bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of FLT3–ITD Mutation Status and Its Ratio in a Cohort of 2901 Patients Undergoing Upfront Intensive Chemotherapy: A PETHEMA Registry Study
Authors: Ayala Rosa , Carreño-Tarragona Gonzalo , Barragán Eva , Boluda Blanca , Larráyoz María J. , Chillón María Carmen , Carrillo-Cruz Estrella , Bilbao Cristina , Sánchez-García Joaquín , Bernal Teresa , Martinez-Cuadron David , Gil Cristina , Serrano Josefina , Rodriguez-Medina Carlos , Bergua Juan , Pérez-Simón José A. , Calbacho María , Alonso-Domínguez Juan M. , Labrador Jorge , Tormo Mar , Amigo Maria Luz , Herrera-Puente Pilar , Rapado Inmaculada , Sargas Claudia , Vazquez Iria , Calasanz María J. , Gomez-Casares Teresa , García-Sanz Ramón , Sanz Miguel A. , Martínez-López Joaquín , Montesinos Pau
Published: November 2022

FLT3–ITD results in a poor prognosis in terms of overall survival (OS) and relapse-free survival (RFS) in acute myeloid leukemia (AML). However, the prognostic usefulness of the allelic ratio (AR) to select post-remission therapy remains controversial. Our study focuses on the prognostic impact of FLT3–ITD and its ratio in a series of 2901 adult patients treated intensively in the pre-FLT3 inhibitor era and reported in the PETHEMA registry. A total of 579 of these patients (20%) harbored FLT3–ITD mutations. In multivariate analyses, patients with an FLT3–ITD allele ratio (AR) of >0.5 showed a lower complete remission (CR rate) and OS (HR 1.47, p = 0.009), while AR > 0.8 was associated with poorer RFS (HR 2.1; p < 0.001). Among NPM1/FLT3–ITD-mutated patients, median OS gradually decreased according to FLT3–ITD status and ratio (34.3 months FLT3–ITD-negative, 25.3 months up to 0.25, 14.5 months up to 0.5, and 10 months ≥ 0.5, p < 0.001). Post-remission allogeneic transplant (allo-HSCT) resulted in better OS and RFS as compared to auto-HSCT in NPM1/FLT3–ITD-mutated AML regardless of pre-established AR cutoff (≤0.5 vs. >0.5). Using the maximally selected log-rank statistics, we established an optimal cutoff of FLT3–ITD AR of 0.44 for OS, and 0.8 for RFS. We analyzed the OS and RFS according to FLT3–ITD status in all patients, and we found that the group of FLT3–ITD-positive patients with AR < 0.44 had similar 5-year OS after allo-HSCT or auto-HSCT (52% and 41%, respectively, p = 0.86), but worse RFS after auto-HSCT (p = 0.01). Among patients with FLT3–ITD AR > 0.44, allo-HSCT was superior to auto-HSCT in terms of OS and RFS. This study provides more evidence for a better characterization of patients with AML harboring FLT3–ITD mutations.
Promote Community Engagement in Participatory Research for Improving Breast Cancer Prevention: The P.I.N.K. Study Framework
Authors: Franchini Michela , Pieroni Stefania , Denoth Francesca , Scalese Urciuoli Marco , Colasante Emanuela , Salvatori Massimiliano , Anastasi Giada , Frontignano Cinzia Katia , Dogliotti Elena , Vidali Sofia , Montrucchio Edgardo , Molinaro Sabrina , Susini Tommaso , Nori Cucchiari Jacopo
Published: November 2022

Breast cancer (BC) has overtaken lung cancer as the most common cancer in the world and the projected incidence rates show a further increase. Early detection through population screening remains the cornerstone of BC control, but a progressive change from early diagnosis only-based to a personalized preventive and risk-reducing approach is widely debated. Risk-stratification models, which also include personal lifestyle risk factors, are under evaluation, although the documentation burden to gather population-based data is relevant and traditional data collection methods show some limitations. This paper provides the preliminary results from the analysis of clinical data provided by radiologists and lifestyle data collected using self-administered questionnaires from 5601 post-menopausal women. The weight of the combinations of women’s personal features and lifestyle habits on the BC risk were estimated by combining a model-driven and a data-driven approach to analysis. The weight of each factor on cancer occurrence was assessed using a logistic model. Additionally, communities of women sharing common features were identified and combined in risk profiles using social network analysis techniques. Our results suggest that preventive programs focused on increasing physical activity should be widely promoted, in particular among the oldest women. Additionally, current findings suggest that pregnancy, breast-feeding, salt limitation, and oral contraception use could have different effects on cancer risk, based on the overall woman’s risk profile. To overcome the limitations of our data, this work also introduces a mobile health tool, the Dress-PINK, designed to collect real patients’ data in an innovative way for improving women’s response rate, data accuracy, and completeness as well as the timeliness of data availability. Finally, the tool provides tailored prevention messages to promote critical consciousness, critical thinking, and increased health literacy among the general population.
Pelvic Lymphadenectomy May Not Improve Biochemical Recurrence-Free Survival in Patients with Prostate Cancer Treated with Robot-Assisted Radical Prostatectomy in Japan (The MSUG94 Group)
Authors: Namiki Sanae , Kawase Makoto , Ebara Shin , Tatenuma Tomoyuki , Sasaki Takeshi , Ikehata Yoshinori , Nakayama Akinori , Toide Masahiro , Yoneda Tatsuaki , Sakaguchi Kazushige , Teishima Jun , Makiyama Kazuhide , Inoue Takahiro , Kitamura Hiroshi , Saito Kazutaka , Koga Fumitaka , Urakami Shinji , Koie Takuya
Published: November 2022

