bluuebunny/crossref_metadata_2025 huggingface dataset:
Combination of Biochar and Trichoderma harzianum Can Improve the Phytoremediation Efficiency of Brassica juncea and the Rhizosphere Micro-Ecology in Cadmium and Arsenic Contaminated Soil
Authors: Yao Shaoxiong , Zhou Beibei , Duan Manli , Cao Tao , Wen Zhaoquan , Chen Xiaopeng , Wang Hui , Wang Min , Cheng Wen , Zhu Hongyan , Yang Qiang , Li Yujin
Published: August 2023

Phytoremediation is an environment-friendly method for toxic elements remediation. The aim of this study was to improve the phytoremediation efficiency of Brassica juncea and the rhizosphere soil micro-ecology in cadmium (Cd) and arsenic (As) contaminated soil. A field experiment was conducted with six treatments, including a control treatment (CK), two treatments with two contents of Trichoderma harzianum (T1: 4.5 g m−2; T2: 9 g m−2), one biochar treatment (B: 750 g m−2), and two combined treatments of T1B and T2B. The results showed Trichoderma harzianum promoted the total chlorophyll and translocation factor of Brassica juncea, while biochar promoted plant biomass compared to CK. T2B treatment showed the best results, which significantly increased Cd accumulation by 187.49–308.92%, and As accumulation by 125.74–221.43%. As a result, the soil’s total Cd content was reduced by 19.04% to 49.64% and total As contents by 38.76% to 53.77%. The combined amendment increased the contents of soil available potassium, phosphorus, nitrogen, and organic matter. Meanwhile, both the activity of glutathione and peroxidase enzymes in plants, together with urease and sucrase enzymes in soil, were increased. Firmicutes (dominant bacterial phylum) and Ascomycota (dominant fungal phylum) showed positive and close correlation with soil nutrients and plant potentially toxic elements contents. This study demonstrated that phytoremediation assisted by biochar and Trichoderma harzianum is an effective method of soil remediation and provides a new strategy for enhancing plant remediation efficiency.
Phenolic Composition and Antioxidant Activity of Tanacetum parthenium Cultivated in Different Regions of Ukraine: Insights into the Flavonoids and Hydroxycinnamic Acids Profile
Authors: Hordiei Karyna , Gontova Tetiana , Trumbeckaite Sonata , Yaremenko Maksym , Raudone Lina
Published: August 2023

Tanacetum parthenium, also known as feverfew, is rich in bioactive compounds, namely sesquiterpene lactones, flavonoids, and volatile oils. Sesquiterpene lactones possess anti-migraine activity, while phenolic compounds possess anti-inflammatory and antioxidant action. Phytochemical composition determines the pharmacological activity and so profiling is essential in quality assessment. The study aimed to evaluate cultivated feverfew plants’ phenolic profiles and antioxidant activity. Eleven phenolic compounds were identified in the samples of feverfew in Ukraine. Hydroxycinnamic acids predominate in the quantitative content of all the samples, namely chlorogenic acid, 3,5-dicaffeoylquinic acid, 3,4-dicaffeoylquinic acid and 4,5-dicaffeoylquinic acid. The total content of flavonoids ranged from 0.8 to 2.6%; the content of hydroxycinnamic acids varied from 3.3 to 6.5%. The obtained data testify to the prospects of using Ukrainian feverfew as a raw material with a significant content of phenolic substances to develop new herbal medicines.
Unveiling Cacao Rootstock-Genotypes with Potential Use in the Mitigation of Cadmium Bioaccumulation
Authors: Galvis Donald A. , Jaimes-Suárez Yeirme Y. , Rojas Molina Jairo , Ruiz Rosalba , León-Moreno Clara E. , Carvalho Fabricio Eulalio Leite
Published: August 2023

The accumulation of high cadmium (Cd) levels in cacao beans (Theobroma cacao) generate several commercial and health issues. We hypothesized that cacao phenotypic and genotypic diversity could provide new insights to decrease Cd accumulation in cacao beans. Nine cacao rootstock genotypes were evaluated for up to 90 days under 0, 6, and 12 (mg·kg−1) of CdCl2 exposure and Cd content and plant growth dynamics were measured in leaves, stems, and roots. Data revealed that all cacao genotypes studied here were highly tolerant to Cd, since they presented tolerance index ≥ 60%. In shoots, EET61 and PA46 presented the higher (~270 mg·kg DW−1) and lower (~20 mg·kg DW−1) Cd concentration, respectively. Accordingly, only the EET61 showed an increase in the shoot cadmium translocation factor over the 90 days of exposure. However, when analyzing cadmium allocation to different organs based on total plant dry mass production, none of the genotypes maintained high Cd compartmentalization into roots, since P46, which was the genotype with the highest allocation of Cd to the roots, presented only 20% of total cadmium per plant in this plant organ and 80% allocated into the shoots, under Cd 12 (mg·kg−1) and after 90 days of exposure. Thus, genotypic/phenotypic variability in cacao rootstocks may provide valuable strategies for maximizing the reduction in Cd content in shoots. In this sense, IMC67 and PA46 were the ones that stood out in the present study.
Optimization of Callus Induction and Shoot Regeneration from Tomato Cotyledon Explants
Authors: Yaroshko Olha , Pasternak Taras , Larriba Eduardo , Pérez-Pérez José Manuel
Published: August 2023

