Miracle-dz/UniFAR-FTUs huggingface dataset:
SCORE TRANSFORMER: TRANSCRIBING QUANTIZED MIDI INTO COMPREHENSIVE MUSICAL SCORE

We explore the tokenized representation of musical scores to generate musical scores with transformers. We design score token representation corresponding to the musical symbols and attributes used in musical scores and train the Transformer model to transcribe note-level representation into musical scores. Evaluations of popular piano scores show that our model significantly outperforms existing methods on all 4 investigated categories. We also explore an effective token representation, including those based on existing text-like score formats, and show that our proposed representation produces the steadiest results.
Resident participation in post-Lushan earthquake housing reconstruction: a multi-stage field research method-based inquiry

ABSTRACT In April 2013, a 7.0 Mw earthquake struck in Lushan County, Sichuan Province, China, causing serious housing damage. Housing reconstruction is a crucial part of disaster recovery, and resident participation has been recognized as a key part of reconstruction success. This paper examined housing reconstruction resident participation in the post-Lushan earthquake period as a multi-stage problem based on multi-stakeholder collaborative perspectives, which covered emergency shelter, temporary housing and permanent housing stages. Multi-stage field research was conducted in the affected areas, and the residents were found to be fully involved in the reconstruction with a ‘high – medium – high' distribution across the three stages. Resident participation experiences were summarized in terms of previous earthquake education, NGO participation and community-based organization functions, and the reasons discussed, such as civic awareness and civic rights. Problems regarding improper reconstruction and cultural conflicts were also examined and valuable suggestions given.
REVIEW ON CONTENT BASED IMAGE RETRIEVAL SYSTEM

: Content Based Image retrieval (CBIR) has been an active research area since past few years. In this thesis we have discussed the three main areas of CBIR which are feature extraction, indexing and the retrieval technique. We have also discussed briefly some of the commercial systems available in the market and apart from that some related work in this field is also discussed. Content based image retrieval has found its application in many areas like government, academic and hospitals. This paper proposed technique retrieves similar images in stages. The images are first retrieved based on their color feature similarity. The relevance of the retrieved images is then further improved by matching their texture and shape features respectively. Generally in CBIR we compare query image feature vector with all other images in the database. This decreases the accuracy of the system as the search encompasses the whole database which contains a wide variety of images. The proposed system in this paper has three layers feed forward architecture where each stage output is the input for next stage. Proposed approach also reduces the problem of high dimensionality of feature vector because at each stage only a part of the feature vector representing the desired feature need to be compared thereby resulting in reduction of computational overhead of the overall system. Retrieval in stages also reduces the semantic gap. Advantages of global and region features are also combined to achieve better retrieval accuracy. Experimental results have shown that the proposed system can improve the retrieval accuracy in terms of precision values.
Investigating Effects of eugenol on nerve conduction and synaptic transmission at neuromuscular junction in an amphibian

Eugenol is a natural anesthetic. This study provides insights into how eugenol affects neuromuscular communication in a vertebrate to address its anesthetic property. Eugenol’s effects at the neuromuscular junction (NMJ) have not been well studied. This study was to determine if eugenol affects the activity of cholinergic synapses at the frog pectoris NMJ. Second, this study set out to determine if eugenol could block evoked compound action potentials (CAP) in the frog sciatic nerve at 0.05 mM. This study also provides a novel procedure for isolating the frog cutaneous pectoris muscle. This thin surface muscle is ideal to use in studying synaptic responses. The results showed evoked excitatory junction potentials at the frog pectoris NMJ were depressed during exposure to eugenol, however, quantal events were not. This indicated that the nicotinic acetylcholine receptors on the muscle fibers were not blocked by eugenol. Eugenol also depressed conduction of compound action potentials along the frog sciatic nerve. These results indicate eugenol likely targets membrane proteins associated with electrical signaling. In summary, this study successfully demonstrated use of the sciatic nerve and cutaneous pectoris muscle for examining the effects of eugenol on neural-muscular function and could potential be extended for use as an anesthetic.
PERCEPTION OF RESIDENTS TOWARDS COMMUNITY TOURISM IMPACTS: A CASE STUDY AT MOUNT LAVINIA, SRI LANKA

