bluuebunny/crossref_metadata_2025 huggingface dataset:
Fuel Consumption Prediction for Construction Trucks: A Noninvasive Approach Using Dedicated Sensors and Machine Learning
Authors: Pereira Gonçalo , Parente Manuel , Moutinho João , Sampaio Manuel
Published: November 2021

Decision support and optimization tools to be used in construction often require an accurate estimation of the cost variables to maximize their benefit. Heavy machinery is traditionally one of the greatest costs to consider mainly due to fuel consumption. These typically diesel-powered machines have a great variability of fuel consumption depending on the scenario of utilization. This paper describes the creation of a framework aiming to estimate the fuel consumption of construction trucks depending on the carried load, the slope, the distance, and the pavement type. Having a more accurate estimation will increase the benefit of these optimization tools. The fuel consumption estimation model was developed using Machine Learning (ML) algorithms supported by data, which were gathered through several sensors, in a specially designed datalogger with wireless communication and opportunistic synchronization, in a real context experiment. The results demonstrated the viability of the method, providing important insight into the advantages associated with the combination of sensorization and the machine learning models in a real-world construction setting. Ultimately, this study comprises a significant step towards the achievement of IoT implementation from a Construction 4.0 viewpoint, especially when considering its potential for real-time and digital twins applications.
Olfactory Sensilla and Olfactory Genes in the Parasitoid Wasp Trichogramma pretiosum Riley (Hymenoptera: Trichogrammatidae)
Authors: Al-Jalely Basman H. , Xu Wei
Published: November 2021

Trichogramma pretiosum Riley (Hymenoptera: Trichogrammatidae) is a tiny natural egg parasitoid of several agricultural pest insects, which has been widely used in the biological control for Plutella xylostella, Helicoverpa armigera, Spodoptera frugiperda and Ectomyelois ceratoniae. However, limited studies have been conducted on T. pretiosum olfactory system, which is critical in regulating insect behaviours. In this study, T. pretiosum adult antennae were investigated under ascanning electron microscopy (SEM). Four types of olfactory sensilla were observed, including chaetica sensilla (CS), trichoid sensilla (TS), faleate sensilla (FS) and placoid sensilla (PS). Using T. pretiosum genome, 22 putative odorant binding proteins (OBPs) and 105 odorant receptors (ORs) were identified, which were further compared with olfactory genes of Apis mellifera, Nasonia vitripennis and Diachasma alloeum. The expression patterns of OBPs between T. pretiosum male and female adults were examined by quantitative real time PCR (qRT-PCR) approaches. Three female-specific OBPs (TpreOBP19, TpreOBP15 and TpreOBP3) were identified, which may play crucial roles in T. pretiosum host-seeking and oviposition behaviours. This study enriches our knowledge of T. pretiosum olfactory genes and improves our understanding of its olfactory system.
Clinical Effects of L-Carnitine Supplementation on Physical Performance in Healthy Subjects, the Key to Success in Rehabilitation: A Systematic Review and Meta-Analysis from the Rehabilitation Point of View
Authors: Vecchio Michele , Chiaramonte Rita , Testa Gianluca , Pavone Vito
Published: November 2021

L-carnitine supplementation improves body strength, sports endurance and exercise capacity, as well as delaying the onset of fatigue. The aim of this study was to identify the correct dosage of supplementation to obtain improvements in physical performance and evaluate the changes related to L-carnitine supplementation in specific metabolic parameters, such as serum lactate, VO2, serum total and free carnitine at rest and after physical activities, in healthy subjects. The search was conducted on PubMed, EMBASE, Cochrane Library, Scopus and Web of Science and identified 6404 articles with the keywords: “carnitine” AND “exercises” OR “rehabilitation” OR “physical functional performance” OR “physical activity” OR “sports” OR “health” OR “healthy”. A total of 30 publications met the inclusion criteria and were included in the systematic review. The meta-analysis did not show any significant differences in serum lactate values at rest and after exercise in healthy subjects who took L-carnitine supplementation (p > 0.05). On the contrary, L-carnitine administration significantly changed maximal oxygen consumption (VO2) at rest (p < 0.005), serum free and total carnitine at rest and after exercise (p < 0.001). The dosage of supplementation that obtained a significant change in serum total carnitine was 2 g/dL for 4 weeks at rest, 1 g/dL for 3 weeks after exercise, and in serum free carnitine was 2 g/dL for 3 weeks and 2 g/dL for 4 weeks at rest. Based on our study, serum total and free carnitine at rest and after exercise, and VO2 at rest could be used to clinically follow individuals during physical activity and rehabilitation programs. Moreover, the supplementation should have a correct dosage to have maximum effect. Other robust trials are needed to find the best dosage to obtain positive results in metabolic parameters and in physical performance.
An Artificial Intelligence-Based Alarm Strategy Facilitates Management of Acute Myocardial Infarction
Authors: Liu Wen-Cheng , Lin Chin , Lin Chin-Sheng , Tsai Min-Chien , Chen Sy-Jou , Tsai Shih-Hung , Lin Wei-Shiang , Lee Chia-Cheng , Tsao Tien-Ping , Cheng Cheng-Chung
Published: November 2021

