bluuebunny/crossref_metadata_2025 huggingface dataset:
Change in the Constricted Airway in Patients after Clear Aligner Treatment: A Retrospective Study
Authors: Fountoulaki Georgia , Thurzo Andrej
Published: September 2022

This retrospective study evaluated changes in the pharyngeal portion of the upper airway in patients with constricted and normal airways treated with clear aligners (Invisalign, Align). Additionally, we assessed the change of tongue position in the oral cavity from a lateral view. Evaluation was performed with specialized software (Invivo 6.0, Anatomage) on pretreatment and post-treatment pairs of cone beam computed tomography imaging (CBCT) data. The level of airway constriction, volume, cross-section minimal area and tongue profile were evaluated. Patients with malocclusion, with pair or initial and finishing CBCT and without significant weight change between the scans, treated with Invisalign clear aligners were distributed into two groups. Group A consisted of fifty-five patients with orthodontic malocclusion and constricted upper airway. Control group B consisted of thirty-one patients with orthodontic malocclusions without any airway constriction. In the group with airway constriction there was a statistically significant increase in volume during therapy (p < 0.001). The surface of the most constricted cross-section of the airway did not change significantly after treatment in any of the groups. The final tongue position was different from the initial position in 62.2% of all clear aligner treatments. The position of the smallest clearance of the airway in the pharynx was similar for both groups localized at the level of 2nd cervical vertebra.
Pediatric COVID-19 Follow-Up with Lung Ultrasound: A Prospective Cohort Study
Authors: La Regina Domenico Paolo , Pepino Daniela , Nenna Raffaella , Iovine Elio , Mancino Enrica , Andreoli Gianmarco , Zicari Anna Maria , Spalice Alberto , Midulla Fabio ,   on behalf of the Long COVID Research Group
Published: September 2022

During the COVID-19 pandemic, lung ultrasound (LUS) was widely used to assess SARS-CoV-2 infection. To date, there are patients with persistence of symptoms after acute infection. Therefore, it may be useful to have an objective tool to follow these patients. The aim of our study was to evaluate the presence of LUS artifacts after SARS-CoV-2 infection in children and to analyze the associations between time elapsed since infection and symptomatology during acute infection. We conducted an observational study, enrolling 607 children infected with SARS-CoV-2 in the previous twelve months. All patients performed a LUS and medical history of demographic and clinical data. We observed irregular pleural lines in 27.5%, B-lines in 16.9%, and subpleural consolidations in 8.6% of the cases. These artifacts were more frequently observed in the lower lobe projections. We have observed that the frequency of artifacts decreases with increasing time since infection. In symptomatic patients during COVID infection, B-lines (p = 0.02) were more frequently found. In our sample, some children, even after months of acute infection, have ultrasound artifacts and showed an improvement with the passage of time from the acute episode. Our study provides additional evidence about LUS in children with previous COVID-19 as a support to follow these patients in the months following the infection.
The Usefulness of Magnetic Resonance Imaging (MRI) for the Detection of Local Recurrence after Mastectomy with Reconstructive Surgery in Breast Cancer Patients
Authors: Lee Jeongmin , Kang Bong Joo , Park Ga Eun , Kim Sung Hun
Published: September 2022

The purpose of this study is to investigate the usefulness of magnetic resonance imaging (MRI) for the detection of local recurrence after nipple-sparing mastectomy (NSM) or skin-sparing mastectomy (SSM) with immediate reconstructive surgery for breast cancer. Two hundred and eighty-six NSM or SSM procedures and immediate reconstruction cases between August 2015 and February 2020 were reviewed. The detectability rates of for local recurrence using MRI and ultrasound were assessed, and the characteristics of recurrent and primary cancers were evaluated. The patients with multifocal or multicentric primary cancer and a dense parenchymal pattern showed a higher recurrence rate (p < 0.001). A total of 22 cases showed recurrence, and due to multifocal recurrence, a total of 27 recurrent lesions were identified in the reconstructed breast, of which 12 were symptomatic and 15 were asymptomatic (p < 0.001). With the exception of skin recurrence (n = 6), MRI showed a significantly higher detectability rate (95.2%, 20 of 21) than ultrasound (38.1%, 8 of 21) for the recurrence of cancer in the reconstructed breast (p < 0.001), especially for small-sized (<1 cm) asymptomatic lesions. In addition, the mean recurrence interval of MRI-detected asymptomatic lesions was 21.7 months (SD ± 17.7), which was significantly longer than that of symptomatic recurrence. In conclusion, postoperative MRI can be useful for identifying small-sized (<1 cm) asymptomatic recurrence lesions in reconstructed breast tissue after NSM or SSM, which can be implemented within two years of surgery.
Pediatric Thymoma: A Review and Update of the Literature
Authors: Rossi Cristiana , Zanelli Magda , Sanguedolce Francesca , Zizzo Maurizio , Palicelli Andrea , Ricci Linda , Corsi Matteo , Caprera Cecilia , Cresta Camilla , Sollitto Francesco , Broggi Giuseppe , Caltabiano Rosario , Cavazza Alberto , Lococo Filippo , Loizzi Domenico , Ascani Stefano
Published: September 2022

