bluuebunny/crossref_metadata_2025 huggingface dataset:
Shell Waste Management and Utilization: Mitigating Organic Pollution and Enhancing Sustainability
Authors: Topić Popović Natalija , Lorencin Vanesa , Strunjak-Perović Ivančica , Čož-Rakovac Rozelindra
Published: January 2023

Every year, close to 8 million tons of waste crab, shrimp and lobster shells are produced globally, as well as 10 million tons of waste oyster, clam, scallop and mussel shells. The disposed shells are frequently dumped at sea or sent to landfill, where they modify soils, waters and marine ecosystems. Waste shells are a major by-product, which should become a new raw material to be used to the best of their potential. There are a number of applications for waste shells in many fields, such as agriculture, medicine, chemical production, construction, environmental protection, cosmetic industry, food and feed industry, and a plethora of other (often niche) applications, which are being developed by the day. This review provides a broad picture of crustacean and mollusc shell waste management and reutilization possibilities, reviewing well established, current, and potential strategies, particularly from the standpoint of sustainability challenges and energy demand.
Mathematical Model for Determining the Time of Preventive Replacements in the Agricultural Machinery Service System with Minimal Repair
Authors: Borowski Sylwester , Szubartowski Mirosław , Migawa Klaudiusz , Sołtysiak Agnieszka , Neubauer Andrzej , Hujo L’ubomír , Nosian Jozef
Published: January 2023

In this paper, a semi-Markov model for determining the optimal time for preventive replacements according to the age of technical objects is presented. In the analyzed system of transportation, due to its specific characteristics, the basic type of renewal process carried out is minimal repair. Minimal repairs of technical objects in semi-Markov models have been analyzed in the literature to date. In the system studied, the technical objects (sets of agricultural tractors with trailers), due to the continuous operation of combine harvesters, should carry out the assigned tasks of transporting agricultural crops without interruption. The damage to agricultural tractors that arises during the implementation of transport tasks should be repaired in the shortest possible time. The repairs to damaged tractors are carried out primarily by the Technical Emergency Service and, due to their purpose and scope, may be considered minimal repairs. The effectiveness of the function of the tested technical objects is analyzed by two criteria functions, which are very important for the system managers. These are profit per unit of time and availability. In the analyzed case, it is the availability to carry out the assigned transport tasks. The conditions for the existence of a maximum of criterion functions have been written for the assumptions. The analyzes carried out, which are presented in the work, are illustrated with sample calculations. It has been proven that, under general assumptions, the criterion functions considered in the paper have exactly one maximum. On the basis of the conducted analysis, sufficient conditions for the existence of a maximum of these functions were formulated. In the analyzed transport system, it is possible to increase the efficiency of the function of the technical facilities in use as a result of planning additional preventive replacements (increasing the frequency of these replacements). This is especially important for a system where transport units must have high availability.
Metabolomic Profiling in Patients with Different Hemodynamic Subtypes of Severe Aortic Valve Stenosis
Authors: Bengel Philipp , Elkenani Manar , Beuthner Bo E. , Pietzner Maik , Mohamed Belal A. , Pollok-Kopp Beatrix , Krätzner Ralph , Toischer Karl , Puls Miriam , Fischer Andreas , Binder Lutz , Hasenfuß Gerd , Schnelle Moritz
Published: January 2023

Severe aortic stenosis (AS) is a common pathological condition in an ageing population imposing significant morbidity and mortality. Based on distinct hemodynamic features, i.e., ejection fraction (EF), transvalvular gradient and stroke volume, four different AS subtypes can be distinguished: (i) normal EF and high gradient, (ii) reduced EF and high gradient, (iii) reduced EF and low gradient, and (iv) normal EF and low gradient. These subtypes differ with respect to pathophysiological mechanisms, cardiac remodeling, and prognosis. However, little is known about metabolic changes in these different hemodynamic conditions of AS. Thus, we carried out metabolomic analyses in serum samples of 40 AS patients (n = 10 per subtype) and 10 healthy blood donors (controls) using ultrahigh-performance liquid chromatography–tandem mass spectroscopy. A total of 1293 biochemicals could be identified. Principal component analysis revealed different metabolic profiles in all of the subgroups of AS (All-AS) vs. controls. Out of the determined biochemicals, 48% (n = 620) were altered in All-AS vs. controls (p < 0.05). In this regard, levels of various acylcarnitines (e.g., myristoylcarnitine, fold-change 1.85, p < 0.05), ketone bodies (e.g., 3-hydroxybutyrate, fold-change 11.14, p < 0.05) as well as sugar metabolites (e.g., glucose, fold-change 1.22, p < 0.05) were predominantly increased, whereas amino acids (e.g., leucine, fold-change 0.8, p < 0.05) were mainly reduced in All-AS. Interestingly, these changes appeared to be consistent amongst all AS subtypes. Distinct differences between AS subtypes were found for metabolites belonging to hemoglobin metabolism, diacylglycerols, and dihydrosphingomyelins. These findings indicate that relevant changes in substrate utilization appear to be consistent for different hemodynamic subtypes of AS and may therefore reflect common mechanisms during AS-induced heart failure. Additionally, distinct metabolites could be identified to significantly differ between certain AS subtypes. Future studies need to define their pathophysiological implications.
Herbs as a Source for the Treatment of Polycystic Ovarian Syndrome: A Systematic Review
Authors: Lakshmi Jada Naga , Babu Ankem Narendra , Kiran S. S. Mani , Nori Lakshmi Prasanthi , Hassan Nageeb , Ashames Akram , Bhandare Richie R. , Shaik Afzal B.
Published: January 2023

