bluuebunny/crossref_metadata_2025 huggingface dataset:
Rhein ameliorates transverse aortic constriction-induced cardiac hypertrophy via regulating STAT3 and p38 MAPK signaling pathways
Authors: Li Run-Jing , Xu Jia-Jia , Zhang Zheng-Hao , Chen Min-Wei , Liu Shi-Xiao , Yang Cui , Li Yan-Ling , Luo Ping , Liu Yi-Jiang , Tang Rong , Shan Zhong-Gui
Published: August 2022

The progression from compensatory hypertrophy to heart failure is difficult to reverse, in part due to extracellular matrix fibrosis and continuous activation of abnormal signaling pathways. Although the anthraquinone rhein has been examined for its many biological properties, it is not clear whether it has therapeutic value in the treatment of cardiac hypertrophy and heart failure. In this study, we report for the first time that rhein can ameliorate transverse aortic constriction (TAC)-induced cardiac hypertrophy and other cardiac damage in vivo and in vitro. In addition, rhein can reduce cardiac hypertrophy by attenuating atrial natriuretic peptide, brain natriuretic peptide, and β-MHC expression; cardiac fibrosis; and ERK phosphorylation and transport into the nucleus. Furthermore, the inhibitory effect of rhein on myocardial hypertrophy was similar to that of specific inhibitors of STAT3 and ERK signaling. In addition, rhein at therapeutic doses had no significant adverse effects or toxicity on liver and kidney function. We conclude that rhein reduces TAC-induced cardiac hypertrophy via targeted inhibition of the molecular function of ERK and downregulates STAT3 and p38 MAPK signaling. Therefore, rhein might be a novel and effective agent for treating cardiac hypertrophy and other cardiovascular diseases.
Pharmacokinetic and pharmacodynamic similarity evaluation between an insulin glargine biosimilar product and Lantus® in healthy subjects: Pharmacokinetic parameters of both parent insulin glargine and M1 were used as endpoints
Authors: Wang Yiya , Zhou Ying , Ding Juefang , Li Xianjing , Guo Fengxue , Zhang Jianfei , Ding Li
Published: August 2022

Insulin glargine is a long-acting insulin analog, which plays an important role in the treatment of diabetes mellitus. Biosimilar products of insulin glargine can provide patients with additional safe, high-quality, and potentially cost-effective options for treating diabetes. This article presents a randomized, double-blind, single-dose, two-treatment, four-period, replicate crossover, euglycemic clamp study which was designed to evaluate the PK and PD similarity between the recombinant insulin glargine developed by Wanbang (test) and Lantus® (reference) in healthy volunteers. Subjects received subcutaneous administration of the insulin glargine formulation (0.4 U/kg) on two occasions for the test and reference drug, respectively, and a 20% dextrose solution was infused at variable rate to clamp the blood glucose concentrations at 0.3 mmol/L below the subjects’ fasting glucose for 24 h. Taking advantage of the improved sensitivity of the bioanalytical method applied and the solution of the matrix stability problem, the parent insulin glargine was determined in the vast majority of plasma samples using a fully validated UHPLC-MS/MS method. The PK characteristics of the parent insulin glargine were revealed for the first time: after subcutaneous injection, concentrations of the parent insulin glargine increased to a relative high level within 3 h, and then, a relatively flat concentration–time profile lasting for at least 12 h post-dose was observed. For the first time, the pharmacokinetic parameters of the parent insulin glargine were used as endpoints for similarity evaluation, which complied with the regulatory guidance better and made the similarity conclusion more powerful. The ratios of geometric means of all PK and PD endpoints were close to 100.00%. For the PK endpoints (AUC0–24h, Cmax, AUC0–12h, and AUC12–24h of the parent insulin glargine and its metabolite M1), the 90% confidence intervals of geometric mean ratios of test to reference were entirely contained within 80.00%–125.00%. For the PD endpoints [AUCGIR(0–24h), GIRmax, AUCGIR(0–12h), and AUCGIR(12–24h)], the 95% confidence intervals of geometric mean ratios of test to reference were entirely contained within 80.00%–125.00%. Based on the above mentioned results, it can be concluded that the PK and PD characteristics of the biosimilar drug developed by Wanbang are similar to those of Lantus.
Application of physiologically-based pharmacokinetic/pharmacodynamic models to evaluate the interaction between nifedipine and apatinib
Authors: Liu Hongrui , Yu Yiqun , Liu Lu , Wang Chunyan , Guo Nan , Wang Xiaojuan , Xiang Xiaoqiang , Han Bing
Published: August 2022

Aim: It has been found that the co-administration of nifedipine with apatinib could cause exposure changes of nifedipine in vivo. But, whether this pharmacokinetic drug-drug interaction (DDI) between nifedipine and apatinib could enhance the antihypertensive effect of nifedipine, causing sever changes of blood pressure was unknown. Therefore, the aim of the present study was to conduct the pharmacokinetic/pharmacodynamic (PK/PD) modelling to evaluate the effect of pharmacokinetic changes on the antihypertensive effect of nifedipine. Thus, the results could guide the co-administration of these two drugs in clinic.

