bluuebunny/crossref_metadata_2025 huggingface dataset:
Lung Inflammation Predictors in Combined Immune Checkpoint-Inhibitor and Radiation Therapy—Proof-of-Concept Animal Study
Authors: Spieler Benjamin , Giret Teresa M. , Welford Scott , Totiger Tulasigeri M. , Mihaylov Ivaylo B.
Published: May 2022

Purpose: Combined radiotherapy (RT) and immune checkpoint-inhibitor (ICI) therapy can act synergistically to enhance tumor response beyond what either treatment can achieve alone. Alongside the revolutionary impact of ICIs on cancer therapy, life-threatening potential side effects, such as checkpoint-inhibitor-induced (CIP) pneumonitis, remain underreported and unpredictable. In this preclinical study, we hypothesized that routinely collected data such as imaging, blood counts, and blood cytokine levels can be utilized to build a model that predicts lung inflammation associated with combined RT/ICI therapy. Materials and Methods: This proof-of-concept investigational work was performed on Lewis lung carcinoma in a syngeneic murine model. Nineteen mice were used, four as untreated controls and the rest subjected to RT/ICI therapy. Tumors were implanted subcutaneously in both flanks and upon reaching volumes of ~200 mm3 the animals were imaged with both CT and MRI and blood was collected. Quantitative radiomics features were extracted from imaging of both lungs. The animals then received RT to the right flank tumor only with a regimen of three 8 Gy fractions (one fraction per day over 3 days) with PD-1 inhibitor administration delivered intraperitoneally after each daily RT fraction. Tumor volume evolution was followed until tumors reached the maximum size allowed by the Institutional Animal Care and Use Committee (IACUC). The animals were sacrificed, and lung tissues harvested for immunohistochemistry evaluation. Tissue biomarkers of lung inflammation (CD45) were tallied, and binary logistic regression analyses were performed to create models predictive of lung inflammation, incorporating pretreatment CT/MRI radiomics, blood counts, and blood cytokines. Results: The treated animal cohort was dichotomized by the median value of CD45 infiltration in the lungs. Four pretreatment radiomics features (3 CT features and 1 MRI feature) together with pre-treatment neutrophil-to-lymphocyte (NLR) ratio and pre-treatment granulocyte-macrophage colony-stimulating factor (GM-CSF) level correlated with dichotomized CD45 infiltration. Predictive models were created by combining radiomics with NLR and GM-CSF. Receiver operating characteristic (ROC) analyses of two-fold internal cross-validation indicated that the predictive model incorporating MR radiomics had an average area under the curve (AUC) of 0.834, while the model incorporating CT radiomics had an AUC of 0.787. Conclusions: Model building using quantitative imaging data, blood counts, and blood cytokines resulted in lung inflammation prediction models justifying the study hypothesis. The models yielded very-good-to-excellent AUCs of more than 0.78 on internal cross-validation analyses.
CD24 Is a Potential Immunotherapeutic Target for Mantle Cell Lymphoma
Authors: Freile Jimena Álvarez , Ustyanovska Avtenyuk Natasha , Corrales Macarena González , Lourens Harm Jan , Huls Gerwin , van Meerten Tom , Cendrowicz Ewa , Bremer Edwin
Published: May 2022

CD24 and its ligand Siglec-10 were described as an innate immune checkpoint in carcinoma. Here, we investigated this axis in B-cell lymphoma by assessing CD24 expression and evaluating pro-phagocytic effects of CD24 antibody treatment in comparison to hallmark immune checkpoint CD47. In mantle cell lymphoma (MCL) and follicular lymphoma patients, high mRNA expression of CD24 correlated with poor overall survival, whereas CD47 expression did not. Conversely, CD24 expression did not correlate with survival in diffuse large B-cell lymphoma (DLBCL), whereas CD47 did. CD24 was also highly expressed on MCL cell lines, where treatment with CD24 antibody clones SN3 or ML5 potently induced phagocytosis, with SN3 yielding >90% removal of MCL cells and triggering phagocytosis of primary patient-derived MCL cells by autologous macrophages. Treatment with CD24 mAb was superior to CD47 mAb in MCL and was comparable in magnitude to the effect observed in carcinoma lines. Reversely, CD24 mAb treatment was less effective than CD47 mAb treatment in DLBCL. Finally, phagocytic activity of clone SN3 appeared at least partly independent of antibody-dependent cellular phagocytosis (ADCP), suggesting CD24/Siglec-10 checkpoint activity, whereas clone ML5 solely induced ADCP. In conclusion, CD24 is an immunotherapeutic target of potential clinical relevance for MCL, but not DLBCL.
TRP Family Genes Are Differently Expressed and Correlated with Immune Response in Glioma
Authors: Fang Chaoyou , Xu Houshi , Liu Yibo , Huang Chenkai , Wang Xiaoyu , Zhang Zeyu , Xu Yuanzhi , Yuan Ling , Zhang Anke , Shao Anwen , Lou Meiqing
Published: May 2022

