bluuebunny/crossref_metadata_2025 huggingface dataset:
Trinity: Neural Network Adaptive Distributed Parallel Training Method Based on Reinforcement Learning
Authors: Zeng Yan , Wu Jiyang , Zhang Jilin , Ren Yongjian , Zhang Yunquan
Published: March 2022

Deep learning, with increasingly large datasets and complex neural networks, is widely used in computer vision and natural language processing. A resulting trend is to split and train large-scale neural network models across multiple devices in parallel, known as parallel model training. Existing parallel methods are mainly based on expert design, which is inefficient and requires specialized knowledge. Although automatically implemented parallel methods have been proposed to solve these problems, these methods only consider a single optimization aspect of run time. In this paper, we present Trinity, an adaptive distributed parallel training method based on reinforcement learning, to automate the search and tuning of parallel strategies. We build a multidimensional performance evaluation model and use proximal policy optimization to co-optimize multiple optimization aspects. Our experiment used the CIFAR10 and PTB datasets based on InceptionV3, NMT, NASNet and PNASNet models. Compared with Google’s Hierarchical method, Trinity achieves up to 5% reductions in runtime, communication, and memory overhead, and up to a 40% increase in parallel strategy search speeds.
Editorial Paper for the Special Issue “Algorithms in Hyperspectral Data Analysis”
Authors: Pizzolante Raffaele
Published: March 2022

This Special Issue contains four papers focused on hyperspectral data analysis [...]
An Analysis of Fixed-Wing Stall-Type Accidents in the United States
Authors: Fala Nicoletta
Published: March 2022

Spin training has not been required for students working towards their private or commercial certificates for the past 70 years. Switching to a stall-prevention mindset within training aimed to make spin recovery unnecessary; however, stall-type accidents, consisting of stalls, spins, and spirals, still occur and are highly fatal. Although past studies have analyzed accidents, interviewed pilots at different levels, and made recommendations for changes in the industry, stall-type accidents are no less fatal now, at a fatality ratio of approximately 40–50% yearly. The research discussed in this paper aims to summarize and present accident stall-type statistics in aggregate over the past five decades and motivate future pilot- and training-centered research to address the high presence of stall-type accidents in aviation. Specifically, this article uses NTSB accident reports to answer the research question of whether there have been changes in the prevalence of spins among both fatal and non-datal fixed-wing accidents in the United States over the past sixty years. The methodology breaks down the accident analysis in three groups, based on the time period in which they occurred, due to differences in the reporting methods used. This paper finds that the prevalence and fatality ratio of stall-type accidents has remained high over the past six decades and that stall-type accidents are more than twice as fatal as an average accident. To remedy the high accident count, we recommend experimental ground and simulator-based training to improve pilot knowledge, skill, and performance.
Prediction of Harvest Time of Tomato Using Mask R-CNN
Authors: Minagawa Daichi , Kim Jeyeon
Published: March 2022

In recent years, the agricultural field has been confronting difficulties such as the aging of farmers, a shortage of workers, and difficulties for new farmers. Harvesting time prediction has the potential to solve these problems, and is expected to effectively utilize human resources, save labor, and reduce labor costs. To achieve harvesting time prediction, various works are being actively conducted. Methods for harvesting time prediction using meteorological information such as temperature and solar radiation, etc., and methods for harvesting time prediction using neural networks based on color information from fruit bunch images are being investigated. However, the prediction accuracy is still insufficient, and the harvesting time prediction for individual tomato fruits has not been studied. In this study, we propose a novel method to predict the harvesting time for individual tomato fruits. The method uses Mask R-CNN to detect tomato bunches and uses two types of ripeness determination to predict the harvesting time of individual tomato fruits. The experimental results showed that the accuracy of the prediction using the ratio of R values was better for the harvesting time prediction of tomatoes that are close to the harvesting time, and the accuracy of the prediction using the average of the differences between R and G in RGB values was better for the harvesting time prediction of tomatoes that are far from the harvesting time. These results show the effectiveness of the proposed method.
Waterlogging Stress Physiology in Barley
Authors: De Castro James , Hill Robert D. , Stasolla Claudio , Badea Ana
Published: March 2022

Barley (Hordeum vulgare L.) is the most susceptible cereal species to excess moisture stress. Waterlogging-induced hypoxia causes major morphological, physiological, and metabolic changes, some of which are regulated by the action of plant growth regulators and signal molecules including nitric oxide. Recent studies have evidenced the participation of phytoglobins in attenuating hypoxic stress during conditions of excessive moisture through their ability to scavenge nitric oxide and influence the synthesis and response of growth regulators. This review will highlight major cellular changes linked to plant responses to waterlogging stress with emphasis on phytoglobins.
The Posttranscriptional Mechanism in Salvia miltiorrhiza Bunge Leaves in Response to Drought Stress Using Phosphoproteomics
Authors: Zhang Jin , Li Jingyu , Su Yuekai , Song Zhenqiao , Wang Jianhua
Published: March 2022

