bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectively Combining Risk Evaluation Metrics for Precise Fault Localization
Authors: Ajibode Adekunle , Shu Ting , Gulsher Laghari , Ding Zuohua
Published: October 2022

Spectrum-based fault localization (SBFL) is an automated fault localization technique that uses risk evaluation metrics to compute the suspiciousness scores from program spectra. Thus, risk evaluation metrics determine the technique’s performance. However, the existing experimental studies still show no optimal metric for different program structures and error types. It is possible to further optimize SBFL’s performance by combining different metrics. Therefore, this paper effectively explores the combination of risk evaluation metrics for precise fault localization. Based on extensive experiments using 92 faults from SIR and 357 faults from Defects4J repositories, we highlight what and which risk evaluation metrics to combine to maximize the efficiency and accuracy of fault localization. The experimental results show that combining risk evaluation metrics with high negative correlation values can improve fault localization effectiveness. Similarly, even though the combination of positively correlated effective risk evaluation metrics can outperform most negatively correlated non-effective ones, it still cannot improve the fault localization effectiveness. Furthermore, low-correlated risk evaluation metrics should also be considered for fault localization. The study concluded that getting highly negatively correlated risk evaluation metrics is almost impossible. The combination of such risk evaluation metrics would improve fault localization accuracy.
Residual Information in Deep Speaker Embedding Architectures
Authors: Stan Adriana
Published: October 2022

Speaker embeddings represent a means to extract representative vectorial representations from a speech signal such that the representation pertains to the speaker identity alone. The embeddings are commonly used to classify and discriminate between different speakers. However, there is no objective measure to evaluate the ability of a speaker embedding to disentangle the speaker identity from the other speech characteristics. This means that the embeddings are far from ideal, highly dependent on the training corpus and still include a degree of residual information pertaining to factors such as linguistic content, recording conditions or speaking style of the utterance. This paper introduces an analysis over six sets of speaker embeddings extracted with some of the most recent and high-performing deep neural network (DNN) architectures, and in particular, the degree to which they are able to truly disentangle the speaker identity from the speech signal. To correctly evaluate the architectures, a large multi-speaker parallel speech dataset is used. The dataset includes 46 speakers uttering the same set of prompts, recorded in either a professional studio or their home environments. The analysis looks into the intra- and inter-speaker similarity measures computed over the different embedding sets, as well as if simple classification and regression methods are able to extract several residual information factors from the speaker embeddings. The results show that the discriminative power of the analyzed embeddings is very high, yet across all the analyzed architectures, residual information is still present in the representations in the form of a high correlation to the recording conditions, linguistic contents and utterance duration. However, we show that this correlation, although not ideal, could still be useful in downstream tasks. The low-dimensional projections of the speaker embeddings show similar behavior patterns across the embedding sets with respect to intra-speaker data clustering and utterance outlier detection.
Basic Contractions of Suzuki-Type on Quasi-Metric Spaces and Fixed Point Results
Authors: Romaguera Salvador
Published: October 2022

This paper deals with the question of achieving a suitable extension of the notion of Suzuki-type contraction to the framework of quasi-metric spaces, which allows us to obtain reasonable fixed point theorems in the quasi-metric context. This question has no an easy answer; in fact, we here present an example of a self map of Smyth complete quasi-metric space (a very strong kind of quasi-metric completeness) that fulfills a simple and natural contraction of Suzuki-type but does not have fixed points. Despite it, we implement an approach to obtain two fixed point results, whose validity is supported with several examples. Finally, we present a general method to construct non-T1 quasi-metric spaces in such a way that it is possible to systematically generate non-Banach contractions which are of Suzuki-type. Thus, we can apply our results to deduce the existence and uniqueness of solution for some kinds of functional equations which is exemplified with a distinguished case.
Dynamic Scheduling Strategy for Shared Agricultural Machinery for On-Demand Farming Services
Authors: Ma Li , Xin Minghan , Wang Yi-Jia , Zhang Yanjiao
Published: October 2022

With the development of the “Internet +” model and the sharing economy model, the “online car-hailing” operation model has promoted the emergence of “online-hailing agricultural machinery”. This new supply and demand model of agricultural machinery has brought greater convenience to the marketization of agricultural machinery services. However, although this approach has solved the use of some agricultural machinery resources, it has not yet formed a scientific and systematic scheduling model. Referring to the existing agricultural machinery scheduling modes and the actual demand of agricultural production, based on the idea of resource sharing, in this research, the soft and hard time windows were combined to carry out the research on the dynamic demand scheduling strategy of agricultural machinery. The main conclusions obtained include: (1) Based on the ideas of order resource sharing and agricultural machinery resource sharing, a general model of agricultural machinery scheduling that meet the dynamic needs was established, and a more scientific scheduling plan was proposed; (2) Based on the multi-population coevolutionary genetic algorithm, the dynamic scheduling scheme for shared agricultural machinery for on-demand farming services was obtained, which can reasonably insert the dynamic orders on the basis of the initial scheduling scheme, and realize the timely response to farmers’ operation demands; (3) By comparing with the actual production situation, the path cost and total operating cost were saved, thus the feasibility and effectiveness of the scheduling model were clarified.
Convergence Criteria of a Three-Step Scheme under the Generalized Lipschitz Condition in Banach Spaces
Authors: Saxena Akanksha , Jaiswal Jai Prakash , Pardasani Kamal Raj , Argyros Ioannis K.
Published: October 2022

