bluuebunny/crossref_metadata_2025 huggingface dataset:
A High-Throughput In Vitro Radiobiology Platform for Megavoltage Photon Linear Accelerator Studies
Authors: Thippu Jayaprakash Kamalram , Mostafa Denis , Hussein Mohammad , Shaffer Richard , Michael Agnieszka , Ajaz Mazhar , Nisbet Andrew
Published: January 2022

We designed and developed a multiwell tissue culture plate irradiation setup, and intensity modulated radiotherapy plans were generated for 96-, 24-, and 6-well tissue culture plates. We demonstrated concordance between planned and measured/imaged radiation dose profiles using radiochromic film, a 2D ion chamber array, and an electronic portal-imaging device. Cell viability, clonogenic potential, and γ-H2AX foci analyses showed no significant differences between intensity-modulated radiotherapy and open-field, homogeneous irradiations. This novel platform may help to expedite radiobiology experiments within a clinical environment and may be used for wide-ranging ex vivo radiobiology applications.
EmmDocClassifier: Efficient Multimodal Document Image Classifier for Scarce Data
Authors: Kanchi Shrinidhi , Pagani Alain , Mokayed Hamam , Liwicki Marcus , Stricker Didier , Afzal Muhammad Zeshan
Published: January 2022

Document classification is one of the most critical steps in the document analysis pipeline. There are two types of approaches for document classification, known as image-based and multimodal approaches. Image-based document classification approaches are solely based on the inherent visual cues of the document images. In contrast, the multimodal approach co-learns the visual and textual features, and it has proved to be more effective. Nonetheless, these approaches require a huge amount of data. This paper presents a novel approach for document classification that works with a small amount of data and outperforms other approaches. The proposed approach incorporates a hierarchical attention network (HAN) for the textual stream and the EfficientNet-B0 for the image stream. The hierarchical attention network in the textual stream uses dynamic word embedding through fine-tuned BERT. HAN incorporates both the word level and sentence level features. While earlier approaches rely on training on a large corpus (RVL-CDIP), we show that our approach works with a small amount of data (Tobacco-3482). To this end, we trained the neural network at Tobacco-3482 from scratch. Therefore, we outperform the state-of-the-art by obtaining an accuracy of 90.3%. This results in a relative error reduction rate of 7.9%.
Estimation of SMPS’ Conducted Emission According to CISPR Standards
Authors: Malczyk Robert , Bara Mateusz , Lu Haihui
Published: January 2022

Switched-mode power supplies are very efficient and commonly used components in products nowadays. However, due to currents switched at a high frequency, the conducted emission test is a high concern for designers. The market is increasingly demanding in terms of the size of the components and their efficiency. In order to meet market requirements and reduce the size of the power supply (both built into the product or standalone), the switching frequency of the SMPS is rising; hence the base frequency and its harmonics cover a frequency range of the conducted emission test. Due to this fact, the estimation of the test result becomes a great concern for the designer. This paper describes the approach that one can utilize to estimate the switched-mode power supply’s conducted emission as a standalone component with simulation tools using only the power supply being designed. The workflow, which is the result of this work, can be utilized in order to optimize the design of power suppliers from the conducted emission perspective.
The MINLP Approach to Topology, Shape and Discrete Sizing Optimization of Trusses
Authors: Šilih Simon , Kravanja Zdravko , Kravanja Stojan
Published: January 2022

The paper presents the Mixed-Integer Non-linear Programming (MINLP) approach to the synthesis of trusses. The solution of continuous/discrete non-convex and non-linear optimization problems is discussed with respect to the simultaneous topology, shape and discrete sizing optimization of trusses. A truss MINLP superstructure of different topology and design alternatives has been generated, and a special MINLP model formulation for trusses has been developed. In the optimization model, a mass objective function of the structure has been defined and subjected to design, load and dimensioning constraints. The MINLP problems are solved using the Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm. Multi-level MINLP strategies are introduced to accelerate the convergence of the algorithm. The Modified Two-Phase and the Sequential Two-Phase MINLP strategies are proposed in order to solve highly combinatorial topology, shape and discrete sizing optimization problems. The importance of local buckling constraints on topology optimization is also discussed. Some simple numerical examples are shown at the end of the paper to demonstrate the suitability and efficiency of the proposed method.
Citizens’ Behavior as a Driver of Energy Transition and Greening of the Economy in the Russian Arctic: Findings of a Sociological Survey in the Murmansk Region and Karelia
Authors: Tishkov Sergey , Tleppayev Arsen , Karginova-Gubinova Valentina , Volkov Alexander , Shcherbak Anton
Published: January 2022

