bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of Carnosine Effect on Human Microglial Cells under Basal Conditions
Authors: Caruso Giuseppe , Privitera Anna , Saab Miriam Wissam , Musso Nicolò , Maugeri Salvatore , Fidilio Annamaria , Privitera Anna Provvidenza , Pittalà Alessandra , Jolivet Renaud Blaise , Lanzanò Luca , Lazzarino Giuseppe , Caraci Filippo , Amorini Angela Maria
Published: February 2023

The activity of microglia is fundamental for the regulation of numerous physiological processes including brain development, synaptic plasticity, and neurogenesis, and its deviation from homeostasis can lead to pathological conditions, including numerous neurodegenerative disorders. Carnosine is a naturally occurring molecule with well-characterized antioxidant and anti-inflammatory activities, able to modulate the response and polarization of immune cells and ameliorate their cellular energy metabolism. The better understanding of microglia characteristics under basal physiological conditions, as well as the possible modulation of the mechanisms related to its response to environmental challenges and/or pro-inflammatory/pro-oxidant stimuli, are of utmost importance for the development of therapeutic strategies. In the present study, we assessed the activity of carnosine on human HMC3 microglial cells, first investigating the effects of increasing concentrations of carnosine on cell viability. When used at a concentration of 20 mM, carnosine led to a decrease of cell viability, paralleled by gene expression increase and decrease, respectively, of interleukin 6 and heme oxygenase 1. When using the maximal non-toxic concentration (10 mM), carnosine decreased nitric oxide bioavailability, with no changes in the intracellular levels of superoxide ion. The characterization of energy metabolism of HMC3 microglial cells under basal conditions, never reported before, demonstrated that it is mainly based on mitochondrial oxidative metabolism, paralleled by a high rate of biosynthetic reactions. The exposure of HMC3 cells to carnosine seems to ameliorate microglia energy state, as indicated by the increase in the adenosine triphosphate/adenosine diphosphate (ATP/ADP) ratio and energy charge potential. The improvement of cell energy metabolism mediated by 10 mM carnosine could represent a useful protective weapon in the case of human microglia undergoing stressing conditions.
Flexural Performance of a Novel Steel Cold-Formed Beam–PSSDB Slab Composite System Filled with Concrete Material
Authors: Liejy Mohammed Chyad , Al Zand Ahmed W. , Mutalib Azrul A. , Alghaaeb Mustafa Farooq , Abdulhameed Ali A. , Al-Attar Alyaa A. , Tawfeeq Wadhah M. , Hilo Salam J.
Published: February 2023

In this study, the flexural performance of a new composite beam–slab system filled with concrete material was investigated, where this system was mainly prepared from lightweight cold-formed steel sections of a beam and a deck slab for carrying heavy floor loads as another concept of a conventional composite system with a lower cost impact. For this purpose, seven samples of a profile steel sheet–dry board deck slab (PSSDB/PDS) carried by a steel cold-formed C-purlins beam (CB) were prepared and named “composite CBPDS specimen”, which were tested under a static bending load. Specifically, the effects of the profile steel sheet (PSS) direction (parallel or perpendicular to the span of the specimen) using different C-purlins configurations (double sections connected face-to-face, double separate sections, and a single section) were investigated. The research discussed the specimens’ failure modes, flexural behavior, bending capacity, bending strain relationships, and energy absorption index of specimens. Generally, the CBPDS specimens with the PSS slab placed in a parallel direction achieved approximately a 13–40% higher bending capacity compared with the corresponding specimens with a perpendicular PSS direction (depending on the configuration of the beam). Fabricating the beam of the CBPDS specimen with double C-purlins (face-to-face) led to more effective concrete confinement behavior compared with the double separate C-purlins beam. The related specimen recorded a 10% higher bending capacity. Finally, the suggested composite CBPDS system exhibited a sufficient energy absorption capability of the static bending load because it demonstrated high strength and high ductility.
Numerical Model Calibration and a Parametric Study Based on the Out-Of-Plane Drift Capacity of Stone Masonry Walls
Authors: Misir Ibrahim Serkan , Yucel Gokhan
Published: February 2023

Failure under seismic action generally occurs in the form of out-of-plane collapses of walls before reaching their in-plane strength in historical stone masonry buildings. Consistent finite element (FE) macro modeling has emerged as a need for use in seismic assessments of these walls. This paper presents the numerical model calibration of U-shaped multi-leaf stone masonry wall specimens tested under ambient vibrations and out-of-plane (OOP) load reversals. The uncertain elastic parameters were obtained by manual calibration of the numerical models based on ambient vibration test (AVT) data of the specimens. To obtain nonlinear calibration parameters, static pushover analyses were performed on FE models simulating quasi-static tests. The calibrated numerical models matched well with the experimental results in terms of load–drift response and damage distribution. As a result, the modulus of elasticity and tensile and compressive degrading strength parameters of masonry walls were proposed. A parametric study was conducted to examine the effects of different materials and geometric properties (tensile strength, aspect ratio, slenderness ratio, and geometric scale) on the OOP behavior of stone masonry walls. A quite different strain distribution was obtained in the case of a large aspect ratio, while it was determined that the geometric scale had no effect on the strain distribution. Tensile strength was the dominant parameter affecting the load–drift response of the models. Within the presented work, a practical tool for out-of-plane seismic assessment has been proposed for the structures covered in this paper.
BIM and Digital Twin for Developing Convergence Technologies as Future of Digital Construction
Authors: Sepasgozar Samad , Khan Ayaz , Smith Kai , Romero Juan , Shen Xiaohan , Shirowzhan Sara , Li Heng , Tahmasebinia Faham
Published: February 2023

