bluuebunny/crossref_metadata_2025 huggingface dataset:
The Crack Angle of 60° Is the Most Vulnerable Crack Front in Graphene According to MD Simulations
Authors: Alahmed Ishaq I. , Altanany Sameh M. , Abdulazeez Ismail , Shoaib Hassan , Alsayoud Abduljabar Q. , Abbout Adel , Peng Qing
Published: November 2021

Graphene is a type of 2D material with unique properties and promising applications. Fracture toughness and the tensile strength of a material with cracks are the most important parameters, as micro-cracks are inevitable in the real world. In this paper, we investigated the mechanical properties of triangular-cracked single-layer graphene via molecular dynamics (MD) simulations. The effect of the crack angle, size, temperature, and strain rate on the Young’s modulus, tensile strength, fracture toughness, and fracture strain were examined. We demonstrated that the most vulnerable triangle crack front angle is about 60°. A monitored increase in the crack angle under constant simulation conditions resulted in an enhancement of the mechanical properties. Minor effects on the mechanical properties were obtained under a constant crack shape, constant crack size, and various system sizes. Moreover, the linear elastic characteristics, including fracture toughness, were found to be remarkably influenced by the strain rate variations.
The Photovoltaic Performance of Sensitizers for Organic Solar Cells Containing Fluorinated Chalcones with Different Halogen Substituents
Authors: Mohd Nizar Siti Nabilla Aliya , Ab Rahman Siti Noor Farhana , Zaini Muhamad Fikri , Anizaim Ainizatul Husna , Abdul Razak Ibrahim , Arshad Suhana
Published: November 2021

Two newly halogenated chalcones, derivatives of C15H10ClFO (CH-ClF) and C15H10F2O (CH-FF), were synthesized using the Claisen–Schmidt condensation method. Both compounds were crystallized using a slow evaporation method, forming a monoclinic crystal system with a space group of P21 and P21/c, respectively. The compounds were further analyzed using spectroscopic techniques such as Fourier Transform Infrared (FTIR), Nuclear Magnetic Resonance (NMR), and Ultraviolet–Visible (UV–vis) analyses. The single crystal X-ray diffraction method revealed the existence of C−H⋯O and C−H⋯F intermolecular interactions in CH-FF. Hirshfeld surface analysis was performed to confirm the existence of intermolecular interactions in the compounds. The molecular geometries obtained from the X-ray structure determination were further used to optimize the structures using density functional theory (DFT), with the B3LYP/6-311G++(d,p) basis set in the ground state. The TD-DFT/B3LYP method was used to obtain the electronic properties and the HOMO–LUMO energy gap. Both compounds exhibited A-π-A architecture with different halogen substituents in which the CH-FF, containing -fluoro substituents, possessed good electron injection ability due to its electronegative properties. This increased the flow of the charge transfer for the dye regeneration process and enhanced the efficiency of the dye-sensitized solar cell (DSSC).
NUTM1-Rearranged Neoplasms—A Heterogeneous Group of Primitive Tumors with Expanding Spectrum of Histology and Molecular Alterations—An Updated Review
Authors: Luo Wenyi , Stevens Todd M. , Stafford Phillip , Miettinen Markku , Gatalica Zoran , Vranic Semir
Published: November 2021

Nuclear protein of testis (NUT), a protein product of the NUTM1 gene (located on the long arm of chromosome 15) with highly restricted physiologic expression in post-meiotic spermatids, is the oncogenic driver of a group of emerging neoplasms when fused with genes involved in transcription regulation. Although initially identified in a group of lethal midline carcinomas in which NUT forms fusion proteins with bromodomain proteins, NUTM1-rearrangement has since been identified in tumors at non-midline locations, with non-bromodomain partners and with varied morphology. The histologic features of these tumors have also expanded to include sarcoma, skin adnexal tumors, and hematologic malignancies that harbor various fusion partners and are associated with markedly different clinical courses varying from benign to malignant. Most of these tumors have nondescript primitive morphology and therefore should be routinely considered in any undifferentiated neoplasm. The diagnosis is facilitated by the immunohistochemical use of the monoclonal C52 antibody, fluorescence in situ hybridization (FISH), and, recently, RNA-sequencing. The pathogenesis is believed to be altered expression of oncogenes or tumor suppressor genes by NUT-mediated genome-wide histone modification. NUTM1-rearranged neoplasms respond poorly to classical chemotherapy and radiation therapy. Targeted therapies such as bromodomain and extraterminal domain inhibitor (BETi) therapy are being developed. This current review provides an update on NUTM1-rearranged neoplasms, focusing on the correlation between basic sciences and clinical aspects.
Advances in Breast Cancer Management and Extracellular Vesicle Research, a Bibliometric Analysis
Authors: Teles Ramon Handerson Gomes , Yano Rafael Sussumu , Villarinho Nicolas Jones , Yamagata Ana Sayuri , Jaeger Ruy Gastaldoni , Meybohm Patrick , Burek Malgorzata , Freitas Vanessa Morais
Published: November 2021