Methods: A physiologically-based pharmacokinetic (PBPK) model was first developed for nifedipine. The pharmacokinetic DDI between nifedipine and apatinib was evaluated. Then the verified PBPK models were linked to a PD model for investigating whether the exposure changes of nifedipine could cause severe changes in blood pressure. Furthermore, the changes in blood pressure caused by combination with apatinib were also assessed in patients with hepatic impairment via the PBPK/PD models.

Results: The predicted area under plasma concentration-time profile (AUC), maximum concentration (Cmax), area under effect-time profile (AUE), and maximum reduction in systolic blood pressure (Rmax) are all within 0.5–2.0-fold of the observed data, indicating that the PBPK/PD models for nifedipine are successfully established. The increases of predicted AUC and Cmax of nifedipine in the presence of apatinib are 1.73 and 1.41-fold, respectively. Co-administration of nifedipine with apatinib could cause exposure changes of nifedipine in vivo. However, the predicted AUE and Rmax changes of nifedipine in the presence to the absence of apatinib in cancer patients as well as in patients with hepatic impairment are all within 1.25-fold. The results indicate that the exposure changes of nifedipine caused by combination of apatinib has little effect on the changes of systolic blood pressure both in cancer patients and patients with hepatic impairment.

Conclusion: The pharmacokinetic changes of nifedipine caused by co-administration with apatinib has little impact on the antihypertensive effect of nifedipine. Apatinib is unlikely to cause severe pharmacodynamic DDI via inhibition of CYP3A4. It is suggested that nifedipine could be used in combination with apatinib without dose adjustment in clinic.
The education index in the context of sustainability: Thermo-economic considerations
Authors: Grisolia Giulia , Fino Debora , Lucia Umberto
Published: August 2022

Sustainable development requires new technical solutions to be realized, due to the new approach to production, consumption, and management of resources. These technologies also require technical skills from workers and citizens. These technical abilities are mostly based on the knowledge of mathematics and sciences, acquired during schooling years. In this study, we develop a thermo-economic analysis of sustainable development in relation to the needs of mathematical and technical skills of future workers. To do so, the Education Index is considered to improve it toward a measure of the technical abilities of young people, maintaining its present social meaning of preventing child exploitation. The result is an improvement of the Thermodynamic Human Development Index, by introducing the OECD-PISA assessment, to allow the decision makers to analyze their policies, based on a more comprehensive vision of the present, to better design the future. Finally, we point out the need to focus public policies on the continuous stimulus of intellectual reasoning and on problem-solving-based education to develop the processing capacity and foster the creative capabilities of the younger population that builds the backbone of the future workforce.
A convergent mechanism of sex determination in dioecious plants: Distinct sex-determining genes display converged regulation on floral B-class genes
Authors: Zhang Xianzhi , Pan Linsi , Guo Wei , Li Yongquan , Wang Wencai
Published: August 2022

Sex determination in dioecious plants has been broadly and progressively studied with the blooming of genome sequencing and editing techniques. This provides us with a great opportunity to explore the evolution and genetic mechanisms underlining the sex-determining system in dioecious plants. In this study, comprehensively reviewing advances in sex-chromosomes, sex-determining genes, and floral MADS-box genes in dioecious plants, we proposed a convergent model that governs plant dioecy across divergent species using a cascade regulation pathway connecting sex-determining genes and MADS-box genes e.g., B-class genes. We believe that this convergent mechanism of sex determination in dioecious plants will shed light on our understanding of gene regulation and evolution of plant dioecy. Perspectives concerning the evolutionary pathway of plant dioecy are also suggested.
Reduced basal and increased topdressing fertilizer rate combined with straw incorporation improves rice yield stability and soil organic carbon sequestration in a rice–wheat system
Authors: Zhang Jianwei , Wang Jidong , Zhou Yan , Xu Lei , Chen Yinglong , Ding Yanfeng , Ning Yunwang , Liang Dong , Zhang Yongchun , Li Ganghua
Published: August 2022

Fertilizer management is vital for sustainable agriculture under climate change. Reduced basal and increased topdressing fertilizer rate (RBIT) has been reported to improve the yield of in–season rice or wheat. However, the effect of RBIT on rice and wheat yield stability and soil organic carbon (SOC) sequestration potential is unknown, especially when combined with straw incorporation. Here, we report the effect of RBIT with/without straw incorporation on crop yields, yield stability, SOC stock, and SOC fractions in the lower Yangtze River rice–wheat system region over nine years. RBIT with/without straw incorporation significantly increased nine–year average and annual rice yields but not wheat yields. Compared with conventional fertilization (CF), RBIT did not significantly affect wheat or rice yield stability, but combined with straw incorporation, it increased the sustainable yield index (SYI) of wheat and rice by 7.6 and 12.8%, respectively. RBIT produced a higher C sequestration rate (0.20 Mg C ha−1 year−1) than CF (0.06 Mg ha−1 year−1) in the 0–20 cm layer due to higher root C input and lower C mineralization rate, and RBIT in combination with straw incorporation produced the highest C sequestration rate (0.47 Mg ha−1 year−1). Long–term RBIT had a greater positive effect on silt+clay (0.053 mm)–associated C, microbial biomass C (MBC), dissolved organic C, and hot water organic C in the surface layer (0–10 cm) than in the subsurface layer (10–20 cm). In particular, the increases in SOC pools and mean weight diameter (MWD) of soil aggregates were greater when RBIT was combined with straw incorporation. Correlation analysis indicated that topsoil SOC fractions and MWD were positively correlated with the SYI of wheat and rice. Our findings suggest that the long–term application of RBIT combined with straw incorporation contributed to improving the sustainability of rice production and SOC sequestration in a rice–wheat system.
Rapid identification and deployment of major genes for flowering time and awn traits in common wheat
Authors: Wu Jizhong , Qiao Linyi , Liu Ying , Fu Bisheng , Nagarajan Ragupathi , Rauf Yahya , Jia Haiyan , Yan Liuling
Published: August 2022

