bluuebunny/crossref_metadata_2025 huggingface dataset:
Accurate Triage of Oncological Patients for Safely Continuing Cancer Therapy During the SARS-CoV-2 Pandemic
Authors: Gurizzan Cristina , Pedersini Rebecca , Fornaro Carla , Sardini Chiara , Zamparini Manuel , Monteverdi Sara , Tovazzi Valeria , Cosentini Deborah , Dalla Volta Alberto , Baggi Alice , Turla Antonella , Di Mauro Pierluigi , Lorini Luigi , Laganà Marta , Bianchi Susanna , Grisanti Salvatore , Consoli Francesca , Conti Elisabetta , Bossi Paolo , Berruti Alfredo
Published: October 2021

Objective

To evaluate the efficacy of clinical triage of oncological patients for safe continuation of cancer therapy implemented during the first SARS-CoV-2 outbreak.

Methods

Between 25 February and 21 April 2020, patients attending the Medical Oncology Unit, Spedali Civili Hospital, Brescia (Italy) for cancer therapy underwent triage to identify those with no signs and symptoms suspicious for SARS-CoV-2 infection in which antineoplastic treatment could be continued as scheduled. Triage questions investigated common symptoms (e.g., fever, cough, dyspnea, anosmia, dysgeusia, headache, nasal congestion, conjunctival congestion, sore throat, diarrhea, nausea and vomiting); body temperature and pulse oximetry were also recorded. All patients were followed-up for overt SARS-CoV-2 through to 18th May 2020.

Results

Overall, 1180 patients (median age 65 years) underwent triage during the study period. The most frequent primary malignances were breast (32%), gastrointestinal (18%), and lung (16.5%) cancer. Thirty-one (2.5%) presented with clinically evident SARS-CoV-2 infection and tested positive on nasopharyngeal swab testing and/or radiological imaging. Triage identified 69 (6%) grey zone patients with symptoms suspicious for SARS-CoV-2; 5 (7.2%) subsequently developed symptomatic disease. Neither the symptomatic nor the grey zone patients received their scheduled treatment; instead, they were referred for hospitalization or home quarantine.

Conclusion

Triage of oncological patients at our Unit provided for safe continuation of scheduled cancer treatment in 91.5% of patients during the initial SARS-CoV-2 outbreak.
The Sequence of Intracranial Radiotherapy and Systemic Treatment With Tyrosine Kinase Inhibitors for Gene-Driven Non-Small Cell Lung Cancer Brain Metastases in the Targeted Treatment Era: A 10-Year Single-Center Experience
Authors: Yang Siran , Xiao Jianping , Liu Qingfeng , Zhang Ye , Bi Nan , Huang Xiaodong , Chen Xuesong , Wang Kai , Ma Yuchao , Deng Lei , Wang Wenqing , Zhao Ruizhi , Li Junling , Yi Junlin , Wang Shulian , Li Yexiong
Published: October 2021

Purpose

The high intracranial efficacy of targeted therapeutic agents poses a challenge in determining the optimal sequence of local radiation therapy (RT) and systemic treatment with tyrosine kinase inhibitors (TKIs) in non-small cell lung cancer (NSCLC) patients with brain metastasis (BM). Therefore, we conducted a cohort study to elucidate the appropriate treatment strategy, either upfront RT or deferred RT including a toxicity assessment, in these patients.

Patients and Methods

We retrospectively evaluated patients with gene-driven BMs from a single institution and divided them into deferred and upfront RT groups. Survival was estimated using a log-rank test. Intracranial progression was estimated using Fine-Gray competing risks model. Cox proportional hazards regression was performed for multivariable analysis in the entire group and subgroups.

Results

Among the 198 eligible patients, 94 and 104 patients received deferred and upfront RT, respectively. The upfront RT group showed a lower intracranial progression risk with an adjusted sub-distribution hazard ratios of 0.41 (95% CI, 0.30–0.57) than did the deferred RT group (median intracranial progression-free survival [iPFS], 19.9 months vs. 11.1 months; p < 0.001). The median overall survival (OS; 43.2 months vs. 49.1 months, p = 0.377) and BM-specific survival (92.1 months vs. 82.9 months, p = 0.810) after salvage therapy were not significantly different between the upfront and deferred groups. Among patients with progressed extracranial disease, the deferred RT group showed significantly better OS than did the upfront RT group (44.0 vs. 28.1 months, p = 0.022). Grade 3–4 treatment-related adverse events were rare, and similar toxicities were observed between the two groups.

Conclusion

Compared to the deferred RT group, the upfront RT group achieved longer iPFS and similar survival outcomes in most patients with gene-driven NSCLC BM, although patients with progression of extracranial disease might benefit from deferred RT. Both groups showed well-tolerated toxicities.

Trial registration ID

NCT04832672.
Visual and Verbal Working Memory and Processing Speed Across the Adult Lifespan: The Effect of Age, Sex, Educational Level, Awakeness, and Hearing Sensitivity
Authors: Kestens Katrien , Degeest Sofie , Miatton Marijke , Keppler Hannah
Published: October 2021

Objective: To strengthen future methodological choices regarding the measurement of cognition within the field of audiology, the current study aimed to examine the effect of, among other things, hearing sensitivity on the backward corsi tapping task (i.e., visual working memory and processing speed) and the letter-number sequencing task (i.e., verbal working memory and processing speed).