Background: Polycystic ovarian syndrome (PCOS) is a neuroendocrine metabolic disorder characterized by an irregular menstrual cycle. Treatment for PCOS using synthetic drugs is effective. However, PCOS patients are attracted towards natural remedies due to the effective therapeutic outcomes with natural drugs and the limitations of allopathic medicines. In view of the significance of herbal remedies, herein, we discuss the role of different herbs in PCOS. Methods: By referring to the Scopus, PubMed, Google Scholar, Crossref and Hinari databases, a thorough literature search was conducted and data mining was performed pertaining to the effectiveness of herbal remedies against PCOS. Results: In this review, we discuss the significance of herbal remedies in the treatment of PCOS, and the chemical composition, mechanism of action and therapeutic application of selected herbal drugs against PCOS. Conclusions: The present review will be an excellent resource for researchers working on understanding the role of herbal medicine in PCOS.
Pristine TiO2 and Sr-Doped TiO2 Nanostructures for Enhanced Photocatalytic and Electrocatalytic Water Splitting Applications
Authors: Fazil Mohd , Ahmad Tokeer
Published: January 2023

Pristine TiO2 and Sr-doped TiO2 (1%, 2.5% and 5%) nanoparticles were synthesized at low temperatures via an eco-friendly hydrothermal route for water-splitting applications. XRD, EDAX and Raman analysis were performed to analyze the crystallinity, purity and structure of the as-synthesized materials. TEM, SEM, BET and UV-DRS studies were carried out to elucidate the size, morphology, surface area and optoelectronic properties of the nanoparticles. High surface areas of 169, 182, 178 and 141.16 m2 g−1 for pristine TiO2 (12 ± 0.6 nm) and 1% (11.1 ± 0.6 nm), 2.5% (12.1 ± 0.6 nm) and 5% (13 ± 0.7 nm) Sr-doped TiO2 nanoparticles were obtained, respectively. One-percent Sr-doped TiO2 nanoparticles were found to be active photocatalysts, as they showed higher hydrogen production (26.30 mmolgcat−1). Furthermore, electrocatalysis was investigated for HER and OER in 0.5 N H2SO4 and 0.1 N KOH electrolytic solutions using calomel as a reference electrode, revealing that 1% and 5% Sr-doped TiO2 showed maximum current density for both HER (≈10 mA/cm2) and OER (≈2.49 mA/cm2), with an onset potential of 0.96 V for HER and 1.55 V for OER, and Tafel slopes of 84.09 and 91.60 mV/dec, respectively.
Role of Chiral Skeleton in Chiral Phosphoric Acids Catalyzed Asymmetric Transfer Hydrogenation: A DFT Study
Authors: Li Xu , Dong Shanshan , Fan Ting , Wang Qingji , Shi Tongfei
Published: January 2023

Chiral phosphoric acids (CPAs) have received considerable attention due to their high activity for enantioselective transformations. However, the role of various chiral skeletons of CPAs in regulating the mechanism and enantioselectivity of asymmetric transfer hydrogenation has remained unclear. Density functional theory (DFT) calculations are performed to elucidate the role of chiral skeletons on the acidity, mechanism, enantioselectivity, and kinetic stabilities of transition states (TSs) in Asymmetric Transfer Hydrogen (ATH) reaction catalyzed by five CPAs. We found that the acidity of CPAs is strongly dependent on the chiral skeleton. The origin of enantioselectivity of ATH reaction arises from the differential noncovalent interactions between TSs and CPAs. Moreover, the shape and size of the catalyst pocket depending on chiral skeletons play key roles in the stability of TSs and the enantioselectivity of ATH. This study might facilitate to design and computationally screening of CPAs and guide the strategic choice of CPA skeletons to reduce the experimental workload.
Editorial: Highlights in Autophagy—From Basic Mechanisms to Human Disorder Treatments
Authors: Lin Pei-Hui , Combaret Lydie
Published: January 2023

Autophagy is an evolutionarily conserved catabolic process and represents a field of research that is constantly growing [...]
Maternal Hyperhomocysteinemia Disturbs the Mechanisms of Embryonic Brain Development and Its Maturation in Early Postnatal Ontogenesis
Authors: Vasilev Dmitrii S. , Shcherbitskaia Anastasiia D. , Tumanova Natalia L. , Mikhel Anastasiia V. , Milyutina Yulia P. , Kovalenko Anna A. , Dubrovskaya Nadezhda M. , Inozemtseva Daria B. , Zalozniaia Irina V. , Arutjunyan Alexander V.
Published: January 2023