Extracellular vesicles transport variable content and have crucial functions in cell–cell communication. The role of extracellular vesicles in cancer is a current hot topic, and no bibliometric study has ever analyzed research production regarding their role in breast cancer and indicated the trends in the field. In this way, we aimed to investigate the trends in breast cancer management involved with extracellular vesicle research. Articles were retrieved from Scopus, including all the documents published concerning breast cancer and extracellular vesicles. We analyzed authors, journals, citations, affiliations, and keywords, besides other bibliometric analyses, using R Studio version 3.6.2. and VOSviewer version 1.6.0. A total of 1151 articles were retrieved, and as the main result, our analysis revealed trending topics on biomarkers of liquid biopsy, drug delivery, chemotherapy, autophagy, and microRNA. Additionally, research related to extracellular vesicles in breast cancer has been focused on diagnosis, treatment, and mechanisms of action of breast tumor-derived vesicles. Future studies are expected to explore the role of extracellular vesicles on autophagy and microRNA, besides investigating the application of extracellular vesicles from liquid biopsies for biomarkers and drug delivery, enabling the development and validation of therapeutic strategies for specific cancers.
Clinical or Imaging Diagnosis of the Current Medical Practice for Superior Vena Cava Syndrome?
Authors: Dragomir Liliana , Marina Virginia , Anghele Mihaela , Anghele Aurelian-Dumitrache
Published: November 2021

Most cases of superior vena cava syndrome are easily diagnosed bya clinical examination alone, but several diagnostic tests and procedures can be helpful. When a patient presentswith a suspected diagnosis of superior vena cava syndrome, the first step is to obtain an imaging study that confirms the diagnosis and aids treatment decisions. Magnetic resonance imaging, contrast-enhanced CT scanning, radionuclide flow studies and traditional venography are all appropriate techniques. Still, the CT scan is the most readily available technology in most centers. The CT scan and magnetic resonance imaging also provide information on possible etiologies and can therefore direct the approach towards a tissue diagnosis.
Development of a Subjective Symptom Rating Scale for Postoperative Oral Dysfunction in Patients with Oral Cancer: Reliability and Validity of the Postoperative Oral Dysfunction Scale-10
Authors: Matsuda Yuhei , Kumakura Isami , Okui Tatsuo , Karino Masaaki , Aoi Noriaki , Okuma Satoe , Takeda Mayu , Hayashida Kenji , Sakamoto Tatsunori , Kanno Takahiro
Published: November 2021

Currently, there is no scale to subjectively assess postoperative oral dysfunction in patients with oral cancer. The purpose of this study was to evaluate the reliability and validity of the Postoperative Oral Dysfunction Scale (POD-10) that we developed. Between September 2019 and August 2021, 62 eligible oral cancer patients (median age, 72 years; 42 men and 20 women) were enrolled in the study. The Cronbach’s alpha coefficient, which indicates the internal consistency of the scale, was 0.94, and the intraclass correlation coefficient, which indicates reproducibility, was 0.85 (95% confidential interval: 0.40–0.96, p < 0.05). Concurrent validity testing showed a statistically significant correlation between POD-10 and Eating Assessment Tool (EAT-10) (r = 0.89, p < 0.05). To test discriminant validity, statistically significant differences were found between early-stage cancer (stage I and II) and advanced-stage cancer (stage III and IV) (p < 0.05). Twenty-four points were calculated as the cutoff value for POD-10 using receiver operating characteristic analysis to calculate the cutoff value. The POD-10 was shown to be a clinically reliable and valid scale that can be used to subjectively assess postoperative oral dysfunction in patients with oral cancer and is expected to be used as a simple diagnostic tool.
Automated Motion Analysis of Bony Joint Structures from Dynamic Computer Tomography Images: A Multi-Atlas Approach
Authors: Keelson Benyameen , Buzzatti Luca , Ceranka Jakub , Gutiérrez Adrián , Battista Simone , Scheerlinck Thierry , Van Gompel Gert , De Mey Johan , Cattrysse Erik , Buls Nico , Vandemeulebroucke Jef
Published: November 2021

Dynamic computer tomography (CT) is an emerging modality to analyze in-vivo joint kinematics at the bone level, but it requires manual bone segmentation and, in some instances, landmark identification. The objective of this study is to present an automated workflow for the assessment of three-dimensional in vivo joint kinematics from dynamic musculoskeletal CT images. The proposed method relies on a multi-atlas, multi-label segmentation and landmark propagation framework to extract bony structures and detect anatomical landmarks on the CT dataset. The segmented structures serve as regions of interest for the subsequent motion estimation across the dynamic sequence. The landmarks are propagated across the dynamic sequence for the construction of bone embedded reference frames from which kinematic parameters are estimated. We applied our workflow on dynamic CT images obtained from 15 healthy subjects on two different joints: thumb base (n = 5) and knee (n = 10). The proposed method resulted in segmentation accuracies of 0.90 ± 0.01 for the thumb dataset and 0.94 ± 0.02 for the knee as measured by the Dice score coefficient. In terms of motion estimation, mean differences in cardan angles between the automated algorithm and manual segmentation, and landmark identification performed by an expert were below 1°. Intraclass correlation (ICC) between cardan angles from the algorithm and results from expert manual landmarks ranged from 0.72 to 0.99 for all joints across all axes. The proposed automated method resulted in reproducible and reliable measurements, enabling the assessment of joint kinematics using 4DCT in clinical routine.
Prominent Asymmetric Muscle Weakness and Atrophy in Seronegative Immune-Mediated Necrotizing Myopathy
Authors: Park Sunha , Jang Dae-Hyun , Kim Jae-Min , Yoon Nara
Published: November 2021