Cultivated tomato (Solanum lycopersicum L.) is one of the most important horticultural crops in the world. The optimization of culture media for callus formation and tissue regeneration of different tomato genotypes presents numerous biotechnological applications. In this work, we have analyzed the effect of different concentrations of zeatin and indole-3-acetic acid on the regeneration of cotyledon explants in tomato cultivars M82 and Micro-Tom. We evaluated regeneration parameters such as the percentage of callus formation and the area of callus formed, as well as the initiation percentage and the number of adventitious shoots. The best hormone combination produced shoot-like structures after 2–3 weeks. We observed the formation of leaf primordia from these structures after about 3–4 weeks. Upon transferring the regenerating micro-stems to a defined growth medium, it was possible to obtain whole plantlets between 4 and 6 weeks. This hormone combination was applied to other genotypes of S. lycopersicum, including commercial varieties and ancestral tomato varieties. Our method is suitable for obtaining many plantlets of different tomato genotypes from cotyledon explants in a very short time, with direct applications for plant transformation, use of gene editing techniques, and vegetative propagation of elite cultivars.
A Water-Resistant, Self-Healing Encapsulation Layer for a Stable, Implantable Wireless Antenna
Authors: An Soojung , Lyu Hyunsang , Seong Duhwan , Yoon Hyun , Kim In Soo , Lee Hyojin , Shin Mikyung , Hwang Keum Cheol , Son Donghee
Published: August 2023

Polymers for implantable devices are desirable for biomedical engineering applications. This study introduces a water-resistant, self-healing fluoroelastomer (SHFE) as an encapsulation material for antennas. The SHFE exhibits a tissue-like modulus (approximately 0.4 MPa), stretchability (at least 450%, even after self-healing in an underwater environment), self-healability, and water resistance (WVTR result: 17.8610 g m−2 day−1). Further, the SHFE is self-healing in underwater environments via dipole–dipole interactions, such that devices can be protected from the penetration of biofluids and withstand external damage. With the combination of the SHFE and antennas designed to operate inside the body, we fabricated implantable, wireless antennas that can transmit information from inside the body to a reader coil that is outside. For antennas designed considering the dielectric constant, the uniformity of the encapsulation layer is crucial. A uniform and homogeneous interface is formed by simply overlapping two films. This study demonstrated the possibility of wireless communication in vivo through experiments on rodents for 4 weeks, maintaining the maximum communication distance (15 mm) without chemical or physical deformation in the SHFE layer. This study illustrates the applicability of fluoroelastomers in vivo and is expected to contribute to realizing the stable operation of high-performance implantable devices.
Synergistic Use of All-Acceptor Strategies for the Preparation of an Organic Semiconductor and the Realization of High Electron Transport Properties in Organic Field-Effect Transistors
Authors: Ren Shiwei , Zhang Wenqing , Wang Zhuoer , Yassar Abderrahim , Liao Zhiting , Yi Zhengran
Published: August 2023

The development of n-type organic semiconductor materials for transporting electrons as part of logic circuits is equally important to the development of p-type materials for transporting holes. Currently, progress in research on n-type materials is relatively backward, and the number of polymers with high electron mobility is limited. As the core component of the organic field-effect transistor (OFET), the rational design and judicious selection of the structure of organic semiconductor materials are crucial to enhance the performance of devices. A novel conjugated copolymer with an all-acceptor structure was synthesized based on an effective chemical structure modification and design strategy. PDPPTT-2Tz was obtained by the Stille coupling of the DPPTT monomer with 2Tz-SnMe3, which features high molecular weight and thermal stability. The low-lying lowest unoccupied molecular orbital (LUMO) energy level of the copolymer was attributed to the introduction of electron-deficient bithiazole. DFT calculations revealed that this material is highly planar. The effect of modulation from a donor–acceptor to acceptor–acceptor structure on the improvement of electron mobility was significant, which showed a maximum value of 1.29 cm2 V−1 s−1 and an average value of 0.81 cm2 V−1 s−1 for electron mobility in BGBC-based OFET devices. Our results demonstrate that DPP-based polymers can be used not only as excellent p-type materials but also as promising n-type materials.
Crystallization and Performance of Polyamide Blends Comprising Polyamide 4, Polyamide 6, and Their Copolymers
Authors: Zhang Yajing , Wang Mingda , Zhang Di , Wang Yibing , Wang Li , Qiu Yongjun , Wang Liquan , Chen Tao , Zhao Liming
Published: August 2023