In this multicenter retrospective cohort study, we aimed to evaluate whether pelvic lymph node dissection (PLND) improved biochemical recurrence (BCR) in patients with prostate cancer (PCa) who underwent robot-assisted radical prostatectomy (RARP) in Japan. A multicenter retrospective cohort study of 3195 PCa patients undergoing RARP at nine institutions in Japan was conducted. Enrolled patients were divided into two groups: those who underwent RARP without PLND (non-PLND group) and those who underwent PLND (PLND group). The primary endpoint was biochemical recurrence-free survival (BRFS) in PCa patients who underwent PLND. We developed a propensity score analysis to reduce the effects of selection bias and potential confounding factors. Propensity score matching resulted in 1210 patients being enrolled in the study. The 2-year BRFS rate was 95.0% for all patients, 95.8% for the non-PLND group, and 94.3% for the PLND group (p = 0.855). For the all-risk group according to the National Comprehensive Cancer Network risk stratification, there were no significant differences between patients who did and did not undergo PLND. Based on the results of the log-rank study, PLND may be unnecessary for patients with PCa undergoing RARP.
Radiomics for Discriminating Benign and Malignant Salivary Gland Tumors; Which Radiomic Feature Categories and MRI Sequences Should Be Used?
Authors: Zhang Rongli , Ai Qi Yong H. , Wong Lun M. , Green Christopher , Qamar Sahrish , So Tiffany Y. , Vlantis Alexander C. , King Ann D.
Published: November 2022

The lack of a consistent MRI radiomic signature, partly due to the multitude of initial feature analyses, limits the widespread clinical application of radiomics for the discrimination of salivary gland tumors (SGTs). This study aimed to identify the optimal radiomics feature category and MRI sequence for characterizing SGTs, which could serve as a step towards obtaining a consensus on a radiomics signature. Preliminary radiomics models were built to discriminate malignant SGTs (n = 34) from benign SGTs (n = 57) on T1-weighted (T1WI), fat-suppressed (FS)-T2WI and contrast-enhanced (CE)-T1WI images using six feature categories. The discrimination performances of these preliminary models were evaluated using 5-fold-cross-validation with 100 repetitions and the area under the receiver operating characteristic curve (AUC). The differences between models’ performances were identified using one-way ANOVA. Results show that the best feature categories were logarithm for T1WI and CE-T1WI and exponential for FS-T2WI, with AUCs of 0.828, 0.754 and 0.819, respectively. These AUCs were higher than the AUCs obtained using all feature categories combined, which were 0.750, 0.707 and 0.774, respectively (p < 0.001). The highest AUC (0.846) was obtained using a combination of T1WI + logarithm and FS-T2WI + exponential features, which reduced the initial features by 94.0% (from 1015 × 3 to 91 × 2). CE-T1WI did not improve performance. Using one feature category rather than all feature categories combined reduced the number of initial features without compromising radiomic performance.
The Aurora Kinase Inhibitor TAK901 Inhibits Glioblastoma Growth by Blocking SREBP1-Mediated Lipid Metabolism
Authors: Zhan Xiudan , Qiu Ru , He Yi , Zhao Zijin , Huang Meng , Liu Qing , Zhi Feng , Long Wenyong
Published: November 2022

Glioblastoma (GBM) is the most common and lethal malignant primary brain tumor. The standard treatment for GBM including surgical resection followed by radiation therapy and adjuvant chemotherapy with temozolomide remains unsatisfactory. In this study, we investigated the effects of the Aurora kinase inhibitor, TAK901, in GBM both in vitro and in vivo, and explored its key downstream targets. The effects of TAK901 were investigated using cell viability, cell apoptosis, live/dead, cell cycle, Transwell, 3D cell invasion, neuro-sphere, and self-renewal assays. Mechanistic studies were conducted using RNA-seq, lipid measurements, reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and Western blotting. The in vivo efficacy of TAK901 was validated using orthotopic xenograft GBM mouse models. In both GBM cells and GSCs, TAK901 remarkably reduced cell viability, self-renewal, migration and invasion and induced apoptosis and cell cycle arrest. Treatment with TAK901 considerably inhibited GBM growth in vivo. RNA-seq and RT-qPCR analyses showed that TAK901 downregulated the expression and activation of SREBP1. Moreover, SREBP1 overexpression alleviated the TAK901-mediated suppression of cell viability and apoptosis in GBM cells. Our results provide evidence that TAK901 inhibits GBM growth by suppressing SREBP1-mediated lipid metabolism.
Enhanced CuAl2O4 Catalytic Activity via Alkalinization Treatment toward High CO2 Conversion during Reverse Water Gas Shift Reaction
Authors: Hu Mian , Hu Hongyu , Tang Suqin , Pan Zhiyan
Published: November 2022

