bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effectiveness of an Intervention Programme for Reducing Peer Rejection in Early Childhood Education
Authors: Molinero-González Paula , Martín-Antón Luis J. , Carbonero-Martín Miguel Á. , Arteaga-Cedeño Wendy L. , Rodríguez-Sáez José Luis
Published: November 2023

In the early years of schooling, peer groups are key to fostering students’ overall learning and development. Yet it has been found that around 10% of children suffer from peer rejection in the classroom, with this problem entailing negative consequences both in the short and long term. The problem proves difficult for adults to detect, which usually leads to a delay in measures being taken to intervene and prevent it. This study applies an experimental design with pre-test and post-test measurements in two groups—experimental and control—in order to address the problem of rejection in the early years of schooling. It explores aspects such as sociometric type, degree of victimisation, social and antisocial behaviour, as well as problematic situations among 637 students at six schools. We then implement an intervention programme for socioemotional competence throughout a school year in an effort to improve students’ social skills and relationships, focusing specifically on preventing and reducing the rejection experienced by some of these children. The programme comprises 35 teaching activities and strategies that promote the development of competences for student inclusion (curbing aggression, encouraging teamwork, fostering self-esteem, etc.) and that seek to involve all students, teachers, and relatives by offering an array of complementary resources that enrich the initiatives applied (a programme calendar, assessment notebook, questionnaires, related website, material resources). After the intervention programme, it was found that the experimental group had reduced the percentage of students who suffered rejection from 9.9% to 7.3%, although the same was not true of the control group, which went from 9.5% of rejected students to 10.2%. The reduction in the percentage of rejected students in the experimental group after the application of the programme is an encouraging result that invites us to continue working on more comprehensive interventions to prevent and reduce this phenomenon.
A Scoping Review of Studies on Assistive Technology Interventions and Their Impact on Individuals with Autism Spectrum Disorder in Arab Countries
Authors: Al-Hendawi Maha , Hussein Esraa , Al Ghafri Badriya , Bulut Sefa
Published: November 2023

The rising prevalence of autism spectrum disorder (ASD) in Arab countries necessitates evidence-based interventions. Assistive technology (AT) presents a promising approach. However, data on the pervasiveness of AT use and its effectiveness for individuals with ASD, specifically within Arab countries, remain scarce. Objective: To review the current literature on the AT interventions and outcomes reported for individuals with ASD in Arab countries. Methods: A scoping review adhering to PRISMA guidelines was undertaken to explore the utilization of AT, segmented into three categories: low-technology (low-tech), mid-technology (mid-tech), and high-technology (high-tech) devices. Results: Twelve studies had a pooled sample of 1547 participants, primarily male school-aged children with ASD. The AT applications evaluated ranged from low-tech visual schedules and support to high-tech virtual reality systems. Studies have reported the potential benefits of AT in improving communication, social, academic, adaptive, and functional abilities; however, comparative evidence between AT interventions is limited. The identified barriers to the adoption of AT included caregiver uncertainty about the use of AT and a lack of awareness of AT among professionals and the Arab community in general. Conclusion: Available studies suggest that the adoption of AT can enhance the skills of individuals with ASD in Arab countries. However, more rigorous studies across diverse demographic groups and Arab national regions are needed to strengthen the evidence base and provide appropriate recommendations.
Prevalence and Determinants of Diarrhea, Fever, and Coexistence of Diarrhea and Fever in Children Under-Five in Bangladesh
Authors: Islam Md. Shariful , Chowdhury Mohammad Rocky Khan , Bornee Farzana Akhter , Chowdhury Hasina Akhter , Billah Baki , Kader Manzur , Rashid Mamunur
Published: November 2023

Diarrhea and fever are prevalent childhood illnesses with potentially severe consequences, especially when they co-occur. This study investigates the prevalence and determinants of diarrhea, fever, and their coexistence among children under-five in Bangladesh. Data from the 2017–2018 Bangladesh Demography and Health Survey (BDHS) were analyzed using multivariable stepwise logistic regression with backward selection. This study found that 5.0% for diarrhea, 34.0% for fever, and 3.0% for the coexistence of both illnesses. Common factors associated with childhood diarrhea and fever included the child’s age (12–23 months), and the mother’s education. Diarrhea was associated with households with improved water sources and children in the Barisal division, while fever was linked to underweight children and those from more affluent backgrounds. The coexistence of both was significantly linked to underweight children, higher birth orders, and children from the Rajshahi division. Notably, child illnesses were associated with parental education, higher socio-economic status, and access to improved drinking water sources. Diarrhea affects one in 20 children, fever affects one in three, and the coexistence of both conditions affects one in 35 children in Bangladesh. The findings need further research and policy reviews to develop effective interventions and improve child health in Bangladesh.
Effects of Graphene Oxide on Tribological Properties of Micro-Arc Oxidation Coatings on Ti-6Al-4V
Authors: Hu Qingyuan , Li Xingming , Zhao Gai , Ruan Yuling , Wang Guoqing , Ding Qingjun
Published: November 2023

