bluuebunny/crossref_metadata_2025 huggingface dataset:
Voltage-Gated Sodium Channel NaV1.5 Controls NHE−1−Dependent Invasive Properties in Colon Cancer Cells
Authors: Lopez-Charcas Osbaldo , Poisson Lucile , Benouna Oumnia , Lemoine Roxane , Chadet Stéphanie , Pétereau Adrien , Lahlou Widad , Guyétant Serge , Ouaissi Mehdi , Pukkanasut Piyasuda , Dutta Shilpa , Velu Sadanandan , Besson Pierre , Moussata Driffa , Roger Sébastien
Published: December 2022

Colorectal cancer (CRC) is the second leading cause of death worldwide, with 0.9 million deaths per year. The metastatic stage of the disease is identified in about 20% of cases at the first diagnosis and is associated with low patient-survival rates. Voltage-gated sodium channels (NaV) are abnormally overexpressed in several carcinomas including CRC and are strongly associated with the metastatic behavior of cancer cells. Acidification of the extracellular space by Na+/H+ exchangers (NHE) contributes to extracellular matrix degradation and cell invasiveness. In this study, we assessed the expression levels of pore-forming α-subunits of NaV channels and NHE exchangers in tumor and adjacent non-malignant tissues from colorectal cancer patients, CRC cell lines and primary tumor cells. In all cases, SCN5A (gene encoding for NaV1.5) was overexpressed and positively correlated with cancer stage and poor survival prognosis for patients. In addition, we identified an anatomical differential expression of SCN5A and SLC9A1 (gene encoding for NHE-1) being particularly relevant for tumors that originated on the sigmoid colon epithelium. The functional activity of NaV1.5 channels was characterized in CRC cell lines and the primary cells of colon tumors obtained using tumor explant methodologies. Furthermore, we assessed the performance of two new small-molecule NaV1.5 inhibitors on the reduction of sodium currents, as well as showed that silencing SCN5A and SLC9A1 substantially reduced the 2D invasive capabilities of cancer cells. Thus, our findings show that both NaV1.5 and NHE-1 represent two promising targetable membrane proteins against the metastatic progression of CRC.
Quality of Sarcoma Care: Longitudinal Real-Time Assessment and Evidence Analytics of Quality Indicators
Authors: Heesen Philip , Studer Gabriela , Bode Beata , Windegger Hubi , Staeheli Benjamin , Aliu Paul , Martin-Broto Javier , Gronchi Alessandro , Blay Jean-Yves , Le Cesne Axel , Fuchs Bruno
Published: December 2022

Sarcomas represent a large group of rare to very rare diseases, requiring complex management with a transdisciplinary approach. Overall progress has been hampered because of discipline, institution and network fragmentation, and there is no global data harmonization or quality standards. To report on and improve quality, a common definition of quality indicators (QIs) of sarcoma care as well as the capacity to assess longitudinal real-time data is required. An international advisory board of world-renowned sarcoma experts defined six categories of QIs, totaling more than 80 quality indicators. An interoperable (web-based) digital platform was then created combining the management of the weekly sarcoma board meeting with the sarcoma registry and incorporating patient-reported outcome measures (PROMs) into the routine follow-up care to assess the entire care cycle of the patient. The QIs were then programmed into the digital platform for real-time analysis and visualization. The definition of standardized QIs covering all physician- (diagnostics and therapeutics), patient- (PROMS/PREMS), and cost-based aspects in combination with their real-time assessment over the entire sarcoma care cycle can be realized. Standardized QIs as well as their real-time assessment and data visualization are critical to improving the quality of sarcoma care. By enabling predictive modelling and introducing VBHC, precision health care for a complex disease is on the horizon.
Systemic Therapy for HER2-Positive Metastatic Breast Cancer: Current and Future Trends
Authors: Vega Cano Kreina Sharela , Marmolejo Castañeda David Humberto , Escrivá-de-Romaní Santiago , Saura Cristina
Published: December 2022

Approximately 20% of breast cancers (BC) overexpress human epidermal growth factor receptor 2 (HER2). This subtype of BC is a clinically and biologically heterogeneous disease that was associated with an increased risk for the development of systemic and brain metastases and poor overall survival before anti-HER2 therapies were developed. The standard of care was dual blockade with trastuzumab and pertuzumab as first-line followed by TDM-1 as second-line. However, with the advent of new HER2-targeted monoclonal antibodies, tyrosine kinase inhibitors and antibody- drug conjugates, the clinical outcomes of patients with HER2-positive BC have changed dramatically in recent years, leading to a paradigm shift in the treatment of the disease. Notably, the development of new-generation ADCs has led to unprecedented results compared with T-DM1, currently establishing trastuzumab deruxtecan as a new standard of care in second-line. Despite the widespread availability of HER2-targeted therapies, patients with HER2-positive BC continue to face the challenges of disease progression, treatment resistance, and brain metastases. Response rate and overall life expectancy decrease with each additional line of treatment, and tumor heterogeneity remains an issue. In this review, we update the new-targeted therapeutic options for HER2-positive BC and highlight the future perspectives of treatment in this setting.
Highlights on the Role of Galectin-3 in Colorectal Cancer and the Preventive/Therapeutic Potential of Food-Derived Inhibitors
Authors: Aureli Anna , Del Cornò Manuela , Marziani Beatrice , Gessani Sandra , Conti Lucia
Published: December 2022

