bluuebunny/crossref_metadata_2025 huggingface dataset:
Loci and Natural Alleles for Low-Nitrogen-Induced Growth Response Revealed by the Genome-Wide Association Study Analysis in Rice (Oryza sativa L.)
Authors: Lv Yang , Ma Jie , Wang Yueying , Wang Quan , Lu Xueli , Hu Haitao , Qian Qian , Guo Longbiao , Shang Lianguang
Published: November 2021

Nitrogen is essential for plant growth and yield, and it is, therefore, crucial to increase the nitrogen-use efficiency (NUE) of crop plants in fields. In this study, we measured four major low-nitrogen-induced growth response (LNGR) agronomic traits (i.e., plant height, tiller number, chlorophyll content, and leaf length) of the 225-rice-variety natural population from the Rice 3K Sequencing Project across normal nitrogen (NN) and low nitrogen (LN) environments. The LNGR phenotypic difference between NN and LN levels was used for gene analysis using a genome-wide association study (GWAS) combined with 111,205 single-nucleotide polymorphisms (SNPs) from the available sequenced data from the 3K project. We obtained a total of 56 significantly associated SNPs and 4 candidate genes for 4 LNGR traits. Some loci were located in the candidate regions, such as MYB61, OsOAT, and MOC2. To further study the role of candidate genes, we conducted haplotype analyses to identify the elite germplasms. Moreover, several other plausible candidate genes encoding LN-related or NUE proteins were worthy of mining. Our study provides novel insight into the genetic control of LNGR and further reveals some related novel haplotypes and potential genes with phenotypic variation in rice.
Transformation and Overexpression of Primary Cell Wall Synthesis-Related Zinc Finger Gene Gh_A07G1537 to Improve Fiber Length in Cotton
Authors: Razzaq Abdul , Zafar Muhammad Mubashar , Li Pengtao , Qun Ge , Deng Xiaoying , Ali Arfan , Hafeez Abdul , Irfan Muhammad , Liu Aiying , Ren Maozhi , Shang Haihong , Shi Yuzhen , Gong Wankui , Yuan Youlu
Published: November 2021

Molecular interventions have helped to explore the genes involved in fiber length, fiber strength, and other quality parameters with improved characteristics, particularly in cotton. The current study is an extension and functional validation of previous findings that Gh_A07G1537 influences fiber length in cotton using a chromosomal segment substitution line MBI7747 through RNA-seq data. The recombinant Gh_A07G1537 derived from the MBI7747 line was over-expressed in CCRI24, a genotype with a low profile of fiber quality parameters. Putative transformants were selected on MS medium containing hygromycin (25mg/ml), acclimatized, and shifted to a greenhouse for further growth and proliferation. Transgene integration was validated through PCR and Southern Blot analysis. Stable integration of the transgene (ΔGh_A07G1537) was validated by tracking its expression in different generations (T0, T1, and T2) of transformed cotton plants. It was found to be 2.97-, 2.86-, and 2.92-folds higher expression in T0, T1, and T2 plants, respectively, of transgenic compared with non-transgenic cotton plants. Fiber quality parameters were also observed to be improved in the engineered cotton line. Genetic modifications of Gh_A07G1537 support the improvement in fiber quality parameters and should be appreciated for the textile industry.
Patient and Public Involvement in Youth Mental Health Research: Protocol for a Systematic Review of Practices and Impact
Authors: Sales Célia M. D. , Martins Filipa , Alves Marisa M. , Carletto Sara , Conejo-Cerón Sonia , da Silva Luis Costa , Čuš Anja , Edridge Chloe , Ferreira Nuno , Hancheva Camellia , Lima Esperanca M. A. , Liverpool Shaun , Midgley Nick , Moltrecht Bettina , Moreno-Peral Patricia , Morgan Nicholas , Mortimer Rose , Mota Catarina Pinheiro , Pietrabissa Giada , Sousa Sonia , Ulberg Randi , Edbrooke-Childs Julian
Published: November 2021

Various health settings have advocated for involving patients and members of the public (PPI) in research as a means to increase quality and relevance of the produced knowledge. However, youth PPI has been an understudied area. This protocol paper describes a new project that aims to summarize what is known about PPI with young people in mental health research. In line with the Preferred Reporting Items for Systematic reviews and Meta-Analyses Statement guidelines we will identify and appraise suitable articles and extract and synthesize relevant information including at least two reviewers at each stage of the process. Results will be presented in two systematic reviews that will describe (a) how youth PPI has been conducted (Review1) and (b) what impact youth PPI had on the subsequent research and on stakeholders (Review2). To our knowledge, this is the first set of reviews that uses a critical appraisal tool, which is co-developed with children and young people. Findings from this project will provide valuable insights and set out the key steps to adopting adequate PPI methods when involving children and young people in mental health research.
Temporal Team Mental Model and Performance: From the Perspective of Team Process
Authors: Li Dan , Zhang Qian
Published: November 2021

This paper, based on the survey data of 506 knowledge-based innovation team leaders, employed the regression model and adopted the bootstrap method, to explore the influence of the temporal team mental model on team performance from the perspective of team process. The study results showed that the temporal team mental model has a significant positive predictive effect on team performance; behavioral integration has a mediating effect between temporal team mental model and team performance; task complexity positively moderates the relationship between behavioral integration and team performance and moderates the mediating effects of behavioral integration.
Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study
Authors: Levy Joshua J. , Lebeaux Rebecca M. , Hoen Anne G. , Christensen Brock C. , Vaickus Louis J. , MacKenzie Todd A.
Published: November 2021

What is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks?