Pediatric thymomas are extremely rare and slow-growing malignant tumors. The recent publication of the first Union for International Cancer Control (UICC)/American Joint Committee on Cancer (AJCC) Tumor–Node–Metastasis (TNM) stage classification and updated treatment guidelines for thymomas has prompted us to perform a review of the literature on pediatric thymomas. A search of English-language articles in the PubMed, Cochrane, Web of Science, and Embase databases was conducted. Additional articles were identified through reference lists of retrieved publications. Thirty-two articles involving 82 pediatric thymomas were included. Males comprised 60% of patients, and 13% manifested myasthenia gravis (MG). Histotype B1 (45%) and stage I (52% Masaoka–Koga and 71% UICC/AJCC TNM) were the most frequent. Of note is the possibility that the lack of cases with mixed histologies in the reviewed publications might be related to a sampling issue, as it is well known that the more sections are available for review, the more likely it is that the majority of these neoplasms will show mixed histologies. Both staging systems showed a gradual increase in the percentage of cases, with more advanced stages of disease moving from type A to B3 thymomas. Complete surgical resection (R0) was the main therapeutic approach in Masaoka–Koga stage I (89%) and UICC/AJCC TNM stage I (70%) thymomas. Advanced stages of disease and incomplete surgical resection were most often associated with recurrence and death. An association between stage and outcome, and completeness of resection and outcome, was found. Interestingly, though an association between histotype and staging was found, this does not take into account the possibility of mixed histologies which would reduce the clinical impact of histologic subtyping over staging.
The Diagnostic Value of Circulating Biomarkers and Role of Drug-Coated Balloons for In-Stent Restenosis in Patients with Peripheral Arterial Disease
Authors: Montelione Nunzio , Catanese Vincenzo , Nenna Antonio , Jawabra Mohamad , Verghi Emanuele , Loreni Francesco , Nappi Francesco , Lusini Mario , Mastroianni Ciro , Jiritano Federica , Serraino Giuseppe Filiberto , Mastroroberto Pasquale , Codispoti Francesco Alberto , Chello Massimo , Spinelli Francesco , Stilo Francesco
Published: September 2022

Peripheral arterial disease (PAD) is an increasingly pathological condition that commonly affects the femoropopliteal arteries. The current fashionable treatment is percutaneous transluminal angioplasty (PTA), often with stenting. However, the in-stent restenosis (ISR) rate after the stenting of the femoropopliteal (FP) district remains high. Many techniques have been proposed for the treatment of femoropopliteal ISR, such as intravascular brachytherapy, laser atherectomy, second stenting and drug-coated balloons angioplasty (DCB). DCB showed a significantly lower rate of restenosis and target lesions revascularization (TLR) compared to conventional PTA. However, further studies and multi-center RCTs with dedicated long-term follow-up are needed to verify the true efficiency of this approach. Nowadays, the correlation between PAD and inflammation biomarkers is well known. Multiple studies have shown that proinflammatory markers (such as C-reactive proteins) and the high plasma levels of microRNA could predict the outcomes after stent placement. In particular, circulating microRNA-320a, microRNA-3937, microRNA-642a-3p and microRNA-572 appear to hold promise in diagnosing ISR in patients with PAD, but also as predictors of stent patency. This narrative review intends to summarize the current knowledge on the value of circulating biomarkers as predictors of ISR and to foster the scientific debate on the advantages of using DCB in the treatment of ISR in the FP district.
Human Breast Milk: The Key Role in the Maturation of Immune, Gastrointestinal and Central Nervous Systems: A Narrative Review
Authors: Dimitroglou Margarita , Iliodromiti Zoi , Christou Evangelos , Volaki Paraskevi , Petropoulou Chrysa , Sokou Rozeta , Boutsikou Theodora , Iacovidou Nicoletta
Published: September 2022

Premature birth is a major cause of mortality and morbidity in the pediatric population. Because their immune, gastrointestinal and nervous systems are not fully developed, preterm infants (<37 weeks of gestation) and especially very preterm infants (VPIs, <32 weeks of gestation) are more prone to infectious diseases, tissue damage and future neurodevelopmental impairment. The aim of this narrative review is to report the immaturity of VPI systems and examine the role of Human Breast Milk (HBM) in their development and protection against infectious diseases, inflammation and tissue damage. For this purpose, we searched and synthesized the data from the existing literature published in the English language. Studies revealed the significance of HBM and indicate HBM as the best dietary choice for VPIs.
Electroencephalogram Signals for Detecting Confused Students in Online Education Platforms with Probability-Based Features
Authors: Daghriri Talal , Rustam Furqan , Aljedaani Wajdi , Bashiri Abdullateef H. , Ashraf Imran
Published: September 2022