This paper investigates the effect of graphene oxide (GO) particles on the friction reduction and wear resistance of coatings on a Ti-6Al-4V alloy generated using the micro-arc oxidation (MAO) technique. Different concentrations of GO were added in aluminate–phosphate electrolyte. The composition of the MAO coatings was investigated using X-ray diffraction and the energy dispersive spectrum. Measurements of the coating’s thickness, hardness, and roughness have also been conducted. Ball-on-disk friction tests under dry conditions were carried out to reveal the tribological behavior of the MAO coating. The results showed that the coating consisted of Al2TiO5 and γ-Al2O3. The addition of GO greatly reduced the friction coefficient by 25%. The coating with 5 g/L of GO particles exhibited the lowest friction coefficient (reduced from 0.47 to 0.35). Moreover, the coating thickness become thicker (from 10 to 20 μm) with an increase in GO concentration from 0 to 10 g/L. The wear mechanism was revealed via worn surface analysis. This study provides a helpful way to improve the surface wear resistance of titanium alloys.
Comparative Study of Keccak SHA-3 Implementations
Authors: Dolmeta Alessandra , Martina Maurizio , Masera Guido
Published: November 2023

This paper conducts an extensive comparative study of state-of-the-art solutions for implementing the SHA-3 hash function. SHA-3, a pivotal component in modern cryptography, has spawned numerous implementations across diverse platforms and technologies. This research aims to provide valuable insights into selecting and optimizing Keccak SHA-3 implementations. Our study encompasses an in-depth analysis of hardware, software, and software–hardware (hybrid) solutions. We assess the strengths, weaknesses, and performance metrics of each approach. Critical factors, including computational efficiency, scalability, and flexibility, are evaluated across different use cases. We investigate how each implementation performs in terms of speed and resource utilization. This research aims to improve the knowledge of cryptographic systems, aiding in the informed design and deployment of efficient cryptographic solutions. By providing a comprehensive overview of SHA-3 implementations, this study offers a clear understanding of the available options and equips professionals and researchers with the necessary insights to make informed decisions in their cryptographic endeavors.
Observation of Micro-Scale Domain Structure Evolution under Electric Bias in Relaxor-Based PIN-PMN-PT Single Crystals
Authors: Li Kai , Zheng Huashan , Qi Xudong , Cong Shan , Zhao Zhenting , Zhao Junfeng , Mei Haijuan , Zhang Duoduo , Sun Enwei , Zheng Limei , Gong Weiping , Yang Bin
Published: November 2023

Relaxor ferroelectrics play a vital role as functional components in electromechanical devices. The observation of micro-scale domain structure evolution under electric bias in relaxor ferroelectrics has posed challenges due to their complex domain morphology characterized by small-sized domains. The present study aims to investigate the dielectric diffusion–relaxation characteristics, domain structure, and domain switching evolution under electric bias in high-performance single crystals of Pb(In1/2Nb1/2)O3-Pb(Mg1/3Nb2/3)O3-33PbTiO3. The findings reveal the presence of strip-like domain patterns that interlock irregular small-sized nanodomains in PIN-PMN-33PT single crystals. Furthermore, the sample undergoes three distinct stages under electric bias, including the nucleation of new domains, the gradual forward expansion of domains, and the lateral expansion of domains. These observations provide valuable insights for understanding and exploring domain engineering techniques in relaxor ferroelectrics.
Photochromism, UV-Vis, Vibrational and Fluorescence Spectroscopy of Differently Colored Hackmanite
Authors: Song Chuchu , Guo Qingfeng , Liu Yang , Rao Yinghua , Liao Libing
Published: November 2023

Because of the rich fluorescent color and unique photochromic properties, hackmanite has attracted many mineralogists. In this paper, the basic gemmological characteristics and photochromic and fluorescence mechanisms of four different colors of hackmanite are further investigated through the study of their structural, compositional, and spectroscopic features. The results show the change in the color of hackmanite in photochromism is caused by the joint action of the F-center and the oxygen hole centers. The change in the UV-Vis spectra may be caused by the superposition of two peaks. Under 365 nm UV excitation, the peak of fluorescence spectra of 662 nm is related to the 2∏g→2∏u transition of S2−, the blue emission at 441 nm is caused by the 3P0.1→1S0 transition of s2 ions (Pb2+, Tl+, Sn2+ Sb2+), and at 541 nm is caused by the Mn2+ center. The results are helpful in deepening the understanding of photochromism, fluorescence mechanism, and its structure, expanding the application of hackmanite.
Perilipin1 Expression as a Prognostic Factor in Patients with Squamous Cell Carcinoma of the Lung
Authors: Kim Min Hye , Lee Jeong Hee , Lee Jong Sil , Kim Dong Chul , Yang Jung Wook , An Hyo Jung , Na Ji Min , Jung Wook Jae , Song Dae Hyun
Published: November 2023