Colorectal cancer (CRC) is a leading cause of death worldwide. Despite advances in surgical and therapeutic management, tumor metastases and resistance to therapy still represent major hurdles. CRC risk is highly modifiable by lifestyle factors, including diet, which strongly influences both cancer incidence and related mortality. Galectin-3 (Gal-3) is a multifaceted protein involved in multiple pathophysiological pathways underlying chronic inflammation and cancer. Its versatility is given by the ability to participate in a wide range of tumor-promoting processes, including cell–cell/cell–matrix interactions, cell growth regulation and apoptosis, and the immunosuppressive tumor microenvironment. This review provides an updated summary of preclinical and observational human studies investigating the pathogenetic role of Gal-3 in intestinal inflammation and CRC, as well as the potential of Gal-3 activity inhibition by plant-source food-derived bioactive compounds to control CRC onset/growth. These studies highlight both direct and immuno-mediated effects of Gal-3 on tumor growth and invasiveness and its potential role as a CRC prognostic biomarker. Substantial evidence indicates natural food-derived Gal-3 inhibitors as promising candidates for CRC prevention and therapy. However, critical issues, such as their bioavailability and efficacy, in controlled human studies need to be addressed to translate research progress into clinical applications.
A Novel Method for Primary Blood Cell Culturing and Selection in Drosophila melanogaster
Authors: Kúthy-Sutus Enikő , Kharrat Bayan , Gábor Erika , Csordás Gábor , Sinka Rita , Honti Viktor
Published: December 2022

The blood cells of the fruit fly Drosophila melanogaster show many similarities to their vertebrate counterparts, both in their functions and their differentiation. In the past decades, a wide palette of immunological and transgenic tools and methods have been developed to study hematopoiesis in the Drosophila larva. However, the in vivo observation of blood cells is technically restricted by the limited transparency of the body and the difficulty in keeping the organism alive during imaging. Here we describe an improved ex vivo culturing method that allows effective visualization and selection of live blood cells in primary cultures derived from Drosophila larvae. Our results show that cultured hemocytes accurately represent morphological and functional changes following immune challenges and in case of genetic alterations. Since cell culturing has hugely contributed to the understanding of the physiological properties of vertebrate blood cells, this method provides a versatile tool for studying Drosophila hemocyte differentiation and functions ex vivo.
Ethylene: A Master Regulator of Plant–Microbe Interactions under Abiotic Stresses
Authors: Shekhawat Kirti , Fröhlich Katja , García-Ramírez Gabriel X. , Trapp Marilia A. , Hirt Heribert
Published: December 2022

The plant phytohormone ethylene regulates numerous physiological processes and contributes to plant–microbe interactions. Plants induce ethylene production to ward off pathogens after recognition of conserved microbe-associated molecular patterns (MAMPs). However, plant immune responses against pathogens are essentially not different from those triggered by neutral and beneficial microbes. Recent studies indicate that ethylene is an important factor for beneficial plant–microbial association under abiotic stress such as salt and heat stress. The association of beneficial microbes with plants under abiotic stresses modulates ethylene levels which control the expression of ethylene-responsive genes (ERF), and ERFs further regulate the plant transcriptome, epi-transcriptome, Na+/K+ homeostasis and antioxidant defense mechanisms against reactive oxygen species (ROS). Understanding ethylene-dependent plant–microbe interactions is crucial for the development of new strategies aimed at enhancing plant tolerance to harsh environmental conditions. In this review, we underline the importance of ethylene in beneficial plant–microbe interaction under abiotic stresses.
Mesenchymal Stromal Cells-Derived Extracellular Vesicles Regulate Dendritic Cell Functions in Dry Eye Disease
Authors: Guo Rongjie , Liang Qi , He Yun , Wang Chenchen , Jiang Jiaxuan , Chen Taige , Zhang Di , Hu Kai
Published: December 2022

