bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectiveness of pharmacist-led medication reconciliation on medication errors at hospital discharge and healthcare utilization in the next 30 days: a pragmatic clinical trial
Authors: Jošt Maja , Kerec Kos Mojca , Kos Mitja , Knez Lea
Published: March 2024

Transitions of care often lead to medication errors and unnecessary healthcare utilization. Medication reconciliation has been repeatedly shown to reduce this risk. However, the great majority of evidence is limited to the provision of medication reconciliation within clinical trials and countries with well-established clinical pharmacy. Thus, this pragmatic, prospective, controlled trial evaluated the effectiveness of routine pharmacist-led medication reconciliation compared to standard care on medication errors and unplanned healthcare utilization in adult general medical patients hospitalized in a teaching hospital in Slovenia. All patients hospitalized in a ward where medication reconciliation was integrated into routine clinical practice were included in the intervention group and received admission and discharge medication reconciliation, coupled with patient counselling. The control group consisted of randomly selected patients from the remaining medical wards. The primary study outcome was unplanned healthcare utilization within 30 days of discharge, and the secondary outcomes were clinically important medication errors at hospital discharge and serious unplanned healthcare utilization within 30 days of discharge. Overall, 414 patients (53.4% male, median 71 years) were included—225 in the intervention group and 189 in the control group. In the intervention group, the number of patients with clinically important medication errors at discharge was significantly lower (intervention vs control group: 9.3% vs 61.9%). Multiple logistic regression revealed that medication reconciliation reduced the likelihood of a clinically important medication error by 20-fold, while a higher number of medications on admission was associated with an increased likelihood. However, no significant differences were noted in any and serious unplanned healthcare utilization (intervention vs control group: 33.9% vs 27.8% and 20.3% vs 14.6%, respectively). The likelihood of serious healthcare utilization increased with the age of the patient, the number of medications on admission and being hospitalized for an acute medical condition. Our pragmatic trial confirmed that medication reconciliation, even when performed as part of routine clinical practice, led to a substantial reduction in the risk of clinically important medication errors at hospital discharge but not to a reduction in healthcare utilization. Medication reconciliation is a fundamental, albeit not sufficient, element to ensure patient safety after hospital discharge.

Clinical Trial Registration:https://clinicaltrials.gov/search?id=NCT06207500, identifier NCT06207500
Simulating short-term light responses of photosynthesis and water use efficiency in sweet sorghum under varying temperature and CO2 conditions
Authors: Yang Xiao-Long , Ma Xiao-Fei , Ye Zi-Piao , Yang Long-Sheng , Shi Jun-Bo , Wang Xun , Zhou Bei-Bei , Wang Fu-Biao , Deng Zi-Fa
Published: March 2024

Climate change, characterized by rising atmospheric CO2 levels and temperatures, poses significant challenges to global crop production. Sweet sorghum, a prominent C4 cereal extensively grown in arid areas, emerges as a promising candidate for sustainable bioenergy production. This study investigated the responses of photosynthesis and leaf-scale water use efficiency (WUE) to varying light intensity (I) in sweet sorghum under different temperature and CO2 conditions. Comparative analyses were conducted between the An-I, gs-I, Tr-I, WUEi-I, and WUEinst-I models proposed by Ye et al. and the widely utilized the non-rectangular hyperbolic (NRH) model for fitting light response curves. The Ye's models effectively replicated the light response curves of sweet sorghum, accurately capturing the diminishing intrinsic WUE (WUEi) and instantaneous WUE (WUEinst) trends with increasing I. The fitted maximum values of An, gs, Tr, WUEi, and WUEinst and their saturation light intensities closely matched observations, unlike the NRH model. Despite the NRH model demonstrating high R2 values for An-I, gs-I, and Tr-I modelling, it returned the maximum values significantly deviating from observed values and failed to generate saturation light intensities. It also inadequately represented WUE responses to I, overestimating WUE. Across different leaf temperatures, An, gs, and Tr of sweet sorghum displayed comparable light response patterns. Elevated temperatures increased maximum An, gs, and Tr but consistently declined maximum WUEi and WUEinst. However, WUEinst declined more sharply due to the disproportionate transpiration increase over carbon assimilation. Critically, sweet sorghum An saturated at current atmospheric CO2 levels, with no significant gains under 550 μmol mol−1. Instead, stomatal closure enhanced WUE under elevated CO2 by coordinated gs and Tr reductions rather than improved carbon assimilation. Nonetheless, this response diminished under simultaneously high temperature, suggesting intricate interplay between CO2 and temperature in modulating plant responses. These findings provide valuable insights into photosynthetic dynamics of sweet sorghum, aiding predictions of yield and optimization of cultivation practices. Moreover, our methodology serves as a valuable reference for evaluating leaf photosynthesis and WUE dynamics in diverse plant species.
A deep multi-task learning approach to identifying mummy berry infection sites, the disease stage, and severity
Authors: Qu Hongchun , Zheng Chaofang , Ji Hao , Huang Rui , Wei Dianwen , Annis Seanna , Drummond Francis
Published: March 2024

Introduction

Mummy berry is a serious disease that may result in up to 70 percent of yield loss for lowbush blueberries. Practical mummy berry disease detection, stage classification and severity estimation remain great challenges for computer vision-based approaches because images taken in lowbush blueberry fields are usually a mixture of different plant parts (leaves, bud, flowers and fruits) with a very complex background. Specifically, typical problems hindering this effort included data scarcity due to high manual labelling cost, tiny and low contrast disease features interfered and occluded by healthy plant parts, and over-complicated deep neural networks which made deployment of a predictive system difficult.

