bluuebunny/crossref_metadata_2025 huggingface dataset:
Spectroscopic Analysis of NF3 Plasmas with Oxygen Additive for PECVD Chamber Cleaning
Authors: An Surin , Hong Sang Jeen
Published: January 2023

As semiconductors’ device fabrication is highly integrated, the number of the deposition processes is continuously increasing, and the chamber cleaning process becomes essential for deposition equipment to maintain a normal chamber condition. Although the use of NF3 gas for the chamber cleaning is common, it causes several environmental and safety issues. However, not much research has been performed on NF3 plasma at high pressures, such as in cleaning processes. To understand fluorine in NF3, herein, oxygen was added to N2 and NF3 plasma and then compared. Plasma emission spectra were compared using an OES data, and their analyses were performed via a line-ratio method employing the collisional-radiative model. As a result confirmed that the changes in electron temperature, electron density, and chemical species in the plasma could be explained. Additionally, the characteristics of NF3 plasmas with respect to fluorine were confirmed by comparing the oxygenated N2 plasma and the NF3 plasma.
The Influence of H Content on the Properties of a-C(W):H Coatings
Authors: Evaristo Manuel , Fernandes Filipe , Jeynes Chris , Cavaleiro Albano
Published: January 2023

Diamond-like-carbon “DLC” coatings can be deposited in many different ways, giving a large range of material properties suitable for many different types of applications. Hydrogen content significantly influences the mechanical properties and the tribological behavior of DLC coatings, but its determination requires techniques that are not available in many research centers. Thus, it is important to find alternative indirect techniques, such as Raman spectroscopy or nanoindentation (hardness measurements), which can give comparative and indicative values of the H contents in the coatings, particularly when depositions with a reactive gas flow are being studied. In this work, “DLC” composite coatings with varying H content were deposited via Physical Vapor Deposition (PVD) magnetron sputtering in a reactive atmosphere (Ar + CH4). An Ion Beam Analysis was used to determine the elemental depth profile across the coating thickness (giving both average C:W:H ratios and film density when combined with profilometer measurements of film thickness). The hardness was evaluated with nanoindentation, and a decrease from 16 to 6 GPa (and a decrease in the film density by a factor of two) with an increasing CH4 flow was observed. Then, the hardness and Raman results were correlated with the H content in the coatings, showing that these indirect methods can be used to find if there are variations in the H content with the increase in the CH4 flow. Finally, the adhesion and tribological performance of the coatings were evaluated. No significant differences were found in the adhesion as a function of the H content. The tribological properties presented a slight improving trend with the increase in the H content with a decrease in the wear rate and friction.
Extending High Fatty Foods Shelf-Life Protecting from Lipid Oxidation and Microbiological Contamination: An Approach Using Active Packaging with Pomegranate Extract
Authors: Andrade Mariana A. , Rodrigues Pedro V. , Barros Carolina , Cruz Vasco , Machado Ana Vera , Barbosa Cássia H. , Coelho Anabela , Furtado Rosália , Correia Cristina Belo , Saraiva Margarida , Vilarinho Fernanda , Ramos Fernando , Silva Ana Sanches
Published: January 2023

The search for new forms to extend foodstuffs’ shelf-life through the use of natural compounds and extracts continues to grow among researchers and the industry. In this line of thought, the main objective of this work was to develop, characterize and evaluate the effectiveness of an active food packaging based on polylactic acid (PLA) and incorporated with natural extracts obtained from grape and/or pomegranate by-products. In vitro, antioxidant methods were applied to evaluate the antioxidant capacity of three extracts: wort extract, freeze-dried pomegranate peels extract (PPE-FD), and natural pomegranate peels (PPE-N). Punicalagin (A + B) and ellagic acid were determined in PPE-FD, PPE-N, and active films by UHPLC-DAD. New PLA-based active packaging with PPE-FD (PLA/3PPE) and pomegranate peels (PLA/3PP) were developed, and their chemical, mechanical, and barrier properties were evaluated. Moreover, the effectiveness of the new film was carried out through the study of lipid oxidation state and microbial contamination of two high-fat content foodstuffs, almonds and beef meat. PPE-FD presented high antioxidant capacity and high content in total phenolics and flavonoid compounds. The PLA/3PPE and PLA/3PP prevented the lipid oxidation of meat and presented antimicrobial activity against Staphylococcus aureus. The addition of the PPE-FD and the pomegranate peels to the PLA did not affect the morphology of the polymer. Although both PPE-FD and pomegranate peels presented punicalagin (A + B) and ellagic acid, only ellagic acid was identified and quantified in the active PLA. Active PLA films were not effective in delaying the lipid oxidation of almonds, but they showed to be significantly effective in delaying the lipid oxidation of beef meat and reducing the microbial growth in this food matrix over time.
Sparse Reconstruction Using Hyperbolic Tangent as Smooth l1-Norm Approximation
Authors: Haider Hassaan , Shah Jawad Ali , Kadir Kushsairy , Khan Najeeb
Published: January 2023

