bluuebunny/crossref_metadata_2025 huggingface dataset:
Metabolic Effects of Elicitors on the Biosynthesis of Tropane Alkaloids in Medicinal Plants
Authors: Wen Yuru , Liao Yiran , Tang Yueli , Zhang Hongbo , Zhang Jiahui , Liao Zhihua
Published: August 2023

Tropane alkaloids (TAs) are large secondary metabolite alkaloids that find extensive applications in the synthesis of antidotes, anesthetics, antiemetics, motion sickness drugs, and antispasmodics. The current production method primarily depends on extraction from medicinal plants of the Solanaceae family. Elicitation, as a highly effective biotechnological approach, offers significant advantages in augmenting the synthesis of secondary metabolites. The advantages include its simplicity of operation, low cost, and reduced risk of contamination. This review focuses on the impact of elicitation on the biosynthesis of TAs from three aspects: single-elicitor treatment, multiple-elicitor treatment, and the combination of elicitation strategy with other strategies. Some potential reasons are also proposed. Plant hormones and growth regulators, such as jasmonic acid (JA), salicylic acid (SA), and their derivatives, have been extensively employed in the separate elicitation processes. In recent years, novel elicitors represented by magnetic nanoparticles have emerged as significant factors in the investigation of yield enhancement in TAs. This approach shows promising potential for further development. The current utilization of multi-elicitor treatment is constrained, primarily relying on the combination of only two elicitors for induction. Some of these combinations have been found to exhibit synergistic amplification effects. However, the underlying molecular mechanism responsible for this phenomenon remains largely unknown. The literature concerning the integration of elicitation strategy with other strategies is limited, and several research gaps require further investigation. In conclusion, the impact of various elicitors on the accumulation of TAs is well-documented. However, further research is necessary to effectively implement elicitation strategies in commercial production. This includes the development of stable bioreactors, the elucidation of regulatory mechanisms, and the identification of more potent elicitors.
Invasive Wedelia trilobata Performs Better Than Its Native Congener in Various Forms of Phosphorous in Different Growth Stages
Authors: Hu Die , Khan Irfan Ullah , Wang Jiahao , Shi Xinning , Jiang Xinqi , Qi Shanshan , Dai Zhicong , Mao Hanping , Du Daolin
Published: August 2023

At present, many hypotheses have been proposed to explain the mechanism of alien plants’ successful invasion; the resource fluctuations hypothesis indicates that nutrient availability is a main abiotic factor driving the invasion of alien plants. Higher phosphorus utilization and absorption efficiency might be one of the important reasons for alien plants successful invasion. Wedelia trilobata, one of the notorious invasive weeds in China, possesses a strong ability to continue their development under infertile habitats. In this study, firstly, W. trilobata and its native congener, W. chinensis, were grown in various phosphorus forms to test their absorption efficiency of phosphorus. Secondly, the different responses of W. trilobata and W. chinensis to the insoluble phosphorus in three growth stages (at 30, 60, and 150 days cultivation) were also tested. The results showed that the growth rate, root morphology, and phosphorus absorption efficiency of W. trilobata under various insoluble, organic, or low phosphorus conditions were significantly higher than that of W. chinensis. During the short-term cultivation period (30 d), the growth of W. trilobata under insoluble and low phosphorus treatments had no significant difference, and the growth of W. trilobata in insoluble phosphorus treatment also had no significant effect in long-term cultivation (60 and 150 d). However, the growth of W. chinensis in each period under the conditions of insoluble and low phosphorus was significantly inhibited throughout these three growth stages. Therefore, invasive W. trilobata had a higher phosphorus utilization efficiency than its native congener. This study could explain how invasive W. trilobata performs under nutrient-poor habitats, while also providing favorable evidence for the resource fluctuations hypothesis.
Enhancing Phosphorus and Nitrogen Uptake in Maize Crops with Food Industry Biosolids and Azotobacter nigricans
Authors: Vera-García Sara-Luz , Rodríguez-Casasola Felipe-Neri , Barrera-Cortés Josefina , Albores-Medina Arnulfo , Muñoz-Páez Karla M. , Cañizares-Villanueva Rosa-Olivia , Montes-Horcasitas Ma.-Carmen
Published: August 2023

The problem of phosphorus and nitrogen deficiency in agricultural soils has been solved by adding chemical fertilizers. However, their excessive use and their accumulation have only contributed to environmental contamination. Given the high content of nutrients in biosolids collected from a food industry waste treatment plant, their use as fertilizers was investigated in Zea mays plants grown in sandy loam soil collected from a semi-desert area. These biosolids contained insoluble phosphorus sources; therefore, given the ability of Azotobacter nigricans to solubilize phosphates, this strain was incorporated into the study. In vitro, the suitable conditions for the growth of Z. mays plants were determined by using biosolids as a fertilizer and A. nigricans as a plant-growth-promoting microorganism; in vitro, the ability of A. nigricans to solubilize phosphates, fix nitrogen, and produce indole acetic acid, a phytohormone that promotes root formation, was also evaluated. At the greenhouse stage, the Z. mays plants fertilized with biosolids at concentrations of 15 and 20% (v/w) and inoculated with A. nigricans favored the development of bending strength plants, which was observed on the increased stem diameter (>13.5% compared with the negative control and >7.4% compared with the positive control), as well as a better absorption of phosphorus and nitrogen, the concentration of which increased up to 62.8% when compared with that in the control treatments. The interactions between plants and A. nigricans were observed via scanning electron microscopy. The application of biosolids and A. nigricans in Z. mays plants grown in greenhouses presented better development than when Z. mays plants were treated with a chemical fertilizer. The enhanced plant growth was attributed to the increase in root surface area.
Real-Time Detection Algorithm for Kiwifruit Canker Based on a Lightweight and Efficient Generative Adversarial Network
Authors: Xiang Ying , Yao Jia , Yang Yiyu , Yao Kaikai , Wu Cuiping , Yue Xiaobin , Li Zhenghao , Ma Miaomiao , Zhang Jie , Gong Guoshu
Published: August 2023