Immune-mediated necrotizing myopathy, a new subgroup of inflammatory myopathies, usually begins with subacute onset of symmetrical proximal muscle weakness. A 35-year-old male presented with severe asymmetric iliopsoas atrophy and low back pain with a previous history of left lower extremity weakness. Although his first left lower extremity weakness occurred 12 years ago, he did not receive a clear diagnosis. Magnetic resonance imaging of both thigh muscles showed muscle edema and contrast enhancement in patch patterns, and the left buttock and thigh muscles were more atrophied compared to the right side. Serum creatine kinase levels were elevated, and serologic testings were all negative. Genetic testing using a targeted gene-sequencing panel for neuromuscular disease including myopathy identified no pathogenic variants. Muscle biopsy on the right vastus lateralis showed scattered myofiber necrosis with phagocytosis and an absence of prominent inflammatory cells, consistent with seronegative necrotizing myopathy. Thus, unusual asymmetric muscle weakness and atrophy can be a manifestation of inflammatory myopathy.
Transactional Interpretation for the Principle of Minimum Fisher Information
Authors: Makowski Marcin , Piotrowski Edward W. , Frąckiewicz Piotr , Szopa Marek
Published: November 2021

The principle of minimum Fisher information states that in the set of acceptable probability distributions characterizing the given system, it is best done by the one that minimizes the corresponding Fisher information. This principle can be applied to transaction processes, the dynamics of which can be interpreted as the market tendency to minimize the information revealed about itself. More information involves higher costs (information is physical). The starting point for our considerations is a description of the market derived from the assumption of minimum Fisher information for a strategy with a fixed financial risk. Strategies of this type that minimize Fisher information overlap with the well-known eigenstates of a the quantum harmonic oscillator. The analytical extension of this field of strategy to the complex vector space (traditional for quantum mechanics) suggests the study of the interference of the oscillator eigenstates in terms of their minimization of Fisher information. It is revealed that the minimum value of Fisher information of the superposition of the two strategies being the ground state and the second excited state of the oscillator, has Fisher information less than the ground state of the oscillator. Similarly, less information is obtained for the system of strategies (the oscillator eigenstates) randomized by the Gibbs distribution. We distinguish two different views on the description of Fisher information. One of them, the classical, is based on the value of Fisher information. The second, we call it transactional, expresses Fisher information from the perspective of the constant risk of market strategies. The orders of the market strategies derived from these two descriptions are different. From a market standpoint, minimizing Fisher information is equivalent to minimizing risk.
The World Is Not a Theorem
Authors: Kauffman Stuart , Roli Andrea
Published: November 2021

The evolution of the biosphere unfolds as a luxuriant generative process of new living forms and functions. Organisms adapt to their environment, exploit novel opportunities that are created in this continuous blooming dynamics. Affordances play a fundamental role in the evolution of the biosphere, for organisms can exploit them for new morphological and behavioral adaptations achieved by heritable variations and selection. This way, the opportunities offered by affordances are then actualized as ever novel adaptations. In this paper, we maintain that affordances elude a formalization that relies on set theory: we argue that it is not possible to apply set theory to affordances; therefore, we cannot devise a set-based mathematical theory to deduce the diachronic evolution of the biosphere.
Momentum-Space Decoherence of Distinguishable and Identical Particles in the Caldeira–Leggett Formalism
Authors: Khani Z. , Mousavi S. V. , Miret-Artés S.
Published: November 2021

In this work, momentum-space decoherence using minimum and nonminimum-uncertainty-product (stretched) Gaussian wave packets in the framework of Caldeira–Leggett formalism and under the presence of a linear potential is studied. As a dimensionless measure of decoherence, purity, a quantity appearing in the definition of the linear entropy, is studied taking into account the role of the stretching parameter. Special emphasis is on the open dynamics of the well-known cat states and bosons and fermions compared to distinguishable particles. For the cat state, while the stretching parameter speeds up the decoherence, the external linear potential strength does not affect the decoherence time; only the interference pattern is shifted. Furthermore, the interference pattern is not observed for minimum-uncertainty-product-Gaussian wave packets in the momentum space. Concerning bosons and fermions, the question we have addressed is how the symmetry of the wave functions of indistinguishable particles is manifested in the decoherence process, which is understood here as the loss of being indistinguishable due to the gradual emergence of classical statistics with time. We have observed that the initial bunching and anti-bunching character of bosons and fermions, respectively, in the momentum space are not preserved as a function of the environmental parameters, temperature, and damping constant. However, fermionic distributions are slightly broader than the distinguishable ones and these similar to the bosonic distributions. This general behavior could be interpreted as a residual reminder of the symmetry of the wave functions in the momentum space for this open dynamics.
The Eco-Evo Mandala: Simplifying Bacterioplankton Complexity into Ecohealth Signatures
Authors: Galbraith Elroy , Convertino Matteo
Published: November 2021