In the Compressed Sensing (CS) framework, the underdetermined system of linear equation (USLE) can have infinitely many possible solutions. However, we intend to find the sparsest possible solution, which is l0-norm minimization. However, finding an l0 norm solution out of infinitely many possible solutions is NP-hard problem that becomes non-convex optimization problem. It has been a practically proven fact that l0 norm penalty can be adequately estimated by l1 norm, which recasts a non-convex minimization problem to a convex problem. However, l1 norm non-differentiable and gradient-based minimization algorithms are not applicable, due to this very reason there is a need to approximate l1 norm by its smooth approximation. Iterative shrinkage algorithms provide an efficient method to numerically minimize l1-regularized least square optimization problem. These algorithms are required to induce sparsity in their solutions to meet the CS recovery requirement. In this research article, we have developed a novel recovery method that uses hyperbolic tangent function to recover undersampled signal/images in CS framework. In our work, l1 norm and soft thresholding are both approximated with the hyperbolic tangent functions. We have also proposed the criteria to tune optimization parameters to get optimal results. The error bounds for the proposed l1 norm approximation are evaluated. To evaluate performance of our proposed method, we have utilized a dataset comprised of 1-D sparse signal, compressively sampled MR image and cardiac cine MRI. The MRI is an important imaging modality for assessing cardiac vascular function. It provides the ejection fraction and cardiac output of the heart. However, this advantage comes at the cost of a slow acquisition process. Hence, it is essential to speed up the acquisition process to take the full benefits of cardiac cine MRI. Numerical results based on performance metrics, such as Structural Similarity (SSIM), Peak Signal to Noise Ratio (PSNR) and Root Mean Square Error (RMSE) show that the proposed tangent hyperbolic based CS recovery offers a much better performance as compared to the traditional Iterative Soft Thresholding (IST) recovery methods.
Effect of Heat Treatment Process on the Optimization of Grain Boundary Character Distribution in Heavy Gage Austenitic Stainless Steel
Authors: Wang Zhiguo , Zhang Weina , Ma Aoran , Li Jianyuan , Gao Fei , Li Chengang , Liu Zhenyu
Published: January 2023

The optimization of grain boundary character distribution (GBCD) is of great significance to improve the GB-related properties for heavy-gauge austenitic stainless steels worked in harsh environments such as reactors of nuclear power, which can usually be realized by regulating the thermomechanical process. In this paper, special solution annealing processes for a hot-rolled nuclear grade 316H plate were designed to introduce different character distribution of Σ3n boundaries (1 ≤ n ≤ 3) and random high-angle GBs (RHAGBs), and the regulation principle among them were clarified. It was worked out that the optimized GBCD by characterization of large twin related domains, abundant interconnected Σ3n boundaries and interrupted topology network of RHAGBs could be effectively facilitated through solution annealing with a long time period at lower temperature or short time period at higher temperature, in which the recrystallization, grain growth and GB migration during heat treatment process played key roles. Moreover, the length fraction of Σ3n boundaries were found to be hardly changed when they reached about 77%, but their character distribution could be continuously optimized.
Two-Step GaN Layer Growth for High-Voltage Lateral AlGaN/GaN HEMT
Authors: Yusuf Yusnizam , Samsudin Muhammad Esmed Alif , Taib Muhamad Ikram Md , Ahmad Mohd Anas , Mohamed Mohamed Fauzi Packeer , Kawarada Hiroshi , Falina Shaili , Zainal Norzaini , Syamsul Mohd
Published: January 2023

This paper presents reduced dislocation of the AlGaN/GaN heterostructure for high-voltage lateral high-electron-mobility transistor (HEMT) devices. AlGaN/GaN heterostructure was grown on sapphire substrate. Prior to the growth of the AlGaN layer, the GaN layer was grown via two-step growth. In the first step, the V/III ratio was applied at 1902 and then at 3046 in the second step. The FWHMs of the XRD (002) and (102) peaks of the GaN layer were around 205 arcsec ((002) peak) and 277 arcsec ((102) peak). Moreover, the surface of the GaN layer showed clear evidence of step flows, which resulted in the smooth surface of the layer as well as the overgrown of the AlGaN layer. Subsequently, the AlGaN/GaN heterostructure was fabricated into a lateral HEMT with wide gate-to-drain length (LGD). The device exhibited a clear working HEMT characteristic with high breakdown voltages up to 497 V. In comparison to many reported AlGaN/GaN HEMTs, no AlGaN interlayer was inserted in our AlGaN/GaN heterostructure. By improving the growth conditions for the two-step growth, the performance of AlGaN/GaN HEMTs could be improved further.
Additive Manufacturing (AM) for Advanced Materials and Structures: Green and Intelligent Development Trend
Authors: Liu Menglin , Yi Hao , Cao Huajun
Published: January 2023

Additive manufacturing (AM) is an emerging and rapidly evolving technology that has revolutionized the way products are developed, fabricated and commercialized [...]
A Solemys Skull from the Late Cretaceous of Southern France
Authors: Tong Haiyan , Buffetaut Eric , Méchin Patrick , Méchin-Salessy Annie , Claude Julien
Published: January 2023

The first skull of Solemys (Testudines: Helochlydridae) is reported from the Late Cretaceous (Rognacian) Bastide Neuve locality, Fox Amphoux, Var, France. It is assigned to Solemys gaudryi (Matheron, 1869) on the basis of associated shell elements. Our study provides new insights regarding the skull morphology of the family Helochelydridae and suggests that Helochelydra from England and Naomichelys from North America appear to be closer to each other than to Solemys.
Numerical Ecology and Social Network Analysis of the Forest Community in the Lienhuachih Area of Taiwan
Authors: Hsieh Tung-Yu , Yang Chun-Jheng , Li Feng , Chiou Chyi-Rong
Published: January 2023

