Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Fast Local Community Detection Algorithm Using the Number of Common Neighbours

Recent years have witnessed the rapid growth of social network services. Consequently, the problems in this area have become more complex. Community detection is one of the most important problems in social networks. A good community can be defined as a group of vertices that are highly connected and loosely connected to the vertices outside the community. Regarding the fact that social networks are huge in size, having complete information of the whole network is almost impossible. As a result, the problem of local community detection has become more popular in recent years. In this paper, a new fast local community detection algorithm is proposed using a new metric, called P. The proposed algorithm includes three different steps in which relevant nodes are added in the first step and irrelevant nodes are removed in the second and third steps. Regarding the experimental results, it is shown that the proposed algorithm outperforms state-of-the-art local community detection algorithms. Also, the proposed algorithm is considerably faster than other compared algorithms.
Diptera and Drosophila Karyotype Databases: A Useful Dataset to Guide Evolutionary and Genomic Studies

Karyotypes and chromosome data have been widely used in many subfields of biology over the last century. Unfortunately, this data is largely scattered among hundreds of articles, books, and theses, many of which are only available behind paywalls. This creates a barrier to new researchers wishing to use this data, especially those from smaller institutions or in countries lacking institutional access to much of the scientific literature. We solved this problem by building two datasets for true flies (Order: Diptera and one specific to Drosophila), These datasets are available via a public interactive database that allows users to explore, visualize and download all data. The Diptera karyotype databases currently contain a total of 3,474 karyotype records from 538 publications. Synthesizing this data, we show several groups are of particular interest for future investigations by whole genome sequencing.
Novel SKIP Features for LIDAR Odometry and Mappings

This work proposes a refined feature extractor for the LiDAR Odometry and Mapping (LOAM) algorithm often rely on features extracted from point clouds. This paper proposes a novel detection algorithm SKIP-3D (SKeleton Interest Point) for extraction of features namely edges and planner patches from multi-layer LiDAR scan. SKIP-3D make use of the organization of LiDAR measurements to search for salient points in each layer through an iterative bottum-up procedure. In the process it removes the low curvature points to find edges and classifies the points from point clouds acquired from different view points are associated and used for their alignment. Experimental results showed that Fast LiDAR Odometry and Mapping (F-LOAM) based on SKIP-3D feature extractor performs at least better than original F-LOAM feature extractor.
Speech Localization at Low Bitrates in Wireless Acoustics Sensor Networks

The use of speech source localization (SSL) and its applications offer great possibilities for the design of speaker local positioning systems with wireless acoustic sensor networks (WASNs). Recent works have shown that data-driven front-ends can outperform traditional algorithms for SSL when trained to work in specific domains, depending on factors like reverberation and noise levels. However, such localization models consider localization directly from raw sensor observations, without consideration for transmission losses in WASNs. In contrast, when sensors reside in separate real-life devices, we need to quantize, encode and transmit sensor data, decreasing the performance of localization, especially when the transmission bitrate is low. In this work, we investigate the effect of low bitrate transmission on a Direction of Arrival (DoA) estimator. We analyze a deep neural network (DNN) based framework performance as a function of the audio encoding bitrate for compressed signals by employing recent communication codecs including PyAWNeS, Opus, EVS, and Lyra. Experimental results show that training the DNN on input encoded with the PyAWNeS codec at 16.4 kB/s can improve the accuracy significantly, and up to 50% of accuracy degradation at a low bitrate for almost all codecs can be recovered. Our results further show that for the best accuracy of the trained model when one of the two channels can be encoded with a bitrate higher than 32 kB/s, it is optimal to have the raw data for the second channel. However, for a lower bitrate, it is preferable to similarly encode the two channels. More importantly, for practical applications, a more generalized model trained with a randomly selected codec for each channel, shows a large accuracy gain when at least one of the two channels is encoded with PyAWNeS.
Strawberry Quality Classification Utilizing Convolutional Neural Network

