bluuebunny/crossref_metadata_2025 huggingface dataset:
Caregiving and Shared Decision Making in Breast and Prostate Cancer Patients: A Systematic Review
Authors: Cincidda Clizia , Pizzoli Silvia Francesca Maria , Ongaro Giulia , Oliveri Serena , Pravettoni Gabriella
Published: January 2023

Background: A cancer diagnosis can impact patients’ and caregivers’ lives, posing different challenging situations. In particular, breast cancer and prostate cancer are two types of cancer involving families and especially spouses in challenges linked with the diagnosis and treatment process. Caregivers are usually involved in the treatment decision-making (TDM) process concerning patients’ clinical pathway, cancer treatment, and ongoing therapies. To date, no contributions provide an exhaustive overview of the role of caregivers in cancer care and their involvement in the TDM process related to the therapies. Methods: We performed a systematic review of caregiver and patients experiences and perceptions of caregiver involvement in cancer TDM. Articles were searched on Public/Publisher MEDLINE (PubMed), Excerpta Medica Database (Embase), Medical Literature Analysis and Retrieval System Online (Medline), and American Psychological Association APA PsycINFO. Results: 17 studies were included, 10 on prostate cancer and 7 on breast cancer. According to the reviewed studies, patients and caregivers experienced the cancer diagnosis with a sense of unity. Most patients preferred to have an active or collaborative role with caregivers in TDM, feeling it was important to consult or share the decision made with their caregivers. Caregivers preferred to collaborate with patients or let patients decide by themselves after considering their opinions. Caregiver involvement could have a positive influence on the patient’s medical decisions, even if cancer diagnosis and treatments overwhelmed patients and caregivers. Conclusions: These findings highlight the importance of using a perspective that focuses on the relationship between a patient and caregivers when they receive a cancer diagnosis and have to make a treatment decision. Targeting caregiver–patient dyads, rather than individuals, is important since a supported relationship could have a protective effect on psychological distress, quality of life (QOL), and relationship satisfaction. Moreover, dyads may benefit from interventions that focus on the needs of both the patient and caregiver.
Pain Incidence and Associated Risk Factors among Cancer Patients within 72 Hours after Surgery: A Large Retrospective Analysis
Authors: Qiu Junlan , Xin Yirong , Yao Jiazhen , Xu Lingkai , Meng Fang , Feng Lin , Shu Xiaochen , Zhuang Zhixiang
Published: January 2023

Background: A fundamental principle of pain management is to determine the distribution and causes of pain. However, relevant data among postoperative cancer patients based on a large amount of data remain sparse. Objective: We aimed to investigate the incidence of postoperative pain in cancer patients and to explore the associated risk factors. Methods: We retrospectively collected information on postoperative pain-evaluation records of cancer patients who underwent surgery between 1 January 2014 and 31 December 2019. Descriptive statistics were presented, and multinominal logistic regression analysis was performed to explore the risk factors associated with postoperative pain. Results: Among the 11,383 patients included in the study, the incidence of mild/moderate to severe pain at the 24th hour after surgery was 74.9% and 18.3%, respectively. At the 48th and 72nd hour after surgery, the incidence of mild pain increased slightly, while the incidence of moderate to severe pain continued to decrease. Female patients experienced a higher risk of pain (ORs: 1.37–1.58). Undergoing endoscopic surgery was associated with a higher risk of pain (ORs: 1.40–1.56). Patients with surgical sites located in the respiratory system had a higher risk of pain compared to in the digestive system (ORs: 1.35–2.13), and other patients had a relatively lower risk of pain (ORs: 0.11–0.61). Conclusion: The majority of cancer patients experienced varying degrees of postoperative pain but may not receive adequate attention and timely treatment. Female, young age and endoscopic surgery were associated with increased pain risk, and effective identification of these high-risk groups had positive implications for enhanced postoperative pain management.
Copepod Assemblages in A Large Arctic Coastal Area: A Baseline Summer Study
Authors: Dvoretsky Vladimir G. , Dvoretsky Alexander G.
Published: January 2023

To provide a baseline description of copepod assemblages in the Pechora Sea, an estuarine area with great economical and ecological importance, we conducted a survey during the summer season. A total of 24 copepod taxa were identified in the study, with Acartia longiremis, Calanus finmarchicus, Centropages hamatus, Copepoda nauplii, Eurytemora affinis, Oithona similis, Pseudocalanus spp., and Temora longicornis being the most numerous. The high diversity (Shannon index = 2.51 ± 0.06), density (18,720 ± 3376 individuals m−3) and biomass (89 ± 18 mg dry mass m−3) of copepods were revealed. Populations of common small copepod taxa were dominated by the young stages, indicating spawning, while older copepodites prevailed among medium- and large-sized species, showing that their reproduction occurred before our survey. Cluster analysis indicated three groups of stations that mainly differed in the abundance of particular species. There were clear associations between copepod assemblages and environmental variables. Statistical analyses showed significant correlations between copepod abundance and water temperature or sampling depth, while other factors had a lesser influence. Our results suggest a strong effect of local circulation and currents on the spatial pattern of the copepod assemblages in the study area. This study may be useful for future biomonitoring in the south-eastern Barents Sea.
Effect of EDTA Gel on Residual Subgingival Calculus and Biofilm: An In Vitro Pilot Study
Authors: Cobb Charles M. , Harrel Stephen K. , Zhao Donggao , Spencer Paulette
Published: January 2023

