bluuebunny/crossref_metadata_2025 huggingface dataset:
Privacy-Friendly Datasets of Synthetic Fingerprints for Evaluation of Biometric Algorithms
Authors: Makrushin Andrey , Mannam Venkata Srinath , Dittmann Jana
Published: September 2023

The datasets of synthetic biometric samples are created having in mind two major objectives: bypassing privacy concerns and compensating for missing sample variability in datasets of real biometric samples. If the purpose of generating samples is the evaluation of biometric systems, the foremost challenge is to generate so-called mated impressions—different fingerprints of the same finger. Note that for fingerprints, the finger’s identity is given by the co-location of minutiae points. The other challenge is to ensure the realism of generated samples. We solve both challenges by reconstructing fingerprints from pseudo-random minutiae making use of the pix2pix network. For controlling the identity of mated impressions, we derive the locations and orientations of minutiae from randomly created non-realistic synthetic fingerprints and slightly modify them in an identity-preserving way. Our previously trained pix2pix models reconstruct fingerprint images from minutiae maps, ensuring that the realistic appearance is transferred from training to synthetic samples. The main contribution of this work lies in creating and making public two synthetic fingerprint datasets of 500 virtual subjects with 8 fingers each and 10 impressions per finger, totaling 40,000 samples in each dataset. Our synthetic datasets are designed to possess characteristics of real biometric datasets. Thus, we believe they can be applied for the privacy-friendly testing of fingerprint recognition systems. In our evaluation, we use NFIQ2 for approving the visual quality and Verifinger SDK for measuring the reconstruction success.
Prediction of Cotton Yarn Quality Based on Attention-GRU
Authors: Dai Ning , Jin Haiwei , Xu Kaixin , Hu Xudong , Yuan Yanhong , Shi Weimin
Published: September 2023

With the diversification of spinning order varieties and process parameters, the conventional method of determining production plans through trial spinning no longer satisfies the processing requirements of enterprises. Currently, deficiencies exist in predicting spinning quality relying on manual experience and traditional methods. The back propagation (BP) neural network within the realm of deep learning theory faces challenges in handling time series data, while the long short-term memory (LSTM) neural network, despite its intricate mechanism, exhibits an overall lower predictive accuracy. Consequently, a more precise predictive methodology is imperative to assist production personnel in efficiently ascertaining cotton-blending schemes and processing parameters, thereby elevating the production efficiency of the enterprise. In response to this challenge, we propose an attention-GRU-based cotton yarn quality prediction model. By employing the attention mechanism, the model is directed towards the input features most significantly impacting yarn quality. Real-world performance indicators of raw cotton and process parameters are utilized to predict yarn tensile strength. A comparative analysis is conducted against prediction results of BP, LSTM, and gated recurrent unit (GRU) neural networks that do not incorporate the attention mechanism. The outcomes reveal that the GRU model enhanced with the attention mechanism demonstrates reductions of 56.3%, 38.5%, and 36.4% in root mean square error (RMSE), along with 0.367%, 0.158%, and 0.190% in mean absolute percentage error (MAPE), respectively. The model attains a coefficient of determination R-squared of 0.954, indicating a high degree of fitness. This study underscores the potential of the proposed attention-GRU model in refining cotton yarn quality prediction and its consequential implications for process optimization and enhanced production efficiency within textile enterprises.
Electrochemical Detection of SARS-CoV-2 Using Immunomagnetic Separation and Gold Nanoparticles on Unmodified Screen-Printed Carbon Electrodes
Authors: Lambert Christopher J. , Jayamohan Harikrishnan , Gale Bruce K. , Laurentius Lars B. , Patel Dhruv , Hansen Madison , Mahmood Tawsif , Sant Himanshu Jayant
Published: September 2023

The COVID-19 pandemic has underscored the critical need for virus detection methods that are precise, simple, quick, and cost-effective. Electrochemical immunoassay-based methods are a practical solution given their ability to quickly, inexpensively, sensitively, and selectively detect the virus at the point of care. This study details the immunomagnetic capture of SARS-CoV-2 nucleocapsid protein in nasal samples, followed by electrochemical detection using gold nanoparticle labels on a screen-printed carbon electrode. We determined ideal conditions for the size of the gold nanoparticles and the length of the deposition time to maximize the electrochemical signal. The limit of detection for nucleocapsid protein was determined to be 2.64 ng/mL in PBS. The assay was successfully demonstrated to detect nucleocapsid protein in SARS-CoV-2-positive samples with a viral load as low as Ct = 25 (p-value < 0.0001 vs. negative patient control).
Simulation Analysis of Working Circuit Performance of Mountain Pepper Harvester Based on Improved Load-Sensitive System
Authors: Wu Di , Ma Zhihao , Zhang Jianlong , Xu Weiping , He Haifeng , Li Zhenlin
Published: September 2023