Disease diagnosis and control play important roles in agriculture and crop protection. Traditional methods of identifying plant disease rely primarily on human vision and manual inspection, which are subjective, have low accuracy, and make it difficult to estimate the situation in real time. At present, an intelligent detection technology based on computer vision is becoming an increasingly important tool used to monitor and control crop disease. However, the use of this technology often requires the collection of a substantial amount of specialized data in advance. Due to the seasonality and uncertainty of many crop pathogeneses, as well as some rare diseases or rare species, such data requirements are difficult to meet, leading to difficulties in achieving high levels of detection accuracy. Here, we use kiwifruit trunk bacterial canker (Pseudomonas syringae pv. actinidiae) as an example and propose a high-precision detection method to address the issue mentioned above. We introduce a lightweight and efficient image generative model capable of generating realistic and diverse images of kiwifruit trunk disease and expanding the original dataset. We also utilize the YOLOv8 model to perform disease detection; this model demonstrates real-time detection capability, taking only 0.01 s per image. The specific contributions of this study are as follows: (1) a depth-wise separable convolution is utilized to replace part of ordinary convolutions and introduce noise to improve the diversity of the generated images; (2) we propose the GASLE module by embedding a GAM, adjust the importance of different channels, and reduce the loss of spatial information; (3) we use an AdaMod optimizer to increase the convergence of the network; and (4) we select a real-time YOLOv8 model to perform effect verification. The results of this experiment show that the Fréchet Inception Distance (FID) of the proposed generative model reaches 84.18, having a decrease of 41.23 compared to FastGAN and a decrease of 2.1 compared to ProjectedGAN. The mean Average Precision (mAP@0.5) on the YOLOv8 network reaches 87.17%, which is nearly 17% higher than that of the original algorithm. These results substantiate the effectiveness of our generative model, providing a robust strategy for image generation and disease detection in plant kingdoms.
Phylogenetic Partitioning of Gansu Flora: Unveiling the Core Transitional Zone of Chinese Flora
Authors: Li Zizhen , Tian Qing , Chong Peifang , Du Weibo , Wei Jia , Huang Rong
Published: August 2023

Floristic regions, conventionally established using species distribution patterns, have often overlooked the phylogenetic relationships among taxa. However, how phylogenetic relationships influence the historical interconnections within and among biogeographic regions remains inadequately understood. In this research, we compiled distribution data for seed plants in Gansu, a region of significant biogeographic diversity located in northwestern China.We proposed a novel framework for floristic regions within Gansu, integrating distribution data and phylogenetic relationships of genera-level native seed plants, aiming to explore the relationship between phylogenetic relatedness, taxonomic composition, and regional phylogenetic delineation. We found that (1) phylogenetic relatedness was strongly correlated with the taxonomic composition among floras in Gansu. (2) The southeastern Gansu region showed the lowest level of spatial turnover in both phylogenetic relationships and the taxonomic composition of floristic assemblages across the Gansu region. (3) Null model analyses indicated nonrandom phylogenetic structure across the region, where most areas showed higher phylogenetic turnover than expected given the underlying taxonomic composition between sites. (4) Our results demonstrated a consistent pattern across various regionalization schemes and highlighted the preference for employing the phylogenetic dissimilarity approach in biogeographical regionalization investigations. (5) Employing the phylogenetic dissimilarity approach, we identified nine distinct floristic regions in Gansu that are categorized into two broader geographical units, namely the northwest and southeast. (6) Based on the phylogenetic graphic regions of China across this area.
Hybrid CNN-LSTM Deep Learning for Track-Wise GNSS-R Ocean Wind Speed Retrieval
Authors: Arabi Sima , Asgarimehr Milad , Kada Martin , Wickert Jens
Published: August 2023

