bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Fumarate and Nitroglycerin on In Vitro Rumen Fermentation, Methane and Hydrogen Production, and on Microbiota
Authors: Li Jichao , Zhao Shengwei , Meng Zhenxiang , Gao Yunlong , Miao Jing , Mao Shengyong , Jin Wei
Published: July 2023

This study aimed to investigate the effects of fumarate and nitroglycerin on rumen fermentation, methane and hydrogen production, and microbiota. In vitro rumen fermentation was used in this study with four treatment groups: control (CON), fumarate (FA), nitroglycerin (NG) and fumarate plus nitroglycerin (FN). Real-time PCR and 16S rRNA gene sequencing were used to analyze microbiota. The results showed that nitroglycerin completely inhibited methane production and that this resulted in hydrogen accumulation. Fumarate decreased the hydrogen accumulation and improved the rumen fermentation parameters. Fumarate increased the concentration of propionate and microbial crude protein, and decreased the ratio of acetate to propionate in FN. Fumarate, nitroglycerin and their combination did not affect the abundance of bacteria, protozoa and anaerobic fungi, but altered archaea. The PCoA showed that the bacterial (Anosim, R = 0.747, p = 0.001) and archaeal communities (Anosim, R = 0.410, p = 0.005) were different among the four treatments. Compared with CON, fumarate restored Bacteroidetes, Firmicutes, Spirochaetae, Actinobacteria, Unclassified Ruminococcaceae, Streptococcus, Treponema and Bifidobacterium in relative abundance in FN, but did not affect Succinivibrio, Ruminobacter and archaeal taxa. The results indicated that fumarate alleviated the depressed rumen fermentation caused by the inhibition of methanogenesis by nitroglycerin. This may potentially provide an alternative way to use these chemicals to mitigate methane emission in ruminants.
Molecular Anatomy of the Class I Ligase Ribozyme for Elucidation of the Activity-Generating Unit
Authors: Kasuga Miho , Mutsuro-Aoki Hiromi , Ando Tadashi , Tamura Koji
Published: July 2023

The class I ligase ribozyme consists of 121 nucleotides and shows a high catalytic rate comparable to that found in natural proteinaceous polymerases. In this study, we aimed to identify the smaller active unit of the class I ligase ribozyme comprising ~50 nucleotides, comparable to the estimated length of prebiotically synthesized RNA. Based on the three-dimensional structure of the class I ligase ribozyme, mutants were prepared and their ligation activities were analyzed. Sufficient ligation activity was maintained even when shortening to 94 nucleotides. However, because it would be difficult to approach the target of ~50 nucleotides by removing only the partial structure, the class I ligase ribozyme was then split into two molecules. The ligation activity was maintained even when splitting into two molecules of 55 and 39 nucleotides. Using a system with similar split ribozymes, we analyzed the ligation activity of mutants C30, C47, and A71, which have been previously identified as the positions that contribute to catalytic activity, and discussed the structural basis of the activity of these bases. Our findings suggest the rationale for the class I ligase ribozyme’s assembling from multiple fragments that would be achievable with prebiotic synthesis.
Identification of Molecular Targets and Anti-Cancer Agents in GBM: New Perspectives for Cancer Therapy
Authors: D’Amico Agata Grazia , Caruso Bavisotto Celeste , Virtuoso Assunta
Published: July 2023

The authors of the present literature piece were invited to participate in the present Special Issue at the beginning of 2022, and we were all very enthusiastic at the prospect of assembling a series of articles on new molecular targets and anti-cancer agents in glioblastoma multiforme (GBM) [...]
Correction: Wadsley, M.; Ihssen, N. A Systematic Review of Structural and Functional MRI Studies Investigating Social Networking Site Use. Brain Sci. 2023, 13, 787
Authors: Wadsley Michael , Ihssen Niklas
Published: July 2023

During the final proofreading step of this paper [...]
Psychosocial Factors of Subjective Well-Being in Women with Eating Disorders
Authors: Matkovic Helena , Brajkovic Lovorka , Kopilaš Vanja
Published: July 2023

Eating disorders are known as the most lethal mental health conditions, and lately there has been a significant increase in the prevalence of these disorders. The aim of this research was to determine the perceived quality of professional support, the relationship between subjective well-being, loneliness, resilience, and the quality of family functioning, and the possibility of predicting subjective well-being based on knowledge of psychosocial factors in people with eating disorders. Eighty-six women with a diagnosed eating disorder participated in the online survey. The Diener Subjective Well-Being Scale, the UCLA Loneliness Scale, the Brief Resilience Scale, and the Self-Report Family Inventory were used to measure the constructs. Questions were constructed to collect information about the perceived quality and availability of professional support. Results showed lower levels of life satisfaction and flourishing and more frequent negative experiences. Reports of medium levels of loneliness, lower levels of flourishing, and lower perceived quality of family functioning were also obtained. Significant predictors of subjective well-being were loneliness and resilience, while family cohesion was significant in predicting positive and negative experiences and flourishing. These findings can contribute to the recognition of aspects existent prior to the development of the disorder, based on which experts can determine what to focus on in the treatment process.
Study on Temperature Distribution along the Ultra-Long Underwater Tunnel: Based on the Long-Term Measured Results of the Shanghai Yangtze River Tunnel
Authors: Gao Jun , Guo Weichen , Ma Mingyao , Hou Yumei , Zhang Ruiyan , Zeng Lingjie , Zhang Chengquan , Xu Yukun , Wei Xiaobin , Cao Changsheng
Published: July 2023

