Miracle-dz/UniFAR-FTUs huggingface dataset:
Bioinformatics and Experimental Validation for Identifying Biomarkers Associated with AMG510 (Sotorasib) Resistance in KRASG12C-Mutated Lung Adenocarcinoma

The Kirsten rat sarcoma viral oncogene homolog (KRAS)G12C mutation is prevalent in lung adenocarcinoma (LUAD), driving tumor progression and indicating a poor prognosis. While the FDA-approved AMG510 (Sotorasib) initially demonstrated efficacy in treating KRASG12C-mutated LUAD, resistance emerged within months. Data from AMG510 treatment-resistant LUAD (GSE204753) and single-cell datasets (GSE149655) were analyzed. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were used to explore enriched signaling pathways, nomogram models were constructed, and transcription factors predicting resistance biomarkers were predicted. CIBERSORT identified immune cell subpopulations, and their association with resistance biomarkers was assessed through single-cell analysis. AMG510-resistant LUAD cells (H358-AR) were constructed, and proliferative changes were evaluated using a CCK-8 assay. Key molecules for AMG510 resistance, including SLC2A1, TLE1, FAM83A, HMGA2, FBXO44, and MTRNR2L12, were recognized. These molecules impacted multiple signaling pathways and the tumor microenvironment and were co-regulated by various transcription factors. Single-cell analysis revealed a dampening effect on immune cell function, with associations with programmed cell death ligand 1 (PDL1) expression, cytokine factors, and failure factors. The findings indicate that these newly identified biomarkers are linked to the abnormal expression of PDL1 and have the potential to induce resistance through immunosuppression. These results highlight the need for further research and therapeutic intervention to address this issue effectively.
Sexual dimorphism in morphometric characters of Mystus singaringan from Klawing River in Central Java, Indonesia: Strategic instruction for conservation development

Abstract. Pramono TB, Arfiati D, Widodo MS, Yanuhar U. 2019. Sexual dimorphism in morphometric characters of Mystus singaringan from Klawing River in Central Java, Indonesia: Strategic instruction for conservation development. Biodiversitas 20: 1133-1139. This study aims to determine the sexual dimorphism of Mystus singaringan (Senggaringan fish) based on morphometric characters. The measurement of 24 morphometric characters in 30 M. singaringan from Klawing River was carried out using a digital caliper (0.01 mm). Morphometric data of M. singaringan analyzed using t-test have showed significant difference in 12 morphometric characters between sexes, such as standard length, head height, distance of the tip of the muzzle to eyes, distance of the tip of the muzzle to adipose fin, height of dorsal fin, height of pectoral fin, basic length of adipose fin, height of adipose fin, maximum height, length of first nasal barbel, length of first mandibular barbel, and length of second mandibular barbel. Analysis of growth of morphometric characters shows that there is a linear relationship between all morphometric characters and total length. The type of growth of all morphometric characters in both male and female M. singaringan is negative allometric.
Some Geospatial Insights on Orange Grove Site Selection in a Portion of the Northern Citrus Belt of Mexico

This study aimed to delineate the most suitable areas for sustainable citrus production by integrating multi-criteria decision analysis, time-series remote sensing, and principal component analysis in a portion of the northern citrus belt of Mexico, particularly in the Rioverde Valley. Fourteen specific factors were grouped into four main factors, i.e., topography, soil, climate, and proximity to water sources, to carry out a multi-criteria decision analysis for classifying production areas according to suitability levels. To explore the effect of precipitation on land suitability for citrus production, we analyzed the historical record of annual precipitation estimated by processing 20-year NDVI daily data. The multi-criteria model was run for every precipitation year. The final map of land suitability was obtained by using the first component after principal component analysis on annual land suitability maps. The results indicate that approximately 30% of the study area is suitable for growing orange groves, with specific areas designated as suitable based on both mean annual precipitation (MAP) and principal component analysis (PCA) criteria, resulting in 84,415.7 ha and 95,485.5 ha of suitable land, respectively. The study highlighted the importance of remotely sensed data-based time-series precipitation in predicting potential land suitability for growing orange groves in semiarid lands. Our results may support decision-making processes for the effective land management of orange groves in the Mexico’s Rioverde region.
Design and Experimental Study of a Coupled U and L-Shape Negative Index Metamaterial for Aircraft Navigation Applications

