bluuebunny/crossref_metadata_2025 huggingface dataset:
Circadian Effects on Attention and Working Memory in College Students With Attention Deficit and Hyperactivity Symptoms
Authors: Gabay Lily , Miller Pazia , Alia-Klein Nelly , Lewin Monica P.
Published: May 2022

Objective

Individuals with an evening chronotype prefer to sleep later at night, wake up later in the day and perform best later in the day as compared to individuals with morning chronotype. Thus, college students without ADHD symptoms with evening chronotypes show reduced cognitive performance in the morning relative to nighttime (i.e., desynchrony effect). In combination with symptoms presented in attention deficit hyperactivity disorder (ADHD), we predicted that having evening chronotype renders impairment in attention during the morning, when students require optimal performance, amplifying desynchrony.

Method

Four hundred college students were surveyed for evening chronotype and symptoms of ADHD. Of those surveyed, 43 students with evening chronotype (19 with ADHD symptoms) performed laboratory attention tasks and were queried about fatigue during morning and evening sessions.

Results

Students with ADHD symptoms demonstrated a greater decrement in sustained attentional vigilance when abstaining from stimulants and asked to perform cognitive tests at times misaligned with natural circadian rhythms in arousal compared to their non-ADHD counterparts with the same chronotype. While individuals with ADHD symptoms had slower reaction-times during sustained attention tasks in the morning session compared to those without symptoms, there was no significant group difference in working memory performance, even though both groups made more errors in the morning session compared to the evening session.

Conclusion

These findings suggest that evening chronotype students with ADHD symptoms are at a greater disadvantage when having to perform sustained attention tasks at times that are not aligned to their circadian rhythm compared to their neuro-typical peers. The implications of this finding may be useful for the provision of disability accommodations to college age students with ADHD when they are expected to perform tasks requiring sustained attention at times misaligned with their circadian rhythms.
Effects of Ambidextrous Leadership on Employees’ Work Behavior: The Mediating Role of Psychological Empowerment
Authors: Wang Li , Sun Yuchen , Li Jinzhi , Xu Yunxia , Chen Meifen , Zhu Xiaoyu , Wang Dawei
Published: May 2022

The complexity of today’s organizational environment increasingly requires leaders to think in a dynamic and flexible way to resolve contradictory issues. This study explored and compared the effects of servant leadership and authoritarian leadership on employees’ work behavior from the perspectives of ambidextrous leadership theory and social exchange theory, and further examined the mediating role of psychological empowerment. In this study, 315 employees from state-owned communication companies in Shandong and Zhejiang Provinces in China were selected as subjects, and path analysis was used to test the hypotheses. The results showed that servant leadership positively predicted organizational citizenship behavior and task performance. While authoritarian leadership negatively predicted organizational citizenship behavior and positively predicted task performance, psychological empowerment mediated the relationship between the two leadership styles and organizational citizenship behavior and task performance. Moreover, psychological empowerment and organizational citizenship behavior played a multiple mediating role between the two leadership styles and task performance. The theoretical implications of these findings for advancing the ambidextrous leadership theory in Chinese organizational contexts and practical approaches for corporate managers to effectively use ambidextrous leadership style were discussed.
Inflammatory Cytokines, but Not Dietary Patterns, Are Related to Somatic Symptoms of Depression in a Sample of Women
Authors: Hazeltine Danielle Belden , Polokowski Ashley Rose , Reigada Laura Christine
Published: May 2022

Background

Depression is a heterogenous disorder with both cognitive and somatic symptom dimensions that may differentially relate to systemic inflammation. Diet, which has the potential to modulate both inflammation levels and mood, is yet to be studied within the context of individual depression dimensions. This study examined the associations between inflammatory cytokines and dietary patterns with depressive symptom dimension profiles among a sample of women recruited in a non-clinical setting.

Methods

Inflammatory cytokines (IL-6 and TNF-α), inflammatory diet (Diet Inflammatory Index; DII), and depressive symptoms (Beck Depression Inventory-II; BDI-II) were measured in 136 females (Mage = 22.01 ± 4.02, range 18–59 years). Multiple linear regressions were used to investigate the relationships between inflammatory cytokines and diet with self-reported cognitive, somatic, and total depressive symptoms, adjusting for demographic factors.

Results

Findings showed that increased somatic dimension scores were positively associated with IL-6 (ß = 0.273, p = 0.002) and TNF-α (ß = 0.215, p = 0.017), but not inflammatory diet (p = 0.300). Total BDI-II scores were only positively associated with IL-6 (ß = 0.221, p = 0.012), and cognitive dimension scores were not associated with any inflammation measures.

