reached 1.00 in the training set and 0.80 in the test set. The other MIR diagnostic model of effectively distinguishing mastitis and chronic/persistent mastitis cows was “DIFF-SVM-274 wavenumbers”, with an AUC of 0.87 in the training set and 0.85 in the test set. For more effective use of the model on dairy farms, it is necessary and worthwhile to gather more representative and diverse samples to improve the diagnostic precision and versatility of these models. Full article

Objectives: This randomized controlled trial investigated the effects of an 8-week, volume-equated eccentric training program comprising Nordic hamstring and reverse Nordic exercises performed either once or twice per week on measures of physical fitness in pubertal male soccer players. Methods: A total of 34 participants were randomly assigned into a 1-day (n = 16; age = 14.58 ± 0.28 years) or 2-day (n = 18; age = 14.84 ± 0.22 years) per week training group. Physical fitness was assessed using 5 m and 10 m sprints, the 505 change in direction (CiD) speed test, Y-shaped agility test, countermovement jump (CMJ), and standing long jump (SLJ). Results: Significant group-by-time interactions were observed for the 505 CiD test, agility, and CMJ performance (effect sizes [ES] = 0.80 to 1.13). However, no significant interactions were found for the 5 and 10 m sprints or for SLJ (p > 0.05). Compared to the 1-day group, the 2-day training group showed greater improvements in CiD speed (∆7.36%; p < 0.001; ES = 0.92), agility (∆7.91%; p < 0.001; ES = 1.68), and CMJ (∆7.44%; p < 0.01; ES = 0.35), while no differences were observed in 5 and 10 m linear sprints or SLJ performance. According to individual response analysis, improvements across the physical fitness parameters beyond the smallest worthwhile change (SWC_0.2) were observed in 22–83% of players in the 1-day group and 77–100% in the 2-day group. Conclusions: In summary, the findings suggest that when training volume is matched, distributing the eccentric training regimen over two days per week may lead to greater improvements in CiD speed, agility, and CMJ performance compared to a single-day approach. Full article

Background: Change of direction (COD) and sprint abilities are essential in soccer, while reactive agility involves decision-making and perceptual/cognitive skills. This study aimed to examine the relationships between sprint speed, COD, and reactive agility in U12 soccer players. Methods: Thirty-three male players (age 10.40 ± 0.32 years) completed sprint tests (5 m, 10 m, 15 m), the Modified Agility T-Test (MAT), and the Y-Shaped Reactive Agility (Y-RSA) test, across two sessions. Results: The sprint, COD, and reactive agility tests showed high reliability. The Y-RSA test demonstrated strong reliability in regard to the initial sprint, COD-phase time, and total time. Significant correlations were found between sprint, COD, and reactive agility metrics. The sprint times were positively associated with the MAT and reactive agility times (e.g., sprint 15 m vs. total Y-RSA time: r = 0.740, p < 0.01). The smallest worthwhile changes (SWCs) indicated that these tests effectively detect performance improvements. Conclusions: This study demonstrated significant correlations between sprint speed, change of direction, and reactive agility in U12 soccer players, with the 15 m sprint showing the strongest association with reactive agility. These findings support the combined use of physical and perceptual/cognitive assessments to better inform soccer-specific training and evaluate the performance of youth players. Full article

