bluuebunny/crossref_metadata_2025 huggingface dataset:
RSMDA: Random Slices Mixing Data Augmentation
Authors: Kumar Teerath , Mileo Alessandra , Brennan Rob , Bendechache Malika
Published: January 2023

Advanced data augmentation techniques have demonstrated great success in deep learning algorithms. Among these techniques, single-image-based data augmentation (SIBDA), in which a single image’s regions are randomly erased in different ways, has shown promising results. However, randomly erasing image regions in SIBDA can cause a loss of the key discriminating features, consequently misleading neural networks and lowering their performance. To alleviate this issue, in this paper, we propose the random slices mixing data augmentation (RSMDA) technique, in which slices of one image are placed onto another image to create a third image that enriches the diversity of the data. RSMDA also mixes the labels of the original images to create an augmented label for the new image to exploit label smoothing. Furthermore, we propose and investigate three strategies for RSMDA: (i) the vertical slices mixing strategy, (ii) the horizontal slices mixing strategy, and (iii) a random mix of both strategies. Of these strategies, the horizontal slice mixing strategy shows the best performance. To validate the proposed technique, we perform several experiments using different neural networks across four datasets: fashion-MNIST, CIFAR10, CIFAR100, and STL10. The experimental results of the image classification with RSMDA showed better accuracy and robustness than the state-of-the-art (SOTA) single-image-based and multi-image-based methods. Finally, class activation maps are employed to visualize the focus of the neural network and compare maps using the SOTA data augmentation methods.
Assessing the Relationship between Cognitive Workload, Workstation Design, User Acceptance and Trust in Collaborative Robots
Authors: Panchetti Tommaso , Pietrantoni Luca , Puzzo Gabriele , Gualtieri Luca , Fraboni Federico
Published: January 2023

Collaborative robots are revolutionising the manufacturing industry and the way workers perform their tasks. When designing shared workspaces between robots and humans, human factors and ergonomics are often overlooked. This study assessed the relationship between cognitive workload, workstation design, user acceptance and trust in collaborative robots. We combined subjective and objective data to evaluate the cognitive workload during an assembly task in three different scenarios in which we manipulated various features of the workstation and interaction modalities. Our results showed that participants experienced a reduction in cognitive workload in each of the three trials, indicating an improvement in cognitive performance. Additionally, we found that user acceptance predicted perceived stress across the trials but did not significantly impact the cognitive workload. Trust was not found to moderate the relationship between cognitive workload and perceived stress. This study has the potential to make a significant contribution to the field of collaborative assembly systems by providing valuable insights and helping to bridge the gap between researchers and practitioners. This study can potentially impact companies looking to improve safety, productivity and efficiency.
Influence of Annealing on Gas-Sensing Properties of TiOx Coatings Prepared by Gas Impulse Magnetron Sputtering with Various O2 Content
Authors: Wojcieszak Damian , Kapuścik Paulina , Kijaszek Wojciech
Published: January 2023

TiOx films were prepared by gas impulse magnetron sputtering under oxygen-deficient (ODC) and oxygen-rich conditions (ORC) and annealing at 100–800 °C was used. The O2 content had an effect on their transparency level (Tλ). The films from the ORC mode had ca. Tλ = 60%, which decreased slightly in the VIS range after annealing. The film from the ODC mode had lower transmission (ca. <10%), which increased in the NIR range after annealing by up to ca. 60%. Differences in optical band gap (Egopt) and Urbach energy (Eu) were also observed. The deposition parameters had an influence on the microstructure of TiOx coatings. The ORC and ODC modes resulted in columnar and grainy structures, respectively. Directly after deposition, both coatings were amorphous according to the GIXRD results. In the case of TiOxORC films, this state was retained even after annealing, while for TiOxODC, the crystalline forms of Ti and TiO2-anatase were revealed with increasing temperature. Sensor studies have shown that the response to H2 in the coating deposited under oxygen-rich conditions was characteristic of n-type conductivity, while oxygen-deficient conditions led to a p-type response. The highest sensor responses were achieved for TiOxODC annealed at 300 °C and 400 °C.
Special Issue on Soil Erosion: Dust Control and Sand Stabilization (Volume II)
Authors: Katra Itzhak
Published: January 2023

This is the second volume of the Special Issue on Soil Erosion: Dust Control and Sand Stabilization, following the first volume published in 2020 [...]
Engineering Safety Evaluation of the High Rock Slope of a Hydropower Project: A Case Study of 684 m-High Slope Related to Lianghekou Hydropower Project at Yalong River
Authors: Xu Xiaoyi , Zhang Guike , Huang Wei , Chen Shizhuang , Yan Long , Xu Weiya
Published: January 2023