We explored the therapeutic efficacy of Mesenchymal stromal cells-derived extracellular vesicles (MSC-EVs) and its inhibition of the functions of dendritic cells (DCs) in dry eye disease (DED). MSC-EVs were isolated from the culture supernatants of mesenchymal stromal cells (MSCs) and characterized. In vitro, human corneal epithelial cells (HCECs) were cultured in hyperosmotic medium to simulate the DED hyperosmotic environment and treated with MSC-EVs. Cell viability was assessed, and the expression of inflammatory cytokines was quantified. Next, we induced DED in female C57BL/6 mice and divided the mice into groups treated with either MSC-EVs or phosphate buffer solution (PBS) eye drops. Disease severity was assessed; mRNA expression of inflammatory cytokines was analyzed by RT-PCR; and Th17 cells were detected by flow cytometry. Lastly, we evaluated DCs by immunofluorescence and flow cytometric analysis to assess its amounts and maturation. MSC-EVs showed protective effects on HCECs under hyperosmotic stress in vitro, suppressing the expression of inflammatory cytokines. In vivo, mice topically treated with MSC-Evs presented reduced DED disease severity compared to PBS-treated mice. MSC-Evs downregulated the expression of inflammatory cytokines, including TNF-α, IL-6, and IL-1β, as well as the frequency of Th17 cells. Further investigation showed that MSC-EVs suppressed the increase of amounts and the maturation of DCs in DED. Changes of morphological characters of DCs were also inhibited by MSC-EVs. Our study revealed that MSC-EVs suppressed ocular surface inflammation by inhibiting DCs activation-mediated Th17 immune responses, explicating the therapeutic potential of MSC-EVs in DED and other ocular surface diseases.
The Ti0.2V1.8C MXene Ink-Prepared Chemiresistor: From Theory to Tests with Humidity versus VOCs
Authors: Simonenko Nikolay P. , Glukhova Olga E. , Plugin Ilya A. , Kolosov Dmitry A. , Nagornov Ilya A. , Simonenko Tatiana L. , Varezhnikov Alexey S. , Simonenko Elizaveta P. , Sysoev Victor V. , Kuznetsov Nikolay T.
Published: December 2022

The 2D structure of MXenes attracts wide research attention toward an application of these materials in gas sensors. These structures are extremely sensitive to minor variations in their composition, which are employed for tuning their functional properties. Here, we consider the partially substituted MXenes of the composition of TixV2-xC, where x = 0.2, via quantum chemical calculations, and test their chemiresistive characteristics as a receptor component of the planar-type sensor and on-chip multisensor array. We thoroughly discuss the synthesis process of Ti0.2V1.8AlC MAX-phase and the corresponding MXenes, to prepare functional inks and, furthermore, deposit the films by microextrusion printing over an array of planar multi-electrode structures at the surface of a pen-sized chip. The crystal structure of the obtained materials is evaluated via X-ray diffraction analysis. The developed chip has been exposed upon few gaseous analytes, of alcohol VOCs, NH3, and H2O, of a 500–16,000 ppm concentration, at room temperature to ensure that we could observe the positive chemiresistive effect matured from resistance enhancing, with up to 10% vs. water vapors. The calculations carried in the framework of the density-functional theory for V2C, Ti2C, and Ti0.2V1.8C crystals ensured that the variations in their electronic structure were almost consistent with the experiment fundings: the most prominent effect is observed in relation to the H2O vapors. Therefore, these Ti0.2V1.8C structures could be considered for applying them in room temperature-operated hygrometers.
Andy Warhol and His Amazing Technicolor Shoes: Characterizing the Synthetic Dyes Found in Dr. Ph. Martin’s Synchromatic Transparent Watercolors and Used in À la Recherche du Shoe Perdu
Authors: Haddad Abed , Nakie-Miller Toni , Jenks Josephine Brilliant , Kowach Glen
Published: December 2022

Synthetic organic dyes were extensively used by artists in the first half of the 20th century, knowingly or otherwise. This included Andy Warhol and his À la Recherche du Shoe Perdu (c. 1955), a major portfolio of hand-colored prints, a copy of which resides in the collection of The Museum of Modern Art (MoMA). Warhol and his friends were known to use Dr. Ph. Martin’s Synchromatic Transparent Water Colors to bring these prints to life. A historical set of Synchromatic Transparent Watercolors were initially investigated by UV-visible spectroscopy, and samples from the historic set were also characterized by µ-Fourier transform infrared spectroscopy for fingerprint identification. To better elucidate the nature of the mixtures present, thin-layer chromatography was coupled with surface-enhanced Raman spectroscopy to separate the components of all colorants in the set. The dyes decisively identified include Acid Red 73, Acid Red 87, Acid Red 17, Acid Red 103, Basic Red 1, Acid Orange 7, Acid Yellow 23, Acid Green 1, Basic Green 4, Acid Blue 3, Acid Blue 93, Basic Violet 3, Basic Violet 10, Basic Violet 17, and Acid Black 2. Overall, Acid Blue 3, along with Acid Orange 7 and Acid Black 2, were found in the greatest number of dyes in the Dr. Ph. Martin’s set. Data from the historic set was subsequently used for direct comparison with reflectance spectra from the Warhol portfolio using principal component analysis. Microfade testing on a Synchromatic Transparent Watercolors brochure was also conducted to identify fugitive colorants, the results of which were extrapolated to each of the prints in the Warhol portfolio. The analysis provided further insight into the dyes used in À la Recherche du Shoe Perdu and confirmed the extreme light sensitivity of some colorants and the fastness of others.
Ex Situ Conservation of Atriplex taltalensis I.M. Johnst. via In Vitro Culturing of Its Axillary Shoots
Authors: Muñoz-Alcayaga Carolina , Soto Jorge , Román-Figueroa Celián , Paneque Manuel
Published: December 2022

