bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Novel Therapeutics for Schizophrenia Treatment Based on a Selective Positive Allosteric Modulation of α1-Containing GABAARs—In Silico Approach
Authors: Đorđević Vladimir , Petković Milan , Živković Jelena , Nikolić Goran M. , Veselinović Aleksandar M.
Published: August 2022

For the development of atypical antipsychotics, the selective positive allosteric modulation of the ionotropic GABAA receptor (GABAAR) has emerged as a promising approach. In the presented research, two unrelated methods were used for the development of QSAR models for selective positive allosteric modulation of 1-containing GABAARs with derivatives of imidazo [1,2-a]-pyridine. The development of conformation-independent QSAR models, based on descriptors derived from local molecular graph invariants and SMILES notation, was achieved with the Monte Carlo optimization method. From the vast pool of 0D, 1D, and 2D molecule descriptors, the GA-MLR method developed additional QSAR models. Various statistical methods were utilised for the determination of the developed models’ robustness, predictability, and overall quality, and according to the obtained results, all QSAR models are considered good. The molecular fragments that have a positive or negative impact on the studied activity were obtained from the studied molecules’ SMILES notations, and according to the obtained results, nine novel compounds were designed. The binding affinities to GABAAR of designed compounds were assessed with the application of molecular docking studies and the obtained results showed a high correlation with results obtained from QSAR modeling. To assess all designed molecules’ “drug-likeness”, their physicochemical descriptors were computed and utilised for the prediction of medicinal chemistry friendliness, pharmacokinetic properties, ADME parameters, and druglike nature.
Resistance of Human Liver Mesenchymal Stem Cells to FAS-Induced Cell Death
Authors: Kholodenko Irina V. , Gisina Alisa M. , Manukyan Garik V. , Majouga Alexander G. , Svirshchevskaya Elena V. , Kholodenko Roman V. , Yarygin Konstantin N.
Published: August 2022

Mesenchymal stem cells (MSCs) have a pronounced therapeutic potential in various pathological conditions. Though therapeutic effects of MSC transplantation have been studied for a long time, the underlying mechanisms are still not clear. It has been shown that transplanted MSCs are rapidly eliminated, presumably by apoptosis. As the mechanisms of MSC apoptosis are not fully understood, in the present work we analyzed MSC sensitivity to Fas-induced apoptosis using MSCs isolated from the biopsies of liver fibrosis patients (L-MSCs). The level of cell death was analyzed by flow cytometry in the propidium iodide test. The luminescent ATP assay was used to measure cellular ATP levels; and the mitochondrial membrane potential was assessed using the potential-dependent dye JC-1. We found that human L-MSCs were resistant to Fas-induced cell death over a wide range of FasL and anti-Fas mAb concentrations. At the same time, intrinsic death signal inducers CoCl2 and staurosporine caused apoptosis of L-MSCs in a dose-dependent manner. Despite the absence of Fas-induced cell death treatment of L-MSCs with low concentrations of FasL or anti-Fas mAb resulted in a cellular ATP level decrease, while high concentrations of the inducers caused a decline of the mitochondrial membrane potential. Pre-incubation of L-MSCs with the pro-inflammatory cytokine TNF-α did not promote L-MSC cell death. Our data indicate that human L-MSCs have increased resistance to receptor-mediated cell death even under inflammatory conditions.
The Role of the Electron Transport Layer in the Degradation of Organic Photovoltaic Cells
Authors: Al-Ahmad Alaa , Vaughan Benjamin , Holdsworth John , Belcher Warwick , Zhou Xiaojing , Dastoor Paul
Published: August 2022

The performance of the electron transport layer (ETL) plays a critical role in extending the operational lifespan of organic photovoltaic devices. ZnO is an excellent electron transport layer used in the printable organic photovoltaic cells. A comparison of Ca and ZnO as the ETL in encapsulated bulk heterojunction OPV devices has been undertaken with the device stability dependence on light soaking, temperature, irradiance, and thermal cycling recorded. It was observed that the OPV devices using Ca ETL decayed faster than the ZnO ETL devices under the same light illumination. The degradation in a Ca ETL device is ascribed to the formation of an insulating calcium oxide layer at the ETL interfaces. Photoluminescence (PL) spectroscopy revealed a higher PL signal for the degraded Ca ETL devices compared to the ZnO ETL devices. Power conversion efficiency (PCE) of the ZnO ETL devices was found to be much more stable than the Ca devices. The PCE for ZnO ETL devices still retained 40% of their initial value while the Ca ETL devices failed completely over the period of 18 days in the study, leading to a clear outcome of the study.
First-Principles Calculations of Interfacial Structure and Properties between WC Substrate and TiN Coating Based on Density Functional Theory
Authors: Wang Mengchao , Liu Yan , Chen Hui , Wang Lijun , Hu Dengwen
Published: August 2022

