bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimation of Indoor 222Rn Concentration in Lima, Peru Using LR-115 Nuclear Track Detectors Exposed in Different Modes
Authors: Pereyra Patrizia , Guevara-Pillaca Cesar J. , Liza Rafael , Pérez Bertin , Rojas Jhonny , Vilcapoma L. Luis , Gonzales Susana , Sajo-Bohus Laszlo , López-Herrera María Elena , Palacios Fernández Daniel
Published: May 2023

Radon is the main source of natural radioactivity, and its measurement is considered extremely important in radioprotection, given its relationship with the occurrence of lung cancer. In the last two years, measurements of this radioactive gas were carried out in Lima considering a grid of 5 km2 and the population density to determine the number of measurements to be carried out. Cellulose nitrate nuclear track detectors exposed in bare mode and diffusion chamber mode were used to estimate 222Rn concentrations. In diffusion chamber mode, non-commercial monitors and commercial monitors were used. The monitoring results are presented for 43 districts of the Lima Province whose population is approximately ten million inhabitants occupying a total area of 2655.15 km2. Measurements were made obtaining an average concentration of 49 Bq·m−3 using bare detectors and 66 Bq·m−3 using non-commercial diffusion chambers. Average concentrations obtained by both detector exposure modes were below the maximum concentration recommended by the WHO. A radon (222Rn) map was also obtained as a visual representation of the 222Rn levels in the Lima province using inverse distance weighting (IDW) interpolation.
Intraoperative Cochlear Nerve Monitoring in Cochlear Implantation after Vestibular Schwannoma Resection
Authors: Di Pasquale Fiasca Valerio Maria , Tealdo Giulia
Published: May 2023

Background: The use of a cochlear implant (CI) for hearing rehabilitation after vestibular schwannoma (VS) resection is widely spreading. The procedure is usually performed simultaneously to tumor resection with a translabyrinthine approach. To ensure the best device function, assessing the integrity of the cochlear nerve is of primary importance. Methods: A narrative review of the literature on the present topic was carried out up to June 2022. Finally, nine studies were considered. Results: Electrically evoked auditory brainstem responses (eABR) is the most widely used method of intraoperative monitoring of cochlear nerve (CN) during VS resection, although its limits are known. It can be assessed through the CI electrode array or through an intracochlear test electrode (ITE). Variations of the graph are evaluated during the surgical procedure, in particular the wave V amplitude and latency. As tumor dissection progresses, the parameters may change, informing of the CN status, and the surgical procedure may be modulated. Conclusion: An eABR positive result seems to be reliably correlated with a good CI outcome in those cases in which a clear wave V is recorded before and after tumor removal. On the contrary, in those cases in which the eABR is lost or altered during the surgical procedure, the positioning of a CI is still debatable.
A Mathematical Analysis of the Stress Statement of the Soil Basis under Complex Loading near the Retaining Wall
Authors: Ter-Martirosyan Armen Z. , Vanina Yulia V.
Published: May 2023

The present paper describes and provides an analytical solution to the problem of the stress state of a limited-thickness soil basis resting on an incompressible soil base, under the action of two distributed loads of different intensities near the retaining wall of an excavation pit. It is proposed that the method for identifying components of the stress statement within the framework of the engineering problem in question is improved, and the solution is based on the trigonometric Ribiere–Fileon series. The results obtained by the authors allow for an evaluation of the supplementary effect on a retaining wall produced by loads from heavy machinery and materials stored near this retaining wall. These findings are useful for the design of underground constructions of buildings and structures. Theoretical results are provided together with those of numerical experiments to validate the research reliability.
3D Heterogeneous Model for Electrodes in Lithium-Ion Batteries and Its Application to a Modified Continuum Model
Authors: Mirsalehian Mohammadali , Vossoughi Bahareh , Kaiser Jörg , Pischinger Stefan
Published: May 2023

The microstructures of porous electrodes in lithium-ion cells strongly affect their electrochemical performance. Experimental tomography techniques to investigate the microstructure during electrode development is costly and time consuming. To address this issue, a numerical method is presented to create a digital morphology to realize a realistic microstructure. In this study, the spherical harmonics in a straightforward mathematical approach are proposed to develop the virtual 3D morphology of the electrode’s heterogeneous structure. The introduced method offers a numerically light procedure which enables effective iterative virtual testing and optimization. The generated morphology model is parameterized to reproduce a NMC cathode microstructure observed in the literature. The electrode model allows evaluation of the spatially resolved geometric, transport and electric potential characteristics of the microstructure. The computed characteristics are employed to improve the parametrization of the continuum model as the most widely used physics-based model. For this purpose, the electrochemical impedance spectra of a lithium foil/separator/NMC half-cell is virtually modeled by heterogeneous and continuum approaches. Then, the modified continuum model is compared to the heterogeneous model as a benchmark, in terms of the kinetics and transport characteristics underlying the electrochemical impedance spectra. The modified continuum model shows an improved response in both frequency and time domains.
MicroRNA (miRNA) Complexity in Alzheimer’s Disease (AD)
Authors: Lukiw Walter J.
Published: May 2023