Online education has emerged as an important educational medium during the COVID-19 pandemic. Despite the advantages of online education, it lacks face-to-face settings, which makes it very difficult to analyze the students’ level of interaction, understanding, and confusion. This study makes use of electroencephalogram (EEG) data for student confusion detection for the massive open online course (MOOC) platform. Existing approaches for confusion detection predominantly focus on model optimization and feature engineering is not very well studied. This study proposes a novel engineering approach that uses probability-based features (PBF) for increasing the efficacy of machine learning models. The PBF approach utilizes the probabilistic output from the random forest (RF) and gradient-boosting machine (GBM) as a feature vector to train machine learning models. Extensive experiments are performed by using the original features and PBF approach through several machine learning models with EEG data. Experimental results suggest that by using the PBF approach on EEG data, a 100% accuracy can be obtained for detecting confused students. K-fold cross-validation and performance comparison with existing approaches further corroborates the results.
Research on Bi–ISAR Sparse Aperture High Resolution Imaging Algorithm under Low SNR
Authors: Zhu Hanshen , Hu Wenhua , Guo Baofeng , Jiao Liting , Zhu Xiaoxiu , Zhu Chang’an
Published: September 2022

In the imaging process of bistatic inverse synthetic aperture radar (Bi–ISAR), the echo is easily affected by the internal interference and external environment of the radar system, resulting in the problems of sparse aperture and low echo signal noise ratio. The efficiency of conventional sparse aperture imaging methods is greatly reduced. To solve the above problems, a Bi–ISAR sparse aperture imaging algorithm based on Complex Variational Modal Decomposition (CVMD) and wavelet threshold de–noising is proposed. Firstly, the Bi–ISAR sparse aperture echo signal model is established, the sparse basis matching the echo is constructed, the echo signal is decomposed into different intrinsic mode functions (IMF) by CVMD, and the IMFs belonging to the signal are separated by the energy relationship criterion. Then, after the IMFs is de–noising by the improved wavelet threshold de–noising algorithm, the original signal is synthesized, and the signal after de–noising is reconstructed by using the orthogonal matching pursuing algorithm. Simulation results show that the proposed algorithm can achieve Bi–ISAR sparse aperture high−resolution imaging under low signal noise ratio and has fine anti−noise performance.
Microfabrication, Characterization, and Cold-Test Study of the Slow-Wave Structure of a Millimeter-Band Backward-Wave Oscillator with a Sheet Electron Beam
Authors: Starodubov Andrey , Torgashov Roman , Galushka Viktor , Pavlov Anton , Titov Vladimir , Ryskin Nikita , Abhishek Anand , Kumar Niraj
Published: September 2022

In this paper, the results of the microfabrication, characterization, and cold-test study of the previously proposed truncated sine-waveguide interaction structure with wideband-matched output couplers for the millimeter-band backward-wave oscillator (BWO) driven by a high-current-density sheet electron beam are presented. Computer-numerical-control (CNC) micromilling was used to fabricate the designed interaction structure. The first sample was microfabricated from an aluminum alloy to test the milling process. The final sample was made from oxygen-free copper. Scanning electron microscopy (SEM) and optical microscopy were used to investigate the morphology of the microfabricated samples, and stylus profilometry was used to estimate the level of the surface roughness. Cold S-parameters were measured in Q- and V-bands (40–70 GHz), using a vector network analyzer (VNA). Using the experimentally measured phase data of the transmitted signal, the dispersion of the fabricated interaction structure was evaluated. The experimentally measured dispersion characteristic is in good agreement with the numerically calculated.
Rapid Harmonic Detection Scheme Based on Expanded Input Observer
Authors: Zhu Zuoping , Xu Maoguang , Li Po , Wang Qiuyu
Published: September 2022

The existence of harmonics will cause the quality of power supply in a power system to decline and will affect the normal use of the power system. Therefore, it is important to suppress harmonics in the power system, and the first step of harmonic suppression is harmonic detection. To address this phenomenon, a fast harmonic detection method is proposed in this paper. It is based on the input observer theory to construct a state space model based on the original signal and harmonic components and estimate the state variables so as to achieve harmonic extraction. The characteristic roots are used to prove the convergence of the observer. In addition, the Second-Order Generalized Integration (SOGI) frequency estimation method is chosen to cascade with it so that harmonic detection can be accomplished with unknown frequencies. The simulation results prove that the proposed method can quickly converge and accurately extract each harmonic in the case of fluctuations in the fundamental amplitude, fundamental frequency and phase of the input signal, and the whole process can be completed in 0.02 s. The possible effects of white noise on harmonic extraction are also simulated, and the results prove that the accuracy of harmonic extraction can still be guaranteed in the presence of white noise. By using the Speedgoat real-time target machine built Rapid Control Prototype (RCP) as a testbed, experiments with similar simulation conditions were performed. The results show that the method has fast and accurate harmonic detection performance.
An AI-Based Adaptive Surrogate Modeling Method for the In-Service Response of UVLED Modules
Authors: Yuan Cadmus
Published: September 2022

