bluuebunny/crossref_metadata_2025 huggingface dataset:
SODCNN: A Convolutional Neural Network Model for Small Object Detection in Drone-Captured Images
Authors: Meng Lu , Zhou Lijun , Liu Yangqian
Published: October 2023

Drone images contain a large number of small, dense targets. And they are vital for agriculture, security, monitoring, and more. However, detecting small objects remains an unsolved challenge, as they occupy a small proportion of the image and have less distinct features. Conventional object detection algorithms fail to produce satisfactory results for small objects. To address this issue, an improved algorithm for small object detection is proposed by modifying the YOLOv7 network structure. Firstly, redundant detection head for large objects is removed, and the feature extraction for small object detection advances. Secondly, the number of anchor boxes is increased to improve the recall rate for small objects. And, considering the limitations of the CIoU loss function in optimization, the EIoU loss function is employed as the bounding box loss function, to achieve more stable and effective regression. Lastly, an attention-based feature fusion module is introduced to replace the Concat module in FPN. This module considers both global and local information, effectively addressing the challenges in multiscale and small object fusion. Experimental results on the VisDrone2019 dataset demonstrate that the proposed algorithm achieves an mAP50 of 54.03% and an mAP50:90 of 32.06%, outperforming the latest similar research papers and significantly enhancing the model’s capability for small object detection in dense scenes.
Quantifying Within-Flight Variation in Land Surface Temperature from a UAV-Based Thermal Infrared Camera
Authors: Elfarkh Jamal , Johansen Kasper , Angulo Victor , Camargo Omar Lopez , McCabe Matthew F.
Published: October 2023

Land Surface Temperature (LST) is a key variable used across various applications, including irrigation monitoring, vegetation health assessment and urban heat island studies. While satellites offer moderate-resolution LST data, unmanned aerial vehicles (UAVs) provide high-resolution thermal infrared measurements. However, the continuous and rapid variation in LST makes the production of orthomosaics from UAV-based image collections challenging. Understanding the environmental and meteorological factors that amplify this variation is necessary to select the most suitable conditions for collecting UAV-based thermal data. Here, we capture variations in LST while hovering for 15–20 min over diverse surfaces, covering sand, water, grass, and an olive tree orchard. The impact of different flying heights and times of the day was examined, with all collected thermal data evaluated against calibrated field-based Apogee SI-111 sensors. The evaluation showed a significant error in UAV-based data associated with wind speed, which increased the bias from −1.02 to 3.86 °C for 0.8 to 8.5 m/s winds, respectively. Different surfaces, albeit under varying ambient conditions, showed temperature variations ranging from 1.4 to 6 °C during the flights. The temperature variations observed while hovering were linked to solar radiation, specifically radiation fluctuations occurring after sunrise and before sunset. Irrigation and atmospheric conditions (i.e., thin clouds) also contributed to observed temperature variations. This research offers valuable insights into LST variations during standard 15–20 min UAV flights under diverse environmental conditions. Understanding these factors is essential for developing correction procedures and considering data inconsistencies when processing and interpreting UAV-based thermal infrared data and derived orthomosaics.
EdgeSVDNet: 5G-Enabled Detection and Classification of Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images
Authors: Bilal Anas , Liu Xiaowen , Baig Talha Imtiaz , Long Haixia , Shafiq Muhammad
Published: October 2023

The rise of vision-threatening diabetic retinopathy (VTDR) underscores the imperative for advanced and efficient early detection mechanisms. With the integration of the Internet of Things (IoT) and 5G technologies, there is transformative potential for VTDR diagnosis, facilitating real-time processing of the burgeoning volume of fundus images (FIs). Combined with artificial intelligence (AI), this offers a robust platform for managing vast healthcare datasets and achieving unparalleled disease detection precision. Our study introduces a novel AI-driven VTDR detection framework that integrates multiple models through majority voting. This comprehensive approach encompasses pre-processing, data augmentation, feature extraction using a hybrid convolutional neural network-singular value decomposition (CNN-SVD) model, and classification through an enhanced SVM-RBF combined with a decision tree (DT) and K-nearest neighbor (KNN). Validated on the IDRiD dataset, our model boasts an accuracy of 99.89%, a sensitivity of 84.40%, and a specificity of 100%, marking a significant improvement over the traditional method. The convergence of the IoT, 5G, and AI technologies herald a transformative era in healthcare, ensuring timely and accurate VTDR diagnoses, especially in geographically underserved regions.
A Critical Review on Battery Aging and State Estimation Technologies of Lithium-Ion Batteries: Prospects and Issues
Authors: Roy Probir Kumar , Shahjalal Mohammad , Shams Tamanna , Fly Ashley , Stoyanov Stoyan , Ahsan Mominul , Haider Julfikar
Published: October 2023