Background: Residual calculus, following scaling and root planing (SRP), is associated with persistent inflammation and the progression of periodontitis. This study examined the effects of a 24% neutral ethylenediaminetetraacetic acid (EDTA) gel on subgingival calculus and biofilms. Methods: Eleven single-rooted teeth extracted because of severe periodontal disease were randomly assigned to the following treatment groups: (1) three teeth served as untreated controls; (2) three teeth were treated by scaling and root planing (SRP) only; and (3) three teeth were treated by SRP + EDTA. The remaining two teeth, one SRP only and the other SRP + EDTA were designated for energy-dispersive X-ray spectroscopy (EDS) analysis. EDTA gel was placed on the SRP surface for 2 min and then burnished with a sterile cotton pellet. Results: SRP + EDTA treated specimens exhibited severely damaged biofilm and the disruption of the extracellular polymeric matrix. EDS scans of the smear layer and calculus featured reductions in the Weight % and Atomic % for N, F, Na, and S and increases in Mg, P, and Ca. Conclusions: A 25% neutral EDTA gel was applied after SRP severely disrupted the residual biofilm and altered the character of dental calculus and the smear layer as shown by reductions in the Weight % and Atomic % for N, F, Na, and S and increases in Mg, P, and Ca.
Distributed Model Predictive Consensus Control of Unmanned Surface Vehicles with Post-Verification
Authors: Yang Weilin , Shen Tianjing , Pan Tinglong , Hu Guanyang , Xu Dezhi
Published: January 2023

In this paper, the consensus control of unmanned surface vehicles (USVs) is investigated by employing a distributed model predictive control approach. A hierarchical control structure is considered during the controller design, where the upper layer determines the reference signals of USV velocities while the lower layer optimizes the control inputs of each USV. The main feature of this work is that a post-verification procedure is proposed to address the failure states caused by local errors or cyberattacks. Each USV compares the actual state and the predicted one obtained at the previous moment. This allows the estimation of local perturbations. In addition, the failure state of the USV can also be determined if a preset condition is satisfied, thus forcing a change in the communication topology and avoiding further impact. Simulations show that the proposed method is effective in USV formation control. Compared with the method without post-verification, the proposed approach is more robust when failure states occur.
Unsupervised Anomaly Detection for Intermittent Sequences Based on Multi-Granularity Abnormal Pattern Mining
Authors: Fan Lilin , Zhang Jiahu , Mao Wentao , Cao Fukang
Published: January 2023

In the actual maintenance of manufacturing enterprises, abnormal changes in after-sale parts demand data often make the inventory strategies unreasonable. Due to the intermittent and small-scale characteristics of demand sequences, it is difficult to accurately identify the anomalies in such sequences using current anomaly detection algorithms. To solve this problem, this paper proposes an unsupervised anomaly detection method for intermittent time series. First, a new abnormal fluctuation similarity matrix is built by calculating the squared coefficient of variation and the maximum information coefficient from the macroscopic granularity. The abnormal fluctuation sequence can then be adaptively screened by using agglomerative hierarchical clustering. Second, the demand change feature and interval feature of the abnormal sequence are constructed and fed into the support vector data description model to perform hypersphere training. Then, the unsupervised abnormal point location detection is realized at the micro-granularity level from the abnormal sequence. Comparative experiments are carried out on the actual demand data of after-sale parts of two large manufacturing enterprises. The results show that, compared with the current representative anomaly detection methods, the proposed approach can effectively identify the abnormal fluctuation position in the intermittent sequence of small samples, and also obtain better detection results.
A Conway–Maxwell–Poisson-Binomial AR(1) Model for Bounded Time Series Data
Authors: Chen Huaping , Zhang Jiayue , Liu Xiufang
Published: January 2023

Binomial autoregressive models are frequently used for modeling bounded time series counts. However, they are not well developed for more complex bounded time series counts of the occurrence of n exchangeable and dependent units, which are becoming increasingly common in practice. To fill this gap, this paper first constructs an exchangeable Conway–Maxwell–Poisson-binomial (CMPB) thinning operator and then establishes the Conway–Maxwell–Poisson-binomial AR (CMPBAR) model. We establish its stationarity and ergodicity, discuss the conditional maximum likelihood (CML) estimate of the model’s parameters, and establish the asymptotic normality of the CML estimator. In a simulation study, the boxplots illustrate that the CML estimator is consistent and the qqplots show the asymptotic normality of the CML estimator. In the real data example, our model takes a smaller AIC and BIC than its main competitors.
Fusions of Consciousness
Authors: Hoffman Donald D. , Prakash Chetan , Prentner Robert
Published: January 2023