Strawberry quality has been a crucial factor when it comes to consumer satisfaction. Having quality and cost-efficient strawberries would increase consumer satisfaction while increasing sales from the merchants’ perspective. As such, being able to classify strawberries into the desirable and undesirable categories would aid small businesses and consumers in determining whether the strawberries sold and bought are desirable based on key indicators such as shape and color. To address that, this study was conducted with the use of convolutional neural networks. The strawberry datasets used are a combination of a pre-classified dataset from another study and a dataset of images photographed solely for the purpose of this study. The images are classified as desirable and undesirable wherein 350 images of each set are used for training, 200 images for validation, and 100 images for testing. The generated CNN model is simulated using epochs=15 and batch size=8. The resulting CNN model has a training accuracy=98.41%, a validation accuracy=92.75%, and a testing accuracy=100% which makes the model efficient in classifying strawberries into the desirable and undesirable categories.
Development and Cross-Validation of a Predictive Equation for Fat-Free Mass in Brazilian Adolescents by Bioelectrical Impedance

The bioelectrical impedance analysis (BIA) is one of the most commonly used techniques for assessing body composition in a clinical setting and in field approaches, as it has the advantages of easy application, fast, and non-invasive, in addition to its relatively low cost. However, the available predictive equations need to be valid for the evaluated subjects. The aim of this study was to verify the validity of several published BIA equations in estimating fat-free mass (FFM) among Brazilian adolescents, in addition to developing and cross-validating a BIA equation to estimate FFM appropriate for Brazilian adolescents. This is a cross-sectional study with 257 adolescents (128 girls) aged 10–19 years, randomly divided into two groups, namely, development (n = 172) and cross-validation (n = 85). The standard technique for assessing FFM was dual X-ray absorptiometry (DXA). The paired t-test, multiple regression, and the Bland-Altman plots were used to test the validity of the proposed models and to perform cross-validation of the model. The equation derived in this study was as follows: FFM = −17.189 + 0.498 (Height2/Resistance) + 0.226 Weight + 0.071 Reactance − 2.378 Sex + 0.097 Height + 0.222 Age; r2 = 0.92; standard error of the estimate = 2.49 kg; the new equation for FFM showed better agreement when compared with that of the equations developed in other countries. In conclusion, the newly developed equations provide a valid FFM estimation and are recommended for Brazilian adolescents with similar characteristics.
Effects of PEF-Assisted Freeze-Drying on Protein Quality, Microstructure, and Digestibility in Chilean Abalone “Loco” (Concholepas concholepas) Mollusk

The purpose of this study was to apply different pulsed electric field (PEF) conditions as a pretreatment to the freeze-drying (FD) process of Chilean abalone and to assess its effects on protein quality, microstructure, and digestibility of the freeze-dried product. The treatments PEF (0.5, 1.0, and 2.0 kV cm−1) and cooking (CO) were applied at 100°C × 15 min. Then, their performances were subjected to a FD process. PEF + CO pretreated freeze-dried samples showed shorter process times than freeze-dried control samples without PEF + CO, where the treatment PEF at 2.0 kV cm−1 reached the shortest time. In addition, the abovementioned samples presented the best textural parameters but a low protein content. The thermal properties indicate a total denaturation of the proteins, where the amide I region presented greater mobility in the sample pretreated with an electric field of 2.0 kV cm−1. The assay for digestibility shows better hydrolysis for the 2.0 kV cm−1 PEF sample and has a higher Computer-Protein Efficiency Ratio (C-PER). Thereby, variations in thermal behavior and physicochemical parameters in comparison to combined PEF + CO pretreatments were observed. In addition, high protein quality and digestibility of pretreated freeze-dried Chilean abalones were maintained to the desired properties (texture and C-PER) and conditions (FD time).
Hyperoxygenation During Mid-Neurogenesis Accelerates Cortical Development in the Fetal Mouse Brain