The construction industry is slow to adopt new technologies. The implementation of digital technologies and remote operations using robots were considered farfetched affairs and unbelievable approaches. However, the effect of COVID-19 on clients and construction companies put high pressure on construction managers to seek digital solutions and justified the need for remote operating or distant controlling technologies. This paper aims to investigate the state of play in construction technology implementation and presents a roadmap for developing and implementing required technologies for the construction industry. The COVID-19 disruption required new methods of working safely and remotely and coincided with the advent of advanced automation and autonomous technologies. This paper aims to identify gaps and 11 disruptive technologies that may lead to upheaval and transformation of the construction sector, perhaps in this decade. A road map for technology implementation can be helpful in developing business strategies at the organizational level as a theoretical measure, and it can facilitate the technology implementation process at the industry level as a practical measure. The roadmap can be used as a framework for policymakers to set industry or company strategies for the next 10 years (2030).
Data Cooperatives as a Catalyst for Collaboration, Data Sharing and the Digital Transformation of the Construction Sector
Authors: Bühler Michael Max , Nübel Konrad , Jelinek Thorsten , Riechert David , Bauer Thomas , Schmid Thomas , Schneider Martin
Published: February 2023

Digital federated platforms and data cooperatives for secure, trusted and sovereign data exchange will play a central role in the construction industry of the future. With the help of platforms, cooperatives and their novel value creation, the digital transformation and the degree of organization of the construction value chain can be taken to a new level of collaboration. The goal of this research project was to develop an experimental prototype for a federated innovation data platform along with a suitable exemplary use case. The prototype is to serve the construction industry as a demonstrator for further developments and form the basis for an innovation platform. It exemplifies how an overall concept is concretely implemented along one or more use cases that address high-priority industry pain points. This concept will create a blueprint and a framework for further developments, which will then be further established in the market. The research project illuminates the perspective of various governance innovations to increase industry collaboration, productivity and capital project performance and transparency as well as the overall potential of possible platform business models. However, a comprehensive expert survey revealed that there are considerable obstacles to trust-based data exchange between the key stakeholders in the industry value network. The obstacles to cooperation are predominantly not of a technical nature but rather of a competitive, predominantly trust-related nature. To overcome these obstacles and create a pre-competitive space of trust, the authors therefore propose the governance structure of a data cooperative model, which is discussed in detail in this paper.
Effect of the Deposition of Vanadium-Oxide on the Photocatalytic Activity of TiO2 Nanotubes and Its Photodiode Performance Interfaced with CH3NH3PbI3 Single Crystal
Authors: Vujančević Jelena , Andričević Pavao , Djokić Veljko , Blagojević Vladimir , Pavlović Vera P. , Ćirković Jovana , Horváth Endre , Forró László , Karoui Abdennaceur , Pavlović Vladimir B. , Janaćković Djordje
Published: February 2023

In this study, we report the influence of vanadium oxide (VO), as a photosensitive component, on the photoactivity of TiO2 nanotubes (TNTs). A series of TNTs of varying tube diameter were synthesized by the anodization of titanium foils at different voltages, while vanadium oxide was deposited on TNTs by wet chemical deposition. An improvement in the optical properties of nanotubes was observed after the deposition of vanadium oxide. An improvement in the optical properties (redshift in UV-Vis spectra) of TNTs and TNT/VO was noted. The photocatalytic activity was improved with increasing tube diameter, while it was weakened after the deposition of VO. Furthermore, photoactivity was investigated in photodiodes based on TNTs or TNT/VO and single crystals of CH3NH3PbI3. The photoelectric measurement revealed that different TNT diameters did not influence the I-V characteristic of the photodiodes, while the deposition of VO improved the photocurrent for smaller TNTs.
Cocatalysts for Photocatalytic Overall Water Splitting: A Mini Review
Authors: Tian Li , Guan Xiangjiu , Zong Shichao , Dai Anna , Qu Jingkuo
Published: February 2023

Photocatalyst overall water splitting is usually restricted by low carrier separation efficiency and a slow surface reaction rate. Cocatalysts provide a satisfactory solution to significantly improve photocatalytic performance. In this review, some recent advances in cocatalysts for photocatalytic overall water splitting are gathered and divided into groups. Firstly, the loading method of the cocatalyst is introduced. Then, the role of the cocatalyst applied for the photocatalytic overall water splitting process is further discussed. Finally, the key challenges and possible research directions of photocatalytic overall water splitting are proposed. This review is expected to promote research on the design of efficient cocatalysts in photocatalytic systems for overall water splitting.
The Role of TP53 in Adaptation and Evolution
Authors: Voskarides Konstantinos , Giannopoulou Nefeli
Published: February 2023