The stability of the slope is a very important topic in the construction of hydropower projects, especially the slope engineering in the dam area, as its stability will directly affect the safety of engineering. Taking the inlet slope of the flood discharge structure of Lianghekou Hydropower Project as the research object, based on the analysis and exploration of the geological condition of the slope and the field monitoring data, GA-LSSVM is used to establish the non-linear mapping relationship, and the BP neural network is used to establish the mechanical parameters back analysis of the slope at different water impoundment stages. A numerical simulation model is also established to set up different reservoir impoundments to study the stability and sensibility of the slope and provide guidance for slope operation. This case study shows that there is a hysteresis in the response of slope deformation to reservoir impoundment. At the same time, the mechanical parameters of the slope will be weakened by the seepage. In the process of water level changes, the stability of the slope decreases due to the decrease in mechanical parameters. The study will be practically useful for engineering applications.
Monocular 3D Object Detection Based on Pseudo Multimodal Information Extraction and Keypoint Estimation
Authors: Zhao Dan , Ji Chaofeng , Liu Guizhong
Published: January 2023

Three-dimensional object detection is an essential and fundamental task in the field of computer vision which can be widely used in various scenarios such as autonomous driving and visual navigation. In view of the current insufficient utilization of image information in current monocular camera-based 3D object detection algorithms, we propose a monocular 3D object detection algorithm based on pseudo-multimodal information extraction and keypoint estimation. We utilize the original image to generate pseudo-lidar and a bird’s-eye view, and then feed the fused data of the original image and pseudo-lidar to the keypoint-based network for an initial 3D box estimation, finally using the bird’s-eye view to refine the initial 3D box. The experimental performance of our method exceeds state-of-the-art algorithms under the evaluation criteria of 3D object detection and localization on the KITTI dataset, achieving the best experimental performance so far.
One-Class SVM Model-Based Tunnel Personnel Safety Detection Technology
Authors: Huang Guosheng , Chen Jinchuan , Liu Lei
Published: January 2023

The judgment of tunnel personnel’s safety status mainly requires the collection of construction personnel’s physical signs and cave environment data, and the early warning of abnormal status usually requires professional staff to make rapid judgments in a short time, which is costly and inefficient in terms of operation and maintenance. A single-classification support vector machine-based personnel safety status detection and early warning model is proposed to address this phenomenon. First, by deploying sensor devices at the site, we obtain data on the safety state of an actual tunnel construction scene and construct an OCSVM model for abnormal state prediction. Then the model is retained for early warning state testing, collecting relevant environmental data as well as construction personnel’s physical signs data from engineering examples. Finally, we conduct horizontal different parameter model experiments and vertical different early warning state proportional data experiments to evaluate the performance of the model for personnel information security state judgment. The experimental results show that the accuracy rate of personnel security status early warning reaches more than 90%. In particular, it provides a more efficient detection means for the judgment of personnel security status.
A Lightweight YOLOv5 Optimization of Coordinate Attention
Authors: Wu Jun , Dong Jiaming , Nie Wanyu , Ye Zhiwei
Published: January 2023

As Machine Learning technologies evolve, there is a desire to add vision capabilities to all devices within the IoT in order to enable a wider range of artificial intelligence. However, for most mobile devices, their computing power and storage space are affected by factors such as cost and the tight supply of relevant chips, making it impossible to effectively deploy complex network models to small processors with limited resources and to perform efficient real-time detection. In this paper, YOLOv5 is studied to achieve the goal of lightweight devices by reducing the number of original network channels. Then detection accuracy is guaranteed by adding a detection head and CA attention mechanism. The YOLOv5-RC model proposed in this paper is 30% smaller and lighter than YOLOv5s, but still maintains good detection accuracy. YOLOv5-RC network models can achieve a good balance between detection accuracy and detection speed, with potential for its widespread use in industry.
An Accelerated Method for Protecting Data Privacy in Financial Scenarios Based on Linear Operation
Authors: Huo Huairong , Guo Jiangyi , Yang Xinze , Lu Xinai , Wu Xiaotong , Li Zongrui , Li Manzhou , Ren Jinzheng
Published: January 2023

With the support of cloud computing technology, it is easier for financial institutions to obtain more key information about the whole industry chain. However, the massive use of financial data has many potential risks. In order to better cope with this dilemma and better protect the financial privacy of users, we propose a privacy protection model based on cloud computing. The model provides four levels of privacy protection according to the actual needs of users. At the highest level of protection, the server could not access any information about the user and the raw data, nor could it recover the computational characteristics of the data. In addition, due to the universality of the mathematical principle of linear operators, the model could effectively protect and accelerate all models based on linear operations. The final results showed that the method can increase the speed by 10 times, compared with the privacy protection method that only uses local computing power instead of the cloud server. It can also effectively prevent the user’s privacy from being leaked with relatively minimal delay cost, compared with no privacy protection method. Finally, we design a multi-user scheduling model to deploy the model in a real scenario, which could maximise server power and protect user privacy as well.
Deep Learning-Based Virtual Optical Image Generation and Its Application to Early Crop Mapping
Authors: Park No-Wook , Park Min-Gyu , Kwak Geun-Ho , Hong Sungwook
Published: January 2023