Drought stress is a major constraint to the quality and production of Salvia miltiorrhiza Bunge (Danshen). This study aimed to investigate the posttranslational molecular mechanisms in S. miltiorrhiza leaves in response to drought stress using quantitative phosphoproteomics analysis. S. miltiorrhiza plants were stressed by withholding water for two (moderate drought stress) and four weeks (high drought stress). Leaf samples were prepared with tandem mass tag labeling. Liquid chromatography-tandem mass spectrometry was performed for the quantitative phosphoproteomics. Bioinformatics methods were used to identify the phosphosites and phosphoproteins that had significantly changed phosphorylation levels upon drought stresses. A total of 119 common phosphoproteins were significantly changed by both high and moderate drought stresses. The phosphorylation levels of proteins related to protein processing, photosynthesis, RNA binding, and splicing were significantly changed upon high drought, not moderate drought. Additionally, we identified that the Ser phosphorylation levels of most proteins related to terpene metabolism and RNA splicing were regulated by drought stresses. The Ser and Thr phosphorylation levels of energy metabolism proteins (including FBA2/8, PPC4, and PPCC) and heat shock proteins (including HSP70 and HSP90) were upregulated by drought stresses. Our study showed the posttranscriptional mechanisms in S. miltiorrhiza leaves in response to drought stress.
Calibration of Near-Infrared Spectra for Phosphorus Fractions in Grassland Soils on the Tibetan Plateau
Authors: Cao Zuonan , Kühn Peter , He Jin-Sheng , Bauhus Jürgen , Guan Zhen-Huan , Scholten Thomas
Published: March 2022

Soil phosphorus (P) is essential for plant growth and influences biological processes. Determining the amounts of available P to plants has been challenging, and many different approaches exist. The traditional Hedley sequential extraction method and its subsequent modification are applied to determine different soil P forms, which is critical for understanding its dynamics and availability. However, quantifying organic and inorganic P (Po & Pi) in different extracts is labor-intensive and rarely used with large sample numbers. As an alternative, near-infrared spectroscopy (NIRS) has been employed to determine different P fractions at reasonable costs in a short time. This study aimed to test whether the analysis of P fractions with NIRS is an appropriate method to disentangle the effects of P limitation on high-altitude grassland ecosystems, particularly with fertilizer amendments. We explored NIRS in soils from the grassland soil samples on the northern Tibetan Plateau. First, we extracted the P fractions of 191 samples from the Haibei Alpine Meadow Ecosystem Research Station at four depth increments (0–10 cm, 10–20 cm, 20–40 cm, and 40–70 cm), including nutrient additions of nitrogen (N) and P. We compared the results of the Hedley extraction with the laboratory-based NIRS model. The fractionation data were correlated with the corresponding NIRS soil spectra; the coefficient of determination (R2) of the NIRS calibrations to predict P in P fractions ranged between 0.12 and 0.90; the ratio of (standard error of) prediction to the standard deviation (RPD) ranged between 1.07 and 3.21; the ratio of performance to inter-quartile distance (RPIQ) ranged from 0.3 to 4.3; and the model prediction quality was higher for Po than Pi fractions, and decreased with fertilizer amendment. However, the external-validation results were not precise enough for the labile P fractions (RPD < 1.4) due to the limited number of samples. The results indicate that using NIRS to predict the more stable P pools, combined with Hedley fractionation focusing on the labile P pool, can be a promising approach for soils in alpine grasslands on the Tibetan Plateau.
Does Phosphorus Fertilization Increase Biomass Production and Salinity Tolerance of Blue Panicum (Panicum antidotale Retz.) in the Salt-Affected Soils of Arid Regions?
Authors: Bouras Hamza , Choukr-Allah Redouane , Mosseddaq Fatema , Bouaziz Ahmed , Devkota Krishna Prasad , Mouttaqi Ayoub El , Bouazzama Bassou , Hirich Abdelaziz
Published: March 2022

High soil salinity, drought, and poor soil fertility, especially phosphorus (P) deficiency, are serious challenges for crop production in arid and desert climate regions. In these regions, irrigation water (mostly groundwater) is saline, and fertilization is one of the strategies used to cope with salinity stress. Crop livestock is one of the major agricultural activities in marginal regions, and blue panicum (Panicum antidotale Retz.), the perennial forage grass, has the potential to furnish forage demand. Thus, a field experiment testing the combination of three levels of irrigation water salinity and three P rate was carried out to evaluate the potential of P fertilizer to enhance yield and salinity tolerance of blue panicum grass. The experiment was conducted for two years between 2019 and 2020 in Foum el Oued, Laayoune, Morocco. It was implemented in a split-plot design with three replications considering irrigation water salinity as the main plot and P rates as sub-plot treatments. The evaluated P rates were 0, 90, and 108 kg P2O5 ha−1 (P1, P2, and P3, respectively), and the irrigation water salinities were 5, 12, and 17 dS·m−1. The results revealed that increasing irrigation water salinity significantly decreased the biomass production and stomatal conductance of blue panicum. Increasing irrigation water salinity from 5 to 12 and 17 dS·m−1 decreased fresh biomass production by 20 and 29%, respectively. Irrigation water salinity also decreased (p < 0.05) leaf N, P, K, Ca, and Zn concentration. However, supplementation of P fertilization enhanced (p < 0.05) biomass production and stomatal conductance mainly by improving leaf OM, Zn, and Fe content. P fertilization at 108 kg P2O5 ha−1 increased fresh biomass by 27%, 32%, and 19% under 5, 12, and 17 dS·m−1, respectively. Considering increased fresh biomass yield, P application at the rate of 108 kg P2O5 ha−1 can be suggested for saline drylands. P application is recommended to reduce the adverse effects of high salinity on growth and productivity and improve salinity tolerance of blue panicum in salt-affected arid and desert regions.
Water Yam (Dioscorea alata L.) Growth and Tuber Yield as Affected by Rotation and Fertilization Regimes across an Environmental Gradient in West Africa
Authors: Pouya Nestor , Hgaza Valérie Kouamé , Kiba Delwendé Innocent , Bomisso Lezin , Aighewi Beatrice , Aké Sévérin , Frossard Emmanuel
Published: March 2022

