Miracle-dz/UniFAR-FTUs huggingface dataset:
Contrastive Learning for Graph-Based Vessel Trajectory Similarity Computation

With the increasing popularity of automatic identification system AIS devices, mining latent vessel motion patterns from AIS data has become a hot topic in water transportation research. Trajectory similarity computation is a fundamental issue to many maritime applications such as trajectory clustering, prediction, and anomaly detection. However, current non-learning-based methods face performance and efficiency issues, while learning-based methods are limited by the lack of labeled sample and explicit spatial modeling, making it difficult to achieve optimal performance. To address the above issues, we propose CLAIS, a contrastive learning framework for graph-based vessel trajectory similarity computation. A combined parameterized trajectory augmentation scheme is proposed to generate similar trajectory sample pairs and a constructed spatial graph of the study region is pretrained to help model the input trajectory graph. A graph neural network encoder is used to extract spatial dependency from the trajectory graph to learn better trajectory representations. Finally, a contrastive loss function is used to train the model in an unsupervised manner. We also propose an improved experiment and three related metrics and conduct extensive experiments to evaluate the performance of the proposed framework. The results validate the efficacy of the proposed framework in trajectory similarity calculation.
TROPICAL CYCLONE GENESIS EFFICIENCY:MID-LEVEL VERSUS BOTTOM VORTEX

Cloud resolving Weather Research and Forecasting(WRF)model simulations are used to investigate tropical cyclone(TC)genesis efficiency in an environment with a near bottom vortex(EBV)and an environment with a mid-level vortex(EMV). Sensitivity experiments show that the genesis timing depends greatly on initial vorticity vertical profiles.The larger the initial column integrated absolute vorticity,the greater the genesis efficiency is.Given the same column integrated absolute vorticity,a bottom vortex has higher genesis efficiency than a mid-level vortex.A common feature among these experiments is the formation of a mid-level vorticity maximum prior to TC genesis irrespective where the initial vorticity maximum locates.Both the EMV and EBV scenarios share the following development characteristics:1)a transition from non-organized cumulus-scale(~5 km)convective cells into an organized meso-vortex-scale(~50 to 100 km)system through upscale cascade processes,2)the establishment of a nearly saturated air column prior to a rapid drop of the central minimum pressure,and 3)a multiple convective-stratiform phase transition.A genesis efficiency index(GEI)is formulated that includes the following factors:initial column integrated absolute vorticity,vorticity at top of the boundary layer and vertically integrated relative humidity.The calculated GEI reflects well the simulated genesis efficiency and thus may be used to estimate how fast a tropical disturbance develops into a TC.
Mesoporous polydopamine delivery system for intelligent drug release and photothermal-enhanced chemodynamic therapy using MnO2 as gatekeeper

Abstract The non-specific leakage of drugs from nanocarriers seriously weakened the safety and efficacy of chemotherapy, and it was very critical of constructing tumor microenvironment (TME)-responsive delivery nanocarriers, achieving the modulation release of drugs. Herein, using manganese dioxide (MnO2) as gatekeeper, an intelligent nanoplatform based on mesoporous polydopamine (MPDA) was developed to deliver doxorubicin (DOX), by which the DOX release was precisely controlled, and simultaneously the photothermal therapy (PTT) and chemodynamic therapy (CDT) were realized. In normal physiological environment, the stable MnO2 shell effectively avoided the leakage of DOX. However, in TME, the overexpressed glutathione (GSH) degraded MnO2 shell, which caused the DOX release. Moreover, the photothermal effect of MPDA and the Fenton-like reaction of the generated Mn2+ further accelerated the cell death. Thus, the developed MPDA-DOX@MnO2 nanoplatform can intelligently modulate the release of DOX, and the combined CDT/PTT/chemotherapy possessed high-safety and high-efficacy against tumors.
Classification of Hyperspectral Images Based on Multiclass Spatial–Spectral Generative Adversarial Networks