CO2 catalytic conversion to CO would likely be an important part of CO2 mitigation and utilization. In this work, CuAl2O4 was developed with a spinel structure that acts as an active and stable catalyst for this reaction. Here, the fundamental characteristics of CuAl2O4 catalyst were studied to understand the catalytic mechanism for the Reverse Water Gas Shift reaction. Based on the catalytic mechanism, the CuAl2O4 catalyst was found to have exceptional catalytic activity due to the high dispersion of copper on its surface, and it could have higher catalytic activity by increasing the oxygen vacancies on the surface of the catalyst via alkalinization treatment. By combining with XPS spectra, the relationship between the Raman mode and the oxygen vacancy structure on the CuAl2O4 surface was proved. Through these studies, it was proved that alkalinization treatment can regulate the oxygen vacancies on the surface of the catalyst and thus enhance the catalytic activity.
NLRP3 and Gut Microbiota Homeostasis: Progress in Research
Authors: Pan Hongming , Jian Yuting , Wang Feijie , Yu Shaokun , Guo Jiannan , Kan Juntao , Guo Wei
Published: November 2022

The inflammasome is a platform for inflammatory signaling, and the NLRP3 inflammasome recognizes stimuli in vitro and in vivo, and releases inflammatory cytokines that trigger inflammation and pyroptosis. In the gut, the NLRP3 inflammasome is a key sensor for protecting the body from damage and exogenous pathogens. It plays a fundamental role in maintaining the stability of the gut’s immune system. We focus on the role of NLRP3 as a key node in maintaining the homeostasis of gut microbiota which has not been fully highlighted in the past; gut microbiota and innate immunity, as well as the NLRP3 inflammasome, are discussed in this article.
10th Anniversary of Cells—Advances in Plant, Algae and Fungi Cell Biology
Authors: Allakhverdiev Suleyman I.
Published: November 2022

In 2021, the 10th anniversary of the publication of Cells occurred [...]
Identification of the Inner Cell Mass and the Trophectoderm Responses after an In Vitro Exposure to Glucose and Insulin during the Preimplantation Period in the Rabbit Embryo
Authors: Via y Rada Romina , Daniel Nathalie , Archilla Catherine , Frambourg Anne , Jouneau Luc , Jaszczyszyn Yan , Charpigny Gilles , Duranthon Véronique , Calderari Sophie
Published: November 2022

The prevalence of metabolic diseases is increasing, leading to more women entering pregnancy with alterations in the glucose-insulin axis. The aim of this work was to investigate the effect of a hyperglycemic and/or hyperinsulinemic environment on the development of the preimplantation embryo. In rabbit embryos developed in vitro in the presence of high insulin (HI), high glucose (HG), or both (HGI), we determined the transcriptomes of the inner cell mass (ICM) and the trophectoderm (TE). HI induced 10 differentially expressed genes (DEG) in ICM and 1 in TE. HG ICM exhibited 41 DEGs involved in oxidative phosphorylation (OXPHOS) and cell number regulation. In HG ICM, proliferation was decreased (p < 0.01) and apoptosis increased (p < 0.001). HG TE displayed 132 DEG linked to mTOR signaling and regulation of cell number. In HG TE, proliferation was increased (p < 0.001) and apoptosis decreased (p < 0.001). HGI ICM presented 39 DEG involved in OXPHOS and no differences in proliferation and apoptosis. HGI TE showed 16 DEG linked to OXPHOS and cell number regulation and exhibited increased proliferation (p < 0.001). Exposure to HG and HGI during preimplantation development results in common and specific ICM and TE responses that could compromise the development of the future individual and placenta.
Clinical Decision-Making in Practice with New Critical Care Ultrasound Methods for Assessing Respiratory Function and Haemodynamics in Critically Ill Patients
Authors: Schmidt Stefan , Dieks Jana-Katharina , Quintel Michael , Moerer Onnen
Published: November 2022

Situations often arise in intensive care units (ICUs) for which only sparse primary evidence or guidelines are applicable or to which existing evidence cannot be applied owing to interactions of multiple disease states. To improve and guide intensive care management in complex scenarios, ultrasonography and echocardiography are invaluable. In five clinical scenarios involving acute deterioration, serial ultrasound examinations of the respiratory system, general critical care ultrasound (GCCUS), and non-invasive haemodynamic critical care echocardiography (CCE) were used routinely. Ultrasonographic results were used to guide further management and initiate experimental therapy or transition from curative to supportive care. The process of initiation of ultrasound examinations to clinical decision-making in these complex scenarios is outlined. These case vignettes highlight the utility of ultrasound and echocardiography. When clinical management is not clear, or evidence is not available, the use of ultrasound for the evaluation of the respiratory system, GCCUS, and non-invasive haemodynamic CCE can help to guide management, reveal newly developed pathologies, lead to clinical management changes, and support the decision for employing experimental therapy approaches in a dynamic way of which few other imaging modalities or monitoring tools are currently capable.
Thin Films on the Surface of GaAs, Obtained by Chemically Stimulated Thermal Oxidation, as Materials for Gas Sensors
Authors: Kostryukov V. F. , Parshina A. S. , Sladkopevtsev B. V. , Mittova I. Ya.
Published: November 2022

Semiconductor metal oxide films on the surface of gallium arsenide are obtained by chemostimulated oxidation under the influence of a Sb2O3 + Y2O3 composition. The chemical composition of the obtained films and the surface morphology are determined by EPXMA, IR spectroscopy, and AFM. The main components of the films are gallium and arsenic, which are in the oxidized state. The content of the chemical stimulator (Sb2O3) does not exceed 2%. Films obtained under the influence of composites 60% Sb2O3 + 40% Y2O3 and 80% Sb2O3 + 20% Y2O3 are characterized by the maximum surface roughness. The samples obtained in this work demonstrate n-type semiconductor properties in the temperature range of 20–400 °C. It is established that the obtained samples have a gas-sensitive response to NH3 and CO. The maximum value of the sensory signal appears for the samples obtained under the influence of compositions 80% Sb2O3 + 20% Y2O3, which are characterized by the most developed surfaces. The resulting films are selective to the studied gases—the difference in temperature for the maximum signal is 60 °C (200 °C for CO and 260 °C for NH3).
Conversion of Nastrophites to Fibrous Strontium Apatites and Their Crystallographic Characterization
Authors: Furukawa Akira , Tanaka Yasuhito
Published: November 2022

