bluuebunny/crossref_metadata_2025 huggingface dataset:
Formulation and Biopharmaceutical Evaluation of Capsules Containing Freeze-Dried Cranberry Fruit Powder
Authors: Šedbarė Rima , Janulis Valdimaras , Ramanauskiene Kristina
Published: March 2023

Cranberry fruits are an important source of anthocyanins and anthocyanidins. The aim of the present study was to investigate the effect of excipients on the solubility of cranberry anthocyanins and their dissolution kinetics as well as on the disintegration time of the capsules. Selected excipients (sodium carboxymethyl cellulose, beta-cyclodextrin and chitosan) were found to affect the solubility and release kinetics of anthocyanins in freeze-dried cranberry powder. Capsule formulations N1–N9 had a disintegration time of less than 10 min, and capsule formulation N10 containing 0.200 g of freeze-dried cranberry powder, 0.100 g of Prosolv (combination of microcrystalline cellulose and colloidal silicon dioxide), and 0.100 g of chitosan had a capsule disintegration time of over 30 min. The total amount of anthocyanins released into the acceptor medium ranged from 1.26 ± 0.06 mg to 1.56 ± 0.03 mg. Capsule dissolution test data showed that the time to release into the acceptor medium was statistically significantly longer for the chitosan-containing capsule formulations compared to the control capsules (p < 0.05). Freeze-dried cranberry fruit powder is a potential source of anthocyanin-rich dietary supplements, and the choice of excipient chitosan could be a suitable solution in capsule formulations providing greater anthocyanin stability and modified release in the gastrointestinal tract.
Aggressiveness and Patulin Production in Penicillium expansum Multidrug Resistant Strains with Different Expression Levels of MFS and ABC Transporters, in the Presence or Absence of Fludioxonil
Authors: Ntasiou Panagiota , Samaras Anastasios , Papadakis Emmanouil-Nikolaos , Menkissoglu-Spiroudi Urania , Karaoglanidis George S.
Published: March 2023

Penicillium expansum is the most common postharvest pathogen of apple fruit, causing blue mold disease. Due to the extensive use of fungicides, strains resistant to multiple chemical classes have been selected. A previous study by our group proposed that the overexpression of MFS (major facilitator superfamily) and ABC (ATP binding cassette) transporters constitute an alternative resistance mechanism in Multi Drug resistant (MDR) strains of this pathogen. This study was initiated to determine two main biological fitness parameters of MDR strains: aggressiveness against apple fruit and patulin production. In addition, the expression pattern of efflux transporters and hydroxylase-encoding genes that belong to the patulin biosynthesis pathway, in the presence or absence of fludioxonil and under in vitro and in vivo conditions were investigated. Results showed that the MDR strains produced higher concentrations of patulin but showed a lower pathogenicity compared to the wild-type isolates. Moreover, expression analysis of patC, patM and patH genes indicated that the higher expression levels do not correlate with the detected patulin concentration. The selection of MDR strains in P. expansum populations and the fact that they produce more patulin, constitutes a serious concern not only for successful disease control but also for human health. The above-mentioned data represent the first report of MDR in P. expansum associated with its patulin-production ability and the expression level of patulin biosynthesis pathway genes.
Alleviation of Associated Drought and Salinity Stress’ Detrimental Impacts on an Eggplant Cultivar (‘Bonica F1’) by Adding Biochar
Authors: Hannachi Sami , Signore Angelo , Mechi Lassaad
Published: March 2023

To investigate the impact of biochar on eggplant growth, physiology, and yield parameters under separate and associated drought and salt stress, a pot experiment was carried out. An eggplant variety (‘Bonica F1’) was exposed to one NaCl concentration (S1 = 300 mM), three irrigation regimes (FI: full irrigation; DI: deficit irrigation; ARD: alternate root-zone drying irrigation), and one dose of biochar (B1 = 6% by weight). Our findings demonstrated that associated drought and salt stress had a greater negative impact on ‘Bonica F1’ performance in comparison to single drought or salt stress. Whereas, adding biochar to the soil improved the ability of ‘Bonica F1’ to alleviate the single and associated effects of salt and drought stress. Moreover, in comparison to DI under salinity, biochar addition in ARD significantly increased plant height, aerial biomass, fruit number per plant, and mean fresh weight per fruit by 18.4%, 39.7%, 37.5%, and 36.3%, respectively. Furthermore, under limited and saline irrigation, photosynthetic rate (An), transpiration rate (E), and stomatal conductance (gs) declined. In addition, the interaction between ARD and biochar effectively restored the equilibrium between the plant chemical signal (ABA) and hydraulic signal (leaf water potential). As a result, mainly under salt stress, with ARD treatment, intrinsic water use efficiency (WUEi) and yield traits were much higher than those in DI. Overall, biochar in combination with ARD could be an efficient approach for preserving crop productivity.
Improved Diaphorina citri (Hemiptera: Liviidae) Adults Biocontrol in Citrus by Hirsutella citriformis (Hypocreales: Ophiocordycipitaceae) Gum-Enhanced Conidia Formulation
Authors: Pérez-González Orquídea , Gomez-Flores Ricardo , Montesinos-Matías Roberto , Mellín-Rosas Marco A. , Cantú-Bernal Servando H. , Tamez-Guerra Patricia
Published: March 2023