Due to the depletion of traditional energy sources, the rising costs of their operation and the need to transition to a sustainable economy, it becomes relevant to increase the share of renewable energy sources in total consumption. The purpose of this study is to determine the role of renewable energy and the establishment of factors determining pro-environmental behavior. The data of the author’s sociological survey of the population of the Arctic regions of Russia and methods of descriptive statistics were used, and regression analysis was carried out. The study shows the ecological and energy characteristics of the Arctic regions of Russia. The main advantages and possibilities of transition to renewable energy sources have been identified. A relationship has been established between the degree of involvement in pro-environmental behavior and knowledge about renewable energy, the perceived importance of environmental problems, age, income, education, amount of waste produced and current electricity costs. It is shown that the degree of involvement in pro-environmental behavior affects the willingness to pay more for renewable energy. A number of institutional measures to promote renewable energy, increase willingness to pay for renewable energy and spread pro-environmental behavior are proposed.
Dynamics and Control of Typical Orbits around Saturn
Authors: Zhan Chaojin , Jiang Yu , Li Hengnian , Liu Yongjie
Published: January 2022

This paper investigates the dynamics of some typical orbits around Saturn, including sun-synchronous orbits, repeating ground track orbits, frozen orbits, and stationary orbits, and corresponding control methods mainly based on the mean element theory. The leading terms of Saturn’s aspheric gravitational field, J2 and J4 terms, are used when designing the orbits around Saturn. Two control methods of sun-synchronous orbits, including initial inclination-biased method and periodic inclination-biased method, are used to damp the local time drift at the descending node, which is caused by solar gravitation and atmospheric drag. The compensation of semimajor axis and maneuver period to maintain the recursive feature of repeating ground orbits are calculated. While only J2 and J3 terms are taken into account, we examine the argument that the perigee of frozen orbits around Saturn should be 270 deg to promise meaningful eccentricity. The perturbations of inclination and eccentricity of stationary orbits due to solar gravitation and solar radiation pressure are presented. Meanwhile, the preliminary control strategies of inclination perturbation and eccentricity perturbation are naturally introduced.
Different Types of Continuous Track Irregularities as Sources of Train-Induced Ground Vibration and the Importance of the Random Variation of the Track Support
Authors: Auersch Lutz
Published: January 2022

Irregularities of the track are a main cause of train-induced ground vibration, and track maintenance is of great importance. Although geometric irregularities at the wheel-rail contact are widely used, other types of irregularities, such as stiffness irregularities, irregularities from different track positions and irregularities in the wave propagation, were analysed in the present study. The track behaviour was investigated by a multi-beam-on-soil model. This track model is coupled with a vehicle model to calculate the vehicle–track interaction. The track model was also used for the track filtering, which transfers a track support error to the equivalent rail irregularity or, conversely, the sharp axle pulse on the rail to a smoother pulse on the soil. In the case in which this filtering varies randomly along the track, the pulses of the moving static load induce a certain ground vibration component (“the scatter of axle pulses”). This effect was calculated by the superposition of axle pulses in the frequency domain and by a stochastic simulation. Simultaneous vehicle, track and soil measurements at a certain site were used to evaluate the different excitation and ground vibration components. The agreement between calculations and axle-box and soil measurements is good. The ground vibrations calculated from rail irregularities and corresponding dynamic loads, however, clearly underestimate the measured ground vibration amplitudes. Only the static load that is moving over a varying track support stiffness can produce the important mid-frequency ground vibration component by the scatter of axle pulses.
Artificial Intelligence and Women Researchers in the Czech Republic
Authors: Lhotska Lenka , Stepankova Olga
Published: January 2022

Artificial intelligence as a research area has been continuously growing for several decades. Many applications were developed in various domains. Medicine and health care have attracted more intensive attention thanks to rapid technological development that has accelerated generation of large volumes of data requiring intelligent analysis and evaluation. This article illustrates, through examples of women researchers and selected AI projects in medicine, the wide spectrum of applications developed during the last fifteen years in the Czech Republic, and in particular at the Czech Technical University in Prague. Women researchers played an important and irreplaceable role since the advent of AI research in the Czech Republic. By their example, they motivated many young female students to join the community and start their research career in the AI area. They frequently participated in research projects led by the senior women researchers. The presented overview of projects illustrates the diversity of the medical area and the potential of AI methods that can be used for solving data- and knowledge-intensive problems. We briefly touch on the AI study programs. In conclusion, we point out the future challenges in AI and its applications in medicine and health care.
Traits and Transports: The Effects of Personality on the Choice of Urban Transport Modes
Authors: Roos John Magnus , Sprei Frances , Holmberg Ulrika
Published: January 2022

We examine the influence of personality on car driving, usage of public transport and cycling. Personality is measured through the Big Five personality traits (i.e., Openness, Conscientiousness, Extraversion, Agreeableness and Neuroticism) and Environmental personality. Data were collected through a Web-based panel of adult citizen in the city of Gothenburg, Sweden (N = 1068). Age, gender, income, children at home and residential area were used as control variables. Car driving is influenced by low degree of Openness, high degree of Conscientiousness, and low degree of Environmental personality. Usage of public transport is influenced by low degree of Conscientiousness, high degree of Agreeableness, and high degree of Environmental personality. Cycling is foremost influenced by a high degree of Environmental personality.
Liposomes as Carriers for the Delivery of Efavirenz in Combination with Glutathione—An Approach to Combat Opportunistic Infections
Authors: Kenchappa Vanaja , Cao Ruoqiong , Venketaraman Vishwanath , Betageri Guru V.
Published: January 2022