(1) Background: glioma is the most prevalent primary tumor of the human central nervous system and accompanies extremely poor prognosis in patients. The transient receptor potential (TRP) channels family consists of six different families, which are closely associated with cancer cell proliferation, differentiation, migration, and invasion. TRP family genes play an essential role in the development of tumors. Nevertheless, the function of these genes in gliomas is not fully understood. (2) Methods: we analyze the gene expression data of 28 TRP family genes in glioma patients through bioinformatic analysis. (3) Results: the study showed the aberrations of TRP family genes were correlated to prognosis in glioma. Then, we set enrichment analysis and selected 10 hub genes that may play an important role in glioma. Meanwhile, the expression of 10 hub genes was further established according to different grades, survival time, IDH mutation status, and 1p/19q codeletion status. We found that TRPC1, TRPC3, TRPC4, TRPC5, TRPC6, MCOLN1, MCOLN2, and MCOLN3 were significantly correlated to the prognosis in glioma patients. Furthermore, we illustrated that the expression of hub genes was associated with immune activation and immunoregulators (immunoinhibitors, immunostimulators, and MHC molecules) in glioma. (4) Conclusions: we proved that TRP family genes are promising immunotherapeutic targets and potential clinical biomarkers in patients with glioma.
Synaptophysin, CD117, and GATA3 as a Diagnostic Immunohistochemical Panel for Small Cell Neuroendocrine Carcinoma of the Urinary Tract
Authors: Kim Gi Hwan , Cho Yong Mee , Kim So-Woon , Park Ja-Min , Yoon Sun Young , Jeong Gowun , Shin Dong-Myung , Ju Hyein , Jeong Se Un
Published: May 2022

Although SCNEC is based on its characteristic histology, immunohistochemistry (IHC) is commonly employed to confirm neuroendocrine differentiation (NED). The challenge here is that SCNEC may yield negative results for traditional neuroendocrine markers. To establish an IHC panel for NED, 17 neuronal, basal, and luminal markers were examined on a tissue microarray construct generated from 47 cases of 34 patients with SCNEC as a discovery cohort. A decision tree algorithm was employed to analyze the extent and intensity of immunoreactivity and to develop a diagnostic model. An external cohort of eight cases and transmission electron microscopy (TEM) were used to validate the model. Among the 17 markers, the decision tree diagnostic model selected 3 markers to classify NED with 98.4% accuracy in classification. The extent of synaptophysin (>5%) was selected as the initial parameter, the extent of CD117 (>20%) as the second, and then the intensity of GATA3 (≤1.5, negative or weak immunoreactivity) as the third for NED. The importance of each variable was 0.758, 0.213, and 0.029, respectively. The model was validated by the TEM and using the external cohort. The decision tree model using synaptophysin, CD117, and GATA3 may help confirm NED of traditional marker-negative SCNEC.
Platelets Increase the Expression of PD-L1 in Ovarian Cancer
Authors: Cho Min Soon , Lee Hani , Gonzalez-Delgado Ricardo , Li Dan , Sasano Tomoyuki , Carlos-Alcalde Wendolyn , Ma Qing , Liu Jinsong , Sood Anil K. , Afshar-Kharghan Vahid
Published: May 2022

The interactions between platelets and cancer cells activate platelets and enhance tumor growth. Platelets increase proliferation and epithelial–mesenchymal transition in cancer cells, inhibit anoikis, enhance the extravasation of cancer cells, and protect circulating tumor cells against natural killer cells. Here, we have identified another mechanism by which platelets dampen the immune attack on cancer cells. We found that platelets can blunt the antitumor immune response by increasing the expression of inhibitory immune checkpoint (PD-L1) on ovarian cancer cells in vitro and in vivo. Platelets increased PD-L1 in cancer cells via contact-dependent (through NF-κB signaling) and contact-independent (through TFGβR1/Smad signaling) pathways. Inhibition of NF-κB or TGFβR1 signaling in ovarian cancer cells abrogated platelet-induced PD-L1 expression. Reducing platelet counts or inhibiting platelet functions reduced the expression of PD-L1 in ovarian cancer. On the other hand, an increase in platelet counts increased the expression of PD-L1 in tumor-bearing mice.
Radioactive Iodine Treatment for Thyroid Cancer Patients Increases the Risk of Long-Term Gastrointestinal Disorders: A Nationwide Population-Based Cohort Analysis
Authors: Lee Yueh , Chung Chi-Hsiang , Lin Li-Fan , Chiu Chuang-Hsin , Chen Yi-Feng , Chang Chao-Feng , Cheng Cheng-Yi , Chien Wu-Chien
Published: May 2022

(1) Background: The study aimed to investigate the association between radioactive iodine (RAI) treatment and long-term gastrointestinal disorders including ulcers, atrophic gastritis, and secondary malignant neoplasm of the stomach in patients with thyroid cancer. (2) Methods: The data of the study were extracted from the National Health Insurance Database (NHIRD) of Taiwan between 2000 to 2015. Patients of ages older than 20 with thyroid cancer after thyroidectomy were included and divided into groups with RAI (study cohort) and without RAI (comparison cohort). Multivariate Cox proportional hazards regression analysis and the Kaplan–Meier method were used for statistical analysis. (3) Results: A total of 7250 (with RAI: 5800, without RAI: 1450) patients were included. The Kaplan-Meier analysis revealed a significantly higher cumulative risk for overall gastrointestinal disorders in the group with RAI (log-rank p = 0.034). The risk for gastrointestinal disorders was higher when receiving a cumulative RAI dose higher than 1.11 GBq in the Cox regression analysis. In the subgroup analysis, the risks of gastric and duodenal ulcers are significantly higher in the group with RAI treatment. (4) Conclusions: This study revealed that RAI was associated with an increased risk for long-term gastrointestinal disorders, specifically gastric and duodenal ulcers, in thyroid cancer, especially when the cumulative dose exceeds 1.11 GBq.
Gliomas Infiltrating the Corpus Callosum: A Systematic Review of the Literature
Authors: Palmisciano Paolo , Ferini Gianluca , Watanabe Gina , Ogasawara Christian , Lesha Emal , Bin-Alamer Othman , Umana Giuseppe E. , Yu Kenny , Cohen-Gadol Aaron A. , El Ahmadieh Tarek Y. , Haider Ali S.
Published: May 2022