Design and Study Sample: The backward corsi tapping task and the letter-number sequencing task were administered to 184 participants, aged between 18 and 69 years. The effect of age, sex, educational level, awakeness, and hearing sensitivity on verbal and visual working memory and processing speed was assessed using stepwise multiple regression analyses.

Results: For all outcome variables, a decrease in performance was observed with increasing age. For visual and verbal working memory, males outperformed females, whereas no clear sex effect was observed for visual and verbal processing speed. Hearing sensitivity had only a significant impact on visual processing speed.

Conclusion: The importance to evaluate cognitive construct validity within audiological research was highlighted. Further research should focus on investigating the associations between speech understanding on the one hand and the backward corsi tapping task and letter-number sequencing task on the other hand.
Accessing the Influence of Perceived Value on Social Attachment: Developing Country Perspective
Authors: Wang Qingqing , Yang Maosheng , Zhang Wensong
Published: October 2021

Perceived value has a positive impact on users’ social attachment in social media usage contexts and is a topic at the forefront of current research in consumer behavior. Although studies have begun to investigate the factors influencing social attachment, there is a lack of research on how perceived value affects social attachment. Therefore, this study uses privacy concern theory, to build a theoretical model with moderated and mediation roles, using Chinese Tik Tok users as data and survey sample, and applying Mplus7.0 to analyze the mediation mechanism and boundary conditions of the relationship between perceived value and social attachment through the structural equation model. In Study 1, data were collected from 600 Tik Tok users to verify the mediating role of the sense of belonging in perceived value and social attachment relationship. The users participating in the questionnaire survey were mainly from mainland China. In Study 2, two waves of data were collected from 500 Tik Tok users to verify the mediating role of the sense of belonging, and support part of the moderating role of privacy concern. However, except that the relationship between information value and social attachment is inhibited by privacy concern, the relationship between entertainment and social value and social attachment is not regulated by privacy concern. This research examines the practical effects of perceived value in the context of social media use, reveals the internal mechanism of the impact of perceived value on social attachment, and provides a reference for the innovative management and commercial practice of social media.
Effects of Online Problem-Solving Instruction and Identification Attitude Toward Instructional Strategies on Students' Creativity
Authors: Wang Yi-Ping
Published: October 2021

Problem-solving ability is an essential part of daily life. Thus, curiosity and a thirst for knowledge should be cultivated in students to help them develop problem solving and independent thinking skills. Along with positive attitudes and an active disposition, these abilities are needed to solve problems throughout the lifespan and develop -confidence. To achieve educational objectives in the context of globalization, creative ability is necessary for generating competitive advantages. Therefore, creative thinking, critical thinking, and problem-solving ability are important basic competencies needed for future world citizens. Creativity should also be integrated into subject teaching to cultivate students' lifelong learning and a creative attitude toward life. A questionnaire was distributed to 420 students in colleges and universities in Fujian, China. After removing invalid and incomplete responses, 363 copies were found to be valid yielding a response rate of 86%. Findings indicate that the new generation requires high levels of support to develop creativity and integrate diverse subjects such as nature, humanities, and technology. A rich imagination is needed to root creativity in the new generation.
Prediction of Obstetric Patient Flow and Horizontal Allocation of Medical Resources Based on Time Series Analysis
Authors: Li Hua , Mu Dongmei , Wang Ping , Li Yin , Wang Dongxuan
Published: October 2021

Objective: Given the ever-changing flow of obstetric patients in the hospital, how the government and hospital management plan and allocate medical resources has become an important problem that needs to be urgently solved. In this study a prediction method for calculating the monthly and daily flow of patients based on time series is proposed to provide decision support for government and hospital management.

Methods: The historical patient flow data from the Department of Obstetrics and Gynecology of the First Hospital of Jilin University, China, from January 1, 2018, to February 29, 2020, were used as the training set. Seven models such as XGBoost, SVM, RF, and NNAR were used to predict the daily patient flow in the next 14 days. The HoltWinters model is then used to predict the monthly flow of patients over the next year.

Results: The results of this analysis and prediction model showed that the obstetric inpatient flow was not a purely random process, and that patient flow was not only accompanied by the random patient flow but also showed a trend change and seasonal change rule. ACF,PACF,Ljung_box, and residual histogram were then used to verify the accuracy of the prediction model, and the results show that the Holtwiners model was optimal. R2, MAPE, and other indicators were used to measure the accuracy of the 14 day prediction model, and the results showed that HoltWinters and STL prediction models achieved high accuracy.