In this study, the integration of useful statistical methods from different disciplines for analyzing the forest community of the Lienhuachih area of central Taiwan was attempted. We employed a seriated heat map to confirm the presence of multiple community patterns in the area and used the gap statistics and a clustplot to confirm the number and structure of the patterns, respectively. A minimum spanning tree was used to display a succession series among the quadrats, and Renyi diversity was used to indicate the species composition of these patterns. The results confirmed the existence of six patterns with different biodiversity structures in which pattern C was the succession prototype of the local community patterns. Next, we used the patterns as nodes of a social network to perform bipartite network analysis. The results showed that a community network consisted of 108 taxa and six syntaxa. The syntaxa were highly vulnerable to extinction; therefore, the optimal conservation strategy for local species would be to first protect the syntaxa. The random forest method and bipartite modularity were used to analyze the dominant characteristic species of the six syntaxa. The results showed that these two methods are useful for detecting characteristic species of the syntaxa. Therefore, this study proposed a new nomenclature system, namely the Mathematic Code of Syntaxonomic Nomenclature, to support the results of numerical vegetation analysis. Finally, the potential for an apparently competitive network was examined, the role of an apparently competitive network in the local structuring community was explored, and six new associations in the Lienhuachih area were described.
Low Bioerosion Rates on Inshore Turbid Reefs of Western Australia
Authors: Dee Shannon , DeCarlo Thomas , Lozić Ivan , Nilsen Jake , Browne Nicola K.
Published: January 2023

Bioerosion on inshore reefs is expected to increase with global climate change reducing reef stability and accretionary potential. Most studies investigating bioerosion have focused on external grazers, such as parrotfish and urchins, whose biomass is more easily measured. Yet, cryptic endolithic bioeroders such as macroboring (worms, sponges and bivalves) and microboring taxa (fungus and algae) have the potential to be the dominant source of reef erosion, especially among inshore reef systems exposed to increased nutrient supply. We measured bioerosion rates of bioeroder functional groups (microborers, macroborers, and grazers), and their response to environmental parameters (temperature, light, turbidity, chlorophyll a), as well as habitat variables (coral cover, turfing algae, macroalgae) across two inshore turbid reefs of north Western Australia. Total bioerosion rates were low (0.163 ± 0.012 kg m−2 year−1) likely due to low light and nutrient levels. Macroborers were the dominant source of bioerosion and were positively correlated with turfing algae cover, highlighting the role of turf-grazing fish on endolithic bioerosion rates. Overall low bioerosion rates suggest that despite the reduced coral cover and carbonate production, these reefs may still maintain positive reef accretion rates, at least under current environmental conditions. However, an improved understanding of relationships between environmental drivers, habitat and grazing pressure with bioeroding communities is needed to improve predictions of reef carbonate loss with future climate change.
Lungfish and the Long Defeat
Authors: Kemp Anne
Published: January 2023

Australia has an excellent fossil record of lungfish that begins in the Devonian and includes many species in Tertiary and Quaternary deposits. The extant Australian lungfish, Neoceratodus forsteri, occurs in Pliocene deposits, but is now restricted to a handful of coastal rivers in Queensland. Some of the fossil taxa, belonging to species related to N. forsteri, are represented by only a few specimens, but others include large numbers of tooth plates. The existence of these taxa, even if they are represented by only a few specimens, indicates that lungfish were present in lakes and rivers in central and northern Australia in the past, and that the potential habitats for these fish were more extensive then than they are now. Many of the fossil populations died out because Australia became more arid, and the remaining species became isolated in large river systems in the north and east of the continent. However, the cause of extinction of some fossil populations was not always related to increasing aridity. Several fossil populations were apparently living in poor conditions. They stopped spawning and adding new members to the population. The remaining individuals showed advanced age and many diseases before the population disappeared. This can be observed in the present day, and one population in an isolated reservoir is already extinct.
A Review of Recent Advances in Deep Learning Models for Chest Disease Detection Using Radiography
Authors: Ait Nasser Adnane , Akhloufi Moulay A.
Published: January 2023

Chest X-ray radiography (CXR) is among the most frequently used medical imaging modalities. It has a preeminent value in the detection of multiple life-threatening diseases. Radiologists can visually inspect CXR images for the presence of diseases. Most thoracic diseases have very similar patterns, which makes diagnosis prone to human error and leads to misdiagnosis. Computer-aided detection (CAD) of lung diseases in CXR images is among the popular topics in medical imaging research. Machine learning (ML) and deep learning (DL) provided techniques to make this task more efficient and faster. Numerous experiments in the diagnosis of various diseases proved the potential of these techniques. In comparison to previous reviews our study describes in detail several publicly available CXR datasets for different diseases. It presents an overview of recent deep learning models using CXR images to detect chest diseases such as VGG, ResNet, DenseNet, Inception, EfficientNet, RetinaNet, and ensemble learning methods that combine multiple models. It summarizes the techniques used for CXR image preprocessing (enhancement, segmentation, bone suppression, and data-augmentation) to improve image quality and address data imbalance issues, as well as the use of DL models to speed-up the diagnosis process. This review also discusses the challenges present in the published literature and highlights the importance of interpretability and explainability to better understand the DL models’ detections. In addition, it outlines a direction for researchers to help develop more effective models for early and automatic detection of chest diseases.
Molecular Genetics of Thrombotic Myeloproliferative Neoplasms: Implications in Precision Oncology
Authors: Chia Yuh Cai , Siti Asmaa Mat Jusoh , Ramli Marini , Woon Peng Yeong , Johan Muhammad Farid , Hassan Rosline , Islam Md Asiful
Published: January 2023

