bluuebunny/crossref_metadata_2025 huggingface dataset:
Health-Promoting Behaviours following Primary Treatment for Cancer: A Rural–Urban Comparison from a Cross-Sectional Study
Authors: Nelson David , McGonagle Ian , Jackson Christine , Tsuro Trish , Scott Emily , Gussy Mark , Kane Ros
Published: January 2023

Aim: To compare health-promoting behaviours among rural and urban residents following primary treatment for cancer. Methods: A cross-sectional survey collecting demographic variables and data pertaining to health-promoting behaviours, documented using the 52-item Health Promotion Lifestyle Profile II (HPLP-II) measure, which is categorised into six subscales: (1) health responsibility, (2) spiritual growth, (3) physical activity, (4) interpersonal relations, (5) nutrition, and (6) stress management. Residence was defined using the U.K. Office for National Statistics RUC 2011 Rural Urban Classifications. The Index of Multiple Deprivation (IMD) Decile was used to measure deprivation. Quantitative data were analysed using independent samples t-test and multiple linear regression. Qualitative data from open-ended questions were analysed thematically. Results: In total, 227 participants with a range of cancer types completed the questionnaire. Fifty-three percent were residents in urban areas and forty-five percent in rural areas. Rural participants scored significantly higher on health responsibility (p = 0.001), nutrition (p = 0.001), spiritual growth (p = 0.004), and interpersonal relationships (p = 0.001), as well as on the overall HPLP-II (p = 0.001). When controlling for deprivation, age, marital status, and education, rural–urban residence was a significant predictor of exhibiting health-promoting behaviours. A central theme from the qualitative data was the concept of “moving on” from cancer following treatment, by making adjustments to physical, social, psychological, spiritual, and emotional wellbeing. Conclusions: This research revealed, for the first time, differences in health-promoting behaviours among rural and urban U.K. populations who have completed primary cancer treatment. Rural residence can provide a positive environment for engaging with health-promoting behaviours following a cancer diagnosis and treatment.
Sociodemographic and Clinical Correlates Associated with the Frequent Service Users in an Italian Psychiatric Emergency Department
Authors: Aguglia Andrea , Corsini Giovanni Pietro , Costanza Alessandra , Berti Andrea , Bruno Edoardo , Escelsior Andrea , Sanvi James , Trabucco Alice , Vai Eleonora , Amerio Andrea , Serafini Gianluca , Amore Mario
Published: January 2023

Background: The aim of the present study is to identify the main sociodemographic and clinical correlates associated with frequent service users (FSUs) in an Italian psychiatric emergency department. Methods: This study is an observational and prospective clinical investigation. All subjects (N = 549) consecutively admitted to the Psychiatric Inpatient Unit of the IRCCS Ospedale Policlinico San Martino ((Genoa, Italy) were recruited over a period of 18 months. Results: On average, FSUs were more likely to be single (75.0% vs. 64.0, p = 0.001), younger (38.79 years ± 14.68 vs. 45.94 years ± 16.94, p = 0.028), with an earlier onset (20.15 years ± 7.22 vs. 29.33 years ± 15.96, p < 0.001), and longer length of hospitalisation (13.65 days ± 12.40 vs. 9.89 ± 10.15, p = 0.006) compared to non-FSUs. While bipolar disorder was the most common primary diagnosis in both FSUs and non-FSUs, cluster B personality disorder was particularly elevated in FSUs (30.3% vs. 10.4%, p < 0.001). Furthermore, FSUs were more prone to substance use disorder (63.6% vs. 40.0%, p < 0.001), particularly cannabis (45.5% vs. 15.3%, p < 0.001), cocaine (33.3% vs. 10.4%, p < 0.001), and heroin (19.7% vs. 5.8%, p < 0.001), and were more likely to have non-suicidal self-injuries (21.2% vs. 6.8%, p < 0.001). FSUs were significantly more likely to be discharged against medical advice (18.2% vs. 5.6%, p < 0.001) or to have at least one escape attempt from the psychiatric ward (12.1% vs. 0.8%, p < 0.001). Conclusions: Specific clinical and social profiles of patients who repeatedly utilised the services of a psychiatric emergency department have been identified. Our findings can be used to develop suitable structures to support and reintegrate FSUs into society and work life.
Cardiovascular Involvement in Tuberculosis: From Pathophysiology to Diagnosis and Complications—A Narrative Review
Authors: Marcu Dragos Traian Marius , Adam Cristina Andreea , Mitu Florin , Cumpat Carmen , Aursulesei Onofrei Viviana , Zabara Mihai Lucian , Burlacu Alexandru , Crisan Dabija Radu
Published: January 2023

