bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficient Continuous Subgraph Matching Scheme Based on Trie Indexing for Graph Stream Processing
Authors: Choi Dojin , Lee Somin , Kim Sanghyeuk , Lee Hyeonbyeong , Lim Jongtae , Bok Kyoungsoo , Yoo Jaesoo
Published: April 2023

With the expansion of the application range of big data and artificial intelligence technologies, graph data have been increasingly used to analyze the relationships among objects. With the advancement of network technology and the spread of social network services, there has been an increasing need for a continuous query processing algorithm that can manage large-volume graph streams generated in real time. In this paper, a sliding-window-based continuous subgraph matching algorithm that can efficiently control graph streams is proposed. The proposed scheme uses a query processing technique based on trie indexing. It establishes an index based on a materialized view of similar queries and conducts continuous query processing based on the materialized view to perform continuous query processing efficiently. It also provides wildcard operations on vertices and edges to consider various query types. Moreover, in this study, a two-level cache technique that can manage frequently used subgraphs and subgraphs that may be used in the future is developed, to handle intermediate query results in the form of a materialized view. Cache replacement techniques based on statistical data are also presented to improve the performance of the developed cache technique. The excellent performance of the proposed algorithm is verified by a conducting independent performance evaluation and comparative performance evaluation.
Using Statistical Test Method to Establish a Decision Model of Performance Evaluation Matrix
Authors: Liu Chin-Chia , Yu Chun-Hung , Chen Kuen-Suan
Published: April 2023

Many studies have pointed out that the Performance Evaluation Matrix (PEM) is a convenient and useful tool for the evaluation, analysis, and improvement of service operating systems. All service items of the operating system can collect customer satisfaction and importance through questionnaires and then convert them into satisfaction indices and importance indices to establish PEM and its evaluation rules. Since the indices have unknown parameters, if the evaluation is performed directly by the point estimates of the indices, there will be a risk of misjudgment due to sampling error. In addition, most of the studies only determine the critical-to-quality (CTQ) that needs to be improved, and do not discuss the treatment rules in the case of limited resources nor perform the confirmation after improvement. Therefore, to address similar research gaps, this paper proposed the unbiased estimators of these two indices and determined the critical-to-quality (CTQ) service items which need to be improved through the one-tailed statistical hypothesis test by building a PEM method of the satisfaction index. In addition, through the one-tailed statistical hypothesis test method of the importance index, the improvement priority of service items was determined under the condition of limited resources. Confirmation of the effect on improvement is an important step in management. Thus, this paper adopted a statistical two-tailed hypothesis test to verify whether the satisfaction of all the CTQ service items that need to be improved was enhanced. Since the method proposed in this paper was established through statistical hypothesis tests, the risk of misjudgment due to sampling error could be reduced. Obviously, reducing the misjudgment risk is the advantage of the method in this paper. Based on the precondition, utilizing the model in this study may assist the industries to determine CTQ rapidly, implement the most efficient improvement under the condition of limited resources and also confirm the improvement effect at the same time. Finally, a case study of computer-assisted language learning system (CALL System) was used to illustrate a way to apply the model proposed in this paper.
Order-Preserving Multiple Pattern Matching in Parallel
Authors: Park Somin , Park Jinhyeok , Kim Youngho , Sim Jeong Seop
Published: April 2023

The order-preserving multiple pattern matching problem is to find all substrings of T whose relative orders are the same for any pattern in a set of patterns. Various sequential algorithms have been studied for the order-preserving multiple pattern matching problems. In this paper, we propose two parallel algorithms, each of which uses Aho–Corasick automata and fingerprint tables, respectively. We also present experimental results of comparing the execution times of each parallel algorithm on various types of time-series data.
Understanding and Predicting Ride-Hailing Fares in Madrid: A Combination of Supervised and Unsupervised Techniques
Authors: Silveira-Santos Tulio , Papanikolaou Anestis , Rangel Thais , Manuel Vassallo Jose
Published: April 2023

App-based ride-hailing mobility services are becoming increasingly popular in cities worldwide. However, key drivers explaining the balance between supply and demand to set final prices remain to a considerable extent unknown. This research intends to understand and predict the behavior of ride-hailing fares by employing statistical and supervised machine learning approaches (such as Linear Regression, Decision Tree, and Random Forest). The data used for model calibration correspond to a ten-month period and were downloaded from the Uber Application Programming Interface for the city of Madrid. The findings reveal that the Random Forest model is the most appropriate for this type of prediction, having the best performance metrics. To further understand the patterns of the prediction errors, the unsupervised technique of cluster analysis (using the k-means clustering method) was applied to explore the variation of the discrepancy between Uber fares predictions and observed values. The analysis identified a small share of observations with high prediction errors (only 1.96%), which are caused by unexpected surges due to imbalances between supply and demand (usually occurring at major events, peak times, weekends, holidays, or when there is a taxi strike). This study helps policymakers understand pricing, demand for services, and pricing schemes in the ride-hailing market.
Web Interface of NER and RE with BERT for Biomedical Text Mining
Authors: Park Yeon-Ji , Lee Min-a , Yang Geun-Je , Park Soo Jun , Sohn Chae-Bong
Published: April 2023

