bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanical Properties and Structural Optimization of Continuous Welded Rail on Super-Long-Span Suspension Bridges for High-Speed Railway
Authors: Zhao Guanyuan , Cai Xiaopei , Liu Wanli , Wang Tielin , Wang Tao
Published: December 2021

In order to ensure driving safety and comfort, it is necessary to figure out the complex interaction between continuous welded rail (CWR) and suspension bridges for high-speed railway. A spatial finite element model for a 1092 m main span suspension bridge was established based on the bridge-track interaction theory. A specific correction method was put forward to keep the rail in a zero-stress state when just laid. Three rail expansion joint (REJ) layout schemes were proposed according to practical engineering experience. Both static and dynamic analysis methods were used to evaluate the feasibility of these schemes. The results show that the REJ should be laid at the position with a distance away from the primary beam end, and the beam with more substantial integral stiffness should be preferentially selected. For the recommended scheme, the REJ expansion reaches more than 380 mm under expansion load. The factors affecting the REJ expansion from major to minor are temperature, earthquake, rail fracture, braking, and bending load. The superposition effect of the above factors is suggested to be considered in the selection of REJ range.
Review of Visual Saliency Prediction: Development Process from Neurobiological Basis to Deep Models
Authors: Yan Fei , Chen Cheng , Xiao Peng , Qi Siyu , Wang Zhiliang , Xiao Ruoxiu
Published: December 2021

The human attention mechanism can be understood and simulated by closely associating the saliency prediction task to neuroscience and psychology. Furthermore, saliency prediction is widely used in computer vision and interdisciplinary subjects. In recent years, with the rapid development of deep learning, deep models have made amazing achievements in saliency prediction. Deep learning models can automatically learn features, thus solving many drawbacks of the classic models, such as handcrafted features and task settings, among others. Nevertheless, the deep models still have some limitations, for example in tasks involving multi-modality and semantic understanding. This study focuses on summarizing the relevant achievements in the field of saliency prediction, including the early neurological and psychological mechanisms and the guiding role of classic models, followed by the development process and data comparison of classic and deep saliency prediction models. This study also discusses the relationship between the model and human vision, as well as the factors that cause the semantic gaps, the influences of attention in cognitive research, the limitations of the saliency model, and the emerging applications, to provide new saliency predictions for follow-up work and the necessary help and advice.
Best-Estimate for System Codes (BeSYC): A New Software to Perform Best-Estimate Plus Uncertainty Analyses with Thermal-Hydraulic and Safety System Codes for Both Fusion and Fission Scenarios
Authors: Gonfiotti Bruno , Angelucci Michela , Ghidersa Bradut-Eugen , Jin Xue Zhou , Ionescu-Bujor Mihaela , Paci Sandro , Stieglitz Robert
Published: December 2021

The development and the validation of old and new software in relevant DEMO reactor conditions have been exploited in the latest years within the EUROfusion Consortium. The aim was to use—if possible—the software already validated for fission reactors and to fill the gaps with new ad-hoc software. As contribution to this effort, the Karlsruhe Institute of Technology (KIT) developed and tested a novel software to apply the Best-Estimate Model Calibration and Prediction through Experimental Data Assimilation methodology to the system codes RELAP5-3D, MELCOR 1.8.6, and MELCOR 2.2. This software is called Best-estimate for SYstem Codes (BeSYC), and it is developed as a MATLAB App. The application is in charge of applying the mathematical framework of the methodology, writing and executing the code runs required by the methodology, and printing the obtained results. The main goal of BeSYC is to wrap up the methodology in a software suitable to be used by any user through a simple graphical user interface. Albeit developed in the fusion research context, BeSYC can be applied to any reactor/scenario type supported by the specific system code. The goals of BeSYC, the mathematical framework, the main characteristics, and the performed verification and validation activities are described in this paper.
Graphene on Silicon Photonics: Light Modulation and Detection for Cutting-Edge Communication Technologies
Authors: Yan Siqi , Adcock Jeremy , Ding Yunhong
Published: December 2021

Graphene—a two-dimensional allotrope of carbon in a single-layer honeycomb lattice nanostructure—has several distinctive optoelectronic properties that are highly desirable in advanced optical communication systems. Meanwhile, silicon photonics is a promising solution for the next-generation integrated photonics, owing to its low cost, low propagation loss and compatibility with CMOS fabrication processes. Unfortunately, silicon’s photodetection responsivity and operation bandwidth are intrinsically limited by its material characteristics. Graphene, with its extraordinary optoelectronic properties has been widely applied in silicon photonics to break this performance bottleneck, with significant progress reported. In this review, we focus on the application of graphene in high-performance silicon photonic devices, including modulators and photodetectors. Moreover, we explore the trend of development and discuss the future challenges of silicon-graphene hybrid photonic devices.
New Business Models on Artificial Intelligence—The Case of the Optimization of a Blast Furnace in the Steel Industry by a Machine Learning Solution
Authors: Redchuk Andrés , Walas Mateo Federico
Published: December 2021