Polyamide 4 (PA4) is a biobased and biodegradable polyamide. The high hydrogen bond density of PA4 bestows it with a high melting point that is close to its thermal decomposition temperature, thereby limiting the melt processing of PA4. In this study, PA4 was blended with polyamide 6 (PA6) and further modified with copolyamide 4/6 (R46). The effects of composition on the crystallization behavior of the blends were studied. The results demonstrated that the binary PA4/PA6 (B46) and ternary PA4/PA6/R46 (B46/R46) blends formed two crystalline phases (PA4- and PA6-rich phases) through crystallization-induced phase separation. With increasing PA6 content, the thermal stability and crystallinity of the B46 blend increased and decreased, respectively, and the contribution of PA6 toward the crystallization of the PA4-rich phase diminished. Molecular dynamics simulations showed the molecular chain orientation of the B46 blends well. The melting points, crystallinities, and grain sizes of the B46/R46 blends were lower than those of the B46 blends. The crystallization of the PA4-rich phase was restrained by the dilution effect of molten-state PA6, and the nucleation and crystallization of the PA6-rich phase were promoted by the presence of crystallized PA4. The B46 blends with 30–40 wt% PA6 had the best mechanical properties.
Molecularly Imprinted Polymers for Pharmaceutical Impurities: Design and Synthesis Methods
Authors: Hasanah Aliya Nur , Susanti Ike
Published: August 2023

The safety of a medicinal product is determined by its pharmacological and toxicological profile, which depends not only on the active substance’s toxicological properties, but also on the impurities it contains. Because impurities are a problem that must be considered to ensure the safety of a drug product, many studies have been conducted regarding the separation or purification of active pharmaceutical ingredients (APIs) and the determination of impurities in APIs and drug products. Several studies have applied molecularly imprinted polymers (MIPs) to separate impurities in active ingredients and as adsorbents in the sample preparation process. This review presents the design of MIPs and the methods used to synthesise MIPs to separate impurities in APIs and drug product samples, the application of MIPs to separate impurities, and a view of future studies involving MIPs to remove impurities from pharmaceutical products. Based on a comparison of the bulk and surface-imprinting polymerisation methods, the MIPs produced by the surface-imprinting polymerisation method have a higher adsorption capacity and faster adsorption kinetics than the MIPs produced by the bulk polymerisation method. However, the application of MIPs in the analysis of APIs and drug products are currently only related to organic compounds. Considering the advantages of MIPs to separate impurities, MIPs for other impurities still need to be developed, including multi-template MIPs for simultaneous separation of multiple impurities.
Evaluating a Novel Fly Ash Resin-Reinforced Cement’s Interactions under Acidic, Basic, High-Salinity, and High-Temperature Conditions
Authors: Fakher Sherif , El-Sayed Ali , Sameh Layla , Abdeltawab Bassel
Published: August 2023

The ability of cement to withstand harsh conditions is one of its most vital properties, especially in hydrocarbon wells, due to their association with high temperatures, high pressures, acidic components, and erosion. Conventional cement is prone to failure under extreme conditions and is also a costly component in oil and gas wells. This research evaluated the ability of a newly developed cement composed of fly ash reinforced with epoxy resin to withstand the harsh conditions of oil and gas wells. The novel cement was tested for its ability to resist high concentrations of hydrochloric acid (HCl) and sodium hydroxide (NaOH), high salinity, high temperatures, high pressures, gaseous and supercritical carbon dioxide (CO2), and crude oil. Results showed that the novel cement had an overall excellent ability to perform under extreme conditions. The performance of the cement was a strong function of the fly ash concentration, with an increase in the fly ash concentration resulting in improvement in the cement. For all tests, the highest degradation for the novel cement that occurred was 0.62% after 7 continuous days of exposure, which is considered an extremely low value. This shows that the novel cement has a strong ability to maintain its integrity under extreme conditions.
Investigation of the Thermal Characteristics of a Novel Laser Sintering Machine for Additive Manufacturing of Continuous Carbon Fibre-Reinforced Polymer Parts
Authors: Baranowski Michael , Basalla Felix , Kößler Florian , Fleischer Jürgen
Published: August 2023

This paper presents the thermal analysis of a novel laser sintering machine for additive manufacturing of continuous carbon fibre-reinforced polymer parts. The core element of this machine is a fibre integration unit with a heated fibre nozzle. With the help of an additional heat source, which is mounted on the bottom side of the fibre integration unit, the temperature of the powder bed surface is kept within the sintering window of the PA12 material used in the investigations. Different heat source variants differing in shape and material were analysed experimentally concerning the heat distribution achieved within the powder bed surface using an infrared camera. Based on the best-rated variant showing the most homogeneous heat distribution, operating points for successful continuous fibre integration were experimentally identified. An aluminium plate with a closed fibre nozzle slot and symmetrical surface heating power has proven to keep the powder bed surface reliably warm. Compared to the initial state, the resulting increased uniformity of heat-affected zones created by the heated fibre nozzle HAZ was evaluated by fabricating a horseshoe part made of PA12. Furthermore, a CCFRP flat pedal for mountain bikes demonstrated roving integration’s process reliability and reproducibility.
Experimental Study on the Influence of Wind Speed on the Start-Up Characteristics and Thermoelectric Generation Characteristics of Gravity Heat Pipe in Gangue Dump
Authors: Zhang Bailin , Fang Shuhua , Zhang Songlin , Zhang Runxu , Zang Yu
Published: August 2023