Classical BCR-ABL-negative myeloproliferative neoplasms (MPN) include polycythaemia vera, essential thrombocythaemia, and primary myelofibrosis. Unlike monogenic disorders, a more complicated series of genetic mutations are believed to be responsible for MPN with various degrees of thromboembolic and bleeding complications. Thrombosis is one of the early manifestations in patients with MPN. To date, the driver genes responsible for MPN include JAK2, CALR, MPL, TET2, ASXL1, and MTHFR. Affords have been done to elucidate these mutations and the incidence of thromboembolic events. Several lines of evidence indicate that mutations in JAK2, MPL, TET2 and ASXL1 gene and polymorphisms in several clotting factors (GPIa, GPIIa, and GPIIIa) are associated with the occurrence and prevalence of thrombosis in MPN patients. Some polymorphisms within XRCC1, FBG, F2, F5, F7, F12, MMP9, HPA5, MTHFR, SDF-1, FAS, FASL, TERT, ACE, and TLR4 genes may also play a role in MPN manifestation. This review aims to provide an insightful overview on the genetic perspective of thrombotic complications in patients with MPN.
Determining HER2 Status by Artificial Intelligence: An Investigation of Primary, Metastatic, and HER2 Low Breast Tumors
Authors: Palm Christiane , Connolly Catherine E. , Masser Regina , Padberg Sgier Barbara , Karamitopoulou Eva , Simon Quentin , Bode Beata , Tinguely Marianne
Published: January 2023

The expression of human epidermal growth factor receptor 2 (HER2) protein or gene transcripts is critical for therapeutic decision making in breast cancer. We examined the performance of a digitalized and artificial intelligence (AI)-assisted workflow for HER2 status determination in accordance with the American Society of Clinical Oncology (ASCO)/College of Pathologists (CAP) guidelines. Our preliminary cohort consisted of 495 primary breast carcinomas, and our study cohort included 67 primary breast carcinomas and 30 metastatic deposits, which were evaluated for HER2 status by immunohistochemistry (IHC) and in situ hybridization (ISH). Three practicing breast pathologists independently assessed and scored slides, building the ground truth. Following a washout period, pathologists were provided with the results of the AI digital image analysis (DIA) and asked to reassess the slides. Both rounds of assessment from the pathologists were compared to the AI results and ground truth for each slide. We observed an overall HER2 positivity rate of 15% in our study cohort. Moderate agreement (Cohen’s κ 0.59) was observed between the ground truth and AI on IHC, with most discrepancies occurring between 0 and 1+ scores. Inter-observer agreement amongst pathologists was substantial (Fleiss´ κ 0.77) and pathologists’ agreement with AI scores was 80.6%. Substantial agreement of the AI with the ground truth (Cohen´s κ 0.80) was detected on ISH-stained slides, and the accuracy of AI was similar for the primary and metastatic tumors. We demonstrated the feasibility of a combined HER2 IHC and ISH AI workflow, with a Cohen’s κ of 0.94 when assessed in accordance with the ASCO/CAP recommendations.
Special Issue on “Advances in Image-Guided Diagnosis and Treatment of Abdominal Diseases”
Authors: Marra Paolo , Giurazza Francesco
Published: January 2023

This Special Issue is a collection of five scientific papers and five reviews concerning current topics in abdominal imaging with attention on the diagnosis and interventional management of specific diseases [...]
A Novel Computer-Aided Detection/Diagnosis System for Detection and Classification of Polyps in Colonoscopy
Authors: Tang Chia-Pei , Chang Hong-Yi , Wang Wei-Chun , Hu Wei-Xuan
Published: January 2023

Using a deep learning algorithm in the development of a computer-aided system for colon polyp detection is effective in reducing the miss rate. This study aimed to develop a system for colon polyp detection and classification. We used a data augmentation technique and conditional GAN to generate polyp images for YOLO training to improve the polyp detection ability. After testing the model five times, a model with 300 GANs (GAN 300) achieved the highest average precision (AP) of 54.60% for SSA and 75.41% for TA. These results were better than those of the data augmentation method, which showed AP of 53.56% for SSA and 72.55% for TA. The AP, mAP, and IoU for the 300 GAN model for the HP were 80.97%, 70.07%, and 57.24%, and the data increased in comparison with the data augmentation technique by 76.98%, 67.70%, and 55.26%, respectively. We also used Gaussian blurring to simulate the blurred images during colonoscopy and then applied DeblurGAN-v2 to deblur the images. Further, we trained the dataset using YOLO to classify polyps. After using DeblurGAN-v2, the mAP increased from 25.64% to 30.74%. This method effectively improved the accuracy of polyp detection and classification.
The Relationship between Intracranial Pressure and Visual Field Zones in Normal-Tension Glaucoma Patients
Authors: Stoskuviene Akvile , Siaudvytyte Lina , Januleviciene Ingrida , Vaitkus Antanas , Simiene Evelina , Bakstyte Viktorija , Ragauskas Arminas , Antman Gal , Siesky Brent , Harris Alon
Published: January 2023