Yam (Dioscorea spp.) is a staple food crop and a source of income for millions of people in West Africa. Traditionally, in West Africa, yams are grown without any external inputs, leading to low tuber yields. The rapid decrease of tuber yield observed after the first yam cropping season has been ascribed to nutrient depletion and/or to the accumulation of yam-specific pests and diseases. This has led farmers to grow yam on new surfaces under fallow each year. Using a transdisciplinary approach, we identified different yam-based rotations and fertilization regimes that could stabilize yam production in rotational cropping systems and improve water yam (D. alata) productivity. These innovations were tested in researcher-managed field trials established along an environmental gradient crossing four yam growing zones spanning from the Humid Forest (Liliyo in Côte d’Ivoire) to the Derived Savanna/Forest Transition (Tiéningboué in Côte d’Ivoire), the Southern Guinean Savanna (Midebdo in Burkina Faso), and the Northern Guinean Savanna (Léo in Burkina Faso) between 2016 and 2018. The fertilization factor implemented at each site included a control with no fertilization (NON), sole mineral fertilization as NPK (MIN), combined organic and mineral fertilization (MINORG) and sole organic fertilization as manure (ORG), while the rotation factor included water yam in rotation with cereal (YamCer), legume (YamLeg), and white yam (YamYam). The average water yam tuber yields were 32.8, 20.3, 2.7, and 2.5 t fresh matter ha−1 in 2016, and 16.4, 10.7, 8.9, and 5.2 t fresh matter ha−1 in 2018 in Liliyo, Tiéningboué, Midebdo, and Léo, respectively. The most important determinants of tuber yields were the total amount of rainfall recorded during the yam growing period and between tuber initiation and maximum canopy development, and the soil carbon stocks in the 0–30-cm layer. We confirmed in this study that soil surface coverage measured between 70 and 98 days after planting was an early indicator of tuber yield. Fertilization impacted positively the soil surface cover but had a weak impact on tuber yields. Rotation had no impact on either the soil surface cover or tuber yields. This lack of observable impacts was partly due to the very large variability of tuber yields, to the variable rainfall, and to an anthracnose attack in two sites in 2018. The impacts of fertilization and rotation on yam yields should be studied over longer periods. This is, to our knowledge, the first publication showing the relative impacts of site-specific properties (rainfall and soil carbon stocks) versus management practices on water yam yield along an environmental gradient going across the West African yam belt.
Green Corridors May Sustain Habitats for Earthworms in A Partially Converted Grassland
Authors: Simon Barbara , Boziné Pullai Krisztina , Selmeczi Dóra , Sebők András , Tóthné Bogdányi Franciska , Weldmichael Tsedekech G. , Zalai Mihály , Nsima Justine Phenson , Tóth Ferenc
Published: March 2022

Permanent grasslands provide a healthy and undisturbed environment. We investigated how mulching altered the soil physicochemical parameters, earthworm abundance, biomass, species composition and vegetation cover compared to grassland and cultivated alfalfa field. Microplots (2 × 2 m) were mulched with either weed control fabric (WF) alone or WF combined with straw (WF + S) on a grassland to grow tomato in Ősagárd (Nógrád county, Hungary) between 2018 and 2021. We had two other microhabitats: a conventionally cultivated alfalfa field (CA) and grassland (GR). We measured soil parameters (physical: soil moisture content (SMC), soil penetration resistance (SPR); chemical: pH, soil organic matter; and biological: earthworm abundance, biomass, species composition and vegetation). SMC was significantly higher on covered plots (WF; WF + S) compared to CA and GR. SPR values were the highest in CA and GR at 20 cm depth. The abundance and biomass of earthworms were the highest in GR and lowest in CA in all seasons. Plant abundance was highly influenced by season and habitat. Despite the higher compaction and lower SMC figures, grass vegetation still provided a more suitable environment for earthworms than mulched plots (WF, WF + S). Therefore, where there is agricultural production on grassland, we suggest leaving uncultivated and uncovered patches as biodiversity corridors.
Nutrient Release Dynamics in Argentinean Pampean Soils Amended with Composts under Laboratory Conditions
Authors: Orden Luciano , Iocoli Gastón A. , Bustamante María Ángeles , Moral Raúl , Rodríguez Roberto A.
Published: March 2022

