bluuebunny/crossref_metadata_2025 huggingface dataset:
Single-Shot Common-Path Off-Axis Dual-Wavelength Digital Holographic Microscopy Based on Two-Dimensional Grating Diffraction
Authors: Wang Jieyu , Wang Xue , Dong Zhao , Wang Huaying , Zhu Qiaofen , Men Gaofu , Gao Yafei , Wang Wenjian
Published: February 2022

We present a single-shot dual-wavelength common-path off-axis digital holographic microscopic (CO-DHM) imaging method based on two-dimensional grating diffraction. This method improves the utilization rate of the interference field under the limited photosensitive size of the camera, and further expands the original camera’s field of view (FOV). In addition, the mode of orthogonal carrier frequencies close to the diagonal direction can optimize the utilization of the camera’s spatial bandwidth. Compared with the traditional dual-wavelength CO-DHM using one-dimensional grating or prism beam splitting, this method effectively avoids the aliasing of high-frequency components of the +1-order spectrum of different wavelengths in the frequency domain. We provide quantitative phase imaging experiments for the full FOV of USAF resolution chart, onion epidermal cells and standard polystyrene beads. The results prove that the system can enlarge the interferometric FOV by nearly 74.0% without changing the imaging parameters, such as magnification and resolution, and can achieve high-precision quantitative phase imaging with only a single hologram.
Linking the Pattern Structures to System Robustness Based on Dynamical Models and Statistical Method
Authors: Sun Gui-Quan , Pang Yizhi , Li Li , Liu Chen , Wu Yongping , Feng Guolin , Jin Zhen , Li Bai-Lian , Wang Zhen
Published: February 2022

Pattern structures are usually used to describe the spatial and temporal distribution characteristics of individuals. However, the corresponding relationship between the pattern structure and system robustness is not well understood. In this work, we use geostatistical method–semivariogram to study system robustness for different pattern structures based on three dynamical models in different fields. The results show that the structural ratio of different pattern structures including the mixed state of spot and stripe, cold spot, stripe only, and hot spot are more than 75%, which indicated those patterns all have strong spatial dependence and heterogeneity. It was revealed that the systems corresponding to the mixed state of spot and stripe or cold spot are more robust. This article proposed a method to characterize the robustness of the system corresponding to the pattern structure and also provided a feasible approach for the study of “how structures determine their functions.”
Serum From Preeclamptic Women Triggers Endoplasmic Reticulum Stress Pathway and Expression of Angiogenic Factors in Trophoblast Cells
Authors: Castro Karla R. , Prado Karen M. , Lorenzon Aline R. , Hoshida Mara S. , Alves Eliane A. , Francisco Rossana P. V. , Zugaib Marcelo , Marques Aldilane L. X. , Silva Elaine C. O. , Fonseca Eduardo J. S. , Borbely Alexandre U. , Veras Mariana M. , Bevilacqua Estela
Published: February 2022

Preeclampsia (PE) is a hypertensive disease of pregnancy-associated with placental cell death and endoplasmic reticulum (ER) stress. It is unknown whether systemic factors aggravate placental dysfunction. We investigated whether serum factors in pregnant women with PE activate ER stress and unfolded protein responses (UPRs) in placental explants and trophoblast cells lineage. We cultured placental explants from third-trimester term placentas from control non-preeclamptic (NPE) pregnant women with serum from women with PE or controls (NPE). In PE-treated explants, there was a significant increase in gene expression of GADD34, CHOP, and SDF2. At the protein level, GRP78, SDF2, p-eIF2α, and p-eIF2α/eIF2α ratio were also augmented in treated explants. Assays were also performed in HTR8/SV-neo trophoblast cell line to characterize the putative participation of trophoblast cells. In PE serum-treated protein levels of p-eIF2a and the ratio p-elF2 α/elF2α increased after 12 h of treatment, while the gene expression of GADD34, ATF4, and CHOP was greater than control. Increased expression of SDF2 was also detected after 24 h-cultured HTR8/SV-neo cells. PE serum increased sFLT1 gene expression and decreased PlGF gene expression in placental explants. Morphologically, PE serum increased the number of syncytial knots and reduced placental cell metabolism and viability. Analysis of the serum of pregnant women with PE through Raman spectroscopy showed changes in amino acids, carotenoids, lipids, and DNA/RNA, which may be associated with the induction of ER stress found in chorionic villi treated with this serum. In conclusion, this study provides evidence that the serum of pregnant women with PE may impact placental villi changing its morphology, viability, and secreted functional factors while triggers ER stress and an UPR. The differences between PE and control sera include molecules acting as inducing factors in these processes. In summary, the results obtained in our assays suggest that after the development of PE, the serum profile of pregnant women may be an additional factor that feeds a continuous imbalance of placental homeostasis. In addition, this study may expand the possibilities for understanding the pathogenesis of this disorder.
Twenty Years’ Development of Teacher Identity Research: A Bibliometric Analysis
Authors: Zhang Yunyun , Wang Ping
Published: February 2022