The aircraft collision avoidance system (ACAS) is a surveillance system required in all airplanes to ensure a safe flight. To locate the presence of any surrounding aircraft that may pose a threat, the ACAS sequentially scans the fixed sectors (0° to 90°, 90° to 180°, 180° to 270°, and 270° to 360°) for a specified duration. As a result, ACAS necessitates a highly directional multi-element antenna capable of spanning the whole 360° azimuth plane. Over the past decade, studies on the performance enhancement of ACAS antennas have become increasingly prevalent due to the numerous limitations of the typical ACAS antenna, which include poor gain (<inline-formula> <tex-math notation="LaTeX">$3.6dB$ </tex-math></inline-formula>), larger size (<inline-formula> <tex-math notation="LaTeX">$>\lambda$ </tex-math></inline-formula>), high side-lobe level (<inline-formula> <tex-math notation="LaTeX">$-7dB$ </tex-math></inline-formula>), challenges with beam tuning, etc. The main focus of this study is to improve the gain and bandwidth (BW) of an ACAS antenna using the notion of MTM, hence a novel U and L-shaped compact negative index MTM structure is developed. Because the ACAS antenna broadcasts the signal in the entire azimuth region, the proposed MTM should be competent to endure its double negative behavior for all incident angles; thus, the MTM cell is evaluated for different incident angles ranging from 0° to 360° in the azimuth plane with a 60° offset, and for all incident angles, the proposed design exhibits DNG behavior in the required frequency spectrum. The effective medium ratio (EMR) of 12.86 at 1.06GHz demonstrates the efficacy and compactness of the proposed design. The proposed MTM cell is expanded as a <inline-formula> <tex-math notation="LaTeX">$5\times 4$ </tex-math></inline-formula> array, and placed as a superstrate at a fixed distance from the proposed ACAS antenna, and the MTM-loaded antenna outperforms the conventional antenna in terms of overall gain by 2.09dB and BW by 27.2MHz. Further, for the experimental verification, the MTM cell and its array structures are fabricated, and in both designs, the fabricated results correspond well with the simulated results.
Comprehensive Analysis of Phenolic Constituents, Biological Activities, and Derived Aroma Differences of Penthorum chinense Pursh Leaves after Processing into Green and Black Tea

Penthorum chinense Pursh (Penthoraceae) is a traditional herb used in Miao medical systems that is also processed into foods (e.g., tea products) in China. Different processing methods significantly affect the volatile compounds, phenolic constituents, and biological activities. This study aimed to produce P. chinense green tea leaves (GTL), black tea leaves (BTL), and untreated leaves (UL) to investigate differences in their flavor substances, functional components, antioxidant activity, alcohol dehydrogenase (ADH) activity, and acetaldehyde dehydrogenase (ALDH) activity. The results showed that 63, 56, and 56 volatile compounds were detected in UL, GTL, and BTL, respectively, of which 43 volatile compounds were identified as differential metabolites among them. The total phenolic content (97.13–179.34 mg GAE/g DW), flavonoid content (40.07–71.93 mg RE/g DW), and proanthocyanidin content (54.13–65.91 mg CE/g DW) exhibited similar trends, decreasing in the order of UL > BTL > GTL. Fourteen phenolic compounds were determined, of which gallic acid, (−)-epicatechin, and pinocembrin 7-O-glucoside showed a sharp decrease in content from UL to BTL, while the content of pinocembrin 7-O-(3″-O-galloy-4″, 6″-hexahydroxydiphenoyl)-glucoside and pinocembrin significantly increased. GTL showed better DPPH/ABTS·+ scavenging ability and ferric-reducing ability than UL. The ADH and ALDH activities decreased in the order of GTL > UL > BTL. Therefore, tea products made with P. chinense leaves contained an abundance of functional compounds and showed satisfactory antioxidant and hepatoprotective activities, which are recommended for daily consumption.
Multi-objective parametric synthesis of loss functions in neural networks with evolutionary algorithms