Conclusions

These findings contribute to existing evidence that inflammatory cytokines are associated with the somatic symptoms of depression. Inflammatory diet index was not associated with depression measures.
Protocol for a Pragmatic Trial of Pharmacotherapy Options Following Unsatisfactory Initial Treatment in OCD (PROCEED)
Authors: Wang Pei , Gu Wenjie , Gao Jian , Wang Changhong , Fang Jianqun , Hu Maorong , Xiang Hui , Li Bin , Liu Na , Tang Wenxin , Wang Xijin , Jia Yanbin , Li Yi , Cheng Yuqi , Tang Zhen , Simpson Helen Blair , Stein Dan J. , Wang Zhen
Published: May 2022

Background

Selective serotonin reuptake inhibitors (SSRIs) are the first-line pharmacotherapy for obsessive-compulsive disorder (OCD), but a large proportion of patients do not achieve remission after an adequate SSRI trial. To the best of our knowledge, there have been no well-powered randomized controlled trials (RCTs) of sequenced pharmacotherapy using pragmatic research designs. China provides a unique context for undertaking such a trial that will recruit the largest treatment-naïve participants and systematically compare the efficacy of different sequenced pharmacotherapy.

Methods

A pragmatic research design will be adopted, with n = 1,600 treatment-naïve OCD patients initially treated for sertraline for 12 weeks, and with non-remitters then randomized to 5 different augmentation or switching pharmacotherapy options for another 12 weeks. The 5 arms will include: (1) treatment with higher than usual doses of sertraline, (2) switch to fluvoxamine, (3) switch to venlafaxine, (4) augmentation with memantine, and (5) augmentation with aripiprazole.

Discussion

China is uniquely positioned to recruit sufficiently large sample sizes of treatment-naïve OCD patients to compare different pharmacotherapy options; data from the proposed trial promises to help inform current clinical practice guidelines by providing important information about optimal pharmacotherapy choice for those who demonstrate no response or response but no remission to first line pharmacotherapy.

Trial Registration

The trail was registered on 27 August 2020 in ClinicalTrials.gov (https://register.clinicaltrials.gov/) (NCT04539951).
Effect of Repeated Home Quarantine on Anxiety, Depression, and PTSD Symptoms in a Chinese Population During the COVID-19 Pandemic: A Cross-sectional Study
Authors: Tang Qiao , Wang Ya , Li Jing , Luo Dan , Hao Xiaoting , Xu Jiajun
Published: May 2022

Background

Strict quarantines can prevent the spread of the COVID-19 pandemic, but also increase the risk of mental illness. This study examined whether the people who have experienced repeated home quarantine performance more negative emotions such as anxiety, depression, and post-traumatic stress disorder (PTSD) in a Chinese population.

Methods

We collected data from 2,514 participants in Pi County, Chengdu City, and stratified them into two groups. Group 1 comprised 1,214 individuals who were quarantined only once in early 2020, while Group 2 comprised 1,300 individuals who were quarantined in early 2020 and again in late 2020. Both groups were from the same community. The GAD-7, PHQ-9, and PCL-C scales were used to assess symptoms of anxiety, depression, and PTSD between the two groups.

Results

Analyses showed that total PHQ-9 scores were significantly higher in Group 2 than in Group 1 (p < 0.001) and the quarantine times and age are independent predictors of symptoms of depression (p < 0.001). The two groups did not differ significantly in total GAD-7 or PCL-C scores.

Conclusion

Increasing quarantine times was associated with moderate to severe depression symptoms, but not with an increase in symptoms of anxiety or PTSD.
Tiny Habits® for Gratitude-Implications for Healthcare Education Stakeholders
Authors: Hollingsworth Joshua C. , Redden David T.
Published: May 2022

The COVID-19 pandemic has led to diminished sleep and increased stress, anxiety, and burnout for many health professionals and health professions students. One simple approach that may be effective for bolstering personal well-being is consciously cultivating gratitude. Gratitude is positively associated with physical health, psychological health, hope, sleep, and health behavior engagement; and randomized studies indicate that gratitude interventions can improve psychological well-being and sleep. The primary aim of this study was to assess the impact of practicing Tiny Habits® on self-reported gratitude, as measured by the 6-Item Gratitude Questionnaire (GQ-6). In January 2021, 154 adult participants with GQ-6 <35/42 were randomized to one of 3 groups: Tiny Habits for Gratitude (n = 50), Tiny Habits Control (n = 52), and Inactive Control (n = 52). Both Tiny Habits groups chose 3 Tiny Habits Recipes to practice daily and participated in the free, email-based 5-Day Program with automated daily check-in emails and personalized feedback from a Certified Tiny Habits Coach. The Recipes for the Tiny Habits for Gratitude group focused on cultivating gratitude, while those for the Tiny Habits Control group did not. Post-intervention, the mean change in GQ-6 scores in the Tiny Habits for Gratitude (Δ = ↑6.9 ± 5.6; n = 37/50, 74%; p< 0.001, Cohen's d = 0.85) and Tiny Habits Control (Δ = ↑5.6 ± 4.1; n = 31/52, 60%; p = 0.009, Cohen's d = 0.71) groups were greater than that of the Inactive Control group (Δ = ↑2.5 ± 4.4; N = 42/52, 81%). At 1 month, the mean change in GQ-6 scores in the Tiny Habits for Gratitude group (Δ = ↑7.0 ± 5.3; N = 28/50, 56%) was greater than that of the Inactive Control group (Δ = ↑2.9 ± 5.4; N = 39/52, 72%; p = 0.002, Cohen's d = 0.78). These findings suggest that practicing Tiny Habits Recipes and participating in the 5-Day Program can significantly increase gratitude in the short term and focusing specifically on gratitude during this process can sustain the increase in gratitude for up to 1 month. Implementation is quick, simple, and free. This has significant implications for healthcare education stakeholders.
A Framework for Characterizing the Multilateral and Directional Interaction Relationships Between PM Pollution at City Scale: A Case Study of 29 Cities in East China, South Korea and Japan
Authors: Liu Jianzheng , Ho Hung Chak
Published: May 2022

