bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of carbon source addition in rearing water on sediment characteristics, growth and health of cultured marron (Cherax cainii)
Authors: Nguyen Thi Thu Thuy , Foysal Md Javed , Gupta Sanjay Kumar , Tay Alfred , Fotedar Ravi , Gagnon Marthe Monique 
Published: January 2024

AbstractCarbon sources are considered as critical input for the health and immunity of aquatic animals. The present study investigated the impact of different carbon sources on water quality parameters, carbon to nitrogen (C/N) ratio and microbial community in sediments, and health responses of marron (Cherax cainii) under laboratory conditions. Following one week of acclimation, 120 marron were randomly assigned to 12 experimental tanks. There were four treatments including one untreated control and three groups with carbon addition to maintain a C/N ratio of 12 maintained in culture water. Carbon supplementation groups included corn flour (CBC12), molasses (MBC12) and wheat flour (WBC12). At the end of the 60-day trial, MBC12 resulted in the highest sediment C/N ratio, followed by CBC12. Weight gain and specific growth rate were higher in MBC12, compared to control. The protease activity in marron hepatopancreas, total haemocyte count and lysozyme activity in haemolymph were highest in MBC12. Analysis of 16S rRNA sequence data of tank sediments revealed increased bacterial alpha diversity in MBC12 and WBC12. Proteobacteria was the most abundant phylum in MBC12 (88.6%), followed by control (82.4%) and CBC12 (72.8%). Sphingobium and Novosphingobium were the most abundant genera in control and MBC12 groups, respectively. Higher Aeromonas abundance in CBC12 and Flavobacterium in WBC12 were observed. Overall results indicated that MBC12 led to improved water quality, retaining high C/N ratio and enriched the bacterial populations in sediments resulting in improved growth and immune performance of marron.
Raman spectra simulation of antiplatelet drug-platelet interaction using DFT
Authors: Kundalevich Anna , Kapitunova Anastasia , Berezin Kirill , Zyubin Andrey , Moiseeva Ekaterina , Rafalskiy Vladimir , Samusev Ilia 
Published: January 2024

AbstractThe paper reflects the results of molecular docking and mathematical DFT simulation for antiplatelet drugs and the target platelet receptor/ferment interaction in the limited area. The results of Raman spectra simulation are implemented and obtained from the interaction of the clopidogrel metabolite of the P2Y12 receptor. The interaction of aspirin with the COX-1 enzyme was also investigated. As a result, theoretical Raman spectra of the drug-receptor area were obtained. The theoretical data were compared with the experimental SERS results. The characteristic bands corresponding to metabolite/ferment and antiplatelet drug vibrations were clarified. The prospects of obtaining results for pathologies based on platelet conformations during cardiovascular diseases have been demonstrated.
Transcriptomics identifies blunted immunomodulatory effects of vitamin D in people with multiple sclerosis
Authors: Yeh Wei Z. , Lea Rodney , Stankovich Jim , Sampangi Sandeep , Laverick Louise , Van der Walt Anneke , Jokubaitis Vilija , Gresle Melissa , Butzkueven Helmut 
Published: January 2024

AbstractVitamin D deficiency is a risk factor for developing multiple sclerosis (MS). However, the immune effects of vitamin D in people with MS are not well understood. We analyzed transcriptomic datasets generated by RNA sequencing of immune cell subsets (CD4+, CD8+T cells, B cells, monocytes) from 33 healthy controls and 33 untreated MS cases. We utilized a traditional bioinformatic pipeline and weighted gene co-expression network analysis (WGCNA) to determine genes and pathways correlated with endogenous vitamin D. In controls, CD4+and CD8+T cells had 1079 and 1188 genes, respectively, whose expressions were correlated with plasma 25-hydroxyvitamin D level (P < 0.05). Functional enrichment analysis identified association with TNF-alpha and MAPK signaling. In CD4+T cells of controls, vitamin D level was associated with expression levels of several genes proximal to multiple sclerosis risk loci (P = 0.01). Genes differentially associated with endogenous vitamin D by case–control status were enriched in TNF-alpha signaling via NF-κB. WGCNA suggested a blunted response to vitamin D in cases relative to controls. Collectively, our findings provide further evidence for the immune effects of vitamin D, and demonstrate a differential immune response to vitamin D in cases relative to controls, highlighting a possible mechanism contributing to MS pathophysiology.
User identification system based on 2D CQT spectrogram of EMG with adaptive frequency resolution adjustment
Authors: Kim Jae Myung , Choi Gyuho , Pan Sungbum 
Published: January 2024