As an efficient heat exchange component, the gravity heat pipe can effectively control the accumulated temperature inside gangue dumps and enable reuse of transferred heat. This study establishes a similar simulation experimental platform for gravity heat pipes to control gangue dumps and thermoelectric generation. The influence of wind speed on the start-up performance and isothermal performance of gravity heat pipes is analyzed, along with the impact of wind speed on their thermoelectric generation performance. Initially, the optimal working fluid height and heating height are determined, followed by a comparison and analysis of the isothermal performance, start-up performance, and thermoelectric generation performance of the gravity heat pipe under different wind speeds. The results indicate that at a wind speed of 1.0 m/s, the gravity heat pipe exhibits better start-up and isothermal performance. At a wind speed of 2.0 m/s, the thermoelectric power generation reaches its peak. In the range of 1.0~2.0 m/s wind speeds, the curve of thermoelectric generation exhibits the most fluctuations.
Atomic Force Microscopy as a Tool to Study Transport Phenomena in Biological Systems
Authors: Kandapal Sneha , Xu Bingqian
Published: August 2023

Biological interactions often involve the transport of molecules, ions, or other species across biological membranes or between interacting proteins. The understanding of these transport phenomena is crucial for the development of therapies for various diseases. Atomic force microscopy is a powerful tool that has been increasingly used to study biological systems at the nano scale. The high resolution, quantitative measurements, and the ability to probe biological interactions under near-physiological conditions make AFM an attractive tool for investigating transport phenomena in biological systems. In this article, we focus on the use of AFM in the study of the transport phenomena in biological systems. We discuss the principles of AFM, its instrumentation, and its application in the study of biomolecules and biological systems. We also provide a comprehensive overview of recent articles that have utilized AFM in the study of biomarkers in biological systems.
Study on Enhanced Heat Transfer of the Convex Columns in the Cooling Channel of Motorized Spindle Based on Field Synergy
Authors: Li Yang , Nie Zhe , Su Dongxu , Tian Jingyao , He Wenlei , Zhao Wanhua
Published: August 2023

The cooling performance of motorized spindles plays an important role in accuracy in high-speed machining. Aiming at improving the cooling performance of traditional motorized spindles, convex columns were built in the cooling channel. Based on field synergy, the effects of quadrilateral, circular and triangular convex columns on the heat transfer performance of the cooling channel were analyzed numerically. We also compared the pressure drop between the inlet and outlet under the same conditions. The results show that the cooling channels with triangular convex columns provide the best cooling effect with the smallest increase in area compared to quadrilateral convex columns and circular convex columns. The pressure drop in the cooling channels with a circular convex column is minimized. By optimizing the spacing of the convex column, the best effect was found at a spacing of 7 mm. By optimizing the angle of the top angle of the triangular column, it is found that the enhanced heat transfer effect is best at 120° when the heat transfer area is the same. In addition, when considering the addition of convex columns, it is important to ensure sufficient pressure drop to achieve a good cooling effect.
Development of Ultrasound Piezoelectric Transducer-Based Measurement of the Piezoelectric Coefficient and Comparison with Existing Methods
Authors: Ravikumar Chandana , Markevicius Vytautas
Published: August 2023

Energy harvesting using the piezoelectric material in the development of compact vibration energy harvesters can be used as a backup power source for wireless sensors or to fully replace the use of fossil-resource-wasting batteries and accumulators to power a device or sensor. Generally, the coefficient is used as the metric for evaluating the property in materials. Recent research reports that accurate measurement and calculation of the coefficient in materials, especially in polymers, can be challenging for various reasons. From the reviewed references, different methods, including the quasi-static, dynamic, interferometric, and acoustic methods, are discussed and compared based on the direct and indirect effect, accuracy, repeatability, frequency range, and so on. A development of an ultrasound piezoelectric transducer is conducted to estimate d33 coefficient with a reference value. The purpose of the method was mainly to measure the values of piezoelectric material in order to measure the efficiency of the poling process in piezoelectric materials. The test setup described in this study allowed for the effective measurement of the d33 factor of piezoelectric materials using a 1.4 MHz PZT ultrasonic piezoelectric transducer. The arrangement of the components, including the use of organic glass, copper, and aluminum electrodes, ensured accurate and reliable measurements. This setup can be valuable for various applications requiring the characterization of piezoelectric materials and for understanding their behavior under specific conditions. The advantages and challenges in this method are discussed and compared with existing works.
Fused Data-Driven Approach for Early Warning Method of Abnormal Conditions in Chemical Process
Authors: Song Xiaomiao , Yin Fabo , Zhao Dongfeng
Published: August 2023

The utilization of data-driven methods in chemical process modeling has been extensively acknowledged due to their effectiveness. However, with the increasing complexity and variability of chemical processes, predicting and warning of anomalous conditions have become challenging. Extracting valuable features and constructing relevant warning models are critical problems that require resolution. This research proposed a novel fused method that integrates K-means density-based spatial clustering of applications with noise (DBSCAN) clustering and bi-directional long short-term memory multilayer perceptron (Bi-LSTM-MLP) to enable early warning of abnormal conditions in chemical processes. The paper applied the proposed method to analyze the early warning using actual process data from Eastman Tennessee and the atmospheric pressure reduction unit as an example. In the TE model and example, the root mean square error (RMSE) of this method is 0.006855 and 0.052546, respectively, which is quite low when compared to other methods. The experimental results confirmed the effectiveness of our approach.
Evaluation of Fracture Volume and Complexity of Tight Oil Wells Based on Flowback Data
Authors: Li Jie , Liu Sen , Li Jianmin , Liu Zhigang , Chen Xi , Li Jiayan , Liang Tianbo
Published: August 2023

