bluuebunny/crossref_metadata_2025 huggingface dataset:
Paradise by the far-red light: Far-red and red:blue ratios independently affect yield, pigments, and carbohydrate production in lettuce, Lactuca sativa
Authors: Van Brenk Jordan B. , Courbier Sarah , Kleijweg Celestin L. , Verdonk Julian C. , Marcelis Leo F. M.
Published: April 2024

In controlled environment agriculture, customized light treatments using light-emitting diodes are crucial to improving crop yield and quality. Red (R; 600-700 nm) and blue light (B; 400-500 nm) are two major parts of photosynthetically active radiation (PAR), often preferred in crop production. Far-red radiation (FR; 700-800 nm), although not part of PAR, can also affect photosynthesis and can have profound effects on a range of morphological and physiological processes. However, interactions between different red and blue light ratios (R:B) and FR on promoting yield and nutritionally relevant compounds in crops remain unknown. Here, lettuce was grown at 200 µmol m-2 s-1 PAR under three different R:B ratios: R:B87.5:12.5 (12.5% blue), R:B75:25 (25% blue), and R:B60:40 (40% blue) without FR. Each treatment was also performed with supplementary FR (50 µmol m-2 s-1; R:B87.5:12.5+FR, R:B75:25+FR, and R:B60:40+FR). White light with and without FR (W and W+FR) were used as control treatments comprising of 72.5% red, 19% green, and 8.5% blue light. Decreasing the R:B ratio from R:B87.5:12.5 to R:B60:40, there was a decrease in fresh weight (20%) and carbohydrate concentration (48% reduction in both sugars and starch), whereas pigment concentrations (anthocyanins, chlorophyll, and carotenoids), phenolic compounds, and various minerals all increased. These results contrasted the effects of FR supplementation in the growth spectra; when supplementing FR to different R:B backgrounds, we found a significant increase in plant fresh weight, dry weight, total soluble sugars, and starch. Additionally, FR decreased concentrations of anthocyanins, phenolic compounds, and various minerals. Although blue light and FR effects appear to directly contrast, blue and FR light did not have interactive effects together when considering plant growth, morphology, and nutritional content. Therefore, the individual benefits of increased blue light fraction and supplementary FR radiation can be combined and used cooperatively to produce crops of desired quality: adding FR increases growth and carbohydrate concentration while increasing the blue fraction increases nutritional value.
Health risk perception and exercise intention of college students: a moderated mediation model of health anxiety and lay theories of health
Authors: Wang Kun , Liu Chen , Yang Xiao , Wang Yue
Published: April 2024

Background

Health risk perception is an important predictor of health-protective behaviors according to the health belief model. However, the underlying mechanism connecting health risk perception and exercise behaviors is not well understood. The current study investigates how health risk perception predicts college students' exercise intention in the post-pandemic era in China and analyzes the mediating effect of health anxiety and the moderating effect of lay theories of health.

Materials and methods

This cross-sectional study adopted convenience sampling and recruited 767 students from a province in central China. The Health Risk Perception Scale, Health Anxiety Scale, Lay Theories of Health Scale, and the Chinese version of the Exercise Intention Scale were used to measure the levels of health risk perception, health anxiety, implicit health theory, and exercise intention, respectively.

Results

The results of the moderated mediation model indicated that the health risk perception of college students significantly and positively affected exercise intention (β = 0.110, t = 2.852, p < 0.01). Meanwhile, the indirect effect of health anxiety on the relationship between health risk perception and exercise intention was significant. Furthermore, lay theories of health buffered the association between health anxiety and exercise intention, according to the moderated mediation analysis (β = 0.068, t = 2.067, p < 0.05). For college students holding incremental health theory, the influence of health anxiety on exercise intention was positively and statistically significant.

Conclusion

The health risk perception of college students can lead to health anxiety, which can positively affect their exercise intention. In addition, lay theories of health can moderate the effect of health anxiety on exercise intention. The results have practical implications for developing effective, applicable, and scalable interventions to promote physical exercise by reducing the level of entity theory of health or increasing the level of incremental theory.
Parent–child interactive behavior in a German sample of parents with and without a mental illness: model replication and adaption of the Coding Interactive Behavior system
Authors: Fahrer Julia , Doebler Philipp , Hagelweide Klara , Kern Pius , Nonnenmacher Nora , Seipp Vanessa , Reck Corinna , Schwenck Christina , Weigelt Sarah , Zietlow Anna-Lena , Christiansen Hanna
Published: April 2024