This article took the case of the adoption of a Machine Learning (ML) solution in a steel manufacturing process through a platform provided by a Canadian startup, Canvass Analytics. The content of the paper includes a study around the state of the art of AI/ML adoption in steel manufacturing industries to optimize processes. The work aimed to highlight the opportunities that bring new business models based on AI/ML to improve processes in traditional industries. Methodologically, bibliographic research in the Scopus database was performed to establish the conceptual framework and the state of the art in the steel industry, then the case was presented and analyzed, to finally evaluate the impact of the new business model on the operation of the steel mill. The results of the case highlighted the way the innovative business model, based on a No-Code/Low-Code solution, achieved results in less time than conventional approaches of analytics solutions, and the way it is possible to democratize artificial intelligence and machine learning in traditional industrial environments. This work was focused on opportunities that arise around new business models linked to AI. In addition, the study looked into the framework of the adoption of AI/ML in a traditional industrial environment toward a smart manufacturing approach. The contribution of this article was the proposal of an innovative methodology to put AI/ML in the hands of process operators. It aimed to show how it was possible to achieve better results in a less complex and time-consuming adoption process. The work also highlighted the need for an important quantity of data from the process to approach this kind of solution.
Investigation of Sources, Diversity, and Variability of Bacterial Aerosols in Athens, Greece: A Pilot Study
Authors: Metaxatos Angelina , Manibusan Sydonia , Mainelis Gediminas
Published: December 2021

We characterized the composition, diversity, and potential bacterial aerosol sources in Athens’ urban air by DNA barcoding (analysis of 16S rRNA genes) during three seasons in 2019. Air samples were collected using the recently developed Rutgers Electrostatic Passive Sampler (REPS). It is the first field application of REPS to study bacterial aerosol diversity. REPS samplers captured a sufficient amount of biological material to demonstrate the diversity of airborne bacteria and their variability over time. Overall, in the air of Athens, we detected 793 operational taxonomic units (OTUs), which were fully classified into the six distinct taxonomic categories (Phylum, Class, Order, etc.). These OTUs belonged to Phyla Actinobacteria, Firmicutes, Proteobacteria, Bacteroidetes, Cyanobacteria, and Fusobacteria. We found a complex community of bacterial aerosols with several opportunistic or potential pathogens in Athens’ urban air. Referring to the available literature, we discuss the likely sources of observed airborne bacteria, including soil, plants, animals, and humans. Our results on bacterial diversity are comparable to earlier studies, even though the sampling sites are different or geographically distant. However, the exact functional and ecological role of bioaerosols and, even more importantly, their impact on public health and the ecosystem requires further air monitoring and analysis.
A Comparison of Machine Learning Methods to Forecast Tropospheric Ozone Levels in Delhi
Authors: Juarez Eliana Kai , Petersen Mark R.
Published: December 2021

Ground-level ozone is a pollutant that is harmful to urban populations, particularly in developing countries where it is present in significant quantities. It greatly increases the risk of heart and lung diseases and harms agricultural crops. This study hypothesized that, as a secondary pollutant, ground-level ozone is amenable to 24 h forecasting based on measurements of weather conditions and primary pollutants such as nitrogen oxides and volatile organic compounds. We developed software to analyze hourly records of 12 air pollutants and 5 weather variables over the course of one year in Delhi, India. To determine the best predictive model, eight machine learning algorithms were tuned, trained, tested, and compared using cross-validation with hourly data for a full year. The algorithms, ranked by R2 values, were XGBoost (0.61), Random Forest (0.61), K-Nearest Neighbor Regression (0.55), Support Vector Regression (0.48), Decision Trees (0.43), AdaBoost (0.39), and linear regression (0.39). When trained by separate seasons across five years, the predictive capabilities of all models increased, with a maximum R2 of 0.75 during winter. Bidirectional Long Short-Term Memory was the least accurate model for annual training, but had some of the best predictions for seasonal training. Out of five air quality index categories, the XGBoost model was able to predict the correct category 24 h in advance 90% of the time when trained with full-year data. Separated by season, winter is considerably more predictable (97.3%), followed by post-monsoon (92.8%), monsoon (90.3%), and summer (88.9%). These results show the importance of training machine learning methods with season-specific data sets and comparing a large number of methods for specific applications.
Monitoring and Predictive Estimations of Atmospheric Parameters in the Catchment Area of Lake Baikal
Authors: Abasov Nikolay V. , Nikitin Viacheslav M. , Berezhnykh Tamara V. , Osipchuk Evgeny N.
Published: December 2021

The paper is concerned with a methodological approach to monitoring the state of atmospheric parameters in the catchment area of Lake Baikal, including real-time analysis of actual distributed data with the determination of analog years according to the preset proximity of comparative indicators and the most probable long-term predictive distributions of surface temperatures, precipitation, pressure, and geopotential with a lead time of up to 9–12 months. We have developed the information-analytical system GeoGIPSAR to conduct the real-time analysis of spatial and point data by various processing methods and obtain long-term prognostic estimates of water inflow into the lake.
Effects of the COVID-19 Pandemic on the Air Quality of the Metropolitan Region of São Paulo: Analysis Based on Satellite Data, Monitoring Stations and Records of Annual Average Daily Traffic Volumes on the Main Access Roads to the City
Authors: Pérez-Martínez Pedro José , Magalhães Tiago , Maciel Isabela , de Miranda Regina M. , Kumar Prashant
Published: December 2021