In the given study, we investigate the three-step NTS’s ball convergence for solving nonlinear operator equations with a convergence order of five in a Banach setting. A nonlinear operator’s first-order derivative is assumed to meet the generalized Lipschitz condition, also known as the κ-average condition. Furthermore, several theorems on the convergence of the same method in Banach spaces are developed with the conditions that the derivative of the operators must satisfy the radius or center-Lipschitz condition with a weak κ-average and that κ is a positive integrable but not necessarily non-decreasing function. This novel approach allows for a more precise convergence analysis even without the requirement for new circumstances. As a result, we broaden the applicability of iterative approaches. The theoretical results are supported further by illuminating examples. The convergence theorem investigates the location of the solution ϵ* and the existence of it. In the end, we achieve weaker sufficient convergence criteria and more specific knowledge on the position of the ϵ* than previous efforts requiring the same computational effort. We obtain the convergence theorems as well as some novel results by applying the results to some specific functions for κ(u). Numerical tests are carried out to corroborate the hypotheses established in this work.
Fast Algorithms for Estimating the Disturbance Inception Time in Power Systems Based on Time Series of Instantaneous Values of Current and Voltage with a High Sampling Rate
Authors: Senyuk Mihail , Beryozkina Svetlana , Gubin Pavel , Dmitrieva Anna , Kamalov Firuz , Safaraliev Murodbek , Zicmane Inga
Published: October 2022

The study examines the development and testing of algorithms for disturbance inception time estimation in a power system using instantaneous values of current and voltage with a high sampling rate. The algorithms were tested on both modeled and physical data. The error of signal extremum forecast, the error of signal form forecast, and the signal value at the so-called joint point provided the basis for the suggested algorithms. The method of tuning for each algorithm was described. The time delay and accuracy of the algorithms were evaluated with varying tuning parameters. The algorithms were tested on the two-machine model of a power system in Matlab/Simulink. Signals from emergency event recorders installed on real power facilities were used in testing procedures. The results of this study indicated a possible and promising application of the suggested methods in the emergency control of power systems.
Age-Dependent Survival Rates in SIR-SI Dengue Transmission Model and Its Application Considering Human Vaccination and Wolbachia Infection in Mosquitoes
Authors: Supriatna Asep K. , Husniah Hennie , Soewono Edy , Ghosh Bapan , Purwanto Yedhi , Nurlaelah Elah
Published: October 2022

In this paper, an SIR-SI mathematical model in the form of a system of integral equations describing the transmission of dengue disease between human and mosquitoes is proposed and analyzed. Age-dependent functions are used to describe the survival of individuals in human and mosquito populations. The basic reproduction number is derived and its relationship to the equilibria is also explored. The results show that the existence of the positive endemic equilibrium is determined by a threshold number. This threshold number is also the same one that determines the global stability of the equilibrium. The threshold acts like the known basic reproduction number in the counterpart differential equations model and also follows the same rule for the critical level of intervention. Furthermore, as an application, the effect of wolbachia infection is explored, such as how this infection changes the resulting threshold and what the consequence of its presence is in the dynamics of the disease. In this case, the decrease of the mosquitoes’ life expectancy and biting rate are used to reflect the effect of wolbachia bacterial infection on the mosquitoes. In other words, a mosquito which is infected by wolbachia has a lower life expectancy than a normal mosquito. The results, both from mathematical analysis and numerical examples, show that the presence of wolbachia has the potential as a biological control agent to eliminate the dengue in the human population. A comparison of the wolbachia introduction into the mosquito population with the existing strategy, such as vaccination, is also presented.
Intelligent Bearing Fault Diagnosis Based on Open Set Convolutional Neural Network
Authors: Zhang Bo , Zhou Caicai , Li Wei , Ji Shengfei , Li Hengrui , Tong Zhe , Ng See-Kiong
Published: October 2022

Traditional data-driven intelligent fault diagnosis methods have been successfully developed under the closed set assumption (CSA). CSA-based fault diagnosis assumes that the fault types in the test set are consistent with that in the training set, which can achieve high accuracy, but this is generally not valid in real-world industrial applications where the collection of data in industrial applications is often limited. As it is unrealistic to assume that the training set will cover all fault types, the application of the fault classifier may fail when the test set contains unknown fault types because the probability of input samples belonging to unknown types cannot be obtained. To solve the problem of how unknown fault types may be accurately identified, this paper further studies the open set assumption (OSA) fault diagnosis. We propose an open set convolutional neural network (OS-CNN) method and apply our OS-CNN model to an improved OpenMax method as a deep network to accurately detect unknown fault types. The overall performance was significantly improved as our OS-CNN model was able to effectively tighten the boundary of known classes and limit the open-space risk for the OpenMax method based on distance modeling. The overall effectiveness of the proposed method was verified by experimental studies based on four different bearing datasets. Compared with state-of-the-art OSA fault diagnosis method, our method cannot only realize the correct classification of the known fault classes, but it can also accurately detect the unknown fault classes.
Carbon Source Influences Antioxidant, Antiglycemic, and Antilipidemic Activities of Haloferax mediterranei Carotenoid Extracts
Authors: Giani Micaela , Gervasi Luigia , Loizzo Monica Rosa , Martínez-Espinosa Rosa María
Published: October 2022