The BioBERT Named Entity Recognition (NER) model is a high-performance model designed to identify both known and unknown entities. It surpasses previous NER models utilized by text-mining tools, such as tmTool and ezTag, in effectively discovering novel entities. In previous studies, the Biomedical Entity Recognition and Multi-Type Normalization Tool (BERN) employed this model to identify words that represent specific names, discern the type of the word, and implement it on a web page to offer NER service. However, we aimed to offer a web service that includes Relation Extraction (RE), a task determining the relation between entity pairs within a sentence. First, just like BERN, we fine-tuned the BioBERT NER model within the biomedical domain to recognize new entities. We identified two categories: diseases and genes/proteins. Additionally, we fine-tuned the BioBERT RE model to determine the presence or absence of a relation between the identified gene–disease entity pairs. The NER and RE results are displayed on a web page using the Django web framework. NER results are presented in distinct colors, and RE results are visualized as graphs in NetworkX and Cytoscape, allowing users to interact with the graphs.
Evaluation of Water Sorption and Solubility and FTIR Spectroscopy of Thermoplastic Orthodontic Retainer Materials Subjected to Thermoforming and Thermocycling
Authors: Albilali Alaa T. , Baras Bashayer H. , Aldosari Mohammad A.
Published: April 2023

Due to the fact that retainers are often recommended for a lifetime, their endurance and longevity are directly related to the quality of the materials used in their production. Our study examined the water sorption, water solubility, and Fourier transform infrared (FTIR) spectroscopy of six commercially available thermoplastic retainer materials (Essix Plus, Zendura, Duran Plus, Tru-Tain DX, Imprelon S pd, and Essix ACE). Moreover, this study evaluated the effect of thermoforming and thermocycling on the water sorption and solubility and surface molecular composition of the tested materials. The present study found that the type of retainer material affected water sorption and solubility capabilities. In addition, the aging methods employed significantly affected some retainer materials’ water sorption and solubility. Moreover, the surface molecular composition evaluated by FTIR spectroscopy revealed that most of the evaluated materials had similar FTIR spectra except for Zendura. All materials had a spectrum that resembled polyethylene terephthalate glycol (PETG) while Zendura had a spectrum similar to semi-rigid polyurethane (PU). Only Zendura had relatively unstable surface structural composition evaluated under the effects of (thermoforming and thermocycling) compared to all tested materials.
An Equal Precision Programmed Cymometer Design Using Low-Power Technique
Authors: Liu Yuan , Tang Jian , Feng Chen , Zhang Chen , Xue Yuwei , Zhang Lei , Xu Shuxi , Wang Jian , Dai Fang , Wang Ning
Published: April 2023

Based on equal precision frequency measurement and pulse counting technique, a multi-period synchronous frequency measurement method is proposed in this paper. A programmed cymometer is designed with a full frequency band with equal precision measurement and improved measurement accuracy. In addition to adopting a low-power gate-control clock technique, the strong stability of our design is also carried out through the filtering of interference signals. Finally, the designed circuit is implemented with FPGA. The experimental results show that the static power consumption of the programmable frequency meter testing platform designed after continuous operation for 100 h is only 0.56 W, and the input impedance is 1 M Ω/40 pF. At the same time, the errors of frequency, cycle measurement, duty cycle measurement, and time interval are within a reasonable range. In addition, the measurement accuracy requirements for various indicators can also be met at a maximum frequency of 100 MHz. Therefore, this work can provide a feasible design method for low-power consumption electrical systems that are easy to replicate.
Non-Compliance Distalization Appliances Supported by Mini-Implants: A Systematic Review
Authors: Karvelas Nikolaos , Dragomir Bogdan Radu , Chehab Alice , Panaite Tinela , Papadopoulos Moschos A. , Zetu Irina
Published: April 2023

Background: A common strategy for the correction of Class II malocclusion is to initially distalize the maxillary molars to create a Class I relationship. Material and Methods: PubMed, Embase, Cochrane Library, Google Scholar, and Clinicaltrials.gov databases were searched to identify and retrieve orthodontic articles that evaluated non-compliance distalization appliances supported by mini-implants up to 11 November 2022. Results: A total of 505 articles were initially identified, and after applying the inclusion criteria, 28 studies were enlisted for evaluation. For the prospective studies, the Risk of bias in non-randomized studies of interventions assessment tool was used, and for the retrospective studies, the Newcastle-Ottawa quality assessment scale. Regarding the palatal devices with mini-implants, the maxillary molars were distalized with a mean value ranging from 2.4 to 5.9 mm, along with a distal tipping ranging between 0.01° and 11°, while when Pendulums were used with mini-implants, the maxillary molars were distalized with a mean value from 1.8 mm to 7.9 mm, and the distal tipping ranged from 7.34° to 22.8°. Further, in the second subgroup, including the appliances placed buccally, the maxillary molars were distalized with a mean value ranging from 1.83 mm to 4.2 mm and a distal tipping ranging between 0.6° and 4.8°. Conclusions: Non-compliance appliances supported by mini-implants are effective in maxillary molar distalization, presenting no anchorage loss of the anterior dental unit in most of the appliances, while distal tipping was found to be more pronounced when the mini-implants were used with Pendulums.
Improving Graphite Ore Grade Identification with a Novel FRCNN-PGR Method Based on Deep Learning
Authors: Xiang Junchen , Shi Haoyu , Huang Xueyu , Chen Daogui
Published: April 2023