Molecular markers are developed to accelerate deployment of genes for desirable traits segregated in a bi-parental population of recombinant inbred lines (RILs) or doubled haplotype (DH) lines for mapping. However, it would be the most effective if such markers for multiple traits could be identified in an F2 population. In this study, single nucleotide polymorphisms (SNP) chips were used to identify major genes for heading date and awn in an F2 population without developing RILs or DH lines. The population was generated from a cross between a locally adapted spring wheat cultivar “Ningmaizi119” and a winter wheat cultivar “Tabasco” with a diverse genetic background. It was found that the dominant Vrn-D1 allele could make Ningmaizi119 flowered a few months earlier than Tabasco in the greenhouse and without vernalization. The observed effects of the allele were validated in F3 populations. It was also found that the dominant Ali-A1 allele for awnless trait in Tabasco or the recessive ali-A1 allele for awn trait in Ningmaizi119 was segregated in the F2 population. The allelic variation in the ALI-A1 gene relies not only on the DNA polymorphisms in the promoter but also on gene copy number, with one copy ali-A1 in Ningmaizi119 but two copies Ali-A1 in Tabasco based on RT-PCR results. According to wheat genome sequences, cultivar “Mattis” has two copies Ali-A1 and cultivar “Spelta” has four copies Ali-A in a chromosome that was uncharacterized (ChrUN), in addition to one copy on chromosome 5A. This study rapidly characterized the effects of the dominant Vrn-D1 allele and identified the haplotype of Ali-A1 in gene copy number in the F2 segregation population of common wheat will accelerate their deployment in cycling lines in breeding.
Rapid adaptation of predictive models during language comprehension: Aperiodic EEG slope, individual alpha frequency and idea density modulate individual differences in real-time model updating
Authors: Bornkessel-Schlesewsky Ina , Sharrad Isabella , Howlett Caitlin A. , Alday Phillip M. , Corcoran Andrew W. , Bellan Valeria , Wilkinson Erica , Kliegl Reinhold , Lewis Richard L. , Small Steven L. , Schlesewsky Matthias
Published: August 2022

Predictive coding provides a compelling, unified theory of neural information processing, including for language. However, there is insufficient understanding of how predictive models adapt to changing contextual and environmental demands and the extent to which such adaptive processes differ between individuals. Here, we used electroencephalography (EEG) to track prediction error responses during a naturalistic language processing paradigm. In Experiment 1, 45 native speakers of English listened to a series of short passages. Via a speaker manipulation, we introduced changing intra-experimental adjective order probabilities for two-adjective noun phrases embedded within the passages and investigated whether prediction error responses adapt to reflect these intra-experimental predictive contingencies. To this end, we calculated a novel measure of speaker-based, intra-experimental surprisal (“speaker-based surprisal”) as defined on a trial-by-trial basis and by clustering together adjectives with a similar meaning. N400 amplitude at the position of the critical second adjective was used as an outcome measure of prediction error. Results showed that N400 responses attuned to speaker-based surprisal over the course of the experiment, thus indicating that listeners rapidly adapt their predictive models to reflect local environmental contingencies (here: the probability of one type of adjective following another when uttered by a particular speaker). Strikingly, this occurs in spite of the wealth of prior linguistic experience that participants bring to the laboratory. Model adaptation effects were strongest for participants with a steep aperiodic (1/f) slope in resting EEG and low individual alpha frequency (IAF), with idea density (ID) showing a more complex pattern. These results were replicated in a separate sample of 40 participants in Experiment 2, which employed a highly similar design to Experiment 1. Overall, our results suggest that individuals with a steep aperiodic slope adapt their predictive models most strongly to context-specific probabilistic information. Steep aperiodic slope is thought to reflect low neural noise, which in turn may be associated with higher neural gain control and better cognitive control. Individuals with a steep aperiodic slope may thus be able to more effectively and dynamically reconfigure their prediction-related neural networks to meet current task demands. We conclude that predictive mechanisms in language are highly malleable and dynamic, reflecting both the affordances of the present environment as well as intrinsic information processing capabilities of the individual.
Behavioral effects on the offspring of rodent mothers exposed to Tetrahydrocannabinol (THC): A meta-analysis
Authors: Ramírez Simón , Miguez Gonzalo , Quezada-Scholz Vanetza E. , Pardo Luis , Alfaro Felipe , Varas Felipe I. , Laborda Mario A.
Published: August 2022