Transboundary particulate matter (PM) pollution has become an increasingly significant public health issue around the world due to its impacts on human health. However, transboundary PM pollution is difficult to address because it usually travels across multiple urban jurisdictional boundaries with varying transportation directions at different times, therefore posing a challenge for urban managers to figure out who is potentially polluting whose air and how PM pollution in adjacent cities interact with each other. This study proposes a statistical analysis framework for characterizing directional interaction relationships between PM pollution in cities. Compared with chemical transport models (CTMs) and chemical composition analysis method, the proposed framework requires less data and less time, and is easy to implement and able to reveal directional interaction relationships between PM pollution in multiple cities in a quick and computationally inexpensive way. In order to demonstrate the application of the framework, this study applied the framework to analyze the interaction relationships between PM2.5 pollution in 29 cities in East China, South Korea and Japan using one year of hourly PM2.5 measurement data in 2018. The results show that the framework is able to reveal the significant multilateral and directional interaction relationships between PM2.5 pollution in the 29 cities in Northeast Asia. The analysis results of the case study show that the PM2.5 pollution in China, South Korea and Japan are linked with each other, and the interaction relationships are mutual. This study further evaluated the framework's validity by comparing the analysis results against the wind vector data, the back trajectory data, as well as the results extracted from existing literature that adopted CTMs to study the interaction relationships between PM pollution in Northeast Asia. The comparisons show that the analysis results produced by the framework are consistent with the wind vector data, the back trajectory data as well as the results using CTMs. The proposed framework provides an alternative for exploring transportation pathways and patterns of transboundary PM pollution between cities when CTMs and chemical composition analysis would be too demanding or impossible to implement.
Supervision for the Public Health Services for Older Adults Under the Background of Government Purchasing: An Evolutionary Game Analysis Framework
Authors: Wang Canyou , Cui Weifang
Published: May 2022

As an important measure to involve services for older adults, the government procurement practices have become a key link for public health services. However, the information asymmetry between public health service purchasers and public health service undertakers triggers a supervision dilemma. Based on this background, this study uses the evolutionary game theory to analyze the symbiotic evolution between local governments and public health service institutions under different reward and punishment mechanisms, explore game evolution, strategy adjustment, and influencing factors of different game subjects, and analyze the necessity and appropriate intensity of dynamic rewards and punishment mechanisms. The results show that: under the static condition, the penalty can change the strategies of local governments to a certain extent, but it is still difficult to achieve complete self-discipline management of public health service institutions. If local governments implement a dynamic reward or penalty mechanism in the supervision process of public health services for older adults, the equilibrium between them tends to be evolutionary stable. For three dynamic mechanisms, a dynamic reward mechanism is more conducive to adopting a self-discipline behavior of public health service institutions, which is helpful to realize the supervision of public health services for older adults. Also, there is a positive correlation between the proportion of public health service institutions who adopt a “self-discipline behavior” strategy and the maximum punishment intensity, and a negative correlation with the reward intensity. This study provides theoretical and decision-making references for governments to explore the promotion and implementation of public health services in older adults.
Undertaking Rehabilitation Research During the COVID-19 Pandemic: Emergent Strategies From a Trainee-Faculty Workshop
Authors: Noguchi Kenneth S. , Nguyen Linda , Mehdipour Ava , Wiley Elise , Saunders Stephanie , Moncion Kevin , Reid Julie C. , Bakaa Nora , Garcia Diaz Laura , Van Damme Jill , D'Amore Cassandra , Kumurenzi Anne , Lu Ze , Knobl Erin , Beauchamp Marla K. , Macedo Luciana G. , Vrkljan Brenda , Moll Sandra E. , Carlesso Lisa C. , Letts Lori J. , Kho Michelle E. , Richardson Julie
Published: May 2022

Background

The COVID-19 pandemic has disrupted everyday rehabilitation research. Many academic institutions have halted in-person human research including rehabilitation sciences. Researchers are faced with several barriers to continuing their research programs. The purpose of this perspective article is to report the results of an interdisciplinary workshop aimed at understanding the challenges and corresponding strategies for conducting rehabilitation research during the COVID-19 pandemic.

Methods

Twenty-five rehabilitation researchers (17 trainees and eight faculty) attended a 2-h facilitated online workshop in to discuss challenges and strategies they had experienced and employed to conduct rehabilitation research during the COVID-19 pandemic.

Results

Rehabilitation researchers reported challenges with (1) pandemic protocol adjustments, (2) participant accessibility, and (3) knowledge dissemination, along with corresponding strategies to these challenges. Researchers experienced disruptions in study outcomes and intervention protocols to adhere to public health guidelines and have suggested implementing novel virtual approaches and study toolkits to facilitate offsite assessment. Participant accessibility could be improved by engaging community stakeholders in protocol revisions to ensure equity, safety, and feasibility. Researchers also experienced barriers to virtual conferences and publication, suggested opportunities for smaller networking events, and revisiting timeframes for knowledge dissemination.