The TP53 gene is a major player in cancer formation, and it is considered the most important tumor suppressor gene. The p53 protein acts as a transcription factor, and it is involved in DNA repair, senescence, cell-cycle control, autophagy, and apoptosis. Beyond cancer, there is evidence that TP53 is associated with fertility, aging, and longevity. Additionally, more evidence exists that genetic variants in TP53 are associated with environmental adaptation. Special TP53 amino-acid residues or pathogenic TP53 mutations seem to be adaptive for animals living in hypoxic and cold environments or having been exposed to starvation, respectively. At the somatic level, it has recently been proven that multiple cancer genes, including TP53, are under positive selection in healthy human tissues. It is not clear why these driver mutations do not transform these tissues into cancerous ones. Other studies have shown that elephants have multiple TP53 copies, probably this being the reason for the very low cancer incidence in these large animals. This may explain the famous Peto’s paradox. This review discusses in detail the multilevel role of TP53 in adaptation, according to the published evidence. This role is complicated, and it extends from cells to individuals and to populations.
Association of the Estrogen Receptor 1 Polymorphisms rs2046210 and rs9383590 with the Risk, Age at Onset and Prognosis of Breast Cancer
Authors: Miedl Heidi , Oswald Denise , Haslinger Isabella , Gstoettner Manuela , Wenzl René , Proestling Katharina , Schneeberger Christian , Yotova Iveta , Schreiber Martin
Published: February 2023

Estrogen receptor α (ERα), encoded by the ESR1 gene, is a key prognostic and predictive biomarker firmly established in routine diagnostics and as a therapeutic target of breast cancer, and it has a central function in breast cancer biology. Genetic variants at 6q25.1, containing the ESR1 gene, were found to be associated with breast cancer susceptibility. The rs2046210 and rs9383590 single nucleotide variants (SNVs) are located in the same putative enhancer region upstream of ESR1 and were separately identified as candidate causal variants responsible for these associations. Here, both SNVs were genotyped in a hospital-based case-control study of 409 female breast cancer patients and 422 female controls of a Central European (Austrian) study population. We analyzed the association of both SNVs with the risk, age at onset, clinically and molecularly relevant characteristics and prognosis of breast cancer. We also assessed the concordances between both SNVs and the associations of each SNV conditional on the other SNV. The minor alleles of both SNVs were found to be non-significantly associated with an increased breast cancer risk. Significant associations were found in specific subpopulations, particularly in patients with an age younger than 55 years. The minor homozygotes of rs2046210 and the minor homozygotes plus heterozygotes of rs9383590 exhibited a several-years-younger age at onset than the common homozygotes, which was more pronounced in ER-positive and luminal patients. Importantly, the observed associations of each SNV were not consistently nullified upon correction for the other SNV nor upon analyses in common homozygotes for the other SNV. We conclude that both SNVs remain independent candidate causal variants.
Development and Validation of the HIV-CARDIO-PREDICT Score to Estimate the Risk of Cardiovascular Events in HIV-Infected Patients
Authors: Karanika Styliani , Karantanos Theodoros , Carneiro Herman , Assoumou Sabrina A.
Published: February 2023

Importance: Commonly used risk assessment tools for cardiovascular disease might not be accurate for HIV-infected patients. Objective: We aimed to develop a model to accurately predict the 10-year cardiovascular disease (CV) risk of HIV-infected patients. Design: In this retrospective cohort study, adult HIV-infected patients seen at Boston Medical Center between March 2012 and January 2017 were divided into model development and validation cohorts. Setting: Boston Medical Center, a tertiary, academic medical center. Participants: Adult HIV-infected patients, seen in inpatient and outpatient setting. Main Outcomes and Measures: We used logistic regression to create a prediction risk model for cardiovascular events using data from the development cohort. Using a point-based risk-scoring system, we summarized the relationship between risk factors and cardiovascular disease (CVD) risk. We then used the area under the receiver operating characteristics curve (AUC) to evaluate model discrimination. Finally, we tested the model using a validation cohort. Results: 1914 individuals met the inclusion criteria. The model had excellent discrimination for CVD risk [AUC 0.989; (95% CI: 0.986–0.993)] and included the following 11 variables: male sex (95% CI: 2.53–3.99), African American race/ethnicity (95% CI: 1.50–3.13), current age (95% CI: 0.07–0.13), age at HIV diagnosis (95% CI: −0.10–(−0.02)), peak HIV viral load (95% CI: 9.89 × 10−7–3.00 × 10−6), nadir CD4 lymphocyte count (95% CI: −0.03–(−0.02)), hypertension (95% CI: 0.20–1.54), hyperlipidemia (95% CI: 3.03–4.60), diabetes (95% CI: 0.61–1.89), chronic kidney disease (95% CI: 1.26–2.62), and smoking (95% CI: 0.12–2.39). The eleven-parameter multiple logistic regression model had excellent discrimination [AUC 0.957; (95% CI: 0.938–0.975)] when applied to the validation cohort. Conclusions and Relevance: Our novel HIV-CARDIO-PREDICT Score may provide a rapid and accurate evaluation of CV disease risk among HIV-infected patients and inform prevention measures.
Generation of Conditional Knockout Alleles for PRUNE-1
Authors: Wu Xiaoli , Simard Louise R. , Ding Hao
Published: February 2023

