bluuebunny/crossref_metadata_2025 huggingface dataset:
Continuous Electrophoretic Separation of Charged Dyes in Liquid Foam
Authors: Fauvel Matthieu , Trybala Anna , Tseluiko Dmitri , Starov Victor Mikhilovich , Bandulasena Himiyage Chaminda Hemaka
Published: June 2023

A novel electrophoretic separation technique is presented, where continuous electrophoretic separation is demonstrated using free flowing liquid foams. Continuous foam electrophoresis combines the principle of capillary electrophoresis and interactions between analytes and the electrical double layer, with the ability of Free Flow Electrophoresis to continuously separate and recover analytes automatically. A liquid foam is used to provide a network of deformable micro and nano channels with a high surface area, presenting a novel platform for electrophoresis, where interfacial phenomena could be exploited to modify analyte migration. The main purpose of this paper is to present a proof-of-concept study and provide fundamental understanding of a complex foam system in continuous separation mode, i.e., flowing liquid foam under an external electric field with electrophoresis and chemical reactions at the electrodes continuously changing the system. Liquid foam is generated using a mixture of anionic and non-ionic surfactants and pumped through a microfluidic separation chamber between two electrodes. The effectiveness of the device is demonstrated using a dye mixture containing a neutral dye and an anionic dye. At the outlet, the foam is separated and collected into five fractions which are individually probed for the concentration of the two dyes used. The anionic dye was concentrated up to 1.75 (±0.05) times the initial concentration in a select outlet, while the neutral dye concentration remained unchanged in all outlets, demonstrating the potential for electrophoretic foam separations.
Improvement of Mg-Doped GaN with Shutter-Controlled Process in Plasma-Assisted Molecular Beam Epitaxy
Authors: Wang Ying-Chieh , Lo Ikai , Lin Yu-Chung , Tsai Cheng-Da , Chang Ting-Chang
Published: June 2023

Mg-doped GaN was grown by plasma-assisted molecular beam epitaxy (PAMBE) on a Fe-doped GaN template substrate by employing a shutter-controlled process. The transition from n-type to p-type conductivity of Mg-doped GaN in relation to the N/Ga flux ratio was studied. The highest p-type carrier concentration in this series was 3.12 × 1018 cm−3 under the most N-rich condition. By modulating the shutters of different effusion cells for the shutter-controlled process, a wide growth window for p-type GaN was obtained. It was found that the presence of Mg flux effectively prevents the formation of structural defects in GaN epi-layers, resulting in the improvement of crystal quality and carrier mobility.
Ensemble Learning for Hormone Binding Protein Prediction: A Promising Approach for Early Diagnosis of Thyroid Hormone Disorders in Serum
Authors: Butt Ahmad Hassan , Alkhalifah Tamim , Alturise Fahad , Khan Yaser Daanial
Published: June 2023

Hormone-binding proteins (HBPs) are specific carrier proteins that bind to a given hormone. A soluble carrier hormone binding protein (HBP), which can interact non-covalently and specifically with growth hormone, modulates or inhibits hormone signaling. HBP is essential for the growth of life, despite still being poorly understood. Several diseases, according to some data, are caused by HBPs that express themselves abnormally. Accurate identification of these molecules is the first step in investigating the roles of HBPs and understanding their biological mechanisms. For a better understanding of cell development and cellular mechanisms, accurate HBP determination from a given protein sequence is essential. Using traditional biochemical experiments, it is difficult to correctly separate HBPs from an increasing number of proteins because of the high experimental costs and lengthy experiment periods. The abundance of protein sequence data that has been gathered in the post-genomic era necessitates a computational method that is automated and enables quick and accurate identification of putative HBPs within a large number of candidate proteins. A brand-new machine-learning-based predictor is suggested as the HBP identification method. To produce the desirable feature set for the method proposed, statistical moment-based features and amino acids were combined, and the random forest was used to train the feature set. During 5-fold cross validation experiments, the suggested method achieved 94.37% accuracy and 0.9438 F1-scores, respectively, demonstrating the importance of the Hahn moment-based features.
Clinical Characteristics of Patients with Intraocular Lens Calcification after Pars Plana Vitrectomy
Authors: Bopp Silvia , Özdemir Hüseyin Baran , Aktaş Zeynep , Khoramnia Ramin , Yildirim Timur M. , Schickhardt Sonja , Auffarth Gerd U. , Özdek Şengül
Published: June 2023