Pre and perinatal administration of Tetrahydrocannabinol (THC) in rodents and their offspring has many effects that have been studied using different methods that have not been integrated using quantitative methods. The effect of THC administration on behavior can be better understood by meta-analytic techniques. We examined whether there is an overall effect on the behavior of the offspring when THC is administered to mothers. Eligibility criteria included experiments using an experimental design with a control group without THC, in which THC is administered to mothers during pregnancy and lactation in rodents, and in which at least one type of behavioral (locomotor, emotional or cognitive) measurement in the offspring was implemented. Cohen’s d was obtained for each study, then each individual study was weighted, and moderator analysis was performed. Analysis was performed using fixed and random effect models, and the heterogeneity was assessed by calculating Qb, I2 and the prediction interval. Furthermore, 3 sub-meta-analyses were carried out according to the type of behavior. The general analysis determined a low weighted effect size of THC on the behavior of the offspring, moderated by type of rat strain. The sub-meta-analyses showed a medium effect for cognitive effects of THC in the offspring, and a low effect on locomotor activity and emotional behavior. In addition, publication bias was not detected. More research is needed to contribute to the understanding of the effect of THC exposure on offspring.
Ethnic and migration-related inequalities in health anxiety: A systematic review and meta-analysis
Authors: Barbek Rieke , Henning Sinje , Ludwig Julia , von dem Knesebeck Olaf
Published: August 2022

Background

Health anxiety exists on a continuum ranging from the absence of health awareness to the obsessive fear of having a serious illness despite reassurance. Its pathological manifestation can be diagnosed as hypochondriacal or illness anxiety or somatic symptom disorder. Health anxiety is associated with psychological distress and adverse life events, among others, and leads to considerable economic burden. Compared to the majority population, migrants, and ethnic minorities often face major health inequalities. Several mental illnesses and psychosomatic complaints are more common among these groups. To date, potential ethnic and migration-related inequalities in health anxiety have not been clearly described. However, they are of high relevance for the provision of adequate health care of this diverse and potentially vulnerable group. Thus, we conducted a systematic review and meta-analysis of health anxiety in migrants and ethnic minorities.

Methods

A systematic literature search of PubMED, Web of Science, PsycINFO, and PSYNDEX was conducted, covering all studies published until 1st of December 2021. Studies were selected if they employed validated measurement tools of health anxiety and examined migrants and/or ethnic minorities in comparison with the majority population. Meta-analytic methods were applied by using a random-effect model. The study quality was assessed with the Effective Public Health Practice Project Quality Assessment Tool (EPHPP).

Results

We identified 18 studies from 445 studies initially screened. Of these, 14 studies conducted in North America with a total number of 5,082 study participants were included in the meta-analysis. The pooled effect size indicated a higher risk of health anxiety in migrants and ethnic minorities compared to the majority population (OR 1.39, 95%-CI 1.01–1.92). The results proved not to be robust according to publication bias (adjusted OR 1.18, 95%-CI 0.83–1.69) and fail-safe N (2/3 < benchmark N = 75) and are limited due to heterogeneity (I2 = 57%), small sample sizes and an overall low quality of included studies.

Conclusion

To address the diversity of migrants and ethnic minorities, inter-sectional approaches across different countries are needed in research to shed further light on social inequalities in health anxiety linked to migration.

Systematic review registration

PROSPERO, registration number CRD42022298458.
Investigating revisit intention of medical tourists in China through nutritional knowledge, perceived medical quality, and trust in the physiologist: A recommendation on health tourism policy measures
Authors: Fengmin Zhai , Baijun Wu , Jiangtao Bai , Li Liu , Patwary Ataul Karim
Published: August 2022

Good medical care has long been a top priority in health tourism to keep the flow of visitors coming for medical treatment. Medical tourism encompasses a range of treatments, from basic check-ups to surgical operations. For its friendly character and high quality of service, China has earned a reputation as one of Asia's top destinations for health tourism. Along with India and Taiwan, Japan, Thailand, and South Korea are China's top tourism destinations. Considering the above fact, this study aims to examine the influence of nutritional knowledge, perceived medical quality, and trust in physiologists on revisiting the intention of medical tourists in China. This study is cross-sectional and follows a quantitative approach. The researchers used questionnaires as a survey tool to obtain information from the respondents. The respondents of this chosen international tourists in China who come for medical treatment purposes. A systematic random sampling technique was used to select the respondents, and 315 usable responses were collected from the respondents and proceeded with further analysis. The study conducted structural equation modeling using Smart PLS version 3. The results found that nutritional knowledge, perceived medical quality, and trust in physiologists significantly influence the revisit intention of medical tourists in China.
Supporting the creation of non-linear everyday AR experiences in exhibitions and museums: An authoring process based on self-contained building blocks
Authors: Rau Linda , Bitter Jessica L. , Liu Yu , Spierling Ulrike , Dörner Ralf
Published: August 2022