Background: Gliomas infiltrating the corpus callosum (G-I-CC) majorly impact patient quality-of-life, but maximally safe tumor resection is challenging. We systematically reviewed the literature on G-I-CC. Methods: PubMed, EMBASE, Scopus, Web of Science, and Cochrane were searched following the PRISMA guidelines to include studies of patients with G-I-CC. Clinicopathological features, treatments, and outcomes were analyzed. Results: We included 52 studies comprising 683 patients. Most patients experienced headache (33%), cognitive decline (18.7%), and seizures (17.7%). Tumors mostly infiltrated the corpus callosum genu (44.2%) with bilateral extension (85.4%) into frontal (68.3%) or parietal (8.9%) lobes. Most G-I-CC were glioblastomas (84.5%) with IDH-wildtype (84.9%) and unmethylated MGMT promoter (53.5%). Resection (76.7%) was preferred over biopsy (23.3%), mostly gross-total (33.8%) and subtotal (32.5%). The tumor-infiltrated corpus callosum was resected in 57.8% of cases. Radiation was delivered in 65.8% of patients and temozolomide in 68.3%. Median follow-up was 12 months (range, 0.1–116). In total, 142 patients (31.8%) experienced post-surgical complications, including transient supplementary motor area syndrome (5.1%) and persistent motor deficits (4.3%) or abulia (2.5%). Post-treatment symptom improvement was reported in 42.9% of patients. No differences in rates of complications (p = 0.231) and symptom improvement (p = 0.375) were found in cases with resected versus preserved corpus callosum. Recurrences occurred in 40.9% of cases, with median progression-free survival of 9 months (0.1–72). Median overall survival was 10.7 months (range, 0.1–116), significantly longer in low-grade tumors (p = 0.013) and after resection (p < 0.001), especially gross-total (p = 0.041) in patients with high-grade tumors. Conclusions: G-I-CC show clinicopathological patterns comparable to other more frequent gliomas. Maximally safe resection significantly improves survival with low rates of persistent complications.
Fagonia cretica-Mediated Synthesis of Manganese Oxide (MnO2) Nanomaterials Their Characterization and Evaluation of Their Bio-Catalytic and Enzyme Inhibition Potential for Maintaining Flavor and Texture in Apples
Authors: Faisal Shah , Khan Shahzar , Abdullah  , Zafar Sania , Rizwan Muhammad , Ali Muhammad , Ullah Riaz , Albadrani Ghadeer M. , Mohamed Hanan R. H. , Akbar Fazal
Published: May 2022

The apple is the most widely used fruit globally. Apples are more prone to fungal spoilage, which leads to browning and subsequent changes in their flavor and texture. Browning is also caused by the tyrosinase enzyme. By inhibiting tyrosinase initiation and fungal spoilage in fruits, the natural flavor and texture of fruits can be maintained. Biogenic NPs can act as antioxidants to inhibit tyrosinase and due to oxidative stress, it also catalyzes the deformation of fungal hyphae and spores. Nanotechnology is a research hotspot that has gained considerable interest due to its potential inferences in biosciences and food preservation technology. The present study aims to use biomass from the Fagonia cretica to create bio-inspired manganese oxide MnO2 NPs and to evaluate its bio-catalytic potential for antifungal anti-browning through the inhibition of tyrosinase and its antioxidant potential for preserving apple flavor and texture. The green synthesized nanoparticles were extensively analyzed using UV spectroscopy, XRD, SEM, EDX, and FTIR techniques. Moreover, the synthesized manganese oxide nanoparticles (MnO2 NPs) were evaluated for their bio-catalytic potential as anti-fungal and anti-spoiling agents. The values of antifungal activity among all the samples were 14.2 ± 86 mm, 8.9 ± 6.0 mm, 17.7 ± 1.26, and 20.7 ± 4.38 mm for Penicillium expansum, Monilinia fructigena, Penicillium chrysogenum, and Aspergillus oryzae at 200 µg/well, respectively. Moreover, the biogenic NPs were evaluated for their anti-browning potential through the inhibition of tyrosinase. MnO2 NPs have been shown to have considerable inhibitory effects on tyrosinase up to 64.8 ± 0.16 at 200 µg/mL and (27.2 ± 0.58) at 25 µg/mL. Biogenic MnO2 NPs can also act as antioxidants to inhibit tyrosinase and fungal growth by the formation of free radicals that damage the fungal hyphae and, as a result, slow down browning. The maximum DPPH free radical scavenging activity was 74.5 ± 0.39% at 200 µg/mL, and the minimum was 12.4 ± 0.27 at 25 µg/mL. The biogenic MnO2 NPs are biocompatible and play a potent role in maintaining the flavor and texture of apples.
Detecting DNA: An Overview of DNA Recognition by Inflammasomes and Protection against Bacterial Respiratory Infections
Authors: Tupik Juselyn D. , Markov Madanick Justin W. , Ivester Hannah M. , Allen Irving C.
Published: May 2022