Maternal hyperhomocysteinemia causes the disruption of placental blood flow and can lead to serious disturbances in the formation of the offspring’s brain. In the present study, the effects of prenatal hyperhomocysteinemia (PHHC) on the neuronal migration, neural tissue maturation, and the expression of signaling molecules in the rat fetal brain were described. Maternal hyperhomocysteinemia was induced in female rats by per os administration of 0.15% aqueous methionine solution in the period of days 4–21 of pregnancy. Behavioral tests revealed a delay in PHHC male pups maturing. Ultrastructure of both cortical and hippocampus tissue demonstrated the features of the developmental delay. PHHC was shown to disturb both generation and radial migration of neuroblasts into the cortical plate. Elevated Bdnf expression, together with changes in proBDNF/mBDNF balance, might affect neuronal cell viability, positioning, and maturation in PHHC pups. Reduced Kdr gene expression and the content of SEMA3E might lead to impaired brain development. In the brain tissue of E20 PHHC fetuses, the content of the procaspase-8 was decreased, and the activity level of the caspase-3 was increased; this may indicate the development of apoptosis. PHHC disturbs the mechanisms of early brain development leading to a delay in brain tissue maturation and formation of the motor reaction of pups.
The Role of Instability Indices in Forecasting Thunderstorm and Non-Thunderstorm Days across Six Cities in India
Authors: Arora Kopal , Ray Kamaljit , Ram Suresh , Mehajan Rajeev
Published: January 2023

Thunderstorms are one of the most damaging natural hazards demanding in-depth understanding and prediction. These convective systems form in an unstable environment which is quantitatively expressed in terms of instability indices. These indices are studied over six locations across the Indian landmass in an attempt to predict thunderstorm activity on any given day. A combination of multiple regression, logistic regression, and range analysis provides new insight into the prediction of these storms. A supervised machine learning-based logistic regression model is developed in this study for thunderstorm prediction over Patna and can be further extended for operational forecasting of Thunderstorms over the region. Critical thresholds for the instability indices are determined over the considered locations providing valuable insight into the domain of Thunderstorm prediction
Radiation Therapy for Retroperitoneal Sarcomas: A Strass-Ful Situation
Authors: Farooqi Ahsan S. , Guadagnolo B. Ashleigh , Mitra Devarati , Bishop Andrew J.
Published: January 2023

Locoregional recurrence (LRR) is the predominant pattern of relapse and often the cause of death in patients with retroperitoneal sarcomas (RPS). As a result, reducing LRR is a critical objective for RPS patients. However, unlike soft tissue sarcomas (STS) of the superficial trunk and extremity where the benefits of radiation therapy (RT) are well-established, the role of RT in the retroperitoneum remains controversial. Historically, preoperative or postoperative RT, either alone or in combination with intraoperative radiation (IORT), was commonly justified for RPS based on extrapolation from the superficial trunk and extremity STS literature. However, long-awaited results were recently published from the European Organization for Research and Treatment of Cancer (EORTC) STRASS study of preoperative radiotherapy plus surgery versus surgery alone for patients with RPS; there was no statistical difference in the primary endpoint of abdominal recurrence-free survival. However, several subset analyses and study limitations complicate the interpretation of the results. This review explores and contextualizes the body of evidence regarding RT’s role in managing RPS.
Efficiency Improvement with Data Center Monitoring Based on Building Information Modeling on the Facility Management Stage
Authors: Pogorelskiy Sergey , Kocsis Imre
Published: January 2023

Building Management Systems can be used for effective monitoring, management, planning, and improving the quality of work on large objects (office buildings, factories). Moreover, these systems can reduce costs during the operational phase. One of the technically complex and expensive facilities in which functions of Building Management Systems are used are data centers. To achieve a high level of efficiency at the Facility Management stage, it is important to work with data centers from the design stage. Data center design issues can be solved using Building Information Modeling, but during the transition to the operation of the facility some problems arise, namely the correct data export for Facility Management, the connection of real sensors with the model, and the receipt of data. All of these also affect the efficiency of the data center systems management. This article introduces a novel methodology for interconnecting Building Information Models with real sensors in data centers, which can provide a basis for further optimization. Furthermore, it can result in a more efficient operation in the operational phase. The proposed method is implemented and the experience gained as a result of the application is described.
Universality and beyond in Optical Microcavity Billiards with Source-Induced Dynamics
Authors: Seemann Lukas , Hentschel Martina
Published: January 2023

Optical microcavity billiards are a paradigm of a mesoscopic model system for quantum chaos. We demonstrate the action and origin of ray-wave correspondence in real and phase space using far-field emission characteristics and Husimi functions. Whereas universality induced by the invariant-measure dominated far-field emission is known to be a feature shaping the properties of many lasing optical microcavities, the situation changes in the presence of sources that we discuss here. We investigate the source-induced dynamics and the resulting limits of universality while we find ray-picture results to remain a useful tool in order to understand the wave behaviour of optical microcavities with sources. We demonstrate the source-induced dynamics in phase space from the source ignition until a stationary regime is reached comparing results from ray, ray-with-phase, and wave simulations and explore ray–wave correspondence.
Wildfire and Smoke Detection Using Staged YOLO Model and Ensemble CNN
Authors: Bahhar Chayma , Ksibi Amel , Ayadi Manel , Jamjoom Mona M. , Ullah Zahid , Soufiene Ben Othman , Sakli Hedi
Published: January 2023

