bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Dense Citrus Fruits by Combining Coordinated Attention and Cross-Scale Connection with Weighted Feature Fusion
Authors: Liu Xiaoyu , Li Guo , Chen Wenkang , Liu Binghao , Chen Ming , Lu Shenglian
Published: June 2022

The accuracy detection of individual citrus fruits in a citrus orchard environments is one of the key steps in realizing precision agriculture applications such as yield estimation, fruit thinning, and mechanical harvesting. This study proposes an improved object detection YOLOv5 model to achieve accurate the identification and counting of citrus fruits in an orchard environment. First, the latest visual attention mechanism coordinated attention module (CA) was inserted into an improved backbone network to focus on fruit-dense regions to recognize small target fruits. Second, an efficient two-way cross-scale connection and weighted feature fusion BiFPN in the neck network were used to replace the PANet multiscale feature fusion network, giving effective feature corresponding weights to fully fuse the high-level and bottom-level features. Finally, the varifocal loss function was used to calculate the model loss for better model training results. The results of the experiments on four varieties of citrus trees showed that our improved model proposed to this study could effectively identify dense small citrus fruits. Specifically, the recognized AP (average precision) reached 98.4%, and the average recognition time was 0.019 s per image. Compared with the original YOLOv5 (including deferent variants of n, s, m, l, and x), the increase in the average accuracy precision of the improved YOLOv5 ranged from 7.5% to 0.8% while maintaining similar average inference time. Four different citrus varieties were also tested to evaluate the generalization performance of the improved model. The method can be further used as a part in a vision system to provide technical support for the real-time and accurate detection of multiple fruit targets during mechanical picking in citrus orchards.
Towards Trust Hardware Deployment of Edge Computing: Mitigation of Hardware Trojans Based on Evolvable Hardware
Authors: Li Zeyu , Wang Junjie , Huang Zhao , Luo Nan , Wang Quan
Published: June 2022

Hardware Trojans (HTs) are malicious hardware components designed to leak confidential information or cause the chip/circuit on which they are integrated to malfunction during operation. When we deploy such hardware platforms for edge computing, FPGA-based implementations of Coarse-Grained Reconfigurable Array (CGRA) are also currently falling victim to HT insertion. However, for CGRA, an evolvable hardware (EHW) platform, which has the ability to dynamically change its configuration and behavioral characteristics based on inputs from the environment, provides us with a new way to mitigate HT attacks. In this regard, we investigate the feasibility of using EHW to mitigate HTs that disrupt normal functionality in CGRA in this paper. When it is determined that HT is inserted into certain processing elements (PEs), the array autonomously reconfigures the circuit structure based on an evolutionary algorithm (EA) to avoid the use of HT-infected (HT-I) PEs. We show that the proposed approach is applicable to: (1) hardware platforms that support coarse-grained reconfiguration; and (2) pure combinatorial circuits. In a simulation environment built in Python, this paper reports experimental results for two target evolutionary circuits and outlines the effectiveness of the proposed method.
Three-Dimensional Object Segmentation and Labeling Algorithm Using Contour and Distance Information
Authors: Lo Wen-Chien , Chiu Chung-Cheng , Yang Jia-Horng
Published: June 2022

Object segmentation and object labeling are important techniques in the field of image processing. Because object segmentation techniques developed using two-dimensional images may cause segmentation errors for overlapping objects, this paper proposes a three-dimensional object segmentation and labeling algorithm that combines the segmentation and labeling functions using contour and distance information for static images. The proposed algorithm can segment and label the object without relying on the dynamic information of consecutive images and without obtaining the characteristics of the segmented objects in advance. The algorithm can also effectively segment and label complex overlapping objects and estimate the object’s distance and size according to the labeling contour information. In this paper, a self-made image capture system is developed to capture test images and the actual distance and size of the objects are also measured using measuring tools. The measured data is used as a reference for the estimated data of the proposed algorithm. The experimental results show that the proposed algorithm can effectively segment and label the complex overlapping objects, obtain the estimated distance and size of each object, and satisfy the detection requirements of objects at a long-range in outdoor scenes.
Evolutionary Game—Theoretic Approach for Analyzing User Privacy Disclosure Behavior in Online Health Communities
Authors: Xu Zhongyang , Chen Xihui , Hong Yuanxiao
Published: June 2022

Privacy disclosure is one of the most common user information behaviors in online health communities. Under the premise of implementing privacy protection strategies in online health communities, promoting user privacy disclosure behavior can result in a “win–win” scenario for users and online health communities. Combining the real situation and evolutionary game theory, in this study, we first constructed an evolutionary game model of privacy disclosure behavior with users and online health communities as the main participants. Then, we solved the replication dynamic equations for both parties and analyzed the evolutionary stable strategies (ESSs) in different scenarios. Finally, we adopted MATLAB for numerical simulations to verify the accuracy of the model. Studies show that: (1) factors such as medical service support and community rewards that users receive after disclosing their private personal information affect user game strategy; and (2) the additional costs of the online health communities implementing the “positive protection” strategy and the expected loss related to the privacy leakage risk affect the online health communities’ game strategy. In this regard, this paper puts forward the following suggestions in order to optimize the benefits of both sets of participants: the explicit benefits of users should be improved, the internal environment of the communities should be optimized, the additional costs of the “positive protection” strategy should be reduced, and penalties for privacy leakages should be increased.
Visual Demands of Walking Are Reflected in Eye-Blink-Evoked EEG-Activity
Authors: Wascher Edmund , Arnau Stefan , Gutberlet Marie , Chuang Lewis L. , Rinkenauer Gerhard , Reiser Julian Elias
Published: June 2022