(1) Background: While an artificial intelligence (AI)-based, cardiologist-level, deep-learning model for detecting acute myocardial infarction (AMI), based on a 12-lead electrocardiogram (ECG), has been established to have extraordinary capabilities, its real-world performance and clinical applications are currently unknown. (2) Methods and Results: To set up an artificial intelligence-based alarm strategy (AI-S) for detecting AMI, we assembled a strategy development cohort including 25,002 visits from August 2019 to April 2020 and a prospective validation cohort including 14,296 visits from May to August 2020 at an emergency department. The components of AI-S consisted of chest pain symptoms, a 12-lead ECG, and high-sensitivity troponin I. The primary endpoint was to assess the performance of AI-S in the prospective validation cohort by evaluating F-measure, precision, and recall. The secondary endpoint was to evaluate the impact on door-to-balloon (DtoB) time before and after AI-S implementation in STEMI patients treated with primary percutaneous coronary intervention (PPCI). Patients with STEMI were alerted precisely by AI-S (F-measure = 0.932, precision of 93.2%, recall of 93.2%). Strikingly, in comparison with pre-AI-S (N = 57) and post-AI-S (N = 32) implantation in STEMI protocol, the median ECG-to-cardiac catheterization laboratory activation (EtoCCLA) time was significantly reduced from 6.0 (IQR, 5.0–8.0 min) to 4.0 min (IQR, 3.0–5.0 min) (p < 0.01). The median DtoB time was shortened from 69 (IQR, 61.0–82.0 min) to 61 min (IQR, 56.8–73.2 min) (p = 0.037). (3) Conclusions: AI-S offers front-line physicians a timely and reliable diagnostic decision-support system, thereby significantly reducing EtoCCLA and DtoB time, and facilitating the PPCI process. Nevertheless, large-scale, multi-institute, prospective, or randomized control studies are necessary to further confirm its real-world performance.
Investigation of the Structural, Mechanical and Tribological Properties of Plasma Electrolytic Hardened Chromium-Nickel Steel
Authors: Rakhadilov Bauyrzhan , Seitkhanova Ainur , Satbayeva Zarina , Yerbolatova Gulnara , Icheva Yulianna , Sagdoldina Zhuldyz
Published: November 2021

This paper investigates how electrolytic plasma hardening (PEH) bears upon the changes in the phase structural and tribological properties of steel 0.34C-1Cr-1Ni-1Mo-Fe, which is widely used in manufacturing highly stressed gears. The samples of steel 0.34C-1Cr-1Ni-1Mo-Fe went through the PEH in an electrolyte containing an aqua solution of 20% calcined soda (Na2CO3) and 10% carbamide ((NH2)2CO). The initial steel 0.34C-1Cr-1Ni-1Mo-Fe is stated to have the following structural components: a lamellar pearlite with volume share of 35%, a ferrite-carbide mixture of ~45% and a fragmented ferrite of ~20%; after the PEH it contains lath-lamellar martensite, fine particles of cementite and M23C6 carbide. The durability of steel 0.34C-1Cr-1Ni-1Mo-Fe was found to rise by 3.4 times after the PEH and its microhardness increased in 2.6 times. The curve-tension of the crystal lattice was established to be like plastic (χ = χpl) and does not cause the formation of microcracks in the material.
Hydrosoluble and Liposoluble Vitamins: New Perspectives through ADMET Analysis
Authors: Nicolov Mirela , Cocora Mioara , Buda Valentina , Danciu Corina , Duse Adina Octavia , Watz Claudia , Borcan Florin
Published: November 2021

Background and Objectives: The present study demonstrates that apart from the well-known toxicity of liposoluble vitamins, some hydrosoluble vitamins may also exert toxicity; thus, routine supplementation with vitamins or ingestion of fortified foods should not be considered harmless. The study addresses the possible correlations between the physico-chemical properties and the side effects of vitamins when taken in high doses or for a too long a period. Materials and Methods: The FAFDrugs4.0 computational tool was used for computational assessment of the ADMET profile of several hydro- and liposoluble vitamins. Results: ADMET analysis revealed the following major data: vitamin B3 and B13 showed reduced structural complexity; thus, a relative toxicological potential may be exerted. Vitamins B1 and B7 were found to have good oral absorption and thus good bioavailability, while Vitamin B3 was found to have decreased oral absorption. In addition, all of the liposoluble vitamins reflected higher complexity, much greater than most of the potentially therapeutically-proven compounds. Conclusions: The present study emphasizes the importance between the physico-chemical properties of vitamins and their possible toxicological impact.
Biophysical Stimulation in Athletes’ Joint Degeneration: A Narrative Review
Authors: Moretti Lorenzo , Bizzoca Davide , Giancaspro Giovanni Angelo , Cassano Giuseppe Danilo , Moretti Francesco , Setti Stefania , Moretti Biagio
Published: November 2021