Human immunodeficiency virus (HIV)-infected individuals display an enhanced production of reactive oxygen species (ROS). This reduction of antioxidant capacity in host tissues has been related to the decrease in total levels of ROS scavengers such as glutathione (GSH). Prevention of opportunistic infections due to a weakened immune system is becoming a key strategy along with HIV elimination. Research in these directions is clearly warranted, especially a combination of antiretrovirals and antioxidants to ameliorate oxidative stress, improve intracellular uptake and target viral reservoirs. Hence, we aimed to formulate liposomes loaded with the antiretroviral drug efavirenz (EFA) in the presence of glutathione, as these carriers can be engineered to enhance the ability to reach the target reservoirs. The goal of the present work was to investigate the intracellular uptake of EFA-loaded liposome (with and without GSH) by human monocytic leukemia cells (THP-1 cells) and examine cell viability and ROS scavenging activity. Results obtained provided significant data as follows: (i) treatment with EFA and GSH combination could enhance the uptake and reduce cytotoxicity; (ii) encapsulation of EFA into liposomes increased its levels in the macrophages, which was further enhanced in the presence of GSH; (iii) delivery of EFA in the presence of GSH quenched the intracellular ROS, which was significantly higher when delivered via liposomes. Data revealed that a combination of EFA and GSH encompasses advantages; hence, GSH supplementation could be a safe and cost-effective treatment to slow the development of HIV infection and produce an immune-enhancing effect.
Smoke Back-Layering Phenomenon under the Combined External Wind and Stack Effects in a Staircase
Authors: Li Man , Wang Lingling , Chen Junya , Mu Zhenrong , Liu Suqi
Published: January 2022

The external wind can change smoke movement patterns inside the staircase and affect smoke exhaust efficiency. This paper analyzes the smoke back-layering phenomenon in the staircase with open stair doors below the fire floor. The effect of the open stair door location and the heat release rate of fires and external wind velocities on smoke movement patterns are investigated numerically. The external wind ranges from 0–5.5 m/s. At 0 m/s, the smoke back-layering phenomenon driven by pressure difference can be found in the staircase with all stair doors closed. With the increasing wind velocity, four smoke behaviors are identified: upward moving smoke, first downward then upward moving smoke, downward moving smoke, and no smoke. Results show that the back-layering distance is mainly influenced by the external wind and heat release rate of fires. Correlations are modified and used to predict the longest back-layering distance with the first downward then upward moving smoke. This helps with arranging the smoke detectors inside a staircase and the fire safety design of high-rise buildings.
Building a Production-Ready Multi-Label Classifier for Legal Documents with Digital-Twin-Distiller
Authors: Csányi Gergely Márk , Vági Renátó , Nagy Dániel , Üveges István , Vadász János Pál , Megyeri Andrea , Orosz Tamás
Published: January 2022

One of the most time-consuming parts of an attorney’s job is finding similar legal cases. Categorization of legal documents by their subject matter can significantly increase the discoverability of digitalized court decisions. This is a multi-label classification problem, where each relatively long text can fit into more than one legal category. The proposed paper shows a solution where this multi-label classification problem is decomposed into more than a hundred binary classification problems. Several approaches have been tested, including different machine-learning and text-augmentation techniques to produce a practically applicable model. The proposed models and the methodologies were encapsulated and deployed as a digital-twin into a production environment. The performance of the created machine learning-based application reaches and could also improve the human-experts performance on this monotonous and labor-intensive task. It could increase the e-discoverability of the documents by about 50%.
An Ontology-Driven Learning Assessment Using the Script Concordance Test
Authors: Radovic Maja , Petrovic Nenad , Tosic Milorad
Published: January 2022

Assessing the level of domain-specific reasoning acquired by students is one of the major challenges in education particularly in medical education. Considering the importance of clinical reasoning in preclinical and clinical practice, it is necessary to evaluate students’ learning achievements accordingly. The traditional way of assessing clinical reasoning includes long-case exams, oral exams, and objective structured clinical examinations. However, the traditional assessment techniques are not enough to answer emerging requirements in the new reality due to limited scalability and difficulty for adoption in online education. In recent decades, the script concordance test (SCT) has emerged as a promising tool for assessment, particularly in medical education. The question is whether the usability of SCT could be raised to a level high enough to match the current education requirements by exploiting opportunities that new technologies provide, particularly semantic knowledge graphs (SCGs) and ontologies. In this paper, an ontology-driven learning assessment is proposed using a novel automated SCT generation platform. SCTonto ontology is adopted for knowledge representation in SCT question generation with the focus on using electronic health records data for medical education. Direct and indirect strategies for generating Likert-type scores of SCT are described in detail as well. The proposed automatic question generation was evaluated against the traditional manually created SCT, and the results showed that the time required for tests creation significantly reduced, which confirms significant scalability improvements with respect to traditional approaches.
Laser Ablation ICP-MS Analysis of Chemically Different Regions of Rat Prostate Gland with Implanted Cancer Cells
Authors: Ruszczyńska Anna , Skrajnowska Dorota , Jagielska Agata , Bobrowska-Korczak Barbara , Wagner Barbara
Published: January 2022