Perilipin (PLIN) is a major structural protein located on the surface of lipid droplets. PLIN plays an important role in human metabolism and is associated with metabolic diseases, such as obesity, diabetes, hypertension, and endocrine disorders. The dysregulation of lipid metabolism is one of the most prominent metabolic changes observed in cancers. Therefore, the PLIN protein family has recently attracted attention owing to its role in lipid metabolism and cancer. To date, no studies have addressed the association between the prognosis of lung cancer and PLIN1 expression. For the first time, we found that high PLIN1 expression was significantly correlated with worse disease-free survival (DFS) in lung squamous cell carcinoma (SCC). We examined PLIN1 expression by the immunohistochemical analysis of surgical lung SCC specimens obtained from 94 patients. We analyzed the correlation between PLIN1 expression, clinicopathological data, and patient survival, using a chi-squared test, Kaplan–Meier analysis with log-rank tests, and the multivariate Cox proportional hazards regression test. High PLIN1 expression was significantly correlated with lower DFS in the Kaplan–Meier analysis and the multivariate Cox proportional hazards regression model. High PLIN1 expression was significantly correlated with worse prognosis in lung SCC.
Hyper-Dense_Lung_Seg: Multimodal-Fusion-Based Modified U-Net for Lung Tumour Segmentation Using Multimodality of CT-PET Scans
Authors: Alshmrani Goram Mufarah , Ni Qiang , Jiang Richard , Muhammed Nada
Published: November 2023

The majority of cancer-related deaths globally are due to lung cancer, which also has the second-highest mortality rate. The segmentation of lung tumours, treatment evaluation, and tumour stage classification have become significantly more accessible with the advent of PET/CT scans. With the advent of PET/CT scans, it is possible to obtain both functioning and anatomic data during a single examination. However, integrating images from different modalities can indeed be time-consuming for medical professionals and remains a challenging task. This challenge arises from several factors, including differences in image acquisition techniques, image resolutions, and the inherent variations in the spectral and temporal data captured by different imaging modalities. Artificial Intelligence (AI) methodologies have shown potential in the automation of image integration and segmentation. To address these challenges, multimodal fusion approach-based U-Net architecture (early fusion, late fusion, dense fusion, hyper-dense fusion, and hyper-dense VGG16 U-Net) are proposed for lung tumour segmentation. Dice scores of 73% show that hyper-dense VGG16 U-Net is superior to the other four proposed models. The proposed method can potentially aid medical professionals in detecting lung cancer at an early stage.
Cardiac Laterality: Surgical Results of Right Atrial Isomerism
Authors: Ortega-Zhindón Diego B. , Pérez-Hernández Nonanzit , Rodríguez-Pérez José Manuel , García-Montes José A. , Calderón-Colmenero Juan , Rivera-Buendía Frida , Cervantes-Salazar Jorge L.
Published: November 2023

Right atrial isomerism (RAI) is a complex entity with varying diagnostic and treatment outcomes due to its rarity. Treatment options range from palliative to corrective surgeries, resulting in heterogeneous outcomes. The aim of this study was to analyze the results obtained after cardiac surgery in patients with RAI. A retrospective study was conducted, including patients diagnosed with RAI who underwent cardiac surgery. Their follow-up was from 1 January 2010 to 31 March 2020. Demographic characteristics and perioperative conditions were described. Thirty-eight patients were included, the median age was 4 years (IQR 2–9.2) and 57.9% were men. The main diagnoses were atrioventricular canal (63.2%) and pulmonary stenosis (55.3%). The most common surgical procedures were modified Blalock–Taussig shunt (65.8%) and total cavopulmonary connection with an extracardiac conduit fenestrated without cardiopulmonary bypass (15.9%). We did not find any factors associated with negative outcomes in these patients. The overall survival was 86.8%, with a better outcome in those who did not require reintubation (log rank, p < 0.01). The survival of RAI was similar to other centers. Individuals with RAI should be evaluated rigorously to determine an adequate repair strategy, considering high morbidity and mortality.
Artificial Intelligence Applied to Chest X-ray: A Reliable Tool to Assess the Differential Diagnosis of Lung Pneumonia in the Emergency Department
Authors: Ippolito Davide , Maino Cesare , Gandola Davide , Franco Paolo Niccolò , Miron Radu , Barbu Vlad , Bologna Marco , Corso Rocco , Breaban Mihaela Elena
Published: November 2023

Background: Considering the large number of patients with pulmonary symptoms admitted to the emergency department daily, it is essential to diagnose them correctly. It is necessary to quickly solve the differential diagnosis between COVID-19 and typical bacterial pneumonia to address them with the best management possible. In this setting, an artificial intelligence (AI) system can help radiologists detect pneumonia more quickly. Methods: We aimed to test the diagnostic performance of an AI system in detecting COVID-19 pneumonia and typical bacterial pneumonia in patients who underwent a chest X-ray (CXR) and were admitted to the emergency department. The final dataset was composed of three sub-datasets: the first included all patients positive for COVID-19 pneumonia (n = 1140, namely “COVID-19+”), the second one included all patients with typical bacterial pneumonia (n = 500, “pneumonia+”), and the third one was composed of healthy subjects (n = 1000). Two radiologists were blinded to demographic, clinical, and laboratory data. The developed AI system was used to evaluate all CXRs randomly and was asked to classify them into three classes. Cohen’s κ was used for interrater reliability analysis. The AI system’s diagnostic accuracy was evaluated using a confusion matrix, and 95%CIs were reported as appropriate. Results: The interrater reliability analysis between the most experienced radiologist and the AI system reported an almost perfect agreement for COVID-19+ (κ = 0.822) and pneumonia+ (κ = 0.913). We found 96% sensitivity (95% CIs = 94.9–96.9) and 79.8% specificity (76.4–82.9) for the radiologist and 94.7% sensitivity (93.4–95.8) and 80.2% specificity (76.9–83.2) for the AI system in the detection of COVID-19+. Moreover, we found 97.9% sensitivity (98–99.3) and 88% specificity (83.5–91.7) for the radiologist and 97.5% sensitivity (96.5–98.3) and 83.9% specificity (79–87.9) for the AI system in the detection of pneumonia+ patients. Finally, the AI system reached an accuracy of 93.8%, with a misclassification rate of 6.2% and weighted-F1 of 93.8% in detecting COVID+, pneumonia+, and healthy subjects. Conclusions: The AI system demonstrated excellent diagnostic performance in identifying COVID-19 and typical bacterial pneumonia in CXRs acquired in the emergency setting.
High-Performance Detection-Based Tracker for Multiple Object Tracking in UAVs
Authors: Li Xi , Zhu Ruixiang , Yu Xianguo , Wang Xiangke
Published: November 2023