Hirsutella citriformis Speare is the only entomopathogenic fungus involved in Diaphorina citri Kuwayama natural epizootics. The aim of the present study was to evaluate different protein sources as supplements to stimulate Hirsutella citriformis growth, improve conidiation on solid culture, and evaluate its produced gum for conidia formulation against D. citri adults. Hirsutella citriformis INIFAP-Hir-2 strain was grown on agar media enriched with wheat bran, wheat germ, soy, amaranth, quinoa, and pumpkin seed, in addition to oat with wheat bran and/or amaranth. The results demonstrated that 2% wheat bran significantly (p < 0.05) promoted mycelium growth. However, 4% and 5% wheat bran achieved the highest conidiation (3.65 × 107 conidia/mL and 3.68 × 107 conidia/mL, respectively). Higher conidiation (p < 0.05) was observed on oat grains supplemented with wheat bran, as compared with culturing on oat grains without supplements (7.25 × 107 versus 5.22 × 107 conidia/g), after a 14 d instead of 21 d incubation period. After supplementing synthetic medium or oat grains with wheat bran and/or amaranth, INIFAP-Hir-2 conidiation increased, whereas production time was reduced. After using Acacia and Hirsutella gums to formulate conidia produced on wheat bran and amaranth at 4%, field trial results showed that the highest (p < 0.05) D. citri mortality was achieved by Hirsutella gum-formulated conidia (80.0%), followed by the Hirsutella gum control (57.8%). Furthermore, Acacia gum-formulated conidia caused 37.8%, whereas Acacia gum and negative controls induced 9% mortality. In conclusion, Hirsutella citriformis gum used to formulate its conidia improved biological control against D. citri adults.
Synergistic Effects of Water Management and Silicon Foliar Spraying on the Uptake and Transport Efficiency of Cadmium in Rice (Oryza sativa L.)
Authors: Huang Xiaoyun , Fan Chengwu , Xie Dongyi , Chen Hongxing , Zhang Song , Chen Hui , Qin Song , Fu Tianling , He Tengbing , Gao Zhenran
Published: March 2023

To study the synergistic effects of water management and silicon (Si) foliar spraying on the uptake and transport of cadmium (Cd) in rice, we designed four treatments: conventional intermittent flooding + no Si foliar spraying (CK), continuous flooding throughout the growth stage + no Si foliar spraying (W), conventional intermittent flooding + Si foliar spraying (Si) and continuous flooding throughout the growth stage + Si foliar spraying (WSi). The results show that WSi treatment reduced the uptake and translocation of Cd by rice and significantly reduced the brown rice Cd content, with no effect on rice yield. Compared with CK, the Si treatment increased the net photosynthetic rate (Pn), stomatal conductance (Gs) and transpiration rate (Tr) of rice by 6.5–9.4%, 10.0–16.6% and 2.1–16.8%, respectively. The W treatment decreased these parameters by 20.5–27.9%, 8.6–26.8% and 13.3–23.3%, respectively, and the WSi treatment decreased them by 13.1–21.2%, 3.7–22.3% and 2.2–13.7%, respectively. The superoxide dismutase (SOD) and peroxidase (POD) activity decreased by 6.7–20.6% and 6.5–9.5%, respectively, following the W treatment. Following the Si treatment, SOD and POD activity increased by 10.2–41.1% and 9.3–25.1%, respectively, and following the WSi treatment, they increased by 6.5–18.1% and 2.6–22.4%, respectively. Si foliar spraying ameliorated the detrimental effects of continuous flooding throughout the growth stage on photosynthesis and antioxidant enzyme activity. We conclude that synergistic continuous flooding throughout the growth stage, combined with Si foliar spraying, can significantly block Cd uptake and translocation and is therefore an effective means of reducing the accumulation of Cd in brown rice.
Knowledge Maps as Support Tool for Managing Scientific Competences: A Case Study at a Portuguese Research Institute
Authors: Génio João , Trifan Alina , Neves António J. R.
Published: March 2023

In a research organization, finding someone who is an expert in a field and that can take up a given role, defining areas of excellence, or employing a new member all require understanding the competences that are available in-house. This work explores the idea of using knowledge or competence maps as support tools for managing scientific competences. We implemented a use case at the Institute of Electronics and Informatics Engineering of Aveiro, a research institute at the University of Aveiro, but the methodology we proposed can be adapted to virtually any research organization. Knowledge maps are visual representations of information that can be designed with variable granularities with respect to the knowledge assets of an organization. From a research management perspective, knowledge maps support the discovery of research competences and provide an instant overview of a topic by showing the main areas at a glance. This solution explored in this work employed data mining approaches for gathering information from public databases and presenting it using knowledge maps. Other visualization tools, such as bar graphs, tables, filters and search functionalities, were created and integrated into a web platform. When put together, these components could turn the platform into a key component for the administration of a research organization.
A Translation of the Arabic Duʿāʾ al-Saḥar (The Dawn Supplication) or Duʿāʾ al-Bahāʾ (The Supplication of Splendour) with Select Expository Scriptural Writings of the Bāb and Bahāʾu’llāh
Authors: Lambden Stephen
Published: March 2023