Generative adversarial networks (GANs) are famous for generating samples by training a generator and a discriminator via an adversarial procedure. For hyperspectral image classification, the collection of samples is always difficult. However, directly applying GAN to hyperspectral image classification exists two problems. One is that the generated samples lack discriminative information. Meanwhile, the discriminator has no discriminative ability for multiclassification. Another is that spatial and spectral information requires to be considered in hyperspectral image classification simultaneously. To address these problems, a novel multiclass spatial–spectral GAN (MSGAN) method is proposed. In MSGAN, two generators are devised to generate the samples containing spatial and spectral information, respectively, and the discriminator is devised to extract joint spatial–spectral features and output multiclass probabilities. Moreover, novel adversarial objectives for multiclass are defined. The discriminator is devised to predict training samples belonging to true classes and generated samples belonging to all the classes with the same probability. The generators are devised to make the discriminator mistake. By adversarial learning between the discriminator and generators, the classification performance of the discriminator is promoted with the assistance of discriminative generated samples. Experimental results on hyperspectral images demonstrate that the proposed method achieves encouraging classification performance compared with several state-of-the-art methods, especially with the limited training samples.
Racialised capitalism, decoloniality and the university: an exploration of the colour line and colonial unreason in higher education

Over the last decade, there has been an increase in calls to address important questions on race and decolonisation within the university, administratively, pedagogically, and socially. This study investigates the relationship between the university, the coloniser, and the colonised during the colonial era and the afterlife. It aims to demonstrate that the university has made the act of abstraction and theorisation central across disciplines in a way that shears theoretical principles from the historical contexts they emerge from, distancing them from the purposes, people, and interests they were meant to serve, as well as the populations they were meant to dispossess and disempower. The study provides a conceptual framework for deconstructive analysis of the university’s pedagogical operations and societal function with the view to elucidate the university’s colonial and racial blind spots, notably, with a reliance on disciplinary narratives from development, international relations, and international law to offer tentative answers to the questions of decolonial praxis, the decolonial scholar, and coloniality in the contemporary university.
Screening and Stability Analysis of Reference Genes for Gene Expression Normalization in Hybrid Yellow Catfish (Pelteobagrus fulvidraco ♀ × Pelteobagrus vachelli ♂) Fed Diets Containing Different Soybean Meal Levels

In this study, we screened the expression stability of six reference genes (18S rRNA, β-actin, GAPDH, EF1a, B2M, and HPRT1) in hybrid yellow catfish (n = 6), considering the SBM levels, sampling time points, and different tissues. Four different statistical programs, BestKeeper, NormFinder, Genorm, and Delta Ct, combined with a method that comprehensively considered all results, were used to evaluate the expression stability of these reference genes systematically. The results showed that SBM levels significantly impacted the expression stability of most of the reference genes studied and that this impact was time-, dose-, and tissue-dependent. The expression stability of these six reference genes varied depending on tissue, sampling time point, and SBM dosage. Additionally, more variations were found among different tissues than among different SBM levels or sampling time points. Due to its high expression, 18S rRNA was excluded from the list of candidate reference genes. β-actin and GAPDH in the liver and β-actin, HPRT1 and EF1a in the intestine were the most stable reference genes when SBM levels were considered. HPRT1, and EF1a in tissues sampled at 2 W and EF1a and β-actin in tissues sampled at 4 and 6 W were proposed as two stable reference genes when different tissues were considered. When the sampling time points were considered, β-actin, EF1a, and HPRT1 were the top three stable reference genes in the intestine. In contrast, β-actin and B2M are the most stable reference genes in the liver. In summary, β-actin, EF1a, and HPRT1 were the more stable reference genes in this study. The stability of reference genes depends on the tissues, sampling time points, and SBM diet levels in hybrid yellow catfish. Therefore, attention should be paid to these factors before selecting suitable reference genes for normalizing the target genes.
Cell–Cell and Cell–Matrix Interactions at the Presumptive Stem Cell Niche of the Chick Corneal Limbus