For tight reservoirs, horizontal wells and multi-stage fracturing can generate a complex fracture network that realizes economic and effective development. The volume and complexity of the fracture network are of great significance to accurately predicting the productivity of tight oil wells. In this work, a mathematical model of a multiphase flow is proposed to evaluate the stimulation effect based on the early flowback data. The model showing the early slope of the material balance time (MBT) and production balance pressure (RNP) can help estimate the effective stimulated volume of the horizontal well. The linear flow region can be determined from the slope of the log–log plot of the MBT versus RNP curve, which equals 1. The method is verified by commercial simulation software, and the calculated stimulated volume is consistent with the statistical results of simulation results. Results also show that the flow pattern of the fracture–matrix system can be judged by the slope of the flowback characteristic curve in the early stage of flowback, and then the complexity of the fracture network can also be obtained. The proposed method can provide an avenue to evaluate the fracturing work using the flowback data quickly.
Investigation into the Perforation Optimization in Conglomerate Reservoir Based on a Field Test
Authors: Fan Qinghu , Ma Yonggui , Wang Junping , Chen Liang , Ye Zhiquan , Xu Yajun , Li Huan , Wang Bo
Published: August 2023

The Mahu conglomerate reservoir is characterized by strong heterogeneity and the uneven stimulation of the horizontal lateral during hydraulic fracturing. The optimization of the perforation number per cluster is of great value for horizontal well multi-stage fracturing (HWMF) because the suitable perforation number not only promotes the uniform propagation of multiple fractures but also prevents excessive perforation erosion. In this work, a typical well in the Mahu conglomerate reservoir was selected, and a field test of optimizing the perforation number was carried out. The perforation schemes of three, five, and eight perforations per cluster were designed in nine fracturing stages, respectively. The wellhead pressure under different perforation schemes was compared and analyzed with the step-down flow rate test, and the optimal perforation number per cluster in the Mahu conglomerate reservoir was selected as eight. The theoretical calculation results show that eight perforations per cluster can generate the perforation friction of 5 MPa, sufficient to overcome the mechanical property differences among multiple clusters within one stage. The downhole video technology shows that the perforation erosion area is the most uniform with the case of eight perforations per cluster. Moreover, the optical fiber monitoring results show that the perforation number of eight per cluster can realize the simultaneous initiation and uniform propagation of six fractures or five fractures within one stage. This work is of great significance for the efficient development of the Mahu conglomerate reservoir through HWMF.
Metaphors as Knowledge in Mystical Writings
Authors: Xie Cécile
Published: August 2023

Writers anchored in the Christian mystical tradition generally present their spiritual experience as loaded with cognitive content bearing on things divine. The nature of this mystical knowledge, the way they receive it, and its effect on their existence can be fruitfully approached only by elucidating the way their language and discourse make use of metaphors. Accordingly, starting with references to the early modern period, this article investigates a set of classical mystical metaphors so as to gain insight into the unique mode of metaphorical cognition, highlight the epistemological status proper to mystical experience, and distinguish the latter from other theological cognitive modes. Metaphors borrowed from daily life endow the mystical experience—of which the object is described as being beyond senses and reason—with a perceptible, comprehensible, and communicable configuration. At the same time, metaphors should not be regarded as being merely an approximate expression of an ineffable experience. Through the “gestalt” or structure of a metaphor, mystical experience locates itself and develops in spacetime, thus laying out the path of the spiritual journey. The way various metaphors naturally associate allows the expression, intensity, and self-understanding of spiritual experience to “grow” from one image to another. Thanks to the metaphorical operation, mystics are able to describe their journey and give spiritual direction, providing disciples and readers with concrete directions for reforming and renewing their lives. Furthermore, the connection that metaphor establishes between everyday routines and things divine allows for a two-way exchange of meanings: the objects or events met in daily life are “sanctified” as they become metaphors that convey spiritual understanding and allow an ever-growing number of people to “seek and find God in all things”.
Overview of Some Recent Results of Energy Market Modeling and Clean Energy Vision in Canada
Authors: Swishchuk Anatoliy
Published: August 2023

This paper overviews our recent results of energy market modeling, including The option pricing formula for a mean-reversion asset, variance and volatility swaps on energy markets, applications of weather derivatives on energy markets, pricing crude oil options using the Lévy processes, energy contracts modeling with delayed and jumped volatilities, applications of mean-reverting processes on Alberta energy markets, and alternatives to the Black-76 model for options valuation of futures contracts. We will also consider the clean renewable energy prospective in Canada, and, in particular, in Alberta and Calgary.
A Passivity-Based Framework for Safe Physical Human–Robot Interaction
Authors: Ding Zhangchi , Baghbahari Masoud , Behal Aman
Published: August 2023