This study aims to demonstrate a detailed knowledge map of teacher identity researchviaa 20-year data set from the Web of Science (WoS) database. A bibliometric analysis was employed for analyzing the articles published between 2001 and 2021 to show the status of teacher identity research in the past 20 years, research topics on teacher identity, and future research directions. Using the keyword “teacher identity” and filtering data by selecting articles and early access in teaching and education, 848 articles were retrieved. Through production, content, and citation analysis with the help of a bibliometric tool, this study found that teacher identity remained a popular research theme in the academic field over the past 20 years, and its booming production involved many authors, institutions, and sources, and countries. Furthermore, teachers’ “beliefs,” “emotions,” “professional development,” and “context” impacting the construction and reconstruction of teacher identity were the popular topics in teacher identity research, and fundamental issues, including “identity,” “teacher identity,” “professional identity,” “development,” “teacher development,” “beliefs,” and “intersectionality” of teacher identity keep good topics in future research.
Case Report: Mechanisms in Misdiagnosis of Autism as Borderline Personality Disorder
Authors: Iversen Stine , Kildahl Arvid Nikolai
Published: February 2022

Autistic individuals without intellectual disabilities are sometimes not diagnosed until adolescence/adulthood. Due to increased risk of co-occurring mental health problems, these individuals may initially be referred to general, mental health services and not always be identified as autistic; some may be misdiagnosed with personality disorder (PD) prior to identification of autism. To explore possible mechanisms in misdiagnosis of autism, we report on the case of a young man with severe, non-suicidal self-injury (NSSI) and attention deficit disorder (ADD) who had been diagnosed with and treated for borderline PD prior to being diagnosed with autism. Following reassessment by mental health clinicians with experience of working with autistic individuals, the patient was diagnosed with autism, ADD, and depression—but not PD. Experiences from this case suggest that presence of co-occurring NSSI, depression, and ADD, as well as lack of comprehensive assessment and lack of autism knowledge in general mental health services, may contribute to risk that autism is misdiagnosed as PD. These findings highlight the need for autism expertise in general mental health services to facilitate appropriate diagnosis for autistic individuals who encounter these services, as well as the importance of undertaking comprehensive assessments.
Language Learning Motivation and Burnout Among English as a Foreign Language Undergraduates: The Moderating Role of Maladaptive Emotion Regulation Strategies
Authors: Yu Xiaoxiao , Wang Yabing , Liu Fangsong
Published: February 2022

In the context of English as a Foreign Language (EFL), burnout study dominantly revolves around teachers but learners’ academic burnout is largely underexplored. Academic burnout is a concerning issue worldwide that is particularly predicted by academic motivation. However, we know little about the association between motivation and burnout among EFL learners and whether maladaptive emotion regulation strategies (ERS) could moderate their association. To fill this research gap, we recruited 841 EFL undergraduates from two universities in China. Descriptive analysis showed that participants reported high levels of language learning burnout. Correlational and bootstrapped moderation analysis found that motivation and maladaptive ERS were significantly correlated with burnout in opposite directions and the correlation between motivation and burnout was significantly influenced by students’ use of two maladaptive ERS (avoiding and venting). The more frequently students chose to avoid and vent unpleasant feelings, the protective role of motivation on burnout was weaker. The implications of these findings are discussed.
The Association Between Patient-Centered Communication and Primary Care Quality in Urban China: Evidence From a Standardized Patient Study
Authors: Su Min , Zhou Zhongliang , Si Yafei , Fan Xiaojing
Published: February 2022

Background

Effective patient-physician communication has been considered a central clinical function and core value of health system. Currently, there are no studies directly evaluating the association between patient-centered communication (PCC) and primary care quality in urban China. This study aims to investigate the association between PCC and primary care quality.

Methods

The standardized patients were used to measure PCC and the quality of health care. We recruited 12 standardized patients from local communities presenting fixed cases (unstable angina and asthma), including 492 interactions between physicians and standardized patients across 63 CHCs in Xi'an, China. PCC was scored on three dismissions: (1) exploring disease and illness experience, (2) understanding the whole person, and (3) finding common ground. We measured the quality of the primary care by (1) accuracy of diagnosis, (2) consultation time, (3) appropriateness of treatment, (4) unnecessary exams; (5) unnecessary drugs, and (6) medical expenditure. Ordinary least-squares regression models with fixed effects were used for the continuous variables and logistic regression models with fixed effects were used for the categorical variables.

Results

The average score of PCC1, PCC2, and PCC3 was 12.24 ± 4.04 (out of 64), 0.79 ± 0.64 (out of 3), and 10.19 ± 3.60 (out of 17), respectively. The total score of PCC was 23.22 ± 6.24 (out of 84). We found 44.11% of the visits having a correct diagnosis, and 24.19% of the visits having correct treatment. The average number of unnecessary exams and drugs was 0.91 ± 1.05, and 0.45 ± 0.82, respectively. The average total cost was 35.00 ± 41.26 CNY. After controlling for the potential confounding factors and fixed effects, the PCC increased the correct diagnosis by 10 percentage points (P < 0.01), the correct treatment by 7 percentage points (P < 0.01), the consultation time by 0.17 min (P < 0.01), the number of unnecessary drugs by 0.03 items (P < 0.01), and the medical expenditure by 1.46 CNY (P < 0.01).