China’s Guizhou is a typical karst landscape province with high production of chili pepper, but it is mostly planted in mountainous areas, while manual harvesting of chili pepper has the deficiencies of high labor intensity, low efficiency, and high labor cost; in addition, there is no harvesting machinery applicable to the dense planting pattern of the chili pepper in mountainous areas in China. The fully hydraulic mountain track-based self-propelled pepper harvester 4JZ-1.0A is designed to solve the above problems. The pepper harvester spiral comb picking head is an important part of the whole machine design, the design of the hydraulic system of the working circuit of the picking head is the key to realizing the hydraulic control part of the whole system. In this paper, the working principle diagram of the improved load-sensitive hydraulic system is designed and analyzed for the study of whether the working circuit of the pepper picking head of the pepper machine can meet the requirements of mountain operation, taking the working circuit of the mountain pepper harvester as the research object. In addition, the load-sensitive pump model and the simulation model of the whole working circuit are established by the AMESim platform 2019.2 (Siemens simcenter amesim). The operating performance of the system under variable flow conditions, variable load conditions, and an improved sensitive system is analyzed. The simulation results show that the improved load-sensitive system can effectively reduce the oscillation and cavitation during cylinder operation and improve the system efficiency and the performance and service life of the components. The performance of the hydraulic system of the working circuit of the mountain pepper harvester was verified in the test, meeting the requirements of working use. This provides a theoretical basis for the improvement and optimal design of a mountain pepper harvester hydraulic system.
Solar Power Prediction Modeling Based on Artificial Neural Networks under Partial Shading
Authors: Lee Younghyun , Lee Jonghwan
Published: September 2023

Photovoltaic systems are emerging as an important device to address the environmental pollution generated from conventional energy production. The objectives of this study are to accurately predict the power of photovoltaic systems under partial shading conditions and to model high-efficiency photovoltaic systems. First, the power loss under partial shading conditions was addressed using a bypass diode. In previous studies, for the power prediction, one or two parameters were trained through artificial neural networks. In this study, we employ five main parameters to improve the accuracy: the photo-current (Iph), diode saturation current (I0 ), diode idealization factor (n), series resistance (Rs), and shunt resistance (Rsh). Compared to the results of previous studies, the proposed model yielded consistent results. As a result, more accurate power predictions are possible with variations in temperature and irradiation.
Dynamic Graph Convolution-Based Spatio-Temporal Feature Network for Urban Water Demand Forecasting
Authors: Jia Zhiwei , Li Honghui , Yan Jiahe , Sun Jing , Han Chengshan , Qu Jingqi
Published: September 2023

Urban water demand forecasting is the key component of smart water, which plays an important role in building a smart city. Although various methods have been proposed to improve forecast accuracy, most of these methods lack the ability to model spatio-temporal correlations. When dealing with the rich water demand monitoring data currently, it is difficult to achieve the desired prediction results. To address this issue from the perspective of improving the ability to extract temporal and spatial features, we propose a dynamic graph convolution-based spatio-temporal feature network (DG-STFN) model. Our model contains two major components, one is the dynamic graph generation module, which builds the dynamic graph structure based on the attention mechanism, and the other is the spatio-temporal feature block, which extracts the spatial and temporal features through graph convolution and conventional convolution. Based on the Shenzhen urban water supply dataset, five models SARIMAX, LSTM, STGCN, DCRNN, and ASTGCN are used to compare with DG-STFN proposed. The results show that DG-STFN outperforms the other models.
Machine Learning-Based Garbage Detection and 3D Spatial Localization for Intelligent Robotic Grasp
Authors: Lv Zhenwei , Chen Tingyang , Cai Zhenhua , Chen Ziyang
Published: September 2023

Garbage detection and 3D spatial localization play a crucial role in industrial applications, particularly in the context of garbage trucks. However, existing approaches often suffer from limited precision and efficiency. To overcome these challenges, this paper presents an algorithmic architecture that leverages advanced techniques in computer vision and machine learning. The proposed approach integrates cutting-edge computer vision methodologies to improve the precision of waste classification and spatial localization. By utilizing RGB-D data captured by the RealSenseD415 camera, the algorithm incorporates state-of-the-art computer vision algorithms and machine learning models, including the Yolactedge model, for real-time instance segmentation of garbage objects based on RGB images. This enables the accurate prediction of garbage class and the generation of masks for each instance. Furthermore, the predicted masks are utilized to extract the point cloud corresponding to the garbage instances. The oriented bounding boxes of the segmented point cloud is calculated as the spatial location information of the garbage instances using the DBSCAN clustering algorithm to remove the interfering points. The findings indicate that the proposed approach can run at a maximum speed of 150 FPS. The usefulness of the proposed method in achieving accurate garbage recognition and spatial localization in a vision-driving robot grasp system has been tested experimentally on datasets that were custom-collected. The results demonstrate the algorithmic architecture’s ability to transform waste management procedures while also enabling intelligent garbage sorting and enabling robotic grasp applications.
Unveiling the Potential of Unexplored Winery By-Products from the Dão Region: Phenolic Composition, Antioxidants, and Antimicrobial Properties
Authors: Costa Cátia , Campos Joana , Gouvinhas Irene , Pinto Ana Rita , Saavedra Maria José , Novo Barros Ana
Published: September 2023