Background: Following a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images, prior work has demonstrated associations of the built environment with income, education, access to care, and health factors such as obesity. However, assessment of learned image feature relationships with variation in crude mortality rate across the United States has been lacking.

Objective: We sought to investigate if county-level mortality rates in the U.S. could be predicted from satellite images.

Methods: Satellite images of neighborhoods surrounding schools were extracted with the Google Static Maps application programming interface for 430 counties representing ~68.9% of the US population. A convolutional neural network was trained using crude mortality rates for each county in 2015 to predict mortality. Learned image features were interpreted using Shapley Additive Feature Explanations, clustered, and compared to mortality and its associated covariate predictors.

Results: Predicted mortality from satellite images in a held-out test set of counties was strongly correlated to the true crude mortality rate (Pearson r = 0.72). Direct prediction of mortality using a deep learning model across a cross-section of 430 U.S. counties identified key features in the environment (e.g., sidewalks, driveways, and hiking trails) associated with lower mortality. Learned image features were clustered, and we identified 10 clusters that were associated with education, income, geographical region, race, and age.

Conclusions: The application of deep learning techniques to remotely-sensed features of the built environment can serve as a useful predictor of mortality in the United States. Although we identified features that were largely associated with demographic information, future modeling approaches that directly identify image features associated with health-related outcomes have the potential to inform targeted public health interventions.
Racial and Urban-Rural Difference in the Frequency of Ischemic Stroke as Initial Manifestation of Atrial Fibrillation
Authors: Guo Jingchuan , Gabriel Nico , Magnani Jared W. , Essien Utibe R. , Gellad Walid F. , Brooks Maria M. , Trinquart Ludovic , Benjamin Emelia J. , Hernandez Inmaculada
Published: November 2021

Objective: Atrial fibrillation (AF) may remain undiagnosed until the development of complications. We aimed to examine the epidemiology and racial/ethnic and rural/urban differences in the frequency of newly diagnosed AF manifesting as ischemic stroke in a nationally representative sample of Medicare beneficiaries.

Methods: We used a 5% random sample of Medicare claims to identify patients newly diagnosed with AF in 2016. The primary dependent variable was stroke or transient ischemic attack (TIA) in the 7 days prior to the first AF diagnosis, i.e., stroke or TIA as the initial manifestation of AF. We constructed a multivariable logistic regression to quantify the association between race/ethnicity, urban/rural residence, and the primary dependent variable.

Results: Among 39,409 patients newly diagnosed with AF (mean age 77 ± 10 years; 58% women; 7.2% Black, 87.8% White, 5.1% others), 2,819 (7.2%) had ischemic stroke or TIA in the 7 days prior to AF diagnosis. Black patients (adjusted OR [95% CI]: 1.21 [1.05, 1.40], vs. White) and urban residents (1.21 [1.08, 1.35], vs. rural) were at increased risk of stroke as the initial manifestation of AF. Racial differences were larger among patients aged ≥75 years, with adjusted ORs of 1.43 (1.19, 1.73) for Black vs. White patients, but non-significant for those aged <75 (P for interaction = 0.03).

Conclusion: We observed significant and important differences in the risk of stroke as initial manifestation of AF between White and Black patients and between rural and urban residents. Our results suggest potential disparities in the identification AF across race/ethnicity groups and urban/rural areas.
Communication Apprehension and Eye Contact Anxiety in Video Conferences Involving Teleoperated Robot Avatars: A Subjective Evaluation Study
Authors: Mehmood Faisal , Mahzoon Hamed , Yoshikawa Yuichiro , Ishiguro Hiroshi
Published: November 2021

Communication apprehension (CA), defined as anxiety in oral communication, and anxiety in eye contact (AEC), defined as the discomfort felt in communication while being stared at by others, limit communication effectiveness. In this study, we examined whether using a teleoperated robot avatar in a video teleconference provides communication support to people with CA and AEC. We propose a robotic telecommunication system in which a user has two options to produce utterance for own responses in online interaction with interviewer i.e., either by a robot avatar that faces the interviewer, or by self. Two imagination-based experiments were conducted, in which a total of 400 participants were asked to watch videos for interview scenes with or without the proposed system; 200 participants for each experiment. The participants then evaluated their impressions by imagining that they were the interviewee. In the first experiment, a video conference with the proposed system was compared with an ordinary video conference, where the interviewer and interviewee faced each other. In the second experiment, it was compared with an ordinary video conference where the interviewer’s attentional focus was directed away from the interviewee. A significant decrease in the expected CA and AEC of participants with the proposed system was observed in both experiments, whereas a significant increase in the expected sense of being attended (SoBA) was observed in the second experiment. This study contributes to the literature in terms of examining the expected impact of using a teleoperated robot avatar for better video conferences, especially for supporting individuals with CA and AEC.
Quick Setup of Force-Controlled Industrial Gluing Tasks Using Learning From Demonstration
Authors: Iturrate Iñigo , Kramberger Aljaz , Sloth Christoffer
Published: November 2021