AD is a complex, progressive, age-related neurodegenerative disorder representing the most common cause of senile dementia and neurological dysfunction in our elderly domestic population. The widely observed heterogeneity of AD is a reflection of the complexity of the AD process itself and the altered molecular-genetic mechanisms operating in the diseased human brain and CNS. One of the key players in this complex regulation of gene expression in human pathological neurobiology are microRNAs (miRNAs) that, through their actions, shape the transcriptome of brain cells that normally associate with very high rates of genetic activity, gene transcription and messenger RNA (mRNA) generation. The analysis of miRNA populations and the characterization of their abundance, speciation and complexity can further provide valuable clues to our molecular-genetic understanding of the AD process, especially in the sporadic forms of this common brain disorder. Current in-depth analyses of high-quality AD and age- and gender-matched control brain tissues are providing pathophysiological miRNA-based signatures of AD that can serve as a basis for expanding our mechanistic understanding of this disorder and the future design of miRNA- and related RNA-based therapeutics. This focused review will consolidate the findings from multiple laboratories as to which are the most abundant miRNA species, both free and exosome-bound in the human brain and CNS, which miRNA species appear to be the most prominently affected by the AD process and review recent developments and advancements in our understanding of the complexity of miRNA signaling in the hippocampal CA1 region of AD-affected brains.
Gasdermin D Plays an Oncogenic Role in Glioma and Correlates to an Immunosuppressive Microenvironment
Authors: Li Mengyuan , Jiang Ping , Wei Shuhua , Yang Yuhan , Xiong Liting , Wang Junjie , Li Chunxiao
Published: May 2023

Background: Understanding the molecular mechanisms driving oncogenic processes in glioma is important in order to develop efficient treatments. Recent studies have proposed gasdermin D (GSDMD) as a newly discovered pyroptosis executive protein associated with tumorigenesis. However, the precise effect of GSDMD on glioma progression remains unknown. Methods: The expression levels of GSDMD in 931 glioma and 1157 normal control tissues were collected. A series of bioinformatic approaches and in vivo and in vitro experiments were used to investigate the roles and mechanisms of GDSMD in glioma. Results: Significant upregulation of GSDMD was detected in glioma tissues compared to normal brain tissues. Patients with glioma and higher GSDMD levels had shorter overall survival, and the Cox regression analysis revealed that GSDMD was an independent risk factor. In addition, upregulation of GSDMD was associated with higher tumor mutation burden and PD-1/PD-L1 expression. Immune infiltration and single-cell analyses indicated that GSDMD was positively associated with an immunosuppressive microenvironment with more infiltrated macrophages and cancer-associated fibroblasts. Furthermore, the in vitro and in vivo experiments revealed that GSDMD knockdown inhibited glioma proliferation, migration, and growth in vivo. Conclusion: Our analyses revealed a relatively comprehensive understanding of the oncogenic role of GSDMD in glioma. GSDMD is a promising prognostic biomarker and a potential target for glioma treatment.
Reducing Visuospatial Pseudoneglect in Healthy Subjects by Active Video Gaming
Authors: Gambino Giuditta , Pia Lorenzo , Ferraro Giuseppe , Brighina Filippo , Di Majo Danila , Di Giovanni Fabrizio , Ciorli Tommaso , Sardo Pierangelo , Giglia Giuseppe
Published: May 2023

Pseudoneglect phenomenon refers to a condition in which healthy subjects tend to perceive the left side of exactly bisected lines as being slightly longer than the right one. However, behavioural data showed that athletes practising an open-skill sport display less pseudoneglect than the general population. Given the fact that so-called exergames (also known as active video games) are platforms designed to fully mimic sport activity, this work intends to investigate whether and how a one-week training period of exergame open-skill sport can determine a similar decrease in pseudoneglect. Fifteen healthy participants (non-athletes) responded to a visuospatial attention task and a control memory task in basal conditions (t0: Pre-game) and after a short period (one week, one hour/day) of tennis exergaming (t1: Post-game). In the Post-game condition, subjects from this experimental group (ExerGame group: EG) reduced leftward space overestimation and made significantly fewer leftward errors compared to the Pre-game condition. Additionally, two other experimental groups were employed: one evaluated within the same conditions of the main experiment but using a non-exergame (Non-Exergame groups: NEG) and the other one without any video game stimulus (Sedentary group: SE). Our findings suggest that daily training of a tennis exergame seems to be able to improve visuospatial attention isotropy by reducing leftward space overestimation, whereas outcomes from non-exergaming and sedentary activity do not modify subjects’ performance.
Natural Ventilation in Low-Cost Housing: An Evaluation by CFD
Authors: Rocha Lívia A. , Gomez Ricardo S. , Delgado João M. P. Q. , Vieira Antônio N. O. , Santos Ivonete B. , Luiz Márcia R. , Oliveira Vital A. B. , Oliveira Neto Guilherme L. , Vasconcelos Danielle B. T. , Silva Márcio J. V. , Cabral Adriano S. , Lima Antonio G. B.
Published: May 2023