This article provides a full English translation of the Du’ā’ al-saḥar or Dawn Supplication for the Islamic month of Ramaḍān. Attributed to certain Imams whom Twelver Shī`ī Muslims regard as the successors of the Prophet Muhammad, it is an Arabic invocatory devotional also known from around the 13th century CE after its opening words, as the Du‘ā al-Bahā (Supplication of Splendour–Glory–Light). It is commonly ascribed to the fifth Imam Muhammad al-Bāqir (d. c. 126/743) or as transmitted through his son, the sixth Imam Ja‘far al-Ṣādiq (d. c. 138/765). The former version or recension has around 22 invocations, while the sixth Imam’s recension is known as the Du‘ā’ al-mubāhalah (The Supplication for Mutual Imprecation) and is considerably longer, consisting of over 30 supplicatory lines. This latter recension had its origin at a time when Muhammad was challenged near Medina by certain Yemenite Christians of Najrān about his messianic status as a Prophet in the light of theological and Christological issues. Both Sayyid ‘Alī Muḥammad Shīrāzī, “the Bāb” (1819–1850), and Mīrzā Ḥusayn ‘Alī Nūrī, “Bahā’u’llāh” (1817–1892) gave great importance to this supplication (or these two related supplications) and were much influenced by its vocabulary and rhythmic, cascading content relating the Names of God. The Bāb interpreted it on Islamic and imamological lines in his Persian Dalā’il-i saba‘ (The Seven Proofs). He cited it often, both in early texts and within numerous later major writings, including the Kitāb al-asmā’ (The Book of Names) and the Kitāb-i panj sha’n (The Book of the Seven Modes [of Revelation]). In his Persian Bayān and other writings, he used nineteen of its invocatory divine Names to frame the structure and names of his annual calendar of nineteen months: his new, wondrous or Badī‘ calendar (“The New/Regenerative Calendar”). This calendar was furthermore adopted by Baha’u’llah in his Kitāb-i aqdas (The Most Holy Book). His own theophanic title, evolving from “Jināb-i Bahā’” (His eminence the Glory) to “Bahā’u’llāh” (the Glory of God) is closely related and is rooted in this and certain similar texts. Baha’u’llah referred to the Du‘ā’ al-saḥar as the Lawh-i baqā’ (The Scriptural Tablet of Eternity) and understood its opening lines as an allusion to his person as the embodiment of the Supreme or Greatest Name of God (al-ism al-a`ẓam). Several of the Arabic and Persian writings in which the founder of the Baha’i religion interprets the Du‘ā’ al-saḥar are translated in this current paper. Their content demonstrates the extent to which he elevated this powerful Islamic text.
Multi-Disciplinary Monitoring Networks for Mesoscale Underground Experiments: Advances in the Bedretto Reservoir Project
Authors: Plenkers Katrin , Reinicke Andreas , Obermann Anne , Gholizadeh Doonechaly Nima , Krietsch Hannes , Fechner Thomas , Hertrich Marian , Kontar Karam , Maurer Hansruedi , Philipp Joachim , Rinderknecht Beat , Volksdorf Manuel , Giardini Domenico , Wiemer Stefan
Published: March 2023

The Bedretto Underground Laboratory for Geosciences and Geoenergies (BULGG) allows the implementation of hectometer (>100 m) scale in situ experiments to study ambitious research questions. The first experiment on hectometer scale is the Bedretto Reservoir Project (BRP), which studies geothermal exploration. Compared with decameter scale experiments, the financial and organizational costs are significantly increased in hectometer scale experiments and the implementation of high-resolution monitoring comes with considerable risks. We discuss in detail risks for monitoring equipment in hectometer scale experiments and introduce the BRP monitoring network, a multi-component monitoring system combining sensors from seismology, applied geophysics, hydrology, and geomechanics. The multi-sensor network is installed inside long boreholes (up to 300 m length), drilled from the Bedretto tunnel. Boreholes are sealed with a purpose-made cementing system to reach (as far as possible) rock integrity within the experiment volume. The approach incorporates different sensor types, namely, piezoelectric accelerometers, in situ acoustic emission (AE) sensors, fiber-optic cables for distributed acoustic sensing (DAS), distributed strain sensing (DSS) and distributed temperature sensing (DTS), fiber Bragg grating (FBG) sensors, geophones, ultrasonic transmitters, and pore pressure sensors. The network was realized after intense technical development, including the development of the following key elements: rotatable centralizer with integrated cable clamp, multi-sensor in situ AE sensor chain, and cementable tube pore pressure sensor.
Visual Parking Occupancy Detection Using Extended Contextual Image Information via a Multi-Branch Output ConvNeXt Network
Authors: Encío Leyre , Díaz César , del-Blanco Carlos R. , Jaureguizar Fernando , García Narciso
Published: March 2023

Along with society’s development, transportation has become a key factor in human daily life, increasing the number of vehicles on the streets. Consequently, the task of finding free parking slots in metropolitan areas can be dramatically challenging, increasing the chance of getting involved in an accident and the carbon footprint, and negatively affecting the driver’s health. Therefore, technological resources to deal with parking management and real-time monitoring have become key players in this scenario to speed up the parking process in urban areas. This work proposes a new computer-vision-based system that detects vacant parking spaces in challenging situations using color imagery processed by a novel deep-learning algorithm. This is based on a multi-branch output neural network that maximizes the contextual image information to infer the occupancy of every parking space. Every output infers the occupancy of a specific parking slot using all the input image information, unlike existing approaches, which only use a neighborhood around every slot. This allows it to be very robust to changing illumination conditions, different camera perspectives, and mutual occlusions between parked cars. An extensive evaluation has been performed using several public datasets, proving that the proposed system outperforms existing approaches.
An Event-Classification Neural Network Approach for Rapid Railroad Bridge Impact Detection
Authors: Lawal Omobolaji , V. Shajihan Shaik Althaf , Mechitov Kirill , Spencer Billie F.
Published: March 2023