Oxygen tension is well-known to affect cortical development. Fetal brain hyperoxygenation during mid-neurogenesis in mice (embryonic stage E14.5. to E16.5) increases brain size evoked through an increase of neuroprecursor cells. Nevertheless, it is unknown whether these effects can lead to persistent morphological changes within the highly orchestrated brain development. To shed light on this, we used our model of controlled fetal brain hyperoxygenation in time-pregnant C57BL/6J mice housed in a chamber with 75% atmospheric oxygen from E14.5 to E16.5 and analyzed the brains from E14.5, E16.5, P0.5, and P3.5 mouse embryos and pups via immunofluorescence staining. Mid-neurogenesis hyperoxygenation led to an acceleration of cortical development by temporal expansion of the cortical plate with increased NeuN+ neuron counts in hyperoxic brains only until birth. More specifically, the number of Ctip2+ cortical layer 5 (L5) neurons was increased at E16.5 and at birth in hyperoxic brains but normalized in the early postnatal stage (P3.5). The absence of cleaved caspase 3 within the extended Ctip2+ L5 cell population largely excluded apoptosis as a major compensatory mechanism. Timed BrdU/EdU analyses likewise rule out a feedback mechanism. The normalization was, on the contrary, accompanied by an increase of active microglia within L5 targeting Ctip2+ neurons without any signs of apoptosis. Together, hyperoxygenation during mid-neurogenesis phase of fetal brain development provoked a specific transient overshoot of cortical L5 neurons leading to an accelerated cortical development without detectable persistent changes. These observations provide insight into cortical and L5 brain development.
The APOEε3/ε4 Genotype Drives Distinct Gene Signatures in the Cortex of Young Mice

Introduction Restrictions on existing APOE mouse models have impacted research toward understanding the strongest genetic risk factor contributing to Alzheimer’s disease (AD) and dementia, APOEε4, by hindering observation of a key, common genotype in humans – APOEε3/ε4. Human studies are typically underpowered to address APOEε4 allele risk as the APOEε4/ε4 genotype is rare, which leaves human and mouse research unsupported to evaluate the APOEε3/ε4 genotype on molecular and pathological risk for AD and dementia. Methods As a part of MODEL-AD, we created and validated new versions of humanized APOEε3/ε3 and APOEε4/ε4 mouse strains that, due to unrestricted breeding, allow for the evaluation of the APOEε3/ε4 genotype. As biometric measures are often translatable between mouse and human, we profiled circulating lipid concentrations. We also performed transcriptional profiling of the cerebral cortex at 2 and 4 months (mos), comparing APOEε3/ε4 and APOEε4/ε4 to the reference APOEε3/ε3 using linear modeling and WGCNA. Further, APOE mice were exercised and compared to litter-matched sedentary controls, to evaluate the interaction between APOEε4 and exercise at a young age. Results Expression of human APOE isoforms were confirmed in APOEε3/ε3, APOEε3/ε4 and APOEε4/ε4 mouse brains. At two mos, cholesterol composition was influenced by sex, but not APOE genotype. Results show that the APOEε3/ε4 and APOEε4/ε4 genotype exert differential effects on cortical gene expression. APOEε3/ε4 uniquely impacts ‘hormone regulation’ and ‘insulin signaling,’ terms absent in APOEε4/ε4 data. At four mos, cholesterol and triglyceride levels were affected by sex and activity, with only triglyceride levels influenced by APOE genotype. Linear modeling revealed APOEε3/ε4, but not APOEε4/ε4, affected ‘extracellular matrix’ and ‘blood coagulation’ related terms. We confirmed these results using WGCNA, indicating robust, yet subtle, transcriptional patterns. While there was little evidence of APOE genotype by exercise interaction on the cortical transcriptome at this young age, running was predicted to affect myelination and gliogenesis, independent of APOE genotype with few APOE genotype-specific affects identified. Discussion APOEε4 allele dosage-specific effects were observed in circulating lipid levels and cortical transcriptional profiles. Future studies are needed to establish how these data may contribute to therapeutic development in APOEε3/ε4 and APOEε4/ε4 dementia patients.
Linking Alzheimer’s Disease and Type 2 Diabetes: Characterization and Inhibition of Cytotoxic Aβ and IAPP Hetero-Aggregates