Aim: To determine the clinical risk factors that may increase the occurrence of intraocular lens (IOL) calcification in patients who had undergone pars plana vitrectomy (PPV). Methods: The medical records of 14 patients who underwent IOL explantation due to clinically significant IOL opacification after PPV were reviewed. The date of primary cataract surgery, technique and implanted IOL characteristics; the time, cause and technique of PPV; tamponade used; additional surgeries; the time of IOL calcification and explantation; and IOL explantation technique were investigated. Results: PPV had been performed as a combined procedure with cataract surgery in eight eyes and solely in six pseudophakic eyes. The IOL material was hydrophilic in six eyes, hydrophilic with a hydrophobic surface in seven eyes and undetermined in one eye. The endotamponades used during primary PPV were C2F6 in eight eyes, C3F8 in one eye, air in two eyes and silicone oil in three eyes. Two of three eyes underwent subsequent silicone oil removal and gas tamponade exchange. Gas in the anterior chamber was detected in six eyes after PPV or silicone oil removal. The mean interval between PPV and IOL opacification was 20.5 ± 18.6 months. The mean BCVA in logMAR was 0.43 ± 0.42 after PPV, which significantly decreased to 0.67 ± 0.68 before IOL explantation for IOL opacification (p = 0.007) and increased to 0.48 ± 0.59 after the IOL exchange (p = 0.015). Conclusions: PPV with endotamponades in pseudophakic eyes, particularly gas, seems to increase the risk for secondary IOL calcification, especially in hydrophilic IOLs. IOL exchange seems to solve this problem when clinically significant vision loss occurs.
A New Deep-Learning-Based Model for Breast Cancer Diagnosis from Medical Images
Authors: Zakareya Salman , Izadkhah Habib , Karimpour Jaber
Published: June 2023

Breast cancer is one of the most prevalent cancers among women worldwide, and early detection of the disease can be lifesaving. Detecting breast cancer early allows for treatment to begin faster, increasing the chances of a successful outcome. Machine learning helps in the early detection of breast cancer even in places where there is no access to a specialist doctor. The rapid advancement of machine learning, and particularly deep learning, leads to an increase in the medical imaging community’s interest in applying these techniques to improve the accuracy of cancer screening. Most of the data related to diseases is scarce. On the other hand, deep-learning models need much data to learn well. For this reason, the existing deep-learning models on medical images cannot work as well as other images. To overcome this limitation and improve breast cancer classification detection, inspired by two state-of-the-art deep networks, GoogLeNet and residual block, and developing several new features, this paper proposes a new deep model to classify breast cancer. Utilizing adopted granular computing, shortcut connection, two learnable activation functions instead of traditional activation functions, and an attention mechanism is expected to improve the accuracy of diagnosis and consequently decrease the load on doctors. Granular computing can improve diagnosis accuracy by capturing more detailed and fine-grained information about cancer images. The proposed model’s superiority is demonstrated by comparing it to several state-of-the-art deep models and existing works using two case studies. The proposed model achieved an accuracy of 93% and 95% on ultrasound images and breast histopathology images, respectively.
Ultrasound Diagnosis and Guided Intervention of Musculoskeletal/Neuromuscular Pathology 2022
Authors: Chang Ke-Vin
Published: June 2023

The field of musculoskeletal medicine has been revolutionized by the introduction of ultrasound imaging [...]
Evaluating the Utility of a Large Language Model in Answering Common Patients’ Gastrointestinal Health-Related Questions: Are We There Yet?
Authors: Lahat Adi , Shachar Eyal , Avidan Benjamin , Glicksberg Benjamin , Klang Eyal
Published: June 2023

Background and aims: Patients frequently have concerns about their disease and find it challenging to obtain accurate Information. OpenAI’s ChatGPT chatbot (ChatGPT) is a new large language model developed to provide answers to a wide range of questions in various fields. Our aim is to evaluate the performance of ChatGPT in answering patients’ questions regarding gastrointestinal health. Methods: To evaluate the performance of ChatGPT in answering patients’ questions, we used a representative sample of 110 real-life questions. The answers provided by ChatGPT were rated in consensus by three experienced gastroenterologists. The accuracy, clarity, and efficacy of the answers provided by ChatGPT were assessed. Results: ChatGPT was able to provide accurate and clear answers to patients’ questions in some cases, but not in others. For questions about treatments, the average accuracy, clarity, and efficacy scores (1 to 5) were 3.9 ± 0.8, 3.9 ± 0.9, and 3.3 ± 0.9, respectively. For symptoms questions, the average accuracy, clarity, and efficacy scores were 3.4 ± 0.8, 3.7 ± 0.7, and 3.2 ± 0.7, respectively. For diagnostic test questions, the average accuracy, clarity, and efficacy scores were 3.7 ± 1.7, 3.7 ± 1.8, and 3.5 ± 1.7, respectively. Conclusions: While ChatGPT has potential as a source of information, further development is needed. The quality of information is contingent upon the quality of the online information provided. These findings may be useful for healthcare providers and patients alike in understanding the capabilities and limitations of ChatGPT.
An Enhanced Energy-Efficient Data Collection Optimization Algorithm for UAV Swarm in the Intelligent Internet of Things
Authors: Sun Zeyu , Xu Chen , Wang Guoyong , Lan Lan , Shi Mingxing , Xing Xiaofei , Liao Guisheng
Published: June 2023