Railroads are a critical part of the United States’ transportation sector. Over 40 percent (by weight) of the nation’s freight is transported by rail, and according to the Bureau of Transportation statistics, railroads moved $186.5 billion of freight in 2021. A vital part of the freight network is railroad bridges, with a good number being low-clearance bridges that are prone to impacts from over-height vehicles; such impacts can cause damage to the bridge and lead to unwanted interruption in its usage. Therefore, the detection of impacts from over-height vehicles is critical for the safe operation and maintenance of railroad bridges. While some previous studies have been published regarding bridge impact detection, most approaches utilize more expensive wired sensors, as well as relying on simple threshold-based detection. The challenge is that the use of vibration thresholds may not accurately distinguish between impacts and other events, such as a common train crossing. In this paper, a machine learning approach is developed for accurate impact detection using event-triggered wireless sensors. The neural network is trained with key features which are extracted from event responses collected from two instrumented railroad bridges. The trained model classifies events as impacts, train crossings, or other events. An average classification accuracy of 98.67% is obtained from cross-validation, while the false positive rate is minimal. Finally, a framework for edge classification of events is also proposed and demonstrated using an edge device.
EMG-Based Estimation of Lower Limb Joint Angles and Moments Using Long Short-Term Memory Network
Authors: Truong Minh Tat Nhat , Ali Amged Elsheikh Abdelgadir , Owaki Dai , Hayashibe Mitsuhiro
Published: March 2023

One of the fundamental limitations in human biomechanics is that we cannot directly obtain joint moments during natural movements without affecting the motion. However, estimating these values is feasible with inverse dynamics computation by employing external force plates, which can cover only a small area of the plate. This work investigated the Long Short-Term Memory (LSTM) network for the kinetics and kinematics prediction of human lower limbs when performing different activities without using force plates after the learning. We measured surface electromyography (sEMG) signals from 14 lower extremities muscles to generate a 112-dimensional input vector from three sets of features: root mean square, mean absolute value, and sixth-order autoregressive model coefficient parameters for each muscle in the LSTM network. With the recorded experimental data from the motion capture system and the force plates, human motions were reconstructed in a biomechanical simulation created using OpenSim v4.1, from which the joint kinematics and kinetics from left and right knees and ankles were retrieved to serve as output for training the LSTM. The estimation results using the LSTM model deviated from labels with average R2 scores (knee angle: 97.25%, knee moment: 94.9%, ankle angle: 91.44%, and ankle moment: 85.44%). These results demonstrate the feasibility of the joint angle and moment estimation based solely on sEMG signals for multiple daily activities without requiring force plates and a motion capture system once the LSTM model is trained.
Domain Adaptation with Contrastive Simultaneous Multi-Loss Training for Hand Gesture Recognition
Authors: Baptista Joel , Santos Vítor , Silva Filipe , Pinho Diogo
Published: March 2023

Hand gesture recognition from images is a critical task with various real-world applications, particularly in the field of human–robot interaction. Industrial environments, where non-verbal communication is preferred, are significant areas of application for gesture recognition. However, these environments are often unstructured and noisy, with complex and dynamic backgrounds, making accurate hand segmentation a challenging task. Currently, most solutions employ heavy preprocessing to segment the hand, followed by the application of deep learning models to classify the gestures. To address this challenge and develop a more robust and generalizable classification model, we propose a new form of domain adaptation using multi-loss training and contrastive learning. Our approach is particularly relevant in industrial collaborative scenarios, where hand segmentation is difficult and context-dependent. In this paper, we present an innovative solution that further challenges the existing approach by testing the model on an entirely unrelated dataset with different users. We use a dataset for training and validation and demonstrate that contrastive learning techniques in simultaneous multi-loss functions provide superior performance in hand gesture recognition compared to conventional approaches in similar conditions.
Lightweight SM-YOLOv5 Tomato Fruit Detection Algorithm for Plant Factory
Authors: Wang Xinfa , Wu Zhenwei , Jia Meng , Xu Tao , Pan Canlin , Qi Xuebin , Zhao Mingfu
Published: March 2023