The response forecasting of in-service complex electronic systems remains a challenge due to its uncertainty. An AI-based adaptive surrogate modeling method, including offline and online learning procedures, is proposed in this research for different systems with significant variety. The offline learning aims to abstract the knowledge from the known information and represent it as root models. The in-service response is modeled by a linear combination of the online learning of these root models against the continuous new measurement. This research applies a performance measurement dataset of the UVLED modules with considerable deviation to verify the proposed method. Part of the datasets is selected to generate the root models by offline learning, and these root models are applied to the online learning procedures for the adaptive surrogate model (ASM) of the different systems. The results show that after approximately 10 online learning iterations, the ASM achieves the capability of predicting 1000 h of response.
Diagnosis of Histopathological Images to Distinguish Types of Malignant Lymphomas Using Hybrid Techniques Based on Fusion Features
Authors: Al-Mekhlafi Zeyad Ghaleb , Senan Ebrahim Mohammed , Mohammed Badiea Abdulkarem , Alazmi Meshari , Alayba Abdulaziz M. , Alreshidi Abdulrahman , Alshahrani Mona
Published: September 2022

Malignant lymphoma is one of the types of malignant tumors that can lead to death. The diagnostic method for identifying malignant lymphoma is a histopathological analysis of lymphoma tissue images. Because of the similar morphological characteristics of the lymphoma types, it is difficult for doctors and specialists to manually distinguish the types of lymphomas. Therefore, deep and automated learning techniques aim to solve this problem and help clinicians reconsider their diagnostic decisions. Because of the similarity of the morphological characteristics between lymphoma types, this study aimed to extract features using various algorithms and deep learning models and combine them together into feature vectors. Two datasets have been applied, each with two different systems for the reliable diagnosis of malignant lymphoma. The first system was a hybrid system between DenseNet-121 and ResNet-50 to extract deep features and reduce their dimensions by the principal component analysis (PCA) method, using the support vector machine (SVM) algorithm for classifying low-dimensional deep features. The second system was based on extracting the features using DenseNet-121 and ResNet-50 and combining them with the hand-crafted features extracted by gray level co-occurrence matrix (GLCM), fuzzy color histogram (FCH), discrete wavelet transform (DWT), and local binary pattern (LBP) algorithms and classifying them using a feed-forward neural network (FFNN) classifier. All systems achieved superior results in diagnosing the two datasets of malignant lymphomas. An FFNN classifier with features of ResNet-50 and hand-crafted features reached an accuracy of 99.5%, specificity of 100%, sensitivity of 99.33%, and AUC of 99.86% for the first dataset. In contrast, the same technique reached 100% for all measures to diagnose the second dataset.
Privacy-Preserving Top-k Query Processing Algorithms Using Efficient Secure Protocols over Encrypted Database in Cloud Computing Environment
Authors: Kim Hyeong-Jin , Kim Yong-Ki , Lee Hyun-Jo , Chang Jae-Woo
Published: September 2022

Recently, studies on secure database outsourcing have been highlighted for the cloud computing environment. A few secure Top-k query processing algorithms have been proposed in the encrypted database. However, the previous algorithms can support either security or efficiency. Therefore, we propose a new Top-k query processing algorithm using a homomorphic cryptosystem, which can support both security and efficiency. For security, we propose new secure and efficient protocols based on arithmetic operations. To obtain a high level of efficiency, we also propose a parallel Top-k query processing algorithm using an encrypted random value pool. Through our performance analysis, the proposed Top-k algorithms present about 1.5∼7.1 times better performance with regard to a query processing time, compared with the existing algorithms.
Modification of SPWM Modulating Signals for Energy Balancing Purposes
Authors: Reyes-Severiano Yesenia , De León Aldaco Susana Estefany , Aguayo Alquicira Jesus , Carrillo-Santos Luis Mauricio , Lozoya-Ponce Ricardo Eliú , Medrano Hermosillo Jesús Alfonso
Published: September 2022

There is currently a growing interest in efficient power generation and transformation without increasing the cost and complexity of a system. One type of transformation is the conversion of energy from a direct current to an alternating current, which is used in various applications, for example, in photovoltaic systems. One of the elementary components of these systems is the inverter. However, there are several drawbacks in the design of these systems, such as the energy balance between their semiconductor devices. Therefore, it is important to study alternatives to balance the energy and thus achieve a positive impact on both the economic and reliability aspects of the system. This article deals with the study, design, and implementation of the modification of a modulation technique with reconstructed modulating signals, which aims to ensure the energy balance in each cell of a multilevel inverter and, at the same time, present better results concerning the different parameters of comparison established, such as harmonic distortion, percentage of unbalance, percentage of use of digital resources, and power transferred to the load.
Clustering Algorithm Based on the Ground-Air Cooperative Architecture in Border Patrol Scenarios
Authors: Shao Yanling , Liu Liming , Gao Hewen , Xu Hao , Wang Yaokuan , Gong Siliang , Huang Hanyao
Published: September 2022

The border security situation is complex and severe, and the border patrol system relying on the ground-air cooperative architecture has been paid attention to by all countries as an important means of protecting national security. In the flying ad-hoc network (FANET), under the ground-air cooperative architecture, an unmanned aerial vehicle (UAV) uses a patrol mobility model to improve patrol efficiency. Since the patrol mobility model leads to frequent changes in UAV movement direction to improve patrol efficiency, selecting some clustering utility factors and calculating utility factors in previous clustering algorithms do not apply to this scenario. To solve the above problems, in this paper, we propose a border patrol clustering algorithm (BPCA) based on the ground-air cooperative architecture, which is based on the existing weighted clustering algorithm and improved in terms of the selection of utility factors and calculations of utility factors in cluster head selection. This algorithm comprehensively considers the effects of relative speed, relative distance, and the movement model of the UAV on the network topology. Extensive simulation results show that this algorithm can extend the duration time of cluster heads and cluster members and improve the stability of clusters and the reliability of links.
Design of Light-Weight Timing Error Detection and Correction Circuits for Energy-Efficient Near-Threshold Voltage Operation
Authors: Fan Xuemei , Liu Hao , Li Hongwei , Lu Shengli , Han Jie
Published: September 2022