Studies using observational measures often fail to meet statistical standards for both reliability and validity. The present study examined the psychometric properties of the Coding Interactive Behavior (CIB) System within a German sample of parent–child dyads. The sample consisted of 149 parents with and without a mental illness and their children [n experimental group (EG) = 75, n control group (CG) = 74] who participated in the larger Children of Mentally Ill Parents at Risk Evaluation (COMPARE) study. The age of the children ranged from 3 to 12 years (M = 7.99, SD = 2.5). Exploratory factor analysis supported a five-factor model of the CIB with items describing 1) parental sensitivity/reciprocity, 2) parental intrusiveness, 3) child withdrawal, 4) child involvement, and 5) parent limit setting/child compliance. Compared to international samples, the model was reduced by two independent dyadic factors. Testing for predictive validity identified seven items with predictive power to differentiate parental group membership. The CIB factors did not seem to be sufficiently sensitive to illustrate differences in interaction within a sample of parents with various mental illnesses. To apply the CIB to the described sample or similar ones in the future, additional measurement instruments may be necessary.
Public perception of psychiatry, psychology and mental health professionals: a 15-year analysis
Authors: Domingo-Espiñeira Javier , Varaona Andrea , Montero María , Lara-Abelenda Francisco J. , Gutierrez-Rojas Luis , Fernández del Campo Elena Ameyugo , Rodriguez-Jimenez Roberto , Pinto da Costa Mariana , Ortega Miguel A. , Alvarez-Mon M. , Alvarez-Mon Miguel Angel
Published: April 2024

Background

X (previously known as “Twitter”) serves as a platform for open discussions on mental health, providing an avenue for scrutinizing public perspectives regarding psychiatry, psychology and their associated professionals.

Objective

To analyze the conversations happening on X about psychiatrists, psychologists, and their respective disciplines to understand how the public perception of these professionals and specialties has evolved over the last 15 years.

Methods

We collected and analyzed all tweets posted in English or Spanish between 2007 and 2023 referring to psychiatry, psychology, neurology, mental health, psychiatrist, psychologist, or neurologist using advance topic modelling and sentiment analysis.

Results

A total of 403,767 tweets were analyzed, 155,217 (38%) were in English and 248,550 (62%) in Spanish. Tweets about mental health and mental health professionals and disciplines showed a consistent volume between 2011 and 2016, followed by a gradual increase from 2016 through 2022. The proportion of tweets discussing mental health doubled from 2016 to 2022, increasing from 20% to 67% in Spanish and from 15% to 45% in English. Several differences were observed on the volume of tweets overtime depending on the language they were written. Users associated each term with varied topics, such as seeking for help and recommendation for therapy, self-help resources, medication and side effects, suicide prevention, mental health in times of crisis, among others. The number of tweets mentioning these topics increased by 5-10% from 2016 to 2022, indicating a growing interest among the population. Emotional analysis showed most of the topics were associated with fear and anger.

Conclusion

The increasing trend in discussions about mental health and the related professionals and disciplines over time may signify an elevated collective awareness of mental health. Gaining insights into the topics around these matters and user’s corresponding emotions towards them presents an opportunity to combat the stigma surrounding mental health more effectively.
Causal relationship between air pollution, lung function, gastroesophageal reflux disease, and non-alcoholic fatty liver disease: univariate and multivariate Mendelian randomization study
Authors: Cao Runmin , Jiang Honghe , Zhang Yurun , Guo Ying , Zhang Weibin
Published: April 2024

Background

The association between air pollution, lung function, gastroesophageal reflux disease, and Non-alcoholic fatty liver disease (NAFLD) remains inconclusive. Previous studies were not convincing due to confounding factors and reverse causality. We aim to investigate the causal relationship between air pollution, lung function, gastroesophageal reflux disease, and NAFLD using Mendelian randomization analysis.

Methods

In this study, univariate Mendelian randomization analysis was conducted first. Subsequently, Steiger testing was performed to exclude the possibility of reverse association. Finally, significant risk factors identified from the univariate Mendelian analysis, as well as important factors affecting NAFLD from previous observational studies (type 2 diabetes and body mass index), were included in the multivariable Mendelian randomization analysis.

Results

The results of the univariable Mendelian randomization analysis showed a positive correlation between particulate matter 2.5, gastroesophageal reflux disease, and NAFLD. There was a negative correlation between forced expiratory volume in 1 s, forced vital capacity, and NAFLD. The multivariable Mendelian randomization analysis indicated a direct causal relationship between gastroesophageal reflux disease (OR = 1.537, p = 0.011), type 2 diabetes (OR = 1.261, p < 0.001), and NAFLD.

Conclusion

This Mendelian randomization study confirmed the causal relationships between air pollution, lung function, gastroesophageal reflux, and NAFLD. Furthermore, gastroesophageal reflux and type 2 diabetes were identified as independent risk factors for NAFLD, having a direct causal connection with the occurrence of NAFLD.
The bidirectional relationship between activities of daily living and frailty during short-and long-term follow-up period among the middle-aged and older population: findings from the Chinese nationwide cohort study
Authors: Li Xiaoping , Li Xiaoguang , Sun Lu , Yang Liu , Wang Congzhi , Yuan Ting , Lei Yunxiao , Li Jing , Liu Mingming , Zhang Dongmei , Hua Ying , Liu Haiyang , Zhang Lin
Published: April 2024

Objective

Frailty and activities of daily living (ADL) disability are common conditions among older population. Studies on the bidirectional relationship between frailty and ADL are limited. The current study examined the cross-sectional and longitudinal associations between frailty and ADL in middle-aged and older Chinese individuals.

Methods

The data was collected through the China Health and Retirement Longitudinal Study (CHARLS), conducted in 2011, 2013, and 2015, encompassing 17,284 individuals aged ≥45 years. We excluded individuals without follow-up data. 2,631 participants finished the baseline survey. The definition of ADL disability encompasses difficulty in engaging in either basic activities of daily living (BADL) or instrumental activities of daily living (IADL). Frailty was assessed according to the Fried criteria. Logistic regression was utilized to examine odds ratios (ORs) and 95% confidence intervals (CIs) for assessing the cross-sectional relationships between ADL with frailty at baseline. The prediction effects were explored using Cox proportional hazards analysis, testing hazard ratios (HRs) and 95%CIs.

