bluuebunny/crossref_metadata_2025_split huggingface dataset:
The potential of Jellytoring 2.0 smart tool as a global jellyfish monitoring platform
Authors: Ruiz‐Frau Ana , Martin‐Abadal Miguel , Jennings Charlotte L. , Gonzalez‐Cid Yolanda , Hinz Hilmar 
Published: November 2022

AbstractDespite the recent recognition of jellyfish as an important component of marine ecosystems and existing concerns on their potential population increase, they are rarely monitored at the appropriate spatial and temporal scales. Traditional jellyfish monitoring techniques are costly and generally restrict the spatial–temporal resolution limiting the quantity and quality of monitoring data. We introduce Jellytoring 2.0, an automatic recognition tool for jellyfish species based on convolutional neural networks (CNN). We trained Jellytoring 2.0 to identify 15 jellyfish species with a global distribution. Our aim is to offer Jellytoring 2.0 as an open‐access tool to serve as the backbone for a system that promotes the creation of large‐scale and long‐term jellyfish monitoring data. Results reveal that Jellytoring 2.0 performed well in the identification of the 15 species with average precision values ranging between 90% and 99% for most of the species. Four of the species presented slightly lower values (75%–80%). Our system was trained on a relatively small dataset, implying that additional integration of image data will further improve the performance of the CNN. We show how the application of CNNs to image data can deliver a tool that will enable the cost‐effective collection of jellyfish data on larger spatial and temporal scales. For Jellytoring 2.0 to become a truly global automatic identification system, we ask scientists and nonscientists to actively contribute with jellyfish image data to extend the number of species it can identify.
Coordinated evaporative demand and precipitation maximize rainfed maize and soybean crop yields in the USA
Authors: Luan Xiangyu , Bommarco Riccardo , Vico Giulia 
Published: November 2022

AbstractTo understand how climate change affects crop yields, we need to identify the climatic indices that best predict yields. Grain yields are most often predicted using precipitation and temperature in statistical models, assuming linear dependences. However, soil water availability is more influential for plant growth than precipitation and temperature, and there is ecophysiological evidence of intermediate yield maximizing conditions. Using rainfed maize and soybean yields for 1970–2010 across the USA, we tested whether the aridity index, that is, the ratio of precipitation and potential evapotranspiration seasonal totals and a proxy of soil water availability, better predicts yield than growing season precipitation total, average temperature and their interaction. We also tested for non‐monotonic responses allowing for intermediate yield‐maximizing conditions. The aridity index alone explained 77% and 72% of maize and soybean yield variability, compared with 78% and 73% explained by temperature, precipitation and their interaction. Yield responses were non‐monotonic, with yields maximized at intermediate precipitation and temperature as well as at intermediate aridity index of 0.79 for maize and 0.98 for soybean. The yield maximizing precipitation also increased with growing season average temperature, faster in maize than soybean. The intermediate yield maximizing conditions show that rainfed maize and soybean yields could both increase and decrease depending on whether climatic conditions come closer to or deviate from the yield maximizing conditions in the future. In most counties, during 1970–2010, the precipitation and aridity index were lower and temperature higher compared with those maximizing yields, suggesting that climate change will reduce yields.
Toward quantitative metabarcoding
Authors: Shelton Andrew Olaf , Gold Zachary J. , Jensen Alexander J. , D′Agnese Erin , Andruszkiewicz Allan Elizabeth , Van Cise Amy , Gallego Ramón , Ramón‐Laca Ana , Garber‐Yonts Maya , Parsons Kim , Kelly Ryan P. 
Published: November 2022