Conclusion

This perspective article served as a catalyst for discussion among rehabilitation researchers to identify novel and creative approaches that address the complexities of conducting rehabilitation research during the COVID-19 pandemic and beyond.
Peripheralization, Ejidos and Agricultural Livelihoods in Intermediate Mexican Cities: The Importance of Collective Agency to Reduce Vulnerabilities
Authors: Méndez-Lemus Yadira , Vieyra Antonio , Poncela Lorena , de la Tejera Beatriz , Ruiz-López Cinthia
Published: May 2022

This paper focuses on the interactions between peripheralization, vulnerabilities of agricultural livelihoods, and local collective agency in the creation of new capabilities in intermediate cities. It discusses the theoretical implications of a study conducted in the municipality of Tarímbaro, part of the intermediate city of Morelia, Mexico; it expands on results already published in preliminary form. The unit of analysis was the ejido, since this type of social land tenure, granted to landless peasants in 1917 after the Mexican Revolution, is one of the most important forms of social organization in rural Mexico. About one-half of the Mexican territory comprises >30,000 community-based land tenures (mainly ejidos), and a high proportion of the land now occupied by urban centers was ejido land. This paper uses the example of 15 ejidos, notably affected by the expansion of Morelia city, to illustrate how local (rural) organizations can foster collective agency to reduce differential vulnerabilities in peri-urban agricultural livelihoods in intermediate cities. In 2015, a semi-structured interview was undertaken with the president of each ejido, followed by a survey of 61 individuals from 11 of the 15 ejidos. The peripheralization of Morelia has produced inequalities in the adjacent municipality of Tarímbaro. Differential vulnerabilities in peri-urban agricultural livelihoods were found in the participant ejidos. Not all the ejidos have been successful in addressing vulnerabilities associated with urbanization of agricultural land, but those who have achieved some success have certain characteristics that reinforce common values and motivations to establish common goals to sustain local livelihoods. This paper highlights the importance of functional (rural) organizations in regulating access to, and distribution of, resources in the peripheries of intermediate cities.
Why Can’t You Escape a Black Hole?
Authors: Kersting Magdalena , Ruggiero Matteo Luca
Published: May 2022

Have you ever heard of black holes? Black holes sound like objects from a science fiction story. These objects are dark, dense regions in the universe, and their gravitational pull is so strong that nothing can escape them—not even light! This is why black holes are so black: without light, we cannot see them. Physicists think that black holes are some of the universe’s most exciting objects to study. Why? Because once something has fallen into a black hole, it can never return. And more fantastic still: the laws of physics do not tell us what happens when something falls into a black hole and reaches its center. In other words, black holes are huge cosmic mysteries. In this article, we present an analogy that helps us make sense of these mysteries. The analogy offers a new way of thinking about space and time.
Enhancing Wheat Flour Quality Through Introgression of High-Molecular-Weight Glutenin Subunits From Aegilops tauschii Accessions
Authors: Mohamed Ikram Elsadig Suliman , Oe Haruka , Kamal Nasrein Mohamed , Mustafa Hala Mohammed , Gorafi Yasir Serag Alnor , Tahir Izzat Sidahmed Ali , Tsujimoto Hisashi , Tanaka Hiroyuki
Published: May 2022

Narrow genetic diversity in the wheat gene pool restricts the improvement of wheat quality traits. Aegilops tauschii possesses valuable genetic diversity that can be used to improve not only biotic and abiotic stresses in arid regions but also wheat yield and quality. Our study, which used 392 multiple synthetic derivatives (MSD) panel developed with Ae. tauschii Coss. introgressions, had three main aims: to explore the genetic diversity of high-molecular-weight glutenin subunits (HMW-GS), to investigate the dough strength and the relationship between protein content and grain yield, and to identify lines with a good flour quality. A wide range of allelic diversity was observed at the Glu-D1 locus, reflecting the impact of the different introgressed portions of Ae. tauschii, and a wide variation was found in dough strength even between lines having the same composition of HMW-GS. We report a negative impact on dough strength of subunit 5t+10t from Ae. tauschii and a relatively positive impact of subunit 2t+12.1t. We identified four MSD lines with significantly enhanced flour quality. Regressing the grain yield of the MSD lines against protein content showed no correlation between the two traits and identified lines with comparable grain yield to the recurrent parent and higher protein content. The identified MSD lines could provide a valuable genetic resource for enhancing the end-use quality of flour without any loss in productivity.
Circumferential Fusion Employing Transforaminal vs. Direct Lateral Lumbar Interbody Fusion—A Potential Impact on Implants Stability
Authors: Bokov Andrey , Kalinina Svetlana , Leontev Andrei , Mlyavykh Sergey
Published: May 2022

Background

Different fusion techniques were introduced in clinical practice in patients with lumbar degenerative disc disease, however, no evidence has been provided on the advantages of one technique over another.