Although primarily a lung disease, extra-pulmonary tuberculosis (TB) can affect any organ or system. Of these, cardiovascular complications associated with disease or drug toxicity significantly worsen the prognosis. Approximately 60% of patients with TB have a cardiovascular disease, the most common associated pathological entities being pericarditis, myocarditis, and coronary artery disease. We searched the electronic databases PubMed, MEDLINE, and EMBASE for studies that evaluated the impact of TB on the cardiovascular system, from pathophysiological mechanisms to clinical and paraclinical diagnosis of cardiovascular involvement as well as the management of cardiotoxicity associated with antituberculosis medication. The occurrence of pericarditis in all its forms and the possibility of developing constrictive pericarditis, the association of concomitant myocarditis with severe systolic dysfunction and complication with acute heart failure phenomena, and the long-term development of aortic aneurysms with risk of complications, as well as drug-induced toxicity, pose complex additional problems in the management of patients with TB. In the era of multidisciplinarity and polymedication, evidence-based medicine provides various tools that facilitate an integrative management that allows early diagnosis and treatment of cardiac pathologies associated with TB.
Reproducibility and Predictive Value of White-Coat Hypertension in Young to Middle-Age Subjects
Authors: Palatini Paolo , Mos Lucio , Saladini Francesca , Vriz Olga , Fania Claudio , Ermolao Andrea , Battista Francesca , Rattazzi Marcello
Published: January 2023

(1) Aim. The aim of the study was to investigate the reproducibility of white-coat hypertension (WCH) and its predictive capacity for hypertension needing antihypertensive treatment (HT) in young to middle-age subjects. (2) Methods. We investigated 1096 subjects from the HARVEST. Office and 24 h blood pressures (BP) were measured at baseline and after 3 months. The reproducibility of WCH was evaluated with kappa statistics. The predictive capacity of WCH was tested in multivariate Cox models (N = 1050). (3) Results. Baseline WCH was confirmed at 3-month assessment in 33.3% of participants. Reproducibility was fair (0.27, 95%CI 0.20–0.37) for WCH, poor (0.14, 95%CI 0.09–0.19) for office hypertension, and moderate (0.47, 95%CI 0.41–0.53) for ambulatory hypertension. WCH assessed either at baseline or after 3 months (unstable WCH) was not a significant predictor of HT during 17.4 years of follow-up. However, participants who had WCH both at baseline and after 3 months (stable WCH) had an increased risk of HT compared to the normotensives (Hazard ratio, 1.50, 95%CI 1.06–2.1). (4) Conclusions. These results show that WCH has limited reproducibility. WCH diagnosed with two BP assessments but not with one showed an increased risk of future HT. Our data indicate that WCH should be identified with two sets of office and ambulatory BP measurements.
Texture Analysis in Uterine Cervix Carcinoma: Primary Tumour and Lymph Node Assessment
Authors: Ștefan Paul-Andrei , Coțe Adrian , Csutak Csaba , Lupean Roxana-Adelina , Lebovici Andrei , Mihu Carmen Mihaela , Lenghel Lavinia Manuela , Pușcas Marius Emil , Roman Andrei , Feier Diana
Published: January 2023

The conventional magnetic resonance imaging (MRI) evaluation and staging of cervical cancer encounters several pitfalls, partially due to subjective evaluations of medical images. Fifty-six patients with histologically proven cervical malignancies (squamous cell carcinomas, n = 42; adenocarcinomas, n = 14) who underwent pre-treatment MRI examinations were retrospectively included. The lymph node status (non-metastatic lymph nodes, n = 39; metastatic lymph nodes, n = 17) was assessed using pathological and imaging findings. The texture analysis of primary tumours and lymph nodes was performed on T2-weighted images. Texture parameters with the highest ability to discriminate between the two histological types of primary tumours and metastatic and non-metastatic lymph nodes were selected based on Fisher coefficients (cut-off value > 3). The parameters’ discriminative ability was tested using an k nearest neighbour (KNN) classifier, and by comparing their absolute values through an univariate and receiver operating characteristic analysis. Results: The KNN classified metastatic and non-metastatic lymph nodes with 93.75% accuracy. Ten entropy variations were able to identify metastatic lymph nodes (sensitivity: 79.17–88%; specificity: 93.48–97.83%). No parameters exceeded the cut-off value when differentiating between histopathological entities. In conclusion, texture analysis can offer a superior non-invasive characterization of lymph node status, which can improve the staging accuracy of cervical cancers.
Automated Rice Phenology Stage Mapping Using UAV Images and Deep Learning
Authors: Lu Xiangyu , Zhou Jun , Yang Rui , Yan Zhiyan , Lin Yiyuan , Jiao Jie , Liu Fei
Published: January 2023

Accurate monitoring of rice phenology is critical for crop management, cultivars breeding, and yield estimating. Previously, research for phenology detection relied on time-series data and orthomosaic and manually plotted regions, which are difficult to automate. This study presented a novel approach for extracting and mapping phenological traits directly from the unmanned aerial vehicle (UAV) photograph sequence. First, a multi-stage rice field segmentation dataset containing four growth stages and 2600 images, namely PaddySeg, was built. Moreover, an efficient Ghost Bilateral Network (GBiNet) was proposed to generate trait masks. To locate the trait of each pixel, we introduced direct geo-locating (DGL) and incremental sparse sampling (ISS) techniques to eliminate redundant computation. According to the results on PaddySeg, the proposed GBiNet with 91.50% mean-Intersection-over-Union (mIoU) and 41 frames-per-second (FPS) speed outperformed the baseline model (90.95%, 36 FPS), while the fastest GBiNet_t reached 62 FPS which was 1.7 times faster than the baseline model, BiSeNetV2. Additionally, the measured average DGL deviation was less than 1% of the relative height. Finally, the mapping of rice phenology was achieved by interpolation on trait value–location pairs. The proposed approach demonstrated great potential for automatic rice phenology stage surveying and mapping.
Comparing the Conditional Logit Estimates and True Parameters under Preference Heterogeneity: A Simulated Discrete Choice Experiment
Authors: Jumamyradov Maksat , Craig Benjamin M. , Munkin Murat , Greene William
Published: January 2023