AbstractAmplicon‐sequence data from environmental DNA (eDNA) and microbiome studies provide important information for ecology, conservation, management, and health. At present, amplicon‐sequencing studies—known also as metabarcoding studies, in which the primary data consist of targeted, amplified fragments of DNA sequenced from many taxa in a mixture—struggle to link genetic observations to the underlying biology in a quantitative way, but many applications require quantitative information about the taxa or systems under scrutiny. As metabarcoding studies proliferate in ecology, it becomes more important to develop ways to make them quantitative to ensure that their conclusions are adequately supported. Here we link previously disparate sets of techniques for making such data quantitative, showing that the underlying polymerase chain reaction mechanism explains the observed patterns of amplicon data in a general way. By modeling the process through which amplicon‐sequence data arise, rather than transforming the data post hoc, we show how to estimate the starting DNA proportions from a mixture of many taxa. We illustrate how to calibrate the model using mock communities and apply the approach to simulated data and a series of empirical examples. Our approach opens the door to improve the use of metabarcoding data in a wide range of applications in ecology, public health, and related fields.
Hybrid simulation method with restoring force correction for structural testing characterized by incomplete boundary conditions
Authors: Wang Shangzhang , Yang Ge , Wang Zhen , Wu Bin , Xiao Jiajun , Ning Xizhan 
Published: November 2022

AbstractHybrid simulation is a powerful testing method that combines numerical analysis and physical experiments through on‐line interaction. The substructuring technology enables hybrid simulation to evaluate the structural performance with large‐scale specimens. However, this technology also increases the complexity of specimen boundary conditions. Due to limited equipment resources of structural laboratories, not all the degrees of freedom of the boundary conditions can be realized during tests, which will induce error to the experimental restoring forces and decrease of accuracy of hybrid simulation. In this case, the hybrid simulation method based on restoring force correction was proposed to reduce this error. In this method, the error in experimental restoring forces were corrected using an auxiliary numerical model of the experimental substructure. The effectiveness of the proposed method was verified through both theoretical analysis and numerical examples. This method was then adopted to evaluate the seismic performance of a spatial reinforced concrete frame with buckling‐restrained braces numerically. Results showed that the proposed method can enhance the accuracy of tests compared to conventional hybrid simulation, and keep computational efficiency in the meanwhile.
Designing Modular Assembly of Electrochemical Flow Microreactor as an Enabling Technology of Electrosynthesis in Laminar Flow
Authors: Yata Ayano , Nakamura Yuto , Okamoto Kazuhiro , Shida Naoki , Atobe Mahito 
Published: November 2022

AbstractFlow microreactors are well‐suited for organic electrosynthesis because they provide a large surface area for reactions and enable precise control of the residence time. Here, we developed three novel electrochemical flow microreactors for organic electrosynthesis: undivided, divided, and electrophotochemical reactors. These flow reactors were easily assembled using modules made of solvent‐resistant plastics and feature high interchangeability of each component and the applicability of a reference electrode. We evaluated our reactors on the basis of the redox response of ferrocene and ferrocenemethanol. The results suggested that the reactors maintain laminar flow with both aqueous and nonaqueous electrolytes. We applied these reactors to paired electrosynthesis and electrophotocatalysis, demonstrating the utility of these systems for electrosynthesis in a laminar flow.
Footsteps I would like to follow? How gender quotas affect the acceptance of women leaders as role models and inspirations for leadership
Authors: Nater Christa , Heilman Madeline E. , Sczesny Sabine 
Published: November 2022

AbstractThis research examines how the method of selecting women leaders affects other women's leadership interest. The results of three experiments (N = 1,015) indicated that only when women leaders were selected due to merit, not quota‐based policies, did they boost female participants’ interest in a leadership position. These reactions were mediated by perceptions of the woman leader's deservingness of her position (Studies 1–3) and consequent acceptance as a role model (Studies 2 and 3). Accordingly, success information validating quota‐based selected leaders’ competence provided a boost in leadership interest equal to that of merit‐based selected leaders (Study 2). For male participants, quota but not merit‐based selected women leaders lowered interest in leadership due to their pessimistic assessment of the probability of being selected (Study 1). These results suggest that a wise implementation of quota regulations includes validating women's competence so they are perceived as deserving of their leader roles and can thus serve as inspiring role models.
Experimental investigations on the performance of solar cooker using nichrome heating coil—Photovoltaic with microcontroller PIC 16F877A
Authors: Simon Prabu Arulraj , Chithambaram Venkatesan , Muthucumaraswamy Rajamanickam , Shanmugan Sengottaiyan 
Published: November 2022