PRUNE1 is a member of the aspartic acid-histidine-histidine (DHH) protein superfamily, which could display an exopolyphosphatase activity and interact with multiple cellular proteins involved in the cytoskeletal rearrangement. It is widely expressed during embryonic development and is essential for embryogenesis. PRUNE1 could also be critical for postnatal development of the nervous system as it was found to be mutated in patients with microcephaly, brain malformations, and neurodegeneration. To determine the cellular function of PRUNE1 during development and in disease, we have generated conditional mouse alleles of the Prune1 in which loxP sites flank exon 6. Crossing these alleles with a ubiquitous Cre transgenic line resulted in a complete loss of PRUNE1 expression and embryonic defects identical to those previously described for Prune1 null embryos. In addition, breeding these alleles with a Purkinje cell-specific Cre line (Pcp2-Cre) resulted in the loss of Purkinje cells similar to that observed in patients carrying a mutation with loss of PRUNE1 function. Therefore, the Prune1 conditional mouse alleles generated in this study provide important genetic tools not only for dissecting the spatial and temporal roles of PRUNE1 during development but also for understanding the pathogenic role of PRUNE1 dysfunction in neurodegenerative or neurodevelopmental disease. In addition, from this work, we have described an approach that allows one to efficiently generate conditional mouse alleles based on mouse zygote electroporation.
Familial Glucocorticoid Deficiency Presenting with Tonic-Clonic Seizure: A Case Report
Authors: Alghamdi Ahmed Hassan
Published: February 2023

Introduction: Familial glucocorticoid deficiency (FGD) is a rare cause of adrenal insufficiency in children. The condition can present with features of low cortisol and high adrenocorticotropic hormone (ACTH). Late diagnosis can be associated with high morbidity and high mortality rates. Patient: The presented case was a three-year-old Saudi girl who presented with dehydration and seizures as a complication of hypoglycemia. The initial examination and investigations revealed hyperpigmentation and normal arterial blood pressure. The lab investigation and genetic study revealed hypoglycemia, metabolic acidosis, low serum cortisol: 53 nmol/L (N: 140–690 nmol/L), normal androgens: 0.65 nmol/L (N: 0.5–2.4 nmol/L) and aldosterone: 50 pgmL (N: 2–200 pg/mol), and normal serum electrolytes. The ACTH level was more than 2000 pg/mL. A genetic study indicated a homozygous likely variant in the nicotinamide nucleotide transhydrogenase (NNT) gene, consistent with a genetic diagnosis of autosomal recessive glucocorticoid deficiency type 4. No mutations were found regarding MC2R, MRAP, and TXNRD2. Intervention and outcome: The child was started on hydrocortisone, initially at 100 mg/m2/dose IV and then 100 mg/m2/day divided to q 6 hr. The dose was gradually decreased to 15 mg/m2/day PO BID, with clinical improvement and normalization of the serum ACTH level. Conclusions: The autosomal recessive glucocorticoid deficiency, a variant of FGD type 4, is a very rare condition that may lead to high rates of mortality when the diagnosis and treatment occur late. Therefore, early diagnosis and treatment is essential for good outcomes.
Adipose Stem Cells in Modern-Day Ophthalmology
Authors: Musa Mutali , Zeppieri Marco , Enaholo Ehimare S. , Salati Carlo , Parodi Pier Camillo
Published: February 2023

Stem cells (SCs) have evolved as an interesting and viable factor in ophthalmologic patient care in the past decades. SCs have been classified as either embryonic, mesenchymal, tissue-specific, or induced pluripotent cells. Multiple novel management techniques and clinical trials have been established to date. While available publications are predominantly animal-model-based, significant material is derived from human studies and case-selected scenarios. This possibility of explanting cells from viable tissue to regenerate/repair damaged tissue points to an exciting future of therapeutic options in all fields of medicine, and ophthalmology is surely not left out. Adipose tissue obtained from lipo-aspirates has been shown to produce mesenchymal SCs that are potentially useful in different body parts, including the oculo-visual system. An overview of the anatomy, physiology, and extraction process for adipose-tissue-derived stem cells (ADSC) is important for better understanding the potential therapeutic benefits. This review examines published data on ADSCs in immune-modulatory, therapeutic, and regenerative treatments. We also look at the future of ADSC applications for ophthalmic patient care. The adverse effects of this relatively novel therapy are also discussed.
Study of Ion-Assisted E-Beam Evaporation Coating Process on Chirped Mirrors
Authors: Chen Yu-Long , Wang Pei-Jen
Published: February 2023

A chirped mirror designed with 60 fs2 in group delay dispersion and reflectance large than 97.5% in the bandwidth between 700 and 900 nm by open-sourced thin film filter design software is presented. The chirped mirrors are then fabricated by an ion-assisted deposition coater. First, the optical constants of the thin films deposited by specific process parameters are calibrated by trial runs with single-layer samples measured by variable-angle spectroscopic ellipsometer; then factors are entered to compensate for the settings on film thickness. Afterward, the spectral phase of the coated mirrors is measured by polarization gating frequency-resolved optical gating whereas the reflectance is measured by photo-spectrometer. In conclusion, the measured results indicate a reasonable match with the design goals to show the effectiveness of the proposed method. It is noted that ion-assisted electron gun evaporation coating systems are applicable to the mass production of chirped mirrors employed for ultrafast lasers.
A Novel Oxidation–Reduction Route for the Morphology-Controlled Synthesis of Manganese Oxide Nanocoating as Highly Effective Material for Pseudocapacitors
Authors: Lobinsky Artem A. , Kodintzev Ilya A. , Tenevich Maxim I. , Popkov Vadim I.
Published: February 2023