The comparison of tissues analyzed by LA-ICP-MS is challenging in many aspects, both medical and mathematical. The concept of distinguishing regions of interest (ROIs) was proposed in the literature, allowing for data reduction and targeted comparative analysis. ROIs can be drawn before any analysis, by indicating the anatomical parts of tissue, or after the first step of analysis, by using elemental distribution maps and characteristic regions of enrichment in selected elements. A simple method for identifying different regions, without the manual extraction of image fragments, is highly needed in biological experiments, where large groups of individuals (with samples taken from each of them) is very common. In the present study, two ROIs were distinguished: (1) tissue-rich in fat (and tissue-poor in water); and (2) tissue-rich in water (and tissue-poor in fat). ROIs were extracted mathematically, using an algorithm based on the relationship between 13C and 23Na signal intensities. A cut-off point was indicated in the point of the simultaneous decrease in 13C and increase in 23Na signal intensity. Separate analyses of chemically different ROIs allow for targeted comparison, which is a great advantage of laser ablation over liquid introductions to ICP-MS. In the present experiment, tissues were provided from animals with implanted prostate cancer cells as well as supplemented with mineral compounds particularly important both for prostate gland functions (Zn and Se) and neoplastic processes (Ca, Fe, and Cu). One of the goals was to try to determine whether dietary supplementation qualitatively and quantitatively affects the mineral composition of the prostate gland.
Cardioprotective Mechanisms of Interrupted Anesthetic Preconditioning with Sevoflurane in the Setting of Ischemia/Reperfusion Injury in Rats
Authors: Popescu Mihaela Roxana , Pavel Bogdan , Isvoranu Gheorghita , Ceafalan Laura Cristina , Panaitescu Anca Maria , Sava Ruxandra Irina , Vlad Adelina , Zagrean Leon
Published: January 2022

Background: Anesthetic preconditioning (AP) is known to mimic ischemic preconditioning. The purpose of this study was to investigate the effects of an interrupted sevoflurane administration protocol on myocardial ischemia/reperfusion (I/R) injury. Methods: Male Wistar rats (n = 60) were ventilated for 30 min with room air (control group, CG) or with a mixture of air and sevoflurane (1 minimum alveolar concentration—MAC) in 5-min cycles, alternating with 5-min wash-out periods (preconditioned groups). Cytokines implicated in the AP response were measured. An (I/R) lesion was produced immediately after the sham intervention (CG) and preconditioning protocol (early AP group, EAPG) or 24 h after the intervention (late AP group, LAPG). The area of fibrosis, the degree of apoptosis and the number of c-kit+ cells was estimated for each group. Results: Cytokine levels were increased post AP. The area of fibrosis decreased in both EAPG and LAPG compared to the CG (p < 0.0001). When compared to the CG, the degree of apoptosis was reduced in both LAPG (p = 0.006) and EAPG (p = 0.007) and the number of c-kit+ cells was the greatest for the LAPG (p < 0.0001). Conclusions: Sevoflurane preconditioning, using an interrupted anesthesia protocol, is efficient in myocardial protection and could be beneficial to reduce perioperative or periprocedural ischemia in patients with increased cardiovascular risk.
System Invariant Method for Ultrasonic Flaw Classification in Weldments Using Residual Neural Network
Authors: Park Jinhyun , Lee Seung-Eun , Kim Hak-Joon , Song Sung-Jin , Kang Sung-Sik
Published: January 2022

The industrial use of ultrasonic flaw classification using neural networks in weldments must overcome many challenges. A major constraint is the use of numerous systems, including a combination of transducers and equipment. This causes high complexity in the datasets used in the training of neural networks, which decreases performance. In this study, the performance of a neural network was enhanced using signal processing on an ultrasonic weldment flaw dataset to achieve system invariance. The dataset contained 5839 ultrasonic flaw signals collected by various types of transducers connected to KrautKramer USN60. Every signal in the dataset was from 45 FlawTech/Sonaspection weldment specimens with five types of flaw: crack, lack of fusion, slag inclusion, porosity, and incomplete penetration. The neural network used in this study is a residual neural network with 19 layers. The performance evaluation of the same network structure showed that the original database can achieve 62.17% ± 4.13% accuracy, and that the invariant database using the system invariant method can achieve 91.45% ± 1.77% accuracy. The results demonstrate that using a system invariant method for ultrasonic flaw classification in weldments can improve the performance of a neural network with a highly complex dataset.
Improving the Accuracy of Predictive Models for Outcomes of Antidepressants by Using an Ontological Adjustment Approach
Authors: Min Hua , Alemi Farrokh , Hane Christopher A. , Nori Vijay S.
Published: January 2022

