bluuebunny/crossref_metadata_2025 huggingface dataset:
ROADLANE—The Modular Framework to Support Recognition Algorithms of Road Lane Markings
Authors: Franco Felipe , Santos Max Mauro Dias , Yoshino Rui Tadashi , Yoshioka Leopoldo Rideki , Justo João Francisco
Published: November 2021

One of the main actions of the driver is to keep the vehicle in a road lane within its markings, which could be aided with modern driver-assistance systems. Forward digital cameras in vehicles allow deploying computer vision strategies to extract the road recognition characteristics in real-time to support several features, such as lane departure warning, lane-keeping assist, and traffic recognition signals. Therefore, the road lane marking needs to be recognized through computer vision strategies providing the functionalities to decide on the vehicle’s drivability. This investigation presents a modular architecture to support algorithms and strategies for lane recognition, with three principal layers defined as pre-processing, processing, and post-processing. The lane-marking recognition is performed through statistical methods, such as buffering and RANSAC (RANdom SAmple Consensus), which selects only objects of interest to detect and recognize the lane markings. This methodology could be extended and deployed to detect and recognize any other road objects.
Ovarian Masses-Applicable IOTA ADNEX Model versus Morphological Findings for Accurate Diagnosis and Treatment
Authors: Butureanu Tudor , Socolov Demetra , Matasariu Daniela Roxana , Ursache Alexandra , Apetrei Ana-Maria , Dumitrascu Irina , Vasilache Ingrid , Rudisteanu Dorina , Boiculese Vasile Lucian , Lozneanu Ludmila
Published: November 2021

A common problem in gynecological practice is the differential diagnosis of the ovarian masses. The clinician must apply the IOTA (International Ovarian Tumor Analysis) ADNEX (Assessment of Different Neoplasia in the Adnexa) model criteria to evaluate the risk of benign, borderline or malignant tumors. The aim of this study was to verify if the IOTA ADNEX model is a practical tool to be used before surgery and if there is a significant difference between IOTA ADNEX criteria and histological findings. A prospective single center study was performed between January 2017 and December 2019 in Obstetrics and Gynecology Hospital “Cuza-Voda”, Iasi, Romania. The study included 230 patients between 17 and 74 years old diagnosed with persistent adnexal masses. We applied the IOTA ADNEX model protocol predicting the risk of benign, borderline or malignant masses. The golden standard remains the histological diagnosis of the surgically removed mass. The patients that had been diagnosed using ultrasonography with persistent adnexal masses between 30 and 291 mm were operated on in our clinic. In our study. the majority of patients had benign ovarian tumor mass, these being 223 (96.96%) patients, from whom, according to IOTA ADNEX protocol, the correspondence was: 91.8–99.7% at risk of benign tumors, 0.3–4.5% at risk of borderline tumors and 0.3–8.2% at risk of malignant masses. Unexpected findings were obtained from the malignant group that included five patients (2.17%) with the following correspondence: 96.1–99% at risk of benign tumors, 0.6–2.4% at risk of borderline tumors and 1–3.9% at risk of malignant masses. After applying the IOTA ADNEX model criteria, the patients with a suspicion of malignant disease were correctly guided towards surgical treatment in an oncological center. In our hospital, surgical treatment was only proposed to those patients with high suspicion of benign masses.
Screening Support System Based on Patient Survey Data—Case Study on Classification of Initial, Locally Collected COVID-19 Data
Authors: Henzel Joanna , Tobiasz Joanna , Kozielski Michał , Bach Małgorzata , Foszner Paweł , Gruca Aleksandra , Kania Mateusz , Mika Justyna , Papiez Anna , Werner Aleksandra , Zyla Joanna , Jaroszewicz Jerzy , Polanska Joanna , Sikora Marek
Published: November 2021

New diseases constantly endanger the lives of populations, and, nowadays, they can spread easily and constitute a global threat. The COVID-19 pandemic has shown that the fight against a new disease may be difficult, especially at the initial stage of the epidemic, when medical knowledge is not complete and the symptoms are ambiguous. The use of machine learning tools can help to filter out those sick patients who do not need to be tested for spreading the pathogen, especially in the event of an overwhelming increase in disease transmission. This work presents a screening support system that can precisely identify patients who do not carry the disease. The decision of the system is made on the basis of patient survey data that are easy to collect. A case study on a data set of symptomatic COVID-19 patients shows that the system can be effective in the initial phase of the epidemic. The case study presents an analysis of two classifiers that were tuned to achieve an assumed acceptable threshold of negative predictive values during classification. Additionally, an explanation of the obtained classification models is presented. The explanation enables the users to understand the basis of the decision made by the model. The obtained classification models provide the basis for the DECODE service, which could serve as support in screening patients with COVID-19 disease at the initial stage of the pandemic. Moreover, the data set constituting the basis for the analyses performed is made available to the research community. This data set, consisting of more than 3000 examples, is based on questionnaires collected at a hospital in Poland.
Fine-Grained Named Entity Recognition Using a Multi-Stacked Feature Fusion and Dual-Stacked Output in Korean
Authors: Kim Hongjin , Kim Harksoo
Published: November 2021