As a result of increasing urbanization, traffic monitoring in cities has become a challenging task. The use of Unmanned Aerial Vehicles (UAVs) provides an attractive solution to this problem. Multi-Object Tracking (MOT) for UAVs is a key technology to fulfill this task. Traditional detection-based-tracking (DBT) methods begin by employing an object detector to retrieve targets in each image and then track them based on a matching algorithm. Recently, the popular multi-task learning methods have been dominating this area, since they can detect targets and extract Re-Identification (Re-ID) features in a computationally efficient way. However, the detection task and the tracking task have conflicting requirements on image features, leading to the poor performance of the joint learning model compared to separate detection and tracking methods. The problem is more severe when it comes to UAV images due to the presence of irregular motion of a large number of small targets. In this paper, we propose using a balanced Joint Detection and Re-ID learning (JDR) network to address the MOT problem in UAV vision. To better handle the non-uniform motion of objects in UAV videos, the Set-Membership Filter is applied, which describes object state as a bounded set. An appearance-matching cascade is then proposed based on the target state set. Furthermore, a Motion-Mutation module is designed to address the challenges posed by the abrupt motion of UAV. Extensive experiments on the VisDrone2019-MOT dataset certify that our proposed model, referred to as SMFMOT, outperforms the state-of-the-art models by a wide margin and achieves superior performance in the MOT tasks in UAV videos.
Implementation of an Edge-Computing Vision System on Reduced-Board Computers Embedded in UAVs for Intelligent Traffic Management
Authors: Bemposta Rosende Sergio , Ghisler Sergio , Fernández-Andrés Javier , Sánchez-Soriano Javier
Published: November 2023

Advancements in autonomous driving have seen unprecedented improvement in recent years. This work addresses the challenge of enhancing the navigation of autonomous vehicles in complex urban environments such as intersections and roundabouts through the integration of computer vision and unmanned aerial vehicles (UAVs). UAVs, owing to their aerial perspective, offer a more effective means of detecting vehicles involved in these maneuvers. The primary objective is to develop, evaluate, and compare different computer vision models and reduced-board (and small-power) hardware for optimizing traffic management in these scenarios. A dataset was constructed using two sources, several models (YOLO 5 and 8, DETR, and EfficientDetLite) were selected and trained, four reduced-board computers were chosen (Raspberry Pi 3B+ and 4, Jetson Nano, and Google Coral), and the models were tested on these boards for edge computing in UAVs. The experiments considered training times (with the dataset and its optimized version), model metrics were obtained, inference frames per second (FPS) were measured, and energy consumption was quantified. After the experiments, it was observed that the combination that best suits our use case is the YoloV8 model with the Jetson Nano. On the other hand, a combination with much higher inference speed but lower accuracy involves the EfficientDetLite models with the Google Coral board.
Percolation Theories for Quantum Networks
Authors: Meng Xiangyi , Hu Xinqi , Tian Yu , Dong Gaogao , Lambiotte Renaud , Gao Jianxi , Havlin Shlomo
Published: November 2023

Quantum networks have experienced rapid advancements in both theoretical and experimental domains over the last decade, making it increasingly important to understand their large-scale features from the viewpoint of statistical physics. This review paper discusses a fundamental question: how can entanglement be effectively and indirectly (e.g., through intermediate nodes) distributed between distant nodes in an imperfect quantum network, where the connections are only partially entangled and subject to quantum noise? We survey recent studies addressing this issue by drawing exact or approximate mappings to percolation theory, a branch of statistical physics centered on network connectivity. Notably, we show that the classical percolation frameworks do not uniquely define the network’s indirect connectivity. This realization leads to the emergence of an alternative theory called “concurrence percolation”, which uncovers a previously unrecognized quantum advantage that emerges at large scales, suggesting that quantum networks are more resilient than initially assumed within classical percolation contexts, offering refreshing insights into future quantum network design.
When It Counts—Econometric Identification of the Basic Factor Model Based on GLT Structures
Authors: Frühwirth-Schnatter Sylvia , Hosszejni Darjus , Lopes Hedibert Freitas
Published: November 2023