Blinking is a natural user-induced response which paces visual information processing. This study investigates whether blinks are viable for segmenting continuous electroencephalography (EEG) activity, for inferring cognitive demands in ecologically valid work environments. We report the blink-related EEG measures of participants who performed auditory tasks either standing, walking on grass, or whilst completing an obstacle course. Blink-related EEG activity discriminated between different levels of cognitive demand during walking. Both behavioral parameters (e.g., blink duration or head motion) and blink-related EEG activity varied with walking conditions. Larger occipital N1 was observed during walking, relative to standing and traversing an obstacle course, which reflects differences in bottom-up visual perception. In contrast, the amplitudes of top-down components (N2, P3) significantly decreased with increasing walking demands, which reflected narrowing attention. This is consistent with blink-related EEG, specifically in Theta and Alpha power that, respectively, increased and decreased with increasing demands of the walking task. This work presents a novel and robust analytical approach to evaluate the cognitive demands experienced in natural work settings, which precludes the use of artificial task manipulations for data segmentation.
Construction of Disease-Symptom Knowledge Graph from Web-Board Documents
Authors: Pechsiri Chaveevan , Piriyakul Rapepun
Published: June 2022

The research aim is to construct a disease-symptom knowledge graph (DSKG) as a cause-effect knowledge graph containing disease-symptom relations as a cause-effect relation type determined from downloaded documents on medical web-board resources. Each disease-symptom relation connects a disease-name concept node (a causative-concept node) to a corresponding node having a group of correlated symptom-concept/effect-concept features as common symptom-concept/effect-concept features among some disease-name concepts. The DSKG benefits non-professionals in preliminary diagnosis through a recommender web-board. There are three main problems: how to determine symptom concepts from sentences without annotation on the documents having disease-name concepts as the documents’ topic-names; how to determine the disease-symptom relations from the documents with/without complications; and how to construct the DSKG involving high dimensional symptom-concept features after union of the correlated symptom-concept groups. Therefore, we apply a word co-occurrence pattern including medical-symptom expressions from Wikipedia including MeSH and the Lexitron Dictionary to determine the symptom concepts. The Cartesian product is applied for automatic-supervised machine learning to determine the disease-symptom relation. We propose using Principal Component Analysis for constructing the DSKG by dimensionality reduction in the symptom-concept features with minimized information loss. In contrast to previous works, the proposed approach enables the DSKG construction with precise and concise representation scores of 7.8 and 9, respectively.
Smartphone LiDAR Technologies for Surveying and Reality Modelling in Urban Scenarios: Evaluation Methods, Performance and Challenges
Authors: Costantino Domenica , Vozza Gabriele , Pepe Massimiliano , Alfio Vincenzo Saverio
Published: June 2022

The aim of the research was to evaluate the performance of smartphone depth sensors (Time of Flight Camera(ToF) and Light Detection and Ranging (LiDAR)) from Android (Huawei P30 Pro) and iOS (iPhone 12 Pro and iPAD 2021 Pro) devices in order to build a 3D point cloud. In particular, the smartphones were tested in several case studies involving the scanning of several objects: 10 building material samples, a statue, an interior room environment and the remains of a Doric column in a major archaeological site. The quality of the point clouds was evaluated through visual analysis and using three eigenfeatures: surface variation, planarity and omnivariance. Based on this approach, some issues with the point clouds generated by smartphones were highlighted, such as surface splitting, loss of planarity and inertial navigation system drift problems. In addition, it can finally be deduced that, in the absence of scanning problems, the accuracies achievable from this type of scanning are ~1–3 cm. Therefore, this research intends to describe a method of quantifying anomalies occurring in smartphone scans and, more generally, to verify the quality of the point cloud obtained with these devices.
Increased Exposure of China’s Cropland to Droughts under 1.5 °C and 2 °C Global Warming
Authors: Miao Lijuan , Zhang Jing , Kattel Giri Raj , Liu Ran
Published: June 2022