Growing evidence suggests that intracranial pressure (ICP) plays an important role in the pathophysiology of glaucoma, especially in normal-tension glaucoma (NTG) patients. Controversial results exist about ICP’s relationship to visual field (VF) changes. With the aim to assess the relationship between ICP and VF zones in NTG patients, 80 NTG patients (age 59.5 (11.6) years) with early-stage glaucoma were included in this prospective study. Intraocular pressure (IOP) (Goldmann), visual perimetry (Humphrey) and non-invasive ICP (via a two-depth Transcranial Doppler, Vittamed UAB, Lithuania) were evaluated. Translaminar pressure difference (TPD) was calculated according to the formula TPD = IOP − ICP. The VFs of each patient were divided into five zones: nasal, temporal, peripheral, central, and paracentral. The average pattern deviation (PD) scores were calculated in each zone. The level of significance p < 0.05 was considered significant. NTG patients had a mean ICP of 8.5 (2.4) mmHg. Higher TPD was related with lower mean deviation (MD) (p = 0.01) and higher pattern standard deviation (PSD) (p = 0.01). ICP was significantly associated with the lowest averaged PD scores in the nasal VF zone (p < 0.001). There were no significant correlations between ICP and other VF zones with the most negative mean PD value. (p > 0.05). Further studies are needed to analyze the involvement of ICP in NTG management.
Risk of Myelopathy Following Second Local Treatment after Initial Irradiation of Spine Metastasis
Authors: Gales Laurentia , Mitrea Diana , Chivu Bogdan , Radu Adrian , Bocai Silvia , Stoica Remus , Dicianu Andrei , Mitrica Radu , Trifanescu Oana , Anghel Rodica , Serbanescu Luiza
Published: January 2023

Metastatic lesions of the spine occur in up to 40% of cancer patients and are a frequent source of pain and neurologic deficit due to cord compression. Palliative radiotherapy is the main first-intent local treatment in the form of single-fraction radiotherapy or fractionated courses. Reirradiation is a viable option for inoperable patients where spinal decompression is needed but with an increased risk of radiation-induced myelopathy (RM) and subsequent neurologic damage. This review summarizes reported data on local treatment options after initial irradiation in patients with relapsed spine metastasis and key dosimetric correlations between the risk of spinal cord injury and reirradiation technique, total dose, and time between treatments. The Linear Quadratic (LQ) model was used to convert all the published doses into biologically effective doses and normalize them to EQD2. For 3D radiotherapy, authors used cumulative doses from 55.2 Gy2/2 to 65.5 Gy2/2 EQD2 with no cases of RM mentioned. We found little evidence of RM after SBRT in the papers that met our criteria of inclusion, usually at the median reported dose to critical neural tissue around 93.5 Gy2/2. There is a lack of consistency in reporting the spinal cord dose, which leads to difficulty in pooling data.
Which Risk Factors and Colposcopic Patterns Are Predictive for High-Grade VAIN? A Retrospective Analysis
Authors: Iacobone Anna Daniela , Radice Davide , Guerrieri Maria Elena , Spolti Noemi , Grossi Barbara , Bottari Fabio , Boveri Sara , Martella Silvia , Vidal Urbinati Ailyn Mariela , Pino Ida , Franchi Dorella , Preti Eleonora Petra
Published: January 2023

Colposcopic patterns of Vaginal Intraepithelial Neoplasia (VAIN) are not definitively related to histological grade. The aim of the present study was to investigate any correlation between clinical and colposcopic features and the development of high-grade VAIN. Two hundred and fifty-five women diagnosed with VAIN (52 VAIN1, 55 VAIN2 and 148 VAIN3) at the European Institute of Oncology, Milan, Italy, from January 2000 to June 2022, were selected for a retrospective analysis. Multivariate logistic regression was performed to estimate the association of risk factors and colposcopic patterns with VAIN grade. Smoking was associated with the development of VAIN (34.1%, p = 0.01). Most women diagnosed with VAIN3 (45.3%, p = 0.02) had a previous history of hysterectomy for CIN2+. At multivariate analysis, colposcopic grade G2 (OR = 20.4, 95%CI: 6.67–61.4, p < 0.001), papillary lesion (OR = 4.33, 95%CI: 1.79–10.5, p = 0.001) and vascularity (OR = 14.4, 95%CI: 1.86–112, p = 0.01) were significantly associated with a greater risk of VAIN3. The risk of high-grade VAIN should not be underestimated in women with a history of smoking and previous hysterectomy for CIN2+, especially when colposcopic findings reveal vaginal lesions characterized by grade 2, papillary and vascular patterns. Accurate diagnosis is crucial for an optimal personalized management, based on risk factors, colposcopic patterns and histologic grade of VAIN.
A Narrative Review Discussing the Efficiency of Personalized Dosing Algorithm of Follitropin Delta for Ovarian Stimulation and the Reproductive and Clinical Outcomes
Authors: Doroftei Bogdan , Ilie Ovidiu-Dumitru , Anton Nicoleta , Marcu Olivia-Andreea , Scripcariu Ioana-Sadyie , Ilea Ciprian
Published: January 2023