The NASA Cyclone GNSS (CYGNSS) mission provides one Delay Doppler Map (DDM) per second along observational tracks. To account for spatiotemporal correlations within adjacent DDMs in a track, a deep hybrid CNN-LSTM model is proposed for wind speed prediction. The model combines convolutional and pooling layers to extract features from DDMs in one track, which are then processed by LSTM as a sequence of data. This method leads to a test RMSE of 1.84 m/s. The track-wise processing approach outperforms the architectures that process the DMMs individually, namely based on Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN), and a network based solely on fully connected (FC) layers, as well as the official retrieval algorithm of the CYGNSS mission with RMSEs of 1.92 m/s, 1.92 m/s, 1.93 m/s, and 1.90 m/s respectively. Expanding on the CNN-LSTM model, the CNN-LSTM+ model is proposed with additional FC layers parallel with convolutional and pooling layers to process ancillary data. It achieves a notable reduction in test RMSE to 1.49 m/s, demonstrating successful implementation. This highlights the significant potential of track-wise processing of GNSS-R data, capturing spatiotemporal correlations between DDMs along a track. The hybrid deep learning model processing the data sequentially in one track learns these dependencies effectively, improving the accuracy of wind speed predictions.
A Geospatial Analysis-Based Method for Railway Route Selection in Marine Glaciers: A Case Study of the Sichuan-Tibet Railway Network
Authors: Deng Tao , Sharafat Abubakar , Wie Young Min , Lee Ki Gang , Lee Euiong , Lee Kang Hoon
Published: August 2023

Marine glaciers play a significant role in shaping landforms due to their erosive nature coupled with their surrounding environment. During this process, they pose a natural hazard threat to man-made infrastructure. The dynamic nature of these glaciers poses a particular threat, especially to railway infrastructure constructed in remote areas with glacial activity. Substantial research has been undertaken on the role of threats posed by marine glaciers to railway infrastructure. However, a detailed study of favorable glacier landforms prior to railway construction has yet to be explored. In this study, we propose a geospatial analysis-based method to determine the favorable most landforms shaped by marine glaciers for railway network route selection. This study provides a novel approach by first analyzing the availability of four major favorable landforms shaped by marine glaciers (glacier canyons, valley shoulders, moraine terraces, and ancient dammed lake basins), then proposes a railway route selection method for marine glacier distribution areas involving three steps. First, it is necessary to understand the basic situation of regional glaciers; then, to determine a feasible location for the railway based on judgment of the direct and indirect action areas of glaciers; and finally, through a thematic study of glacial geomorphology, to devise corresponding strategies for using glacial landforms to optimize the railway route. In order to verify the feasibility of the proposed method, it was implemented in the Palong Zangbo watershed of the Sichuan–Tibet railway network. Utilizing the power function method, the glacier basin areas of 22 glacier canyons along the Sichuan–Tibet railway line were identified and the maximum annual average velocity of 75 glaciers over the past ten years was calculated by offset tracking technology. The results indicate that the proposed optimization strategies utilizing glacier canyons for a short and straight route scheme and leveraging moraine terraces for a high-line scheme can provide comprehensive guidance for railway route selection in marine glacial areas.
An Investigation on the Ionospheric Response to the Volcanic Explosion of Hunga Ha’apai, 2022, Based on the Observations from the Meridian Project: The Plasma Drift Variations
Authors: Qiu Shican , Shi Mengxi , Wang Xinye , Zhang Zhanming , Soon Willie , Velasco Herrera Victor Manuel
Published: August 2023

The Hunga Ha’apai volcano eruption (20.536°S, 175.382°W in Tonga) reached its maximum outbreak on 15 January 2022, at 04:15 UT, leading to huge oceanic fluctuations and atmospheric disturbances. This study focuses on the response of the ionosphere to the eruption of Tonga volcano, based on observations from a low-latitude station of the Meridian Project at Fuke, Hainan (19.310°N, 109.080°E). We identified the anomalies in the plasma drift caused by the volcanic eruption and discussed the possible mechanisms. The following results were obtained: (1) The anomalies of ionospheric plasma drift were observed at Fuke Station, during the main eruption; (2) A sudden increase and inversion of the plasma drift velocity occurred on January 15, and a large fluctuation of the drift velocity occurred afterwards; (3) By comparing the anomalous propagation velocity with the background drift, it was confirmed that the anomaly was the response of the low latitude ionosphere to the Tonga volcano eruption. Furthermore, we analyzed a possible mechanism for the effect of volcanic eruptions on ionospheric plasma drift. A large number of charged particles could be brought out by the explosion to generate an atmospheric electric field, which may cause the ionospheric plasma to change its original motion.
Dynamic Lane Reversal Strategy in Intelligent Transportation Systems in Smart Cities
Authors: Li Wenting , Li Jianqing , Han Di
Published: August 2023

Route guidance strategies are an important part of advanced traveler information systems, which are a subsystem of intelligent transportation systems (ITSs). In previous research, many scholars have proposed a variety of route guidance strategies to guide vehicles in order to relieve traffic congestion, but few scholars have considered a strategy to control transportation infrastructure. In this paper, to cope with tidal traffic, we propose a dynamic lane reversal strategy (DLRS) based on the density of congestion clusters over the total road region. When the density reaches 0.37, the reversible lane converts to the opposite direction. When the density falls off to below 0.22, the reversible lane returns back to the conventional direction. The simulation results show that the DLRS has better adaptability for coping with the fluctuation in tidal traffic.
Indoor Content Delivery Solution for a Museum Based on BLE Beacons
Authors: Verde David , Romero Luís , Faria Pedro Miguel , Paiva Sara
Published: August 2023