With the spread of sustainability concepts, due to the global energy crisis and the unrestrained consumption of natural resources, the importance of rational use and reduction of energy consumption has been intensified, albeit in short steps. This concern has taken up bioclimatic concepts in buildings, especially housing buildings for low-income people, aiming at improving the quality of housing production in terms of its habitability. The objective of this research is to theoretically and experimentally study the natural ventilation in a housing building, which fits into the low-cost pattern. The use of Computational Fluid Dynamics to predict natural ventilation was adopted as a tool to perform these analyses. Experiments were carried out by visiting the study area to collect data on air velocity, temperature, and relative humidity in all rooms of the residence in order to carry out the intended analyses. Computer simulation of natural ventilation considering the building with the doors and windows open and with fixed geometry was performed. Results proved that the proposed mathematical model was able to reproduce, with rich details and physical coherence, the internal and external air flow inside the building, indicating better internal ventilation performance in environments that have door and window openings, with recesses, revealing the importance of cross ventilation to reduce the internal temperature and consequent improvement in thermal comfort. The idea is to help civil engineers and specialists in the economically viable design of low-cost buildings from the economic, social, and thermal comfort points of view.
A Bim-Based Automatic Design Optimization Method for Modular Steel Structures: Rectangular Modules as an Example
Authors: Kang Jingliang , Dong Wei , Huang Yimiao
Published: May 2023

During the promotion of the modular steel structure in the architecture, engineering, and construction (AEC) industry, building information modeling (BIM) is leveraged to integrate the design process into the whole construction sequence. The absence of standards and interactive, tech-friendly tools for project participants limits the general implementation of the BIM-based design process. The present study proposes an automatic design optimization method based on the BIM platform for modular steel structures. The method consists of digital modeling sequences that contain data exchange between different software applications and the program of structural design optimization. A prototype workflow of the method is explained and assessed in a case study to indicate its reliability and practicability. The proposed design coheres with common design rules and enhances the utilization rate of column structure by 40–50% with minimal redundancy compared to initial designs. The proposed method is also discussed through interviews with and surveys of engineers working in the AEC industry in terms of its potential adoption in actual projects. The discussion shows that this method can reduce the time consumption of the model creation and optimization of modular steel structures effectively. Special knowledge of the relevant software is no longer a hindrance for engineers.
Accelerating the Delivery of Low-Carbon Buildings by Addressing Common Constraints: Perspectives from High-Rise, High-Density Cities
Authors: Kumaraswamy Mohan M. , Hewa Welege Nandun Madhusanka , Pan Wei
Published: June 2023

The delivery of low-carbon buildings (LCBs) in high-rise, high-density cities is still hindered by various common and interdependent constraints. However, a study that developed innovative strategies to address the common constraints to delivering LCBs focusing on traditional high-rise, high-density cities could not be identified in the previous literature. Therefore, this study aimed to identify potential strategies for accelerating the delivery of LCBs in high-rise, high-density cities by addressing relevant common constraints that were identified in recent studies. Accordingly, potentially relevant strategies were identified through eight semi-structured interviews with well-experienced experts in industry and academia. Consequently, 71 strategies were identified under six categories, i.e., policy implementation, building energy/carbon data utilisation, awareness raising/training, technology advancement, incentives, and organisational level commitments. This also required closer collaboration with different stakeholders/stakeholder classes in implementing these strategies, who were, therefore, also identified. An SNA-based analysis was also conducted to explore the connections between constraints and strategies. The strategies related to energy/carbon policy development, standardisation, codes and certifications, mandatory regulations, financial incentives, and technology adoption showed the ability to address a majority of the driving constraints related to policies and technologies. These study findings will assist policymakers and other relevant stakeholders in the arena of the project and asset management in accelerating the delivery of LCBs by adopting an innovative approach to prioritise potential strategies in order to suitably address and synergise the complex interdependencies among the constraints.
Standardization of Body Composition Status in Patients with Advanced Urothelial Tumors: The Role of a CT-Based AI-Powered Software for the Assessment of Sarcopenia and Patient Outcome Correlation
Authors: Borrelli Antonella , Pecoraro Martina , Del Giudice Francesco , Cristofani Leonardo , Messina Emanuele , Dehghanpour Ailin , Landini Nicholas , Roberto Michela , Perotti Stefano , Muscaritoli Maurizio , Santini Daniele , Catalano Carlo , Panebianco Valeria
Published: May 2023

Background: Sarcopenia is a well know prognostic factor in oncology, influencing patients’ quality of life and survival. We aimed to investigate the role of sarcopenia, assessed by a Computed Tomography (CT)-based artificial intelligence (AI)-powered-software, as a predictor of objective clinical benefit in advanced urothelial tumors and its correlations with oncological outcomes. Methods: We retrospectively searched patients with advanced urothelial tumors, treated with systemic platinum-based chemotherapy and an available total body CT, performed before and after therapy. An AI-powered software was applied to CT to obtain the Skeletal Muscle Index (SMI-L3), derived from the area of the psoas, long spine, and abdominal muscles, at the level of L3 on CT axial images. Logistic and Cox-regression modeling was implemented to explore the association of sarcopenic status and anthropometric features to the clinical benefit rate and survival endpoints. Results: 97 patients were included, 66 with bladder cancer and 31 with upper-tract urothelial carcinoma. Clinical benefit outcomes showed a linear positive association with all the observed body composition variables variations. The chances of not experiencing disease progression were positively associated with ∆_SMI-L3, ∆_psoas, and ∆_long spine muscle when they ranged from ~10–20% up to ~45–55%. Greater survival chances were matched by patients achieving a wider ∆_SMI-L3, ∆_abdominal and ∆_long spine muscle. Conclusions: A CT-based AI-powered software body composition and sarcopenia analysis provide prognostic assessments for objective clinical benefits and oncological outcomes.
Pictorial Review of MRI Findings in Acute Neck Infections in Children
Authors: Nurminen Janne , Heikkinen Jaakko , Happonen Tatu , Nyman Mikko , Sirén Aapo , Vierula Jari-Pekka , Velhonoja Jarno , Irjala Heikki , Soukka Tero , Ivaska Lauri , Mattila Kimmo , Hirvonen Jussi
Published: May 2023