This paper investigates the potential of cloud-free virtual optical imagery generated using synthetic-aperture radar (SAR) images and conditional generative adversarial networks (CGANs) for early crop mapping, which requires cloud-free optical imagery at the optimal date for classification. A two-stage CGAN approach, including representation and generation stages, is presented to generate virtual Sentinel-2 spectral bands using all available information from Sentinel-1 SAR and Sentinel-2 optical images. The dual-polarization-based radar vegetation index and all available multi-spectral bands of Sentinel-2 imagery are particularly considered for feature extraction in the representation stage. A crop classification experiment using Sentinel-1 and -2 images in Illinois, USA, demonstrated that the use of all available scattering and spectral features achieved the best prediction performance for all spectral bands, including visible, near-infrared, red-edge, and shortwave infrared bands, compared with the cases that only used dual-polarization backscattering coefficients and partial input spectral bands. Early crop mapping with an image time series, including the virtual Sentinel-2 image, yielded satisfactory classification accuracy comparable to the case of using an actual time-series image set, regardless of the different combinations of spectral bands. Therefore, the generation of virtual optical images using the proposed model can be effectively applied to early crop mapping when the availability of cloud-free optical images is limited.
Automatic Detection of Multilevel Communities: Scalable, Selective and Resolution-Limit-Free
Authors: Gao Kun , Ren Xuezao , Zhou Lei , Zhu Junfang
Published: January 2023

Community structure is one of the most important features of complex networks. Modularity-based methods for community detection typically rely on heuristic algorithms to optimize a specific community quality function. Such methods have two major limits: (1) the resolution limit problem, which prohibits communities of heterogeneous sizes being simultaneously detected, and (2) divergent outputs of the heuristic algorithm, which make it difficult to differentiate relevant and irrelevant results. In this paper, we propose an improved method for community detection based on a scalable community “fitness function.” We introduce a new parameter to enhance its scalability, and a strict strategy to filter the outputs. Due to the scalability, on the one hand, our method is free of the resolution limit problem and performs excellently on large heterogeneous networks, while on the other hand, it is capable of detecting more levels of communities than previous methods in deep hierarchical networks. Moreover, our strict strategy automatically removes redundant and irrelevant results; it selectively but inartificially outputs only the best and unique community structures, which turn out to be largely interpretable by the a priori knowledge of the network, including the implanted community structures within synthetic networks, or metadata observed for real-world networks.
Research on Queue Equilibrium Control Algorithm of Urban Traffic Based on Game Theory
Authors: Wang Li , Pan Ke , Zhao Qi , Zhang Lili , Zhang Lingyu
Published: January 2023

The intersection traffic signal control is an essential means of urban traffic. To solve the problem of urban congestion, it is necessary to consider the optimal signal control strategy for intersections. Using the store-and-forward method of traffic control modeling, the in-queue vehicle number of the key signal phase as the payoff index, this paper designs an optimal intersection signal-timing strategy based on the game theory method. In this strategy, each key phase is regarded as a game player, and each player competes for the release time to maximize their own payoff and minimize the queue. To optimize the intersection efficiency, a game strategy is designed to achieve the Nash equilibrium state, which is the queueing equilibrium of each key phase. Finally, by VISSIM simulation, the total number of stops can be decreased by 5% to 10% compared with the MA-DD-DACC method.
Frequency-Tuned Porous Polyethylene Glycol Films Obtained in Atmospheric-Pressure Dielectric Barrier Discharge (DBD) Plasma
Authors: Rusu Bogdan-George , Ursu Cristian , Olaru Mihaela , Barboiu Mihail
Published: January 2023

This study focuses on the fabrication of plasma-polymerized polyethylene glycol (pp-PEG) with porous morphology in a pulsed dielectric barrier discharge (DBD) plasma under atmospheric pressure. The signal frequency that modulates the plasma discharge was found to have a major influence on the pp-PEG film morphology. The recorded discharge current–voltage characteristic allowed us to establish a homogeneous regime of the DBD plasma operated in helium gas flow upon the frequency range 2–10 kHz. The as-prepared pp-PEG films were characterized by the Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and liquid-phase chromatography (HPLC) techniques. The performed analysis revealed that as the discharge frequency increases, the morphology of the obtained films becomes porous due to the plasma-induced stronger monomer fragmentation. To gain knowledge about the plasma species and the interaction processes that impact the film morphology, optical emission spectroscopy (OES) and intensified charge-coupled device (ICCD) fast imaging technique were applied. The determined vibrational (Tvib) and rotational (Trot) temperatures exhibit a decrease with the introduction of monomer vapors into the discharge gap. For instance, Trot drops from approximately 475 K to 350 K, and Tvib falls from 2850 K to 2650 K for a monomer vapor injection rate of 16 µL/min. This was attributed to the energy losses of the plasma-generated particles, as the inelastic collisions augment with the injection of a monomer. Concurrently with the change in temperature, the discharge current varies significantly for the investigated frequency range and exhibits a drop at high frequencies. This discharge current drop was explained by an enhancement of the recombination rate of charged particles and seems to confirm the prevalence of a plasma-induced monomer fragmentation process at high frequencies.
C-, N-, S-, and P-Substrate Spectra in and the Impact of Abiotic Factors on Assessing the Biotechnological Potential of Paracoccus pantotrophus
Authors: Bachmann Denise , Pal Upasana , Bockwoldt Julia A. , Schaffert Lena , Roentgen Robin , Büchs Jochen , Kalinowski Jörn , Blank Lars M. , Tiso Till
Published: January 2023