The digital transformation advancement enables multiple areas to provide modern services to their users. Culture is one of the areas that can benefit from these advances, more specifically museums, by presenting many benefits and the most emergent technologies to the visitors. This paper presents an indoor location system and content delivery solution, based on Bluetooth Low Energy Beacons, that enable visitors to walk freely inside the museum and receive augmented reality content based on the acquired position, which is done using the Received Signal Strength Indicator (RSSI). The solution presented in this paper was created for the Foz Côa Museum in Portugal and was tested in the real environment. A detailed study was carried out to analyze the RSSI under four different scenarios, and detection tests were carried out that allowed us to measure the accuracy of the room identification, which is needed for proper content delivery. Of the 89 positions tested in the four scenarios, 70% of the received signals were correctly received throughout the entire duration of the tests, 20% were received in an intermittent way, 4% were never detected and 6% of unwanted beacons were detected. The signal detection is fundamental for the correct room identification, which was performed with 96% accuracy. Thus, we verified that this technology is suitable for the proposed solution.
Sensor Selection for Tidal Volume Determination via Linear Regression—Impact of Lasso versus Ridge Regression
Authors: Laufer Bernhard , Docherty Paul D. , Murray Rua , Krueger-Ziolek Sabine , Jalal Nour Aldeen , Hoeflinger Fabian , Rupitsch Stefan J. , Reindl Leonhard , Moeller Knut
Published: August 2023

The measurement of respiratory volume based on upper body movements by means of a smart shirt is increasingly requested in medical applications. This research used upper body surface motions obtained by a motion capture system, and two regression methods to determine the optimal selection and placement of sensors on a smart shirt to recover respiratory parameters from benchmark spirometry values. The results of the two regression methods (Ridge regression and the least absolute shrinkage and selection operator (Lasso)) were compared. This work shows that the Lasso method offers advantages compared to the Ridge regression, as it provides sparse solutions and is more robust to outliers. However, both methods can be used in this application since they lead to a similar sensor subset with lower computational demand (from exponential effort for full exhaustive search down to the order of O (n2)). A smart shirt for respiratory volume estimation could replace spirometry in some cases and would allow for a more convenient measurement of respiratory parameters in home care or hospital settings.
Perforated Concave Earplug (pCEP): A Proof-of-Concept Earplug to Improve Sound Localization without Compromising Noise Attenuation
Authors: Fink Nir , Levitas Rachel , Eisenkraft Arik , Wagnert-Avraham Linn , Gertz S. David , Fostick Leah
Published: August 2023

Combat soldiers are currently faced with using a hearing-protection device (HPD) at the cost of adequately detecting critical signals impacting mission success. The current study tested the performance of the Perforated-Concave-Earplug (pCEP), a proof-of-concept passive HPD consisting of a concave bowl-like rigid structure attached to a commercial roll-down earplug, designed to improve sound localization with minimal compromising of noise attenuation. Primarily intended for combat/military training settings, our aim was an evaluation of localization of relevant sound sources (single/multiple gunfire, continuous noise, spoken word) compared to 3M™-Combat-Arms™4.1 earplugs in open-mode and 3M™-E-A-R™-Classic™ earplugs. Ninety normal-hearing participants, aged 20–35 years, were asked to localize stimuli delivered from monitors evenly distributed around them in no-HPD and with-HPD conditions. The results showed (1) localization abilities worsened using HPDs; (2) the spoken word was localized less accurately than other stimuli; (3) mean root mean square errors (RMSEs) were largest for stimuli emanating from rear monitors; and (4) localization abilities corresponded to HPD attenuation levels (largest attenuation and mean RMSE: 3M™-E-A-R™-Classic™; smallest attenuation and mean RMSE: 3M™-Combat-Arms™4.1; pCEP was mid-range on both). These findings suggest that the pCEP may benefit in military settings by providing improved sound localization relative to 3M™ E-A-R™-Classic™ and higher attenuation relative to 3M™-Combat Arms™-4.1, recommending its use in noisy environments.
Reliability Testing of a Low-Cost, Multi-Purpose Arduino-Based Data Logger Deployed in Several Applications Such as Outdoor Air Quality, Human Activity, Motion, and Exhaust Gas Monitoring
Authors: Hernández-Rodríguez Erik , González-Rivero Rosa Amalia , Schalm Olivier , Martínez Alain , Hernández Luis , Alejo-Sánchez Daniellys , Janssens Tim , Jacobs Werner
Published: August 2023

This contribution shows the possibilities of applying a low-cost, multi-purpose data logger built around an Arduino Mega 2560 single-board computer. Most projects use this kind of hardware to develop single-purpose data loggers. In this work, a data logger with a more general hardware and software architecture was built to perform measurement campaigns in very different domains. The wide applicability of this data logger was demonstrated with short-term monitoring campaigns in relation to outdoor air quality, human activity in an office, motion of a journey on a bike, and exhaust gas monitoring of a diesel generator. In addition, an assessment process and corresponding evaluation framework are proposed to assess the credibility of low-cost scientific devices built in-house. The experiences acquired during the development of the system and the short measurement campaigns were used as inputs in the assessment process. The assessment showed that the system scores positively on most product-related targets. However, unexpected events affect the assessment over the longer term. This makes the development of low-cost scientific devices harder than expected. To assure stability and long-term performance of this type of design, continuous evaluation and regular engineering corrections are needed throughout longer testing periods.
Adaptation of an IRAM W-Band SIS Receiver to the INAF Sardinia Radio Telescope: A Feasibility Study and Preliminary Tests
Authors: Ladu Adelaide , Schirru Luca , Ortu Pierluigi , Saba Andrea , Pili Mauro , Navarrini Alessandro , Gaudiomonte Francesco , Marongiu Pasqualino , Pisanu Tonino
Published: August 2023