Strontium apatite has attracted considerable attention from researchers in various disciplines, including the medical field, owing to its excellent biocompatibility and beneficial effects on enhanced bone regeneration. In addition to their chemical characteristics, morphological aspects of apatite crystals are of great importance because they can exert a significant influence on various biological functions. In this study, a versatile method for the synthesis of fibrous strontium apatite is developed for the first time. Highly crystalline strontium apatite nanofibers were prepared by alkaline hydrolysis of strontium hydrogen phosphate (SrHPO4) at ambient temperature via nastrophite (NaSrPO4) intermediates. Some strontium ions in the crystal lattice of strontium hydrogen phosphate were substituted with barium (Ba) ions with various molar ratios up to Ba/Sr = 5/5, and their molar ratios were retained in the final products of the substituted fibrous apatites. The products, including hydrogen phosphates, nastrophites, and apatite nanofibers, were characterized using powder X-ray diffraction (XRD), field emission-scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), wavelength dispersive X-ray fluorescence (WDX) analysis, and transmission electron microscopy (TEM) with selected area electron diffraction (SAED). These analyses verified the integrity of the speculated structures of the fibrous apatites. The lattice parameters of apatites and other intermediates were calculated using a newly developed calculation process based on the least-squares method and the results were compared to those of EXPO2014.
Synthesis, Mesomorphic Properties and Application of (R,S)-1-Methylpentyl 4′-Hydroxybiphenyl-4-carboxylate Derivatives
Authors: Urbańska Magdalena , Szala Mateusz
Published: November 2022

Thirteen new liquid crystalline racemic mixtures were synthesized and investigated. For these racemic mixtures, the phase sequences and their changes were determined by polarizing optical microscopy (POM). The phase transition temperatures and transition enthalpies were checked by differential scanning calorimetry (DSC). All new racemates have an anticlinic smectic CA phase in a broad temperature range. Three highly tilted antiferroelectric mixtures were doped with six racemates at a concentration of 20% by weight. The helical pitch of the prepared mixtures was measured by the spectrophotometry method. All doped mixtures have a longer helical pitch than the base mixtures.
Synthesis of Nickel Cobaltite/Multiwalled Carbon Nanotubes Composites and Their Application for Removing Uranium (VI)
Authors: Zhang Xiaofei , Ni Binshan , Li Xiaoxuan , Guan Xin , Xia Wandong , Hao Jiabin , Tan Lichao
Published: November 2022

A facile hydrothermal method has been developed to prepare a nickel cobaltite/multiwalled carbon nanotubes (NiCo2O4/MWCNTs) composite. The structure and morphology of NiCo2O4/MWCNTs were tested by X-ray diffraction, X-ray photoelectron spectroscopy, transmission electron microscope, and nitrogen sorption isotherm. The nitrogen sorption isotherms of the NiCo2O4/MWCNTs composite indicate that NiCo2O4/MWCNT is a typical mesoporous material. The average pore width of NiCo2O4/MWCNTs is 10.0 nm. When serving as the adsorbent for uranium, the NiCo2O4/MWCNTs composite exhibits a high adsorption capacity, suggesting their potential use in water treatment. The influences of pH, temperature, and time on the adsorption efficiency of uranium by NiCo2O4/MWCNTs were studied. The experimental results show that the maximum adsorption capacity of NiCo2O4/MWCNTs for uranium(VI) is 247.4 mg g−1, suggesting that it is an effective uranium(VI) sorbent in water treatment. Thermodynamic analysis results show that the process is endothermic in nature. As the adsorption capacity does not increase significantly with the increase in T, the uranium adsorption by NiCo2O4/MWCNTs can be carried out at room temperature to reduce energy consumption. The NiCo2O4/MWCNTs composite can be a good alternative to remove uranium(VI).
Identifying Severity Grading of Knee Osteoarthritis from X-ray Images Using an Efficient Mixture of Deep Learning and Machine Learning Models
Authors: Ahmed Sozan Mohammed , Mstafa Ramadhan J.
Published: November 2022

Recently, many diseases have negatively impacted people’s lifestyles. Among these, knee osteoarthritis (OA) has been regarded as the primary cause of activity restriction and impairment, particularly in older people. Therefore, quick, accurate, and low-cost computer-based tools for the early prediction of knee OA patients are urgently needed. In this paper, as part of addressing this issue, we developed a new method to efficiently diagnose and classify knee osteoarthritis severity based on the X-ray images to classify knee OA in (i.e., binary and multiclass) in order to study the impact of different class-based, which has not yet been addressed in previous studies. This will provide physicians with a variety of deployment options in the future. Our proposed models are basically divided into two frameworks based on applying pre-trained convolutional neural networks (CNN) for feature extraction as well as fine-tuning the pre-trained CNN using the transfer learning (TL) method. In addition, a traditional machine learning (ML) classifier is used to exploit the enriched feature space to achieve better knee OA classification performance. In the first one, we developed five classes-based models using a proposed pre-trained CNN for feature extraction, principal component analysis (PCA) for dimensionality reduction, and support vector machine (SVM) for classification. While in the second framework, a few changes were made to the steps in the first framework, the concept of TL was used to fine-tune the proposed pre-trained CNN from the first framework to fit the two classes, three classes, and four classes-based models. The proposed models are evaluated on X-ray data, and their performance is compared with the existing state-of-the-art models. It is observed through conducted experimental analysis to demonstrate the efficacy of the proposed approach in improving the classification accuracy in both multiclass and binary class-based in the OA case study. Nonetheless, the empirical results revealed that the fewer multiclass labels used, the better performance achieved, with the binary class labels outperforming all, which reached a 90.8% accuracy rate. Furthermore, the proposed models demonstrated their contribution to early classification in the first stage of the disease to help reduce its progression and improve people’s quality of life.
OCT Angiography Features in Diabetes Mellitus Type 1 and 2
Authors: Oliverio Giovanni William , Meduri Alessandro , De Salvo Gabriella , Trombetta Luigi , Aragona Pasquale
Published: November 2022