Global warming and human activities have intensified the duration, frequency, and extent of climatic extremes. The projected rise in global mean annual temperature of 1.5 °C/2 °C is thought to have severe impacts on the population exposed to droughts. Although these impacts on humans have been widely explored, the impacts associated with the cropland exposed to droughts have not been widely investigated. Here, we have examined the spatiotemporal pattern of China’s drought conditions and cropland exposure to droughts under global warming of 1.5 °C and 2 °C, along with the avoided impacts (as evaluated by the cropland exposure to droughts) when limiting the global warming to 1.5 °C instead of 2 °C. Results suggest that compared to the reference period (1995–2014), drought conditions will be alleviated when the projected rise in mean global temperature is limited to 1.5 °C rather than 2.0 °C. Although severe droughts tend to be mainly distributed in northwestern China, drought severities are increasing in southern China, especially in the southeastern region. In addition, the total cropland exposure to droughts across China exhibits an increasing trend in response to the 0.5 °C of additional global warming, especially in northwestern China and Huang−Huai−Hai region. If global warming could be limited to 1.5 °C, the avoided impact will exceed 30%, especially in northwestern China, southwestern China, and the Huang−Huai−Hai Plain. Furthermore, the rising cropland exposure to droughts under the 2 °C global warming is likely to be triggered by the rising frequencies of moderate and extreme droughts. Therefore, climate mitigation strategies are urgently needed to keep the global temperature rise below 1.5 °C, for the future sustainability of China’s cropland.
Mapping Heat Wave Hazard in Urban Areas: A Novel Multi-Criteria Decision Making Approach
Authors: Shafiei Shiva Javad , Chandler David G. , Kunkel Kenneth E.
Published: June 2022

Global population is experiencing more frequent, longer, and more severe heat waves due to global warming and urbanization. Episodic heat waves increase mortality and morbidity rates and demands for water and energy. Urban managers typically assess heat wave risk based on heat wave hazard, population exposure, and vulnerability, with a general assumption of spatial uniformity of heat wave hazard. We present a novel analysis that demonstrates an approach to determine the spatial distribution of a set of heat wave properties and hazard. The analysis is based on the Livneh dataset at a 1/16-degree resolution from 1950 to 2009 in Maricopa County, Arizona, USA. We then focused on neighborhoods with the most frequent, severe, earlier, and extended periods of heat wave occurrences. On average, the first heat wave occurs 40 days earlier in the eastern part of the county; the northeast part of this region experiences 12 days further extreme hot days and 30 days longer heat wave season than other regions of the area. Then, we applied a multi-criteria decision-making (MCDM) tool (TOPSIS) to evaluate the total hazard posed by heat wave components. We found that the northern and central parts of the metropolitan area are subject to the greatest heat wave hazard and that individual heat wave hazard components did not necessarily indicate heat hazard. This approach is intended to support local government planning for heat wave adaptation and mitigation strategies, where cooling centers, heat emergency water distribution networks, and electrical energy delivery can be targeted based on current and projected local heat wave characteristics.
Field Measurement and Evaluation of Effective Ventilation and Particulate Matter Discharge Efficiency of Air Shafts in Subway Tunnels
Authors: Qu Haibo , Zang Jianbin , Wu Yan
Published: June 2022

The ventilation performance of air shafts is important to the air quality of subway tunnels, but there is no unified evaluation index of ventilation performance. In this paper, the air shafts at different locations in subway tunnels were taken as research objects, and the wind speed as well as the particulate matter concentration of each air shaft was tested. The effective ventilation volume and PM2.5 discharge efficiency of the air shafts were defined to evaluate the ventilation performance. It was found that on average, during the subway train service, the station air shaft on the train-arriving side can discharge 2050 m3 of dirty air in the tunnels and inhale 218 m3 of fresh air from the outside environment, while the station air shaft on the train-leaving side can absorb 2430 m3 of fresh air but can hardly effectively discharge dirty air; meanwhile, the middle air shaft can not only effectively exhaust 1519 m3 of dirty air but can also absorb 7572 m3 of fresh air. In addition, the middle air shaft has better ventilation performance if its inner opening is set on the top rather than on the side of the tunnel. The PM2.5 discharge efficiency of the station air shaft on the train-arriving side is 52.0~62.8%, higher than that of the middle air shaft of which the value is 26.8~40.7%. This research can provide guidance for ventilation performance evaluation of subway air shafts and provide a reference for subway tunnel air shaft location design.
A Rainfall Forecast Model Based on GNSS Tropospheric Parameters and BP-NN Algorithm
Authors: Fu Huanian , Zhang Wenfeng , Li Chunjin , Hu Zaihuang
Published: June 2022

The occurrence of rainfall is the result of a combination of various meteorological factors. Traditional rainfall early warning models solely use Global Navigation Satellite System (GNSS)-derived Zenith Total Delay (ZTD) or Precipitable Water Vapor (PWV) to forecast rainfall, resulting in a low true detected rate. While non-linear rainfall early warning models based on the Back-Propagation Neural Network (BP-NN) algorithm consider the influences of various meteorological factors, the forecasts often exhibit a high false rate. To further improve the prediction of rainfall, a short-term rainfall early warning model based on the GNSS and BP-NN algorithms is proposed in this study. The method uses the traditional rainfall forecasting model and utilizes the BP-NN algorithm to combine various meteorological factors for rainfall early warning. The results of GNSS and BP-NN together improve the precision of rainfall early warning. Observation data from eight GNSS stations, the fifth-generation reanalysis of European Centre for Medium-Range Weather Forecast (ECMWF ERA5), and temperature, pressure, and rainfall data from corresponding meteorological stations in Ningbo, China were utilized to verify the rainfall early warning model proposed in this study. The results show that the proposed model can complement the advantages of the traditional linear and non-linear rainfall early warning methods. The model can maintain a high True Detected Rate (TDR) of rainfall early warning while simultaneously reducing the False Forecasted Rate (FFR). The average TDR of the eight GNSS stations is 100% and the FFR is 20.75%, which are both better than those of existing traditional linear and non-linear rainfall early warning models.
Selected Flavonoids to Target Melanoma: A Perspective in Nanoengineering Delivery Systems
Authors: Coutinho Tiago E. , Souto Eliana B. , Silva Amélia M.
Published: June 2022