Radio telescopes are used by astronomers to observe the naturally occurring radio waves generated by planets, interstellar molecular clouds, galaxies, and other cosmic objects. These telescopes are equipped with radio receivers that cover a portion of the radio frequency (RF) and millimetre-wave spectra. The Sardinia Radio Telescope (SRT) is an Italian instrument designed to operate between 300 MHz and 116 GHz. Currently, the SRT maximum observational frequency is 26.5 GHz. A feasibility study and preliminary tests were performed with the goal of equipping the SRT with a W-band (84–116 GHz) mono-feed radio receiver, whose results are presented in this paper. In particular, we describe the adaptation to the SRT of an 84–116 GHz cryogenic receiver developed by the Institute de Radio Astronomie Millimétrique (IRAM) for the Plateau de Bure Interferometer (PdBI) antennas. The receiver was upgraded by INAF with a new electronic control system for the remote control from the SRT control room, with a new local oscillator (LO), and with a new refrigeration system. Our feasibility study includes the design of new receiver optics. The single side band (SSB) receiver noise temperature measured in the laboratory, Trec ≈ 66 K at 86 GHz, is considered sufficiently low to carry out the characterisation of the SRT active surface and metrology system in the 3 mm band.
An Individualized Machine Learning Approach for Human Body Weight Estimation Using Smart Shoe Insoles
Authors: Sanghavi Foram , Jinadu Obafemi , Oludare Victor , Panetta Karen , Kezebou Landry , Roberts Susan B.
Published: August 2023

Rapid significant weight fluctuations can indicate severe health conditions such as edema due to congestive heart failure or severe dehydration that could require prompt intervention. Daily body weighing does not accurately represent the patient’s body weight fluctuations occurring within a day. The patient’s lack of compliance with tracking their weight measurements is also a predominant issue. Using shoe insole sensors embedded into footwear could achieve accurate real-time monitoring systems for estimating continuous body weight changes. Here, the machine learning models’ predictive capabilities for continuous real-time weight estimation using the insole data are presented. The lack of availability of public datasets to feed these models is also addressed by introducing two novel datasets. The proposed framework is designed to adapt to the patient, considering several unique factors such as shoe type, posture, foot shape, and gait pattern. The proposed framework estimates the mean absolute percentage error of 0.61% and 0.74% and the MAE of 1.009 lbs. and 1.154 lbs. for the less controlled and more controlled experimental settings, respectively. This will help researchers utilize machine learning techniques for more accurate real-time continuous weight estimation using sensor data and enable more reliable aging-in-place monitoring and telehealth.
Objective Methods of Monitoring Usage of Orthotic Devices for the Extremities: A Systematic Review
Authors: Devanand Devi Baruni , Kedgley Angela E.
Published: August 2023

Orthoses are commonly prescribed to relieve symptoms for musculoskeletal and neurological conditions; however, patients stop wearing orthoses as recommended for many reasons. When considering the effectiveness of orthoses, there needs to be an objective way to monitor whether participants wear the orthosis as instructed, because if this is not followed, the orthoses will not work as intended. This review aimed to identify, summarise, and compare objective methods used to measure compliance with orthoses applied to the extremities. Databases (Scopus, Web of Science, Embase, CINAHL, and MEDLINE) were searched for eligible studies. Twenty-three studies were accepted in the final review, including five studies that employed upper limb orthoses, two that employed hip orthoses, and fifteen that employed lower limb orthoses. To measure compliance objectively, studies utilised temperature sensors, pressure sensors, accelerometers, a step counter, or a combination of sensors. All sensor types have their own advantages and disadvantages and should be chosen based on study-specific parameters. Sensor-derived monitoring provides quantitative, objective data that are beneficial in both clinical and research settings. The ideal solution to monitoring compliance would consist of both objective and user-reported aspects that, in combination, would provide an all-encompassing picture of the orthotic treatment prescribed.
Smooth Autonomous Patrolling for a Differential-Drive Mobile Robot in Dynamic Environments
Authors: Šelek Ana , Seder Marija , Petrović Ivan
Published: August 2023