Tunnels play a vital role in enhancing traffic flow and supporting public transportation systems. However, the discharge of polluted air and waste heat from vehicles passing through tunnels significantly raises the temperature inside, presenting challenges in terms of occupant comfort, tunnel safety, and infrastructure integrity. Therefore, ensuring proper temperature control is essential for their efficient operation. This study aims to investigate the phenomenon of temperature rise in ultra-long tunnels during normal operations, as limited research has been conducted in this area. The Shanghai Yangtze River Tunnel serves as a case study, utilizing temperature and air velocity data collected throughout the year (2021) from the management company. The analysis reveals that the temperature distribution near the tunnel exit is influenced by outdoor temperature fluctuations and traffic volume. The highest temperatures occur on 25 August (39.74 °C) during peak traffic hours. On-site measurements of tunnel temperature, humidity, and air velocity during winter and summer seasons yield the following results. During winter, the air temperature and wall temperature inside the tunnel experience significant increases along its length. The air temperature rises by approximately 11 °C from the entrance to the exit, while the wall temperature increases by about 15 °C. In contrast, during summer, the air temperature only rises by 2.7 °C, and the wall temperature increases by around 3 °C. Consequently, the humidity decreases along the tunnel, and this decrease is correlated with the magnitude of temperature increase. Furthermore, measurements of air velocity indicate that natural and traffic-induced winds contribute to the overall airflow inside the tunnel. A temperature data logger installed in the tunnel recorded temperature changes during the period of pandemic lockdown and subsequent recovery, spanning the spring and summer seasons. During the lockdown period, there was a relatively small increase in temperature along the tunnel, suggesting that vehicle heat dissipation is the primary factor contributing to temperature rise inside. Additionally, a method is proposed to predict the cross-sectional temperature of the tunnel using measured air velocities.
Comparative Analysis of Photon Stereotactic Radiotherapy and Carbon-Ion Radiotherapy for Elderly Patients with Stage I Non-Small-Cell Lung Cancer: A Multicenter Retrospective Study
Authors: Aoki Shuri , Onishi Hiroshi , Karube Masataka , Yamamoto Naoyoshi , Yamashita Hideomi , Shioyama Yoshiyuki , Matsumoto Yasuo , Matsuo Yukinori , Miyakawa Akifumi , Matsushita Haruo , Ishikawa Hitoshi
Published: July 2023

The emergence of an aging society and technological advances have made radiotherapy, especially stereotactic body radiotherapy (SBRT), a common alternative to surgery for elderly patients with early stage non-small-cell lung cancer (NSCLC). Carbon-ion radiotherapy (CIRT) is also an attractive treatment option with potentially lower toxicity for elderly patients with comorbidities. We compared the clinical outcomes of the two modalities using Japanese multicenter data. SBRT (n = 420) and single-fraction CIRT (n = 70) data for patients with stage I NSCLC from 20 centers were retrospectively analyzed. Contiguous patients ≥ 80 years of age were enrolled, and overall survival (OS), disease-specific survival (DSS), local control (LC), and adverse event rates were compared. The median age was 83 years in both groups and the median follow-up periods were 28.5 and 42.7 months for SBRT and CIRT, respectively. The 3-year OS, DSS, and LC rates were 76.0% vs. 72.3% (p = 0.21), 87.5% vs. 81.6% (p = 0.46), and 79.2% vs. 78.2% (p = 0.87), respectively, for the SBRT vs. CIRT groups. Regarding toxicity, 2.9% of the SBRT group developed grade ≥ 3 radiation pneumonitis, whereas none of the CIRT group developed grade ≥ 2 radiation pneumonitis. SBRT and CIRT in elderly patients showed similar survival and LC rates, although CIRT was associated with less severe radiation pneumonitis.
Overview of Pancreatic Cancer Epidemiology in Europe and Recommendations for Screening in High-Risk Populations
Authors: Partyka Olga , Pajewska Monika , Kwaśniewska Daria , Czerw Aleksandra , Deptała Andrzej , Budzik Michał , Cipora Elżbieta , Gąska Izabela , Gazdowicz Lucyna , Mielnik Aneta , Sygit Katarzyna , Sygit Marian , Krzych-Fałta Edyta , Schneider-Matyka Daria , Grochans Szymon , Cybulska Anna M. , Drobnik Jarosław , Bandurska Ewa , Ciećko Weronika , Ratajczak Piotr , Kamecka Karolina , Marczak Michał , Kozłowski Remigiusz
Published: July 2023