Conclusions

This study revealed pretty poor communication between primary care providers and patients. The PCC model has not been achieved, which could be one source of the intensified physician-patient relationship. Our findings showed the PCC model in the primary care settings has positive associations with the quality of the primary care. Interactions with a higher score of PCC were more likely to have a correct diagnosis and correct treatment, more consultation time, more unnecessary drugs, and higher medical expenditure. To improve PCC, the clinical capacity and communication skills of primary care providers need to be strengthened. Also, strategies on reforming the pay structure to better reflect the value of physicians and providing a stronger motivation for performance improvement are urgently needed.
Social Isolation and the Use of Technology in Caregiving Dyads Living With Dementia During COVID-19 Restrictions
Authors: Hoel Viktoria , Wolf-Ostermann Karin , Ambugo Eliva Atieno
Published: February 2022

Background

People with dementia (PwD) and their informal caregivers (caregiving dyads) face multiple impacts of the COVID-19 pandemic, including restricted social support services and social isolation. With limited opportunities for caregiving dyads to participate in social activities during the pandemic, the potential of social technology to support social participation and dyadic relationships should be explored. As a part of an ongoing feasibility trial, this study assesses how COVID-19 has impacted community-dwelling dyads in a dementia caregiving context. The dyads' use of social technology and their motivations to invite technology into social interactions are explored.

Methods

A pilot case study employing baseline interview data from three community-dwelling caregiving dyads. Each dyad consisted of a husband with a dementia diagnosis and his wife, who performed most caregiving tasks. Interviews were audio-recorded, transcribed verbatim, and subjected to inductive thematic analysis. Two researchers independently coded the data, and collated the codes and themes collaboratively.

Results

Two themes and seven subthemes were identified: (i) living with dementia during COVID-19 (subthemes: social and leisure activities, dyadic interactions, adjusting as caregiver); and (ii) the role of technology in a pandemic (subthemes: facilitating social activities, facilitating dementia care-related activities, barriers and facilitators to using social technology, the underlying motivation to invite technology into interactions). Dyads who were socially active pre-COVID-19, and who managed to make good use of technology to facilitate and maintain their social engagement during COVID-19, reported to have been less negatively impacted by COVID-related social restrictions.

Conclusion

The dyads differed in how COVID-19 restrictions impacted their lives and how they coped with dementia, revealing different motivations for wanting to invite technology into their social interactions. During and beyond this pandemic, social technology can be a valuable tool for promoting social participation in this population, especially when in-person social contact is restricted. Successful uptake of social technology is dependent on customizing it to the individual's needs and conditions. Therefore, efforts are needed to tackle barriers that exist for older adults in using such technology.
Analysis of the Weight Management Behavior of Chinese Pregnant Women: An Integration of the Protection Motivation Theory and the Information-Motivation-Behavioral Skills Model
Authors: Ge Jinjin , Zhao Shiqi , Peng Xueqing , Walker Anita Nyarkoa , Yang Ni , Zhou Hua , Wang Li , Zhang Chi , Zhou Meng , You Hua
Published: February 2022

Inappropriate gestational weight gain has become a public health concern that threatens maternal and child health. Pregnant women's ability to manage their weight during pregnancy directly impacts their weight gain. In this study, we integrated the protection motivation theory and the information-motivation-behavioral skills model to develop an integrative theoretical model suitable for pregnancy weight management and reveal significant explainable factors of weight management behaviors during pregnancy. Based on a cross-sectional survey of 550 pregnant women from Jiangsu province, we came up with our findings. The results showed that several factors influenced pregnancy weight management behavior. According to the research, information, self-efficacy, response costs, and behavioral skills were significantly associated with weight management behaviors during pregnancy, while behavioral skills were also significant mediators of information, self-efficacy, and behavior. Furthermore, the information related to pregnancy weight management had the biggest impact on weight management behavior during pregnancy. The results of the model fit were acceptable and the integrative model could explain 30.6% of the variance of weight management behavior during pregnancy, which implies that the integrative theoretical model can effectively explain and predict weight management behaviors during pregnancy. Our study provides practical implications for the integrative model in improving pregnancy weight management behavior and offers a theoretical base for the weight management of pregnant women.
Symptom Clustering Patterns and Population Characteristics of COVID-19 Based on Text Clustering Method
Authors: Cheng Xiuwei , Wan Hongli , Yuan Heng , Zhou Lijun , Xiao Chongkun , Mao Suling , Li Zhirui , Hu Fengmiao , Yang Chuan , Zhu Wenhui , Zhou Jiushun , Zhang Tao
Published: February 2022

Background

Descriptions of single clinical symptoms of coronavirus disease 2019 (COVID-19) have been widely reported. However, evidence of symptoms associations was still limited. We sought to explore the potential symptom clustering patterns and high-frequency symptom combinations of COVID-19 to enhance the understanding of people of this disease.

Methods

In this retrospective cohort study, a total of 1,067 COVID-19 cases were enrolled. Symptom clustering patterns were first explored by a text clustering method. Then, a multinomial logistic regression was applied to reveal the population characteristics of different symptom groups. In addition, time intervals between symptoms onset and the first visit were analyzed to consider the effect of time interval extension on the progression of symptoms.