Results

In cross-sectional analysis, BADL [OR = 6.660 (4.519–9.815)], IADL [OR = 5.950 (4.490–7.866)], and ADL [OR = 5.658 (4.278–7.483)] exhibited significant associations with frailty; frailty demonstrated significant associations with BADL [OR = 6.741 (4.574–9.933)], IADL [OR = 6.042 (4.555–8.016)] and ADL [OR = 5.735 (4.333–7.591)]. In longitudinal analysis, IADL and ADL were significantly associated with frailty in participants without baseline frailty in the short-term period [IADL: HR = 1.971 (1.150–3.379), ADL: HR = 1.920 (1.146–3.215)], IADL exhibited a significant association with frailty in the long-term period [HR = 2.056 (1.085–3.895)]. There was no significant link observed between frailty and an elevated risk of disability onset in BADL, IADL and ADL during the short-term period. When considering the long-term perspective, frailty exhibited a significant association with an elevated risk of disability onset in BADL [HR= 1.820 (1.126–2.939)] and IADL [HR = 1.724 (1.103–2.694)].

Conclusion

In middle-aged and older adults, ADL and IADL disability predicted frailty after 2-year follow-up, IADL disability predicted frailty after 4-year follow-up. Moreover, frailty did not predict BADL, IADL and ADL disability after 2-year follow-up. However, frailty predicted BADL and IADL disability after 4-year follow-up.
Application of empathy theory in the study of the effectiveness and timeliness of information dissemination in regional public health events
Authors: Zhang Min , Lu Xiaobing
Published: April 2024

Introduction

This study examines the role of empathy theory in enhancing the effectiveness and timeliness of information dissemination during regional public health events, with a focus on the SARS and COVID-19 pandemics as case studies. Utilizing an anthropological interview method, the research delves into the public's transformation from passive recipients to active participants in information dissemination, emphasizing the impact of empathy.

Objective

The study aims to evaluate the application of empathy theory in the context of public health emergencies and to determine its influence on the quality of information dissemination and public engagement.

Methods

The research involved two distinct surveys, each collecting 50 questionnaires from participants in different regions, to capture a diverse range of perspectives. The surveys assessed participants' views on information dissemination, their levels of empathy, and their behaviors in receiving and sharing health-related information.

Results

The findings indicate that empathy plays a crucial role in facilitating the active involvement of the public in information dissemination. There is a notable difference in the public's emotional response and information sharing behaviors between regions with direct experience of the health events and those less affected.

Conclusion

The study concludes that empathy theory, when applied to information dissemination during public health emergencies, can significantly improve the public's engagement and the overall effectiveness of communication strategies. The results underscore the need for empathetic communication to foster a sense of solidarity and collective action in response to public health crises.
PASAT: pathfinder in solar adaptive telescope
Authors: Rao Changhui , Ji Haisheng , Bao Hua , Rao Xuejun , Yang Jinsheng , Guo Youming , Zhang Lanqiang , Zhong Libo , Fan Xinlong , Zhang Qingmin , Li Cheng , Bian Qing
Published: April 2024

In the forefront of quantitative solar physics research using large-aperture ground-based solar optical telescopes, high-contrast observation along with high-accuracy polarimetric measurement in the solar active region are required. In this paper, we propose a novel high-contrast imaging telescope construction with a 60 cm medium aperture, namely, the PAthfinder in Solar Adaptive Telescope (PASAT), in which a deformable secondary mirror is used as the adaptive optical correction device and a symmetrical optical path design is employed, leading to the least Muller matrix polarization instruments. The telescope can provide a high-resolution magnetic field with high accuracy for the solar active regions, as well as high-contrast images with a superior signal-to-noise ratio and photometric accuracy of the solar photosphere and chromosphere. These data will be directly used for a better understanding of the evolution and release of magnetic energy, which will help in improving space weather forecasting. Meanwhile, PASAT will accumulate the relevant techniques for constructing similar, larger solar telescopes in the future.
Guidance Design for Escape Flight Vehicle against Multiple Pursuit Flight Vehicles Using the RNN-Based Proximal Policy Optimization Algorithm
Authors: Hu Xiao , Wang Hongbo , Gong Min , Wang Tianshu
Published: April 2024