What are conscious experiences? Can they combine to form new experiences? What are conscious subjects? Can they combine to form new subjects? Most attempts to answer these questions assume that spacetime, and some of its particles, are fundamental. However, physicists tell us that spacetime cannot be fundamental. Spacetime, they say, is doomed. We heed the physicists, and drop the assumption that spacetime is fundamental. We assume instead that subjects and experiences are entities beyond spacetime, not within spacetime. We make this precise in a mathematical theory of conscious agents, whose dynamics are described by Markov chains. We show how (1) agents combine into more complex agents, (2) agents fuse into simpler agents, and (3) qualia fuse to create new qualia. The possible dynamics of n agents form an n(n−1)-dimensional polytope with nn vertices—the Markov polytopeMn. The total fusions of n agents and qualia form an (n−1)-dimensional simplex—the fusion simplexFn. To project the Markovian dynamics of conscious agents onto scattering processes in spacetime, we define a new map from Markov chains to decorated permutations. Such permutations—along with helicities, or masses and spins—invariantly encode all physical information used to compute scattering amplitudes. We propose that spacetime and scattering processes are a data structure that codes for interactions of conscious agents: a particle in spacetime is a projection of the Markovian dynamics of a communicating class of conscious agents.
Cellular Competency during Development Alters Evolutionary Dynamics in an Artificial Embryogeny Model
Authors: Shreesha Lakshwin , Levin Michael
Published: January 2023

Biological genotypes do not code directly for phenotypes; developmental physiology is the control layer that separates genomes from capacities ascertained by selection. A key aspect is cellular competency, since cells are not passive materials but descendants of unicellular organisms with complex context-sensitive behavioral capabilities. To probe the effects of different degrees of cellular competency on evolutionary dynamics, we used an evolutionary simulation in the context of minimal artificial embryogeny. Virtual embryos consisted of a single axis of positional information values provided by cells’ ‘structural genes’, operated upon by an evolutionary cycle in which embryos’ fitness was proportional to monotonicity of the axial gradient. Evolutionary dynamics were evaluated in two modes: hardwired development (genotype directly encodes phenotype), and a more realistic mode in which cells interact prior to evaluation by the fitness function (“regulative” development). We find that even minimal ability of cells with to improve their position in the embryo results in better performance of the evolutionary search. Crucially, we observed that increasing the behavioral competency masks the raw fitness encoded by structural genes, with selection favoring improvements to its developmental problem-solving capacities over improvements to its structural genome. This suggests the existence of a powerful ratchet mechanism: evolution progressively becomes locked in to improvements in the intelligence of its agential substrate, with reduced pressure on the structural genome. This kind of feedback loop in which evolution increasingly puts more effort into the developmental software than perfecting the hardware explains the very puzzling divergence of genome from anatomy in species like planaria. In addition, it identifies a possible driver for scaling intelligence over evolutionary time, and suggests strategies for engineering novel systems in silico and in bioengineering.
Educational Mobile Apps for Programming in Python: Review and Analysis
Authors: Schnieder Maren , Williams Sheryl
Published: January 2023

The interest in educational apps is continuously increasing due to their potential to improve the learning environment of students through the personalisation and interaction of the technology. This paper provides an overview of educational mobile apps that teach programming in Python. Existing apps were reviewed, and suggestions for future development within this field are provided within this paper. A search was performed in the Android Google Play Store. The marketplace for educational apps teaching Python was illustrated based on 78 apps. A framework to categorise the apps based on the interactivity of the user interface was applied. Key revenue streams and features were identified (e.g., interactivity, user interface, cost/adds, reviews, downloads, and country). Their effect on download frequency and user rating was evaluated. The offer of multiple dynamic features, a certificate, and a Python IDE might have a positive influence on the number of downloads or user rating. More than one-third of these apps showed static content like a book, while the remainder had dynamic features such as a Python IDE, community support, competitions, interactive tutorials, and/or quizzes. The recommendation for future app developments is proposed based on these findings.
A Hybrid Method of Adaptive Cross Approximation Algorithm and Chebyshev Approximation Technique for Fast Broadband BCS Prediction Applicable to Passive Radar Detection
Authors: Wang Xing , Chen Lin , Li Fang , Liu Chunheng , Liu Ying , Xu Zhou , Zhang Hairong
Published: January 2023

A hybrid method combining the adaptive cross approximation method (ACA) and the Chebyshev approximation technique (CAT) is presented for fast wideband BCS prediction of arbitrary-shaped 3D targets based on non-cooperative radiation sources. The incident and scattering angles can be computed by using their longitudes, latitudes and altitudes according to the relative positions of the satellite, the target and the passive bistatic radar. The ACA technique can be employed to reduce the memory requirement and computation time by compressing the low-rank matrix blocks. By exploiting the CAT into ACA, it is only required to calculate the currents at several Chebyshev–Gauss frequency sampling points instead of direct point-by-point simulations. Moreover, a wider frequency band can be obtained by using the Maehly approximation. Three numerical examples are presented to validate the accuracy and efficiency of the hybrid ACA-CAT method.
Single-Image Dehazing Based on Improved Bright Channel Prior and Dark Channel Prior
Authors: Li Chuan , Yuan Changjiu , Pan Hongbo , Yang Yue , Wang Ziyan , Zhou Hao , Xiong Hailing
Published: January 2023