In this paper, the problem of making a safe compliant contact between a human and an assistive robot is considered. Users with disabilities have a need to utilize their assistive robots for physical human–robot interaction (PHRI) during certain activities of daily living (ADLs). Specifically, we propose a hybrid force/velocity/attitude control for a PHRI system based on measurements from a six-axis force/torque sensor mounted on the robot wrist. While automatically aligning the end-effector surface with the unknown environmental (human) surface, a desired commanded force is applied in the normal direction while following desired velocity commands in the tangential directions. A Lyapunov-based stability analysis is provided to prove both the convergence as well as passivity of the interaction to ensure both performance and safety. Simulation as well as experimental results verify the performance and robustness of the proposed hybrid controller in the presence of dynamic uncertainties as well as safe physical human–robot interactions for a kinematically redundant robotic manipulator.
Tethered Unmanned Aerial Vehicles—A Systematic Review
Authors: Marques Miguel Nakajima , Magalhães Sandro Augusto , Dos Santos Filipe Neves , Mendonça Hélio Sousa
Published: August 2023

In recent years, there has been a remarkable surge in the development and research of tethered aerial systems, thus reflecting a growing interest in their diverse applications. Long-term missions involving aerial vehicles present significant challenges due to the limitations of current battery solutions. Tethered vehicles can circumvent such restrictions by receiving their power from an element on the ground such as a ground station or a mobile terrestrial platform. Tethered Unmanned Aerial Vehicles (UAVs) can also be applied to load transportation achieved by a single or multiple UAVs. This paper presents a comprehensive systematic literature review, with a special focus on solutions published in the last five years (2017–2022). It emphasizes the key characteristics that are capable of grouping publications by application scope, propulsion method, energy transfer solution, perception sensors, and control techniques adopted. The search was performed in six different databases, thereby resulting in 1172 unique publications, from which 182 were considered for inclusion in the data extraction phase of this review. Among the various aircraft types, multirotors emerged as the most widely used category. We also identified significant variations in the application scope of tethered UAVs, thus leading to tailored approaches for each use case, such as the fixed-wing model being predominant in the wind generation application and the lighter-than-air aircraft in the meteorology field. Notably, the classical Proportional–Integral–Derivative (PID) control scheme emerged as the predominant control methodology across the surveyed publications. Regarding energy transfer techniques, most publications did not explicitly describe their approach. However, among those that did, high-voltage DC energy transfer emerged as the preferred solution. In summary, this systematic literature review provides valuable insights into the current state of tethered aerial systems, thereby showcasing their potential as a robust and sustainable alternative to address the challenges associated with long-duration aerial missions and load transportation.
Drone-Based Assessment of Marine Megafauna off Wave-Exposed Sandy Beaches
Authors: Kelaher Brendan P. , Monteforte Kim I. , Morris Stephen G. , Schlacher Thomas A. , March Duane T. , Tucker James P. , Butcher Paul A.
Published: August 2023

The wave-impacted waters off exposed sandy beaches support marine megafauna, including dolphins, whales, sharks, rays and turtles. To characterise variation in megafaunal assemblages in this challenging habitat, we used drone-based remote sensing to survey marine megafauna off 23 beaches along 1050 km of the New South Wales (NSW, Australia) coast from 2017 to 2020. The surveys occurred from September to May and included 17,085 drone flights, with megafaunal abundances standardised by flight hours. In total, we identified 3838 individual animals from 16 taxa, although no megafauna was observed off 5 of the 23 beaches surveyed. Bottlenose dolphins were the most commonly sighted taxa and accounted for 82.3% of total megafaunal abundance. Cownose (6.7%) and eagle (3.4%) rays were the next most abundant taxa, with potentially dangerous sharks being rarely sighted (<1% of total megafauna). The megafaunal assemblages off wave-exposed beaches in northern NSW significantly differed from those in the central region, whereas the assemblages off the central region and southern NSW did not differ significantly. Wave exposure and water temperature were the best predictors of megafaunal assemblage structure. The richness of marine megafauna off ocean beaches was significantly greater in northern than southern NSW, and turtles were only observed off beaches in the northern region. However, variation in megafaunal richness, as well as the abundances of total megafauna, dolphins, rays, sharks and turtles were not significantly explained by water temperature, wave height, distance to estuary, or proximity to the nearest reef. Overall, drone-based surveys determined that megafaunal assemblages off wave-exposed beaches are characterised by sparse individuals or small groups of sharks, turtles and rays, punctuated by occasional large aggregations of dolphins, cownose rays and schooling sharks. The exception to this pattern was bottlenose dolphins, which routinely patrolled some beaches in northern NSW.
Identification of Ecological Restoration Approaches and Effects Based on the OO-CCDC Algorithm in an Ecologically Fragile Region
Authors: Wei Caiyong , Xue Xiaojing , Tian Lingwen , Yang Qin , Hou Bowen , Wang Wenlong , Ma Dawei , Meng Yuanyuan , Liu Xiangnan
Published: August 2023