The innate immune system plays a key role in modulating host immune defense during bacterial disease. Upon sensing pathogen-associated molecular patterns (PAMPs), the multi-protein complex known as the inflammasome serves a protective role against bacteria burden through facilitating pathogen clearance and bacteria lysis. This can occur through two mechanisms: (1) the cleavage of pro-inflammatory cytokines IL-1β/IL-18 and (2) the initiation of inflammatory cell death termed pyroptosis. In recent literature, AIM2-like Receptor (ALR) and Nod-like Receptor (NLR) inflammasome activation has been implicated in host protection following recognition of bacterial DNA. Here, we review current literature synthesizing mechanisms of DNA recognition by inflammasomes during bacterial respiratory disease. This process can occur through direct sensing of DNA or indirectly by sensing pathogen-associated intracellular changes. Additionally, DNA recognition may be assisted through inflammasome–inflammasome interactions, specifically non-canonical inflammasome activation of NLRP3, and crosstalk with the interferon-inducible DNA sensors Stimulator of Interferon Genes (STING) and Z-DNA Binding Protein-1 (ZBP1). Ultimately, bacterial DNA sensing by inflammasomes is highly protective during respiratory disease, emphasizing the importance of inflammasome involvement in the respiratory tract.
Alterations of Mitochondrial Network by Cigarette Smoking and E-Cigarette Vaping
Authors: Kanithi Manasa , Junapudi Sunil , Shah Syed Islamuddin , Matta Reddy Alavala , Ullah Ghanim , Chidipi Bojjibabu
Published: May 2022

Toxins present in cigarette and e-cigarette smoke constitute a significant cause of illnesses and are known to have fatal health impacts. Specific mechanisms by which toxins present in smoke impair cell repair are still being researched and are of prime interest for developing more effective treatments. Current literature suggests toxins present in cigarette smoke and aerosolized e-vapor trigger abnormal intercellular responses, damage mitochondrial function, and consequently disrupt the homeostasis of the organelle’s biochemical processes by increasing reactive oxidative species. Increased oxidative stress sets off a cascade of molecular events, disrupting optimal mitochondrial morphology and homeostasis. Furthermore, smoking-induced oxidative stress may also amalgamate with other health factors to contribute to various pathophysiological processes. An increasing number of studies show that toxins may affect mitochondria even through exposure to secondhand or thirdhand smoke. This review assesses the impact of toxins present in tobacco smoke and e-vapor on mitochondrial health, networking, and critical structural processes, including mitochondria fission, fusion, hyper-fusion, fragmentation, and mitophagy. The efforts are focused on discussing current evidence linking toxins present in first, second, and thirdhand smoke to mitochondrial dysfunction.
Slack Potassium Channels Modulate TRPA1-Mediated Nociception in Sensory Neurons
Authors: Zhou Fangyuan , Metzner Katharina , Engel Patrick , Balzulat Annika , Sisignano Marco , Ruth Peter , Lukowski Robert , Schmidtko Achim , Lu Ruirui
Published: May 2022

The transient receptor potential (TRP) ankyrin type 1 (TRPA1) channel is highly expressed in a subset of sensory neurons where it acts as an essential detector of painful stimuli. However, the mechanisms that control the activity of sensory neurons upon TRPA1 activation remain poorly understood. Here, using in situ hybridization and immunostaining, we found TRPA1 to be extensively co-localized with the potassium channel Slack (KNa1.1, Slo2.2, or Kcnt1) in sensory neurons. Mice lacking Slack globally (Slack−/−) or conditionally in sensory neurons (SNS-Slack−/−) demonstrated increased pain behavior after intraplantar injection of the TRPA1 activator allyl isothiocyanate. By contrast, pain behavior induced by the TRP vanilloid 1 (TRPV1) activator capsaicin was normal in Slack-deficient mice. Patch-clamp recordings in sensory neurons and in a HEK cell line transfected with TRPA1 and Slack revealed that Slack-dependent potassium currents (IKS) are modulated in a TRPA1-dependent manner. Taken together, our findings highlight Slack as a modulator of TRPA1-mediated, but not TRPV1-mediated, activation of sensory neurons.
The Atomic Layer Etching Technique with Surface Treatment Function for InAlN/GaN Heterostructure
Authors: Du Fangzhou , Jiang Yang , Wu Zhanxia , Lu Honghao , He Jiaqi , Tang Chuying , Hu Qiaoyu , Wen Kangyao , Tang Xinyi , Hong Haimin , Yu Hongyu , Wang Qing
Published: May 2022

