bluuebunny/crossref_metadata_2025 huggingface dataset:
SRV Method: Lubricating Oil Screening Test for FZG
Authors: Massocchi Davide , Lattuada Marco , Chatterton Steven , Pennacchi Paolo
Published: July 2022

Governments and institutions have the following sustainable development goals: the improvement of energy efficiency and the reduction of CO2 emissions, in a “green economy” approach, have currently become the fundamental drivers that push research and development activity toward the optimization of rotating machine components in the industrial sector, with a special focus on lubrication systems too. The activity is directed towards the optimization of tribological testing methods and equipment to better discriminate the performance of lubricants in operating conditions as predictive as possible of real applications. In this context, the present paper describes the results of an experimental campaign based on the use of a well-selected linear oscillation SRV * (Schwingung, Reibung, Verschleiss) tribometer procedure as a screening of a rig test, the FZG ** (ForschungsstellefürZahnräderundGetreibebau(German:ResearchCentreforGearsandGear;UniversityofMunich;Munich,Germany)) test, leading to concrete benefits such as saving time (time duration is 76% less without mentioning visual inspection and mounting/dismounting phase) and operative costs. Four cases for the determination of the failure load stage of SRV have been defined as links to seizure and microseizure phenomena. The procedure was tested for ten oils differing in scope (gas turbine oil, turbine oil, gear oil and circulating oil). The tests have been repeated three times and a procedure was defined for repeatability (± 1 stage difference between the minimum and maximum) for nine out of ten cases a failure stage could be defined. The same oils were also tested using the FZG scuffing test, and it can be seen that the results are very comforting as follows: a good correlation with the FZG rig test has been found for eight out of ten oils.
A Task Allocation Approach of Multi-Heterogeneous Robot System for Elderly Care
Authors: Zhao Donghui , Yang Chenhao , Zhang Tianqi , Yang Junyou , Hiroshi Yokoi
Published: July 2022

Roboticized nursing technology is a significant means to implement efficient elderly care and improve their welfare. Introducing multi-heterogeneous robot systems (MHRS) and sensor networks into a smart home is a promising approach to improve the safety and acceptability of elderly care services in daily life. Among them, the energy consumption and task planning of MHRS determine nursing safety, which is particularly important in the real nursing process. Therefore, we established a novel smart home for elderly care based on seven heterogeneous nursing robots, and proposed a multi-robot task allocation (MRTA) algorithm, considering execution time and energy consumption. The whole system efficiency makes up for the functional limitations and service continuity of traditional MHRS. To realize efficiently conducted multitasks, we established an architecture with centralized task allocation center, robot alliance layer and distributed execution layer for the MHRS. The self-organizing architecture contributes to overall task allocation, communication and adaptive cooperative control between different robots. Then, to clearly describe the continuous nursing process with multiple simultaneous demands and emergency tasks, we modeled the whole nursing process with continuity, multi-priority, and interpretability. A novel MRTA algorithm with a dynamic bidding mechanism was proposed. Comprehensive experiments showed that the proposed algorithm could effectively solve the three key problems of multi-priority tasks, multi-robot safe and adaptive cooperation, and emergency task call in the scene of elderly care. The proposed architecture regarding the smart home could be applied in nursing centers, hospitals, and other places for elderly care.
Advancing Algebra Achievement Using Affordances of Classroom Connectivity Technology: The Case for Noticing through Discussion
Authors: Pape Stephen , Gunpinar Yasemin , JohnBull Ranjini , Bell Clare
Published: July 2022

This article reports on two aspects of a professional learning (PL) and research study. Twenty-five teachers participated in a two-year PL program that sought to support teachers to implement classroom connectivity technology (CCT) in their Algebra I classrooms. Students in one school who learned Algebra I with CCT outperformed their peers who learned without CCT. Therefore, we explored the classroom practices of one teacher whose students attained higher achievement. There were several aspects of this teacher’s instruction that created the context for noticing and potentially led to the significant difference in Algebra I achievement. First, we describe the foundational components of the classroom context that established the expectations for learning and lesson mini cycles that provided a consistent format for students. We discuss several components of this work that supported student noticing, including connections to prior knowledge, task analysis, and carefully curated lessons. Students’ observations were codified in the conjectures that they developed individually and in groups as well as in the summaries of the classroom engagement in several ways. The implications of these results and future research are discussed.
Unsupervised Deep Relative Neighbor Relationship Preserving Cross-Modal Hashing
Authors: Yang Xiaohan , Wang Zhen , Wu Nannan , Li Guokun , Feng Chuang , Liu Pingping
Published: July 2022