Pediatric neck infections and their complications, such as abscesses extending to deep neck compartments, are potentially life-threatening acute conditions. Medical imaging aims to verify abscesses and their extensions and exclude other complications. Magnetic resonance imaging (MRI) has proven to be a useful and highly accurate imaging method in acute neck infections in children. Children and adults differ in terms of the types of acute infections and the anatomy and function of the neck. This pictorial review summarizes typical findings in pediatric patients with neck infections and discusses some difficulties related to image interpretation.
Developmental Dysplasia of the Hip: How Many Risk Factors Are Needed?
Authors: Ionescu Adelina , Dragomirescu Mihai-Codrut , Herdea Alexandru , Ulici Alexandru
Published: May 2023

Developmental dysplasia of the hip (DDH) is a progressive condition that lacks clear diagnostic and management protocols, due to insufficient data. While some advocate for universal screening, others recommend using risk factors as landmarks. In this study, we aimed to assess the risk factors associated with DDH incidence among a large population. We conducted a retrospective single-center multifactorial study between January 2019 and March 2022, including 3720 children who were investigated anamnestically, clinically, and through an ultrasound scan. We classified them into two groups: the control group with 3300 healthy children and the study group with 420 newborns diagnosed with DDH. Our analysis identified several risk factors associated with DDH, including gender, prematurity, non-vertex birth presentation, oligohydramnios, gestational diabetes, maternal hypertension, family history, associated deformities, and swaddling. We found that every DDH patient had at least two risk factors. Based on our findings, we recommend that children who present two or more risk factors for DDH be mandatorily evaluated sonographically, as well as children with clinical signs. DDH screening is recommended for each newborn for the long-term benefits of early detection and treatment.
Origin of Wild Polyploid Avena Species Inferred from Polymorphism of the ITS1 rDNA in Their Genomes
Authors: Gnutikov Alexander A. , Nosov Nikolai N. , Loskutov Igor G. , Blinova Elena V. , Shneyer Victoria S. , Rodionov Alexander V.
Published: May 2023

In this article, we analyzed the origin of wild polyploid oats (Avena L., Poaceae) using the region 18S rDNA (partially)–ITS1–5.8S rDNA obtained via NGS. There are six tetraploid (2n = 28) and four hexaploid (2n = 42) wild species differing by specific genome combinations: A. barbata, A. vaviloviana (AB), A. agadiriana (AB or BB), A. magna, A. murphyi, A. insularis (AC or CD), A. ludoviciana, A. sterilis, A. fatua, and A. occidentalis (ACD). We compared the pool of marker sequences of polyploid oats with those of their putative diploid ancestors: A. atlantica (As-genome), A. hirtula (As), A. canariensis (Ac), A. ventricosa (Cv), and A. clauda (paleopolyploid with Cp and A-related rDNA). We found 15 major ribotypes (more than 1000 reads per rDNA pool) in polyploid oats. Comparing them, we found that the AB-tetraploid oats possibly inherited their A-genome ribotypes from A. atlantica (As1-ribotype), whereas their B-genome ribotype is specific and can be a derivative of the A-genome family. Our data do not support the hypothesis of the CD-genome set in A. magna, A. murphyi, and A. insularis: they have an AC-genome ribotype constitution instead. The C-genome-related sequences could have been obtained from A. ventricosa. Hexaploids show a different ribotype pattern than tetraploids; the main ribotypes of A. fatua, A. ludoviciana, and A. sterilis probably belong to the D-group and are also shared with one of the major ribotypes of A. clauda.
Nest Change and Individual Fitness in a Scopoli’s Shearwater Population: A Capture-Recapture Multistate Analysis
Authors: Sacchi Massimo , Zenatello Marco , Pezzo Francesco , Cozzo Mario , Pollonara Enrica , Gotti Camilla , De Faveri Adriano , Baccetti Nicola
Published: May 2023