This paper studied an atomic layer etching (ALE) technique with a surface treatment function for InAlN/GaN heterostructures with AlN spacer layers. Various parameters were attempted, and 30 s O2 + 15 W BCl3 was chosen as the optimal recipe. The optimal ALE approach exhibited satisfactory etching results, with regard to the etch-stop effect, compared with other techniques. The atomic force microscopy (AFM) results showed an etching per cycle (EPC) value of 0.15 nm/cycle, with a 0.996 fit coefficient and root mean square (RMS) surface roughness of around 0.61 nm (0.71 nm for as-grown sample), which was the lowest in comparison with digital etching (0.69 nm), Cl2/BCl3 continuous etching (0.91 nm) and BCl3 continuous etching (0.89 nm). X-ray photoelectron spectroscopy (XPS) and scanning transmission electron microscopy with energy dispersive X-ray spectroscopy measurements (STEM/EDS) verified the indium clustered phenomena at the bottom apex of V-pit defects in the epi structure of InAlN/GaN high electron mobility transistors (HEMTs) for the first time, in addition to the surface morphology optimization for the ALE under-etching technique used in this work. The resistor hall effect (Hall) and AFM measurements demonstrated that after 4 or 5 ALE cycles, the two-dimensional electron gas (2-DEG) density and RMS roughness were improved by 15% and 11.4%, respectively, while the sheet resistance (Rsh) was reduced by 6.7%, suggesting a good surface treatment function. These findings were important for realizing high-performance InAlN/GaN HEMTs.
In Situ Measurement Method Based on Edge Detection and Superpixel for Crystallization Imaging at High-Solid Concentrations
Authors: Huo Yan , Guan Diyuan , Li Xin
Published: May 2022

To facilitate measuring crystal sizes during batch crystallization at high-solid concentrations by using an invasive imaging system, an in situ imaging measurement strategy based on edge detection and superpixel is proposed for the ambiguous boundary problem of large amounts of crystals. Firstly, an image filtering is employed to cope with image degradation caused by noise disturbance and suspension turbulence in the crystallizer. Subsequently, an image segmentation method is developed by utilizing improved edge detection and superpixel, which can be easily performed for crystal extraction. Accordingly, crystal size measurement can be developed for evaluation of the crystal size distribution. The experiment results on α-form L-glutamic acid present the effectiveness of the proposed method.
Extracting Quantitative Information from Images Taken in the Wild: A Case Study of Two Vicariants of the Ophrys aveyronensis Species Complex
Authors: Gibert Anais , Louty Florian , Buscail Roselyne , Baguette Michel , Schatz Bertrand , Bertrand Joris A. M.
Published: May 2022

Characterising phenotypic differentiation is crucial to understand which traits are involved in population divergence and establish the evolutionary scenario underlying the speciation process. Species harbouring a disjunct spatial distribution or cryptic taxa suggest that scientists often fail to detect subtle phenotypic differentiation at first sight. We used image-based analyses coupled with a simple machine learning algorithm to test whether we could distinguish two vicariant population groups of an orchid species complex known to be difficult to tease apart based on morphological criteria. To assess whether these groups can be distinguished on the basis of their phenotypes, and to highlight the traits likely to be the most informative in supporting a putative differentiation, we (i) photographed and measured a set of 109 individuals in the field, (ii) extracted morphometric, colour, and colour pattern information from pictures, and (iii) used random forest algorithms for classification. When combined, field- and image-based information provided identification accuracy of 95%. Interestingly, the variables used by random forests to discriminate the groups were different from those suggested in the literature. Our results demonstrate the interest of field-captured pictures coupled with machine learning classification approaches to improve taxon identification and highlight candidate traits for further eco-evolutionary studies.
The Use of the BIM Approach from the Conceptual Planning to the Construction Phase: The Case Study of the SHiP Experiment
Authors: Salzano Antonio , Miano Andrea , Prota Andrea , Jacobsson Richard
Published: May 2022

The Search for Hidden Particles (SHiP) experiment is a new purpose fixed target facility proposed for the CERN Super Proton Synchrotron accelerator to search for long-lived exotic particles associated with Hidden Sectors and Dark Matter. This paper reports on the development of BIM integrated design for the SHiP experiment, applied initially to the Decay Volume, a >2000 m3 conical steel vessel under a vacuum hosting several large particle physics detector systems. A BIM methodology is used to address all the design phases of the Decay Volume of the SHiP experiment from the conceptual planning to the constructive drawings production. This proposed workflow is a basic plan to be repeated for each sub-component of the SHiP experiment in order to have a full and overall integration of the experiment. In particular, the Decay Volume’s geometrical and structural design and the simulation of its assembly process, both in factory and on site, are proposed. Moreover, the use of collaborative platforms to speed up the ideas exchange, as the basis of a highly multidisciplinary and complex project, is discussed. The complexity, multidisciplinary nature, and size of the SHiP project severely challenge design information management. The final plan to solve this issue is to have a BIM integrated design of each experiment sub-component, such as that demonstrated in this work for the Decay Volume, in order to have a full and multidisciplinary integration of the overall project.
E-Learning Performance Prediction: Mining the Feature Space of Effective Learning Behavior
Authors: Qiu Feiyue , Zhu Lijia , Zhang Guodao , Sheng Xin , Ye Mingtao , Xiang Qifeng , Chen Ping-Kuo
Published: May 2022