One of the most expensive and fatal natural disasters in the world is forest fires. For this reason, early discovery of forest fires helps minimize mortality and harm to ecosystems and forest life. The present research enriches the body of knowledge by evaluating the effectiveness of an efficient wildfire and smoke detection solution implementing ensembles of multiple convolutional neural network architectures tackling two different computer vision tasks in a stage format. The proposed architecture combines the YOLO architecture with two weights with a voting ensemble CNN architecture. The pipeline works in two stages. If the CNN detects the existence of abnormality in the frame, then the YOLO architecture localizes the smoke or fire. The addressed tasks are classification and detection in the presented method. The obtained model’s weights achieve very decent results during training and testing. The classification model achieves a 0.95 F1-score, 0.99 accuracy, and 0.98e sensitivity. The model uses a transfer learning strategy for the classification task. The evaluation of the detector model reveals strong results by achieving a 0.85 mean average precision with 0.5 threshold (mAP@0.5) score for the smoke detection model and 0.76 mAP for the combined model. The smoke detection model also achieves a 0.93 F1-score. Overall, the presented deep learning pipeline shows some important experimental results with potential implementation capabilities despite some issues encountered during training, such as the lack of good-quality real-world unmanned aerial vehicle (UAV)-captured fire and smoke images.
Detecting Breast Arterial Calcifications in Mammograms with Transfer Learning
Authors: Khan Rimsha , Masala Giovanni Luca
Published: January 2023

Cardiovascular diseases, which include all heart and circulatory diseases, are among the major death-causing diseases in women. Cardiovascular diseases are not subject to screening programs, and early detection can reduce their mortal effect. Recent studies have shown a strong association between severe Breast Arterial Calcifications and cardiovascular diseases. The aim of this study is to use the screening programs for breast cancer to detect the high severity of BACs and therefore to obtain indirect information about coronary diseases. Previous attempts in the literature on the detection of BACs from digital mammograms still need improvements to be used as a standalone technique. In this study, a dataset of mammograms with BACs is divided into 4 grades of severity, and this study aims to improve their classification through a transfer learning approach to overcome the need for a large dataset of training. The performances achieved in this study by using pre-trained models to detect four Breast Arterial Calcifications severity grades reached an accuracy of 94% during testing. Therefore, it is possible to benefit from the advantage of Deep Learning models to define a rapid marker of BACs along Brest Cancer screening programs.
MODELING of Rarefied Gas Flows Inside a Micro-Nozzle Based on the DSMC Method Coupled with a Modified Gas–Surface Interaction Model
Authors: Liu Xuhui , Li Dong , Fu Xinju , Gao Yong , Wang Xudong
Published: January 2023

In this study, we first considered the influence of micro-nozzle wall roughness structure on molecular collision and reflection behavior and established a modified CLL model. The DSMC method was used to simulate and analyze the flow of the micro-nozzle in the cold gas micro-propulsion system, and the deviation of simulation results before and after the improvement of CLL model were compared. Then, the rarefied flow characteristics under a small needle valve opening (less than 1%) were focused on the research, and the particle position, molecular number density, and spatial distribution of internal energy in the micro-nozzle were calculated. The spatial distributions of the flow mechanism in the micro-nozzle under different needle valve openings were compared and analyzed. It was found that when the needle valve opening is lower than 1%, the slip flow and transition flow regions move significantly upstream of the nozzle, the free molecular flow distribution region expands significantly, and the relationship between thrust force and needle valve opening is obviously different from that of medium and large needle valve openings. The effect of nitrogen temperature on the rarefied flow and thrust force is also discussed in this research. The numerical results showed that as gas temperature increases, the molecular internal energy, momentum, and molecular number density near the nozzle exit are enhanced. The thrust at small needle valve openings was significantly affected by the temperature of the working mass. The results of this study will provide key data for the design and development of cold gas micro-thrusters.
Application of the Navigational Air-Sea Methane Exchange Flux Observation System in the Qiongdongnan Basin of the Northern South China Sea
Authors: Zhong Chao , Lu Jing’an , Kang Dongju , Liang Qianyong
Published: January 2023

The sources and sinks of dissolved CH4 in offshore waters are becoming diversified with the rapid increase in human activities. The concentration and air–sea exchange flux of dissolved CH4 present new characteristics of more intense spatiotemporal evolution, and the contribution to atmospheric CH4 continues to increase. Herein, a new model based on navigable air–sea exchange flux observations was proposed, which replaced the traditional station-based sampling analysis and testing method, realizing the synchronous measurement of methane in the atmosphere and surface seawater carried by ships. Based on the Marine Geological Survey project of the China Geological Survey, comprehensive environmental surveys were conducted in April 2018, September 2018, and June 2019 in the Qiongdongnan area in the northern part of the South China Sea, and the dissolved methane content in the sea surface atmosphere and surface seawaters in 2019 were simultaneously obtained. The methane exchange flux ranges of the southeastern sea area were calculated as −0.001~−0.0023 μmol·m−2·d−1 and −0.00164~−0.00395 μmol·m−2·d−1 by using the Liss and Merlivat formula (LM86), the Wanninkhof formula (W92), and the field-measured wind speed. The feasibility of the navigational air–sea methane exchange flux observation system was proven in a sea trial, and the measurement accuracy and observation efficiency of air-sea flux were improved with the designed system, providing a new technical means for further research on multiscale air–sea interactions and global climate change.
Wind Turbine Load Optimization Control Strategy Based on LIDAR Feed-Forward Control for Primary Frequency Modulation Process with Pitch Angle Reservation
Authors: Fu Deyi , Kong Lingxing , Gong Lice , Wang Anqing , Jia Haikun , Zhao Na
Published: January 2023