Composted manure is the greatest nitrogen (N) source in organic agriculture, where the use of chemical fertilizers, except the use of rock phosphate as P source, is not allowed. The aim of this study was to evaluate the effect of the soil type and compost characteristics on the potential rates of mineralization and on the kinetics of the nitrogen (N), phosphorus (P), and carbon (C) release patterns. For this, an aerobic incubation study was conducted over the course of 119 days at 25 °C using two different composts as amendments: a compost from biosolids and wood shavings (CRUB), and a compost from poultry manure with wheat straw (CSP). The composts were incorporated into two different soils of contrasting texture, sandy loam (S1) and silty clay loam (S2), at the dose of 160 kg N ha−1. Samples were collected eight times during the incubation period. The N and C dynamics were studied separately according to the different soil type. In both soils, a predominance of the nitrification process immediately after compost application was observed, showing a higher mineralization in the sandy loam soil, this trend being followed by a decrease and even an immobilization process, associated with stable organic materials such as compost. Moreover, both composts presented high contents of available P, but without exceeding 50 mg P kg−1, due to the slow release from the stable organic P fractions present in compost. The results obtained showed that despite the initial mineralization, both composts showed a significant period of N immobilization after their application into the pampean soils, which makes it necessary to anticipate their incorporation to avoid this lack period for crops. Furthermore, the application of these composts to the pampean soils implied an incorporation of available P, but with a slow release that avoided overfertilization, but also reducing N:P ratio and producing a relative deficit of N. Therefore, the results obtained suggested that it is necessary to study nutrient mineralization processes of the amendments prior to their use, according to the edaphoclimatic condition of each crop, in order to predict the release dynamics on soils and the fertilization potential to minimize potential environmental impacts.
Emerging Role of Antibody-Drug Conjugates and Bispecific Antibodies for the Treatment of Multiple Myeloma
Authors: Tai Waqqas , Wahab Ahsan , Franco Diana , Shah Zunairah , Ashraf Aqsa , Abid Qurrat-Ul-Ain , Mohammed Yaqub Nadeem , Lal Darshan , Anwer Faiz
Published: March 2022

Multiple myeloma (MM) is characterized by malignant proliferation of malignant plasma cells; it is the second most common hematological malignancy associated with significant morbidity. Genetic intricacy, instability, and diverse clinical presentations remain a barrier to cure. The treatment of MM is modernized with the introduction of newer therapeutics agents, i.e., target-specific monoclonal antibodies. The currently available literature lacks the benefits of newer targeted therapy being developed with an aim to reduce side effects and increase effectiveness, compared to conventional chemotherapy regimens. This article aims to review literature about the current available monoclonal antibodies, antibody-drug conjugates, and bispecific antibodies for the treatment of MM.
Population Pharmacokinetic Model of Piperacillin in Critically Ill Patients and Describing Interethnic Variation Using External Validation
Authors: Sanches Cristina , Alves Geisa C. S. , Farkas Andras , da Silva Samuel Dutra , de Castro Whocely Victor , Chequer Farah Maria Drummond , Beraldi-Magalhães Francisco , Magalhães Igor Rafael dos Santos , Baldoni André de Oliveira , Chatfield Mark D. , Lipman Jeffrey , Roberts Jason A. , Parker Suzanne L.
Published: March 2022

Objectives: This study aimed to develop a piperacillin population PK model for critically ill Brazil-ian patients and describe interethnic variation using an external validation. Methods: Plasma samples were obtained from 24 ICU patients during the fifth day of piperacillin treatment and assayed by HPLC-UV. Population pharmacokinetic modelling was conducted using Pmetrics. Empiric dose of 4 g IV 6- and 8-hourly were simulated for 50 and 100% fT > MIC and the probabil-ity of target attainment (PTA) and the fractional target attainment (FTA) determined. Results: A two-compartment model was designed to describe the pharmacokinetics of critically ill Brazillian patients. Clearance and volume of distribution were (mean ± SD) 3.33 ± 1.24 L h−1 and 10.69 ± 4.50 L, respectively. Creatinine clearance was positively correlated with piperacillin clearance and a high creatinine clearance was associated with lower values of PTA and FTA. An external vali-dation was performed using data from two different ethnic ICU populations (n = 30), resulting in acceptable bias and precision. Conclusion: The primary pharmacokinetic parameters obtained from critically ill Brazilian patients were similar to those observed in studies performed in critically ill patients of other ethnicities. Based on our results, the use of dose adjustment based on creati-nine clearance is required in Brazilian patients.
Synthesis of Metal-Loaded Carboxylated Biopolymers with Antibacterial Activity through Metal Subnanoparticle Incorporation
Authors: Noori Farzaneh , Megoura Meriem , Labelle Marc-André , Mateescu Mircea Alexandru , Azzouz Abdelkrim
Published: March 2022