Single-image dehazing plays a significant preprocessing role in machine vision tasks. As the dark-channel-prior method will fail in the sky region of the image, resulting in inaccurately estimated parameters, and given the failure of many methods to address a large band of haze, we propose a simple yet effective method for single-image dehazing based on an improved bright prior and dark channel prior. First, we use the Otsu method by particle swarm optimization to divide the hazy image into sky regions and non-sky regions. Then, we use the improved bright channel prior and dark channel prior to estimate the parameters in the physical model. Second, we propose a weighted fusion function to efficiently fuse the parameters estimated by two priors. Finally, the clear image is restored through the physical model. Experiments illustrate that our method can solve the problem of the invalidation of the dark channel prior in the sky region well and achieve high-quality image restoration, especially for images with limited haze.
Self-Calibration Method of Noncontact AC Voltage Measurement
Authors: Zhang Wenbin , Wei Ran , Jiu Aerduoni , Cheng Kang , Yang Yonglong , Suo Chunguang
Published: January 2023

Realizing stable and reliable monitoring of a distribution network voltage environment can obtain real-time power parameter information and ensure the normal and safe operation of transmission lines, which is of great research significance and engineering value. Based on the distributed capacitance relationship between sensor and transmission line, an equivalent circuit capacitance voltage dividing model is proposed, and the relevant factors affecting the stability of the voltage dividing ratio are analyzed. The self-calibration principle of noncontact AC voltage measurement is proposed based on the system identification theory. The noncontact sensing structure is designed, a sensor probe prototype is fabricated, and a back-end conditioning circuit is designed to realize the overall measurement system. Finally, the validity of the measurement model is verified by simulation and experiment, and a measurement platform is built which proves the feasibility of the self-calibration method for noncontact voltage measurement. The experimental results show that the error is less than ±2%. This method can correctly restore the measured voltage waveform, has good linearity, and can realize wireless data transmission, which provides a new idea for the voltage measurement method of a distribution network.
A Novel Power Distribution Strategy and Its Online Implementation for Hybrid Energy Storage Systems of Electric Vehicles
Authors: Jiang Nanmei , Wang Xuemei , Kang Longyun
Published: January 2023

Hybrid energy storage systems (HESS) composed of a battery and ultracapacitor (UC) provide a feasible solution to the economy of electric vehicles (EVs). To fully exploit the potential of HESSs, a power distribution strategy that can split power between the battery and UC in HESSs plays an important role. Therefore, a novel power distribution strategy and its online application are proposed in this paper. First, a new and simple power distribution model of HESSs is proposed, and the model parameters are optimized offline through particle swarm optimization (PSO). Then, a driving condition recognizer based on a neural network is introduced, and the online application of the strategy is realized by combining offline global optimization and online recognition. Compared with the traditional rule-based strategy, the strategy proposed reduces the average fluctuation of the battery current by 52.53% and the average amplitude of the battery current by 11.51%. Meanwhile, it can be seen from the results that the strategy proposed is very close to the offline PSO-based strategy proposed and exhibits good performance under all driving cycles.
Secure Medical Data Collection in the Internet of Medical Things Based on Local Differential Privacy
Authors: Wang Jinpeng , Li Xiaohui
Published: January 2023

As big data and data mining technology advance, research on the collection and analysis of medical data on the internet of medical things (IoMT) has gained increasing attention. Medical institutions often collect users’ signs and symptoms from their devices for analysis. However, the process of data collection may pose a risk of privacy leakage without a trusted third party. To address this issue, we propose a medical data collection based on local differential privacy and Count Sketch (MDLDP). The algorithm first uses a random sampling technique to select only one symptom for perturbation by a single user. The perturbed data is then uploaded using Count Sketch. The third-party aggregates the user-submitted data to estimate the frequencies of the symptoms and the mean extent of their occurrence. This paper theoretically demonstrates that the designed algorithm satisfies local differential privacy and unbiased estimation. We also evaluated the algorithm experimentally with existing algorithms on a real medical dataset. The results show that the MDLDP algorithm has good utility for key-value type medical data collection statistics in the IoMT.
A Linear Quadratic Regression-Based Synchronised Health Monitoring System (SHMS) for IoT Applications
Authors: Upadhyay Divya , Garg Puneet , Aldossary Sultan Mesfer , Shafi Jana , Kumar Sachin
Published: January 2023