The winery industry generates significant amounts of organic waste, such as pruning firewood, stems, and wine lees, which can cause environmental issues and affect the economic sustainability and competitiveness of the industry. Given the known antioxidant and antimicrobial properties of phenolic compounds, we analyzed these by-products to quantify their phenolic composition and evaluate the effectiveness of pruning firewood and stem extracts from six autochthonous varieties of the Dão Region in inhibiting the growth of bacteria from diabetic foot wounds isolated from hospital patients. The study employed colorimetric methods to measure total phenols, ortho-diphenols, and flavonoids in the phenolic composition. The ABTS, DPPH, and FRAP methods were applied to assess the antioxidant capacity, and the disk diffusion method was applied to determine the antimicrobial activity of Gram-positive and Gram-negative bacteria. The results showed that Jaen had the most ortho-diphenols and flavonoids in pruning firewood, and the highest levels of these compounds were located in stem extracts. Jaen also had the highest antioxidant capacity in both pruning firewood and stems across all methods used. Notably, red wine lees displayed the highest biological and antioxidant activities. Moreover, pruning firewood extract displayed great efficacy in inhibiting the growth of Gram-positive bacteria, making it a promising candidate as a natural alternative against antibiotic resistance, which is a global public health concern.
Exploring the Efficacy of Sparse Feature in Pavement Distress Image Classification: A Focus on Pavement-Specific Knowledge
Authors: Yuan Ye , Chen Jiang , Lang Hong , Lu Jian (John)
Published: September 2023

Road surface deterioration, such as cracks and potholes, poses a significant threat to both road safety and infrastructure longevity. Swift and accurate detection of these issues is crucial for timely maintenance and user security. However, current techniques often overlook the unique characteristics of pavement images, where the small distressed areas are vastly outnumbered by the background. In response, we propose an innovative road distress classification model that capitalizes on sparse perception. Our method introduces a sparse feature extraction module using dilated convolution, tailored to capture and combine sparse features of different scales from the image. To further enhance our model, we design a specialized loss function rooted in domain-specific knowledge about pavement distress. This loss function enforces sparsity during feature extraction, guiding the model to align precisely with the sparse distribution of target features. We validate the strength and effectiveness of our model through comprehensive evaluations of a diverse dataset of road images containing various distress types and conditions. Our approach exhibits significant potential in advancing traffic safety by enabling more efficient and accurate detection and classification of road distress.
QCA-Based Secure RAM Cell Structure Using Logic Transformation and Cell Interaction with Signal Reliability and Energy Dissipation in Quantum Computing
Authors: Seo Duck-Kyu , Jeon Jun-Cheol
Published: September 2023

A RAM cell, one of the components that greatly affects the performance of quantum computing, outputs mostly stored values on quantum-dot cellular automata (QCA) as they are. Currently, a problem is that the stored value may be initialized according to the selection input. To solve this problem, circuits that separate the stored value from the output value have recently been designed, but most of them have long latency, large areas, and many plane structure intersections, resulting in unstable signals. Therefore, in this paper, we propose a new secure QRAM (QCA-based RAM) cell logic by analyzing and modifying the existing cell logic in nanotechnology. We initially propose 2-to-1 multiplexers based on cell interaction, and a QRAM cell is proposed based on our multiplexer and an optimized QRAM cell logic diagram. Compared with existing designs, the proposed circuits produce superior results in terms of circuit performance and energy dissipation. Additionally, the operation of our multiplexers is verified mathematically using physical proof. The secure QRAM cell proposed in this paper does not have the initialization problem based on the selection input that is present in some existing circuits, thus it is very easy to design an extension to N × N RAM, and it has high signal stability, reliability, connectivity, and scalability because there is no intersection.
Novel Fluoride Matrix for Dual-Range Optical Sensors and Visualization
Authors: Alexandrov Alexander A. , Petrova Lada A. , Pominova Daria V. , Romanishkin Igor D. , Tsygankova Maria V. , Kuznetsov Sergey V. , Ivanov Vladimir K. , Fedorov Pavel P.
Published: September 2023

Novel tetragonal matrix Ba0.5−xLn0.5NaxF2.5−x with x = 0.08, doped by Yb3+, Ho3+, Er3+, was synthesized by molten salt synthesis (MSS) from nitrate flux. XRD data show that the tetragonal phase with a = 4.122(1) Å, c = 17.672(1) Å is stable in an argon atmosphere up to 960 °C. Luminescence spectra recorded in 500–900 nm and 1050–1700 nm upon 974 nm pumping demonstrated the characteristic luminescence at 1550 nm (4I13/2 → 4I15/2) for Er3+ and 1150 nm (5I6 → 5I8) for Ho3+. The relative thermal sensitivity (Sr) at 296–316 K were 0.3%×K−1 and 5.5%×K−1 in shortwave infrared (SWIR) and visible range, respectively. Synthesized luminophores can be used as dual-range optical temperature sensors, which simultaneously operate in visible and SWIR ranges.
Aerosol Optical Depth Retrieval for Sentinel-2 Based on Convolutional Neural Network Method
Authors: Jiang Jie , Liu Jiaxin , Jiao Donglai
Published: September 2023