AbstractIn this article, a solar cooker with photovoltaic was developed and manufactured, which offers an electrical emergency power supply and a nichrome heating element in order to be able to cook even on cloudy days and nights. An effective charge controller is made with the microcontroller PIC 16F877A to charge and power the nichrome heating element wound on the cooking vessel. The charge controller prevented the battery from overcharging by effectively regulating the voltage and current from the solar panel. The current through the nichrome coil provides additional heating and the thermal energy that is absorbed by the cooker's absorber plate. Hence the hot water needs a minimum amount of auxiliary heat energy to reach the maximum temperature which is well supplied by the nichrome heating coil. Simulation study for the proposed cooker is recommended in the future to commercialize the cooker for a family of four members with minimum cost. The charge stored in the battery during the day is used to cook food at night and on cloudy days.
Long time series of absolute gravity observations in Kulusuk, southeast Greenland
Authors: Francis Olivier 
Published: November 2022

AbstractThis report contains terrestrial absolute gravity measurements performed near the village of Kulusuk in southeast Greenland. It represents an exceptionally long time series of nearly two decades. The measurements began in July 1996 until July 2015. The station is located a few meters beside a permanent GNSS station. The final gravity values (g‐values), more precisely the accelerations due to gravity, are listed along their associated uncertainties. A description of the station, a short explanation on the absolute gravimeter, and the data processing are presented.
Optimal channel and frequency band‐based feature selection for motor imagery electroencephalogram classification
Authors: Meng Ming , Dong Zhichao , Gao Yunyuan , She Qingshan 
Published: November 2022

AbstractCommon spatial pattern (CSP) is a widely adopted method for electroencephalogram (EEG) feature extraction in brain‐computer interface (BCI) based on motor imagery. Bandpass‐filtering EEG into several subbands related to brain activity tasks is an effective approach to improve the performance of CSP based algorithm. However, this approach tends to suffer the over‐fitting problem because of the increase in feature dimension. Therefore, we proposed an optimal channel and frequency band‐based CSP feature selection method in this paper. Firstly, the correlation coefficient was calculated to select the optimal channels, and these channels were bandpass‐filtered into multiple overlapping subbands. The subbands with higher power spectrum density were chosen for CSP feature extraction. Next, the pair‐wise relevance was utilized to remove subband features with less difference. And then the screened subband features were combined with features extracted from the broadband signal. The Fisher ratio was exploited to carry out further feature selection. Finally, a support vector machine (SVM) was trained to classify the selected CSP features. An experimental study was implemented on BCI competition III dataset IVa and BCI competition IV dataset 1. The average classification accuracy reached 89.33% and 84.08%, which indicated the rationality and effectiveness of the proposed method.
Field effect transistor‐based tactile sensors: From sensor configurations to advanced applications
Authors: Wang Jian , Xu Shuyan , Zhang Congcong , Yin Ailing , Sun Mingyuan , Yang Hongru , Hu Chenguo , Liu Hong 
Published: November 2022