Learning analysis provides a new opportunity for the development of online education, and has received extensive attention from scholars at home and abroad. How to use data and models to predict learners’ academic success or failure and give teaching feedback in a timely manner is a core problem in the field of learning analytics. At present, many scholars use key learning behaviors to improve the prediction effect by exploring the implicit relationship between learning behavior data and grades. At the same time, it is very important to explore the association between categories and prediction effects in learning behavior classification. This paper proposes a self-adaptive feature fusion strategy based on learning behavior classification, aiming to mine the effective E-learning behavior feature space and further improve the performance of the learning performance prediction model. First, a behavior classification model (E-learning Behavior Classification Model, EBC Model) based on interaction objects and learning process is constructed; second, the feature space is preliminarily reduced by entropy weight method and variance filtering method; finally, combined with EBC Model and a self-adaptive feature fusion strategy to build a learning performance predictor. The experiment uses the British Open University Learning Analysis Dataset (OULAD). Through the experimental analysis, an effective feature space is obtained, that is, the basic interactive behavior (BI) and knowledge interaction behavior (KI) of learning behavior category has the strongest correlation with learning performance.And it is proved that the self-adaptive feature fusion strategy proposed in this paper can effectively improve the performance of the learning performance predictor, and the performance index of accuracy(ACC), F1-score(F1) and kappa(K) reach 98.44%, 0.9893, 0.9600. This study constructs E-learning performance predictors and mines the effective feature space from a new perspective, and provides some auxiliary references for online learners and managers.
Joint Optimization of Control Strategy and Energy Consumption for Energy Harvesting WSAN
Authors: Wang Zhuwei , Liu Zhicheng , Liu Lihan , Fang Chao , Li Meng , Zhao Jingcheng
Published: May 2022

With the rapid development of wireless sensor technology, recent progress in wireless sensor and actuator networks (WSANs) with energy harvesting provide the possibility for various real-time applications. Meanwhile, extensive research activities are carried out in the fields of efficient energy allocation and control strategy design. However, the joint design considering physical plant control, energy harvesting, and consumption is rarely concerned in existing works. In this paper, in order to enhance system control stability and promote quality of service for the WSAN energy efficiency, a novel three-step joint optimization algorithm is proposed through control strategy and energy management analysis. First, the optimal sampling interval can be obtained based on energy harvesting, consumption, and remaining conditions. Then, the control gain for each sampling interval is derived by using a backward iteration. Finally, the optimal control strategy is determined as a linear function of the current plant states and previous control strategies. The application of UAV formation flight system demonstrates that better system performance and control stability can be achieved by the proposed joint optimization design for all poor, sufficient, and general energy harvesting scenarios.
A Path Planning Strategy of Wearable Manipulators with Target Pointing End Effectors
Authors: Zou Kaifan , Guan Xiaorong , Li Zhong , Li Huibin , Gao Xin’an , Zhu Meng , Tong Wei , Wang Xinrui
Published: May 2022

End effectors like firearms, cameras and fire water guns can be classified as pointing end effectors. When installed on wearable manipulators, a new function can be given to the wearer. Different from gripper end effectors (GEEs), target pointing end effectors (TPEEs) have different working tasks, and the requirements for path planning are also different. There is very limited research on wearable manipulators with TPEEs. Meanwhile, manipulator with GEE path planning tends to be mature, but with a relatively low efficiency concerning its algorithm in solving high-dimensional problems. In this paper, a degree of freedom (DOF) allocation scheme and a path planning strategy (unlike manipulator with gripper end effector) were proposed for manipulators with a target pointing end effector in order to reduce the difficulty of path planning. Besides, this paper describes a new algorithm-dimension rapid-exploration random tree (dimension-RRT) to divide the manipulator DOFs into groups and unify DOFs groups by adding a fake time. The dimension-RRT was compared with the rapid-exploration random tree star algorithm (RRT*) in the same simulation environment; when there are 500 random points, the dimension-RRT time consumption is 0.556 of RRT* and the path length is 0.5 of RRT *. To quickly obtain a path that can avoid the human body, dynamic movement primitives (DMPs) were used to simulate typical spatial motion path and obstacle avoidance path efficiently.
Game-Theoretic Power and Rate Control in IEEE 802.11p Wireless Networks
Authors: Spyrou Evangelos D. , Vlachos Evangelos , Stylios Chrysostomos
Published: May 2022

Optimization of the transmission power and rate allocation is a significant problem in wireless networks with mobile nodes. Due to mobility, the vehicles establishing wireless networks may exhibit severe fluctuations of their link quality, affecting their connection reliability and throughput. In Vehicular Ad-hoc Networks (VANETS), the IEEE 802.11p standard provides a practical metric for the Packet Reception Ratio (PRR), which is related with the transmission power and rate. Finding a global strategy for optimizing PRR for all mobile nodes can be treated as a potential game where each vehicle is considered as a selfish player, aiming to maximise its transmission reliability while rate constraints are satisfied. To this end, we propose a game-theoretic approach that converges to a Nash equilibrium. The main contributions of this work include: (i) identification of the best case equilibrium, for two cases of interference: diminished or kept stable, and (ii) verification of the equilibrium optimality, by showing that the value of stability is 1. Moreover, numerical results exhibiting the ease of the utility function calculation are provided, especially after an SINR level, whereby the utility function is concave and can be solved efficiently in polynomial time.
Research on High-Resolution Face Image Inpainting Method Based on StyleGAN
Authors: He Libo , Qiang Zhenping , Shao Xiaofeng , Lin Hong , Wang Meijiao , Dai Fei
Published: May 2022