Methods

Using real and raw blueberry field images, this research proposed a deep multi-task learning (MTL) approach to simultaneously accomplish three disease detection tasks: identification of infection sites, classification of disease stage, and severity estimation. By further incorporating novel superimposed attention mechanism modules and grouped convolutions to the deep neural network, enabled disease feature extraction from both channel and spatial perspectives, achieving better detection performance in open and complex environments, while having lower computational cost and faster convergence rate.

Results

Experimental results demonstrated that our approach achieved higher detection efficiency compared with the state-of-the-art deep learning models in terms of detection accuracy, while having three main advantages: 1) field images mixed with various types of lowbush blueberry plant organs under a complex background can be used for disease detection; 2) parameter sharing among different tasks greatly reduced the size of training samples and saved 60% training time than when the three tasks (data preparation, model development and exploration) were trained separately; and 3) only one-sixth of the network parameter size (23.98M vs. 138.36M) and one-fifteenth of the computational cost (1.13G vs. 15.48G FLOPs) were used when compared with the most popular Convolutional Neural Network VGG16.

Discussion

These features make our solution very promising for future mobile deployment such as a drone carried task unit for real-time field surveillance. As an automatic approach to fast disease diagnosis, it can be a useful technical tool to provide growers real time disease information that can prevent further disease transmission and more severe effects on yield due to fruit mummification.
Geographical patterns and environmental influencing factors of variations in Asterothamnus centraliasiaticus seed traits on Qinghai-Tibetan plateau
Authors: Li ZhengSheng , Ma YuShou , Liu Ying , Wang YanLong , Wang XinYou
Published: March 2024

Introduction

Seed traits related to recruitment directly affect plant fitness and persistence. Understanding the key patterns and influencing factors of seed trait variations is conducive to assessing plant colonization and habitat selection. However, the variation patterns of the critical seed traits of shrub species are usually underrepresented and disregarded despite their vital role in alpine desert ecosystems.

Methods

This study gathered seeds from 21 Asterothamnus centraliasiaticus populations across the Qinghai-Tibetan Plateau, analyzing geographical patterns of seed traits to identify external environmental influences. Additionally, it explored how seed morphology and nutrients affect germination stress tolerance, elucidating direct and indirect factors shaping seed trait variations.

Results

The results present substantial intraspecific variations in the seed traits of A. centraliasiaticus. Seed traits except seed length-to-width ratio (LWR) all vary significantly with geographic gradients. In addition, the direct and indirect effects of climatic variables and soil nutrients on seed traits were verified in this study. Climate mainly influences seed nutrients, and soil nutrients significantly affect seed morphology and seed nutrients. Furthermore, climate directly impacts seed germination drought tolerance index (GDTI) and germination saline-alkali tolerance index (GSTI). Seed germination cold tolerance index (GCTI) is influenced by climate and soil nutrients (mostly SOC). GDTI and GSTI are prominently influenced by seed morphology (largely the seed thousand-grain weight (TGW)), and GCTI is evidently affected by seed nutrients (mainly the content of soluble protein (CSP)).

Discussion

The findings of this study amply explain seed trait variation patterns of shrubs in alpine desert ecosystems, possessing significant importance for understanding the mechanism of shrub adaptation to alpine desert ecosystems, predicting the outcomes of environmental change, and informing conservation efforts. This study can be a valuable reference for managing alpine desert ecosystems on the Qinghai-Tibetan Plateau.
Glutamine as sole nitrogen source prevents induction of nitrate transporter gene NRT2.4 and affects amino acid metabolism in Arabidopsis
Authors: Svietlova Nataliia , Zhyr Liza , Reichelt Michael , Grabe Veit , Mithöfer Axel
Published: March 2024

Plants assimilate inorganic nitrogen (N) to glutamine. Glutamine is the most abundant amino acid in most plant species, the N-supplying precursor of all N-containing compounds in the cell and the first organic nitrogen molecule formed from inorganic nitrogen taken up by the roots. In addition to its role in plant nutrition, glutamine most likely also has a function as a signaling molecule in the regulation of nitrogen metabolism. We investigated whether glutamine influences the high-affinity transporter system for nitrate uptake. Therefore, we analyzed the expression of the nitrate transporter NRT2.4, which is inducible by N deficiency, in Arabidopsis thaliana grown under different nitrogen starvation scenarios, comparing nitrate or glutamine as the sole nitrogen source. Using the reporter line ProNRT2.4:GFP and two independent knockout lines, nrt2.4-1 and nrt2.4-2, we analyzed gene expression and amino acid profiles. We showed that the regulation of NRT2.4 expression depends on available nitrogen in general, for example on glutamine as a nitrogen source, and not specifically on nitrate. In contrast to high nitrate concentrations, amino acid profiles changed to an accumulation of amino acids containing more than one nitrogen during growth in high glutamine concentrations, indicating a switch to nitrogen storage metabolism. Furthermore, we demonstrated that the nrt2.4-2 line shows unexpected effects on NRT2.5 gene expression and the amino acids profile in shoots under high glutamine supply conditions compared to Arabidopsis wild type and nrt2.4-1, suggesting non-NRT2.4-related metabolic consequences in this knockout line.
Increased sensitivity for negative emotional images in individuals with problematic pornography use
Authors: Qu Shuangyi , Li Ruiyu , Wang Jianfeng
Published: March 2024