Haloarchaeal carotenoids have attracted attention lately due to their potential antioxidant activity. This work studies the effect of different concentrations of carbon sources on cell growth and carotenoid production. Carotenoid extract composition was characterized by HPLC-MS. Antioxidant activity of carotenoid extracts obtained from cell cultures grown under different nutritional conditions was determined by 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and 1,1-diphenyl-2-picrylhydrazyl (DPPH), Ferric Reducing Ability Power (FRAP) and β-carotene bleaching assays. The ability of these carotenoid extracts to inhibit α-glucosidase, α-amylase, and lipase enzymes was also assessed to determine if they could be used to reduce blood glucose and lipid absorption. The maximum production of carotenoids (92.2 µg/mL) was observed combining 12.5% inorganic salts and 2.5% of glucose/starch. Antioxidant, hypoglycemic, and antilipidemic studies showed that higher carbon availability in the culture media leads to changes in the extract composition, resulting in more active haloarchaeal carotenoid extracts. Carotenoid extracts obtained from high-carbon-availability cell cultures presented higher proportions of all-trans-bacterioruberin, 5-cis-bacterioruberin, and a double isomeric bacterioruberin, whereas the presence 9-cis-bacterioruberin and 13-cis-bacterioruberin decreased. The production of haloarchaeal carotenoids can be successfully optimized by changing nutritional conditions. Furthermore, carotenoid composition can be altered by modifying carbon source concentration. These natural compounds are very promising in food and nutraceutical industries.
Evaluation of Blood Intercellular Adhesion Molecule-1 (ICAM-1) Level in Obstructive Sleep Apnea: A Systematic Review and Meta-Analysis
Authors: Imani Mohammad Moslem , Sadeghi Masoud , Gholamipour Mohammad Amir , Brühl Annette Beatrix , Sadeghi-Bahmani Dena , Brand Serge
Published: October 2022

Background and objective: Intercellular adhesion molecule-1 (ICAM-1) appears to be an active and important biomarker for decreasing the risk of cardiovascular issues among individuals with obstructive sleep apnea (OSA). Herein, a systematic review and meta-analysis was designed to probe whether plasma/serum ICAM-1levels are different in adults with OSA compared to adults with no OSA, as well as adults with severe OSA compared to adults with mild/moderate OSA. Materials and methods: A thorough and systematic literature search was performed in four databases (PubMed/Medline, Web of Science, Scopus, and Cochrane Library) until 17 July 2022, without any age and sample size restrictions to retrieve the relevant articles. The standardized mean difference (SMD) along with a 95% confidence interval (CI) of plasma/serum of ICAM-1 levels was reported. Analyses, including sensitivity analysis, subgroup analysis, trial sequential analysis, meta-regression, and a funnel plot analysis, were performed in the pooled analysis. Results: A total of 414 records were identified in the databases, and 17 articles including 22 studies were entered into the meta-analysis. The pooled SMD of serum/plasma ICAM-1 levels in adults with OSA compared to controls was 2.00 (95%CI: 1.41, 2.59; p < 0.00001). The pooled SMD of serum/plasma ICAM-1 levels in adults with severe compared to mild/moderate OSA was 3.62 (95%CI: 1.74, 5.51; p = 0.0002). Higher serum/plasma ICAM-1 levels were associated with a higher mean age of controls, higher scores for the apnea-hypopnea index, and with a lower mean age of adults with OSA and with smaller sample sizes. Conclusions: Th results of the present meta-analysis showed that serum/plasma ICAM-1 levels in adults with OSA was higher than serum/plasma ICAM-1 levels in controls. Similarly, serum/plasma ICAM-1 levels in adults with severe OSA were higher compared to serum/plasma ICAM-1 levels of adults with mild or moderate OSA. Therefore, ICAM-1 may be used as an additional diagnostic and therapeutic biomarker in adults with OSA.
Headache in Post-COVID-19 Patients: Its Characteristics and Relationship with the Quality of Life
Authors: Mutiawati Endang , Kusuma Hendrix Indra , Fahriani Marhami , Harapan Harapan , Syahrul Syahrul , Musadir Nasrul
Published: October 2022