In recent days, the IoT along with wireless sensor networks (WSNs), have been widely deployed for various healthcare applications. Nowadays, healthcare industries use electronic sensors to reduce human errors while analysing illness more accurately and effectively. This paper proposes an IoT-based health monitoring system to investigate body weight, temperature, blood pressure, respiration and heart rate, room temperature, humidity, and ambient light along with the synchronised clock model. The system is divided into two phases. In the first phase, the system compares the observed parameters. It generates advisory to parents or guardians through SMS or e-mails. This cost-effective and easy-to-deploy system provides timely intimation to the associated medical practitioner about the patient’s health and reduces the effort of the medical practitioner. The data collected using the proposed system were accurate. In the second phase, the proposed system was also synchronised using a linear quadratic regression clock synchronisation technique to maintain a high synchronisation between sensors and an alarm system. The observation made in this paper is that the synchronised technology improved the performance of the proposed health monitoring system by reducing the root mean square error to 0.379% and the R-square error by 0.71%.
Designing Immersive Virtual Reality Simulation for Environmental Science Education
Authors: Cho Yongjoo , Park Kyoung Shin
Published: January 2023

Recently, severe environmental changes, such as global warming, climate change and environmental pollution, have become expected, and thus environmental education is becoming essential. The purpose of environmental education is to instill awareness in students to recognize and solve environmental problems. Virtual reality provides students with a spatial and temporal experience similar to reality, and it can increase their understanding of knowledge through immersion and interaction compared to traditional learning. In previous studies, virtual reality for education has mainly focused on experience, but it is difficult to find examples for environmental education. Hence, this research proposed an immersive virtual reality simulation for environmental education based on the virtual ecosystem model. It also presented two applications developed based on this simulation. This research aims at encouraging students’ active participation and motivation to solve the environmental problems while experiencing the results of interaction related to environmental factors in a virtual environment.
Intrinsic Emotion Recognition Considering the Emotional Association in Dialogues
Authors: Lim Myung-Jin , Yi Moung-Ho , Shin Ju-Hyun
Published: January 2023

Computer communication via text messaging or Social Networking Services (SNS) has become increasingly popular. At this time, many studies are being conducted to analyze user information or opinions and recognize emotions by using a large amount of data. Currently, the methods for the emotion recognition of dialogues requires an analysis of emotion keywords or vocabulary, and dialogue data are mostly classified as a single emotion. Recently, datasets classified as multiple emotions have emerged, but most of them are composed of English datasets. For accurate emotion recognition, a method for recognizing various emotions in one sentence is required. In addition, multi-emotion recognition research in Korean dialogue datasets is also needed. Since dialogues are exchanges between speakers. One’s feelings may be changed by the words of others, and feelings, once generated, may last for a long period of time. Emotions are expressed not only through vocabulary, but also indirectly through dialogues. In order to improve the performance of emotion recognition, it is necessary to analyze Emotional Association in Dialogues (EAD) to effectively reflect various factors that induce emotions. Therefore, in this paper, we propose a more accurate emotion recognition method to overcome the limitations of single emotion recognition. We implement Intrinsic Emotion Recognition (IER) to understand the meaning of dialogue and recognize complex emotions. In addition, conversations are classified according to their characteristics, and the correlation between IER is analyzed to derive Emotional Association in Dialogues (EAD) and apply them. To verify the usefulness of the proposed technique, IER applied with EAD is tested and evaluated. This evaluation determined that Micro-F1 of the proposed method exhibited the best performance, with 74.8% accuracy. Using IER to assess the EAD proposed in this paper can improve the accuracy and performance of emotion recognition in dialogues.
Intelligent Random Access for Massive-Machine Type Communications in Sliced Mobile Networks
Authors: Yang Bei , Wei Fengsheng , She Xiaoming , Jiang Zheng , Zhu Jianchi , Chen Peng , Wang Jianxiu
Published: January 2023

With the emerging Internet of Things paradigm, massive Machine-Type Communication (mMTC) has been identified as one of the prominent services that enables a broad range of applications with various Quality of Service (QoS) requirements for 5G-and-beyond networks. However, it is very difficult to employ a monolithic physical network to support various mMTC applications with differentiated QoS requirements. Moreover, in ultra-dense mobile networks, the scarcity of the preamble and Physical Downlink Control CHannel (PDCCH) resources may easily lead to resource collisions when a large number of devices access the network simultaneously. To tackle these issues, in this paper, we propose a network slicing-enabled intelligent random access framework for mMTC. First, by tailoring a gigantic physical network into multiple lightweight network slices, fine-grained QoS provisioning can be accomplished, and the collision domain of Random Access (RA) can be effectively reduced. In addition, we propose a novel concept of sliced preambles (sPreambles), based on which the transitional RA procedure is optimized, and the issue of preamble shortage is effectively relieved. Furthermore, with the aim of alleviating PDCCH resource shortage and improving transmission efficiency, we propose a learning-based resource-sharing scheme that can intelligently multiplex the PDCCH resources in the naturally dynamic environment. Simulation results show that the proposed framework can efficiently allocate resources to individual mMTC devices while guaranteeing their QoS requirements in random access processes.
Generating Even More Chaotic Instances in Hardware
Authors: de la Fraga Luis Gerardo , Ovilla-Martínez Brisbane
Published: January 2023