Despite the popularity of factor models with simple loading matrices, little attention has been given to formally address the identifiability of these models beyond standard rotation-based identification such as the positive lower triangular (PLT) constraint. To fill this gap, we review the advantages of variance identification in simple factor analysis and introduce the generalized lower triangular (GLT) structures. We show that the GLT assumption is an improvement over PLT without compromise: GLT is also unique but, unlike PLT, a non-restrictive assumption. Furthermore, we provide a simple counting rule for variance identification under GLT structures, and we demonstrate that within this model class, the unknown number of common factors can be recovered in an exploratory factor analysis. Our methodology is illustrated for simulated data in the context of post-processing posterior draws in sparse Bayesian factor analysis.
Did Remittance Inflow in Bangladesh Follow the Gravity Path during COVID-19?
Authors: Goswami Gour Gobinda , Barai Munim Kumar , Atique Mahnaz Aftabi , Rahman Mostafizur
Published: November 2023

Remittances are one of the major driving forces of economic growth in Bangladesh. The paper’s main objective is to empirically investigate the effect of COVID-19 on the remittance inflow to Bangladesh using a gravity model framework. We have employed monthly data of remittance inflow to Bangladesh from January 2018 to September 2022 with its top twelve partners, namely the Kingdom of Saudi Arabia, the United Arab Emirates, Kuwait, Qatar, Oman, Bahrain, Libya, the United Kingdom, Italy, Malaysia, Singapore, and Japan. Using the gravity equation, we tapped the COVID-19 dummy as the critical variable of our interest, along with COVID transmission, mortality, and vaccination data at home and abroad. Using Poisson pseudo-maximum likelihood (PPML), fixed-effect (FE), and random-effect (RE) estimations, we find that during the COVID-19 pandemic, remittance inflow to Bangladesh increased significantly after controlling for other Gravity variables.
FPGA-Based CNN for Eye Detection in an Iris Recognition at a Distance System
Authors: Ruiz-Beltrán Camilo A. , Romero-Garcés Adrián , González-García Martín , Marfil Rebeca , Bandera Antonio
Published: November 2023

Neural networks are the state-of-the-art solution to image-processing tasks. Some of these neural networks are relatively simple, but the popular convolutional neural networks (CNNs) can consist of hundreds of layers. Unfortunately, the excellent recognition accuracy of CNNs comes at the cost of very high computational complexity, and one of the current challenges is managing the power, delay and physical size limitations of hardware solutions dedicated to accelerating their inference process. In this paper, we describe the embedding of an eye detection system on a Zynq XCZU4EV UltraScale+ multiprocessor system-on-chip (MPSoC). This eye detector is used in the application framework of a remote iris recognition system, which requires high resolution images captured at high speed as input. Given the high rate of eye regions detected per second, it is also important that the detector only provides as output images eyes that are in focus, discarding all those seriously affected by defocus blur. In this proposal, the network will be trained only with correctly focused eye images to assess whether it can differentiate this pattern from that associated with the out-of-focus eye image. Exploiting the neural network’s advantage of being able to work with multi-channel input, the inputs to the CNN will be the grey level image and a high-pass filtered version, typically used to determine whether the iris is in focus or not. The complete system synthetises other cores and implements CNN using the so-called Deep Learning Processor Unit (DPU), the intellectual property (IP) block released by AMD/Xilinx. Compared to previous hardware designs for implementing FPGA-based CNNs, the DPU IP supports extensive deep learning core functions, and developers can leverage DPUs to conveniently accelerate CNN inference. Experimental validation has been successfully addressed in a real-world scenario working with walking subjects, demonstrating that it is possible to detect only eye images that are in focus. This prototype module includes a CMOS digital image sensor that provides 16 Mpixel images, and outputs a stream of detected eyes as 640 × 480 images. The module correctly discards up to 95% of the eyes present in the input images as not being correctly focused.
The Modeling of GaN-FET Power Devices in SPICE
Authors: Zarębski Janusz , Bisewski Damian
Published: November 2023

This paper focuses on the problem of the modeling of FET power transistors made of gallium nitride offered by GaN Systems, Transphorm, and Nexperia. The considered devices have been available on the market since 2014. GaN-FETs are built as a cascade connection of a normally on gallium nitride HEMT and a normally off MOSFET made of silicon. On the manufacturer’s sites, one can find models of these devices for like-SPICE tools in the text form. The main goal of this paper is to evaluate the model’s accuracy by comparing calculation results obtained by the use of the considered models with the authors’ measurement results and datasheet. It has been demonstrated that the GaN Systems model built on controlled sources described by a set of arbitrarily selected mathematical functions more accurately reproduces the basic characteristics of a transistor. On the other hand, the models from Transphorm and Nexperia, which are constructed based on built-in semiconductor device models, more precisely calculate the values of selected functional transistor parameters.
Formulation of an Efficiency Model Valid for High Vacuum Flat Plate Collectors
Authors: Gaudino Eliana , Caldarelli Antonio , Russo Roberto , Musto Marilena
Published: November 2023