Electric vehicles (EVs) have had a meteoric rise in acceptance in recent decades due to mounting worries about greenhouse gas emissions, global warming, and the depletion of fossil resource supplies because of their superior efficiency and performance. EVs have now gained widespread acceptance in the automobile industry as the most viable alternative for decreasing CO2 production. The battery is an integral ingredient of electric vehicles, and the battery management system (BMS) acts as a bridge between them. The goal of this work is to give a brief review of certain key BMS technologies, including state estimation, aging characterization methodologies, and the aging process. The consequences of battery aging limit its capacity and arise whether the battery is used or not, which is a significant downside in real-world operation. That is why this paper presents a wide range of recent research on Li-ion battery aging processes, including estimations from multiple areas. Afterward, various battery state indicators are thoroughly explained. This work will assist in defining new relevant domains and constructing commercial models and play a critical role in future research in this expanding area by providing a clear picture of the present status of estimating techniques of the major state indicators of Li-ion batteries.
An Efficient Transmitter Feature Extraction Scheme with IQ Imbalance and Nonlinearity in TDD OFDM Systems
Authors: Huang Yi , Hu Aiqun , Fan Jiayi , Tian Huifeng , Li Xuebao , Zheng Yanfang
Published: October 2023

Radio frequency (RF) fingerprints have been an emerging research topic for the last decade. Numerous algorithms for recognition have been proposed. However, very few algorithms for the accurate extraction of IQI and PA nonlinearity are available, especially when multiple paths are considered. In this study, we present a scheme that uses the transmitter in-phase/quadrature-phase imbalance (IQI) and the power amplifier (PA) nonlinearity as RF fingerprint features in time-division duplexing (TDD) OFDM systems, which are always considered to be harmful to data transmission. The scheme consists of two round trips with four steps for two cases: in the first, the IQI and PA nonlinearity are unknown at the terminal; in the second, they are known at the terminal. A channel state information (CSI)-tracking algorithm based on the sliding-window least squares method is first adopted at the terminal. In case A, the obtained CSI is sent to the base station (BS) to remove its impact there; in case B, this removal is conducted directly by using pre-equalization at the terminal. Then, by following a sequential iterative approach, the IQI and nonlinearity are individually calculated. Theoretical analyses reveal how CSI estimation errors influence subsequent estimates at the BS in these two cases. Furthermore, the approximate unbiasedness is verified. The theoretical variance and Cramer–Rao lower bound (CRLB) are also given. It is indicated that the theoretical minimum variance in case B is lower than that in case A from the perspective of the CRLB. The numerical results demonstrate the efficiency of the scheme in comparison with existing techniques in the literature.
Adaptive Line Enhancer Based on Maximum Correntropy Criterion and Frequency Domain Sparsity for Passive Sonars
Authors: Zhang Nan , An Liang , Yu Yun , Wang Xiaoyan
Published: October 2023

The low-frequency narrowband components (known as lines) in the radiated noise of underwater acoustic targets are an important feature of passive sonar detection. Conventional adaptive line enhancer (ALE) based on the least mean square algorithm has limited performance under colored background noise and low signal-to-noise ratio (SNR). In this paper, by combining the frequency domain sparse model of lines and maximum correntropy criterion (MCC), a β-adaptive l0-MCC-ALE is proposed to solve the above-mentioned problem. The proposed ALE uses a sparse-driven MCC algorithm to update the weight vector in the frequency domain to further suppress the colored background noise. For the problem that the value of parameter β is sensitive to the performance, β is updated adaptively according to the frequency response of ALE in each iteration. Simulation and real data processing results show that the proposed ALE is insensitive to the given parameter β and has excellent performance for line enhancement. Compared with conventional ALE, the SNR of lines can be improved by 7~8 dB.
Power/Area-Efficient ECC Processor Implementation for Resource-Constrained Devices
Authors: Zeghid Medien , Sghaier Anissa , Ahmed Hassan Yousif , Abdalla Osman Ahmed
Published: October 2023

The use of resource-constrained devices is rising nowadays, and these devices mostly operate with sensitive data. Consequently, security is a key issue for these devices. In this paper, we propose a compact ECC (elliptic curve cryptography) architecture for resource-constrained devices based on López–Dahab (LD) projective point arithmetic operations on GF(2m). To achieve an efficient area-power hardware ECC implementation, an efficient digit-serial multiplier is developed. The proposed multiplier is built on a Bivariate Polynomial Basis representation and a modified Radix-n Interleaved Multiplication (mRnIM) method (for area and power complexities reduction). Furthermore, the LD-Montgomery point multiplication algorithm is adjusted for accurate scheduling in the compact ECC architecture to eliminate data reliance and improve signal management. Meanwhile, the area complexity is reduced by reuse of resources, and clock gating and asynchronous counter are exploited to reduce the power consumption. Finally, the proposed compact ECC architecture is implemented over GF(2m) (m = 163, 233, 283, 409, and 571) on Xilinx FPGAs’ (Field-Programmable Gate Array) Virtex 5, Virtex 6, and Virtex 7, showing that the efficiency of this design outperforms to date when compared to reported works individually. It utilizes less area and consumes low power. The FPGA results clearly demonstrate that the proposed ECC architecture is appropriate for constraint-resources devices.
Concept of an Innovative System for Dimensioning and Predicting Changes in the Coastal Zone Topography Using UAVs and USVs (4DBatMap System)
Authors: Specht Oktawia , Specht Mariusz , Stateczny Andrzej , Specht Cezary
Published: October 2023