The microbiome emits informative signals of biological organization and environmental pressure that aid ecosystem monitoring and prediction. Are the many signals reducible to a habitat-specific portfolio that characterizes ecosystem health? Does an optimally structured microbiome imply a resilient microbiome? To answer these questions, we applied our novel Eco-Evo Mandala to bacterioplankton data from four habitats within the Great Barrier Reef, to explore how patterns in community structure, function and genetics signal habitat-specific organization and departures from theoretical optimality. The Mandala revealed communities departing from optimality in habitat-specific ways, mostly along structural and functional traits related to bacterioplankton abundance and interaction distributions (reflected by ϵ and λ as power law and exponential distribution parameters), which are not linearly associated with each other. River and reef communities were similar in their relatively low abundance and interaction disorganization (low ϵ and λ) due to their protective structured habitats. On the contrary, lagoon and estuarine inshore reefs appeared the most disorganized due to the ocean temperature and biogeochemical stress. Phylogenetic distances (D) were minimally informative in characterizing bacterioplankton organization. However, dominant populations, such as Proteobacteria, Bacteroidetes, and Cyanobacteria, were largely responsible for community patterns, being generalists with a large functional gene repertoire (high D) that increases resilience. The relative balance of these populations was found to be habitat-specific and likely related to systemic environmental stress. The position on the Mandala along the three fundamental traits, as well as fluctuations in this ecological state, conveys information about the microbiome’s health (and likely ecosystem health considering bacteria-based multitrophic dependencies) as divergence from the expected relative optimality. The Eco-Evo Mandala emphasizes how habitat and the microbiome’s interaction network topology are first- and second-order factors for ecosystem health evaluation over taxonomic species richness. Unhealthy microbiome communities and unbalanced microbes are identified not by macroecological indicators but by mapping their impact on the collective proportion and distribution of interactions, which regulates the microbiome’s ecosystem function.
Algorithmic Approaches for Assessing Irreversibility in Time Series: Review and Comparison
Authors: Zanin Massimiliano , Papo David
Published: November 2021

The assessment of time irreversibility, i.e., of the lack of invariance of the statistical properties of a system under the operation of time reversal, is a topic steadily gaining attention within the research community. Irreversible dynamics have been found in many real-world systems, with alterations being connected to, for instance, pathologies in the human brain, heart and gait, or to inefficiencies in financial markets. Assessing irreversibility in time series is not an easy task, due to its many aetiologies and to the different ways it manifests in data. It is thus not surprising that several numerical methods have been proposed in the last decades, based on different principles and with different applications in mind. In this contribution we review the most important algorithmic solutions that have been proposed to test the irreversibility of time series, their underlying hypotheses, computational and practical limitations, and their comparative performance. We further provide an open-source software library that includes all tests here considered. As a final point, we show that “one size does not fit all”, as tests yield complementary, and sometimes conflicting views to the problem; and discuss some future research avenues.
Sentiment-Augmented Supply and Demand Equations for the Dry Bulk Shipping Market
Authors: Michail Nektarios A. , Melas Konstantinos D.
Published: November 2021

We present, for the first time in the literature, empirical estimates of the supply and demand curves for the ocean-going dry bulk sector, using a three-stage least squares methodology. Furthermore, we augment these functions with sentiment, which appears to have a positive and significant impact on supply. This supports the view that the outlook that shipowners have about the market will undoubtedly influence their decisions regarding purchasing vessels or bringing them out of lay up. Thus, our results highlight the fact that future expectations have an impact on current pricing, albeit indirectly, through their impact on the supply side. Our results further enhance the behavioral economics literature and provide important insights for both academics and professionals.
Outstanding Primary Leadership in Times of Turbulence
Authors: Howard Colin , Dhillon Jaswinder K.
Published: November 2021

Leadership and management in schools have sought to produce high quality education for all pupils. To inform and support school leaders’ educationalists have developed theories and undertaken research studies identifying the relationships, contexts and characteristics that enable effective leadership. However, recent times of turbulence in primary schools have had an inevitable impact upon the key drivers for successful leadership and management. This study builds upon our previous research into outstanding leadership in primary education to examine the impact that such change has had upon the leadership of serving head teachers. It utilises an adapted Q-sort methodology to identify the views of serving head teachers to gain insights into the impact that such change has had upon their leadership. Overall, the analysis identified a need for aspirational characteristics of leadership, underpinned by personal values to guide schools in such times, as they strive to produce high quality education.
The Digital Girls Response to Pandemic: Impacts of in Presence and Online Extracurricular Activities on Girls Future Academic Choices
Authors: Faenza Francesco , Canali Claudia , Colajanni Michele , Carbonaro Antonella
Published: November 2021