Near-threshold voltage (NTV) operation has the potential to improve the energy efficiency of digital integrated circuits. However, the use of a conservative timing guard band to avoid the timing errors introduces excessive timing margins, thus causing larger energy dissipation in the NTV region. An error-tolerant design based on timing error detection and correction circuits has been shown to be a promising solution to mitigate these issues. This paper presents a light-weight timing error-tolerant flip-flop (ETFF) design. This design detects timing errors using a node transition signal detector with only nine transistors and corrects these errors during the same clock cycle. Moreover, transistor sizing is explored to optimize the trade-off between performance and area overhead. The proposed ETFFs are inserted into a monitored circuit by replacing original flip-flops at timing-monitored points. To further reduce the overhead, we develop a mean-time-to-failure-aware method to select the monitored points by simultaneously considering the critical path coverage and activation rates of flip-flops. The simulation results show that a CNN accelerator using the proposed timing error-tolerant design implemented in the SMIC CMOS 40 nm process can robustly work at 1.1–0.3 V with only 3.5% area overhead. Furthermore, this design reduces the area overhead by 54.68% and improves the energy efficiency by 53.69% at 0.6 V, compared with the Razor flip-flop design. The advantage of the proposed design lies in that it requires smaller circuit overheads and can work reliably in a wider range of supply voltages.
Gain Enhancement of a Dual-Band Antenna with the FSS
Authors: Shi Chengming , Zou Jie , Gao Jing , Liu Changjun
Published: September 2022

A dual-band directional antenna for Industrial, Scientific, and Medical (ISM) band application is proposed in this article. The antenna consists of two layers of substrates. The first layer contains the square loop loading with a meander stub to realize the dual band. The second layer is a frequency selective surface (FSS) structure, which is a periodic array with square loops. The phase shift from the FSS reflection and the distance between two layers are optimized to realize the field superposition, which could achieve gain enhancement and bandwidth improvement at two operating bands, simultaneously. The measured results indicate that within a 2.3–2.62 GHz range and a 4.9–6.45 GHz range, the |S11| of the antenna is less than −10 dB. The −10 dB impedance bandwidth is 13% and 27%, respectively. The gain of the antenna is 6.8 dB at 2.45 GHz and 9.0 dB at 5.8 GHz. Meanwhile, the antenna gain is over 8.5 dB from 5.0 GHz to 6.0 GHz. The working band of the antenna covers all bands of WLAN. The design has a good application prospect in the future.
A Hierarchical Heterogeneous Graph Attention Network for Emotion-Cause Pair Extraction
Authors: Yu Jiaxin , Liu Wenyuan , He Yongjun , Zhong Bineng
Published: September 2022

Recently, graph neural networks (GNN), due to their compelling representation learning ability, have been exploited to deal with emotion-cause pair extraction (ECPE). However, current GNN-based ECPE methods mostly concentrate on modeling the local dependency relation between homogeneous nodes at the semantic granularity of clauses or clause pairs, while they fail to take full advantage of the rich semantic information in the document. To solve this problem, we propose a novel hierarchical heterogeneous graph attention network to model global semantic relations among nodes. Especially, our method introduces all types of semantic elements involved in the ECPE, not just clauses or clause pairs. Specifically, we first model the dependency between clauses and words, in which word nodes are also exploited as an intermediary for the association between clause nodes. Secondly, a pair-level subgraph is constructed to explore the correlation between the pair nodes and their different neighboring nodes. Representation learning of clauses and clause pairs is achieved by two-level heterogeneous graph attention networks. Experiments on the benchmark datasets show that our proposed model achieves a significant improvement over 13 compared methods.
A Survey on Moving Target Defense for Networks: A Practical View
Authors: Jalowski Łukasz , Zmuda Marek , Rawski Mariusz
Published: September 2022

The static nature of many of currently used network systems has multiple practical benefits, including cost optimization and ease of deployment, but it makes them vulnerable to attackers who can observe from the shadows to gain insight before launching a devastating attack against the infrastructure. Moving target defense (MTD) is one of the emerging areas that promises to protect against this kind of attack by continuously shifting system parameters and changing the attack surface of protected systems. The emergence of network functions virtualization (NFV) and software-defined networking (SDN) technology allows for the implementation of very sophisticated MTD techniques. Furthermore, the introduction of such solutions as field-programmable gate array (FPGA) programmable acceleration cards makes it possible to take the MTD concept to the next level. Applying hardware acceleration to existing concepts or developing new, dedicated methods will offer more robust, efficient, and secure solutions. However, to the best of the authors’ knowledge, there are still no major implementations of MTD schemes inside large-scale networks. This survey aims to understand why, by analyzing research made in the field of MTD to show current pitfalls and possible improvements that need to be addressed in future proposals to make MTD a viable solution to address current cybersecurity threats in real-life scenarios.
Feature Map Analysis-Based Dynamic CNN Pruning and the Acceleration on FPGAs
Authors: Li Qi , Li Hengyi , Meng Lin
Published: September 2022