Named entity recognition (NER) is a natural language processing task to identify spans that mention named entities and to annotate them with predefined named entity classes. Although many NER models based on machine learning have been proposed, their performance in terms of processing fine-grained NER tasks was less than acceptable. This is because the training data of a fine-grained NER task is much more unbalanced than those of a coarse-grained NER task. To overcome the problem presented by unbalanced data, we propose a fine-grained NER model that compensates for the sparseness of fine-grained NEs by using the contextual information of coarse-grained NEs. From another viewpoint, many NER models have used different levels of features, such as part-of-speech tags and gazetteer look-up results, in a nonhierarchical manner. Unfortunately, these models experience the feature interference problem. Our solution to this problem is to adopt a multi-stacked feature fusion scheme, which accepts different levels of features as its input. The proposed model is based on multi-stacked long short-term memories (LSTMs) with a multi-stacked feature fusion layer for acquiring multilevel embeddings and a dual-stacked output layer for predicting fine-grained NEs based on the categorical information of coarse-grained NEs. Our experiments indicate that the proposed model is capable of state-of-the-art performance. The results show that the proposed model can effectively alleviate the unbalanced data problem that frequently occurs in a fine-grained NER task. In addition, the multi-stacked feature fusion layer contributes to the improvement of NER performance, confirming that the proposed model can alleviate the feature interference problem. Based on this experimental result, we conclude that the proposed model is well-designed to effectively perform NER tasks.
The Melt Enthalpy of Pu6Fe
Authors: Coe Joshua D. , Anderson William W. , Tobash Paul H.
Published: November 2021

Schwartz, et al., previously reported calorimetry measurements conducted on a Pu-Pu6Fe mixture, from which they derived a melt enthalpy of 31.2 J/g (46.6 kJ/mol) for Pu6Fe. This was the first—and remains the only—such value to appear in the literature. We reanalyze those results in light of two contributions to the measured heat flow not considered in the original report: the melt enthalpy of the excess Pu and the subsequent heating of the liquid mixture. These corrections yield a revised value of 24.4 J/g (36.3 kJ/mol), which we show to be consistent with the melt enthalpy of U6Fe.
An Explainable Artificial Intelligence Model for Detecting Xenophobic Tweets
Authors: Pérez-Landa Gabriel Ichcanziho , Loyola-González Octavio , Medina-Pérez Miguel Angel
Published: November 2021

Xenophobia is a social and political behavior that has been present in our societies since the beginning of humanity. The feeling of hatred, fear, or resentment is present before people from different communities from ours. With the rise of social networks like Twitter, hate speeches were swift because of the pseudo feeling of anonymity that these platforms provide. Sometimes this violent behavior on social networks that begins as threats or insults to third parties breaks the Internet barriers to become an act of real physical violence. Hence, this proposal aims to correctly classify xenophobic posts on social networks, specifically on Twitter. In addition, we collected a xenophobic tweets database from which we also extracted new features by using a Natural Language Processing (NLP) approach. Then, we provide an Explainable Artificial Intelligence (XAI) model, allowing us to understand better why a post is considered xenophobic. Consequently, we provide a set of contrast patterns describing xenophobic tweets, which could help decision-makers prevent acts of violence caused by xenophobic posts on Twitter. Finally, our interpretable results based on our new feature representation approach jointly with a contrast pattern-based classifier obtain similar classification results than other feature representations jointly with prominent machine learning classifiers, which are not easy to understand by an expert in the application area.
The Sonic Resonance Method and the Impulse Excitation Technique: A Comparison Study
Authors: Húlan Tomáš , Obert Filip , Ondruška Ján , Štubňa Igor , Trník Anton
Published: November 2021

In this study, resonant frequencies of flexurally vibrating samples were measured using the sonic resonant method (SRM) and the impulse excitation technique (IET) to assess the equivalency of these two methods. Samples were made from different materials and with two shapes (prism with rectangular cross-section and cylinder with circular cross-section). The mean values and standard deviations of the resonant frequencies were compared using the t-test and the F-test. The tests showed an equivalency of both methods in measuring resonant frequency. The differences between the values measured using SRM and IET were not significant. Graphically, the relationship between the resonant frequencies is a line with a slope of 0.9993 ≈ 1.
TDCMR: Triplet-Based Deep Cross-Modal Retrieval for Geo-Multimedia Data
Authors: Song Jiagang , Lin Yunwu , Song Jiayu , Yu Weiren , Zhang Leyuan
Published: November 2021

Mass multimedia data with geographical information (geo-multimedia) are collected and stored on the Internet due to the wide application of location-based services (LBS). How to find the high-level semantic relationship between geo-multimedia data and construct efficient index is crucial for large-scale geo-multimedia retrieval. To combat this challenge, the paper proposes a deep cross-modal hashing framework for geo-multimedia retrieval, termed as Triplet-based Deep Cross-Modal Retrieval (TDCMR), which utilizes deep neural network and an enhanced triplet constraint to capture high-level semantics. Besides, a novel hybrid index, called TH-Quadtree, is developed by combining cross-modal binary hash codes and quadtree to support high-performance search. Extensive experiments are conducted on three common used benchmarks, and the results show the superior performance of the proposed method.
Environmental Restoration of Metal-Contaminated Soils
Authors: Chiampo Fulvia , Zacchini Massimo
Published: November 2021

The growing industrialization of the last two centuries has improved life to a great extent in the countries where it occurred [...]
A Modified Wavenumber Algorithm of Multi-Layered Structures with Oblique Incidence Based on Full-Matrix Capture
Authors: Yu Bei , Jin Haoran , Mei Yujian , Chen Jian , Wu Eryong , Yang Keji
Published: November 2021