Seabirds are compelled to nest on land, away from their feeding areas, which they can only reach by leaving eggs or chicks in the nest, often for long periods of time. For this reason, almost all of them have evolved social monogamy as a reproductive system, cooperation between partners for incubation and chick rearing, and long-lasting pair bonds. Additionally, nesting conditions are essential for successful reproduction, and the nest can be considered a resource if it provides more guarantees in this aspect. As a result, the nest may be a source of contention and intraspecific competition, especially among males. In this work, we analyze long-term data of the Scopoli’s shearwater (Calonectris diomedea) population to address the fitness consequences of nest change regarding survival and reproductive success. We used capture–recapture multistate models and the AICc model selection approach to test three hypotheses: breeding failure triggers nest change; nest change affects breeding success probability; nest change affects survival. Each year, about 5% of the breeders move to a new nest. For males, it was mainly a way to improve their breeding conditions and was observed in their early years as a breeder. Conversely, for females, it was a way to improve their reproductive performance by trying with a new mate after a failure. Males that changed nests improved their breeding success probability. Instead, in females, there was no causal relation between nest change and breeding success, the latter having been more influenced by the intrinsic quality of the female as a breeder. We did not even find a link between nest change and survival. Instead, we demonstrated that reproductive failure could affect the apparent survival of females, probably because it induces breeding dispersal.
Measurement-Device-Independent Quantum Key Distribution Based on Decoherence-Free Subspaces with Logical Bell State Analyzer
Authors: Wei Jun-Hao , Xu Xin-Yu , Hu Shu-Ming , Zhou Qing , Li Li , Liu Nai-Le , Chen Kai
Published: May 2023

Measurement-device-independent quantum key distribution (MDI-QKD) enables two legitimate users to generate shared information-theoretic secure keys with immunity to all detector side attacks. However, the original proposal using polarization encoding is sensitive to polarization rotations stemming from birefringence in fibers or misalignment. To overcome this problem, here we propose a robust QKD protocol without detector vulnerabilities based on decoherence-free subspaces using polarization-entangled photon pairs. A logical Bell state analyzer is designed specifically for such encoding. The protocol exploits common parametric down-conversion sources, for which we develop a MDI-decoy-state method, and requires neither complex measurements nor a shared reference frame. We have analyzed the practical security in detail and presented a numerical simulation under various parameter regimes, showing the feasibility of the logical Bell state analyzer along with the potential that double communication distance can be achieved without a shared reference frame.
Boosted Binary Quantum Classifier via Graphical Kernel
Authors: Li Yuan , Huang Duan
Published: May 2023

In terms of the logical structure of data in machine learning (ML), we apply a novel graphical encoding method in quantum computing to build the mapping between feature space of sample data and two-level nested graph state that presents a kind of multi-partite entanglement state. By implementing swap-test circuit on the graphical training states, a binary quantum classifier to large-scale test states is effectively realized in this paper. In addition, for the error classification caused by noise, we further explored the subsequent processing scheme by adjusting the weights so that a strong classifier is formed and its accuracy is greatly boosted. In this paper, the proposed boosting algorithm demonstrates superiority in certain aspects as demonstrated via experimental investigation. This work further enriches the theoretical foundation of quantum graph theory and quantum machine learning, which may be exploited to assist the classification of massive-data networks by entangling subgraphs.
Quantum Lernmatrix
Authors: Wichert Andreas
Published: May 2023

We introduce a quantum Lernmatrix based on the Monte Carlo Lernmatrix in which n units are stored in the quantum superposition of log2(n) units representing On2log(n)2 binary sparse coded patterns. During the retrieval phase, quantum counting of ones based on Euler’s formula is used for the pattern recovery as proposed by Trugenberger. We demonstrate the quantum Lernmatrix by experiments using qiskit. We indicate why the assumption proposed by Trugenberger, the lower the parameter temperature t; the better the identification of the correct answers; is not correct. Instead, we introduce a tree-like structure that increases the measured value of correct answers. We show that the cost of loading L sparse patterns into quantum states of a quantum Lernmatrix are much lower than storing individually the patterns in superposition. During the active phase, the quantum Lernmatrices are queried and the results are estimated efficiently. The required time is much lower compared with the conventional approach or the of Grover’s algorithm.
Deeper Exploiting Graph Structure Information by Discrete Ricci Curvature in a Graph Transformer
Authors: Lai Xin , Liu Yang , Qian Rui , Lin Yong , Ye Qiwei
Published: June 2023

Graph-structured data, operating as an abstraction of data containing nodes and interactions between nodes, is pervasive in the real world. There are numerous ways dedicated to extract graph structure information explicitly or implicitly, but whether it has been adequately exploited remains an unanswered question. This work goes deeper by heuristically incorporating a geometric descriptor, the discrete Ricci curvature (DRC), in order to uncover more graph structure information. We present a curvature-based topology-aware graph transformer, termed Curvphormer. This work expands the expressiveness by using a more illuminating geometric descriptor to quantify the connections within graphs in modern models and to extract the desired structure information, such as the inherent community structure in graphs with homogeneous information. We conduct extensive experiments on a variety of scaled datasets, including PCQM4M-LSC, ZINC, and MolHIV, and obtain a remarkable performance gain on various graph-level tasks and fine-tuned tasks.
Improving Semantic Segmentation via Decoupled Body and Edge Information
Authors: Yu Lintao , Yao Anni , Duan Jin
Published: June 2023