Atmospheric aerosol significantly affects the climate environment and public health, and Aerosol Optical Depth (AOD) is a fundamental optical characteristic parameter of aerosols, so it is important to develop methods for obtaining AOD. In this work, a novel AOD retrieval algorithm based on a Convolutional Neural Network (CNN) method that could provide continuous and detailed aerosol distribution is proposed. The algorithm utilizes data from Sentinel-2 and Aerosol Robotic Network (AERONET) spanning from 2016 to 2022. The CNN AOD data are consistent with the AERONET measurements, with an R2 of 0.95 and RMSE of 0.049 on the test dataset. CNN demonstrates superior performance in retrieving AOD compared with other algorithms. CNN retrieves AOD well on high reflectance surfaces, such as urban and bare soil, with RMSEs of 0.051 and 0.042, respectively. CNN efficiently retrieves AOD in different seasons, but it performs better in summer and winter than in spring and autumn. In addition, to study the relationship between image size and model retrieval performance, image datasets of 32 × 32, 64 × 64 and 128 × 128 pixels were created to train and test the CNN model. The results show that the 128-size CNN performs better because large images contain rich aerosol information.
Persistent Meteorological Drought in the Yangtze River Basin during Summer–Autumn 2022: Relay Effects of Different Atmospheric Internal Variabilities
Authors: Wang Ruili , Li Xiao , Ma Hedi , Li Xing , Wang Junchao , Lai Anwei
Published: September 2023

During the summer–autumn (July–October, Jul–Oct) period of 2022, the Yangtze River Basin (YRB) of China experienced an extreme meteorological drought, with Jul–Oct containing the lowest precipitation in the YRB since 1979. The possible causes of this drought were analyzed in the present study. Surprisingly, unlike many previous drought events, we found that this event was not characterized by a consistent atmospheric circulation anomaly regime throughout the entire drought period. Instead, two distinct circulation patterns were responsible for the precipitation deficit in two different stages, i.e., July–August (Jul–Aug) and September–October (Sep–Oct). In Jul–Aug, the YRB precipitation deficit primarily resulted from an intensified and northward-shifted East Asian subtropical jet, which allowed for an extremely northwestward shift of western Pacific subtropical highs, leading to an anomalous descending motion. Such circulation patterns in Jul–Aug originated from the dispersion of Rossby waves upstream from central Asia and Europe. Meanwhile, in Sep–Oct, the YRB drought was primarily attributed to a low-level cyclonic anomaly over the western North Pacific, which was closely associated with frequent tropical cyclones traveling across this region. Observational analysis and a model ensemble hindcast suggest that atmospheric internal variabilities dominated the drought process, while the SSTA, particularly the La Niña event, played a limited role. Therefore, this long-lasting extreme YRB meteorological drought was largely driven by the relay effects of different atmospheric internal variabilities in Jul–Aug and Sep–Oct, respectively, which shows limited model predictability and poses a great challenge for operational climate predictions.
Proof of Concept: The GREENcell—A Lithium Cell with a F-, Ni- and Co-Free Cathode and Stabilized In-Situ LiAl Alloy Anode
Authors: Schad Kathrin , Welti Dominic , Birke Kai Peter
Published: September 2023

Given the rising upscaling trend in lithium-ion battery (LiB) production, there is a growing emphasis on the environmental and economic impacts alongside the high energy density demands. The cost and environmental impact of battery production primarily arise from the critical elements Ni, Co, and F. This drives the exploration of Ni-free and Co-free cathode alternatives such as LiMn2O4 (LMO) and LiFePO4 (LFP). However, the absence of Ni and Co results in reduced capacity and insufficient cyclic stability, particularly in the case of LMO due to Mn dissolution. To compensate for both low cathode capacitance and low cycle stability, we propose the GREENcell, a lithium cell combining a F-free polyisobutene (PIB) binder-based LMO cathode with a stabilized in -situ LiAL alloy anode. A LiAl alloy anode with the chemical composition of LiAl already shows a theoretical capacity of 993 Ah·kg−1. Therefore, it promises extraordinarily higher energy densities compared to a commercial graphite anode with a capacity of 372 Ah·kg−1. Following an iterative development process, different optimization strategies, especially those targeting the stability of the Al-based anode, were evaluated. During Al foil selection, foil purity and thickness could be identified as two of the dominant influencing parameters. A pressed-in stainless steel mesh provides both mechanical stability to the anode and facilitates alloy formation by breaking up the Al oxide layer beforehand. Additionally, a binder-stabilized Al oxide or silicate layer is pre-coated on the Al surface, posing as a SEI-precursor and ensuring a uniform liquid electrolyte distribution at the phase boundary. Employing a commercially available Si-containing Al alloy mitigated the mechanical degradation of the anode, yielding a favorable impact on long-term stability. The applicability of the novel optimized GREENcell is demonstrated using laboratory coin cells with LMO and LFP as the cathode. As a result, the functionality of the GREENcell was demonstrated for the first time, and thanks to the anode stabilization strategies, a capacity retention of >70% after 200 was achieved, representing an increase of 32.6% compared to the initial Al foil.
A Numerical and Experimental Investigation on a Gravity-Assisted Heat-Pipe-Based Battery Thermal Management System for a Cylindrical Battery
Authors: Burkitbayev Arman , Weragoda Delika M. , Ciampa Francesco , Lo Kin Hing , Tian Guohong
Published: September 2023