In the case of limited endurance of unmanned aerial vehicles (UAVs), in order to further improve UAV data collection efficiency, this paper puts forward EDC-UAVIIoT: an enhanced energy-efficient data collection optimization algorithm for UAV swarm in the intelligent Internet of Things. First of all, the algorithm optimizes the UAV cruise path through the intelligent Internet of Things routing mechanism, avoids the occurrence of data errors in the packet transmission process, and uses the end-to-end transmission error probability model. The error probability of data packets in the transmission process is calculated to improve the efficiency of data collection tasks and data throughput. Secondly, considering the relationship between energy harvesting and energy consumption balance, this paper uses semi-definite programming and a convex approximation algorithm to transform the non-convex optimization problem into a convex optimization problem and realize the mapping relationship between the UAV cluster node and the target node coordinates, which reduces the computational complexity. Finally, the simulation results show that the EDC-UAVIIoT algorithm is compared with other algorithms in network energy consumption, running time, network delay, and network throughput. The numerical values are increased by 7.03%, 10.16%, 12.39%, and 8.82%, respectively, thus verifying the effectiveness and stability of the proposed EDC-UAVIIoT algorithm.
Sensory-Processing Sensitivity Is Associated with Increased Neural Entropy
Authors: Walter Nike , Meinersen-Schmidt Nicole , Kulla Patricia , Loew Thomas , Kruse Joachim , Hinterberger Thilo
Published: June 2023

Background: This study aimed at answering the following research questions: (1) Does the self-reported level of sensory-processing sensitivity (SPS) correlate with complexity, or criticality features of the electroencephalogram (EEG)? (2) Are there significant EEG differences comparing individuals with high and low levels of SPS? Methods: One hundred fifteen participants were measured with 64-channel EEG during a task-free resting state. The data were analyzed using criticality theory tools (detrended fluctuation analysis, neuronal avalanche analysis) and complexity measures (sample entropy, Higuchi’s fractal dimension). Correlations with the ‘Highly Sensitive Person Scale’ (HSPS-G) scores were determined. Then, the cohort’s lowest and the highest 30% were contrasted as opposites. EEG features were compared between the two groups by applying a Wilcoxon signed-rank test. Results: During resting with eyes open, HSPS-G scores correlated significantly positively with the sample entropy and Higuchi’s fractal dimension (Spearman’s ρ = 0.22, p < 0.05). The highly sensitive group revealed higher sample entropy values (1.83 ± 0.10 vs. 1.77 ± 0.13, p = 0.031). The increased sample entropy in the highly sensitive group was most pronounced in the central, temporal, and parietal regions. Conclusion: For the first time, neurophysiological complexity features associated with SPS during a task-free resting state were demonstrated. Evidence is provided that neural processes differ between low- and highly-sensitive persons, whereby the latter displayed increased neural entropy. The findings support the central theoretical assumption of enhanced information processing and could be important for developing biomarkers for clinical diagnostics.
Parameter Estimation of the Heston Volatility Model with Jumps in the Asset Prices
Authors: Gruszka  Jarosław , Szwabiński Janusz
Published: June 2023

The parametric estimation of stochastic differential equations (SDEs) has been the subject of intense studies already for several decades. The Heston model, for instance, is based on two coupled SDEs and is often used in financial mathematics for the dynamics of asset prices and their volatility. Calibrating it to real data would be very useful in many practical scenarios. It is very challenging, however, since the volatility is not directly observable. In this paper, a complete estimation procedure of the Heston model without and with jumps in the asset prices is presented. Bayesian regression combined with the particle filtering method is used as the estimation framework. Within the framework, we propose a novel approach to handle jumps in order to neutralise their negative impact on the estimates of the key parameters of the model. An improvement in the sampling in the particle filtering method is discussed as well. Our analysis is supported by numerical simulations of the Heston model to investigate the performance of the estimators. In addition, a practical follow-along recipe is given to allow finding adequate estimates from any given data.
The Effectiveness of a Recreational Behavioural Programme in Reducing Anger among Children with Intellectual Disabilities at the Primary Stage
Authors: Elsayed Ahmed R. , Hassan Ahmed K.
Published: June 2023

This study aimed to investigate the impact of a recreational behavioural programme on reducing the degree of anger among children with intellectual disabilities (ID) in the primary stage. The study was implemented with 24 children who were randomly divided into two groups: an experimental group (n = 12, age = 10.80 ± 1.03 years, IQ = 63.10 ± 4.43 scores, ASW = 55.50 ± 1.51 scores) and a control group (n = 12, age = 10.80 ± 0.92 years, IQ = 63.00 ± 4.16 scores, ASW = 56.00 ± 1.15 scores). We used the PROMIS anger scale with a modification that was used to measure the degree of anger, and the recreational behavioural programme was implemented three times per week for six weeks. The results of the research showed that the improvement percentages for Anger Triggers (AT), Inner Anger (IA), and External Anger (EA) were 9.73%, 9.04%, and 9.60%, respectively, and the Anger scale as a whole (ASW) rate was 9.46%. r = (0.89–0.91). The experimental group using the recreational behavioural programme also outperformed the control group, as the results indicated a decrease in the intensity of anger in the direction of the experimental group. The differences in the improvement percentages for Anger Triggers (AT) Inner Anger (IA), and External Anger (EA) were 32.97%, 31.03%, and 26.63%, respectively, and the Anger scale as a whole (ASW) rate was 30.09%, r = (0.82–0.86). The results of the study confirmed the effectiveness of the recreational activity programme in developing social interaction among children with intellectual disabilities, which indicates the success of the recreational behavioural programme in reducing the degree of anger among children with IDs. Therefore, the recreational behavioural programme had a positive effect in terms of reducing the degree of anger among children with IDs in the primary stage.
Survivability Mapping Strategy for Virtual Wireless Sensor Networks for Link Failures in the Internet of Things
Authors: Li Songnong , Yan Yao , Ji Yongliang , Peng Wenxin , Wan Lingyun , Zhang Puning
Published: June 2023