The excellent adhesion strength between the substrate and coating in the field of cemented carbide-coated tools is the crux of ensuring the durability of coated tools. The TiN coating is often used as a bonding layer to improve the bonding strength between the substrate and outer coating. Insights into detailed information on the interfacial properties between substrate and coating are essential for developing coating structures with optimal adhesion properties. Therefore, first-principles calculations were used to investigate the anisotropy of the elastic characteristics of WC and TiN as well as the bonding mechanism at the interface. The findings demonstrate that WC and TiN bulks have different symmetries in their anisotropy of elastic characteristics. WC(0001) and TiN(111) slabs can be well-lattice matched thanks to the low lattice mismatch ratio (2.7%). The HCP stacking mode has larger bonding energy than the OT and hole stacking modes in the interface structure with identical terminating atoms. The C-HCP-Ti interface forms covalent and ionic bonds, which is thermodynamically stable (γ = −1.127 J/m2) and has the highest bonding strength (Wad = 8.899 J/m2) among all interface structures. The results of this study provide a practical perspective for improving the mechanical properties of cemented carbide-coated tools.
Synthesis and Color Evaluation of Tb4+-Doped Na2ZrO3 for Inorganic Yellow Pigments
Authors: Oka Ryohei , Nouchi Tomoyo , Masui Toshiyuki
Published: August 2022

Tb4+-doped sodium zirconate samples, Na2Zr1−xTbxO3, were synthesized as novel environmentally friendly inorganic yellow pigments by a conventional solid-state reaction method. Their crystal structures, optical properties, and colors were characterized. A single-phase form was obtained for the samples in the x range of x ≤ 0.18, while impurity phases were detected for the sample with x = 0.20. All samples showed strong optical absorption in the blue light region, due to the charge transfer transition between O2− and Tb4+. As a result, the sample color became yellow, which is the complementary color of blue, and the color became more vivid with increasing Tb4+ content in the single-phase region. Among the samples, Na2Zr0.82Tb0.18O3 was the optimal composition, with the highest yellowness (b* = +67.2) and pure yellow hue (h° = 90.1). Although the b* value was lower than commercial yellow pigments such as BiVO4 and ZrSiO4:Pr, this sample had a purer yellow hue. Since Na2Zr0.82Tb0.18O3 is composed of non-toxic elements, it could be a new environmentally friendly inorganic yellow pigment.
SARS-CoV-2 Intermittent Virulence as a Result of Natural Selection
Authors: Rubio-Casillas Alberto , Redwan Elrashdy M. , Uversky Vladimir N.
Published: August 2022

For the first time in history, we have witnessed the origin and development of a pandemic. To handle the accelerated accumulation of viral mutations and to comprehend the virus’ evolutionary adaptation in humans, an unparalleled program of genetic sequencing and monitoring of SARS-CoV-2 variants has been undertaken. Several scientists have theorized that, with the Omicron surge producing a more contagious but less severe disease, the end of COVID-19 is near. However, by analyzing the behavior shown by this virus for 2 years, we have noted that pandemic viruses do not always show decreased virulence. Instead, it appears there is an evolutionary equilibrium between transmissibility and virulence. We have termed this concept “intermittent virulence”. The present work analyzes the temporal and epidemiological behavior of SARS-CoV-2 and suggests that there is a high possibility that new virulent variants will arise in the near future, although it is improbable that SARS-CoV-2’s virulence will be the same as was seen during the alpha or delta waves, due to the fact that the human population has reached a sufficient level of herd immunity through natural infection or due to the vaccination programs. The most recent global mortality data raised a question whether this pandemic is really over. Furthermore, it is uncertain when the endemic phase will begin. Darwin’s words: “the survival of the fittest” are still valid, and the virus will continue killing nonvaccinated old people, vaccinated old people, and those with comorbidities. We have underestimated the SARS-CoV-2 mastery of immune escape and have not yet seen the full adaptive potential this virus can develop through natural selection.
Influence of Vacancy on Structural Stability, Mechanical Properties and Electronic Structures of a Ti5Sn3 Compound from First-Principles Calculations
Authors: Pang Xingzhi , Wei Fenggui , Liu Dong , Yang Wenchao , Zhao Yanjun , Wu Jingwu , Pang Mingjun , Yang Jianbing
Published: August 2022

Titanium alloy is widely used in biomedical materials. Ti-Sn alloy is a new type β titanium alloy with no toxicity. In this paper, the mechanical and electronic properties of Ti5Sn3 with vacancy defects have been studied by using first-principles method. The vacancy formation energy, vacancy formation enthalpy, elastic constant, elastic modulus, hardness and electronic structure of perfect Ti5Sn3 and Ti5Sn3 with different vacancies were also calculated and discussed. The results show that Ti5Sn3 is more likely to form vacancies at VTi2. In addition, the bulk deformation resistance of Ti5Sn3 is weakened by the vacancy, and the shear resistance, stiffness and hardness of Ti5Sn3 are increased by the Ti vacancy, but the brittleness of Ti5Sn3 is increased. On the contrary, the presence of Sn vacancy decreases the shear resistance, stiffness and hardness of Ti5Sn3, and increases the toughness of Ti5Sn3. By analyzing the change of electronic structure, it is found that removing the Ti atom at the VTi2 position can improve the interaction between atoms, while Sn vacancy can weaken the interaction.
Gemological and Mineralogical Studies of Greenish Blue Apatite in Madagascar
Authors: Zhang Zhi-Yi , Xu Bo , Yuan Peng-Yu , Wang Zi-Xuan
Published: August 2022