A thermal management system for lithium-ion batteries is an essential requirement for electric vehicle operation due to the large amount of heat generated by these cylindrical batteries during fast charging/discharging. Previously, researchers have focused mostly on pouch and prismatic cells with heat pipes arranged in the horizontal direction. The current study introduces a novel vertically-oriented heat-pipe-based hybrid cooling battery thermal management system (BTMS) that numerically evaluates the thermal performance of the cylindrical batteries and the flow pattern within the cooling channel at C rates as high as 8C. The model was experimentally validated using five round heat pipes in a vertical orientation utilizing the effect of gravity to assist condensate flow through the heat pipe. The heat pipes were arranged in a staggered pattern to improve the overall heat transfer performance by means of forced convective cooling. This design allowed for maximizing the heat transfer process despite the lack of contact between the cylindrical-shaped batteries and round-shaped heat pipes. During this study, the temperatures of the evaporator end and the condenser end of the heat pipes and battery surfaces were monitored, and the thermal performances of the system were determined at varying inlet cooling liquid temperatures (15, 20, 25 °C) and high rates of 4C and 8C. Representatively, the proposed hybrid BTMS could maintain a maximum battery surface temperature of around 64 °C and a temperature difference between cells under 2.5 °C when the inlet velocity was 0.33 L/min and the cooling liquid temperature was 25 °C. The high temperatures reached the fourth and fifth heat pipes because they are part of the backflow design and are affected by backflow temperature. Nevertheless, the current design shows that the proposed system can maintain battery surface temperatures well within 5 °C.
Effect of Recipient’s Tactile Properties and Expectations on Beer Perception
Authors: Sandilya Shubham , Oroya Natalia , Moral Teresa , Vázquez-Araújo Laura
Published: September 2023

Our perception of food is influenced by various factors, including its sensory properties, the environment in which it is consumed, and the tools we use to consume it (cutlery, glasses, etc.). The purpose of this study was to examine how the texture of the glass used to drink beer affects the perception and emotions generated by the experience. Two tasting sessions were conducted, where participants were served two types of beer (alcoholic and non-alcoholic) in four glasses with different textures. The participants rated liking, the perceived differences in several sensory attributes using a Just-About-Right scale, and the emotions elicited by the drinking experience using a Check-All-That-Apply question. The results indicated that the texture of the container did not affect the participants’ perception of the alcoholic beer. However, for the non-alcoholic beer, participants liked the sample served in the glass with a plain surface over the ceramic glass. Participants’ awareness of drinking a non-alcoholic beer did not affect any of the studied attributes. The results of this study suggested that different textured glasses could be used to differentiate brands, restaurants, etc., from competitors and create a unique identity without significantly affecting the perception of beer properties.
The Gill-Associated Bacterial Community Is More Affected by Exogenous Chlorella pyrenoidosa Addition than the Bacterial Communities of Water and Fish Gut in GIFT Tilapia (Oreochromis niloticus) Aquaculture System
Authors: Meng Shunlong , Xu Huimin , Qin Lu , Chen Xi , Qiu Liping , Li Dandan , Song Chao , Fan Limin , Hu Gengdong , Xu Pao
Published: September 2023

Microalgae has been widely used in aquaculture to improve both the water environment and fish growth; however, the current understanding of the effects of microalgae addition on the key players involved in regulating the water environment and fish health, such as microorganisms, remains limited. Here, a 50-day mesocosm experiment was set up to simulate the culture of Genetic Improvement of Farmed Tilapia (GIFT, Oreochromis niloticus) with an average weight of 14.18 ± 0.93 g and an average length of 82.77 ± 2.80 mm. Different amounts of Chlorella pyrenoidosa were added into these artificial systems to investigate dynamics of bacterial communities in aquaculture water, fish gill, and gut using amplicon-based high-throughput sequencing technology. Our results showed that Chlorella pyrenoidosa addition increased diversity and network complexity of gill-associated bacterial communities rather than those of the water and gut. Furthermore, more biomarkers in the gill-associated bacterial communities were detected in response to Chlorella pyrenoidosa addition than the water and fish gut samples. These findings highlighted the high sensitivity of gill-associated bacterial communities in response to the Chlorella pyrenoidosa addition, implying Chlorella pyrenoidosa addition could play important roles in regulating the fish mucosal immunity by altering the gill-associated microbiota.
Loss of dlx5a/dlx6a Locus Alters Non-Canonical Wnt Signaling and Meckel’s Cartilage Morphology
Authors: Yu Emily P. Y. , Saxena Vishal , Perin Sofia , Ekker Marc
Published: September 2023

The dlx genes encode transcription factors that establish a proximal–distal polarity within neural crest cells to bestow a regional identity during craniofacial development. The expression regions of dlx paralogs are overlapping yet distinct within the zebrafish pharyngeal arches and may also be involved in progressive morphologic changes and organization of chondrocytes of the face. However, how each dlx paralog of dlx1a, dlx2a, dlx5a and dlx6a affects craniofacial development is still largely unknown. We report here that the average lengths of the Meckel’s, palatoquadrate and ceratohyal cartilages in different dlx mutants were altered. Mutants for dlx5a−/− and dlx5i6−/−, where the entire dlx5a/dlx6a locus was deleted, have the shortest lengths for all three structures at 5 days post fertilization (dpf). This phenotype was also observed in 14 dpf larvae. Loss of dlx5i6 also resulted in increased proliferation of neural crest cells and expression of chondrogenic markers. Additionally, altered expression and function of non-canonical Wnt signaling were observed in these mutants suggesting a novel interaction between dlx5i6 locus and non-canonical Wnt pathway regulating ventral cartilage morphogenesis.
Functional Interaction between Adenosine A2A and mGlu5 Receptors Mediates STEP Phosphatase Activation and Promotes STEP/mGlu5R Binding in Mouse Hippocampus and Neuroblastoma Cell Line
Authors: Mallozzi Cinzia , Pepponi Rita , Gaddini Lucia , Casella Ida , Chiodi Valentina , Popoli Patrizia , Domenici Maria Rosaria
Published: September 2023