Modern biotechnology benefits from the introduction of novel chassis organisms in remedying the limitations of already-established strains. For this, Paracoccus pantotrophus was chosen for in-depth assessment. Its unique broad metabolism and robustness against abiotic stressors make this strain a well-suited chassis candidate. This study set out to comprehensively overview abiotic influences on the growth performance of five P. pantotrophus strains. These data can aid in assessing the suitability of this genus for chassis development by using the type strain as a preliminary model organism. The five P. pantotrophus strains DSM 2944T, DSM 11072, DSM 11073, DSM 11104, and DSM 65 were investigated regarding their growth on various carbon sources and other nutrients. Our data show a high tolerance against osmotic pressure for the type strain with both salts and organic osmolytes. It was further observed that P. pantotrophus prefers organic acids over sugars. All of the tested strains were able to grow on short-chain alkanes, which would make P. pantotrophus a candidate for bioremediation and the upcycling of plastics. In conclusion, we were able to gain insights into several P. pantotrophus strains, which will aid in further introducing this species, or even another species from this genus, as a candidate for future biotechnological processes.
Hydrolytic Enzyme Production and Susceptibility to Antifungal Compounds of Opportunistic Candida parapsilosis Strains Isolated from Cucurbitaceae and Rosaceae Fruits
Authors: Glushakova Anna , Kachalkin Aleksey , Rodionova Evgenia
Published: January 2023

Endophytic yeast species were studied in the internal tissues of ripe cultivated vegetables and fruits. A total of 19 yeast species, 11 ascomycete species, and 8 basidiomycete species were observed in the internal tissues of all fruits examined. The opportunistic yeast Candida parapsilosis was present in all plants studied. Several virulence factors (production of hydrolytic enzymes and sensitivity to antifungal agents) were examined in all 107 isolates of C. parapsilosis from the internal tissues of fruits. The most virulent isolates were found in vegetables. C. parapsilosis is widespread in nature and is often isolated from a variety of non-human sources. It is frequently involved in invasive infections that seriously affect human health. This species poses a high risk to immunocompromised individuals, such as HIV patients and surgical patients or children whose immune systems are not sufficiently mature. Since virulent isolates of Candida parapsilosis have been found in vegetables and fruits; their raw consumption may not be safe. Finally, we emphasize the importance of ongoing phenotypic and genetic studies of endophytic isolates of Candida parapsilosis and their comparison with clinical isolates.
Favipiravir in the Treatment of Outpatient COVID-19: A Multicenter, Randomized, Triple-Blind, Placebo-Controlled Clinical Trial
Authors: Vaezi Atefeh , Salmasi Mehrzad , Soltaninejad Forogh , Salahi Mehrdad , Javanmard Shaghayegh Haghjooy , Amra Babak
Published: January 2023

Background: Finding effective outpatient treatments to prevent COVID-19 progression and hospitalization is necessary and is helpful in managing limited hospital resources. Repurposing previously existing treatments is highly desirable. In this study, we evaluate the efficacy of Favipiravir in the prevention of hospitalization in symptomatic COVID-19 patients who were not eligible for hospitalization. Methods: This study was a triple-blind randomized controlled trial conducted between 5 December 2020 and 31 March 2021 in three outpatient centers in Isfahan, Iran. Patients in the intervention group received Favipiravir 1600 mg daily for five days, and the control group received a placebo. Our primary outcome was the proportion of hospitalized participants from day 0 to day 28. The outcome was assessed on days 3, 7, 14, 21, and 28 through phone calls. Results: Seventy-seven patients were randomly allocated to Favipiravir and placebo groups. There was no significant difference between groups considering baseline characteristics. During the study period, 10.5% of patients in the Favipiravir group and 5.1% of patients in the placebo group were hospitalized, but there was no significant difference between them (p-value = 0.3). No adverse event was reported in the treatment group. Conclusions: Our study shows that Favipiravir did not reduce the hospitalization rate of mild to moderate COVID-19 patients in outpatient settings.
A Bagged Ensemble Convolutional Neural Networks Approach to Recognize Insurance Claim Frauds
Authors: Abakarim Youness , Lahby Mohamed , Attioui Abdelbaki
Published: January 2023

Fighting fraudulent insurance claims is a vital task for insurance companies as it costs them billions of dollars each year. Fraudulent insurance claims happen in all areas of insurance, with auto insurance claims being the most widely reported and prominent type of fraud. Traditional methods for identifying fraudulent claims, such as statistical techniques for predictive modeling, can be both costly and inaccurate. In this research, we propose a new way to detect fraudulent insurance claims using a data-driven approach. We clean and augment the data using analysis-based techniques to deal with an imbalanced dataset. Three pre-trained Convolutional Neural Network (CNN) models, AlexNet, InceptionV3 and Resnet101, are selected and minimized by reducing the redundant blocks of layers. These CNN models are stacked in parallel with a proposed 1D CNN model using Bagged Ensemble Learning, where an SVM classifier is used to extract the results separately for the CNN models, which is later combined using the majority polling technique. The proposed method was tested on a public dataset and produced an accuracy of 98%, with a 2% Brier score loss. The numerical experiments demonstrate that the proposed approach achieves promising results for detecting fake accident claims.
Can Air Quality Gas Sensors Be Used for Emission Monitoring of Small-Scale Local Air Pollution Sources? Pilot Test Evaluation
Authors: Buček Pavel , Bílek Jiří , Maršolek Petr , Bílek Ondřej
Published: January 2023