Results

Based on text clustering, the symptoms were summarized into four groups. Group 1: no-obvious symptoms; Group 2: mainly fever and/or dry cough; Group 3: mainly upper respiratory tract infection symptoms; Group 4: mainly cardiopulmonary, systemic, and/or gastrointestinal symptoms. Apart from Group 1 with no obvious symptoms, the most frequent symptom combinations were fever only (64 cases, 47.8%), followed by dry cough only (42 cases, 31.3%) in Group 2; expectoration only (21 cases, 19.8%), followed by expectoration complicated with fever (10 cases, 9.4%) in Group 3; fatigue complicated with fever (12 cases, 4.2%), followed by headache complicated with fever was also high (11 cases, 3.8%) in Group 4. People aged 45–64 years were more likely to have symptoms of Group 4 than those aged 65 years or older (odds ratio [OR] = 2.66, 95% CI: 1.21–5.85) and at the same time had longer time intervals.

Conclusions

Symptoms of COVID-19 could be divided into four clustering groups with different symptom combinations. The Group 4 symptoms (i.e., mainly cardiopulmonary, systemic, and/or gastrointestinal symptoms) happened more frequently in COVID-19 than in influenza. This distinction could help deepen the understanding of this disease. The middle-aged people have a longer time interval for medical visit and was a group that deserve more attention, from the perspective of medical delays.
How to Improve the Cognitive Health of Middle-Aged and Elderly People: Evidence From China Family Panel Studies
Authors: Yuan Wei , Jiang Min , Gong Shuying
Published: February 2022

In the context of the rapid development of the internet and the increasing severity of the aging problem, and in order to promote aged health and help construct a healthy society. We use micro survey data from the 2016 China Family Panel Studies (CFPS) to investigate the impact of the internet on the cognitive health of middle-aged and elderly people (those aged 40 and above). The robust results suggest that the internet plays a significant positive role in the cognitive health of middle-aged and elderly people in terms of internet use and internet involvement. This effect does not change significantly with differences in gender, household registration, location, or household composition, but there are heterogeneity effects due to differences in education. Further analysis indicates that the satisfaction of emotional attachment with children is the internal mechanism of the internet's influence on the cognitive health of people in this age group. Our paper both help scholars and the public to better understand the impact of the internet on the cognitive health of middle-aged and elderly people and clarifies different methods of defining the internet.
Perceptions and Expectations of School-Based Professionals Surrounding School-Based Mindfulness Training in Appalachia During the COVID-19 Pandemic: A Qualitative Study
Authors: Haliwa Ilana , Layman Hannah , Coffman Jessica , Snodgrass Amy , Santer Pamela , Barlett Brittney , Long Kate , Mason Ashley , Pfost Gretchen , Harden Jenny , Dino Geri , Jarrett Traci
Published: February 2022

Background

School-based professionals often report high burnout, particularly in geographic areas like Appalachia, where school-aged children are exposed to high levels of adverse childhood experiences, which may be exacerbated by the COVID-19 pandemic. While school-based mindfulness trainings can reduce burnout, their efficacy is influenced by the expectations of intervention personnel ahead of implementation. The present study assessed expectations and perceptions of a school-based mindfulness training among school personnel in 21 Appalachian schools during the COVID-19 pandemic.

Methods

Upon enrollment in the training, staff (N= 191) responded to open ended survey questions regarding perceived impacts of COVID-19 on students, expected benefits and barriers to school-based mindfulness, and perceived community acceptance of mindfulness.

Results

School personnel identified social isolation and lack of structure as negative impacts of COVID-19 on students. Expected benefits of classroom mindfulness included improved coping skills, focus, and emotion regulation, whereas barriers included lack of time and student ability level (e.g., age, attention). While most respondents indicated that their community was accepting of mindfulness practices, some noted resistance to and misperceptions of mindfulness, which may illustrate the influence of local cultural norms and values on the acceptability of mental health interventions.

Conclusions

Overall, these findings suggest positive expectations and relative perceived support for mindfulness practices within these Appalachian communities, including in response to negative impacts of the COVID-19 pandemic on students. Adapting practices and language to accommodate barriers such as time, student ability, and cultural misconceptions of mindfulness may increase the feasibility and efficacy of these interventions.
Stock Price Forecasting by a Deep Convolutional Generative Adversarial Network
Authors: Staffini Alessio
Published: February 2022

Stock market prices are known to be very volatile and noisy, and their accurate forecasting is a challenging problem. Traditionally, both linear and non-linear methods (such as ARIMA and LSTM) have been proposed and successfully applied to stock market prediction, but there is room to develop models that further reduce the forecast error. In this paper, we introduce a Deep Convolutional Generative Adversarial Network (DCGAN) architecture to deal with the problem of forecasting the closing price of stocks. To test the empirical performance of our proposed model we use the FTSE MIB (Financial Times Stock Exchange Milano Indice di Borsa), the benchmark stock market index for the Italian national stock exchange. By conducting both single-step and multi-step forecasting, we observe that our proposed model performs better than standard widely used tools, suggesting that Deep Learning (and in particular GANs) is a promising field for financial time series forecasting.
The Past, the Present, and the Future: A Bibliometric Analysis of Failed/Fragile/Collapsed State Research During 1990–2020
Authors: Wong Chi Swian
Published: February 2022