The Objective of This Study

Is to assess the potential impact of circumferential fusion employing transforaminal lumbar interbody fusion (TLIF) vs. direct lateral interbody fusion (DLIF) on pedicle screw stability.

Materials and Methods

This is a single-center prospective evaluation of consecutive 138 patients with degenerative instability of lumbar spinal segments. Either conventional transforaminal lumbar interbody fusion (TLIF) with posterior fusion or direct lateral interbody fusion (DLIF) using cages of standard dimensions, were applied. The conventional open technique was used to supplement TLIF with pedicle screws while percutaneous screw placement was used in patients treated with DLIF. The duration of the follow-up accounted for 24 months. Signs of pedicle screws loosening (PSL) and bone union after fusion were assessed by the results of CT imaging. Fisher‘s exact test was used to assess the differences in the rate of CT loosening and revision surgery because of implant instability. Logistic regression was used to assess the association between potential factors and complication rate.

Results

The rate of PSL detected by CT and relevant revision surgery in groups treated with TLIF and DLIF accounted for 25 (32.9%) vs. 2 (3.2%), respectively, for the former and 9 (12.0%) vs. 0 (0%) for the latter (p < 0.0001 and p = 0.0043) respectively. According to the results of logistic regression, a decrease in radiodensity values and a greater number of levels fused were associated with a rise in PSL rate. DLIF application in patients with radiodensity below 140 HU was associated with a considerable decrease in complication rate. Unipolar or bipolar pseudoarthrosis in patients operated on with TLIF was associated with a rise in PSL rate while patients treated with DLIF tolerate delayed interbody fusion formation. In patients treated with TLIF supplementary total or partial posterior fusion resulted in a decline in PSL rate.

Conclusion

Even though the supplementary posterior fusion may considerably reduce the rate of PSL in patients treated with TLIF, the application of DLIF provide greater stability resulting in a substantial decline in PSL rate and relevant revision surgery.
Application of Non-Blood-Derived Fluid Biopsy in Monitoring Minimal Residual Diseases of Lung Cancer
Authors: Yan Xing , Liu Changhong
Published: May 2022

Lung cancer is one of the most fatal malignant tumors in the world. Overcoming this disease is difficult due to its late diagnosis and relapse after treatment. Minimal residual disease (MRD) is described as the presence of free circulating tumor cells or other tumor cell derivatives in the biological fluid of patients without any clinical symptoms of cancer and negative imaging examination after the treatment of primary tumors. It has been widely discussed in the medical community as a bridge to solid tumor recurrence. Radiology, serology (carcinoembryonic antigen), and other clinical diagnosis and treatment methods widely used to monitor the progression of disease recurrence have obvious time-limited and -specific defects. Furthermore, as most samples of traditional liquid biopsies come from patients’ blood (including plasma and serum), the low concentration of tumor markers in blood samples limits the ability of these liquid biopsies in the early detection of cancer recurrence. The use of non-blood-derived fluid biopsy in monitoring the status of MRD and further improving the postoperative individualized treatment of patients with lung cancer is gradually ushering in the dawn of hope. This paper reviews the progress of several non-blood-derived fluid samples (urine, saliva, sputum, and pleural effusion) in detecting MRD in lung cancer as well as selecting the accurate treatment for it.
Antibiotic Bowel Decontamination in Gastrointestinal Surgery—A Single-Center 20 Years’ Experience
Authors: Schardey Josefine , von Ahnen Thomas , Schardey Emily , Kappenberger Alina , Zimmermann Petra , Kühn Florian , Andrassy Joachim , Werner Jens , Arbogast Helmut , Wirth Ulrich
Published: May 2022

Objective

Anastomotic leakage, surgical site infections, and other infectious complications are still common complications in gastrointestinal surgery. The concept of perioperative antibiotic bowel decontamination demonstrates beneficial effects in single randomized controlled trials (RCTs), but data from routine clinical use are still sparse. Our aim was to analyze the data from the routine clinical use of perioperative antibiotic bowel decontamination in gastrointestinal surgery.

Methods

Based on 20 years’ experience, we performed a retrospective analysis of all cases in oncologic gastrointestinal surgery with the use of antibiotic bowel decontamination in gastric, sigmoid, and rectal cancer. Clinical data and perioperative outcomes were analyzed, especially regarding anastomotic leakage, surgical site infections, and other infectious complications.

Results

A total of n = 477 cases of gastrointestinal surgery in gastric cancer (n = 80), sigmoid cancer (n = 168), and rectal cancer (n = 229) using a perioperative regimen of antibiotic bowel decontamination could be included in this analysis. Overall, anastomotic leakage occurred in 4.4% (2.5% gastric cancer, 3.0% sigmoid cancer, 6.1% rectal cancer) and surgical site infections in 9.6% (6.3% gastric cancer, 9.5% sigmoid cancer, 10.9% rectal cancer). The incidence of all infectious complications was 13.6% (12.5% gastric cancer, 11.3% sigmoid cancer, 15.7% rectal cancer). Mortality was low, with an overall rate of 1.1% (1.3% gastric cancer, 1.8% sigmoid cancer, 0.4% rectal cancer). Antibiotic decontamination was completed in 98.5%. No adverse effects of antibiotic bowel decontamination could be observed.