In this paper, we propose a method that uses the idea of decoupling and unites edge information for semantic segmentation. We build a new dual-stream CNN architecture that fully considers the interaction between the body and the edge of the object, and our method significantly improves the segmentation performance of small objects and object boundaries. The dual-stream CNN architecture mainly consists of a body-stream module and an edge-stream module, which process the feature map of the segmented object into two parts with low coupling: body features and edge features. The body stream warps the image features by learning the flow-field offset, warps the body pixels toward object inner parts, completes the generation of the body features, and enhances the object’s inner consistency. In the generation of edge features, the current state-of-the-art model processes information such as color, shape, and texture under a single network, which will ignore the recognition of important information. Our method separates the edge-processing branch in the network, i.e., the edge stream. The edge stream processes information in parallel with the body stream and effectively eliminates the noise of useless information by introducing a non-edge suppression layer to emphasize the importance of edge information. We validate our method on the large-scale public dataset Cityscapes, and our method greatly improves the segmentation performance of hard-to-segment objects and achieves state-of-the-art result. Notably, the method in this paper can achieve 82.6% mIoU on the Cityscapes with only fine-annotated data.
Numerical Research on the Jet Mixing Mechanism of the De-Swirling Lobed Mixer Integrated with OGV
Authors: Lei Zhijun , Deng Hanliu , Ouyang Xiaoqing , Zhang Yanfeng , Lu Xingen , Xu Gang , Zhu Junqiang
Published: May 2023

The outlet guide vane (OGV) is integrated with the lobed mixer to improve the exhaust system’s performance with a high core inlet swirl. The best location for integrating the OGV is along the central line of the lobe’s trough and near the exit plane of the lobed mixer. Two types of lobed mixers (the scalloped reference lobed mixer and the scalloped de-swirling lobed mixer) integrating with/without OGVs, are numerically researched under eight inlet swirl conditions ranging from 0° to 35°. The simulation used the Reynolds-Averaged Navier-Stokes (RANS) method with Shear Stress Transport (SST) model based on an unstructured mesh of 30 million cells. The reserved outlet flow angle of the de-swirling lobed mixer is beneficial for enhancing the strength of downstream streamwise vortices and accelerating the jet mixing. After integrating with OGV: it can significantly suppress the leakage vortex between the lobe trough and the central body and the backflow downstream of the central body; on the other hand, it can further increase the strength and scale of streamwise vortices by expanding the radial range of inner secondary flow, thereby accelerating mixing and reducing total pressure loss & thrust loss. Under the design condition, the integrated de-swirling lobed mixer can increase thrust by 3.18% and reduce the mixing loss by 31.17% compared with the reference lobed mixer. Even under non-design conditions, the integrated de-swirling lobed mixer can still use upstream inlet swirl to enhance the streamwise vortices and accelerate the jet mixing within the conditions studied in this paper. The outlet jet uniformity of the integrated de-swirling lobed mixer is better than that of the integrated reference lobed mixer for the case with the same core inlet swirl. Compared with the latter, the former also has better tolerance to the attack angle, especially for the negative attack angle conditions. Under the condition with a core inlet swirl of 35°, the thrust loss of the integrated de-swirling lobed mixer is 2.15% lower than that of the integrated reference lobed mixer.
Development and Experimental Implementation of Optimized PI-ANFIS Controller for Speed Control of a Brushless DC Motor in Fuel Cell Electric Vehicles
Authors: Intidam Abdessamad , El Fadil Hassan , Housny Halima , El Idrissi Zakariae , Lassioui Abdellah , Nady Soukaina , Jabal Laafou Abdeslam
Published: May 2023

This paper compares the performance of different control techniques applied to a high-performance brushless DC (BLDC) motor. The first controller is a classical proportional integral (PI) controller. In contrast, the second one is based on adaptive neuro-fuzzy inference systems (proportional integral-adaptive neuro-fuzzy inference system (PI-ANFIS) and particle swarm optimization-proportional integral-adaptive neuro-fuzzy inference system (PSO-PI-ANFIS)). The control objective is to regulate the rotor speed to its desired reference value in the presence of load torque disturbance and parameter variations. The proposed controller uses a dSPACE platform (MicroLabBox controller board). The experimental prototype comprises a PEMFC system (the Nexa Ballard FC power generator: 1.2 kW, 52 A) and a brushless DC motor BLDC of 1 kW 1000 rpm. The PSO-PI-ANFIS controller presents better performance than the PI-ANFIS and classical PI controllers due to its ability to optimize the PI-ANFIS controller’s parameters using the particle swarm optimization (PSO) algorithm. This optimization results in improved tracking accuracy and reduced overshoot and settling time.
Numerical and Experimental Investigation of the Decoupling Combustion Characteristics of a Burner with Flame Stabilizer
Authors: Wang Jing , Yang Jingchi , Yang Fengling , Cheng Fangqin
Published: June 2023