This publication is aimed at developing a concept of an innovative system for dimensioning and predicting changes in the coastal zone topography using Unmanned Aerial Vehicles (UAVs) and Unmanned Surface Vehicles (USVs). The 4DBatMap system will consist of four components: 1. Measurement data acquisition module. Bathymetric and photogrammetric measurements will be carried out with a specific frequency in the coastal zone using a UAV equipped with a Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), Light Detection And Ranging (LiDAR) and a photogrammetric camera, as well as a USV equipped with a GNSS Real Time Kinematic (RTK) receiver and a MultiBeam EchoSounder (MBES). 2. Multi-sensor geospatial data fusion module. Low-altitude aerial imagery, hydrographic and LiDAR data acquired using UAVs and USVs will be integrated into one. The result will be an accurate and fully covered with measurements terrain of the coastal zone. 3. Module for predicting changes in the coastal zone topography. As part of this module, a computer application will be created, which, based on the analysis of a time series, will determine the optimal method for describing the spatial and temporal variability (long-term trend and seasonal fluctuations) of the coastal zone terrain. 4. Module for imaging changes in the coastal zone topography. The final result of the 4DBatMap system will be a 4D bathymetric chart to illustrate how the coastal zone topography changes over time.
Analyzing Impacts of Amplitude Modulation Index on Performance Characteristics of Three-Phase Nine-Level Modular Multilevel Converters
Authors: Alhaj Omar Fuad , Pamuk Nihat
Published: October 2023

Modular multilevel converters (MMCs) represent the forefront of power converter technology, with wide-ranging applications across diverse industries. Over recent decades, substantial research and development efforts have been dedicated to enhancing MMCs’ performance. A significant challenge in power conversion processes is the presence of total harmonic distortion (THD) in output waveforms, which can have adverse effects on electrical equipment. In response, extensive studies have been conducted to address THD-related challenges by refining the control and operation of MMCs. This study investigates the effect of the amplitude modulation index (Ma) on the total harmonic distortion (THD) in nine-level MMC output waves. For this, a standard three-phase and nine-level MMC model was built and simulated in MATLAB/ Simulink environment, and the Ma value was shifted between 0.1 and 1.5. The output current and voltage waves were analyzed, and the optimal limits for the Ma values yielding the lowest THD values were determined. The simulation outcomes reveal a crucial Ma range between 0.6 and 1.2, where THD is significantly minimized. Ma values below 0.6 introduce significant harmonic distortion in the voltage waves, while values surpassing 1.2 lead to appreciable harmonic distortion in the current wave. This study contributes valuable insights for engineers and researchers and aids in the refinement of MMC control strategies and the mitigation of THD-related challenges in power systems.
RayBench: An Advanced NVIDIA-Centric GPU Rendering Benchmark Suite for Optimal Performance Analysis
Authors: Wang Peng , Yu Zhibin
Published: October 2023

This study aims to collect GPU rendering programs and analyze their characteristics to construct a benchmark dataset that reflects the characteristics of GPU rendering programs, providing a reference basis for designing the next generation of graphics processors. The research framework includes four parts: GPU rendering program integration, data collection, program analysis, and similarity analysis. In the program integration and data collection phase, 1000 GPU rendering programs were collected from open-source repositories, and 100 representative programs were selected as the initial benchmark dataset. The program analysis phase involves instruction-level, thread-level, and memory-level analysis, as well as five machine learning algorithms for importance ranking. Finally, through Pearson similarity analysis, rendering programs with high similarity were eliminated, and the final GPU rendering program benchmark dataset was selected based on the benchmark’s comprehensiveness and representativeness. The experimental results of this study show that, due to the need to load and process texture and geometry data in rendering programs, the average global memory access efficiency is generally lower compared to the averages of the Rodinia and Parboil benchmarks. The GPU occupancy rate is related to the computationally intensive tasks of rendering programs. The efficiency of stream processor execution and thread bundle execution is influenced by branch statements and conditional judgments. Common operations such as lighting calculations and texture sampling in rendering programs require branch judgments, which reduce the execution efficiency. Bandwidth utilization is improved because rendering programs reduce frequent memory access and data transfer to the main memory through data caching and reuse. Furthermore, this study used multiple machine learning methods to rank the importance of 160 characteristics of 100 rendering programs on four different NVIDIA GPUs. Different methods demonstrate robustness and stability when facing different data distributions and characteristic relationships. By comparing the results of multiple methods, biases inherent to individual methods can be reduced, thus enhancing the reliability of the results. The contribution of this study lies in the analysis of workload characteristics of rendering programs, enabling targeted performance optimization to improve the efficiency and quality of rendering programs. By comprehensively collecting GPU rendering program data and performing characteristic analysis and importance ranking using machine learning methods, reliable reference guidelines are provided for GPU design. This is of significant importance in driving the development of rendering technology.
Effect of Interfacial Oxide Layers on Self-Doped PEDOT/Si Hybrid Solar Cells
Authors: Saha Aditya , Oshima Ryuji , Ohori Daisuke , Sasaki Takahiko , Yano Hirokazu , Okuzaki Hidenori , Tokumasu Takashi , Endo Kazuhiko , Samukawa Seiji
Published: October 2023