A full understanding of the patterns, trends, and strategies for long-term ecosystem changes helps decision-makers evaluate the effectiveness of ecological restoration projects. This study identified the ecological restoration approaches on planted forest, natural forest, and natural grassland protection during 2000–2022 based on a developed object-oriented continuous change detection and classification (OO-CCDC) method. Taking the Loess hilly region in the southern Ningxia Hui Autonomous Region, China as a case study, we assessed the ecological effects after protecting forest or grassland automatically and continuously by highlighting the location and change time of positive or negative effects. The results showed that the accuracy of ecological restoration approaches extraction was 90.73%, and the accuracies of the ecological restoration effects were 86.1% in time and 84.4% in space. A detailed evaluation from 2000 to 2022 demonstrated that positive effects peaked in 2013 (1262.69 km2), while the highest negative effects were observed in 2017 (54.54 km2). In total, 94.39% of the planted forests, 99.56% of the natural forest protection, and 62.36% of the grassland protection were in a stable pattern, and 35.37% of the natural grassland displayed positive effects, indicating a proactive role for forest management and ecological restoration in an ecologically fragile region. The negative effects accounted for a small proportion, only 2.41% of the planted forests concentrated in Pengyang County and 2.62% of the natural grassland protection mainly distributed around the farmland in the central-eastern part of the study area. By highlighting regions with positive effects as acceptable references and regions with negative effects as essential conservation objects, this study provides valuable insights for evaluating the effectiveness of the integrated ecological restoration pattern and determining the configuration of ecological restoration measures.
Sensitivity of Optical Satellites to Estimate Windthrow Tree-Mortality in a Central Amazon Forest
Authors: Emmert Luciano , Negrón-Juárez Robinson Isaac , Chambers Jeffrey Quintin , Santos Joaquim dos , Lima Adriano José Nogueira , Trumbore Susan , Marra Daniel Magnabosco
Published: August 2023

Windthrow (i.e., trees broken and uprooted by wind) is a major natural disturbance in Amazon forests. Images from medium-resolution optical satellites combined with extensive field data have allowed researchers to assess patterns of windthrow tree-mortality and to monitor forest recovery over decades of succession in different regions. Although satellites with high spatial-resolution have become available in the last decade, they have not yet been employed for the quantification of windthrow tree-mortality. Here, we address how increasing the spatial resolution of satellites affects plot-to-landscape estimates of windthrow tree-mortality. We combined forest inventory data with Landsat 8 (30 m pixel), Sentinel 2 (10 m), and WorldView 2 (2 m) imagery over an old-growth forest in the Central Amazon that was disturbed by a single windthrow event in November 2015. Remote sensing estimates of windthrow tree-mortality were produced from Spectral Mixture Analysis and evaluated with forest inventory data (i.e., ground true) by using Generalized Linear Models. Field measured windthrow tree-mortality (3 transects and 30 subplots) crossing the entire disturbance gradient was 26.9 ± 11.1% (mean ± 95% CI). Although the three satellites produced reliable and statistically similar estimates (from 26.5% to 30.3%, p < 0.001), Landsat 8 had the most accurate results and efficiently captured field-observed variations in windthrow tree-mortality across the entire gradient of disturbance (Sentinel 2 and WorldView 2 produced the second and third best results, respectively). As expected, mean-associated uncertainties decreased systematically with increasing spatial resolution (i.e., from Landsat 8 to Sentinel 2 and WorldView 2). However, the overall quality of model fits showed the opposite pattern. We suggest that this reflects the influence of a relatively minor disturbance, such as defoliation and crown damage, and the fast growth of natural regeneration, which were not measured in the field nor can be captured by coarser resolution imagery. Our results validate the reliability of Landsat imagery for assessing plot-to-landscape patterns of windthrow tree-mortality in dense and heterogeneous tropical forests. Satellites with high spatial resolution can improve estimates of windthrow severity by allowing the quantification of crown damage and mortality of lower canopy and understory trees. However, this requires the validation of remote sensing metrics using field data at compatible scales.
Target Recognition in SAR Images Using Complex-Valued Network Guided with Sub-Aperture Decomposition
Authors: Wang Ruonan , Wang Zhaocheng , Chen Yu , Kang Hailong , Luo Feng , Liu Yingxi
Published: August 2023

Synthetic aperture radar (SAR) images have special physical scattering characteristics owing to their unique imaging mechanism. Traditional deep learning algorithms usually extract features from real-valued SAR images in a purely data-driven manner, which may ignore some important physical scattering characteristics and sacrifice some useful target information in SAR images. This undoubtedly limits the improvement in performance for SAR target recognition. To take full advantage of the physical information contained in SAR images, a complex-valued network guided with sub-aperture decomposition (CGS-Net) for SAR target recognition is proposed. According to the fact that different targets have different physical scattering characteristics at different angles, the sub-aperture decomposition is used to improve accuracy with a multi-task learning strategy. Specifically, the proposed method includes main and auxiliary tasks, which can improve the performance of the main task by learning and sharing useful information from the auxiliary task. Here, the main task is the target recognition task, and the auxiliary task is the target reconstruction task. In addition, a complex-valued network is used to extract the features from the original complex-valued SAR images, which effectively utilizes the amplitude and phase information in SAR images. The experimental results obtained using the MSTAR dataset illustrate that the proposed CGS-Net achieved an accuracy of 99.59% (without transfer learning or data augmentation) for the ten-classes targets, which is superior to the other popular deep learning methods. Moreover, the proposed method has a lightweight network structure, which is suitable for SAR target recognition tasks because SAR images usually lack a large number of labeled data. Here, the experimental results obtained using the small dataset further demonstrate the excellent performance of the proposed CGS-Net.
A Small Object Detection Algorithm for Traffic Signs Based on Improved YOLOv7
Authors: Li Songjiang , Wang Shilong , Wang Peng
Published: August 2023