In order to integrate renewable electricity into the power grid, it is crucial for coal-fired power plant boilers to operate stably across a wide load range. Achieving steady combustion with low nitrogen oxide (NOx) emissions poses a significant challenge for boilers burning low-volatile coal in coal-fired power plants. This study focuses on developing a decoupling combustion technology for low-volatile coal-fired boilers operating at low loads. A three-dimensional numerical simulation is employed to analyze and optimize the geometrical parameters of a burner applied in a real 300 MW pulverized coal fired boiler. Detailed analysis of the burner’s decoupling combustion characteristics, including stable combustion ability and NOx reduction principles, is conducted. The results indicate that this burner showed three stages of coal/air separation, and the flame holder facilitates the stepwise spontaneous ignition and combustion of low-volatile coal. By extending the time between coal pyrolysis and carbon combustion, the burner enhances decoupling combustion and achieves low nitrogen oxide emissions. Based on optimization, a flat partition plate without inclination demonstrates excellent performance in terms of velocity vector field distribution, coal air flow rich/lean separation, combustion, and nitrogen oxide generation. Compared with the initial structural design, the average nitrogen oxide concentration at the outlet is reduced by 59%.
Development and Applications of Thermoelectric Oxide Ceramics and Devices
Authors: Zhang Ping , Lou Zhihao , Gong Lingyun , Wu Zhuozhao , Chen Xuanjie , Xu Weihang , Wang Yiqi , Xu Jie , Dashevsky Zinovi , Gao Feng
Published: June 2023

Thermoelectric materials have gained wide attention to realize multilevel efficient energy management to alleviate the increasingly severe energy crisis. Oxide ceramics were well-explored as potential thermoelectric candidates because of their outstanding merits, including abundance, eco-friendliness, high-temperature stability, and chemical stability. In this work, we aim to provide a comprehensive summary of the diversified state-of-the-art oxide ceramics and establish the links between composition designing, preparation process, structural characteristics, and properties to summarize the underlying chemistry and physics mechanism of band engineering, doping, composited with the second phase, defects engineering, and entropy engineering. Furthermore, advanced device design and applications such as thermoelectric modules, miniature generators, sensors, and coolers were reviewed. Ultimately, the challenges and future perspective of oxides ceramics for the device design and thermoelectric applications in the development of energy harvesting technology have been prospected.
Development and Validation of a Variable Displacement Variable Compression Ratio Miller Cycle Technology on an Automotive Gasoline Engine
Authors: Yang Huiyong , Zhang Lei , Liu Jingping , Fu Jianqin , Shen Dazi , Yuan Zhipeng
Published: June 2023

At partial load, traditional automotive gasoline engines have high pumping losses due to the throttling of the intake charge for load control. Variable Valve Timing (VVT) and the introduction of externally cooled EGR could reduce the pumping losses but only with a very limited effect. On the other hand, in the medium to full load range, the engine cannot utilize a high compression ratio due to limitations in knocking. A variable displacement, variable compression ratio device which utilizes an asymmetric camshaft to realize the different closure times of the two intake valves is discussed in this paper. The large-scale change in the intake valve timing leads to the large-scale change in the effective cylinder volume at the intake valve closure, which realizes a variable cylinder volume and a variable effective compression ratio. The device is utilized to reduce the pumping losses and to increase the in-cylinder thermal efficiency at the same time. Engine dyno test results indicate that, in the low to medium load range, a later closure of the intake valve could reduce the effective cylinder volume, and the intake pressure could be significantly increased, and therefore pumping losses reduced. However, the reduced effective cylinder volume due to a later intake valve closure would lead to reduction in the effective compression ratio (ECR) and a drop in in-cylinder thermal efficiency. Therefore, there is a balance point between the pumping loss reduction and the drop in in-cylinder thermal efficiency. On the other side, in the medium to full load range, when avoiding knocking becomes the major controlling factor of the combustion phasing (degree of constant-volume combustion) and the effective expansion ratio (EER), too high of an effective compression ratio would lead to significant drop in the effective expansion ratio EER and also the in-cylinder thermal efficiency. Therefore, there exists a best compromise between the ECR and EER, and the best system would be one with a moderate ECR but an EER as high as possible. The quantitative equations which include both ECR and EER in the thermal efficiency calculations captured the above observations pretty well and can be utilized to optimize for the best compromise of IVC, EVO, ECR, EER and engine performances during the concept stage and/or the calibration stage of an engine.
Optimizing Integration of Fuel Cell Technology in Renewable Energy-Based Microgrids for Sustainable and Cost-Effective Energy
Authors: Singla Manish Kumar , Gupta Jyoti , Alsharif Mohammed H. , Jahid Abu
Published: June 2023

This article presents a cost-effective and reliable solution for meeting the energy demands of remote areas through the integration of multiple renewable energy sources. The proposed system aims to reduce dependence on fossil fuels and promote sustainable development by utilizing accessible energy resources in a self-contained microgrid. Using the Hybrid Optimization Model for Electric Renewable (HOMER) software, the study examined the optimal combination of energy sources and storage technologies for an integrated hybrid renewable energy system (IHRES) in the Patiala location of Punjab. The total life cycle cost (TLCC) is the main objective of this manuscript. The HOMER result is taken as a reference, and the results are compared with the optimization hybrid algorithm (PSORSA). From this, it is clear that the proposed algorithm has less TLCC as compared to others. Two combinations of energy sources and storage technologies were considered, namely solar photovoltaic (PV)/battery and solar PV/fuel cell (FC). The results showed that the solar PV/FC combination is more cost-effective, reliable, and efficient than the solar PV/battery combination. Additionally, the IHRES strategy was found to be more economically viable than the single energy source system, with lower total life cycle costs and greater reliability and efficiency. Overall, the proposed IHRES model offers a promising solution for meeting energy demands in remote areas while reducing dependence on fossil fuels and promoting sustainable development.
Simultaneous Hydrogen and Ethanol Production from Crude Glycerol by a Microbial Consortium Using Fed-Batch Fermentation
Authors: Mehariya Sanjeet , Signorini Antonella , Marone Antonella , Rosa Silvia
Published: June 2023