Deep-learning-based applications bring impressive results to graph machine learning and are widely used in fields such as autonomous driving and language translations. Nevertheless, the tremendous capacity of convolutional neural networks makes it difficult for them to be implemented on resource-constrained devices. Channel pruning provides a promising solution to compress networks by removing a redundant calculation. Existing pruning methods measure the importance of each filter and discard the less important ones until reaching a fixed compression target. However, the static approach limits the pruning effect. Thus, we propose a dynamic channel-pruning method that dynamically identifies and removes less important filters based on a redundancy analysis of its feature maps. Experimental results show that 77.10% of floating-point operations per second (FLOPs) and 91.72% of the parameters are reduced on VGG16BN with only a 0.54% accuracy drop. Furthermore, the compressed models were implemented on the field-programmable gate array (FPGA) and a significant speed-up was observed.
A Multi-Objective Approach for Optimizing Edge-Based Resource Allocation Using TOPSIS
Authors: Mohamed Habiba , Al-Masri Eyhab , Kotevska Olivera , Souri Alireza
Published: September 2022

Existing approaches for allocating resources on edge environments are inefficient and lack the support of heterogeneous edge devices, which in turn fail to optimize the dependency on cloud infrastructures or datacenters. To this extent, we propose in this paper OpERA, a multi-layered edge-based resource allocation optimization framework that supports heterogeneous and seamless execution of offloadable tasks across edge, fog, and cloud computing layers and architectures. By capturing offloadable task requirements, OpERA is capable of identifying suitable resources within nearby edge or fog layers, thus optimizing the execution process. Throughout the paper, we present results which show the effectiveness of our proposed optimization strategy in terms of reducing costs, minimizing energy consumption, and promoting other residual gains in terms of processing computations, network bandwidth, and task execution time. We also demonstrate that by optimizing resource allocation in computation offloading, it is then possible to increase the likelihood of successful task offloading, particularly for computationally intensive tasks that are becoming integral as part of many IoT applications such robotic surgery, autonomous driving, smart city monitoring device grids, and deep learning tasks. The evaluation of our OpERA optimization algorithm reveals that the TOPSIS MCDM technique effectively identifies optimal compute resources for processing offloadable tasks, with a 96% success rate. Moreover, the results from our experiments with a diverse range of use cases show that our OpERA optimization strategy can effectively reduce energy consumption by up to 88%, and operational costs by 76%, by identifying relevant compute resources.
Monthly Dynamical Patterns of Nitrogen and Phosphorus Resorption Efficiencies and C:N:P Stoichiometric Ratios in Castanopsis carlesii (Hemsl.) Hayata and Cunninghamia lanceolata (Lamb.) Hook. Plantations
Authors: Zhang Yaoyi , Yang Jing , Wei Xinyu , Ni Xiangyin , Wu Fuzhong
Published: September 2022

Trees can resorb nutrients to preserve and reuse them before leaves fall, which could efficiently adapt to environmental changes. However, the nutrient requirements of trees in different months with seasonal climate changes are often neglected. In this study, we selected plantations of an evergreen broadleaf tree (Castanopsis carlesii (Hemsl.) Hayata) and a coniferous tree (Cunninghamia lanceolate (Lamb.) Hook.) in the subtropics. The monthly dynamics of leaf nitrogen (N) and phosphorus (P) resorption efficiencies and C:N:P stoichiometric ratios were checked along a growing season from April to October 2021. Trees in both plantations exhibited efficient N and P resorption but with significant monthly variations. The N and P resorption efficiencies in the Cunninghamia lanceolata plantation ranged from 34.26% to 56.28% and 41.01% to 54.85%, respectively, and were highest in September. In contrast, N and P resorption efficiencies in the Castanopsis carlesii plantation ranged from 11.25% to 34.23% and 49.22% to 58.72%, respectively, and were highest in July. Compared with the Cunninghamia lanceolata, the C:N of the Castanopsis carlesii plantation was significantly lower, while its C:P was significantly higher in May and September. The Castanopsis carlesii plantation was strongly limited by P (the N:P ratios in mature leaves were higher than 20), whereas the Cunninghamia lanceolata plantation might be limited by both N and P (the N:P ratios in mature leaves were between 10 and 20). In addition, the statistical analyses revealed that temperature and precipitation were significantly associated with N and P resorption efficiencies, but the relationships were controlled by forest types. These findings highlight that efficient resorption of N and P may be beneficial in regulating nutrient limitation and balance in subtropical forest ecosystems. These results contribute to the understanding of N and P utilization strategies of trees and provide a theoretical basis for vegetation management in the subtropics.
Climate Smart Forestry in the Southern United States
Authors: Shephard Noah , Narine Lana , Peng Yucheng , Maggard Adam
Published: September 2022