The “failed/fragile/collapsed state” refers to state authority's complete or partial collapse, such as Somalia and Bosnia. According to Fragile States Index 2020 annual report, approximately 116 countries among 178 countries were in warning or alerting state quo, which hurts three-quarters of the world's population. A systematic scientometric interpretation of failed/fragile/collapsed state analysis would be helpful but is presently absent in the academic community. This review makes three donations by evaluating the 2,417 articles published in the Web of Science (WoS) Social Science Citation Index (SSCI) Collection between 1990 and 2020. First, it provides a unique prospect in failed/fragile/collapsed state studies through a detailed, systematic, and objective analysis. Second, the author has quantitatively tracked the progression of failed/fragile/collapsed state studies from 1990 to 2020. Finally, the author associated evolutionary trajectory analysis with future research directions, offering new pathways for failed/fragile/collapsed state studies. It also helps novice “failed/fragile/collapsed state” researchers and veteran scholars identify future research trends.
Validation of Sentinel-2 (MSI) and Sentinel-3 (OLCI) Water Quality Products in Turbid Estuaries Using Fixed Monitoring Stations
Authors: Salama Mhd. Suhyb , Spaias Lazaros , Poser Kathrin , Peters Steef , Laanen Marnix
Published: February 2022

It is common in estuarine waters to place fixed monitoring stations, with the advantages of easy maintenance and continuous measurements. These two features make fixed monitoring stations indispensable for understanding the optical complexity of estuarine waters and enable an improved quantification of uncertainties in satellite-derived water quality variables. However, comparing the point-scale measurements of stationary monitoring systems to time-snapshots of satellite pixels suffers from additional uncertainties related to temporal/spatial discrepancies. This research presents a method for validating satellite-derived water quality variables with the continuous measurements of a fixed monitoring station in the Ems Dollard estuary on the Dutch-German borders. The method has two steps; first, similar in-situ measurements are grouped. Second, satellite observations are upscaled to match these point measurements in time and spatial scales. The upscaling approach was based on harmonizing the probability distribution functions of satellite observations and in-situ measurements using the first and second moments. The fixed station provided a continuous record of data on suspended particulate matter (SPM) and chlorophyll-a (Chl-a) concentrations at 1 min intervals for 1 year (2016–2017). Satellite observations were provided by Sentinel-2 (MultiSpectral Instrument, S2-MSI) and Sentinel-3 (Ocean and Land Color Instrument, S3-OLCI) sensors for the same location and time of in-situ measurements. Compared to traditional validation procedures, the proposed method has improved the overall fit and produced valuable information on the ranges of goodness-of-fit measures (slope, intercept, correlation coefficient, and normalized root-mean-square deviation). The correlation coefficient between measured and derived SPM concentrations has improved from 0.16 to 0.52 for S2-MSI and 0.14 to 0.84 for S3-OLCI. For the Chl-a matchup, the improvement was from 0.26 to 0.82 and from 0.14 to 0.63 for S2-MSI and S3-OLCI, respectively. The uncertainty in the derived SPM and Chl-a concentrations was reduced by 30 and 23% for S2-SMI and by 28 and 16% for S3-OLCI. The high correlation and reduced uncertainty signify that the matchup pairs are observing the same fluctuations in the measured variable. These new goodness-of-fit measures correspond to the results of the performed sensitivity analysis, previous literature, and reflect the inherent accuracy of the applied derivation model.
Outcomes of Salvage Lymph Node Dissection in Oligorecurrent Prostate Cancer Post Radical Prostatectomy: Experience of an Oncologic Center in Spain
Authors: Valiquette Anne S. , Vidal Crespo Natalia , Wong Augusto , Mascarós Juan M. , Gómez-Ferrer Álvaro , Collado-Serra Argimiro , Marenco Jose L. , Casanova Ramón-Borja Juan , Rubio-Briones José , Ramirez-Backhaus Miguel
Published: February 2022

Introduction and Objectives

We report our experience with salvage lymph node dissection (sLND) in oligorecurrent prostate cancer (PCa) post radical prostatectomy (RP).

Material and Methods

We retrospectively analyzed data of 24 patients who underwent sLND for biochemical recurrence (BCR) post RP, from July 2012 to February 2018. sLND was performed following an extended bilateral template. Clinical and pathological characteristics of primary RP and sLND were reported. Biochemical response and initiation of additional therapy post sLND were analyzed. Survival analysis was performed using KaplanMeier curves.

Results

24 sLND were performed. RP specimens showed 58.3% of Gleason score 7 and 50% of locally advanced disease. Median time to BCR post RP was 24 months with a median PSA value of 1.4 ng/ml pre sLND. 75% of patients underwent imaging prior to sLND. sLND showed oligometastasis on the final pathology report in 54.2% of patients. Metastatic lymph nodes were mainly identified in the iliac artery territory (61.5%). Complete biochemical response (PSA < 0.2 ng/ml) was maintained throughout the first 12 months of follow-up in 20.83% of patients and 8.33% of patients at the end of the study (median follow-up 70 months). Survival rates free of additional therapy (ADT/RT) were 45.83% at one year and 25% at 5 years.