Purpose: To study the foveal avascular zone (FAZ) and the vessel densities (VD) in diabetic patients using optical coherence tomography angiography (OCT-A) and inner retinal layer changes to compare patients affected by type 1 diabetes (DM1) and type 2 diabetes (DM2). Methods: Cross-sectional observational study involving 150 eyes of 150 patients with DM1, and 155 eyes of 155 patients with DM2 with diabetic retinopathy (DR). Retinal nerve fiber layer (RNFL) and Ganglion cell layer (GCL) were evaluated. OCT-A studied both FAZ and VD at the level of the superficial capillary plexus (SCP) and the deep capillary plexus (DCP). Results: A statistically significant difference in FAZ area and foveal VD measured at the SCP (p < 0.001) was noted between DM1 and DM2 groups when comparing patients with mild and moderate non-proliferative diabetic retinopathy (NPDR), while no differences were found in the severe NPDR and proliferative diabetic retinopathy (PDR) subgroups. Duration of diabetes and stage of DR were directly correlated with enlargement of FAZ area and inversely correlated with foveal VD measured at SCP. RNFL and GCL were not different between DM1 and DM2 groups. Conclusion: Changes in OCT-A parameters detected in FAZ area and VD of diabetic patients with different stages of DR may help to predict the risk for progression of the disease.
The Capacity of Artificial Intelligence in COVID-19 Response: A Review in Context of COVID-19 Screening and Diagnosis
Authors: Ozsahin Dilber Uzun , Isa Nuhu Abdulhaqq , Uzun Berna
Published: November 2022

Artificial intelligence (AI) has been shown to solve several issues affecting COVID-19 diagnosis. This systematic review research explores the impact of AI in early COVID-19 screening, detection, and diagnosis. A comprehensive survey of AI in the COVID-19 literature, mainly in the context of screening and diagnosis, was observed by applying the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Data sources for the years 2020, 2021, and 2022 were retrieved from google scholar, web of science, Scopus, and PubMed, with target keywords relating to AI in COVID-19 screening and diagnosis. After a comprehensive review of these studies, the results found that AI contributed immensely to improving COVID-19 screening and diagnosis. Some proposed AI models were shown to have comparable (sometimes even better) clinical decision outcomes, compared to experienced radiologists in the screening/diagnosing of COVID-19. Additionally, AI has the capacity to reduce physician work burdens and fatigue and reduce the problems of several false positives, associated with the RT-PCR test (with lower sensitivity of 60–70%) and medical imaging analysis. Even though AI was found to be timesaving and cost-effective, with less clinical errors, it works optimally under the supervision of a physician or other specialists.
Risk of Mortality Prediction Involving Time-Varying Covariates for Patients with Heart Failure Using Deep Learning
Authors: Nakamura Keijiro , Zhou Xue , Sahara Naohiko , Toyoda Yasutake , Enomoto Yoshinari , Hara Hidehiko , Noro Mahito , Sugi Kaoru , Huang Ming , Moroi Masao , Nakamura Masato , Zhu Xin
Published: November 2022

Heart failure (HF) is challenging public medical and healthcare systems. This study aimed to develop and validate a novel deep learning-based prognostic model to predict the risk of all-cause mortality for patients with HF. We also compared the performance of the proposed model with those of classical deep learning- and traditional statistical-based models. The present study enrolled 730 patients with HF hospitalized at Toho University Ohashi Medical Center between April 2016 and March 2020. A recurrent neural network-based model (RNNSurv) involving time-varying covariates was developed and validated. The proposed RNNSurv showed better prediction performance than those of a deep feed-forward neural network-based model (referred as “DeepSurv”) and a multivariate Cox proportional hazard model in view of discrimination (C-index: 0.839 vs. 0.755 vs. 0.762, respectively), calibration (better fit with a 45-degree line), and ability of risk stratification, especially identifying patients with high risk of mortality. The proposed RNNSurv demonstrated an improved prediction performance in consideration of temporal information from time-varying covariates that could assist clinical decision-making. Additionally, this study found that significant risk and protective factors of mortality were specific to risk levels, highlighting the demand for an individual-specific clinical strategy instead of a uniform one for all patients.
Exploiting Dual-Attention Networks for Explainable Recommendation in Heterogeneous Information Networks
Authors: Zuo Xianglin , Jia Tianhao , He Xin , Yang Bo , Wang Ying
Published: November 2022