Conclusion: In this paper, the time series model was used to analyze the trend and seasonal changes of obstetric patient flow and predict the patient flow in the next 14 days and 12 months. On this basis, combined with the trend and seasonal changes of obstetric patient flow, a more reasonable and fair horizontal allocation scheme of medical resources is proposed, combined with the prediction of patient flow.
An Inclusive Early Childhood Intervention Program for Children With Disabilities: Possible Effects on Children and Nursery Teachers
Authors: Ueda Kimiko , Goto Aya , Imamoto Toshikazu , Yamazaki Yoshihisa
Published: October 2021

Inclusive early childhood intervention provides opportunities for children with disabilities to receive education with typically developing children. The present study examined the effects of the AI-AI STEP Program, which is designed to help nursery teachers learn the methods of inclusive early childhood intervention for children with disabilities. This study involved 37 managers of 37 nursery schools in Japan, 48 nursery teachers, and 48 children with disabilities. The school managers, who had previously learned about the program through a seminar we offered, provided the nursery teachers with guidance on the program. The guidance provided to the nursery teachers consisted of combined structured explanations with a manual and on-the-job training. The program was performed for 6 months, and changes in the children's development and behavior and the school nursery teachers' self-efficacy and state-trait anxiety, were examined before and after using the program. Multivariate analysis was used to assess factors that had an effect on the children's developmental gains through the program. The developmental quotient of children significantly improved. In addition, “emotional symptoms” and “peer problems” on the Strengths and Difficulties Questionnaire subscale markedly improved. The self-efficacy of nursery teachers significantly improved, and state anxiety decreased. There was a significant relationship between the improvement of the children's development quotient and a lower development quotient at baseline. The provision of inclusive early childhood intervention using the program promoted the children's development, and improved their behavior. Furthermore, it had a positive effect on the nursery teachers.
Managing Scarcity: Innovation and Resilience During the COVID-19 Pandemic
Authors: Pozzi Natalie , Zuckerman Aaron , Son Joohee , Geraci Travis C. , Chang Stephanie H. , Cerfolio Robert J.
Published: October 2021

The Coronavirus Disease 2019 (COVID-19) pandemic remains a disruptive force upon the health care system, with particular import for thoracic surgery given the pulmonary pathophysiology and disease implications of the virus. The rapid and severe onset of disease required expedient innovation and change in patient management and novel approaches to care delivery and nimbleness of workforce. In this review, we detail our approaches to patients with COVID-19, including those that required surgical intervention, our expedited and novel approach to bronchoscopy and tracheostomy, and our expansion of telehealth. The pandemic has created a unique opportunity to reflect on our delivery of care in thoracic surgery and apply lessons learned during this time to “rethink” how to optimize resources and deliver excellent and cutting-edge patient care.
A Laser Irradiation Method for Controlling Pieris rapae Larvae
Authors: Li Yajun , Xiang Yang , Yang Zhongxia , Han Xiongzhe , Lin Jiewen , Hu Zhengfang
Published: October 2021

At present, chemical pesticides remain the main approach for controlling Pieris rapae (L.) (Lepidoptera: Pieridae). This research proposes a novel laser irradiation method for managing P. rapae larvae as an alternative to chemical control. The effectiveness of controlling larvae and the influencing factors of lasers were studied to estimate optimal parameter combinations. Tests using the antifeedant effect and mortality of the larvae as dependent variables showed that the laser power, irradiation area, laser opening time and irradiation position were positively correlated with the P. rapae controlling effect. The optimal parameters for each factor were the following: laser power, 7.5 W; irradiation area, 6.189 mm2; laser opening time, 1.177 s; and irradiation position, middle of the abdomen. Based on these observations, a validation experiment was performed using the optimal combination of parameters, and the results showed that the antifeedant percentage of P. rapae larvae within 24 h posttreatment was 98.49%, whereas the mortality rate was 100%. The optimal parameter combination identified in the study was suitable for P. rapae larvae from the first- to fifth-instar stages, and a more effective controlling effect was observed with the younger larvae. These results can provide a theoretical basis for future pest control using laser pest-killing robots.
A Bayesian Modeling Approach to Situated Design of Personalized Soundscaping Algorithms
Authors: van Erp Bart , Podusenko Albert , Ignatenko Tanya , de Vries Bert
Published: October 2021

Effective noise reduction and speech enhancement algorithms have great potential to enhance lives of hearing aid users by restoring speech intelligibility. An open problem in today’s commercial hearing aids is how to take into account users’ preferences, indicating which acoustic sources should be suppressed or enhanced, since they are not only user-specific but also depend on many situational factors. In this paper, we develop a fully probabilistic approach to “situated soundscaping”, which aims at enabling users to make on-the-spot (“situated”) decisions about the enhancement or suppression of individual acoustic sources. The approach rests on a compact generative probabilistic model for acoustic signals. In this framework, all signal processing tasks (source modeling, source separation and soundscaping) are framed as automatable probabilistic inference tasks. These tasks can be efficiently executed using message passing-based inference on factor graphs. Since all signal processing tasks are automatable, the approach supports fast future model design cycles in an effort to reach commercializable performance levels. The presented results show promising performance in terms of SNR, PESQ and STOI improvements in a situated setting.
Predicting Tumor Budding Status in Cervical Cancer Using MRI Radiomics: Linking Imaging Biomarkers to Histologic Characteristics
Authors: Chong Gun Oh , Park Shin-Hyung , Park Nora Jee-Young , Bae Bong Kyung , Lee Yoon Hee , Jeong Shin Young , Kim Jae-Chul , Park Ji Young , Ando Yu , Han Hyung Soo
Published: October 2021