Conclusion

Overall, in this large cohort, we can report low rates of surgery-related serious morbidity and mortality when perioperative antibiotic bowel decontamination is performed. The rates are lower than other clinical reports. In our clinical experience, the use of perioperative antibiotic bowel decontamination appears to improve patient safety and surgical outcomes during gastrointestinal oncologic procedures in a routine clinical setting.
Statistical Analysis of IABP-Surgery Data with the Co-use of Anticoagulants, Pulse of Dorsalis Pedis Artery, D-Dimer Data, and Coagulation Function
Authors: Chen Huali , Shen Zhoumin , Zhang Yan , Zheng Zhaofen , Li Lihua , Tian Xinyi , Peng Jianqiang , Peng Xi , Zhou Yi
Published: May 2022

Data analysis was performed on IABP (intra-aortic balloon pump) patients for the use of anticoagulants, pulse of dorsalis pedis artery, D-dimer data, and coagulation function. According to the differential diagnosis of 52 patients admitted to hospital, data on the use of anticoagulants, dorsalis pedis artery pulsation, D-dimer data, and coagulation function were collected. These data were analyzed by using a nonparametric test, linear regression analysis, adjustment effect analysis, and chi-square test. Some findings of the analysis included: (1) There were differences in the dorsalis pedis artery pulsation of samples from different sexes, all of which were significant. (2) Coagulation function has a significant positive relationship with D-dimer. (3) When the D-dimer affects the prognosis, the regulatory variable (dorsalis pedis artery pulse) is at different levels, and the influence amplitude has significant differences. (4) Samples taken with different anticoagulants all showed significant differences in the dorsalis pedis artery pulsation.
Smart(Sampling)Augment: Optimal and Efficient Data Augmentation for Semantic Segmentation
Authors: Negassi Misgana , Wagner Diane , Reiterer Alexander
Published: May 2022

Data augmentation methods enrich datasets with augmented data to improve the performance of neural networks. Recently, automated data augmentation methods have emerged, which automatically design augmentation strategies. The existing work focuses on image classification and object detection, whereas we provide the first study on semantic image segmentation and introduce two new approaches: SmartAugment and SmartSamplingAugment. SmartAugment uses Bayesian Optimization to search a rich space of augmentation strategies and achieves new state-of-the-art performance in all semantic segmentation tasks we consider. SmartSamplingAugment, a simple parameter-free approach with a fixed augmentation strategy, competes in performance with the existing resource-intensive approaches and outperforms cheap state-of-the-art data augmentation methods. Furthermore, we analyze the impact, interaction, and importance of data augmentation hyperparameters and perform ablation studies, which confirm our design choices behind SmartAugment and SmartSamplingAugment. Lastly, we will provide our source code for reproducibility and to facilitate further research.
Thermal Design of Blackbody for On-Board Calibration of Spaceborne Infrared Imaging Sensor
Authors: Kim Hye-In , Chae Bong-Geon , Choi Pil-Gyeong , Jo Mun-Shin , Lee Kyoung-Muk , Oh Hyun-Ung
Published: May 2022

In this study, we propose a thermal design for an on-board blackbody (BB) for spaceborne infrared (IR) sensor calibration. The main function of the on-board BB is to provide highly uniform and precise radiation temperature reference sources from 0 °C to 40 °C during the calibration of the IR sensor. To meet the functional requirements of BB, a BB thermal design using a heater to heat the BB during sensor calibration and heat pipes to transfer residual heat to the radiator after calibration is proposed and investigated both numerically and experimentally. The main features of the proposed thermal design are a symmetric temperature gradient on the BB surface with less than 1 K temperature uniformity, ease of temperature sensor implementation to estimate the representative surface temperature of the BB, a stable thermal interface between the heat pipes and BB, and a fail-safe function under one heat pipe failure. The thermal control performance of the BB is investigated via in-orbit thermal analysis, and its effectiveness is verified via a heat-up test of the BB under ambient conditions. These results indicate that the temperature gradient on the BB surface was obtained at less than 1 K, and the representative surface temperature could be estimated with an accuracy of 0.005 °C via the temperature sensor.
Tendencies of Precision Agriculture in Ukraine: Disruptive Smart Farming Tools as Cooperation Drivers
Authors: Hrynevych Oksana , Blanco Canto Miguel , Jiménez García Mercedes
Published: May 2022

Precision farming innovations are designed to improve the efficiency of agricultural activities via minimal initial input of material and human resources and avoiding harmful effects on the environment on one hand and automatizing the production on another hand, thus providing environmental, social and economic benefits. In the article, the tendencies in the adoption of precision agriculture technologies (PAT) in Ukraine were observed, with a specific focus on cooperatives as a valuable tool of social and solidarity economy helping to achieve progress in local rural development. On the example of cooperatives, applying a technology acceptance model (TAM) has identified how the adoption of new smart farming tools influence their behavior in implementing technological innovations. The results of the study will be of particular interest to representatives of other cooperatives and to agribusiness players engaged in agriculture or software development. In addition, the outputs will be useful for researchers in the field of the socio-economic development of territories and the impact of new technologies on it, as well as for local governments and higher-level government officials, which can contribute to the implementation of better rural development strategies.
Evaluation of Agricultural Water Resources Carrying Capacity and Its Influencing Factors: A Case Study of Townships in the Arid Region of Northwest China
Authors: Wang Penglong , Wei Yao , Zhong Fanglei , Song Xiaoyu , Wang Bao , Wang Qinhua
Published: May 2022