The use of Augmented Reality (AR) has the potential to make everyday experiences exciting and educational. For example, AR can augment exhibits in museums with animated and interactive content. The creation of this content, however, is still facing challenges. To meet these, we employ reusable, pattern-based building blocks called AR nuggets. An AR nugget implements one application pattern in a small and self-contained piece of software to provide a complete solution for recurrent AR-based experiences. For example, in the application context of museums and exhibitions, we identify superimposition or visualization of echolocation as general patterns for AR use cases. AR nuggets encapsulate AR-specific knowledge and sophisticated functionalities to support authors and reduce the authoring task to tweaking existing templates to individual exhibits. To connect AR nuggets used in different exhibition rooms, we present novel AR nuggets that encapsulate the functionalities needed for creating a path between the exhibits. Additionally, we provide examples of AR nuggets that implement a virtual character that guides visitors to exhibits of interest. With this new set of AR nuggets, spatial connections can be authored, e.g., in the form of a guided tour with interactive narration. For this authoring task, we introduce an AR nugget manager that supports authors in creating and adapting multiple non-linear AR experiences. We illustrate our approach with the creation of an everyday AR application for a museum of natural history, share our experiences and discuss to what extent our approach can mitigate authoring challenges for everyday AR applications from a museum’s point of view. This work contributes to the field of everyday AR with 1) a pattern-based authoring concept to create complex everyday AR experiences based on self-contained building blocks, 2) a set of patterns that allows for spatial connections of these to create non-linear AR content, 3) means for supporting this authoring process in the form of an AR nugget manager, 4) lessons learned in applying our authoring concept in a real application case in a museum, 5) our observation of hurdles that still prevent more widespread use of AR in everyday applications during the realization of this application case.
Wildfire impacts on western United States snowpacks
Authors: Koshkin Arielle L. , Hatchett Benjamin J. , Nolin Anne W.
Published: August 2022

Mountain snowpacks provide 53–78% of water used for irrigation, municipalities, and industrial consumption in the western United States. Snowpacks serve as natural reservoirs during the winter months and play an essential role in water storage for human consumption and ecosystem functions. However, wildfires across the West are increasing in severity, size, and frequency, progressively putting snowpacks at risk as they burn further into the seasonal snow zone. Following a fire, snow disappears 4–23 days earlier and melt rates increase by up to 57%. In a high burn severity fire in the Oregon Cascades, the black carbon and charred woody debris shed from burned trees onto the snowpack decreased the snow albedo by 40%. Canopy cover loss causes a 60% increase in solar radiation reaching the snow surface. Together, these effects produce a 200% increase in net shortwave radiation absorbed by the snowpack. This mini-review synthesizes the implications of wildfire for snow hydrology in mountainous watersheds with the primary aim to characterize wildfires' varied influences on the volume and timing of water resources across time scales (daily to decadal), space (plot to watershed) and burn severity (low to high). The increase in the geographical overlap between fire and snow poses unique challenges for managing snow-dominated watersheds and highlights deficiencies in research and operational snow hydrologic modeling, emphasizing the need for additional field and remote-sensing observations and model experiments.
Emerging electrochemical tools for microplastics remediation and sensing
Authors: Martic Sanela , Tabobondung Meaghan , Gao Stephanie , Lewis Tyra
Published: August 2022

Microplastics (MPs) are a part of our daily lives and persist in the environment all across the globe. As a recently recognized emerging pollutant, there is a call to action to mitigate and monitor microplastics. Despite traditional remediation and characterization methodologies, MP-related challenges still exist. Electrochemical strategies for microplastic remediation have been reported in recent years, but very few reports exist on using electrochemical sensors for monitoring microplastics. Therefore, this minireview highlights the opportunities within the existing electrochemical remediation platforms towards sensor design and development, and elaborates on microplastic electrochemical sensors so far.
Prognostic nomograms for gastric carcinoma after surgery to assist decision-making for postoperative treatment with chemotherapy cycles <9 or chemotherapy cycles ≥9
Authors: Li Yifan , Zhang Xiaojuan
Published: August 2022

Objective

We sought to develop novel nomograms to accurately predict overall survival (OS) of chemotherapy cycles <9 and chemotherapy cycles ≥9 and construct risk stratification to differentiate low-risk and high-risk of two cohorts.

Methods

Patients who underwent curative-intent resection for gastric cancer between January 2002 and May 2020 at a single China institution were identified. Variables associated with OS were recorded and analyzed according to multivariable Cox models. Nomograms predicting 3- and 5-year OS were built according to variables resulting from multivariable Cox models. Discrimination ability was calculated using the Harrell's Concordance Index. The constructed nomogram was subjected to 1,000 resamples bootstrap for internal validation. Calibration curves for the new nomograms were used to test the consistency between the predicted and actual 3- and 5-year OS. Decision curve analysis (DCA) was performed to assess the clinical net benefit. The Concordance index (C-index) and time-dependent receiver operating characteristic (t-ROC) curves were used to evaluate and compare the discriminative abilities of the new nomograms. Finally, prognostic risk stratification of gastric cancer was conducted with X-tile software and nomograms converted into a risk-stratified prognosis model.

Results

For the nomogram predict OS of chemotherapy cycles <9, C-index was 0.711 (95% CI, 0.663–0.760) in internal validation and 0.722 (95% CI, 0.662–0.783) in external validation, which was better than AJCC 8th edition TNM staging (internal validation: 0.627, 95% CI, 0.585–0.670) and (external validation: 0.595,95% CI, 0.543–0.648). The C-index of the nomogram for chemotherapy cycles ≥9 in internal validation was 0.755 (95% CI, 0.728–0.782) and 0.785 (95% CI, 0.747–0.823) in external validation, which was superior to the AJCC 8th edition TNM staging (internal validation: 0.712 95% CI, 0.688–0.737) and (external validation 0.734, 95% CI, 0.699–0.770).The calibration curves, t-ROC curves and DCA of the two nomogram models show that the recognition performance of the two nomogram models was outstanding. The statistical differences in the prognosis among the two risk stratification groups further showed that our model had an excellent risk stratification performance.