In the case of virtual wireless sensor networks, a link-failure-oriented survivable virtual sensor network mapping algorithm (F-SVNE) is proposed to address the issue of link failure in the underlying wireless sensor network. First, the algorithm utilizes the fast routing strategy and creates a backup route set based on a multi-path selection algorithm to reduce the delay in fault recovery caused by path selection. Second, the survivable virtual sensor network mapping algorithm is adopted based on the routing set. Finally, in the mapping stage, the efficiency and reliability of the algorithm are comprehensively considered, and the path with the largest survival probability is selected from the backup route set of the faulty link to remap the virtual link affected by the link failure. Empirical results demonstrate that the F-SVNE algorithm can efficaciously lessen the failure recovery delay, and improve the long-term average revenue–cost ratio and average failure recovery rate.
A Gray-Box Stability Analysis Method of Grid-Connected Inverter Considering Synchronization Dynamics
Authors: Zheng Tianzhi , Kong Fannie , Li Guojin , Wang Zhenmin , Chen Yanming
Published: June 2023

The Grid-Connected Inverter (GCI) can be considered a gray box when circuit and controller parameters are missing due to intellectual property rights or parameter variations caused by aging, which poses an impediment to assessing the stability of the system. This paper presents a gray-box stability analysis method based on impedance identification of GCI considering the synchronization dynamics. The impedance frequency responses of GCI are measured by the frequency scanning method on the dq-frame. Meanwhile, the influence of synchronization dynamics and background harmonics is theoretically investigated. A vector fitting (VF) algorithm, co-designed with impedance identification, is then applied to generate polynomial transfer functions. Based on the obtained transfer functions, the stability of the GCI can be judged by the distance relationship between the prohibited area boundary and the center of the gershgorin-circle through the distance formula. Finally, the experiments of both RT-LAB and experimental prototypes are conducted to verify the feasibility of the proposed method.
Intrusion Detection in Intelligent Connected Vehicles Based on Weighted Self-Information
Authors: Yu Tianqi , Hu Jianling , Yang Jianfeng
Published: June 2023

The Internet of Vehicles (IoV) empowers intelligent and tailored services for intelligent connected vehicles (ICVs). However, with the increasing number of onboard external communication interfaces, ICVs face the challenges of malicious network intrusions. The closure of traditional vehicles had led to in-vehicle communication protocols, including the most commonly applied controller area network (CAN), and a lack of security and privacy protection mechanisms. Therefore, to protect the connected vehicles and IoV systems from being attacked, an intrusion-detection method is proposed based on the features extracted from the arbitration identifier (ID) field of CAN messages. Specifically, a sliding window is used to continuously extract a frame of streaming CAN messages first. Afterward, the weighted self-information of the CAN message ID is defined, and both the weighted self-information and the normalized value of an ID are extracted as features. Based on the extracted features, a lightweight one-class classifier, the local outlier factor (LOF), is used to identify the outliers and detect malicious network intrusion attacks. Simulation experiments were conducted based on the public CAN dataset provided by the HCR Lab. The proposed method, using four different one-class classifiers, was analyzed, and it is also benchmarked with three information entropy-based intrusion-detection methods in the literature. The experimental results indicate that, compared to the benchmarks, the proposed method dramatically improves the detection accuracy for injection attacks, namely denial-of-service (DoS) and spoofing, especially when the number of injected messages is low.
A Projected AR Serious Game for Shoulder Rehabilitation Using Hand-Finger Tracking and Performance Metrics: A Preliminary Study on Healthy Subjects
Authors: Viglialoro Rosanna M. , Turini Giuseppe , Carbone Marina , Condino Sara , Mamone Virginia , Coluccia Nico , Dell’Agli Stefania , Morucci Gabriele , Ryskalin Larisa , Ferrari Vincenzo , Gesi Marco
Published: June 2023

Research studies show that serious games can increase patient motivation regardless of age or illness and be an affordable and promising solution with respect to conventional physiotherapy. In this paper, we present the latest evolution of our system for shoulder rehabilitation based on hand-finger tracking and projected augmented reality. This version integrates metrics to assess patient performance, monitors the game progress, and allows the selection of the game visualization mode (standard on-screen or projected augmented reality). Additionally, the new software tracks the velocity, acceleration, and normalized jerk of the arm-hand movements of the user. Specifically, sixteen healthy volunteers (eight technical and eight rehabilitation experts) tested our current prototype. The results showed that the serious game is engaging, its design is ergonomically sound, and the overall system could be a useful tool in shoulder rehabilitation. However, clinical validation is needed to assess that the serious game has the same effects as the selected therapy. This is the preliminary step toward laying the foundation for future studies that investigate abnormalities in shoulder movements by using hand-finger tracking.
Combined “Renewable Energy–Thermal Energy Storage (RE–TES)” Systems: A Review
Authors: Elkhatat Ahmed , Al-Muhtaseb Shaheen A.
Published: June 2023