In recent years, pseudocapacitors have been receiving much attention as low-cost and safe energy storage technology for emerging applications in flexible and safe devices. However, creating high-energy-density electrode materials is now the main limit for high-performance pseudocapacitors. In this work, we propose a novel reduction route for the synthesis of uniform MnO2 nanocoating with porous morphology on nickel foam via the SILD method as electrode material for high-effective pseudocapacitors. The obtained nanocoatings were characterized by SEM, TEM, EDX, XRD, XPS, and electrochemical techniques. Comparisons of MnO2 coatings were conducted to obtain the reduction and oxidative routes of synthesis. The influence of the oxidation–reduction reaction type on the structures, morphologies, and capacity performance of manganese oxide was investigated. The results show that the nanocoatings synthesized via the reduction route were formed of amorphous uniform ultra-thick coating MnO2 with a porous morphology of “nanoflakes.” Due to the unique morphology and uniform coating of nanosized manganese oxide, electrodes based on this process have shown a high specific capacity (1490 F/g at 1 A/g) and excellent cycling stability (97% capacity retention after 1000 charge–discharge cycles).
Designing Optical Coatings with Incorporated Thin Metal Films
Authors: Willey Ronald R. , Stenzel Olaf
Published: February 2023

In the world of nanomaterials and meta-materials, thin films are used which are an order of magnitude thinner than historically used in optical thin film coatings. A problem stems from the island structure that is seen as the film nucleates and grows until there is coalescence or percolation of the islands into a nearly continuous film. The application problem is that the indices of refraction, n and k, vary with thickness from zero thickness up to some thickness such as 30 or 40 nanometers for silver. This behavior will be different from material to material and deposition process to deposition process; it is hardly modeled by simple mathematical functions. It has been necessary to design with only fixed thicknesses and associated indices instead. This paper deals with a tool for the practical task of designing optical thin films in this realm of non-bulk behavior of indices of refraction; no new research is reported here. Historically, two applications are known to have encountered this problem because of their thin metal layers which are on the order of 10 nm thick: (1) architectural low emittance (Low-E) coatings on window glazing with thin silver layers, and (2) black mirrors which transmit nothing and reflect as little as possible over the visible spectrum with thin layers of chromium or related metals. The contribution reported here is a tool to remove this software limitation and model thin layers whose indices vary in thickness.
Enhancing Carsharing Experiences for Barcelona Citizens with Data Analytics and Intelligent Algorithms
Authors: Herrera Erika M. , Calvet Laura , Ghorbani Elnaz , Panadero Javier , Juan Angel A.
Published: February 2023

Carsharing practices are spreading across many cities in the world. This paper analyzes real-life data obtained from a private carsharing company operating in the city of Barcelona, Spain. After describing the main trends in the data, machine learning and time-series analysis methods are employed to better understand citizens’ needs and behavior, as well as to make predictions about the evolution of their demand for this service. In addition, an original proposal is made regarding the location of the pick-up points. This proposal is based on a capacitated dispersion algorithm, and aims at balancing two relevant factors, including scattering of pick-up points (so that most users can benefit from the service) and efficiency (so that areas with higher demand are well covered). Our aim is to gain a deeper understanding of citizens’ needs and behavior in relation to carsharing services. The analysis includes three main components: descriptive, predictive, and prescriptive, resulting in customer segmentation and forecast of service demand, as well as original concepts for optimizing parking station location.
Determining Localized Necking in Polycrystalline Sheet Metals Using the Bifurcation Phenomenon in Strain Evolution
Authors: He Ji , Feng Yishuang
Published: February 2023

The forming limit is an important failure criterion for polycrystalline sheet metals when approving the forming process. Recent developments in strain measurement technology, e.g., digital image correlation (DIC), enable the strain evolution to be captured continuously and accurately. This new technology would improve the forming limit measurements if the onset of the necking detection method was developed accordingly. This paper proposes a new method based on the bifurcation phenomenon in strain evolution to detect the onset of localized necking through DIC measurements. This detection method was inspired by a physical understanding and experimental observations of the necking phenomenon. The method eliminates the derivative calculation from the traditional method, while it can directly determine the onset of localized necking through strain evolution curves. The robustness and accuracy of the method are also investigated through experiments. Imperfection and non-defect analyses, based on non-associated and associated flow rules, were utilized and compared to the determined results. The detection method provides satisfactory forming limit results and can be used as an alternative method to determine the forming limit diagram (FLD).
Investigation of Hafnium Oxide Containing Zirconium in the Scaled Region on the Surface of As-Cast Nickel-Based Single Crystal Superalloy Turbine Blades
Authors: Park KeeHyun , Withey Paul
Published: February 2023