Background: Our previous study demonstrated that tumor budding (TB) status was associated with inferior overall survival in cervical cancer. The purpose of this study is to evaluate whether radiomic features can predict TB status in cervical cancer patients. Methods: Seventy-four patients with cervical cancer who underwent preoperative MRI and radical hysterectomy from 2011 to 2015 at our institution were enrolled. The patients were randomly allocated to the training dataset (n = 48) and test dataset (n = 26). Tumors were segmented on axial gadolinium-enhanced T1- and T2-weighted images. A total of 2074 radiomic features were extracted. Four machine learning classifiers, including logistic regression (LR), random forest (RF), support vector machine (SVM), and neural network (NN), were used. The trained models were validated on the test dataset. Results: Twenty radiomic features were selected; all were features from filtered-images and 85% were texture-related features. The area under the curve values and accuracy of the models by LR, RF, SVM and NN were 0.742 and 0.769, 0.782 and 0.731, 0.849 and 0.885, and 0.891 and 0.731, respectively, in the test dataset. Conclusion: MRI-based radiomic features could predict TB status in patients with cervical cancer.
Richter Transformation in Chronic Lymphocytic Leukemia: Update in the Era of Novel Agents
Authors: Tadmor Tamar , Levy Ilana
Published: October 2021

Richter transformation (RT) is a poorly understood complication of chronic lymphocytic leukemia (CLL) with a dismal prognosis. It is associated with a switch in histopathology and biology, generally with a transformation of the original CLL clone to diffuse large B-cell lymphoma (DLBCL) or less frequently to Hodgkin’s variant of Richter transformation (HVRT). It occurs in 2–10% of CLL patients, with an incidence rate of 0.5–1% per year, and may develop in treatment-naïve patients, although it is more common following therapy. In recent years, there has been a deeper understanding of the molecular pathogenesis of RT that involves the inactivation of the TP53 tumor suppressor gene in 50–60% of cases and the activation of aberrations of NOTCH1 and MYC pathways in about 30% of cases. Compared to the preceding CLL, 80% of cases with DLBCL-RT and 30% of HVRT harbor the same IGHV-D-J rearrangements, indicating a clonal evolution of the disease, while the remaining cases represent de novo lymphomas that are clonally unrelated. Despite advances in understanding the molecular variations and the pathogenesis of the disease, there is still no significant improvement in patient outcomes. However, if no clinical trials were designed for patients with RT in the past, now there many studies for these patients that incorporate new drugs and novel combinations that are being explored. In this review, we summarize the new information accumulated on RT with special emphasis on results involving the novel therapy tested for this entity, which represents an unmet clinical need.
Limited Predictive or Prognostic Role of Tumor-Infiltrating Tissue-Resident Memory CD8 T Cells in Patients with Hepatocellular Carcinoma Receiving Immunotherapy
Authors: Shen Ying-Chun , Yeh Ching-Ping , Jeng Yung-Ming , Hsu Chiun , Hsu Chih-Hung , Lin Zhong-Zhe , Shao Yu-Yun , Lu Li-Chun , Liu Tsung-Hao , Chen Chien-Hung , Cheng Ann-Lii
Published: October 2021

Purpose: Tumor-infiltrating tissue-resident memory CD8 T cells (CD8 TRM; CD103+ CD8+) are considered tumor-specific and may correlate better with the tumor response to immune checkpoint blockade (ICB). This study evaluated the association of tumor-infiltrating CD8 TRM and their subsets with the efficacy of immunotherapy in patients with advanced hepatocellular carcinoma (HCC). Experimental Design: Consecutive HCC patients who received ICB in prospective trials were analyzed. Formalin-fixed paraffin-embedded tumor sections were stained for DAPI, CD8, CD103, CD39, programmed cell death-1 (PD-1), and programmed cell death ligand 1 (PD-L1) using a multiplex immunohistochemical method. The densities of CD8 T cells, CD8 TRM, and CD39+ or PD-L1+ subsets of CD8 TRM were correlated with tumor response and overall survival (OS). Results: A total of 73 patients were identified, and 48 patients with adequate pretreatment tumor specimens and complete follow-up were analyzed. A median of 32.7% (range: 0–92.6%) of tumor-infiltrating CD8 T cells were TRM. In subset analyses, 66.6% ± 34.2%, 69.8% ± 33.4%, and 0% of CD8 TRM cells coexpressed CD39, PD-L1, and PD-1, respectively. The objective response rates for CD8 T cell-high, CD8 TRM-high, CD39+ CD8 TRM-high, and PD-L1+ CD8 TRM-high groups were 41.7%, 37.5%, 37.5%, and 29.2%, respectively. Patients with CD8 T cell-high, but not those with CD8 TRM-high, CD39+ CD8 TRM-high, or PD-L1+ CD8 TRM-high, tumors, had significantly prolonged OS (p = 0.0429). Conclusions: Compared with total tumor-infiltrating CD8 T cells, tumor-infiltrating CD8 TRM or their subsets failed to provide additional advantages in predicting the efficacy of immunotherapy for HCC.
Experimental Evaluation of δ2H, δ13C and δ15N Variability in Blood and Feathers of Wild and Captive Birds: Implications for Interspecific Food Web Studies
Authors: Clark Robert G. , Dawson Russell D. , Greenwood Jennifer L. , Johns David W. , Wassenaar Leonard I. , Hobson Keith A.
Published: October 2021