Because wind power is connected to the grid on a large scale, frequency fluctuation in the power grid, which is defined as a system safety risk to the power grid, occurs from time to time. According to the grid code rules of China, wind turbines are required to be equipped with primary frequency modulation or inertia response control capability, which are used to support the safe and stable operation of the power grid. During the traditional frequency modulation process of the wind turbine, power limiting operation or pitch angle reservation is generally adopted to ensure that the reserved energy can be released at any time to support the frequency change in the power grid. However, the frequency support method leads to a large loss of power generation, and does not consider the coordination between mechanical load characteristics control and primary frequency modulation. In this paper, a mechanical load optimization control strategy for a wind turbine during the primary frequency modulation process, based on LIDAR (light detection and ranging) feed forward control technology, is proposed and verified. Through LIDAR feed forward control, the characteristics of incoming wind speed can be sensed in advance, with the consequence that the wind turbine can participate in, and actively control, the primary frequency modulation procedure. According to the characteristics of incoming wind, for instance the amplitude and turbulence, simultaneously, the size of the reserved pitch angle can be adjusted in real time. This kind of method, coordinating with the mechanical load of the wind turbine, can be used to reduce both the ultimate load and fatigue damage as much as possible. Finally, the mechanical load characteristics of the wind turbine with and without the control strategy are compared and studied through simulation. The research results show that the load optimization control strategy based on LIDAR feed-forward control technology can effectively reduce the fatigue and ultimate loads of the wind turbine while supporting the frequency change in the power grid; especially for the fatigue load of tower base tilt and roll bending moments, the reducing proportion will be about 4.3% and 6.3%, respectively.
Short-Circuit Fault Diagnosis on Induction Motors through Electric Current Phasor Analysis and Fuzzy Logic
Authors: Reyes-Malanche Josue A. , Villalobos-Pina Francisco J. , Ramırez-Velasco Efraın , Cabal-Yepez Eduardo , Hernandez-Gomez Geovanni , Lopez-Ramirez Misael
Published: January 2023

Online monitoring of induction motors has increased significantly in recent years because these devices are essential components of any industrial process. Incipient fault detection in induction motors avoids interruptions in manufacturing processes and facilitates maintenance tasks to reduce induction motor timeout. Therefore, the proposal of novel approaches to assist in the detection and classification of induction motor faults is in order. In this work, a reliable and noninvasive novel technique that does not require computational demanding operations, since it just performs arithmetic calculations, is introduced for detecting and locating short-circuit faults in the stator windings of an induction motor. This method relies on phasor analysis and the RMS values of line currents, followed by a small set of simple if-then rules to perform the diagnosis and identification of stator winding faults. Obtained results from different experimental tests on a rewound induction motor stator to induce short-circuit faults demonstrate that the proposed approach is capable of identifying and locating incipient and advanced deficiencies in the windings’ insulation with high effectiveness.
An Experimental Approach for Secondary Consensus Control Tuning for Inverter-Based Islanded Microgrids
Authors: de Doile Gabriel Nasser Doyle , Balestrassi Pedro Paulo , Castilla Miguel , Zambroni de Souza Antonio Carlos , Miret Jaume
Published: January 2023

A microgrid is a group of interconnected loads and distributed energy resources that can fill the gap between the dependence on a bulk power grid and the transition to renewable energies. The islanded mode presents itself as the most interesting scenario, when local controllers should maintain the power quality standards based on several parameters. A tool specifically focused on the process of parameter tuning of the secondary consensus-based control for inverter-based islanded microgrids was proposed in this paper. One often-quoted drawback in this process is the great number of parameters that must be tuned, even for a very simple microgrid structure. To manage such a large number of parameters, the design of experiments was used in this study. The main motivation for this work was to present an optimized way to define the correct parameters for the secondary consensus control for inverter-based islanded microgrids. The study shows how experimental design methodology can be an efficient tool to tune microgrid parameters, which are typically multi-objective-based experiments. From the results, it is correct to state that the design of experiments is able to reach the optimal setting with a minimal number of experiments, which would be almost impossible to obtain with the trial-and-error method.
Dynamic Simulation of Partial Load Operation of an Organic Rankine Cycle with Two Parallel Expanders
Authors: Ekwonu Michael Chukwuemeka , Kim Mirae , Chen Binqi , Tauseef Nasir Muhammad , Kim Kyung Chun
Published: January 2023