Carboxymethyl starch (CMS) and carboxymethyl cellulose (CMC) loaded by highly dispersed metal subnanoparticles (MSNPs) showed antibacterial activity against E. coli and B. subtilis strains. Copper and silver were found to act in both cationic and zero-valence forms. The antibacterial activity depends on the metal species content but only up to a certain level. Silver cation (Ag+) showed higher antibacterial activity as compared to Ag0, which was, however, more effective than Cu0, due to weaker retention. The number of carboxyl groups of the biopolymers was found to govern the material dispersion in aqueous media, the metal retention strength and dispersion in the host-matrices. Cation and metal retention in both biopolymers was found to involve interactions with the oxygen atoms of both hydroxyl and carboxyl groups. There exists a ternary interdependence between the Zeta potential (ZP), pH induced by the biocidal agent and its particle size (PS). This interdependence is a key factor in the exchange processes with the surrounding species, including bacteria. Clay mineral incorporation was found to mitigate material dispersion, due to detrimental competitive clay:polymer interaction. This knowledge advancement opens promising prospects for manufacturing metal-loaded materials for biomedical applications.
Social Media and COVID-19—Perceptions and Public Deceptions of Ivermectin, Colchicine and Hydroxychloroquine: Lessons for Future Pandemics
Authors: Schellack Natalie , Strydom Morné , Pepper Michael S. , Herd Candice L. , Hendricks Candice Laverne , Bronkhorst Elmien , Meyer Johanna C. , Padayachee Neelaveni , Bangalee Varsha , Truter Ilse , Ellero Andrea Antonio , Myaka Thulisa , Naidoo Elysha , Godman Brian
Published: March 2022

The capacity for social media to influence the utilization of re-purposed medicines to manage COVID-19, despite limited availability of safety and efficacy data, is a cause for concern within health care systems. This study sought to ascertain links between social media reports and utilization for three re-purposed medicines: hydroxychloroquine (HCQ), ivermectin and colchicine. A combined retrospective analysis of social media posts for these three re-purposed medicines was undertaken, along with utilization and clinical trials data, in South Africa, between January 2020 and June 2021. In total, 77,257 posts were collected across key social media platforms, of which 6884 were relevant. Ivermectin had the highest number of posts (55%) followed by HCQ (44%). The spike in ivermectin use was closely correlated to social media posts. Similarly, regarding chloroquine (as HCQ is not available in South Africa), social media interest was enhanced by local politicians. Sentiment analysis revealed that posts regarding the effectiveness of these repurposed medicines were positive. This was different for colchicine, which contributed only a small number of mentions (1%). Of concern is that the majority of reporters in social media (85%) were unidentifiable. This study provides evidence of social media as a driver of re-purposed medicines. Healthcare professionals have a key role in providing evidence-based advice especially with unidentifiable posts.
What Are the Potential Benefits of Using Bacteriophages in Periodontal Therapy?
Authors: Kowalski Jan , Górska Renata , Cieślik Martyna , Górski Andrzej , Jończyk-Matysiak Ewa
Published: March 2022

Periodontitis, which may result in tooth loss, constitutes both a serious medical and social problem. This pathology, if not treated, can contribute to the development of, among others, pancreatic cancer, cardiovascular diseases or Alzheimer’s disease. The available treatment methods are expensive but not always fully effective. For this reason, the search for and isolation of bacteriophages specific to bacterial strains causing periodontitis seems to be a great opportunity to target persistent colonization by bacterial pathogens and lower the use of antibiotics consequently limiting further development of antibiotic resistance. Furthermore, antimicrobial resistance (AMR) constitutes a growing challenge in periodontal therapy as resistant pathogens may be isolated from more than 70% of patients with periodontitis. The aim of this review is to present the perspective of phage application in the prevention and/or treatment of periodontitis alongside its complicated multifactorial aetiology and emphasize the challenges connecting composition and application of effective phage preparation.
Efficacy of Antioxidant Supplementation to Non-Surgical Periodontal Therapy on Metabolic Control in Type 2 Diabetes Patients: A Network Meta-Analysis
Authors: Araújo Elisa Grillo , Oliveira Domitilla Marchiori Sant’Anna Leal de , Martins Carolina Castro , Stefani Cristine Miron
Published: March 2022

This network meta-analysis (NMA) investigated the effectiveness of antioxidants as adjuncts to non-surgical periodontal therapy (NSPT) in the glycated hemoglobin (HbA1c) control of type 2 diabetes (T2D) patients with periodontitis. PubMed, Cochrane, LILACS, Web of Science, Scopus, Embase, LIVIVO, and grey literature were searched. Risk of bias was assessed with the RoB v2.0 tool. A frequentist NMA assessed HbA1c improvement, through standardized mean difference under a random-effects model. Certainty of evidence was addressed through the GRADE (Grading of Recommendations, Assessment, Development and Evaluations) partially contextualized framework. Ten randomized controlled clinical trials were included, with 234 patients receiving alpha lipoic acid (ALA), cranberry juice, cranberry juice enriched with omega-3, fenugreek, ginger, grape seed, lycopene, melatonin, omega-3, propolis or vitamin C supplementation to NSPT, and 220 patients receiving NSPT alone or with placebo. Nine studies were meta-analyzed. HbA1c improved when NSPT was combined with propolis, ALA and melatonin supplementation (moderate-to-low certainty), compared to NSPT alone or with placebo. Risk of bias issues were found in eight studies. In conclusion, the use of propolis supplementation to NSPT probably results in HbA1c improvement in T2D patients with periodontitis (large effect with moderate certainty), while ALA and melatonin supplementation may contribute to reduce the HbA1c in T2D patients with periodontitis (large effects with low certainty).
Low-Cost Underwater Communication System: A Pilot Study
Authors: Szlachetko Boguslaw
Published: March 2022