The loss function is a fundamental aspect of neural network training and by choosing a suitable one, better results can be achieved. In classification problems, the cross-entropy loss function is almost exclusively used. In this paper the loss function represented by Taylor's series which are optimized with multi-objective evolutionary algorithm. As results show the new loss function can be better than cross-entropy, however application of multi-objective algorithm does not bring an improvement in comparison with single-objective algorithm.
Phonetic encoding in utterance production: a review of open issues from 1989 to 2018

ABSTRACT Phonetic encoding refers to the mapping of an abstract linguistic code of the utterance into motor programmes which guide speech articulation. The encoding of speech gestures involves complex cognitive-motor planning, which has received limited attention in the psycholinguistic literature on language production relative to linguistic encoding processes. Here we will review some issues on phonetic encoding and the related empirical results by integrating evidence from psycholinguistic, phonetic, neuropsychological and neuroimaging studies from the last 30 years. In particular, we will focus on (i) the distinction between phonological and phonetic encoding, (ii) the nature and size of phonetic representations and (iii) the dynamics of phonetic encoding in the time-course of utterance planning. We will end up showing that the transformation of a linguistic code into motor programmes likely involves a larger proportion of the overall utterance planning time than acknowledged in current models and with many open questions for future research.
Characterization of Diagenetiforms in an Expanded Proteome of the Extinct Moa (Dinornithidae): Identifying Biological, Diagenetic, Experimental Artifact, and Mislabeled Modifications in Degraded Tissues

Proteomic analyses of extinct moa (Dinornithidae; ~800–1000 years) bone tissue previously revealed preserved collagens (I, II, and V), as well as several biological post-translational modifications (PTMs) and diagenetic peptide sequence alterations. The diagenetiforms detected in that study provided a baseline of PTM preservation in degraded tissues, identifying sequence alterations that could be accounted for in bioinformatic data searches (e.g., carboxymethyllysine). Subsequently, an improved extraction and sample preparation methodology, coupled with higher resolution mass spectrometry analyses, identified a wealth of previously unidentified non-collagenous proteins (NCPs) from the specimen. Here, in-depth analyses of the PTMs preserved in the expanded data set provide a detailed look at the types of PTMs (i.e., biological, diagenetic, and potential experimental artifacts) that occur in degraded tissues, the proteins they occur on, and the amino acids they modify. In total, 10 biological PTMs (e.g., ubiquitylation) and 18 diagenetic PTMs, including two advanced glycation end products (e.g., dihydroxy methylglyoxal adduction) and 12 types of oxidative damage (e.g., pyrrolidone formation from proline), were detected. In addition, peptides displaying diagenetic backbone cleavage (hydrolysis) were frequently observed to possess unidentified, variable mass shifts at their broken terminus, which search software would attempt to erroneously identify as different PTMs. The modifications characterized in the bones of this specimen, both in collagens and in NCPs, provide insight into patterns of preservation and degradation that paleoproteomic studies can utilize when searching and interpreting data sets from fossil tissue.
Segmentation of Low-Light Optical Coherence Tomography Angiography Images under the Constraints of Vascular Network Topology