Little is known on the characteristics of headaches associated with coronavirus disease 2019 (COVID-19) in Indonesia. The objective of this study was to describe the characteristics of headache in post-COVID-19 patients, and its impact on the patients’ quality of life (QoL), as well as to determine the associated determinants of the poor QoL. A cross-sectional study was conducted in Banda Aceh, Indonesia. The demographic characteristics, clinical symptoms of COVID-19, characteristics of headache, and the QoL were collected and assessed. Headache was diagnosed and characterized using the International Classification of Headache Disorders, version 3 (ICHD-3). QoL was assessed using a Short Form 36 Health Survey (SF-36) tool. A logistic regression model was used to investigate the associated determinants of poor QoL in post-COVID-19 patients. A total of 215 post-COVID-19 patients were included in the final analysis, and 21.4% (46/215) of them had a poor QoL due to headache following COVID-19. Those who were unemployed and who contracted COVID-19 less than three months prior to the study had higher odds of having poor QoL compared to those who were employed and who contracted COVID-19 more than three months prior to the study. Low QoL was also related to headache that occurred less than one month after recovering from COVID-19 (compared to that which occurred longer than one month after); had a high frequency; had a combination sensation of pulsating, pressing, fiery, and stabbing pain; had a high severity score; and had additional symptoms accompanying the headache. In conclusion, headache related to COVID-19 is associated with low QoL among post-COVID-19 patients. A guideline on prevention measures of headache on COVID-19 patients, therefore, needs to be established to avoid long-term consequences.
Inflammatory Biomarkers as Prognostic Factors of Acute Deep Vein Thrombosis Following the Total Knee Arthroplasty
Authors: Melinte Răzvan , Arbănași Emil , Blesneac Adrian , Zolog Dan , Kaller Réka , Mureșan Adrian , Arbănași Eliza , Melinte Ioana , Niculescu Raluca , Russu Eliza
Published: October 2022

Background and objectives: Deep vein thrombosis (DVT) is one of the most serious post-operative complications in the case of total knee arthroplasty (TKA). This study aims to verify the predictive role of inflammatory biomarkers [monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), platelets-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI)] in acute DVT following TKA. Materials and methods: The present study was designed as an observational, analytical, retrospective cohort study and included all patients over 18 years of age with surgical indications for TKA, admitted to the Department of Orthopedics, Regina Maria Health Network, Targu Mures, Romania, and the Department of Orthopedics, Humanitas MedLife Hospital, Cluj-Napoca, Romania between January 2017 and July 2022. The primary endpoint was the risk of acute DVT following the TKA, and the secondary endpoint was the length of hospital stay, and the outcomes were stratified for the baseline’s optimal MLR, NLR, PLR, SII, SIRI, and AISI cut-off value. Results: DVT patients were associated with higher age (p = 0.01), higher incidence of cardiac disease [arterial hypertension (p = 0.02), atrial fibrillation (p = 0.01)], malignancy (p = 0.005), as well as risk factors [smoking (p = 0.03) and obesity (p = 0.02)]. Multivariate analysis showed a high baseline value for all hematological ratios: MLR (OR: 11.06; p < 0.001), NLR (OR: 10.15; p < 0.001), PLR (OR: 12.31; p < 0.001), SII (OR: 18.87; p < 0.001), SIRI (OR: 10.86; p < 0.001), and AISI (OR: 14.05; p < 0.001) was an independent predictor of DVT after TKA for all recruited patients. Moreover, age above 70 (OR: 2.96; p = 0.007), AH (OR: 2.93; p = 0.02), AF (OR: 2.71; p = 0.01), malignancy (OR: 3.98; p = 0.002), obesity (OR: 2.34; p = 0.04), and tobacco (OR: 2.30; p = 0.04) were all independent predictors of DVT risk. Conclusions: Higher pre-operative hematological ratios MLR, NLR, PLR, SII, SIRI, and AISI values determined before operations strongly predict acute DVT following TKA. Moreover, age over 70, malignancy, cardiovascular disease, and risk factors such as obesity and tobacco were predictive risk factors for acute DVT.
The Value of Myocardium and Kidney Histopathological and Immunohistochemical Findings in Accidental Hypothermia-Related Fatalities
Authors: Hleșcu Andreea Alexandra , Grigoraș Adriana , Covatariu Gabriela , Moscalu Mihaela , Amalinei Cornelia
Published: October 2022