The cytotoxic self-aggregation of β-amyloid (Aβ) peptide and islet amyloid polypeptide (IAPP) is implicated in the pathogenesis of Alzheimer’s disease (AD) and Type 2 diabetes (T2D), respectively. Increasing evidence, particularly the co-deposition of Aβ and IAPP in both brain and pancreatic tissues, suggests that Aβ and IAPP cross-interaction may be responsible for a pathological link between AD and T2D. Here, we examined the nature of IAPP-Aβ40 co-aggregation and its inhibition by small molecules. In specific, we characterized the kinetic profiles, morphologies, secondary structures and toxicities of IAPP-Aβ40 hetero-assemblies and compared them to those formed by their homo-assemblies. We demonstrated that monomeric IAPP and Aβ40 form stable hetero-dimers and hetero-assemblies that further aggregate into β-sheet-rich hetero-aggregates that are toxic (cell viability <50%) to both PC-12 cells, a neuronal cell model, and RIN-m5F cells, a pancreatic cell model for β-cells. We then selected polyphenolic candidates to inhibit IAPP or Aβ40 self-aggregation and examined the inhibitory effect of the most potent candidate on IAPP-Aβ40 co-aggregation. We demonstrated that epigallocatechin gallate (EGCG) form inter-molecular hydrogen bonds with each of IAPP and Aβ40. We also showed that EGCG reduced hetero-aggregate formation and resulted in lower β-sheets content and higher unordered structures in IAPP-Aβ40-EGCG samples. Importantly, we showed that EGCG is highly effective in reducing the toxicity of IAPP-Aβ40 hetero-aggregates on both cell models, specifically at concentrations that are equivalent to or are 2.5-fold higher than the mixed peptide concentrations. To the best of our knowledge, this is the first study to report the inhibition of IAPP-Aβ40 co-aggregation by small molecules. We conclude that EGCG is a promising candidate to prevent co-aggregation and cytotoxicity of IAPP-Aβ40, which in turn, contribute to the pathological link between AD and T2D.
Adaptation to an Intracellular Lifestyle by a Nitrogen-Fixing, Heterocyst-Forming Cyanobacterial Endosymbiont of a Diatom

The symbiosis between the diatom Hemiaulus hauckii and the heterocyst-forming cyanobacterium Richelia intracellularis makes an important contribution to new production in the world’s oceans, but its study is limited by short-term survival in the laboratory. In this symbiosis, R. intracellularis fixes atmospheric dinitrogen in the heterocyst and provides H. hauckii with fixed nitrogen. Here, we conducted an electron microscopy study of H. hauckii and found that the filaments of the R. intracellularis symbiont, typically composed of one terminal heterocyst and three or four vegetative cells, are located in the diatom’s cytoplasm not enclosed by a host membrane. A second prokaryotic cell was also detected in the cytoplasm of H. hauckii, but observations were infrequent. The heterocysts of R. intracellularis differ from those of free-living heterocyst-forming cyanobacteria in that the specific components of the heterocyst envelope seem to be located in the periplasmic space instead of outside the outer membrane. This specialized arrangement of the heterocyst envelope and a possible association of the cyanobacterium with oxygen-respiring mitochondria may be important for protection of the nitrogen-fixing enzyme, nitrogenase, from photosynthetically produced oxygen. The cell envelope of the vegetative cells of R. intracellularis contained numerous membrane vesicles that resemble the outer-inner membrane vesicles of Gram-negative bacteria. These vesicles can export cytoplasmic material from the bacterial cell and, therefore, may represent a vehicle for transfer of fixed nitrogen from R. intracellularis to the diatom’s cytoplasm. The specific morphological features of R. intracellularis described here, together with its known streamlined genome, likely represent specific adaptations of this cyanobacterium to an intracellular lifestyle.
Fault Detection of Electric Motor Coil by YOLOv3 with Spatial Attention

Object detection has been widely applied to the visual inspection of factory products. Moreover, because the detection model must be improved based on the object and problem set, the model parameters must be fine-tuned and new feature extractors must be introduced. We present an automatic fault detection method for electric motor coils based on deep learning in this manuscript. To the best of our knowledge, this is the first deep learning approach for fault detection of electric motor coil. Furthermore, we combine the spatial attention mechanism with the object detection method YOLOv3 to highlight the location information of the defective part in the image. We built a real-time detection system so that anyone could use the detection model we formed.
Microstructural and Genetic Insights Into the Formation of the “Winter Diffusion Layer” in Japanese Pearl Oyster Pinctada fucata and Its Relation to Environmental Temperature Changes