Atriplex taltalensis is an endangered shrub endemic to northern Chile. Sparse populations of this species can be found in areas with extreme edaphoclimatic conditions in the Atacama desert, and its seeds have a poor germination rate. Consequently, mass-cultivating it can be challenging. In this study, the vegetative propagation mechanisms of A. taltalensis were evaluated using an in vitro culture to aid in their conservation. A. taltalensis shoot explants were treated with two phytoregulators, indole-3-butyric acid (IBA) and 6-benzylaminopurine (BAP), to assess the morphogenic responses and their effects on the propagation of the species, based on shoot multiplication, elongation, and rooting, through subculturing. During multiplication, the treatment with IBA alone efficiently promoted explant elongation, lateral root formation, and axillary shoot proliferation, allowing for the rapid development of shoots into whole plants. Alternatively, treatment with IBA and BAP in combination stimulated the proliferation of basal shoots with little elongation and rooting and promoted shoot hyperhydricity at 0.25–1 mg L−1 BAP concentrations. Thus, we conclude that A. taltalensis propagation is viable through in vitro plant tissue culture using a rapid axillary shoot multiplication system, and this method could aid in the conservation of this species through in vitro propagation and rescue programs.
Life Science—Microbial Culture Collections Data Integration Tasks
Authors: Vasilenko Alexander , Kochkina Galina , Ivanushkina Natalya , Ozerskaya Svetlana
Published: December 2022

This paper presents interconnections between catalogs of microbial culture collections and biological databases inspected. Microbial Biological Resources Centers (mBRCs) provide Life Science (LS) and biotechnology with fit-for-use microbiological resources and related data of consistent quality. To optimize the services, facilitate cumulative research, make crosschecks, and avoid duplication of efforts, must ensure that the databases developed and maintained are interconnected with mBRC data. This research shows that, at present, connections are minimal. It proposes ways to plug the mBRC databases into the Life Science community. Such connections could open dialogue by making the mBRC data visible and accessible from the Life Science databases, and reciprocally making the Life Science database records visible and accessible from the mBRC-aggregated catalog. For this purpose, we inspected most of the databases discovered on the Internet. Each database was characterized by name, acronym, year of the last correction, uniform resource location (URL), area of practical use (health system, agriculture, etc.), presence of microbial data and database producer. The databases with microbial data were inspected in more detail in terms of the lists of the partner databases, the lists of ontologies used, the access format from computer programs, and database subjects. Our new metabase has collected 2667 Life Science databases, from which 1123 databases have microbial data.
Assessment of Parotid Gland Tumors by Means of Quantitative Multiparametric Ultrasound (mpUS)
Authors: Wakonig Katharina Margherita , Lerchbaumer Markus Herbert , Dommerich Steffen , Olze Heidi , Hamm Bernd , Fischer Thomas , Arens Philipp
Published: December 2022

Objective: The preoperative diagnostical differentiation of parotid gland tumor (PGT) is not always simple due to several different entities. B-mode-ultrasound (US) remains the imaging modality of choice, while histopathology serves as the gold standard for finalizing the diagnosis. We aimed to evaluate the use of multiparametric US (mpUS) in the assessment of PGT. Methods: We included 97 PGTs from 96 patients. A standardized mpUS protocol using B-mode-US, shear-wave elastography (SWE), and standardized contrast-enhanced ultrasound (CEUS) was performed prior to surgical intervention. SWE was assessed by real-time measurement conducting a minimum of five measurements, while quantitative CEUS parameters were assessed with a post-processing perfusion software. Results: SWE allowed differentiation between benign PGT (Warthin’s Tumor (WT) paired with lymph nodes (LN) and pleomorphic adenoma (PA)), and WT and LN were softer compared to PA. WT showed lower velocities than squamous cell carcinoma (SCC): the most common malignant PGT. CEUS parameters showed significant group differences between WT and PA, WT and malignant lesions, WT and SCC, WT paired with LN versus PA, and WT paired with LN versus SCC. Conclusion: MpUS seems to be beneficial in the assessment of PGT characterization, with benign PGT appearing to be softer in SWE than tumors with malignant tendencies. The quantitative CEUS parameter shows higher perfusion in WT than in PA, and malignant PGTs are less vascularized than WTs.
Postoperative Survival and Clinical Outcomes for Uterine Leiomyosarcoma Spinal Bone Metastasis: A Case Series and Systematic Literature Review
Authors: Contartese Deyanira , Bandiera Stefano , Giavaresi Gianluca , Borsari Veronica , Griffoni Cristiana , Gasbarrini Alessandro , Fini Milena , Salamanna Francesca
Published: December 2022

Spinal bone metastases from uterine leiomyosarcoma (LMS) are relatively uncommon and few data are present in the literature. In this study, cases of nine consecutive patients who underwent spinal surgery for metastatic uterine LMS between 2012 and 2022 at a single institution were retrospectively reviewed. The recorded demographic, operative, and postoperative factors were reviewed, and the functional outcomes were determined by changes in Frankel grade classification during follow-up. A systematic review of the literature was also performed to evaluate operative and postoperative factors and outcomes for patients with the same gynecological metastases to the spine. For our cases, the mean time between primary tumors to bone metastases diagnosis was 5.2 years, and the thoracic vertebrae were the most affected segment. Overall, median survival after diagnosis of metastatic spine lesions was 46 months. For the systematic review, the mean time between primary tumors to bone metastases was 4.9 years, with the lumbar spine as the most involved site of metastasis. Overall, median survival after diagnosis was 102 months. Once a spinal bone lesion from LMS is identified, surgical treatment can be beneficial and successful in alleviating symptoms. Further efforts will be crucial to identify prognostic markers as well as therapeutic targets to improve survival in these patients.
Determination of Anti-Phospholipase A2 and Anti-Thrombospondin Type 1 Domain-Containing Protein 7A in Latin Patients with Membranous Nephropathy
Authors: Battaini Ligia C. , Ranzani Otavio T. , Marçal Lia J. , Antonangelo Leila , Jorge Lecticia B. , Bitencourt Cristiane D. , Woronik Victoria , Malheiros Denise M. A. , Yu Luis
Published: December 2022