Guidance commands of flight vehicles can be regarded as a series of data sets having fixed time intervals; thus, guidance design constitutes a typical sequential decision problem and satisfies the basic conditions for using the deep reinforcement learning (DRL) technique. In this paper, we consider the scenario where the escape flight vehicle (EFV) generates guidance commands based on the DRL technique, while the pursuit flight vehicles (PFVs) derive their guidance commands employing the proportional navigation method. For every PFV, the evasion distance is described as the minimum distance between the EFV and the PFV during the escape-and-pursuit process. For the EFV, the objective of the guidance design entails progressively maximizing the residual velocity, which is described as the EFV’s velocity when the last evasion distance is attained, subject to the constraint imposed by the given evasion distance threshold. In the outlined problem, three dimensionalities of uncertainty emerge: (1) the number of PFVs requiring evasion at each time instant; (2) the precise time instant at which each of the evasion distances can be attained; (3) whether each attained evasion distance exceeds the given threshold or not. To solve the challenging problem, we propose an innovative solution that integrates the recurrent neural network (RNN) with the proximal policy optimization (PPO) algorithm, engineered to generate the guidance commands of the EFV. Initially, the model, trained by the RNN-based PPO algorithm, demonstrates effectiveness in evading a single PFV. Subsequently, the aforementioned model is deployed to evade additional PFVs, thereby systematically augmenting the model’s capabilities. Comprehensive simulation outcomes substantiate that the guidance design method based on the proposed RNN-based PPO algorithm is highly effective.
Characterisation of PVL-Positive Staphylococcus argenteus from the United Arab Emirates
Authors: Monecke Stefan , Burgold-Voigt Sindy , Braun Sascha D. , Diezel Celia , Liebler-Tenorio Elisabeth M. , Müller Elke , Nassar Rania , Reinicke Martin , Reissig Annett , Senok Abiola , Ehricht Ralf
Published: April 2024

Staphylococcus argenteus is a recently described staphylococcal species that is related to Staphylococcus aureus but lacks the staphyloxanthin operon. It is able to acquire both resistance markers such as the SCCmec elements and mobile genetic elements carrying virulence-associated genes from S. aureus. This includes those encoding the Panton–Valentine leukocidin (PVL), which is associated mainly with severe and/or recurrent staphylococcal skin and soft tissue infections. Here, we describe the genome sequences of two PVL-positive, mecA-negative S. argenteus sequence type (ST) 2250 isolates from the United Arab Emirates in detail. The isolates were found in a dental clinic in the United Arab Emirates (UAE). Both were sequenced using Oxford Nanopore Technology (ONT). This demonstrated the presence of temperate bacteriophages in the staphylococcal genomes, including a PVL prophage. It was essentially identical to the published sequence of phiSa2wa_st78 (GenBank NC_055048), a PVL phage from an Australian S. aureus clonal complex (CC) 88 isolate. Besides the PVL prophage, one isolate carried another prophage and the second isolate carried two additional prophages, whereby the region between these two prophages was inverted. This “flipped” region comprised about 1,083,000 bp, or more than a third of the strain’s genome, and it included the PVL prophage. Prophages were induced by Mitomycin C treatment and subjected to transmission electron microscopy (TEM). This yielded, in accordance to the sequencing results, one or, respectively, two distinct populations of icosahedral phages. It also showed prolate phages which presumptively might be identified as the PVL phage. This observation highlights the significance bacteriophages have as agents of horizontal gene transfer as well as the need for monitoring emerging staphylococcal strains, especially in cosmopolitan settings such as the UAE.
The Interplay between Antibiotics and the Host Immune Response in Sepsis: From Basic Mechanisms to Clinical Considerations: A Comprehensive Narrative Review
Authors: Tosi Martina , Coloretti Irene , Meschiari Marianna , De Biasi Sara , Girardis Massimo , Busani Stefano
Published: April 2024

Sepsis poses a significant global health challenge due to immune system dysregulation. This narrative review explores the complex relationship between antibiotics and the immune system, aiming to clarify the involved mechanisms and their clinical impacts. From pre-clinical studies, antibiotics exhibit various immunomodulatory effects, including the regulation of pro-inflammatory cytokine production, interaction with Toll-Like Receptors, modulation of the P38/Pmk-1 Pathway, inhibition of Matrix Metalloproteinases, blockade of nitric oxide synthase, and regulation of caspase-induced apoptosis. Additionally, antibiotic-induced alterations to the microbiome are associated with changes in systemic immunity, affecting cellular and humoral responses. The adjunctive use of antibiotics in sepsis patients, particularly macrolides, has attracted attention due to their immune-regulatory effects. However, there are limited data comparing different types of macrolides. More robust evidence comes from studies on community-acquired pneumonia, especially in severe cases with a hyper-inflammatory response. While studies on septic shock have shown mixed results regarding mortality rates and immune response modulation, conflicting findings are also observed with macrolides in acute respiratory distress syndrome. In conclusion, there is a pressing need to tailor antibiotic therapy based on the patient’s immune profile to optimize outcomes in sepsis management.
The Ongoing Debate on the Use of Prophylactic Antibiotics in Acute Pancreatitis—Is There a Conclusion? A Comprehensive Narrative Review
Authors: Chan Kai Siang , Shelat Vishal G.
Published: April 2024