Oat is a highly nutritious cereal crop, and the moisture content of its seeds plays a vital role in cultivation management, storage preservation, and quality control. To enable efficient and non-destructive prediction of this key quality parameter, this study presents a modeling framework integrating hyperspectral imaging (HSI) technology with a dual-optimization machine learning strategy. Seven spectral preprocessing techniques—standard normal variate (SNV), multiplicative scatter correction (MSC), first derivative (FD), second derivative (SD), and combinations such as SNV + FD, SNV + SD, and SNV + MSC—were systematically evaluated. Among them, SNV combined with FD was identified as the optimal preprocessing scheme, effectively enhancing spectral feature expression. To further refine the predictive model, three feature selection methods—successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), and principal component analysis (PCA)—were assessed. PCA exhibited superior performance in information compression and modeling stability. Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). Bayesian optimization was used for global tuning of network structural parameters, while ASFSSA was applied to fine-tune the initial weights and thresholds, improving convergence efficiency and predictive accuracy. The proposed Bayes-ASFSSA-BP model achieved determination coefficients (R²) of 0.982 and 0.963, and root mean square errors (RMSEs) of 0.173 and 0.188 on the training and test sets, respectively. The corresponding mean absolute error (MAE) on the test set was 0.170, indicating excellent average prediction accuracy. These results significantly outperformed benchmark models such as SSA-BP, ASFSSA-BP, and Bayes-BP. Compared to the conventional BP model, the proposed approach increased the test R² by 0.046 and reduced the RMSE by 0.157. Moreover, the model produced the narrowest 95% confidence intervals for test set performance (Rp²: [0.961, 0.971]; RMSE: [0.185, 0.193]), demonstrating outstanding robustness and generalization capability. Although the model incurred a slightly higher computational cost (480.9 s), the accuracy gain was deemed worthwhile. In conclusion, the proposed Bayes-ASFSSA-BP framework shows strong potential for accurate and stable non-destructive prediction of oat seed moisture content. This work provides a practical and efficient solution for quality assessment in agricultural products and highlights the promise of integrating Bayesian optimization with ASFSSA in modeling high-dimensional spectral data. Full article

Aerosols considerably reduce the upwelling radiance in the thermal infrared (IR) window; thus, it is worthwhile to understand the effects and challenges of assimilating aerosol-affected (i.e., hazy-sky) IR observations for all-sky data assimilation (DA). This study introduces an aerosol-aware DA framework for the Infrared Atmospheric Sounder Interferometer (IASI) to exploit hazy-sky IR observations and investigate the impact of assimilating hazy-sky IR observations on analyses and subsequent forecasts. The DA framework consists of the detection of hazy-sky pixels and an observation error model as the function of the aerosol effect. Compared to the baseline experiment, the experiment utilized an aerosol-aware framework that reduces biases in the sea surface temperature in the tropical region, particularly over the areas affected by heavy dust plumes. There are no significant differences in the evaluation of the analyses and the 7-day forecasts between the experiments. To further improve the aerosol-aware framework, the enhancements in quality control (e.g., aerosol detection) and bias correction need to be addressed in the future. Full article

Social justice has become the panacea for all types of concerns and issues—providing a sense that all concerns are worthwhile, comprehensive, and matter for today’s world. Thus, developing alternative concepts, ideas, and imaginaries can potentially provide solid grounds for scholars to advance beyond conventional understandings about social justice. Therefore, this manuscript aims to experiment with ethics of care as a conceptual device to disrupt Trumpism, as well as propose alternative worlds where sport, youth/athlete development, and social justice can connect otherwise. Specifically, efforts will be deployed to advance notions concerning sport–social justice in ways beyond our contemporary understandings. The work of feminist theorist and scholar Maria Puig de la Bellacasa (and many other human, non-human and more-than-human entities) is used to situate care as a relational doing. Moving forward, alternative worlds with alternative caring responsibilities matter if youth sport is to continuously thrive for justice. The conventional game of sport–social justice inquiry may have consequences and implications for caring that may be deemed unsustainable and continued sources of oppression. Therefore, caring becomes much more than a fact, a concern, or a concept. It becomes an ontological compromise, an ideal, and an ontological project for scholarly work, which implies a willingness to navigate towards the unknown and unprecedented—potentially our main caring responsibility as scholars. Full article