The image-text cross-modal retrieval task, which aims to retrieve the relevant image from text and vice versa, is now attracting widespread attention. To quickly respond to the large-scale task, we propose an Unsupervised Deep Relative Neighbor Relationship Preserving Cross-Modal Hashing (DRNPH) to achieve cross-modal retrieval in the common Hamming space, which has the advantages of storage and efficiency. To fulfill the nearest neighbor search in the Hamming space, we demand to reconstruct both the original intra- and inter-modal neighbor matrix according to the binary feature vectors. Thus, we can compute the neighbor relationship among different modal samples directly based on the Hamming distances. Furthermore, the cross-modal pair-wise similarity preserving constraint requires the similar sample pair have an identical Hamming distance to the anchor. Therefore, the similar sample pairs own the same binary code, and they have minimal Hamming distances. Unfortunately, the pair-wise similarity preserving constraint may lead to an imbalanced code problem. Therefore, we propose the cross-modal triplet relative similarity preserving constraint, which demands the Hamming distances of similar pairs should be less than those of dissimilar pairs to distinguish the samples’ ranking orders in the retrieval results. Moreover, a large similarity marginal can boost the algorithm’s noise robustness. We conduct the cross-modal retrieval comparative experiments and ablation study on two public datasets, MIRFlickr and NUS-WIDE, respectively. The experimental results show that DRNPH outperforms the state-of-the-art approaches in various image-text retrieval scenarios, and all three proposed constraints are necessary and effective for boosting cross-modal retrieval performance.
Estimation of Endogenous Volatility Models with Exponential Trends
Authors: Bobenrieth Juan R. A. , Bobenrieth Eugenio S. A. , Villegas Andrés F. , Wright Brian D.
Published: July 2022

Nonlinearities, exponential trends, and Euler equations are three key features of standard dynamic volatility models of speculation, economic growth, or macroeconomic fluctuations with occasionally binding constraints and endogenous state-dependent volatility. A natural way to estimate a model with all such three features could be to use the observed nonstationary data in a single step without preliminary linearization, log-linearization, or preliminary detrending. Adoption of this natural strategy confronts a serious challenge that has been neither articulated nor solved: a dichotomy in the empirical model implied by the Euler equation. This leads to a discontinuity in the regression in the limit, rendering the approaches employed in available proofs of consistency inapplicable. We characterize the problem and develop a novel method of proof of consistency and asymptotic normality. Our methodological contribution establishes a foundation for consistent estimation and hypothesis testing of nonstationary models without resorting to preliminary detrending, an a priori assumption that any trend is exactly zero, linearization, or other restrictions on the model.
Quasinormal Forms for Chains of Coupled Logistic Equations with Delay
Authors: Kashchenko Sergey
Published: July 2022

In this paper, chains of coupled logistic equations with delay are considered, and the local dynamics of these chains is investigated. A basic assumption is that the number of elements in the chain is large enough. This implies that the study of the original systems can be reduced to the study of a distributed integro–differential boundary value problem that is continuous with respect to the spatial variable. Three types of couplings of greatest interest are considered: diffusion, unidirectional, and fully connected. It is shown that the critical cases in the stability of the equilibrium state have an infinite dimension: infinitely many roots of the characteristic equation tend to the imaginary axis as the small parameter tends to zero, which characterizes the inverse of the number of elements of the chain. In the study of local dynamics in cases close to critical, analogues of normal forms are constructed, namely quasinormal forms, which are boundary value problems of Ginzburg–Landau type or, as in the case of fully connected systems, special nonlinear integro–differential equations. It is shown that the nonlocal solutions of the obtained quasinormal forms determine the principal terms of the asymptotics of solutions to the original problem from a small neighborhood of the equilibrium state.
An Improved Soft-YOLOX for Garbage Quantity Identification
Authors: Lin Junran , Yang Cuimei , Lu Yi , Cai Yuxing , Zhan Hanjie , Zhang Zhen
Published: July 2022

Urban waterlogging is mainly caused by garbage clogging the sewer manhole covers. If the amount of garbage at a sewer manhole cover can be detected, together with an early warning signal when the amount is large enough, it will be of great significance in preventing urban waterlogging from occurring. Based on the YOLOX algorithm, this paper accomplishes identifying manhole covers and garbage and building a flood control system that can automatically recognize and monitor the accumulation of garbage. This system can also display the statistical results and send early warning information. During garbage identification, it can lead to inaccurate counting and a missed detection if the garbage is occluded. To reduce the occurrence of missed detections as much as possible and improve the performance of detection models, Soft-YOLOX, a method using a new detection model for counting, was used as it can prevent the occurrence of missed detections by reducing the scores of adjacent detection frames reasonably. The Soft-YOLOX improves the accuracy of garbage counting. Compared with the traditional YOLOX, the mAP value of Soft-YOLOX for garbage identification increased from 89.72% to 91.89%.
Macroeconomic Effects of Energy Price: New Insight from Korea?
Authors: He Yugang , Lee Moongi
Published: July 2022

Under the double pressure of the Ukrainian–Russian war and the COVID-19 pandemic, the global energy crisis has also engulfed the Korean economy. Based on this context, this article examines the macroeconomic implications of energy prices, using Korea as an example. According to an empirical study using the impulse response function, the results show that an energy price shock causes a decline in production, labor supply, capital stock, and energy consumption, as well as an increase in consumption, wages, the goods price level, inflation, and the deposit interest rate. Meanwhile, variance decomposition findings indicate that the energy price shock has a greater impact on the Korean macroeconomy than other shocks. In addition, the findings of three types of robustness tests validate the reliability and accuracy of the conclusions reached in this work. In conclusion, the information presented in this study may aid Korean policymakers in implementing appropriate countermeasures against macroeconomic volatility caused by the energy price shock.
On Hilfer Generalized Proportional Nabla Fractional Difference Operators
Authors: Wang Qiushuang , Xu Run
Published: July 2022