Graphite stone is widely used in various industries, including the refractory, battery making, steel making, expanded graphite, brake pads, casting coatings, and lubricants industries. In the mineral processing industry, an effective and accurate diagnostic method based on FRCNN-PGR is proposed and evaluated, which involves cutting images to expand the dataset, combining them using the faster R-CNN model with high and low feature layers, and adding a global attention mechanism, Relation-Aware Global Attention Network (RGA), to extract features of interest from both the space and channel. The proposed model outperforms the original faster R-CNN model with 80.21% mAP and 87.61% recall on the split graphite mine dataset.
Utilizing Multilevel Modeling to Measure Neighborhood Dynamics and Their Impact on House Prices
Authors: Guo Baoyun , Li Kenan , Fu Cong
Published: April 2023

For decades, researchers have been concerned with house price modeling, and recognition has grown for the necessity of considering environmental and contextual variables in the process. This research examines the association between neighborhood characteristics and all individual house sale prices in Lucas County, Ohio, from 2012 to 2016, through a multilevel modeling (MLM) approach. Although there are various ways to define neighborhoods, census tracts and school districts are used in this study. Neighborhood characteristics include a foreclosure score, race heterogeneity, median household income, and built environment variables, such as walkability indexes. School district characteristics include student performance, tuition expenditures per pupil, and percent of expenditures spent on classroom instruction. The advantage of the multilevel model, is that it allows us to derive reliable estimates of place differences, representing a considerable improvement over the single-level model. Significant correlations were identified between house prices and foreclosure score, student performance, and tuition expenditures per pupil. The MLM results indicate that house prices not only lay in house characteristics themselves but also in neighborhood features, thus MLM offers good prediction accuracy and high explanatory power.
Icing Wind Tunnel Test Campaign on a Nacelle Lip-Skin to Assess the Effect of a Superhydrophobic Coating on Ice Accretion
Authors: Piscitelli Filomena , Palazzo Salvatore , De Nicola Felice
Published: April 2023

The formation of ice on nacelle causes the reduction or loss of aerodynamic performance, fuel consumption increases, reduced thrust, and the ingestion of ice, which can damage the engine. The piccolo tube anti-icing employed as an active ice protection system has limitations in terms of performance losses and energy costs. Furthermore, according to the FAA regulation, it cannot be activated during takeoff and initial flight phases in order to avoid engine thrust reduction. This work reports on an icing wind tunnel test campaign performed at initial flight phases conditions on the M28 PZL nacelle before and after the application of a superhydrophobic coating in order to study the effect of wettability on ice accretion. Results highlighted that an ice thickness reduction of −49% has been recorded at −12 °C, matched to an increase in the impingement length of 0.5%. At 95 m/s and at 420 s of exposure time, the ice thickness was reduced by −27% and −14%, respectively, whereas the impingement length reductions were −9.6% and −7.6%. Finally, an ice thickness reduction of −8% was observed at a liquid water content of 1 g/m3, matched to an increase in the impingement length of 3.7% and to a reduction in length and number of the frozen rivulets.
Short-Term Risk Estimation and Treatment Planning for Cardiovascular Disease Patients after First Diagnostic Catheterizations with Machine Learning Models
Authors: Ye Guochang , Gamage Peshala Thibbotuwawa , Balasubramanian Vignesh , Li John K.-J. , Subasi Ersoy , Subasi Munevver Mine , Kaya Mehmet
Published: April 2023

Cardiovascular disease (CVD) is the leading cause of death. CVD symptoms may develop within a short-term after diagnostic catheterizations and lead to life-threatening situations. This study is the first to apply machine learning (ML) methods to predict subsequent adverse cardiovascular events/treatments for patients within 90 days after their first diagnostic catheterizations. Patients (6539) without previously diagnosed CVD were selected from the DukeCath dataset. Ten ML methods were used. Three medical outcomes, varied cardiovascular-related scenarios, percutaneous coronary intervention (PCI) treatments, and coronary artery bypass graft (CABG) treatments, were targeted individually. With patient medical history, vital measurements, laboratory results, and the number of diseased vessels, the random forest classifier (RFC) performed best in predicting combined cardiovascular scenarios, including CABG, PCI, valve surgery (VS), stroke, and myocardial infarction (MI), achieving accuracy: 88.17%, sensitivity: 89.72%, specificity: 86.98%, area under receiver operating characteristic (AUROC): 91.68%. The gradient boosting classifier (GBC) performed best in predicting the PCI and CABG treatments (PCI treatments: accuracy: 89.21%, sensitivity: 90.20%, specificity: 88.74%, AUROC: 94.16%; CABG treatments: accuracy: 93.86%, sensitivity: 77.57%, specificity: 96.23%, AUROC: 96.47%). Our results show that the ML applications effectively identify high-risk patients, can provide diagnostic assistance in cardiovascular treatment planning, and improve outcomes in cardiovascular medicine.
Modeling Evacuees’ Intended Responses to a Phased Hurricane Evacuation Order
Authors: Bian Ruijie , Murray-Tuite Pamela , Trainor Joseph , Edara Praveen , Triantis Konstantinos
Published: April 2023