Surface scale is usually formed in the aerofoil part of as-cast nickel-based single crystal turbine blades by the strong interaction between the mould wall and the melt, and the subsequent oxidation of the fresh metallic surface of the casting. For better understanding of the scaling, the scaled region was investigated, and an interesting region containing hafnium oxides and a rhenium-rich particle was found. Generally, a continuous aluminium oxide layer was detected on the outer surface of the base material and covered the surface of an unscaled region. In contrast, there was no oxide on the surface of a scaled region, but it was replaced by several tiny particles remaining locally on the outer surface of the base material. SEM-EDX and TEM-EDX point analysis of these particles indicated not only the existence of high amounts of hafnium, but also several particles such as hafnium oxide, aluminium oxide, and even tiny metallic particles. Most of all, STEM-EDX point analysis clearly detected zirconium in the hafnium oxide. Furthermore, a rhenium-rich particle was also detected towards the outer surface of the base material, which suggested that the surface of the scaled region might be exposed to high enough temperatures to allow the diffusion of heavy alloying elements. Based on the observation, the formation mechanism of hafnium oxide containing zirconium and its meaning was discussed.
Combined Reporting of Surgical Quality and Cancer Control after Surgical Treatment for Penile Tumors with Inguinal Lymph Node Dissection: The Tetrafecta Achievement
Authors: Brassetti Aldo , Anceschi Umberto , Cozzi Gabriele , Chavarriaga Julian , Gavrilov Pavel , Gaya Sopena Josep Maria , Bove Alfredo Maria , Prata Francesco , Ferriero Mariaconsiglia , Mastroianni Riccardo , Misuraca Leonardo , Tuderti Gabriele , Torregiani Giulia , Covotta Marco , Camacho Diego , Musi Gennaro , Varela Rodolfo , Breda Alberto , De Cobelli Ottavio , Simone Giuseppe
Published: February 2023

Background: To optimize results reporting after penile cancer (PC) surgery, we proposed a Tetrafecta and assessed its ability to predict overall survival (OS) probabilities. Methods: A purpose-built multicenter, multi-national database was queried for stage I–IIIB PC, requiring inguinal lymphadenectomy (ILND), from 2015 onwards. Kaplan–Meier (KM) method assessed differences in OS between patients achieving Tetrafecta or not. Univariable and multivariable regression analyses identified its predictors. Results: A total of 154 patients were included in the analysis. The 45 patients (29%) that achieved the Tetrafecta were younger (59 vs. 62 years; p = 0.01) and presented with fewer comorbidities (ASA score ≥ 3: 0% vs. 24%; p < 0.001). Although indicated, ILND was omitted in 8 cases (5%), while in 16, a modified template was properly used. Although median LNs yield was 17 (IQR: 11–27), 35% of the patients had <7 nodes retrieved from the groin. At Kaplan–Maier analysis, the Tetrafecta cohort displayed significantly higher OS probabilities (Log Rank = 0.01). Uni- and multivariable logistic regression analyses identified age as the only independent predictor of Tetrafecta achievement (OR: 0.97; 95%CI: 0.94–0.99; p = 0.04). Conclusions: Our Tetrafecta is the first combined outcome to comprehensively report results after PC surgery. It is widely applicable, based on standardized and reproducible variables and it predicts all-cause mortality.
Prediction of Clinical Outcomes with Explainable Artificial Intelligence in Patients with Chronic Lymphocytic Leukemia
Authors: Hoffmann Joerg , Eminovic Semil , Wilhelm Christian , Krause Stefan W. , Neubauer Andreas , Thrun Michael C. , Ultsch Alfred , Brendel Cornelia
Published: February 2023

Background: The International Prognostic Index (IPI) is applied to predict the outcome of chronic lymphocytic leukemia (CLL) with five prognostic factors, including genetic analysis. We investigated whether multiparameter flow cytometry (MPFC) data of CLL samples could predict the outcome by methods of explainable artificial intelligence (XAI). Further, XAI should explain the results based on distinctive cell populations in MPFC dot plots. Methods: We analyzed MPFC data from the peripheral blood of 157 patients with CLL. The ALPODS XAI algorithm was used to identify cell populations that were predictive of inferior outcomes (death, failure of first-line treatment). The diagnostic ability of each XAI population was evaluated with receiver operating characteristic (ROC) curves. Results: ALPODS defined 17 populations with higher ability than the CLL-IPI to classify clinical outcomes (ROC: area under curve (AUC) 0.95 vs. 0.78). The best single classifier was an XAI population consisting of CD4+ T cells (AUC 0.78; 95% CI 0.70–0.86; p < 0.0001). Patients with low CD4+ T cells had an inferior outcome. The addition of the CD4+ T-cell population enhanced the predictive ability of the CLL-IPI (AUC 0.83; 95% CI 0.77–0.90; p < 0.0001). Conclusions: The ALPODS XAI algorithm detected highly predictive cell populations in CLL that may be able to refine conventional prognostic scores such as IPI.
Application of CRISPR/Cas9 Technology in Cancer Treatment: A Future Direction
Authors: Rabaan Ali A. , AlSaihati Hajir , Bukhamsin Rehab , Bakhrebah Muhammed A. , Nassar Majed S. , Alsaleh Abdulmonem A. , Alhashem Yousef N. , Bukhamseen Ammar Y. , Al-Ruhimy Khalil , Alotaibi Mohammed , Alsubki Roua A. , Alahmed Hejji E. , Al-Abdulhadi Saleh , Alhashem Fatemah A. , Alqatari Ahlam A. , Alsayyah Ahmed , Farahat Ramadan Abdelmoez , Abdulal Rwaa H. , Al-Ahmed Ali H. , Imran Mohd. , Mohapatra Ranjan K.
Published: February 2023