This paper presents an analysis of the effects of the COVID-19 pandemic on the air quality of the Metropolitan Region of São Paulo (MRSP). The effects of social distancing are still recent in the society; however, it was possible to observe patterns of environmental changes in places that had adhered transportation measures to combat the spread of the coronavirus. Thus, from the analysis of the traffic volumes made on some of the main access highways to the MRSP, as well as the monitoring of the levels of fine particulate matter (PM2.5), carbon monoxide (CO) and nitrogen dioxide (NO2), directly linked to atmospheric emissions from motor vehicles–which make up about 95% of air polluting agents in the region in different locations–we showed relationships between the improvement in air quality and the decrease in vehicles that access the MRSP. To improve the data analysis, therefore, the isolation index parameter was evaluated to provide daily information on the percentage of citizens in each municipality of the state that was effectively practicing social distancing. The intersection of these groups of data determined that the COVID-19 pandemic reduced the volume of vehicles on the highways by up to 50% of what it was in 2019, with the subsequent recovery of the traffic volume, even surpassing the values from the baseline year. Thus, the isolation index showed a decline of up to 20% between its implementation in March 2020 and December 2020. These data and the way they varied during 2020 allowed to observe an improvement of up to 50% in analyzed periods of the pollutants PM2.5, CO and NO2 in the MRSP. The main contribution of this study, alongside the synergistic use of data from different sources, was to perform traffic flow analysis separately for light and heavy duty vehicles (LDVs and HDVs). The relationships between traffic volume patterns and COVID-19 pollution were analyzed based on time series.
In Vitro Probiotic Characteristics and Whole Genome Sequence Analysis of Lactobacillus Strains Isolated from Cattle-Yak Milk
Authors: Zheng Juanshan , Du Mei , Jiang Wei , Zhang Jianbo , Shen Wenxiang , Ma Xiaoyu , Liang Zeyi , Shen Jiahao , Wu Xiaohu , Ding Xuezhi
Published: December 2021

Cattle-yak milk is an important raw material and an indispensable source of high-quality food for local farmers and herdsmen to produce ghee, milk residue, yogurt, and other dairy products. In this study, Lactobacillus strains were isolated from cattle-yak milk for potential probiotic candidates using a series of in vitro tests, including probiotic characterization and safety evaluation (antibiotic susceptibility and hemolytic ability). The results found that the Lactobacillus rhamnosus CY12 strain showed a high survival rate in bile salts, under acid conditions, and in the gastrointestinal juice environment, as well as showing high antimicrobial activity and adhesive potential. The safety evaluation showed that all strains were considered non-hemolytic. In addition, the whole-genome sequencing indicated that the strain CY12 spanned 2,506,167 bp, with an average length of 881 bp; the GC content in the gene region (%) was 47.35, contained 1347 protein-coding sequences, and accounted for 85.72% of the genome. The genome annotation showed that genes mainly focused on the immune system process, metabolic process, carbohydrate utilization, carbon metabolism, galactose metabolism, and biological adhesion, etc. This study revealed that the Lactobacillus rhamnosus CY12 strain might be an excellent potential probiotic in the development of feed additives for animals and has the ability to promote health.
Entomopathogenic Nematodes for the Management of Plum Curculio in Highbush Blueberry
Authors: Sousa Ana Luiza , Rodriguez-Saona Cesar , Holdcraft Robert , Kyryczenko-Roth Vera , Koppenhöfer Albrecht M.
Published: December 2021

Conotrachelus nenuphar Herbst (Coleoptera: Curculionidae) is a key pest of stone and pome fruits in the United States. Application of certain entomopathogenic nematode (EPN) species has shown efficacy in some crops when targeting the larval stage of C. nenuphar in soil. To date, however, no EPNs have been tested for the control of this pest in highbush blueberries. In 2020, laboratory and field studies were conducted to: (1) determine the persistence of Steinernema riobrave, S. carpocapsae, S. feltiae, and Heterorhabditis bacteriophora in acidic blueberry soil; (2) compare the virulence of these EPNs to C. nenuphar larvae and pupae; and (3) compare the efficacy of these EPN species to control this pest in blueberry fields. The greatest persistence in blueberry soil was exhibited by S. riobrave followed by S. carpocapsae. Superior virulence was observed in S. riobrave against C. nenuphar larvae and pupae. Promising levels of virulence were also observed in S. carpocapsae and S. feltiae against the larvae, but S. scarabaei had low virulence. In the field, S. riobrave provided significantly higher levels of C. nenuphar suppression (90%) than the other EPNs. The field efficacy of S. riobrave against C. nenuphar at low and high rates was confirmed in 2021. Steinernema riobrave has the potential to become an important component in the management of C. nenuphar in highbush blueberry.
Breast Cancer Surgery 10-Year Survival Prediction by Machine Learning: A Large Prospective Cohort Study
Authors: Lou Shi-Jer , Hou Ming-Feng , Chang Hong-Tai , Lee Hao-Hsien , Chiu Chong-Chi , Yeh Shu-Chuan Jennifer , Shi Hon-Yi
Published: December 2021