(1) Background: Owing to its ready availability and ease of acquisition, developing chick corneal tissue has long been used for research purposes. Here, we seek to ascertain the three-dimensional microanatomy and spatiotemporal interrelationships of the cells (epithelial and stromal), extracellular matrix, and vasculature at the corneo-scleral limbus as the site of the corneal stem cell niche of the chicken eye. (2) Methods: The limbus of developing (i.e., embryonic days (E) 16 and 18, just prior to hatch) and mature chicken eyes was imaged using scanning electron microscopy (SEM), transmission electron microscopy (TEM), and the volume electron microscopy technique, serial-block face SEM (SBF-SEM), the latter technique allowing us to generate three-dimensional reconstructions from data sets of up to 1000 serial images; (3) Results: Data revealed that miniature limbal undulations of the embryonic basement membrane, akin to Palisades of Vogt (PoV), matured into distinct invaginations of epithelial cells that extended proximally into a vascularized limbal stroma. Basal limbal epithelial cells, moreover, occasionally exhibited a high nuclear:cytoplasmic ratio, which is a characteristic feature of stem cells. SBF-SEM identified direct cell–cell associations between corneal epithelial and stromal cells at the base of structures akin to limbal crypts (LCs), with cord-like projections of extracellular matrix extending from the basal epithelial lamina into the subjacent stroma, where they made direct contact with stomal cells in the immature limbus. (4) Conclusion: Similarities with human tissue suggest that the corneal limbus of the mature chicken eye is likely the site of a corneal stem cell niche. The ability to study embryonic corneas pre-hatch, where we see characteristic niche-like features emerge, thus provides an opportunity to chart the development of the limbal stem cell niche of the cornea.
Mutated TP53 in Circulating Tumor DNA as a Risk Level Biomarker in Head and Neck Squamous Cell Carcinoma Patients

Circulating tumor DNA (ctDNA) has been suggested as a surrogate biomarker for early detection of cancer recurrence. We aimed to explore the utility of ctDNA as a noninvasive prognostic biomarker in newly diagnosed head and neck squamous cell carcinoma (HNSCC) patients. Seventy HNSCC specimens were analysed for the detection of TP53 genetic alterations utilizing next-generation sequencing (NGS). TP53 mutations were revealed in 55 (79%). Upon detection of a significant TP53 mutation, circulating cell-free DNA was scrutinized for the presence of the tumor-specific mutation. ctDNA was identified at a minimal allele frequency of 0.08% in 21 out of 30 processed plasma samples. Detectable ctDNA correlated with regional spread (N stage ≥ 1, p = 0.011) and poorer 5-year progression-free survival (20%, 95% CI 10.9 to 28.9, p = 0.034). The high-risk worst pattern of invasion (WPOI grade 4–5) and deep invasion were frequently found in patients whose ctDNA was detected (p = 0.087 and p = 0.072, respectively). Detecting mutated TP53 ctDNA was associated with poor progression-free survival and regional metastases, indicating its potential role as a prognostic biomarker. However, ctDNA detectability in early-stage disease and the mechanisms modulating its release into the bloodstream must be further elucidated.
Proximal and mineral composition of native fish species from Amazonas, Brazil

For decades, researches were developed about the diversity of fishes in the Amazon basin and their consumption by the people. In this context, an important gap identified was a lack of information about the nutritional composition of some of the main Amazon fish species consumed and traded. Front this, the objective of this study was to evaluate the chemical composition and mineral content of filets from 10 fish species with the highest landing volume in Amazonas State. The fish species selected were curimatã, jaraqui, mapará, matrinxã, pacu, piramutaba, sardinha, surubim, tambaqui and tucunaré. Were collected 20 samples (fishes) from each species according to the hydrological cycles of the region (20 samples in the flood and 20 samples in drought). Ten fish samples were processed to determine the proximal composition and 10 fish samples were used to determine mineral content (macro and micro minerals). The proximal composition of fish species analysed varied widely between species and seasons, with an emphasis on moisture and lipid content. Fishes in the flood season presented higher content of nutrients than drought season. This result also was observed in the minerals profile, where fishes in the flood season presented the highest (p < 0.05) minerals content.
Non‐native mammals are weak candidates to substitute ecological function of native avian seed dispersers in an island ecosystem