This paper presents a framework for programming in-contact tasks using learning by demonstration. The framework is demonstrated on an industrial gluing task, showing that a high quality robot behavior can be programmed using a single demonstration. A unified controller structure is proposed for the demonstration and execution of in-contact tasks that eases the transition from admittance controller for demonstration to parallel force/position control for the execution. The proposed controller is adapted according to the geometry of the task constraints, which is estimated online during the demonstration. In addition, the controller gains are adapted to the human behavior during demonstration to improve the quality of the demonstration. The considered gluing task requires the robot to alternate between free motion and in-contact motion; hence, an approach for minimizing contact forces during the switching between the two situations is presented. We evaluate our proposed system in a series of experiments, where we show that we are able to estimate the geometry of a curved surface, that our adaptive controller for demonstration allows users to achieve higher accuracy in a shorter demonstration duration when compared to an off-the-shelf controller for teaching implemented on a collaborative robot, and that our execution controller is able to reduce impact forces and apply a constant process force while adapting to the surface geometry.
Three-Stage Transitional Theory: Egalitarian Gender Attitudes and Housework Share in 24 Countries
Authors: Kan Man-Yee , Kolpashnikova Kamila
Published: November 2021

How does the association between gender attitudes and housework share vary across countries and time? We examine the second demographic transition as it unmasks in the association between gender attitudes and housework participation. Using data of the 2002 and 2012 International Social Survey Programme (ISSP) for 24 countries, we find that the association between gender attitudes and housework share became stronger over time in most countries, signifying that the Second Demographic Transition was in place. The results also show that the association varied across the 24 countries, reaching an equilibrium in many but at different stages. Our findings suggest that equilibria in the domestic division of labour take various forms and paces in the ISSP countries.
Bifurcated Current Sheet Observed on the Boundary of Kelvin-Helmholtz Vortices
Authors: Hwang K-J. , Dokgo K. , Choi E. , Burch J. L. , Sibeck D. G. , Giles B. L. , Norgren C. , Nakamura T. K. M. , Graham D. B. , Khotyaintsev Y. , Shi Q. Q. , Gershman D. J. , Pollock C. J. , Ergun R. E. , Torbert R. B. , Russell C. T. , Strangeway R. J.
Published: November 2021

On May 5, 2017 MMS observed a bifurcated current sheet at the boundary of Kelvin-Helmholtz vortices (KHVs) developed on the dawnside tailward magnetopause. We use the event to enhance our understanding of the formation and structure of asymmetric current sheets in the presence of density asymmetry, flow shear, and guide field, which have been rarely studied. The entire current layer comprises three separate current sheets, each corresponding to magnetosphere-side sunward separatrix region, central near-X-line region, and magnetosheath-side tailward separatrix region. Two off-center structures are identified as slow-mode discontinuities. All three current sheets have a thickness of ∼0.2 ion inertial length, demonstrating the sub-ion-scale current layer, where electrons mainly carry the current. We find that both the diamagnetic and electron anisotropy currents substantially support the bifurcated currents in the presence of density asymmetry and weak velocity shear. The combined effects of strong guide field, low density asymmetry, and weak flow shear appear to lead to asymmetries in the streamlines and the current-layer structure of the quadrupolar reconnection geometry. We also investigate intense electrostatics waves observed on the magnetosheath side of the KHV boundary. These waves may pre-heat a magnetosheath population that is to participate into the reconnection process, leading to two-step energization of the magnetosheath plasma entering into the magnetosphere via KHV-driven reconnection.
Predicting Experimental Sepsis Survival with a Mathematical Model of Acute Inflammation
Authors: Barber Jared , Carpenter Amy , Torsey Allison , Borgard Tyler , Namas Rami A. , Vodovotz Yoram , Arciero Julia
Published: November 2021

Sepsis is characterized by an overactive, dysregulated inflammatory response that drives organ dysfunction and often results in death. Mathematical modeling has emerged as an essential tool for understanding the underlying complex biological processes. A system of four ordinary differential equations (ODEs) was developed to simulate the dynamics of bacteria, the pro- and anti-inflammatory responses, and tissue damage (whose molecular correlate is damage-associated molecular pattern [DAMP] molecules and which integrates inputs from the other variables, feeds back to drive further inflammation, and serves as a proxy for whole-organism health status). The ODE model was calibrated to experimental data from E. coli infection in genetically identical rats and was validated with mortality data for these animals. The model demonstrated recovery, aseptic death, or septic death outcomes for a simulated infection while varying the initial inoculum, pathogen growth rate, strength of the local immune response, and activation of the pro-inflammatory response in the system. In general, more septic outcomes were encountered when the initial inoculum of bacteria was increased, the pathogen growth rate was increased, or the host immune response was decreased. The model demonstrated that small changes in parameter values, such as those governing the pathogen or the immune response, could explain the experimentally observed variability in mortality rates among septic rats. A local sensitivity analysis was conducted to understand the magnitude of such parameter effects on system dynamics. Despite successful predictions of mortality, simulated trajectories of bacteria, inflammatory responses, and damage were closely clustered during the initial stages of infection, suggesting that uncertainty in initial conditions could lead to difficulty in predicting outcomes of sepsis by using inflammation biomarker levels.
Sustainable Supersonic Fuel Flow Method: An Evolution of the Boeing Fuel Flow Method for Supersonic Aircraft Using Sustainable Aviation Fuels
Authors: Fusaro Roberta , Viola Nicole , Galassini Diego
Published: November 2021