It is well known that multiplication inside a computer does not follow the associative property because of roundoff effects. It is possible to use this fact to generate other different chaotic instances of chaotic maps or oscillators when a multiplication of three terms appears. Chaos is very sensitive to small changes in the initial conditions and amplifies these small rounding effects. We use this condition to build different chaotic instances, which give different results, of the Lü oscillator and the 2D map, and we show one application to create new instances of a pseudo random number generator using the 2D map. Both chaotic systems are simulated in software and in hardware within an FPGA where another 144 different 2D map instances and 81 different Lü oscillators can be created. To best of our knowledge, it is the first paper that analyze the construction of new chaotic entities by using the roundoff effects.
A Robust Medical Image Watermarking Scheme Based on Nature-Inspired Optimization for Telemedicine Applications
Authors: Pallaw Vijay Krishna , Singh Kamred Udham , Kumar Ankit , Singh Teekam , Swarup Chetan , Goswami Anjali
Published: January 2023

Medical images and patient information are routinely transmitted to a remote radiologist to assist in diagnosis. It is critical in e-healthcare systems to ensure that data are accurately transmitted. Medical images of a person’s body can be used against them in many ways, including by transmitting them. Copyright and intellectual property laws prohibit the unauthorized use of medical images. Digital watermarking is used to prove the authenticity of the medical images before diagnosis. In this paper, we proposed a hybrid watermarking scheme using the Slantlet transform, randomized-singular value decomposition, and optimization techniques inspired by nature (Firefly algorithm). The watermark image is encrypted using the XOR encryption technique. Extensive testing reveals that our innovative approach outperforms the existing methods based on the NC, SSIM, and PSNR. The SSIM and NC values of watermarked image and extracted watermark are close to or equal to 1 at a scaling factor of 0.06, and the PSNR of the proposed scheme lies between 58 dB and 59 dB, which shows the better performance of the scheme.
An Asymmetrical 19-Level Inverter with a Reduced Number of Switches and Capacitors
Authors: Sagvand Farzad , Siahbalaee Jafar , Koochaki Amangaldi
Published: January 2023

Multilevel inverters are able to provide loads with voltages of high power quality using several DC sources, capacitors, switches, and diodes in their structures. However, the usage of the higher number of semiconductor devices (switches and diodes) and capacitors causes an increase in losses and costs and decreases their efficiency. Thus, lowering the number of switches and capacitors is a challenging issue in designing a multilevel inverter. In this paper, an asymmetrical multilevel inverter is proposed that produces 19-level output voltages. The circuit is composed of nine switches, six diodes, two capacitors, and two isolated DC sources. In comparison with other topologies, the most important advantage of the introduced 19-level topology is the usage of a lower number of switches and capacitors, which leads to a decrease in the number of gate drivers and the total volume of the system. During the charging process, capacitors never connect to each other in series, i.e., they are self-balancing and do not require the extra circuits. The proposed topology offers a total harmonic distortion (THD) of 7.4% in the output voltage, which is less than 8%, complying with the IEEE standards. The performance of the topology is validated under various load conditioning through an experimental setup in the laboratory.
Review of Green Supply-Chain Management Diffusion in the Context of Energy Transformation
Authors: Xu Yan , Liu Aijun , Li Zengxian , Li Jiaxin , Xiong Jiamin , Fan Peng
Published: January 2023

Against the background of continuously rising energy carbon emissions, accelerated energy transformation in developed countries, and increased international attention to energy security, there is still a large amount of energy consumption in the manufacturing industry. Promoting the diffusion of green supply-chain management is becoming a powerful tool to support energy transformation and energy conservation and emission reduction in the manufacturing industry. Based on this, we first conducted a scientific metrological analysis of 4960 articles in relevant fields in the Web of Science database, presenting the research status of green supply-chain management diffusion in the context of energy transformation. Second, we identified factors that affect the implementation of green supply-chain management, and analyzed the diffusion path of green supply-chain management among enterprises. Finally, based on the energy situation, enterprise operation, and implementation of environmental protection laws and regulations in Shaanxi Province, China, we determined the current situation, obstacles, and development direction of green supply-chain management diffusion of enterprises in the context of energy transformation. The research found that: at this stage, there are still some deficiencies in the research on the mechanism of green supply-chain management in the internal communication of enterprises; in the future, the diffusion of green supply-chain management can be further developed around social performance and energy transformation technology; and we can help energy transformation by strengthening policy guidance and assisting enterprise reform.
Advanced Exergy Analysis of Ultra-Low GWP Reversible Heat Pumps for Residential Applications
Authors: Voloshchuk Volodymyr , Gullo Paride , Nikiforovich Eugene
Published: January 2023