Although prominent examples exist of non‐native species causing substantial ecological harm, many have neutral or positive effects, including filling surrogate roles once performed by extinct native organisms. We tested the ecological roles of two non‐native mammals as seed dispersers or seed predators in Guåhan, which, due to invasive brown tree snakes (Boiga irregularis), is devoid of native seed dispersers–birds and bats. We conducted feeding trials with captive rats (Rattus spp.), which are present but uncommon due to predation by snakes, and pigs (Sus scrofa), which are abundant. We examined if and how they interacted with common forest fruits. We then compared how any gut‐passed or animal‐handled seeds germinated compared to seeds left in whole fruit or depulped seeds. Rats and pigs interacted with most of the fruits and seeds (>80%) that they were fed. Of those, most seeds were destroyed—78% for rats and 90% for pigs, across both native and non‐native plant species. Compared to seeds germinating within whole fruits, rats improved germination of the seeds that they handled without ingesting, while pigs diminished the germination of seeds that they handled. The small percentage of seeds (approximately 1.5% for rats and 5% for pigs) that survived gut passage germinated in higher proportions than those in whole fruits. Percentages of seed survival to germination are lower than found in similar studies with native avian frugivores. Our results indicate that pigs and rats have mixed effects on seeds, but are not suitable surrogates for native seed dispersers.
Coordinating Multi-Energy Microgrids for Integrated Energy System Resilience: A Multi-Task Learning Approach

High-impact and low-probability events have occurred more frequently than before, which can seriously damage energy supply infrastructures. As localized small energy systems, multi-energy microgrids (MEMGs) can provide a viable solution for the system-wise load restoration of integrated energy systems (IESs), due to their enhanced flexibility and controllability. However, existing literature tends to realize MEMGs as corrective response rather than load restoration resource after extreme events, which cannot fully exploit the benefits of multi-MEMGs on IES resilience. This article introduces a decentralized operating paradigm for the real-time coordination of local multi-MEMGs towards system-wise IES load restoration, while a novel topology-aware multi-task reinforcement learning method with soft modularization is proposed to solve it. The multi-task learning framework enables MEMGs to simultaneously learn scheduling decisions across different network topologies and better adapt to unanticipated contingencies. Additionally, to avoid insecure MEMG operations, a physics-informed safety layer is embedded on top of the multi-task learning framework for action corrections. Case studies have been conducted on two IESs (33-bus power, 20-node gas, and 20-node heat network as well as 69-bus power, 40-node gas, and 62-node heat network) to evaluate the effectiveness of the proposed method in enabling effective coordination among multi-MEMGs towards system-wise IES load restoration.
Solo tourism: exploration and conceptualization – a semi-supervised machine learning approach

ABSTRACT This study aims at understanding and conceptualizing solo tourism. By using a semi-supervised machine learning approach and scrutinizing 27,208 solo tourist tweets. Based on implicit self-theory we capture solo consumers’ self-development and self-discovery. We provide an all-inclusive slow tourism conceptualization and show that the solo tourism framework is a three-stage journey of self-discovery. This study not only provides tourism scholars and providers with an evidence-based solo tourism conceptualization, but also with a marketing, psychological, and operation tool to manage this segment.
Electric and dielectric properties of CdSO4-doped borate glasses

A system of (100-x)B2O3⋅xCdSO4glasses (0 [Formula: see text]x [Formula: see text] 40) is set by the ordinary quenching method. Density ([Formula: see text]), molar volume (V[Formula: see text]) and oxygen ion density (N[Formula: see text]) are found to increase with the increase of CdSO4in the samples. The dc conductivity ([Formula: see text]) and the ac conductivity ([Formula: see text]) are measured in the temperature range from 308 to 735 K. [Formula: see text] is found to follow the thermal activation Arrhenius relation with activation energies between 0.36 and 0.76 eV. Ac conductivity and the exponent factor (s) confirm that the CBH model is the origin of the conduction. The dielectric constant ([Formula: see text]) and loss ([Formula: see text]) are studied as a function of the temperature and frequency. The dielectric data are fitted according to the Cole–Cole equations. The values of [Formula: see text] parameter are found to vary between 0.2 and 0.58 which means that these glasses exhibit a wide distribution of relaxation times.
Handling Class Imbalance in Google Cluster Dataset Using a New Hybrid Sampling Approach