Phased evacuation is an under-studied strategy, and relatively little is known about compliance with the phased process. This study modelled households’ responses to a phased evacuation order based on a household behavioral intention survey. About 66% of the evacuees reported that they would comply with a phased evacuation order. A latent class logit model sorted evacuees into two classes (“evacuation reluctant” and “evacuation keen”) by their stakeholder perceptions (i.e., whether government agencies have responsibility for the safety of individuals) and evacuation perceptions (i.e., whether evacuation is an effective protective action), while risk perception becomes non-significant in interpreting their compliance behavior to a phased evacuation order. Those that evacuate to the home of friends/relatives and/or bring more vehicles during evacuation are less likely to follow phased evacuation orders. “Evacuation reluctant” individuals with a longer housing tenure are more likely to follow phased evacuation orders. “Evacuation keen” individuals with a longer travel delay expectation are more likely to comply with phased evacuation orders. This study not only unveiled the impacts of incorporating three psychological perceptions (i.e., risk, stakeholder, and evacuation perceptions) in modeling compliance behavior (e.g., parameter sign/significance shift) but also provides insights of evacuees’ compliance behavior to phased evacuation orders.
Signals Intelligence System with Software-Defined Radio
Authors: Radu Florin , Cotfas Petru A. , Alexandru Marian , Bălan Titus C. , Popescu Vlad , Cotfas Daniel T.
Published: April 2023

In this paper, we present the implementation of a system that identifies the modulation of complex radio signals. This is realized using an artificial intelligence model developed, trained, and integrated with Microsoft Azure cloud. We consider that cloud-based platforms offer enough flexibility and processing power to use them instead of conventional computers for signal processing based on artificial intelligence. We tested the implementation using a software-defined radio platform developed in GNU Radio that generates and receives real modulated signals. This process ensures that the solution proposed is viable to be used in real signal processing systems. The results obtained show that for certain modulation types, the identification is performed with a high degree of success. The use of a cloud-based platform allows quick access to the system. The user is able to identify the signal modulation using only a laptop that has access to the internet.
A Study on the Optimization of the Coil Defect Detection Model Based on Deep Learning
Authors: Noh Chun-Myoung , Jang Jun-Gyo , Kim Sung-Soo , Lee Soon-Sup , Shin Sung-Chul , Lee Jae-Chul
Published: April 2023

With increasing interest in smart factories, considerable attention has been paid to the development of deep-learning-based quality inspection systems. Deep-learning-based quality inspection helps productivity improvements by solving the limitations of existing quality inspection methods (e.g., an inspector’s human errors, various defects, and so on). In this study, we propose an optimized YOLO (You Only Look Once) v5-based model for inspecting small coils. Performance improvement techniques (model structure modification, model scaling, pruning) are applied for model optimization. Furthermore, the model is prepared by adding data applied with histogram equalization to improve model performance. Compared with the base model, the proposed YOLOv5 model takes nearly half the time for coil inspection and improves the accuracy of inspection by up to approximately 1.6%, thereby enhancing the reliability and productivity of the final products.
Investigating the Diurnal Variation in Coastal Boundary Layer Winds on Hainan Island Using Three Tower Observations
Authors: Duan Ziqiang , Zhao Bingke , Fu Shiwang , Zhang Shuai , Lin Limin , Tang Jie
Published: April 2023

This study analyzes wind structures up to 509 m in the atmospheric boundary layer in the coastal area of Hainan Island, using a dataset obtained from ultrasonic anemometers housed in three towers. The wind profile, consisting of the measurements from the three towers, followed logarithmic law. In a diurnal variation, the maximum wind speed occurred at night, with a greater component of northerly wind, while the minimum wind speed was observed at noon, with a greater component of easterly wind. The variation in wind speed suggests that the measurements were representative of the wind field in the upper part of the atmospheric boundary layer, and the variation in wind direction might be affected by sea and land breezes, which can be induced by the different thermal conditions of underlying surfaces. The diurnal variation in average wind speed ranged from 0.5 to 1.5 m s−1, and the diurnal variation in wind direction was 10–20 degrees. In our measurements, the diurnal trajectory of the wind vector was observed to be counterclockwise, which differs from previous studies conducted over uniform and flat underlying surfaces. This is partially due to the different thermodynamic conditions of the underlying land and sea surfaces. The impact of topographic relief on wind measurement is also discussed. The measurements suggest that wind speeds at altitudes above 50 m are less influenced by terrain. The height of the reversal layer, which is generated by the different diurnal variations in wind speed in the upper and lower parts of the boundary layer, was estimated to be around 300 m.
Past and Future Responses of Soil Water to Climate Change in Tropical and Subtropical Rainforest Systems in South America
Authors: Arévalo Santiago M. Márquez , Delgado Rafael Coll , Lindemann Douglas da Silva , Gelsleichter Yuri A. , Pereira Marcos Gervasio , Rodrigues Rafael de Ávila , Justino Flávio Barbosa , Wanderley Henderson Silva , Zonta Everaldo , Santana Romário Oliveira de , de Souza Renato Sinquini
Published: April 2023