Exergy-based methods provide engineers with the best information with respect to options for improving the overall thermodynamic efficiency of an energy conversion system. This paper presents the results of an advanced exergy analysis of an air-to-water reversible heat pump whose performance was analyzed with respect to different working fluids. Environmentally deleterious refrigerants, i.e., R410A and R134a (baselines), and their eco-friendly replacements (R290, R152a, R1234ze(E), and R1234yf) were selected. The evaluations were conducted under the same operating conditions (i.e., with the same cooling and heating demands and outdoor temperatures). Based on conventional exergy analysis, it was determined that different priorities should be given for the thermodynamic improvement of the components according to which heating and cooling modes of the system are in use. Therefore, integrated parameters, i.e., the annual values of exergy destruction, were applied for further analysis. The results obtained showed that the heat pump using R410A provided the largest degree of annual exergy destruction estimated on the basis of conventional exergy analysis (5913 kWh), whereas the heat pump using R290 offered the lowest one (4522 kWh). The annual exergy destruction of the R410A cycle with only unavoidable irreversibilities could be decreased by 50%. In this case, compared to R410A and R134a, R152a and R290 provided lower values of the total annual unavoidable aspects of exergy destruction. Considering technological limitations, when removing all the avoidable irreversibilities within the air exchanger, the largest decrease in the total exergy destruction within the system could be reached. The results obtained from the analysis of the removable irreversibilities showed that the mutual interactions between the compressor, evaporator, and condenser were weak. Finally, it was concluded that, from a thermodynamic point of view, the adoption of R152a and R290 in reversible air-to-water heat pumps as replacements for R410A and R134a is advisable.
Cycle-to-Cycle Variation of the Combustion Process in a Diesel Engine Fueled with Rapeseed Oil—Diethyl Ether Blends
Authors: Górski Krzysztof , Smigins Ruslans , Matijošius Jonas , Tziourtzioumis Dimitrios
Published: January 2023

The application of rapeseed oil (RO) blends with diesel fuel and/or alcohols and/or ethers is known to significantly affect the combustion process. Aiming to further investigate the effects of rapeseed oil in a blend with diethyl ether (DEE) on this process, the coefficient of variation of the mean indicated pressure (COVMIP) of a 2.5l direct injection diesel engine was calculated. The analysis of the experimental results revealed the repeatability of the combustion process variability of diesel fuel (DF), rapeseed oil (RO), and DEE/RO blends containing up to 20% DEE. In these cases, the COVMIP does not exceed 4%. Additionally, it became obvious that for a higher content of DEE in blend with RO, the cyclic repeatability of the mean indicated pressure (MIP) was reduced. Thus, the values of COVMIP for fuels containing 30 and 40% of DEE by vol. in blend with RO were even three times higher than the values obtained for the reference fuel i.e., DF. The results indicate that the increased content of DEE in the mixture with RO is disadvantageous as it leads to excessive unevenness of the engine operation compared to its fueling with DF. The observed deterioration of the combustion process is caused by the vapor locks, which are formed due to the evaporation of volatile DEE in the fuel line, leading to the interrupted operation of the fuel injector.
Dynamic Performance of Organic Rankine Cycle Driven by Fluctuant Industrial Waste Heat for Building Power Supply
Authors: Li Tailu , Wang Zeyu , Wang Jingyi , Gao Xiang
Published: January 2023

Organic Rankine cycle (ORC) is widely used to recover low-grade waste heat. The effects of heat-source temperature amplitude and period on ORC systems are discussed based on operating parameters and power-generation performance. The maximum allowable heat-source temperature amplitude under different superheat and average heat-source temperature was discussed. The results showed that the amplitudes of power-generation and operating parameters were proportional to the amplitude. The operating parameters of the system had a certain response time and were proportional to the period. The performance of ORC deteriorated at any amplitude or period. The superheat degree was not conducive to the power-generation performance, but could effectively avoid the working fluid is wet vapor into the expander. This conclusion can be applied to any ORC system driven by a single organic working fluid, which provides theoretical support for the design of control systems and power-generation device.
Multi-Criteria Decision Making (MCDM) Methods and Concepts
Authors: Taherdoost Hamed , Madanchian Mitra
Published: January 2023

Multi-criteria decision-making (MCDM) is one of the main decision-making problems which aims to determine the best alternative by considering more than one criterion in the selection process. MCDM has manifold tools and methods that can be applied in different fields from finance to engineering design. This entry aims to provide a survey on the MCDM concept, its applications, main categories, and different methods. The final section provides manifold information and statistics on the published works in the MCDM fields. Some of the main methods are also listed in this section.
Growth-Season Precipitation Variations in the Joint Area between the Asian Westerly Jet Area and the Climate Transition Zone over the Past Two Centuries
Authors: Sun Bolin , Ma Long , Liu Tingxi , Huang Xing
Published: January 2023