In the last few years, several initiatives based on extracurricular activities have been organized in many countries around the world, with the aim to reduce the digital gender gap in STEM (Science, Technology, Engineering, Math) fields. Among them, the Digital Girls summer camp, organized every year since 2014 by two Italian universities with the aim to attract female students to ICT (Information and Communication Technologies) disciplines, represents quite a unique initiative for its characteristics of long-duration (3–4 entire weeks) and complete gratuitousness for the participants. The COVID-19 emergency imposed severe changes to such activities, that had to be modified and carried out in the online mode as a consequence of social distancing. However, on one hand, the general lack of high-quality evaluations of these initiatives hinders the possibility to understand the actual impact of extracurricular activities on the future academic choices of the participants. On the other hand, the availability of data collected over different editions of Digital Girls has allowed us to analyze the summer camp impact and to evaluate the pros and cons of in-presence and online activities. The main contribution of this paper is twofold. First, we present an overview of existing experiences, at the national (Italian) and international levels, to increase female participation in integrated STEM and ICT fields. Second, we analyze how summer camp participation can influence girls’ future academic choices, with specific attention to ICT-related disciplines. In particular, the collection of a significant amount of data through anonymous surveys conducted before and after the camp activities over the two editions allowed us to evidence the different impacts of in-presence and online extracurricular activities.
Octave-Band Four-Beam Antenna Arrays with Stable Beam Direction Fed by Broadband 4 × 4 Butler Matrix
Authors: Dudek Andrzej , Kanios Piotr , Staszek Kamil , Gruszczynski Slawomir , Wincza Krzysztof
Published: November 2021

A novel concept of four-beam antenna arrays operating in a one-octave frequency range that allows stable beam directions and beamwidths to be achieved is proposed. As shown, such radiation patterns can be obtained when radiating elements are appropriately spaced and fed by a broadband 4 × 4 Butler matrix with directional filters connected to its outputs. In this solution, broadband radiating elements are arranged in such a way that, for the lower and upper frequencies, two separate subarrays can be distinguished, each one consisting of identically arranged radiating elements. The subarrays are fed by a broadband Butler matrix at the output to which an appropriate feeding network based on directional filters is connected. These filters ensure smooth signal switching across the operational bandwidth between elements utilized at lower and higher frequency bands. Therefore, as shown, it is possible to control both beamwidths and beam directions of the resulting multi-beam antenna arrays. Moreover, two different concepts of the feeding network connected in between the Butler matrix and radiating elements for lowering the sidelobes are discussed. The theoretical analyses of the proposed antenna arrays are shown and confirmed by measurements of the developed two-antenna arrays consisting of eight and twelve radiating elements, operating in a 2–4 GHz frequency range.
Stock Market Prediction Using Machine Learning Techniques: A Decade Survey on Methodologies, Recent Developments, and Future Directions
Authors: Rouf Nusrat , Malik Majid Bashir , Arif Tasleem , Sharma Sparsh , Singh Saurabh , Aich Satyabrata , Kim Hee-Cheol
Published: November 2021

With the advent of technological marvels like global digitization, the prediction of the stock market has entered a technologically advanced era, revamping the old model of trading. With the ceaseless increase in market capitalization, stock trading has become a center of investment for many financial investors. Many analysts and researchers have developed tools and techniques that predict stock price movements and help investors in proper decision-making. Advanced trading models enable researchers to predict the market using non-traditional textual data from social platforms. The application of advanced machine learning approaches such as text data analytics and ensemble methods have greatly increased the prediction accuracies. Meanwhile, the analysis and prediction of stock markets continue to be one of the most challenging research areas due to dynamic, erratic, and chaotic data. This study explains the systematics of machine learning-based approaches for stock market prediction based on the deployment of a generic framework. Findings from the last decade (2011–2021) were critically analyzed, having been retrieved from online digital libraries and databases like ACM digital library and Scopus. Furthermore, an extensive comparative analysis was carried out to identify the direction of significance. The study would be helpful for emerging researchers to understand the basics and advancements of this emerging area, and thus carry-on further research in promising directions.
MemBox: Shared Memory Device for Memory-Centric Computing Applicable to Deep Learning Problems
Authors: Choi Yongseok , Lim Eunji , Shin Jaekwon , Lee Cheol-Hoon
Published: November 2021

Large-scale computational problems that need to be addressed in modern computers, such as deep learning or big data analysis, cannot be solved in a single computer, but can be solved with distributed computer systems. Since most distributed computing systems, consisting of a large number of networked computers, should propagate their computational results to each other, they can suffer the problem of an increasing overhead, resulting in lower computational efficiencies. To solve these problems, we proposed an architecture of a distributed system that used a shared memory that is simultaneously accessible by multiple computers. Our architecture aimed to be implemented in FPGA or ASIC. Using an FPGA board that implemented our architecture, we configured the actual distributed system and showed the feasibility of our system. We compared the results of the deep learning application test using our architecture with that using Google Tensorflow’s parameter server mechanism. We showed improvements in our architecture beyond Google Tensorflow’s parameter server mechanism and we determined the future direction of research by deriving the expected problems.
Stable, Low Power and Bit-Interleaving Aware SRAM Memory for Multi-Core Processing Elements
Authors: Yadav Nandakishor , Kim Youngbae , Li Shuai , Choi Kyuwon Ken
Published: November 2021