Today, mobile robots have a wide range of real-world applications where they can replace or assist humans in many tasks, such as search and rescue, surveillance, patrolling, inspection, environmental monitoring, etc. These tasks usually require a robot to navigate through a dynamic environment with smooth, efficient, and safe motion. In this paper, we propose an online smooth-motion-planning method that generates a smooth, collision-free patrolling trajectory based on clothoid curves. Moreover, the proposed method combines global and local planning methods, which are suitable for changing large environments and enabling efficient path replanning with an arbitrary robot orientation. We propose a method for planning a smoothed path based on the golden ratio wherein a robot’s orientation is aligned with a new path that avoids unknown obstacles. The simulation results show that the proposed algorithm reduces the patrolling execution time, path length, and deviation of the tracked trajectory from the patrolling route compared to the original patrolling method without smoothing. Furthermore, the proposed algorithm is suitable for real-time operation due to its computational simplicity, and its performance was validated through the results of an experiment employing a differential-drive mobile robot.
Adaptive Fuzzy Modal Matching of Capacitive Micromachined Gyro Electrostatic Controlling
Authors: Cheng Li , Liu Ruimin , Guo Shumin , Zheng Gaofeng , Liu Yifang
Published: August 2023

A fuzzy PI controller was utilized to realize the modal matching between a driving and detecting model. A simulation model was built to study electrostatic decoupling controlling technology. The simulation results show that the modal matching can be gained by the fuzzy PI controller. The frequency difference between the driving mode and the detection mode is less than 1 Hz, and the offset of the input DC is smaller than 0.6 V. The optimal proportionality factor and integral coefficient are 1.5 and 20, respectively. The fuzzy PI controlling technology provides a good way for the parameter optimization to gain modal matching of micro gyro, via which the detecting accuracy and stability can be improved greatly.
Communicating through Cyberfeminism: Communication Strategies for the Construction of the International Feminist Strike in Portugal
Authors: Lamartine Camila , Cerqueira Carla
Published: August 2023

Despite the considerable attention given to how mainstream media portrays feminism and social movements, there remains a notable research gap regarding the exploration of how these movements themselves engage in internal articulation and employ communication strategies to connect with their publics. To examine communications practices of cyberfeminists within the fourth wave of feminism and the 8M movement (feminist strike), this study analyzes the communication platforms utilized by Rede 8 de Março, which mobilizes the strike in Portugal in three dimensions: (1) institutional and internal communication; (2) content production for online dissemination on digital platforms; and (3) mobilization strategies and action repertoires. Specifically, we focus on the years 2020 and 2021, considering the pandemic context, using a combination of netnography and semi-structured interviews with organizing activists. Our findings indicate a significant rise in Instagram’s platform utilization and exploration, concomitant with the establishment of WhatsApp as a central tool for both organizational and internal communication. These observations enhance our scholarly grasp of the intricate communication dynamics inherent in these organizational contexts and feminist movements, thereby offering significant contributions to our understanding of its operational mechanisms.
A Real-Time Measurement Method and System for the Harvesting Area of a Grain Combine Harvester
Authors: Chen Man , Jin Chengqian , Yang Tengxiang , Liu Zheng
Published: August 2023

A real-time system for measuring harvesting area is crucial for cross-regional operation. In response to the current situation where significant errors often occur in measuring the areas of small and irregular fields, we designed a low-cost and high-precision online real-time measurement system for the harvesting area of grain combines. The real-time measurement hardware system for measuring area was designed using an STM32 microcontroller as the core unit. The system was developed using three modes: intelligent measurement, circular measurement, and fusion measurement. Simulation and field experiments were conducted to verify the performance of the system. The experimental results showed that in the field simulation experiment with four differently shaped operating areas, the average accuracy of the intelligent mode reached 93.76%, and the average accuracy of the circular mode reached 95.48%. In the field experiments, the average accuracy of the intelligent mode reached 95.09%, the average accuracy of the circular mode reached 95.74%, and the average accuracy of the fusion measurement mode reached 98.01%. Therefore, the real-time measurement system for the harvesting area of a grain combine harvester designed in this study has high accuracy when measuring the area of small and irregular farmland, hence meeting the requirements of the design objectives.
Characterization and Design of Circular Binders
Authors: Hendrikse Hans C. , El Khallabi Hamza , Hartog Thomas , Varveri Aikaterini , Tolboom Anthon
Published: August 2023

The concept of a circular economy, where waste materials are transformed into valuable resources, is gaining increasing attention. However, many waste streams are difficult to recycle due to their mixed composition and broad molecular distribution. This paper explores the potential of repurposing mixed materials, specifically focusing on creating a circular alternative to bitumen, a fossil-based binder used in road construction. The molecular weight and composition of bitumen are analyzed using gas chromatography (GC) and infrared spectroscopy (IR). This study proposes using waste plastics and bio-based oils to develop a paving binder with similar molecular distribution. Various plastic types, such as low-density polyethylene (LDPE), high-density polyethylene (HDPE), isotactic polypropylene (PP), polystyrene (PS) and polyethylene terephthalate (PET), are examined for their compatibility with different oils. It is observed that the compatibility of both the molecular weight and composition between the plastic and oil is crucial for the successful dissolution and homogeneity of the binder. Additionally, the crystallinity of the plastic plays a role in the flexibility and durability of the resulting binder. It is demonstrated that by carefully selecting waste materials and understanding their molecular characteristics, it is possible to create circular alternatives to fossil-based materials like bitumen. This approach has the potential to reduce waste, lower dependence on fossil resources, and contribute to sustainable and circular construction materials.
Environmental, Social, and Governance (ESG) Performance and Firm Value: Evidence from Chinese Manufacturing Firms
Authors: Duan Yiqun , Yang Fan , Xiong Lin
Published: August 2023