Osteoarthritis (OA) is the most prevalent degenerative joint disease and the main cause of pain and disability in elderly people. OA currently represents a significant social health problem, since it affects 250 million individuals worldwide, mainly adults aged over 65. Although OA is a multifactorial disease, depending on both genetic and environmental factors, it is reported that joint degeneration has a higher prevalence in former athletes. Repetitive impact and loading, joint overuse and recurrent injuries followed by a rapid return to the sport might explain athletes’ predisposition to joint articular degeneration. In recent years, however, big efforts have been made to improve the prevention and management of sports injuries and to speed up the athletes’ return-to-sport. Biophysics is the study of biological processes and systems using physics-based methods or based on physical principles. Clinical biophysics has recently evolved as a medical branch that investigates the relationship between the human body and non-ionizing physical energy. A physical stimulus triggers a biological response by regulating specific intracellular pathways, thus acting as a drug. Preclinical and clinical trials have shown positive effects of biophysical stimulation on articular cartilage, subchondral bone and synovia. This review aims to assess the role of pulsed electromagnetic fields (PEMFs) and extracorporeal shockwave therapy (ESWT) in the prevention and treatment of joint degeneration in athletes.
Peptide-Based Drug Delivery Systems
Authors: Berillo Dmitriy , Yeskendir Adilkhan , Zharkinbekov Zharylkasyn , Raziyeva Kamila , Saparov Arman
Published: November 2021

Peptide-based drug delivery systems have many advantages when compared to synthetic systems in that they have better biocompatibility, biochemical and biophysical properties, lack of toxicity, controlled molecular weight via solid phase synthesis and purification. Lysosomes, solid lipid nanoparticles, dendrimers, polymeric micelles can be applied by intravenous administration, however they are of artificial nature and thus may induce side effects and possess lack of ability to penetrate the blood-brain barrier. An analysis of nontoxic drug delivery systems and an establishment of prospective trends in the development of drug delivery systems was needed. This review paper summarizes data, mainly from the past 5 years, devoted to the use of peptide-based carriers for delivery of various toxic drugs, mostly anticancer or drugs with limiting bioavailability. Peptide-based drug delivery platforms are utilized as peptide–drug conjugates, injectable biodegradable particles and depots for delivering small molecule pharmaceutical substances (500 Da) and therapeutic proteins. Controlled drug delivery systems that can effectively deliver anticancer and peptide-based drugs leading to accelerated recovery without significant side effects are discussed. Moreover, cell penetrating peptides and their molecular mechanisms as targeting peptides, as well as stimuli responsive (enzyme-responsive and pH-responsive) peptides and peptide-based self-assembly scaffolds are also reviewed.
Assessment of Iodine and Selenium Nutritional Status in Women of Reproductive Age in Latvia
Authors: Veisa Vija , Kalere Ieva , Zake Tatjana , Strele Ieva , Makrecka-Kuka Marina , Upmale-Engela Sabine , Skesters Andrejs , Rezeberga Dace , Lejnieks Aivars , Pudule Iveta , Grinberga Daiga , Velika Biruta , Dambrova Maija , Konrade Ilze
Published: November 2021

Background and Objectives: Adequate dietary intake of iodine and selenium is essential during pregnancy. While iodine is vital for maternal thyroid function and fetal development, selenium contributes to the regulation of thyroid function and thyroid autoimmunity. This study aimed to assess the consumption of iodine- and selenium-containing products by women of reproductive age and the iodine and selenium nutritional status of pregnant women in Latvia. Materials and Methods: Population health survey (2010–2018) data were used to characterize dietary habits in women of reproductive age. Additionally, 129 pregnant women in the first trimester were recruited; they completed a questionnaire and were tested for thyroid function, urinary iodine concentration (UIC), and serum selenium and selenoprotein P levels. Results: The use of some dietary sources of iodine (e.g., milk and dairy products) and selenium (e.g., bread) has decreased in recent years. Less than 10% of respondents reported the use of iodized salt. The use of supplements has become more common (reported by almost 50% of respondents in 2018). Dietary habits were similar in pregnant women, but the use of supplements was even higher (almost 70%). Nevertheless, most supplements used in pregnancy had insufficient contents of iodine and selenium. Thyroid function was euthyreotic in all women, but 13.9% of participants had a thyroid peroxidase antibodies (TPO-ab) level above 60 IU/mL. The median UIC (IQR) was 147.2 (90.0–248.1) μg/gCr, and 52.8% of pregnant women had a UIC below 150 μg/gCr. The mean selenium (SD) level was 101.5 (35.6) μg/L; 30.1% of women had a selenium level below 80 μg/L. The median selenoprotein P level was 6.9 (3.1–9.0) mg/L. Conclusions: Iodine nutrition in Latvian population of pregnant women was near the lower limit of adequate and a third of the population had a selenium deficiency. Supplements were frequently used, but most did not contain the recommended amounts of iodine and selenium.
Study and Analysis on the Influence Degree of Particle Settlement Factors in Pipe Transportation of Backfill Slurry
Authors: Wang Chonghao , Gan Deqing
Published: November 2021

In this study, we developed a pipeline transport model to investigate the influence of particle sedimentation factors on slurry transportation through pipelines. The particle tracking module of the software was used to simulate the transport process, and the influences on the sedimentation rate were analyzed considering the slurry concentration, particle size, and flow velocity. The established model exhibited small calculation errors. In addition, the results revealed that the proposed model is reliable for calculating the degree of influence of various factors on particle sedimentation. The effect of the particle sedimentation rate on the pipeline slurry was explored considering the particle size, slurry concentration, and flow velocity. The sedimentation rate was positively related to particle size and adversely related to the slurry concentration and flow velocity. Indeed, study on the sedimentation rate requires considering a reasonable range of particle sizes, preparing a slurry with an appropriate concentration, and adjusting an appropriate flow velocity. Numerical simulations were performed using the filling data as the background for a sample mining area. The experimental results showed optimal slurry concentration and particle size of 60% and 25.25 µm, respectively.
Convalescent Plasma Reduces Mortality and Decreases Hospitalization Stay in Patients with Moderate COVID-19 Pneumonia
Authors: Basheer Maamoun , Saad Elias , Shlezinger Dorin , Assy Nimer
Published: November 2021