AbstractUser identification systems based on electromyogram (EMG) signals, generated inside the body in different signal patterns and exhibiting individual characteristics based on muscle development and activity, are being actively researched. However, nonlinear and abnormal signals constrain conventional user identification using EMG signals in improving accuracy by using the 1-D feature from each time and frequency domain. Therefore, multidimensional features containing time–frequency information extracted from EMG signals have attracted much attention to improving identification accuracy. We propose a user identification system using constant Q transform (CQT) based 2D features whose time–frequency resolution is customized according to EMG signals. The proposed user identification system comprises data preprocessing, CQT-based 2D image conversion, convolutional feature extraction, and classification by convolutional neural network (CNN). The experimental results showed that the accuracy of the proposed user identification system using CQT-based 2D spectrograms was 97.5%, an improvement of 15.4% and 2.1% compared to the accuracy of 1D features and short-time Fourier transform (STFT) based user identification, respectively.
Excess heat production of the pair annihilation of ionic vacancies in a copper redox reaction using a double bipolar MHD electrode
Authors: Miura Makoto , Sugiyama Atsushi , Oshikiri Yoshinobu , Morimoto Ryoichi , Mogi Iwao , Miura Miki , Yamauchi Yusuke , Aogaki Ryoichi 
Published: January 2024

AbstractThrough a copper double bipolar magnetohydrodynamic (MHD) electrode (MHDE) producing twice the amounts of ionic vacancies than a conventional single MHDE, the molar excess heat of the pair annihilation of ionic vacancies, 702 kJ mol−1 at 10 T on average was obtained in a copper redox reaction. It was about twice as large as that of a single MHDE, 387 kJ mol−1 at the same magnetic field. This result strongly suggests that a multi-channel bipolar MHDE will produce much greater excess heat. To conserve the linear momentum and electric charge during electron transfer in an electrode reaction, ionic vacancies are created, storing the solvation energy in the polarized core of the order of 0.1 nm, and the pair annihilation of the vacancies with opposite charges liberates the energy as excess heat. The promoted excess heat by the double bipolar MHDE with a diffuser at 10 T was 710 ± 144 kJ mol−1, whereas as mentioned above, 702 ± 426 kJ mol−1 was obtained by the same electrode without such a diffuser. From the theoretical excess heat of 1140 kJ mol−1, the collision efficiencies in pair annihilation were 0.623 ± 0.126 and 0.616 ± 0.374, respectively. From these results, the reproducibility of the thermal measurement was experimentally validated. At the same time, it was concluded that at magnetic fields beyond 10 T, the concentration of ionic vacancy and the collision efficiency take constant uppermost values.
Coastal bathymetry in central Dronning Maud Land controls ice shelf stability
Authors: Eisermann H. , Eagles G. , Jokat W. 
Published: January 2024

AbstractKnowledge of the bathymetry of Antarctica’s margins is crucial for models and interpretations of ice-ocean interactions and their influence on ongoing and future sea level change, but remains patchy where ice shelves and multi-year sea ice block measurements. Here, we present a bathymetric model for the central Dronning Maud Land margin, based on a constrained inversion of airborne gravity data. It shows the cavities beneath the region’s two ice shelves to be much deeper than in existing bathymetric compilations, but to be shielded from Warm Deep Water ingress and basal melting by the presence of shallow bathymetric sills along the continental shelf. Over areas of multi-year sea ice, the model returns bathymetric estimates of similar accuracy to gravity interpolation-based methods over open water. Airborne gravity thus presents an opportunity to bathymetrically map hundreds of thousands of square kilometres of the most inaccessible margins of Antarctica at resolutions adequate for regional and global oceanographic and glaciological modelling and interpretation.
Early stage black pepper leaf disease prediction based on transfer learning using ConvNets
Authors: Kini Anita S. , Prema K. V. , Pai Smitha N. 
Published: January 2024