Phenotypic plasticity in molluscan shell microstructures may be related to environmental changes. The “winter diffusion layer,” a shell microstructure of the Japanese pearl oyster Pinctada fucata, is an example of this phenomenon. In this study, we used P. fucata specimens with shared genetic background to evaluate the seasonal plasticity of shell microstructures, at molecular level. To detect the seasonal changes in shell microstructure and mineral composition, shells of multiple individuals were periodically collected and analyzed using scanning electron microscopy and Raman spectrophotometry. Our observations of the winter diffusion layer revealed that this irregular shell layer, located between the outer and middle shell layers, had a sphenoid shape in radial section. This distinct shape might be caused by the internal extension of the outer shell layer resulting from growth halts. The winter diffusion layer could be distinguished from the calcitic outer shell layer by its aragonitic components and microstructures. Moreover, the components of the winter diffusion layer were irregular simple prismatic (the outer and inner sublayers) and homogeneous structures (the middle sublayer). This irregular formation occurred until April, when the animals resumed their “normal” shell formation after hibernation. To check for a correlation between gene expression and the changes in microstructures, we conducted qPCR of seven major biomineralization-related shell matrix protein-coding genes (aspein, prismalin-14, msi7, msi60, nacrein, n16, and n19) in the shell-forming mantle tissue. Tissue samples were collected from the mantle edge (tissue secreting the outer shell layer) and mantle pallium (where the middle shell layer is constructed) of the same individuals used for microstructural observation and mineral identification that were collected in January (winter growth break period), April (irregular shell formation period), and August (normal shell formation period). Statistically significant differences in gene expression levels were observed between mantle edge and mantle pallium, but no seasonal differences were detected in the seasonal expression patterns of these genes. These results suggest that the formation of the irregular shell layer in P. fucata is caused by a currently unknown genetic mechanism unrelated to the genes targeted in the present study. Further studies using big data (transcriptomics and manipulation of gene expression) are required to answer the questions herein raised. Nevertheless, the results herein presented are essential to unravel the intriguing mystery of the formation of the winter diffusion layer, which may allow us to understand how marine mollusks adapt or acclimate to climate changes.
Mechanical Ventilation in Pediatric and Neonatal Patients

Pediatric acute respiratory distress syndrome (PARDS) remains a significant cause of morbidity and mortality, with mortality rates as high as 50% in children with severe PARDS. Despite this, pediatric lung injury and mechanical ventilation has been poorly studied, with the majority of investigations being observational or retrospective and with only a few randomized controlled trials to guide intensivists. The most recent and universally accepted guidelines for pediatric lung injury are based on consensus opinion rather than objective data. Therefore, most neonatal and pediatric mechanical ventilation practices have been arbitrarily adapted from adult protocols, neglecting the differences in lung pathophysiology, response to injury, and co-morbidities among the three groups. Low tidal volume ventilation has been generally accepted for pediatric patients, even in the absence of supporting evidence. No target tidal volume range has consistently been associated with outcomes, and compliance with delivering specific tidal volume ranges has been poor. Similarly, optimal PEEP has not been well-studied, with a general acceptance of higher levels of FiO2 and less aggressive PEEP titration as compared with adults. Other modes of ventilation including airway pressure release ventilation and high frequency ventilation have not been studied in a systematic fashion and there is too little evidence to recommend supporting or refraining from their use. There have been no consistent outcomes among studies in determining optimal modes or methods of setting them. In this review, the studies performed to date on mechanical ventilation strategies in neonatal and pediatric populations will be analyzed. There may not be a single optimal mechanical ventilation approach, where the best method may simply be one that allows for a personalized approach with settings adapted to the individual patient and disease pathophysiology. The challenges and barriers to conducting well-powered and robust multi-institutional studies will also be addressed, as well as reconsidering outcome measures and study design.