Primary membranous nephropathy (MN) is caused by antibodies against podocyte antigens, especially the type M receptor of phospholipase A2 (PLA2R) and thrombospondin type-1 domain containing 7 A (THSD7A). This study’s aim was the determination of anti-PLA2R, anti-THSD7A serum antibodies, and anti-PLA2R renal tissue staining prevalence in a Latin population with MN, as well as evaluating their role as biomarkers for disease activity. The performance of the two anti-PLA2R serum diagnostic methods—ELISA and indirect immunofluorescence (IFI)—was evaluated for the diagnosis of MN. Fifty-nine patients, including 29 with MN, 18 with lupus membranous nephropathy (LMN) and 12 with focal and segmental glomerulosclerosis (FSGS), were evaluated for serum antibodies. Renal biopsies were also evaluated for the presence of anti-PLA2R staining. Twenty-one patients with MN were followed for 1 year. Patients with LMN and FSGS were negative for both antibodies. All 29 MN patients were negative for anti-THSD7A; 16 MN patients were positive for anti-PLA2R by ELISA and/or IFI, and 3 MN patients were positive for anti-PLA2R only by IFI. Thus, the anti-PLA2R ELISA test demonstrated 45% sensitivity and 97% specificity, while the IFI test showed, respectively, 55% and 100% in our MN patients. Among the 28 MN renal biopsies, 20 presented anti-PLA2R positive staining, corresponding to a 72% sensitivity. Positive correlations were observed between the anti-PLA2R ELISA titer and proteinuria. In conclusion, determination of anti-PLA2R antibodies in the MN Latin population showed similar rates to those reported for other populations. The anti-PLA2R serum levels correlated with MN disease activity.
The Effectiveness of a Very Low-Volume Compared to High-Volume Laxative in Colon Capsule Endoscopy
Authors: Schelde-Olesen Benedicte , Nemeth Artur , Johansson Gabriele Wurm , Deding Ulrik , Bjørsum-Meyer Thomas , Thorlacius Henrik , Baatrup Gunnar , Koulaouzidis Anastasios , Toth Ervin
Published: December 2022

Colon capsule endoscopy (CCE) is a promising modality for colonic investigations, but completion rates (CR) and adequate cleansing rates (ACR) must be improved to meet established standards for optical colonoscopy. Improvements should be made with patient acceptability in mind. We aimed to compare a very low-volume polyethylene glycol (PEG) laxative to a conventional high-volume laxative. We carried out a single-center retrospective comparative cohort study including patients referred for CCE. One hundred and sixty-six patients were included in the final analysis, with eighty-three patients in each group. We found a CR and ACR of 77% and 67% in the high-volume group and 72% and 75% in the very low-volume group, respectively. In the high-volume group, 54% had complete transit and adequate cleansing, whereas this was the case for 63% in the very low-volume group. No statistically significant difference in CR, ACR, or a combination of the two was found. A very low-volume bowel preparation regimen was non-inferior to a high-volume regimen before CCE in terms of CR and ACR.
Brain Stroke Classification via Machine Learning Algorithms Trained with a Linearized Scattering Operator
Authors: Mariano Valeria , Tobon Vasquez Jorge A. , Casu Mario R. , Vipiana Francesca
Published: December 2022

This paper proposes an efficient and fast method to create large datasets for machine learning algorithms applied to brain stroke classification via microwave imaging systems. The proposed method is based on the distorted Born approximation and linearization of the scattering operator, in order to minimize the time to generate the large datasets needed to train the machine learning algorithms. The method is then applied to a microwave imaging system, which consists of twenty-four antennas conformal to the upper part of the head, realized with a 3D anthropomorphic multi-tissue model. Each antenna acts as a transmitter and receiver, and the working frequency is 1 GHz. The data are elaborated with three machine learning algorithms: support vector machine, multilayer perceptron, and k-nearest neighbours, comparing their performance. All classifiers can identify the presence or absence of the stroke, the kind of stroke (haemorrhagic or ischemic), and its position within the brain. The trained algorithms were tested with datasets generated via full-wave simulations of the overall system, considering also slightly modified antennas and limiting the data acquisition to amplitude only. The obtained results are promising for a possible real-time brain stroke classification.
Reply to Martetschläger, F.; Wahal, N. Comment on “Feuerriegel et al. Assessment of Acute Lesions of the Biceps Pulley in Patients with Traumatic Shoulder Dislocation Using MR Imaging. Diagnostics 2022, 12, 2345”
Authors: Feuerriegel Georg C. , Neumann Jan , Wurm Markus
Published: December 2022