(1) Background: Recently, we found that adenosine A2A receptor (A2AR) stimulation results in an increase in STEP phosphatase activity. In order to delve into the mechanism through which A2AR stimulation induced STEP activation, we investigated the involvement of mGlu5R since it is well documented that A2AR and mGlu5R physically and functionally interact in several brain areas. (2) Methods: In a neuroblastoma cell line (SH-SY5Y) and in mouse hippocampal slices, we evaluated the enzymatic activity of STEP by using a para-nitrophenyl phosphate colorimetric assay. A co-immunoprecipitation assay and a Western blot analysis were used to evaluate STEP/mGlu5R binding. (3) Results: We found that the A2AR-dependent activation of STEP was mediated by the mGlu5R. Indeed, the A2AR agonist CGS 21680 significantly increased STEP activity, and this effect was prevented not only by the A2AR antagonist ZM 241385, as expected, but also by the mGlu5R antagonist MPEP. In addition, we found that mGlu5R agonist DHPG-induced STEP activation was reversed not only by the mGlu5R antagonist MPEP but also by ZM 241385. Finally, via co-immunoprecipitation experiments, we found that mGlu5R and STEP physically interact when both receptors are activated (4) Conclusions: These results demonstrated a close functional interaction between mGlu5 and A2A receptors in the modulation of STEP activity.
Functionally Relevant Cytokine/Receptor Axes in Myelofibrosis
Authors: Pozzi Giulia , Carubbi Cecilia , Cerreto Giacomo Maria , Scacchi Chiara , Cortellazzi Samuele , Vitale Marco , Masselli Elena
Published: September 2023

Dysregulated inflammatory signaling is a key feature of myeloproliferative neoplasms (MPNs), most notably of myelofibrosis (MF). Indeed, MF is considered the prototype of onco-inflammatory hematologic cancers. While increased levels of circulatory and bone marrow cytokines are a well-established feature of all MPNs, a very recent body of literature is intriguingly pinpointing the selective overexpression of cytokine receptors by MF hematopoietic stem and progenitor cells (HSPCs), which, by contrast, are nearly absent or scarcely expressed in essential thrombocythemia (ET) or polycythemia vera (PV) cells. This new evidence suggests that MF CD34+ cells are uniquely capable of sensing inflammation, and that activation of specific cytokine signaling axes may contribute to the peculiar aggressive phenotype and biological behavior of this disorder. In this review, we will cover the main cytokine systems peculiarly activated in MF and how cytokine receptor targeting is shaping a novel therapeutic avenue in this disease.
Which Comes First, Nonalcoholic Fatty Liver Disease or Arterial Hypertension?
Authors: Golubeva Julia A. , Sheptulina Anna F. , Elkina Anastasia Yu. , Liusina Ekaterina O. , Kiselev Anton R. , Drapkina Oxana M.
Published: September 2023

Non-alcoholic fatty liver disease (NAFLD) and arterial hypertension (AH) are widespread noncommunicable diseases in the global population. Since hypertension and NAFLD are diseases associated with metabolic syndrome, they are often comorbid. In fact, many contemporary published studies confirm the association of these diseases with each other, regardless of whether other metabolic factors, such as obesity, dyslipidemia, and type 2 diabetes mellites, are present. This narrative review considers the features of the association between NAFLD and AH, as well as possible pathophysiological mechanisms.
Editorial: Novel Therapeutic Approaches in Inflammatory Bowel Diseases
Authors: Pallio Giovanni
Published: September 2023

Inflammatory bowel diseases (IBDs) encompass ulcerative colitis (UC) and Crohn’s disease (CD), both of which are inflammatory ailments affecting the gastrointestinal tract [...]
Hybrid Manta Ray Foraging Algorithm with Cuckoo Search for Global Optimization and Three-Dimensional Wireless Sensor Network Deployment Problem
Authors: Wang Meiyan , Luo Qifang , Wei Yuanfei , Zhou Yongquan
Published: September 2023

In this paper, a new hybrid Manta Ray Foraging Optimization (MRFO) with Cuckoo Search (CS) algorithm (AMRFOCS) is proposed. Firstly, quantum bit Bloch spherical coordinate coding is used for the initialization of the population, which improves the diversity of the expansion of the traversal ability of the search space. Secondly, the dynamic disturbance factor is introduced to balance the exploratory and exploitative search ability of the algorithm. Finally, the unique nesting strategy of the cuckoo and Levy flight is introduced to enhance the search ability. AMRFOCS is tested on CEC2017 and CEC2020 benchmark functions, which is also compared and tested by using different dimensions and other state-of-the-art metaheuristic algorithms. Experimental results reveal that the AMRFOCS algorithm has a superior convergence rate and optimization precision. At the same time, the nonparametric Wilcoxon signed-rank test and Friedman test show that the AMRFOCS has good stability and superiority. In addition, the proposed AMRFOCS is applied to the three-dimensional WSN coverage problem. Compared with the other four 3D deployment methods optimized by metaheuristic algorithms, the AMRFOCS effectively reduces the redundancy of sensor nodes, possesses a faster convergence speed and higher coverage and then provides a more effective and practical deployment scheme.
Two Decades of Arrayed Imaging Reflectometry for Sensitive, High-Throughput Biosensing
Authors: Kosoy Gabrielle , Miller Benjamin L.
Published: September 2023