The present study aimed to contribute to the diagnosis and advance the knowledge of the impacts of land use change and climate change on the tropical longleaf forest biome at the continental scale in South America (Biome 1 according to the WWF classification) for realizing scientific progress in the search for convincing strategies and actions by different actors for the preservation of forests in the continent. The status and climate of the area, which harbors the tropical longleaf forests of South America, were assessed. Moreover, volumetric soil moisture (VSM) was evaluated through maps and simulation using the autoregressive integrated moving average model (ARIMA). Furthermore, future climate scenarios were predicted based on El Niño–Southern Oscillation phenomena, meteorological systems, and scientific evidence, such as the shared socioeconomic pathways (SSPs) and sociopolitical dynamics evident in the region from the case analysis of the Brazilian states of Acre and Rio de Janeiro. An increase was noted in the temperature and range of precipitation variation in the biome. ARIMA analysis indicated changes of up to 0.24 m3 m−3 and an increased range of future VSM values. The December–January–February (DJF) quarter recorded the highest VSM median with the measurement scale of 0.05 to 0.44 m3 m−3, while the June–July–August (JJA) quarter recorded the lowest value. The regions of the biome with the lowest VSM values included southern Amazon (Ecuador, Peru, and the Brazilian states of Acre, Mato Grosso, Pará, and Maranhão), Brazilian Atlantic Forest, Southeast Region, and the Brazilian state of Bahia.
The Cauchy–Optimal Stability Results for Cauchy–Jensen Additive Mappings in the Fuzzy Banach Space and the Unital Fuzzy Banach Space
Authors: Eidinejad Zahra , Saadati Reza , Srivastava Hari M.
Published: April 2023

In this article, we apply a new class of fuzzy control functions to approximate a Cauchy additive mapping in fuzzy Banach space (FBS). Further, considering the unital FBS (UFBS), we will investigate the isomorphisms defined in this space. By introducing several specific functions and choosing the optimal control function from among these functions, we evaluate the Cauchy–Optimal stability (C–O-stability) for all defined mappings.
Analyzing Online Fake News Using Latent Semantic Analysis: Case of USA Election Campaign
Authors: Mayopu Richard G. , Wang Yi-Yun , Chen Long-Sheng
Published: April 2023

Recent studies have indicated that fake news is always produced to manipulate readers and that it spreads very fast and brings great damage to human society through social media. From the available literature, most studies focused on fake news detection and identification and fake news sentiment analysis using machine learning or deep learning techniques. However, relatively few researchers have paid attention to fake news analysis. This is especially true for fake political news. Unlike other published works which built fake news detection models from computer scientists’ viewpoints, this study aims to develop an effective method that combines natural language processing (NLP) and latent semantic analysis (LSA) using singular value decomposition (SVD) techniques to help social scientists to analyze fake news for discovering the exact elements. In addition, the authors analyze the characteristics of true news and fake news. A real case from the USA election campaign in 2016 is employed to demonstrate the effectiveness of our methods. The experimental results could give useful suggestions to future researchers to distinguish fake news. This study finds the five concepts extracted from LSA and that they are representative of political fake news during the election.
Density Spectral Array Enables Precise Sedation Control for Supermicrosurgical Lymphaticovenous Anastomosis: A Retrospective Observational Cohort Study
Authors: Wu En-Bo , Lin Yu-Hsuan , Yang Johnson Chia-Shen , Lai Chiung-Wen , Chin Jo-Chi , Wu Shao-Chun
Published: April 2023

Supermicrosurgical lymphaticovenous anastomosis (LVA) is a minimally invasive surgical technique that creates bypasses between lymphatic vessels and veins, thereby improving lymphatic drainage and reducing lymphedema. This retrospective single-center study included 137 patients who underwent non-intubated LVA in southern Taiwan. A total of 119 patients were enrolled and assigned to two study groups: the geriatric (age ≥ 75 years, n = 23) and non-geriatric groups (age < 75 years, n = 96). The primary outcome was to investigate and compare the arousal and maintenance of the propofol effect-site concentration (Ce) using an electroencephalographic density spectral array (EEG DSA) in both groups. The results showed that the geriatric group required less propofol (4.05 [3.73–4.77] mg/kg/h vs. 5.01 [4.34–5.92] mg/kg/h, p = 0.001) and alfentanil (4.67 [2.53–5.82] μg/kg/h vs. 6.68 [3.85–8.77] μg/kg/h, p = 0.047). The median arousal Ce of propofol among the geriatric group (0.6 [0.5–0.7] μg/mL) was significantly lower than that in patients aged ≤ 54 years (1.3 [1.2–1.4] μg/mL, p < 0.001), 55–64 years (0.9 [0.8–1.0] μg/mL, p < 0.001), and <75 years (0.9 [0.8–1.2] μg/mL, p < 0.001). In summary, the combined use of EEG DSA provides the objective and depth of adequate sedation for extensive non-intubated anesthesia in late-elderly patients who undergo LVA without perioperative complications.
A Review of Biomechanical and Physiological Effects of Using Poles in Sports
Authors: Saller Maximilian , Nagengast Niko , Frisch Michael , Fuss Franz Konstantin
Published: April 2023