AbstractThe past several decades have witnessed great progress in high‐performance field effect transistors (FET) as one of the most important electronic components. At the same time, due to their intrinsic advantages, such as multiparameter accessibility, excellent electric signal amplification function, and ease of large‐scale manufacturing, FET as tactile sensors for flexible wearable devices, artificial intelligence, Internet of Things, and other fields to perceive external stimuli has also attracted great attention and become a significant field of general concern. More importantly, FET has a unique three‐terminal structure, which enables its different components to detect external mechanics through different sensing mechanisms. On one hand, it provides an important platform to shed deep insights into the underlying mechanisms of the tactile sensors. On the other hand, these properties could in turn endow excellent components for the construction of tactile matrix sensor arrays with high quality. With special emphasis on the configuration of FETs, this review classified and summarized structure‐optimized FET tactile sensors with gate, dielectric layer, semiconductor layer, and source/drain electrodes as sensing active components, respectively. The working principles and the state‐of‐the‐art protocols in terms of high‐performance tactile sensors are detail discussed and highlighted, the innovative pixel distribution and integration analysis of the transistor sensor matrix array concerning flexible electronics are also introduced. We hope that the introduction of this review can provide some inspiration for future researchers to design and fabricate high‐performance FET‐based tactile sensor chips for flexible electronics and other fields.image
On the real‐time predictive content of financial condition indices for growth
Authors: Amburgey Aaron J. , McCracken Michael W. 
Published: November 2022

SummaryWe provide evidence on the real‐time predictive content of the National Financial Conditions Index (NFCI), for conditional quantiles of U.S. real GDP growth. Our work is distinct from the literature in two specific ways. First, we construct (unofficial) real‐time vintages of the NFCI. This allows us to conduct out‐of‐sample analysis without introducing the kind of look‐ahead biases that are naturally introduced when using a single current vintage. We then develop methods for conducting asymptotic inference on tests of equal tick loss between nested quantile regression models when the data are subject to revision. We conclude by evaluating the real‐time predictive content of NFCI vintages for quantiles of real GDP growth. While our results largely reinforce the literature, we find gains to using real‐time vintages leading up to recessions—precisely when policymakers need such a monitoring device.
Building an oxidation reactor in Taiwan: From volatile organic compounds to secondary organic aerosols
Authors: Lin Yen‐Hsiu , Wu Yen‐Ju , Lin Jim Jr‐Min 
Published: November 2022

AbstractLarge amounts of volatile organic compounds (VOCs) are emitted into the atmosphere from both human and natural sources. A significant portion of VOCs would be oxidized via their reactions with atmospheric oxidants like OH, NO3, ozone, etc. The products of the oxidation reactions are often of low volatility and may condense to form secondary organic aerosols (SOA). To study the effect of VOC oxidation in aerosol formation, we are building an oxidation flow reactor system, which consists of (1) a 22‐l aluminum chamber, (2) an ozone source with an ozone detector, (3) a UV‐C (254 nm) lamp, (4) a photoionization detector to measure the effective VOC concentration, (5) various flow/concentration controlling apparatuses, and (6) a scanning mobility particle sizer to monitor the generated particles. Under the conditions of high UV and ozone levels, the oxidation process can be speeded up by orders of magnitude in this reactor. We hope to use this reactor: (i) to learn the “potential” mass of SOA that can be formed from a given VOC source like a traffic or industry site; (ii) to trace back the SOA source by utilizing the shortened reaction times; (iii) to learn the trends from VOC to SOA.
Increased long non‐coding RNA NORAD reflects serious cardiovascular stenosis, aggravated inflammation status, and higher lipid level in coronary heart disease
Authors: Zhang Xiaoyun , Kan Xuetong , Shen Jingjing , Li Jian 
Published: November 2022