Full-matrix capture (FMC)-based ultrasonic imaging provides good sensitivity to small defects in non-destructive testing and has gradually become a mainstream research topic. Many corresponding algorithms have been developed, e.g., the total focusing method (TFM). However, the efficiency of the TFM is limited, especially in multi-layered structures. Although the appearance of wavenumber algorithms, such as extended phase-shift migration (EPSM) methods, has improved imaging efficiency, these methods cannot be applied to cases with oblique incidence. Therefore, a modified wavenumber method for full-matrix imaging of multi-layered structures with oblique array incidence is proposed. This method performs a coordinate rotation in the frequency domain to adapt it to the oblique incidence. It then utilizes wave-field extrapolation to migrate the transmitting and receiving wave field to each imaging line, and a correlation imaging condition is used to reconstruct a total focused image. The proposed method can deal with any incident angle without precision loss. Moreover, it inherits the computational efficiency advantages of the wavenumber algorithms. The simulation and experimental results show that the proposed method performs better in terms of accuracy and efficiency than the TFM. Specifically, it is nearly 60 times faster than the TFM when processing an FMC dataset with a size of 4096 × 64 × 64.
Removal of Nitrogen and Phosphorus in Synthetic Stormwater Runoff by a Porous Asphalt Pavement System with Modified Zeolite Powder Porous Microsphere as a Filter Column
Authors: Luo Hui , He Baojie , Zhang Wenhao , Jing Zhaoqian
Published: November 2021

Porous asphalt pavement (PAP) system is a widely used treatment measure in sustainable stormwater management and groundwater recharge, but their variable performance in nitrogen (N) and phosphorus (P) removal requires further reinforcement prior to widespread uptake. Two laboratory-scale PAP systems were developed by comparing limestone bedding and zeolite incorporated into modified zeolite powder porous microsphere (MZP-PM) as a filter column under a typical rainfall. The PAP system of zeolite bedding incorporated into MZP-PM (a weight less than 5% of zeolite) removed 74.5% to 90.6% of ammonium (NH4+-N) and 72.9% to 92.4% of total phosphate (TP) from the influent, as compared with 25.7% to 62.7% of NH4+-N and 32.6% to 56.4% of TP by that of the limestone as bed material. This improvement was presumably due to MZP-PM’s high adsorption capacity and surface complexation. The formation of ≡(La)(OH)PO2 was verified to be the dominant pathway for selective phosphate adsorption by MZP-PM and ion-exchange was proved to be the main removal process for ammonium. This study provides promising results for improving N and P removal by modifying a porous asphalt pavement system to include an MZP-PM adsorbent column as a post-treatment.
Few-Shot Charge Prediction with Data Augmentation and Feature Augmentation
Authors: Wang Peipeng , Zhang Xiuguo , Cao Zhiying
Published: November 2021

The task of charge prediction is to predict the charge based on the fact description. Existing methods have a good effect on the prediction of high-frequency charges, but the prediction of low-frequency charges is still a challenge. Moreover, there exist some confusing charges that have relatively similar fact descriptions, which can be easily misjudged. Therefore, we propose a model with data augmentation and feature augmentation for few-shot charge prediction. Specifically, the model takes the text description as the input and uses the Mixup method to generate virtual samples for data augmentation. Then, the charge information heterogeneous graph is introduced, and a novel graph convolutional network is designed to extract distinguishability features for feature augmentation. A feature fusion network is used to effectively integrate the charge graph knowledge into the fact to learn semantic-enhanced fact representation. Finally, the semantic-enhanced fact representation is used to predict the charge. In addition, based on the distribution of each charge, a category prior loss function is designed to increase the contribution of low-frequency charges to the model optimization. The experimental results on real-work datasets prove the effectiveness and robustness of the proposed model.
Zero-Emission of Palm Oil Mill Effluent Final Discharge Promoted Bacterial Biodiversity Rebound in the Receiving Water System
Authors: Mohamad-Zainal Noor Shaidatul Lyana , Ramli Norhayati , Zolkefli Nurhasliza , Jamari Nur Azyani , Mustapha Nurul Asyifah , Hassan Mohd Ali , Maeda Toshinari
Published: November 2021

Zero-emission technology for palm oil mill effluent (POME) has led to a breakthrough in the palm oil industry in relation to the goal of sustainable development. However, there are limited resources on how this technology has affected the bacterial community in the receiving river that has previously been polluted with POME final discharge. Thus, the current study assessed the recoverability of the unexplored bacterial community in the receiving water of a constructed river water system post-zero emission of POME final discharge. An artificial river water system was constructed in this study, where the viability status and the composition of the bacterial community were assessed for 15 days using a flow cytometry-based assay and high-throughput sequencing by Illumina MiSeq, respectively. The zero-emission of POME final discharge reduced not only the physicochemical properties and nutrient contents of the receiving water, but also the bacterial cells’ viability from 40.3% to 24.5% and shifted the high nucleic acid (HNA) to low nucleic acid (LNA) content (38.7% to 34.5%). The proposed POME bacterial indicators, Alcaligenaceae and Chromatiaceae were not detectable in the rainwater (control) but were detected in the artificial river water system after the introduction of POME final discharge at the compositions of 1.0–1.3% and 2.2–5.1%, respectively. The implementation of a zero-emission system decreased the composition of Chromatiaceae from 2.2% on day 8 until it was undetectable on day 15, while Alcaligenaceae was continuously reduced from 1.2% to 0.9% within that similar time frame. As indicated by principal coordinate (PCO) analysis, the reductions in biological oxygen demand (BOD5) would further diminish the compositions of these bioindicators. The zero-emission of POME final discharge has demonstrated its efficacy, not only in reducing the polluting properties, but also in the bacterial biodiversity rebound in the affected water system.
Design and Development of a Self-Diagnostic Mobile Application for Learning Progress in Non-Face-to-Face Practice Learning
Authors: Kim Semin , Mun Hyung-Jin
Published: November 2021