Stable-hydrogen (δ2H), nitrogen (δ15N), and carbon (δ13C) isotopes are used to decipher broad movement patterns and trophic relationships among diverse species, and an improved understanding of factors controlling natural variation in tissue-isotope measurements will enhance these applications. To evaluate the rearing environment and family-related effects on the isotopic composition of tissues, we cross-fostered nestling tree swallows (Tachycineta bicolor, Vieillot 1808) and American kestrels (Falco sparverius, Linnaeus 1758) by swapping recently hatched birds (<4 days old) among nest boxes and collecting blood and feathers prior to fledging. To assess developmental effects, we measured δ2H in blood and feathers of captive mallard (Anas platyrhynchos, Linnaeus 1758) ducklings challenged energetically during growth. Stable isotope composition was not strongly related to nest box type or natal nest (i.e., family of origin) effects in swallows and kestrels; tissue-isotope composition was related to rearing environment, indicative of differences in nest and parental quality or parental provisioning tactics. Blood and feather δ2H values in swallows were positively related to antecedent maximum ambient temperature, and unrelated to elevated energy expenditure in mallards. The average differences between δ2H in blood and feathers were similar for nestling swallows (27‰, 32‰; two sites) and mallards (26‰, 30‰; two age groups), and lower than in nestling kestrels (50‰). Strong species-specific patterns in blood-feather differences were not observed for δ15N and δ13C in swallows or kestrels; divergent δ2H results may be related to differences in nest ambient conditions, diet composition, or physiological processes affecting hydrogen assimilation during growth and feather synthesis. In swallows, tissue-isotope values reflected parental prey selection from spatially distinct food webs during nestling development with little effect(s) of family of origin, egg composition, or early growth.
Entropy and Network Centralities as Intelligent Tools for the Investigation of Terrorist Organizations
Authors: Spyropoulos Alexandros Z. , Bratsas Charalampos , Makris Georgios C. , Ioannidis Evangelos , Tsiantos Vassilis , Antoniou Ioannis
Published: October 2021

In recent years, law enforcement authorities have increasingly used mathematical tools to support criminal investigations, such as those related to terrorism. In this work, two relevant questions are discussed: “How can the different roles of members of a terrorist organization be recognized?” and “are there early signs of impending terrorist acts?” These questions are addressed using the tools of entropy and network theory, more specifically centralities (degree, betweenness, clustering) and their entropies. These tools were applied to data (physical contacts) of four real terrorist networks from different countries. The different roles of the members are clearly recognized from the values of the selected centralities. An early sign of impending terrorist acts is the evolutionary pattern of the values of the entropies of the selected centralities. These results have been confirmed in all four terrorist networks. The conclusion is expected to be useful to law enforcement authorities to identify the roles of the members of terrorist organizations as the members with high centrality and to anticipate when a terrorist attack is imminent, by observing the evolution of the entropies of the centralities.
Utilization of Two Sensors in Offline Diagnosis of Squirrel-Cage Rotors of Asynchronous Motors
Authors: Kacor Petr , Bernat Petr , Moldrik Petr
Published: October 2021

In the manufacture squirrel-cage rotors of asynchronous motors, a high standard of quality is required in every part of the production cycle. The die casting process usually creates porosity in the rotor bars. This most common defect in the rotor often remains hidden during the entire assembly of the machine and is usually only detected during final testing of the motor, i.e., at the end of the production process. This leads to unnecessary production costs. Therefore, the aim is to conduct a continuous control immediately after the rotor has been cast before further processing. In our paper, we are interested in selecting a suitable method of offline rotor diagnostics of an asynchronous motor that would be effective for these needs. In the first step, the selection of the method and its integration into the overall manufacturing process is carried out. The arrangement of the sensors and their calibration is then simulated on a 2D Finite Element Model of the rotor. The proposed offline measurement procedures and technologies are finally validated by testing measurements on a rotor that simulates the most frequently occurring faults. A test system is also developed that provides the operator continuous information about the running rotor measurements and makes it easier to evaluate the quality of the cast rotor by means of graphical visualization of the faults.
Optimization of ORC Power Plants for Geothermal Application in Kenya by Combining Exergy and Pinch Point Analysis
Authors: Bett Alvin Kiprono , Jalilinasrabady Saeid
Published: October 2021