Acute pancreatitis (AP) is a common but often self-limiting disease in the majority of patients. However, in the minority, who may progress to moderately severe or severe AP, high mortality risk has been reported. Infected pancreatitis necrosis (IPN) in necrotising pancreatitis has been shown to result in more than twice the mortality rate compared with in sterile pancreatic necrosis. This raises the question on whether prophylactic antibiotics (PABs) should be given in subgroups of AP to prevent superimposed infection to improve survival outcomes. Despite numerous randomised controlled trials (RCTs), meta-analyses, and guidelines on the management of AP, there is a lack of strong evidence to suggest the use of PABs in AP. Additionally, use of PABs is associated with antimicrobial resistance. Considerable heterogeneity exists and limits the interpretation of results—subgroup of AP benefitting from PAB use, choice/class of PAB, and timing of administration from symptom onset and duration of PAB use. Only a minority of existing meta-analyses suggest mortality benefits and reduction in IPN. The majority of existing guidelines do not recommend the use of PABs in AP. More research is required to make more definitive conclusions. Currently, PAB should only be administered after multidisciplinary discussions led by pancreatology experts.
Research on Driving Scenario Knowledge Graphs
Authors: Zhang Ce , Hong Liang , Wang Dan , Liu Xinchao , Yang Jinzhe , Lin Yier
Published: April 2024

Despite the partial disclosure of driving scenario knowledge graphs, they still fail to meet the comprehensive needs of intelligent connected vehicles for driving knowledge. Current issues include the high complexity of pattern layer construction, insufficient accuracy of information extraction and fusion, and limited performance of knowledge reasoning models. To address these challenges, a hybrid knowledge graph method was adopted in the construction of a driving scenario knowledge graph (DSKG). Firstly, core concepts in the field were systematically sorted and classified, laying the foundation for the construction of a multi-level classified knowledge graph top-level ontology. Subsequently, by deeply exploring and analyzing the Traffic Genome data, 34 entities and 51 relations were extracted and integrated with the ontology layer, achieving the expansion and updating of the knowledge graph. Then, in terms of knowledge reasoning models, an analysis of the training results of the TransE, Complex, Distmult, and Rotate models in the entity linking prediction task of DSKG revealed that the Distmult model performed the best in metrics such as hit rate, making it more suitable for inference in DSKG. Finally, a standardized and widely applicable driving scenario knowledge graph was proposed. The DSKG and related materials have been publicly released for use by industry and academia.
Comprehensive Validation on Reweighting Samples for Bias Mitigation via AIF360
Authors: Blow Christina Hastings , Qian Lijun , Gibson Camille , Obiomon Pamela , Dong Xishuang
Published: April 2024

Fairness Artificial Intelligence (AI) aims to identify and mitigate bias throughout the AI development process, spanning data collection, modeling, assessment, and deployment—a critical facet of establishing trustworthy AI systems. Tackling data bias through techniques like reweighting samples proves effective for promoting fairness. This paper undertakes a systematic exploration of reweighting samples for conventional Machine-Learning (ML) models, utilizing five models for binary classification on datasets such as Adult Income and COMPAS, incorporating various protected attributes. In particular, AI Fairness 360 (AIF360) from IBM, a versatile open-source library aimed at identifying and mitigating bias in machine-learning models throughout the entire AI application lifecycle, is employed as the foundation for conducting this systematic exploration. The evaluation of prediction outcomes employs five fairness metrics from AIF360, elucidating the nuanced and model-specific efficacy of reweighting samples in fostering fairness within traditional ML frameworks. Experimental results illustrate that reweighting samples effectively reduces bias in traditional ML methods for classification tasks. For instance, after reweighting samples, the balanced accuracy of Decision Tree (DT) improves to 100%, and its bias, as measured by fairness metrics such as Average Odds Difference (AOD), Equal Opportunity Difference (EOD), and Theil Index (TI), is mitigated to 0. However, reweighting samples does not effectively enhance the fairness performance of K Nearest Neighbor (KNN). This sheds light on the intricate dynamics of bias, underscoring the complexity involved in achieving fairness across different models and scenarios.
Evaluation of Skin Wound Healing with Biosheets Containing Somatic Stem Cells in a Dog Model: A Pilot Study
Authors: Maeta Noritaka , Iwai Ryosuke , Takemitsu Hiroshi , Akashi Natsuki , Miyabe Masahiro , Funayama-Iwai Marina , Nakayama Yasuhide
Published: April 2024

The administration of mesenchymal stem cells (MSCs) has a positive effect on wound healing; however, the lack of adequate MSC engraftment at the wound site is a major limiting factor in current MSC-based therapies. In this study, a biosheet prepared using in-body tissue architecture (iBTA) was used as a material to address these problems. This study aimed to assess and evaluate whether biosheets containing somatic stem cells would affect the wound healing process in dogs. Biosheets were prepared by subcutaneously embedding molds in beagles. These were then evaluated grossly and histologically, and the mRNA expression of inflammatory cytokines, interleukins, and Nanog was examined in some biosheets. Skin defects were created on the skin of the beagles to which the biosheets were applied. The wound healing processes of the biosheet and control (no biosheet application) groups were compared for 8 weeks. Nanog mRNA was expressed in the biosheets, and SSEA4/CD105 positive cells were observed histologically. Although the wound contraction rates differed significantly in the first week, the biosheet group tended to heal faster than the control group. This study revealed that biosheets containing somatic stem cells may have a positive effect on wound healing.
Mendelian Randomization Reveals: Triglycerides and Sensorineural Hearing Loss
Authors: Ding Shun , Liu Yixuan , Duan Tingting , Fang Peng , Tong Qiling , Li Huawei , Yu Huiqian
Published: April 2024