In recent years we have seen a growing number of applications that use various sensory measurements of physicochemical features. Within the research project “Research on the identification of combustion of unsuitable fuels and systems of self-diagnostics of boilers combustion solid fuels for domestic heating”, the authors tested and evaluated the possible use of an air quality monitoring sensor unit for the measurement of operating parameters of solid fuel burning boilers and stoves. In the Czech Republic, programs to support citizens in the replacement of domestic boilers of poor combustion quality have been subsidized for several years. Unfortunately, no assessment of the impact of subsidies on air quality has been carried out. However, the increased pollutant emissions due to improper use of domestic boilers are supposed to be one of the greatest problems with domestic boilers. Hence, providing users with real-time feedback may lead to changes in combustion conditions and consequently to a reduction in air pollution. We focus on sensory measurements of CO, CO2, NO, and VOCs as compounds that correspond to the operating conditions of the combustion process. The research included sampling, construction of the flue gas dilution duct, and the influence of direct measurement on the service life of the sensors.
A Practical Approach for Determining Multi-Dimensional Spatial Rainfall Scaling Relations Using High-Resolution Time–Height Doppler Data from a Single Mobile Vertical Pointing Radar
Authors: Jameson Arthur R.
Published: January 2023

The rescaling of rainfall requires measurements of rainfall rates over many dimensions. This paper develops one approach using 10 m vertical spatial observations of the Doppler spectra of falling rain every 10 s over intervals varying from 15 up to 41 min in two different locations and in two different years using two different micro-rain radars (MRR). The transformation of the temporal domain into spatial observations uses the Taylor “frozen” turbulence hypothesis to estimate an average advection speed over an entire observation interval. Thus, when no other advection estimates are possible, this paper offers a new approach for estimating the appropriate frozen turbulence advection speed by minimizing power spectral differences between the ensemble of purely spatial radial power spectra observed at all times in the vertical and those using the ensemble of temporal spectra at all heights to yield statistically reliable scaling relations. Thus, it is likely that MRR and other vertically pointing Doppler radars may often help to obviate the need for expensive and immobile large networks of instruments in order to determine such scaling relations but not the need of those radars for surveillance.
Seasonal Variability in Fine Particulate Matter Water Content and Estimated pH over a Coastal Region in the Northeast Arabian Sea
Authors: Shukla Garima , Sudheer A. K. , Gunthe Sachin S. , Beig Gufran , Kumar Ashwini
Published: January 2023

The acidity of atmospheric particles can promote specific chemical processes that result in the production of extra condensed phases from lesser volatile species (secondary fine particulate matter), change the optical and water absorption characteristics of particles, and enhance trace metal solubility that can function as essential nutrients in nutrient-limited environments. In this study, we present an estimated pH of fine particulate matter (FPM) through a thermodynamic model and assess its temporal variability over a coastal location in the northeast Arabian Sea. Here, we have used the chemical composition of FPM (PM2.5) collected during the period between 2017–2019. Chemical composition data showed large variability in water-soluble ionic concentrations (WSIC; range: 2.3–39.9 μg m−3) with higher and lower average values during the winter and summer months, respectively. SO42− ions were predominant among anions, while NH4+ was a major contributor among cations throughout the season. The estimated pH of FPM from the forward and reverse modes exhibits a moderate correlation for winter and summer samples. The estimated pH of FPM is largely regulated by SO42− content and strongly depends on the relative ambient humidity, particularly in the forward mode. Major sources of FPM assessed based on Positive matrix factorization (PMF) and air-mass back trajectory analyses demonstrate the dominance of natural sources (sea salt and dust) during summer months, anthropogenic sources in winter months and mixed sources during the post-monsoon season.
Extreme Dry and Wet Events in the Pacific Region of Colombia estimated in the 21st Century Based on the Standardized Precipitation Index and CORDEX Climate Projections
Authors: Chaulagain Deepak , Aroca Oscar Fernando Meneses , Same Noel Ngando , Yakub Abdulfatai Olatunji , Nsafon Benyoh Emmanuel Kigha , Suh Dongjun , Triolo Jin Mi , Huh Jeung-Soo
Published: January 2023