The machine learning and convolutional neural network (CNN)-based intelligent artificial accelerator needs significant parallel data processing from the cache memory. The separate read port is mostly used to design built-in computational memory (CRAM) to reduce the data processing bottleneck. This memory uses multi-port reading and writing operations, which reduces stability and reliability. In this paper, we proposed a self-adaptive 12T SRAM cell to increase the read stability for multi-port operation. The self-adaptive technique increases stability and reliability. We increased the read stability by refreshing the storing node in the read mode of operation. The proposed technique also prevents the bit-interleaving problem. Further, we offered a butterfly-inspired SRAM bank to increase the performance and reduce the power dissipation. The proposed SRAM saves 12% more total power than the state-of-the-art 12T SRAM cell-based SRAM. We improve the write performance by 28.15% compared with the state-of-the-art 12T SRAM design. The total area overhead of the proposed architecture compared to the conventional 6T SRAM cell-based SRAM is only 1.9 times larger than the 6T SRAM cell.
An Economic Model to Assess Profitable Scenarios of EAF-Based Steelmaking Plants under Uncertain Conditions
Authors: Facchini Francesco , Mossa Giorgio , Mummolo Giovanni , Vitti Micaela
Published: November 2021

The steelmaking processes are considered extremely energy-intensive and carbon-dependent processes. In 2018, it was estimated that the emissions from global steel production represented 7–9% of direct emissions generated by fossil fuels. It was estimated that a specific emissions value of 1.8 tCO2 per ton of steel was produced due to the carbon-dependent nature of the traditional blast furnace and basic oxygen furnace (BF-BOF) route. Therefore, it is necessary to find an alternative solution to the BF-BOF route for steel production to counteract this negative trend, resulting in being sustainable from an environmental and economic point of view. To this concern, the objective of this work consists of developing a total cost function to assess the economic convenience of steelmaking processes considering the variability of specific market conditions (i.e., iron ore price, scraps price, energy cost, etc.). To this purpose, a direct reduction (DR) process fueled with natural gas (NG) to feed an electric arc furnace (EAF) using recycled steel scrap was considered. The approach introduced is totally new; it enables practitioners, managers, and experts to conduct a preliminary economic assessment of innovative steelmaking solutions under market uncertainty. A numerical simulation has been conducted to evaluate the profitability of the investment considering the economic and environmental costs. It emerged that the investment is profitable in any case from an economic perspective. On the contrary, considering the environmental costs, the profitability of the investment is not guaranteed under certain circumstances.
Reliability Enhancement of Power IGBTs under Short-Circuit Fault Condition Using Short-Circuit Current Limiting-Based Technique
Authors: Mohsenzade Sadegh , Naghibi Javad , Mehran Kamyar
Published: November 2021

Like the widely-used semiconductor switch, Insulated Gate Bipolar Transistors (IGBTs) are subject to many failures and degradation in power electronic converters. In Short Circuit Fault (SCF), as the most reported failures in IGBTs, drastic, sudden temperature rise, and peak SCF current are widespread failures owing to a relatively long delay of the protection subsystem. This paper proposes a protection strategy to limit the junction temperature rise by limiting the SCF current by adding a small value resistor in the IGBT emitter. Second, it reduces the SCF current to a value much less than the saturated current. With the proposed control approach, sudden temperature rise during SCF is controlled, preventing significant failure in IGBTs. The extension of the permissible SCF time is achieved even for the cases with temporary arcs. A simple control loop activates in the SCF condition and does not create slow transients for the IGBT. The results of this paper are validated through simulation and experiment.
Formation of a Fast Charge Transfer Channel in Quasi-2D Perovskite Solar Cells through External Electric Field Modulation
Authors: Zhu Xixiang , Peng Liping , Li Jinpeng , Yu Haomiao , Xie Yulin
Published: November 2021

Quasi-2D perovskites solar cells exhibit excellent environmental stability, but relatively low photovoltaic properties, compared with 3D perovskites solar cells. However, charge transport and extraction in quasi-2D perovskite solar cells are still limited by the inevitable quantum well effect, resulting in low power conversion efficiency (PCE). To date, most efforts concentrate on crystal orientation and favorable alignment during materials and films processing. In this paper, we demonstrated that the quasi-2D perovskite [(BA)2(MA)3Pb4I13 (n = 4)] solar cells show an optimized device performance through forming a fast charge transfer channel among 2D quantum wells through external electric field modulation, with appropriate modulation bias and time after the device has been fabricated. Essentially, ions will move directionally due to local polarization in quasi-2D perovskite solar cells under the action of electric field modulation. More importantly, the mobile ions function as a dopant to de-passivate the defects when releasing at grain boundaries, while decreasing built-in potential by applying forward modulation bias with proper modulation time. The capacitance-voltage characteristics indicate that electric field modulation can decrease the charge accumulation and improve the charge collection in quasi-2D perovskite solar cells. Photoluminescence (PL) studies confirm that the non-radiative recombination is reduced by electric field modulation, leading to enhanced charge transfer. Our work indicates that external electric field modulation is an effective method to form a fast charge transfer channel among 2D quantum wells, leading to enhanced charge transfer and charge collection through local polarization toward developing high–performance quasi-2D perovskite devices.
The Impact of Corporate Governance on the Capital Structure of Companies from the Energy Industry. The Case of Poland
Authors: Grabinska Barbara , Kedzior Marcin , Kedzior Dorota , Grabinski Konrad
Published: November 2021