Traffic sign detection is a crucial task in computer vision, finding wide-ranging applications in intelligent transportation systems, autonomous driving, and traffic safety. However, due to the complexity and variability of traffic environments and the small size of traffic signs, detecting small traffic signs in real-world scenes remains a challenging problem. In order to improve the recognition of road traffic signs, this paper proposes a small object detection algorithm for traffic signs based on the improved YOLOv7. First, the small target detection layer in the neck region was added to augment the detection capability for small traffic sign targets. Simultaneously, the integration of self-attention and convolutional mix modules (ACmix) was applied to the newly added small target detection layer, enabling the capture of additional feature information through the convolutional and self-attention channels within ACmix. Furthermore, the feature extraction capability of the convolution modules was enhanced by replacing the regular convolution modules in the neck layer with omni-dimensional dynamic convolution (ODConv). To further enhance the accuracy of small target detection, the normalized Gaussian Wasserstein distance (NWD) metric was introduced to mitigate the sensitivity to minor positional deviations of small objects. The experimental results on the challenging public dataset TT100K demonstrate that the SANO-YOLOv7 algorithm achieved an 88.7% mAP@0.5, outperforming the baseline model YOLOv7 by 5.3%.
Expression-Guided Deep Joint Learning for Facial Expression Recognition
Authors: Fang Bei , Zhao Yujie , Han Guangxin , He Juhou
Published: August 2023

In recent years, convolutional neural networks (CNNs) have played a dominant role in facial expression recognition. While CNN-based methods have achieved remarkable success, they are notorious for having an excessive number of parameters, and they rely on a large amount of manually annotated data. To address this challenge, we expand the number of training samples by learning expressions from a face recognition dataset to reduce the impact of a small number of samples on the network training. In the proposed deep joint learning framework, the deep features of the face recognition dataset are clustered, and simultaneously, the parameters of an efficient CNN are learned, thereby marking the data for network training automatically and efficiently. Specifically, first, we develop a new efficient CNN based on the proposed affinity convolution module with much lower computational overhead for deep feature learning and expression classification. Then, we develop an expression-guided deep facial clustering approach to cluster the deep features and generate abundant expression labels from the face recognition dataset. Finally, the AC-based CNN is fine-tuned using an updated training set and a combined loss function. Our framework is evaluated on several challenging facial expression recognition datasets as well as a self-collected dataset. In the context of facial expression recognition applied to the field of education, our proposed method achieved an impressive accuracy of 95.87% on the self-collected dataset, surpassing other existing methods.
Research on Global Optimization Algorithm of Integrated Energy and Thermal Management for Plug-In Hybrid Electric Vehicles
Authors: Jiang Junyu , Yu Yuanbin , Min Haitao , Sun Weiyi , Cao Qiming , Huang Tengfei , Wang Deping
Published: August 2023

Power distribution and battery thermal management are important technologies for improving the energy efficiency of plug-in hybrid electric vehicles (PHEVs). In response to the global optimization of integrated energy thermal management strategy (IETMS) for PHEVs, a dynamic programming algorithm based on adaptive grid optimization (AGO–DP) is proposed in this paper to improve optimization performance by reducing the optimization range of SOC and battery temperature, and adaptively adjusting the grid distribution of state variables according to the actual feasible region. The simulation results indicate that through AGO–DP optimization, the reduction ratio of the state feasible region is more than 30% under different driving conditions. Meanwhile, the algorithm can obtain better global optimal driving costs more rapidly and accurately than traditional dynamic programming algorithms (DP). The computation time is reduced by 33.29–84.67%, and the accuracy of the global optimal solution is improved by 0.94–16.85% compared to DP. The optimal control of the engine and air conditioning system is also more efficient and reasonable. Furthermore, AGO–DP is applied to explore IETMS energy-saving potential for PHEVs. It is found that the IETMS energy-saving potential range is 3.68–23.74% under various driving conditions, which increases the energy-saving potential by 0.55–3.26% compared to just doing the energy management.
Properties of a Symmetrical Photoacoustic Helmholtz Cell Operating with Imbalanced Counterphase Light Stimulation
Authors: Starecki Tomasz , Pietrzak Michał Henryk , Ścisłowski Marcin Kamil
Published: August 2023

The output signal from a photoacoustic cell based on a symmetrical Helmholtz resonator structure can be substantially increased if a counterphase light stimulation is applied to the cell cavities. However even slight differences in the intensity of the light beams irradiating the cavities may affect the frequency response of the cell and the output signal level. This paper shows the influence of the imbalanced light irradiation on the properties of such a cell. It was found that even at relatively high irradiation mismatch, and even with the photoacoustic signal detection implemented with a single microphone, the influence of the irradiation imbalance on the frequency response of the cell around the resonance frequency is not critical. In the case of differential detection of the photoacoustic signal, the imbalance of the light irradiation does not affect the frequency response of the cell, but only the output signal level.