Madagascar is known as the ‘Island of Gemstones’ because it is full of gemstone resources. Apatite from Madagascar is widely popular because of its greenish blue Paraiba-like color. This study analyzes apatite from Madagascar through standard gemological characteristic methods, spectroscopic tests and chemical analyses (i.e., electron probe and laser ablation inductively coupled plasma mass spectrometry). This work explores the gemological and the diagenesis information recorded on Madagascar apatite by comparing them with apatite from other sources and establishes the origin information of Madagascar apatite. The origin characteristics are as follows: Apatite from Madagascar is fluorapatite, with excellent diaphaneity, greenish–blue color caused by Ce and Nd and crystal structure distortion indicated by spectroscopic tests. The F/Cl ratio (16.47 to 21.89) suggests its magmatic origin Cl loss during the weathering processes forming the source rocks, and lg fO2 (−10.30 to −10.35) reflects the high oxidation degree of magma.
Effect of Lost-Foam Casting Process on Properties of Spiral Blade
Authors: Li Yi , Zhu Pengxiao , Tang Cai , Sun Zhi
Published: August 2022

The wear failure mode of a paver spiral blade was simulated by EDEM software. High-manganese steel, medium chromium alloy steel, and high chromium alloy steel were selected as matrix materials; SiC particles and WC particles were selected as surface particle reinforcement materials; and the spiral blade was prepared by the EPC process. The performance and wear mechanism of the spiral blade prepared by EPC were analyzed by microstructure, hardness, impact, pin disk, erosion wear test, and wear morphology. Modeling with EDEM software and applying the discrete element analysis method of particle system could simulate the actual working situation of the spiral blade of the paver well. Through the simulation, it was found that the wear amount of the spiral blade of the paver from the spiral shaft to the outside of the spiral blade was increasing. SiC and WC particle-reinforced wear-resistant coatings were prepared on the surfaces of high-manganese steel, medium chromium alloy steel, and high chromium alloy steel by the EPC method. The wear-resistant coating of high-manganese steel was 5.05 mm, the coating of medium chromium alloy steel was 5.98 mm, and the coating of high chromium alloy steel was 7.02 mm. The higher the chromium content, the better the diffusion with SiC and WC particles. In the process of the wear test, the soft phase in the coating was first worn away and concaved, and the hard phase protruded to bear the wear. After wear, it was found that the sample with high chromium alloy steel as matrix and SiC and WC particles as wear-resistant coating had the best wear resistance.
Exosomal Non-Coding RNAs: New Insights into the Biology of Hepatocellular Carcinoma
Authors: Zhang Qian , Li Hanlin , Liu Yang , Li Jian , Wu Chunling , Tang Hua
Published: August 2022

Exosomes, extracellular vesicles with a diameter of 40 to 160 nm, are among the smallest extracellular vesicles released by cells. They deliver different cargoes, including proteins, DNAs, and RNAs, and facilitate communication between cells to coordinate a variety of physiological and pathological functions. Hepatocellular carcinoma (HCC) is the sixth common malignant tumor and the fourth leading cause of cancer-related death worldwide. Its molecular mechanism remains largely unknown, and there is a lack of reliable and noninvasive biomarkers for early diagnosis and prognosis prediction. Mounting evidence has shown that exosomes carry a variety of ncRNAs, such as long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs), which play critical roles in the occurrence and progression of HCC. In this review, we summarize the recent findings of exosomal miRNAs, lncRNAs, and circRNAs in HCC from their impact on the development of HCC to their potential applications in the diagnosis and treatment of HCC.
Formica picea and F. candida (Hymenoptera: Formicidae): Synonyms or Two Species?
Authors: Zhigulskaya Zoya A. , Shekhovtsov Sergei V. , Poluboyarova Tatiana V. , Berman Daniil I.
Published: August 2022

Ants of the «Formica picea—F. candida» complex are widespread across Eurasia. However, it is still a matter of debate if it constitutes one or two species. In this study, we collected a sample of specimens from different parts of Eurasia, sequenced the mitochondrial cox1 and cytb genes, as well as three nuclear loci—wg, Top1, and ITS2—and analyzed the available published data. We found this complex to contain a new, yet undescribed, taxon that has a large distribution in Siberia and East Asia. Thus, the «Formica picea—F. candida» complex consists of at least three taxa with distinct distributions.
Composition and Ecological Structure of the Fauna of Litter and Soil True Bugs (Insecta, Heteroptera) in Kazakh Upland (Central Kazakhstan) Pine Forests
Authors: Abukenova Veronika S. , Slavchenko Nadezhda P. , Kartbayeva Gulnaz T. , Myrzabayev Amanay B. , Yeshmagambetova Aliya B. , Duzbayeva Nazira M. , Kabbassova Malika T. , Abukenova Almira K.
Published: August 2022

We assessed true bugs among aboveground and soil inhabitants of four different biocoenoses of pine forests representing the intrazone flora and fauna areas of the Kazakh Upland. True bugs were collected from litter according to the methods of soil zoological studies. The results of a comparative analysis of the similarities and differences of the dominant and ecological structures of Heteroptera complexes of aboriginal and derived forest types are presented. Fourteen species and subspecies of three families were listed for the Central Kazakhstan region for the first time. The species Eremocoris podagricus was not previously registered for the territory of Kazakhstan. Fifteen species (50%) were true aboveground inhabitants or live on grass, whereas other species use soil surfaces and ground litter as temporary habitats. Drymus brunneus and Eremocoris fenestratus play a key role in the structure and function of the true bug assemblages in the studied biotopes. The ecological success of typical forest and boreal inhabitants in biotopes of arid regions is explained by the relict nature of forests and ancient connections with the taiga zone of Western Siberia and the mountain forests of the Urals and Altai.
Challenges in Diagnosis of Uretero–Arterial Fistulas after Complex Pelvic Oncological Procedures—Single Center Experience and Review of the Literature
Authors: Surcel Cristian , Mirvald Cristian , Stoica Robert , Cerempei Vasile , Heidegger Isabel , Labanaris Apostolos , Tsaur Igor , Baston Catalin , Sinescu Ioanel
Published: August 2022