Background and Objectives: The post-mortem diagnosis of hypothermia is challenging in forensics. The aim of our study was to detect the kidney and heart histopathological changes that occurred in a group of hypothermia-related fatalities. Materials and Methods: The cohort included 107 cases identified in the database of our department between 2007 and 2021, which have been associated with extreme cold stress. Demographic and clinicopathological data were collected from the medico-legal reports. Archived tissue samples were evaluated to identify the histopathological features, in routine haematoxylin-eosin (H&E), Periodic acid-Schiff (PAS), and Masson’s trichrome stainings, while cardiac sirtuin1 (SIRT1) and renal ubiquitin (Ub) immunostaining have been performed. Results: The majority of cases exposed to low temperatures were males (76%) from rural regions (68.2%) during the cold season. Paradoxical undressing was documented in 9.3% of cases. The common comorbidities included alcoholism (50.5%), neuropsychiatric diseases (10.3%), diabetes mellitus (3.7%), and lung tuberculosis (4.7%). The microscopic heart exam revealed areas of myocardial degeneration (100%), contraction bands (95.3%), fatty change (13.1%) and focal wavy contractile myocardial cells. Basal vacuolisation of renal tubular epithelial cells (Armanni-Ebstein lesions) (21.5%), focal tubular necrosis (7.5%), tubular renal cysts (7.5%), interstitial haemorrhages (5.6%), diabetic kidney disease (3.7%), background benign nephroangiosclerosis (42.1%), variable thickening of tubules and corpuscles basement membranes, capsular space amorphous material, and intratubular casts were identified in kidney tissue samples. Myocardial cells displayed SIRT1 weak expression, with a loss of immunopositivity correlated with areas with contraction bands, while a variable Ub expression was observed in renal corpuscles capsules, proximal, distal, and collecting renal tubules, Henle’s loops, urothelium, and intratubular casts. Conclusions: In the context of the current concept that death associated with hypothermia is still a diagnosis of exclusion, our findings suggest that the microscopic exam provides relevant data that support the diagnosis of hypothermia-related fatalities in appropriate circumstances of death. A deeper insight into the histopathologic findings in hypothermic patients may lead to new therapeutic approaches in these cases.
Reduced Low–Pressure Membrane Fouling by Inline Coagulation Pretreatment for a Colored River Water
Authors: Ladouceur Joseph D. , Narbaitz Roberto M.
Published: October 2022

Drinking water treatment (DWT) using low–pressure membranes (LPM) has become increasingly popular due to their many reported advantages compared to conventional technologies. Productivity decline due to fouling has prevented LPMs from becoming the technology of choice in DWT, however, coagulation pretreatment either with or without particle separation mitigates fouling phenomena. The effectiveness of coagulation/flocculation/sedimentation (CF–S), coagulation/flocculation/dissolved air flotation (CF–DAF), and inline coagulation (CF–IN) as technologies for pretreatment of feed water has rarely been investigated using the same water source. In this study, CF–S, CF–DAF, and CF–IN are directly compared as pretreatment of a tubular multi–channeled ultrafiltration (UF) membrane using the same highly colored river water. Three–day long filtration tests were performed using an automated bench–scale filtration apparatus with an inside–out configuration. Although CF–DAF had the greatest removal of dissolved organic matter (DOM) and hydrophobic organics, CF–S pretreatment resulted in a similar level of total fouling. Compared to CF–DAF and CF–S, CF–IN pretreatment resulted in lower fouling. The hydraulic and chemical reversibility of CF–IN fouling was seen to be strongly influenced by the feed water zeta potential, suggesting the importance of floc electrostatic and morphological characteristics on inline coagulation performance.
Numerical Modeling in Membrane Processes
Authors: Déon Sébastien , Dutournié Patrick
Published: October 2022

Membrane processes have demonstrated their enormous potential for water treatment, either by removing organic and mineral contaminants before permeating stream discharge, or by concentrating high added-value compounds in retentate stream [...]
Impacts of Calcium Addition on Humic Acid Fouling and the Related Mechanism in Ultrafiltration Process for Water Treatment
Authors: Zou Hui , Long Ying , Shen Liguo , He Yiming , Zhang Meijia , Lin Hongjun
Published: October 2022

Humic acid (HA) is a major natural organic pollutant widely coexisting with calcium ions (Ca2+) in natural water and wastewater bodies, and the coagulation–ultrafiltration process is the most typical solution for surface water treatment. However, little is known about the influences of Ca2+ on HA fouling in the ultrafiltration process. This study explored the roles of Ca2+ addition in HA fouling and the potential of Ca2+ addition for fouling mitigation in the coagulation-ultrafiltration process. It was found that the filtration flux of HA solution rose when Ca2+ concentration increased from 0 to 5.0 mM, corresponding to the reduction of the hydraulic filtration resistance. However, the proportion and contribution of each resistance component in the total hydraulic filtration resistance have different variation trends with Ca2+ concentration. An increase in Ca2+ addition (0 to 5.0 mM) weakened the role of internal blocking resistance (9.02% to 4.81%) and concentration polarization resistance (50.73% to 32.17%) in the total hydraulic resistance but enhanced membrane surface deposit resistance (33.93% to 44.32%). A series of characterizations and thermodynamic analyses consistently suggest that the enlarged particle size caused by the Ca2+ bridging effect was the main reason for the decreased filtration resistance of the HA solution. This work revealed the impacts of Ca2+ on HA fouling and demonstrated the feasibility to mitigate fouling by adding Ca2+ in the ultrafiltration process to treat HA pollutants.
Microstructure-Based Modelling of Flow and Fracture Behavior of Tailored Microstructures of Ductibor® 1000-AS Steel
Authors: Samadian Pedram , Abedini Armin , Butcher Clifford , Worswick Michael J.
Published: October 2022