In face image recognition and other related applications, incomplete facial imagery due to obscuring factors during acquisition represents an issue that requires solving. Aimed at tackling this issue, the research surrounding face image completion has become an important topic in the field of image processing. Face image completion methods require the capability of capturing the semantics of facial expression. A deep learning network has been widely shown to bear this ability. However, for high-resolution face image completion, the network training of high-resolution image inpainting is difficult to converge, thus rendering high-resolution face image completion a difficult problem. Based on the study of the deep learning model of high-resolution face image generation, this paper proposes a high-resolution face inpainting method. First, our method extracts the latent vector of the face image to be repaired through ResNet, then inputs the latent vector to the pre-trained StyleGAN model to generate the face image. Next, it calculates the loss between the known part of the face image to be repaired and the corresponding part of the generated face imagery. Afterward, the latent vector is cut to generate a new face image iteratively until the number of iterations is reached. Finally, the Poisson fusion method is employed to process the last generated face image and the face image to be repaired in order to eliminate the difference in boundary color information of the repaired image. Through the comparison and analysis between two classical face completion methods in recent years on the CelebA-HQ data set, we discovered our method can achieve better completion results of 256*256 resolution face image completion. For 1024*1024 resolution face image restoration, we have also conducted a large number of experiments, which prove the effectiveness of our method. Our method can obtain a variety of repair results by editing the latent vector. In addition, our method can be successfully applied to face image editing, face image watermark clearing and other applications without the network training process of different masks in these applications.
IoDM: A Study on a IoT-Based Organizational Deception Modeling with Adaptive General-Sum Game Competition
Authors: Seo Sang , Kim Dohoon
Published: May 2022

Moving target defense (MTD) and decoy strategies, measures of active defense, were introduced to secure both the proactive security and reactive adaptability of internet-of-things (IoT) networks that have been explosively applied to various industries without any strong security measures and to mitigate the side effects of threats. However, the existing MTD and decoy strategies are limited to avoiding the attacker’s reconnaissance and initial intrusion attempts through simple structural mutations or inducing the attackers to a static trap based on the deceptive path and lack approaches to adaptively optimize IoT in consideration of the unique characteristic information by the domain of IoT. Game theory-based and decoy strategies are other options; however, they do not consider the dynamicity and uncertainty of the decision-making stages by the organizational agent related to the IoT domains. Therefore, in this paper, we present a type of organizational deception modeling, namely IoT-based organizational deception modeling (IoDM), which considers both the dynamic topologies and organizational business fingerprints customized in the IoT domain and operational purpose. For this model, we considered the practical scalability of the existing IoT-enabled MTD and decoy concepts and formulated the partially incomplete deceptive decision-making modeling for the cyber-attack and defense competition for IoT in real-time based on the general-sum game. According to our experimental results, the efficiency of the deceptive defense of the IoT defender could be improved by 70% on average while deriving the optimal defense cost compared to the increased defense performance. The findings of this study will improve the deception performances of MTD and decoy strategies by IoT scenarios related to various operational domains such as smart home networks, industrial networks, and medical networks. To the best of our knowledge, this study has employed social-engineering IoT knowledge and general-sum game theory for the first time.
A Comprehensive Cost Analysis of Intra-Domain Handoff with Authentication Cost in PMIPv6 for Vehicular Ad Hoc Networks (VANETs)
Authors: Goyal Amit Kumar , Agarwal Gaurav , Tripathi Arun Kumar , Goel Vikas , Sharma Girish , Hui Kueh Lee , Sain Mangal
Published: May 2022

In metro cities, the effective and efficient management of traffic is one of the most demanding and time taking tasks. Vehicular ad hoc networks (VANET) provide unfailing, low-cost solutions for transportation systems with intelligence. VANET, a subclass of mobile ad hoc networks (MANET), allows exchange of information among vehicles and/or roadside devices. VANET can be implemented in numerous application areas such as effective traffic management, safety, and user comfort for drivers as well as passengers. It provides phenomenal growth to both in industries and research communities. Secure mobility and handoff management are the most promising and challenging research issues in VANET. In this paper, we have introduced the security in intra domain mobility handoff in PMIPv6 for VANET. Existing intra handover schemes does not include the authentication cost while evaluating the total packet delivery cost for intra domain handoff. Our proposed scheme includes the authentication cost of an intra-domain handover for evaluating the total packet delivery cost of handover for next-generation mobility management protocols, which is PMIPv6 for the vehicular network. We have considered the vital parameters such as the number of MAGs, setup cost, binding update cost, unit transmission cost for analyzing the total packet delivery cost. Furthermore, a comparative study with authentication and without authentication cost for the considered parameters shows that our proposed scheme secures the handover process with slight variation in cost.
A Novel Phase Difference Measurement Method for Coriolis Mass Flowmeter Based on Correlation Theory
Authors: Shen Ting’ao , Huang Siyu , Chen Peng , Chen Liwei , Zhou Yi
Published: May 2022

Aiming at the poor precision problem in phase difference measurements with unknown frequencies in engineering practice, a new phase difference measurement method is proposed for Coriolis mass flowmeter based on correlation theories. Firstly, the signal frequency was estimated by using an adaptive notch filter, which was applied to filter the waves and determined the integer period of the sampling signals, and the non-integer period sampling signals needed to be extended. Then, the Hilbert transformation was conducted relative to the extended signals, and the correlation functions of these extended signals with the transformed signals can be computed. Finally, the formula of phase difference can be obtained by utilizing the sinusoidal function. Compared to traditional methods, such as the correlation method, the Hilbert transformation method, and sliding Goertzel algorithm, the proposed method is suitable for both integer period and non-integer period sampling signals, and its accuracy, real-time, and dynamic performance is superior. Simulation and experiment results validate the superiority and effectiveness of the proposed method.
Nitrogen Atom-Doped Layered Graphene for High-Performance CO2/N2 Adsorption and Separation
Authors: Lyu Weifeng , Sun Linghui , Wang Lu , Ji Zemin , Zhou Sainan , Chen Yong , Lu Xiaoqing
Published: May 2022