Geothermal energy is a sustainable renewable source of energy. The installed capacity of geothermal energy in Kenya is 847.4 MWe of the total 2.7 GWe. This paper presents the effect of six different working fluids to optimize the geothermal of 21.5 MWe of reinjected brine at a single-flash power plant in Kenya. Engineering Equation Solver (EES) code was used to design and optimize simple organic Rankine (ORC) and regenerative cycles. The objective was to combine pinch point analysis and exergy analysis for the optimum utilization of geothermal energy by varying the turbine inlet pressure, pinch point, and reinjection temperature. The turbine inlet pressures, and pinch points were varied to obtain optimum pressures for higher net power output and exergy efficiencies. As the pressure increased, the efficiencies and net power generated increase to optimal at turbine inlet pressures between 2000 and 3000 kPa. By maintaining a condenser temperature at 46.7 °C, the turbine outlet pressures were 557.5 kPa for isobutene, 627.4 kPa for isobutane, 543.7 kPa for butene, 438.9 kPa for trans-2-butene, 412.3 kPa for R236ea, and 622.9 kPa for R142b. For the pinch point of 10 °C, the working fluid with a lower net power is trans-2-butene at 5936 kW for a flow rate of 138.8 kg/s and the highest reinjection at 89.05 °C. On the other hand, R236ae had a flow rate of 398.2 kg/s, a higher power output of 7273 kW, and the lowest reinjection temperature of 73.47 °C for a 5 °C pinch point. In the pinch point consideration, the suitable fluid will depend on the best reinjection temperatures. The pinch point affects the heat transfer rates and effectiveness in the heat exchangers. The best pinch point is 10 °C, since the reinjection temperatures are the highest between 83 and 89 °C. The analysis showed that for unlimited reinjection temperatures, basic ORC is suitable. The regenerative cycle would be best suited where reinjection temperature is constrained by brine geochemistry.
Impact of Charging Electric Vehicles under Different State of Charge Levels and Extreme Conditions
Authors: El-Bayeh Claude Ziad , Zellagui Mohamed , Brahmi Brahim , Alqaisi Walid , Eicker Ursula
Published: October 2021

High penetration levels of Plug-in Electric Vehicles (PEVs) could cause stress on the network and might violate the limits and constraints under extreme conditions, such as exceeding power and voltage limits on transformers and power lines. This paper defines extreme conditions as the state of a load or network that breaks the limits of the constraints in an optimization model. Once these constraints are violated, the optimization algorithm might not work correctly and might not converge to a feasible solution, especially when the complexity of the system increases and includes nonlinearities. Hence, the algorithm may not help in mitigating the impact of penetrating PEVs under extreme conditions. To solve this problem, an original algorithm is suggested that is able to adapt the constraints’ limits according to the energy demand and the energy needed to charge the PEVs. Different case scenarios are studied for validation purposes, such as charging PEVs under different state of charge levels, different energy demands at home, and different pricing mechanisms. Results show that our original algorithm improved the profiles of the voltage and power under extreme conditions. Hence, the algorithm is able to improve the integration of a high number of PEVs on the distribution system under extreme conditions while preserving its stability.
A Multi-Criteria Decision-Making Approach for Energy Storage Technology Selection Based on Demand
Authors: Qie Xiaotong , Zhang Rui , Hu Yanyong , Sun Xialing , Chen Xue
Published: October 2021

Energy storage technologies can reduce grid fluctuations through peak shaving and valley filling and effectively solve the problems of renewable energy storage and consumption. The application of energy storage technologies is aimed at storing energy and supplying energy when needed according to the storage requirements. The existing research focuses on ranking technologies and selecting the best technologies, while ignoring storage requirements. Here, we propose a multi-criteria decision-making (MCDM) framework for selecting a suitable technology based on certain storage requirements. Specifically, we consider nine criteria in four aspects: technological, economic, environmental, and social. The interval number, crisp number, and linguist terms can be transformed into a probabilistic dual hesitant fuzzy set (PDHFS) through the transformation and fusion method we proposed, and a suitable technology can be selected through distance measurements. Subsequently, the proposed method is applied in a representative case study for energy storage technology selection in Shanxi Province, and a sensitivity analysis gives different scenarios for elaboration. The results show that the optimal selection of energy storage technology is different under different storage requirement scenarios. The decision-making model presented herein is considered to be versatile and adjustable, and thus, it can help decision makers to select a suitable energy storage technology based on the requirements of any given use case.
A Fault Diagnosis Design Based on Deep Learning Approach for Electric Vehicle Applications
Authors: Kaplan Halid , Tehrani Kambiz , Jamshidi Mo
Published: October 2021

Diagnosing faults in electric vehicles (EVs) is a great challenge. The purpose of this paper is to demonstrate the detection of faults in an electromechanical conversion chain for conventional or autonomous EVs. The information and data coming from different sensors make it possible for EVs to recover a series of information including currents, voltages, speeds, and so on. This information is processed to detect any faults in the electromechanical conversion chain. The novelty of this study is to develop an architecture for a fault diagnosis model by means of the feature extraction technique. In this regard, the long short-term memory (LSTM) approach for the fault diagnosis is proposed. This approach has been tested for an EV prototype in practice, is superior in accuracy over other fault diagnosis techniques, and is based on machine learning. An EV in an urban context is modeled, and then the fault diagnosis approach is applied based on deep learning architectures. The EV and the fault diagnosis model is simulated in Matlab software. It is also revealed how deep learning contributes to the fault diagnosis of EVs. The simulation and practical results confirm that higher accuracy in the fault diagnosis is obtained by applying the LSTM.
Investigation of Isolation Forest for Wind Turbine Pitch System Condition Monitoring Using SCADA Data
Authors: McKinnon Conor , Carroll James , McDonald Alasdair , Koukoura Sofia , Plumley Charlie
Published: October 2021