AbstractPlants get exposed to diseases, insects and fungus. This causes heavy damages to crop resulting in various leaves diseases. Leaf diseases can be diagnosed at an early stage with the aid of a smart computer vision system and timely disease prevention can be targeted. Black pepper is a medicinal plant that is extensively used in Ayurvedic medicine because of its therapeutic properties. The proposed work represents an intelligent transfer learning technique through state-of-the-art deep learning implementation using convolutional neural network to predict the presence of prominent diseases in black pepper leaves. The ImageNet dataset available online is used for training deep neural network. Later, this trained network is utilized for the prediction of the newly developed black pepper leaf image dataset. The developed data set consist of real time leaf images, which are candidly taken from the fields and annotated under supervision of an expert. The leaf diseases considered are anthracnose, slow wilt, early stage phytophthora, phytophthora and yellowing. The hyperparameters chosen for tuning in to deep learning models are initial learning rates, optimization algorithm, image batches, epochs, validation and training data, etc. The accuracy obtained with 0.001 learning rate ranges from 99.1 to 99.7% for the Inception V3, GoogleNet, SqueezeNet and Resnet18 models. Proposed Resnet18 model outperforms all model with 99.67% accuracy. The resulting validation accuracy obtained using these models is high and the validation loss is low. This work represents improvement in agriculture and a cutting edge deep neural network method for early stage leaf disease identification and prediction. This is an approach using a deep learning network to predict early stage black pepper leaf diseases.
Comparative genomics of monotremes provides insights into the early evolution of mammalian epidermal differentiation genes
Authors: Steinbinder Julia , Sachslehner Attila Placido , Holthaus Karin Brigit , Eckhart Leopold 
Published: January 2024

AbstractThe function of the skin as a barrier against the environment depends on the differentiation of epidermal keratinocytes into highly resilient corneocytes that form the outermost skin layer. Many genes encoding structural components of corneocytes are clustered in the epidermal differentiation complex (EDC), which has been described in placental and marsupial mammals as well as non-mammalian tetrapods. Here, we analyzed the genomes of the platypus (Ornithorhynchus anatinus) and the echidna (Tachyglossus aculeatus) to determine the gene composition of the EDC in the basal clade of mammals, the monotremes. We report that mammal-specific subfamilies of EDC genes encoding small proline-rich proteins (SPRRs) and late cornified envelope proteins as well as single-copy EDC genes such as involucrin are conserved in monotremes, suggesting that they have originated in stem mammals. Monotremes have at least one gene homologous to the group of filaggrin (FLG), FLG2 and hornerin (HRNR) in placental mammals, but no clear one-to-one pairwise ortholog of either FLG, FLG2 or HRNR. Caspase-14, a keratinocyte differentiation-associated protease implicated in the processing of filaggrin, is encoded by at least 3 gene copies in the echidna. Our results reveal evolutionarily conserved and clade-specific features of the genetic regulation of epidermal differentiation in monotremes.
Evaluation and optimization of ecological spatial resilience of Yanhe River Basin based on complex network theory
Authors: Hou Quanhua , Li Qingze , Yang Yuxuan , Zhou Jizhe , Du Yang , Zhang Yahui 
Published: January 2024

AbstractThe loess hilly and gully areas have broken terrain, vertical and horizontal ravines and fragile ecological environments. Improving the resilience of the regional ecological space is conducive to improving the quality of the local ecological environment. With the ecological space of the Yanhe River Basin selected as the research object, this paper constructs a research framework of "network identification topology-resilience evaluation-spatial optimization" and uses morphological spatial pattern analysis (MSPA) and the minimum cumulative resistance model (MCR) to identify ecological spatial networks. Based on circuit theory, the ecological pinch point is identified, the ecological spatial network is optimized, and scenario simulation is performed. Through complex network theory and related indicators, the ecological spatial resilience of the basin is evaluated, and the hierarchical optimization strategy of the ecological space is confirmed. According to the ecological function of the source area and the results of the resilience evaluation, the boundaries of the protected control area, guidance development area, remediation area, and maintenance and improvement area of the basin are delineated. The importance of ecological source and corridor protection is classified, and corresponding protection strategies are proposed. The research results can provide theoretical support and practical guidance for the territorial spatial planning and ecological space construction of the Yanhe River Basin and provide a reference for the ecological restoration, resource development and environmental governance of the Yanhe River Basin.
Evaluating YOLO architectures for detecting road killed endangered Brazilian animals
Authors: Ferrante Gabriel Souto , Vasconcelos Nakamura Luis Hideo , Sampaio Sandra , Filho Geraldo Pereira Rocha , Meneguette Rodolfo Ipolito 
Published: January 2024