PEDOT:PSS/Si hybrid photovoltaic cells have been attracting attention as a potential way to simplify the manufacturing process and democratize solar energy production. Control of the PEDOT/Si interface is also one of the primary ways to ensure the improved performance and lifetimes of multijunction devices, such as perovskite/Si tandem solar cells. In this work, the effects of the interfacial silicon oxide layer were investigated by creating a novel and controllable neutral beam oxide interlayer with different thicknesses. A novel self-doped PEDOT (S-PEDOT) was used to improve interfacial contact and avoid the secondary doping of PEDOT:PSS. X-ray photoelectron spectroscopy (XPS) showed that the saturation of interfacial silicon atoms in SiOx-Si bonds as well as a very thin, (~1 nm) damage-free oxide interlayer were the keys to maintaining good passivation with a high tunneling current. Lifetime measurements also showed that the interlayers with the most SiO2 content degraded the least. The degradation of the devices was due to the continued growth of the oxide layer through reactions with silicon sub-oxides and the degradation of S-PEDOT.
Prediction Modeling of Flue Gas Control for Combustion Efficiency Optimization for Steel Mill Power Plant Boilers Based on Partial Least Squares Regression (PLSR)
Authors: Lee Sang-Mok , Choi So-Won , Lee Eul-Bum
Published: October 2023

The energy-intensive steel industry, which consumes substantial amounts of electricity, meets its power demands through external electricity purchases and self-generation through the operation of its own generators. This study aimed to optimize boiler combustion efficiency and increase power generation output by deriving optimal operational values for O2 and CO within the boiler flue gas using machine learning (ML) with the aim of achieving maximum boiler efficiency. This study focuses on the power-generation boilers at steel mill P in Korea. First, 361 types of operation data from power generation equipment were collected and preprocessed. Subsequently, a partial least squares regression (PLSR) algorithm was used to develop a prediction model for O2 and CO values, known as the Boiler Flue Gas Prediction Model (BFG-PM). The prediction accuracy for O2 was notably high (83.2%), whereas that for CO was lower (53.4%). Nonetheless, the model’s reliability was high because more than 90% of the predicted values were within a 10% error range. Finally, the correlation of the BFG-PM model was applied to the performance test code (PTC) 4.0 for the boiler efficiency calculations formula, deriving the optimal O2 and CO control points. Through a simulation, it was verified that the boiler efficiency was improved by controlling the combustion air. In addition, an average increase in boiler efficiency of 0.29% was confirmed by applying it directly to the generator operating on-site. The results of this study are expected to contribute to annual cost savings, with a reduction of USD 217,000 in electricity purchasing costs and USD 19,700 in greenhouse gas emissions trading expenses.
Performance Assessment of Solar Desiccant Air Conditioning System under Multiple Controlled Climatic Zones of Pakistan
Authors: Ullah Sibghat , Ali Muzaffar
Published: October 2023

Over the past decade, the integration of desiccant technology with evaporative cooling methods has proven to be highly effective and efficient in providing comfortable indoor environments. The performance of desiccant-based direct evaporative cooling (DEC) systems is strongly influenced by environmental conditions, and their output behavior varies across multiple climatic zones. It is not easy to assess the system performance in numerous climatic zones as it is a time-consuming process. The current study focuses on determining the feasibility of a solid desiccant integrated with a direct evaporative cooler (SDI-DEC) for three different climatic zones of Pakistan: Lahore (hot and humid), Islamabad (hot and semi-humid) and Karachi (moderate and humid). To serve this purpose, a specially designed controlled climate chamber with an integrated air handling unit (AHU) was installed to create multiple environmental conditions artificially. It could also provide global climatic conditions under temperature and absolute humidity ranges of 10 °C to 50 °C and 10 g/kg to 20 g/kg, respectively. The weather conditions of the selected cities were artificially generated in the climate chamber. Based on different operating conditions, such as inlet air temperature, humidity and regeneration temperature, the performance of the system was estimated using performance indicators like COP, dehumidification effectiveness, solar fraction and supply air conditions. Results showed that the maximum temperature achieved from solar collectors was about 70 °C from collectors with an area of 9.5 m2. Moreover, the observations showed that when the regeneration temperature was increased from 60 °C to 80 °C, the COP of the system decreased about 41% in a moderate and humid climate, 28% in a hot and semi-humid environment and 23% in a hot and humid climate. The results revealed that an SDI-DEC system has the potential to overcome the humidity and cooling loads of the multiple climatic scenarios of Pakistan.
Investigation of Flow Fields Emanating from Two Parallel Inlet Valves Using LES, PIV, and POD
Authors: Hoffmann Jana , Vera-Tudela Walter , Mirsch Niklas , Wüthrich Dario , Schneider Bruno , Günther Marco , Pischinger Stefan , Weiss Daniel A. , Herrmann Kai
Published: October 2023