Emerging grades of press-hardening steels such as Ductibor® 1000-AS are now commercially available for use within tailor-welded blanks (TWBs) to enhance ductility and energy absorption in hot-stamped automotive structural components. This study examines the constitutive (hardening) response and fracture limits of Ductibor® 1000-AS as functions of the as-quenched microstructure after hot stamping. Three different microstructures consisting of bainite and martensite were obtained by hot stamping with die temperatures of 25 °C, 350 °C, and 450 °C. Mechanical characterization was performed to determine the hardening curves and plane-stress fracture loci for the different quench conditions (cooling rates). Uniaxial-tension and shear tests were conducted to experimentally capture the hardening response to large strain levels. Shear, conical hole-expansion, plane-strain notch tension, and Nakazima tests were carried out to evaluate the stress-state dependence of fracture. A mean-field homogenization (MFH) scheme was applied to model the constitutive and fracture behavior of the mixed-phase microstructures. A dislocation-based hardening model was adopted for the individual phases, which accounts for material chemistry, inter-phase carbon partitioning, and dislocation evolution. The per-phase fracture modelling was executed using a phenomenological damage index based upon the stress state within each phase. The results revealed that the 25 °C hot-stamped material condition with a fully martensite microstructure exhibited the highest level of strength and the lowest degree of ductility. As bainite was formed in the final microstructure by quenching at higher die temperatures, the strength decreased, while the ductility increased. The predicted constitutive and fracture responses in the hot-stamped microstructures were in line with the measured data. Accordingly, the established numerical strategy was extended to predict the mechanical behavior of Ductibor® 1000-AS for a broad range of intermediate as-quenched microstructures.
Phase Transformations and Tellurium Recovery from Technical Copper Telluride by Oxidative-Distillate Roasting at 0.67 kPa
Authors: Nitsenko Alina , Linnik Xeniya , Volodin Valeriy , Tuleutay Farkhat , Burabaeva Nurila , Trebukhov Sergey , Ruzakhunova Galiya
Published: October 2022

This paper presents the results of a study of phase transformations occurring in copper-telluride by-products during its processing of oxidation-distillate roasting at low pressure. The results show that copper telluride is oxidized through intermediate compounds to the most stable tellurate (Cu3TeO6) at low temperatures. The increase in the roasting temperature above 900 °C and the presence of an oxidizer favor the copper orthotellurate decomposition. Thus, the tellurium extraction rate is 90–93% at a temperature of 1000 °C, the oxidant flow rate is 2.2 × 10−2 m3/m2·s, and the roasting time is 60–90 min. One of the decomposition products is copper oxide alloy, which is the basis of the residue. The second product is tellurium in oxide form, which evaporates and then condenses in the cold zone of the condenser in crystalline form. The main constituent phase of the condensate is tellurium oxide (TeO2), which can be further processed during one operation to elemental chalcogen by thermal reduction or electrolytic method.
Technological Insights into the Evolution of Bronze Bell Metal Casting on the Korean Peninsula
Authors: Won Chun-Soo , Jung Jae Pil , Won Kwang-Sik , Sharma Ashutosh
Published: October 2022

Bronze cast bells have been designed and developed for hundreds of years, with the worldwide spread of several faiths and religions such as Buddhism, Catholicism, and Protestantism. The exceptional ringtones of bronze bell metals have scientific healing and cultural importance. In this review article, we highlight the evolution of bronze bell metal over the decades, its composition, and the complex fabrication technologies used to date. Furthermore, we overview ancient and modern casting alloy technology, especially bronze bell castings in Asia. The bell shape, materials, and alloy casting technology have undergone dramatic change over the years. For comparison, we include different bronze cast bells and their characteristics produced from the Middle Ages to the present times. Based on the data obtained from the bell casting technology surrounding the Korean Peninsula, the major trends in the evolution of bronze bell castings and long-standing traditions of mold materials and alloys are described. In the present review, the effects of different elements on bell materials are qualitatively overviewed, with an assessment of the material and casting properties, service life, and bell sound. We also highlight the challenges of conventional bronze casting and possible solutions for future investment castings and rapid prototyping of bronze bells.
Assessing the Influence of Operational Variables on Process Performance in Metallurgical Plants by Use of Shapley Value Regression
Authors: Liu Xiu , Aldrich Chris
Published: October 2022

Shapley value regression with machine learning models has recently emerged as an axiomatic approach to the development of diagnostic models. However, when large numbers of predictor variables have to be considered, these methods become infeasible, owing to the inhibitive computational cost. In this paper, an approximate Shapley value approach with random forests is compared with a full Shapley model, as well as other methods used in variable importance analysis. Three case studies are considered, namely one based on simulated data, a model predicting throughput in a calcium carbide furnace as a function of operating variables, and a case study related to energy consumption in a steel plant. The approximately Shapley approach achieved results very similar to those achieved with the full Shapley approach but at a fraction of the computational cost. Moreover, although the variable importance measures considered in this study consistently identified the most influential predictors in the case studies, they yielded different results when fewer influential predictors were considered, and none of the variable importance measures performed better than the other measures across all three case studies.
Key Technology and Application of Production Scheduling for Heating Forming of Forgings: A Review
Authors: Wang Hui , Zhu Jiejie , Huang Xiang , Ma Huijuan , Chen Yizhe , Zhou Yulong , Chen Jie , Hu Zhili
Published: October 2022