Due to COVID-19, non-F2F (non-face-to-face) learning is being conducted in educational sites around the world. Unlike theoretical subjects, which have a variety of applicable non-F2F learning content, in practical subjects, learners may undergo many difficulties due to many learning activities. Therefore, this research tries to design and develop a mobile application that allows learners to perform a self-diagnostic on their learning progress. In this research, we conducted a mobile application usability evaluation for 36 students who participated in non-F2F Arduino practice learning. To this end, we applied the ADDIE (Analysis, Design, Development, Implement, and Evaluation) model to develop a self-diagnostic mobile application for students’ learning progress according to the learning content. The research tool modified and distributed the question item appropriate for this subject’s study for the mobile usability evaluation that was used in the previous study. This research applied the ADDIE model to analyze the characteristics of students and learning contents, including designed learning contents, database, menu structure, developed learning contents, and mobile application. After using this in non-F2F practice learning for 15 weeks, a mobile application usability evaluation was conducted. As a result of the study, due to receiving usability scores between 3.53 and 4.42, it was found that the learning progress self-diagnostic in non-F2F practice learning was essential and that mobile applications were useful in non-F2F practice learning. Additionally, 33 out of 36 students responded that it would be useful for their learning if they actively used it in other subjects as well. We have found that leveraging self-diagnostic mobile applications through the mobile application usability evaluation tool can be useful for non-F2F practice learning. Additionally, it is expected to be useful for non-F2F practice learning if additional research is conducted on other factors as well such as teaching presence, online learning engagement, and learning flow in the future.
Evaluating Biosedimentation for Strength Improvement in Acidic Soil
Authors: Saad Ahmed Hassan , Nahazanan Haslinda , Yusoff Zainuddin Bin Md , Mustafa Muskhazli , Elseknidy Mohamed Hamdy , Mohammed Angham Ali
Published: November 2021

Marine clay soils are problematic soils in the construction industry when they are subjected to construction loads. When these soils are loaded, they lose their structure. This leads to the soil being unable to withstand loads of any magnitude without exhibiting significant, permanent deformations. In order to stabilize the marine soil, new methods for soil improvement were built upon biogrouting by incorporating physical, biological and chemical treatments into the soil. However, the biggest challenge of this method is the bacteria migration through the soil medium. To overcome this issue, the electrokinetic phenomenon can be utilized alongside biogrouting to prevent the bacteria migration. In this regard, the present study applied electrobiogrouting stabilization to investigate the improvement of acidic marine clay soil with a pH of 3.69. To accomplish this, two large-scale physical models with dimensions of 500 × 300 × 1200 mm were fabricated to examine the influence of two different treated distances between the inlet and outlet—450 mm (D45) and 600 mm (D60)—on the stability of the treated soil. It was observed that the shear strength of the treated soil improved significantly. The shear strength at the D45 treated distance increased from 3.65 kPa (untreated soil) to 28.14 kPa (treated soil). However, the strength increased by increasing the treated distance. In addition, compressibility and soil electrical conductivity were reduced significantly, and the Atterberg limits were significantly enhanced from OH to OL. The reasons for the enhancement of treated soil were the formation of CaCO3, which filled the soil voids, and that the water content was reduced. To address issues with marine clay soil, this study aims to minimize the high cost of a special foundation system and the use of non-environmentally friendly materials such as calcium-based binders, aside from the reduction of deformations caused by loading. The findings of this study can be used for acidic soils and the improvement of soil’s geotechnical behavior in general.
Modeling and Evaluation of a Novel Hybrid-Driven Compliant Hand Exoskeleton Based on Human-Machine Coupling Model
Authors: Meng Qiaoling , Shen Zhijia , Nie Zhiyang , Meng Qingyun , Wu Zhiyu , Yu Hongliu
Published: November 2021

This paper presents the modeling design method for a novel hybrid-driven compliant hand exoskeleton based on the human-machine coupling model for the patients who have requirements on training and assisting. Firstly, the human-machine coupling model is established based on the kinematics characteristics of human fingers and the Bernoulli beam formula. On this basis, the variable stiffness flexible hinge (VSFH) is used to drive the finger extension and the cable-driven mechanism is used to implement the movement of the finger flexion. Here, a hand orthosis is designed in the proposed hand exoskeleton to act as the base and maintain the function position of the hand for patients with hand dysfunction. Then, a final design prototype is fabricated to evaluate the proposed modeling method. In the end, a series of experiments based on the prototype is proceeded to evaluate its capabilities on stretching force for extension, bio-imitability, finger flexion capability, and fingertip force. The results show that the prototype has a significant improvement in all aspects of the ability mentioned above, and has good bionics. The proposed design method can be utilized to implement the rapid design of the hybrid-driven compliant hand exoskeleton with the changed requirements. The novel modeling method can be easily applied in personalized design in rehabilitation engineering.
Improvement of Porous GaN-Based UV Photodetector with Graphene Cladding
Authors: Mohammed Furqan Khairi , Beh Khi Poay , Ramizy Asmiet , Ahmed Naser M. , Yam Fong Kwong , Hassan Zainuriah
Published: November 2021