The development of high-performance CO2 capture and separation adsorbents is critical to alleviate the deteriorating environmental issues. Herein, N atom-doped layered graphene (N-MGN) was introduced to form triazine and pyridine as potential CO2 capture and separation adsorbents via regulation of interlayer spacings. Structural analyses showed that accessible surface area of the N-MGN is 2521.72 m2 g−1, the porosity increased from 9.43% to 84.86%. At ultra-low pressure, N-MGN_6.8 have exhibited a high CO2 adsorption capacity of 10.59 mmol/g at 298 K and 0.4 bar. At high pressure, the absolute adsorption capacities of CO2 in N-MGN_17.0 (40.16 mmol g−1) at 7.0 MPa and 298 K are much larger than that of N-doping slit pore. At 298 K and 1.0 bar, the highest selectivity of CO2 over N2 reached up to ~133 in N-MGN_6.8. The research shows that N doping can effectively improve the adsorption and separation capacity of CO2 and N2 in layered graphene, and the interlayer spacing has an important influence on the adsorption capacity of CO2/N2. The adsorption heat and relative concentration curves further confirmed that the layered graphene with an interlayer spacing of 6.8 Å has the best adsorption and separation ability of CO2 and N2 under low pressure. Under high pressure, the layered graphene with the interlayer spacing of 17.0 Å has the best adsorption and separation ability of CO2 and N2.
Evolution of Biomarker Maturity Parameters and Feedback to the Pyrolysis Process for In Situ Conversion of Nongan Oil Shale in Songliao Basin
Authors: Zeng Hao , He Wentong , Yang Lihong , Su Jianzheng , Meng Xianglong , Cen Xueqi , Guo Wei
Published: May 2022

In the oil shale in situ conversion project, it is urgent to solve the problem that the reaction degree of organic matter cannot be determined. The yield and composition of organic products in each stage of the oil shale pyrolysis reaction change regularly, so it is very important to master the process of the pyrolysis reaction and reservoir change for oil shale in situ conversion project. In the in situ conversion project, it is difficult to directly obtain cores through drilling for kerogen maturity testing, and the research on judging the reaction process of subsurface pyrolysis based on the maturity of oil products has not been carried out in-depth. The simulation experiments and geochemical analysis carried out in this study are based on the oil shale of the Nenjiang Formation in the Songliao Basin and the pyrolysis oil samples produced by the in situ conversion project. Additionally, this study aims to clarify the evolution characteristics of maturity parameters such as effective biomarker compounds during the evolution of oil shale pyrolysis hydrocarbon products and fit it with the kerogen maturity in the Nenjiang formation. The response relationship with the pyrolysis process of oil shale is established, and it lays a theoretical foundation for the efficient, economical and stable operation of oil shale in situ conversion projects.
Industrial End-Users’ Preferred Characteristics for Wood Biomass Feedstocks
Authors: Kons Kalvis , Blagojević Boško , Mola-Yudego Blas , Prinz Robert , Routa Johanna , Kulisic Biljana , Gagnon Bruno , Bergström Dan
Published: May 2022

The use of sustainably sourced biomass is an important tool for mitigating the effects of climate change; but biomass is far from being a homogeneous resource. The aim of this study was to examine the decision-making process of industrial end-users considering biomass procurement. An online, two-part survey generated responses from 27 experienced professionals, representing a portfolio of facilities varying in size, technology, and biomass types, across Australia, Canada, Finland, and Sweden. A PAPRIKA conjoint analysis approach was used to analyze the data so that the attributes that influenced procurement decisions could be weighted and ranked. The results provided an insight into end-users’ views on factors including facility location, size, and biomass storage, handling, and procurement for different wood-based industrial services. The most important decision-making attribute appeared to be the type of biomass assortment, at individual, national, and aggregated levels. Of seven sub-categories of biomass assortments, sawdust (35%) was the most preferred type followed by stem wood chips (20%) and energy wood (15%). We concluded that, from the end-user’s perspective, a pre-defined biomass assortment is the most important factor when deciding on feedstock procurement at a bioenergy facility. These results help us better understand end-users’ perceptions of biomass properties in relation to their conversion processes and supply preferences and can inform product development and the securement of new niches in alternative business environments by existing and future biohubs.
Microgrid Assisted Design for Remote Areas
Authors: Liu Guodong , Li Zhi , Xue Yaosuo , Tomsovic Kevin
Published: May 2022

In this work, we present a three-stage multiobjective mixed-integer linear programming (MILP) for the optimal expansion planning and operation of isolated multienergy microgrids in remote areas. By selecting the optimal distributed generators (DGs) and energy storage systems (ESSs) mix selection, siting, sizing, and scheduling in the remote microgrid, the proposed model is targeted to minimize the annualized total cost of microgrids while enhancing the performance of the system, i.e., minimizing the voltage deviations and line power loss. To represent the electricity and heat flow between generation resources and various electrical, heating, and cooling loads in the isolated microgrid, linearized power flow, and heat flow constraints are employed in the proposed optimization model. The available capacity of DGs and ESSs are modeled as discrete constants instead of continuous variables for practical purpose. Numerical simulation results on a remote microgrid consisting of DGs, ESSs, and various loads validate the proposed method.