Machine learning algorithms have proven to be effective for predicting survival after surgery, but their use for predicting 10-year survival after breast cancer surgery has not yet been discussed. This study compares the accuracy of predicting 10-year survival after breast cancer surgery in the following five models: a deep neural network (DNN), K nearest neighbor (KNN), support vector machine (SVM), naive Bayes classifier (NBC) and Cox regression (COX), and to optimize the weighting of significant predictors. The subjects recruited for this study were breast cancer patients who had received breast cancer surgery (ICD-9 cm 174–174.9) at one of three southern Taiwan medical centers during the 3-year period from June 2007, to June 2010. The registry data for the patients were randomly allocated to three datasets, one for training (n = 824), one for testing (n = 177), and one for validation (n = 177). Prediction performance comparisons revealed that all performance indices for the DNN model were significantly (p < 0.001) higher than in the other forecasting models. Notably, the best predictor of 10-year survival after breast cancer surgery was the preoperative Physical Component Summary score on the SF-36. The next best predictors were the preoperative Mental Component Summary score on the SF-36, postoperative recurrence, and tumor stage. The deep-learning DNN model is the most clinically useful method to predict and to identify risk factors for 10-year survival after breast cancer surgery. Future research should explore designs for two-level or multi-level models that provide information on the contextual effects of the risk factors on breast cancer survival.
Benefits and Risks of the Technological Creep of LED Light Technologies Applied to the Purse Seine Fishery
Authors: Ricci Pasquale , Trivellin Nicola , Cascione Daniela , Cipriano Giulia , Orlandi Viviana Teresa , Carlucci Roberto
Published: December 2021

This study is a first attempt to investigate the catch efficiency of LED light technology compared to the traditional incandescent lamp that is used in the purse seine fishery (PS) in the Central Adriatic Sea (Mediterranean Sea). Catches per unit effort were adopted to assess the performance of lighting systems, considering the electrical energy and the fuel consumption as effort units. Concerning the catch efficiency, the white LED, which emits the same light spectra as the incandescent lamp, increased the yield by over 2 times per consumption unit of energy and fuel. The yield efficiency increased up to approximately 6 and 9 times when adopting the pulsing white or blue LED, respectively. These increases were due to the energy savings resulting from the flashing of the white LED or by the greater water penetration of the blue LED. No significant difference in target species sizes was detected between the use of LEDs and the incandescent lamp. The results obtained from estimates of the hourly fuel consumption and CO2 emissions stress potential benefits in the reduction of the carbon footprint due to the use of LEDs within the PS fishery. Positive economic impacts were derived from the LED technology on the PS fishery, with the fuel cost-saving percentages all being higher than 60%. The LED technology clearly shows potential benefits at the economic level for the fishermen, and the possibility of mitigating indirect negative effects on the environment due to fuel combustion and greenhouse gas emissions. On the other hand, the application of new technology that improves the catch efficiency of fishing gears should be carefully considered. The lack of regulations controlling technological advancement could cause unwanted long-term effects.
The Diagnostic and Therapeutic Potential of Galectin-3 in Cardiovascular Diseases
Authors: Sygitowicz Grażyna , Maciejak-Jastrzębska Agata , Sitkiewicz Dariusz
Published: December 2021

Galectin-3 plays a prominent role in chronic inflammation and has been implicated in the development of many disease conditions, including heart disease. Galectin-3, a regulatory protein, is elevated in both acute and chronic heart failure and is involved in the inflammatory pathway after injury leading to myocardial tissue remodelling. We discussed the potential utility of galectin-3 as a diagnostic and disease severity/prognostic biomarker in different cardio/cerebrovascular diseases, such as acute ischemic stroke, acute coronary syndromes, heart failure and arrhythmogenic cardiomyopathy. Over the last decade there has been a marked increase in the understanding the role of galectin-3 in myocardial fibrosis and inflammation and as a therapeutic target for the treatment of heart failure and myocardial infarction.
Characterization of the LPS and 3OHFA Contents in the Lipoprotein Fractions and Lipoprotein Particles of Healthy Men
Authors: Rehues Pere , Rodríguez Marina , Álvarez Judith , Jiménez Marta , Melià Alba , Sempere Mar , Balsells Clara , Castillejo Gemma , Guardiola Montse , Castro Antoni , Ribalta Josep
Published: December 2021

Atherosclerosis is a chronic inflammatory disease that is caused by the accumulation of LDL particles in the intima, causing the activation of immune cells and triggering an inflammatory response. LPS is a potent activator of the innate immune response and it can be transported by lipoproteins. Since humans are much more sensitive to LPS than other mammals, and very low amounts of LPS can elicit an immune response, the aim of this study is to characterize the distribution of LPS and its immunogenic portion (3OHFAs) among lipoprotein types of healthy men. We separated lipoprotein fractions by ultracentrifugation and the amount of each 3OHFA was measured by MS in each lipoprotein fraction to calculate LPS concentration. Lipoprotein particle concentration was measured by NMR. LDL and HDL fractions transported the highest concentration of LPS (35.7% and 31.5%, respectively), but VLDL particles carried more LPS molecules per particle (0.55 molecules/particle) than LDL or HDL (p < 0.01). The distribution of LPS and all 3OHFAs among lipoprotein fractions showed high interindividual variability, suggesting that they may be studied as a potential biomarker. This may help understand the role of LPS in atherosclerosis in those cases where the disease cannot be explained by traditional risk factors.
COX5B-Mediated Bioenergetic Alterations Modulate Cell Growth and Anticancer Drug Susceptibility by Orchestrating Claudin-2 Expression in Colorectal Cancers
Authors: Chu Yu-De , Lim Siew-Na , Yeh Chau-Ting , Lin Wey-Ran
Published: December 2021