The Pacific region of Colombia is known to be one of the most vulnerable to changes in precipitation patterns. A study was conducted using standardized precipitation index (SPI) analyses to understand the potential changes in precipitation in this region during the 21st century. The analyses were conducted using historical precipitation data from 1950 to 2005 and projected precipitation data from 2022 to 2100 under the Coordinated Regional Climate Downscaling Experiment (CORDEX) climate scenarios (RCP 4.5 and RCP 8.5). The results of the study showed that compared to historical data, SPI3 precipitation in this region is predicted to increase by 2040 under both climatic scenarios. However, in the 2041–2070 period, the region is expected to be wetter under RCP 8.5, although the difference between the two scenarios was not statistically significant. Similarly, SPI 6 precipitation is predicted to increase in the 2022–2040 and 2071–2100 periods under both scenarios. SPI 12 precipitation is also predicted to increase in the 2022–2040 period under RCP 4.5. In the 2041–2070 period, dryness is predicted to be more frequent under RCP 4.5, and wetness is predicted under RCP 8.5. The findings of this study can help in determining the most pertinent reference periods and computation time increments for evaluating the effects of future climate change on agricultural production and food security in the Pacific region of Colombia. It suggests that changes in precipitation patterns are likely to occur in the coming decades, which may significantly impact crop growth, water availability, and other aspects of agricultural production.
The Sensitivityof GPS Precipitable Water Vapor Jumps to Intense Precipitation Associated with Tropical Organized Convective Systems
Authors: Campos Thamiris B. , Sapucci Luiz F. , Eichholz Cristiano , Machado Luiz A. T. , Adams David K.
Published: January 2023

The Global Positioning System (GPS) consists of a constellation of satellites that transmit radio frequency signals to many users with varied applications. For meteorological purposes, the based-ground GPS receivers can provide high-quality column or precipitable water vapor (PWV), as obtained by radiosondes, but with high temporal resolution and low cost. A dense GPS network containing 16 ground-based receivers was installed in Belém city, Brazil, during the period 2–29 June 2011. This network provides a unique opportunity to evaluate the sensitivityof rapid increases in GPS PWV (GPS PWV jumps to the intense precipitation often associated with tropical organized convective systems. Results reveal a characteristic timescale of water vapor convergence before GPS-PWV maximum, which can be used for indicating the occurrence of precipitation associated with organized convective systems. A PWV increase of 4 mm h−1 in a period of an hour or 30 min before the maximum peak GPS-PWV (a peak of at least 57 mm) was observed during organized convection events. The contingency table obtained indicates a probability of detection of 84% and a false alarm ratio of 25% to forecast precipitation events. These results obtained suggest that GPS-PWV jumps can be employed to predict the events associated with organized convection.
Comparison of Radiosonde Measurements of Meteorological Variables with Drone, Satellite Products, and WRF Simulations in the Tropical Andes: The Case of Quito, Ecuador
Authors: Muñoz Luis Eduardo , Campozano Lenin Vladimir , Guevara Daniela Carolina , Parra René , Tonato David , Suntaxi Andrés , Maisincho Luis , Páez Carlos , Villacís Marcos , Córdova Jenry , Valencia Nathalia
Published: January 2023

Radiosondes are the most widely used method for studies of vertical atmospheric behavior, but the high costs associated, and the logistic limitations have forced researchers to look for alternative methods for atmospheric profiling, such as lidar and satellite measurements, or modeling. However, the assessment of the accuracy of alternative methods is recommended, especially in complex terrain, such as the tropical Andes. In this research, the atmospheric profiling of satellite data from AIRS and MODIS products, simulations of the Weather Research and Forecasting model, WRF, and drone measurements are evaluated for a campaign of 10 radio soundings, between August 2021 and January 2022. Additionally, the capability to capture the planetary boundary layer height, hPBL, is studied. The measurements were conducted at Izobamba station near Quito, Ecuador. Temperature, T, Dew Point Temperature, TD, Mixing Ratio, Q, and Potential Temperature, PT, were evaluated from 0 to 300 m above ground level (magl.) for satellite, WRF, and drone data, and from 0 km to 15 km for satellite and WRF data. Additionally, the capability to capture the planetary boundary layer height, HPBL, was assessed. The results show that drone profiles best represented the magnitude of the analyzed variables showing mean RMSE of 0.79 for T, but the noise of the measurements caused a low correlation with radio sounding profiles, which was partially corrected with a quadratic fit on the profile. The WRF results achieved a positive representation in terms of correlation, but error metrics show that there are remarkable differences in magnitude in the first 300 magl., up to the tropopause height, which surpasses satellite representations for all variables. The MODIS profiles do not generally perform well due to their low vertical resolution and limitations with cloud coverage. However, AIRS data, despite its low resolution, show a better representation of vertical profiles than MODIS, for T and TD, surpassing WRF simulations in some dates. For the HPBL, the WRF results show that physical and atmospheric conditions limit its determination, and the methods and conditioning factors should be further analyzed.
Short-Term Variability of Non-Migrating Diurnal Tides in the Stratosphere from CMAM30, ERA-Interim, and FORMOSAT-3/COSMIC
Authors: Debnath Subhajit , Das Uma
Published: January 2023