In an era of great skepticism and distrust, companies’ ESG performances are under ever-increasing scrutiny. Stakeholders are urging companies to integrate ESG goals into their business strategic plans, practices, and value chains. Drawing upon a sample of publicly listed manufacturing companies in China from 2009 to 2021, this study aims to investigate the relationships between ESG performance and corporate values, especially the mediating role of financing constraints and the moderating effect of R&D investment intensity. Findings show that the ESG performance of manufacturing companies has a significant positive effect on corporate value. Financing constraints play a partial intermediary role between ESG performance and enterprise values. R&D investment intensity negatively moderates the relationship between ESG performance and manufacturing companies’ enterprise values. The heterogeneity study indicates that the beneficial impact of ESG performance on company value is particularly pronounced in the eastern region of China, non-state-owned companies, and heavily polluting industrial enterprises. Our findings provide important practical implications for a range of stakeholders, such as enterprises and investors, and enrich our current understanding of ESG research.
Exploring the Impact of Mobile Exams on Saudi Arabian Students: Unveiling Anxiety and Behavioural Changes across Majors and Gender
Authors: Salem Mostafa Aboulnour , Alshebami Ali Saleh
Published: August 2023

Students’ anxiety and behavioural changes while using different examination methods (paper, PC, and mobile exam platforms (MEPs)) were estimated. The influence of academic majors and gender was also determined by answering the following questions: How do anxiety and behavioural changes vary among students using different exam methods? How do students’ anxiety levels vary according to academic majors and gender while using different exam methods? A survey was conducted with 826 students enrolled in eight colleges at King Faisal University in Saudi Arabia. The results revealed less anxiety and fewer harmful behavioural changes among students using MEPs compared with other methods. Furthermore, less anxiety and fewer behavioural changes were observed among health and science majors than humanities and social science majors and among female students than male students while using MEPS. Therefore, MEPs should be gradually adopted by higher education institutions in Saudi Arabia, especially for humanities and social science majors and for male students. Furthermore, researchers and decision-makers should find unique solutions to reduce the positive correlation between anxiety and behavioural changes among health and science majors and female students toward MEPs. This can be achieved by identifying obstacles and introducing modern solutions, such as AI-generated exams, among others.
The Impact of Technological Mergers and Acquisitions on Enterprise Innovation: A Review
Authors: Suo Lingling , Yang Kezhi , Ji Hao
Published: August 2023

Innovation is the source of competitive advantage for enterprises. In the context of global industrial upgrading and increasingly fierce technological competition, enhancing innovation capabilities is key to enterprises’ success. Technology mergers and acquisitions have become an important way for enterprises to acquire external technology, to enhance their innovation capabilities, and to achieve rapid development. Many scholars have extensively researched technology mergers and acquisitions and enterprise innovation. This paper summarizes the relevant research literature according to different research contents. The research content includes the motivation for technology mergers and acquisitions, analyzing the impact mechanism and the path of technology mergers and acquisitions regarding enterprise innovation from the perspectives of technology relevance, the technology absorption capacity, the institutional environment, and corporate governance, as well as related research on the consequences of technology mergers and acquisitions for enterprise innovation and measuring methods for technology mergers and acquisitions and enterprise innovation. This paper summarizes and organizes the relevant literature, aiming to find research directions and enrich future research fields by summarizing it. This effort provides important theoretical support for the strategic decision-making of enterprise technology mergers and acquisitions under the guidance of innovation, and it also provides a reference for further optimizing the innovation incentive environment.
Mixed Multi-Pattern Regression for DNI Prediction in Arid Desert Areas
Authors: Han Tian , Wang Ying , Wang Xiao , Chen Kang , Peng Huaiwu , Gao Zhenxin , Cui Lanxin , Sun Wentong , Peng Qinke
Published: August 2023

As a crucial issue in renewable energy, accurate prediction of direct normal solar irradiance (DNI) is essential for the stable operation of concentrated solar power (CSP) stations, especially for those in arid desert areas. In this study, in order to fully explore the laws of climate change and assess the solar resources in arid desert areas, we have proposed a mixed multi-pattern regression model (MMP) for short-term DNI prediction using prior knowledge provided by the clear-sky solar irradiance (CSI) model and time series patterns of key meteorological factors mined using PR-DTW on different time scales. The contrastive experimental results demonstrated that MMP can outperform existing DNI prediction models in terms of three recognized statistical metrics. To address the challenge of limited data in arid desert areas, we presented the T-MMP model involving combined transfer learning and MMP. The experimental results demonstrated that T-MMP outperformed MMP in DNI prediction by exploiting the significant correlation between meteorological time series patterns in similar areas for data augmentation. Our study provided a valuable prediction model for accurate DNI prediction in arid desert areas, facilitating the economical and stable operation of CSP plants.
Effectiveness of Respiratory Exercises on Perceived Symptoms of Fatigue among Multiple Sclerosis Patients: A Systematic Review
Authors: Torres-Álamo Lucía , López-Liria Remedios , Valverde-Martínez María Ángeles , Benzo-Iglesias María Jesús , Rubio-Arias Jacobo Á.
Published: August 2023