This work presents the role of graphene in improving the performance of a porous GaN-based UV photodetector. The porous GaN-based photodetector, with a mean pore diameter of 35 nm, possessed higher UV sensitivity, about 95% better compared to that of the as-received (non-porous) photodetector. In addition, it exhibits a lower magnitude of leakage current at dark ambient, about 70.9 μA, compared to that of the as-received photodetector with 13.7 mA. However, it is also highly resistive in nature due to the corresponding electrochemical process selectively dissolute doped regions. Herein, two types of graphene, derived from CVD and the electrochemical exfoliation (EC) process, were cladded onto the porous GaN region. The formation of a graphene/porous GaN interface, as evident from the decrease in average distance between defects as determined from Raman spectroscopy, infers better charge accumulation and conductance, which significantly improved UV sensing. While the leakage current shows little improvement, the UV sensitivity was greatly enhanced, by about 460% and 420% for CVD and EC cladded samples. The slight difference between types of graphene was attributed to the coverage area on porous GaN, where CVD-grown graphene tends to be continuous while EC-graphene relies on aggregation to form films.
Chemical Composition of Hexane-Extracted Plectranthus amboinicus Leaf Essential Oil: Maximizing Contents on Harvested Plant Materials
Authors: Ashaari Nur Suhanawati , Mohamad Nurul Elyani , Afzinizam Amirul Hafizin , Ab. Rahim Mohd-Hairul , Lai Kok Song , Ong Abdullah Janna
Published: November 2021

Plectranthus amboinicus (Lour.) Spreng, also known locally as “Bangun-bangun”, is an aromatic medicinal herb known for its therapeutic and nutritional properties attributed to its terpenoid-rich phytochemicals. Information to assist in initiating appropriate harvesting time to maximize the yield of targeted chemicals in harvested plant tissues remains an issue that is seldom highlighted. This study reports on the essential oil distribution in P. amboinicus leaves, and total phenolic and flavonoid contents, in addition to GC-MS analysis of hexane extracts of the leaf samples collected at various times throughout the day. The influence of environmental factors on γ-terpinene, p-cymene, carvacrol, and thymoquinone are also discussed. Oil Red O staining showed the highest oil deposition at 2 p.m., which was consistent with the phenolic and flavonoid contents of this plant. GC-MS analysis of the leaf extract showed carvacrol (47.00–60.00%), γ-terpinene (8.00–10.00%), caryophyllene (~6.00%), p-cymene (4.90–6.50%), trans-α-bergamotene (4.70–5.00%), and thymoquinone (3.30–5.60%) were the major components of this plant. Interestingly, thymoquinone, a phytochemical associated with Nigella sativa, was also detected in this hexane-extracted sample with maximum accumulation during midday and a decrease at night, which could be due to the lower temperature and dimmer light conditions. The chemical polymorphism in the oil content indicated that environmental factors such as light exposure and temperature should be considered during harvesting to ensure consistent quality of the phytochemicals extracted from the plant materials. This study indicates that oversight in selecting plant materials might compromise the yield of quality phytochemicals extracted from harvested tissues.
Transport of Water Vapor from Tropical Cyclones to the Upper Troposphere
Authors: Plotnik Tair , Price Colin , Saha Joydeb , Guha Anirban
Published: November 2021

This paper investigates the influence of tropical cyclones on water vapor concentrations in the upper atmosphere above these storms. We use independent data sets of tropical storm intensity, water vapor and lightning activity to investigate this relationship. Water vapor in the upper troposphere is a key greenhouse gas, with direct impacts on surface temperatures. Both the amount and altitude of water vapor impact the radiative balance and the greenhouse effect of the atmosphere. The water vapor enters the upper troposphere through deep convective storms, often associated with lightning activity. The intensity of the lightning activity represents the intensity of the convection in these storms, and hence the amount of water vapor transported aloft. In this paper, we investigate the role of tropical cyclones on the contribution of water vapor to the upper atmosphere moistening. Tropical cyclones are the largest most intense storms on Earth and can last for up to two weeks at a time. There is also evidence that the intensity of tropical cyclones is increasing, and will continue to increase, due to global warming. In this study we find that the maximum moistening of the upper atmosphere occurs at the 200 hPa level (~12 km altitude), with a lag of 1–2 days after the maximum sustained winds in the tropical cyclone. While the water vapor peaks after the maximum of the storm intensity, the lightning activity peaks before the maximum intensity of the storms, as shown previously. We show here that the absolute amount of water vapor in the upper troposphere above tropical storms increases linearly with the intensity of the storms. For every 10 hPa decrease in the minimum pressure of tropical storms, the specific humidity increases around 0.2 g/kg at the 200 hPa level.
Passive versus Active Transport of Saharan Dust Aerosols by African Easterly Waves
Authors: Grogan Dustin F. P. , Nathan Terrence R.
Published: November 2021