Conclusions

We observed a biochemical response post sLND in 20.83% of our patients, lasting throughout the first year of follow up, with survival rates free of ADT and/or RT of 45.83% at one year and 25% at 5 years.
Large-Scale Crop Production for the Moon and Mars: Current Gaps and Future Perspectives
Authors: Poulet Lucie , Engeling Kenneth , Hatch Tyler , Stahl-Rommel Sarah , Velez Justiniano Yo-Ann , Castro-Wallace Sarah , Bunchek Jess , Monje Oscar , Hummerick Mary , Khodadad Christina L. M. , Spencer LaShelle E. , Pechous Josie , Johnson Christina M. , Fritsche Ralph , Massa Gioia D. , Romeyn Matthew W. , O’Rourke Aubrie E. , Wheeler Raymond W.
Published: February 2022

In this perspectives paper, we identify major challenges for space crop production: altered convection in the microgravity environment, scheduling and logistics, crew time and the need for advanced automation, robotics, modeling, and machine learning. We provide an overview of the existing space crop production gaps identified by the Kennedy Space Center (KSC) space crop production team and discuss efforts in current development in NASA projects to address these gaps. We note that this list may not be exhaustive but aims to present the baseline needs for space crop production implementation and a subset of current solutions to the greater scientific community in order to foster further ingenuity.
Pharmacokinetics and Tissue Distribution of Enrofloxacin Following Single Oral Administration in Yellow River Carp (Cyprinus carpio haematoperus)
Authors: Yang Fan , Zhang Chao-Shuo , Duan Ming-Hui , Wang Han , Song Zhe-Wen , Shao Hao-Tian , Ma Kai-Li , Yang Fang
Published: February 2022

The pharmacokinetics and tissue distribution of enrofloxacin were determined in Yellow River carp (Cyprinus carpio haematopterus) reared at 20°C after single oral administration of enrofloxacin at 10 mg·kg−1body weight (BW). Plasma, bile, and different tissue samples, including liver, kidney, gill, gut, and skin-muscle, were collected at predetermined times points. An HPLC method was developed to simultaneously determine the concentrations of enrofloxacin and its metabolite, ciprofloxacin. However, ciprofloxacin was only detectable in some liver samples with trace levels. Then the average enrofloxacin concentrations vs. time data were subjected to a non-compartmental analysis using WinNonLin 5.2 software. Multiple peaking profiles were observed in all enrofloxacin concentration-time curves. The peak concentration (Cmax) values were observed as 0.79, 1.01, 2.09, 2.85, 4.34, 10.78, and 13.07 μg·ml−1(or g−1) in plasma, skin-muscle, gill, kidney, liver, bile, and gut, respectively, and the corresponding time to reach peak concentration (Tmax) was 8, 8, 1, 8, 1, 72, and 4 h, respectively. The values of elimination half-life (T1/2λZ) of enrofloxacin in different tissues was in the following order: gill (291.13 h) > liver (222.29 h) > kidney (157.22 h) > plasma (129.44 h) > gut (91.47 h) > skin-muscle (87.77 h) > bile (86.22 h). The present results showed that enrofloxacin had a wide distribution in different tissues, however slow absorption and elimination in Yellow River carp. Additionally, enrofloxacin exhibited large distribution in bile, indicating that bile excretion might be the primary elimination route of enrofloxacin in Yellow River carp. A withdrawal period was calculated as 379.2 °C-day for single oral dosing of enrofloxacin at 10 mg/kg BW. Based on the calculated PK/PD indices of AUC/MIC or Cmax/MIC, the current enrofloxacin dosing regimen might have a positive therapeutic effect on the infection ofFlavobacterium columnare, Aeromonas sobria, orAeromonas hydrophila. However, the depletion study following multiple oral doses should be carried out in Yellow River carp reared at lower temperatures, and the withdrawal period should also be further calculated.
Validation of Medicinal Leeches (Hirudo medicinalis) as a Non-invasive Blood Sampling Tool for Hematology and Biochemistry Profiling in Mammals
Authors: Kvapil Pavel , Tomášek Oldřich , Bártová Eva , Harej Mojca , Kastelic Marjan , Primožič Tit , Kašpárková Nikola , Račnik Jožko
Published: February 2022

Blood sampling is a challenging procedure in many captive animals. Although manual restraint or anesthesia are usually possible, they entail intense stress and a high risk of injuries or organ failure. Blood sampling using medicinal leeches (Hirudo medicinalis) represents a promising non-invasive alternative to venipuncture; however, leech blood meal was to date used only for qualitative analyses such as genetic or serological screenings. Hence, the aim of this study was to evaluate the suitability of the leech blood sampling method for quantification of hematological and biochemical parameters. Medicinal leeches were manually applied on 67 zoo animals of eleven species, and control blood samples were obtained by venipuncture of the jugular vein. The leeches drew up to 20 ml of blood in 20 to 55 min. Although most hematological and biochemical parameters were significantly altered in leech-derived samples, their values showed strong (r = 0.62–0.79; 10/24 parameters) to very strong (r > 0.8; 13/24 parameters) correlations with venipuncture in all blood parameters, except for sodium (r = 0.39). As the parameter alterations and correlations were similar among species, simple cross-species regression formulas were sufficient to correct the alterations, thereby ensuring good repeatability between leeches and venipuncture in most parameters. Our data thus suggest that medicinal leeches can be used as a reliable non-invasive and stress-reducing alternative to standard venipuncture, even for quantitative assays. This opens new opportunities for a significant improvement to animal welfare in zoological gardens, conservation programmes, and ecophysiological research, where quantification of blood parameters is often needed.
Multidisciplinary Optimization of Thermal Insulation Layer for Stratospheric Airship with a Solar Array
Authors: Liu Yang , Xu Ziyuan , Du Huafei , Lv Mingyun
Published: February 2022