The water resources carrying capacity (WRCC) strongly determines the agricultural development in arid areas. Evaluation of WRCC is important in balancing the availability of water resources with society’s economic and environmental demands. Given the demand for sustainable utilization of agricultural water resources, we combine the water stress index and comprehensive index of WRCC and use multi-source data to evaluate agricultural WRCC and its influencing factors at the township scale. It makes up for the deficiencies of current research, such as the existence of single-index evaluation systems, limited calibration data, and a lack of a sub-watershed (i.e., township) scale. By applying multi-source data, this study expands the spatial scale of WRCC assessment and establishes a multidimensional evaluation framework for the water resources in dryland agriculture. The results indicate water stress index ranges from 0.52 to 1.67, and the comprehensive index of WRCC ranges from 0.25 to 0.70, which are significantly different in different types of irrigation areas and townships. Water quantity and water management are key factors influencing WRCC, the water ecosystem is an area requiring improvement, and the water environment is not a current constraint. Different irrigation areas and different types of townships should implement targeted measures to improve WRCC.
Genome-Wide Identification and Characterization of Long Non-Coding RNAs in Embryo Muscle of Chicken
Authors: Liu Lingbin , Ren Lingtong , Liu Anfang , Wang Jinxin , Wang Jianhua , Wang Qigui
Published: May 2022

Embryonic muscle development determines the state of muscle development and muscle morphological structure size. Recent studies have found that long non-coding RNAs (lncRNAs) could influence numerous cellular processes and regulated growth and development of flora and fauna. A total of 1056 differentially expressed lncRNAs were identified by comparing the different time points during embryonic muscle development, which included 874 new lncRNAs. Here, we found that there were different gene expression patterns on the 12th day of embryo development (E12). Herein, WGCNA and correlation analyses were used to predict lncRNA function on E12 through the screening and identification of lncRNAs related to muscle development in the embryo leg muscles of Chengkou mountain chickens at different times. GO and KEGG functional enrichment analysis was performed on target genes involved in cis-regulation and trans-regulation. An interaction network diagram was constructed based on the muscle development pathways, such as Wnt, FoxO, and PI3K-AKT signaling pathways, to determine the interaction between mRNAs and lncRNAs. This study preliminarily determined the lncRNA expression pattern of muscle development during the middle and late embryonic stages of Chengkou mountain chickens, and provided a basis to analyze the molecular mechanism of muscle development.
Nanomechanical Characterization of Bacterial Polyhydroxyalkanoates Using Atomic Force Microscopy
Authors: Bagatella Simone , Ciapponi Riccardo , Turri Stefano
Published: May 2022

Polyhydroxyalkanoates are a promising class of biopolymers that can allow the production of sustainable plastic materials. The mechanical properties of such materials are very important for possible industrial applications, but the amount of polymer required for common mechanical testing can be orders of magnitude more than what is possible to achieve with a lab-scale process. Nanoindentation with the Atomic Force Microscope allows an estimation of the Elastic Modulus that can be used as a preliminary measurement on PHA when only a limited amount of material is available. Poly(hydroxybutyrate-co-hydroxyvalerate) copolymers were analyzed, with moduli ranging from 528 ± 62 MPa to 1623 ± 172 MPa, according to both the composition and the crystallization kinetics.
Customer Churn Prediction in B2B Non-Contractual Business Settings Using Invoice Data
Authors: Mirkovic Milan , Lolic Teodora , Stefanovic Darko , Anderla Andras , Gracanin Danijela
Published: May 2022

Customer churn is a problem virtually all companies face, and the ability to predict it reliably can be a cornerstone for successful retention campaigns. In this study, we propose an approach to customer churn prediction in non-contractual B2B settings that relies exclusively on invoice-level data for feature engineering and uses multi-slicing to maximally utilize available data. We cast churn as a binary classification problem and assess the ability of three established classifiers to predict it when using different churn definitions. We also compare classifier performance when different amounts of historical data are used for feature engineering. The results indicate that robust models for different churn definitions can be derived by using invoice-level data alone and that using more historical data for creating some of the features tends to lead to better performing models for some classifiers. We also confirm that the multi-slicing approach to dataset creation yields better performing models compared to the traditionally used single-slicing approach.
Improving Non-Autoregressive Machine Translation Using Sentence-Level Semantic Agreement
Authors: Wang Shuheng , Huang Heyan , Shi Shumin
Published: May 2022