Humans infected with SARS-CoV-2 may develop COVID-19, which manifests across a wide spectrum of clinical severity ranging from mild upper respiratory tract illnesses to diffuse viral pneumonia, causing acute respiratory failure. Many therapies have been tested for their efficacy in treating COVID-19. Controversy surrounds convalescent plasma transfusions as an effective treatment for COVID-19. This study discusses the efficacy of this treatment on COVID-19 patients. Electronic medical record data were collected from patients diagnosed with COVID-19, from November 2020 to August 2021, in the Galilee Medical Center’s COVID-19 departments. Epidemiological, clinical, laboratory and imaging variables were analyzed. Multivariate stepwise regression and discriminant analyses were used to identify and validate the correlation between convalescent treatment and either death or time to negative PCR and hospitalization length. The study population included 270 patients, 100 of them treated with convalescent plasma. The results show that convalescent plasma therapy significantly prevented mortality in moderate patients, reduced hospitalization length and time to negative PCR. Additionally, high BMI, elderly age, high CRP and 4C-scores correlated with the severity and mortality of COVID-19 patients. Convalescent plasma also significantly reduced inflammatory markers, especially in moderate COVID-19 patients. In non-critical hospitalized patients, convalescent plasma therapy reduces morbidity and mortality in moderate COVID-19 patients and hospitalization length. Identifying patients who could benefit from this treatment could reduce the risk of death and shorten their hospitalization stay.
Culturable Endophytic Fungi from Glycyrrhiza inflata Distributed in Xinjiang, China with Antifungal Activity
Authors: Gu Gan , Jia Xiaowei , Wang Weixuan , Li Peng , Zhao Siji , Zhou Zhiyao , Yin Ruya , Lai Daowan , Song Suqin , Zhou Ligang
Published: November 2021

A total of 99 endophytic fungal isolates were obtained from the roots of Glycyrrhiza inflata, which was a traditional medicinal plant mainly distributed in Xinjiang, China. Twenty-two distinct isolates were selected for further taxonomical identification by morphological traits and internal transcribed spacer (ITS) rRNA gene sequence analysis. Eleven genera were identified, among which Aspergillus, Alternaria and Fusarium were dominant. The crude extracts of 22 distinct identified fungi were successively evaluated for their antifungal activities on three rice fungal pathogens using the method of hyphal radial growth rate. Among them, the crude extract of Alternaria an-gustiovoidea Glinf007 showed the significantly mycelial growth inhibitory activity. The results demonstrated that G. inflata contained a diversity of culturable endophytic fungi, which could produce natural antimicrobial compounds that might be of great value to the agriculture and pharmaceutical industries.
Exergy Analysis of Coal-Based Series Polygeneration Systems for Methanol and Electricity Co-Production
Authors: Zhang Jianyun , Yang Zhiwei , Ma Linwei , Ni Weidou
Published: November 2021

This paper quantifies the exergy losses of coal-based series polygeneration systems and evaluates the potential efficiency improvements that can be realized by applying advanced technologies for gasification, methanol synthesis, and combined cycle power generation. Exergy analysis identified exergy losses and their associated causes from chemical and physical processes. A new indicator was defined to evaluate the potential gain from minimizing exergy losses caused by physical processes—the degree of perfection of the system’s thermodynamic performance. The influences of a variety of advanced technical solutions on exergy improvement were analyzed and compared. It was found that the overall exergy loss of a series polygeneration system can be reduced significantly, from 57.4% to 48.9%, by applying all the advanced technologies selected. For gasification, four advanced technologies were evaluated, and the largest reduction in exergy loss (about 2.5 percentage points) was contributed by hot gas cleaning, followed by ion transport membrane technology (1.5 percentage points), slurry pre-heating (0.91 percentage points), and syngas heat recovery (0.6 percentage points). For methanol synthesis, partial shift technology reduced the overall exergy loss by about 1.4 percentage points. For power generation, using a G-class gas turbine decreased the overall exergy loss by about 1.6 percentage points.
ICP-MS Determination of 23 Elements of Potential Health Concern in Liquids of e-Cigarettes. Method Development, Validation, and Application to 37 Real Samples
Authors: Mara Andrea , Langasco Ilaria , Deidda Sara , Caredda Marco , Meloni Paola , Deroma Mario , Pilo Maria I. , Spano Nadia , Sanna Gavino
Published: November 2021