The uneven water resource distribution between different areas across the globe has been worsening. The area where the eastern margin of the Asian westerly jet area meets the low-altitude area of the transition zone (which has a temperate continental monsoon climate) is delicate and sensitive to climate change. An urgent issue is to determine the climate change pattern of this area in the past. On the basis of core samples of four tree species in four typical regions of this joint area, we built a standardized chronological table according to tree-ring width and reconstructed the cumulative precipitation from March to August series in the above area in the past 203–343 years. Since the reconstructed results corresponded well to climate events and drought and flooding periods in historical records, the reconstructed model was stable and reliable. The results were as follows: The precipitation in the study area from east to the west in the growth season has changed dramatically, and the period has gradually shortened. In the 19th century, there was a wet period in the high-latitude area. From the 19th century to the 1950s, the entire study area experienced a significant dry period that lasted for 20–45 years; the starting time of the dry period was gradually delayed from the west to the middle, and the wet period gradually grew shorter at an increasing rate. In the past half-century, this area experienced a significant drought period, and the drying rate was higher in the west and east regions than in the central region. In the past two centuries, the precipitation varied significantly in the study area, and the wet period played a dominant role, growing gradually shorter. The middle and west regions of the Asian westerly jet area and the high-latitude regions of the transition zone all experienced significant wetting or drying processes in the first half of the 19th century, and since then, all areas experienced significant drying processes under the influence of global warming, which may be intensified by the westerly circulation.
Genetic Diversity and Population Structure of Scots Pine (Pinus sylvestris L.) in Middle Siberia
Authors: Sheller Marina , Tóth Endre György , Ciocîrlan Elena , Mikhaylov Pavel , Kulakov Sergey , Kulakova Nadezhda , Melnichenko Natalia , Ibe Aleksey , Sukhikh Tatyana , Curtu Alexandru Lucian
Published: January 2023

Scot pine (Pinus sylvestris L.) is one the main forest-forming tree species in Russia, and is of great ecological, economic and social value. In order to manage the genetic resources of this important forest tree species efficiently, knowledge of its genetic diversity and structure is needed. Here, we assessed the genetic variation of 17 populations representing different parts of Scots pine range in Russia by using nuclear microsatellite markers (nSSR). Specifically, 14 populations were chosen within the natural distribution range of the species in Middle Siberia and three distant populations were sampled from the European part of Russia, the West Siberia and the Russian Far East. All populations showed high values of genetic diversity (HE = 0.514) and AR = 4.150. However, the easternmost population has shown the lowest level of genetic diversity (HE = 0.433) and allelic richness (AR = 3.505). Five genetic groups could be detected that correspond to: the European part of Russia, the south of Middle Siberia, the northwest of Middle Siberia, West and Middle Siberia, and the Russian Far East. However, the European population was the most genetically distinct one. The variation among Scots pine populations accounted for only 5% of the total variance. The highest level of genetic differentiation was found only between westernmost and easternmost populations (FST = 0.097). Our genetic data may contribute to a better understanding of the pattern of genetic diversity of Scots pine populations in Middle Siberia and help the conservation efforts of these genetic resources.
Experimental Study on the Properties of Mixed-Fiber Concrete Shield Tunnel Segments Subjected to High Temperatures
Authors: Zhang Yajun , Wang Yao , Ren Zhaoqing
Published: January 2023

In order to study the mechanical and damage behavior of concrete shield tunnel segments under a high temperature, two self-compacting concrete and three mixed-fiber (steel and polypropylene fiber) self-compacting concrete test blocks were designed. The influence of several key factors, including fire duration, pre-loading, and concrete type, on the fire behavior of concrete shield tunnel segments were studied. The results show that the type of fiber and pre-loading have an important influence on crack development in concrete shield tunnel segments. Compared with undoped segments, cracks in segments with steel fibers and polypropylene fibers appeared later, and the average crack spacing decreased. The pre-loading has an important effect on the vertical deformation before and after the temperature rise. As the load level increases, so does the deformation after the temperature rise. The influence of the initial load level should be considered when designing the fire resistance of the segment.
New Explicit Propagating Solitary Waves Formation and Sensitive Visualization of the Dynamical System
Authors: Zulqarnain Rana Muhammad , Ma Wen-Xiu , Eldin Sayed M. , Mehdi Khush Bukht , Faridi Waqas Ali
Published: January 2023

This work discusses the soliton solutions for the fractional complex Ginzburg–Landau equation in Kerr law media. It is a particularly fascinating model in this context as it is a dissipative variant of the Hamiltonian nonlinear Schrödinger equation with solutions that create localized singularities in finite time. The ϕ6-model technique is one of the generalized methodologies exerted on the fractional complex Ginzburg–Landau equation to find the new solitary wave profiles. As a result, solitonic wave patterns develop, including Jacobi elliptic function, periodic, dark, bright, single, dark-bright, exponential, trigonometric, and rational solitonic structures, among others. The assurance of the practicality of the solitary wave results is provided by the constraint condition corresponding to each achieved solution. The graphical 3D and contour depiction of the attained outcomes is shown to define the pulse propagation behaviors while imagining the pertinent data for the involved parameters. The sensitive analysis predicts the dependence of the considered model on initial conditions. It is a reliable and efficient technique used to generate generalized solitonic wave profiles with diverse soliton families. Furthermore, we ensure that all results are innovative and mark remarkable impacts on the prevailing solitary wave theory literature.