Understanding cycle-to-cycle variations (CCV) is of practical importance for the combustion of fossil and renewable fuels, as increasingly stringent emission regulations require reductions in the negative effects of such variations. The subject of this study is the flow around inlet valves, since oscillations of such inlet flows affect the flow structure in the cylinder and are thus one of the causes of CCV. To this end, a parametric analysis of the influences of the mass flow rate and valve lift of two parallel engine intake valves on the flow structures is performed. This follows on from an earlier similar study where the flow around a single intake valve was investigated. To analyse the flow behaviour and, in particular, the interactions of the flow leaving these two valves, an optical test rig for 2D particle image velocimetry (PIV) and a large eddy simulation (LES) are used. Proper orthogonal decomposition (POD), together with a quadruple decomposition and the Reynolds stress transport equations, are used to study the turbulence phenomena. The PIV and LES results are in good agreement with each other. The detailed LES analysis of the flow structures shows that, for small valve lifts, the flow separates along the whole perimeter of the intake valve, and for larger valve lifts, the flow escapes only to one side. This is, for combustion engines with the tumble concept, the stage at which the tumble movement develops. Moreover, the flow structures are strongly influenced by the valve lift, while they are unaffected by the variation in the mass flow. The turbulent kinetic energy in the flow field increases quadratically with a decreasing valve lift and increasing mass flow. The large, high-energetic flow structures are particularly dominant near the jet, and the small, low-energetic structures are homogeneously distributed within the flow field. The specific Reynolds stress transport equation shows the limitations of two-dimensionality and large timesteps in the PIV results and the limitations of the LES model.
Research on Deployment Scheme and Routing Optimization Algorithm of Distribution Cable Condition Monitoring Devices
Authors: Wu Jun , Li Mingzhen , Gao Chao , Liu Zehui , Zhang Bo , Zhang Xinsong
Published: October 2023

In order to achieve more effective online monitoring of distribution cables, a deployment scheme of the distribution cable condition monitoring devices based on a wireless sensor network (WSN) has been proposed. The proposed deployment scheme can improve the coverage rate and extend the lifetime of the sensor network. Moreover, the clustering method, node density, and node deployment method of the wireless sensor routing algorithm are improved, and based on isosceles triangle non-uniform deployment, a routing optimization algorithm has been proposed to achieve the balance of the energy consumption of each node in the network. Firstly, according to the energy consumption model of the network, the energy consumption of each cluster is calculated, and then by taking the minimum energy consumption of data transmission between clusters as the constraint condition, the optimal clustering distance of the network is solved. Then, according to the scale of network nodes, the density of routing nodes in each cluster is calculated, and the routing nodes in the cluster are deployed by an isosceles triangle. Finally, according to the cluster head election formula, the routing cluster head nodes in each cluster are selected, and the network data information is transmitted to the base station in a multi-hop manner through the routing cluster head nodes. The simulation results indicated that, compared with the traditional routing optimization algorithms, the proposed algorithm could keep the routing coverage at more than 200% all the time, and can effectively balance the energy consumption of nodes, improve the energy utilization efficiency of the routing nodes, and at least extend the lifetime of the network by two times. Moreover, the longer the cables, the more cost savings and the better the life cycle optimization effect of the proposed scheme. In addition, the proposed scheme can greatly reduce the economic cost of network investment, compared with using the demodulator to obtain monitoring data.
Agreement in All-in-One Dataset between Diagnosis and Prescribed Medication for Common Cardiometabolic Diseases in the NDB-K7Ps
Authors: Sekine Airi , Nakajima Kei
Published: October 2023

The Japanese National Database (NDB), a useful data source for epidemiological studies, contains information on health checkups, disease diagnoses, and medications, which can be used when investigating common cardiometabolic diseases. However, before the initiation of an integrated analysis, we need to combine several pieces of information prepared separately into an all-in-one dataset (AIOD) and confirm the validation of the dataset for the study. In this study, we aimed to confirm the degree of agreement in data entries between diagnoses and prescribed medications and self-reported pharmacotherapy for common cardiometabolic diseases in newly assembled AIODs. The present study included 10,183,619 people who underwent health checkups from April 2018 to March 2019. Over 95% of patients prescribed antihypertensive and antidiabetic medications were diagnosed with each disease. For dyslipidemia, over 95% of patients prescribed medications were diagnosed with at least one of the following: dyslipidemia, hypercholesterolemia, or hyperlipidemia. Similarly, over 95% of patients prescribed medications for hyperuricemia were diagnosed with either hyperuricemia or gout. Additionally, over 90% of patients with self-reported medications for hypertension, diabetes, and dyslipidemia were diagnosed with each disease, although the proportions differed among age groups. Our study demonstrated high levels of agreement between diagnoses and prescribed medications for common cardiometabolic diseases and self-reported pharmacotherapy in our AIOD.
Engineering the C3N Pathway as a Short Detour for De Novo NAD+ Biosynthesis in Saccharomyces cerevisiae
Authors: Li Xinli , Tang Yue , Ding Yong , Li Pengwei , Chen Yihua
Published: October 2023