Health preference research (HPR) is the subfield of health economics dedicated to understanding the value of health and health-related objects using observational or experimental methods. In a discrete choice experiment (DCE), the utility of objects in a choice set may differ systematically between persons due to interpersonal heterogeneity (e.g., brand-name medication, generic medication, no medication). To allow for interpersonal heterogeneity, choice probabilities may be described using logit functions with fixed individual-specific parameters. However, in practice, a study team may ignore heterogeneity in health preferences and estimate a conditional logit (CL) model. In this simulation study, we examine the effects of omitted variance and correlations (i.e., omitted heterogeneity) in logit parameters on the estimation of the coefficients, willingness to pay (WTP), and choice predictions. The simulated DCE results show that CL estimates may have been biased depending on the structure of the heterogeneity that we used in the data generation process. We also found that these biases in the coefficients led to a substantial difference in the true and estimated WTP (i.e., up to 20%). We further found that CL and true choice probabilities were similar to each other (i.e., difference was less than 0.08) regardless of the underlying structure. The results imply that, under preference heterogeneity, CL estimates may differ from their true means, and these differences can have substantive effects on the WTP estimates. More specifically, CL WTP estimates may be underestimated due to interpersonal heterogeneity, and a failure to recognize this bias in HPR indirectly underestimates the value of treatment, substantially reducing quality of care. These findings have important implications in health economics because CL remains widely used in practice.
An Artificial Neural Network for Solar Energy Prediction and Control Using Jaya-SMC
Authors: Jlidi Mokhtar , Hamidi Faiçal , Barambones Oscar , Abbassi Rabeh , Jerbi Houssem , Aoun Mohamed , Karami-Mollaee Ali
Published: January 2023

In recent years, researchers have focused on improving the efficiency of photovoltaic systems, as they have an extremely low efficiency compared to fossil fuels. An obvious issue associated with photovoltaic systems (PVS) is the interruption of power generation caused by changes in solar radiation and temperature. As a means of improving the energy efficiency performance of such a system, it is necessary to predict the meteorological conditions that affect PV modules. As part of the proposed research, artificial neural networks (ANNs) will be used for the purpose of predicting the PV system’s current and voltage by predicting the PV system’s operating temperature and radiation, as well as using JAYA-SMC hybrid control in the search for the MPP and duty cycle single-ended primary-inductor converter (SEPIC) that supplies a DC motor. Data sets of size 60538 were used to predict temperature and solar radiation. The data set had been collected from the Department of Systems Engineering and Automation at the Vitoria School of Engineering of the University of the Basque Country. Analyses and numerical simulations showed that the technique was highly effective. In combination with JAYA-SMC hybrid control, the proposed method enabled an accurate estimation of maximum power and robustness with reasonable generality and accuracy (regression (R) = 0.971, mean squared error (MSE) = 0.003). Consequently, this study provides support for energy monitoring and control.
Remote Real-Time Optical Layers Performance Monitoring Using a Modern FPMT Technique Integrated with an EDFA Optical Amplifier
Authors: Ibrahim Ahmed Atef , Fouad Mohammed Mohammed , Hamdi Azhar Ahmed
Published: January 2023

Fiber performance monitoring using modern online technologies in the next generation of intelligent optical networks allows for identifying the source of the degeneration and putting in protective steps to increase remote optical network stability & reliability. In this paper, the performance of the fiber performance monitoring tool (FPMT) technique was improved by integrating it with optical amplifier boards. In this regard, the improved technique detects optical layer events and all fiber soft and hard failures at the online remote rather than disrupting the data flow with a measurement accuracy for defect location of up to ~99.9%, small tolerance of up to ~1 m, the longest distance to detecting optical line defects of up to ~300km, and enhanced power budget for the system with optimum insertion-loss of up to ~0.0 dB. The proposed integration method provides better results with an excellent and efficient solution at fault location measurement & detection in real-time with good financial implications of the technique. The competitiveness of the improved technique over the actual optical networks has been successfully confirmed through application to Huawei labs infrastructure nodes and displayed experimental simulation results.
A Review of Distribution System State Estimation Methods and Their Applications in Power Systems
Authors: Vijaychandra Joddumahanthi , Prasad Bugatha Ram Vara , Darapureddi Vijaya Kumar , Rao Bathina Venkateswara , Knypiński Łukasz
Published: January 2023

This paper summarizes a review of the distribution system state estimation (DSSE) methods, techniques, and their applications in power systems. In recent years, the implementation of a distributed generation has affected the behavior of the distribution networks. In order to improve the performance of the distribution networks, it is necessary to implement state estimation methods. As transmission networks and distribution networks are not similar due to variations in line parameters, buses, and measuring instruments, transmission state estimation cannot be implemented in distribution state estimation. So, some aspects, such as accuracy, computational time, and efficiency, should be taken into account when designing distribution state estimation methods. In this paper, the traditional methods are reviewed and analyzed with data-driven techniques in order to present the advantages and disadvantages of the various methods.
Fast FPGA-Based Multipliers by Constant for Digital Signal Processing Systems
Authors: Bureneva Olga , Mironov Sergey
Published: January 2023