The lack of interest in the determination of toxic elements in liquids for electronic cigarettes (e-liquids) has so far been reflected in the scarce number of accurate and validated analytical methods devoted to this aim. Since the strong matrix effects observed for e-liquids constitute an exciting analytical challenge, the main goal of this study was to develop and validate an ICP-MS method aimed to quantify 23 elements in 37 e-liquids of different flavors. Great attention has been paid to the critical phases of sample pre-treatment, as well as to the optimization of the ICP-MS conditions for each element and of the quantification. All samples exhibited a very low amount of the elements under investigation. Indeed, the sum of their average concentration was of ca. 0.6 mg kg−1. Toxic elements were always below a few tens of a μg per kg−1 and, very often, their amount was below the relevant quantification limits. Tobacco and tonic flavors showed the highest and the lowest concentration of elements, respectively. The most abundant elements came frequently from propylene glycol and vegetal glycerin, as confirmed by PCA. A proper choice of these substances could further decrease the elemental concentration in e-liquids, which are probably barely involved as potential sources of toxic elements inhaled by vapers.
In Vitro and In Silico Interaction Studies with Red Wine Polyphenols against Different Proteins from Human Serum
Authors: Shafreen Raja Mohamed Beema , Lakshmi Selvaraj Alagu , Pandian Shunmugiah Karutha , Kim Young-Mo , Deutsch Joseph , Katrich Elena , Gorinstein Shela
Published: November 2021

Previous reports have shown that consumption of wine has several health benefits; however, there are different types of wine. In the present study, red wines were investigated for their compositions of active ingredients. The interaction of each component in terms of its binding mode with different serum proteins was unraveled, and the components were implicated as drug candidates in clinical settings. Overall, the study indicates that red wines have a composition of flavonoids, non-flavonoids, and phenolic acids that can interact with the key regions of proteins to enhance their biological activity. Among them, rutin, resveratrol, and tannic acid have shown good binding affinity and possess beneficial properties that can enhance their role in clinical applications.
Structure–Activity Relationship of Graphene-Based Materials: Impact of the Surface Chemistry, Surface Specific Area and Lateral Size on Their In Vitro Toxicity
Authors: Achawi Salma , Feneon Bruno , Pourchez Jérémie , Forest Valérie
Published: November 2021

Predictive toxicity and structure–activity relationships (SARs) are raising interest since the number of nanomaterials has become unmanageable to assess their toxicity with a classical case-by-case approach. Graphene-based materials (GBMs) are among the most promising nanomaterials of this decade and their application might lead to several innovations. However, their toxicity impact needs to be thoroughly assessed. In this regard, we conducted a study on 22 GBMs to investigate their potential SARs by performing a complete physicochemical characterization and in vitro toxicity assessment (on RAW264.7 cells). We used GBMs of variable lateral size (0.5–38 µm), specific surface area (SSA, 30–880 m²/g), and surface oxidation (2–17%). We observed that reduced graphene oxides (RGOs) were more reactive than graphene nanoplatelets (GNPs), potentially highlighting the role of GBM’s surface chemistry and surface defects density in their biological impact. We also observed that for GNPs, a smaller lateral size caused higher cytotoxicity. Lastly, GBMs showing a SSA higher than 200 m²/g were found to induce a higher ROS production. Mechanistic explanations are proposed in the discussion. In conclusion, pairing a full physicochemical characterization with a standardized toxicity assessment of a large set of samples allowed us to clarify SARs and provide an additional step toward safe-by-design GBMs.
Determination of Reactivity Ratios from Binary Copolymerization Using the k-Nearest Neighbor Non-Parametric Regression
Authors: Fazakas-Anca Iosif Sorin , Modrea Arina , Vlase Sorin
Published: November 2021

This paper proposes a new method for calculating the monomer reactivity ratios for binary copolymerization based on the terminal model. The original optimization method involves a numerical integration algorithm and an optimization algorithm based on k-nearest neighbour non-parametric regression. The calculation method has been tested on simulated and experimental data sets, at low (<10%), medium (10–35%) and high conversions (>40%), yielding reactivity ratios in a good agreement with the usual methods such as intersection, Fineman–Ross, reverse Fineman–Ross, Kelen–Tüdös, extended Kelen–Tüdös and the error in variable method. The experimental data sets used in this comparative analysis are copolymerization of 2-(N-phthalimido) ethyl acrylate with 1-vinyl-2-pyrolidone for low conversion, copolymerization of isoprene with glycidyl methacrylate for medium conversion and copolymerization of N-isopropylacrylamide with N,N-dimethylacrylamide for high conversion. Also, the possibility to estimate experimental errors from a single experimental data set formed by n experimental data is shown.
Oxidative Desulfurization of Tire Pyrolysis Oil over Molybdenum Heteropolyacid Loaded Mesoporous Catalysts
Authors: Kaur Jasmine , Vedachalam Sundaramurthy , Boahene Philip , Dalai Ajay K.
Published: November 2021