This paper discloses a new algorithm, called sustainable supersonic fuel flow method, to complement the conceptual design of future supersonic aircraft with pollutant and greenhouse gases emissions estimation. Starting from already existing algorithms currently used to assess the environmental impact of already developed and operating aircraft, the authors suggest revisions to improve the formulations, thus extending their application. Specifically, this paper has two objectives: to support the design of future supersonic aircraft and to evaluate the impact of the exploitation of more sustainable aviation fuels, with special focus on biofuels and biofuel blends, since the conceptual design stage. The core of the algorithm developed to predict in-flight emissions of a supersonic aircraft has been validated with public data of Concorde flight experiments. In addition, corrective factors accounting for the most recently developed and certified biofuels have been included in the formulation.
Wild and Traditional Barley Genomic Resources as a Tool for Abiotic Stress Tolerance and Biotic Relations
Authors: Capasso Giorgia , Santini Giorgia , Petraretti Mariagioia , Esposito Sergio , Landi Simone
Published: November 2021

Barley (Hordeum vulgare L.) is one of the main crops cultivated all over the world. As for other cereals, throughout the centuries barley was subjected by human breeding to genetic erosion phenomena, which guaranteed improved yields in organized (and then mechanized) agriculture; on the other hand, this selection weakened the ability of barley to survive under adverse environments. Currently, it is clear that climate change requires an urgent availability of crop varieties able to grow under stress conditions, namely limited irrigation, salinity, high temperatures, and other stresses. In this context, an important role could be played by wild relatives and landraces selected by farmers, particularly in specific field areas and/or climatic conditions. In this review, we investigated the origin of barley and the potentialities of wild varieties and landraces in different contexts, and their resilience to abiotic stress. The data obtained from Next Generation Sequencing technologies were examined to highlight the critical aspects of barley evolution and the most important features for abiotic stress tolerance. Furthermore, the potential of appropriate mycorrhiza is discussed under the view of the essential role played by these symbioses in field crops. The abilities of specific barley wild varieties and landraces may represent novel opportunities and suggest innovative strategies for the improvement of abiotic tolerance in crops and particularly in barley.
Multioutlet Hydrants in Mediterranean Pressurized Irrigation Networks: Operation Problems and Hydraulic Characterization
Authors: Balbastre-Peralta Iban , Arviza-Valverde Jaime , Palau Carmen Virginia , González-Pavón Cesar , Manzano-Juárez Juan Manzano
Published: November 2021

Multioutlet hydrants as joint network infrastructure remain briefly addressed in the literature. Studies have always been limited to the individual treatment of the hydraulic components but not as a whole element. This study presents the main problems in the field of multioutlet hydrants within hydraulic infrastructure for pressure irrigation networks in Mediterranean agriculture. First, a field study with interviews was carried out in 30 water users associations (WUAs) between 2010 and 2018. Following this study, a laboratory test methodology was proposed to characterize this type of hydrant. Subsequently, four laboratory tests were performed on 12 multioutlet hydrants with different and common configurations found in irrigation networks: (i) head losses produced, (ii) global measurement precision in the multioutlet hydrant, (iii) blockage analysis in meters in vertical orientation, and (iv) hydrant behavior in response to hydraulic transients. The tests show that a horizontal configuration of the measuring elements with fewer than ten outlets and a suitable dimensioning of elements improve element maneuverability, instrument metrology, and irrigation emission uniformity. Finally, the importance of adequate design, dimensioning, and maintenance of the multioutlet hydrant devices is evidenced as a key point for the adequate management of collective pressure irrigation networks.
Simulating Canopy Temperature Using a Random Forest Model to Calculate the Crop Water Stress Index of Chinese Brassica
Authors: Yang Mingxin , Gao Peng , Zhou Ping , Xie Jiaxing , Sun Daozong , Han Xiongzhe , Wang Weixing
Published: November 2021