Pancreatic cancer is the seventh most common cause of death in the group of oncological diseases. Due to the asymptomatic course, early diagnosis is difficult. Currently, early detection methods are only used in high-risk groups. A literature review based on the available results of observational studies on patients with pancreatic cancer and people from high-risk groups was used to summarize the knowledge on risk factors. The GLOBOCAN 2020 data were used to assess the epidemiological situation in Europe. A summary of screening recommendations was prepared based on the available documents from medical organizations and associations. Pancreatic cancer risk factors are divided into two main groups: non-modifiable factors, e.g., hereditary factors and age, which increase the risk of developing this disease, and modifiable factors—BMI, smoking, and alcohol consumption. Hereditary factors account for 10% of pancreatic cancer cases. The highly specialized methods of early detection, (MRI, CT, or EUS) are used for screening high-risk populations. Of all the imaging methods, EUS is considered the most sensitive for pancreatic cancer and allows an accurate assessment of the size of even small lesions (<30 mm) and the extent of tumour infiltration into blood vessels. The available studies vary on the level of sensitivity and specificity of these methods for the diagnosis of pancreatic cancer. EUS, MRI, and CT are also expensive procedures and in some patients can be invasive, which is one of the arguments against the introduction of population screening programs based on imaging methods. Therefore, it is important to look for viable solutions that would improve early detection. This is important from the point of view of healthcare systems in Europe, where almost 29% of all global pancreatic cancer cases are reported.
Development of a Smart Portable Hypoxic Chamber with Accurate Sensing, Control and Visualization of In Vitro Cell Culture for Replication of Cancer Microenvironment
Authors: Ramachandramoorthy Harish , Dang Tuan , Srinivasa Ankitha , Nguyen Kytai Truong , Nguyen Phuc
Published: July 2023

Clinical resistance towards treatment is a major concern in cancer therapy. This is due to in vitro studies lacking essential microenvironmental aspects. Tumor-hypoxia is an important pathophysiological phenomenon in numerous malignant tumors. Various studies have shown the importance of a hypoxic microenvironment (HME) in cancer drug resistance and its effects on cellular signaling and metabolism pathways. Most drugs fail in transition from a laboratory to clinical trials because of the variability in the testing microenvironment conditions. It is, thus, very crucial that research work needs to replicate these conditions in vitro to test the drugs and/or drug carriers for cancer therapy. Previous works have used a portable hypoxia chamber to reduce the cell microenvironment to hypoxic conditions. These techniques lack reliability and consistency due to a lack of control and visualization. In this research, we developed a smart portable hypoxia chamber that could accurately control the oxygen inside the portable chamber and have a global visualization. The proposed hypoxia chamber provided ease of use with the ranges of 1% to 20% oxygen with increments of 0.5%, as well as reproducibility and accuracy. The chamber displayed great precision on reaching the set oxygen limit and a high stability in maintaining that set level of oxygen compared to the uncontrolled setup for extended durations (24 h). For instance, at a 2% oxygen level, our automated system maintained this level over 1400 min, whereas the oxygen level fluctuated up to 4.5% in the conventional hypoxic chamber. We have also demonstrated the pitfalls of uncontrolled and non-visualized hypoxia chamber setup and the dire need for our system. The hypoxia-induced factor (HIF-1α) expression in cancer cell lines was tested and compared between the conventional hypoxia setup and our automated hypoxia chamber. We observed that there was a twofold increase in HIF-1α expression in the automated controlled chamber compared to the conventional device. The device also provided real-time sensing, visualization and control of the chamber conditions, which could aid in complex in vitro studies.
CO Oxidation Catalyzed by Au Dispersed on SBA-15 Modified with TiO2 Films Grown via Atomic Layer Deposition (ALD)
Authors: Qin Xiangdong , Ke Wang , Vazquez Yovanny , Lee Ilkeun , Zaera Francisco
Published: July 2023

It has been established that gold, when in nanoparticle (NP) form and in contact with reducible oxides, can promote oxidation reactions under mild conditions. Here, we report results from our exploration of the catalytic oxidation of carbon monoxide using catalysts where Au NPs were combined with thin titanium oxide films deposited on SBA-15 using atomic layer deposition (ALD). Both orders of deposition, with TiO2 added either before or after Au dispersion, were tested for two titania film thicknesses amounting to about half and full TiO2 monolayers. The resulting catalysts were characterized using various techniques, mainly electron microscopy and N2 adsorption–desorption isotherms, and the kinetics of the oxidation of CO with O2 were followed using infrared absorption spectroscopy. A synergy between the Au and TiO2 phases as it relates to the bonding and conversion of CO was identified, the tuning of which could be controlled by varying the synthetic parameters. The ALD of TiO2 films proved to be an effective way to maximize the Au-TiO2 interface sites, and with that help with the activation of molecular oxygen.
Using the Response Surface Methodology to Treat Tannery Wastewater with the Bicarbonate-Peroxide System
Authors: Urbina-Suarez Néstor A. , Salcedo-Pabón Cristian J. , López-Barrera German L. , García-Martínez Janet B. , Barajas-Solano Andrés F. , Machuca-Martínez Fiderman
Published: July 2023