The aim of the paper is to present a simplified implementation of quadrature phase shift keying (QPSK) based underwater communication system. The presented solution addresses the problem of developing inexpensive, compact ultrasound modems able to be mounted on underwater robots. Simplifications introduced into the modulation and demodulation of QPSK signals do not disturb any parameter of the data link. The paper indicates that it is possible to realize modulation and demodulation on a simple microcontroller. Many hints are given on how to use hardware blocks embedded in a microcontroller, such as ADC, DMA, timers, etc. Experiments performed with the prototype modems allow to reach 4 kbps data rate on a distance of about 18 m.
Dispersion Management and Pulse Characterization of Graphene-Based Soliton Mode-Locked Fiber Lasers
Authors: Abas Ahmad Fauzi , Lau Kuen Y. , Abdulkawi Wazie M. , Alresheedi Mohammed T. , Muhammad Farah D. , Mahdi Mohd Adzir
Published: March 2022

This paper presents the generation and characterization of femtosecond pulses utilizing graphene-polymethyl-methacrylate (PMMA) thin-film saturable absorber (SA), which is subjected to different lengths of single-mode fiber (SMF) in an erbium-doped fiber laser cavity. The graphene/PMMA-SA is prepared by using a simple transfer procedure of the thin-film on a fiber ferrule. By increasing the SMF length from 0 to 4 m, the corresponding group velocity dispersion of the entire cavity is estimated to change from −0.033 to −0.121 ps2. Analysis of the pulse performance shows that the pulse width behavior varies from 820 fs to 710 fs against different cavity lengths. Similarly, the pulse repetition rate and the spectral bandwidth can be adjusted from 12.5 to 10.0 MHz, and from 8.2 to 5.6 nm, respectively. A comprehensive discussion on the pulse performance is presented, which can contribute to widening the knowledge on the operation of graphene-based soliton mode-locked erbium-doped fiber lasers based on dispersion management by controlling the cavity length.
Computer-Generated Holograms Application in Security Printing
Authors: Zlokazov Evgenii Y. , Kolyuchkin Vasilii V. , Lushnikov Dmitrii S. , Smirnov Andrei V.
Published: March 2022

In the present article the application of computer-generated holograms in security printing was considered. The main subject was creation of informative memory marks based on CGH for automatic read out of the information embedded in this marks that can be used for identification, copyrighting, or other types of authentication control of security elements. The fundamental theoretical basics of computer-generated holograms and its applications were given. The proposed technical solutions, such as “Printed hologram”, “Smart verification”, and “Holomemory”, were considered in detail. The announced solutions were presented in the schemes of interaction between manufacturers of security printing and its potential consumers—citizens and regulatory government agencies.
Yeast Extract Affecting the Transformation of Biogenic Tooeleite and Its Stability
Authors: Li Qingzhu , Liu Qianwen , Wang Xi , Liao Qi , Liu Hui , Wang Qingwei
Published: March 2022

Highly toxic As(III) is the main form of As in wastewater. The retention of As by tooeleite has gradually attracted attention in recent years due to its great potential for the direct removal of As(III). The existence of natural As-bearing minerals is closely related to microorganisms and organic matters. In this study, yeast extract was found to enhance the stability of biogenic tooeleite by Acidithiobacillus ferrooxidans (A. ferrooxidans). The effects of pH, Fe/As and yeast extract concentration were systematically studied, and the toxicity characteristic leaching procedure (TCLP) was conducted to evaluate the short-term stability of tooeleite. The mineral synthesized in the presence of yeast extract showed that the As leaching concentration decreased from 13.78 mg/L to 7.23 mg/L and the stability increased by more than 40%. In addition, various characteristics confirmed that the precursor was changed from amorphous schwertmannite to basic ferric sulfate in the presence of yeast extract, and then transformed to relatively purer tooeleite with less hollow structure and excellent dispersion, which is favorable for the stability of tooeleite. This result indicated that yeast extract resulted in the formation of different precursors and thus affected the transformation and stability of tooeleite.
On the Design of Regulation Controllers for Automation Systems with RCPetri
Authors: Anguiano-Gijón Carlos Alberto , Cid-Gaona Anibal , Chávez-Delgado José Manuel , Vázquez Carlos Renato
Published: March 2022

Regulation control for Petri nets is a control framework that allows the design of sequence controllers for automation systems in a systematic and efficient way. In order to implement this control framework, the MATLAB® app RCPetri has been developed. In this work, the RCPetri tool functionalities are described, including model generation, automatic specification generation, automatic control design, model and control simulation, automatic translation to PLC code, and communication by Modbus TCP/IP and OPC UA. Furthermore, three examples are presented to illustrate the application of the tool and the regulation framework: an electro-pneumatic device, a process control system, and a robotic manufacturing cell under a decentralized control scheme.
Methodology to Optimize Quality Costs in Manufacturing Based on Multi-Criteria Analysis and Lean Strategies
Authors: Pérez-Fernández Lorena , Sebastián Miguel A. , González-Gaya Cristina
Published: March 2022