Introduction: Uretero–arterial fistula (UAF) represents a rare condition that manifests as massive or intermittent hematuria and requires collaboration between a urologist, vascular surgeon and interventional radiologist. In this article, we present our experience with UAF diagnosis, treatment pathways and the results of a nonsystematic review of the literature published in the last decade regarding modern diagnostic procedures. Material and method: We analyzed the clinical data of nine consecutive patients from our institution diagnosed with UAF in the interval of 2012–2022 who underwent open or endovascular surgical treatment. We reviewed patient characteristics, diagnoses and treatment pathways. The literature search resulted in 14 case series, published from 2012 to 2022, describing a total of 670 cases of UAF. Results: The mean age of patients in our cohort was 65.3 years (IQR: 51–79). UAFs were more common in women (77.7%). All patients presented a history of surgical intervention and ir-radiation for pelvic malignancy with permanent ureteric stenting. Overall, 88.8% of patients had urinary diversion, either via ileal conduit or cutaneous ureterostomy. The most common clinical manifestation of UAF was gross hematuria with or without clots accompanied by flank pain due to stent obstruction, while three patients presented with hypovolemic shock. Angiography represents the best option for diagnosis, followed by angioCT, with a sensitivity of 59.83% and 47.01%, respectively. There is no definitive imaging modality associated with high accuracy in detecting UAF and negative findings do not exclude the disease. In emergency cases with massive bleeding, surgical exploration remains the most appropriate management option for both diagnosis and treatment. Endovascular stent graft placement is preferred over open surgery in stable hemodynamic patients. Conclusions: Uretero–arterial fistulas represent a life-threatening complication and must be treated with great awareness. Angiography represents the best modality for diagnosis, followed by computed tomography. However, there is no definitive imaging modality and, in some cases, open approach remains the only option for diagnosis and treatment.
Predictive Value of Neutrophil–Lymphocyte Ratio as a Marker in Antiresorptive Agent-Related Osteonecrosis of the Jaw: A Retrospective Analysis
Authors: Kurohara Kazuto , Shimizu Kasumi , Murata Taku , Koizumi Gaku , Takigawa Akira , Nagata Kokoro , Okumura Kenya , Arai Naoya
Published: August 2022

Antiresorptive agent-related osteonecrosis of the jaw (ARONJ), a multifactorial disease, can drastically affect a patient’s quality of life. Moreover, disease progression to severe acute inflammation can hinder treatment. Therefore, we aimed to investigate the diagnostic value of the neutrophil–lymphocyte ratio (NLR) and platelet–lymphocyte ratio (PLR) in predicting the risk of acute inflammation in patients with ARONJ. In total, 147 patients with ARONJ were enrolled between 1 January 2011 and 31 December 2019. They were divided into two groups according to their baseline NLR (high NLR vs. low NLR) or PLR (high PLR vs. low PLR) to analyze the relationship between NLR and PLR and the outcomes of acute inflammatory events. An optimal NLR cut-off value of 2.83 was identified for hospitalization for an inflammatory event. Logistic regression analysis showed that NLR > 2.83 was associated with an increased risk of hospitalization for an inflammatory event. A PLR cut-off value of 165.2 was identified for hospitalization for an inflammatory event. However, logistic regression analysis showed that PLR > 165.2 was not significantly associated with hospitalization for an inflammatory event. Our study findings suggest that the NLR has diagnostic value in predicting the risk of hospitalization for inflammatory events among patients with ARONJ.
A Comparative Analysis of Deep Learning Models for Automated Cross-Preparation Diagnosis of Multi-Cell Liquid Pap Smear Images
Authors: Karasu Benyes Yasmin , Welch E. Celeste , Singhal Abhinav , Ou Joyce , Tripathi Anubhav
Published: August 2022

Routine Pap smears can facilitate early detection of cervical cancer and improve patient outcomes. The objective of this work is to develop an automated, clinically viable deep neural network for the multi-class Bethesda System diagnosis of multi-cell images in Liquid Pap smear samples. 8 deep learning models were trained on a publicly available multi-class SurePath preparation dataset. This included the 5 best-performing transfer learning models, an ensemble, a novel convolutional neural network (CNN), and a CNN + autoencoder (AE). Additionally, each model was tested on a novel ThinPrep Pap dataset to determine model generalizability across different liquid Pap preparation methods with and without Deep CORAL domain adaptation. All models achieved accuracies >90% when classifying SurePath images. The AE CNN model, 99.80% smaller than the average transfer model, maintained an accuracy of 96.54%. During consecutive training attempts, individual transfer models had high variability in performance, whereas the CNN, AE CNN, and ensemble did not. ThinPrep Pap classification accuracies were notably lower but increased with domain adaptation, with ResNet101 achieving the highest accuracy at 92.65%. This indicates a potential area for future improvement: development of a globally relevant model that can function across different slide preparation methods.
The Accuracy of Lateral Cephalogram in Representing the Anterior Maxillary Dentoalveolar Position
Authors: Teerakanok Supontep , Charoemratrote Chairat , Chanmanee Pannapat
Published: August 2022