In this paper, the Hilfer type generalized proportional nabla fractional differences are defined. A few important properties in the left case are derived and the properties in the right case are proved by Q-operator. The discrete Laplace transform in the sense of the left Hilfer generalized proportional fractional difference is explored. Furthermore, An initial value problem with the new operator and its generalized solution are considered.
Adaptive Fuzzy Tracking Control of Uncertain Nonlinear Multi-Agent Systems with Unknown Control Directions and a Dead-Zone Fault
Authors: Deng Xiongfeng , Zhang Xiyu
Published: July 2022

In this paper, a class of uncertain nonlinear multi-agent systems with unknown control directions and a dead-zone fault is addressed, where unknown control gains exist in each subsystem. In terms of the approximation characteristic of a fuzzy logic system, it is used to approximate uncertain nonlinear dynamics, and then the relevant adaptive control laws are designed. Considering the presence of unknown control directions and a dead-zone fault, the Nussbaum gain function technique is introduced to design the intermediate control law and the adaptive fuzzy control law. A theoretical analysis shows that the tracking control problem of the given multi-agent systems can be effectively solved through the application of the proposed adaptive fuzzy control law and the tracking errors can converge to a small neighborhood of zero through an adjustment of the relevant parameters. Finally, the effectiveness of the theoretical analysis results is verified by two simulation cases.
Math Can Be Visual—Teaching and Understanding Arithmetical Functions through Visualization
Authors: Svitek Szilárd , Annuš Norbert , Filip Ferdinánd
Published: July 2022

Number theory is an area of mathematics not unknown to students majoring in mathematics teaching. As early as in junior high, they may encounter basic number theory concepts such as prime numbers, multiples, divisors, or even the fundamental theorem of arithmetic—the proof of which, however, will only be included in the university curriculum of mathematics teacher students. When teaching number theory, in addition to inspiring and motivating students, it is important to have them ask the right questions. Proofs are important, but so is the proper formulation of mathematical conjectures, not to mention intuitions regarding mathematical properties and relationships. These processes are facilitated by the software used, developed to visualize functions related to number theory. Our study aims to assess the relevance of visualization in the teaching and understanding of certain arithmetic functions among mathematics teacher students. Furthermore, we aim to investigate the practical usability of our visualization software, relying on student feedback. According to our results, students found the software useful, as it helped them to discover previously unknown relationships in the examined arithmetic functions. We may conclude our software fills a niche, with student feedback indicating its usefulness.
Spatiality Sensitive Learning for Cancer Metastasis Detection in Whole-Slide Images
Authors: Zheng Haixia , Zhou Yu , Huang Xin
Published: July 2022

Metastasis detection in lymph nodes via microscopic examination of histopathological images is one of the most crucial diagnostic procedures for breast cancer staging. The manual analysis is extremely labor-intensive and time-consuming because of complexities and diversities of histopathology images. Deep learning has been utilized in automatic cancer metastasis detection in recent years. Due to the huge size of whole-slide images, most existing approaches split each image into smaller patches and simply treat these patches independently, which ignores the spatial correlations among them. To solve this problem, this paper proposes an effective spatially sensitive learning framework for cancer metastasis detection in whole-slide images. Moreover, a novel spatial loss function is designed to ensure the consistency of prediction over neighboring patches. Specifically, through incorporating long short-term memory and spatial loss constraint on top of a convolutional neural network feature extractor, the proposed method can effectively learn both the appearance of each patch and spatial relationships between adjacent image patches. With the standard back-propagation algorithm, the whole framework can be trained in an end-to-end way. Finally, the regions with high tumor probability in the resulting probability map are the metastasis locations. Extensive experiments on the benchmark Camelyon 2016 Grand Challenge dataset show the effectiveness of the proposed approach with respect to state-of-the-art competitors. The obtained precision, recall, and balanced accuracy are 0.9565, 0.9167, and 0.9458, respectively. It is also demonstrated that the proposed approach can provide more accurate detection results and is helpful for early diagnosis of cancer metastasis.
Finite Dimensional Simple Modules over Some GIM Lie Algebras
Authors: Xia Limeng , Liu Dong
Published: July 2022

GIM Lie algebras are the generalizations of Kac–Moody Lie algebras. However, the structures of GIM Lie algebras are more complex than the latter, so they have encountered many new difficulties to study their representation theory. In this paper, we classify all finite dimensional simple modules over the GIM Lie algebra Qn+1(2,1) as well as those over Θ2n+1.
A Survey on Valdivia Open Question on Nikodým Sets
Authors: López-Alfonso Salvador , López-Pellicer Manuel , Moll-López Santiago , Sánchez-Ruiz Luis M.
Published: July 2022