Stratospheric airships with a solar array have demonstrated overwhelming superiority in many aspects, such as earth observation, meteorological survey, and communication relay. The solar array supplies sufficient power for the airship to be in flight for months, but excessive heat is also transferred to the airship, causing high overpressure of inner gas. However, the optimal arrangement of the insulation layer on the airship has not been investigated. The theoretical method, including the geometry, thermal, and energy models, is developed and validated. The distribution of the temperatures and power of the solar cells, with different installation angles on the curved surface, is investigated. The thickness of insulation layer has a significant effect on the solar output power and internal pressure of the airship. An optimized configuration of the insulation structure is proposed, in order to improve the total output energy of solar array. The optimized configuration of insulations helps to reduce the structural mass by 24.9% and increase the payload mass by 9%. Moreover, the optimized arrangement improves the output energy of solar array in a year, and the maximum improvement is 8.2% on the winter solstice. The work displays the optimization of the thermal insulation layer for the stratospheric airship with a solar array, in order to improve the everyday energy acquirement during flight in a year.
Ecological and Environmental Benefits of Planting Green Manure in Paddy Fields
Authors: Lei Beining , Wang Juan , Yao Huaiying
Published: February 2022

Soil fertility management is one of the most important factors affecting crop production. The use of organic manures, including green manure, is an important strategy to maintain and/or improve soil fertility for sustainable crop production. Green manure generally refers to crops that can provide fertilizer sources for agricultural cash crops and improve soil productivity. The application of green manure is a traditional and valuable practice for agroecosystem management, particularly in paddy systems where green manure is rotated with rice. This paper systematically reviews the effects of green manure on soil microenvironments and greenhouse gas emissions, and the role of green manure in the phytoremediation of paddy fields. The paper concludes that green manure can not only affect soil nutrients and the microbial community, but also reduce greenhouse gas emissions and enhance soil remediation to some extent. Moreover, this review provides theoretical guidance on the selection of green manure germplasm and tillage methods for paddy fields of different climates and textures. However, this review only provides a macro-overview of the effects of green manure on soil nutrients, greenhouse gas emissions, and soil remediation in rice paddies based on a large number of previous studies, and does not provide a comprehensive quantitative assessment due to differences in green manure varieties and soil texture. The prospects for quantitative analysis of the ecological and economic effects of the sustainable development of green manure cultivation are discussed.
YOLO-Banana: A Lightweight Neural Network for Rapid Detection of Banana Bunches and Stalks in the Natural Environment
Authors: Fu Lanhui , Yang Zhou , Wu Fengyun , Zou Xiangjun , Lin Jiaquan , Cao Yongjun , Duan Jieli
Published: February 2022

The real-time detection of banana bunches and stalks in banana orchards is a key technology in the application of agricultural robots. The complex conditions of the orchard make accurate detection a difficult task, and the light weight of the deep learning network is an application trend. This study proposes and compares two improved YOLOv4 neural network detection models in a banana orchard. One is the YOLO-Banana detection model, which analyzes banana characteristics and network structure to prune the less important network layers; the other is the YOLO-Banana-l4 detection model, which, by adding a YOLO head layer to the pruned network structure, explores the impact of a four-scale prediction structure on the pruning network. The results show that YOLO-Banana and YOLO-Banana-l4 could reduce the network weight and shorten the detection time compared with YOLOv4. Furthermore, YOLO-Banana detection model has the best performance, with good detection accuracy for banana bunches and stalks in the natural environment. The average precision (AP) values of the YOLO-Banana detection model on banana bunches and stalks are 98.4% and 85.98%, and the mean average precision (mAP) of the detection model is 92.19%. The model weight is reduced from 244 to 137 MB, and the detection time is shortened from 44.96 to 35.33 ms. In short, the network is lightweight and has good real-time performance and application prospects in intelligent management and automatic harvesting in the banana orchard.
Antibiotic Resistance Awareness among Undergraduate Students in Quito, Ecuador
Authors: Ortega-Paredes David , Larrea-Álvarez César Marcelo , Torres-Elizalde Lilibeth , de Janon Sofia , Vinueza-Burgos Christian , Hidalgo-Arellano Luis , Šefcová Miroslava Anna , Molina-Cuasapaz Gabriel , Fernandez-Moreira Esteban , Larrea-Álvarez Marco
Published: February 2022