Theory and modeling are combined to reveal the physical and dynamical processes that control Saharan dust transport by amplifying African easterly waves (AEWs). Two cases are examined: active transport, in which the dust is radiatively coupled to the circulation; passive transport, in which the dust is radiatively decoupled from the circulation. The theory is built around a dust conservation equation for dust-coupled AEWs in zonal-mean African easterly jets. The theory predicts that, for both the passive and active cases, the dust transports will be largest where the zonal-mean dust gradients are maximized on an AEW critical surface. Whether the dust transports are largest for the radiatively passive or radiatively active case depends on the growth rate of the AEWs, which is modulated by the dust heating. The theoretical predictions are confirmed via experiments carried out with the Weather Research and Forecasting model, which is coupled to a dust conservation equation. The experiments show that the meridional dust transports dominate in the passive case, while the vertical dust transports dominate in the active case.
Spatial and Time Warping for Gauge Adjustment of Rainfall Estimates
Authors: Le Coz Camille , Heemink Arnold , Verlaan Martin , van de Giesen Nick
Published: November 2021

Many satellite-based estimates use gauge information for bias correction. In general, bias-correction methods are focused on the intensity error and do not explicitly correct possible position or timing errors. However, position and timing errors in rainfall estimates can also lead to errors in the rainfall occurrence or the intensity. This is especially true for localized rainfall events such as the convective rainstorms occurring during the rainy season in sub-Saharan Africa. We investigated the use of warping to correct such errors. The goal was to gauge-adjust satellite-based estimates with respect to the position and the timing of the rain event, instead of its intensity. Warping is a field-deformation method that transforms an image into another one. We compared two methods, spatial warping focusing on the position errors and time warping for the timing errors. They were evaluated on two case studies: a synthetic rainfall event represented by an ellipse and a rain event in southern Ghana during the monsoon season. In both cases, the two warping methods reduced significantly the respective targeted (position or timing) errors. In the southern Ghana case, the average position error was decreased by about 45 km by the spatial warping and the average timing error was decreased from more than 1 h to 0.2 h by the time warping. Both warping methods also improved the continuous statistics on the intensity: the correlation went from 0.18 to at least 0.62 after warping in the southern Ghana case. The spatial warping seems more interesting because of its positive impact on both position and timing errors.
Observational Analysis of a Wind Gust Event during the Merging of a Bow Echo and Mini-Supercell in Southeastern China
Authors: Zheng Hui , Zhao Yuchun , Huang Yipeng , Zhang Wei , Luo Changrong , Wei Ming , Qiu Xinfa
Published: November 2021

The merging of a fast-moving bow echo with a convective cell of a hook-echo signature was studied by using polarimetric radar detections. Gusts with wind speeds near 35 m s−1 were recorded by the surface station, which caused significant damage. A convective cell with a mesovortex signature, which is hereafter referred to as a mini-supercell, was observed over the northeast of the bow echo before the convective merging. It was found that the mesovortex possessed cyclonic circulation and resembled a supercell-like feature. The merging of the bow echo and the mini-supercell strengthened the updraft near the apex of the bow echo. The enhanced updraft was also demonstrated by the appearance of a differential reflectivity (ZDR) column with a topmost height of 4 km above the melting layer (~4 km). The bow was separated into northern and southern sectors after merging with the mini-supercell, leading to the gusty wind over the surface of the south sector.
Biological Crusts to Increase Soil Carbon Sequestration: New Challenges in a New Environment
Authors: Duran Paola , Mora María de la Luz , Matus Francisco , Barra Patricio Javier , Jofré Ignacio , Kuzyakov Yakov , Merino Carolina
Published: November 2021

The major priority of research in the present day is to conserve the environment by reducing GHG emissions. A proposed solution by an expert panel from 195 countries meeting at COP 21 was to increase global SOC stocks by 0.4% year−1 to compensate for GHG emissions, the ‘4 per 1000′ agreement. In this context, the application of biocrusts is a promising framework with which to increase SOC and other soil functions in the soil–plant continuum. Despite the importance of biocrusts, their application to agriculture is limited due to: (1) competition with native microbiota, (2) difficulties in applying them on a large scale, (3) a lack of studies based on carbon (C) balance and suitable for model parameterization, and (4) a lack of studies evaluating the contribution of biocrust weathering to increase C sequestration. Considering these four challenges, we propose three perspectives for biocrust application: (1) natural microbiome engineering by a host plant, using biocrusts; (2) quantifying the contribution of biocrusts to C sequestration in soils; and (3) enhanced biocrust weathering to improve C sequestration. Thus, we focus this opinion article on new challenges by using the specialized microbiome of biocrusts to be applied in a new environment to counteract the negative effects of climate change.
Overweight as a Favorable Clinical Biomarker for Checkpoint Inhibitor Therapy Response in Recurrent Gynecologic Cancer Patients
Authors: Bartl Thomas , Onoprienko Arina , Hofstetter Gerda , Müllauer Leonhard , Poetsch Nina , Fuereder Thorsten , Kofler Paul , Polterauer Stephan , Grimm Christoph
Published: November 2021