Arrayed imaging reflectometry (AIR), first introduced in 2004, is a thin-film interference sensor technique that optimizes optical properties (angle of incidence, polarization, substrate refractive index, and thickness) to create a condition of total destructive interference at the surface of a silicon substrate. The advantages of AIR are its sensitivity, dynamic range, multiplex capability, and high-throughput compatibility. AIR has been used for the detection of antibodies against coronaviruses, influenza viruses, Staphylococcus aureus, and human autoantigens. It has also shown utility in detection of cytokines, with sensitivity comparable to bead-based and ELISA assays. Not limited to antibodies or antigens, mixed aptamer and protein arrays as well as glycan arrays have been employed in AIR for differentiating influenza strains. Mixed arrays using direct and competitive inhibition assays have enabled simultaneous measurement of cytokines and small molecules. Finally, AIR has also been used to measure affinity constants, kinetic and at equilibrium. In this review, we give an overview of AIR biosensing technologies and present the latest AIR advances.
Diagnosis and Management of Seronegative Myasthenia Gravis: Lights and Shadows
Authors: Vinciguerra Claudia , Bevilacqua Liliana , Lupica Antonino , Ginanneschi Federica , Piscosquito Giuseppe , Rini Nicasio , Rossi Alessandro , Barone Paolo , Brighina Filippo , Di Stefano Vincenzo
Published: September 2023

Myasthenia gravis (MG) is an antibody-mediated neuromuscular disease affecting the neuromuscular junction. In most cases, autoantibodies can be detected in the sera of MG patients, thus aiding in diagnosis and allowing for early screening. However, there is a small proportion of patients who have no detectable auto-antibodies, a condition termed “seronegative MG” (SnMG). Several factors contribute to this, including laboratory test inaccuracies, decreased antibody production, immunosuppressive therapy, immunodeficiencies, antigen depletion, and immune-senescence. The diagnosis of SnMG is more challenging and is based on clinical features and neurophysiological tests. The early identification of these patients is needed in order to ensure early treatment and prevent complications. This narrative review aims to examine the latest updates on SnMG, defining the clinical characteristics of affected patients, diagnostic methods, management, and therapeutic scenarios.
Anxious-Withdrawal and Sleep Problems during Adolescence: The Moderating Role of Peer Difficulties
Authors: Bowker Julie C. , Gurbacki Jessica N. , Richard Chloe L. , Rubin Kenneth H.
Published: September 2023

Anxious-withdrawal is a well-established individual risk factor for psychosocial difficulties during adolescence. It is unknown, however, whether it also places youth at increased risk for physical health problems, such as sleep difficulties. This study examines the concurrent and prospective associations between anxious-withdrawal and six types of sleep difficulties (i.e., sleeping too much, sleeping too little, talking/walking in sleep, being overtired, nightmares, and general trouble sleeping). We further evaluate whether these associations differ for adolescents who are high versus low in exclusion and victimization. The participants were 395 adolescents (Mage = 13.61 years; 35% ethnic minority) who completed peer nominations of anxious-withdrawal, exclusion, and victimization at Time 1 (T1). Their mothers completed reports of sleep difficulties at T1 and at Time 2 (T2). Path analyses revealed unique associations between anxious-withdrawal and several types of sleep difficulties (e.g., sleeping too much) at T1. Analyses also revealed a significant interaction effect between T1 anxious-withdrawal and exclusion/victimization such that anxious-withdrawal was prospectively associated with trouble sleeping only for those young adolescents who are highly excluded/victimized. Our findings are the first to link anxious-withdrawal to a physical health outcome in adolescence and point to the need for future research to not only examine anxious-withdrawal and physical health but also to include assessments of peer difficulties.
Political Trust and Festival Attachment: Influencing Residents’ Engagement in Traditional Festivals
Authors: Zhang Jing , Dai Guangquan
Published: September 2023

Traditional festivals hold immense cultural and tourism value, but striking a balance between preservation and adaptation in the face of globalization is challenging. This study focuses on the Hmong New Year, the largest traditional festival in a prominent Hmong settlement in China. Through mixed research methods, it examines the impact of festival attachment and political trust on residents’ attitudes toward festival tourism development. The results reveal the significant influence of festival attachment on residents’ perception and judgment of festival tourism, with political trust playing a crucial moderating role. Successful repetition of festival activities fosters stable cognitive perceptions of festival tourism, outweighing potential risks. This research enhances our theoretical understanding of festivals and provides insights into the sustainable development of traditional Hmong festivals, offering support for studying traditional festivals in diverse cultural contexts.
Effect of Chemical Admixtures on the Working Performance and Mechanical Properties of Cement-Based Self-Leveling Mortar
Authors: Wang Yemin , Wu Jiaming , Su Lei , Zhang Zizhuo , Wang Zhenxing , Lei Tianyu , Lu Xiaolei , Ye Zhengmao
Published: September 2023