Background: To evaluate the dentoalveolar position and root diameters of the maxillary incisors from cone beam computed tomograms (CBCT) compared with cephalometric tracings. Methods: A total of 64 sets of initial lateral cephalograms and CBCT images were enrolled. Measurements of dentoalveolar position included bone thicknesses and heights of alveolar, cortical, and cancellous bone. Root diameter and total root-bone thickness were also evaluated. All measurements were performed on cephalograms and CBCT images of the maxillary central incisor (U1CT) and maxillary lateral incisor (U2CT). The data were statistically analyzed using one-way ANOVA and Bonferroni tests (p < 0.01) to compare the cephalograms, U1CT, and U2CT. Results: The cephalograms presented thicker alveolar bone (labial: 0.20–0.67 mm, palatal: 0.41–0.60 mm; p < 0.001) and cortical bone (labial: 0.20–0.67 mm, palatal: 0.41–0.52 mm; p < 0.001) as well as higher alveolar crest (labial: 0.23–0.27 mm, palatal: 0.15–0.17 mm; p < 0.001) and cortical height (labial: 0.35–0.47 mm; p = 0.051, palatal: 0.14–0.18 mm; p < 0.001) than the CBCT images on both the labial and palatal sides, whereas palatal cancellous thickness was not significantly greater (p > 0.01). The cephalograms presented a greater total root-bone thicknesses (0.80–1.08 mm; p < 0.001), whereas the cephalograms traced thinner roots than the CBCT images (0.36–0.52 mm; p < 0.01). Conclusion: Routine lateral cephalograms are not suitable for alveolar bone evaluation in orthodontic treatment due to errors in representing dentoalveolar thicknesses and heights.
A Comprehensive Review of Machine Learning Used to Combat COVID-19
Authors: Gomes Rahul , Kamrowski Connor , Langlois Jordan , Rozario Papia , Dircks Ian , Grottodden Keegan , Martinez Matthew , Tee Wei Zhong , Sargeant Kyle , LaFleur Corbin , Haley Mitchell
Published: August 2022

Coronavirus disease (COVID-19) has had a significant impact on global health since the start of the pandemic in 2019. As of June 2022, over 539 million cases have been confirmed worldwide with over 6.3 million deaths as a result. Artificial Intelligence (AI) solutions such as machine learning and deep learning have played a major part in this pandemic for the diagnosis and treatment of COVID-19. In this research, we review these modern tools deployed to solve a variety of complex problems. We explore research that focused on analyzing medical images using AI models for identification, classification, and tissue segmentation of the disease. We also explore prognostic models that were developed to predict health outcomes and optimize the allocation of scarce medical resources. Longitudinal studies were conducted to better understand COVID-19 and its effects on patients over a period of time. This comprehensive review of the different AI methods and modeling efforts will shed light on the role that AI has played and what path it intends to take in the fight against COVID-19.
Synthetic Arterial Spin Labeling MRI of the Kidneys for Evaluation of Data Processing Pipeline
Authors: Brumer Irène , Bauer Dominik F. , Schad Lothar R. , Zöllner Frank G.
Published: August 2022

Accurate quantification of perfusion is crucial for diagnosis and monitoring of kidney function. Arterial spin labeling (ASL), a completely non-invasive magnetic resonance imaging technique, is a promising method for this application. However, differences in acquisition (e.g., ASL parameters, readout) and processing (e.g., registration, segmentation) between studies impede the comparison of results. To alleviate challenges arising solely from differences in processing pipelines, synthetic data are of great value. In this work, synthetic renal ASL data were generated using body models from the XCAT phantom and perfusion was added using the general kinetic model. Our in-house developed processing pipeline was then evaluated in terms of registration, quantification, and segmentation using the synthetic data. Registration performance was evaluated qualitatively with line profiles and quantitatively with mean structural similarity index measures (MSSIMs). Perfusion values obtained from the pipeline were compared to the values assumed when generating the synthetic data. Segmentation masks obtained by semi-automated procedure of the processing pipeline were compared to the original XCAT organ masks using the Dice index. Overall, the pipeline evaluation yielded good results. After registration, line profiles were smoother and, on average, MSSIMs increased by 25%. Mean perfusion values for cortex and medulla were close to the assumed perfusion of 250 mL/100 g/min and 50 mL/100 g/min, respectively. Dice indices ranged 0.80–0.93, 0.78–0.89, and 0.64–0.84 for whole kidney, cortex, and medulla, respectively. The generation of synthetic ASL data allows flexible choice of parameters and the generated data are well suited for evaluation of processing pipelines.
In-Vitro Phenotypic Response of Human Osteoblasts to Different Degrees of Titanium Surface Roughness
Authors: Osman Muataz A. , Alamoush Rasha A. , Kushnerev Evgeny , Seymour Kevin G. , Shawcross Susan , Yates Julian M.
Published: August 2022