Melanoma is a complex type of cancer that depends on several metabolic factors, while the currently used therapies are not always effective and have unwanted side effects. In this review, the main factors involved in the etiology of cutaneous carcinoma are highlighted, together with the main genes and proteins that regulate cancer invasion and metastization. The role of five selected flavonoids, namely, apigenin, epigallocatechin-3-gallate, kaempferol, naringenin, and silybin, in the modulating receptor tyrosine kinase (RTK) and Wnt pathways is reported with their relevance in the future design of drugs to mitigate and/or treat melanoma. However, as phenolic compounds have some difficulties in reaching the target site, the encapsulation of these compounds in nanoparticles is a promising strategy to promote improved physicochemical stabilization of the bioactives and achieve greater bioavailability. Scientific evidence is given about the beneficial effects of loading these flavonoids into selected nanoparticles for further exploitation in the treatment of melanoma.
Characterization of Extracellular Vesicles Secreted by a Clinical Isolate of Naegleria fowleri and Identification of Immunogenic Components within Their Protein Cargo
Authors: Retana Moreira Lissette , Steller Espinoza María Fernanda , Chacón Camacho Natalia , Cornet-Gomez Alberto , Sáenz-Arce Giovanni , Osuna Antonio , Lomonte Bruno , Abrahams Sandí Elizabeth
Published: June 2022

Extracellular vesicles (EVs) are small lipid vesicles released by both prokaryotic and eukaryotic cells, involved in intercellular communication, immunomodulation and pathogenesis. In this study, we performed a characterization of the EVs produced by trophozoites of a clinical isolate of the free-living amoeba Naegleria fowleri (N. fowleri). Size distribution, zeta potential, protein profile and protease activity were analyzed. Under our incubation conditions, EVs of different sizes were observed, with a predominant population ranging from 206 to 227 nm. SDS-PAGE revealed protein bands of 25 to 260 KDa. The presence of antigenic proteins was confirmed by Western blot, which evidenced strongest recognition by rat polyclonal antibodies raised against N. fowleri in the region close to 80 KDa and included peptidases, as revealed by zymography. Proteins in selected immunorecognized bands were further identified using nano-ESI-MS/MS. A preliminary proteomic profile of the EVs identified at least 184 proteins as part of the vesicles’ cargo. Protease activity assays, in combination with the use of inhibitors, revealed the predominance of serine proteases. The present characterization uncovers the complexity of EVs produced by N. fowleri, suggesting their potential relevance in the release of virulence factors involved in pathogenicity. Owing to their cargo’s diversity, further research on EVs could reveal new therapeutic targets or biomarkers for developing rapid and accurate diagnostic tools for lethal infections such as the one caused by this amoeba.
Extracellular Heat Shock Protein-90 (eHsp90): Everything You Need to Know
Authors: Jay Daniel , Luo Yongzhang , Li Wei
Published: June 2022

“Extracellular” Heat Shock Protein-90 (Hsp90) was initially reported in the 1970s but was not formally recognized until 2008 at the 4th International Conference on The Hsp90 Chaperone Machine (Monastery Seeon, Germany). Studies presented under the topic of “extracellular Hsp90 (eHsp90)” at the conference provided direct evidence for eHsp90’s involvement in cancer invasion and skin wound healing. Over the past 15 years, studies have focused on the secretion, action, biological function, therapeutic targeting, preclinical evaluations, and clinical utility of eHsp90 using wound healing, tissue fibrosis, and tumour models both in vitro and in vivo. eHsp90 has emerged as a critical stress-responding molecule targeting each of the pathophysiological conditions. Despite the studies, our current understanding of several fundamental questions remains little beyond speculation. Does eHsp90 indeed originate from purposeful live cell secretion or rather from accidental dead cell leakage? Why did evolution create an intracellular chaperone that also functions as a secreted factor with reported extracellular duties that might be (easily) fulfilled by conventional secreted molecules? Is eHsp90 a safer and more optimal drug target than intracellular Hsp90 chaperone? In this review, we summarize how much we have learned about eHsp90, provide our conceptual views of the findings, and make recommendations on the future studies of eHsp90 for clinical relevance.
Immunomodulation of Pluripotent Stem Cell-Derived Mesenchymal Stem Cells in Rotator Cuff Tears Model
Authors: Baek Jieun , Ryu Bokyeong , Kim Jin , Lee Seul-Gi , Oh Min-Seok , Hong Ki-Sung , Kim Eun-Young , Kim C-Yoon , Chung Hyung-Min
Published: June 2022