High Vacuum Flat Plate Collectors (HVFPCs) are the only type of flat plate thermal collectors capable of producing thermal energy for middle-temperature applications (up to 200 °C). As the trend in research plans is to develop new Selective Solar Absorbers to extend the range of HVFPC application up to 250 °C, it is necessary to correctly evaluate the collector efficiency up to such temperatures to predict the energy production accurately. We propose an efficiency model for these collectors based on the selective absorber optical properties. The proposed efficiency model explicitly includes the radiative heat exchange with the ambient, which is the main source of thermal losses for evacuated collectors at high temperatures. It also decouples the radiative losses that depend on the optical properties of the absorber adopted from the other thermal losses due to HVFPC architecture. The model has been validated by applying it to MT-Power HVFPC manufactured by TVP-Solar. The dissipative losses other than thermal radiation were found to be mostly conductive with a linear coefficient k = 0.258 W/m2K. The efficiency model has been also used to predict the energy production of HVFPCs equipped with new, optimized Selective Solar Absorbers developed in recent years. Considering the 2019 meteorological data in Cairo and an operating temperature of 250 °C, the annual energy production of an HVFPC equipped with an optimized absorber is estimated to be 638 kWh/m2.
Does the Distance from the Formal Path Affect the Richness, Abundance and Diversity of Geophytes in Urban Forests and Parks?
Authors: Kostrakiewicz-Gierałt Kinga , Gmyrek Katarzyna , Pliszko Artur
Published: November 2023

Geophytes are a characteristic element of deciduous forests in the temperate zone, as well as a common component of urban green spaces due to their early flowering and high decorative value. Nevertheless, in urban areas, geophytes are constantly threatened by recreational activities, especially in parks where intensive trampling occurs. In this study, we tested the effect of the distance from formal paths on the species richness, abundance and diversity of geophytes in relation to habitat conditions in urban forests and parks. We established a total of 400 plots (1 m × 1 m) located close (CL) to and further (FU) from paths in 10 forests and 10 parks in Kraków, southern Poland, in spring 2022. We recorded 23 species from nine groups of geophytes forming different underground storage organs, i.e., bulbs (B), hypocotyl bulbs (HB), rhizomes (RH), runners (RU), runners and rhizomes (RU-RH), runner-like rhizomes (RL-RH), runners and runners with tuberous tip (RU-TU), runners and shoot tubers (RU-ST) and root tubers (RT). The differences in the number, share and cover-abundance of geophytes between the CL and FU plots were statistically insignificant. In contrast, the total number, share and cover-abundance of geophytes were significantly higher in forests than in parks. Additionally, the share and cover-abundance of RH and RT were significantly higher in forests than in parks. Moreover, in CL plots in forests and parks, the cover-abundance of RH and RT were negatively correlated with soil compaction. Urban forests provide a high abundance of RH, RU-RH and RT, while parks support a high abundance of BU. To protect forest geophytes in urban forests and parks, it is recommended to limit trampling and soil eutrophication, as well as reduce the increase in soil pH along paths.
BIOCLIM Modeling for Predicting Suitable Habitat for Endangered Tree Tapiscia sinensis (Tapisciaceae) in China
Authors: Xie Chunping , Chen Lin , Li Meng , Jim Chi Yung , Liu Dawei
Published: November 2023

Climate change jeopardizes species survival, particularly for endangered species. This risk extends to the endangered Chinese endemic tree Tapiscia sinensis. The factors underpinning T. sinensis’s habitat distribution are poorly understood, and its potential response to future climate scenarios remains unclear. With six shortlisted climate factors and 117 occurrence records, we modeled T. sinensis’s potential distribution across China using the BIOCLIM model. We applied principal component analysis to examine the primary climate factors restricting its geographical range. The findings indicate that T. sinensis’ range is principally located in China’s middle subtropical climatic zone at low–mid altitudes. The principal component analysis identified two critical factors representing temperature and precipitation. Temperature was the most critical factor limiting T. sinensis distribution, especially the effect of temperature seasonality and isothermality. The habitat suitability model generated by BIOCLIM under current climate conditions demonstrated strong concordance between the predicted suitable areas and the present actual distribution range. These results verify that the model can reliably identify habitats conducive to T. sinensis growth and survival. However, under a hypothetical future climate scenario of doubled atmospheric CO2 concentrations for 2100, the model indicates a precipitous reduction and fragmentation in the areas with excellent suitability conditions. This predicted decline highlights the considerable threats posed by climate change to the long-term survival of this endangered species in China. Our habitat modeling yields critical insights that inform the development of science-based strategies and best practices to improve conservation management plans for research, protection, nursery cultivation, and sustainable planting in China. Habitat suitability knowledge could aid introduction and cultivation efforts for T. sinensis globally in places with analogous climates.
Improving the Quality and Safety of Pu-erh Tea by Inoculation of Saccharomyces cerevisiae and Lactobacillus plantarum
Authors: Wang Yali , Liu Yifei , Sun Zhaoyue , Brake Joseph , Qin Yuhuan , Li Jing , Wu Xiaobin
Published: November 2023