The energy sector is expected to face fundamental challenges in the near future. On the one hand, it is experiencing a rapidly increasing demand for energy. At the same time, it is subject to the pressure of the climate policy due to environmental issues. For the same reason, the energy sector is forced to undertake costly investments to transform production from black to green energy. The issue of financing has become one of the key problems of the energy sector, especially in those countries in which energy production traditionally is based on fossil fuels, i.e., coal. The paper aims to investigate the impact of corporate governance on the capital structure of companies from the energy industry. We use three proxies of corporate governance quality: institutional investors, the board size, and state ownership and investigate their impact on capital structure. Our findings suggest that the latter two negatively impact debt levels. In our model, we control for financial factors and CEO personal characteristics. We use a Polish setting since transformational problems of the energy sector in Poland are especially visible. At the same time, energy companies in Poland are subject to the strict EU climate policy.
Study on the Positioning Accuracy of GNSS/INS Systems Supported by DGPS and RTK Receivers for Hydrographic Surveys
Authors: Stateczny Andrzej , Specht Cezary , Specht Mariusz , Brčić David , Jugović Alen , Widźgowski Szymon , Wiśniewska Marta , Lewicka Oktawia
Published: November 2021

Hydrographic surveys, in accordance with the International Hydrographic Organization (IHO) S-44 standard, can be carried out in the following five orders: Exclusive, Special, 1a, 1b and 2, for which minimum accuracy requirements for the applied positioning system have been set out. They are as follows, respectively: 1, 2, 5, 5 and 20 m, with a confidence level of 95% in two-dimensional space. The Global Navigation Satellite System (GNSS) network solutions (accuracy: 2–3 cm (p = 0.95)) and the Differential Global Positioning System (DGPS) (accuracy: 1–2 m (p = 0.95)) are now commonly used positioning methods in hydrography. Due to the fact that a new order of hydrographic surveys has appeared in the IHO S-44 standard from 2020—Exclusive, looking at the current positioning accuracy of the DGPS system, it is not known whether it can be used in it. The aim of this article is to determine the usefulness of GNSS/Inertial Navigation Systems (INS) for hydrographic surveys. During the research, the following two INSs were used: Ekinox2-U and Ellipse-D by the SBG Systems, which were supported by DGPS and Real Time Kinematic (RTK) receivers. GNSS/INS measurements were carried out during the manoeuvring of the Autonomous/Unmanned Surface Vehicle (ASV/USV) named “HydroDron” on Kłodno lake in Zawory. The acquired data were processed using the mathematical model that allows us to assess whether any positioning system at a given point in time meets (or not) the accuracy requirements for each IHO order. The model was verified taking into account the historical and current test results of the DGPS and RTK systems. Tests have confirmed that the RTK system meets the requirements of all the IHO orders, even in situations where it is not functioning 100% properly. Moreover, it was proven that the DGPS system does not only meet the requirements provided for the most stringent IHO order, i.e., the Exclusive Order (horizontal position error ≤ 1 m (p = 0.95)). Statistical analyses showed that it was only a few centimetres away from meeting this criterion. Therefore, it can be expected that soon it will be used in all the IHO orders.
Investigation of Water Composition on Formation Damage and Related Energy Recovery from Geothermal Reservoirs: Geochemical and Geomechanics Insights
Authors: Khurshid Ilyas , Afgan Imran
Published: November 2021