Simultaneous bioproduction of hydrogen and ethanol from cheaper waste feedstock has the potential for the development of a more cost-effective biofuel generation process. Crude glycerol (CG), a by-product of the biodiesel industry, is a renewable resource, abundant, sold at low prices and available worldwide. However, the main CG limitations in fermentation processes are mainly related to the presence of impurities and the lack of nitrogen sources, both acting on microbial activity. In this study, a fermentation process with CG was improved using a highly specific microbial consortium called GlyCeroL (GCL). The process was developed in fed-batch fermentation mode using not diluted substrate and carried out under non-sterile conditions and at increasing amounts of the substrate (from 20 to 80 gL−1 of glycerol). The results showed higher H2 (from 6 to 8 LL−1) and EtOH (from 13 to 20 gL−1) production by increasing glycerol concentration from 20 to 40 gL−1. On the other hand, a decrease in glycerol degradation efficiency (from 75 to 56%) was observed. Then, the nitrogen sparging strategy was applied. Using CG of 40 gL−1, process improvement was achieved, leading to the increased production of hydrogen (10 LL−1) but not that of ethanol (20 gL−1). A further increase to 60 gL−1 of glycerol produced a slight increment of EtOH (21 gL−1) and H2 (11 gL−1) but a sharp decrease in glycerol degradation efficiency (41%). Acetate, as the main impurity of CG, was an additional carbon source for GCL microorganisms contributing to EtOH production and increasing that of lactic acid to restore the redox balance. The Denaturing Gradient Gel Electrophoresis (DGGE) fingerprint at the end of all fed-batch fermentations supported the robustness of GCL functional units and their adaptability to fermentation conditions.
Thermal Decomposition Processes in Relation to the Type of Organic Matter, Mineral and Maceral Composition of Menilite Shales
Authors: Labus Małgorzata , Matyasik Irena , Ziemianin Konrad
Published: June 2023

The aim of the research presented in this article was to analyse the processes of source-rock decomposition, including kinetic parameters of pyrolysis, in relation to the type of the organic matter and its maturity. The examined source rocks were Menilite shales from several units within the Flysch Carpathians (Poland). The samples were analysed with use of thermal methods, including Rock-Eval and thermogravimetry coupled with an FTIR detector. Kinetic parameters were determined with use of the model-free integral isoconversion method Kissinger–Akahira–Sunose. The observed gas evolution from the source rocks indicates two stages of organic matter decomposition for some samples. The main stage of pyrolysis takes place in the temperature range from 300 to 500 °C, while the secondary—cracking—takes place in the temperature range from 500 to 650 °C. Using FTIR, we detected vibrations derived from N-H groups, which provide information on the presence of nitrogen in the organic matter, and indicate a low maturity level. C=C stretching vibrations of aromatic hydrocarbons prove a higher maturity of organic matter. The Menilite source rocks have different activation energies, which are related to different organic and mineral compositions. The maturity of organic matter does not have a decisive influence on the kinetic parameters. A high share of carbonates in the rock increases the value of the apparent activation energy. The high share of bituminite within maceral components reduces the value of activation energy.
Automatically Extracting Rubber Tree Stem Shape from Point Cloud Data Acquisition Using a B-Spline Fitting Program
Authors: Li Tuyu , Zheng Yong , Huang Chang , Cao Jianhua , Wang Lingling , Wang Guihua
Published: May 2023

Natural rubber is an important and strategic raw material, used in tires, gloves, and insulating products, that is mainly obtained by cutting the bark of rubber trees. However, the complex contour curve of the rubber tree trunk is hard to fit using a tapping machine. Thus, a trunk contour curve collection would be useful for the development of tapping machines. In this study, an acquisition system based on laser-ranging technology was proposed to collect the point cloud data of rubber tree trunks, and a B-spline fitting program was compiled in Matrix Laboratory (MATLAB) to extract the trunks’ contour curves. The acquisition system is composed of power, a controller, a driver, a laser range finder, and data transmission modules. An automatic extraction experiment on the contour curves of rubber tree trunks was carried out to verify the feasibility and accuracy of using the acquisition system. The results showed that the degree of rubber tree trunk characteristic recognition reached 94.67%, which means that the successful extraction of the rubber tree trunk contour curves and the B-spline fitting program are suitable for the extraction of irregular curves of rubber tree trunks. The coefficient of variation of repeated collection was 0.04%, which indicates that changes in relative positions and acquisition directions have little influence on the extraction and the accuracy of the acquisition system, which are high and stable. Therefore, it was unnecessary to adjust the position of the acquisition device before the collecting process, which helped to improve the efficiency of acquisition considerably. The acquisition system proposed in this study is meaningful to the practical production and application of agroforestry and can not only improve the precision of the rubber tapping process by combining with an automatic rubber tapping machine but can also provide technical support for the prediction of rubber wood volume and the development of ring-cutting equipment for other fruit trees.