Traditionally, the usual multipliers are used to multiply signals by a constant, but multiplication by a constant can be considered as a special operation requiring the development of specialized multipliers. Different methods are being developed to accelerate multiplications. A large list of methods implement multiplication on a group of bits. The most known one is Booth’s algorithm, which implements two-digit multiplication. We propose a modification of the algorithm for the multiplication by three digits at the same time. This solution reduces the number of partial products and accelerates the operation of the multiplier. The paper presents the results of a comparative analysis of the characteristics of Booth’s algorithm and the proposed algorithm. Additionally, a comparison with built-in FPGA multipliers is illustrated.
Effects of Alcohol-Blended Waste Plastic Oil on Engine Performance Characteristics and Emissions of a Diesel Engine
Authors: Kaewbuddee Chalita , Maithomklang Somkiat , Aengchuan Prasert , Wiangkham Attasit , Klinkaew Niti , Ariyarit Atthaphon , Sukjit Ekarong
Published: January 2023

The current study aims to investigate and compare the effects of waste plastic oil blended with n-butanol on the characteristics of diesel engines and exhaust gas emissions. Waste plastic oil produced by the pyrolysis process was blended with n-butanol at 5%, 10%, and 15% by volume. Experiments were conducted on a four-stroke, four-cylinder, water-cooled, direct injection diesel engine with a variation of five engine loads, while the engine’s speed was fixed at 2500 rpm. The experimental results showed that the main hydrocarbons present in WPO were within the range of diesel fuel (C13–C18, approximately 74.39%), while its specific gravity and flash point were out of the limit prescribed by the diesel fuel specification. The addition of n-butanol to WPO was found to reduce the engine’s thermal efficiency and increase HC and CO emissions, especially when the engine operated at low-load conditions. In order to find the suitable ratio of n-butanol blends when the engine operated at the tested engine load, the optimization process was carried out by considering the engine’s load and ratio of the n-butanol blend as input factors and the engine’s performance and emissions as output factors. It was found that the multi-objective function produced by the general regression neural network (GRNN) can be modeled as the multi-objective function with high predictive performances. The coefficient of determination (R2), mean absolute percentage error (MAPE), and root mean square error (RSME) of the optimization model proposed in the study were 0.999, 2.606%, and 0.663, respectively, when brake thermal efficiency was considered, while nitrogen oxide values were 0.998, 6.915%, and 0.600, respectively. As for the results of the optimization using NSGA-II, a single optimum value may not be attained as with the other methods, but the optimization’s boundary was obtained, which was established by making a trade-off between brake thermal efficiency and nitrogen oxide emissions. According to the Pareto frontier, the engine load and ratio of the n-butanol blend that caused the trade-off between maximum brake thermal efficiency and minimum nitrogen oxides are within the approximate range of 37 N.m to 104 N.m and 9% to 14%, respectively.
Tips for Buildings Energy Saving: Results of Some Research
Authors: Faranda Roberto Sebastiano , Fumagalli Kim , Oliva Francesca
Published: January 2023

Increasing global warming is largely attributable to human activities. International strategies have already been implemented to reduce emissions to zero, thus reducing energy consumption. Given the current world situation and the rising costs of raw materials (gas and oil), it is incumbent on us to find savings solutions that can also be implemented in our own small way; there are many solutions, especially in the domestic sphere. In this paper, the focus is on building energy savings that can be achieved using modern technologies and starting with the simplest solutions. In particular, this paper shows how the conscious use of natural lighting can lead to significant electricity savings. Moreover, it describes the effect of innovative building insulation materials and the effect due to the installation of a local photovoltaic power generation system; at the end, it illustrates the new horizons that are opening with the introduction of new building control techniques. Some studies are also reported where the extent of achievable savings can be understood.
A Sensorless Intelligent System to Detect Dust on PV Panels for Optimized Cleaning Units
Authors: Alfaris Faris E.
Published: January 2023

Deployment of photovoltaic (PV) systems has recently been encouraged for large-scale and small-scale businesses in order to meet the global green energy targets. However, one of the most significant hurdles that limits the spread of PV applications is the dust accumulated on the PV panels’ surfaces, especially in desert regions. Numerous studies sought the use of cameras, sensors, power datasets, and other detection elements to detect the dust on PV panels; however, these methods pose more maintenance, accuracy, and economic challenges. Therefore, this paper proposes an intelligent system to detect the dust level on the PV panels to optimally operate the attached dust cleaning units (DCUs). Unlike previous strategies, this study utilizes the expanded knowledge and collected data for solar irradiation and PV-generated power, along with the forecasted ambient temperature. An expert artificial intelligence (AI) computational system, adopted with the MATLAB platform, is utilized for a high level of data prediction and processing. The AI was used in this study in order to estimate the unprovided information, emulate the provided measurements, and accommodate more input/output data. The feasibility of the proposed system is investigated using actual field data during all possible weather conditions.
Transesterification of Algae Oil and Little Amount of Waste Cooking Oil Blend at Low Temperature in the Presence of NaOH
Authors: Jain Siddharth , Kumar Nitin , Singh Varun Pratap , Mishra Sachin , Sharma Naveen Kumar , Bajaj Mohit , Khan T. M. Yunus
Published: January 2023