Current industrial civilization relies on conventional energy sources and utilizes large and inefficient energy conversion systems. Increasing concerns regarding conventional fuel supplies and their environmental impacts (including greenhouse gas emissions, which contribute to climate change) have promoted the importance of renewable energy (RE) sources for generating electricity and heat. This comprehensive review investigates integrating renewable energy sources (RES) with thermal energy storage (TES) systems, focusing on recent advancements and innovative approaches. Various RES (including solar, wind, geothermal, and ocean energy sources) are integrated with TES technologies such as sensible and latent TES systems. This review highlights the advantages and challenges of integrating RES and TES systems, emphasizing the importance of hybridizing multiple renewable energy sources to compensate for their deficiencies. Valuable outputs from these integrated systems (such as hydrogen production, electric power and freshwater) are discussed. The overall significance of RES–TES hybrid systems in addressing global energy demand and resource challenges is emphasized, demonstrating their potential to substitute fossil-fuel sources. This review provides a thorough understanding of the current state of RES–TES integration and offers insights into future developments in optimizing the utilization of renewable energy sources.
Performance Analysis of Variable Cross-Section TEGs under Constant Heat Flux Conditions
Authors: Liu Junpeng , Sun Yajing , Chen Gang , Zhai Pengcheng
Published: June 2023

In this paper, five shapes of thermoelectric generator (TEG) models (cylindrical, barrel shaped, hourglass shaped, cup shaped, and inverse cup shaped) are built under the boundary conditions of heat flux at the hot end and convection at the cold end of the TEGs. Based on the numerical simulation results, the configuration of the variable cross-section can effectively boost the performance of TEGs. Remarkably, the hourglass-shaped TEG generated the maximum output power and efficiency, which were 69.62% and 70.96% higher than that of the conventional cylindrical TEG, respectively. The results indicate that the hourglass shape is beneficial to enlarge the temperature difference between the two ends of the TEG, which results in performance improvement. In addition, the effects of heat flux and convection on the performance of TEGs are explored and discussed. After choosing the appropriate boundary conditions, the relationships between the maximum output power and efficiency and the shape factor of the hourglass-shaped TEG are obtained according to the fitting results. Finally, some conclusions are drawn to provide guidance for TEG applications.
Grass from Road Verges as a Substrate for Biogas Production
Authors: Czubaszek Robert , Wysocka-Czubaszek Agnieszka , Banaszuk Piotr , Zając Grzegorz , Wassen Martin J.
Published: June 2023

Maintenance of urban green infrastructure generates a large amount of biomass that can be considered a valuable feedstock for biogas production. This study aims to determine the effect of the cutting time and method of substrate preservation on the specific methane yield (SMY) of urban grass collected from road verges and median strips between roadways in wet (WF) and dry fermentation (DF) technology. The grass was collected three times in a growing season, including in spring, summer, and autumn. The biochemical methane potential (BMP) test was performed on fresh grass, grass ensiled without additives, and grass ensiled with microbiological additives. In addition, the energy potentially produced from biogas and the avoided CO2 emissions were calculated. The highest SMY (274.18 ± 22.59 NL kgVS−1) was observed for the fresh grass collected in spring and subjected to WF. At the same time, the lowest CH4 production (182.63 ± 0.48 NL kgVS−1) was found in the grass ensiled without additives, collected in summer, and digested in DF technology. A comparison of the SMY obtained from the same grass samples in the WF and DF technologies revealed that higher CH4 yields were produced in WF. The electricity and heat production were affected by the time of grass cutting, ensilage method, and AD technology. Generally, less electricity but more heat was produced in DF technology. The least electricity (469–548 kWh tDM−1) was produced from the grass cut in spring and subjected to DF, while the most electricity (621–698 kWh tDM−1) was obtained from the grass collected in autumn and subjected to WF. In the case of heat production, the situation was reversed. The least heat (1.4–1.9 GJ tDM−1) was produced by the grass collected in spring and subjected to WF, while the most heat (2.2–2.7 GJ tDM−1) was produced by the grass collected in autumn and subjected to DF. Ensilage decreased the electricity and heat production in almost all the cuttings. The total reduction in CO2 emissions may amount to 2400 kg CO2 per 1 hectare of road verges. This significant reduction demonstrates that the use of grass from roadside verges in biogas plants should be considered a feasible option. Even though urban grass should be considered a co-substrate only, it can be a valuable feedstock that may partially substitute energy crops and reduce the area needed for energy purposes. Our results reveal that biogas production from the grass waste in WF technology is a stable process. The cutting time and preservation method do not affect the AD process. In DF technology, fresh grass, especially from the late growing season used as feedstock, extends the time of biomass decomposition and, therefore, should be avoided in a real-life biogas plant.
Critical Progress of Polymer Solar Cells with a Power Conversion Efficiency over 18%
Authors: Tian Hongyue , Zhao Mingxin , Ma Xiaoling , Xu Chunyu , Xu Wenjing , Liu Zhongyuan , Zhang Miao , Zhang Fujun
Published: June 2023