Oxidative phosphorylation (OXPHOS) consists of four enzyme complexes and ATP synthase, and is crucial for maintaining physiological tissue and cell growth by supporting the main bioenergy pool. Cytochrome c oxidase (COX) has been implicated as a primary regulatory site of OXPHOS. Recently, COX subunit 5B (COX5B) emerged as a potential biomarker associated with unfavorable prognosis by modulating cell behaviors in specific cancer types. However, its molecular mechanism remains unclear, particularly in colorectal cancers (CRCs). To understand the role of COX5B in CRCs, the expression and postoperative outcome associations using independent in-house patient cohorts were evaluated. A higher COX5B tumor/nontumor expression ratio was associated with unfavorable clinical outcomes (p = 0.001 and 0.011 for overall and disease-free survival, respectively. In cell-based experiments, the silencing of COX5B repressed cell growth and enhanced the susceptibility of CRCs cells to anticancer drugs. Finally, downstream effectors identified by RNA sequencing followed by RT-qPCR and functional compensation experiments revealed that the tight junction protein Claudin-2 (CLDN2) acts downstream of COX5B-mediated bioenergetic alterations in controlling cell growth and the sensitivity to anticancer drugs in CRCs cells. In conclusion, it was found that COX5B promoted cell growth and attenuated anticancer drugs susceptibility in CRCs cells by orchestrating CLDN2 expression, which may contribute to unfavorable postoperative outcomes of patients with CRCs.
Effect of Gliadin Stimulation on HLA-DQ2.5 Gene Expression in Macrophages from Adult Celiac Disease Patients
Authors: Farina Federica , Pisapia Laura , Laezza Mariavittoria , Serena Gloria , Rispo Antonio , Ricciolino Simona , Gianfrani Carmen , Fasano Alessio , Del Pozzo Giovanna
Published: December 2021

Macrophages play an important role in the pathogenesis of celiac disease (CD) because they are involved in both inflammatory reaction and antigen presentation. We analyzed the expression of CD-associated HLA-DQ2.5 risk alleles on macrophages isolated by two cohorts of adult patients, from the U.S. and Italy, at different stages of disease and with different genotypes. After isolating and differentiating macrophages from PBMC, we assessed the HLA genotype and quantified the HLA-DQ2.5 mRNAs by qPCR, before and after gliadin stimulation. The results confirmed the differences in expression between DQA1*05:01 and DQB1*02:01 predisposing alleles and the non-CD associated alleles, as previously shown on other types of APCs. The gliadin challenge confirmed the differentiation of macrophages toward a proinflammatory phenotype, but above all, it triggered an increase of DQA1*05:01 mRNA, as well as a decrease of the DQB1*02:01 transcript. Furthermore, we observed a decrease in the DRB1 genes expression and a downregulation of the CIITA transactivator. In conclusion, our findings provide new evidences on the non-coordinated regulation of celiac disease DQ2.5 risk genes and support the hypothesis that gliadin could interfere in the three-dimensional arrangement of chromatin at the HLA locus.
Supramolecular Nanostructures for Vaccines
Authors: Carmona-Ribeiro Ana Maria
Published: December 2021

Although this is an era of pandemics and many devastating diseases, this is also a time when bionanotechnology flourishes, illuminating a multidisciplinary field where vaccines are quickly becoming a balsam and a prevention against insidious plagues. In this work, we tried to gain and also give a deeper understanding on nanovaccines and their way of acting to prevent or cure cancer, infectious diseases, and diseases caused by parasites. Major nanoadjuvants and nanovaccines are temptatively exemplified trying to contextualize our own work and its relative importance to the field. The main properties for novel adjuvants seem to be the nanosize, the cationic character, and the biocompatibility, even if it is achieved in a low dose-dependent manner.
CBM: An IoT Enabled LiDAR Sensor for In-Field Crop Height and Biomass Measurements
Authors: Banerjee Bikram Pratap , Spangenberg German , Kant Surya
Published: December 2021

The phenotypic characterization of crop genotypes is an essential, yet challenging, aspect of crop management and agriculture research. Digital sensing technologies are rapidly advancing plant phenotyping and speeding-up crop breeding outcomes. However, off-the-shelf sensors might not be fully applicable and suitable for agricultural research due to the diversity in crop species and specific needs during plant breeding selections. Customized sensing systems with specialized sensor hardware and software architecture provide a powerful and low-cost solution. This study designed and developed a fully integrated Raspberry Pi-based LiDAR sensor named CropBioMass (CBM), enabled by internet of things to provide a complete end-to-end pipeline. The CBM is a low-cost sensor, provides high-throughput seamless data collection in field, small data footprint, injection of data onto the remote server, and automated data processing. The phenotypic traits of crop fresh biomass, dry biomass, and plant height that were estimated by CBM data had high correlation with ground truth manual measurements in a wheat field trial. The CBM is readily applicable for high-throughput plant phenotyping, crop monitoring, and management for precision agricultural applications.
Evaluation of Anesthetic Specific EEG Dynamics during State Transitions between Loss and Return of Responsiveness
Authors: Kreuzer Matthias , Kiel Tobias , Ernst Leonie , Lipp Marlene , Schneider Gerhard , Pilge Stefanie
Published: December 2021