The parallel expander ORC system is one of the solutions for providing an additional power output by improving the partial-load performance of an ORC. The parallel expander system corresponds to partial-load conditions by switching between various combinations of the expanders. During this process, the dynamic behavior occurs, which have not been characterized well in the open literature according to the best of the authors’ knowledge. In this study, we developed a dynamic modeling of an ORC system using dual expanders (DE-ORC) to study the dynamic responses during its mode changes. System components were simulated using an open-source library of ThermoCycle written in Modelica language. For each component, empirical parameters were implemented based on the experimental results. Furthermore, during the mode change that involved going from dual expander mode to singular expander mode, and to prevent the formation of the droplet in the expanders, a control strategy was proposed and simulated. The strategy involved lowering of the mass flow rate and then shifting the mode. Several timings between flow rate lowering and shifting the mode were analyzed, and the optimum shifting time was found to be in between 40 to 50 s.
Thermal Energy and Luminosity Characterization of an Advanced Ignition System Using a Non-Intrusive Methodology in an Optically Accessible Calorimeter
Authors: Martinelli Roberto , Ricci Federico , Discepoli Gabriele , Petrucci Luca , Papi Stefano , Grimaldi Carlo N.
Published: January 2023

To restrain the environmental impact of modern SI engines, igniters must guarantee stable combustions with low cycle-to-cycle variability in extreme operating conditions (high EGR, ultra-lean), via high energy release in the combustion chamber. The direct measurement of this energy is not trivial and requires a controlled environment. Luminosity detection is a non-intrusive diagnostic technique to indirectly measure the thermal energy released by the discharge on optically accessible apparatus. This work compares energy and luminosity produced by a plasma igniter in a constant volume vessel at realistic working conditions (ignition at 8 bar and air as a medium). A calibration factor can be defined to describe the thermal energy behavior as a function of the discharge luminosity and to give an assessment of such approach for its use in optically accessible engine. This study shows that thermal energy and luminosity are influenced by the gas type and related by a linear relationship for both air and nitrogen. The presence of oxygen resulted in discharges with reduced energy delivery to the medium and a lower discharge luminosity compared to nitrogen. This work outcome could improve the use of a non-intrusive methodology, based on luminosity detection, to characterize the igniter performance, exploitable for 3D-CFD.
The Effectiveness of Distributed Acoustic Sensing (DAS) for Broken Rail Detection
Authors: Wagner Adrian , Nash Andrew , Michelberger Frank , Grossberger Hirut , Lancaster Gavin
Published: January 2023

Broken rails remain one of the main causes of railway accidents despite improved rail quality and inspections. Today, signalling system with track circuits are often used to detect broken rails, however new signalling systems such as the European Train Control System (ETCS) with axle counters are replacing track circuits and therefore new methods are needed to detect broken rails. One promising technology is distributed acoustic sensing (DAS). The best DAS analytical techniques to show the position of the rail break are gradient analysis, convolution using the train consist and 2 D sinusoidal convolution. This paper describes field tests carried out on DAS to evaluate its ability to detect broken rails and the moment when rails break. The testing showed that DAS has good potential for detecting broken rails in both scenarios. Especially helpful is the ability of DAS to identify the moment of rail breakage and its potential for determining the break’s location on open lines. Recommendations for further research include testing these qualities in more detail and considering how DAS could be efficiently combined with new signalling systems.
The Oxygenic Photogranules—Current Progress on the Technology and Perspectives in Wastewater Treatment: A Review
Authors: Smetana German , Grosser Anna
Published: January 2023

Wastewater generation is a worldwide problem, and its treatment is an important practice for maintaining public health and environmental protection. Oxygenic photogranules (OPGs) are a relatively novel type of biogranules that have the potential to substitute the conventional activated sludge (AS) process due to the production of in situ oxygen, better physical properties such as settling velocity and density, as well as carbon and nutrient removal efficiencies. The formation of the granules is attributed to many factors, among which the most influential are light intensity, ammonium nitrogen concentration, and the presence of filamentous cyanobacteria that, along with heterotrophic microorganisms situated in the granule’s core, create a self-sustainable system that combines denitrification, carbon removal, and oxygen production. Hydrostatic and hydrodynamic cultivations are two ways that allow for obtaining OPGs. These two cultivation methods lead to the formation of various types of granules which differ in both structures as well as physical properties. This review article aims to aggregate the available literature information regarding the methods of cultivation of OPGs, their formation mechanisms, and factors that influence the cultivation as well as an overview of studies that were conducted thus far concerning this type of biogranules. Additionally, further research directions are proposed in the article.
Network Pathway Extraction Focusing on Object Level
Authors: Alqahtani Ali
Published: January 2023

In this paper, I propose an efficient method of identifying important neurons that are related to an object’s concepts by mainly considering the relationship between these neurons and their object concept or class. I first quantify the activation values among neurons, based on which histograms of each neuron are generated. Then, the obtained histograms are clustered to identify the neurons’ importance. A network-wide holistic approach is also introduced to efficiently identify important neurons and their influential connections to reveal the pathway of a given class. The influential connections as well as their important neurons are carefully evaluated to reveal the sub-network of each object’s concepts. The experimental results on the MNIST and Fashion MNIST datasets show the effectiveness of the proposed method.
CFD Simulation of a Hybrid Solar/Electric Reactor for Hydrogen and Carbon Production from Methane Cracking
Authors: Msheik Malek , Rodat Sylvain , Abanades Stéphane
Published: January 2023