Background

Despite the frequent comorbidity of affective and addictive disorders, the significance of affective dysregulation in problematic pornography use (PPU) is commonly disregarded. The objective of this study is to investigate whether individuals with PPU demonstrate increased sensitivity to negative emotional stimuli in comparison to healthy controls (HCs).

Methods

Electrophysiological responses were captured via event-related potentials (ERPs) from 27 individuals with PPU and 29 HCs. They completed an oddball task involving the presentation of deviant stimuli in the form of highly negative (HN), moderately negative (MN), and neutral images, with a standard stimulus being a neutral kettle image. To evaluate participants' subjective feelings of valence and arousal, the Self-Assessment Manikin (SAM) was employed.

Results

Regarding subjective evaluations, individuals with PPU indicated diminished valence ratings for HN images as opposed to HCs. Concerning electrophysiological assessments, those with PPU manifested elevated N2 amplitudes in response to both HN and MN images when contrasted against neutral images. Additionally, PPU participants displayed an intensified P3 response to HN images in contrast to MN images, a distinction not evident within the HCs.

Discussion

These outcomes suggest that individuals with PPU exhibited heightened reactivity toward negative stimuli. This increased sensitivity to negative cues could potentially play a role in the propensity of PPU individuals to resort to pornography as a coping mechanism for managing stress regulation.
Parents’ perceptions of the impact of the novel coronavirus (COVID-19) on the eating behaviors and routines of children with autism spectrum disorders (ASD)
Authors: Alharbi Mudi H.
Published: March 2024

Background

Restricted interests and repetitive behavior are characteristics of autism spectrum disorder (ASD). The likelihood that persons with ASD will respond adversely to unfamiliar situations is great. The novel coronavirus outbreak has resulted in disruptions to all aspects of routine and behavior. Hence, this study proposed to investigate the impact of the outbreak on the eating behavior and routines of children with ASD in Saudi Arabia through the perceptions of their parents.

Method

A cross-sectional study with a quantitative approach was utilized to obtain data from 150 parents of children with ASD aged ≤18 years in Saudi Arabia. The data collected included demographic data of the parents, the ASD status of the family, impact of COVID-19 to the family, eating behavior of the children with ASD, and daily routines of the children with ASD. Moreover, parents were able to provide comments regarding their children’s eating behavior or daily routines.

Results

The study found that changes in the eating behavior of children with ASD were found to differ significantly (p<0.05) based on the number of children with ASD, the age of the children with ASD, the gender of the children with ASD, and the severity of their ASD symptoms. Moreover, changes to dinner-time routines were found to differ significantly (p<0.05) based on the age of the children with ASD. Also, changes to morning routines were found to differ significantly (p<0.05) based on the age of the children with ASD, their gender, and the severity of their ASD symptoms. Additionally, impact of COVID-19 to the family had a significant impact to eating behavior and daily routines of the children with ASD.

Conclusion

This study found that the eating behavior and daily routines of children with ASD in Saudi Arabia have been considerably worsened and changed. The study recommends the collaboration of multidisciplinary teams and parents to modify or design interventions that help to change their eating behavior and routine can be implemented in the home. It also recommends the provision of virtual helplines to aid parents of children with ASD in such cases.
Evaluation of China’s long-term care insurance policies
Authors: Li Qiang , Chen Yiwen , Zhang Yongmei , Liu Xue
Published: March 2024

Introduction

In response to the increasing demand for long-term care services for older people, the Chinese government has launched a pilot program for long-term care insurance (LTCI) since 2016. The objective of this study is to evaluate the performance and effectiveness of this program in China and provide recommendations for the future development and expansion of the LTCI system.

Methods

We developed a comprehensive evaluation framework to assess these LTCI policies implemented in all 49 pilot cities in China.

Results

Based on our evaluation, the average assessment score for the LTCI program across all pilot cities was 71.8 points, with scores ranging from 57.5 to 92.5 points in these cities. Furthermore, most of the pilot cities achieved higher scores in the fact-based assessment compared to the value-based assessment.