Objectives: This study aimed to investigate human osteoblast (HOB) responses towards different degrees of titanium (Ti) implant surface roughness. Methods: Four degrees of Ti surface roughness were investigated on a micrometer roughness scale: smooth (S: 0.08–0.1 µm), minimally rough (MM: 0.3–0.5 µm), moderately rough (MR: 1.2–1.4 µm), and rough (R: 3.3–3.7 µm). HOB cells were cultured, expanded, and maintained according to the supplier’s protocol. Cell proliferation and cytotoxicity were assessed at day 1, 3, 5, and 10 using alamarBlue and lactate dehydrogenase colorimetric assays. Data were analyzed with one-way ANOVA, two-way ANOVA, and Tukey’s post hoc test (p = 0.05 for all tests). Results: There was no significant difference in the cell proliferation or cytotoxicity of the HOB cells in contact with the different degrees of Ti surface roughness. There was, however, a significant time effect on cell proliferation (p < 0.0001) with different exposure durations for each roughness degree. Furthermore, a positive correlation (non-significant) between proliferation and cytotoxicity was observed for all investigated degrees of surface roughness. Conclusion: All investigated roughness degrees showed comparable HOB proliferation, with the MR surface presenting the highest percentage, followed by the R, MM, ad S, surfaces, respectively. The S surface showed the highest cytotoxic effect on HOBs; however, it did not reach the cytotoxic level suggested by the ISO for any medical device to be considered cytotoxic.
A Four-Dimensional Space-Time Automatic Obstacle Avoidance Trajectory Planning Method for Multi-UAV Cooperative Formation Flight
Authors: Zhang Jie , Sheng Hanlin , Chen Qian , Zhou Han , Yin Bingxiong , Li Jiacheng , Li Mengmeng
Published: August 2022

Trajectory planning of multiple unmanned aerial vehicles (UAVs) is the basis for them to form the formation flight. By considering trajectory planning of multiple UAVs in formation flight in three-dimensional space, a trajectory planning method in four-dimensional space-time is proposed which, firstly, according to the formation configuration, adopts the Hungarian algorithm to optimize the formation task allocation. Based on that, by considering the flight safety of UAVs in formation, a hierarchical decomposition algorithm in four-dimensional space-time is innovatively put forward with spatial positions and time constraints both considered. It is applied to trajectory planning and automatic obstacle avoidance under the condition of no communication available between UAVs in the formation. The simulation results illustrated that the proposed method is effective in cooperative trajectory planning and automatic obstacle avoidance in advance for multiple UAVs. Meanwhile, it has been tested in a Swarm Unmanned Aerial System project and boasts quite significant value in engineering applications.
Research on the Robustness of the Chinese Input–Output Network Based on Relative Entropy Theory
Authors: Li Weidong , Wang Anjian , Xing Wanli
Published: August 2022

The input–output (IO) network is the quantitative description of an IO-based economy in which nodes represent industries and edges connecting nodes represent the economic connection between industries. Robustness refers to the ability of tolerating perturbations that might affect the system’s functional body. There is both practical and theoretical significance to explore the robustness of the IO network for economic development. In this paper, we probe the robustness of the Chinese IO network based on the relative entropy of the probability distribution of network parameters (node degree, strongest path betweenness, downstream closeness and upstream closeness) under random node or edge failure and intentional node or edge attack. It is found that the Chinese IO network shows relatively weak robustness when it is under intentional attack, but relatively strong robustness when it is under random failure. Our experiment also verifies the applicability and effectiveness of the relative entropy model in measuring the robustness of the IO network.
Cardio-Hypothalamic-Pituitary Coupling during Rest and in Response to Exercise
Authors: Berry Nathaniel T. , Rhea Christopher K. , Wideman Laurie
Published: August 2022

The objective of this study was to examine cardio hypothalamic-pituitary coupling and to better understand how the temporal relations between these systems are altered during rest and exercise conditions. An intensive within subjects study design was used. Seven adult males completed two visits, each consisting of either a 24 h period of complete rest or a 24 h period containing a high-intensity exercise bout. An intravenous catheter was used to collect serum samples every 10 min throughout the 24 h period (i.e., 145 samples/person/condition) to assess growth hormone (GH) dynamics throughout the 24 h period. Cardiac dynamics were also collected throughout the 24 h period and epoched into 3 min windows every 10 min, providing serial short-time measurements of heart rate variability (HRV) concurrent to the GH sampling. The standard deviation of the normal RR interval (SDNN), the root mean square of successive differences (rMSSD), and sample entropy (SampEn) was calculated for each epoch and used to create new profiles. The dynamics of these profiles were individually quantified using SampEn and recurrence quantification analysis (RQA). To address our central question, the coupling between these profiles with GH was assessed using cross-SampEn and cross-RQA (cRQA). A comparison between the epoched HRV profiles indicated a main effect between profiles for sample entropy (p < 0.001) and several measures from RQA. An interaction between profile and condition was observed for cross-SampEn (p = 0.04) and several measures from cRQA. These findings highlight the potential application of epoched HRV to assess changes in cardiac dynamics, with specific applications to assessing cardio hypothalamic-pituitary coupling.
Multi-View Travel Time Prediction Based on Electronic Toll Collection Data
Authors: Luo Sijie , Zou Fumin , Zhang Cheng , Tian Junshan , Guo Feng , Liao Lyuchao
Published: August 2022