Pyrolysis oil derived from waste tires consists of sulfur content in the range of 7000 to 9000 ppm. For use in diesel engines, its sulfur content must be lowered to 10 to 15 ppm. Though conventional hydrodesulfurization is suitable for the removal of sulfur from tire pyrolysis oil, its high cost provides an avenue for alternative desulfurization technologies to be explored. In this study, oxidative desulfurization (ODS), a low-cost technology, was explored for the desulfurization of tire pyrolysis oil. Two categories of titanium-incorporated mesoporous supports with 20 wt% loaded heteropoly molybdic acid catalyst (HPMo/Ti-Al2O3 and HPMo/Ti-TUD-1) were developed and tested for ODS of tire pyrolysis oil at mild process conditions. Catalysts were characterized by X-ray diffraction, BET-N2 physisorption, and X-ray photoelectron spectroscopy (XPS). The incorporation of Ti into Al2O3 and TUD-1 frameworks was confirmed by XPS. The surface acidity of catalysts was studied by the temperature-programmed desorption of NH3 and pyridine FTIR analyses. HPMo/Ti-Al2O3 and HPMo/Ti-TUD-1 catalysts contained both Lewis and Brønsted acid sites. The presence of titanium in catalysts was found to promote the ODS activity of phosphomolybdic acid. The Ti-TUD-1-supported catalysts performed better than the Ti-Al2O3-supported catalysts for the ODS of tire pyrolysis oil. Hydrogen peroxide and cumene peroxide were found to be better oxidants than tert-butyl hydroperoxide for oxidizing sulfur compounds of tire pyrolysis oil. Process parameter optimization by the design of experiments was conducted with an optimal catalyst along with the catalyst regeneration study. An ANOVA statistical analysis demonstrated that the oxidant/sulfur and catalyst/oil ratios were more significant than the reaction temperature for the ODS of tire pyrolysis oil. It followed the pseudo-first-order kinetics over HPMo/Ti-TUD-1.
A 10-Year Perspective on the Utility of Three Adjuvants Often Used in IVF: Growth Hormone, Melatonin and DHEA
Authors: Yovich John L. , Hinchliffe Peter M.
Published: November 2021

Since 2010, numerous studies reported from PIVET, a pioneer IVF facility established over 40 years ago, have explored the use of three adjuvants designed to improve laboratory and clinical outcomes in cases where a poor prognosis has been demonstrated. The adjuvants reported commenced with recombinant growth hormone (rGH), followed by dehydroepiandrosterone (DHEA) after developing a unique troche to avoid the first-pass effect and, subsequently, melatonin. The studies show that rGH is beneficial in the situation where women have poor-quality embryos in the setting of additional poor prognosis factors, such as advanced female age, a very low ovarian reserve, an insulin growth factor profile in the lowest quartile or recurrent implantation failure. The studies also imply that the adjuvants may actually reduce live birth productivity rates if used on women without poor prognosis factors; hence, further studies, which can now be better designed, should be undertaken to explore the notion of underlying adult growth hormone deficiency in some cases as well as the suggestion that DHEA can provide equivalent benefits in some poor prognosis settings. Melatonin showed no suggestive benefits in any of the studies and can be excluded from consideration in this context. Future studies should compare rGH and DHEA with a focus on those women who have poor embryo quality with additional poor prognosis factors. Such trials should be extended to 12 weeks to cover the entire period of oocyte activation.
Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction
Authors: Silva Ricardo Petri , Zarpelão Bruno Bogaz , Cano Alberto , Junior Sylvio Barbon
Published: November 2021

A wide range of applications based on sequential data, named time series, have become increasingly popular in recent years, mainly those based on the Internet of Things (IoT). Several different machine learning algorithms exploit the patterns extracted from sequential data to support multiple tasks. However, this data can suffer from unreliable readings that can lead to low accuracy models due to the low-quality training sets available. Detecting the change point between high representative segments is an important ally to find and thread biased subsequences. By constructing a framework based on the Augmented Dickey-Fuller (ADF) test for data stationarity, two proposals to automatically segment subsequences in a time series were developed. The former proposal, called Change Detector segmentation, relies on change detection methods of data stream mining. The latter, called ADF-based segmentation, is constructed on a new change detector derived from the ADF test only. Experiments over real-file IoT databases and benchmarks showed the improvement provided by our proposals for prediction tasks with traditional Autoregressive integrated moving average (ARIMA) and Deep Learning (Long short-term memory and Temporal Convolutional Networks) methods. Results obtained by the Long short-term memory predictive model reduced the relative prediction error from 1 to 0.67, compared to time series without segmentation.
Single Fault Diagnosis Method of Sensors in Cascade System Based on Data-Driven
Authors: Na Wenbo , Guo Siyu , Gao Yanfeng , Yang Jianxing , Huang Junjie
Published: November 2021

The reliability and safety of the cascade system, which is widely applied, have attached attention increasingly. Fault detection and diagnosis can play a significant role in enhancing its reliability and safety. On account of the complexity of the double closed-loop system in operation, the problem of fault diagnosis is relatively complex. For the single fault of the second-order valued system sensors, a real-time fault diagnosis method based on data-driven is proposed in this study. Off-line data is employed to establish static fault detection, location, estimation, and separation models. The static models are calibrated with on-line data to obtain the real-time fault diagnosis models. The real-time calibration, working flow and anti-interference measures of the real-time diagnosis system are given. Experiments results demonstrate the validity and accuracy of the fault diagnosis method, which is suitable for the general cascade system.
Dynamic Traffic Assignment Model Based on GPS Data and Point of Interest (POI) in Shanghai
Authors: Song Xueying , Yang Zheng , Wang Tao , Li Chaoyang , Zhang Yi , Chen Ganyu
Published: November 2021