AbstractWildlife roadkill is a recurring, dangerous problem that affects both humans and animals and has received increasing attention from environmentalists worldwide. Addressing this problem is difficult due to the high investments required in road infrastructure to effectively reduce wildlife vehicle collisions. Despite recent applications of machine learning techniques in low-cost and economically viable detection systems, e.g., for alerting drivers about the presence of animals and collecting statistics on endangered animal species, the success and wide adoption of these systems depend heavily on the availability of data for system training. The lack of training data negatively impacts the feature extraction of machine learning models, which is crucial for successful animal detection and classification. In this paper, we evaluate the performance of several state-of-the-art object detection models on limited data for model training. The selected models are based on the YOLO architecture, which is well-suited for and commonly used in real-time object detection. These include the YoloV4, Scaled-YoloV4, YoloV5, YoloR, YoloX, and YoloV7 models. We focus on Brazilian endangered animal species and use the BRA-Dataset for model training. We also assess the effectiveness of data augmentation and transfer learning techniques in our evaluation. The models are compared using summary metrics such as precision, recall, mAP, and FPS and are qualitatively analyzed considering classic computer vision problems. The results show that the architecture with the best results against false negatives is Scaled-YoloV4, while the best FPS detection score is the nano version of YoloV5.
Construction of an immune-related risk score signature for gastric cancer based on multi-omics data
Authors: Wang Ying , Huang Wenting , Zheng Shanshan , Wang Liming , Zhang Lili , Pei Xiaojuan 
Published: January 2024

AbstractEarly identification of gastric cancer (GC) is associated with a superior survival rate compared to advanced GC. However, the poor specificity and sensitivity of traditional biomarkers suggest the importance of identifying more effective biomarkers. This study aimed to identify novel biomarkers for the prognosis of GC and construct a risk score (RS) signature based on these biomarkers, with to validation of its predictive performance. We used multi-omics data from The Cancer Genome Atlas to analyze the significance of differences in each omics data and combined the data using Fisher's method. Hub genes were subsequently subjected to univariate Cox and LASSO regression analyses and used to construct the RS signature. The RS of each patient was calculated, and the patients were divided into two subgroups according to the RS. The RS signature was validated in two independent datasets from the Gene Expression Omnibus and subsequent analyses were subsequently conducted. Five immune-related genes strongly linked to the prognosis of GC patients were obtained, namely CGB5, SLC10A2, THPO, PDGFRB, and APOD. The results revealed significant differences in overall survival between the two subgroups (p < 0.001) and indicated the high accuracy of the RS signature. When validated in two independent datasets, the results were consistent with those in the training dataset (p = 0.003 and p = 0.001). Subsequent analyses revealed that the RS signature is independent and has broad applicability among various GC subtypes. In conclusion, we used multi-omics data to obtain five immune-related genes comprising the RS signature, which can independently and effectively predict the prognosis of GC patients with high accuracy.
The impact of local pinning sites in magnetic tunnel junctions with non-homogeneous free layers
Authors: Jenkins Alex. S. , Martins Leandro , Benetti Luana C. , Schulman Alejandro , Anacleto Pedro , Claro Marcel S. , Caha Ihsan , Deepak Francis Leonard , Paz Elvira , Ferreira Ricardo 
Published: January 2024