Discussion

The results suggested that the overall pilot effect regarding LTCI was favorable, but there were significant regional disparities. Moreover, in most of pilot cities, current LTCI policies were designed to alleviate both the financial burden and the burden of caring for people with disabilities that families faced. However, some challenges still remained, such as the lack of community and home-based care services, the need to expand the coverage of insurance, and the importance of diversifying funding sources.
The relationship between self-reported poor mental health and complete tooth loss among the US adult population in 2019
Authors: Powell Tasha , Taylor Heather
Published: March 2024

Objective

Very little is known about the association between poor mental health and poor oral health outcomes in the United Sates. This study investigated the prevalence of complete tooth loss among those with and without perceived poor mental health in a nationally representative sample of noninstitutionalized U.S. adults.

Methods

Using a cross-sectional study design, we analyzed the 2019 Medical Expenditures Panel Survey to determine the unweighted and weighted prevalence of complete tooth loss among adults. Chi-squared and multivariate logit regression with marginal effects were used to measure the association between complete tooth loss and perceived poor mental health, controlling for respondent characteristics.

Results

The prevalence of adults (ages 18 and older) experiencing complete tooth loss was 6% (95% CI: 5.6–6.4). Individuals who have perceived poor mental health were 1.90 percentage points (pps) more likely to report missing all their natural teeth (P = 0.006: 95% CI: 0.5–3.3). Other relevant predictors of complete tooth loss included current smoking status (5.9 pps; 95% CI: 4.5 to 7.2) and secondary education (−6.4 pps (95% CI: −7.0 to −4.8).

Conclusions

Overall, self-reported poor mental health was found to be associated with a greater likelihood of reporting complete tooth loss. Findings from this study underscore the need for greater integration of care delivery between behavioral health specialists and dental providers.
Dynamic Events in the Flexible Job-Shop Scheduling Problem: Rescheduling with a Hybrid Metaheuristic Algorithm
Authors: Fuladi Shubhendu Kshitij , Kim Chang-Soo
Published: March 2024

In the real world of manufacturing systems, production planning is crucial for organizing and optimizing various manufacturing process components. The objective of this paper is to present a methodology for both static scheduling and dynamic scheduling. In the proposed method, a hybrid algorithm is utilized to optimize the static flexible job-shop scheduling problem (FJSP) and dynamic flexible job-shop scheduling problem (DFJSP). This algorithm integrates the genetic algorithm (GA) as a global optimization technique with a simulated annealing (SA) algorithm serving as a local search optimization approach to accelerate convergence and prevent getting stuck in local minima. Additionally, variable neighborhood search (VNS) is utilized for efficient neighborhood search within this hybrid algorithm framework. For the FJSP, the proposed hybrid algorithm is simulated on a 40-benchmark dataset to evaluate its performance. Comparisons among the proposed hybrid algorithm and other algorithms are provided to show the effectiveness of the proposed algorithm, ensuring that the proposed hybrid algorithm can efficiently solve the FJSP, with 38 out of 40 instances demonstrating better results. The primary objective of this study is to perform dynamic scheduling on two datasets, including both single-purpose machine and multi-purpose machine datasets, using the proposed hybrid algorithm with a rescheduling strategy. By observing the results of the DFJSP, dynamic events such as a single machine breakdown, a single job arrival, multiple machine breakdowns, and multiple job arrivals demonstrate that the proposed hybrid algorithm with the rescheduling strategy achieves significant improvement and the proposed method obtains the best new solution, resulting in a significant decrease in makespan.
Regression Rate and Combustion Efficiency of Composite Hybrid Rocket Grains Based on Modular Fuel Units
Authors: Pan Junjie , Lin Xin , Wang Zezhong , Wang Ruoyan , Wu Kun , Liang Jinhu , Yu Xilong
Published: March 2024

This study investigated combustion characteristics of composite fuel grains designed based on a modular fuel unit strategy. The modular fuel unit comprised a periodical helical structure with nine acrylonitrile–butadiene–styrene helical blades. A paraffin-based fuel was embedded between adjacent blades. Two modifications of the helical structure framework were researched. One mirrored the helical blades, and the other periodically extended the helical blades by perforation. A laboratory-scale hybrid rocket engine was used to investigate combustion characteristics of the fuel grains at an oxygen mass flux of 2.1–6.0 g/(s·cm2). Compared with the composite fuel grain with periodically extended helical blades, the modified composite fuel grains exhibited higher regression rates and a faster rise of regression rates as the oxygen mass flux increased. At an oxygen mass flux of 6.0 g/(s·cm2), the regression rate of the composite fuel grains with perforation and mirrored helical blades increased by 8.0% and 14.1%, respectively. The oxygen-to-fuel distribution of the composite fuel grain with mirrored helical blades was more concentrated, and its combustion efficiency was stable. Flame structure characteristics in the combustion chamber were visualized using a radiation imaging technique. A rapid increase in flame thickness of the composite fuel grains based on the modular unit was observed, which was consistent with their high regression rates. A simplified numerical simulation was carried out to elucidate the mechanism of the modified modular units on performance enhancement of the composite hybrid rocket grains.
Optimizing Straw Mulching Methods to Control Soil and Water Losses on Loess Sloped Farmland
Authors: Zhao Xinkai , Song Xiaoyu , Wang Danyang , Li Lanjun , Meng Pengfei , Fu Chong , Wang Long , Wei Wanyin , Yang Nan , Liu Yu , Li Huaiyou
Published: March 2024