The use of poles in sports, to support propulsion, is an integral and inherent component of some sports disciplines such as skiing (cross-country and roller), Nordic walking, and trail running. The aim of this review is to summarize the current state-of-the-art of literature on multiple influencing factors of poles in terms of biomechanical and physiological effects. We evaluated publications in the subfields of biomechanics, physiology, coordination, and pole properties. Plantar pressure and ground reaction forces decreased with the use of poles in all included studies. The upper body and trunk muscles were more active. The lower body muscles were either less active or no different from walking without poles. The use of poles led to a higher oxygen consumption (VO2) without increasing the level of perceived exertion (RPE). Furthermore, the heart rate (HR) tended to be higher. Longer poles reduced the VO2 and provided a longer thrust phase and greater propulsive impulse. The mass of the poles showed no major influence on VO2, RPE, or HR. Solely the activity of the biceps brachii increased with the pole mass.
A Review of Voice-Based Pain Detection in Adults Using Artificial Intelligence
Authors: Borna Sahar , Haider Clifton R. , Maita Karla C. , Torres Ricardo A. , Avila Francisco R. , Garcia John P. , De Sario Velasquez Gioacchino D. , McLeod Christopher J. , Bruce Charles J. , Carter Rickey E. , Forte Antonio J.
Published: April 2023

Pain is a complex and subjective experience, and traditional methods of pain assessment can be limited by factors such as self-report bias and observer variability. Voice is frequently used to evaluate pain, occasionally in conjunction with other behaviors such as facial gestures. Compared to facial emotions, there is less available evidence linking pain with voice. This literature review synthesizes the current state of research on the use of voice recognition and voice analysis for pain detection in adults, with a specific focus on the role of artificial intelligence (AI) and machine learning (ML) techniques. We describe the previous works on pain recognition using voice and highlight the different approaches to voice as a tool for pain detection, such as a human effect or biosignal. Overall, studies have shown that AI-based voice analysis can be an effective tool for pain detection in adult patients with various types of pain, including chronic and acute pain. We highlight the high accuracy of the ML-based approaches used in studies and their limitations in terms of generalizability due to factors such as the nature of the pain and patient population characteristics. However, there are still potential challenges, such as the need for large datasets and the risk of bias in training models, which warrant further research.
The Role of Augmented Reality in the Advancement of Minimally Invasive Surgery Procedures: A Scoping Review
Authors: Brockmeyer Phillipp , Wiechens Bernhard , Schliephake Henning
Published: April 2023

The purpose of this review was to analyze the evidence on the role of augmented reality (AR) in the improvement of minimally invasive surgical (MIS) procedures. A scoping literature search of the PubMed and ScienceDirect databases was performed to identify articles published in the last five years that addressed the direct impact of AR technology on MIS procedures or that addressed an area of education or clinical care that could potentially be used for MIS development. A total of 359 studies were screened and 31 articles were reviewed in depth and categorized into three main groups: Navigation, education and training, and user-environment interfaces. A comparison of studies within the different application groups showed that AR technology can be useful in various disciplines to advance the development of MIS. Although AR-guided navigation systems do not yet offer a precision advantage, benefits include improved ergonomics and visualization, as well as reduced surgical time and blood loss. Benefits can also be seen in improved education and training conditions and improved user-environment interfaces that can indirectly influence MIS procedures. However, there are still technical challenges that need to be addressed to demonstrate added value to patient care and should be evaluated in clinical trials with sufficient patient numbers or even in systematic reviews or meta-analyses.
Aromatic Plants and Their Associated Arbuscular Mycorrhizal Fungi Outcompete Tuber melanosporum in Compatibility Assays with Truffle-Oaks
Authors: Barou Vasiliki , Rincón Ana , Calvet Cinta , Camprubí Amelia , Parladé Javier
Published: April 2023

The high value of black truffle recompenses the slow growth of the fungus when established in the field. Adding a secondary crop, such as medicinal and aromatic plants (MAPs), could further enhance the sustainability of truffle production agro-forest systems. The dual cultures of ectomycorrhizal truffle-oak seedlings and MAPs (lavender, thyme, and sage) previously inoculated and non-inoculated with native arbuscular mycorrhizal fungi (AMF), were established to evaluate plant–fungi relationships. After 12 months in a shadehouse, plants’ growth, mycorrhizal colonization, and extraradical soil mycelium (both of Tuber melanosporum and AMF) were measured. Overall, truffle-oaks’ growth was negatively affected by the presence of MAPs, especially when inoculated with AMF. In turn, the presence of truffle-oaks barely affected the co-cultured MAPs, and only lavenders showed a significant growth reduction. All AMF-inoculated MAPs showed higher shoot and root biomass than non-inoculated ones. Compared to truffle-oaks growing alone, the presence of co-cultured MAPs, especially when they were AMF-inoculated, significantly decreased both the ectomycorrhizas and soil mycelium of T. melanosporum. These results reveal the strong competition between AMF and T. melanosporum and warn about the need for the protection of intercropping plants and their associated symbiotic fungi to avoid reciprocal counterproductive effects in mixed truffle-oak–AMF–MAP plantations.
Cofilin Inhibitor Protects against Traumatic Brain Injury-Induced Oxidative Stress and Neuroinflammation
Authors: Bahader Ghaith A. , James Antonisamy William , Almarghalani Daniyah A. , Shah Zahoor A.
Published: April 2023