Wind turbine pitch system condition monitoring is an active area of research, and this paper investigates the use of the Isolation Forest Machine Learning model and Supervisory Control and Data Acquisition system data for this task. This paper examines two case studies, turbines with hydraulic or electric pitch systems, and uses an Isolation Forest to predict failure ahead of time. This novel technique compared several models per turbine, each trained on a different number of months of data. An anomaly proportion for three different time-series window lengths was compared, to observe trends and peaks before failure. The two cases were compared, and it was found that this technique could detect abnormal activity roughly 12 to 18 months before failure for both the hydraulic and electric pitch systems for all unhealthy turbines, and a trend upwards in anomalies could be found in the immediate run up to failure. These peaks in anomalous behaviour could indicate a future failure and this would allow for on-site maintenance to be scheduled. Therefore, this method could improve scheduling planned maintenance activity for pitch systems, regardless of the pitch system employed.
A Novel Energy-Safe Algorithm for Enhancing the Battery Life for IoT Sensors’ Applications
Authors: Zouinkhi Ahmed , Flah Aymen , Mihet-Popa Lucian
Published: October 2021

Energy safe is mandatory for all isolated IoT tools, such as in long way roads, mountains, or even in smart cities. If increasing the lifetime of these tools, the rentability of the global network loop becomes more efficient. Therefore, this paper presents a new approach for saving energy inside the source nodes by supervising the state of energy inside each source node and calculating the duty cycle factor. The relationship between these parameters is based on an optimization problem formulation. In this respect, the present paper is designed to propose a new approach that deals with increasing the lifetime of the wireless sensor network (WSN)-attached nodes, as fixed in the application. The newly devised design is based on implementing the IEEE 802.15.4 standard beacon-enabled mode, involving a cluster tree topology. Accordingly, every subgroup is allotted to apply a specifically different duty cycle, depending on the battery’s remaining energy level, which contributes to creating a wide range of functional modes. Hence, various thresholds are defined. Simulation results prove the efficiency of the proposed approach and show the energetic benefit. The proposed flowchart has minimized the consumed energy for the WSN, which improves the battery lifetime and enhances the IoT application’s robustness. Simulations and experiments have been carried out under different conditions and the results prove that the proposed method is a viable solution.
Depositional Heterogeneities and Brittleness of Mudstone Lithofacies in the Marcellus Subgroup, Appalachian Basin, New York, U.S.A.
Authors: Haq Izhar Ul , Padmanabhan Eswaran , Iqbal Omer
Published: October 2021

Organic-rich rocks of the Marcellus subgroup in the study area consist of a diverse suite of mudstone lithofacies that were deposited in distinct facies belts. Lithofacies in the succession range in composition from argillaceous to siliceous, calcareous, and carbonaceous mudstone. Heterogeneities in the succession occurs in the form of varying mineralogical composition, slightly bioturbated to highly bioturbated chaotic matrix, organic-rich and organic-lean laminae, scattered fossil shells in the matrix, and fossils acting as lamination planes. Lithofacies were deposited in three facies belts from the proximal to the distal zone of the depositional system. Bedded siliceous mudstone (BSM) facies occur in the proximal facies belt and consists of a high quartz content in addition to clay minerals and pyrite. In the medial part of the facies belt lies the laminated argillaceous mudstone (LAM), bedded calcareous mudstone (BCaM), and bedded carbonaceous mudstone (BCM). The size of detrital mineral grains in the lithofacies of the medial facies belt is larger than bedded argillaceous mudstone (BAM) of the distal facies belt, characterized by clay-rich matrix with occasional fossil shells and horizontally aligned fossils. Two types of horizontal traces and one type of fecal string characterize the proximal mud-stone facies, whereas only single horizontal trace fossil is found in the mudstones of the medial and distal facies belt. Parallel alignment of fossil shells and fossil lags in lithofacies indicate that bed-load transport was active periodically from the proximal source of the depositional system. Bioturbation has heavily affected all of the lithofacies and presence of mottled burrows as well as Devonian fauna indicate that oxic to dysoxic conditions prevailed during deposition. The deposition of this organic-rich mudstone succession through dynamic processes in an overall oxic to dysoxic environment is different from conventional anoxic depositional models interpreted for most of the organic rich black shales worldwide. Total organic content (TOC) varies from top to bottom in the succession and is highest in BCM facies. The brittleness index, calculated on the basis of mineralogy, allowed classification of the lithofacies into three distinct zones, i.e., a brittle zone, a less brittle zone, and a ductile zone with a general proximal to distal decrease in the brittle behavior due to a decrease in the size of the sediments.
Mechanical Switch Based Adaptive Fault Ride-through Strategy for Power Quality Improvement Device
Authors: Shen Yu , Hu Wei , Xiao Yaoyao , Zhang Ganghua , Han Mingyu , Yang Fan , Zuo Wenping
Published: October 2021

Cascaded H-bridge power quality improving device (PQID) has garnered extensive attention for its flexible electric energy conversion and fast voltage response. However, the failure rate of PQID is relatively high due to the use of large numbers of power electronic devices. This paper proposes a mechanical-switch based adaptive fault ride-through strategy for improving the operational stability and power supply reliability of PQID. According to the features of the topology and working principle of PQID, this paper summarized the types of internal faults and analyzed the characteristics of different types of faults. Based on the shortcomings of existing mechanical switches as a bypass method, corresponding adaptive fault ride-through strategies are proposed for different types of faults, and a comprehensive simulation test has been carried out. The results show that the proposed strategy can adaptively ride through unit faults and effectively improve the output waveform quality during the ride through time.
Intelligent Permanent Magnet Motor-Based Servo Drive System Used for Automated Tuning of Piano
Authors: Zhou Ying , Wu Zuyu , Wu Yutong
Published: October 2021