The present study describes the single-step transesterification method of biodiesel production from high free fatty acid (FFA) waste cooking oil blended with algae oil using a homogeneous base catalyst. Due to high FFA contents, two step transesterification is needed to convert oil into biodiesel and therefore the high FFA content of waste cooking oil is decreased by blending it with low FFA content algae oil, which would further lead only to single step transesterification of low FFA oil. The design and optimization studies were conducted using Response Surface Methodology (RSM). The box-Behnken design technique is applied to optimize the three process parameters, i.e., catalyst concentration (0–2 wt%), methanol concentration (v/v) (20–60%) and reaction time (60–180 min) at a uniform reaction temperature of 50 °C. The result of the current study indicates that an effective biodiesel yield of 92% can be obtained at the optimized condition of catalyst concentration of 1.5% (w/w), methanol/oil ratio of 21:1 and reaction time of 110 min at a constant reaction temperature of 50 °C. This analysis clearly shows that this study can resolve the storage problem of high FFA oils from different feedstock and RSM can be successfully used to model the reaction to maximize the biodiesel yield.
In Pursuit of Understanding the Rumen Microbiome
Authors: Sanjorjo Rey Anthony , Tseten Tenzin , Kang Min-Kyoung , Kwon Moonhyuk , Kim Seon-Won
Published: January 2023

The rumen plays an indispensable role in ruminants to utilize ligno-cellulosic material and convert non-protein nitrogen into nutrients otherwise unavailable for human consumption. Recent advancements in the sequencing technology and omics approach have provided profound insights into the rumen world, wherein a consortium of archaea, bacteria, protozoa, fungi, and viruses exist and interact. These ruminal microbes alter the ruminal environment and execute several interlinked metabolic cascades that produce substrates for the host’s energy and body requirements. Methane is emitted as a by-product during this complex fermentation process in ruminants leading to a loss in productivity while negatively impacting the environment. As ruminants play an ever-increasing role in our food supply chain, manipulating the rumen is the critical step towards maximizing the ruminant product’s nutritional value while reducing its carbon footprint. Diet is the most straightforward way to alter the rumen microbiome, possibly in conjunction with phytobiotics and probiotics as feed supplements. Early life interventions allow the manipulation of microbial population structure and function that could persist later on in adult life. It has also been proven that the host exerts influence on the rumen microbiome as a heritable trait. The goal of this review is to provide a better understanding of the rumen, its key organisms, and its development to better identify, characterize, and engineer the rumen microbiome for efficient feed conversion and methane reduction.
Spatially Offset Raman Spectroscopic (SORS) Analysis of Wine Alcoholic Fermentation: A Preliminary Study
Authors: Schorn-García Daniel , Ezenarro Jokin , Aceña Laura , Busto Olga , Boqué Ricard , Giussani Barbara , Mestres Montserrat
Published: January 2023

Spatially offset Raman spectroscopy (SORS) is a non-invasive analytical technique that allows the analysis of samples through a container. This makes it an effective tool for studying food and beverage products, as it can measure the sample without being affected by the packaging or the container. In this study, a portable SORS equipment was used for the first time to analyse the alcoholic fermentation process of white wine. Different sample measurement arrangements were tested in order to determine the most effective method for monitoring the fermentation process and predicting key oenological parameters. The best results were obtained when the sample was directly measured through the glass container in which the fermentation was occurring. This allowed for the accurate monitoring of the process and the prediction of density and pH with a root mean square error of cross-validation (RMSECV) of 0.0029 g·L−1 and 0.04, respectively, and R2 values of 0.993 and 0.961 for density and pH, respectively. Additionally, the sources of variability depending on the measurement arrangements were studied using ANOVA-Simultaneous Component Analysis (ASCA).
Optimal Mobility-Aware Wireless Edge Cloud Support for the Metaverse
Authors: Huang Zhaohui , Friderikos Vasilis
Published: January 2023

Mobile-augmented-reality (MAR) applications extended into the metaverse could provide mixed and immersive experiences by amalgamating the virtual and physical worlds. However, the consideration of joining MAR and the metaverse requires reliable and high-quality support for foreground interactions and rich background content from these applications, which intensifies their consumption of energy, caching and computing resources. To tackle these challenges, a more flexible request assignment and resource allocation framework with more efficient processing are proposed in this paper through anchoring decomposed metaverse AR services at different edge nodes and proactively caching background metaverse region models embedded with target augmented-reality objects (AROs). Advanced terminals are also considered to further reduce service delays at an acceptable energy-consumption cost. We, then, propose and solve a joint-optimization problem which explicitly considers the balance between service delay and energy consumption under the constraints of perceived user quality in a mobility event. By also explicitly taking into account the capabilities of user terminals, the proposed optimized scheme is compared to a terminal-oblivious scheme. According to a wide set of numerical investigations, the proposed scheme has wide-ranging advantages in service latency and energy efficiency over other nominal baseline schemes which neglect the capabilities of terminals, user physical mobility, service decomposition and the inherent multimodality of the metaverse MAR service.
Food Credence Attributes: A Conceptual Framework of Supply Chain Stakeholders, Their Motives, and Mechanisms to Address Information Asymmetry
Authors: Schrobback Peggy , Zhang Airong , Loechel Barton , Ricketts Katie , Ingham Aaron
Published: January 2023