Background: Follitropin delta is the third recombinant human follicle-stimulating hormone (r-hFSH) expressed in a host cell line of human fetal retinal origin that currently emphasizes that the actual tendency of administration is a personalized dosing algorithm based on the anti-Müllerian hormone (AMH) and body mass index (BMI) for ovarian stimulation. Methods: In this context, we aimed, in the present manuscript, to gather all available data published between 2018–2022 regarding the co-administration and administration of follitropin delta and the clinical outcomes reported following an in vitro fertilization (IVF). Results: Follitropin delta is non-inferior in contrast to its previously launched agents for ovarian stimulation, enhancing a similar-to-superior response reflected by both the reproductive and pregnancy outcomes in parallel with a low risk of ovarian hyperstimulation syndrome (OHSS), being well tolerated. The body weight and AMH level are factors that may influence the outcome in a patient. Despite controversy and results that refute these arguments on several occasions, follitropin delta exceeds the benefits of conventional dosing with either follitropin alfa or follitropin beta. Thus, all post hoc, derived analyses and subsets of patients that participated in subsequent studies support this statement. Conclusions: Despite the relatively limited spectrum of data in the current literature, most authors brought potent proof, supporting the subsequent use of this drug depending on the patient’s profile and overcoming ethnic-related limitations. Although others contradict these observations, this topic and drug possess substantial potential, which is why additional studies are mandatory to fill the existing gaps in our knowledge and expand these experiences at a larger scale supported by the obtained reproductive and clinical outcomes that clearly indicate an overcoming of all limitations.
Transcriptome Analysis Revealed Potential Neuro-Immune Interaction in Papillary Thyroid Carcinoma Tissues
Authors: Hu Haibei , Chen Qiang , Zheng Siqi , Du Shan , Ding Siqin , Lun Yongzhi
Published: January 2023

Background: A recent study reported that papillary thyroid carcinoma (PTC) was associated with increased adrenergic nerve density. Meanwhile, emerging evidence suggested that tumor-innervating nerves might play a role in shaping the tumor microenvironment. We aimed to explore the potential interaction between neuronal markers and tumor microenvironmental signatures through a transcriptomic approach. Methods: mRNA sequencing was conducted using five pairs of PTC and adjacent normal tissues. The Gene Set Variation Analysis (GSVA) was performed to calculate enrichment scores of gene sets related to tumor-infiltrating immune cells and the tumor microenvironment. The potential interaction was tested using the expression levels of a series of neuronal markers and gene set enrichment scores. Results: PTC tissues were associated with increased enrichment scores of CD8 T cells, cancer-associated fibroblasts, mast cells, and checkpoint molecules. The neuronal marker for cholinergic neurons was positively correlated with CD8 T cell activation, while markers for serotonergic and dopaminergic neurons showed an inverse correlation. Conclusion: Distinct neuronal markers exerted different correlations with tumor microenvironmental signatures. Tumor-innervating nerves might play a role in the formation of the PTC microenvironment.
Visual-Inertial Odometry Using High Flying Altitude Drone Datasets
Authors: George Anand , Koivumäki Niko , Hakala Teemu , Suomalainen Juha , Honkavaara Eija
Published: January 2023

Positioning of unoccupied aerial systems (UAS, drones) is predominantly based on Global Navigation Satellite Systems (GNSS). Due to potential signal disruptions, redundant positioning systems are needed for reliable operation. The objective of this study was to implement and assess a redundant positioning system for high flying altitude drone operation based on visual-inertial odometry (VIO). A new sensor suite with stereo cameras and an inertial measurement unit (IMU) was developed, and a state-of-the-art VIO algorithm, VINS-Fusion, was used for localisation. Empirical testing of the system was carried out at flying altitudes of 40–100 m, which cover the common flight altitude range of outdoor drone operations. The performance of various implementations was studied, including stereo-visual-odometry (stereo-VO), monocular-visual-inertial-odometry (mono-VIO) and stereo-visual-inertial-odometry (stereo-VIO). The stereo-VIO provided the best results; the flight altitude of 40–60 m was the most optimal for the stereo baseline of 30 cm. The best positioning accuracy was 2.186 m for a 800 m-long trajectory. The performance of the stereo-VO degraded with the increasing flight altitude due to the degrading base-to-height ratio. The mono-VIO provided acceptable results, although it did not reach the performance level of the stereo-VIO. This work presented new hardware and research results on localisation algorithms for high flying altitude drones that are of great importance since the use of autonomous drones and beyond visual line-of-sight flying are increasing and will require redundant positioning solutions that compensate for potential disruptions in GNSS positioning. The data collected in this study are published for analysis and further studies.
Accounting for Heterogeneity in Performance Evaluation of Norwegian Dairy and Crop-Producing Farms
Authors: Alem Habtamu
Published: January 2023

It is critical to analyze the performance of enterprises to achieve sustainable agricultural development. Several studies have been conducted to assess farm performance. However, the studies have been criticized for failing to account for farm heterogeneity (which is frequently unobserved) in their evaluation of Norwegian agricultural performance. Technically, a farm is efficient if it can produce a certain amount of output with the fewest possible inputs and no input waste. In this paper, efficiency scores are calculated using a production function with both a random intercept and a random slope parameter, addressing the issue of unobserved heterogeneity in stochastic frontier analysis. Using Norwegian dairy and crop farms as a case study, we demonstrate the viability of improving the agriculture industry and reducing resource waste. The case study was established on data collected from 5884 dairy farms and 1880 crop farms from the years 2000 to 2019. According to the empirical findings of the case study, dairy and crop producers used inefficient technologies and squandered production resources. If all farmers follow a sustainable and efficient path to produce agricultural output, they could increase output by 15–18%. Farmers must follow sustainable paths, and politicians must encourage farm experience exchange so that less efficient dairy and crop-producing farms can learn from the most efficient farms to achieve sustainable development.
Nonlinear Fiscal Multipliers in Saudi Arabia
Authors: AlMarzoqi Raja , Ben Slimane Sarra , Altamimi Saud
Published: January 2023