Background: Rotator cuff tears (RCTs) induce chronic muscle weakness and shoulder pain. Treatment of RCT using surgery or drugs causes lipid infiltration and fibrosis, which hampers tissue regeneration and complete recovery. The pluripotent stem cell-derived multipotent mesenchymal stem cells (M-MSCs) represent potential candidate next-generation therapies for RCT. Methods: The difference between M-MSCs and adult-MSCs was compared and analyzed using next-generation sequencing (NGS). In addition, using a rat model of RCT, the muscle recovery ability of M-MSCs and adult-MSCs was evaluated by conducting a histological analysis and monitoring the cytokine expression level. Results: Using NGS, it was confirmed that M-MSC was suitable for transplantation because of its excellent ability to regulate inflammation that promotes tissue repair and reduced apoptosis and rejection during transplantation. In addition, while M-MSCs persisted for up to 8 weeks in vivo, they significantly reduced inflammation and adipogenesis-related cytokine levels in rat muscle. Significant differences were also confirmed in histopathological remission. Conclusions: M-MSCs remain in the body longer to modulate immune responses in RCTs and have a greater potential to improve muscle recovery by alleviating acute inflammatory responses. This indicates that M-MSCs could be used in potential next-generation RCT therapies.
Resting-State EEG Functional Connectivity in Children with Rolandic Spikes with or without Clinical Seizures
Authors: Tsai Min-Lan , Wang Chuang-Chin , Lee Feng-Chin , Peng Syu-Jyun , Chang Hsi , Tseng Sung-Hui
Published: June 2022

Alterations in dynamic brain network function are increasingly recognized in epilepsy. Benign childhood epilepsy with centrotemporal spikes (BECTS), or benign rolandic seizures, is the most common idiopathic focal epilepsy in children. In this study, we analyzed EEG functional connectivity (FC) among children with rolandic spikes with or without clinical seizures as compared to controls, to investigate the relationship between FC and clinical parameters in children with rolandic spikes. The FC analysis based on graph theory and network-based statistics in different frequency bands evaluated global efficiency, clustering coefficient, betweenness centrality, and nodal strength in four frequency bands. Similar to BECTS patients with seizures, children with rolandic spikes without seizures had significantly increased global efficiency, mean clustering coefficient, mean nodal strength, and connectivity strength, specifically in the theta frequency band at almost all proportional thresholds, compared with age-matched controls. Decreased mean betweenness centrality was only present in BECTS patients with seizures. Age at seizure onset was significantly positively associated with the strength of EEG-FC. The decreased function of betweenness centrality was only presented in BECTS patients with clinical seizures, suggesting weaker local connectivity may lower the seizure threshold. These findings may affect treatment policy in children with rolandic spikes.
Agents Strongly Preferred: ERP Evidence from Natives and Non-Natives Processing Intransitive Sentences in Spanish
Authors: Zawiszewski Adam , Martinez de la Hidalga Gillen , Laka Itziar
Published: June 2022

Are non-native speakers able to process their second language in a native-like way? The present study used the Event-Related Potentials’ (ERPs) method to address this issue by focusing (1) on agent vs. agentless intransitive sentences and (2) on person vs. number agreement morphology. For that purpose, native and high proficiency and early non-native speakers of Spanish were tested while processing intransitive sentences containing grammatical and ungrammatical subject–verb agreement. Results reveal greater accuracy in the agent (unergative) condition as compared with the agentless (unaccusative) condition and different ERP patterns for both types of verbs in all participants, suggesting a larger processing cost for the agentless sentences than for the agentive ones. These effects were more pronounced in the native group as compared with the non-native one in the early time window (300–500 ms). Differences between person and number agreement processing were also found at both behavioral and electrophysiological levels, indicating that those morphological features are distinctively processed. Importantly, this pattern of results held for both native and non-native speakers, thus suggesting that native-like competence is attainable given early Age of Acquisition (AoA), frequent use and high proficiency.
Epidemiology of Cerebral Palsy among Children and Adolescents in Arabic-Speaking Countries: A Systematic Review and Meta-Analysis
Authors: Mushta Sami Mukhdari , King Catherine , Goldsmith Shona , Smithers-Sheedy Hayley , Badahdah Al-Mamoon , Rashid Harunor , Badawi Nadia , Khandaker Gulam , McIntyre Sarah
Published: June 2022

Background: Studies on cerebral palsy among children and adolescents in Arabic-speaking countries are scarce. In this systematic review, we aimed to describe the epidemiology of cerebral palsy among children and adolescents in Arabic-speaking countries in terms of prevalence, risk factors, motor types, and rehabilitation. Methods: Six key bibliographic databases were searched for relevant literature published to 17 July 2021. Titles and abstracts were screened for potential inclusion and two independent reviewers screened the full texts of potential articles following pre-defined inclusion/exclusion criteria. The included studies were evaluated independently by three reviewers. The risk of bias was assessed, and data were extracted and analysed. Results: A total of 32 studies from 7 countries met our inclusion criteria. The prevalence of cerebral palsy in Arabic-speaking countries was 1.8/1000 live births (95% CI: 1.2–2.5). Spastic cerebral palsy was the most common motor type, representing 59.8% (95% CI: 46.2–72.7) of pooled estimates. This included children with spastic quadriplegia, diplegia, and hemiplegia; 25.1% (95% CI: 18.2–32.8), 16.2% (95% CI: 11.4–23.3), and 10.4% (95% CI: 7.3–13.8), respectively. Consanguinity was high and represented 37.7% (95% CI: 29.3–46.6). Only one included study reported the types of rehabilitation received (e.g., physiotherapy and assistance devices). Conclusions: This paper provides a summary of the epidemiology of cerebral palsy in Arabic-speaking countries and highlights areas for future research. There is still a substantial knowledge gap on the epidemiology of cerebral palsy in these regions. Countries in the Arab region should follow examples of countries that have successfully established cerebral palsy registries to generate evidence on epidemiology of cerebral palsy and opportunities for prevention.
Delta Opioid Receptors and Enkephalinergic Signaling within Locus Coeruleus Promote Stress Resilience
Authors: Tkaczynski John A. , Borodovitsyna Olga , Chandler Daniel J.
Published: June 2022