Conclusion

This is first reported risk stratification for chemotherapy cycles of gastric carcinoma. Our proposed nomograms can effectively evaluate postoperative prognosis of patients with different chemotherapy cycles of gastric carcinoma. Chemotherapy cycles ≥9 is therefore recommended for high-risk patients with chemotherapy cycles <9, but not for low-risk patients. Meanwhile, combination with multiple therapies are essential to high-risk patients with chemotherapy cycles ≥9 and unnecessary for low-risk patients.
Optimal Design Parameters for Hybrid DC Circuit Breakers Using a Multi-Objective Genetic Algorithm
Authors: Nguyen Van-Vinh , Nguyen Nhat-Tung , Nguyen Quang-Thuan , Bui Van-Hai , Su Wencong
Published: August 2022

The primary function of hybrid direct current circuit breakers (HCBs) is to quickly interrupt fault currents to protect high-voltage direct current (HVDC) systems. To enhance the reliability and stability of HVDC systems, optimal design of HCBs is required to minimize the peak fault current, interruption time, and recovery time. Therefore, this study develops a multi-objective genetic algorithm (MOGA)-based optimization model to identify the optimal parameters for HCBs. The MOGA model consists of three objective functions that provide trade-offs among reductions in the peak fault current, the interruption time, and the recovery time. The proposed algorithm is verified with a novel HCB topology using inverse current injection techniques. The performance of the HCB topology with the optimal parameters is validated in the MATLAB/Simulink environment. In addition, a comparison study between the optimal design of an HCB using the proposed algorithm and a typical HCB model is presented in this study to show the effectiveness of the proposed optimization method. Our simulation results show that the optimal parameter design of HCBs significantly reduces the magnitude of the peak fault current and operating time, thus maintaining the safe and stable operation of the entire system.
Double-Talk Detection-Aided Residual Echo Suppression via Spectrogram Masking and Refinement
Authors: Shachar Eran , Cohen Israel , Berdugo Baruch
Published: August 2022

Acoustic echo in full-duplex telecommunication systems is a common problem that may cause desired-speech quality degradation during double-talk periods. This problem is especially challenging in low signal-to-echo ratio (SER) scenarios, such as hands-free conversations over mobile phones when the loudspeaker volume is high. This paper proposes a two-stage deep-learning approach to residual echo suppression focused on the low SER scenario. The first stage consists of a speech spectrogram masking model integrated with a double-talk detector (DTD). The second stage consists of a spectrogram refinement model optimized for speech quality by minimizing a perceptual evaluation of speech quality (PESQ) related loss function. The proposed integration of DTD with the masking model outperforms several other configurations based on previous studies. We conduct an ablation study that shows the contribution of each part of the proposed system. We evaluate the proposed system in several SERs and demonstrate its efficiency in the challenging setting of a very low SER. Finally, the proposed approach outperforms competing methods in several residual echo suppression metrics. We conclude that the proposed system is well-suited for the task of low SER residual echo suppression.
Optimizing the Path of Plug Tray Seedling Transplanting by Using the Improved A* Algorithm
Authors: Li Xiaojun , Wang Weibing , Liu Ganghui , Li Runze , Li Fei
Published: August 2022

In greenhouse nurseries, one of the important tasks of the automatic transplanter is replanting missing or bad seedling holes with healthy seedlings. This requires the transplanter to spend significant time moving between the supply trays and target trays during replanting. The diversity and complexity of the transplanting routes affect transplanter efficiency. Path planning method can find a better path for the manipulator and improve the efficiency of transplantation. The A* algorithm (A*), which is one of the optimal path search algorithms, is often used in practical applications of path planning. In this paper, the heuristic function of the A* is optimized by the ant colony algorithm (ACA), and an improved A* algorithm (Imp-A*) is obtained. Simulation tests and transplanting trials of Imp-A*, A*, ACA, Dijkstra (DA), and common sequence method (CSM) were carried out using 32-, 50-, 72-, and 128-hole plug trays. The results show that Imp-A* inherits the advantages of A* and ACA in terms of path planning length and computation time. Compared to A*, ACA, DA, and CSM, the transplanting time for Imp-A* was reduced by 2.4%, 12.84%, 11.63%, and 14.27%, respectively. In just six trays of transplanting tasks, Imp-A* saves 60.91 s compared to CSM, with an average time saving of 10.15 s per tray. The combination optimization algorithm has similar application prospects in agriculture.
Maturity Classification of “Hupingzao” Jujubes with an Imbalanced Dataset Based on Improved MobileNet V2
Authors: Sun Haixia , Zhang Shujuan , Ren Rui , Su Liyang
Published: August 2022