Purpose: electroencephalographic (EEG) information is used to monitor the level of cortical depression of a patient undergoing surgical intervention under general anesthesia. The dynamic state transitions into and out of anesthetic-induced loss and return of responsiveness (LOR, ROR) present a possibility to evaluate the dynamics of the EEG induced by different substances. We evaluated changes in the EEG power spectrum during anesthesia emergence for three different anesthetic regimens. We also assessed the possible impact of these changes on processed EEG parameters such as the permutation entropy (PeEn) and the cerebral state index (CSI). Methods: we analyzed the EEG from 45 patients, equally assigned to three groups. All patients were induced with propofol and the groups differed by the maintenance anesthetic regimen, i.e., sevoflurane, isoflurane, or propofol. We evaluated the EEG and parameter dynamics during LOR and ROR. For the emergence period, we focused on possible differences in the EEG dynamics in the different groups. Results: depending on the substance, the EEG emergence patterns showed significant differences that led to a substance-specific early activation of higher frequencies as indicated by the “wake” CSI values that occurred minutes before ROR in the inhalational anesthetic groups. Conclusion: our results highlight substance-specific differences in the emergence from anesthesia that can influence the EEG-based monitoring that probably have to be considered in order to improve neuromonitoring during general anesthesia.
Disentangling the Association between ADHD and Alcohol Use Disorder in Individuals Suffering from Bipolar Disorder: A Systematic Review and Meta-Analysis
Authors: Bartoli Francesco , Callovini Tommaso , Calabrese Angela , Cioni Riccardo M. , Riboldi Ilaria , Crocamo Cristina , Carrà Giuseppe
Published: December 2021

Attention Deficit-Hyperactivity disorder (ADHD) may influence rates of Alcohol Use Disorder (AUD) among individuals suffering from Bipolar Disorder (BD). The aim of this systematic review and meta-analysis was to estimate the strength and consistency of the potential association between ADHD and AUD in BD. We searched main electronic databases for studies indexed up to November 2020. We included observational studies investigating the association between ADHD and AUD among individuals with BD. The association between ADHD and AUD was estimated using odds ratios (ORs) with 95% Confidence Intervals (CIs). Eleven studies, involving 2734 individuals with BD (516 with ADHD), were included in the meta-analysis. Individuals with both BD and ADHD had higher rates of AUD as compared with subjects with BD only (34.0% vs. 18.3%). The estimated OR of AUD for ADHD was 2.50 (95% CI: 1.91 to 3.27; I2 = 13.0%). Study-level characteristics did not influence the effect size. No risk of publication bias was estimated. Despite some limitations, this meta-analysis estimated an association between ADHD and AUD among individuals suffering from BD. At least a portion of the high rates of AUD in BD may, thereby, be related to comorbid ADHD. Longitudinal studies are needed to clarify the nature of this relationship.
Digital Innovation in Multiple Sclerosis Management
Authors: Ziemssen Tjalf , Haase Rocco
Published: December 2021

The development of digital applications and remote communication technologies for people with multiple sclerosis (pwMS) has increased rapidly in recent years [...]
Neurophysiological Characterization of Posteromedial Hypothalamus in Anaesthetized Patients
Authors: Pastor Jesús , Vega-Zelaya Lorena , Martín-Abad Elena
Published: December 2021

Deep brain stimulation (DBS) requires a precise localization, which is especially difficult at the hypothalamus, because it is usually performed in anesthetized patients. We aimed to characterize the neurophysiological properties posteromedial hypothalamus (PMH), identified by the best neurophysiological response to electrical stimulation. We obtained microelectrode recordings from four patients with intractable aggressivity operated under general anesthesia. We pooled data from 1.5 mm at PMH, 1.5 mm upper (uPMH) and 1.5 mm lower (lPMH). We analyzed 178 units, characterized by the mean action potential (mAP). Only 11% were negative. We identified the next types of units: P1N1 (30.9%), N1P1N2 (29.8%), P1P2N1 (16.3%), N1P1 and N1N2P1 (6.2%) and P1N1P2 (5.0%). Besides, atypical action potentials (amAP) were recorded in 11.8%. PMH was highly different in cell composition from uPMH and lPMH, exhibiting also a higher percentage of amAP. Different kinds of cells shared similar features for the three hypothalamic regions. Although features for discharge pattern did not show region specificity, the probability mass function of inter-spike interval were different for all the three regions. Comparison of the same kind of mAP with thalamic neurons previously published demonstrate that most of cells are different for derivatives, amplitude and/or duration of repolarization and depolarization phases and also for the first phase, demonstrating a highly specificity for both brain centers. Therefore, the different properties described for PMH can be used to positively refine targeting, even under general anesthesia. Besides, we describe by first time the presence of atypical extracellular action potentials.
A Study on Instructional Humor: How Much Humor Is Used in Presentations?
Authors: Shoda Vera Paola , Yamanaka Toshimasa
Published: December 2021

Humor is applied in pedagogy to create a positive learning environment. Recent research focuses on the theories, effects, individual differences, and qualitative aspects of humor for instruction. However, there is a lack of studies focusing on quantitative features. Therefore, this research explored the quantitative characteristics of instructional humor in a naturalistic setting and applied techniques from natural language processing (NLP). This paper describes the results of two studies. The first study focused on instructional humor frequency and the placement of humor, while the linguistic features of instructional humor and non-instructional humor were compared in the second study. Two corpora were used in this research: TED Talks and user-submitted jokes from “stupidstuff.org” The results found that educators used humor 12.92 times for popular talks, while less popular talks only had 3.92 times. Humor is also more commonly placed during the first parts of the talk and lessens toward the end. There were also significant differences between the linguistic features of instructional and non-instructional humor in terms of readability scores and sentiment. These results provide a substantial update on quantitative instructional humor research and help educators understand how to use humor in the classroom in terms of quantitative and linguistic features.
Cancer-Associated Stromal Cells Promote the Contribution of MMP2-Positive Bone Marrow-Derived Cells to Oral Squamous Cell Carcinoma Invasion
Authors: Oo May Wathone , Kawai Hotaka , Takabatake Kiyofumi , Shan Qiusheng , Eain Htoo Shwe , Sukegawa Shintaro , Nakano Keisuke , Nagatsuka Hitoshi
Published: December 2021