Background: Sensorineural hearing loss (SNHL) is a multifactorial disorder with potential links to various physiological systems, including the cardiovascular system via blood lipid levels such as triglycerides (TG). This study investigates the causal relationship between TG levels and SNHL using Mendelian randomization (MR), which offers a method to reduce confounding and reverse causality by using genetic variants as instrumental variables. Methods: Utilizing publicly available genome-wide association study (GWAS) data, we performed a two-sample MR analysis. The initial analysis unveiled a causal relationship between TG (GWAS ID: ebi-a-GCST90018975) and SNHL (GWAS ID: finn b-H8_HL_SEN-NAS). Subsequent analysis validated this through MR with a larger sample size for TG (GWAS ID: ieu-b-111) and SNHL. To conduct the MR analysis, we utilized several methods including inverse-variance weighted (IVW), MR Egger, weighted median, and weighted mode. We also employed Cochrane’s Q test to identify any heterogeneity in the MR results. To detect horizontal pleiotropy, we conducted the MR-Egger intercept test and MR pleiotropy residual sum and outliers (MR-PRESSO) test. We performed a leave-one-out analysis to assess the sensitivity of this association. Finally, a meta-analysis of the MR results was undertaken. Results: Our study found a significant positive correlation between TG and SNHL, with OR values of 1.14 (95% CI: 1.07–1.23, p < 0.001) in the IVW analysis and 1.09 (95% CI: 1.03–1.16, p < 0.006) in the replicate analysis. We also found no evidence of horizontal pleiotropy or heterogeneity between the genetic variants (p > 0.05), and a leave-one-out test confirmed the stability and robustness of this association. The meta-analysis combining the initial and replicate analyses showed a significant causal effect with OR values of 1.11 (95% CI: 1.06–1.16, p = 0.01). Conclusion: These findings indicate TG as a risk factor for SNHL, suggesting potential pathways for prevention and intervention in populations at risk. This conclusion underscores the importance of managing TG levels as a strategy to mitigate the risk of developing SNHL.
Ultra-High Contrast MRI: Using Divided Subtracted Inversion Recovery (dSIR) and Divided Echo Subtraction (dES) Sequences to Study the Brain and Musculoskeletal System
Authors: Cornfeld Daniel , Condron Paul , Newburn Gil , McGeown Josh , Scadeng Miriam , Bydder Mark , Griffin Mark , Handsfield Geoffrey , Perera Meeghage Randika , Melzer Tracy , Holdsworth Samantha , Kwon Eryn , Bydder Graeme
Published: April 2024

Divided and subtracted MRI is a novel imaging processing technique, where the difference of two images is divided by their sum. When the sequence parameters are chosen properly, this results in images with a high T1 or T2 weighting over a small range of tissues with specific T1 and T2 values. In the T1 domain, we describe the implementation of the divided Subtracted Inversion Recovery Sequence (dSIR), which is used to image very small changes in T1 from normal in white matter. dSIR has shown widespread changes in otherwise normal-appearing white matter in patients suffering from mild traumatic brain injury (mTBI), substance abuse, and ischemic leukoencephalopathy. It can also be targeted to measure small changes in T1 from normal in other tissues. In the T2 domain, we describe the divided echo subtraction (dES) sequence that is used to image musculoskeletal tissues with a very short T2*. These tissues include fascia, tendons, and aponeuroses. In this manuscript, we explain how this contrast is generated, review how these techniques are used in our research, and discuss the current challenges and limitations of this technique.
Innovations in Peripheral Nerve Regeneration
Authors: Lam Ting Chak , Leung Yiu Yan
Published: April 2024

The field of peripheral nerve regeneration is a dynamic and rapidly evolving area of research that continues to captivate the attention of neuroscientists worldwide. The quest for effective treatments and therapies to enhance the healing of peripheral nerves has gained significant momentum in recent years, as evidenced by the substantial increase in publications dedicated to this field. This surge in interest reflects the growing recognition of the importance of peripheral nerve recovery and the urgent need to develop innovative strategies to address nerve injuries. In this context, this article aims to contribute to the existing knowledge by providing a comprehensive review that encompasses both biomaterial and clinical perspectives. By exploring the utilization of nerve guidance conduits and pharmacotherapy, this article seeks to shed light on the remarkable advancements made in the field of peripheral nerve regeneration. Nerve guidance conduits, which act as artificial channels to guide regenerating nerves, have shown promising results in facilitating nerve regrowth and functional recovery. Additionally, pharmacotherapy approaches have emerged as potential avenues for promoting nerve regeneration, with various therapeutic agents being investigated for their neuroprotective and regenerative properties. The pursuit of advancing the field of peripheral nerve regeneration necessitates persistent investment in research and development. Continued exploration of innovative treatments, coupled with a deeper understanding of the intricate processes involved in nerve regeneration, holds the promise of unlocking the complete potential of these groundbreaking interventions. By fostering collaboration among scientists, clinicians, and industry partners, we can accelerate progress in this field, bringing us closer to the realization of transformative therapies that restore function and quality of life for individuals affected by peripheral nerve injuries.
An Automated Video Analysis System for Retrospective Assessment and Real-Time Monitoring of Endoscopic Procedures (with Video)
Authors: Zhu Yan , Du Ling , Fu Pei-Yao , Geng Zi-Han , Zhang Dan-Feng , Chen Wei-Feng , Li Quan-Lin , Zhou Ping-Hong
Published: April 2024