Dynamic traffic flow, which can facilitate the efficient operation of traffic road networks, is an important prerequisite for the application of reasonable assignment of traffic demands in an urban road network. In order to improve the accuracy of dynamic traffic flow assignment, this paper proposes a dynamic traffic flow assignment model based on GPS trajectory data and the influence of POI. First, this paper explores the impact patterns of POI on regional road network congestion during peak hours through qualitative and quantitative analysis. Then, based on the user equilibrium theory, a dynamic traffic flow assignment model, in which the effect of POI on links is reflected using the link-node impedance function, is proposed. Finally, the accuracy of the model is validated by the GPS trajectory data and origin–destination (OD) traffic data of motor vehicles in Xuhui District, Shanghai, China. The results show that the model can be used to coordinate and optimize the traffic assignment of the regional road network under the influence of POI during peak hours and alleviate the congestion of the road network. The findings can provide a powerful reference for developing scientific and rational traffic assignment decisions and management strategies for urban road network traffic.
Wideband MOEMS for the Calibration of Optical Readout Systems
Authors: Volkov Petr , Lukyanov Andrey , Goryunov Alexander , Semikov Daniil , Vopilkin Evgeniy , Kraev Stanislav , Okhapkin Andrey , Tertyshnik Anatoly , Arkhipova Ekaterina
Published: November 2021

The paper proposes a technology based on UV-LIGA process for microoptoelectromechanical systems (MOEMS) manufacturing. We used the original combination of materials and technological steps, in which any of the materials does not enter chemical reactions with each other, while all of them are weakly sensitive to the effects of oxygen plasma. This made it suitable for long-term etching in the oxygen plasma at low discharge power with the complete preservation of the original geometry, including small parts. The micromembranes were formed by thermal evaporation of Al. This simplified the technique compared to the classic UV-LIGA and guaranteed high quality and uniformity of the resulting structure. To demonstrate the complete process, a test MOEMS with electrostatic control was manufactured. On one chip, a set of micromembranes was created with different stiffness from 10 nm/V to 100 nm/V and various working ranges from 100 to 300 nm. All membranes have a flat frequency response without resonant peaks in the frequency range 0–200 kHz. The proposed technology potentially enables the manufacture of wide low-height membranes of complex geometry to create microoptic fiber sensors.
Optimized Classification of Suspended Particles in Seawater by Dense Sampling of Polarized Light Pulses
Authors: Guo Zhiming , Deng Hanbo , Li Jiajin , Liao Ran , Ma Hui
Published: November 2021

Suspended particles affect the state and vitality of the marine ecosystem. In situ probing and accurately classifying the suspended particles in seawater have an important impact on ecological research and environmental monitoring. Individual measurement of the optical polarization parameters scattered by the suspended particles has been proven to be a powerful tool to classify the particulate compositions in seawater. In previous works, the temporal polarized light pulses are sampled and averaged to evaluate the polarization parameters. In this paper, a method based on dense sampling of polarized light pulses is proposed and the experimental setup is built. The experimental results show that the dense sampling method optimizes the classification and increases the average accuracy by at least 16% than the average method. We demonstrate the feasibility of dense sampling method by classifying the multiple types of particles in mixed suspensions and show its excellent generalization ability by multi-classification of the particles. Additional analysis indicates that the dense sampling method basically takes advantage of the high-quality polarization parameters to optimize the classification performance. The above results suggest that the proposed dense sampling method has the potential to probe the suspended particles in seawater in red-tide early warning, as well as sediment and microplastics monitoring.
Optical Fiber Sensors for Ultrasonic Structural Health Monitoring: A Review
Authors: Soman Rohan , Wee Junghyun , Peters Kara
Published: November 2021

Guided waves (GW) and acoustic emission (AE) -based structural health monitoring (SHM) have widespread applications in structures, as the monitoring of an entire structure is possible with a limited number of sensors. Optical fiber-based sensors offer several advantages, such as their low weight, small size, ability to be embedded, and immunity to electro-magnetic interference. Therefore, they have long been regarded as an ideal sensing solution for SHM. In this review, the different optical fiber technologies used for ultrasonic sensing are discussed in detail. Special attention has been given to the new developments in the use of FBG sensors for ultrasonic measurements, as they are the most promising and widely used of the sensors. The paper highlights the physics of the wave coupling to the optical fiber and explains the different phenomena such as directional sensitivity and directional coupling of the wave. Applications of the different sensors in real SHM applications have also been discussed. Finally, the review identifies the encouraging trends and future areas where the field is expected to develop.
Effects on Microstructure and Ionic Conductivity of the Co-Doping with Strontium and Samarium of Ceria with Constant Oxygen Vacancy Concentration
Authors: Sherwood Toby , Baker Richard T.
Published: November 2021

Partially substituted cerias are attractive materials for use as electrolytes in intermediate-temperature solid oxide fuel cells (SOFCs). Ceria doped with Sm or Gd has been found to have high ionic conductivities. However, there is interest in whether doping with multiple elements could lead to materials with higher ionic conductivities. The present study looks at the effects of co-doping Sr and Sm in ceria. A compositional series, Ce0.8+xSm0.2−2xSrxO2−δ (with x = 0–0.08), designed to have a constant oxygen vacancy concentration, was successfully prepared using the citrate–nitrate complexation method. A solubility limit of ~5 cation% Sr was found to impact material structure and conductivity. For phase-pure materials, with increasing Sr content, sinterability increased slightly and intrinsic conductivity decreased roughly linearly. The grain boundaries of phase-pure materials showed only a very small blocking effect, linked to the high-purity synthesis method employed, while at high %Sr, they became more blocking due to the presence of a SrCeO3 impurity. Grain capacitances were found to be 50–60 pF and grain boundary capacitances, 5–50 nF. The variation in the bulk capacitance with Sr content was small, and the variation in grain boundary capacitance could be explained by the variation in grain size. Slight deviations at high %Sr were attributed to the SrCeO3 impurity. In summary, in the absence of deleterious effects due to poor microstructure or impurities, such as Si, there is no improvement in conductivity on co-doping with Sr and Sm.
An Extraordinary Rosette and Resurrection New Spikemoss, Selaginella iridescens (Selaginellaceae) from Hainan Island, China
Authors: Yang Jie , Zhang Meng-Hua , Wang Ya-Rong , Yuan Lang-Xing , Zhang Xian-Chun
Published: November 2021