A bicarbonate-peroxide (BAP) system was evaluated to improve the quality of industrial tannery wastewater using an I-optimal experimental design with four variables (temperature, initial pH, bicarbonate, and H2O2 concentration). The response variables were COD removal, ammonia nitrogen removal, and nitrate concentration. The most critical variables were optimized using a The process was carried out in 500 mL reactors, the operational volume of 250 mL, and the agitation was at 550 rpm. A new I-optimal reaction surface design at two levels (bicarbonate concentration 0.01–0.3 mol/L and H2O2 0.05–0.35 mol/L) was used to obtain the optimal data of the experimental design. Optimal conditions were validated by one-way ANOVA statistical analysis using Prism software. Temperatures above 50 °C promote the efficiency of the BAP system, and slightly acidic initial pHs allow stabilization of the system upon inclusion of bicarbonate and peroxide in the concentration of bicarbonate, which is critical for the reaction with peroxide and formation of reactive oxygen species. With the validated optimal data, removal percentages above 78% were achieved for nitrites, ammonia nitrogen, chromium, TSS, BOD, conductivity, chromium, and chlorides; for COD and TOC, removal percentages were above 45%, these results being equal and even higher than other AOPs implemented for this type of water.
Follistatin Is Associated with Bone Mineral Density in Lean Adolescent Girls with Increased Physical Activity
Authors: Jürimäe Jaak , Remmel Liina , Tamm Anna-Liisa , Purge Priit , Maasalu Katre , Tillmann Vallo
Published: July 2023

Follistatin is a member of the activin–follistatin–inhibin hormonal system and is proposed to affect bone metabolism. However, data regarding the effect of follistatin on bone are relatively scarce and contradictory in humans. The purpose of the current study was to investigate possible associations of serum follistatin concentration with bone mineral characteristics in lean and physically active adolescent girls. Bone mineral density, body composition, resting energy expenditure and different energy homeostasis hormones in serum including follistatin, leptin and insulin were investigated. Significant relationships (p < 0.05) between serum follistatin (1275.1 ± 263.1 pg/mL) and whole-body (WB) bone mineral content (r = 0.33), WB areal bone mineral density (aBMD) (r = 0.23) and lumbar spine (LS) aBMD (r = 0.29) values were observed. Serum follistatin remained associated with LS aBMD independent of body fat and lean masses (r = 0.21; p < 0.05). However, the follistatin concentration explained only 3% (R2 × 100; p = 0.049) of the total variance in LS aBMD values. In conclusion, serum follistatin concentrations were associated with bone mineral values in lean adolescent girls with increased physical activity. Follistatin was an independent predictor of lumbar spine areal bone mineral density, which predominantly consists of trabecular bone.
Geographic Variation in Preventable Hospitalizations among US Children with Autism
Authors: Zhang Wanqing , Johnson Khalilah R.
Published: July 2023

There is a limited amount of research on geographic differences in preventable hospitalizations for ambulatory care sensitive conditions (ACSCs) among children with autism. The purpose of this study was to examine US regional differences in potentially preventable hospital admissions for pediatric inpatients diagnosed with autism. Hospital discharge data for six pediatric preventable conditions were obtained from the 2016–2019 National Inpatient Sample (NIS) under the US Agency for Healthcare Research and Quality. Geographic differences in preventable hospitalizations for children with autism were examined by US census regions and divisions. Multiple logistic regression analyses were conducted to examine child and clinical characteristics associated with ACSCs hospitalization across four US regions; the dependent variable was the likelihood of ACSCs hospitalization. Additionally, this study further explored the variation in preventable hospitalization among racial and ethnic groups for each region or division. Of the 138,305 autistic inpatients aged 2–17 years, about 10% had a primary diagnosis related to ACSCs. The results showed that the highest proportion of preventable hospitalizations for autistic children occurred in the middle Atlantic division of the northeast region. Racial differences were observed across all US regions, particularly in the northeast and south regions. Black children with autism were more likely to be hospitalized for ACSCs compared to White children with autism in three of the four US regions. Our results highlight the significant racial disparities in potentially avoidable hospitalizations among US children with autism. Examining geographic and racial differences in potentially avoidable hospitalizations could inform policy and practice while gaining a better understanding of pediatric patients with autism and where their families access health services. The findings of this study may help policymakers to identify where intervention is needed to tackle health inequities in the accessibility to quality primary care in the US. Further studies with more detailed investigation are recommended to better understand the mechanisms underlying these disparities, and to formulate effective regional policy and clinical practices while considering the unique needs and challenges of underserved children with autism.
Generation of Site-Specific Accelerograms and Response Spectra Involving Sampling Information from Borehole Records
Authors: Hu Yiwei , Lam Nelson , Khatiwada Prashidha , Tsang Hing-Ho , Menegon Scott
Published: July 2023