The determination of crop water status has positive effects on the Chinese Brassica industry and irrigation decisions. Drought can decrease the production of Chinese Brassica, whereas over-irrigation can waste water. It is desirable to schedule irrigation when the crop suffers from water stress. In this study, a random forest model was developed using sample data derived from meteorological measurements including air temperature (Ta), relative humidity (RH), wind speed (WS), and photosynthetic active radiation (Par) to predict the lower baseline (Twet) and upper baseline (Tdry) canopy temperatures for Chinese Brassica from 27 November to 31 December 2020 (E1) and from 25 May to 20 June 2021 (E2). Crop water stress index (CWSI) values were determined based on the predicted canopy temperature and used to assess the crop water status. The study demonstrated the viability of using a random forest model to forecast Twet and Tdry. The coefficients of determination (R2) in E1 were 0.90 and 0.88 for development and 0.80 and 0.77 for validation, respectively. The R2 values in E2 were 0.91 and 0.89 for development and 0.83 and 0.80 for validation, respectively. Our results reveal that the measured and predicted CWSI values had similar R2 values related to stomatal conductance (~0.5 in E1, ~0.6 in E2), whereas the CWSI showed a poor correlation with transpiration rate (~0.25 in E1, ~0.2 in E2). Finally, the methodology used to calculate the daily CWSI for Chinese Brassica in this study showed that both Twet and Tdry, which require frequent measuring and design experiment due to the trial site and condition changes, have the potential to simulate environmental parameters and can therefore be applied to conveniently calculate the CWSI.
Pigment and Fatty Acid Heterogeneity in the Sea Slug Elysia crispata Is Not Shaped by Habitat Depth
Authors: Vital Xochitl Guadalupe , Rey Felisa , Cartaxana Paulo , Cruz Sónia , Domingues Maria Rosário , Calado Ricardo , Simões Nuno
Published: November 2021

Long-term retention of functional chloroplasts in animal cells occurs only in sacoglossan sea slugs. Analysis of molecules related to the maintenance of these organelles can provide valuable information on this trait (kleptoplasty). The goal of our research was to characterize the pigment and fatty acid (FA) composition of the sea slug Elysia crispata and their associated chloroplasts that are kept functional for a long time, and to quantify total lipid, glycolipid and phospholipid contents, identifying differences between habitats: shallow (0–4 m) and deeper (8–12 m) waters. Specimens were sampled and analyzed after a month of food deprivation, through HPLC, GC-MS and colorimetric methods, to ensure an assessment of long-term kleptoplasty in relation to depth. Pigment signatures indicate that individuals retain chloroplasts from different macroalgal sources. FA classes, phospholipid and glycolipid contents displayed dissimilarities between depths. However, heterogeneities in pigment and FA profiles, as well as total lipid, glycolipid and phospholipid amounts in E. crispata were not related to habitat depth. The high content of chloroplast origin molecules, such as Chl a and glycolipids after a month of starvation, confirms that E. crispata retains chloroplasts in good biochemical condition. This characterization fills a knowledge gap of an animal model commonly employed to study kleptoplasty.
Association of Melatonin Administration in Pregnant Ewes with Growth, Redox Status and Immunity of Their Offspring
Authors: Bouroutzika Efterpi , Ciliberti Maria Giovanna , Caroprese Mariangela , Theodosiadou Ekaterini , Papadopoulos Serafeim , Makri Sotiria , Skaperda Zoi-Vasiliki , Kotsadam Georgios , Michailidis Marios-Lazaros , Valiakos George , Chadio Stella , Kouretas Dimitris , Valasi Irene
Published: November 2021

In this study, the effects of melatonin treatment on growth, redox status and immunity in prenatally stressed newborn lambs were evaluated. Thirty-seven newborn lambs were allocated into two groups (melatonin-MEL and control-CON), based on whether their mothers were treated with melatonin implants or not, respectively. All pregnant ewes were exposed to heat stress. The body weight of lambs was recorded at birth (L0), and then on days 15 (L15) and 40 (L40). Redox biomarkers [total antioxidant capacity (TAC), glutathione (GSH), thiobarbituric acid reactive substances (TBARS)] were assayed in blood samples collected from lambs on days L0, L1, L2, L5, L10 and L40. Chemical analysis and antioxidant capacity were evaluated in colostrum and milk samples collected at the same time points with blood samples. Cytokines (IL-1β, IL-6, IL-10, IFN-γ) and immunoglobulin (IgG) were assayed in blood and colostrum samples collected from ewes on days L0 and L1, and in lambs’ blood on days L0, L1 and L2. The results revealed that body weight gain of newborn lambs did not differ between the two groups (p > 0.05). Better redox status was found in MEL lambs until L2, as well as higher antioxidant capacity in the colostrum of MEL ewes compared to CON ones on day L0 (p < 0.05). In MEL ewes’ colostrum, higher protein content was measured on day L0 and higher fat content on L1 compared to CON group (p < 0.05). The highest level of IL-6 was found in MEL ewes on L1, with a concomitant increase of IL-10 level in MEL lambs in comparison to CON lambs on L2. Moreover, CON colostrum resulted in a higher level of IL-10 within time, coupled with an increased level of IgG found in lambs’ plasma on L2 (p = 0.04). This study indicated that melatonin could be administered as antioxidant and immune-modulatory regime in prenatally stressed offspring in order to cope with the crucial first days of their life. This effect of melatonin was also amplified by crosstalk between IL-6, IL-10 and IgG production, resulting in an improved quality of produced milk.
Antibacterial Effects of Modified Implant Abutment Surfaces for the Prevention of Peri-Implantitis—A Systematic Review
Authors: Jennes Marie-Elise , Naumann Michael , Peroz Simon , Beuer Florian , Schmidt Franziska
Published: November 2021