Multiple sclerosis (MS) is an autoimmune disease in which fatigue is one of the most frequent and disabling symptoms, and it is believed to be associated with respiratory involvement. Individuals who are physically inactive for long lengths of time display greater symptomatic fatigue. The objective of this systematic review was to analyze the effectiveness of breathing exercises within rehabilitation programs in improving fatigue in patients with MS. A systematic search of electronic databases, including PubMed, Web of Science, Scopus, and PEDro, was conducted up until November 2022. Nine articles, with a total of 290 participants, were selected. The studies combined breathing exercises with other treatment techniques, such as Ai-Chi, Pilates, and upper and lower limb exercises. Four studies used the Modified Fatigue Severity scale, observing a reduction in the perception of fatigue, in favor of the experimental group. Incorporating respiratory exercises into physical exercise programs, such as Ai-Chi and Pilates, may help to reduce the perception of fatigue. However, the heterogeneity in the protocols and outcome measures makes the generalization of the results difficult. Nonetheless, further studies that include specific respiratory variables are needed to analyze whether this perceived improvement is associated with enhanced pulmonary capacity.
The Implicit Numerical Method for the Radial Anomalous Subdiffusion Equation
Authors: Błasik Marek
Published: August 2023

This paper presents a numerical method for solving a two-dimensional subdiffusion equation with a Caputo fractional derivative. The problem considered assumes symmetry in both the equation’s solution domain and the boundary conditions, allowing for a reduction of the two-dimensional equation to a one-dimensional one. The proposed method is an extension of the fractional Crank–Nicolson method, based on the discretization of the equivalent integral-differential equation. To validate the method, the obtained results were compared with a solution obtained through the Laplace transform. The analytical solution in the image of the Laplace transform was inverted using the Gaver–Wynn–Rho algorithm implemented in the specialized mathematical computing environment, Wolfram Mathematica. The results clearly show the mutual convergence of the solutions obtained via the two methods.
Evolution of Three-Finger Toxin Genes in Neotropical Colubrine Snakes (Colubridae)
Authors: Srodawa Kristy , Cerda Peter A. , Davis Rabosky Alison R. , Crowe-Riddell Jenna M.
Published: August 2023

Snake venom research has historically focused on front-fanged species (Viperidae and Elapidae), limiting our knowledge of venom evolution in rear-fanged snakes across their ecologically diverse phylogeny. Three-finger toxins (3FTxs) are a known neurotoxic component in the venoms of some rear-fanged snakes (Colubridae: Colubrinae), but it is unclear how prevalent 3FTxs are both in expression within venom glands and more broadly among colubrine species. Here, we used a transcriptomic approach to characterize the venom expression profiles of four species of colubrine snakes from the Neotropics that were dominated by 3FTx expression (in the genera Chironius, Oxybelis, Rhinobothryum, and Spilotes). By reconstructing the gene trees of 3FTxs, we found evidence of putative novel heterodimers in the sequences of Chironius multiventris and Oxybelis aeneus, revealing an instance of parallel evolution of this structural change in 3FTxs among rear-fanged colubrine snakes. We also found positive selection at sites within structural loops or “fingers” of 3FTxs, indicating these areas may be key binding sites that interact with prey target molecules. Overall, our results highlight the importance of exploring the venoms of understudied species in reconstructing the full evolutionary history of toxins across the tree of life.
Does Perioperative Administration of Rabies Vaccine in Dogs Undergoing Surgical Sterilization Induce an Adequate Antibody Response?
Authors: Peda Andrea , Samaniego Paulina , Daugherty Christy , Wood Theresa , Wang Chengming , Knobel Darryn
Published: August 2023

High-volume spay/neuter events may facilitate access to free-roaming dogs to administer rabies vaccination, but important questions remain regarding the effect of surgery and anesthesia on the immune response to a vaccine administered in the perioperative period. This study evaluated the immunogenicity of primary rabies vaccination in dogs when administered during the immediate perioperative period at the time of surgical sterilization (ovariohysterectomy/orchidectomy). Healthy dogs of both sexes presenting for surgical sterilization who had never been vaccinated against rabies virus were eligible for enrollment in the study. Fifty dogs ranging in age from 5 to 96 months were enrolled and were vaccinated against rabies virus during the recovery period following anesthesia and surgery. Rabies virus neutralizing antibody (RVNA) titers were measured preoperatively and 28 days postoperatively. This cohort was compared to a historical control cohort of 57 dogs who received primary rabies vaccination for travel purposes and had RVNA titers measured at the same laboratory as the study group 28–35 days post-vaccination. After controlling for age and sex, there was no statistically significant difference in immunogenicity of a rabies vaccine administered to dogs during the perioperative period in comparison to dogs that received the rabies vaccine for travel alone in the absence of surgery. Perioperative administration of a rabies vaccine in dogs undergoing surgical sterilization induces an adequate antibody response. We recommend that rabies vaccine be administered perioperatively during spay/neuter campaigns in canine rabies endemic areas if other opportunities to access veterinary care and rabies vaccination are limited.