The noradrenergic nucleus locus coeruleus is a key component of the stress circuitry of the brain. During stress, the neuropeptide corticotropin-releasing factor (CRF) is secreted onto LC, increasing LC output and norepinephrine concentration in the brain, which is thought to promote anxiety-like behavior. LC is also innervated by several structures that synthesize and release the endogenous opioid peptide enkephalin onto LC upon stressor termination. While the role of CRF neurotransmission within LC in mediating anxiety-like behavior and the behavioral response to stress has been well characterized, the role of enkephalinergic signaling at LC-expressed δ-opioid receptors has been comparatively understudied. We have previously shown that acute stressor exposure increases LC activity and anxiety-like behavior for at least one week. Here, we extend these findings by showing that these effects may be mediated at least in part through stress-induced downregulation of DORs within LC. Furthermore, overexpression of DORs in LC blocks the effects of stress on both LC firing properties and anxiety-like behavior. In addition, intra-LC infusions of enkephalin blocked stress-induced freezing behavior and promoted conditioned place preference. These findings indicate that enkephalinergic neurotransmission at DORs within LC is an important component of the behavioral response to stress and may drive reward-related behavior as well.
Examining the Intention of Authorization via Apps: Personality Traits and Expanded Privacy Calculus Perspectives
Authors: Tang Jie , Zhang Bin , Xiao Shuochen
Published: June 2022

By integrating the extended privacy calculus theory with the Big Five personality theory, this research proposes and validates a conceptual model in the context of mobile application (App) information authorization. It investigates the implications of each component of privacy costs, privacy advantages, and trust on users’ willingness to authorize their information, and explores how the five personality traits affect App users’ perceived benefits, privacy concern, and trust. Simultaneously, the links between prior negative experience and privacy concern as well as the final authorizing willingness were uncovered. We employed a questionnaire to collect 455 users’ data, and the partial least squares structural equation model (PLS-SEM) was used to test the hypotheses. The findings demonstrate that App users’ perceived benefits and trust have a positive impact on their privacy authorization intention, whereas privacy concerns negatively affect their disclosure willingness. Just as Extraversion and Agreeableness would make someone pay a heightened attention to the benefits, agreeable, neurotic, and conscientious users are more easily stimulated by privacy concern. Respectively, Agreeableness and Neuroticism affect users’ trust positively and negatively. Additionally, prior negative experience will trigger an individual’s privacy concern, which in turn hinders their willingness to authorize his/her information. All of the aforementioned can serve as a guide for App providers as they optimize the features of their products and services, implement the necessary privacy protections to alleviate users’ privacy concern, and boost users’ trust belief. More importantly, these results effectively demonstrate the significance of personal traits in the formation of users’ privacy perceptions.
A Novel Combination of PCA and Machine Learning Techniques to Select the Most Important Factors for Predicting Tunnel Construction Performance
Authors: Wang Jiangfeng , Mohammed Ahmed Salih , Macioszek Elżbieta , Ali Mujahid , Ulrikh Dmitrii Vladimirovich , Fang Qiancheng
Published: June 2022

Numerous studies have reported the effective use of artificial intelligence approaches, particularly artificial neural networks (ANNs)-based models, to tackle tunnelling issues. However, having a high number of model inputs increases the running time and related mistakes of ANNs. The principal component analysis (PCA) approach was used in this work to select input factors for predicting tunnel boring machine (TBM) performance, specifically advance rate (AR). A reliable and precise forecast of TBM AR is desirable and critical for mitigating risk throughout the tunnel building phase. The developed PCAs (a total of four PCAs) were used with the artificial bee colony (ABC) method to predict TBM AR. To assess the created PCA-ANN-ABC model’s capabilities, an imperialist competitive algorithm-ANN and regression-based methods for estimating TBM AR were also suggested. To evaluate the artificial intelligence and statistical models, many statistical evaluation metrics were evaluated and generated, including the coefficient of determination (R2). The findings indicate that the PCA-ANN-ABC model (with R2 values of 0.9641 for training and 0.9558 for testing) is capable of predicting AR values with a high degree of accuracy, precision, and flexibility. The modelling approach utilized in this study may be used to other comparable studies involving the solution of engineering challenges.
Advances in Diagnosis and Therapy for Bladder Cancer
Authors: Hu Xinzi , Li Guangzhi , Wu Song
Published: June 2022