Food credence attributes (e.g., food safety, organic, and carbon neutral production methods) are quality characteristics of products that cannot be assessed by buyers at the point of sale without additional information (e.g., certification labels). Hence, the ability to access credence attributes of a particular product can result in a situation termed as asymmetric distributed information among supply chain stakeholders (e.g., producers, processors, wholesalers, retailers, consumer) where one party of a market transaction is in possession of more information about a product than the other party. This situation can lead to potential inefficiencies, e.g., misinformation, risk of food borne illness, or opportunistic behavior such as fraud. The present study sought to develop a conceptual framework that describes a) the motivation for key stakeholders to participate in the market for food credence attributes, b) the type of food credence attributes that key stakeholders provide, and c) current mechanisms to address the issue of information asymmetry among the stakeholders in the food system. The study was conducted using an integrative literature review. The developed framework consists of two components: a) the food supply chain and b) the attribute assurance system among which multiple links exist. The findings suggest that retailers, processors, NGOs, and government authorities are influential stakeholders within the supply chain of food credence attributes by imposing food quality standards which can address information asymmetry among food actors. While the credence attribute assurance system (e.g., food standards, third party food attribute assurance providers) can potentially address the issue of asymmetric information among market stakeholders, a range of issues remain. These include food standards as a potential market entry barrier for food producers and distributors, limited food standard harmonization, and communication challenges of food attribute assurance (e.g., consumers’ signal processing, signal use and trust). The syntheses presented in this study contributes to stakeholders’ (e.g., supply chain actors, scientists, policy makers) improved understanding about the components of the credence food system and their integration as well as the drivers for change in this system.
A Miniaturized Tri-Wideband Sierpinski Hexagonal-Shaped Fractal Antenna for Wireless Communication Applications
Authors: Benkhadda Omaima , Saih Mohamed , Ahmad Sarosh , Al-Gburi Ahmed Jamal Abdullah , Zakaria Zahriladha , Chaji Kebir , Reha Abdelati
Published: January 2023

This paper introduces a new tri-wideband fractal antenna for use in wireless communication applications. The fractal manufactured antenna developed has a Sierpinski hexagonal-shaped radiating element and a partial ground plane loaded with three rectangular stubs and three rectangular slits. The investigated antenna has a small footprint of 0.19λ0 × 0.24 λ0 × 0.0128 λ0 and improved bandwidth and gain. According to the measurements, the designed antenna resonates throughout the frequency ranges of 2.19–4.43 GHz, 4.8–7.76 GHz, and 8.04–11.32 GHz. These frequency ranges are compatible with a variety of wireless technologies, including WLAN, WiMAX, ISM, LTE, RFID, Bluetooth, 5G spectrum band, C-band, and X-band. The investigated antenna exhibited good gain with almost omnidirectional radiation patterns. Utilizing CST MWS, the performance of the suggested Sierpinski hexagonal-shaped fractal antenna was achieved. The findings were then compared to the experimental results, which were found to be in strong agreement.
Characterization and Expression of Holothurian Wnt Signaling Genes during Adult Intestinal Organogenesis
Authors: Auger Noah A. , Medina-Feliciano Joshua G. , Quispe-Parra David J. , Colón-Marrero Stephanie , Ortiz-Zuazaga Humberto , García-Arrarás José E.
Published: January 2023

Wnt signaling has been shown to play multiple roles in regenerative processes, one of the most widely studied of which is the regeneration of the intestinal luminal epithelia. Most studies in this area have focused on self-renewal of the luminal stem cells; however, Wnt signaling may also have more dynamic functions, such as facilitating intestinal organogenesis. To explore this possibility, we employed the sea cucumber Holothuria glaberrima that can regenerate a full intestine over the course of 21 days after evisceration. We collected RNA-seq data from various intestinal tissues and regeneration stages and used these data to define the Wnt genes present in H. glaberrima and the differential gene expression (DGE) patterns during the regenerative process. Twelve Wnt genes were found, and their presence was confirmed in the draft genome of H. glaberrima. The expressions of additional Wnt-associated genes, such as Frizzled and Disheveled, as well as genes from the Wnt/β-catenin and Wnt/Planar Cell Polarity (PCP) pathways, were also analyzed. DGE showed unique distributions of Wnt in early- and late-stage intestinal regenerates, consistent with the Wnt/β-catenin pathway being upregulated during early-stages and the Wnt/PCP pathway being upregulated during late-stages. Our results demonstrate the diversity of Wnt signaling during intestinal regeneration, highlighting possible roles in adult organogenesis.
Deep Learning-Based Multiclass Instance Segmentation for Dental Lesion Detection
Authors: Fatima Anum , Shafi Imran , Afzal Hammad , Mahmood Khawar , Díez Isabel de la Torre , Lipari Vivian , Ballester Julien Brito , Ashraf Imran
Published: January 2023