Background: Transcutaneous CO₂ (TcCO₂) measurement is widely used in the diagnosis and monitoring of ventilatory failure. Robust data on the success rates of measurement is scant. We aimed to discern the factors affecting the success rate of TcCO₂ measurement in a regional LTV service. Methods: Patients undergoing TcCO₂ measurement between October 2019 and January 2022 were identified retrospectively. Notes were analysed for basic demographics, indications for TcCO₂ measurement, measurement outcome, device used (Radiometer TCM5 or Sentec, based on availability), setup (self, carer, or clinician), inpatient or domiciliary study, and number of TcCO₂ measurement attempts occurred. Statistical comparisons were made by Fisher’s exact test. Results: We identified 435 recording events on 288 patients, mean age of 53, and 56% were males. A total of 189 (66%) had a neuromuscular disorder (NMD). The commonest indications for TcCO₂ measurement were ‘assessing ventilatory failure’ (43%) in treatment-naïve patients and ‘adequacy of ventilation therapy due to persistent symptoms’ (26%) in those established on LTV. Over 80% of our recording events were applied by patients or their carers. Overall, TCM5 devices had statistically higher successful recording rates (197/268, 73.5%) than Sentec (100/165, 60.6%) [p = 0.0056]. In domiciliary studies, TCM5’s success rate of 187/253 (73.9%) versus Sentec’s 94/154 (61.0%) was significantly better [p = 0.0079]. The success rate of each measurement attempt ranged between 62.9 and 67.0%, with up to three attempts on each subject. Conclusions: Home TcCO₂ is helpful in managing those with respiratory failure. Repeating tests after initial failure of recording is worthwhile. There may be differences in performance across devices which warrants further study. Full article

Background: Aneurysm-related subarachnoid hemorrhage is a life-threatening form of stroke. While medical image acquisition for aneurysm screening is limited to high-risk patients, advances in artificial intelligence (AI)-based image analysis suggest that AI-driven routine screening of imaging studies acquired for other clinical reasons could be valuable. Methods: A representative cohort of 1761 routine cranial magnetic resonance imaging scans [cMRIs] (with time-of-flight angiographies) from patients without previously known intracranial aneurysms was established by combining 854 general radiology 1.5T and 907 neuroradiology 3.0T cMRIs. TOF-MRAs were analyzed with a commercial AI algorithm for aneurysm detection. Neuroradiology consultants re-assessed cMRIs with AI results, providing Likert-based confidence scores (0–3) and work-up recommendations for suspicious findings. Original cMRI reports from more than 90 radiologists and neuroradiologists were reviewed, and patients with new findings were contacted for consultations including follow-up imaging (cMRI / catheter angiography [DSA]). Statistical analysis was conducted based on descriptive statistics, common diagnostic metrics, and the number needed to screen (NNS), defined as the number of cMRIs that must be analyzed with AI to achieve specific clinical endpoints. Results: Initial cMRI reporting by radiologists/neuroradiologists demonstrated a high risk of incidental aneurysm non-reporting (94.4% / 86.4%). A finding-based analysis revealed high AI algorithm sensitivities (100% [3T] / 94.1% [1.5T] for certain aneurysms of any size, well above 90% for any suspicious findings > 2 mm), associated with AI alerts triggered in 22% of cMRIs with PPVs of 7.5–25.2% (depending on the inclusion of inconclusive findings). The NNS to prompt further imaging work-/follow-up was 22, while the NNS to detect an aneurysm with a possible therapeutic impact was 221. Reference readings and patient consultations suggest that routine AI-driven cMRI screening would lead to additional imaging for 4–5% of patients, with 0.45% to 0.74% found to have previously undetected aneurysms with possibly therapeutic implications. Conclusions: AI-based second-reader screening substantially reduces incidental aneurysm non-reporting but may disproportionally increase follow-/work-up imaging demands also for minor or inconclusive findings with associated patient concern. Future research should focus on (subgroup-specific) AI optimization and cost-effectiveness analyses. Full article