Gene editing, especially with clustered regularly interspaced short palindromic repeats associated protein 9 (CRISPR-Cas9), has advanced gene function science. Gene editing’s rapid advancement has increased its medical/clinical value. Due to its great specificity and efficiency, CRISPR/Cas9 can accurately and swiftly screen the whole genome. This simplifies disease-specific gene therapy. To study tumor origins, development, and metastasis, CRISPR/Cas9 can change genomes. In recent years, tumor treatment research has increasingly employed this method. CRISPR/Cas9 can treat cancer by removing genes or correcting mutations. Numerous preliminary tumor treatment studies have been conducted in relevant fields. CRISPR/Cas9 may treat gene-level tumors. CRISPR/Cas9-based personalized and targeted medicines may shape tumor treatment. This review examines CRISPR/Cas9 for tumor therapy research, which will be helpful in providing references for future studies on the pathogenesis of malignancy and its treatment.
Non-Invasive Retinal Imaging Modalities for the Identification of Prognostic Factors in Vitreoretinal Surgery for Full-Thickness Macular Holes
Authors: Nicolosi Cristina , Vicini Giulio , Bacherini Daniela , Giattini Dario , Lombardi Noemi , Esposito Claudio , Rizzo Stanislao , Giansanti Fabrizio
Published: February 2023

In this review, we will focus on different non-invasive retinal imaging techniques that can be used to evaluate morphological and functional features in full-thickness macular holes with a prognostic purpose. Technological innovations and developments in recent years have increased the knowledge of vitreoretinal interface pathologies by identifying potential biomarkers useful for surgical outcomes prediction. Despite a successful surgery of full-thickness macular holes, the visual outcomes are often puzzling, so the study and the identification of prognostic factors is a current topic of interest. Our review aims to provide an overview of the current knowledge on prognostic biomarkers identified in full-thickness macular holes by means of different retinal imaging tools, such as optical coherence tomography, optical coherence tomography angiography, microperimetry, fundus autofluorescence, and adaptive optics.
Molecular Imaging Diagnosis of Renal Cancer Using 99mTc-Sestamibi SPECT/CT and Girentuximab PET-CT-Current Evidence and Future Development of Novel Techniques
Authors: Tataru Octavian Sabin , Marchioni Michele , Crocetto Felice , Barone Biagio , Lucarelli Giuseppe , Del Giudice Francesco , Busetto Gian Maria , Veccia Alessandro , Lo Giudice Arturo , Russo Giorgio Ivan , Luzzago Stefano , Piccinelli Mattia Luca , Vartolomei Mihai Dorin , Musi Gennaro , Ferro Matteo
Published: February 2023

Novel molecular imaging opportunities to preoperatively diagnose renal cell carcinoma is under development and will add more value in limiting the postoperative renal function loss and morbidity. We aimed to comprehensively review the research on single photon emission computed tomography/computed tomography (SPECT/CT) and positron emission tomography computed tomography (PET-CT) molecular imaging and to enhance the urologists’ and radiologists’ knowledge of the current research pattern. We identified an increase in prospective and also retrospective studies that researched to distinguish between benign and malignant lesions and between different clear cell renal cell carcinoma subtypes, with small numbers of patients studied, nonetheless with excellent results on specificity, sensitivity and accuracy, especially for 99mTc-sestamibi SPECT/CT that delivers quick results compared to a long acquisition time for girentuximab PET-CT, which instead gives better image quality. Nuclear medicine has helped clinicians in evaluating primary and secondary lesions, and has lately returned with new and exciting insights with novel radiotracers to reinforce its diagnostic potential in renal carcinoma. To further limit the renal function loss and post-surgery morbidity, future research is mandatory to validate the results and to clinically implement the diagnostic techniques in the context of precision medicine.
Correction: Vargas et al. Solving Schrödinger Bridges via Maximum Likelihood. Entropy 2021, 23, 1134
Authors: Vargas Francisco , Thodoroff Pierre , Lamacraft Austen , Lawrence Neil
Published: February 2023

In the original publication [...]
A Novel Approach to Parameter Determination of the Continuous Spontaneous Localization Collapse Model
Authors: Piscicchia Kristian , Porcelli Alessio , Bassi Angelo , Bazzi Massimiliano , Bragadireanu Mario , Cargnelli Michael , Clozza Alberto , De Paolis Luca , Del Grande Raffaele , Derakhshani Maaneli , Lajos Diósi , Donadi Sandro , Guaraldo Carlo , Iliescu Mihai , Laubenstein Matthias , Manti Simone , Marton Johann , Miliucci Marco , Napolitano Fabrizio , Scordo Alessandro , Sgaramella Francesco , Sirghi Diana Laura , Sirghi Florin , Vazquez Doce Oton , Zmeskal Johann , Curceanu Catalina
Published: February 2023

Models of dynamical wave function collapse consistently describe the breakdown of the quantum superposition with the growing mass of the system by introducing non-linear and stochastic modifications to the standard Schrödinger dynamics. Among them, Continuous Spontaneous Localization (CSL) was extensively investigated both theoretically and experimentally. Measurable consequences of the collapse phenomenon depend on different combinations of the phenomenological parameters of the model—the strength λ and the correlation length rC—and have led, so far, to the exclusion of regions of the admissible (λ−rC) parameters space. We developed a novel approach to disentangle the λ and rC probability density functions, which discloses a more profound statistical insight.
Unsupervised Embedding Learning for Large-Scale Heterogeneous Networks Based on Metapath Graph Sampling
Authors: Zhong Hongwei , Wang Mingyang , Zhang Xinyue
Published: February 2023