In the United States, Climate Smart Forestry (CSF) has quickly become a popular topic within the academic, political, and industry realms, without substantial delineation of what exactly CSF is. In this review, the aim is to provide a broad overview of CSF by highlighting one of the most productive and prolific forest systems in the United States, loblolly pine (Pinus taeda L.) plantations. One major objective of CSF is to increase forest carbon storage to combat rising atmospheric carbon or climate change mitigation. Fortuitously, increased forest carbon storage can work harmoniously with on-going Southern pine plantation forestry. With a Southern commercial focus, we show (1) traditional plantation practices such as genetic improvement, site preparation, weed control, and fertilization have aided increased forest carbon storage; (2) forest products and forest product carbon are essential to increase carbon storage beyond the stand-carbon baseline; (3) forest carbon data collection must be improved to realize climate change mitigation goals; and (4) additional avenues for future CSF research.
Effects of Soundscapes on Human Physiology and Psychology in Qianjiangyuan National Park System Pilot Area in China
Authors: Wang Peng , He Youjun , Yang Wenjuan , Li Nan , Chen Jiaojiao
Published: September 2022

The development of China’s national parks is still in the initial stage, and few scholars have studied the effects of soundscapes on human physiology and psychology from the perspective of the auditory senses in national parks. In this study, the Qianjiangyuan National Park System Pilot Area was taken as the research subject, physiological indicators of subjects were collected through a biopAC-MP150 multi-channel physiological instrument data platform, and the subjective psychological response of soundscapes was measured using a Likert scale. The results showed that the sound of water had the most significant effect on the heart rate and respiratory rate of the subjects. Agricultural sound had the greatest impact on the skin conduction levels, while conversation had the least overall impact on human physiology. There were significant differences in comfort, excitement, and significance among the different soundscapes (p < 0.001). The sounds of insects are more likely to elicit feelings of comfort and excitement, while the sounds of birds are more likely to arouse curiosity. No significant correlation was observed between the physiological indices and psychological indices. The study on the effects of different soundscapes on human physiology and psychology in China’s national parks will provide a basis for the decision makers of national parks to formulate more effective planning, design, and management policies regarding soundscapes.
Dynamics of Forage and Management Implications for Large Herbivore Habitat in Seasonally Dry Forest of Southeast Asia
Authors: Chankhao Andaman , Kraichak Ekaphan , Phumsathan Sangsan , Pongpattananurak Nantachai
Published: September 2022

Forage plants, as primary producers, play an essential role in maintaining populations of large herbivores. The availability and quality of these forage plants can affect the health and viability of these animals. Seasonally dry forests of Huai Kha Khaeng Wildlife Sanctuary and Huai Thab Salao-Huai Rabum Non-Hunting Area are recognized as one of the largest contiguous pieces of forests in mainland Southeast Asia and serve as a home to many large herbivore species, particularly banteng (Bos javanicus birmanicus). However, our understanding of forage plants and their dynamics is still limited. Therefore, the current study was undertaken to understand the dynamics of forage plants, prescribed burning effects, and the associated environmental factors. During 2018–2019, the results showed that the highest forage availability was in June after the prescribed burns at 156.2–252.6 kg ha−1 and the lowest in February before the burning at 16.8–39.8 kg ha−1. Environmental factors that impacted the forage availability include canopy cover, tree density, tree basal area, soil bulk density, soil pH, and topography. However, the impacts of these factors varied among the studied plant life forms, suggesting the importance of active habitat management through prescribed burns and stand improvement to maintain sufficient forage for large herbivores in the future.
Do AI Models Improve Taper Estimation? A Comparative Approach for Teak
Authors: Fernández-Carrillo Víctor Hugo , Quej-Chi Víctor Hugo , De los Santos-Posadas Hector Manuel , Carrillo-Ávila Eugenio
Published: September 2022

Correctly estimating stem diameter at any height is an essential task in determining the profitability of a commercial forest plantation, since the integration of the cross-sectional area along the stem of the trees allows estimating the timber volume. In this study the ability of four artificial intelligence (AI) models to estimate the stem diameter of Tectona grandis was assessed. Genetic Programming (PG), Gaussian Regression Process (PGR), Category Boosting (CatBoost) and Artificial Neural Networks (ANN) models’ ability was evaluated and compared with those of Fang 2000 and Kozak 2004 conventional models. Coefficient of determination (R2), Root Mean Square of Error (RMSE), Mean Error of Bias (MBE) and Mean Absolute Error (MAE) statistical indices were used to evaluate the models’ performance. Goodness of fit criterion of all the models suggests that Kozak’s model shows the best results, closely followed by the ANN model. However, PG, PGR and CatBoost outperformed the Fang model. Artificial intelligence methods can be an effective alternative to describe the shape of the stem in Tectona grandis trees with an excellent accuracy, particularly the ANN and CatBoost models.
Blood-Based Non-Invasive Tests of Hepatic Fibrosis in Autoimmune Hepatitis: Application among Selected Patients Leads to Higher Accuracy
Authors: Ferronato Marco , Lenzi Marco , Muratori Paolo , Muratori Luigi
Published: September 2022