Long-term ECMOs are expected to be put into practical use in order to prepare for the next emerging severe infectious diseases after the novel coronavirus pandemic in 2019–2023. While polypropylene (PP) and polymethylpentene (PMP) are currently the mainstream materials for the hollow fiber membranes of ECMO, the PP membrane coated with a silicone layer on the outer surface has also been commercialized. In this study, we sought a method to accurately observe the detailed pore morphologies of the PP membrane by suppressing irreversible changes in the morphology in SEM observation, which is a general-purpose observation with higher resolution. As a result, the convex surface morphologies of the PP membrane, which was a non-conductive porous structure, were confirmed in detail by utilizing the lower secondary electron image (LEI) mode (FE-SEM, JSM-7610F, JEOL Ltd., Tokyo, Japan) at low acceleration voltage, low magnification, and long working distance, to minimize morphological alterations caused by osmium (Os) sputtering. On the other hand, although the sputter-coating on non-conductive samples is mandatory for imaging morphologies with SEM, the non-sputtering method is also worthwhile for porous and fragile structures such as this sample to minimize morphological alterations. Furthermore, we propose a method to confirm the morphology of the deep part of the sample by utilizing the secondary electron image (SEI) mode at an appropriate acceleration voltage and high magnification with higher resolution. Full article

Proton-Exchange-Membrane Fuel Cell (PEMFC) systems are proving to be a promising solution for decarbonizing various means of transport, especially heavy ones. However, their reliability, availability, performance, durability, safety and operating costs are not yet fully competitive with industrial and commercial systems (actual systems). Predictive maintenance (PrM) is proving to be one of the most promising solutions for improving these critical points. In this paper, several PrM approaches will be developed considering the constraints of actual systems. The first approach involves estimating the overall State of Health (SOH) of a PEMFC operating under a dynamic load according to an FC-DLC (Fuel Cell Dynamic Load Cycle) profile, using a Health Indicator (HI). This section will also discuss the relevance of current End-of-Life (EoL) indicators by putting the performance, safety and economic profitability of PEMFC systems into perspective. The second approach involves predicting the voltage of the PEMFC while operating under this same profile in order to estimate its overall Remaining Useful Life (RUL). Finally, the last approach proposed will make it possible to estimate the time when it will be worthwhile, or even economically necessary, to replace a degraded PEMFC with a new one. Full article

To pursue the total decarbonization goal set at 2050, the introduction of hydrogen to replace the usage of fossil fuel in hard-to-abate industrial sectors is crucial. Hydrogen will replace natural gas in hard-to-abate sectors where natural gas is required to make heat necessary for the industrial process. Naturally, all this is worthwhile if hydrogen is produced following a green pathway, meaning that it is connected with renewable sources. In this manuscript, a techno-economic analysis related to a real case scenario is carried out. The real system addressed involves continuous high-temperature industrial furnace operation with a seasonally variable but stable thermal energy demand, representing typical conditions of hard-to-abate industrial processes. Solar photovoltaic panels combined with batteries are used to generate and store electricity that in turn is used to generate green hydrogen. Different scenarios are considered, including mixed natural gas/hydrogen, the seasonal variability of industrial needs, and the variability of solar production. The economic aspects considered include the usage of anion exchange membrane water electrolyzers (AEMWEs) to produce green hydrogen, the improvement in efficiency during operations (operational costs, OPEX), and the decrease in the AEMWE cost (Capital expenditures, CAPEX) that occur over time. The study shows that the hydrogen production cost could decrease from 12.6 EUR kg⁻¹ in 2024 to 9.7 EUR kg⁻¹ in 2030, with further reduction to 8.7 EUR kg⁻¹ achievable through seasonal blending strategies. CO₂ emissions are significantly reduced through partial displacement of natural gas with green hydrogen, highlighting the environmental potential of the system. Full article