This paper presents an estimation of the fiscal multipliers for Saudi Arabia, conducted by applying the local projection (LP) method. It also presents an exploration of the non-linear features of fiscal multipliers. The findings showed that (i) consistent with earlier studies, fiscal multipliers are generally moderate; (ii) the investment spending multiplier is larger in magnitude than the current spending multiplier; (iii) the non-oil revenue multiplier is negative; (iv) the output response to fiscal shocks is larger during expansions; and (v) fiscal multipliers are stronger during a contractionary fiscal policy phase.
Producing Staged Videos for Teacher Education: Development and Content Validation of Video Scripts on the Topic of Handling Classroom Disruptions
Authors: Kilbury Maxie , Böhnke Anja , Thiel Felicitas
Published: January 2023

Video-based teacher training has become an important component of teacher education. A special form of instructional videos is scripted videos, also known as staged videos. They can be used to accomplish several didactic objectives and visualise problematic situations, such as severe classroom disruptions caused by specific behavioural motives, which are very difficult to videotape in a real classroom. However, reservations exist due to limited authenticity, and thus content validity of staged videos. This paper describes the process of a theory-led script development as the key role for authentic and valid scripts. Therefore, we refine four crucial criteria, relevant, engaging, challenging, and realistic, for staged videos dealing with classroom disruptions. We show the content–validation process with reference to the applied theory-led criteria. A key output of this study is a manual for the development of scripted videos which will be perceived as authentic, and which reach the intended cognitive demands. An expert validation and two evaluative studies with data from 274 and 70 preservice teachers confirm the success of the final products.
Long Short-Term Fusion Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting
Authors: Zeng Hui , Jiang Chaojie , Lan Yuanchun , Huang Xiaohui , Wang Junyang , Yuan Xinhua
Published: January 2023

Traffic flow forecasting, as one of the important components of intelligent transport systems (ITS), plays an indispensable role in a wide range of applications such as traffic management and city planning. However, complex spatial dependencies and dynamic changes in temporal patterns exist between different routes, and obtaining as many spatial-temporal features and dependencies as possible from node data has been a challenging task in traffic flow prediction. Current approaches typically use independent modules to treat temporal and spatial correlations separately without synchronously capturing such spatial-temporal correlations, or focus only on local spatial-temporal dependencies, thereby ignoring the implied long-term spatial-temporal periodicity. With this in mind, this paper proposes a long-term spatial-temporal graph convolutional fusion network (LSTFGCN) for traffic flow prediction modeling. First, we designed a synchronous spatial-temporal feature capture module, which can fruitfully extract the complex local spatial-temporal dependence of nodes. Second, we designed an ordinary differential equation graph convolution (ODEGCN) to capture more long-term spatial-temporal dependence using the spatial-temporal graph convolution of ordinary differential equation. At the same time, by integrating in parallel the ODEGCN, the spatial-temporal graph convolution attention module (GCAM), and the gated convolution module, we can effectively make the model learn more long short-term spatial-temporal dependencies in the processing of spatial-temporal sequences.Our experimental results on multiple public traffic datasets show that our method consistently obtained the optimal performance compared to the other baselines.
Digital Programmable Metasurface with Element-Independent Visible-Light Sensing
Authors: Jiang Xuqian , Ye Fuju , Tan Hongrui , Luo Sisi , Cui Haoyang , Chen Lei
Published: January 2023

The application of jointing multiple physical field sensing with electromagnetic (EM) wave manipulation is a hot research topic recently. Refined perception and unit-level independent regulation of metasurfaces still have certain challenges. In this paper, we propose a digital programmable metasurface that can adaptively achieve various EM functions by sensing the color changes of the incident light, which enables unit-level sensing and modulation. Integrating trichromatic sensors, FPGA, and algorithm onto the metasurface has established a metasurface architecture for electromagnetic scattering field modulation from complex optics to microwave wavelengths, which enables a wide variety of light sensing for modulation. The metasurface integrated with PIN diodes and trichromatic color sensors forms a complete intelligent system of adaptive and reconfigurable coding patterns, within the pre-designed control of FPGA. We fabricated the metasurface using standard printed circuit board (PCB) technology and measured the metasurface in far-fields. The measurement results show good agreement with the simulation results, verifying our design. We envision that the proposed programmable metasurface with visible light sensing will provide a new dimension of manipulation from this perspective.
Flatness-Based Backstepping Antisway Control of Underactuated Crane Systems under Wind Disturbance
Authors: Yu Zian , Niu Wangqiang
Published: January 2023