The sensory quality and health benefits of Pu-erh tea are mainly determined by microbial fermentation processing. The directed exogenous inoculation of specific microorganisms is an effective method to improve the quality and flavor of Pu-erh tea. In this study, Lactobacillus plantarum and Saccharomyces cerevisiae were introduced into the fermentation processes of Pu-erh tea, as they are the main contributors to enzyme secretion, to change the tea’s functional components. The raw tea materials, spontaneous fermentation tea and microbiological fermentation tea were analyzed by microbiomics and metabolomics. A total of 248 metabolites were characterized, 71 of which were identified as essential metabolites involved in the metabolic changes. These essential metabolites were produced by specific dominant microbial species with multivariate analysis methods. Metabolites essential to the sensory quality and health benefits of Pu-erh tea, such as flavonoids and free amino acids, were increased in tea samples inoculated with Lactobacillus plantarum and Saccharomyces cerevisiae following fermentation. Fungal diversity decreased after fermentation, and both the diversity and richness of bacteria were significantly decreased. In conclusion, our results demonstrate the advantages of Lactobacillus plantarum and Saccharomyces cerevisiae in forming the unique sensory characteristics of Pu-erh tea, and they indicate that the microbial composition is a key factor in altering the tea’s metabolic profile. Our work establishes a theoretical foundation for the promotion of the safety and quality of Pu-erh tea through exogenous inoculation with Lactobacillus plantarum and Saccharomyces cerevisiae.
Spatial Distribution of Major Fish Species Catches and Their Relationship with Environmental Factors in the Beibu Gulf, South China Sea
Authors: Li Menghui , Wang Xuehui , Du Feiyan , Peng Shuai , Wang Lianggen , Sun Dianrong , Wang Yuezhong , Chen Pimao , Qiu Yongsong
Published: November 2023

This study focused on major fish species caught from different ecological habitats to analyze the habitat changes in economically important fish in the Beibu Gulf. The maximum entropy model was constructed based on the data from 26 voyages obtained through the otter trawl fishery stock surveys conducted in the Beibu Gulf from 2006 to 2018. A total of 10 taxa of major fish catches, belonging to 4 families, 1 genus, and 5 species, were analyzed for their distribution characteristics in potential habitats during various ecological periods, specifically the withered and high-water periods, as well as their relationships with crucial environmental factors. During both the withered and high-water periods, the average area under the curve was 0.927, and all models had values exceeding 0.9. Salinity was identified as the principal factor during both periods. The salinity niche of Acropoma japonicum and the primary productivity niche of Sciaenidae were identified as the most restricted factors. The total distribution area of potentially suitable regions for major fish catches extended between 106°30′–109°45′ E and 17°30′–20°45′ N, and the area was lesser during the withered period. During the withered period, the distribution areas of Sciaenidae, Leiognathidae, and Saurida increased, while the distribution area of Trachurus japonicus increased during the high-water period. Sciaenidae and Trachurus japonicus exhibited the highest rates of change at 6.22% and 10.92%, respectively. This indicates that the high-water period may expand the range of suitable habitats for large catches that have an ideal habitat status in the Beibu Gulf. Therefore, it is crucial to anticipate the potential fish habitats in the Beibu Gulf and clarify their spatial distribution patterns.
Correction: Antognazza et al. Current and Historical Genetic Variability of Native Brown Trout Populations in a Southern Alpine Ecosystem: Implications for Future Management. Fishes 2023, 8, 411
Authors: Antognazza Caterina M. , Palandaćić Anja , Delmastro Giovanni B. , Crosa Giuseppe , Zaccara Serena
Published: November 2023

In the original publication [...]
Life-Long Experience with Male Mating Tactics Shapes Spatial Cognition and Coercion Evasion in Female Swordtails
Authors: Queller Philip S. , Adams Elena R. M. , Cummings Molly E.
Published: November 2023

Social experiences can shape adult behavior and cognition. Here, we use El Abra swordtails (Xiphophorus nigrensis) to assess how life-long experience with different male mating tactics shapes coercion evasion ability and female spatial cognition. We raised females from birth to adulthood in environments that varied by male mating tactic: coercers only, courtship displayers only, coercers and displayers together, mixed-strategists, and female only. In adulthood, we tested females’ behavioral responses to a coercive male and spatial cognition in a maze. Females reared with only displayers were significantly worse at distancing themselves from the coercive male than females raised with coercers and displayers and females raised with only coercers. Females raised with a single mating tactic (either courtship display or coercion) exhibited significantly higher accuracy in the spatial maze than females from other rearing groups, and showed significant reduction in total errors (courtship display group) or latency to reward (coercion group) over successive trials. These more predictable environments (one tactic), and not the more complex environments (two tactics), showed evidence for spatial learning. The results are discussed in light of the existing literature on two components of environmental change (environmental predictability and the certainty with which cues predict the best behavioral response) and their effect on the development of cognitive abilities.
From Co-Operation to Coercion in Fisheries Management: The Effects of Military Intervention on the Nile Perch Fishery on Lake Victoria in Uganda
Authors: Mpomwenda Veronica , Tómasson Tumi , Pétursson Jón Geir , Kristófersson Daði Mar
Published: November 2023