Due to their rapid development and wide application in modern agriculture, robots, mobile terminals, and intelligent devices have become vital technologies and fundamental research topics for the development of intelligent and precision agriculture. Accurate and efficient target detection technology is required for mobile inspection terminals, picking robots, and intelligent sorting equipment in tomato production and management in plant factories. However, due to the limitations of computer power, storage capacity, and the complexity of the plant factory (PF) environment, the precision of small-target detection for tomatoes in real-world applications is inadequate. Therefore, we propose an improved Small MobileNet YOLOv5 (SM-YOLOv5) detection algorithm and model based on YOLOv5 for target detection by tomato-picking robots in plant factories. Firstly, MobileNetV3-Large was used as the backbone network to make the model structure lightweight and improve its running performance. Secondly, a small-target detection layer was added to improve the accuracy of small-target detection for tomatoes. The constructed PF tomato dataset was used for training. Compared with the YOLOv5 baseline model, the mAP of the improved SM-YOLOv5 model was increased by 1.4%, reaching 98.8%. The model size was only 6.33 MB, which was 42.48% that of YOLOv5, and it required only 7.6 GFLOPs, which was half that required by YOLOv5. The experiment showed that the improved SM-YOLOv5 model had a precision of 97.8% and a recall rate of 96.7%. The model is lightweight and has excellent detection performance, and so it can meet the real-time detection requirements of tomato-picking robots in plant factories.
Bilateral Cross-Modal Fusion Network for Robot Grasp Detection
Authors: Zhang Qiang , Sun Xueying
Published: March 2023

In the field of vision-based robot grasping, effectively leveraging RGB and depth information to accurately determine the position and pose of a target is a critical issue. To address this challenge, we proposed a tri-stream cross-modal fusion architecture for 2-DoF visual grasp detection. This architecture facilitates the interaction of RGB and depth bilateral information and was designed to efficiently aggregate multiscale information. Our novel modal interaction module (MIM) with a spatial-wise cross-attention algorithm adaptively captures cross-modal feature information. Meanwhile, the channel interaction modules (CIM) further enhance the aggregation of different modal streams. In addition, we efficiently aggregated global multiscale information through a hierarchical structure with skipping connections. To evaluate the performance of our proposed method, we conducted validation experiments on standard public datasets and real robot grasping experiments. We achieved image-wise detection accuracy of 99.4% and 96.7% on Cornell and Jacquard datasets, respectively. The object-wise detection accuracy reached 97.8% and 94.6% on the same datasets. Furthermore, physical experiments using the 6-DoF Elite robot demonstrated a success rate of 94.5%. These experiments highlight the superior accuracy of our proposed method.
Detection of Power Line Insulators in Digital Images Based on the Transformed Colour Intensity Profiles
Authors: Tomaszewski Michał , Gasz Rafał , Osuchowski Jakub
Published: March 2023

Proper maintenance of the electricity infrastructure requires periodic condition inspections of power line insulators, which can be subjected to various damages such as burns or fractures. The article includes an introduction to the problem of insulator detection and a description of various currently used methods. Afterwards, the authors proposed a new method for the detection of the power line insulators in digital images by applying selected signal analysis and machine learning algorithms. The insulators detected in the images can be further assessed in depth. The data set used in the study consists of images acquired by an Unmanned Aerial Vehicle (UAV) during its overflight along a high-voltage line located on the outskirts of the city of Opole, Opolskie Voivodeship, Poland. In the digital images, the insulators were placed against different backgrounds, for example, sky, clouds, tree branches, elements of power infrastructure (wires, trusses), farmland, bushes, etc. The proposed method is based on colour intensity profile classification on digital images. Firstly, the set of points located on digital images of power line insulators is determined. Subsequently, those points are connected using lines that depict colour intensity profiles. These profiles were transformed using the Periodogram method or Welch method and then classified with Decision Tree, Random Forest or XGBoost algorithms. In the article, the authors described the computational experiments, the obtained results and possible directions for further research. In the best case, the proposed solution achieved satisfactory efficiency (F1 score = 0.99). Promising classification results indicate the possibility of the practical application of the presented method.
Non-Destructive Inspection of High Temperature Piping Combining Ultrasound and Eddy Current Testing
Authors: Santos David , Machado Miguel A. , Monteiro João , Sousa José P. , Proença Carla S. , Crivellaro Fernando S. , Rosado Luís S. , Santos Telmo G.
Published: March 2023

This paper presents an automated Non-Destructive Testing (NDT) system for the in-service inspection of orbital welds on tubular components operating at temperatures as high as 200 °C. The combination of two different NDT methods and respective inspection systems is here proposed to cover the detection of all potential defective weld conditions. The proposed NDT system combines ultrasounds and Eddy current techniques with dedicated approaches for dealing with high temperature conditions. Phased array ultrasound was employed, searching for volumetric defects within the weld bead volume while Eddy currents were used to look for surface and sub-surface cracks. The results from the phased array ultrasound results showed the effectiveness of the cooling mechanisms and that temperature effects on sound attenuation can be easily compensated for up to 200 °C. The Eddy current results showed almost no influence when temperatures were raised up to 300 °C.
Elastic Textile Wristband for Bioimpedance Measurements
Authors: Monti Giuseppina , Raheli Federica , Recupero Andrea , Tarricone Luciano
Published: March 2023

In this paper, wristband electrodes for hand-to-hand bioimpedance measurements are investigated. The proposed electrodes consist of a stretchable conductive knitted fabric. Different implementations have been developed and compared with Ag/AgCl commercial electrodes. Hand-to-hand measurements at 50 kHz on forty healthy subjects have been carried out and the Passing–Bablok regression method has been exploited to compare the proposed textile electrodes with commercial ones. It is demonstrated that the proposed designs guarantee reliable measurements and easy and comfortable use, thus representing an excellent solution for the development of a wearable bioimpedance measurement system.
Recognition of Occluded Goods under Prior Inference Based on Generative Adversarial Network
Authors: Cao Mingxuan , Xie Kai , Liu Feng , Li Bohao , Wen Chang , He Jianbiao , Zhang Wei
Published: March 2023