Background/Objectives: Pharmacogenetic (PGx) testing can predict drug efficacy, toxicity, and risk of adverse drug reactions (ADRs). However, PGx-guided prescribing for pediatric chronic pain is underutilized. Methods: We evaluated the rate of deviance from standard drug dosing regimens in children and adolescents with chronic pain based on PGx testing of drug-metabolizing genes. We also assessed the acceptability and feasibility of PGx testing and implementation of PGx-guided recommendations from patient, caregiver, and prescriber perspectives. Finally, we explored whether PGx results could predict self-reported therapeutic responses and/or ADRs to medications. Results: Forty-eight participants aged 8–17 years with chronic pain provided DNA via buccal swab. Genetic variant data for CYP2D6, CYP2C9, and CYP2C19 metabolism genes and associated metabolizer status were analyzed with respect to clinical PGx guidelines for dosing recommendations of analgesics and psychotropic medications. Participants, their caregivers, and their prescribers also completed quantitative questionnaires evaluating their experience with PGx testing. Twenty-three (50%) participants were predicted to benefit from non-standard dosing for medications with clinical PGx guidelines. Participants expressed satisfaction with the PGx testing process and felt it was safe and worthwhile. Prescribers also reported that PGx results were relevant for medication choices in 42 (91%) participants. Seven (15%) participants had genotyping results which may have predicted their self-reported therapeutic responses and/or ADRs to specific medications. Conclusions: Though further research on pharmacodynamic associations is required to sufficiently address the complexity of interpatient responses to medications for the treatment of pediatric pain and mental health conditions, PGx testing may be used to inform individualized medication choices based on genetic make-up. Full article

Background: This study examined external intensity and acute neuromuscular responses across multiple games played during a single-day official 3 × 3 basketball tournament. Methods: Twelve male players (Tier 2–3; age: 24.7 ± 4.5 years; height: 186.4 ± 8.5 cm; body mass: 86.5 ± 13.0 kg) were monitored with microsensors (Movement Intensity (MI), while countermovement jump (CMJ) variables—jump height (JH); time to takeoff (TTTO); and Modified Reactive Strength Index (RSI_mod)—were obtained before the start of the tournament and after each game. Linear mixed models examined differences in MI and CMJ variables across tournament phases. Additionally, the smallest worthwhile change (SWC) calculations were applied to all comparisons. Results: No statistical differences were found across tournament stages for MI (p = 0.466), JH (p = 0.762), TTTO (p = 0.990), or RSI_mod (p = 0.951). SWC comparisons showed that MI was higher in GG1 than GG2, GG3, and QF; higher in GG2 than GG3; and lower in G3 than QF and SF. Regarding JH, the post-QF value was higher than the baseline and post-GG2. For TTTO, post-QF was higher than post-GG1. RSI_mod post-GG2 was lower than post-GG3 and post-SF. Conclusions: While no significant changes were observed, MI showed a practically meaningful decline in GG3 and recovery in QF, while RSI_mod initially declined before improving post-SF. These findings highlight the importance of pacing and recovery strategies in 3 × 3 basketball tournaments. Full article

Background: There is currently no study examining the mental health consequences of deployed German service members in Iraq. The aim is, therefore, to determine the cumulative incidence and latency period until the first diagnosis of deployment-related mental disorders. We hypothesized a lower rate than for Afghanistan with 2.4%. Methods: All registered N = 1635 German military personnel who were deployed to the mission “Training support contingent Northern Iraq” between 2015 and 2018 were included. Individuals with mental disorders attributed to this deployment were identified in a central database. Differences in latency between diagnoses were calculated by t-tests for independent samples. Results: By January 2024, n = 55 (3.4%) individuals had been recorded who developed a mental disorder as a result of this deployment. Most of them (54.5%) had a post-traumatic stress disorder (PTSD) as the main or comorbid diagnosis. There were no gender differences in the cumulative incidence (male 3.6%; female 2.9). The latency period between the onset of disease and initial diagnosis was, on average, 1.0 years (standard deviation 1.1 years; Q₂₅ < 1 year, Q₅₀ = 1 year and Q₇₅ = 2 years). With 1.3 vs. 0.6 years, the latency was significantly longer for individuals with PTSD. Conclusions: The cumulative incidence appears to be higher after the Iraq deployment than after most other Bundeswehr deployments. This is attributed to particular threats. The latency period is higher for those affected with PTSD than with other disorders. This could be due to a higher degree of stigmatization. It is, therefore, worthwhile to compare the different deployments in order to be able to derive better preventive and aftercare measures as well as destigmatization programs to prevent chronification. Full article