Tumor stromal components contribute to tumor development and invasion. However, the role of stromal cells in the contribution of bone marrow-derived cells (BMDCs) in oral squamous cell carcinoma (OSCC) invasion is unclear. In the present study, we created two different invasive OSCC patient-derived stroma xenografts (PDSXs) and analyzed and compared the effects of stromal cells on the relation of BMDCs and tumor invasion. We isolated stromal cells from two OSCC patients: less invasive verrucous OSCC (VSCC) and highly invasive conventional OSCC (SCC) and co-xenografted with the OSCC cell line (HSC-2) on green fluorescent protein (GFP)-positive bone marrow (BM) cells transplanted mice. We traced the GFP-positive BM cells by immunohistochemistry (IHC) and detected matrix metalloproteinase 2 (MMP2) expression on BM cells by double fluorescent IHC. The results indicated that the SCC-PDSX promotes MMP2-positive BMDCs recruitment to the invasive front line of the tumor. Furthermore, microarray analysis revealed that the expressions of interleukin 6; IL-6 mRNA and interleukin 1 beta; IL1B mRNA were higher in SCC stromal cells than in VSCC stromal cells. Thus, our study first reports that IL-6 and IL1B might be the potential stromal factors promoting the contribution of MMP2-positive BMDCs to OSCC invasion.
YK-4-279 Attenuates Progression of Pre-Existing Pigmented Lesions to Nodular Melanoma in a Mouse Model
Authors: Huang Lee , Zhai Yougang , Fajardo Cristian D. , Lang Deborah
Published: December 2021

More options are needed for the effective treatment of melanoma. In a previous study, we discovered the small molecule drug YK-4-279 almost completely inhibited tumor progression in the BrafCA;Tyr-CreERT2;Ptenflox/flox transgenic mouse model. YK-4-279 had no effect on tumor initiation but blocked progression of invasive melanoma. Our current study was designed as a treatment model, where YK-4-279 was administered during pigmented lesion formation. The study design included the use of three groups: (1) a control group that received only DMSO without a drug (MOCK), (2) mice following our prior studies with YK-4-279 administered at the time of tumor induction (YK-4-279), and (3) mice treated during tumor initiation (YK-4-279 delay). While the MOCK mice had progression of tumors, both YK-4-279 and YK-4-279 delay groups had a significant block or delay of progression. The majority of mice in the YK-4-279 groups had a block of progression, while the YK-4-279 delay group had either a partial block (60% in male mice or 29% in females) or a delay in disease progression in females (28 days in controls to 50 days in YK-4-279 delay group). Here, we demonstrate that YK-4-279 has a significant impact on blocking or delaying tumor progression in a pre-clinical treatment model of melanoma.
Assessment of Health-Related Quality of Life in Patients with Advanced Prostate Cancer—Current State and Future Perspectives
Authors: Kretschmer Alexander , van den Bergh Roderick C. N. , Martini Alberto , Marra Giancarlo , Valerio Massimo , Tsaur Igor , Heidegger Isabel , Kasivisvanathan Veeru , Kesch Claudia , Preisser Felix , Fankhauser Christian D. , Zattoni Fabio , Ceci Francesco , Olivier Jonathan , Chiu Peter , Puche-Sanz Ignacio , Thibault Constance , Gandaglia Giorgio , Tilki Derya ,   on behalf of the YAU Prostate Cancer Working Group
Published: December 2021

With the therapeutic landscape of advanced prostate cancer rapidly evolving and oncological benefits being shown for a plethora of new agents and indications, health-related quality of life (HRQOL)-associated evidence is still subpar. In the current comprehensive review, we discuss the importance of HRQOL for patients with advanced PC (metastatic hormone-sensitive prostate cancer (mHSPC), metastatic castration-resistant prostate cancer (mCRPC) and non-metastatic castration-resistant prostate cancer (nmCRPC)), and present the most frequently used tools to evaluate HRQOL in recent randomized trials. Furthermore, we discuss the ease of use of these validated questionnaires for clinicians and try to focus on the suggested appropriate use in clinical practice, as well as potential strategies for improvement of HRQOL evaluation in these clinical scenarios of advanced prostate cancer.
Early PSA Change after [177Lu]PSMA-617 Radioligand Therapy as a Predicator of Biochemical Response and Overall Survival
Authors: Kind Felix , Fassbender Thomas F. , Andrieux Geoffroy , Boerries Melanie , Meyer Philipp T. , Ruf Juri
Published: December 2021