How to learn the embedding vectors of nodes in unsupervised large-scale heterogeneous networks is a key problem in heterogeneous network embedding research. This paper proposes an unsupervised embedding learning model, named LHGI (Large-scale Heterogeneous Graph Infomax). LHGI adopts the subgraph sampling technology under the guidance of metapaths, which can compress the network and retain the semantic information in the network as much as possible. At the same time, LHGI adopts the idea of contrastive learning, and takes the mutual information between normal/negative node vectors and the global graph vector as the objective function to guide the learning process. By maximizing the mutual information, LHGI solves the problem of how to train the network without supervised information. The experimental results show that, compared with the baseline models, the LHGI model shows a better feature extraction capability both in medium-scale unsupervised heterogeneous networks and in large-scale unsupervised heterogeneous networks. The node vectors generated by the LHGI model achieve better performance in the downstream mining tasks.
Visual Sorting of Express Packages Based on the Multi-Dimensional Fusion Method under Complex Logistics Sorting
Authors: Ren Chuanxiang , Ji Haowei , Liu Xiang , Teng Juan , Xu Hui
Published: February 2023

Visual sorting of express packages is faced with many problems such as the various types, complex status, and the changeable detection environment, resulting in low sorting efficiency. In order to improve the sorting efficiency of packages under complex logistics sorting, a multi-dimensional fusion method (MDFM) for visual sorting in actual complex scenes is proposed. In MDFM, the Mask R-CNN is designed and applied to detect and recognize different kinds of express packages in complex scenes. Combined with the boundary information of 2D instance segmentation from Mask R-CNN, the 3D point cloud data of grasping surface is accurately filtered and fitted to determining the optimal grasping position and sorting vector. The images of box, bag, and envelope, which are the most common types of express packages in logistics transportation, are collected and the dataset is made. The experiments with Mask R-CNN and robot sorting were carried out. The results show that Mask R-CNN achieves better results in object detection and instance segmentation on the express packages, and the robot sorting success rate by the MDFM reaches 97.2%, improving 2.9, 7.5, and 8.0 percentage points, respectively, compared to baseline methods. The MDFM is suitable for complex and diverse actual logistics sorting scenes, and improves the efficiency of logistics sorting, which has great application value.
DOA Estimation Based on Convolutional Autoencoder in the Presence of Array Imperfections
Authors: Chang Dah-Chung , Liu Yan-Ting
Published: February 2023

Array imperfections may exist in an antenna system subject to non-ideal design and practical limitations. It is difficult to accurately model array imperfections, and thus complicated algorithms are usually inevitable for model-based methods to estimate the direction of arrival (DOA) with imperfect arrays. Deep neural network (DNN)-based methods do not need to rely on pre-modeled antenna array geometries, and have been explored to handle flawed array models because of their better flexibility than model-based methods. The DNN autoencoder (DAE) method has been proposed for the array imperfection problem, which decomposes the input into multiple components in different spatial subregions. These components have more concentrated distributions than the original input, which avoid a large number of connections and nodes used in the layers to realize DOA estimation classifiers. In this paper, we study the convolutional AE (CAE) method that substantially focuses on the learning of local features in a different manner from the previous DAE method. The advantage of the convolutional operation using a kernel in CAE is to capture features in a more efficient manner than the DAE, and thus be able to reduce the number of parameters that are required to be trained in the neural networks. From the numerical evaluation of DOA estimation accuracy, the proposed CAE method is also more resistant to the noise effect than the DAE method such that the CAE method has better accuracy at a lower signal-to-noise ratio.
Sign Language Gesture Recognition and Classification Based on Event Camera with Spiking Neural Networks
Authors: Chen Xuena , Su Li , Zhao Jinxiu , Qiu Keni , Jiang Na , Zhai Guang
Published: February 2023

Sign language recognition has been utilized in human–machine interactions, improving the lives of people with speech impairments or who rely on nonverbal instructions. Thanks to its higher temporal resolution, less visual redundancy information and lower energy consumption, the use of an event camera with a new dynamic vision sensor (DVS) shows promise with regard to sign language recognition with robot perception and intelligent control. Although previous work has focused on event camera-based, simple gesture datasets, such as DVS128Gesture, event camera gesture datasets inspired by sign language are critical, which poses a great impediment to the development of event camera-based sign language recognition. An effective method to extract spatio-temporal features from event data is significantly desired. Firstly, the event-based sign language gesture datasets are proposed and the data have two sources: traditional sign language videos to event stream (DVS_Sign_v2e) and DAVIS346 (DVS_Sign). In the present dataset, data are divided into five classification, verbs, quantifiers, position, things and people, adapting to actual scenarios where robots provide instruction or assistance. Sign language classification is demonstrated in spike neuron networks with a spatio-temporal back-propagation training method, leading to the best recognition accuracy of 77%. This work paves the way for the combination of event camera-based sign language gesture recognition and robotic perception for the future intelligent systems.