As a life-essential coenzyme, nicotinamide adenine dinucleotide (NAD+) has been explored for more than a century. In Saccharomyces, the natural NAD+de novo biosynthetic pathway initiating from tryptophan has been well elucidated. To bypass this stringently controlled natural pathway in yeast, an economical C3N pathway that was developed in Escherichia coli previously was constructed in Saccharomyces as a short detour for de novo NAD+ biosynthesis. After the functional expressions of the C3N genes were identified in Saccharomyces cerevisiae BY4741 by in vitro enzymatic assays, the C3N module was introduced into an NAD+ auxotrophic S. cerevisiae strain BY01, in which the BNA2 gene encoding tryptophan 2,3-dioxygenase was inactivated. The efficient NAD+ synthesis via the C3N pathway was confirmed by both plate assays and fermentation analysis. The applicability of the C3N pathway in cofactor engineering was tested by introducing it into S. cerevisiae BY4741, which improved the cellular NAD(H) level considerably. Consequently, this study proved that the de novo NAD+ biosynthetic pathway can be replaced by an artificial pathway in yeast, which paves a way to design more promising schemes in eukaryotes for rational manipulation of the cellular NAD(H) levels.
Application of Thymol Vapors to Control Postharvest Decay Caused by Penicillium digitatum and Lasiodiplodia theobromae in Grapefruit
Authors: Olmedo Gabriela M. , Zhang Jiuxu , Zhao Wei , Mattia Matthew , Rosskopf Erin N. , Ritenour Mark , Plotto Anne , Bai Jinhe
Published: October 2023

Two of the major postharvest diseases impacting grapefruit shelf life and marketability in the state of Florida (USA) are stem-end rot (SER) caused by Lasiodiplodia theobromae and green mold (GM) caused by Penicillium digitatum. Here, we investigated the in vitro and in vivo efficacy of vapors of thymol, a natural compound found in the essential oil of various plants and the primary constituent of thyme (Thymus vulgaris) oil, as a potential solution for the management of GM and SER. Thymol vapors at concentrations lower than 10 mg L−1 significantly inhibited the mycelial growth of both pathogens, causing severe ultrastructural damage to P. digitatum conidia. In in vivo trials, the incidence and lesion area of GM and SER on inoculated grapefruit were significantly reduced after a 5 d exposure to 50 mg L−1 thymol vapors. In addition, the in vitro and in vivo sporulation of P. digitatum was suppressed by thymol. When applied in its vapor phase, thymol had no negative effect on the fruit, neither introducing perceivable off-flavor nor causing additional weight loss. Our findings support the pursuit of further studies on the use of thymol, recognized as safe for human health and the environment, as a promising strategy for grapefruit postharvest disease management.
Marinades Based on Natural Ingredients as a Way to Improve the Quality and Shelf Life of Meat: A Review
Authors: Latoch Agnieszka , Czarniecka-Skubina Ewa , Moczkowska-Wyrwisz Małgorzata
Published: October 2023

Marinating is a traditional method of improving the quality of meat, but it has been modified in response to consumer demand for “clean label” products. The aim of this review is to present scientific literature on the natural ingredients contained in marinades, the parameters of the marinating process, and certain mechanisms that bring about changes in meat. A review was carried out of publications from 2000 to 2023 available in Web of Science on the natural ingredients of meat marinades: fruit and vegetables, seasonings, fermented dairy products, wine, and beer. The review showed that natural marinades improve the sensory quality of meat and its culinary properties; they also extend its shelf life. They affect the safety of meat products by limiting the oxidation of fats and proteins. They also reduce biogenic amines and the formation of heterocyclic aromatic amines (HAAs) and polycyclic aromatic hydrocarbons (PAHs). This is possible due to the presence of biologically active substances and competitive microflora from dairy products. However, some marinades, especially those that are acidic, cause a slightly acidic flavour and an unfavourable colour change. Natural compounds in the ingredients of marinades are accepted by consumers. There are no results in the literature on the impact of natural marinades on the nutritional value and health-promoting potential of meat products, so it can be assumed that this is a future direction for scientific research.
Effect of Adding Different Commercial Propylene Glycol Alginates on the Properties of Mealworm-Flour-Formulated Bread and Steamed Bread
Authors: Xie Xinyuan , Zhao Xiaolong , Meng Fanjian , Ren Yupeng , An Jianhui , Deng Lingli
Published: October 2023

Mealworm-flour-formulated flour-based products have gained increasing attention; however, their textural properties need to be improved. Propylene glycol alginate (PGA) is a commercial food additive with excellent emulsifying and stabilizing capabilities. We evaluated the effects of adding three commercially available PGAs (0.3% w/w, as food additive) on the properties of 10% concentration of mealworm-flour-formulated bread and steamed bread. The results showed that, compared with the control (2.17 mL/g), three PGA brands (Q, M, and Y) significantly increased the specific volume of the bread to 3.34, 3.40, and 3.36 mL/g, respectively. Only PGA from brand Q significantly improved the specific volumes of bread and steamed bread. The color of the bread was affected by the Maillard reaction. The addition of PGAs also augmented the moisture content of the fresh bread crumbs and steamed bread crumbs. All three PGAs improved the textural properties of bread and steamed bread. During storage, PGA addition delayed the staling of bread and steamed bread. In summary, our study showed that the addition of 0.3% PGA from three different producers improved bread properties, with PGA from brand Q having the most substantial effect. PGA had a more substantial effect on bread than steamed bread. Our results provide a theoretical basis to guide the development of insect-formulated flour-based products.
Prevalence of Foodborne Bacterial Pathogens and Antibiotic Resistance Genes in Sweets from Local Markets in Iran
Authors: Pakbin Babak , Amani Zahra , Rahimi Zahra , Najafi Somayeh , Familsatarian Behnaz , Khakpoor Alireza , Brück Wolfram Manuel , Brück Thomas B.
Published: October 2023