Manufacturing quality cost optimization is a priority in any manufacturing sector due to quality issues impacting companies’ reputations and has financial consequences. Quality costs are composed of tangible and intangible costs, however, only tangible costs used to be analyzed because there is no suitable methodology for measuring intangible costs. In this context, an innovative decision support system is developed with an empirical base, applying Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), and Lean methodology to reduce all quality costs in an efficient way. In quality departments, perceptions, thoughts, and judgments (intangible costs) are not measured and controlled. This study develops an innovative methodology that allows to address this issue in an effective way. Another major innovation is the application of both multi-criteria methodologies to obtain the best combined result for decision making and the optimization of this result, developing an effort–impact matrix based on Lean manufacturing methodology. This system speeds up the decision-making process and assures its efficiency for quality department applications. Moreover, this decision support system may be applicable to any manufacturing sector.
Investigation of an Influence Function Model as a Self-Rotating Wheel Polishing Tool and Its Application in High-Precision Optical Fabrication
Authors: Yao Yongsheng , Li Qixin , Ding Jiaoteng , Wang Yongjie , Ma Zhen , Fan Xuewu
Published: March 2022

A new and patented polishing tool (ZL2020102387137) called a Self-rotating Wheel Polishing Tool (SWPT) was built, and its tool influence function (TIF) was investigated in this study. The polishing wheel is an innovative two-layer structure: a rigid hub inside and a flexible polishing pad outside. By using finite element analysis, the dynamic contact characteristics between the polishing wheel and the workpiece were studied, and the theoretical TIF was modeled. Due to the influence of friction resistance, the TIF is not circular, but oval. We then ran material removal experiment, and it was found that the experimental TIF and the theoretical TIF are very close and both are close to the Gaussian shape. Finally, optical fabrication was performed. After four times of about 3 h fabrication, the form error converged from PV-1.434λ (λ = 632 nm), RMS-0.308λ to PV-0.144λ, RMS-0.009λ, and PV and RMS converged by 90% and 97%, respectively. The form accuracy achieved the expected target of RMS-0.02λ, which proves that the SWPT has the characteristics of high convergence rate and high fabrication accuracy. The SWPT has a broad application prospect in the field of high-precision optical fabrication.
A Current Sharing State Estimation Method of Redundant Switched-Mode Power Supply Based on LSTM Neural Network
Authors: He Peng , Zhou Quan , Bai Libing , Xie Songlin , Zhang Weijing
Published: March 2022

Redundant Switched-mode Power supplies (SMPSs) are commonly used to improve electronic systems’ reliability, and accurate estimation of the current sharing state is significant for evaluating the system’s health. Currently, the current sharing state estimation is mainly realized by using current sensors to detect each branch’s current, and the deployment and maintenance costs are high. In this paper, a method for power supply current sharing state estimation based on LSTM recurrent neural network is proposed. By taking advantage of subtle differences in the inherent spectral characteristics of SMPSs, this method only needs to detect the voltage ripple at the switching frequency of the load terminal to estimate the output current of each power supply branch. The verification experiment on the three-power redundant experimental platform shows that the estimation error is less than 10%. The method has the characteristics of simple structure, non-invasion, convenient deployment and maintenance, so it has high application and promotion value.
Ensuring the Long-Term Preservation of and Access to the Italian Federated Electronic Health Record
Authors: Guaglianone Maria Teresa , Aracri Giovanna , Chiaravalloti Maria Teresa , Cardillo Elena , Arena Camillo Francesco , Sorrentino Elisa , Spagnuolo Anna Federica
Published: March 2022

The Italian Electronic Health Record (called the FSE) is based on a federated architectural model and involves various types of health data and documents deriving from public and private health stakeholders. Clinical documents are stored in repositories and indexed in a central regional index (registry) according to a defined metadata schema. The FSE repositories can be distributed in the regional network or centralized at the regional level, or regions can use subsidiarity services offered by the National Infrastructure for the regional FSEs Interoperability. In this scenario, this study addresses the open issue of the FSE documents’ long-term preservation and access over time, since the responsibility of their preservation is distributed among different stakeholders. As a consequence, the process traceability is necessary to ensure that a document indexed in an FSE is accessible over time, regardless of the document local discard policies applied for legal fulfilments. The results of this study show that the enhancement of metadata use could support the management and long-term preservation of the FSE documents. Addressing this issue is, finally, fundamental to guarantee the correct tracing and access to the clinical path of a patient and to ensure the efficiency of the entire care setting.
Isolating the Role of the Transport System in Individual Accessibility Differences: A Space-Time Transport Performance Measure
Authors: Dianin Alberto , Gidam Michael , Hauger Georg
Published: March 2022