The aim of explainable recommendation is not only to provide recommended items to users, but also to make users aware of why these items are recommended. Traditional recommendation methods infer user preferences for items using user–item rating information. However, the expressive power of latent representations of users and items is relatively limited due to the sparseness of the user–item rating matrix. Heterogeneous information networks (HIN) provide contextual information for improving recommendation performance and interpreting the interactions between users and items. However, due to the heterogeneity and complexity of context information in HIN, it is still a challenge to integrate this contextual information into explainable recommendation systems effectively. In this paper, we propose a novel framework—the dual-attention networks for explainable recommendation (DANER) in HINs. We first used multiple meta-paths to capture high-order semantic relations between users and items in HIN for generating similarity matrices, and then utilized matrix decomposition on similarity matrices to obtain low-dimensional sparse representations of users and items. Secondly, we introduced two-level attention networks, namely a local attention network and a global attention network, to integrate the representations of users and items from different meta-paths for obtaining high-quality representations. Finally, we use a standard multi-layer perceptron to model the interactions between users and items, which predict users’ ratings of items. Furthermore, the dual-attention mechanism also contributes to identifying critical meta-paths to generate relevant explanations for users. Comprehensive experiments on two real-world datasets demonstrate the effectiveness of DANER on recommendation performance as compared with the state-of-the-art methods. A case study illustrates the interpretability of DANER.
Mutual Information and Multi-Agent Systems
Authors: Moskowitz Ira S. , Rogers Pi , Russell Stephen
Published: November 2022

We consider the use of Shannon information theory, and its various entropic terms to aid in reaching optimal decisions that should be made in a multi-agent/Team scenario. The methods that we use are to model how various agents interact, including power allocation. Our metric for agents passing information are classical Shannon channel capacity. Our results are the mathematical theorems showing how combining agents influences the channel capacity.
Study of Bulk Properties of Strange Particles in Au+Au Collisions at sNN = 54.4 GeV
Authors: Li Li-Li , Haj Ismail Abd Al Karim
Published: November 2022

We analyzed the transverse momentum pT spectra of various strange hadrons KS0, Λ(Λ¯) and Ξ−(Ξ¯+) at mid-rapidity (y) in different centrality intervals from Au+Au collisions at sNN= 54.4 GeV. The pT spectra of these strange hadrons are investigated by the Tsallis-like distribution, which satisfactorily fits the experimental data. The bulk properties of the medium produced in ultra-relativistic heavy-ion collisions at the kinetic freeze-out are reflected by measuring the hadron spectra. The effective temperature T, transverse flow velocity βT, and mean pT along with other parameters that are strongly dependent on centrality and particle specie are extracted. The effective temperature of multi-strange particle (Ξ−(Ξ¯+)) is larger as compared to singly-strange particles Λ(Λ¯) and KS0. Furthermore, the kinetic freeze-out temperature T, transverse flow velocity βT. and mean pT (⟨pT⟩) show a decreasing trend towards lower centrality, while the entropy parameter q increases from central to peripheral collisions. In addition, a positive correlation of ⟨pT⟩ and T and a negative correlation of q and T are also reported.
Entropy Optimization, Generalized Logarithms, and Duality Relations
Authors: Plastino Angel R. , Tsallis Constantino , Wedemann Roseli S. , Haubold Hans J.
Published: November 2022

Several generalizations or extensions of the Boltzmann–Gibbs thermostatistics, based on non-standard entropies, have been the focus of considerable research activity in recent years. Among these, the power-law, non-additive entropies Sq≡k1−∑ipiqq−1(q∈R;S1=SBG≡−k∑ipilnpi) have harvested the largest number of successful applications. The specific structural features of the Sq thermostatistics, therefore, are worthy of close scrutiny. In the present work, we analyze one of these features, according to which the q-logarithm function lnqx≡x1−q−11−q(ln1x=lnx) associated with the Sq entropy is linked, via a duality relation, to the q-exponential function characterizing the maximum-entropy probability distributions. We enquire into which entropic functionals lead to this or similar structures, and investigate the corresponding duality relations.
An NMR Investigation of the Influence of Cation Content in Polymer Ion Retarder on Hydration of Oil Well Cement
Authors: Qi Zhigang , Chen Yang , Yang Haibo , Gao Hui , Hu Chenhui , You Qing
Published: November 2022

Low field pulse nuclear magnetic resonance (LF-NMR) was used to analyze the effects of a polymeric ion retarder and the amount of acryloxyethyl trimethylammonium chloride (DMC) in the retarder on the distribution of T2, thickening property, and strength of cement paste. The effect of pressure and temperature on the thickening curve was investigated, and the hydration products were analyzed using XRD. The result shows that the wrapped water of the precipitation is the main reaction aqueous phase of cement slurry in the hydration, with short T2 time and a large relaxation peak area. The retarder weakens the van der Waals force and electrostatic adsorption force between the water and cement particles, reducing the hydration rate of cement particles. An appropriate increase in the cationic content of polymeric ion retarder can improve the early strength of cement slurry.
Energy-Efficient Network Protocols and Resilient Data Transmission Schemes for Wireless Sensor Networks—An Experimental Survey
Authors: Dhabliya Dharmesh , Soundararajan Rajasoundaran , Selvarasu Parthiban , Balasubramaniam Maruthi Shankar , Rajawat Anand Singh , Goyal S. B. , Raboaca Maria Simona , Mihaltan Traian Candin , Verma Chaman , Suciu George
Published: November 2022