For patients with rare comorbidities, there are insufficient observations to accurately estimate the effectiveness of treatment. At the same time, all diagnosis, including rare diagnosis, are part of the International Classification of Disease (ICD). Grouping ICD into broader concepts (i.e., ontology adjustment) can not only increase accuracy of estimating antidepressant effectiveness for patients with rare conditions but also prevent overfitting in big data analysis. In this study, 3,678,082 depressed patients treated with antidepressants were obtained from OptumLabs® Data Warehouse (OLDW). For rare diagnoses, adjustments were made by using the likelihood ratio of the immediate broader concept in the ICD hierarchies. The accuracy of models in training (90%) and test (10%) sets was examined using the area under the receiver operating curves (AROC). The gap in training and test AROC shows how much random noise was modeled. If the gap is large, then the parameters of the model, including the reported effectiveness of the antidepressant for patients with rare conditions, are suspect. There was, on average, a 9.0% reduction in the AROC gap after using the ontological adjustment. Therefore, ontology adjustment can reduce model overfitting, leading to better parameter estimates from the training set.
Effect of Post-Activation Potentiation on Sprint Performance after Combined Electromyostimulation and Back Squats
Authors: Sari Cengizhan , Koz Mitat , Salcman Vaclav , Gabrys Tomasz , Karayigit Raci
Published: January 2022

Post-activation potentiation (PAP) is a phenomenon which can improve force performance executed after a previous conditioning activity. PAP is usually evoked through heavy resistance, but many new methods are being suggested that acutely improve performance in post-activation potentiation protocols. The purpose of this study was to examine the effect of simultaneous application of Smith machine back squats (BS) with electromyostimulation (EMS) on sprint performance. Sixteen male (age = 22.9 ± 2.3 years, body mass = 79.9 ± 13.8 kg, BS one-repetition maximum (1 RM) = 120.5 ± 17.3) amateur football and rugby players volunteered for this study. Participants randomly performed PAP protocols (CON = no load, BS = 3 × 85% of 1 RM BS, EMS = 3 × weightless squat with electric current and BS + EMS = 3 × 85% 1 RM BS with electric current) on four different days with at least 48 h intervals. Participants rested passively for 7 min after preloads and performed the 30 m sprint test. Sprint times for 10 and 30 m were recorded for each condition. As a result, no significant difference was found in the 10 m (p = 0.13) and 30 m (p = 0.10) sprint performance between the preload protocols. The effect size was found to be trivial (ηp2: 0.13 for 10 m; ηp2: 0.11 for 30 m). In individual results, the 10 m sprint performance of five participants and 30 m sprint performance of two participants decreased in BS, EMS, or BS + EMS conditions compared with CON. No PAP effect in other participants was observed. In conclusion, preloads did not affect 10 m and 30 m sprint performance of football and rugby players. It can be said that the applied PAP protocols or physical exertion alone may cause fatigue in some individuals.
Evaluation of Skeletal, Dentoalveolar, and Sagittal Airway Changes Induced by the Mandibular Anterior Repositioning Appliance (MARA) in Class II Malocclusion: A Retrospective Controlled Study on Lateral Cephalograms
Authors: Statie Maria Denisa , Franceschi Debora , Pierleoni Felicita , Barone Valeria , Popovic Nenad , Nardi Cosimo , Franchi Lorenzo , Giuntini Veronica
Published: January 2022

The aim of the study was to evaluate the changes in skeletal, dentoalveolar, and airway dimensions induced by the mandibular anterior repositioning appliance (MARA) in the treatment of Class II malocclusion. A group of 24 Class II patients treated with MARA was evaluated with lateral cephalograms at the start (13.8 ± 2 years) and at the end of treatment (15.7 ± 1.9 years) and compared with a matched untreated Class II group of 20 subjects selected from the archive of the AOOF Legacy. Statistical comparisons were performed with the Student’s t-test. No significant differences were observed for the sagittal airway dimensions. The MARA group showed a significant improvement of Wits (−1.4 mm; p = 0.009) and ANB angle (−0.6°; p = 0.038), a reduction in the overjet (−1.9 mm; p = 0.001), of the overbite (−1.5 mm; p = 0.005), an improvement of molar relationship (1.8 mm; p = 0.000) and a proclination of the lower incisors (2.7°; p = 0.012). During active treatment, MARA did not produce significant favorable changes in the sagittal airway dimensions in Class II subjects when compared with untreated controls. Clinically, these findings highlighted that MARA was able to provide an effective correction of Class II malocclusion with favorable dentoskeletal changes.
Biorefinery Processing of Waste to Supply Cost-Effective and Sustainable Inputs for Two-Stage Microalgal Cultivation
Authors: Wensel Pierre C. , Bule Mahesh , Gao Allan , Pelaez-Samaniego Manuel Raul , Yu Liang , Hiscox William , Helms Gregory L. , Davis William C. , Kirchhoff Helmut , Garcia-Perez Manuel , Chen Shulin
Published: January 2022