Fruits with various maturity levels coexist among the harvested jujubes, and have different tastes and uses. Manual grading has a low efficiency and a strong subjectivity. The number of “Hupingzao” jujubes between different maturity levels is unbalanced, which affects the performance of the classifier. To solve the above issue, the class balance loss (CB) was used to improve the MobileNet V2 network, and a transfer learning strategy was used to train the model. The model was optimized based on the selection of an optimizer and learning rate. The model achieved the best classification results using the AdamW optimizer and a learning rate of 0.0001. The application of transfer learning and class balance loss improved the model’s performance. The precision was 96.800~100.000%, the recall was 95.833~100.000%, and the F1 score was 0.963~1.000. To compare the CB-MobileNet V2 performance, the CB-AlexNet, CB-GoogLeNet, CB-ShuffleNet, CB-Inception V3, CB-ResNet 50, and CB-VGG 16 with transfer learning were used to build classification models. Achieving a validation accuracy of 99.058%, and a validation loss value of 0.055, the CB-MobileNet V2 model showed a better overall performance compared with other models. The maturity detection system of “Hupingzao” jujubes was developed to test the model. The testing accuracy of the CB-MobileNet V2 model was 99.294%. The research indicates that the CB-MobileNet V2 model improves the performance of maturity classification, and provides a theoretical basis for intelligent classification of the quality of “Hupingzao” jujubes.
GIS-Based Evaluation of Soil Suitability for Optimized Production on U.S. Tribal Lands
Authors: Smith Harrison W. , Ashworth Amanda J. , Owens Phillip R.
Published: August 2022

Optimizing soil—crop—landscape occurrence is essential for sustainable intensification and food security, but little work has been done to evaluate these parameters on Tribal lands. The objective of this study was to develop first ever high-resolution crop suitability maps and compare two established crop suitability models for their ability to optimize soil resource management of the Quapaw Tribal lands. We built on previously developed continuous soil properties maps for 22,880 ha of Quapaw Tribal lands that used a digital elevation model and a fuzzy-logic based data mining approach to calculate and evaluate the Dideriksen and Storie crop suitability indices. Suitability index results were evaluated against observed yield (n ≥ 130,000) within the study area. Results showed that the observed yield was positively correlated with the Storie suitability index (Spearman rho = 0.16, p < 0.01), but not the Dideriksen index, suggesting the Storie index is more appropriate than the Dideriksen for modeling crop suitability in this area. Additionally, very little (<13%) of the highly suitable soils in the Quapaw Tribal lands are currently used for crop production, suggesting potential yield gaps from the underutilization of highly suitable soils. Future research could improve estimates through the development of novel suitability indices for closing yield gaps and further improved sustainable intensification.
A Review of Research Progress on Soil Organic Cover Machinery in China
Authors: Lin Han , He Jin , Li Hui , Li Hongwen , Wang Qingjie , Lu Caiyun , Li Yanjie , Jiang Shaomei
Published: August 2022

Soil organic cover technology is an effective way to solve agricultural productivity and agro-environmental issues. However, some factors limit the widespread adoption of its application, including unclear soil organic cover effects and the lack of high-performance soil organic cover machinery. Aiming to solve the existing problems, improve soil organic cover quality, and reduce energy consumption, this article reviewed the common and commercial machines by reviewing the existing literature and company products. The current problems and technical difficulties of the machines were expounded. Simultaneously, the method of design and optimization of the device (chopper, spreader, rotary tiller, and plow) and its key parts (blades, discs, and plows) were reviewed. Furthermore, the features and differences of the devices and their key parts were compared, and their advantages and disadvantages were analyzed. In conclusion, the future directions for soil organic cover technology and machinery development were suggested, including clarifying the soil organic cover effect, selecting the suitable soil organic cover patterns, and developing soil organic cover machinery.
Printed Sowing of High-Density Mechanical Transplanted Hybrid Rice Can Reduce the Amount of Fertilizer Needed
Authors: Shi Nan , Wen Shuangya , Gao Qianwen , Gao Zhiqiang , Yang Huibing
Published: August 2022

In this study, we investigated how printed sowing machine transplanting impacts the yield of single-season rice by increasing the planting density and decreasing the amount of fertilizer needed. The study was aimed at exploring the relationships between the amount of fertilizer, transplanting density, and rice yield. During the rice growing season from 2019 to 2020 in the middle and lower reaches of the Yangtze River, six different field trials were conducted: low density and high fertilizer (LDHF), low density and low fertilizer (LDLF), middle density and high fertilizer (MDHF), middle density and low fertilizer (MDLF), high density and high fertilizer (HDHF), and high density and low fertilizer (HDLF). It turns out that compared to the LDHF, the thousand seed weight, the spikelets per panicle, the seed-setting rate, and the SPAD value at the filling stage decreased by 0.17% and 0.60%, 5.36% and 10.59%, 5.70% and 4.66%, and 17.52% and 4.93% in 2019 and 2020, respectively. However, compared to the LDHF, the panicles increased by 15.31% and 17.18%, respectively, the LAI at the filling stage increased by 1.92% and 0.48%, respectively, and the accumulation of dry matter above ground at the maturity stage also increased by 3.74% and 16.79% in 2019 and 2020, respectively. Therefore, compared to the yield of rice in the LDHF, the yield of rice in the HDLF increased by 5.06% and 6.64%. The yields of rice in the LDLF, MDHF, MDLF, and HDHF were lower than that in the LDHF and HDLF. The partial least squares path model (PLSPM) analysis showed that the fertilizer, density, and aboveground dry matter had positive effects on the yield, while the SPAD value and LAI had negative effects on the yield. This research shows that increasing the transplanting density can compensate for the yield loss caused by reducing the fertilizer amount. However, no combination of the transplanting density and fertilization amount can achieve the purpose of increasing the yield.
Effects of Foliar and Soil Boron Fertilization on Yield, Leaf Physiological Traits and Fruit Attributes in Rainfed Almond Orchards
Authors: Silva Ana P. , Aires Alfredo , Barreales David , Rodrigues Manuel Â. , Ribeiro António C. , Gonçalves Berta , Morais Maria C.
Published: August 2022