This paper is aimed at serving the needs of structural engineering designers of an important structure (or a group of structures located on the same site) who is seeking guidance on how to obtain accelerograms and/or derive response spectra that accurately represent the site subsoil conditions as informed by the borelogs. The presented site-specific seismic action model may be used to replace the default seismic action model stipulated for the designated site class. Presented in this article is a procedure for generating soil surface motions in an earthquake, and their associated site-specific response spectra, taking into account details of the soil layers. Dynamic site response analyses are involved. The conditional mean spectrum methodology is employed for selecting and scaling accelerograms for obtaining input motion on bedrock. The selection depends on the natural period of both the site and the structure. Multiple borelogs taken from within the same site are analysed to identify the critical soil column models without having to conduct site response analysis on every borelog. The technique for simplifying the soil layers utilising the shear strain profile is introduced to further cut down on the time of analyses. The procedures described in this article have been written into a web-based program that is freely accessible to engineering practitioners.
Synthesis of CoFe2O4 through Wet Ferritization Method Using an Aqueous Extract of Eucalyptus Leaves
Authors: Gingasu Dana , Culita Daniela C. , Calderon Moreno Jose Maria , Marinescu Gabriela , Bartha Cristina , Oprea Ovidiu , Preda Silviu , Chifiriuc Mariana Carmen , Popa Marcela
Published: July 2023

This study explored a new green approach of the wet ferritization method to obtain magnetic cobalt ferrite (CoFe2O4) by using eucalyptus leaves aqueous extract as a reducing/chelating/capping agent. The spinel single cubic phases of prepared samples were proved by powder X-ray diffraction (XRD), Fourier-Transform Infrared (FTIR) and Raman spectroscopy. The average crystallite size is in the range between 3 and 20 nm. The presence of the functional groups coating the obtained material is confirmed from FTIR and thermal analysis. The scanning electron microscopy (SEM) analysis showed a morphology consisting of nanoparticle aggregates. Raman spectroscopy detects the characteristic bands of spinel-type CoFe2O4. Magnetic investigations reveal the formation of ferromagnetic compounds with cubic magnetic anisotropy and a blocking temperature around 140 K, specific for this type of material. The biosynthesized CoFe2O4 could be an attractive candidate for biomedical applications, exhibiting promising antimicrobial and antibiofilm activity, particularly against Gram-negative bacteria and fungal strains.
The Application of Tribological Tests to Study the Wear Behavior of Asphalt Cutter Teeth: An Experimental Investigation Using Baroid Tribometer
Authors: Dumitru Teodor , Petrescu Marius Gabriel , Tănase Maria , Laudacescu Eugen
Published: July 2023

In this paper, the authors present the results obtained within a complex experimental program that focuses on determining the tribological characteristics of the active part (tungsten carbide tooth tip) of the cutter teeth of asphalt milling equipment. The experiments are performedunderdifferent testing conditions (in a dry environment and in water) to highlight the need to use water, when milling the asphalt coating, with the purpose to reduce the wear of milling teeth. The experimental results show that water contributes to the substantial reduction of wear rate (more than eight times) on the active area of the tooth. The proposed test method—testing with the Baroid tribometer—is intended to evaluate the tribological characteristics of the materials using parallelepiped-shaped samples. The authors of the work performed the tests on samples that represent the teeth of the milling cutter having the real shape (so not on samples). The obtained results demonstrate that the test method can be used with good results on real parts.
On the Optical Properties of Cr2Ge2Te6 and Its Heterostructure
Authors: Idzuchi Hiroshi , Llacsahuanga Allcca Andres E. , Haglund Amanda Victo , Pan Xing-Chen , Matsuda Takuya , Tanigaki Katsumi , Mandrus David , Chen Yong P.
Published: July 2023

Recently, there has been a growing interest in two-dimensional van der Waals (vdW) magnets owing to their unique two-dimensional magnetic phenomena and potential applications. Most vdW ferromagnets have the Curie temperature below room temperature, highlighting the need to explore how to enhance their magnetism. In our previous report, we successfully increased the Curie temperature of the prototypical vdW magnet Cr2Ge2Te6 using a NiO overlayer. In layered materials, the presence of wrinkles is often observed and evaluating them using optical microscopy proves to be useful; however, there have been limited investigations into the optical constants of vdW magnets, hampering progress in understanding their optical properties. In this study, we present the optical constants of Cr2Ge2Te6 obtained through ellipsometry measurements. To account for the presence of wrinkles, we model a vacuum region between the substrate and the vdW magnet, and we calculate the reflectivity as a function of wavelength and vacuum thickness to visualize the optical image. Furthermore, we discuss the relationship between the optical constants and the electronic structure of the material.
Theoretical Study of Electronic and Thermal Transport Properties through a Single-Molecule Junction of Catechol
Authors: Soto-Gómez Erika Y. , Ojeda Silva Judith Helena , Gil-Corrales John A. , Gallego Daniel , Hurtado Morales Mikel F. , Morales Alvaro L. , Duque Carlos A.
Published: July 2023

The study of molecular nanoelectronic devices has recently gained significant interest, especially their potential use as functional junctions of molecular wires. Aromatic systems with π-conjugated bonds within their chemical backbones, such as catechol, have attracted particular attention in this area. In this work, we focused on calculating and determining catechol’s electrical and thermal transport properties using the theoretical method of Green’s functions renormalized in a real space domain within a framework of tight-binding approximation to the first neighbors. Thus, we studied two theoretical models of catechol as a function of its geometry, obtaining striking variations in the profiles of electrical and thermal conductance, the Seebeck coefficient, and the figure of merit. The analyses of the results suggest the potential application of catechol as a likely conductive and thermoelectric molecule serving as a novel material to use in molecular electronic devices.
A Review of Rhodolith/Maerl Beds of the Italian Seas
Authors: Ingrassia Michela , Pierdomenico Martina , Casalbore Daniele , Falese Francesco Giuseppe , Chiocci Francesco Latino
Published: July 2023