Overcoming obstacles to commercialization of algal-based processes for biofuels and co-products requires not just piecemeal incremental improvements, but rather a comprehensive and fundamental re-consideration starting with the selected algae and its associated cultivation, harvesting, biomass conversion, and refinement. A novel two-stage process designed to address challenges of mass outdoor microalgal cultivation for biofuels and co-products was previously demonstrated using an oleaginous, haloalkaline-tolerant, and multi-trophic green Chlorella vulgaris. ALP2 from a soda lake. This involved cultivating the microalgae in a fermenter heterotrophically or photobioreactor mixotrophically (first-stage) to rapidly obtain high cell densities and inoculate an open-pond phototrophic culture (second-stage) featuring high levels of NaHCO3, pH, and salinity. An improved two-stage cultivation that instead sustainably used as more cheap and sustainable inputs the organic carbon, nitrogen, and phosphorous from fractionation of waste was here demonstrated in a small-scale biorefinery process. The first cultivation stage consisted of two simultaneous batch flask cultures featuring (1) mixotrophic cell productivity of 7.25 × 107 cells mL−1 day−1 on BG-110 medium supplemented with 1.587 g L−1 urea and an enzymatic hydrolysate of pre-treated (torrefaction + grinding + ozonolysis + soaking ammonia) wheat-straw that corresponded to 10 g L−1 glucose, and (2) mixotrophic cell productivity of 2.25 × 107 cells mL−1 day−1 on BG-110 medium supplemented with 1.587 g L−1 urea and a purified and de-toxified condensate of pre-treated (torrefaction + grinding) wheat straw that corresponded to 0.350 g L−1 of potassium acetate. The second cultivation stage featured 1H NMR-determined phototrophic lipid productivity of 0.045 g triacylglycerides (TAG) L−1 day−1 on BG-110 medium supplemented with 16.8 g L−1 NaHCO3 and fed batch-added 22% (v/v) anaerobically digested food waste effluent at HCl-mediated pH 9.
A Blockchain and Metaheuristic-Enabled Distributed Architecture for Smart Agricultural Analysis and Ledger Preservation Solution: A Collaborative Approach
Authors: Khan Abdullah Ayub , Shaikh Zaffar Ahmed , Belinskaja Larisa , Baitenova Laura , Vlasova Yulia , Gerzelieva Zhanneta , Laghari Asif Ali , Abro Abdul Ahad , Barykin Sergey
Published: January 2022

Distributed forecasting of agriculture commodity prices has an attractive research perspective that delivers active breakthrough analysis of the rapid fluctuations in pricing forecasts for participating stakeholders without being manually dispatched lists. The increased use of an efficient forecasting mechanism for the agriculture information management of generated records and processing creates emerging challenges and limitations. These include new government mandates and regulations, the price of land for expansion, forecasting the growing demand for commodities, fluctuations in the global financial market, food security, and bio-based fuels. Building and deploying distributed dynamic scheduling, management, and monitoring systems of agricultural activities for commodity price forecasting and supply chains require a significant secure and efficient approach. Thus, this paper discusses a collaborative approach where two different folds are demonstrated to cover distinct aspects with different objectives. A metaheuristic-enabled genetic algorithm is designed to receive day-to-day agricultural production details and process and analyze forecast pricing from the records by scheduling, managing, and monitoring them in real-time. The blockchain hyperledger sawtooth distributed modular technology provides a secure communication channel between stakeholders, a private network, protects the forecasting ledger, adds and updates commodity prices, and preserves agricultural information and node transactions in the immutable ledger (IPFS). To accomplish this, we design, develop, and deploy two distinct smart contracts to register the system’s actual stakeholders and allow for the addition of node transactions and exchanges. The second smart contract updates the forecasting commodity pricing ledger and distributes it to participating stakeholders while preserving detailed addresses in storage. The simulation results of the proposed collaborative approach deliver an efficient E-agriculture commodity price forecast with an accuracy of 95.3%. It also maintains ledger transparency, integrity, provenance, availability, and secure operational control and access of agricultural activities.
Wind-Induced Response and Its Controlling of Long-Span Cross-Rope Suspension Transmission Line
Authors: Li Zhengliang , Hu Yujing , Tu Xi
Published: January 2022

In mountainous areas, the installation of steel towers was the major obstacle to the construction of transmission lines. In long-span cross-rope suspension (CRS) structures, the conductors are supported by hundreds-meters-long suspension cables crossing valleys instead of steel towers. Though long-span CRS is an innovative structural system, its structural performance needs to be clarified. Firstly, an assembled FE model was established based on initial deformed components for long-span cross-rope suspension structure. The wind load response of long-span cross-rope suspension structure with different lengths or number of spans was established and analyzed. Vortex-induced vibration (VIV), which was the major factor regarding fatigue and service life, and its controlling by Stockbridge damper for a long-span CRS were discussed. The numerical simulation results showed that the tensile force of the suspension cable increased with the length and number of spans of the conductor. In addition, considering the ice covering the transmission line, the interaction between the wind load and ice load induced the nonlinear lateral deformation characteristics of the conductor. Moreover, the vibration characteristics of the conductor in the long-span CRS were studied and compared with the traditional tower-line system. An analysis of the long-span CRS with a Stockbridge damper showed that additional dampers were essential for controlling the maximum dynamic bending stress of conductors at both ends.
HAADF STEM and Ab Initio Calculations Investigation of Anatase TiO2/LaAlO3 Heterointerface
Authors: Islam Mahabul , Rajak Piu , Knez Daniel , Chaluvadi Sandeep Kumar , Orgiani Pasquale , Rossi Giorgio , Dražić Goran , Ciancio Regina
Published: January 2022