Aiming at the recognition of intelligent retail dynamic visual container goods, two problems that lead to low recognition accuracy must be addressed; one is the lack of goods features caused by the occlusion of the hand, and the other is the high similarity of goods. Therefore, this study proposes an approach for occluding goods recognition based on a generative adversarial network combined with prior inference to address the two abovementioned problems. With DarkNet53 as the backbone network, semantic segmentation is used to locate the occluded part in the feature extraction network, and simultaneously, the YOLOX decoupling head is used to obtain the detection frame. Subsequently, a generative adversarial network under prior inference is used to restore and expand the features of the occluded parts, and a multi-scale spatial attention and effective channel attention weighted attention mechanism module is proposed to select fine-grained features of goods. Finally, a metric learning method based on von Mises–Fisher distribution is proposed to increase the class spacing of features to achieve the effect of feature distinction, whilst the distinguished features are utilized to recognize goods at a fine-grained level. The experimental data used in this study were all obtained from the self-made smart retail container dataset, which contains a total of 12 types of goods used for recognition and includes four couples of similar goods. Experimental results reveal that the peak signal-to-noise ratio and structural similarity under improved prior inference are 0.7743 and 0.0183 higher than those of the other models, respectively. Compared with other optimal models, mAP improves the recognition accuracy by 1.2% and the recognition accuracy by 2.82%. This study solves two problems: one is the occlusion caused by hands, and the other is the high similarity of goods, thus meeting the requirements of commodity recognition accuracy in the field of intelligent retail and exhibiting good application prospects.
Embracing the Collective: Challenges and Opportunities in Teaching and Teacher Education in the Wake of COVID-19
Authors: Borrero Noah
Published: March 2023

Ongoing impacts of the COVID-19 pandemic highlight structural inequities in our educational systems and force educators to ask prominent questions about the role of school as conditions continue to shift. This paper explores challenges and opportunities for moving forward in the fields of teaching and teacher education. Through presenting a framework of education for liberation, sociocultural learning theory, and fostering cultural assets, the value of live, in-person teaching is highlighted. Embracing this moment in history through honoring the lived experiences of students and striving for more collective approaches to teaching and learning are discussed as future possibilities in education.
The Role of Financial Sector Development and Educational Attainment in the Achievement of Economic Sustainability: Evidence from BRICS Economies
Authors: Tekin Turhan Gökçe , Tokal Pınar , Sart Gamze
Published: March 2023

The worldwide serious deteriorations in environmental and social quality have led many countries to follow institutional, social, and economic policies eliminating the negative environmental and social costs of economic growth and development, urbanization, and population growth. This study investigates the influence of financial sector development and educational attainment on economic sustainability in a sample of BRICS economies over the 1995–2020 term through causality and cointegration tests. The results of the causality test find a bidirectional causal interplay between financial development and economic sustainability and a unilateral causal effect from educational attainment on economic sustainability. Furthermore, cointegration analysis unveils a long-term positive influence of financial development and educational attainment on economic sustainability, but the effect of educational attainment on economic sustainability is ascertained to be slightly higher when compared with that of financial sector development. As a result, both educational attainment and financial development with environmental and social measures can be useful instruments to achieve economic sustainability.
Bilingual Teachers’ Contextualization in Teaching Chinese as a Foreign Language in Australian Schools
Authors: Ling Xufeng , Han Jinghe , Ma Yue
Published: March 2023

This research focuses on the practice of contextualization in teaching Chinese as a foreign language among a cohort of bilingual language teacher-researchers. It aims to extend the prevalent emphasis in the current literature that acknowledges the role of context in language education; however, these research studies primarily give voice to linguistic contexts or relegates context into a static physical space such as ‘environment’. This research is grounded in a social constructionism perspective whereby context is regarded as a dynamic relation-building process, or more accurately, a contextualizing process, enabled through various sociocultural activities. The data reveal that the teacher-researchers employed various forms of contextualization in teaching and linked these to particular teaching content through identifiable, purposeful activities, resulting in a variety of students’ responses. This research provides an evidence-based understanding of contextualization in CFL teaching for a more sustainable second language education.
Are Customers Always Right? The Importance of Sincerity and Keenness in Creating Retail Sustainable Development
Authors: Huang Ting-Chung , Ho Chien-Ta
Published: March 2023

In recent years, sustainability has become one of the essential elements of corporate management. There are many ways retailers can influence and develop a sustainable environment. The Taiwanese retail sector accounts for 10% of GDP. The capital city Taipei has the world’s highest department store density (per capita). This study encapsulates retail expertise to generate ten dimensions from 46 retail service quality scale indicators: SNAKE ROSES. The study first adopts qualitative analysis by conducting semi-structured interviews with five experts in the industry. Fifteen Delphi technique experts were then consulted for both qualitative and quantitative analysis of the indicators. Based on the Analytic Hierarchy Process (AHP), the most important aspects of customer service were ranked. The study shows that service quality dimensions are Sincerity, Neatness, Attentiveness, Keenness, Empathy, Reliability, Optimism, Steadfastness, Expertise, and Store Policy. Sincerity and Keenness are the most crucial globally. Although numerous researchers have examined the broader topic of perceived service quality, studies have yet to explore the critical role of Eastern culture, and therefore this study introduces an innovative framework. Implications include a conceptual framework for the key factors influencing customer satisfaction, one of the most critical dimensions of perceived service quality and customer satisfaction in the Taiwanese retail industry. A specification for retailers is delivered, intending to improve their sustainability strategies.
Perspectives of Next-Generation Live-Attenuated Rift Valley Fever Vaccines for Animal and Human Use
Authors: Wichgers Schreur Paul J. , Bird Brian H. , Ikegami Tetsuro , Bermúdez-Méndez Erick , Kortekaas Jeroen
Published: March 2023