In 2017, Uganda’s small-scale inland fisheries underwent a significant transformation, shifting from local co-management to state military enforcement owing to ineffective enforcement of regulations and declining exports. Employing a mixed-methods approach and blending qualitative and quantitative data, we assessed the impact of military intervention on Lake Victoria’s Nile perch fishery, focusing on fishing effort, catch, and exports. Our findings indicate that military operations adhered to regulations, gaining primary support from key stakeholders, specifically motorized fishing operators. Consequently, between 2016 and 2020, legal fishing activities experienced substantial growth. By 2021, approximately 90% of Nile perch catches were made by motorized vessels using longlines and gillnets, despite a declining trend in catch-per-unit effort. Between 2015 and 2021, the Nile perch fishery saw changes: boat seines made up about 5% of motorized fleet catches in 2021, while catches in paddled vessels increased from 20% to over 50%, suggesting a potential role in the growing longline fishery. Therefore, the current management approach does not increase catches or exports compared with the co-management period. The observed decline in catch-per-unit effort among motorized gillnets suggests overcapacity. Further research is needed to comprehend the broader sociological and ecological impacts of the present enforcement strategy for sustainable fishery management.
Extract of Ginkgo biloba Leaves (EGb) Decrease Lipid Oxidation in Fish Feed and Meat and Enhance Growth and Antioxidant Capacity in Jian Carp (Cyprinus carpio var. Jian)
Authors: Chen Gangfu , Xu Jing , Wu Min , Li Huatao , Yang Qihui , Feng Lin
Published: November 2023

Firstly, a linoleic and linolenic acid emulsion were incubated with petroleum ether extract, ethyl acetate extract (EAE), ethanol extract and aqueous extract of Ginkgo biloba leaves. The flavonoids content, total antioxidant capacity (T-AOC) and metal-chelating ability (MCA) were determined in EGbs above. Results showed that the extracts of Ginkgo biloba leaves (EGbs) inhibited the lipid oxidation in material above. Of all of EGbs, EAE showed the strongest T-AOC, MCA and protective effects against the lipid oxidation. Next, fish feeds were incubated with graded levels of EAE. The results showed that EAE inhibited lipid oxidation in fish feeds. The optimal inclusion levels of EAE for minimizing lipid oxidation were 4.26 g kg−1 feeds. The effect of EGbs on the lipid oxidation may be closely associated with their flavonoid content. Finally, juvenile carp (14.8 ± 0.4 g) were fed with EAE at concentrations ranging from 0.0 to 6.0 g kg−1 for 60 days. Current data displayed that dietary EAE increased the growth performance of fish. This result of EAE may be ascribed to its enhancing effect on the activity of digestive and absorptive enzymes and antioxidant capacity in digestive organs of fish. Furthermore, dietary EAE decreased the hot-drying-induced lipid oxidation in fish meat through inhibiting the induction effect of hemoglobin in erythrocytes. Our study suggests that EGb can be considered as a potential natural antioxidant for fish and fish feed.
The Effects of Different Roasting Methods on the Phenolic Contents, Antioxidant Potential, and In Vitro Inhibitory Activities of Sacha Inchi Seeds
Authors: Kittibunchakul Suwapat , Kemsawasd Varongsiri , Hudthagosol Chatrapa , Sanporkha Promluck , Sapwarobol Suwimol , Suttisansanee Uthaiwan
Published: November 2023

Roasted sacha inchi seeds are now commercialized as a health food product, but the influence of roasting methods on their proclaimed health effects has yet to be explored. This study investigated the total phenolic contents (TPCs), antioxidant potential, and inhibitory activities of raw and roasted sacha inchi seeds in vitro. Individual phenolics in raw seeds were also identified in an attempt to explain the bioactivities of the seeds. The results suggested that roasting in a cooking pan, vacuum oven, and tray dryer had distinct impact on TPC in sacha inchi seeds, and thus differentially altered their antioxidant and inhibitory properties. Seeds that underwent roasting exhibited 1.5–2.7-fold higher antioxidant potentials than raw seeds. Certain roasting methods provided the products with anti-α-amylase and anti-cholinesterase activities, while inhibitions of these enzymes were not detected in raw seeds. Roasted seeds also possessed superior anti-lipase and anti-glycation activities when compared with raw seeds (up to 1.7- and 4.8-fold, respectively). The inhibitory properties observed in the seed samples might be attributed to their p-coumaric acid, ferulic acid, and quercetin, as these potential enzyme inhibitors were predominant in raw seeds. The overall results showed that pan-roasting could be used to obtain relatively high health benefits from the antioxidant and inhibitory activities of sacha inchi seeds. The information obtained from this study may serve as the basis for the proper processing of sacha inchi seeds to optimize their functional food and nutraceutical applications.
Plant-Based Meat Proteins: Processing, Nutrition Composition, and Future Prospects
Authors: Yu Jialing , Wang Liyuan , Zhang Zhaowei
Published: November 2023

The growing need for plant-based meat alternatives promotes the rapid progress of the food industry. Processing methods employed in plant-based meat production are critical to preserving and enhancing their nutritional content and health benefits, directly impacting consumer acceptance. Unlike animal-based food processing, the efficiency of protein extraction and processing methods plays a crucial role in preserving and enriching the nutritional content and properties. To better understand the factors and mechanisms affecting nutrient composition during plant-based meat processing and identify key processing steps and control points, this work describes methods for extracting proteins from plants and processing techniques for plant-based products. We investigate the role of nutrients and changes in the nutrients during plant protein product processing. This article discusses current challenges and prospects.