The main challenge in extracting geothermal energy is to overcome issues relating to geothermal reservoirs such as the formation damage and formation fracturing. The objective of this study is to develop an integrated framework that considers the geochemical and geomechanics aspects of a reservoir and characterizes various formation damages such as impairment of formation porosity and permeability, hydraulic fracturing, lowering of formation breakdown pressure, and the associated heat recovery. In this research study, various shallow, deep and high temperature geothermal reservoirs with different formation water compositions were simulated to predict the severity/challenges during water injection in hot geothermal reservoirs. The developed model solves various geochemical reactions and processes that take place during water injection in geothermal reservoirs. The results obtained were then used to investigate the geomechanics aspect of cold-water injection. Our findings presented that the formation temperature, injected water temperature, the concentration of sulfate in the injected water, and its dilution have a noticeable impact on rock dissolution and precipitation. In addition, anhydrite precipitation has a controlling effect on permeability impairment in the investigated case study. It was observed that the dilution of water could decrease formation of scale while the injection of sulfate rich water could intensify scale precipitation. Thus, the reservoir permeability could decrease to a critical level, where the production of hot water reduces and the generation of geothermal energy no longer remains economical. It evident that injection of incompatible water would decrease the formation porosity. Thus, the geomechanics investigation was performed to determine the effect of porosity decrease. It was found that for the 50% porosity reduction case, the initial formation breakdown pressure reduced from 2588 psi to 2586 psi, and for the 75% porosity reduction case it decreased to 2584 psi. Thus, geochemical based formation damage is significant but geomechanics based formation fracturing is insignificant in the selected case study. We propose that water composition should be designed to minimize damage and that high water injection pressures in shallow reservoirs should be avoided.
Comparison Study on High Force Density Linear Motors for Compressor Application
Authors: Zhao Fei , Jiang Yunshuai , Yang Kuang , Zhang Chengming , Lian Wei , Wang Guangyin
Published: November 2021

This paper presents the modular topologies of the dual-stator dual-winding permanent magnet (PM) linear motors for linear compressors used in the electrified transportation application. Compared to the conventional PM linear motor in compressor, the proposed modular model is designed with the same volume but a higher thrust force density and a further higher air pressure in air cylinder, which are competitive in the compressor industry. The proposed compact PM linear motors are constructed with tubular windings in both inner and outer stators, as well as the ring-type magnet in mover. Simulation results of motor characteristics are compared by three-dimensional finite element method (3D FEM). Finally, the prototypes of the proposed PM linear motors are manufactured and tested for the linear compressor application.
Field-Based Prediction Models for Stop Penalty in Traffic Signal Timing Optimization
Authors: Alshayeb Suhaib , Stevanovic Aleksandar , Park B. Brian
Published: November 2021

Transportation agencies optimize signals to improve safety, mobility, and the environment. One commonly used objective function to optimize signals is the Performance Index (PI), a linear combination of delays and stops that can be balanced to minimize fuel consumption (FC). The critical component of the PI is the stop penalty “K”, which expresses an FC stop equivalency estimated in seconds of pure delay. This study applies vehicular trajectory and FC data collected in the field, for a large fleet of modern vehicles, to compute the K-factor. The tested vehicles were classified into seven homogenous groups by using the k-prototype algorithm. Furthermore, multigene genetic programming (MGGP) is utilized to develop prediction models for the K-factor. The proposed K-factor models are expressed as functions of various parameters that impact its value, including vehicle type, cruising speed, road gradient, driving behavior, idling FC, and the deceleration duration. A parametric analysis is carried out to check the developed models’ quality in capturing the individual impact of the included parameters on the K-factor. The developed models showed an excellent performance in estimating the K-factor under multiple conditions. Future research shall evaluate the findings by using field-based K-values in optimizing signals to reduce FC.
Short Term Elevated CO2 Interacts with Iron Deficiency, Further Repressing Growth, Photosynthesis and Mineral Accumulation in Soybean (Glycine max L.) and Common Bean (Phaseolus vulgaris L.)
Authors: Deuchande Teresa , Soares José , Nunes Fábio , Pinto Elisabete , Vasconcelos Marta W.
Published: November 2021

Elevated CO2 (eCO2) has been reported to cause mineral losses in several important food crops such as soybean (Glycine max L.) and common bean (Phaseolus vulgaris L.). In addition, more than 30% of the world’s arable land is calcareous, leading to iron (Fe) deficiency chlorosis and lower Fe levels in plant tissues. We hypothesize that there will be combinatorial effects of eCO2 and Fe deficiency on the mineral dynamics of these crops at a morphological, biochemical and physiological level. To test this hypothesis, plants were grown hydroponically under Fe sufficiency (20 μM Fe-EDDHA) or deficiency (0 μM Fe-EDDHA) at ambient CO2 (aCO2, 400 ppm) or eCO2 (800 ppm). Plants of both species exposed to eCO2 and Fe deficiency showed the lowest biomass accumulation and the lowest root: shoot ratio. Soybean at eCO2 had significantly higher chlorophyll levels (81%, p < 0.0001) and common bean had significantly higher photosynthetic rates (60%, p < 0.05) but only under Fe sufficiency. In addition, eCO2 increased ferric chelate reductase acivity (FCR) in Fe-sufficient soybean by 4-fold (p < 0.1) and in Fe-deficient common bean plants by 10-fold (p < 0.0001). In common bean, an interactive effect of both environmental factors was observed, resulting in the lowest root Fe levels. The lowering of Fe accumulation in both crops under eCO2 may be linked to the low root citrate accumulation in these plants when grown with unrestricted Fe supply. No changes were observed for malate in soybean, but in common bean, shoot levels were significantly lower under Fe deficiency (77%, p < 0.05) and Fe sufficiency (98%, p < 0.001). These results suggest that the mechanisms involved in reduced Fe accumulation caused by eCO2 and Fe deficiency may not be independent, and an interaction of these factors may lead to further reduced Fe levels.