The travel time prediction of vehicles is an important part of intelligent expressways. It can not only provide the vehicle distribution trend of each section for the expressway management department to assist the fine management of the expressway, but it can also provide owners with dynamic and accurate travel time prediction services to assist the owners to formulate more reasonable travel plans. However, there are still some problems in the current travel time prediction research (e.g., different types of vehicles are not processed separately, the proximity of the road network is not considered, and the capture of important information in the spatial-temporal perspective is not considered in depth). In this paper, we propose a Multi-View Travel Time Prediction (MVPPT) model. First, the travel times of different types of vehicles of each section in the expressway are analyzed, and the main differences in the travel times of different types of vehicles are obtained. Second, multiple travel time features are constructed, which include a novel spatial proximity feature. On this basis, we use CNN to capture the spatial correlation and the spatial attention mechanism to capture key information, the BiLSTM to capture the time correlation of time series, and the time attention mechanism capture key time information. Experiments on large-scale real traffic data demonstrate the effectiveness of our proposal over state-of-the-art methods.
Multivariate Time Series Imputation: An Approach Based on Dictionary Learning
Authors: Zheng Xiaomeng , Dumitrescu Bogdan , Liu Jiamou , Giurcăneanu Ciprian Doru
Published: August 2022

The problem addressed by dictionary learning (DL) is the representation of data as a sparse linear combination of columns of a matrix called dictionary. Both the dictionary and the sparse representations are learned from the data. We show how DL can be employed in the imputation of multivariate time series. We use a structured dictionary, which is comprised of one block for each time series and a common block for all the time series. The size of each block and the sparsity level of the representation are selected by using information theoretic criteria. The objective function used in learning is designed to minimize either the sum of the squared errors or the sum of the magnitudes of the errors. We propose dimensionality reduction techniques for the case of high-dimensional time series. For demonstrating how the new algorithms can be used in practical applications, we conduct a large set of experiments on five real-life data sets. The missing data (MD) are simulated according to various scenarios where both the percentage of MD and the length of the sequences of MD are considered. This allows us to identify the situations in which the novel DL-based methods are superior to the existing methods.
Lexicons of Key Terms in Scholarly Texts and Their Disciplinary Differences: From Quantum Semantics Construction to Relative-Entropy-Based Comparisons
Authors: Koponen Ismo , Södervik Ilona
Published: August 2022

Complex networks are often used to analyze written text and reports by rendering texts in the form of a semantic network, forming a lexicon of words or key terms. Many existing methods to construct lexicons are based on counting word co-occurrences, having the advantage of simplicity and ease of applicability. Here, we use a quantum semantics approach to generalize such methods, allowing us to model the entanglement of terms and words. We show how quantum semantics can be applied to reveal disciplinary differences in the use of key terms by analyzing 12 scholarly texts that represent the different positions of various disciplinary schools (of conceptual change research) on the same topic (conceptual change). In addition, attention is paid to how closely the lexicons corresponding to different positions can be brought into agreement by suitable tuning of the entanglement factors. In comparing the lexicons, we invoke complex network-based analysis based on exponential matrix transformation and use information theoretic relative entropy (Jensen–Shannon divergence) as the operationalization of differences between lexicons. The results suggest that quantum semantics is a viable way to model the disciplinary differences of lexicons and how they can be tuned for a better agreement.
Laying the Foundations of Continuing Education in Health in the Family Health Strategy
Authors: Moura Cleson , Moreira Katia , Costa Andreia , Baixinho Cristina Lavareda , Henriques Maria Adriana , da Silva Marcelle Miranda
Published: August 2022

Primary healthcare must guarantee health and well-being for the community as a whole, ensuring equity and quality in different responses. For this goal to be achieved, teams must be trained and integrated, and service flows must be functional. Continuing education in health, as a form of training professionals in the workplace, helps to center responses around the needs and preferences of people and families, and to balance the fulfillment of demands by using better work management as a starting point. The objectives of the present qualitative study were to elucidate the meaning given by health professionals who developed their activities in the Family Health Strategy in order to continue education in health, and to discuss the qualification and structuring of work management with this type of education as a background. The methodology used was Straussian grounded theory. Thirty professionals in four Brazilian health units who had experience in the family health field participated in the study. Data were collected between June 2018 and May 2019. Based on three categories, the emerging substantive theory was as follows: laying the foundations of continuing education in health in a collective dialogic and dialectical effort to contribute to the qualification of the work processes in the Family Health Strategy. The professionals’ accounts showed that they recognize the importance of continuing education in health and the need to discuss it, given its potential to transform and to assist in the education of professionals with autonomy in the management of their work processes.
Task Offloading in Wireless Powered Mobile Crowd Sensing: A Matching-Based Approach
Authors: Yi Difei , Li Jun , Tang Chengpei , Lin Ziqi , Han Yu , Qiu Rui
Published: August 2022

Mobile crowd sensing (MCS) is a new sensing paradigm that leverages participatory sensing data from mobile devices for accomplishing large-scale sensing tasks. Incentivizing device owners to contribute high-quality sensing data is a prerequisite for the success of MCS services. In this paper, we first propose a pre-contracting incentive mechanism that involves the participation of not only the device owners located in close proximity to Point of Interests (PoIs) but also the device owners that are going to pass through those locations. Furthermore, the quality of sensing data is guaranteed through the use of redundancy. In particular, sensing data from multiple device owners is processed and compared at an edge side (i.e., base station) so as to detect the measurement error at the proximity of data sources. Simulation results confirm that the proposed incentive mechanism is efficient in terms of improving the total utility.
CMT-SCTP and MPTCP Multipath Transport Protocols: A Comprehensive Review
Authors: Tomar Parul , Kumar Gyanendra , Verma Lal Pratap , Sharma Varun Kumar , Kanellopoulos Dimitris , Rawat Sur Singh , Alotaibi Youseef
Published: August 2022