Automated dental imaging interpretation is one of the most prolific areas of research using artificial intelligence. X-ray imaging systems have enabled dental clinicians to identify dental diseases. However, the manual process of dental disease assessment is tedious and error-prone when diagnosed by inexperienced dentists. Thus, researchers have employed different advanced computer vision techniques, as well as machine and deep learning models for dental disease diagnoses using X-ray imagery. In this regard, a lightweight Mask-RCNN model is proposed for periapical disease detection. The proposed model is constructed in two parts: a lightweight modified MobileNet-v2 backbone and region-based network (RPN) are proposed for periapical disease localization on a small dataset. To measure the effectiveness of the proposed model, the lightweight Mask-RCNN is evaluated on a custom annotated dataset comprising images of five different types of periapical lesions. The results reveal that the model can detect and localize periapical lesions with an overall accuracy of 94%, a mean average precision of 85%, and a mean insection over a union of 71.0%. The proposed model improves the detection, classification, and localization accuracy significantly using a smaller number of images compared to existing methods and outperforms state-of-the-art approaches.
Understanding Patient Experience with Outpatient Cancer Rehabilitation Care
Authors: Wood Kelley C. , Bertram Jessica J. , Kendig Tiffany D. , Pergolotti Mackenzi
Published: January 2023

Background: Understanding patient experience is key to optimize access and quality of outpatient cancer rehabilitation (physical or occupational therapy, PT/OT) services. Methods: We performed a retrospective mixed-method analysis of rehabilitation medical record data to better understand patient experience and aspects of care that influenced experience. From the medical record, we extracted case characteristics, patient experience data (Net Promoter Survey®, NPS) and patient-reported outcome (PRO) data. We categorized cases as ‘promoters’ (i.e., highly likely to recommend rehabilitation) or ‘detractors’, then calculated NPS score (−100 [worst] to 100 [best]). We identified key themes from NPS free-text comments using inductive content analysis, then used Pearson [r] or Spearman [ρ] correlation to explore relationships between NPS, characteristics, and PRO improvement. Results: Patients (n = 383) were 60.51 ± 12.02 years old, predominantly women with breast cancer (69.2%), and attended 14.23 ± 12.37 visits. Most were ‘promoters’ (92%); NPS score was 91.4. Patients described two experiences (themes) that influenced their likelihood to recommend rehabilitation: (1) feeling comfortable with the process and (2) observable improvement in health/functioning, and described attributes of clinic staff, environment and clinical care that influenced themes. Likelihood to recommend rehabilitation was associated with achieving the minimal clinical important difference on a PRO (ρ = 0.21, p < 0.001) and cancer type (ρ = 0.10, p < 0.001). Conclusion: Patients who received specialized cancer PT/OT were highly likely to recommend rehabilitation. Feeling comfortable with the rehabilitation process and making observable improvements in health and/or functioning influenced likelihood to recommend. Rehabilitation providers should leverage the findings of this study optimize access to and quality of cancer rehab services.
Developing a Theory of Community Caring for Public Health Nursing
Authors: Iwamoto Saori
Published: January 2023

Nursing theories focus on individual and community care and human relationships in unique contexts. One of these contexts is the community in which a theory-based systematic nursing practice process is warranted. This article describes a theory of Community Caring for Public Health Nursing (CCPHN), which is grounded in four nursing metaparadigms by Fawcett: persons, environment, health, and nursing. This theory has three assumptions: (1) community caring fosters care demonstrations in nursing, (2) caring communities comprise members with community attachments united by their common values rather than rigid customs, and (3) community caring is expressed competently in mutual-care practices. From these assumptions, a nursing perspective supporting the community caring process is exhibited as the expression of caring by public health nurses toward supportive and promotive nursing processes that enhance a caring community. Nurses play critical roles in leading the establishment of caring communities. In future research, it is critical to verify whether building a caring community by public health nursing practices based on this theory of CCPHN contributes to the health and well-being of the people in the community.
Earth Science Frontier at Urban Periphery: Geoheritage from the Vicinity of Kazan City, Russia
Authors: Zorina Svetlana O. , Ermolaev Vladimir A. , Ruban Dmitry A.
Published: January 2023

Characterizing geological heritage sites (geosites) available in Russia remains an urgent task. The present study focuses on two geosites from the vicinity of Kazan—a large city on the Volga River. They are attributed to the standardized geoheritage types and scored by means of several criteria. It is found out that the Pechischi geosite represents nine geoheritage types, from which the stratigraphical type (stratotype section of the Upper Kazanian regional unit of the Guadalupian) and the geohistorical type (history of the Permian System studies) are the most important. This geosite reaches 675 out of 750 maximum possible scores, and it is ranked globally. The Cheremushki geosite represents six geoheritage types, from which the stratigraphical type (reference section of the Urzhumian regional unit of the Guadalupian) and the paleontological type (locality of diverse fossils, including tetrapods) are the most important. This geosite reaches a score of 250 and is ranked nationally. The undertaken study allows for recommending several actions for the effective conservation and exploitation of these geosites. The innovative interpretation is that the presence of geosites at the urban periphery makes its general (not only geological) heritage value comparable to that of the city’s center.
Impact of Environmental Regulation on Carbon Emissions in Countries along the Belt and Road—An Empirical Study Based on PSTR Model
Authors: Wu Lei , Zhu Chengao , Song Xinhao , He Junge
Published: January 2023