Let A be an algebra of subsets of a set Ω and ba(A) the Banach space of bounded finitely additive scalar-valued measures on A endowed with the variation norm. A subset B of A is a Nikodým set for ba(A) if each countable B-pointwise bounded subset M of ba(A) is norm bounded. A subset B of A is a Grothendieck set for ba(A) if for each bounded sequence μnn=1∞ in ba(A) the B-pointwise convergence on ba(A) implies its ba(A)*-pointwise convergence on ba(A). A subset B of an algebra A is a strong-Nikodým (Grothendieck) set for ba(A) if in each increasing covering {Bn:n∈N} of B there exists Bm which is a Nikodým (Grothendieck) set for ba(A). The answer of the following open question for an algebra A of subsets of a set Ω, proposed by Valdivia in 2013, has not yet been found: Is it true that if A is a Nikodým set for ba(A) then A is a strong Nikodým set for ba(A)? In this paper we surveyed some results related to this Valdivia’s open question, as well as the corresponding problem for strong Grothendieck sets. The new Propositions 1 and 3 provide more simplified proofs, particularly in their application to Theorems 1 and 2, which were the main results surveyed. Moreover, the proofs of almost all other propositions are wholly or partially original.
Hybrid Deep Learning Applied on Saudi Smart Grids for Short-Term Load Forecasting
Authors: Alrasheedi Abdullah , Almalaq Abdulaziz
Published: July 2022

Despite advancements in smart grid (SG) technology, effective load forecasting utilizing big data or large-scale datasets remains a complex task for energy management, planning, and control. The Saudi SGs, in alignment with the Saudi Vision 2030, have been envisioned as future electrical grids with a bidirectional flow of power and data. To that end, data analysis and predictive models can enhance Saudi SG planning and control via artificial intelligence (AI). Recently, many AI methods including deep learning (DL) algorithms for SG applications have been published in the literature and have shown superior time series predictions compared with conventional prediction models. Current load-prediction research for the Saudi grid focuses on identifying anticipated loads and consumptions, on utilizing limited historical data and the behavior of the load’s consumption, and on conducting shallow forecasting models. However, little scientific proof on complex DL models or real-life application has been conducted by researchers; few articles have studied sophisticated large-scale prediction models for Saudi grids. This paper proposes hybrid DL methods to enhance the outcomes in Saudi SG load forecasting, to improve problem-relevant features, and to accurately predict complicated power consumption, with the goal of developing reliable forecasting models and of obtaining knowledge of the relationships between the various features and attributes in the Saudi SGs. The model in this paper utilizes a real dataset from the Jeddah and Medinah grids in Saudi Arabia for a full year, 2021, with a one-hour time resolution. A benchmark strategy using different conventional DL methods including artificial neural network, recurrent neural network (RNN), conventional neural networks (CNN), long short-term memory (LSTM), gated recurrent unit (GRU), and different real datasets is used to verify the proposed models. The prediction results demonstrate the effectiveness of the proposed hybrid DL models, with CNN–GRU and CNN–RNN with NRMSE obtaining 1.4673% and 1.222% improvements, respectively, in load forecasting accuracy.
PCDM and PCDM4MP: New Pairwise Correlation-Based Data Mining Tools for Parallel Processing of Large Tabular Datasets
Authors: Homocianu Daniel , Airinei Dinu
Published: July 2022

The paper describes PCDM and PCDM4MP as new tools and commands capable of exploring large datasets. They select variables based on identifying the absolute values of Pearson’s pairwise correlation coefficients between a chosen response variable and any other existing in the dataset. In addition, for each pair, they also report the corresponding significance and the number of non-null intersecting observations, and all this reporting is performed in a record-oriented manner (both source and output). Optionally, using threshold values for these three as parameters of PCDM, any user can select the most correlated variables based on high magnitude, significance, and support criteria. The syntax is simple, and the tools show the exploration progress in real-time. In addition, PCDM4MP can trigger different instances of Stata, each using a distinct class of variables belonging to the same dataset and resulting after simple name filtering (first letter). Moreover, this multi-processing (MP) version overcomes the parallelization limitations of the existing parallel module, and this is accomplished by using vertical instead of horizontal partitions of large flat datasets, dynamic generation of the task pattern, tasks, and logs, all within a single execution of this second command, and the existing qsub module to automatically and continuously allocate the tasks to logical processors and thereby emulating with fewer resources a cluster environment. In addition, any user can perform further selections based on the results printed in the console. The paper contains examples of using these tools for large datasets such as the one belonging to the World Values Survey and based on a simple variable naming practice. This article includes many recorded simulations and presents performance results. They depend on different resources and hardware configurations used, including cloud vs. on-premises, large vs. small amounts of RAM and processing cores, and in-memory vs. traditional storage.
A Rare Case of Undifferentiated Pleomorphic Cardiac Sarcoma with Inflammatory Pattern
Authors: Stoica Alexandra Iulia , Harpa Marius Mihai , Banceu Cosmin Marian , Ghiragosian Claudiu , Opris Carmen Elena , Al-Hussein Hussam , Al-Hussein Hamida , Flamind Oltean Sanziana , Mezei Tibor , Mares Razvan Gheorghita , Suciu Horatiu
Published: July 2022