We would like to thank you for your kind letter and thoughtful comments [...]
Behavior of 3D Printed Stretchable Structured Sensors
Authors: Kim Eugene , Khaleghian Seyedmeysam , Emami Anahita
Published: December 2022

Piezoresistive structures inspired by serpentines, auxetic, and kirigami arrangements have demonstrated good flexibility and sensitivity under tension. Piezoresistive structures display optimal performance when the characteristics entail reliable stretchability and repeatability. These structures can be implemented as wearable sensors by compressing and elongating the conductive nanocomposites to vary the flow of electrons and to provide resistance change. To guarantee the reliability of these structures for strain sensing, it is important that the resistance change in these structures remains constant under repeated loads. In this study, the performance of different piezoresistive structures under cyclic tensile load is investigated and compared. Based on the performance of different types of structures, novel hybrid structures have been also proposed to design for both high stretchability and sensitivity of piezoresistive sensors. All the structures were tested with position limits rather than a fixed force to avoid permanent deformation. First, small position limits were used to determine Young’s Modulus, then a 10-cycle tensile test with larger position limits was used to further study the electromechanical behavior of different piezoresistive structures under larger deformation and repetition. Finally, the gage factor was derived for all the studied structures, and they were re-categorized based on properties’ similarities.
Optical Solitons for a Concatenation Model by Trial Equation Approach
Authors: Wang Ming-Yue , Biswas Anjan , Yıldırım Yakup , Moraru Luminita , Moldovanu Simona , Alshehri Hashim M.
Published: December 2022

This paper addresses the newly proposed concatenation model by the usage of trial equation approach. The concatenation is a chain model that is a combination of the nonlinear Schrodinger’s equation, Lakshmanan–Porsezian–Daniel model as well as the Sasa–Satsuma equation. The recovered solutions are displayed in terms of dark solitons, singular solitons, cnoidal waves and singular periodic waves. The trial equation approach enables to recover a wide spectrum of solutions to the governing model. The numerical schemes give a visual perspective to the solutions derived analytically.
Remote Big Data Management Tools, Sensing and Computing Technologies, and Visual Perception and Environment Mapping Algorithms in the Internet of Robotic Things
Authors: Andronie Mihai , Lăzăroiu George , Karabolevski Oana Ludmila , Ștefănescu Roxana , Hurloiu Iulian , Dijmărescu Adrian , Dijmărescu Irina
Published: December 2022

The purpose of our systematic review was to inspect the recently published research on Internet of Robotic Things (IoRT) and harmonize the assimilations it articulates on remote big data management tools, sensing and computing technologies, and visual perception and environment mapping algorithms. The research problems were whether robotic manufacturing processes and industrial wireless sensor networks shape IoRT and lead to improved product quality by use of remote big data management tools, whether IoRT devices communicate autonomously regarding event modeling and forecasting by leveraging machine learning and clustering algorithms, sensing and computing technologies, and image processing tools, and whether smart connected objects, situational awareness algorithms, and edge computing technologies configure IoRT systems and cloud robotics in relation to distributed task coordination through visual perception and environment mapping algorithms. A Shiny app was harnessed for Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines to configure the flow diagram integrating evidence-based gathered and processed data (the search outcomes and screening procedures). A quantitative literature review of ProQuest, Scopus, and the Web of Science databases was carried out throughout June and October 2022, with search terms including “Internet of Robotic Things” + “remote big data management tools”, “sensing and computing technologies”, and “visual perception and environment mapping algorithms”. Artificial intelligence and intelligent workflows by use of AMSTAR (Assessing the Methodological Quality of Systematic Reviews), Dedoose, DistillerSR, and SRDR (Systematic Review Data Repository) have been deployed as data extraction tools for literature collection, screening, and evaluation, for document flow monitoring, for inspecting qualitative and mixed methods research, and for establishing robust outcomes and correlations. For bibliometric mapping by use of data visualization, Dimensions AI was leveraged and with regards to layout algorithms, VOSviewer was harnessed.
High-Accuracy Gaussian Function Generator for Neural Networks
Authors: Popa Cosmin Radu
Published: December 2022

A new improved accuracy CMOS Gaussian function generator will be presented. The original sixth-order approximation function that represents the basis for designing the proposed Gaussian circuit allows a large increase in the circuit accuracy and also of the input variable maximal range. The original proposed computational structure has a large dynamic output range of 27 dB, for a variation smaller than 1 dB as compared with the ideal Gaussian function. The circuit is simulated for 0.18 μm CMOS technology and has a low supply voltage (VDD = 0.7 V). Its power consumption is smaller than 0.22 μW, for VDD = 0.7 V, while the chip area is about 7 μm2. The new proposed architecture is re-configurable, the convenient modification of the coefficients allowing to obtain many mathematical functions using the same computational structure.
ISSA-ELM: A Network Security Situation Prediction Model
Authors: Sun Hongzhe , Wang Jian , Chen Chen , Li Zhi , Li Jinjin
Published: December 2022