The aim of the present study was to systematically review studies investigating antibacterial implant abutment surfaces or coatings, which may suppress bacterial growth to prevent plaque-induced peri-implant inflammatory disease. Data were collected after identification of case, assay/laboratory procedure, predicate/reference standard and outcome (CAPO). Seven hundred and twenty (720) records were identified through data base searching. After screening nine publications fulfilled inclusion criteria and were included. The following surfaces/coatings showed antibacterial properties: Electrochemical surface modification of titanium by the anodic spark deposition technique; doxycycline coating by cathodic polarization; silver coating by DC plasma sputter; titanium nitride; zirconium nitride and microwave assistant nano silver coating. Since the current state of the literature is rather descriptive, a meta-analysis was not performed. While several abutment coatings showed to have antibacterial capacity, some of them also influenced the behavior of investigated human cells. None of the studies investigated the long-term effect of surface modifications. Since surface changes are the main contributing factor in the development of antibacterial effects, the biodegradation behavior must be characterized to understand its durability. To date there is no effective structure, material or strategy to avoid peri-implant inflammation used as clinical routine. Furthermore, clinical studies are scarce.
LC-MS/MS-QTOF Screening and Identification of Phenolic Compounds from Australian Grown Herbs and Their Antioxidant Potential
Authors: Ali Akhtar , Bashmil Yasmeen M. , Cottrell Jeremy J. , Suleria Hafiz A. R. , Dunshea Frank R.
Published: November 2021

Culinary spices and herbs have been used to impart a characteristic flavour and aroma in food due to their appealing fragrance. Recently, bioactive compounds from herbs, especially phenolics, have gained much attention due to their potential health outcomes. The aim of this study was to characterize and quantify the phenolic compounds from 10 widely used Australian-grown herbs (oregano, rosemary, bay, basil, sage, fenugreek, dill, parsley, mint and thyme). For this purpose, liquid chromatography mass spectrometry (LC-MS) was used for the complete profiling of polyphenolic compounds and quantification of abundant phenolic compounds was completed with high-performance liquid chromatography—photodiode array detection (HPLC-PDA). Polyphenols from Australian-grown herbs were estimated through total phenolic content (TP), total flavonoids (TF) and total tannins (TT) along with their in-vitro antioxidant activities. Oregano and mint were estimated with the highest value of TP (140.59 ± 9.52 and 103.28 ± 8.08 mg GAE/g, milligram gallic acid equivalent/gram) while rosemary and mint had the highest TF (8.19 ± 0.74 and 7.05 ± 0.43 mg QE (quercetin equivalent)/g). In this study, eighty-four (84) phenolic compounds were screened and confirmed through LC-MS/MS by comparing their masses and fragmentation pattern with published libraries. The results of this study validate the use of these herbs as bioactives and their positive impact on human health.
Exploring the Chemical Profiles and Biological Values of Two Spondias Species (S. dulcis and S. mombin): Valuable Sources of Bioactive Natural Products
Authors: Sinan Kouadio Ibrahime , Zengin Gokhan , Zheleva-Dimitrova Dimitrina , Gevrenova Reneta , Picot-Allain Marie Carene Nancy , Dall’Acqua Stefano , Behl Tapan , Goh Bey Hing , Ying Patrick Tang Siah , Mahomoodally Mohamad Fawzi
Published: November 2021

Spondias species have been used in traditional medicine for different human ailments. In this study, the effect of different solvents (ethyl acetate, methanol, and water) and extraction methods (infusion, maceration, and Soxhlet extraction) on the enzyme inhibitory activity against acetylcholinesterase, butyrylcholinesterase, tyrosinase, α-amylase, α-glucosidase, and antioxidant properties of S. mombin and S. dulcis leaves and stem bark were evaluated. Ultra-high-performance liquid chromatography–high resolution mass spectrometry (UHPLC-HRMS) yield in the identification and/or annotation of 98 compounds showing that the main secondary metabolites of the plant are gallic and ellagic acids and their derivatives, ellagitannins, hydroxybenzoic, hydroxycinnamic, acylquinic acids and flavonols, flavanones, and flavanonols. The leaves infusion of both Spondias species showed highest inhibition against acetylcholinesterase (AChE) (10.10 and 10.45 mg galantamine equivalent (GALAE)/g, for S. dulcis and S. mombin, respectively). The ethyl acetate extracts of the stem bark of S. mombin and S. dulcis actively inhibited α-glucosidase. Methanolic extracts of the leaves and stem bark exhibited highest tyrosinase inhibitory action. Antioxidant activity and higher levels of phenolics were observed for the methanolic extracts of Spondias. The results suggested that the Spondias species could be considered as natural phyto-therapeutic agents in medicinal and cosmeceutical applications.
Assembly Quality Detection Based on Class-Imbalanced Semi-Supervised Learning
Authors: Lu Zichen , Jiang Jiabin , Cao Pin , Yang Yongying
Published: November 2021