Straw mulching is a key method for controlling soil and water losses. Mulching costs may be reduced by applying it in strips rather than over entire areas. However, the effect of different straw mulching methods on the effectiveness of reducing soil erosion is unclear. In this study, the effects of straw mulching strip length (covering 1/4, 1/2, 3/4, and 4/4 of the slope length) and coverage rate (0.2, 0.5, and 0.8 kg m−2) on interception, infiltration, runoff, and soil erosion were investigated at the plot scale using rainfall simulation experiments. The further complex correlations between these variables were analyzed using structural equation modeling (SEM). Bare slopes were used as a control group. The rainfall intensity was chosen to be 60 mm h−1. The results showed that (1) the modified Merriam interception model can describe the change in interception with time under straw mulching conditions well (R2 > 0.91, NSE > 0.75). (2) A total of 35.39–78.79% of the rainwater is converted into infiltration on straw-covered slopes, while this proportion is 36.75% on bare slopes. The proportion of rainwater converted to infiltration was greatest (78.79%) when the straw covered 3/4 of the slope length at a coverage rate of 0.5 kg m−2, which was the most conducive to rainwater harvesting on the slope. (3) Straw mulching protects the topsoil from the impact of raindrops and directly affects the sediment yield (direct effect = −0.44). Straw mulching can also indirectly affect sediment yield by increasing interception, reducing runoff, and decreasing the sediment carrying capacity of runoff (indirect effect = −0.83). Compared with bare slopes, straw covering at least 1/2 of the slope length can significantly reduce runoff yield, but straw covering only 1/4 of the slope length can significantly reduce sediment yield. Moreover, once the straw mulch slope length reaches 3/4 and the coverage rate reaches 0.5 kg m−2, further increases in mulch slope length and coverage rate will not significantly reduce the runoff and sediment yields. These results assessed the effectiveness of different straw mulching methods in controlling soil and water losses on sloping farmland.
Transcriptomic and Metabolomic Analyses Reveal the Response to Short-Term Drought Stress in Bread Wheat (Triticum aestivum L.)
Authors: Fu Xiaoyi , Liu Zhilian , Du Xiong , Duan Huijun , Zhen Wenchao , Zhang Yuechen , Shi Zhanliang , He Mingqi , Li Ruiqi
Published: March 2024

Drought stress, a major abiotic stress, significantly affects wheat (Triticum aestivum L.) production globally. To identify genes and metabolic pathways crucial for responding to short-term drought stress, we conducted transcriptomic and metabolomic analyses of winter wheat cultivar Jimai 418 at four developmental stages: jointing (GS31), booting (GS45), anthesis (GS65), and 8 days after anthesis (DAA8). Transcriptomic analysis identified 14,232 differentially expressed genes (DEGs) under drought stress compared to the control. Specifically, 1387, 4573, 7380, and 892 DEGs were identified at the four developmental stages, respectively. Enriched pathways associated with these DEGs included plant hormone signal transduction, mitogen-activated protein kinase (MAPK) signaling, galactose metabolism, and starch and sucrose metabolism. Totals of 222, 633, 358, and 38 differentially accumulated metabolites (DAMs) were identified at the four stages, respectively. Correlation analysis of both datasets revealed DEGs and DAMs associated with plant hormone signal transduction, arginine and proline metabolism, ABC transporters, and amino acid biosynthesis. These findings offer significant insights into Jimai 418’s molecular response to short-term drought stress. The identified DEGs, DAMs, and enriched pathways contribute to our understanding of wheat drought tolerance. This research will facilitate further investigations into drought tolerance mechanisms and guide the breeding of wheat varieties with enhanced drought resistance.
Trend Prediction of Vegetation and Drought by Informer Model Based on STL-EMD Decomposition of Ha Cai Tou Dang Water Source Area in the Maowusu Sandland
Authors: Zheng Hexiang , Hou Hongfei , Li Ruiping , Tong Changfu
Published: March 2024

To accurately forecast the future development trend of vegetation in dry areas, it is crucial to continuously monitor phenology, vegetation health indices, and vegetation drought indices over an extended period. This is because drought caused by high temperatures significantly affects vegetation. This study thoroughly investigated the spatial and temporal variations in phenological characteristics and vegetation health indices in the abdominal part of Maowusu Sandland in China over the past 20 years. Additionally, it established a linear correlation between vegetation health and temperature indices in the arid zone. To address the issue of predicting long-term trends in vegetation drought changes, we have developed a method that combines the Informer deep learning model with seasonal and Seasonal Trend decomposition using Loess (STL) and empirical mode decomposition (EMD). Additionally, we have utilized the linearly correlated indices of vegetation health and meteorological data spanning 20 years to predict the Normalized Difference Vegetation Index (NDVI) and Temperature Vegetation Dryness Index (TVDI). The study’s findings indicate that over the 20-year observation period, there was an upward trend in NDVI, accompanied by a decrease in both the frequency and severity of droughts. Additionally, the STL-EMD-Informer model successfully predicted the mean absolute percentage error (MAPE = 1.16%) of the future trend in vegetation drought changes for the next decade. This suggests that the overall health of vegetation is expected to continue improving during that time. This work examined the plant growth circumstances in dry locations from several angles and developed a complete analytical method for predicting long-term droughts. The findings provide a strong scientific basis for ecological conservation and vegetation management in arid regions.
Task Allocation of Multi-Machine Collaborative Operation for Agricultural Machinery Based on the Improved Fireworks Algorithm
Authors: Zhu Suji , Wang Bo , Pan Shiqi , Ye Yuting , Wang Enguang , Mao Hanping
Published: March 2024