To resolve the problems of low prediction accuracy and slow convergence speed of traditional extreme learning machines in network security situation prediction methods, we combine a meta-heuristic search algorithm with neural networks and propose a prediction method based on the improved sparrow search algorithm optimization of an extreme learning machine. Firstly, the initial population is initialized by cat-mapping chaotic sequences to enhance the randomness and ergodicity of the initial population and improve the global search ability of the algorithm. Secondly, the Cauchy mutation and tent chaos disturbance are introduced to expand the local search ability, so that the individuals caught in the local extremum can jump out of the limit and continue the search. Finally, the explorer-follower number adaptive adjustment strategy is proposed to enhance the global search ability in the early stage and the local depth mining ability in the later stage of the algorithm by using the change of the explorer and follower numbers in each stage to improve the optimization-seeking accuracy of the algorithm. The improvement not only guarantees the diversity of the population, but also makes up for the defect that the sparrow search algorithm is easily trapped in the local optima in later iterations, and greatly improves the accuracy of the network security situation prediction.
Few-Shot Learning Based on Double Pooling Squeeze and Excitation Attention
Authors: Xu Qiuyu , Su Jie , Wang Ying , Zhang Jing , Zhong Yixin
Published: December 2022

Training a generalized reliable model is a great challenge since sufficiently labeled data are unavailable in some open application scenarios. Few-shot learning (FSL) aims to learn new problems with only a few examples that can tackle this problem and attract extensive attention. This paper proposes a novel few-shot learning method based on double pooling squeeze and excitation attention (dSE) for the purpose of improving the discriminative ability of the model by proposing a novel feature expression. Specifically, the proposed dSE module adopts two types of pooling to emphasize features responding to foreground object channels. We employed both the pixel descriptor and channel descriptor to capture locally identifiable channel features and pixel features of an image (as opposed to traditional few-shot learning methods). Additionally, in order to improve the robustness of the model, we designed a new loss function. To verify the performance of the method, a large number of experiments were performed on multiple standard few-shot image benchmark datasets, showing that our framework can outperform several existing approaches. Moreover, we performed extensive experiments on three more challenging fine-grained few-shot datasets, the experimental results demonstrate that the proposed method achieves state-of-the-art performances. In particular, this work achieves 92.36% accuracy under the 5-way–5-shot classification setting of the Stanford Cars dataset.
Design and Verification of Petri-Net-Based Cyber-Physical Systems Oriented toward Implementation in Field-Programmable Gate Arrays—A Case Study Example
Authors: Wiśniewski Remigiusz , Wojnakowski Marcin , Li Zhiwu
Published: December 2022

This paper presents a novel design approach of a Petri-net-based cyber-physical system (CPS). The idea is oriented toward implementation in a field-programmable gate array (FPGA). The proposed technique permits error detection in the system at the early specification stage in order to reduce the time and prototyping cost of the CPS. Due to the state explosion problem, the traditional verification methods have exponential computational complexity. In contrast, we show that under certain assumptions, the proposed algorithm is able to detect possible errors in the system even in cubic O(|T|2|P|) time. Furthermore, all the required steps of the proposed design method are presented and discussed. The idea is illustrated by a real-life case study example of a traffic light crossroad. The system was modelled, analysed, implemented, and finally validated within the FPGA device (Virtex-5 family).
Fiscal Policy, Growth, Financial Development and Renewable Energy in Romania: An Autoregressive Distributed Lag Model with Evidence for Growth Hypothesis
Authors: Doran Marius Dalian , Poenaru Maria Magdalena , Zaharia Alexandra Lucia , Vătavu Sorana , Lobonț Oana Ramona
Published: December 2022

This research aims to identify the influence of fiscal policy, financial development and economic growth on the increase of renewable consumption in Romania. To achieve our objective, we employ bivariate regressions through the Autoregressive Distributed Lag method, over the 2000–2020 period, to examine these influences. We find clear evidence that the variables observed (implicit tax rate on energy, external debt stocks, real GDP per capita, environmental tax revenues from energy taxes, and market capitalisation of listed domestic companies) have significant effects on the use of renewable energy. Four unidirectional causal relationships were identified in the long run: two from independent variables towards the dependent variable and two from the dependent variables towards two other independent variables. The importance of this study is that its results can contribute to the finding of the most suitable solutions to improve renewable energy consumption in Romania and mitigate the impact of climate change. Consequently, the results of this study reveal significant conclusions and policy recommendations for Romania moving towards sustainable and green economic growth, through a balanced set of policies and measures smartly applied, accompanied by a solid rate of absorption of green funds.
Control of Cascaded Multilevel Converter for Wave Energy Applications
Authors: Zapata Henry M. , Perez Marcelo A. , Marquez Alcaide Abraham
Published: December 2022

This paper proposes a control scheme for a wave energy conversion system based on a linear generator and a cascaded multilevel converter. The mechanical conversion system is composed of a buoy connected directly to a linear generator. The windings of the generator are individually controlled by a cascaded multilevel power converter using independent maximum power point tracking to improve energy harvesting. The output of the cascaded converter is controlled to keep the DC capacitors balanced and generate a multilevel voltage at the output terminals which reduces the losses in the underwater transmission line. Experimental results show the performance of the proposed control scheme maximizing the power generation by imposing a current with the same waveform of the induced voltage and balancing the DC capacitors.
Reactive Power Control of a Converter in a Hardware-Based Environment Using Deep Reinforcement Learning
Authors: Bokker Ode , Schlachter Henning , Beutel Vanessa , Geißendörfer Stefan , von Maydell Karsten
Published: December 2022