Despite increasing clinical interest in adapting checkpoint inhibitor (CPI) therapies for patients with gynecologic malignancies, no accurate clinical biomarkers to predict therapy response and prognosis are currently available. Therefore, we aimed to assess the predictive and prognostic value of pretherapeutic body mass index (BMI) for recurrent gynecologic cancer patients as previously validated for other solid tumors. We evaluated patients with programmed cell death ligand 1 (PD-L1) positive and, in endometrial cancer, also mismatch repair deficient (MMR) gynecologic malignancies, who received the PD-1 inhibitor pembrolizumab as monotherapy (200 mg fixed-dose q3 w) from 2017 to 2020 (n = 48). Thirty-six patients receiving at least four courses were included in the final analysis. Associations between a BMI increase per 5 kg/m2 and overall response rate (ORR; complete + partial response), disease control rate (DCR; ORR + stable disease), progression-free (PFS), and overall survival (OS) were assessed. An elevated BMI was univariately associated with ORR (OR 10.93 [CI 2.39–49.82], p = 0.002), DCR (OR 2.19 [CI 0.99–4.83], p = 0.048), prolonged PFS (HR 1.54 [CI 1.03–2.34], p = 0.038), and OS (HR 1.87 [CI 1.07–3.29], p = 0.028). All results could be confirmed in the multivariate analyses. Pretherapeutic BMI therefore appears to be a promising readily available biomarker to identify patients with PD-L1-positive and/or MMR-deficient gynecologic malignancies who could particularly benefit from CPI treatment.
NK Cells Can Preferentially Target Prostate Cancer Stem-like Cells via the TRAIL/DR5 Signaling Pathway
Authors: Seki Taiga , Shimizu Yui , Ishii Kyota , Takahama Yuzuki , Kato Kazunori , Yano Tomohiro
Published: November 2021

Background: The occurrence of androgen-dependent prostate cancer mainly depends on prostate cancer stem cells. To reduce the risk of androgen-dependent prostate cancer, the direct elimination of prostate cancer stem cells is important, but an elimination strategy has not yet been established. A previous study showed that natural killer (NK) cells can preferentially target cancer stem cells in several solid tumors except prostate cancer. In this context, this study was undertaken to investigate if NK cells can selectively attack androgen-dependent prostate cancer stem cells. Methods: Prostate cancer stem-like cells were separated from an androgen-dependent prostate cancer cell line (LNCaP) using a three-dimensional culture system. LNCaP stem-like cells or LNCaP cells were co-cultured with human NK cells (KHYG-1) for 24–72 h, and cell viability was determined using the WST-8 method. The expression of each protein in the cell membrane was evaluated through FACS analysis, and mRNA levels were determined using real-time PCR. Results: KHYG-1 cells had more potent cytotoxicity against LNCaP stem-like cells than LNCaP cells, and the potency of the cytotoxicity was strongly related to the TRAIL/DR5 cell death pathway. Conclusion: NK cells can preferentially target prostate cancer stem-like cells via the TRAIL/DR5 pathway.
Effects of Sulfur Assimilation in Pseudomonas fluorescens SS101 on Growth, Defense, and Metabolome of Different Brassicaceae
Authors: Jeon Je-Seung , Etalo Desalegn W. , Carreno-Quintero Natalia , de Vos Ric C. H. , Raaijmakers Jos M.
Published: November 2021

Genome-wide analysis of plant-growth-promoting Pseudomonas fluorescens strain SS101 (PfSS101) followed by site-directed mutagenesis previously suggested that sulfur assimilation may play an important role in growth promotion and induced systemic resistance in Arabidopsis. Here, we investigated the effects of sulfur metabolism in PfSS101 on growth, defense, and shoot metabolomes of Arabidopsis and the Brassica crop, Broccoli. Root tips of seedlings of Arabidopsis and two Broccoli cultivars were treated with PfSS101 or with a mutant disrupted in the adenylsulfate reductase cysH, a key gene in cysteine and methionine biosynthesis. Phenotyping of plants treated with wild-type PfSS101 or its cysH mutant revealed that sulfur assimilation in PfSS101 was associated with enhanced growth of Arabidopsis but with a reduction in shoot biomass of two Broccoli cultivars. Untargeted metabolomics revealed that cysH-mediated sulfur assimilation in PfSS101 had significant effects on shoot chemistry of Arabidopsis, in particular on chain elongation of aliphatic glucosinolates (GLSs) and on indole metabolites, including camalexin and the growth hormone indole-3-acetic acid. In Broccoli, PfSS101 sulfur assimilation significantly upregulated the relative abundance of several shoot metabolites, in particular, indolic GLSs and phenylpropanoids. These metabolome changes in Broccoli plants coincided with PfSS101-mediated suppression of leaf infections by Xanthomonas campestris. Our study showed the metabolic interconnectedness of plants and their root-associated microbiota.
Peri-Prostatic Adipocyte-Released TGFβ Enhances Prostate Cancer Cell Motility by Upregulation of Connective Tissue Growth Factor
Authors: La Civita Evelina , Liotti Antonietta , Cennamo Michele , Crocetto Felice , Ferro Matteo , Liguoro Pasquale , Cimmino Amelia , Imbimbo Ciro , Beguinot Francesco , Formisano Pietro , Terracciano Daniela
Published: November 2021