Bladder cancer (BCa) is one of the most common and expensive urinary system malignancies for its high recurrence and progression rate. In recent years, immense amounts of studies have been carried out to bring a more comprehensive cognition and numerous promising clinic approaches for BCa therapy. The development of innovative enhanced cystoscopy techniques (optical techniques, imaging systems) and tumor biomarkers-based non-invasive urine screening (DNA methylation-based urine test) would dramatically improve the accuracy of tumor detection, reducing the risk of recurrence and progression of BCa. Moreover, intravesical instillation and systemic therapeutic strategies (cocktail therapy, immunotherapy, vaccine therapy, targeted therapy) also provide plentiful measures to break the predicament of BCa. Several exploratory clinical studies, including novel surgical approaches, pharmaceutical compositions, and bladder preservation techniques, emerged continually, which are supposed to be promising candidates for BCa clinical treatment. Here, recent advances and prospects of diagnosis, intravesical or systemic treatment, and novel drug delivery systems for BCa therapy are reviewed in this paper.
External Validation of a Breath-Based Prediction Model for Malignant Pleural Mesothelioma
Authors: Janssens Eline , Schillebeeckx Eline , Zwijsen Kathleen , Raskin Jo , Van Cleemput Joris , Surmont Veerle F. , Nackaerts Kristiaan , Marcq Elly , van Meerbeeck Jan P. , Lamote Kevin
Published: June 2022

During the past decade, volatile organic compounds (VOCs) in exhaled breath have emerged as promising biomarkers for malignant pleural mesothelioma (MPM). However, as these biomarkers lack external validation, no breath test for MPM has been implemented in clinical practice. To address this issue, we performed the first external validation of a VOC-based prediction model for MPM. The external validation cohort was prospectively recruited, consisting of 47 MPM patients and 76 asbestos-exposed (AEx) controls. The predictive performance of the previously developed model was assessed by determining the degree of agreement between the predicted and actual outcome of the participants (patient/control). Additionally, to optimise the performance, the model was updated by refitting it to the validation cohort. External validation revealed a poor performance of the original model as the accuracy was estimated at only 41%, indicating poor generalisability. However, subsequent updating of the model improved the differentiation between MPM patients and AEx controls significantly (73% accuracy, 92% sensitivity, and 92% negative predictive value), substantiating the validity of the original predictors. This updated model will be more generalisable to the target population and exhibits key characteristics of a potential screening test for MPM, which could significantly impact MPM management.
Reirradiation of Locally Recurrent Prostate Cancer with Cyberknife® System or Volumetric Modulated Arc Therapy (VMAT) and IGRT-Clarity®: Outcomes, Toxicities and Dosimetric Evaluation
Authors: Di Franco Rossella , Borzillo Valentina , Scipilliti Esmeralda , Ametrano Gianluca , Serra Marcello , Arrichiello Cecilia , Savino Federica , De Martino Fortuna , D’Alesio Valentina , Cammarota Fabrizio , Crispo Anna , Pignata Sandro , Rossetti Sabrina , Quarto Giuseppe , Muto Paolo
Published: June 2022

The management of prostate cancer recurrence following external beam radiotherapy is not defined yet. Stereotaxic body reirradiation therapy showed encouraging results for local and biochemical control. From April 2017 to December 2020, 29 patients with prostate cancer recurrence were collected, joining the retrospective studies CyPro (prot. 46/19 OSS) and CLARO (Prot. 19/20 OSS) trials. Patients received Cyberknife® treatment (17 pts) or alternatively VMAT (Volumetric Modulated Arc Technique) therapy by IGRT (Image-Guided Radiation Therapy)/Clarity® (12 pts). By comparing the reirradiation of two groups, urinary (GU), rectal (GI) toxicities, and biochemical control were investigated. Further, the two techniques were dosimetrically compared by rival plans. The VMAT-IGRT Clarity® treatments were replanned with an optimized template developed for prostate VMAT-SBRT in FFF mode keeping the same dose and fractionation scheduled for Cyberknife Group (30 Gy in 5 fx, at 80% isodose). In the CK group, 23% of patients experienced grade 2 acute GU, while 6% grade 2 acute GI. In the VMAT-Clarity® group, acute GU toxicity was recorded in 17%, while for 8% grade 2 late toxicity was recorded. The dosimetric analysis shows that the VMAT-FFF allows to deliver a biological equivalent dose to CK, with the advantage of reducing the likelihood of toxicities arising.
Metal Ions (Li, Mg, Zn, Ce) Doped into La2O3 Nanorod for Boosting Catalytic Oxidative Coupling of Methane
Authors: Xiong Jing , Yu Hongbin , Wei Yuechang , Xie Chengshu , Lai Kezhen , Zhao Zhen , Liu Jian
Published: June 2022