Cardiac undifferentiated pleomorphic sarcoma (UPS) associated with fever and inflammatory response is an extremely rare condition. Herein, we report a rare case of cardiac UPS with unusual clinical presentation and inflammatory response. A 67-year-old male complaining of progressive dyspnea and intermittent fever of unknown cause was referred to our hospital for surgical resection of a left atrial mass. Laboratory analysis showed leukocytosis (26 × 103/μL) and high C-reactive protein (CRP) levels (155.4 mg/L). Hemoculture tests and urine analysis were negative for infection. A contrast chest computed tomography revealed a mass measuring 5.5 × 4.5 cm, occupying the left atrium cavity. The patient underwent surgical excision of the mass, however, surgical margin of the resected tumor could not be evaluated, due to the multifragmented nature of the resection specimen. Postoperative CRP and leukocyte levels normalized, highlighting the relationship between the tumor and the inflammatory status. Early diagnosis is crucial for a proper management and favorable outcome, enabling patients to undergo chemotherapy and achieve complete surgical resection.
Sociodemographic Determinants in Breast Cancer Screening among Uninsured Women of West Texas
Authors: Jensen Brooke , Khan Hafiz , Layeequr Rahman Rakhshanda
Published: July 2022

Background and Objectives: Early detection through appropriate screening is key to curing breast cancer. The Access to Breast Care for West Texas (ABC4WT) program offers no-cost mammography to underserved women in West Texas. The U.S. Preventative Task Force (USPSTF) guidelines are breast cancer screening guidelines which suggest screening for all women at the age of 50 years. The focus of this study was to identify sociodemographic barriers and determinants for breast cancer screenings, as well as screening outcomes, in low income, uninsured, or under-insured communities in West Texas. Materials and Methods: The ABC4WT program’s patient database was queried from 1 November, 2018, to 1 June, 2021, for sociodemographic variables, screening history, and results to identify high-risk groups for outreach. The American College of Radiology’s risk assessment and quality assurance tool, BI-RADS (Breast Imaging-Reporting and Data System), a widely accepted lexicon and reporting schema for breast imaging, was used for risk differentiation. Results: The cancer rate for ABC4WT’s program was significantly higher than the national mean (5.1), at 23.04 per 1000 mammograms. Of the 1519 mammograms performed, women between 40 and 49 years old represented the highest percentages of BI-RADS 4 and 5 (42.0% and 28.0%, respectively; p = 0.049). This age group also received 43.7% of biopsies performed and comprised 28.6% (n = 10) of cancers diagnosed (n = 35) (p = 0.031). Additionally, participants with a monthly household income of less than USD 800/month/person were more likely to result in a cancer diagnosis (70.6%) than higher incomes (29.4%) (p = 0.021). Conclusions: These determinants most starkly impacted women 40–49 years old who would not have been screened by U.S. Preventative Services Task Force (USPSTF) guidelines. This population with increased cancer risk should be encouraged to undergo screening for breast cancer via mammography.
The Case of a 44-Year-Old Survivor of Unrepaired Tetralogy of Fallot, Right Aortic Arch and Abdominal Aortopulmonary Collateral Vessels
Authors: Ciltea Roxana , Nicula Alina Ioana , Bajdechi Mircea , Scafa-Udriste Alexandru , Rimbas Roxana , Iana Gheorghe , Vinereanu Dragos
Published: July 2022

The most common congenital cyanotic heart disease is described in the literature as the Tetralogy of Fallot. This abnormality is characterized by the presence of ventricular septal defect (VSD), obstruction of the right ventricular (RV) outflow tract, right ventricular hypertrophy, and overriding aorta. In patients with pulmonary atresia with ventricular septal defect (PA/VSD), major aortopulmonary collateral arteries (MAPCA) are common; however, although some of them do not have PA/VSD, they do have other particular anatomical variants. The case we are presenting in this article is a rare mild symptomatic adult noncorrected TOF, with preserved RV function, right aortic arch, and MAPCAs (“classic” thoracic MAPCAs but also abdominal MAPCAs). The anatomy of a complex congenital defect is well illustrated by cardiac magnetic resonance (CMR) and computer tomography angiography (CTA), and these imaging techniques are mostly used to understand the relative clinical “silence” TOF. Imaging scans thus play a key role in the evaluation of these patients, being very important to know the indications and limitations of each method, but also to learn to combine them with each other depending on the clinical picture of the patient’s presentation. Additionally, the close collaboration between clinicians and imagers is essential for a correct, complete and detailed preoperative evaluation, being subsequently essential for cardiovascular surgeons, the whole team thus deciding the best therapeutic management.
Unique Characteristics and Applications of Reverse Superior Labial Artery Island Flaps: A Case Series
Authors: Zwierz Aleksander , Masna Krystyna , Perczak Marcin , Burduk Paweł
Published: July 2022