Periprostatic adipose tissue (PPAT) has emerged as a key player in the prostate cancer (PCa) microenvironment. In this study, we evaluated the ability of PPAT to promote PCa cell migration, as well as the molecular mechanisms involved. Methods: We collected conditioned mediums from in vitro differentiated adipocytes isolated from PPAT taken from PCa patients during radical prostatectomy. Migration was studied by scratch assay. Results: Culture with CM of human PPAT (AdipoCM) promotes migration in two different human androgen-independent (AI) PCa cell lines (DU145 and PC3) and upregulated the expression of CTGF. SB431542, a well-known TGFβ receptor inhibitor, counteracts the increased migration observed in presence of AdipoCM and decreased CTGF expression, suggesting that a paracrine secretion of TGFβ by PPAT affects motility of PCa cells. Conclusions: Collectively, our study showed that factors secreted by PPAT enhanced migration through CTGF upregulation in AI PCa cell lines. These findings reveal the potential of novel therapeutic strategies targeting adipocyte-released factors and TGFβ/CTGF axis to fight advanced PCa dissemination.
Hospital Frailty Risk Score Is Independently Associated with Mortality and Encephalopathy in Hospitalized Patients with Hepatocellular Carcinoma
Authors: Ramai Daryl , Dang-Ho Khoi P. , Kewalramani Anjali , Bandaru Praneeth , Sacco Rodolfo , Giacomelli Luca , Shah Aashni , Papa Simonetta , Cappellini Francesca , Perversi Fabio , di Nunzio Sara , Facciorusso Antonio
Published: November 2021

Frailty represents a state of vulnerability to multiple internal physiologic factors, as well as external pressures, and has been associated with clinical outcomes. We aim to understand the impact of frailty on patients admitted with hepatocellular carcinoma (HCC) by using the validated Hospital Frailty Risk Score, which is implemented in several hospitals worldwide. We conducted a nation-wide retrospective cohort study to determine the effect of frailty on the risk of in-patient mortality, hepatic encephalopathy, length of stay and cost. Frailty was associated with a 4.5-fold increased risk of mortality and a 2.3-fold increased risk of hepatic encephalopathy. Adjusted Cox regression showed that frailty was correlated with increased risk of in-patient mortality (hazard ratio: 2.3, 95% CI 1.9–2.8, p < 0.001). Frail HCC patients had longer hospital stay (median 5 days) vs. non-frail HCC patients (median 3 days). Additionally, frail patients had higher total costs of hospitalization ($40,875) compared with non-frail patients ($31,667). Frailty is an independent predictor of hepatic encephalopathy and in-patient mortality. Frailty is a surrogate marker of hospital length of stay and cost.
Hydrogels: 3D Drug Delivery Systems for Nanoparticles and Extracellular Vesicles
Authors: Chabria Yashna , Duffy Garry , Lowery Aoife , Dwyer Róisín
Published: November 2021

Synthetic and naturally occurring nano-sized particles present versatile vehicles for the delivery of therapy in a range of clinical settings. Their small size and modifiable physicochemical properties support refinement of targeting capabilities, immune response, and therapeutic cargo, but rapid clearance from the body and limited efficacy remain a major challenge. This highlights the need for a local sustained delivery system for nanoparticles (NPs) and extracellular vesicles (EVs) at the target site that will ensure prolonged exposure, maximum efficacy and dose, and minimal toxicity. Biocompatible hydrogels loaded with therapeutic NPs/EVs hold immense promise as cell-free sustained and targeted delivery systems in a range of disease settings. These bioscaffolds ensure retention of the nano-sized particles at the target site and can also act as controlled release systems for therapeutics over a prolonged period of time. The encapsulation of stimuli sensitive components into hydrogels supports the release of the content on-demand. In this review, we highlight the prospect of the sustained and prolonged delivery of these nano-sized therapeutic entities from hydrogels for broad applications spanning tissue regeneration and cancer treatment. Further understanding of the parameters controlling the release rate of these particles and efficient transfer of cargo to target cells will be fundamental to success.
Non-Alcoholic Fatty Liver Disease (NAFLD) and Potential Links to Depression, Anxiety, and Chronic Stress
Authors: Shea Sue , Lionis Christos , Kite Chris , Atkinson Lou , Chaggar Surinderjeet S. , Randeva Harpal S. , Kyrou Ioannis
Published: November 2021

Non-alcoholic fatty liver disease (NAFLD) constitutes the most common liver disease worldwide, and is frequently linked to the metabolic syndrome. The latter represents a clustering of related cardio-metabolic components, which are often observed in patients with NAFLD and increase the risk of cardiovascular disease. Furthermore, growing evidence suggests a positive association between metabolic syndrome and certain mental health problems (e.g., depression, anxiety, and chronic stress). Given the strong overlap between metabolic syndrome and NAFLD, and the common underlying mechanisms that link the two conditions, it is probable that potentially bidirectional associations are also present between NAFLD and mental health comorbidity. The identification of such links is worthy of further investigation, as this can inform more targeted interventions for patients with NAFLD. Therefore, the present review discusses published evidence in relation to associations of depression, anxiety, stress, and impaired health-related quality of life with NAFLD and metabolic syndrome. Attention is also drawn to the complex nature of affective disorders and potential overlapping symptoms between such conditions and NAFLD, while a focus is also placed on the postulated mechanisms mediating associations between mental health and both NAFLD and metabolic syndrome. Relevant gaps/weaknesses of the available literature are also highlighted, together with future research directions that need to be further explored.