—Class imbalance is a classical problem in data mining, where the classes in a dataset have a disproportionate number of instances. Most machine learning tasks fail to work properly with an imbalanced dataset. There exist various approaches to balance a dataset, but suffer from issues such as overfitting and information loss. This manuscript proposes a novel and improved cluster-based undersampling method for handling two and multi-class imbalanced dataset. Ensemble learning algorithm integrated with the pre-processing technique is used to address the class imbalance problem. The proposed approach is tested using a publicly available imbalanced Google cluster dataset, in case of imbalanced dataset the F1-score value for each class has to be checked, it is observed that the existing approaches F1-score for class 0 was not good, whereas the proposed algorithm had a balanced F1-score of 0.97 for class 0 and 0.96 for class 1. There is an improvement in F1-score of about 2% compared to the existing technique. Similarly for multi-class problem the proposed novel algorithm gave balanced AUC values of 0.87, 0.83 and 0.97 for class 0, class 1 and class 2 respectively.
Public Usage of E-Government in EU Countries: Are There Any Consequences for Tax Evasion?

Due to the processes of digitalization and automation, the e-Government has become an essential tool of public administration. The paper deals with the problem of e-Government usage by the public and its potential connection to tax evasion. The analysis is based on available secondary panel and cross-sectional data on the level of EU countries in the period 2008 to 2021. We compare the situation in the countries and classify them into homogenous clusters based on the overall public usage of e-Government. Principal component analysis and cluster analysis have been used as tools for dimension reduction and clustering. Moreover, we also found evidence of a potential relationship between the usage of e-Government and tax evasion. The provision of online information and services by the government to its citizens as well as online communication with public authorities are related to the lower level of tax evasion in the country. Hence, public authorities should support e-Government usage and e-filing systems to fight against tax evasion.
PROPERTY VALUE ASSESSMENT USING ARTIFICIAL NEURAL NETWORKS, HEDONIC REGRESSION AND NEAREST NEIGHBORS REGRESSION METHODS

Bu calismada hedonik regresyon, en yakin komsu regresyon ve yapay sinir aglari metotlari Turkiye’nin Adana iline ait gercek ve guncel bir veri seti uzerinde uygulanmistir. Geleneksel olarak, ev fiyatlarinin tahmininde hedonic regresyon metotlari kullanilmaktadir. Ev fiyatlarini etkileyen faktorler arasindaki iliskilerin yapisinin genel olarak dogrusal olmamasi nedeniyle bazi alternatif metotlara ihtiyac duyulmaktadir. En yakin komsuluk regresyon ve yapay sinir aglari hem esnek hem de dogrusal olmayan uyumlar sunmaktadir. Klasik hedonic regresyon yaklasimi ve dogrusal olmayan alternatifleri karma yapida ki bir veri kumesine uygulanmis ve hata kareler ortalamasi, belirleyicilik katsayisi (R kare) ve ortalama mutlak hatayi iceren bazi performans olcutlerine dayanarak karsilastirilmistir.En yakin komsu ve yapay sinir aglari icin uygun model parametrelerini belirlemek icin capraz gecerlilik metodu kullanilmistir.Sonuclara gore, yapay sinir aglari diger metotlarla karsilastirildiginda tum olculere gore daha iyi bulunmustur.Ayrica en yakin komsu metodu hedonik regresyon metodundan daha dusuk performansli olmasina ragmen makul sonuclar saglamaktadir. Yapay sinir aglarinin ev fiyatlarinin tahmininde guclu bir arac oldugu gorulmustur.