A series of La2O3 nanorod catalysts with doping of active metal ions (Li, Mg, Zn and Ce) were synthesized successfully by the hydrothermal method. The La2O3 nanorods show a uniform size with the length of 50–200 nm and the width of 5–20 nm, and the {110} crystal facet is a preferentially exposed surface. The active metal ions (Li, Mg, Zn and Ce) doped into the lattice of La2O3 nanorods enhance the selectivity of the desired products during oxidative coupling of methane (OCM) and decrease the reaction temperature. Among these catalysts, the Mg-La2O3 catalyst exhibits the best catalytic performance during the OCM reaction, i.e., its selectivity and yield of C2 products at 780 °C is 73% and 21%, respectively. The effect of doped metal ions on catalytic activity for OCM was systematically investigated. Insight into the fabrication strategy and promoting factors of the OCM reaction indicates the potential to further design a high-efficient catalyst in the future.
Differential Transcriptional Responses in Two Old World Bemisia tabaci Cryptic Species Post Acquisition of Old and New World Begomoviruses
Authors: Mugerwa Habibu , Gautam Saurabh , Catto Michael A. , Dutta Bhabesh , Brown Judith K. , Adkins Scott , Srinivasan Rajagopalbabu
Published: June 2022

Begomoviruses are transmitted by several cryptic species of the sweetpotato whitefly, Bemisia tabaci (Gennadius), in a persistent and circulative manner. Upon virus acquisition and circulative translocation within the whitefly, a multitude of molecular interactions occur. This study investigated the differentially expressed transcript profiles associated with the acquisition of the Old World monopartite begomovirus, tomato yellow leaf curl virus (TYLCV), and two New World bipartite begomoviruses, sida golden mosaic virus (SiGMV) and cucurbit leaf crumple virus (CuLCrV), in two invasive B. tabaci cryptic species, Middle East-Asia Minor 1 (MEAM1) and Mediterranean (MED). A total of 881 and 559 genes were differentially expressed in viruliferous MEAM1 and MED whiteflies, respectively, compared with their non-viruliferous counterparts, of which 146 genes were common between the two cryptic species. For both cryptic species, the number of differentially expressed genes (DEGs) associated with TYLCV and SiGMV acquisition were higher compared with DEGs associated with CuLCrV acquisition. Pathway analysis indicated that the acquisition of begomoviruses induced differential changes in pathways associated with metabolism and organismal systems. Contrasting expression patterns of major genes associated with virus infection and immune systems were observed. These genes were generally overexpressed and underexpressed in B. tabaci MEAM1 and MED adults, respectively. Further, no specific expression pattern was observed among genes associated with fitness (egg production, spermatogenesis, and aging) in viruliferous whiteflies. The weighted gene correlation network analysis of viruliferous B. tabaci MEAM1 and MED adults identified different hub genes potentially implicated in the vector competence and circulative tropism of viruses. Taken together, the results indicate that both vector cryptic species and the acquired virus species could differentially affect gene expression.
Proteomics, Phosphoproteomics and Mirna Analysis of Circulating Extracellular Vesicles through Automated and High-Throughput Isolation
Authors: Zhang Hao , Cai Yu-Han , Ding Yajie , Zhang Guiyuan , Liu Yufeng , Sun Jie , Yang Yuchen , Zhan Zhen , Iliuk Anton , Gu Zhongze , Gu Yanhong , Tao W. Andy
Published: June 2022

Extracellular vesicles (EVs) play an important role in the diagnosis and treatment of diseases because of their rich molecular contents involved in intercellular communication, regulation, and other functions. With increasing efforts to move the field of EVs to clinical applications, the lack of a practical EV isolation method from circulating biofluids with high throughput and good reproducibility has become one of the biggest barriers. Here, we introduce a magnetic bead-based EV enrichment approach (EVrich) for automated and high-throughput processing of urine samples. Parallel enrichments can be performed in 96-well plates for downstream cargo analysis, including EV characterization, miRNA, proteomics, and phosphoproteomics analysis. We applied the instrument to a cohort of clinical urine samples to achieve reproducible identification of an average of 17,000 unique EV peptides and an average of 2800 EV proteins in each 1 mL urine sample. Quantitative phosphoproteomics revealed 186 unique phosphopeptides corresponding to 48 proteins that were significantly elevated in prostate cancer patients. Among them, multiple phosphoproteins were previously reported to associate with prostate cancer. Together, EVrich represents a universal, scalable, and simple platform for EV isolation, enabling downstream EV cargo analyses for a broad range of research and clinical applications.
Graphene-Wine Waste Derived Carbon Composites for Advanced Supercapacitors
Authors: Ureña-Torres Violeta , Moreno-Fernández Gelines , Gómez-Urbano Juan Luis , Granados-Moreno Miguel , Carriazo Daniel
Published: June 2022

In this work, we investigate the potential of a novel carbon composite as an electrode for high-voltage electrochemical double-layer capacitors. The carbon composite was prepared following a sustainable synthetic approach that first involved the pyrolysis and then the activation of a precursor formed by winery wastes and graphene oxide. The composite prepared in this way shows a very high specific surface area (2467 m2·g−1) and an optimum pore size distribution for their use in supercapacitor electrodes. Graphene-biowaste-derived carbon composites are tested as active electrode materials in two different non-aqueous electrolytes, the ammonium salt-based conventional organic electrolyte and one imidazolium-based ionic liquid (1 M Et4NBF4/ACN and EMINTFSI). It was found that the presence of graphene oxide led to significant morphological and textural changes, which result in high-energy and power densities of ~27 W·h·kg−1 at 13,026 W·kg−1. Moreover, the devices assembled retain above 70% of the initial capacitance after 6000 cycles in the case of the organic electrolyte.