Forgings represented by rocket body rings, engine casings, vehicle drive shafts, etc., are key components of important equipment in the fields of aerospace, automobiles and high-speed rail. In recent years, with the rapid development of the manufacturing industry, it is also facing an increasingly fierce international competition environment. In order to adapt to the new production mode and quickly respond to the changing market demand, forging enterprises urgently need a reasonable and efficient forging production scheduling method, and based on the excellent production organization, in order to further build an intelligent production line, develop a forging production intelligent management and control integration architecture. This paper analyzes the production scheduling problem of forging thermoforming from two aspects: forging production line scheduling and forging production workshop scheduling. The research progress of optimization objectives and optimization algorithms of production scheduling is systematically reviewed. The subsystems serving the production and processing process and the intelligent management and control architecture based on system integration are summarized. It is of great significance to effectively reduce production costs, improve product quality, realize energy saving and emission reduction in the production process and promote further intelligent upgrading of the forging industry through production scheduling and intelligent management and control of the heating and forming process of forgings.
Determining the Optimal Cutting Parameters for Required Productivity for the Case of Rough External Turning of AISI 1045 Steel with Minimal Energy Consumption
Authors: Stojković Miloš , Madić Miloš , Trifunović Milan , Turudija Rajko
Published: October 2022

One of the most important challenges for every machining shopfloor, especially a small one, is to achieve the required productivity with minimal energy consumption and engaged power. The paper presents a way to determine the optimal combination of values of cutting parameters such as depth of cut, feed rate and cutting speed from the range of their recommended values, which are usually additionally limited by the real conditions of available machines and tools. The optimal combination is the one which ensures targeted productivity and maximum energy savings at the same time. As an example, a real practice case of external rough turning of an AISI 1045 steel workpiece is presented. The selection of the optimal combination of cutting parameter values is based on a model which is developed using in situ measurements of energy consumption and engaged power in an experiment that emulates the critical operation in terms of energy consumption. The results show that optimization of cutting parameter values that enables the minimum of total energy consumption while achieving target productivity, does not necessarily enable the maximum of energy savings for a given operation. In the example from real practice shown in the paper, this optimization approach can cause higher total energy consumption by as much as 15.9% compared to the combination of parameters that ensure maximum productivity.
Machine Learning for Predicting Fracture Strain in Sheet Metal Forming
Authors: Marques Armando , Dib Mario , Khalfallah Ali , Soares Martinho , Oliveira Marta , Fernandes José , Ribeiro Bernardete , Prates Pedro
Published: October 2022

Machine learning models are built to predict the strain values for which edge cracking occurs in hole expansion tests. The samples from this test play the role of sheet metal components to be manufactured, in which edge cracking often occurs associated with a uniaxial tension stress state at the critical edges of components. For the construction of the models, a dataset was obtained experimentally for rolled ferritic carbon steel sheets of different qualities and thicknesses. Two types of tests were performed: tensile and hole expansion tests. In the tensile test, the yield stress, the tensile strength, the strain at maximum load and the elongation after fracture were determined in the rolling and transverse directions. In the hole expansion test, the strain for which edge cracking occurs, was determined. It is intended that the models can predict the strain at fracture in this test, based on the knowledge of the tensile test data. The machine learning algorithms used were Multilayer Perceptron, Gaussian Processes, Support Vector Regression and Random Forest. The traditional polynomial regression that fits a 2nd order polynomial function was also used for comparison. It is shown that machine learning-based predictive models outperform the traditional polynomial regression method; in particular, Gaussian Processes and Support Vector Regression were found to be the best machine learning algorithms that enable the most robust predictive models.
Esterified Oxylipins: Do They Matter?
Authors: Annevelink Carmen E. , Walker Rachel E. , Shearer Gregory C.
Published: October 2022

Oxylipins are oxygenated metabolites of fatty acids that share several similar biochemical characteristics and functions to fatty acids including transport and trafficking. Oxylipins are most commonly measured in the non-esterified form which can be found in plasma, free or bound to albumin. The non-esterified form, however, reflects only one of the possible pools of oxylipins and is by far the least abundant circulating form of oxylipins. Further, this fraction cannot reliably be extrapolated to the other, more abundant, esterified pool. In cells too, esterified oxylipins are the most abundant form, but are seldom measured and their potential roles in signaling are not well established. In this review, we examine the current literature on experimental oxylipin measurements to describe the lack in reporting the esterified oxylipin pool. We outline the metabolic and experimental importance of esterified oxylipins using well established roles of fatty acid trafficking in non-esterified fatty acids and in esterified form as components of circulating lipoproteins. Finally, we use mathematical modeling to simulate how exchange between cellular esterified and unesterified pools would affect intracellular signaling.. The explicit inclusion of esterified oxylipins along with the non-esterified pool has the potential to convey a more complete assessment of the metabolic consequences of oxylipin trafficking.
Suppression of the Electrical Crosstalk of Planar-Type High-Density InGaAs Detectors with a Guard Hole
Authors: Zhang Jiaxin , Wang Wei , Ye Haifeng , Huang Runyu , Hou Zepeng , Liu Chen , Zhao Weilin , Li Yunxue , Ma Xu , Shi Yanli
Published: October 2022