The inappropriate use of antibiotics leads to antibiotic resistance, which reduces their efficacy. The education of undergraduates is likely to influence their practices. Assessing awareness is critical in the general effort to confront the spread of antibiotic resistance. This cross-sectional investigation was carried out using the questionnaire “Antibiotic resistance: Multi-country public awareness” developed by the World Health Organization. Students from different backgrounds at the Central University participated in the study (n = 733). The survey comprised five sections: demographics, knowledge, usage, sources of information, and attitudes. The rate of correct answers was 64.88%; differences were detected between programs of study (p < 0.001); effect size analysis showed that these differences cannot be considered large. Individuals from applied sciences scored higher than their counterparts from social studies. Mostly, interviewees were knowledgeable about usage, but mistakenly associated antibiotics with conditions such as cold/flu or viral illnesses; also, they associated antibiotic resistance with the patient and not with bacteria. Despite these misconceptions, positive attitudes were registered overall, and students generally adhered to common practices. They cited doctors/nurses and teachers as sources of information. As a consequence, it is recommended to develop courses that address deficient knowledge regarding antibiotic resistance, especially for individuals affiliated to social disciplines.
Variability of Phenolic Compound Accumulation and Antioxidant Activity in Wild Plants of Some Rumex Species (Polygonaceae)
Authors: Feduraev Pavel , Skrypnik Liubov , Nebreeva Sofia , Dzhobadze Georgii , Vatagina Anna , Kalinina Evgeniia , Pungin Artem , Maslennikov Pavel , Riabova Anastasiia , Krol Olesya , Chupakhina Galina
Published: February 2022

Today, more than ever, the search for non-trivial sources of biologically active substances is critical. Plants of the genus Rumex are noteworthy. Plants of this genus stand out for a number of advantages from the dominant plant core of meadow phytocenoses of the temperate climatic zone: a short growing season, an intensive increase in biomass, and undemanding growth conditions. In addition, this plant genus is known as a super-producer of secondary phenolic compounds. The wide distribution and intensive synthesis of biologically active substances make plants from the genus Rumex a promising object for study. Seven species of the genus Rumex (R. acetosa, R. acetosella, R. confertus, R. crispus, R. maritimus, R.obtusifolius, and R. sanguineus) were analyzed. Plants were collected under relatively uniform growing conditions. For subsequent extraction and analysis of phenolic compounds, as well as antioxidant activity, plants leaves were used. R. acetosella, R. crispus, R. maritimus, R. obtusifolius, and R. sanguineus were characterized by a high total content of phenolic compounds (111–131 mg g–1). The maximum content of flavonoids was found in the leaves of R. maritimus and R. acetosella. At the same time, according to high-performance liquid chromatography with diode-array detection (HPLC-DAD) analysis, derivatives of flavones (apigenin and luteolin) predominated in the leaves of R. acetosella, while in other species, mainly derivatives of flavonols (quercetin and kaempferol) were identified. Plants of R. acetosa, in comparison with other studied species, were characterized by a lower content of the studied groups of phenolic compounds, with the exception of hydroxycinnamic acids, the content of which in this species was comparable to the content of flavonoids. The maximum content of catechins was found in R. sanguineus; proanthocyanidins—in R. sanguineus, R. obtusifolius, and R. crispus; and tannins—in R. obtusifolius. Extracts from R. crispus were characterized by high antioxidant activity, measured by 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS), and ferric reducing antioxidant power (FRAP) assays. In addition, the assessment of the phenolic profile of the plant made it possible to group the plants within the framework of cluster analysis. The distribution pattern in the clusters corresponded to the generally accepted taxonomy, with a characteristic division into subgenera (Acetosa, Acetosella, and Rumex). Thus, the phenolic profile can be considered as an additional instrumental approach when drawing up a systematic hierarchy.
Fine-Tuning BERT Models for Intent Recognition Using a Frequency Cut-Off Strategy for Domain-Specific Vocabulary Extension
Authors: Fernández-Martínez Fernando , Luna-Jiménez Cristina , Kleinlein Ricardo , Griol David , Callejas Zoraida , Montero Juan Manuel
Published: February 2022

Intent recognition is a key component of any task-oriented conversational system. The intent recognizer can be used first to classify the user’s utterance into one of several predefined classes (intents) that help to understand the user’s current goal. Then, the most adequate response can be provided accordingly. Intent recognizers also often appear as a form of joint models for performing the natural language understanding and dialog management tasks together as a single process, thus simplifying the set of problems that a conversational system must solve. This happens to be especially true for frequently asked question (FAQ) conversational systems. In this work, we first present an exploratory analysis in which different deep learning (DL) models for intent detection and classification were evaluated. In particular, we experimentally compare and analyze conventional recurrent neural networks (RNN) and state-of-the-art transformer models. Our experiments confirmed that best performance is achieved by using transformers. Specifically, best performance was achieved by fine-tuning the so-called BETO model (a Spanish pretrained bidirectional encoder representations from transformers (BERT) model from the Universidad de Chile) in our intent detection task. Then, as the main contribution of the paper, we analyze the effect of inserting unseen domain words to extend the vocabulary of the model as part of the fine-tuning or domain-adaptation process. Particularly, a very simple word frequency cut-off strategy is experimentally shown to be a suitable method for driving the vocabulary learning decisions over unseen words. The results of our analysis show that the proposed method helps to effectively extend the original vocabulary of the pretrained models. We validated our approach with a selection of the corpus acquired with the Hispabot-Covid19 system obtaining satisfactory results.