Background: The reverse superior labial artery (rSLA) island flap can be used to reconstruct the cheek, ala, columella and vestibule of the nose when other techniques appear insufficient or impractical. The aim of this case series was to present applications of rSLA pedicle flaps in the post-ablative oncologic reconstruction of the face. Patients and Methods: Using a retrospective case-series study design, the investigators enrolled a cohort of patients undergoing procedures involving rSLA flaps treated at a Polish Otolaryngology Department for facial reconstruction after tumour excision. The main outcomes were functional and aesthetic aspects. Descriptive statistics were computed as appropriate. Results and Conclusions: The use of rSLA flaps allows surgeons to obtain a large skin island with only minimal cosmetic and functional alterations. In all of the cases in this series, the use of this pedicle flap resulted in both optimal healing and satisfactory cosmetic and functional outcomes.
Incidence of Type 1 Diabetes Mellitus and Characteristics of Diabetic Ketoacidosis in Children and Adolescents during the First Two Years of the COVID-19 Pandemic in Vojvodina
Authors: Vorgučin Ivana , Savin Marijana , Stanković Đurđina , Miljković Dejan , Ilić Tatjana , Simić Danijela , Vrebalov Mirjana , Milanović Borko , Barišić Nenad , Stojanović Vesna , Vijatov-Đurić Gordana , Koprivšek Katarina , Vilotijević-Dautović Gordana , Antić Jelena
Published: July 2022

Background and Objectives: The COVID-19 pandemic has led to significant changes globally, which has also affected patients with type 1 diabetes mellitus (T1DM). This study aimed to determine the incidence of T1DM and the characteristics of diabetic ketoacidosis (DKA) during the pandemic comparing it to pre-pandemic period. Materials and Methods: Data from patients <19 years with newly diagnosed T1DM between 1st January 2017 and 31st December 2021 from four regional centers in Vojvodina were retrospectively collected and analyzed. Results: In 2021, the highest incidence of T1DM in the last five years was recorded, 17.3/100,000. During the pandemic period (2020–2021), there were 99 new-onset T1DM, of which 42.4% presented in DKA, which is significantly higher than in the pre-pandemic period (34.1%). During the pandemic, symptom duration of T1DM lasted significantly longer than before the COVID-19 period. At the age of 10–14 years, the highest incidence of T1DM and COVID-19, the highest frequency rate of DKA, and severe DKA were observed. Conclusions: The pandemic is associated with a high incidence rate of T1DM, longer duration of symptoms of T1DM, a high frequency of DKA, and a severe DKA at diagnosis. Patients aged 10–14 years are a risk group for the occurrence of T1DM with severe clinical presentation. Additional studies are needed with a longer study period and in a wider geographical area, with data on exposure to COVID-19 infection, the permanence of new-onset T1DM, and the psychosocial impact of the pandemic.
Utility of PIVKA-II and AFP in Differentiating Hepatocellular Carcinoma from Non-Malignant High-Risk Patients
Authors: Hadi Hana , Wan Shuaib Wan Muhammad Azfar , Raja Ali Raja Affendi , Othman Hanita
Published: July 2022

Background and Objectives: We aim to compare the diagnostic performance of Protein induced by vitamin K absence-II (PIVKA-II), a biomarker for hepatocellular carcinoma (HCC), and alpha-fetoprotein (AFP) in differentiating HCC and non-malignant high-risk (NMHR) groups and to determine their cut-off values. Materials and Methods: A total of 163 patients, including 40 with HCC and 123 with NMHR (100 with liver cirrhosis and 23 with non-cirrhotic high-risk patients) were prospectively enrolled. The levels of AFP and PIVKA-II were measured, and their cut-off values were determined. We calculated and compared the areas under the receiver operating characteristic (AUROC) curves of PIVKA-II, AFP, and their combination. Results: The levels of PIVKA-II and AFP were found to be significantly higher in the HCC compared to NMHR patients (p < 0.0001). For the differentiation of HCC from NMHR, the optimal cutoff values for PIVKA-II and AFP were 36.7 mAU/mL (90% sensitivity; 82.1% specificity) and 14.2 ng/mL (75% sensitivity; 93.5% specificity), respectively. The AUROC of PIVKA-II (0.905, p < 0.0001) was higher compared to AFP (0.869, p < 0.0001), but the combination of PIVKA–II and AFP gave the highest AUROC value (0.911, p < 0.0001). However, their differences were not statistically significant (AFP vs. PIVKA; p = 0.4775, AFP vs. Combination; p = 0.3808, PIVKA vs. Combination; p = 0.2268). Conclusions: PIVKA-II and AFP showed equal performance in detecting HCC in high-risk patients. AFP as a screening marker for HCC may be adequate, and replacing or adding the PIVKA-II test in current clinical practice may be of little value.
Development and Application of Asynchronous Roll Shifting Strategy of Double Attenuation Work Roll in Hot Rolling
Authors: Li Zhaoyang , Zhou Guanyu , Yao Chihuan , Wang Shuhuan , Qi Zhi , Guo Lantian , Zhao Dingguo , He Anrui
Published: July 2022