The variability of non-migrating tides in the stratosphere is investigated using temperature data from Canadian Middle Atmosphere Model (CMAM30), ERA-interim reanalysis and Formosa Satellite-3 and Constellation Observing System for Meteorology, Ionosphere, and Climate (FORMOSAT-3/COSMIC) from 2006 to 2010 using a ±10-day window. CMAM30 and ERA results show that the amplitudes of non-migrating tides, DS0 and DW2, are negligible in the mid and high-latitude stratosphere, and the results from satellite datasets are significantly affected by aliasing in this region, in spite of using a smaller window size for analysis (±10 days). Significant short term variability ranging from 30 to 100 days is observed in DS0 and DW2 over the equatorial and tropical latitudes. These tides are seen as two prominent bands around the equator with DS0 maximising during boreal summers and DW2 maximising during boreal winters. These variabilities are compared with the variability in amplitude of the stationary planetary wave with wavenumber one (SPW1) in the high-latitude stratosphere using the continuous wavelet transform (CWT). It is found that during boreal winters, the variability of SPW1 at 10 hPa over 65° N is similar to that of DS0 and DW2 over the equator at 0.0007 hPa. This provides evidence that SPW1 from the high-altitude stratosphere moving upward and equator-ward could be interacting with the migrating diurnal tide and generating the non-migrating tides in the equatorial mesosphere and lower thermosphere (MLT). The variabilities, however, are not comparable during summers, with SPW1 being absent in the Northern Hemisphere. It is thus concluded that non-linear interactions could be a source of non-migrating tidal variability in the equatorial MLT region during boreal winters, but during summers, the tidal variabilities have other sources in the lower atmosphere. The anti-symmetric nature of the vertical global structures indicates that these tides could be the result of global atmospheric oscillations proposed by the classical tidal theory.
Preliminary Analysis of Early Identification of Three-Body Scatter Spike Signature in Hailstorms in Catalonia
Authors: Rigo Tomeu , Farnell Carme
Published: January 2023

Three-body scatter spike (TBSS) is one of the most common signatures associated with hailstorms using weather radar. It consists of an appendage appearing behind the storms in the radar imagery. The cause is the multi-scattering between hail particles and the ground. The TBSS is detected in plan position indicator (PPI) reflectivity fields at the elevation coinciding with the hail core. Surveillance staff usually analyzes low-level PPI in real-time, but the signature can appear at mid or high elevations. This study takes advantage of the three-dimensional maximum reflectivity (MAX) product for detecting the presence of the TBSS in thunderstorms more easily, instead of the usual way of analyzing the PPI fields. The new technique is more direct and immediate, crucial in real-time surveillance tasks. This preliminary analysis has focused on the hail days with ground registers that occurred in Catalonia between January and August of 2022, observing this signature in the MAX product in 96% of days with large hail and 72% of small hail events. This fact indicates that MAX can be useful for identifying large hail in thunderstorms, but the efficiency decreases for hail smaller than 2 cm.
Bivariate Analysis of Extreme Precipitation Using Copula Functions in Arid and Semi-Arid Regions
Authors: Pabaghi Zeynab , Bazrafshan Ommolbanin , Zamani Hossein , Shekari Marzieh , Singh Vijay P.
Published: January 2023

This study analyzed extreme precipitation events, using daily rainfall data for 1966–2015. A Mann–Kendall trend test was used to evaluate trends in extreme precipitation, copula functions were applied to compute the joint return periods of extreme events, and univariate and bivariate distributions were used to determine risk. The results showed that the decrease in consecutive wet days (CWD) was significant in the west and the northwest of Iran, while the consecutive dry days (CDD) index was increasing therein. The precipitation on more than the 90th percentile (P90) very wet days and annual number of days with precipitation less than the 90th percentile threshold (D90) indices followed similar patterns, with no significant trend in most parts of Iran, but at several stations in the north, west, and northwest, their decline was extreme. Furthermore, the increase of D10 (annual number of days with precipitation less than the 90th percentile threshold) and P10 (total precipitation of D10 of a year) was extreme in the wet regions of Iran, including the north, west, and northwest areas, and also part of the center. More than 50 percent of Iran experienced a low risk level, with a return period of extreme events (CWD, CDD) of more than 27.5 years, and the joint return periods of (D10, D90), (P10, P90), and (D10, P10) pairs were less than 100 years in most regions of Iran. Due to the increasing number of dry days in the north, west, and northwest of Iran, the drought risk increased. Based on the changes in extreme precipitation indices in recent years, the findings of this study will be useful for copula-based frequency analysis under a changing environment at regional and global scales.
Spatio-Temporal Changes and Contribution of Human and Meteorological Factors to Grassland Net Primary Productivity in the Three-Rivers Headwater Region from 2000 to 2019
Authors: Song Yang , Liang Tian , Zhang Linbo , Hao Chaozhi , Wang Hao
Published: January 2023