A huge amount of generated data is regularly exploding into the network by the users through smartphones, laptops, tablets, self-configured Internet-of-things (IoT) devices, and machine-to-machine (M2M) communication. In such a situation, satisfying critical quality-of-service (QoS) requirements (e.g., throughput, latency, bandwidth, and reliability) is a large challenge as a vast amount of data travels into the network. Nowadays, strict QoS requirements must be satisfied efficiently in many networked multimedia applications when intelligent multi-homed devices are used. Such devices support the concept of multi-homing. To be precise, they have multiple network interfaces that aim to connect and communicate concurrently with different networking technologies. Therefore, many multipath transport protocols are provided to multi-homed devices, which aim (1) to take advantage of several network paths at the transport layer (Layer-4) and (2) to meet the strict QoS requirements for providing low network latency, higher data rates, and increased reliability. To this end, this survey first presents the challenges/problems for supporting multipath transmission with possible solutions. Then, it reviews recent research efforts related to the concurrent multipath transmission (CMT) protocol and the multipath transmission control protocol (MPTCP). It reviews the latest research efforts by considering (1) how a multipath transport protocol operates (i.e., its functionality); (2) in what type of network; (3) what path characteristics it should consider; and (4) how it addresses various design challenges. Furthermore, it presents some lessons learned and discusses open research issues in multipath transport protocols.
Emotion Recognition from EEG Signals Using Recurrent Neural Networks
Authors: Chowdary M. Kalpana , Anitha J. , Hemanth D. Jude
Published: August 2022

The application of electroencephalogram (EEG)-based emotion recognition (ER) to the brain–computer interface (BCI) has become increasingly popular over the past decade. Emotion recognition systems involve pre-processing and feature extraction, followed by classification. Deep learning has recently been used to classify emotions in BCI systems, and the results have been improved when compared to classic classification approaches. The main objective of this study is to classify the emotions from electroencephalogram signals using variant recurrent neural network architectures. Three architectures are used in this work for the recognition of emotions using EEG signals: RNN (recurrent neural network), LSTM (long short-term memory network), and GRU (gated recurrent unit). The efficiency of these networks, in terms of performance measures was confirmed by experimental data. The experiment was conducted by using the EEG Brain Wave Dataset: Feeling Emotions, and achieved an average accuracy of 95% for RNN, 97% for LSTM, and 96% for GRU for emotion detection problems.
MultiSec: A Multi-Protocol Security Forwarding Mechanism Based on Programmable Data Plane
Authors: Liu Zeying , Cui Pengshuai , Dong Yongji , Xue Lei , Hu Yuxiang
Published: August 2022

With the development of network technology, various network protocols different from TCP/IP have emerged. The heterogeneous integrated network has been proposed to realize the interconnection between heterogeneous networks running different protocols. However, current protocol conversion mechanisms often can only handle a few pre-defined protocols and do not support the flexible expansion of new protocols, which cannot meet the needs of the efficient convergence of different heterogeneous networks. Addirionally, due to the lack of security mechanisms, data in the core network is confronted with the risk of stealing and tampering. Our aim is to provide a protocol-extensible protocol conversion and secure transmission integration mechanism, MultiSec, for heterogeneous converged networks. First, based on the programmable data plane, the parser is reconfigured to realize multi-protocol parsing. Furthermore, the encryption mechanism implemented in the P4 extern is proposed and unified to the data plane together with the protocol conversion mechanism. Finally, the MultiSec prototype is implemented on a programmable software switch and accelerated by a dedicated encryption card. Experiments show that MultiSec successfully realizes multi-protocol conversion and data encryption, and the system performance is significantly improved with the help of an encryption card.
Characteristic Mode Analysis of a Ka-Band CPW-Slot-Couple Fed Patch Antenna with Enhanced Bandwidth and Gain
Authors: Deng Kun , Yang Fuxing , Zhou Jiali , Lai Chengqi , Wang Yucheng , Han Ke
Published: August 2022

A Ka-band CPW-Slot-Couple (CSC) fed microstrip antenna with enhanced bandwidth and gain is presented in this paper. To simplify the feed network, the matching slots are designed at the end of the CPW. Consequently, the patch antenna is designed with a low profile, which has a size of 7.2 × 32.6 × 0.508 mm3. Characteristic mode analysis (CMA) is applied to illustrate the principle of the enhancement of the band with the form characteristic mode point of view. A slot based on inductive loading is employed on the parasitic patch to move the resonant frequency of CM3 to the resonant frequency of CM2 for enhanced bandwidth, which avoids introducing additional impedance matching networks. The measured results show that the bandwidth of the proposed monolayer antenna is 14.18% from 24.84 to 28.6 GHz and the peak gain is 7.9 dBi. Due to its attractive properties of low profile, compact configuration, wide band, and high gain, the proposed antenna could be applied to miniaturized millimeter-wave applications.