Background and Aims: Accurate recognition of endoscopic instruments facilitates quantitative evaluation and quality control of endoscopic procedures. However, no relevant research has been reported. In this study, we aimed to develop a computer-assisted system, EndoAdd, for automated endoscopic surgical video analysis based on our dataset of endoscopic instrument images. Methods: Large training and validation datasets containing 45,143 images of 10 different endoscopic instruments and a test dataset of 18,375 images collected from several medical centers were used in this research. Annotated image frames were used to train the state-of-the-art object detection model, YOLO-v5, to identify the instruments. Based on the frame-level prediction results, we further developed a hidden Markov model to perform video analysis and generate heatmaps to summarize the videos. Results: EndoAdd achieved high accuracy (>97%) on the test dataset for all 10 endoscopic instrument types. The mean average accuracy, precision, recall, and F1-score were 99.1%, 92.0%, 88.8%, and 89.3%, respectively. The area under the curve values exceeded 0.94 for all instrument types. Heatmaps of endoscopic procedures were generated for both retrospective and real-time analyses. Conclusions: We successfully developed an automated endoscopic video analysis system, EndoAdd, which supports retrospective assessment and real-time monitoring. It can be used for data analysis and quality control of endoscopic procedures in clinical practice.
Defect Structures of Rare Earth-Doped Lutetium Oxide and Impacts of Li Co-Dopant
Authors: Zhao Yanfeng , Cormack Alastair N. , Wu Yiquan
Published: April 2024

Defect complexes consisting of point defects induced by the doping of rare earth elements (Nd, Er) into lutetium oxide (Lu2O3) host were investigated with respect to defect formation energies and defect configurations using atomistic simulations with General Utility Lattice Program (GULP). The site preferences of the substitutional point defects of the dopants and the occupation between the two available cationic sites, the 8b and 24d sites, were analyzed. Additionally, the impacts of Li on the doping of rare earth elements into Lu2O3 were revealed from the viewpoints of energy and structure. Dopant pairs in the nearest neighbor configurations (8b + 8b), (8b + 24d), and (24d + 24d) were considered. The results contribute to the understanding of structures of defects in rare earth-doped Lu2O3.
On the Accurate Estimation of Information-Theoretic Quantities from Multi-Dimensional Sample Data
Authors: Álvarez Chaves Manuel , Gupta Hoshin V. , Ehret Uwe , Guthke Anneli
Published: April 2024

Using information-theoretic quantities in practical applications with continuous data is often hindered by the fact that probability density functions need to be estimated in higher dimensions, which can become unreliable or even computationally unfeasible. To make these useful quantities more accessible, alternative approaches such as binned frequencies using histograms and k-nearest neighbors (k-NN) have been proposed. However, a systematic comparison of the applicability of these methods has been lacking. We wish to fill this gap by comparing kernel-density-based estimation (KDE) with these two alternatives in carefully designed synthetic test cases. Specifically, we wish to estimate the information-theoretic quantities: entropy, Kullback–Leibler divergence, and mutual information, from sample data. As a reference, the results are compared to closed-form solutions or numerical integrals. We generate samples from distributions of various shapes in dimensions ranging from one to ten. We evaluate the estimators’ performance as a function of sample size, distribution characteristics, and chosen hyperparameters. We further compare the required computation time and specific implementation challenges. Notably, k-NN estimation tends to outperform other methods, considering algorithmic implementation, computational efficiency, and estimation accuracy, especially with sufficient data. This study provides valuable insights into the strengths and limitations of the different estimation methods for information-theoretic quantities. It also highlights the significance of considering the characteristics of the data, as well as the targeted information-theoretic quantity when selecting an appropriate estimation technique. These findings will assist scientists and practitioners in choosing the most suitable method, considering their specific application and available data. We have collected the compared estimation methods in a ready-to-use open-source Python 3 toolbox and, thereby, hope to promote the use of information-theoretic quantities by researchers and practitioners to evaluate the information in data and models in various disciplines.
A Study of Adjacent Intersection Correlation Based on Temporal Graph Attention Network
Authors: Li Pengcheng , Dong Baotian , Li Sixian
Published: April 2024

Traffic state classification and relevance calculation at intersections are both difficult problems in traffic control. In this paper, we propose an intersection relevance model based on a temporal graph attention network, which can solve the above two problems at the same time. First, the intersection features and interaction time of the intersections are regarded as input quantities together with the initial labels of the traffic data. Then, they are inputted into the temporal graph attention (TGAT) model to obtain the classification accuracy of the target intersections in four states—free, stable, slow moving, and congested—and the obtained neighbouring intersection weights are used as the correlation between the intersections. Finally, it is validated by VISSIM simulation experiments. In terms of classification accuracy, the TGAT model has a higher classification accuracy than the three traditional classification models and can cope well with the uneven distribution of the number of samples. The information gain algorithm from the information entropy theory was used to derive the average delay as the most influential factor on intersection status. The correlation from the TGAT model positively correlates with traffic flow, making it interpretable. Using this correlation to control the division of subareas improves the road network’s operational efficiency more than the traditional correlation model does. This demonstrates the effectiveness of the TGAT model’s correlation.
Effect of Water Injection on Combustion and Emissions Parameters of SI Engine Fuelled by Hydrogen–Natural Gas Blends
Authors: Pukalskas Saugirdas , Korsakas Vidas , Stankevičius Tomas , Kriaučiūnas Donatas , Mikaliūnas Šarūnas
Published: April 2024