Theinference stage can be accelerated significantly using a Non-Autoregressive Transformer (NAT). However, the training objective used in the NAT model also aims to minimize the loss between the generated words and the golden words in the reference. Since the dependencies between the target words are lacking, this training objective computed at word level can easily cause semantic inconsistency between the generated and source sentences. To alleviate this issue, we propose a new method, Sentence-Level Semantic Agreement (SLSA), to obtain consistency between the source and generated sentences. Specifically, we utilize contrastive learning to pull the sentence representations of the source and generated sentences closer together. In addition, to strengthen the capability of the encoder, we also integrate an agreement module into the encoder to obtain a better representation of the source sentence. The experiments are conducted on three translation datasets: the WMT 2014 EN → DE task, the WMT 2016 EN → RO task, and the IWSLT 2014 DE → DE task, and the improvement in the NAT model’s performance shows the effect of our proposed method.
Damage Detection of Insulators in Catenary Based on Deep Learning and Zernike Moment Algorithms
Authors: Li Teng , Hao Tian
Published: May 2022

The intelligent damage detection of catenary insulators is one of the key steps in maintaining the safe and stable operation of railway traction power supply systems. However, traditional deep learning algorithms need to train a large number of images with damage features, which are hard to obtain; and feature-matching algorithms have limitations in anti-complex background interference, affecting the accuracy of damage detection. The current work proposes a method that combines deep learning and Zernike moment algorithms. The Mask R-CNN algorithm is firstly used to identify the catenary insulators to realize the region proposal of the insulators. After image preprocessing, the Zernike moment algorithm is used to replace the existing Hu moment algorithm to extract more detailed insulator contour features, then the similarity value and its standard deviation are further calculated, so as to complete the damage detection of the catenary insulator. The experimental results show that the mean average precision of insulator identification can reach 96.4%, and the Zernike moment algorithm has an accuracy of 93.36% in judging the damage of insulators. Compared with the existing Hu moment algorithm, the accuracy is increased by 10.94%, which provides a new method for the automatic detection of damaged insulators in catenary and even other scenarios.
Improved Ultrasonic Dead Zone Detectability of Work Rolls Using a Convolutional Neural Network
Authors: Yeom Yun-Taek , Kim Hun-Hee , Park Jinhyun , Kim Hak-Joon , Song Sung-Jin
Published: May 2022

Rolled carbon steel sheets used in industrial and construction sites are formed by passing metal stock between two rotating rolls using a rolling mill, and the work roll is an essential part of the rolling mill. As the work rolls are in direct contact with the workpiece, the process quality is highly sensitive to their surface integrity, which is maintained through rough and finish cuttings; ultrasonic inspection is often performed after rough cutting the surfaces of work rolls. Ultrasonic inspection signals comprise signals reflected from and below the surface. Depending on the size of the subsurface defects, the thickness of the finish cutting is determined. The signals reflected by defects close to the surface overlap with those from the work roll surface, which is referred to as the ultrasonic dead zone and makes defect detection difficult. Since visual detection of flaws is not possible from signals collected from the dead zone, finish cutting is commonly performed up to the dead zone depth; this requires unnecessary cost and process time, which must be improved. Therefore, in this study a convolutional neural network is used to improve defect detection performance in the ultrasonic dead zone during the inspection of work rolls.
Continuous-Time Nonlinear Model Predictive Tracking Control with Input Constraints Using Feedback Linearization
Authors: Kuo Yong-Lin , Pongpanyaporn Peeraya
Published: May 2022

This paper presents a tracking control scheme for nonlinear systems with input constraints by combining the continuous-time model predictive control and the feedback linearization. Although there are some similar combinations for nonlinear systems presented in literature, their formulations are complex and massive computations are unavoidable. This study aims to simplify the formulations and reduce the computational loads by imposing the Laguerre functions to approximate the control signals. Since the Laguerre functions have the property of orthogonality, the tracking control problem, by applying the combination, leads to a constrained quadratic optimization problem in terms of the coefficients associated with the Laguerre functions, where the input constraints are converted so as to be state-dependent, based on feedback linearization. The Hildreth’s quadratic programming algorithm is used to solve the optimization problem, so as to determine the coefficients. Moreover, this study also summarizes some common linearization schemes and shows their pros and cons. Furthermore, the proposed approach is applied to two illustrative examples, and the control performances are compared with those by linear control strategies combined with those linearization schemes.
Estimation Method for Road Link Travel Time Considering the Heterogeneity of Driving Styles
Authors: Zhang Yuhui , Ji Yanjie , Yu Jiajie
Published: May 2022

To solve the problem of low automatic number plate recognition (ANPR) data integrity and low completion accuracy of incomplete traffic data, which affects the quality and utilization of ANPR data, this paper proposed a model for estimating the travel time of the road link that considers the heterogeneity of the driving styles. The travel time of historical road sections in the road network was extracted from ANPR data. The driving crowd was clustered through density-based spatial clustering of applications with noise (DBSCAN) based on the time slot, the number of trips, and the travel time. To avoid the excessive data difference between different classes and the distortion of the complement data, the Lagrange interpolation method was adopted to complement the missing road link travel time within each cluster. Taking Ningbo city in China as an example, the travel time completion accuracies of the proposed method and the direct interpolation method were compared. The results show that the interpolation method considering the heterogeneity of driving styles is more sufficient to increase the completion accuracy by 37.4% compared with the direct interpolation manner. The comparison result verifies the effectiveness of the proposed method and can provide more reliable data support for the construction of the transportation system.