Wireless sensor networks (WSNs) are considerably used for various environmental sensing applications. The architecture and internal specifications of WSNs have been chosen based on the requirements of particular applications. On this basis, WSNs consist of resource (energy and memory)-limited wireless sensor nodes. WSNs initiate data communication from source to destination via physical layer management principles, channel slot scheduling principles (time division multiple access), wireless medium access control (WMAC) protocols, wireless routing protocols and application protocols. In this environment, the development of WMAC principles, routing protocols and channel allotment schemes play crucial roles in network communication phases. Consequently, these layering functions consume more energy at each sensor node, which leads to minimal network lifetime. Even though the channel management schemes, medium control protocols and routing protocols are functionally suitable, the excessive energy consumption affects the overall network performance. In this situation, energy optimization algorithms are advised to minimize the resource wastage of WSNs during regular operations (medium control and routing process). Many research works struggle to identify the optimal energy-efficient load balancing strategies to improve WSN functions. With this in mind, the proposed article has conducted a detailed literature review and notable experimental comparisons on energy-efficient MAC protocols, channel scheduling policies and energy-efficient routing protocols. To an extent, the detailed analysis over these wireless network operations helps to understand the benefits and limitations of recent research works. In the experimental section of this article, eight existing techniques are evaluated under energy optimization strategies (WMAC, channel allocation, sleep/wake protocols, integrated routing and WMAC policies, balanced routing and cooperative routing). The proposed review and the classified technical observations collected from notable recent works have been recognized as crucial contributions. The results infer the suggestions for feasible WSN communication strategies with optimal channel management policies and routing policies. Notably, the simulation results show that cross-layer or multi-layer energy optimization policies perform better than homogeneous energy optimization models.
An Online Archimedes Optimization Algorithm Identifier-Controlled Adaptive Modified Virtual Inertia Control for Microgrids
Authors: Fawzy Asmaa , Mobarak Youssef , Osheba Dina S. , Hemeida Mahmoud G. , Senjyu Tomonobu , Roshdy Mohamed
Published: November 2022

Single widespread employment of renewable energy sources (RESs) contributes to the shortage in the inertia of the microgrid (MG). After this, frequency stability may regress as a result of power imbalance or minor load fluctuations. This paper proposes an explicit adaptive modified virtual inertia control (VIC) based on an online Archimedes optimization algorithm (AOA) identifier for MG containing thermal, wind, and solar photovoltaic power plants. The Rung Kutta approach is used to construct the proposed online identifier, which acts as a model of the MG. AOA predicts the coefficients of the online identifier based on the input and output of MG to mimic the frequency deviation of the MG online. AOA estimates online the inertia and damping coefficients of the VIC system with an energy storage device based on online AOA identifier coefficients. The frequency deviation of the MG based on the proposed explicit adaptive modified VIC is compared with the conventional VIC based on fixed parameters and the VIC system based on optimal parameters using AOA offline under mutation in loads, weather-dependent input, and MG parameters using MATLAB/Simulink software. Furthermore, the proposed explicit adaptive modified VIC based on an online AOA identifier is evaluated with the adaptive VIC system based on fuzzy logic control, which adjusts only the inertial gain online. The simulation results demonstrate the capabilities of the proposed explicit adaptive modified VIC to improve the frequency stability and enhance low-inertia islanded MGs with RESs.
Study on Carbon Emission Pathways in the Rural Areas of Guangdong Province
Authors: Tang Zhihua , Li Dianhong , Guo Huafang
Published: November 2022

In response to global warming, China has formulated the “double carbon” strategic goals of peaking carbon dioxide emissions before 2030 and reaching carbon neutrality before 2060. The problem of rural carbon emissions is often ignored due to underdeveloped industries and services. In this paper, the carbon emission pathways in the rural areas of Guangdong Province are investigated. Since energy consumption is the main source of carbon emissions, the factor analysis was used to analyze the main factors affecting rural household energy consumption and agricultural production energy consumption. Multiple linear regression was conducted to predict the rural energy consumption demand in Guangdong. Furthermore, the current situation and development trend of rural energy supply, demand and consumption structure, and the potential of renewable energy development were considered to predict carbon emissions in the rural areas of Guangdong. Moreover, the carbon emission pathways in the rural areas of Guangdong were discussed under two scenarios: the base scenario and the radical model.
Frequency Regulation of an Islanded Microgrid Using Hydrogen Energy Storage Systems: A Data-Driven Control Approach
Authors: Lee Gi-Ho , Kim Young-Jin
Published: November 2022

Hydrogen energy storage (HES) systems have recently received attention due to their potential to support real-time power balancing in a power grid. This paper proposes a data-driven model predictive control (MPC) strategy for HES systems in coordination with distributed generators (DGs) in an islanded microgrid (MG). In the proposed strategy, a data-driven model of the HES system is developed to reflect interactive operations of an electrolyzer, hydrogen tank, and fuel cell, and hence the optimal power sharing with DGs is achieved to support real-time grid frequency regulation (FR). The MG-level controller cooperates with a device-level controller of the HES system that overrides the FR support based on the level of hydrogen. Small-signal analysis is used to evaluate the contribution of FR support. Simulation case studies are also carried out to verify the accuracy of the data-driven model and the proposed strategy is effective for improving the real-time MG frequency regulation compared with the conventional PI-based strategy.
The Methods and Stands for Testing Fixed Sorbent and Sorbent Polymer Composite Materials for the Removal of Mercury from Flue Gases
Authors: Gorecki Jerzy , Macherzynski Mariusz , Chmielowiec Jacek , Borovec Karel , Wałeka Mateusz , Deng Yinyou , Sarbinowski Janusz , Pasciak Grzegorz
Published: November 2022