Microglial activation and failure of the antioxidant defense mechanisms are major hallmarks in different brain injuries, particularly traumatic brain injury (TBI). Cofilin is a cytoskeleton-associated protein involved in actin binding and severing. In our previous studies, we identified the putative role of cofilin in mediating microglial activation and apoptosis in ischemic and hemorrhagic conditions. Others have highlighted the involvement of cofilin in ROS production and the resultant neuronal death; however, more studies are needed to delineate the role of cofilin in oxidative stress conditions. The present study aims to investigate the cellular and molecular effects of cofilin in TBI using both in vitro and in vivo models as well as the first-in-class small-molecule cofilin inhibitor (CI). An in vitro H2O2-induced oxidative stress model was used in two different types of cells, human neuroblastoma (SH-SY5Y) and microglia (HMC3), along with an in vivo controlled cortical impact model of TBI. Our results show that treatment with H2O2 increases the expression of cofilin and slingshot-1 (SSH-1), an upstream regulator of cofilin, in microglial cells, which was significantly reduced in the CI-treated group. Cofilin inhibition significantly attenuated H2O2-induced microglial activation by reducing the release of proinflammatory mediators. Furthermore, we demonstrate that CI protects against H2O2-induced ROS accumulation and neuronal cytotoxicity, activates the AKT signaling pathway by increasing its phosphorylation, and modulates mitochondrial-related apoptogenic factors. The expression of NF-E2-related factor 2 (Nrf2) and its associated antioxidant enzymes were also increased in CI-treated SY-SY5Y. In the mice model of TBI, CI significantly activated the Nrf2 and reduced the expression of oxidative/nitrosative stress markers at the protein and gene levels. Together, our data suggest that cofilin inhibition provides a neuroprotective effect in in vitro and in vivo TBI mice models by inhibiting oxidative stress and inflammatory responses, the pivotal mechanisms involved in TBI-induced brain damage.
Deregulation of Plasma microRNA Expression in a TARDBP-ALS Family
Authors: Ruffo Paola , Catalano Stefania , La Bella Vincenzo , Conforti Francesca Luisa
Published: April 2023

TDP-43 intracellular aggregates are a pathogenic sign of most amyotrophic lateral sclerosis (ALS) cases. Familial ALS, brought on by TARDBP gene mutations, emphasizes the relevance of this altered protein in pathophysiology. Growing evidence suggests a role for dysregulated microRNA (miRNA) in ALS disease. Furthermore, several studies showed that miRNAs are highly stable in various biological fluids (CSF, blood, plasma, and serum), and they are expressed differentially by comparing ALS patients and controls. In 2011, our research group discovered a rare mutation in a TARDBP gene (G376D) in a large ALS Apulian family with affected members exhibiting a rapidly progressing disease. To identify potential non-invasive biomarkers of preclinical and clinical progression in the TARDBP-ALS family, we assessed the expression levels of plasma microRNAs in affected patients (n = 7) and asymptomatic mutation carriers (n = 7) compared with healthy controls (n = 13). Applying qPCR, we investigate 10 miRNAs that bind TDP-43 in vitro during their biogenesis or in their mature form, and the other nine are known to be deregulated in the disease. We highlight the potential of miR-132-5p, miR-132-3p, miR-124-3p, and miR-133a-3p expression levels in plasma as biomarkers of preclinical progression for G376D-TARDBP-associated ALS. Our research strongly supports the potential of plasma miRNAs as biomarkers for performing predictive diagnostics and identifying new therapeutic targets.
A Soluble Platelet-Derived Growth Factor Receptor-β Originates via Pre-mRNA Splicing in the Healthy Brain and Is Upregulated during Hypoxia and Aging
Authors: Payne Laura Beth , Abdelazim Hanaa , Hoque Maruf , Barnes Audra , Mironovova Zuzana , Willi Caroline E. , Darden Jordan , Houk Clifton , Sedovy Meghan W. , Johnstone Scott R. , Chappell John C.
Published: April 2023