In view of the problems of the violent crown fluctuation and unstable shape control in the endless rolling production line, the field measurement results show that the abnormal crown fluctuation is related to the shifting limit position of the work roll after the uneven wear occurs. For this reason, the asynchronous roll shifting strategy is developed, which has double attenuation of roll shifting amplitude and roll shifting step. By coupling the roll wear contour model, the roll thermal contour model and the rolls-strip integrated model, the strip crown calculation model of the whole rolling unit is established, and the causes of abnormal crown fluctuation are revealed theoretically. In addition, the simulation analysis of the important parameters of asynchronous roll shifting strategy of double attenuation working roll is made by using this model. The number of strips in a roll shifting cycle is found to be too large or too small, which is not benefited by the control of the strip crown stability due to the influence of roll wear and roll thermal crown. A rolling unit has many shifting cycles. When the roll shifting amplitude at the end of a rolling unit is smaller, which can make the amplitude difference between adjacent roll shifting cycles greater, it is easier to avoid the uneven edge wear area and to control the strip crown stability. The industrial test shows that the maximum crown fluctuation in a rolling unit decreases by 21.05%, and the maximum crown fluctuation of adjacent strips decreases by 28.57%, which significantly improves the stability of crown control.
Increasing the Efficiency of Foundry Production by Changing the Technology of Pretreatment with Quartzite
Authors: Kukartsev Viktor Alekseevich , Cherepanov Aleksandr Ivanovich , Kukartsev Vladislav Viktorovich , Tynchenko Vadim Sergeevich , Kurashkin Sergei Olegovich , Sergienko Roman Borisovich , Tynchenko Valeriya Valerievna , Bashmur Kirill Aleksandrovich
Published: July 2022

The efficiency of the production of foundry products depends on the reliable operation of the melting furnace including, therefore, the durability of its lining. The most common material adopted for the production of an acid furnace crucible lining is quartzite, in which during the pretreatment (heating to 800 °C followed by holding), a tridymite phase appears that maintains a constant volume at 840–1470 °C for a long time and provides high lining durability of 300–350 melts, but only when using melting temperature regimes not exceeding 1500 °C. However, the absence of iron scrap leads to the smelting of synthetic iron from only one steel scrap using higher melting temperatures (1550–1570 °C), which sharply reduces the lifetime of the lining to 220 melts. This work is devoted to research aimed at establishing technology for the pretreatment with the original quartzite, which ensures the formation of a phase state that successfully withstands elevated temperatures for a long time. The studies were carried out using a Bruker D8 ADVANCE diffractometer and a Shimadzu XRF-1800 X-ray wave-dispersive spectrometer. The work consisted of drying samples of the original quartzite at temperatures of 200 and 800 °C with subsequent exposure to temperatures of 200, 400, 600, 870, 1000, 1200, 1470 and 1550 °C. As a result, the conditions for pretreatment of quartzite were established, during which during its further use, a cristobalite phase can be obtained, which makes it possible manufacture a high-temperature lining that ensures its high durability. The introduction of this technology will ensure the efficiency of the production of foundry products for enterprises operating induction crucible furnaces at industrial frequency.
Probabilistic Risk Assessment for Life Extension of Turbine Engine Rotors
Authors: Carter Jace A. , Goswami Tarun
Published: July 2022

Maintaining the component service life beyond its historical limits requires the ability to accurately quantify component reliability and address the uncertainties in material responses. A probabilistic method for predicting the total fatigue life was developed and applied to determine the probability of failure of a Ti-6Al-4V turbine disk component. The total fatigue life incorporates a dual mechanism approach including the crack initiation life and propagation life while simultaneously determining the associated initial flaw sizes. A microstructure-based model was employed to address the uncertainties in material response and relate the crack initiation life with crack size. The propagation life was characterized using both small and large crack growth models to ensure accurate fatigue life prediction. Fatigue life predictions were found to correlate with experimental data at high stress levels. The risk assessment can be used to estimate the expected initial crack sizes from variability in material properties, which can further be used to establish an enhanced inspection planning.
Spatial Path Planning for Robotic Milling of Automotive Casting Components Based on Optimal Machining Posture
Authors: Wu Hao , Wang Yudi , Wei Xiaoxu , Zhu Dahu
Published: July 2022

The robotic milling of automotive casting components can effectively reduce human participation in the production process and enhance production efficiency and quality, but the premise addresses the reasonable planning of machining paths. To address major challenges, this paper proposes a spatial path planning method for the robotic milling of casting flash and burrs on an automotive engine flywheel shell based on the optimal machining posture. Firstly, an improved stereolithography slicing algorithm in arbitrary tangent plane direction is put forward, which solves the problem that the existing stereolithography slicing algorithm cannot accurately extract the contour of complex components. Secondly, the contour path curve fitting of the slicing points of the flywheel shell is realized based on the B-spline curve. Next, a machining posture evaluation function is established based on the robot’s stiffness performance, and the optimal machining posture is solved and verified with simulation according to the machining posture evaluation function and posture interpolation. Finally, the experiments indicate that the proposed method can significantly enhance the machining quality, with an average allowance height of 0.33 mm, and reduce the machining time to 9 min, compared with the conventional manual operation, both of which satisfy the machining requirements.
The Quantitative Profiling of Oxylipins from Arachidonic Acid by LC-MS/MS in Feces at Birth 3 Days and 21 Days of Piglets
Authors: Huang Ningning , Liu Xiangchen , Pei Xiaoqi , Peng Jian , Wei Hongkui
Published: July 2022