The power conversion efficiencies (PCEs) of organic photovoltaics (OPVs) have reached more than 19%, along with the prosperous development of materials and device engineering. It is meaningful to make a comprehensive review of the research of OPVs for further performance improvement. In this review, some typical materials of high-performance OPVs are summarized, including representative polymer donor materials, non-fullerene acceptor materials, and interfacial modification materials, as well as their design rules for molecular engineering. From the point of view of device engineering, active layer treatment and deposition technology are introduced, which can play a critical role in adjusting the degree of molecular aggregation and vertical distribution. Meanwhile, a ternary strategy has been confirmed as an efficient method for improving the performance of OPVs, and the multiple roles of the appropriate third component in the photo-electronic conversion process are emphasized and analyzed. The challenges and perspectives concerning this region are also put forward for further developing high-performance OPVs.
Forest Tent Caterpillar Outbreaks Drive Change in Ant Communities in Boreal Forests
Authors: Caron Anne-Sophie , Koudji Essivi Gagnon , Handa Ira Tanya , Montoro Girona Miguel , Despland Emma
Published: June 2023

Insect outbreaks are major drivers of natural disturbances in forest ecosystems. Outbreaks can have both direct and indirect effects on the composition of soil arthropod communities through canopy opening, nutrient addition and predator-prey interactions. In this study, we aimed to understand the effects of forest tent caterpillar (Malacosoma disstria; FTC) outbreaks through cascading effects on ant communities in both temperate and boreal forests in Canada. Pitfall traps and Berlese funnels were used to compare the ant communities, as well as the surrounding arthropod communities, between control and outbreak sites in boreal and temperate forests (in Quebec, Canada). Using the Sørensen dissimilarity index, we determined the alpha and beta diversity of the ant community. Other arthropods collected in the traps were counted to evaluate the richness and abundance of potential prey for the ants and other potential predators of the FTC. We used an indicator species analysis to examine the species associated with sites defoliated by the outbreak. In the boreal forest, we found that FTC outbreaks caused decreases in species richness and increases in the evenness of ant communities in defoliated sites. In the boreal forest sites, species composition varied significantly between control and outbreak sites. This pattern was driven in part by the presence of other predators. A similar, but weaker pattern was observed in the temperate forest. We saw no changes in the beta diversity in the boreal forest, but did see a significant decrease in the temperate forest between the outbreak sites and the control sites. Ant species in the boreal forest tended to exhibit a more marked preference for either control or previously defoliated sites than species in the temperate forest. Our study showed that disturbances such as insect outbreaks can drive changes in the ant community. While we saw small effects of outbreaks, manipulation experiments using resource addition could help us validate the mechanisms behind these relationships.
Isolation, Identification, and Characterization of an Acid-Tolerant Pichia kudriavzevii and Exploration of Its Acetic Acid Tolerance Mechanism
Authors: Wang Ning , Zhang Puyu , Zhou Xiaoli , Zheng Jia , Ma Yi , Liu Chenguang , Wu Tao , Li Hong , Wang Xiaoqin , Wang Hong , Zhao Xudong , Mehmood Muhammad Aamer , Zhu Hui
Published: June 2023

Pichia kudriavzevii is one of the major non-Saccharomyces cerevisiae yeasts in Chinese baijiu brewing, which has shown a substantially higher tolerance to acid, heat, and ethanol. Exploring the mechanism of P. kudriavzevii could have a positive effect on the artificially controlled production of baijiu. In this study, an efficient acetic-acid-tolerant P. kudriavzevii strain, Y2, was isolated from the yellow water of strong-flavored baijiu brewing waste, and its molecular mechanism of acetic acid tolerance was investigated through a comparative transcriptomic analysis. The strain Y2 could tolerate 12 g/L of acetic acid. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, differentially expressed genes (DEGs) were mainly enriched in oxidative phosphorylation, the citrate cycle, glycolysis/gluconeogenesis, and carbon metabolism under low (AL group) and high (AH group) concentrations of acetic acid. However, the DEG enrichment was more profound in the AH group when compared to the control. Compared with the AL group, the expression of genes related to oxidative phosphorylation was more significantly upregulated, while in terms of the TCA cycle, phosphoenolpyruvate carboxykinase was significantly upregulated in both the AH and AL groups and was positively correlated with tolerance to acetic acid. This was followed by citrate synthase, isocitrate dehydrogenase, malate dehydrogenase, and succinate dehydrogenase. These results illustrated a possible mechanism of acid tolerance by regulating the metabolism-related pathways in P. kudriavzevii and provided a basis for the further investigation of the acid tolerance mechanism.
Dietary Nanocurcumin Impacts Blood Biochemical Parameters and Works Synergistically with Florfenicol in African Catfish Challenged with Aeromonas veronii
Authors: Mansour Salwa , Bakry Karima , Alwaleed Eman , Ahmed Hassan , Al-Amgad Zeinab , Mohammed Haitham , Emeish Walaa
Published: June 2023