AbstractPinning at local defects is a significant road block for the successful implementation of technological paradigms which rely on the dynamic properties of non-trivial magnetic textures. Here, a comprehensive study of the influence of local pinning sites for non-homogeneous magnetic layers integrated as the free layer of a magnetic tunnel junction is presented, both experimentally and with corresponding micromagnetic simulations. The pinning sites are found to be extremely detrimental to the frequency controllability of the devices, a key requirement for their use as synapses in a frequency multiplexed artificial neural networks. In addition to describing the impact of the local pinning sites in the more conventional NiFe, a vortex-based magnetic tunnel junction with an amorphous free layer is presented which shows significantly improved frequency selectivity, marking a clear direction for the design of future low power devices.
Non-covalent interactions in the diastereoselective synthesis of cis-2,3-dihydrobenzofurans: experimental and computational studies
Authors: Jamis-Oliva Omar , López Roger , Galdámez Antonio , Gallardo-Fuentes Sebastián , Vilches-Herrera Marcelo 
Published: January 2024

The diastereoselective synthesis of 2,3-DHBs can be afforded via an intramolecular Michael addition reaction using Cs2CO3.
Articulatory and Vocal Fold Movement Patterns During Loud Speech in Children With Cerebral Palsy
Authors: Nip Ignatius S. B. 
Published: January 2024

Purpose:
Speech motor control changes underlying louder speech are poorly understood in children with cerebral palsy (CP). The current study evaluates changes in the oral articulatory and laryngeal subsystems in children with CP and their typically developing (TD) peers during louder speech.

Method:
Nine children with CP and nine age- and sex-matched TD peers produced sentence repetitions in two conditions: (a) with their habitual rate and loudness and (b) with louder speech. Lip and jaw movements were recorded with optical motion capture. Acoustic recordings were obtained to evaluate vocal fold articulation.

Results:
Children with CP had smaller jaw movements, larger lower lip movements, slower jaw speeds, faster lip speeds, reduced interarticulator coordination, reduced low-frequency spectral tilt, and lower cepstral peak prominences (CPP) in comparison to their TD peers. Both groups produced louder speech with larger lip and jaw movements, faster lip and jaw speeds, increased temporal coordination, reduced movement variability, reduced spectral tilt, and increased CPP.

Conclusions:
Children with CP differ from their TD peers in the speech motor control of both the oral articulatory and laryngeal subsystems. Both groups alter oral articulatory and vocal fold movements when cued to speak loudly, which may contribute to the increased intelligibility associated with louder speech.

Supplemental Material:

https://doi.org/10.23641/asha.24970302
Counting short cycles of QC‐LDPC codes in base graph
Authors: Wang Liqian , Zou Jingke , Zhu Miao , Zhao Yatong 
Published: January 2024

AbstractThe performance of quasi‐cyclic low‐density parity‐check codes is closely tied to the number of short cycles. Here, a method is proposed to accurately count short cycles within the base matrix. By searching for all distinct and non‐redundant cyclic paths and combining the number of cycles from each path, the total number of short cycles is obtained. These results demonstrate that the complexity of our algorithm is independent of the code length and directly proportional to the number of edges in the base graph. Moreover, as the lifting degree of the codes increases, the proposed algorithm achieves faster cycle counting.
An adaptive neuro‐fuzzy inference system optimized by genetic algorithm for brain tumour detection in magnetic resonance images
Authors: Ghahramani Marzieh , Shiri Nabiollah 
Published: January 2024

AbstractAn adaptive neuro‐fuzzy inference system is presented which is optimized by a genetic algorithm to classify normal and abnormal brain tumours. The classifier is fast and simple, named genetic algorithm‐adaptive neuro‐fuzzy inference system, and the determined learning rules minimize its error and improve its accuracy. The presented system follows five steps including preprocessing, morphological operation, feature extraction, feature selection, and classification. Morphological operators segment the abnormal regions and calculate the tumour area. The statistical features and the grey‐level co‐occurrence matrix are employed for feature extraction. Magnetic resonance images are considered and 12 statistical features are extracted, then the genetic algorithm‐based selection technique helps to select features and reduce the extracted features and improves the accuracy and decision time. So, the high dimensionality and the computational complexity of the adaptive neuro‐fuzzy inference system are reduced, and the classifier decides more efficiently. The input data are the figshare brain tumour dataset with 670 abnormal and 670 normal magnetic resonance images, and the classifier requires 10.788 s for classification. The efficient performance of the genetic algorithm‐adaptive neuro‐fuzzy inference system is confirmed by the accuracy of 99.85%, sensitivity of 99.7%, specificity of 100%, precision of 100%, and mean square error of 0.0027.