Technologies used in the transport sector have a substantial impact on air pollution and global warming. Due to the immense impact of air pollution on Earth, it is crucial to investigate novel ways to reduce emissions. One way to reduce pollution from ICE is to use alternative fuels. However, blends of alternative fuels in different proportions are known to improve some emissions’ parameters, while others remain unchanged or even worsen. It is therefore necessary to find ways of reducing all the main pollutants. For SI engines, mixtures of hydrogen and natural gas can be used as alternative fuels. The use of such fuel mixtures makes it possible to reduce CO, HC, and CO2 emissions from the engine, but the unique properties of hydrogen tend to increase NOx emissions. One way to address this challenge is to use port water injection (PWI). This paper describes studies carried out under laboratory conditions on an SI engine fuelled with CNG and CNG + H2 mixtures (H2 = 5, 10, 15% by volume) and injected with 60 and 120 mL/min of water into the engine. The tests showed that the additional water injection reduced CO and NOx emissions by about 20% and 4–5 times, respectively. But, the results also show that water injection at the rate of 120 mL/min increases fuel consumption by between 2.5% and 7% in all cases.
A Hybrid Tri-Stable Piezoelectric Energy Harvester with Asymmetric Potential Wells for Rotational Motion Energy Harvesting Enhancement
Authors: Man Dawei , Jiang Bangdong , Zhang Yu , Tang Liping , Xu Qinghu , Chen Dong , Han Tingting
Published: April 2024

This paper proposes an asymmetric hybrid tri-stable piezoelectric energy harvester for rotational motion (RHTPEH). The device features an asymmetric tri-stable piezoelectric cantilever beam positioned at the edge of a rotating disk. This beam is uniquely configured with an asymmetric arrangement of magnets. Additionally, an elastic amplifier composed of a vertical and a rotating spring connects the beam’s fixed end and the disk. This setup enhances both the rotational amplitude and vertical displacement of the beam during motion. A comprehensive dynamical model of the RHTPEH was developed using Lagrange’s equations. This model facilitated an in-depth analysis of the system’s behavior under various conditions, focusing on the influence of key parameters such as the asymmetry in the potential well, the stiffness ratio of the amplifier springs, the radius of the disk, and the disk’s rotational speed on the nonlinear dynamic response of the system. The results show that the asymmetric hybrid tri-stable piezoelectric energy harvester makes it easier to harvest the vibration energy in rotational motion and has excellent power output performance compared with the symmetric tri-stable piezoelectric energy harvester. The output power magnitude of the system at higher rotational speeds increases as the radius of rotation expands, but when the rotational speed is low, the steady-state output power magnitude of the system is not sensitive to changes in the radius of rotation. Theoretical analysis and numerical simulations validate the effectiveness of the proposed asymmetric RHTPEH for energy harvesting in low-frequency rotating environments.
Research on Capacity Configuration for Green Power Substitution in an Isolated Grid Containing Electrolytic Aluminum
Authors: You Min , Wang Yunguang , Wang Haiyun , Wusiman Aisikaer , Lv Liangnian
Published: April 2024

The deployment of a green power alternative within an isolated network, powered by renewable energy sources, in the “Three North” region of China can facilitate the substitution of high-energy-consuming industrial loads with green power. However, an inadequate power supply configuration may lead to economic and reliability issues. To address this problem, effective capacity allocation within the green power alternative isolated network is proposed. The capacity allocation process starts with the design of a network structure that aligns with local conditions. Subsequently, a capacity allocation model is developed, considering economic factors, renewable energy utilization efficiency, and system reliability. The gray wolf optimizer is enhanced to establish a capacity allocation method for the green power alternative isolated network. This method is then employed to simulate and assess the performance of the network. The results indicate that the green alternative isolated grid can successfully facilitate green power substitution, satisfying the energy requirements of the loads.
Biomass Higher Heating Value Estimation: A Comparative Analysis of Machine Learning Models
Authors: Brandić Ivan , Pezo Lato , Voća Neven , Matin Ana
Published: April 2024

The research conducted focused on the capabilities of various non-linear and machine learning (ML) models in estimating the higher heating value (HHV) of biomass using proximate analysis data as inputs. The research was carried out to identify the most appropriate model for the estimation of HHV, which was determined by a statistical analysis of the modeling error. In this sense, artificial neural networks (ANNs), support vector machine (SVM), random forest regression (RFR), and higher-degree polynomial models were compared. After statistical analysis of the modeling error, the ANN model was found to be the most suitable for estimating the HHV biomass and showed the highest specific regression coefficient, with an R2 of 0.92. SVM (R2 = 0.81), RFR, and polynomial models (R2 = 0.84), on the other hand, also exhibit a high degree of estimation, albeit with somewhat larger modelling errors. The study conducted suggests that ANN models are best suited for the non-linear modeling of HHV of biomass, as they can generalize and search for links between input and output data that are more robust but also more complex in structure.