This paper presents an intelligent permanent magnet synchronous motor-based servo drive system used in automated piano tuning applications. The permanent magnet synchronous motor-based drives are able to improve the accuracy of the piano tuning process in comparison with the traditional direct-current motor-based and step motor-based servo drives. To explain the techniques, firstly, the structure and principles of the automated piano tuning devices with a surface-mounted permanent magnet synchronous motor-based drive system integrated are introduced, illustrating that it is feasible to implement the proposed piano tuning strategy. Secondly, the piano tuning devices have two functions: low-speed rotation and position holding. To ensure that the surface-mounted permanent magnet synchronous motor can rotate stably over the low-speed range with strong anti-interference capacity, a double closed-loop speed-regulation-based control scheme is employed. And to ensure high position control performance, a fuzzy-adaptive triple closed-loop position-regulation-based control scheme is employed. It terms of the control schemes, it deserves to be mentioned that main contributions include, firstly, the parameters of the proportional integral controllers in the double closed-loop speed-regulation structure is tuned relying on both stability and bandwidth analyses. Then, a fuzzy-adaptive proportional integral controller is specially-designed for the triple closed-loop position-regulation to adapt to the piano tuning applications. Simulation is conducted on a 20 rpm three-phase permanent magnet synchronous motor servo drive-based piano tuning system to validate the proposed piano tuning method and to verify the proposed control techniques.
Characterization of Pliocene Biogenic Gas Reservoirs from the Western Black Sea Shelf (Romanian Offshore) by Integration of Well Logs and Core Data
Authors: Niculescu Bogdan Mihai , Mocanu Victor
Published: October 2021

The successful interpretation of open-hole well logging data relies on jointly using all available petrophysical and geological information. This paper presents relevant case studies related to the integration of well logs with core measurements for exploration wells drilled in the Romanian continental shelf area of the Western Black Sea basin. The analyzed wells targeted gas-bearing sands and silts complexes of Early Pliocene (Dacian) age, developed in a deltaic to shallow marine sedimentary environment in two distinct fields. The wireline logging programs included conventional formation evaluation logs, pressure surveys, nuclear magnetic resonance, and borehole electrical imaging logs. The core dataset comprised routine and special measurements (porosity, grain density, permeability, water saturation, and Archie parameters) carried out at quasi-reservoir confining pressure. The wireline logging suites were interpreted via a deterministic workflow, including core-derived interpretation parameters. Other core-derived parameters were used for constraining and validating the log interpretations. The results show that a problem related to the ambiguity of formation water resistivity can be overcome through resistivity–porosity dependencies constructed to include potential aquifer zones in the proximity of the Dacian gas-bearing reservoirs. This study also revealed and quantified uncertainties regarding the estimation of gas–water contacts from formation pressure surveys, which can be mitigated by the confirmation or correction of pressure-derived fluid contacts via the well log interpretation results. Lastly, we identified a probable resistivity logs suppression effect related both to high contents of capillary-bound water and also to the limited resolution of electrical logging tools in the presence of sand-shale thin bedding or laminations.
Induction Heating in Domestic Cooking and Industrial Melting Applications: A Systematic Review on Modelling, Converter Topologies and Control Schemes
Authors: Vishnuram Pradeep , Ramachandiran Gunabalan , Sudhakar Babu Thanikanti , Nastasi Benedetto
Published: October 2021

In the current scenario, power electronic device-based induction heating (IH) technologies are widely employed in domestic cooking, industrial melting and medical applications. These IH applications are designed using different converter topologies, modulation and control techniques. This review article mainly focuses on the modelling of half-bridge series resonant inverter, electrical and thermal model of IH load. This review also analyses the performance of the converter topologies based on the power conversion stages, switching frequency, power rating, power density, control range, modulation techniques, load handling capacity and efficiency. Moreover, this paper provides insight into the future of IH application, with respect to the adaptation of wide band-gap power semiconductor materials, multi-output topologies, variable-frequency control schemes with minimum losses and filters designed to improve source-side power factor. With the identified research gap in the literature, an attempt has also been made to develop a new hybrid modulation technique, to achieve a wide range of power control with high efficiency. A 100 W full-bridge inverter prototype is realised both in simulation and hardware, with various modulation schemes using a PIC16F877A microcontroller. The results are compared with existing techniques and the comparisons reveal that the proposed scheme is highly viable and effective for the rendered applications.
Use of Kane’s Method for Multi-Body Dynamic Modelling and Control of Spar-Type Floating Offshore Wind Turbines
Authors: Sarkar Saptarshi , Fitzgerald Breiffni
Published: October 2021

This paper demonstrates the use of Kane’s method to derive equations of motion for a spar-type floating offshore wind turbine taking into account the flexibility of the members. The recently emerged Kane’s method reduces the effort required to derive equations of motion for complex multi-body systems, making them simpler to model and more readily solved by computers. Further, the installation procedure of external vibration control devices on the wind turbine using Kane’s method is described, and the ease of using this method has been demonstrated. A tuned mass damper inerter (TMDI) is installed in the tower for illustration. The excellent vibration mitigation properties of the TMDI are also presented in this paper.