Live-attenuated Rift Valley fever (RVF) vaccines transiently replicate in the vaccinated host, thereby effectively initiating an innate and adaptive immune response. Rift Valley fever virus (RVFV)-specific neutralizing antibodies are considered the main correlate of protection. Vaccination with classical live-attenuated RVF vaccines during gestation in livestock has been associated with fetal malformations, stillbirths, and fetal demise. Facilitated by an increased understanding of the RVFV infection and replication cycle and availability of reverse genetics systems, novel rationally-designed live-attenuated candidate RVF vaccines with improved safety profiles have been developed. Several of these experimental vaccines are currently advancing beyond the proof-of-concept phase and are being evaluated for application in both animals and humans. We here provide perspectives on some of these next-generation live-attenuated RVF vaccines and highlight the opportunities and challenges of these approaches to improve global health.
Seroprevalence and Risk Factors for Toxoplasma gondii Infection in Horses
Authors: Marzok Mohamed , AL-Jabr Omar A. , Salem Mohamed , Alkashif Khalid , Sayed-Ahmed Mohamed , Wakid Majed H. , Kandeel Mahmoud , Selim Abdelfattah
Published: March 2023

Background: Toxoplasma gondii is classified as intracellular protozoa and is one of the major zoonotic parasites. Most warm-blooded intermediate hosts, including humans, are commonly infected by this parasite. The epidemiology of T. gondii infection in Egyptian horses is currently poorly understood. Methods: 420 blood samples were randomly collected from horses raised in four governorates in Northern Egypt (110 each from Giza and Kafr El Sheikh, and 100 each from Qalyubia and Gharbia) to investigate the existence of antibodies against T. gondii using a commercial ELISA kit, and to ascertain the risk factors for the infection. Results: the antibodies for T. gondii were found in 16.2% (68/420) of the examined horses, with no significant differences among the four studied governorates. The highest prevalence rate was observed in Giza. The results revealed that sex, breed, age, and contact with domestic ruminants or cats were recognized as potential risk factors. The high prevalence rate was found in mixed breed horses (OR = 2.63, 95% CI: 0.95–7.26), mares (OR = 2.35, 95% CI: 1.31–4.19), and horses aged over 10 years (OR = 2.78, 95% CI: 1.30–3.44). Moreover, the likelihood of seropositivity for T. gondii infection was higher in horses raised in environments with cats (OR = 1.97, 95% CI: 1.13–3.44, p = 0.017) or domestic ruminants (OR = 2.16, 1.21–3.86, p = 0.010). This report confirms that horses in Northern Egypt are exposed to T. gondii and thus raises the possibility that people and other animals could contract the disease. Conclusions: routine examination and management of T. gondii infection in horses in these governorates is advised.
Relationship between activity styles of medical college students and danger experience during the COVID-19 pandemic
Authors:   Autonomous Professional Educational Institution of the Udmurt Republic ", Nikitina O. V. ,   Republican Medical College named after the Hero of the Soviet Union F.A. Pushina of the Ministry of Health of the Udmurt Republic”
Published: March 2023

The article presents the results of studying the relationship between student activity styles as a subject of life activity and experiencing the vital threat of the COVID-19 pandemic. The relevance of the research in the framework of the study of the diverse activity of medical students is indicated. The results of the study can be used in psychological counseling, as well as become the basis for the development of psychological support programs for the educational process of medical students during a pandemic. The purpose of the research. To study of the relationship between the activity styles of medical college students and the experience of the threat of the COVID-19 pandemic. Results. The study has established a connection in medical college students between the "Cognitive- reflexive" style of activity and the experience of "Danger-safety" in relation to the mental "I" and in relation to people; the "Communicative-reflexive" style of activity is associated with the experience of the insecurity of the world. Conclusion. The research is of practical importance for psychologists of educational organizations in the conduct of psychological education and individual psychological counseling of students.
PETRO: Программа для получения и обработки микрофотографий шлифов с использованием Android-смартфона
Authors:   North-East Interdisciplinary Scientific Research Institute n. a. N. A. Shilo, FEB RAS, Magadan, Polzunenkov G. O. , Kondratiev M. N. ,   North-East Interdisciplinary Scientific Research Institute n. a. N. A. Shilo, FEB RAS, Magadan
Published: March 2023