Due to the imperfect assembly process, the unqualified assembly of a missing gasket or lead seal will affect the product’s performance and possibly cause safety accidents. Machine vision method based on deep learning has been widely used in quality inspection. Semi-supervised learning (SSL) has been applied in training deep learning models to reduce the burden of data annotation. The dataset obtained from the production line tends to be class-imbalanced because the assemblies are qualified in most cases. However, most SSL methods suffer from lower performance in class-imbalanced datasets. Therefore, we propose a new semi-supervised algorithm that achieves high classification accuracy on the class-imbalanced assembly dataset with limited labeled data. Based on the mean teacher algorithm, the proposed algorithm uses certainty to select reliable teacher predictions for student learning dynamically, and loss functions are modified to improve the model’s robustness against class imbalance. Results show that when only 10% of the total data are labeled, and the imbalance rate is 5.3, the proposed method can improve the accuracy from 85.34% to 93.67% compared to supervised learning. When the amount of annotated data accounts for 20%, the accuracy can reach 98.83%.
An Optimized System to Reduce Procurement Risks and Stock-Outs: A Simulation Case Study for a Component Manufacturer
Authors: Gallego-García Diego , Gallego-García Sergio , García-García Manuel
Published: November 2021

In the current global system; supply chains are at risk due to increasing procurement shortages, supply disruptions, and the reliability of on-time deliveries with the original order quantities. As a result, an anticipated management model is of vital importance to provide companies with the productive flexibility necessary to adapt quickly to supply changes, in order to ensure the quality and delivery time through efficient management of stocks and supply costs. In this context, this research aims to develop a system to complement classical procurement planning based on inventory management methods and MRP (material requirements planning) systems by considering suppliers’ behavior regarding procurement risks. For this purpose, a system is developed that seeks to simulate the impacts of procurement shortages of different natures. Moreover, the research investigates the development of a system that performs procurement planning of a component manufacturer to determine the supply orders necessary to meet the master production schedule. The system is analyzed based on a set of indicators in the event that the supplier of a material needed for production does not supply on time or has short-term problems. Several scenarios are simulated, and the results are quantified by changing the procurement order quantities, which may or may not follow the economic order quantity (EOQ) model, and the potential procurement disruptions or shortages. The results show how the simulation and anticipation of potential suppliers’ procurement behavior concerning potential shortages and their probability are key for successful procurement within a joint strategy with classical procurement methods.
Efficient Use of GPU Memory for Large-Scale Deep Learning Model Training
Authors: Choi Hyeonseong , Lee Jaehwan
Published: November 2021

To achieve high accuracy when performing deep learning, it is necessary to use a large-scale training model. However, due to the limitations of GPU memory, it is difficult to train large-scale training models within a single GPU. NVIDIA introduced a technology called CUDA Unified Memory with CUDA 6 to overcome the limitations of GPU memory by virtually combining GPU memory and CPU memory. In addition, in CUDA 8, memory advise options are introduced to efficiently utilize CUDA Unified Memory. In this work, we propose a newly optimized scheme based on CUDA Unified Memory to efficiently use GPU memory by applying different memory advise to each data type according to access patterns in deep learning training. We apply CUDA Unified Memory technology to PyTorch to see the performance of large-scale learning models through the expanded GPU memory. We conduct comprehensive experiments on how to efficiently utilize Unified Memory by applying memory advises when performing deep learning. As a result, when the data used for deep learning are divided into three types and a memory advise is applied to the data according to the access pattern, the deep learning execution time is reduced by 9.4% compared to the default Unified Memory.
Long-Range Dependence and Multifractality of Ship Flow Sequences in Container Ports: A Comparison of Shanghai, Singapore, and Rotterdam
Authors: Liu Chan-Juan , Wu Jinran , Jayetileke Harshanie Lakshika , Hu Zhi-Hua
Published: November 2021

The prediction of ship traffic flow is an important fundamental preparation for layout and design of ports as well as management of ship navigation. However, until now, the temporal characteristics and accurate prediction of ship flow sequence in port are rarely studied. Therefore, in this study, we investigated the presence of long-range dependence in container ship flow sequences using the Multifractal Detrended Fluctuation Analysis (MF-DFA). We considered three representative container ports in the world—including Shanghai, Singapore, and Rotterdam container ports—as the study sample, from 1 January 2013 to 31 December 2017. Empirical results suggested that the ship flow sequences are deviated from normal distribution, and the sequences with different time scales exhibited varying degrees of long-range dependence. Furthermore, the ship flow sequences possessed a multifractal nature, where the larger the time scale of ship flow time series, the stronger the multifractal characteristics are. The weekly ship flow sequence in the port of Singapore owned the highest degree of multifractality. Furthermore, the multifractality presented in the ship flow sequences of container ports are due to the correlation properties as well as the probability density function of the ship flow sequences. The study outlines the importance of adopting these features for an accurate modeling and prediction for maritime ship flow series.
A Brief Review on Challenges in Design and Development of Nanorobots for Medical Applications
Authors: Giri Gautham , Maddahi Yaser , Zareinia Kourosh
Published: November 2021