The present study investigated the effects of dietary supplementation of nanocurcumin (NCur = 150 ppm) in African catfish feed for 15 days along with two doses of florfenicol—a therapeutic dose (FFC1 = 10 mg/kg.BW) and a high dose (FFC2 = 30 mg/kg.BW). Serum biochemical parameters and histopathological changes in liver and kidney tissues were determined post-feeding. Additionally, fish were experimentally challenged with a virulent strain of Aeromonas veronii to explore the fish’s capacity to resist infections. Results indicated that the serum level of total protein was significantly elevated in the FFC2 + Ncur group compared with control, Ncur, and FFC2 groups. Total protein level was also higher in FFC1 + Ncur compared with that of the FFC1 group. Moreover, feeding NCur, FFC1 + Ncur, and FFC2 + Ncur resulted in a significant increase in globulin levels compared to control, FFC1, and FFC2-Fed groups. However, the albumin level was unaffected. Serum levels of AST, ALT, ALP, and urea significantly increased in FFC2-fed fish compared to controls indicating liver damage. The higher dosage of FFC2 induced histological alterations in the liver and kidney architecture, represented by a rupture of the central vein, cytoplasmic vacuolation, hepatocytes necrosis, and severe inflammation. Surprisingly, NCur inclusion improved most of the altered biochemical parameters and mitigated FFC-induced histological damage in the hepatic and renal tissues. Similarly, fish that were fed a combination of both FFC and Ncur showed a higher resistance when exposed to A. veronii infection, as the mortality rates were significantly lower than those of the control group. Our findings indicated that incorporating NCur into the diet can have multiple benefits for the sustainable aquaculture of African catfish. These advantages encompass mitigating drug-induced damage to the liver and kidney tissues, augmenting the therapeutic efficacy of FFC in a synergistic manner and providing protection against A. veronii infections.
Tyrosinase Inhibitory Peptides from Enzyme Hydrolyzed Royal Jelly: Production, Separation, Identification and Docking Analysis
Authors: Ge Zhen , Liu Jun-Cai , Sun Jian-An , Mao Xiang-Zhao
Published: June 2023

Tyrosinase is inextricably related to the development of Alzheimer’s disease. The effects of natural tyrosinase inhibitors on human health have attracted widespread attention. This study aimed to isolate and analyze the tyrosinase (TYR) inhibitory peptides in the enzymatic digestion products of royal jelly. We first analyzed optimal process conditions for the enzymatic digestion of royal jelly by single-factor and orthogonal experiments and then used gel filtration chromatography to obtain five fractions (D1~D5) with molecular weights ranging from 600 to 1100 Da. LC-MS/MS was applied to identify the fractions with the highest activity, and the obtained peptides were screened and molecularly docked using AutoDock Vina. The results showed that the optimal enzymatic conditions for tyrosinase inhibition rate were acid protease, enzyme addition 10,000 U/g, initial pH 4, feed-to-liquid ratio 1:4, enzymatic temperature 55 °C, and enzymatic time 4 h. The D4 fraction had the most significant TYR inhibitory activity. The IC50 values of the three new peptides with the strongest TYR inhibitory activity, TIPPPT, IIPFIF, and ILFTLL, were obtained as 7.59 mg/mL, 6.16 mg/mL, and 9.25 mg/mL, respectively. The molecular docking results showed that aromatic and hydrophobic amino acids were more favorable to occupy the catalytic center of TYR. In conclusion, the new peptide extracted from royal jelly has the potential to be used as a natural TYR inhibitory peptide in food products with health-promoting properties.
Textural and Consumer-Aided Characterisation and Acceptability of a Hybrid Meat and Plant-Based Burger Patty
Authors: Petrat-Melin Bjørn , Dam Svend
Published: June 2023

The hamburger has been targeted for substitution by numerous plant-based alternatives. However, many consumers find the taste of these alternatives lacking, and thus we proposed a hybrid meat and plant-based burger as a more acceptable alternative for these consumers. The burger was made from 50% meat (beef and pork, 4:1) and 50% plant-based ingredients, including texturised legume protein. Texture and sensory properties were evaluated instrumentally and through a consumer survey (n = 381) using the check-all-that-apply (CATA) method. Expressible moisture measurements indicated a significantly juicier eating experience for the hybrid compared to a beef burger (33.5% vs. 22.3%), which was supported by the CATA survey where “juicy” was used more to describe the hybrid than the beef burger (53% vs. 12%). Texture profile analysis showed the hybrid burger was significantly softer (Young’s modulus: 332 ± 34 vs. 679 ± 80 kPa) and less cohesive than a beef burger (Ratio 0.48 ± 0.02 vs. 0.58 ± 0.01). Despite having different textural and CATA profiles, overall liking of the hybrid burger and a beef burger were not significantly different. Penalty analysis indicated that “meat flavour”, “juiciness”, “spiciness” and “saltiness” were the most important attributes for a burger. In conclusion, the hybrid burger had different attributes and was described with different CATA terms than a beef burger but had the same overall acceptability.
Efficient Generators of the Generalized Fractional Gaussian Noise and Cauchy Processes
Authors: Sousa-Vieira María Estrella , Fernández-Veiga Manuel
Published: June 2023

In the last years of the past century, complex correlation structures were empirically observed, both in aggregated and individual traffic traces, including long-range dependence, large-timescale self-similarity and multi-fractality. The use of stochastic processes consistent with these properties has opened new research fields in network performance analysis and in simulation studies, where the efficient synthetic generation of samples is one of the main topics. Nowadays, networks have to support data services for traffic sources that are poorly understood or still insufficiently observed, for which simple, reproducible, and good traffic models are yet to be identified, and it is reasonable to expect that previous generators could be useful. For this reason, as a continuation of our previous work, in this paper, we describe efficient and online generators of the correlation structures of the generalized fractional noise process (gfGn) and the generalized Cauchy (gC) process, proposed recently. Moreover, we explain how we can use the Whittle estimator in order to choose the parameters of each process that give rise to a better adjustment of the empirical traces.
Vertical Distribution of Suspended Sediment Concentration in the Unsaturated Jingjiang Reach, Yangtze River, China
Authors: Liu Meng , Chen Dong , Sun Hong-Guang , Zhang Feng
Published: June 2023