AbstractObjectiveLong non‐coding RNA activated by DNA damage (lnc‐NORAD) modulates inflammation, lipid level, and atherosclerosis in various cardiovascular diseases. This study intended to investigate the dysregulated expression of lnc‐NORAD, and its linkage with clinical characteristics, inflammatory cytokines, and accumulating major adverse cardiovascular events (MACE) in coronary heart disease (CHD) patients.MethodsTotally, 160 CHD patients, 30 disease controls (DCs), and 30 healthy controls (HCs) were included. The reverse transcription‐quantitative polymerase chain reaction was used to detect lnc‐NORAD expression in peripheral blood mononuclear cell samples from all participants. Enzyme‐linked immunosorbent assay was applied to detect proinflammatory cytokines and adhesion molecules in CHD patients. Then, MACE was recorded during a median follow‐up of 12 (range: 1.0–27.0) months.ResultsLnc‐NORAD was highest in CHD patients, followed by DCs, and lowest in HCs (p < 0.001). In CHD patients, lnc‐NORAD was positively linked with Gensini score (p = 0.001). Meanwhile, lnc‐NORAD was positively linked to C‐reactive protein (p = 0.023), tumor necrosis factor‐alpha (p = 0.016), interleukin (IL)‐6 (p = 0.003), IL‐8 (P = 0.018), and IL‐17A (p = 0.029). No relation of lnc‐NORAD with vascular cell adhesion molecule‐1 (p = 0.094) and intercellular adhesion molecule‐1 (p = 0.060) was found. Furthermore, lnc‐NORAD was positively related to total cholesterol (p = 0.014) and low‐density lipoprotein cholesterol (p = 0.004), whereas lnc‐NORAD was not linked to triglyceride (p = 0.103) and high‐density lipoprotein cholesterol (p = 0.533). However, lnc‐NORAD (high vs. low), and its higher quartiles were both not linked to accumulating MACE rate (p > 0.05).ConclusionIncreased lnc‐NORAD is linked with aggravated stenosis degree, inflammation status, and blood lipid in CHD patients. However, further validation is required.
Current status of cone‐beam computed tomography teaching in Brazilian undergraduate endodontic programs – A web‐based survey
Authors: Coelho Marcelo Santos , Rios Marcos de Azevêdo 
Published: November 2022

AbstractPurposesThis study aimed to assess the current status of cone‐beam computed tomography (CBCT) education in Brazilian undergraduate Endodontic programs.MethodsOne hundred program directors were emailed. The questionnaire asked whether the CBCT topic was included in the program, the availability of a CBCT machine, and, the total length of the dental program. For the group that does not teach, seven questions discussed the reasons for not teaching and whether another subject included this topic. For the programs that included CBCT, seven questions discussed the number of hours included, and the impression of the program directors with the quality of the teaching. The chi‐square test was used for the correlation between the availability of the CBCT machine and the length of the dental program with the inclusion of the topic.ResultsThirty‐five program directors replied to the questionnaire. Twenty‐six (74.3%) reported that the topic of CBCT is not included in their programs. There was no impact of the availability of a CBCT machine on the inclusion of the topic (p > 0.05). The increased length of the dental program decreased the inclusion of the topic (p < 0.05). Fifty percent of the directors replied that lack of time is the reason for not including the topic. Among the programs that include CBCT, the majority (55.6%) deliver 3–5 h of lectures. The practical activities range from 1 to 5 h or more. The majority (77.8%) of the directors are satisfied with the content delivered and 44.4% understand that the students are competent in the interpretation of CBCT images.ConclusionsThe majority of the Endodontic undergraduate programs in Brazil do not include CBCT in the program. The availability of a CBCT machine does not impact the inclusion of the topic, the increased duration of the dental program decreases the inclusion of the CBCT topic.
Prediction of serial perpetrator residence: Part II—Evaluation of prediction model accuracy
Authors: Spaulding Jamie S. , Morris Keith B. 
Published: November 2022

AbstractA novel approach for geographic profiling was developed which assesses and integrates available information and evidence relevant to the case for the development of a geographic profile (Part I). The approach is flexible when lesser information is available, in the form of a centrographic model for when solely the victim abandonment or murder sites are known and a perpetrator trek model for instances where both encounter and abandonment sites are available. Eleven case studies were used to evaluate these models including a comprehensive application of the evidence driven model to the Yorkshire Ripper investigation from the view of the 1980 advisory team. The calculation of weights for and inclusion of factors in the prediction of perpetrator residence appears to be a viable method for geographic profiling. This method demonstrated the lowest average search area across all cases when compared to both centrographic spatial distribution strategies and the probability distance strategies implemented in software. Implications for casework include a reduction of resource use per serial incident such as manpower, time, and software expenses.