Coralline algal beds are comprised of biogenic calcareous formations considered a habitat of high conservation interest, hosting a high great biodiversity. To assess the status of this habitat in the Italian seas, we report results from a systematic analysis of the available scientific literature. Italian rhodolith/maerl beds are reported on 31 Italian sites mostly located around islands, shoals, banks, terraces, and gentley sloping shelves, from 9 m to 130 m water depth (with a mean depth of about 56 m). The dominant species occurring in the Italian submarine sites are Phymatolithon calcareum and Lithothamnion corallioides, with a rich associated fauna including sponges, bryozoans, hydrozoans, polichaetes, molluscs, amphipods, gastropods, echinoderms. Despite the high biodiversity characterizing the Italian rhodolith/maerl beds, only seven submarine sites hosting this sensitive habitat are part of Marine Protected Areas (MPAs). This evidence highlights the need for actions focused on the implementation of effective management and proper conservation measures to preserve such precious habitats. Protection of this habitat cannot be effectively provided without access to multidisciplinary data (e.g., geospatial, biological, geophysical, geomorphological data) capable of assessing its spatial distribution and biological characteristics over wide areas. An increased research effort to improve the production of fine-scale distribution maps and monitoring activities is therefore needed.
Histopathological Images Analysis and Predictive Modeling Implemented in Digital Pathology—Current Affairs and Perspectives
Authors: Moscalu Mihaela , Moscalu Roxana , Dascălu Cristina Gena , Țarcă Viorel , Cojocaru Elena , Costin Ioana Mădălina , Țarcă Elena , Șerban Ionela Lăcrămioara
Published: July 2023

In modern clinical practice, digital pathology has an essential role, being a technological necessity for the activity in the pathological anatomy laboratories. The development of information technology has majorly facilitated the management of digital images and their sharing for clinical use; the methods to analyze digital histopathological images, based on artificial intelligence techniques and specific models, quantify the required information with significantly higher consistency and precision compared to that provided by optical microscopy. In parallel, the unprecedented advances in machine learning facilitate, through the synergy of artificial intelligence and digital pathology, the possibility of diagnosis based on image analysis, previously limited only to certain specialties. Therefore, the integration of digital images into the study of pathology, combined with advanced algorithms and computer-assisted diagnostic techniques, extends the boundaries of the pathologist’s vision beyond the microscopic image and allows the specialist to use and integrate his knowledge and experience adequately. We conducted a search in PubMed on the topic of digital pathology and its applications, to quantify the current state of knowledge. We found that computer-aided image analysis has a superior potential to identify, extract and quantify features in more detail compared to the human pathologist’s evaluating possibilities; it performs tasks that exceed its manual capacity, and can produce new diagnostic algorithms and prediction models applicable in translational research that are able to identify new characteristics of diseases based on changes at the cellular and molecular level.
Application of Machine Learning Models for Early Detection and Accurate Classification of Type 2 Diabetes
Authors: Iparraguirre-Villanueva Orlando , Espinola-Linares Karina , Flores Castañeda Rosalynn Ornella , Cabanillas-Carbonell Michael
Published: July 2023

Early detection of diabetes is essential to prevent serious complications in patients. The purpose of this work is to detect and classify type 2 diabetes in patients using machine learning (ML) models, and to select the most optimal model to predict the risk of diabetes. In this paper, five ML models, including K-nearest neighbor (K-NN), Bernoulli Naïve Bayes (BNB), decision tree (DT), logistic regression (LR), and support vector machine (SVM), are investigated to predict diabetic patients. A Kaggle-hosted Pima Indian dataset containing 768 patients with and without diabetes was used, including variables such as number of pregnancies the patient has had, blood glucose concentration, diastolic blood pressure, skinfold thickness, body insulin levels, body mass index (BMI), genetic background, diabetes in the family tree, age, and outcome (with/without diabetes). The results show that the K-NN and BNB models outperform the other models. The K-NN model obtained the best accuracy in detecting diabetes, with 79.6% accuracy, while the BNB model obtained 77.2% accuracy in detecting diabetes. Finally, it can be stated that the use of ML models for the early detection of diabetes is very promising.
A Two-Phase Feature Selection Method for Identifying Influential Spreaders of Disease Epidemics in Complex Networks
Authors: Wang Xiya , Han Yuexing , Wang Bing
Published: July 2023