The Rouse formula and its variants have been widely used to describe the vertical distribution of the sediment concentration in sediment-laden flows in equilibrium. Han’s formula extends the Rouse formula to non-equilibrium regimes, where the diffusive flux is still assumed to be Fickian. The turbulent flow and suspension regimes downstream of a mega-reservoir, e.g., the Three Gorges Reservoir, usually exhibit fractal and unsaturated properties, respectively. To characterize the non-Fickian dynamics of suspended sediment and the non-equilibrium regime in natural dammed rivers, this study proposes a new formula for the concentration profile of unsaturated sediment based on the Hausdorff fractal derivative advection–dispersion equation. In addition, we find that the order of the Hausdorff fractal derivative is related to the sizes of the sediment and the degrees of non-equilibrium. Compared to Rouse and Han’s formulae, the new formula performs better in describing the sediment concentration profiles in the Jingjiang Reach, approximately 100 km below the Three Gorges Dam.
Simple Mediation in a Cheap-Talk Game
Authors: Ganguly Chirantan , Ray Indrajit
Published: June 2023

In the Crawford–Sobel (uniform, quadratic utility) cheap-talk model, we consider a simple mediation scheme (a communication device) in which the informed agent reports one of the N possible elements of a partition to the mediator and then the mediator suggests one of the N actions to the uninformed decision-maker according to the probability distribution of the device. We show that no such simple mediated equilibrium can improve upon the unmediated N-partition Crawford–Sobel equilibrium when the preference divergence parameter (bias) is small.
Investigating Gravitationally Lensed Quasars Observable by Nancy Grace Roman Space Telescope
Authors: Hamolli Lindita , Hafizi Mimoza , De Paolis Francesco , Guliqani Esmeralda
Published: June 2023

In this work, we investigate the possibility of observing quasars, particularly lensed quasars, by the Nancy Grace Roman Space Telescope (Roman). To this aim, based on the capabilities of the Roman Space Telescope and the results from the quasar luminosity function (QLF) in the infrared band of the Spitzer Space Telescope imaging survey, we calculated the number of quasars expected to be in its field of view. In order to estimate the number of lensed quasars, we develop a Monte Carlo simulation to estimate the probability that a quasar is lensed once or more times by foreground galaxies. Using the mass–luminosity distribution function of galaxies and the redshift distributions of galaxies and quasars, we find that 1 per 180 observed quasars will be lensed by foreground galaxies. Further on, adopting a singular isothermal sphere (SIS) model for lens galaxies, we calculate the time delay between lensed images for single and multiple lensing systems and present their distributions. We emphasize that detailed studies of these lensing systems will provide a powerful probe of the physical properties of quasars and may allow testing the mass distribution models of galaxies in addition to being extremely helpful for constraining the cosmological parameters.
Formulation of Intranasal Mucoadhesive Thermotriggered In Situ Gel Containing Mirtazapine as an Antidepressant Drug
Authors: Ghazwani Mohammed , Vasudevan Rajalakshimi , Kandasamy Geetha , Manusri Naredla. , Devanandan Praveen , Puvvada Ranadheer Chowdary , Veeramani Vinoth Prabhu , Paulsamy Premalatha , Venkatesan Krishnaraju , Chidmabaram Kumarappan , Dhurke Rajeshri
Published: June 2023

The purpose of the present work was to develop nanoemulsion-based formulations of mirtazapine for intranasal delivery using a spray actuator to target the brain for treating depression. Research on the solubility of medications in different oils, surfactants, co-surfactants, and solvents has been done. Using pseudo-ternary phase diagrams, the various ratios of the surfactant and co-surfactant mix were computed. Thermotriggered nanoemulsion was formulated using different concentrations of poloxamer 407 (i.e., 15%, 15.5%, 16%, 16.5% up to 22%). Similarly, mucoadhesive nanoemulsion using 0.1% Carbopol and water-based plain nanoemulsions were also prepared for comparative assessment. The developed nanoemulsions were analyzed for physicochemical properties, i.e., physical appearance, pH, viscosity, and drug content. Drug-excipient incompatibility was determined by Fourier transform infrared spectral (FTIR) analysis and differential scanning calorimetry (DSC). In vitro drug diffusion studies were conducted for optimized formulations. Among the three formulations, RD1 showed the highest percentage of drug release. Ex vivo drug diffusion studies were conducted on freshly excised sheep nasal mucosa with Franz diffusion cell simulated nasal fluid (SNF) for all three formulations up to 6 h, and the thermotriggered nanoemulsion (RD1) showed 71.42% drug release with 42.64 nm particle size and a poly dispersity index of 0.354. The zeta potential was found to be −6.58. Based on the above data, it was concluded that thermotriggered nanoemulsion (RD1) has great potential to be used as an intranasal gel for treating depression in patients. It can offer great benefits by reducing dosing frequency and improving bioavailability of mirtazapine by direct nose-to-brain delivery.