Accessibility differences across individuals are a core topic in the transport equity debate. Space-Time Accessibility measures (STAs) have often been used to show such differences, given their sensitiveness to individual spatial and temporal constraints. However, given their complexity, STAs cannot properly isolate the specific role of the transport system in individual accessibility differences, since it is mixed with several other spatial, individual and temporal factors. To isolate the role of the transport system, this study introduces a Space-Time Transport Performance measure (STTP) that (a) grounds on the individual daily schedule of fixed activities, (b) calculates the generalised transport costs each individual has to bear to perform such schedule, and (c) weights it against the Euclidean distance between the activities of such a schedule. STTP is tested together with STA for a small sample of individuals living and performing their daily activities within the 22nd district of Vienna. This test provides two main findings: first, individual differences registered by STTP tend to be smaller than those highlighted by STA, according to the former’s more narrowed and transport-specific approach. Second, individuals with the highest STA do not necessarily register the highest STTP (and vice versa). Indeed, some may experience limited transport performances when running their mandatory daily schedule, while registering a high degree of access to discretionary activities according to their constraints and opportunities at disposal (and vice versa). Considering these results, STTP may be seen as a complementary indicator to be used together with STA to analyse both general and transport-specific individual accessibility differences. Its role is particularly important for transport policy makers, who should understand which accessibility differences are directly linked to the performances of the transport system and could be remediated through transport policies.
Data Quality Assessment of Time-Variable Surface Microgravity Surveys in the Southeastern Tibetan Plateau
Authors: Zheng Qiuyue , Yao Xiuyi , Chen Shi , Yang Jinling , Liu Dong , Chen Zhengyu
Published: March 2022

Ground-based time-variable gravimetry with high accuracy is an important approach in monitoring geodynamic processes. The uncertainty of instruments including scale factor (SF) and drift rate are the primary factors affect the quality of observation data. Differing from the conventional gravity adjustment procedure, this study adopted the modified Bayesian gravity adjustment (MBGA) method, which accounts for the nonlinear drift rate, and where the SF is considered as one of the hyperparameters estimated using Akaike’s Bayesian information criterion. Based on the terrestrial time-variable gravity datasets (2018–2020) from the southeastern Tibetan Plateau, errors caused by nonlinear drift rate and SF were processed quantitatively through analysis of the gravity difference (GD) residuals and the mutual difference of the GD. Additionally, cross validation from absolute gravity (AG) values was also applied. Results suggest that: (1) the drift rate of relavive instruments show nonlinear characteristics, and owing to their different spring features, the drift rate of CG-5 is much larger than that of LCR-G gravimeters; (2) the average bias between the original and optimized SF of the CG-5 gravimeters is approximately 169 ppm, while that of the LCR-G is no more than 63 ppm; (3) comparison of the differences in gravity values (GV) suggests that the uncertainty caused by the nonlinear drift rate is smaller than that attributable to SF. Overall, the novel approach adopted in this study was found effective in removing errors, and shown to be adaptive and robust for large-scale hybrid surface gravity campaign which providing high accuracy gravity data for the geoscience research.
An Earthquake Forecast Model Based on Multi-Station PCA Algorithm
Authors: Liu Yibin , Yong Shanshan , He Chunjiu , Wang Xin’an , Bao Zhenyu , Xie Jinhan , Zhang Xing
Published: March 2022

With the continuous development of human society, earthquakes are becoming more and more dangerous to the production and life of human society. Researchers continue to try to predict earthquakes, but the results are still not significant. With the development of data science, sensing and communication technologies, there are increasing efforts to use machine learning methods to predict earthquakes. Our work raises a method that applies big data analysis and machine learning algorithms to earthquakes prediction. All data are accumulated by the Acoustic and Electromagnetic Testing All in One System (AETA). We propose the multi-station Principal Component Analysis (PCA) algorithm and extract features based on this method. At last, we propose a weekly-scale earthquake prediction model, which has a 60% accuracy using LightGBM (LGB).
Risk Assessment of Artifact Degradation in a Museum, Based on Indoor Climate Monitoring—Case Study of “Poni-Cernătescu” Museum from Iași City
Authors: Florescu Oana , Ichim Pavel , Sfîcă Lucian , Kadhim-Abid Adriana-Lucia , Sandu Ion , Nănescu Monica
Published: March 2022

Preservation of the cultural heritage of museums includes measures to prevent degrading effects induced by air temperature and humidity factors which are difficult to control. The present paper includes a synopsis of values of air temperature and relative humidity characterizing the indoor climate of the “Poni-Cernătescu” Museum of Iași, Romania for a period of one year. The objective of this research was to describe the museum microclimate and to identify and analyze the degradation risk of museum artifacts in order to study the impact of hygrothermal indoor and outdoor loads on indoor microclimate parameters. To achieve the objective, the following activities were carried out: acquisition of data on the relative humidity and the temperature of indoor and outdoor air; analysis of data with climate analysis tools and statistical methods; and transformation of data into quantitative and qualitative numerical measures of collection decay risks. The collected data enabled us to accurately describe the indoor climate conditions of the analyzed building. The main conclusions of the assessment were that the May–July period represented the interval with the highest degradation risk for all types of cultural assets (wood, leather, photos and paintings); this occurred because of the combination of a high amount of water vapor and high air temperature conditions. Based on charts and tabular data, this study presents the evolution of two parameters of internal microclimate, air temperature and relative humidity, and their correlation with external climate factors. The structural and functional parameters of the museum, the working levels of heating and air conditioning systems, the arrangement, the load, and the typological complexity of the artifacts displayed, were also considered in the analysis. The results obtained enabled us to develop useful recommendations to stabilize climate conditions inside the museum. Specific measures to mitigate the detrimental impact of the analyzed environmental factors are proposed. The results obtained show that in the basement, favorable conditions for mycelium growth occurred. In the summer months, across the entire museum space, the preservation indices were the lowest, from 20 to 25, so suitable conditions for storing the artifacts were not met.