Selaginella iridescens (Selaginellaceae), a new species of spikemoss from Hainan Island, China, is described based on morphological and molecular evidence. The new species morphologically resembles S. pseudotamariscina from Vietnam which was recently recognized and segregated from S. tamariscina and S. pulvinata. Some characters of S. iridescens, including the iridescent leaves and long arista (0.35–1.20 mm long), the widely membranaceous margin of axillary leaves (ca. 2/3), dorsal leaves sulcate extending to the top, and slender main stem, dorsoventrally prostrate, distinguish it from S. pseudotamariscina. Phylogenetic results based on rbcL of 28 Selaginella species indicate that S. iridescens is sister to S. pseudotamariscina, and distant from the S. tamariscina-S.pulvinata clade. The ancestral character reconstruction result reveals that the rosette is apomorphic and has evolved independently at least six times in Selaginella.
Structural Analysis in Transit System Using Network Theory Case of Guadalajara, Mexico
Authors: Barraza Orlando , Estrada Miquel
Published: November 2021

Structural analysis in a transit network is a key aspect used to evaluate in a planning process. In this sense, the use of network science was applied in this work to generate a framework of the main structural features of a transport network. In this case, an alternative transport network in Guadalajara, Mexico was taken as an example. The network properties selected were grade of accessibility, spatial friction, and vulnerability. In the case of the grade of accessibility, this propriety makes reference to the efficiency of the travel time that the network gives due to its structural features. The spatial friction measures how direct in terms of distance the trips that the network provides are, and the vulnerability relates to the ease with which the network can comprise its performance by affectations to their nodes or links. In this sense, this work presents a detailed methodology and a set of open-source tools that can be used to measure these key structural elements for decision making.
Influence of Charging Losses on Energy Consumption and CO2 Emissions of Battery-Electric Vehicles
Authors: Reick Benedikt , Konzept Anja , Kaufmann André , Stetter Ralf , Engelmann Danilo
Published: November 2021

Due to increasing sales figures, the energy consumption of battery-electric vehicles is moving further into focus. In addition to efficient driving, it is also important that the energy losses during AC charging are as low as possible for a sustainable operation. In many situations it is not possible or necessary to charge the vehicle with the maximum charging power e.g., in apartment buildings. The influence of the charging mode (number of phases used, in-cable-control-box or used wallbox, charging current) on the charging efficiency is often unknown. In this work, the energy consumption of two electric vehicles in the Worldwide Harmonized Light-Duty Vehicles Test Cycle is presented. In-house developed measurement technology and vehicle CAN data are used. A detailed breakdown of charging losses, drivetrain efficiency, and overall energy consumption for one of the vehicles is provided. Finally, the results are discussed with reference to avoidable CO2 emissions. The charging losses of the tested vehicles range from 12.79 to 20.42%. Maximum charging power with three phases and 16 A charging current delivers the best efficiencies. Single-phase charging was considered down to 10 A, where the losses are greatest. The drivetrain efficiency while driving is 63.88% on average for the WLTC, 77.12% in the “extra high” section and 23.12% in the “low” section. The resulting energy consumption for both vehicles is higher than the OEM data given (21.6 to 44.9%). Possible origins for the surplus on energy consumption are detailed. Over 100,000 km, unfavorable charging results in additional CO2 emissions of 1.24 t. The emissions for an assumed annual mileage of 20,000 km are three times larger than for a class A+ refrigerator. A classification of charging modes and chargers thus appears to make sense. In the following work, efficiency improvements in the charger as well as DC charging will be proposed.
Optimizing ADM1 Calibration and Input Characterization for Effective Co-Digestion Modelling
Authors: Catenacci Arianna , Grana Matteo , Malpei Francesca , Ficara Elena
Published: November 2021

Anaerobic co-digestion in wastewater treatment plants is looking increasingly like a straightforward solution to many issues arising from the operation of mono-digestion. Process modelling is relevant to predict plant behavior and its sensitivity to operational parameters, and to assess the feasibility of simultaneously feeding a digester with different organic wastes. Still, much work has to be completed to turn anaerobic digestion modelling into a reliable and practical tool. Indeed, the complex biochemical processes described in the ADM1 model require the identification of several parameters and many analytical determinations for substrate characterization. A combined protocol including batch Biochemical Methane Potential tests and analytical determinations is proposed and applied for substrate influent characterization to simulate a pilot-scale anaerobic digester where co-digestion of waste sludge and expired yogurt was operated. An iterative procedure was also developed to improve the fit of batch tests for kinetic parameter identification. The results are encouraging: the iterative procedure significantly reduced the Theil’s Inequality Coefficient (TIC), used to evaluate the goodness of fit of the model for alkalinity, total volatile fatty acids, pH, COD, volatile solids, and ammoniacal nitrogen. Improvements in the TIC values, compared to the first iteration, ranged between 30 and 58%.