Background: This study aimed to investigate the prevalences of some important antibiotic-resistance genes (ARGs) and foodborne bacterial pathogens in sweet samples collected from local markets in Iran. Methods: Forty sweet samples were collected. Foodborne pathogens and ARGs were detected in the sweet samples by conventional and multiplex PCR assays using species-specific primers. Results: Staphylococcus aureus, Cronobacter sakazakii, Shigella spp., Campylobacter jejuni, and Campylobacter coli were detected and identified in 47.5%, 20%, 45%, 5%, and 30% of the sweet samples, respectively. We found S. aureus and Shigella spp. were the most prevalent bacterial pathogens. S. aureus was found to be the most frequent pathogenic bacteria profiled in these samples. We also found a significant correlation between the presence of C. coli and Cr. sakazakii. We detected the blaSHV resistance gene in 97.5% of the sweet samples; however, blaTEM was detected in only one sample (2.5%). Conclusions: Regarding these results, we suggest preventive strategies such as implementing automation of food processing; monitoring the personal hygiene and health of food handlers, and testing regularly for antibiotic resistance in raw materials and products.
Cooking Methods for Preserving Isothiocyanates and Reducing Goitrin in Brassica Vegetables
Authors: Panduang Thanaporn , Phucharoenrak Pakkapong , Karnpanit Weeraya , Trachootham Dunyaporn
Published: October 2023

Glucosinolates in Brassica vegetables can be hydrolyzed into various products, e.g., chemopreventive agents, isothiocyanates (ITCs) and anti-thyroid substance, goitrin. Cooking can reduce goitrin but destroy isothiocyanates. This study aimed to optimize cooking conditions for reducing goitrin while preserving isothiocyanates in Brassica vegetables. Cabbage and Chinese kale samples were divided evenly into raw, blanched, steamed, and water-based stir-fried samples. Cooking temperature and time were varied at 60, 80, or 100 °C for 2, 4, or 6 min. The levels of goitrin, benzyl isothiocyanate (BITC), and sulforaphane (SFN) were measured using LC-MS/MS. Response surface model (RSM) was used to identify the optimal cooking conditions to reduce goitrin but preserve ITCs. Results showed that goitrin content in cabbage depended on the cooking methods, temperature, and time, while that of Chinese kale only depended on the methods. In contrast, the concentrations of SFN in cabbage and BITC in kale depended on the cooking temperature and time but not methods. Based on RSM analysis, the suggested household cooking methods for preserving isothiocyanates and reducing goitrin are steaming cabbage at 80–100 °C for 4 min and stir-frying Chinese kale at 60–100 °C for 2 min. Such methods may preserve the bioactive compounds while reducing food hazards.
Precise Conditions on the Unique Solvability of the Linear Fractional Functional Differential Equations Related to the ς-Nonpositive Operators
Authors: Dilna Natalia
Published: October 2023

Exact conditions for the existence of the unique solution of a boundary value problem for linear fractional functional differential equations related to ς-nonpositive operators are established. The exact solvability conditions are based on the a priori estimation method. All theoretical investigations are illustrated by an example of the pantograph-type model from electrodynamics.
Fractal Derivatives and Singularity Analysis of Frequency—Depth Clusters of Earthquakes along Converging Plate Boundaries
Authors: Cheng Qiuming
Published: October 2023

Fractional calculus (FC) has recently received increasing attention due to its applications in many fields involving complex and nonlinear systems. However, one of the key challenges in using FC to deal with fractal or multifractal phenomena is how to relate functions to geometries with fractal dimensions. The current paper demonstrates how fractal calculus can be used to represent physical properties such as density defined on fractal geometries that no longer have the Lebesgue additive properties required for ordinary calculus. First, it introduces the recently proposed concept of fractal density, that is, densities defined on fractals and multifractals, and then shows how fractal calculus can be used to describe fractal densities. Finally, the singularity analysis based on fractal density calculation is used to analyze the depth clustering distribution of seismic frequencies around the Moho transition zone in the subduction zone of the Pacific plates and the Tethys collision zones. The results show that three solutions (linear, log-linear, and double log-linear) of a unified differential equation can describe the decay rate of the fractal density of depth clusters at the number (frequencies) of earthquakes. The spatial distribution of the three groups of earthquakes is further divided according to the three attenuation relationships. From north latitude to south latitude, from the North Pacific subduction zone to the Tethys collision zone, and then to the South Pacific subduction zone, the attenuation relationships of the earthquake depth distribution are generally from a linear, to log-linear, to double log-linear pattern. This provides insight into the nonlinearity of the depth distribution of earthquake swarms.
Controllability Analysis of Impulsive Multi-Term Fractional-Order Stochastic Systems Involving State-Dependent Delay
Authors: Arthi G. , Vaanmathi M. , Ma Yong-Ki
Published: October 2023