Robotics is a rapidly growing field, and the innovative idea to scale down the size of robots to the nanometer level has paved a new way of treating human health. Nanorobots have become the focus of many researchers aiming to explore their many potential applications in medicine. This paper focuses on manufacturing techniques involved in the fabrication of nanorobots and their associated challenges in terms of design architecture, sensors, actuators, powering, navigation, data transmission, followed by challenges in applications. In addition, an overview of various nanorobotic systems addresses different architectures of a nanorobot. Moreover, multiple medical applications, such as oncology, drug delivery, and surgery, are reviewed and summarized.
Estimation of Skid-Steered Wheeled Vehicle States Using STUKF with Adaptive Noise Adjustment
Authors: Zhang Xing , Yuan Shihua , Yin Xufeng , Li Xueyuan , Qu Xinyi , Liu Qi
Published: November 2021

Skid-steered wheeled vehicles are commonly adopted in outdoor environments with the benefits of mobility and flexible structure. However, different from Ackerman turning vehicles, skid-steered vehicles do not possess geometric constraint but only dynamic constraint when steered, which leads to motion control and state estimation problems for skid-steered vehicles. The controlling accuracy of a skid-steered vehicle depends largely on feedback state information from sensors and an observer. In this study, a 3-DOF dynamic model using a Brush nonlinear tire model is built, first, to model a 6 × 6 skid-steered wheeled vehicle in flat ground driving conditions. Then, an observer using the unscented Kalman filter with a strong tracking algorithm and adaptive noise matrix adjustment (AN-STUKF) is established to estimate vehicle motion states based on the 3-DOF dynamic model. Finally, the experiment is carried out in three different driving conditions to verify the accuracy and stability of the proposed method. The results show that the AN-STUKF method possesses better accuracy and tracking rate than the traditional UKF, and the phenomenon of ICRs shifting forward of the skid-steered wheeled vehicle is also verified.
One-Dimensional Mathematical Model for Kayak Propulsion
Authors: Delgado Diego , Ruiz Camilo
Published: November 2021

The displacement of a sprint kayak can be described by a one-dimensional mathematical model, which, in its simplest case, is analogous to the free-fall problem with quadratic drag and constant propulsion. To describe realistic cases, it is necessary to introduce a propulsion capable of reproducing the characteristics of the kayak stroke, including periodicity, average force and effects of stroke frequency, among others. Addressing the problem in terms of a Fourier series allows us to separate the equation into two parts, one of which is equivalent to the constant propulsion case and results in an asymptotic expression, while the second accounts for the periodic contributions. This approach allows us to solve several cases of interest: to propose a quadrature rule for the asymptotic part that allows fast estimations; to compare results with the literature; and finally to propose a general mathematical method for this problem which could help to understand some key strategies in the kayak race.
Influence of Spectral Filtration on Pulse Dynamics in Ring-Cavity Mamyshev Oscillator
Authors: Bednyakova Anastasia , Kuprikov Evgeny , Geraseva Irina , Kokhanovskiy Alexey
Published: November 2021

Here we present a numerical study of pulsing build-up dynamics inside the fiber Mamyshev Oscillator (MO). The main scope of the investigation is to describe the influence of the spectral separation between the filters on self-starting MO dynamics and transition from multipulse to single-pulse generation regimes. It was found that Floquet stability analysis provides a straightforward way to determine whether the system will be self-starting or if it has to be excited by external source and predicts the repetition rate of the pulse train. We showed that spectrally overlapped bandpass filters provide reliable multi-pulse generation due to Faraday instability. Adiabatic increase in the spectral separation between the filters decreases the number of pulses down to single-pulse regime, therefore providing a flexible way to generate adjustable number of mode-locked pulses on demand.
Economic Impact Analysis of the Application of Different Pavement Performance Models on First-Class Roads with Selected Repair Technology
Authors: Kozel Matúš , Remek Ľuboš , Ďurínová Michaela , Šedivý Štefan , Šrámek Juraj , Danišovič Peter , Hostačná Vladimíra
Published: November 2021

Mathematical expression of the deterioration of individual pavement parameters is, from the point of optimal repair and maintenance strategy decision-making process, an important part of the application of any pavement management system (PMS). The reliability of individual PMS depends on the quality of the inputs and the reliability of its internal sub-systems; thus, deterioration equations derived from high-quality input data play pivotal roles in a system for the prediction of the pavement life cycle. This paper describes the application of pavement performance models within pavement life cycle analysis (LCA) with the use of the integrated system of economic evaluation (ISEH), which is a calculation tool used for first-class roads with a standardized pavement composition of asphalt binders, where changes in operational capability parameters are modeled using individual model simulations. The simulations presented in this paper demonstrate changes in main economic indicators (net present value and internal rate of return) on two different pavement performance models. Both simulations share the same input parameters (traffic intensity, construction intervention, maintenance costs, discount rate) but differ in deterioration evaluation, all of which were applied to each model (a total of five models).