The understanding of the origin of a two-dimensional electron gas (2DEG) at the surface of anatase TiO2 remains a challenging issue. In particular, in TiO2 ultra-thin films, it is extremely difficult to distinguish intrinsic effects, due to the physics of the TiO2, from extrinsic effects, such as those arising from structural defects, dislocations, and the presence of competing phases at the film/substrate interface. It is, therefore, mandatory to unambiguously ascertain the structure of the TiO2/substrate interface. In this work, by combining high angle annular dark-field scanning transmission electron microscopy (HAADF-STEM), density functional theory calculations, and multislice image simulations, we have investigated the nature of strainless anatase TiO2 thin films grown on LaAlO3 substrate. In particular, the presence of oxygen vacancies in anatase TiO2 has been proved to stabilize the formation of an extra alloy layer, Ti2AlO4, by means of interface rearrangement. Our results, therefore, elucidate why the growth of anatase TiO2 directly on LaAlO3 substrate has required the deposition of a TiOx extra-layer to have a 2DEG established, thus confirming the absence of a critical thickness for the TiO2 to stabilize a 2DEG at its surface. These findings provide fundamental insights on the underlying formation mechanism of the 2DEG in TiO2/LAO hetero-interfaces to engineer the 2DEG formation in anatase TiO2 for tailored applications.
An Improved Aeromagnetic Compensation Method Robust to Geomagnetic Gradient
Authors: Feng Yongqiang , Zhang Qimao , Zheng Yaoxin , Qu Xiaodong , Wu Fang , Fang Guangyou
Published: January 2022

Aeromagnetic surveys play an important role in many fields, for example, archaeology, anti-submarine warfare, and geophysical exploration. Being in the geomagnetic field, the aircraft generates a great deal of magnetic interference, resulting in bad performance during detection surveys. Thus, it is necessary and important to perform aeromagnetic compensation in advance. Conventional aeromagnetic compensation methods consider that the geomagnetic gradient is approximately zero after bandpass filtering, bringing about the inaccuracy of compensation coefficients. To address this issue, an improved aeromagnetic compensation method robust to geomagnetic gradient is proposed. In this study, the International Geomagnetic Reference Field (IGRF) model was employed to model the geomagnetic gradient. Then, the estimated geomagnetic gradient was subtracted from the measured data, which improved the accuracy of the compensation equations. Field experiments were conducted to verify the effectiveness of the proposed method. The experimental results show that compared to the traditional method, the compensation performance of the proposed method was improved by 152% to 329%. For the level flight, the standard deviation of residual noise after compensation can be as low as 3.3pT. The results indicate that the proposed method can significantly improve the compensation effect, showing great benefits for weak magnetic anomaly detection.
Energy-Aware Multi-Objective Job Shop Scheduling Optimization with Metaheuristics in Manufacturing Industries: A Critical Survey, Results, and Perspectives
Authors: Para Jesus , Del Ser Javier , Nebro Antonio J.
Published: January 2022

In recent years, the application of artificial intelligence has been revolutionizing the manufacturing industry, becoming one of the key pillars of what has been called Industry 4.0. In this context, we focus on the job shop scheduling problem (JSP), which aims at productions orders to be carried out, but considering the reduction of energy consumption as a key objective to fulfill. Finding the best combination of machines and jobs to be performed is not a trivial problem and becomes even more involved when several objectives are taken into account. Among them, the improvement of energy savings may conflict with other objectives, such as the minimization of the makespan. In this paper, we provide an in-depth review of the existing literature on multi-objective job shop scheduling optimization with metaheuristics, in which one of the objectives is the minimization of energy consumption. We systematically reviewed and critically analyzed the most relevant features of both problem formulations and algorithms to solve them effectively. The manuscript also informs with empirical results the main findings of our bibliographic critique with a performance comparison among representative multi-objective evolutionary solvers applied to a diversity of synthetic test instances. The ultimate goal of this article is to carry out a critical analysis, finding good practices and opportunities for further improvement that stem from current knowledge in this vibrant research area.
Improving Graph-Based Movie Recommender System Using Cinematic Experience
Authors: Lee CheonSol , Han DongHee , Han Keejun , Yi Mun
Published: January 2022

With the advent of many movie content platforms, users face a flood of content and consequent difficulties in selecting appropriate movie titles. Although much research has been conducted in developing effective recommender systems to provide personalized recommendations based on customers’ past preferences and behaviors, not much attention has been paid to leveraging users’ sentiments and emotions together. In this study, we built a new graph-based movie recommender system that utilized sentiment and emotion information along with user ratings, and evaluated its performance in comparison to well known conventional models and state-of-the-art graph-based models. The sentiment and emotion information were extracted using fine-tuned BERT. We used a Kaggle dataset created by crawling movies’ meta-data and review data from the Rotten Tomatoes website and Amazon product data. The study results show that the proposed IGMC-based models coupled with emotion and sentiment are superior over the compared models. The findings highlight the significance of using sentiment and emotion information in relation to movie recommendation.
Communication Aspects about Heat in an Era of Global Warming—The Lessons Learnt by Germany and Beyond
Authors: Matzarakis Andreas
Published: January 2022