The most common methods of reducing mercury emissions are the use of fixed bed granular sorbents and sorbent injection. However, both of these methods have disadvantages, such as increasing the flow resistance or the need to remove the sorbent from flue gas, respectively. These disadvantages can be eliminated by using sorbents permanently bound to construction materials (fixed sorbent materials—FSMs) or mixed with construction materials (sorbent polymer composites—SPCs). The approach is unique in the world literature as well as the development of three stands and procedures enabling the testing of FSMs or SPC materials based on Tarflen as a construction material. In order to further tests of FSMs and SPCs, the system for laboratory tests and two systems for industrial tests are developed. These stands and procedures enable determination of the influence of: FSM or SPC module shapes, flue gas properties (e.g., composition, temperature, flow rate), and mercury concentration on the effectiveness of mercury removal by SPCs and FSMs. In this paper, the influence of module shapes, gas velocity, and temperature is particularly considered. In the final industrial tests, the FSM removes 99.5% Hg after 42 days and the SPC removes from 99.5% to 82.3% after 34 days.
Optimum Design and Performance Analysis of Superconducting Cable with Different Conductor Layout
Authors: Peng Sisi , Cai Chuanbing , Cai Jiaqi , Zheng Jun , Zhou Difan
Published: November 2022

Compared with the traditional cable, the high-temperature superconducting (HTS) cable has the advantages of low loss and large capacity transmission. At present, the research on HTS cables mainly focuses on the calculation of AC loss, the performance under specific working conditions and cooling system design. Relatively little research has been carried out on the basic design and overall layout optimization of the cables. In this paper, an HTS cable with a rated current of 4 kA was designed. Firstly, according to the selected superconducting cable parameters, the body design of cables with different structures was carried out and the corresponding finite element models were built. Then, the performance analysis of HTS cables with different layouts was carried out based on the proposed cable performance evaluation indicators and the CORC double-layer structure was determined as the scheme of this cable. Finally, the AC loss of the cable with this topology was calculated to be 9.81 J/m under rated conditions. The cooling system can ensure the safe operation of the cable in the rated temperature range.
Photovoltaic Power Generation Forecasting for Regional Assessment Using Machine Learning
Authors: Borunda Monica , Ramírez Adrián , Garduno Raul , Ruíz Gerardo , Hernandez Sergio , Jaramillo O. A.
Published: November 2022

Solar energy currently plays a significant role in supplying clean and renewable electric energy worldwide. Harnessing solar energy through PV plants requires problems such as site selection to be solved, for which long-term solar resource assessment and photovoltaic energy forecasting are fundamental issues. This paper proposes a fast-track methodology to address these two critical requirements when exploring a vast area to locate, in a first approximation, potential sites to build PV plants. This methodology retrieves solar radiation and temperature data from free access databases for the arbitrary division of the region of interest into land cells. Data clustering and probability techniques were then used to obtain the mean daily solar radiation per month per cell, and cells are clustered by radiation level into regions with similar solar resources, mapped monthly. Simultaneously, temperature probabilities are determined per cell and mapped. Then, PV energy is calculated, including heat losses. Finally, PV energy forecasting is accomplished by constructing the P50 and P95 estimations of the mean yearly PV energy. A case study in Mexico fully demonstrates the methodology using hourly data from 2000 to 2020 from NSRDB. The proposed methodology is validated by comparison with actual PV plant generation throughout the country.
Two-Step Pretreatment of Lignocellulosic Biomass for High-Sugar Recovery from the Structural Plant Polymers Cellulose and Hemicellulose
Authors: Sjulander Nikki , Kikas Timo
Published: November 2022

Nitrogen explosive decompression pretreatment was tested on barley straw, aspen wood, and pine wood in a two-step pretreatment approach. The two-step approach aims to avoid the uncontrolled degradation of hemicellulose during pretreatment and to recover high sugar yields from hemicellulose and cellulose. Additionally, the pretreated biomass was filtered after each pretreatment step with a fine metal sieve so that fermentation and hydrolysis inhibitors were removed. A total sugar yield of 43 g per 100 g of dry biomass was achieved from barley straw and aspen wood. For pine wood, the total sugar yield was significantly lower, with 12 g per 100 g of dry biomass. Possible reasons for this low sugar yield are the adsorption and deactivation of cellulases on softwood hemicellulose and on repolymerized lignin after pretreatment.
Fast Fault Detection and Active Isolation of Bidirectional Z-Source Circuit Breaker with Mechanical Switch
Authors: Lee Hyeon-Seung , Cho Young-Maan , Lee Kun-A , Rhee Jae-Ho
Published: November 2022

In this paper, a new design is provided so that the Z-source circuit breaker with a mechanical switch operates quickly at a low-impedance fault. When the fault occurs, the Z-source circuit breaker uses an impedance network to generate forced current zero crossing on the switch. This current zero-crossing time is not sufficient when mechanical switches are applied. In addition, since the MS switch operates through the fault detection sensor, the speed is slowed down. At a slower speed, the circuit breaker may not allow fault current isolation. To solve this problem, the Thomson coil was added to the circuit. It operates immediately in a low-impedance fault without additional fault detection devices. As a result, the faster operating speed is expected to reduce the size of the Z-source circuit breaker component and the stress of the breaker. It is mathematically analyzed and derived, and verified through simulations and experiments. The main features of the proposed model are fast detection and operation, normal-state circuit disconnect, fault current limitation, and low conduction loss.