Currently, the multi-machine collaboration of agricultural machinery is one of the international frontiers and a topic of research interest in the field of agricultural equipment. However, the multi-machine cooperative operation of agricultural machinery is mostly limited to the research on task goal planning and cooperative path optimization of a single operation. To address the mentioned shortcomings, this study addresses the problem of multi-machine cooperative operation of fertilizer applicators in fields with different fertility and fertilizer cooperative distribution of fertilizer trucks. The research uses the task allocation method of a multi-machine cooperative operation of applying fertilizer-transporting fertilizer. First, the problems of fertilizer applicator operation and fertilizer truck fertilizer distribution are defined, and the operating time and the distribution distance are used as optimization objectives to construct functions to establish task allocation mathematical models. Second, a Chaos–Cauchy Fireworks Algorithm (CCFWA), which includes a discretized decoding method, a population initialization with a chaotic map, and a Cauchy mutation operation, is developed. Finally, the proposed algorithm is verified by tests in an actual scenario of fertilizer being applied in the test area of Jimo District, Qingdao City, Shandong Province. The results show that compared to the Fireworks Algorithm, Genetic Algorithm, and Particle Swarm Optimization, the proposed CCFWA can address the problem of falling into a local optimum while guaranteeing the convergence speed. Also, the variance of the CCFWA is reduced by more than 48% compared with the other three algorithms. The proposed method can realize multi-machine cooperative operation and precise distribution of seeds and fertilizers for multiple seeding-fertilizer applicators and fertilizer trucks.
Development of a Predictive Model for Iron Levels in Bovine Muscle Tissue Using Hair as a Predictor
Authors: Narozhnykh Kirill
Published: March 2024

The assessment of iron levels in cattle muscle tissue is crucial for livestock management because it influences both animal health and meat quality, key factors in sustainable development. This study aimed to develop an optimal model for noninvasively predicting the iron content in Hereford cattle muscle tissue, contributing to a comprehensive understanding of the animals’ elemental status. The research involved the atomic absorption analysis of muscle tissue and hair samples from cattle. A regression model was constructed using the least squares method to identify the most effective approach. These findings have ecological applications, aiding in evaluating environmental health and establishing acceptable iron thresholds for animals. The proposed mathematical model utilizing biomarkers (levels of Mg, K, Fe, Al, Cr in hair) will allow for the assessment of iron levels in cattle muscle tissue throughout the period of productive use, with the possibility of adjustment and tracking the changes in elemental status over time. The utilization of the developed method will enable the diagnosis of animal elementosis and assessment of the iron level burden. Subsequently, this will allow for the improvement of the qualitative characteristics of the final product. Thus, the obtained data contribute to fundamental knowledge regarding the content and variability of iron levels in the muscle tissue of cattle.
Automatic Identification of Pangolin Behavior Using Deep Learning Based on Temporal Relative Attention Mechanism
Authors: Wang Kai , Hou Pengfei , Xu Xuelin , Gao Yun , Chen Ming , Lai Binghua , An Fuyu , Ren Zhenyu , Li Yongzheng , Jia Guifeng , Hua Yan
Published: March 2024

With declining populations in the wild, captive rescue and breeding have become one of the most important ways to protect pangolins from extinction. At present, the success rate of artificial breeding is low, due to the insufficient understanding of the breeding behavior characteristics of pangolins. The automatic recognition method based on machine vision not only monitors for 24 h but also reduces the stress response of pangolins. This paper aimed to establish a temporal relation and attention mechanism network (Pangolin breeding attention and transfer network, PBATn) to monitor and recognize pangolin behaviors, including breeding and daily behavior. There were 11,476 videos including breeding behavior and daily behavior that were divided into training, validation, and test sets. For the training set and validation set, the PBATn network model had an accuracy of 98.95% and 96.11%, and a loss function value of 0.1531 and 0.1852. The model is suitable for a 2.40 m × 2.20 m (length × width) pangolin cage area, with a nest box measuring 40 cm × 30 cm × 30 cm (length × width × height) positioned either on the left or right side inside the cage. A spherical night-vision monitoring camera was installed on the cage wall at a height of 2.50 m above the ground. For the test set, the mean Average Precision (mAP), average accuracy, average recall, average specificity, and average F1 score were found to be higher than SlowFast, X3D, TANet, TSN, etc., with values of 97.50%, 99.17%, 97.55%, 99.53%, and 97.48%, respectively. The recognition accuracies of PBATn were 94.00% and 98.50% for the chasing and mounting breeding behaviors, respectively. The results showed that PBATn outperformed the baseline methods in all aspects. This study shows that the deep learning system can accurately observe pangolin breeding behavior and it will be useful for analyzing the behavior of these animals.
A High Vitamin C Micronutrient Supplement Is Unable to Attenuate Inflammation in People with Metabolic Syndrome but May Improve Metabolic Health Indices: A Randomised Controlled Trial
Authors: Vlasiuk Emma , Zawari Masuma , Whitehead Rebekah , Williman Jonathan , Carr Anitra C.
Published: March 2024