Heat is a specific issue in terms of climate change due to the negative effects on morbidity/mortality and on human health in general [...]
PM Dimensional Characterization in an Urban Mediterranean Area: Case Studies on the Separation between Fine and Coarse Atmospheric Aerosol
Authors: Manigrasso Maurizio , Soggiu Maria Eleonora , Settimo Gaetano , Inglessis Marco , Protano Carmela , Vitali Matteo , Avino Pasquale
Published: January 2022

Fine particulate matter (PM) is object of particular attention due to its health effects. It is currently regulated by adopting PM2.5 as an indicator to control anthropogenic combustion emissions. Therefore, it is crucial to collect aerosol samples representative of such sources, without including PM from natural sources. Thus, a clean separation between coarse and fine mode aerosol should be set. With this purpose, aerosol size mass distribution was taken in the aerodynamic diameter range from 0.5 to 10 µm. In comparison with a base scenario, characterized by local pollution sources, three case studies were considered, involving desert dust advection, sea salt advection and forest fire aerosol from a remote area. In the base scenario, PM2.5 represented a suitable fine-mode indicator, whereas it was considerably affected by coarse PM in case of desert dust and sea salt aerosol advection. Such interference was considerably reduced by setting the fine/coarse separation at 1.0 µm. Such separation underrepresented fine PM from forest fire long-range transport, nonetheless in the case studies considered, PM1 represented the best indicator of fine aerosol since less affected by coarse natural sources. The data presented clearly support the results from other studies associating the health effects of PM2.5 to PM1, rather than to PM1–2.5. Overall, there is a need to reconsider PM2.5 as an indicator of fine atmospheric aerosol.
Application of 3D Embedded Discrete Fracture Model for Simulating CO2-EOR and Geological Storage in Fractured Reservoirs
Authors: Du Xulin , Cheng Linsong , Cao Renyi , Zhou Jinchong
Published: January 2022

For greenhouse gas control and environment protection, CO2 emission reduction has become a hot spot in global research. CO2 injection in developed oil reservoirs to enhance oil recovery is widely regarded as one of the most economical and promising measures for reducing anthropogenic CO2 emissions into the atmosphere. In this paper, a three-dimensional embedded discrete fracture model is proposed and applied to simulate CO2 flooding and geological storage processes in hydraulically fractured reservoirs. The gas injection is simplified as a two-phase two-component mathematical model with the varying pressure-related fluid physical properties, and its accuracy is verified by commercial software tNavigator®. The advantage of this model is that it can deal with the complex geological conditions of three-dimensional arbitrary-inclined fracture networks and accurately assess the effects of CO2-EOR and geological sequestration in real reservoirs. Two application cases of CO2 huff-and-puff with a single well and inter-fracture asynchronous injection and production are demonstrated and explained in detail. The optimized technological parameters and CO2 saturation distribution can provide key technical parameters for field operations.
Teleconnections of Large-Scale Climate Patterns to Regional Drought in Mid-Latitudes: A Case Study in Xinjiang, China
Authors: Yang Ruting , Xing Bing
Published: January 2022

Drought is one of the most important environmental disasters. Assessment of the effects of oceanic atmospheric oscillations upon regional drought behavior has valuable implications for water resources management, especially for arid regions. This study aims to explore the climate drivers of drought conditions in Xinjiang, an arid region in mid-latitude Asia. Standardized Precipitation Evapotranspiration Index (SPEI) was adopted to describe drought variation over Xinjiang during the period of 1951–2020. Teleconnection effects of El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), and Arctic Oscillation (AO) on Xinjiang drought variability were analyzed based on cross-correlation and stepwise regression methods. Partial correlation analysis was applied to discuss the responding mechanism of drought behavior to teleconnection signals from the perspective of regional climate factors. Findings from this study indicate that synchronous ENSO featured by Nino3.4 index has a significant positive correlation with Xinjiang dry/wet variation. El Niño may favor to wetness in Xinjiang, while La Niña may exacerbate drought effect in the region. ENSO mainly acts on the short-term drought variability in Xinjiang region. The synchronous PDO makes a leading contribution on drought variation at 12-month time scale among the four signals. The significant positive correlation between PDO and drought variation suggests that positive-phase (negative-phase) PDO may contribute to wetting (drying) epochs in Xinjiang region. AMO indicates a significant negative correlation with Xinjiang drought on both synchronous and asynchronous modes. Positive (negative) phase AMO may favor to dry (wet) effects in Xinjiang. AMO appears a predominant teleconnection effect on long-term drought variability, and fluctuates a persistent anti-phase mode with Xinjiang dry/wet variability since the mid-1980s. AO mainly acts on short-term drought fluctuations, indicating a significant negative correlation with drought behavior within a 12-month moving time window. Positive (negative) phase AO may contribute to dry (wet) epochs over Xinjiang. ENSO and PDO affect short-term dry/wet variation mainly through the teleconnection effect on precipitation variability. AMO mainly influences Xinjiang drought evolution by acting on regional temperature variation. The influence of internal atmospheric variability on regional climate behavior has a delayed effect, and drought variability is affected by precursor pattern of teleconnection likewise.