Boron (B) fertilizers are recognized as essential for ensuring yield and fruit quality. However, the importance of soil and foliar B fertilization in almond orchards under rainfed conditions is presently unclear. To address this literature gap, in the present study, the impact of soil and foliar application of B on leaf gas exchange, leaf photosynthetic pigments, yield, and fruit quality in almonds was investigated across three consecutive growing seasons. Boron fertilizer was applied to the soil at four rates (0, 1, 2, and 3 kg ha−1) in the presence or absence of foliar application (0.36 g L−1) of the same micronutrient. Borax pentahydrate was used as the B source. When compared to foliar B fertilization, the soil application of B positively affected the gas exchange parameters, mainly the net CO2 assimilation rate, stomatal conductance, and transpiration rate (percentage of gain between 15% and 80%), but did not influence the chlorophyll content. The almond yield and fruit characteristics were also enhanced (about 25–72%) in response to lower soil B fertilization rates. In the 3 kg ha−1 dose, B had an adverse effect on the yield and resulted in lighter fruits. On the other hand, foliar B fertilization did not benefit any of the evaluated parameters. Overall, these results suggest that, under the studied conditions, almond orchards do not respond to higher B rates in soil or foliar B fertilization.
EURL ECVAM Literature Review Series on Advanced Non-Animal Models for Respiratory Diseases, Breast Cancer and Neurodegenerative Disorders
Authors: Gribaldo Laura , Dura Adelaide
Published: August 2022

In vivo models are used in biomedical research to reproduce human disease and develop new drugs. However, they do not mimic the disease as it occurs in humans, and their use has failed to identify novel therapies effective for many highly prevalent non-communicable diseases, such as Alzheimer’s disease. Indeed, the clinical failure rate in drug development remains very high, with an overall likelihood of approval from Phase I of about 9.6%. On the other hand, human-based models, advanced imaging techniques and human epidemiological studies may increase our understanding of disease aetiology and pathogenesis and enable the advance of safe and effective therapies. Particularly when human tissues are used, they may produce faster, cheaper results, more predictive for humans, whilst yielding greater comprehensions of human biochemical processes. A first effort to collect existing knowledge about non-animal models of highly prevalent human diseases was made by the Joint Research Centre of the European Commission. The final aim was to identify and share information on the capabilities and limits of human-based models at different levels: scientific communities, universities and secondary schools, national committees for animal welfare and the public at large.
VR Games in Cultural Heritage: A Systematic Review of the Emerging Fields of Virtual Reality and Culture Games
Authors: Theodoropoulos Anastasios , Antoniou Angeliki
Published: August 2022

In recent years, the use of VR games in cultural heritage has been growing. VR Games have increasingly found their way into museums and exhibitions, highlighting the increasing cultural value associated with games and the institutionalization of game culture. In particular, serious VR games have a variety of benefits for educational purposes. There are several studies that deployed VR games to improve visitor experiences in several contexts. However, there are not sufficient studies in the field that examine the benefits and drawbacks of VR gaming. This lack of classification studies is regarded as an obstacle to developing more effective games and proposing guidance on the best way of using them in cultural heritage. This review aims to analyze how VR games are used in cultural heritage settings, to explore the evolution and opportunities of this emerging field, the challenges and tensions these innovations present, and to collectively advance this work to benefit visitor experiences.
A Fiber Vibration Signal Recognition Method Based on CNN-CBAM-LSTM
Authors: Huang Jincheng , Mo Jiaqing , Zhang Jiangwei , Ma Xinrong
Published: August 2022

By trying to solve the issue of identifying multiple types of intrusion vibration signals collected by distributed vibrating fiber optic sensors, this study investigates the signal identification and feature extraction of intrusion signals, and proposes an optical fiber vibration signal (OFVS) identification method based on deep learning. The external vibration signal is collected by the Sagnac fiber optic interferometer, and then denoised by spectral subtraction. Endpoint detection is carried out by combining the short-time logarithmic energy method and the spectral entropy method. Finally, the equal-length signal containing valid information is intercepted and the corresponding preprocessing is carried out. The method for feature processing incorporates the strong feature learning capability of the long-short-term memory (LSTM) and the great short-term feature extraction capability of the convolutional neural network (CNN). At the same time, to further enhance the signal feature identification, a convolutional block attention module (CBAM) is introduced to perform adaptive feature refinement on the signal. In summary, a network model combining CNN, LSTM, and CBAM is proposed to process the signal features, and finally, the multi-layer perceptron (MLP) is used to complete the task of classification and recognition of multi-type intrusion signals. The experimental findings indicate that the OFVS method of CNN-CBAM-LSTM can effectively identify four kinds of OFVS, and the overall average recognition accuracy reaches 97.9%. Walking and knocking signals among them are recognized with over 99% accuracy.