Chronic low-grade inflammation is a characteristic of people with metabolic syndrome and is thought to contribute to the condition progressing to the more severe type 2 diabetes and cardiovascular disease (CVD). The aim was to carry out a double-blind randomised placebo-controlled trial in people with metabolic syndrome to determine if supplementation with a micronutrient formula containing 1000 mg/d vitamin C could attenuate inflammation in people with metabolic syndrome. We recruited 72 adults aged a median of 52 years with metabolic syndrome, defined as obesity (based on waist circumference or BMI), and at least two of hyperglycaemia, raised triglycerides, lowered HDL cholesterol, hypertension, or taking medications for these conditions. A further inclusion criteria comprised C-reactive protein (CRP) concentrations ≥ 3 mg/L, i.e., high risk of CVD. The participants were randomised to daily micronutrient formula (n = 37) or matched placebo control (n = 35) for 12 weeks. The primary outcome was change in CRP concentrations and secondary outcomes included changes in vitamin C concentrations, pro-inflammatory cytokines (IL-6, TNFα), oxidative stress marker (F2isoprostanes), glycaemic indices (glucose, insulin, HbA1c), lipid markers (triglycerides, LDL and HDL cholesterol), anthropometric parameters (weight, BMI), insulin resistance and insulin sensitivity, and metabolic severity score. The participants had a low median (Q1, Q3) vitamin C status of 29 (15, 41) µmol/L and a high proportion of hypovitaminosis C (38%) and outright deficiency (19%). Following 12 weeks of micronutrient supplementation, at least 70% of the participants reached adequate vitamin C status (≥50 µmol/L), however, there was no change in CRP concentrations relative to the placebo group (Δ−0.3 [95%CI −2.7, 2.1] mg/L, p = 0.8). Similar trends were observed for IL-6, TNFα and F2isoprostanes (p > 0.05). Instead, there were small improvements in BMI, fasting glucose and HbA1c concentrations, insulin sensitivity and metabolic severity score in the micronutrient group relative to placebo (p < 0.05). Overall, 12-week micronutrient supplementation was unable to mitigate systemic inflammation in people with metabolic syndrome but may improve several metabolic health indices.
Optimization of Ultrasonic Extraction Parameters for the Recovery of Phenolic Compounds in Brown Seaweed: Comparison with Conventional Techniques
Authors: Lee Zu Jia , Xie Cundong , Duan Xinyu , Ng Ken , Suleria Hafiz A. R.
Published: March 2024

Seaweed, in particular, brown seaweed, has gained research interest in the past few years due to its distinctive phenolic profile that has a multitude of bioactive properties. In order to obtain the maximum extraction efficiency of brown seaweed phenolic compounds, Response Surface Methodology was utilized to optimize the ultrasound-assisted extraction (UAE) conditions such as the amplitude, time, solvent:solid ratio, and NaOH concentration. Under optimal conditions, UAE had a higher extraction efficiency of free and bound phenolic compounds compared to conventional extraction (stirred 16 h at 4 °C). This led to higher antioxidant activity in the seaweed extract obtained under UAE conditions. The profiling of phenolic compounds using LC-ESI-QTOF-MS/MS identified a total of 25 phenolics with more phenolics extracted from the free phenolic extraction compared to the bound phenolic extracts. Among them, peonidin 3-O-diglucodise-5-O-glucoside and hesperidin 5,7-O-diglucuronide are unique compounds that were identified in P. comosa, E. radiata and D. potatorum, which are not reported in plants. Overall, our findings provided optimal phenolic extraction from brown seaweed for research into employing brown seaweed as a functional food.
Analysis of Underlapped Symmetrically Ported Valve-Controlled Asymmetric Cylinder Drive
Authors: Wang Huankun , Xu Man , Cao Zijian
Published: March 2024

The valve-controlled cylinder drive system is the most common type among hydraulic applications. Nonlinear behaviour in such systems is inevitable when the valve spool is around its null position. We utilised the component linking method to investigate the nonlinearities in a Moog valve-controlled asymmetric cylinder drive system by simulation in Fortran, in which a generalised concept is introduced and validated by comparing to the experimental results. An X factor is proposed in the generalised concept to describe the asymmetric cylinder state, which is a constant when the cylinder is extending or retracting, but numerically calculated when the valve spool is in the underlap region. This analytical solution is approximately 200 times more computationally efficient than the numerical solution method. This paper utilises the component linking method to simulate the Moog valve-controlled asymmetric cylinder drive system in Matlab Simulink, and proposes an analytical solution for the X factor when the valve spool is in the underlap region. This analytical solution is approximately 200 times more computationally efficient than the numerical solution method.
Natural Killer Cell Mechanosensing in Solid Tumors
Authors: Lightsey Suzanne , Sharma Blanka
Published: March 2024