Optical coherence tomography angiography (OCTA) offers critical insights into the retinal vascular system, yet its full potential is hindered by challenges in precise image segmentation. Current methodologies struggle with imaging artifacts and clarity issues, particularly under low-light conditions and when using various high-speed CMOS sensors. These challenges are particularly pronounced when diagnosing and classifying diseases such as branch vein occlusion (BVO). To address these issues, we have developed a novel network based on topological structure generation, which transitions from superficial to deep retinal layers to enhance OCTA segmentation accuracy. Our approach not only demonstrates improved performance through qualitative visual comparisons and quantitative metric analyses but also effectively mitigates artifacts caused by low-light OCTA, resulting in reduced noise and enhanced clarity of the images. Furthermore, our system introduces a structured methodology for classifying BVO diseases, bridging a critical gap in this field. The primary aim of these advancements is to elevate the quality of OCTA images and bolster the reliability of their segmentation. Initial evaluations suggest that our method holds promise for establishing robust, fine-grained standards in OCTA vascular segmentation and analysis.
Open to Ridicule – Deploying Plaything Technology for 3D Modelling of Urban Informal Settlements in Asia

As technology affine urban landscape researchers, working in Asian mega cities, we roam through crowded and narrow, widely informal city layouts, where we apply digital fieldwork equipment and conduct design work. We use low cost cameras and camera drones, tools that had been developed as gadgets for outdoor freaks or plaything for nerds. In this paper, we describe recent advances in the development of a method of onsite data and image gathering, which allows the processing of concrete 3D models of informal city spaces. The visual quality of these models is still moderate, but the resulting three-dimensional spatial puzzle makes a widely inaccessible and undocumented piece of city terrain visible, understandable and designable. The software used is free.
HIV-1 Reverse Transcriptase Expression in HPV16-Infected Epidermoid Carcinoma Cells Alters E6 Expression and Cellular Metabolism, and Induces a Hybrid Epithelial/Mesenchymal Cell Phenotype

The high incidence of epithelial malignancies in HIV-1 infected individuals is associated with co-infection with oncogenic viruses, such as high-risk human papillomaviruses (HR HPVs), mostly HPV16. The molecular mechanisms underlying the HIV-1-associated increase in epithelial malignancies are not fully understood. A collaboration between HIV-1 and HR HPVs in the malignant transformation of epithelial cells has long been anticipated. Here, we delineated the effects of HIV-1 reverse transcriptase on the in vitro and in vivo properties of HPV16-infected cervical cancer cells. A human cervical carcinoma cell line infected with HPV16 (Ca Ski) was made to express HIV-1 reverse transcriptase (RT) by lentiviral transduction. The levels of the mRNA of the E6 isoforms and of the factors characteristic to the epithelial/mesenchymal transition were assessed by real-time RT-PCR. The parameters of glycolysis and mitochondrial respiration were determined using Seahorse technology. RT expressing Ca Ski subclones were assessed for the capacity to form tumors in nude mice. RT expression increased the expression of the E6*I isoform, modulated the expression of E-CADHERIN and VIMENTIN, indicating the presence of a hybrid epithelial/mesenchymal phenotype, enhanced glycolysis, and inhibited mitochondrial respiration. In addition, the expression of RT induced phenotypic alterations impacting cell motility, clonogenic activity, and the capacity of Ca Ski cells to form tumors in nude mice. These findings suggest that HIV-RT, a multifunctional protein, affects HPV16-induced oncogenesis, which is achieved through modulation of the expression of the E6 oncoprotein. These results highlight a complex interplay between HIV antigens and HPV oncoproteins potentiating the malignant transformation of epithelial cells.
Comparative Study of Erasure Code in Distributed Systems and Blockchain

As the data generated by various applications continues to grow exponentially, the need for efficient methods of storage and transmission increases. Erasure codes offer a promising solution by providing redundant information without completely recreating the data. Although erasure codes have been extensively studied, their integration and effectiveness in distributed systems and blockchain networks are still being explored. This paper explores and compares the foundations and applications of erasure codes in distributed systems and blockchain networks, and provides a comprehensive literature review of erasure code implementations and their impact on data storage and transmission. This study explores the foundations of erasure codes in distributed systems, including array and RS codes, and LDPC codes. The study also explores the use of erasure codes in distributed systems and blockchain and analyzes how these codes can improve the efficiency and scalability of decentralized storage solutions. The study examines the strengths and weaknesses of different erasure codes based on analysis and comparisons. The findings highlight the potential of erasure codes to revolutionize data storage and transmission in distributed systems and blockchain networks.
Generating images using generative adversarial networks based on text descriptions