Background. Assessment of liver fibrosis is essential to guide treatment in autoimmune hepatitis (AIH), but non-invasive tests (NITs) showed poor accuracy. Our study aims to evaluate the performance of NITs among different AIH presentations. Methods. Monocentric retrospective study among 122 AIH patients. NITs were compared to histological grading of liver fibrosis. We performed an accuracy analysis among acute (jaundice and/or transaminases > 10 times upper limit of normal) and non-acute patients. Results. A significant difference in the distribution of NIT values for each Ishak stage was found for spleen-diameter-to-platelet-count ratio (SD/PC) (p < 0.001), fibrosis-4-score (FIB-4) (p = 0.002), AST-to-ALT ratio (AAR) (p = 0.002), red-blood-cell-width-distribution-to-platelet-count ratio (RDW/PC) (p = 0.008) and AST-to-platelet-count ratio (APRI) (p = 0.029). The AUC for advanced fibrosis of SD/PC, FIB-4, RDW/PC, APRI and AAR were, respectively, 0.814, 0.770, 0.768, 0.708 and 0.694. The AUC of SD/PC, FIB-4 and APRI in non-acute subgroup were 0.902, 0.834 and 0.758, while in acute patients they were 0.754, 0.724 and 0.716. RDW/PC and AAR weren’t different among the two subgroups. Conclusions. For SD/PC, FIB-4 and APRI, diagnostic accuracy is higher in patients with non-acute presentation. In this context, SD/PC and FIB-4 showed an overall performance that could be of interest in clinical practice alongside other non-invasive techniques.
Evaluation of Intracellular Gene Transfers from Plastome to Nuclear Genome across Progressively Improved Assemblies for Arabidopsis thaliana and Oryza sativa
Authors: Wang Haoqi , Liao Xuezhu , Tembrock Luke R. , Yang Zuoren , Wu Zhiqiang
Published: September 2022

DNA originating from organellar genomes are regularly discovered in nuclear sequences during genome assembly. Nevertheless, such insertions are sometimes omitted during the process of nuclear genome assembly because the inserted DNA is assigned to organellar genomes, leading to a systematic underestimation of their frequency. With the rapid development of high-throughput sequencing technology, more inserted fragments from organelle genomes can now be detected. Therefore, it is necessary to be aware of the insertion events from organellar genomes during nuclear genome assembly to properly attribute the impact and rate of such insertions in the evolution of nuclear genomes. Here, we investigated the impact of intracellular gene transfer (IGT) from the plastome to the nuclear genome using genome assemblies that were refined through time with technological improvements from two model species, Arabidopsis thaliana and Oryza sativa. We found that IGT from the plastome to the nuclear genome is a dynamic and ongoing process in both A. thaliana and O. sativa, and mostly occurred recently, as the majority of transferred sequences showed over 95% sequence similarity with plastome sequences of origin. Differences in the plastome-to-nuclear genome IGT between A. thaliana and O. sativa varied among the different assembly versions and were associated with the quality of the nuclear genome assembly. IGTs from the plastome to nuclear genome occurred more frequently in intergenic regions, which were often associated with transposable elements (TEs). This study provides new insights into intracellular genome evolution and nuclear genome assembly by characterizing and comparing IGT from the plastome into the nuclear genome for two model plant species.
Complete Chloroplast Genomes of 14 Subspecies of D. glomerata: Phylogenetic and Comparative Genomic Analyses
Authors: Jiao Yongjuan , Feng Guangyan , Huang Linkai , Nie Gang , Li Zhou , Peng Yan , Li Dandan , Xiong Yanli , Hu Zhangyi , Zhang Xinquan
Published: September 2022

Orchardgrass (Dactylis glomerata L.) is a species in the Gramineae family that is highly important economically and valued for its role in ecology. However, the phylogeny and taxonomy of D. glomerata are still controversial based on current morphological and molecular evidence. The study of chloroplast (cp) genomes has developed into a powerful tool to develop molecular markers for related species and reveal the relationships between plant evolution and phylogenetics. In this study, we conducted comparative genomic analyses and phylogenetic inferences on 14 cp genomes of D. glomerata originating from the Mediterranean and Eurasia. The genome size ranged from 134,375 bp to 134,993 bp and exhibited synteny of gene organization and order. A total of 129–131 genes were identified, including 85–87 protein coding genes, 38 tRNA genes and 8 rRNA genes. The cp sequences were highly conserved, and key sequence variations were detected at the junctions of inverted repeats (IRs)/small single–copy (SSC) regions. Moreover, nine highly variable regions were identified among the subspecies based on a sequence divergence analysis. A total of 285 RNA editing sites were detected that were relevant to 52 genes, where rpoB exhibited the most abundant RNA editing sites. The phylogenetic analysis revealed that all Dactylis subspecies clustered into a monophyletic group and most branches provided a high support bootstrap. The main divergence time of D. glomerata was dated to the Miocene era, and this could have been due to changes in the climate. These findings will provide useful insights for further studies on phylogeny, the identification of subspecies and the development of hypotheses for the evolutionary history of the genus Dactylis and of the Gramineae family.