Network epidemiology plays a fundamental role in understanding the relationship between network structure and epidemic dynamics, among which identifying influential spreaders is especially important. Most previous studies aim to propose a centrality measure based on network topology to reflect the influence of spreaders, which manifest limited universality. Machine learning enhances the identification of influential spreaders by combining multiple centralities. However, several centrality measures utilized in machine learning methods, such as closeness centrality, exhibit high computational complexity when confronted with large network sizes. Here, we propose a two-phase feature selection method for identifying influential spreaders with a reduced feature dimension. Depending on the definition of influential spreaders, we obtain the optimal feature combination for different synthetic networks. Our results demonstrate that when the datasets are mildly or moderately imbalanced, for Barabasi–Albert (BA) scale-free networks, the centralities’ combination with the two-hop neighborhood is fundamental, and for Erdős–Rényi (ER) random graphs, the centralities’ combination with the degree centrality is essential. Meanwhile, for Watts–Strogatz (WS) small world networks, feature selection is unnecessary. We also conduct experiments on real-world networks, and the features selected display a high similarity with synthetic networks. Our method provides a new path for identifying superspreaders for the control of epidemics.
Wireless Device with Energy Management for Closed-Loop Deep Brain Stimulation (CLDBS)
Authors: Matheus Nordi Tiago , Augusto Ginja Gabriel , Gounella Rodrigo , Talanoni Fonoff Erich , Colombari Eduardo , Moreira Melkzedekue M. Alcântara , Afonso Jose A. , Monteiro Vitor , Afonso Joao L. , Carmo João Paulo
Published: July 2023

Deep brain stimulation (DBS) is an effective and safe medical treatment that improves the lives of patients with a wide range of neurological and psychiatric diseases, and has been consolidated as a first-line tool in the last two decades. Closed-loop deep brain stimulation (CLDBS) pushes this tool further by automatically adjusting the stimulation parameters to the brain response in real time. The main contribution of this paper is a low-size/power-controlled, compact and complete CLDBS system with two simultaneous acquisition channels, two simultaneous neurostimulation channels and wireless communication. Each channel has a low-noise amplifier (LNA) buffer in differential configuration to eliminate the DC signal component of the input. Energy management is efficiently done by the control and communication unit. The battery supports almost 9 h with both the acquisition and stimulation circuits active. If only the stimulation circuit is used as an Open Loop DBS, the battery can hold sufficient voltage for 24 h of operation. The whole system is low-cost and portable and therefore it could be used as a wearable device.
ACC-RL: Adaptive Congestion Control Based on Reinforcement Learning in Power Distribution Networks with Data Centers
Authors: Huang Tairan , Lu Xiaojuan , Zhang Dian , Cheng Haoran , Dong Pingping , Zhang Lianming
Published: July 2023

Modern data center power distribution networks place greater demands on the stability and reliability of power supply. Growing network computing demands and complex network environments can cause network congestion, which in turn leads to network traffic overload and power supply equipment overload. Therefore, network congestion is one of the most important problems faced by data center power distribution networks. In this paper, we propose an approach called ACC-RL based on reinforcement learning (RL), which can effectively avoid network congestion and improve energy performance. ACC-RL models the congestion control task as a Partially Observable Markov Decision Process (POMDP). It is independent of the estimated value function and supports deterministic policies. It also sets the reward value function using real-time network information such as the transmission rate, RTT, and switch queue length, with the target transmission rate as the target equilibrium point. ACC-RL is highly general, can be trained on datasets running in different network environments, and generates a robust congestion control policy. The experimental results show that ACC-RL can solve the congestion problem without any predefined scenarios in different network environments. It can control the network traffic well, thus ensuring the stability and reliability of the power supply in the distribution network. We conduct network simulation experiments through NS-3. We set up different scenarios for experiments and data analysis in many-to-one, all-to-all, and long–short network environments. Compared with the popular rule-based congestion control algorithms such as TIMELY, DCQCN, and HPCC, ACC-RL shows different degrees of energy performance advantages in network metrics such as fairness, link utilization, and throughput.
Techno-Economic Assessment of CPVT Spectral Splitting Technology: A Case Study on Saudi Arabia
Authors: Lucio Cesar , Behar Omar , Dally Bassam
Published: July 2023

Concentrating PV thermal (CPVT) collector with spectral splitting technology is a promising solution for heat and electricity production. To extend the use of this technology, a novel and cost-effective CPVT collector for harsh environments, such as those in Saudi Arabia, is presented and evaluated using theoretical energy, economy, and environmental analysis. Two questions are answered in this study, namely: which is the best operation strategy, and which is the best energy storage technology for CPVT. The potential of using a CPVT under the climate conditions of six cities in Saudi Arabia is also evaluated. It is found that a heat/electricity production strategy and a thermal energy storage are the most suitable for the CPVT technology. The economic assessment shows a levelized cost of electricity (LCOE) of $0.0847/kWh and a levelized cost of heat (LCOH) of $0.0536/kWh when water is used as a spectral filter, and a LCOE of $0.0906/kWh and a LCOH of $0.0462/kWh when ZnO nanoparticles are added. The CO2-equivalent emissions in a 20 MW CPVT plant are cut from 5675 tonnes to 7822 tonnes per year for Saudi Arabian weather and present power generation conditions.
Study of Combustor–Turbine Interactions by Performing Coupled and Decoupled Hybrid RANS-LES Simulations under Representative Engine-like Conditions
Authors: Tomasello Stella Grazia , Meloni Roberto , Andrei Luca , Andreini Antonio
Published: July 2023