Methane pyrolysis is a transitional technology for environmentally benign hydrogen production with zero greenhouse gas emissions, especially when concentrated solar energy is the heating source for supplying high-temperature process heat. This study is focused on solar methane pyrolysis as an attractive decarbonization process to produce both hydrogen gas and solid carbon with zero CO2 emissions. Direct normal irradiance (DNI) variations arising from inherent solar resource variability (clouds, fog, day-night cycle, etc.) generally hinder continuity and stability of the solar process. Therefore, a novel hybrid solar/electric reactor was designed at PROMES-CNRS laboratory to cope with DNI variations. Such a design features electric heating when the DNI is low and can potentially boost the thermochemical performance of the process when coupled solar/electric heating is applied thanks to an enlarged heated zone. Computational fluid dynamics (CFD) simulations through ANSYS Fluent were performed to investigate the performance of this reactor under different operating conditions. More particularly, the influence of various process parameters including temperature, gas residence time, methane dilution, and hybridization on the methane conversion was assessed. The model combined fluid flow hydrodynamics and heat and mass transfer coupled with gas-phase pyrolysis reactions. Increasing the heating temperature was found to boost methane conversion (91% at 1473 K against ~100% at 1573 K for a coupled solar-electric heating). The increase of inlet gas flow rate Q0 lowered methane conversion since it affected the gas space-time (91% at Q0 = 0.42 NL/min vs. 67% at Q0 = 0.84 NL/min). A coupled heating also resulted in significantly better performance than with only electric heating, because it broadened the hot zone (91% vs. 75% methane conversion for coupled heating and only electric heating, respectively). The model was further validated with experimental results of methane pyrolysis. This study demonstrates the potential of the hybrid reactor for solar-driven methane pyrolysis as a promising route toward clean hydrogen and carbon production and further highlights the role of key parameters to improve the process performance.
Detection of Partial Blockages in Pressurized Pipes by Transient Tests: A Review of the Physical Experiments
Authors: Brunone Bruno , Maietta Filomena , Capponi Caterina , Duan Huan-Feng , Meniconi Silvia
Published: January 2023

Pressure waves, while traveling along pressurized pipes, collect precious information about possible faults (e.g., leaks and partial blockages). In fact, the characteristics of the pressure wave reflected by the fault are strongly related to it. To encourage the use of the transient test-based technologies (TTBTs) for partial blockage (PB) detection in pressurized pipe systems, it can be of interest to critically analyze the available experimental results and to point out the aspects that need to be investigated in more detail, since no review has been executed so far. Such a deficiency has two negative consequences. The first one is that TTBTs are still relegated to limbo by technicians. The second one is that not enough material is available for refining tools to extract all the information contained in the acquired pressure signals and then to pursue an effective PB detection. As main results of the executed analysis, the following issues can be counted: (i) the lack of tests carried out in large diameter and concrete pipes; (ii) the absence of tests carried out in complex pipe systems (e.g., looped networks); and (iii) the extreme need for considering real pipe systems. The fulfillment of the last issue will greatly contribute to the solutions of the other ones.
Application of Multifractal Analysis Theory to Interpret T2 Cutoffs of NMR Logging Data: A Case Study of Coarse Clastic Rock Reservoirs in Southwestern Bozhong Sag, China
Authors: Wang Zefan , Yao Yanbin , Ma Ruying , Zhang Xiaona , Zhang Guibin
Published: January 2023

The Paleocene Kongdian Formation coarse clastic rock reservoir in Bozhong Sag is rich in oil and gas resources and has huge exploration potential. However, the coarse clastic rock reservoir has the characteristics of a complex pore structure and strong heterogeneity, which restrict the accuracy of evaluating the reservoir’s physical properties, such as porosity and permeability, for field evaluation. Nuclear magnetic resonance (NMR) technology has become a popular methods for unconventional reservoir evaluation because it can obtain abundant reservoir physical property information and because of its ability to identify fluid characteristics information. The transverse relaxation time (T2) cutoff (T2C) value is an important input parameter in the application of NMR technology. The accuracy of the T2C value affects the accuracy of the reservoir evaluation. The standard method for determining the T2C value requires a series of complicated centrifugation experiments in addition to the NMR experiments, and its application scope is limited by obtaining enough core samples. In this study, 14 core samples from the coarse clastic rock reservoir in the southwestern Bozhong sag of the Bohai Bay Basin were selected, and NMR measurements were carried out under the conditions of fully saturated water and irreducible water to determine the T2C value. Based on the multifractal theory, the NMR T2 spectrum of the saturated sample was analyzed, and the results show that the NMR T2 distribution of the saturated sample has multifractal characteristics, and the multifractal parameter Dq and the singular intensity range Δα have a strong correlation with the T2C value. Thus, based on multiple regression analyses of the multifractal parameters with the experimental T2C value of 10 core samples, we propose a method to predict the T2C value. After applying this method to 4 samples that were not used in the modeling, we confirmed that this method can be used to predict the T2C value of core samples. Furthermore, we expanded this method to the field application of a production well in Bozhong sag by adding an empirical index in the model. The new model can be used to directly calculate the T2C value of NMR logging data, and it does not require any other extra data, such as those from core analysis. This method is applicable in fast reservoir evaluations by only using NMR logging data in the field. The research results improve the accuracy of field NMR logging reservoir evaluations.
Evaluation of Mobile and Community Dental Service Use among People Experiencing Homelessness
Authors: Novak Bohuslav , Matajs Marek , Sangalli Alessandro Emanuele , Pruts Halyna , Korpasova Anna , Leptos Nikos , Stanko Peter , Tinak Michal , Kosticova Michaela
Published: January 2023