This study deals with the controllability of multi-term fractional-order stochastic systems with impulsive effects and state-dependent delay that exhibit damping behavior. Based on fractional calculus theory, the Caputo fractional derivative is utilized to analyze the controllability of fractional-order systems. Mittag–Leffler functions and Laplace transform are used to derive the solution set of the problem. Sufficient conditions for the controllability of nonlinear systems are achieved using fixed-point techniques and stochastic theory. Finally, the results stated in the paper are validated using examples.
Editorial for Special Issue: Advances in Smart and Tough Hydrogels
Authors: Zhang Dong , Yang Jintao , Le Xiaoxia , Song Dianwen
Published: October 2023

Smart hydrogels possess both intelligent and responsive properties, which are designed to exhibit specific responses to external stimuli such as changes in temperature, pH, or the presence of specific ions/counterions, making them “smart” or “responsive” materials [...]
Emerging Advances in Microfluidic Hydrogel Droplets for Tissue Engineering and STEM Cell Mechanobiology
Authors: Orabi Mohamad , Lo Joe F.
Published: October 2023

Hydrogel droplets are biodegradable and biocompatible materials with promising applications in tissue engineering, cell encapsulation, and clinical treatments. They represent a well-controlled microstructure to bridge the spatial divide between two-dimensional cell cultures and three-dimensional tissues, toward the recreation of entire organs. The applications of hydrogel droplets in regenerative medicine require a thorough understanding of microfluidic techniques, the biocompatibility of hydrogel materials, and droplet production and manipulation mechanisms. Although hydrogel droplets were well studied, several emerging advances promise to extend current applications to tissue engineering and beyond. Hydrogel droplets can be designed with high surface-to-volume ratios and a variety of matrix microstructures. Microfluidics provides precise control of the flow patterns required for droplet generation, leading to tight distributions of particle size, shape, matrix, and mechanical properties in the resultant microparticles. This review focuses on recent advances in microfluidic hydrogel droplet generation. First, the theoretical principles of microfluidics, materials used in fabrication, and new 3D fabrication techniques were discussed. Then, the hydrogels used in droplet generation and their cell and tissue engineering applications were reviewed. Finally, droplet generation mechanisms were addressed, such as droplet production, droplet manipulation, and surfactants used to prevent coalescence. Lastly, we propose that microfluidic hydrogel droplets can enable novel shear-related tissue engineering and regeneration studies.
Formulation and Characterization of Hesperidin-Loaded Transethosomal Gel for Dermal Delivery to Enhance Antibacterial Activity: Comprehension of In Vitro, Ex Vivo, and Dermatokinetic Analysis
Authors: Alam Perwez , Imran Mohd , Jahan Samreen , Akhtar Ali , Hasan Zafrul
Published: October 2023

In this study, hesperidin was loaded into a transethosome and was developed employing the rotary evaporator method. The formulation was optimized using the Box–Behnken design (BBD). The optimized HSD-TE formulation has a spherical shape, vesicle size, polydispersity index, entrapment efficiency, and zeta potential within the range of 178.98 nm; the PDI was 0.259 with a zeta potential of −31.14 mV and % EE of 89.51%, respectively. The in vitro drug release shows that HSD-TE exhibited the release of 81.124 ± 3.45% in comparison to HSD suspension. The ex vivo skin permeation showed a 2-fold increase in HSD-TE gel permeation. The antioxidant activity of HSD-TE was found to be 79.20 ± 1.77% higher than that of the HSD solution. The formulation showed 2-fold deeper HSD-TE penetration across excised rat skin membranes in confocal laser microscopy scanning, indicating promising in vivo prospects. In a dermatokinetic study, HSD-TE gel was compared to HSD conventional gel where TE significantly boosted HSD transport in the epidermis and dermal layers. The formulation showed greater efficacy than free HSD in the inhibition of microbial growth, as evidenced by antibacterial activity on the Gram-negative and positive bacteria. These investigations found that the HSD-TE formulation could enhance the topical application in the management of cutaneous bacterial infections.
Do Pegmatites Crystallise Fast? A Perspective from Petrologically-Constrained Isotopic Dating
Authors: Popov Daniil V.
Published: October 2023

Most recent studies consider the formation of individual pegmatite bodies to be a fast process with estimated crystal growth rates reaching a walloping 10 m/day. This opinion is presumably underpinned by the traditional way of thinking of them as the end products of magmatic fractionation. Indeed, modelling has shown that if a pegmatite-forming substance with a temperature near granitic solidus intrudes into a much colder host rock, as recorded in some outcrops, it must cool rapidly. From here, a conclusion is made that the crystallisation must likewise be rapid. However, this view is challenged by several studies that published isotopic dates supported by petrological characterisation of the analysed materials, which suggested or can be used to suggest that some minerals in pegmatites grew over millions of years. Surprisingly, such in-depth work on the geochronology of individual pegmatite bodies is relatively uncommon, so it is early to make generalisations. Here, I highlight some of the existing evidence with the aim to stimulate further research into the timescales of pegmatite crystallisation, including the use of petrologically constrained isotopic dating.