Purpose: Radioligand therapy with [177Lu]PSMA-617 (PSMA-RLT) is a promising therapeutic option for metastatic castration-resistant prostate cancer (mCPRP). This study assessed the prognostic value of early PSA measurements during PSMA-RLT. Methods: 27 patients with mCRPC scheduled for PSMA-RLT were prospectively enrolled for a serial short-interval PSA-assessment. Change in PSA (∆%PSA) during two treatment cycles was correlated with biochemical response (BR) and change in tumor volume on PET (TV) after 16 weeks (w16), as well as overall survival (OS). PCWG3 criteria and the recently recommended threshold of ∆%PSA ≤ −30% were assessed for their predictive value. Results: ∆%PSA first correlated with BR, TV and OS after 4 weeks (c1w4). At c1w4, ∆%PSA ≤ −30% was associated with the biochemical response at w16 (p = 0.003) and a longer median OS (p = 0.025), whereas the PCWG3-derived threshold of ∆%PSA ≤ −50% showed no such correlation. In contrast, ∆%PSA ≥ 25% at c1w4 was associated with biochemical progression at w16 (p = 0.003) and a shorter median OS (p < 0.001). Conclusion: PSA changes as early as four weeks after PSMA-RLT allow a significant prediction of later biochemical and PET-based imaging response, as well as OS. At this early time point, a more lenient threshold for a PSA decrease of at least 30% appears better-suited for the prediction of a positive biochemical response and longer OS. In contrast, the PCWG3-derived threshold for PSA increase (+25%) reliably anticipates biochemical progression and shorter OS.
Novel ADCs and Strategies to Overcome Resistance to Anti-HER2 ADCs
Authors: Díaz-Rodríguez Elena , Gandullo-Sánchez Lucía , Ocaña Alberto , Pandiella Atanasio
Published: December 2021

During recent years, a number of new compounds against HER2 have reached clinics, improving the prognosis and quality of life of HER2-positive breast cancer patients. Nonetheless, resistance to standard-of-care drugs has motivated the development of novel agents, such as new antibody-drug conjugates (ADCs). The latter are a group of drugs that benefit from the potency of cytotoxic agents whose action is specifically guided to the tumor by the target-specific antibody. Two anti-HER2 ADCs have reached the clinic: trastuzumab-emtansine and, more recently, trastuzumab-deruxtecan. In addition, several other HER2-targeted ADCs are in preclinical or clinical development, some of them with promising signs of activity. In the present review, the structure, mechanism of action, and potential resistance to all these ADCs will be described. Specific attention will be given to discussing novel strategies to circumvent resistance to ADCs.
Immune-Mediated Effects of Microplanar Radiotherapy with a Small Animal Irradiator
Authors: Bazyar Soha , O’Brien Edward Timothy , Benefield Thad , Roberts Victoria R. , Kumar Rashmi J. , Gupta Gaorav P. , Zhou Otto , Lee Yueh Z.
Published: December 2021

Spatially fractionated radiotherapy has been shown to have effects on the immune system that differ from conventional radiotherapy (CRT). We compared several aspects of the immune response to CRT relative to a model of spatially fractionated radiotherapy (RT), termed microplanar radiotherapy (MRT). MRT delivers hundreds of grays of radiation in submillimeter beams (peak), separated by non-radiated volumes (valley). We have developed a preclinical method to apply MRT by a commercial small animal irradiator. Using a B16-F10 murine melanoma model, we first evaluated the in vitro and in vivo effect of MRT, which demonstrated significant treatment superiority relative to CRT. Interestingly, we observed insignificant treatment responses when MRT was applied to Rag−/− and CD8-depleted mice. An immuno-histological analysis showed that MRT recruited cytotoxic lymphocytes (CD8), while suppressing the number of regulatory T cells (Tregs). Using RT-qPCR, we observed that, compared to CRT, MRT, up to the dose that we applied, significantly increased and did not saturate CXCL9 expression, a cytokine that plays a crucial role in the attraction of activated T cells. Finally, MRT combined with anti-CTLA-4 ablated the tumor in half of the cases, and induced prolonged systemic antitumor immunity.
Synthesis of Mesoporous Cu-Ni/Al2O4 Catalyst for Hydrogen Production via Hydrothermal Reconstruction Route
Authors: Lin Kai-Jhei , Chih Yi-Kai , Chen Wei-Hsin , Huang Hsin-Kai , Lin Hong-Ping , Hsu Chun-Han
Published: December 2021

Mesoporous Cu-Ni/Al2O4 catalyst of high surface area (176 m2g−1) is synthesized through a simple hydrothermal reconstruction process by using low-cost activated alumina as the aluminate source without organic templates. The desired mesoporous structure of the catalyst is formed by the addition of Cu2+ and Ni2+ metal ions in the gel solution of the activated alumina followed by hydrothermal treatment at 70 °C and calcination at temperatures in the range of 600 to 800 °C. To consider the environmental concern, we found the concentration of the Cu2+ and Ni2+ ion in the residual filtrate is less than 0.1 ppm which satisfies the effluent standard in Taiwan (<1.0 ppm). The effects of the pH value, hydrothermal treatment time, and calcination temperature on the structure, morphology and surface area of the synthesized Cu-Ni/Al2O4 composites are investigated as well. In addition, the Cu-Ni/Al2O4 catalyst synthesized at pH 9.0 with a hydrothermal treatment time of 24 h and a calcination temperature of 600 °C is used for hydrogen production via the partial oxidation of methanol. The conversion efficiency is found to be >99% at a reaction temperature of around 315 °C, while the H2 yield is 1.99 mol H2/mol MeOH. The catalyst retains its original structure and surface area following the reaction process, and is thus inferred to have a good stability. Overall, the hydrothermal reconstruction route described herein is facile and easily extendable to the preparation of other mesoporous metal-alumina materials for catalyst applications.