Natural killer (NK) cells, which are an exciting alternative cell source for cancer immunotherapies, must sense and respond to their physical environment to traffic to and eliminate cancer cells. Herein, we review the mechanisms by which NK cells receive mechanical signals and explore recent key findings regarding the impact of the physical characteristics of solid tumors on NK cell functions. Data suggest that different mechanical stresses present in solid tumors facilitate NK cell functions, especially infiltration and degranulation. Moreover, we review recent engineering advances that can be used to systemically study the role of mechanical forces on NK cell activity. Understanding the mechanisms by which NK cells interpret their environment presents potential targets to enhance NK cell immunotherapies for the treatment of solid tumors.
Fabrication of a Novel 3D Extrusion Bioink Containing Processed Human Articular Cartilage Matrix for Cartilage Tissue Engineering
Authors: Aitchison Alexandra Hunter , Allen Nicholas B. , Shaffrey Isabel R. , O’Neill Conor N. , Abar Bijan , Anastasio Albert T. , Adams Samuel B.
Published: March 2024

Cartilage damage presents a significant clinical challenge due to its intrinsic avascular nature which limits self-repair. Addressing this, our study focuses on an alginate-based bioink, integrating human articular cartilage, for cartilage tissue engineering. This novel bioink was formulated by encapsulating C20A4 human articular chondrocytes in sodium alginate, polyvinyl alcohol, gum arabic, and cartilage extracellular matrix powder sourced from allograft femoral condyle shavings. Using a 3D bioprinter, constructs were biofabricated and cross-linked, followed by culture in standard medium. Evaluations were conducted on cellular viability and gene expression at various stages. Results indicated that the printed constructs maintained a porous structure conducive to cell growth. Cellular viability was 87% post printing, which decreased to 76% after seven days, and significantly recovered to 86% by day 14. There was also a notable upregulation of chondrogenic genes, COL2A1 (p = 0.008) and SOX9 (p = 0.021), suggesting an enhancement in cartilage formation. This study concludes that the innovative bioink shows promise for cartilage regeneration, demonstrating substantial viability and gene expression conducive to repair and suggesting its potential for future therapeutic applications in cartilage repair.
Current and Future Applications of Arterial Spin Labeling MRI in Cerebral Arteriovenous Malformations
Authors: De Simone Matteo , Fontanella Marco Maria , Choucha Anis , Schaller Karl , Machi Paolo , Lanzino Giuseppe , Bijlenga Philippe , Kurz Felix T. , Lövblad Karl-Olof , De Maria Lucio
Published: March 2024

Arterial spin labeling (ASL) has emerged as a promising noninvasive tool for the evaluation of both pediatric and adult arteriovenous malformations (AVMs). This paper reviews the advantages and challenges associated with the use of ASL in AVM assessment. An assessment of the diagnostic workup of AVMs and their variants in both adult and pediatric populations is proposed. Evaluation after treatments, whether endovascular or microsurgical, was similarly examined. ASL, with its endogenous tracer and favorable safety profile, offers functional assessment and arterial feeder identification. ASL has demonstrated strong performance in identifying feeder arteries and detecting arteriovenous shunting, although some studies report inferior performance compared with digital subtraction angiography (DSA) in delineating venous drainage. Challenges include uncertainties in sensitivity for specific AVM features. Detecting AVMs in challenging locations, such as the apical cranial convexity, is further complicated, demanding careful consideration due to the risk of underestimating total blood flow. Navigating these challenges, ASL provides a noninvasive avenue with undeniable merits, but a balanced approach considering its limitations is crucial. Larger-scale prospective studies are needed to comprehensively evaluate the diagnostic performance of ASL in AVM assessment.
Cognitive Flexibility Moderates the Predictive Effect of Phonological Awareness on Focus Structures in Chinese Preschool Children
Authors: Tan Xueqing , Song Jun
Published: March 2024

Focus structures, a complex aspect of information structure in language, have garnered significant attention in psycholinguistics. The question of whether Chinese preschoolers aged 4–6 years possess the ability to process focus structures in oral communication, and how cognitive factors influence this ability, remains a research focal point. To address this, we recruited 100 Chinese preschoolers aged 4–6 years as participants in our study. This study manipulated the positions of focus particles in sentences to investigate the impact of phonological awareness on young children’s comprehension of focus structures. Additionally, we examined the mediating roles of cognitive flexibility and inhibitory control. Our findings indicate the following: (1) phonological awareness positively predicted the accuracy of focus structural processing; (2) inhibitory control did not significantly predict the accuracy of focus structural processing; and (3) cognitive flexibility partially mediated the relationship between phonological awareness and focus structural comprehension. These results confirmed the predictive effect of cognitive flexibility on children’s comprehension of focus structures. Moreover, they demonstrate that young children’s phonological awareness can predict their focus structure comprehension ability through the mediating role of cognitive flexibility. This suggests that children’s cognitive flexibility can aid in understanding sentences with focus structures.