Due to the increasing penetration of the power grid with renewable, distributed energy resources, new strategies for voltage stabilization in low voltage distribution grids must be developed. One approach to autonomous voltage control is to apply reinforcement learning (RL) for reactive power injection by converters. In this work, to implement a secure test environment including real hardware influences for such intelligent algorithms, a power hardware-in-the-loop (PHIL) approach is used to combine a virtually simulated grid with real hardware devices to emulate as realistic grid states as possible. The PHIL environment is validated through the identification of system limits and analysis of deviations to a software model of the test grid. Finally, an adaptive volt–var control algorithm using RL is implemented to control reactive power injection of a real converter within the test environment. Despite facing more difficult conditions in the hardware than in the software environment, the algorithm is successfully integrated to control the voltage at a grid connection point in a low voltage grid. Thus, the proposed study underlines the potential to use RL in the voltage stabilization of future power grids.
Large Scale Microalgae Biofuel Technology—Development Perspectives in Light of the Barriers and Limitations
Authors: Dębowski Marcin , Świca Izabela , Kazimierowicz Joanna , Zieliński Marcin
Published: December 2022

Microalgal biomass can be used to derive many different types of biofuels. In order to widely commercialize this technology, its limitations and weaknesses must be eliminated. Many technical and economic issues also need to be clarified and unknowns answered. Microalgae-based technologies have been shown to be versatile, efficient and suitable for practical and commercial use. However, the current technological readiness level (TRL) of most microalgae-based bioenergy production systems precludes their quick and widespread implementation. Their development is limited by a combination of factors that must be precisely identified, after which their negative impact on scale-up prospects can be eliminated or minimized. The present study identifies the main barriers to the development of industrial microalgae-production and microalgae-to-biofuel systems. In addition, it proposes measures and efforts necessary to achieve a higher TRL, which will provide investors with sought-after performance and cost-efficiency data for the given project. The main barriers to the development of microalgae cultivation and processing systems have been identified to include: the complex nature of the cultivation process with multiple variables involved; lack of sufficient data from pilot-scale and near-full-scale plants, which often precludes reliable life cycle assessment (LCA); and insufficient legal assistance, advisory assistance, subsidies and funding for innovative projects. Potential ways of improving performance and competitiveness of microalgae-based systems include: process optimization techniques, genetic engineering, yield improvement through advanced process control and monitoring, use of waste as feedstock and dedicated support programs. The presented summary of the current stage of microalgal biofuel production technology development indicates the directions for further research and implementation work, which are necessary for the final verification of the application potential of these solutions.
Research on Hydrogen Production by Water Electrolysis Using a Rotating Magnetic Field
Authors: Guo Hao , Kim Hyeon-Jung , Kim Sang-Young
Published: December 2022

In this paper, the effect of rotating magnetic fields on hydrogen generation from water electrolysis is analyzed, aiming to provide a research reference for hydrogen production and improving hydrogen production efficiency. The electrolytic environment is formed by alkaline solutions and special electrolytic cells. The two electrolytic cells are connected to each other in the form of several pipes. The ring magnets are used to surround the pipes and rotate the magnets so that the pipes move relative to the magnets within the ring magnetic field area. Experimentally, the electrolysis reaction of an alkaline solution was studied by using a rotating magnetic field, and the effect of magnetic field rotation speed on the electrolysis reaction was analyzed using detected voltage data. The experimental phenomenon showed that the faster the rotation speed of the rotating magnetic field, the faster the production speed of hydrogen gas.
Bibliometric Analysis of Global Trends around Hydrogen Production Based on the Scopus Database in the Period 2011–2021
Authors: Camargo Luis , Comas Daniel , Escorcia Yulineth Cardenas , Alviz-Meza Anibal , Carrillo Caballero Gaylord , Portnoy Ivan
Published: December 2022

Given the increase in population and energy demand worldwide, alternative methods have been adopted for the production of hydrogen as a clean energy source. This energy offers an alternative energy source due to its high energy content, and without emissions to the environment. In this bibliometric analysis of energy production using electrolysis and taking into account the different forms of energy production. In this analysis, it was possible to evaluate the research trends based on the literature in the Scopus database during the years 2011–2021. The results showed a growing interest in hydrogen production from electrolysis and other mechanisms, with China being the country with the highest number of publications and the United States TOP in citations. The trend shows that during the first four years of this study (2011–2014), the average number of publications was 74 articles per year, from 2015 to 2021 where the growth is an average of 209 articles, the journal that published the most on this topic is Applied Energy, followed by Energy, contributing with almost 33% in the research area. Lastly, the keyword analysis identified six important research points for future discussions, which we have termed clusters. The study concludes that new perspectives on clean hydrogen energy generation, environmental impacts, and social acceptance could contribute to the positive evolution of the hydrogen energy industry.