Oxylipins (also called eicosanoids) are enzymatically or nonenzymatically generated by oxidation of arachidonic acid (ARA) and are major mediators of ARA effects in the body. Previous studies demonstrated the importance of ARA in infant growth, brain development, immune response, and health. With the developments in lipidomic methodologies, it is important for exploring more ARA-deprived oxylipins to better understand the physiological functions of ARA. The concentrations of oxylipins in feces were determined from days 3 to 21 postnatally of suckling piglets in vivo. Feces were collected at two critical time points of the suckling piglets (3d and 21d after birth) and about 48 oxylipins were analyzed by using a target metabolomics approach based on Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). Here, 21 oxylipins were derived from ARA, and 11 differential oxylipins (Log2|fold change| ≥ 1.0) at birth 3d and 21d were identified. Particularly, 12-HETE was more abundant in feces at birth 3 days rather than 21 days. Considering that 12-HETE was a racemic mixture of stereoisomers containing the S and R enantiomers, we further detected the concentrations of 12(S)-HETE and 12(R)-HETE between the two time points by chiral LC-MS/MS analysis. There was no significant difference in the concentrations of 12(S)-HETE and 12(R)-HETE. It was showed that ARA - derived oxylipins might be related to the physiological changes of piglets during growing. Our results provided new information for describing the physiological changes of the piglets over the suckling period.
Metabolic Fingerprinting of Fabry Disease: Diagnostic and Prognostic Aspects
Authors: Rocchetti Maria Teresa , Spadaccino Federica , Catalano Valeria , Zaza Gianluigi , Stallone Giovanni , Fiocco Daniela , Netti Giuseppe Stefano , Ranieri Elena
Published: July 2022

Fabry disease (FD) is an X-linked lysosomal disease due to a deficiency in the activity of the lysosomal-galactosidase A (GalA), a key enzyme in the glycosphingolipid degradation pathway. FD is a complex disease with a poor genotype–phenotype correlation. In the early stages, FD could involve the peripheral nervous system (acroparesthesias and dysautonomia) and the ski (angiokeratoma), but later kidney, heart or central nervous system impairment may significantly decrease life expectancy. The advent of omics technologies offers the possibility of a global, integrated and systemic approach well-suited for the exploration of this complex disease. In this narrative review, we will focus on the main metabolomic studies, which have underscored the importance of detecting biomarkers for a diagnostic and prognostic purpose in FD. These investigations are potentially useful to explain the wide clinical, biochemical and molecular heterogeneity found in FD patients. Moreover, the quantitative mass spectrometry methods developed to evaluate concentrations of these biomarkers in urine and plasma will be described. Finally, the complex metabolic biomarker profile depicted in FD patients will be reported, which varies according to gender, types of mutations, and therapeutic treatment.
Salivary Concentrations of Chemerin, α-Defensin 1, and TNF-α as Potential Biomarkers in the Early Diagnosis of Colorectal Cancer
Authors: Waniczek Dariusz , Świętochowska Elżbieta , Śnietura Mirosław , Kiczmer Paweł , Lorenc Zbigniew , Muc-Wierzgoń Małgorzata
Published: July 2022

Colorectal cancer is one of the most prevalent cancers worldwide. There is a great interest and need to find simple, inexpensive, and minimally invasive diagnostic tests. The aim of the study was to analyze the salivary concentrations of chemerin, α-defensin 1, and TNF-α in colorectal cancer (CRC) patients and in a healthy control group. The concentration of these proteins was simultaneously determined in the serum of subjects. We also aimed to assess the correlation of these results and selected clinicopathological features. This prospective study was comprised of 39 CRC patients and 40 control group patients. Salivary and serum concentrations were determined by enzyme immunoassays. The salivary and serum concentrations of chemerin, α-defensin 1, and TNF-α were significantly higher in cancer patients compared to the control group. No correlation was found between concentrations of the proteins and the clinical stage of cancer and tumor location. The ROC curve analysis showed that although salivary concentrations of all proteins showed 100% sensitivity and 100% specificity, serum concentrations of the analyzed proteins were characterized by 100% sensitivity and over 90% specificity. The assessment of chemerin, α-defensin 1, and TNF-α concentrations in saliva seem to have great potential as quick and useful biomarkers in the early diagnosis of CRC.
Microstructure and Corrosion Resistance of LaNi5-xMgx Alloys
Authors: Giza Krystyna , Owczarek Edyta
Published: July 2022

This study analysed the corrosion parameters of LaNi5-xMgx hydrogen-absorbing alloys depending on the degree of replacement of nickel with magnesium and the exposure time of samples in a strongly alkaline solution. The microstructure and composition of the alloys were analysed using SEM and EDS, respectively. A correlation was observed between the corrosion rate and the magnesium content in the alloy and the exposure time of the investigated materials in the corrosive solution. The obtained research results showed that the LaNi5 phase, rich in Mg, corroded easily, and the presence of Mg in LaNi5-xMgx alloys became beneficial only for longer exposure times of samples in an alkaline solution. The corrosion layer formed during the contact of the magnesium alloys with the electrolyte promoted faster H2 evolution compared to the non-magnesium-substituted alloy.