The platelet-derived growth factor-BB (PDGF-BB) pathway provides critical regulation of cerebrovascular pericytes, orchestrating their investment and retention within the brain microcirculation. Dysregulated PDGF Receptor-beta (PDGFRβ) signaling can lead to pericyte defects that compromise blood-brain barrier (BBB) integrity and cerebral perfusion, impairing neuronal activity and viability, which fuels cognitive and memory deficits. Receptor tyrosine kinases such as PDGF-BB and vascular endothelial growth factor-A (VEGF-A) are often modulated by soluble isoforms of cognate receptors that establish signaling activity within a physiological range. Soluble PDGFRβ (sPDGFRβ) isoforms have been reported to form by enzymatic cleavage from cerebrovascular mural cells, and pericytes in particular, largely under pathological conditions. However, pre-mRNA alternative splicing has not been widely explored as a possible mechanism for generating sPDGFRβ variants, and specifically during tissue homeostasis. Here, we found sPDGFRβ protein in the murine brain and other tissues under normal, physiological conditions. Utilizing brain samples for follow-on analysis, we identified mRNA sequences corresponding to sPDGFRβ isoforms, which facilitated construction of predicted protein structures and related amino acid sequences. Human cell lines yielded comparable sequences and protein model predictions. Retention of ligand binding capacity was confirmed for sPDGFRβ by co-immunoprecipitation. Visualizing fluorescently labeled sPDGFRβ transcripts revealed a spatial distribution corresponding to murine brain pericytes alongside cerebrovascular endothelium. Soluble PDGFRβ protein was detected throughout the brain parenchyma in distinct regions, such as along the lateral ventricles, with signals also found more broadly adjacent to cerebral microvessels consistent with pericyte labeling. To better understand how sPDGFRβ variants might be regulated, we found elevated transcript and protein levels in the murine brain with age, and acute hypoxia increased sPDGFRβ variant transcripts in a cell-based model of intact vessels. Our findings indicate that soluble isoforms of PDGFRβ likely arise from pre-mRNA alternative splicing, in addition to enzymatic cleavage mechanisms, and these variants exist under normal physiological conditions. Follow-on studies will be needed to establish potential roles for sPDGFRβ in regulating PDGF-BB signaling to maintain pericyte quiescence, BBB integrity, and cerebral perfusion—critical processes underlying neuronal health and function, and in turn, memory and cognition.
Mechanisms of Diseases Associated with Mutation in GJC2/Connexin 47
Authors: Abrams Charles K.
Published: April 2023

Connexins are members of a family of integral membrane proteins that provide a pathway for both electrical and metabolic coupling between cells. Astroglia express connexin 30 (Cx30)-GJB6 and Cx43-GJA1, while oligodendroglia express Cx29/Cx31.3-GJC3, Cx32-GJB1, and Cx47-GJC2. Connexins organize into hexameric hemichannels (homomeric if all subunits are identical or heteromeric if one or more differs). Hemichannels from one cell then form cell-cell channels with a hemichannel from an apposed cell. (These are termed homotypic if the hemichannels are identical and heterotypic if the hemichannels differ). Oligodendrocytes couple to each other through Cx32/Cx32 or Cx47/Cx47 homotypic channels and they couple to astrocytes via Cx32/Cx30 or Cx47/Cx43 heterotypic channels. Astrocytes couple via Cx30/Cx30 and Cx43/Cx43 homotypic channels. Though Cx32 and Cx47 may be expressed in the same cells, all available data suggest that Cx32 and Cx47 cannot interact heteromerically. Animal models wherein one or in some cases two different CNS glial connexins have been deleted have helped to clarify the role of these molecules in CNS function. Mutations in a number of different CNS glial connexin genes cause human disease. Mutations in GJC2 lead to three distinct phenotypes, Pelizaeus Merzbacher like disease, hereditary spastic paraparesis (SPG44) and subclinical leukodystrophy.
Health Disparities in Multiple Sclerosis among Hispanic and Black Populations in the United States
Authors: Moore Michael Z. , Pérez Carlos A. , Hutton George J. , Patel Hemali , Cuascut Fernando X.
Published: April 2023

Multiple sclerosis (MS) is an acquired demyelinating disease of the central nervous system (CNS). Historically, research on MS has focused on White persons with MS. This preponderance of representation has important possible implications for minority populations with MS, from developing effective therapeutic agents to understanding the role of unique constellations of social determinants of health. A growing body of literature involving persons of historically underrepresented races and ethnicities in the field of multiple sclerosis is assembling. Our purpose in this narrative review is to highlight two populations in the United States: Black and Hispanic persons with multiple sclerosis. We will review the current understanding about the patterns of disease presentation, genetic considerations, response to treatment, roles of social determinants of health, and healthcare utilization. In addition, we explore future directions of inquiry as well as practical methods of meeting these challenges.
Colorimetric Sensing of the Peroxide Number of Milk Powder Using CsPbBr3 Perovskite Nanocrystals
Authors: Zhang Li , Zhu Yimeng , Guo Zhiyong , You Longjie , Zhang Chen , Chen Xi
Published: April 2023

In this study, a wavelength-shift-based colorimetric sensing approach for the peroxide number of milk powder using CsPbBr3 perovskite nanocrystals (CsPbBr3 NCs) has been developed. Through the fat extraction, REDOX reactions and halogen exchange, as well as the optimized experimental conditions, a colorimetric sensing method was established to determine the peroxide number of milk powder samples. The integrated process of milk powder fat extraction and the REDOX process greatly shortened the determination time. This colorimetric method has a good linear correlation in the range of the peroxide number from 0.02 to 1.96 mmol/kg, and the detection limit was found to be 3 μmol/kg. This study further deepens the application prospect of wavelength-shift-based colorimetric sensing using CsPbBr3 NCs.