The article discusses the method for obtaining thin section microphotographs using an Android smartphone, with further processing of them in the PETRO program. The paper outlines the principle of working with the software written in the Python programming language. When conducting petrographic studies with the use of a microscope, the PETRO program permits to properly catalog the resulting photographs and to save time on additional processing (setting the scale, applying masks, etc.). In addition to taking photos of thin sections with a smartphone, it is possible to upload photos directly from a computer disk.
Emerging Nano-/Biotechnology Drives Oncolytic Virus-Activated and Combined Cancer Immunotherapy
Authors: Fang Chao , Xiao Gaozhe , Wang Taixia , Song Li , Peng Bo , Xu Bin , Zhang Kun
Published: March 2023

Oncolytic viruses (OVs) as one promising antitumor methods have made important contributions to tumor immunotherapy, which arouse increasing attention. They provide the dual mechanisms including direct killing effect toward tumor cells and immune activation for elevating antitumor responses, which have been proved in many preclinical studies. Especially, natural or genetically modified viruses as clinical immune preparations have emerged as a new promising approach objective to oncology treatment. The approval of talimogene laherparepvec (T-VEC) by the U.S. Food and Drug Administration (FDA) for the therapy of advanced melanoma could be considered as a milestone achievement in the clinical translation of OV. In this review, we first discussed the antitumor mechanisms of OVs with an emphasis on targeting, replication, and propagation. We further outlined the state of the art of current OVs in tumor and underlined the activated biological effects especially including immunity. More significantly, the enhanced immune responses based on OVs were systematically discussed from different perspectives such as combination with immunotherapy, genetic engineering of OVs, integration with nanobiotechnology or nanoparticles, and antiviral response counteraction, where their principles were shed light on. The development of OVs in the clinics was also highlighted to analyze the actuality and concerns of different OV applications in clinical trials. At last, the future perspectives and challenges of OVs as an already widely accepted treatment means were discussed. This review will provide a systematic review and deep insight into OV development and also offer new opportunities and guidance pathways to drive the further clinical translation.
Multiphysics Numerical Simulation and Geometric Optimization of a Micronozzle for the MEMS Thruster
Authors: Li Xingchen , Liang Haopeng , Zhang Ruofan , Yao Wen , Chen Xiaoqian
Published: March 2023

This paper reports a numerical research on MEMS (microelectromechanical system) micronozzles through multiphysics coupling simulation along with design optimization based on simulation results. The micronozzle, which is a core component of the electrothermal microthruster, features a micron-scale geometry, a 2-dimensional (2D) Laval configuration, a rectangular cross section, and a highly thermal conductive silicon wall due to MEMS fabrication. As a result, viscous loss in the flow field and heat transfer to the nozzle wall can strongly influence nozzle performance, namely, thrust force and specific impulse. To accurately understand the flow field inside the micronozzle and how the highly thermal conductive silicon wall interacts with gas flow, a numerical simulation that couples fluid dynamics field and solid heat transfer field is employed in the research. The influence of different structural parameters on micronozzle performance is then investigated to set a basis for design optimization. The optimum design of the linear expander micronozzle is obtained through constrained optimization by linear approximation. To further improve micronozzle performance, the bell-shaped expander is adapted. The optimization result shows that the bell-shaped expander is not suitable for micronozzle featuring 2D Laval configuration, and the reason behind the phenomenon is thoroughly discussed.
Застосування абстрактних автоматів Мілі та Мура для реалізації алгорит-мів рекомендації та вибору
Authors: Гуляєв Кирило Дмитрович , Ющенко Катерина Сергіївна , Купрін Олексій Миколайович
Published: March 2023

Інформатизація суспільства та проникнення Інтернету у повсякденне життя вимагають вдосконалення різноманітних сервісів, що працюють на вебплатформах. Серед таких сервісів окремо можна виділити сервіси, пов’язані з можливістю вибрати деяку дію або продукт та рекомендаційні системи, що дозволяють запропонувати користувачу товар або послугу. Задачею роботи є представлення підходу до створення алгоритмів рекомендації та вибору з використанням абстрактних автоматів для реалізації рекомендаційних систем, 3D-резюме та сервісів добору спеціалістів і пошуку роботи за заданими параметрами, реалізації інструментів оцінювання знань та вмінь, здійснення переборів характеристик товарів та послуг, представлених на вебплатформах. Задача реалізується за допомогою використання в алгоритмізації рекомендаційних систем та алгоритмів вибору абстрактних автоматів Мілі та Мура. Запропоновано алгоритми з використанням зазначених автоматів, які дозволяють отримати відповідь у вигляді алфавіту, символів або слів при наявності декількох елементів (алфавіту, символів, слів) на вході та їх переборі (алфавіту станів, отримання словосполучень, конструкцій відповідей). Особливістю вирішених задач є те, що запропонований підхід можна використовувати в розробці штучного інтелекту для опису поведінки користувача Інтернет, коли на початку є деякі вхідні слова, що описують відношення особи до товарів, послуг, виконання робіт, вчинення конкретних дій, а на виході, після складного перебору обмежень, є вибір конкретного об’єкта або дії, стосовно якої прийняти рішення може як користувач, так і стороння особа, яка щось пропонує користувачу. Запропоновані алгоритми можуть використовуватися при розробці інтерактивних сервісів відбору персоналу, визначення необхідності навчання кадрів та підвищення кваліфікації, рекомендаційних систем фінансово-кредитних установ, інтернет-магазинів для проведення агресивного маркетингу, а також реалізації онлайн-сервісів оцінки знань.