The aim of the study was to evaluate the patterns of mobile and community dental service use among people experiencing homelessness in Bratislava, Slovakia. Data from medical records of homeless people who visited the mobile and community dental clinic from November 2012 to July 2018 have been retrospectively reviewed. The experience of providing dental services has been reported from the perspective of the dental care provider. Descriptive statistics were used for data analysis. In total, 319 patients (75.5% men) attended the clinic. Extraction of a tooth was the main dental treatment indicated in more than 80% (n = 276) of patients. A total of 363 teeth were extracted with an average number of 1.6 extracted teeth per patient. The main indications for extraction were dental caries and its sequelae (83.7%) and periodontal disease (15.2%). The patients with the need for prosthetic and conservative treatment were referred to the clinics at University Hospital; however, only 19 patients received the treatment. The barriers to accessing dental care were cost, logistic problems and individual psychological factors. We found that people experiencing homelessness in Slovakia have high needs and demands of emergency dental care and many systemic and individual barriers prevent them from accessing care. Community-based dental services are important for improving access to dental care and reducing oral health inequities.
Longitudinal Trends in Blood Pressure Associated with The Changes in Living Environment Caused by the Great East Japan Earthquake: The Fukushima Health Management Survey
Authors: Ikeda Satomi , Ikeda Ai , Ohira Tetsuya , Sakai Akira , Shimabukuro Michio , Maeda Masaharu , Yabe Hirooki , Nagao Masanori , Yasumura Seiji , Ohto Hitoshi , Kamiya Kenji , Tanigawa Takeshi
Published: January 2023

The Great East Japan Earthquake occurred on 11 March 2011, forcing Fukushima Prefecture residents to change their living environment. Such sudden changes possibly have long-term effects on cardiovascular-related diseases. We therefore sought to identify temporal relationships between living environment changes and blood pressure levels over three years following the earthquake. Participants included 14,941 men and 21,533 women aged 16 years or older who answered self-administered questionnaires, including questions on living environment changes at baseline (2012). Blood pressure levels were measured each year from 2012 to 2015. Linear mixed-effects models were used to analyze associations between living environment changes and blood pressure levels. Men with changes in living environment (i.e., those living in shelters or in temporary housing, rental apartments, relatives’ houses, or others) showed significantly higher diastolic blood pressure levels than those who lived in their home at baseline (77.3 mmHg vs. 77.8 mmHg; p < 0.001). The time-dependent effect of diastolic blood pressure levels associated with living environment was not statistically significant, indicating a sustained difference in diastolic blood pressure associated with living environment changes at baseline after three years. The effect of living environment changes on diastolic blood pressure increment was also evident in men without antihypertensive medication use during the study period and in men who were current drinkers at baseline. There were no associations between living environment changes and diastolic blood pressure levels among women. Sudden changes in living environment due to the disaster had an impact on the long-term effects of higher diastolic blood pressure among middle-aged men.
Sources, Migration, Transformation, and Environmental Effects of Organic Carbon in Eutrophic Lakes: A Critical Review
Authors: Xu Xiaoguang , Wu Chao , Xie Dongyu , Ma Jie
Published: January 2023

Organic carbon (OC) plays a leading role in the carbon cycle of lakes and is crucial to carbon balances at regional and even global scales. In eutrophic lakes, in addition to external river inputs, the decomposition of endogenous grass and algae is a major source of organic carbon. Outbreaks of algal blooms (algal eutrophication) and the rapid growth of aquatic grasses (grass eutrophication) can lead to the accumulation and decay of large amounts of algae and aquatic grass debris, which increases the intensity of the carbon cycle of lakes and greatly impacts aquatic environments and ecosystems. The structures, decomposition processes, and distribution characteristics of algae and higher aquatic plant debris in eutrophic lakes are different from mesotrophic and oligotrophic lakes. Studying their accumulation dynamics and driving mechanisms is key to further understanding lake carbon cycles and their many interdependent pathways. This paper focuses on the carbon sources, tracing technologies, migration and transformation processes, and environmental effects of OC in eutrophic lakes. Based on the existing knowledge, we further combed the literature to identify the most important knowledge gaps preventing an in-depth understanding of the processes and driving mechanisms of the organic carbon cycle in eutrophic lakes.