In this work, the effect of cellulose ether (CE), tartaric acid (TA), and polycarboxylate superplasticizer (PCE) on the working performance and mechanical properties of cement-based self-leveling mortar is investigated. According to the orthogonal experiment analysis, TA is identified as the most influential factor affecting the working performance, as indicated by factors such as fluidity, fluidity loss, and viscosity. Upon conducting a comprehensive assessment of the working performance and mechanical properties, the optimal parameters are found to be CE = 0.6 wt.‰, TA = 0.5 wt.‰, and PCE = 2.0 wt.‰. A univariate test highlights that that the working performance improves with the higher TA dosages. Specifically, the exponential reduction of fluidity loss corresponds with an increased TA content. Regarding the mechanical properties of cement-based self-leveling mortar, the compressive and flexural strength exhibit enhancement when the TA dosage remains below 0.4 wt.‰ at the early stage, implying that TA has some influence on the hydration process. Impressively, the 1 d compressive and flexural strengths surpass 7 MPa and 2 MPa, respectively, ensuring the viability of subsequent construction activities. Through an analysis of hydration heat, the effect mechanism of TA on the cement-based self-leveling mortar is derived. The result shows that the addition of TA decelerates the hydration process within the initial 10 h, followed by acceleration in the subsequent 20 h to 30 h. Consequently, this delayed formation of the early hydration product, ettringite, contributes to a more porous structure in the slurry, with low friction leading to a better working performance. A large number of hydration products, such as alumina gel and calcium–silicon–hydrate gel, presented in the hardened paste results in the good mechanical properties at 1 d. This study may lay a foundation for the optimization of the dosage of chemical admixtures in the self-leveling mortar and high-performance cement-based materials, and also impart valuable insights for practical applications extending to the realm of building construction and decoration.
Vulnerable Neighbourhoods, Disaffiliated Populations? A Comprehensive Index of Social Capital and Social Infrastructure in Barcelona
Authors: Piasek Gonzalo , Garcia-Almirall Pilar
Published: September 2023

This article aims to understand the probable links between social capital and social infrastructure. The inclusion of these two dimensions into urban analysis may help to better understand the nature and characteristics of the relationships between the built environment and the level of organisation of the residents, and whether these have an impact on the vulnerability of the territories. Through use of statistical techniques (visual grouping and cluster analysis, among others), this article seeks to construct a comprehensive measure of social capital, as well as a comprehensive index of social infrastructure. These two in combination show, as the main results, that the characteristics of the built environment may promote higher levels of social interaction, also leading to higher levels of civic engagement and participation. However, the results also suggest that this relationship may be bidirectional. Finally, the mapping of the two indices applied in the city of Barcelona is presented and these results are compared with a previously constructed index of vulnerability for the same territory, allowing an overall better understanding of Barcelona’s socio-urban behaviour.
A Model Calibration Approach to U-Value Measurements with Thermography
Authors: Patel Dhruvkumar , Estevam Schmiedt Jacob , Röger Marc , Hoffschmidt Bernhard
Published: September 2023

The thermal properties of a building envelope are key indicators of the energy performance of the building. Therefore, methods are needed to determine quantities like the thermal transmittance (U-value) or heat capacitance in a fast, reliable way and with as little impact on the use of the building as possible. In this paper a technique is proposed that relies on a simplified electrical analogical model of building envelope components which can cover their dynamic thermal behavior. The parameters of this model are optimized to produce the best fit between simulated and measured outside surface temperatures. As the temperatures can be measured remotely with an infrared camera this approach requires significantly less installation effort and intrusion in the building than other methods. At the same time, a single measurement provides data for a large range of locations on a facade or a roof. The paper describes the method and a first experimental implementation of it. The experiment indicates that this method has the potential to produce results which have an accuracy that is comparable to standardized reference methods.
Cooling Energy Benefits of Increased Green Infrastructure in Subtropical Urban Building Environments
Authors: Mohammed Afifa , Khan Ansar , Khan Hassan Saeed , Santamouris Mattheos
Published: September 2023

Due to urban warming, the energy demand for cooling buildings is rising. The current study used CitySim (building energy model) to estimate the cooling energy requirements for 40 buildings in downtown Dubai using high-resolution climate data from weather research and forecasting (WRF) coupled with the single layer urban canopy model (SLUCM). Simulating the four mitigation scenarios allowed for the examination of the reduction in cooling load caused by the addition of greenery at a rate ranging from 25% to 100%. The insulated building’s cooling demand reduced by a maximum of 13.89% under 100% GI (M4). Scenario M4 resulted in a reduction of 4.6 kWh/m2 and 3.1 kWh/m2 for the non-insulated and insulated low-rise residential buildings, respectively, while the high-rise buildings saw a reduction of 3.09–4.91 kWh/m2 for the non-insulated and 2.07–3.09 kWh/m2 for the insulated buildings. This study offers a potential remedy to deal with the problem of urban heating in subtropical environments.