Combustion–turbine interaction phenomena are attracting ever-growing interest in recent years. As a matter of fact, the strong unsteady and three-dimensional flow field that characterizes the combustor is usually conserved up to the first-stage nozzle, possibly affecting its design and performance in terms of aerodynamics and the effectiveness of the cooling system as well. Such conditions are also exacerbated by the employment of lean-burn combustors, where high turbulence levels are required for the flame stabilization, resulting in even greater temperature and velocity distortions at the inlet of the first-stage nozzle. Even if it has been proven by several past studies that the best way of studying the combustor–turbine interaction is simulating the two components together, performing coupled simulations is still challenging from a numerical point of view, especially in an industrial context. For this reason, the application and generation of the most representative and reliable boundary conditions possible at the inlet of the S1N have assumed an increased importance in order to study the two components separately by performing decoupled simulations. In this context, the purpose of the present work is to compare fully integrated combustor–stator SBES simulations to isolated stator ones. To perform the stator-only calculations, the fully unsteady inlet conditions of the stator have been recorded at the interface plane between the two components in the integrated SBES simulation and then they have been reconstructed by applying the proper orthogonal decomposition (POD) technique. The SBES simulations of the isolated stator have been so performed with the aim of determining whether the flow field obtained is comparable with the one of the integrated simulation, thus allowing more realistic results to be obtained rather than imposing time-averaged 2D maps, as per standard design practice.
Case Studies for Supplying the Alternating Current Auxiliary Systems of Substations with a Voltage Equal to or Higher than 230 kV
Authors: Cavalcanti Mariana de Morais , Costa Tatiane , Pereira Alex C. , Jatobá Eduardo B. , Filho José Bione de Melo , Barreto Elisabete , Mohamed Mohamed A. , Ilinca Adrian , Marinho Manoel H. N.
Published: July 2023

This paper presents case studies for replacing diesel generators (DGs) that are used as the main and emergency power sources for alternating current (AC) auxiliary services in substations (SS) within the transmission network (voltage greater than or equal to 230 kV). The objective of this research is to present a solution that is more reliable, environmentally friendly, and financially viable than DGs. To achieve this, the proposed solutions incorporate Battery Energy Storage Systems (BESSs) with or without the integration of Photovoltaic (PV) Systems. These solutions were simulated using the HOMER PRO Version 3.14.5 software for the Messias SS /AL, and the results were analyzed and compared to the DG in terms of reliability, financial viability, and environmental impact. Based on the conducted analyses, the BESS solution with the PV system was found to be the most suitable for the main source. However, in the case of the emergency source, if one of the main sources is a DG/BESS, maintaining the emergency DG is the preferable option. If both main sources are independent, the BESS solution with the PV system is a suitable solution.
A Method for Fault Section Identification of Distribution Networks Based on Validation of Fault Indicators Using Artificial Neural Network
Authors: Kim Myong-Soo , An Jae-Guk , Oh Yun-Sik , Lim Seong-Il , Kwak Dong-Hee , Song Jin-Uk
Published: July 2023

A fault section in Korean distribution networks is generally determined as a section between a switch with a fault indicator (FI) and a switch without an FI. However, the existing method cannot be applied to distribution networks with distributed generations (DGs) due to false FIs that are generated by fault currents flowing from the load side of a fault location. To identify the false FIs and make the existing method applicable, this paper proposes a method to determine the fault section by utilizing an artificial neural network (ANN) model for validating FIs, which is difficult to determine using mathematical equations. The proposed ANN model is built by training the relationship between the measured A, B, C, and N phase fault currents acquired by numerous simulations on a sample distribution system, and guarantees 100% FI validations for the test data. The proposed method can accurately distinguish genuine and false Fis by utilizing the ability of the ANN model, thereby enabling the conventional FI-based method to be applied to DG-connected distribution networks without any changes to the equipment and communication infrastructure. To verify the performance of the proposed method, various case studies considering real fault conditions are conducted under a Korean distribution network using MATLAB.
Research on IPFC-Based Dynamic Droop Control Strategy
Authors: Ding Chaofan , Li Xiaopeng , Li Baohong , Jiang Qin , Wen Menghao , Liu Tianqi
Published: July 2023

The interline power flow controller (IPFC) presents a promising solution for managing the directional and quantitative interaction of power between different lines, facilitating a significant improvement in power system stability. Based on such a background, this paper proposes a dynamic droop control strategy to improve frequency stability through the use of IPFC equipment. To enhance the active power support ability of the IPFC, additional frequency control for the IPFC’s active power control loop is designed with droop control, where each IPFC’s power flow control limitations are also considered to make sure the original power of each line is controllable. Besides the addition of such basic control, the proposed droop strategy is designed in a dynamic style. The droop coefficients of each IPFC can be varied according to each line’s power transmission margin, such that the power fluctuations can be shared more reasonably based on such a dynamic droop coordination strategy. The proposed methods are verified through PSCAD simulations. The results show that the dynamic droop control cannot only suppress the frequency disturbance, but also make power dispatch more efficient.