Since China has put forward the Belt and Road Initiative in 2013, research on the BRI-related countries along the Belt and Road has sprung up. With the advent of the era of carbon peak and carbon neutralization, environmental regulation, as one of the important methods to control carbon emissions, is becoming increasingly prominent. Research on the impact pathway of environmental regulation of countries along the Belt and Road on carbon emissions has important implications for environmental protection and carbon emission reduction. Based on the panel data of 38 countries along the Belt and Road from 2005 to 2018, this research applied linear Tobit model and nonlinear dynamic panel regression model (PSTR) to evaluate the direct impacts on carbon emissions from environmental regulation of countries along the Belt and Road, and to analyze the different impacts of environmental regulation on carbon emissions in terms of technical innovation, industrial structure, and energy intensity. We found that (1) the direct impact of environmental regulation on carbon emissions in the countries along the Belt and Road is positive, with slight differences between the Silk Road Economic Belt and 21st Century Maritime Silk Road (2) when technical innovation is at a low level, environmental regulation promotes carbon emissions, while at a high level, environmental regulation significantly inhibits carbon emissions. (3) When industrial structure is at both a low and high level, environmental regulation inhibits carbon emissions, with a stronger degree of inhibition at a higher level. (4) When energy intensity is at a low level, environmental regulation promotes carbon emissions, while at a high level, environmental regulation inhibits carbon emissions. Accordingly, we suggest that countries along the Belt and Road follow the road of sustainable and low-carbon development, which should further enhance their focus on environment protection, improve their environmental awareness, and take environmental regulation measures rationally to reduce carbon emissions. Meanwhile, relevant adjustments should be done on technical innovation, industrial structure, and energy intensity to achieve carbon emission reduction.
Experimental and Clinical Aspects of Sevoflurane Preconditioning and Postconditioning to Alleviate Hepatic Ischemia-Reperfusion Injury: A Scoping Review
Authors: Benoit Loïc , Dieu Audrey , Foguenne Maxime , Bonaccorsi-Riani Eliano
Published: January 2023

Ischemia-reperfusion injury (IRI) is an inflammatory process inherent in organ transplantation procedures. It is associated with tissue damage and, depending on its intensity, can impact early graft function. In liver transplantation (LT), strategies to alleviate IRI are essential in order to increase the use of extended criteria donor (ECD) grafts, which are more susceptible to IRI, as well as to improve postoperative graft and patient outcomes. Sevoflurane, a commonly used volatile anesthetic, has been shown to reduce IRI. This scoping review aims to give a comprehensive overview of the existing experimental and clinical data regarding the potential benefits of sevoflurane for hepatic IRI (HIRI) and to identify any gaps in knowledge to guide further research. We searched Medline and Embase for relevant articles. A total of 380 articles were identified, 45 of which were included in this review. In most experimental studies, the use of sevoflurane was associated with a significant decrease in biomarkers of acute liver damage and oxidative stress. Administration of sevoflurane before hepatic ischemia (preconditioning) or after reperfusion (postconditioning) appears to be protective. However, in the clinical setting, results are conflicting. While some studies showed a reduction of postoperative markers of liver injury, the benefit of sevoflurane on clinical outcomes and graft survival remains unclear. Further prospective clinical trials remain necessary to assess the clinical relevance of the use of sevoflurane as a protective factor against HIRI.
Voriconazole Eye Drops: Enhanced Solubility and Stability through Ternary Voriconazole/Sulfobutyl Ether β-Cyclodextrin/Polyvinyl Alcohol Complexes
Authors: Soe Hay Man Saung Hnin , Kerdpol Khanittha , Rungrotmongkol Thanyada , Pruksakorn Patamaporn , Autthateinchai Rinrapas , Wet-osot Sirawit , Loftsson Thorsteinn , Jansook Phatsawee
Published: January 2023

Voriconazole (VCZ) is a broad-spectrum antifungal agent used to treat ocular fungal keratitis. However, VCZ has low aqueous solubility and chemical instability in aqueous solutions. This study aimed to develop VCZ eye drop formulations using cyclodextrin (CD) and water-soluble polymers, forming CD complex aggregates to improve the aqueous solubility and chemical stability of VCZ. The VCZ solubility was greatly enhanced using sulfobutyl ether β-cyclodextrin (SBEβCD). The addition of polyvinyl alcohol (PVA) showed a synergistic effect on VCZ/SBEβCD solubilization and a stabilization effect on the VCZ/SBEβCD complex. The formation of binary VCZ/SBEβCD and ternary VCZ/SBEβCD/PVA complexes was confirmed by spectroscopic techniques and in silico studies. The 0.5% w/v VCZ eye drop formulations were developed consisting of 6% w/v SBEβCD and different types and concentrations of PVA. The VCZ/SBEβCD systems containing high-molecular-weight PVA prepared under freeze–thaw conditions (PVA-H hydrogel) provided high mucoadhesion, sustained release, good ex vivo permeability through the porcine cornea and no sign of irritation. Additionally, PVA-H hydrogel was effective against the filamentous fungi tested. The stability study revealed that our VCZ eye drops provide a shelf-life of more than 2.5 years at room temperature, while a shelf-life of only 3.5 months was observed for the extemporaneous Vfend® eye drops.