Modern developments in the fields of natural language processing (NLP) and computer vision (CV) emphasize the increasing importance of generating images from text descriptions. The presented article analyzes and compares two key methods in this area: generative adversarial network with conditional latent semantic analysis (GAN-CLS) and ultra-long transformer network (XLNet). The main components of GAN-CLS, including the generator, discriminator, and text encoder, are discussed in the context of their functional tasks—generating images from text inputs, assessing the realism of generated images, and converting text descriptions into latent spaces, respectively. A detailed comparative analysis of the performance of GAN-CLS and XLNet, the latter of which is widely used in the organic light-emitting diode (OEL) field, is carried out. The purpose of the study is to determine the effectiveness of each method in different scenarios and then provide valuable recommendations for selecting the best method for generating images from text descriptions, taking into account specific tasks and resources. Ultimately, our paper aims to be a valuable research resource by providing scientific guidance for NLP and CV experts.
The Exploration of Emotional Aspects of Artificial Intelligence (AI) in Artistic Design

The article explores the emotional aspect of artificial intelligence in art and design. With technological advancements, AI has shown tremendous potential in the realm of artistic creation. Firstly, the article reviews the development of AI in art and design, introducing applications of technologies such as generative art, deep learning, and generative adversarial networks. Secondly, it delves into the emotional dimension of AI in artistic design. Despite significant progress in learning and imitating artistic styles, AI's expression of emotions remains limited to simulating programs and data, creating a gap with human emotional experiences. However, by learning from human aesthetic experiences, AI utilizes universally recognized emotional symbols in artistic works, evoking aesthetic resonance among audiences. Furthermore, the article emphasizes the importance of human designers in the creative process and the potential for collaboration between AI and humans. Lastly, it discusses the future possibilities wherein AI, as technology advances, may enter an era of strong artificial intelligence, potentially disrupting the ecosystem of art and design. Although AI might acquire emotional and creative capabilities in the future, the emotional experiences and unique creativity of human creators remain irreplaceable. Therefore, the future of art and design might be a product of collaboration between humans and AI, opening new spaces for exploration and contemplation in the art world.
A Novel Deep Learning Pipeline for Vertebra Labeling and Segmentation of Spinal Computed Tomography Images

Automatic segmentation of vertebrae from computed tomography (CT) scans play an important role in the clinical interpretation and treatment of spinal co-morbidities. Labelling and segmentation of vertebrae is labour intensive and challenging, due to various fields of view and fuzzy boundaries in CT scans. Therefore, successful labelling and segmentation is highly dependent on the level of expertise of the radiologist. In this paper, we propose a three-step fully-automated end-to-end pipeline for vertebra labelling and segmentation of spinal CT images. A novel deep learning architecture, Unbalanced-UNet, is proposed for extracting the region proposals for spine detection. A modified SpatialConfiguration-Net, 3D SCN, is used for labelling of vertebra and centroid extraction. Finally, a 3D U-Net is employed for the segmentation of each vertebra. The models were validated on VERSE’19 public dataset. An identification rate of 90.20% and 91.47% was obtained for the first and second test sets of the VERSE’19 dataset, respectively. Mean localization distance of 4.97 mm and 5.32 mm was obtained for the first and second test sets, respectively. The final segmentation stage shows a dice score and Hausdorff surface distance of 93.07% and 5.36 mm, respectively, for the first test set, and 92.01% and 5.63 mm, respectively, for the second test set. The results show that the proposed approach outperforms the state-of-art models for segmentation of vertebrae. The proposed Unbalanced-UNet architecture increased the accuracy of accruing the region proposals for spine detection. The proposed fully automated pipeline has potential clinical applications in treatment and surgical planning of spinal deformities.