The resolution of InGaAs FPA detectors is degraded by the electrical crosstalk, which is especially severe in high–density FPAs. We propose a guard-hole structure to suppress the electrical crosstalk in a planar-type 640 × 512 15 μm InGaAs short wavelength infrared FPA detector. For comparison, the frequently used guard ring is also prepared according to the same processing. The calculation results show that the electrical crosstalk with a guard hole is suppressed from 13.4% to 4.5%, reducing by 66%, while the electrical crosstalk with a guard ring is suppressed to 0.4%. Furthermore, we discuss the effects of the guard ring and the guard hole on the dark current, quantum efficiency, and detectivity. Experimental results show the detector with a guard-hole structure has higher performance compared with the detector with a guard-ring structure, the dark current density is reduced by 60%, the QE is increased by 64.5%, and the detectivity is increased by 1.36 times, respectively. The guard-hole structure provides a novel suppression method for the electrical crosstalk of high-density InGaAs detectors.
Generic Cutting Force Modeling with Comprehensively Considering Tool Edge Radius, Tool Flank Wear and Tool Runout in Micro-End Milling
Authors: Gao Shuaishuai , Duan Xianyin , Zhu Kunpeng , Zhang Yu
Published: October 2022

Accurate cutting force prediction is crucial in improving machining precision and surface quality in the micro-milling process, in which tool wear and runout are essential factors. A generic analytic cutting force model considering the effect of tool edge radius on tool flank wear and tool runout in the micro-end milling process is proposed. Based on the analytic modeling of the cutting part of the cutting edge in the end face of the micro-end mill bottom, the actual radius model of the worn tool is established, considering the tool edge radius and tool flank wear. The tool edge radius, tool wear, tool runout, trochoidal trajectories of the current cutting edge, and all cutting edges in the previous cycle are comprehensively considered in the instantaneous uncut chip thickness calculation and the cutter–workpiece engagement determination. The cutting force coefficient model including tool wear is established. A series of milling experiments are performed to verify the accuracy and effectiveness of the proposed cutting force model. The results show that the predicted cutting forces are in good agreement with the experimental cutting forces, and it is necessary to consider tool wear in the micro-milling force modeling. The results indicate that tool wear has a significant influence on the cutting forces and cutting force coefficients in the three directions, and the influences of tool wear on the axial cutting force and axial force coefficient are the largest, respectively. The proposed cutting force model can contribute to real-time machining process monitoring, cutting parameters optimization and ensuring machining quality.
Simulation of Silicon Surface Barrier Detector with PN Junction Guard Rings to Improve the Breakdown Voltage
Authors: Wang Bolong , Jia Rui , Li Xing , Tao Ke , Luo Wei , Wang Longjie , Chen Jiawang
Published: October 2022

Silicon surface barrier detectors (SSBDs) are normally used to detect high-energy particles due to their excellent properties. For better charge collection efficiency (CCE), the SSBD device should be operated at higher reverse voltages, but this can lead to device breakdown. Therefore, we used a PN junction as a guard ring to increase the breakdown voltage of the SSBD. The structures of two SSBD devices are drawn and simulated in this work. Compared with a conventional SSBD (c-SSBD), the use of a PN junction as a guard ring for an SSBD (Hybrid-SSBD) achieves higher breakdown voltages, of over 1500 V under reverse bias. This means that Hybrid-SSBD devices can operate at higher reverse voltages for better charge collection efficiency (CCE) to detect high-energy particles. Then, we simulated the different structure parameters of the Hybrid-SSBD guard rings. Among them, the doping depth and gap width of the guard ring (between the innermost guard ring and the active area) have a greater impact on the breakdown voltage. Finally, for Hybrid-SSBD devices, the optimal characteristics of the guard ring were 1 × 1019 cm−3 doping concentration, 1 μm doping depth, and innermost guard ring width and gap width of 5 μm and 3 μm, respectively.
A Ku-Band Miniaturized System-in-Package Using HTCC for Radar Transceiver Module Application
Authors: Yang Fan , Zhang Bowen , Song Leijun
Published: October 2022

This paper introduces a miniaturized system in package (SIP) for a Ku-band four-channel RF transceiver front-end. The SIP adopts the packaging scheme of an inner heat-dissipation gasket and multi-layer substrate in the high temperature co-fired ceramics (HTCC) shell with a metal heat sink at the bottom. The gasket effectively solves the heat-dissipation problem of high-power transceiver chips, and the multi-layer substrate achieves the interconnection between multiple chips. Within the limited size of 14.0 × 14.0 × 2.5 mm3, the SIP integrates five bidirectional amplifier chips, an amplitude-phase control multi-function chip, and two power modulation chips to realize the Ku-band four-channel RF transceiver front-end. Transmitting power over 0.5 W (27dBm) and receiving noise figure of 3.4 dB are achieved in the Ku-band. The efficient heat dissipation, high air tightness, and excellent integration are simultaneously realized in this SIP. The measurement results show that the performance is stable in the receiving and transmitting states, and the SIP based on HTCC technology has specific prospects for radar transceiver application.