A control method that combines trajectory planning and backstepping is proposed for the antisway problem of underactuated overhead cranes under wind disturbance. First, a set of flat outputs is proposed so that the crane system dynamics can be represented by each order of flat outputs. Sufficient relevant constraints are given to ensure that the trolley can arrive at the desired position in a limited time under variable rope lengths, and that the swing angle can be suppressed when the payload is lifted or lowered during operation. The planned trajectory is obtained by solving for the optimal parameters of the flat output. Next, to reduce the deviation caused by wind disturbance on the actual control of the trajectory, a tracking controller is designed. Because the system output space and flat output space are differentiable homeomorphisms, the backstepping controller constructed based on the flat output can indirectly control the system output, which makes the backstepping method applicable to underactuated cranes. The simulation results show that the proposed method is effective and has strong robustness.
Analysis of Series-Parallel (SP) Compensation Topologies for Constant Voltage/Constant Current Output in Capacitive Power Transfer System
Authors: Li Shiqi , Tang Chunlin , Cheng Hao , Wang Zhulin , Luo Bo , Jiang Jing
Published: January 2023

This paper analyzed the four series-parallel (SP) compensation topologies to achieve constant current (CC) and voltage (CV) output characteristics and zero phase angle (ZPA) input conditions with fewer compensation components in the capacitive power transfer (CPT) system. There are three main contributions. Firstly, the universal methodology of SP compensation topologies was constructed to achieve CC, CV output, and ZPA conditions. Secondly, four specific SP compensation topologies were investigated and summarized, including double-sided LC, double-sided CL, CL−LC, and LC−CL topologies. Their input–output characteristics are provided, and system efficiency is analyzed. Thirdly, the CL−LC and LC−CL topologies were proposed to realize ZPA conditions under CC and CV output without any external regulating circuit. A CV output LC−CL experiment prototype was implemented to validate the theoretical analysis.
Machine-Learning-Based Scoring System for Antifraud CISIRTs in Banking Environment
Authors: Srokosz Michal , Bobyk Andrzej , Ksiezopolski Bogdan , Wydra Michal
Published: January 2023

The number of fraud occurrences in electronic banking is rising each year. Experts in the field of cybercrime are continuously monitoring and verifying network infrastructure and transaction systems. Dedicated threat response teams (CSIRTs) are used by organizations to ensure security and stop cyber attacks. Financial institutions are well aware of this and have increased funding for CSIRTs and antifraud software. If the company has a rule-based antifraud system, the CSIRT can examine fraud cases and create rules to counter the threat. If not, they can attempt to analyze Internet traffic down to the packet level and look for anomalies before adding network rules to proxy or firewall servers to mitigate the threat. However, this does not always solve the issues, because transactions occasionally receive a “gray” rating. Nevertheless, the bank is unable to approve every gray transaction because the number of call center employees is insufficient to make this possible. In this study, we designed a machine-learning-based rating system that provides early warnings against financial fraud. We present the system architecture together with the new ML-based scoring extension, which examines customer logins from the banking transaction system. The suggested method enhances the organization’s rule-based fraud prevention system. Because they occur immediately after the client identification and authorization process, the system can quickly identify gray operations. The suggested method reduces the amount of successful fraud and improves call center queue administration.
Unidirectional Finite Control Set-Predictive Torque Control of IPMSM Fed by Three-Level NPC Inverter with Simplified Voltage-Vector Lookup Table
Authors: Alsofyani Ibrahim Mohd , Halabi Laith M.
Published: January 2023

This paper proposes a unidirectional finite control set-predictive toque control (UFCS-PTC) method for a three-level neutral-point-clamped (3L-NPC) inverter fed interior permanent magnet synchronous motor (IPMSM). The proposed algorithm can lower the complexity of PTC fed by 3L-NPC by reducing the number of admissible voltage vectors (VVs) effectively. The candidate VVs are restricted within 60° of the voltage space voltage diagram (VSVD), which is the nearest to the flux trajectory for each 60° flux sector. After the segmentation of the VSVD and flux trajectory, the proposed method can keep VVs in one direction during the prediction process, which can result in significant torque/flux reduction. Therefore, the UFCS-PTC can reduce the number of admissible VVs from twenty-seven to six while achieving excellent steady-state performance in terms of reduced flux and torque ripples. Additionally, the proposed method eliminates the need for weighting factor calculation for neutral point voltage associated with a 3L-NPC inverter. The UFCS-PTC of IPMSM also has other features, such as improved balancing capability of the DC-link capacitors’ voltage, small computation time due to the reduced number of admissible voltage vectors considered in the cost function, and easy implementation. The effectiveness of the proposed method is verified through experimental results.
End-to-End Underwater Acoustic Communication Based on Autoencoder with Dense Convolution
Authors: Xie Fangtong , Zhu Yunan , Wang Biao , Wang Wu , Jin Pian
Published: January 2023

To address the problems of the high complexity and poor bit error rate (BER) performance of traditional communication systems in underwater acoustic environments, this paper incorporates the theory of deep learning into a conventional communication system and proposes data-driven underwater acoustic filter bank multicarrier (FBMC) communications based on convolutional autoencoder networks. The proposed system is globally optimized by two one-dimensional convolutional (Conv1D) modules at the transmitter and receiver, it realizes signal reconstruction through end-to-end training, it effectively avoids the inherent imaginary interference of the system, and it improves the reliability of the communication system. Furthermore, dense-block modules are constructed between Conv1D layers and are connected across layers to achieve feature reuse in the network. Simulation results show that the BER performance of the proposed method outperforms that of the conventional FBMC system with channel equalization algorithms such as least squares (LS) estimation and virtual time reversal mirrors (VTRM) under the measured channel conditions at a certain moment in the Qingjiang River.