Since the beginning of the 21st century, the net primary productivity (NPP) of grassland in the Three-Rivers Headwaters (TRH) region has changed significantly. In this study, NPP was assessed by the Carnegie-Ames-Stanford approach (CASA) model in TRH from 2000 to 2019. The abrupt changes of NPP and meteorological factors were analyzed by cumulative departure, MK test, and Pettitt test. The contributions of meteorological and human factors to changes in grassland NPP were quantitatively assessed using the scenario simulation method. The obtained results showed that: (1) From 2000 to 2019, the NPP of grasslands increased from 135.72 to 141.16 gC/m−2a−1. However, the overall growth trend was not significant, and the proportion of significant growth was only 31.45%; (2) An abrupt increase in meteorological factors occurred around 2005, while an abrupt increase in NPP occurred around 2008, which showed that 2008 was the year when human factors, such as ecological projects and policies, began to show a significant impact on the growth of NPP; and (3) The contribution of human factors to the abrupt increase in NPP was significantly greater than the contribution of meteorological factors. The contribution of human factors exceeded 70% in 93.68% of the studied area, reaching 98% in general, while the contribution of meteorological factors was less than 2%. Among them, the human contributions to the Yangtze River Source, the Yellow River Source, and the Lancang River Source all exceeded 95%. The negative effects of meteorological factors on the growth of NPP in the abovementioned three regions were as high as 47.35%, 48.66%, and 36.91%, respectively. Human factors have contributed greatly to the increase in NPP in most of the source areas of the Yellow River, the eastern part of Tanggulashan County, the southeastern part of Zhiduo County, and the western part of Zaduo County at the source of the Yangtze River.
Prevalence of Congenital Infections in Newborns and Universal Neonatal Hearing Screening in Santa Catarina, Brazil
Authors: Besen Eduarda , Paiva Karina Mary , Cigana Luciana Berwanger , Machado Marcos José , Samelli Alessandra Giannella , Haas Patrícia
Published: January 2023

Objective: to verify the frequency of congenital infections in newborns and their possible associations with the universal-neonatal-hearing-screening (UNHS) results, and evaluate a reference UNHS service in the Unified Health System (Sistema Único de Saúde—SUS), according to quality indicators. Methods: Historical cohort study with data analysis of newborns attending prestigious hearing-health SUS services from January 2017 to December 2021, in Santa Catarina, Brazil. The quality of screening coverage was assessed based on the quality indicators proposed by the Brazilian neonatal-hearing-screening-care guidelines (Diretrizes de Atenção da Triagem Auditiva Neonatal—DATAN). Logistic-regression analysis, crude OR calculations, Cochran–Mantel–Haenszel OR calculation, and chi-square test were performed to estimate the association between risk indicators for hearing loss and UNHS failure. Results: In the last five years, the prestigious services performed UNHS on 34,801 newborns and met the DATAN quality indicators. Congenital syphilis was the most frequent (1.59%) congenital infection in newborns, followed by HIV (0.87%), whereas the least frequent was rubella (0.029%). Conclusion: Prestigious UNHS services reached ≥95% hearing screening coverage. Considering all congenital infections, the prevalence was 2.87%, with congenital syphilis the most frequent. Newborns with congenital syphilis or HIV are more likely to fail UNHS.
Optimal Dynamic Control of Proxy War Arms Support
Authors: Lohmander Peter
Published: January 2023

A proxy war between a coalition of countries, BLUE, and a country, RED, is considered. RED wants to increase the size of the RED territory. BLUE wants to involve more regions in trade and other types of cooperation. GREEN is a small and independent nation that wants to become a member of BLUE. RED attacks GREEN and tries to invade. BLUE decides to give optimal arms support to GREEN. This support can help GREEN in the war against RED and simultaneously can reduce the military power of RED, which is valuable to BLUE also outside this proxy war, since RED may confront BLUE also in other regions. The optimal control problem of dynamic arms support, from the BLUE perspective, is defined in general form. From the BLUE perspective, there is an optimal position of the front. This position is a function of the weights in the objective function and all other parameters. Optimal control theory is used to determine the optimal dynamic BLUE strategy, conditional on a RED strategy, which is observed by BLUE military intelligence. The optimal arms support strategy for BLUE is to initially send a large volume of arms support to GREEN, to rapidly move the front to the optimal position. Then, the support should be almost constant during most of the war, keeping the war front location stationary. In the final part of the conflict, when RED will have almost no military resources left and tries to retire from the GREEN territory, BLUE should strongly increase the arms support and make sure that GREEN rapidly can regain the complete territory and end the war.
Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics
Authors: Cook Taylor W. , Wilstermann Amy M. , Mitchell Jackson T. , Arnold Nicholas E. , Rajasekaran Surender , Bupp Caleb P. , Prokop Jeremy W.
Published: January 2023

Insulin is amongst the human genome’s most well-studied genes/proteins due to its connection to metabolic health. Within this article, we review literature and data to build a knowledge base of Insulin (INS) genetics that influence transcription, transcript processing, translation, hormone maturation, secretion, receptor binding, and metabolism while highlighting the future needs of insulin research. The INS gene region has 2076 unique variants from population genetics. Several variants are found near the transcriptional start site, enhancers, and following the INS transcripts that might influence the readthrough fusion transcript INS–IGF2. This INS–IGF2 transcript splice site was confirmed within hundreds of pancreatic RNAseq samples, lacks drift based on human genome sequencing, and has possible elevated expression due to viral regulation within the liver. Moreover, a rare, poorly characterized African population-enriched variant of INS–IGF2 results in a loss of the stop codon. INS transcript UTR variants rs689 and rs3842753, associated with type 1 diabetes, are found in many pancreatic RNAseq datasets with an elevation of the 3′UTR alternatively spliced INS transcript. Finally, by combining literature, evolutionary profiling, and structural biology, we map rare missense variants that influence preproinsulin translation, proinsulin processing, dimer/hexamer secretory storage, receptor activation, and C-peptide detection for quasi-insulin blood measurements.