This study has found the perceptions of the local community towards the developments in tourism and their perceptions towards the community tourism impacts. The host population was taken from the Mount Lavinia, Sri Lanka and 120 questionnaires were distributed. And the direct observations of the researcher have also included. The respondents of the study can be divided into mainly two parts. They are: The community with tourism income in their household and the community who has not engage in tourism income generation activity. Most of the community at Mount Lavinia who were not engage in tourism agreed that there are so many negative impacts of tourism while the community who engage in tourism were not concern much about the negativity that bring through tourism to their lives. The researcher has suggested that local governments and tourism promoters should pay particular emphasis to the residents to feel that their concerns are being considered, then they will support tourism.
Equivariant and Modular DeepSets with Applications in Cluster Cosmology

We design modular and rotationally equivariant DeepSets for predicting a continuous background quantity from a set of known foreground particles. Using this architecture, we address a crucial problem in Cosmology: modelling the continuous electron pressure ﬁeld inside massive structures known as “clusters. ” Given a simulation of pressureless, dark matter particles, our networks can directly and accurately predict the background electron pressure ﬁeld. The modular design of our architecture makes it possible to physically interpret the individual components. Our most powerful deterministic model improves by 70 % on the benchmark. A conditional-VAE extension yields further improvement by 7 % , being limited by our small training set however. We envision use cases beyond theoretical cosmology, for example in soft condensed matter physics, or meteorology and climate science. 2
Exchange of cellular components between platelets and tumor cells: impact on tumor cells behavior

Background: Platelets are active players in tumorigenesis, although the exact interactive mechanisms and their direct impact on tumor cells remain largely unknown. Methods: Bidirectional transference of lipids, proteins and RNA between platelets and tumor cells and its impact on tumor cell behavior and tumor process are analyzed in this work. Phenotypic, genetic and functional modifications induced by platelets were analyzed both in tumor cell lines and in circulating tumor cells (CTCs). Results: Data from these assays showed that platelets transferred structural components to tumor cells with higher efficiency than tumor cells to platelets (p = 0.001). This biological interplay occurred by direct contact, internalization or via extracellular vesicles. As a result, tumor cells acquired platelet markers (CD61 and CD42), showed decreased EpCAM, expressed epithelial-to-mesenchymal transition markers, and increased proliferation rates. Moreover, we were able to detect CD61 in CTCs from early and advanced prostate cancer. Conclusions: Our results demonstrated, for the first time, that platelets educate tumor cells by highly efficient transference of lipids, proteins and RNA through different mechanisms. These results suggest that tumor cells and CTCs might acquire highly dynamic and aggressive phenotypes due to platelets interaction including EMT, stem-like phenotype and high proliferative rates.
Mechanism of northern pike invasion in the Columbia River Basin

The spread of aquatic invasive species typically occurs through a combination of natural and human mediated dispersal. For many aquatic invasive species, natural dispersal is limited to aquatic corridors connecting habitat. In contrast, human transport may facilitate more distant dispersal and transport among disconnected waterbodies. Genetic information can serve as a powerful tool to track invasion histories and identify both the sources and mechanisms of invasive species dispersal. We used genetic information to understand invasion history and dynamics of expanding northern pike invasion in the Columbia River basin. Results indicate that the initial introduction of northern pike into the Pend Oreille River (in eastern Washington State) resulted from human transport of fish, not dispersal from established populations upstream. Subsequent reproduction and natural dispersal from the Pend Oreille River resulted in downstream expansion of northern pike into Lake Roosevelt, a reservoir within the mainstem Columbia River. These results highlight the need for a holistic approach to suppression of invasive species. Immediate efforts must address the biological mechanisms of natural dispersal. Sustained suppression and eradication must take a broad approach that includes coordination between management agencies, as well as policy and public outreach aimed at prevention of repeated human transport events. The genetic database created from this study has already been used to eliminate potential source populations for new northern pike invasions in Washington State outside the Columbia River basin. This highlights the utility of genetic monitoring for both immediate and long-term applications to managing aquatic species invasions.
Cislunar Periodic Orbit Family Classification from Astrometric and Photometric Observations Using Machine Learning 1

As a means of aiding initial orbit determination for objects in cislunar space, we train various machine-learning algorithms to predict membership in one of 31 elemental periodic orbit families (Doedel, et al., 2007) (e.g. HN2 for northern halo orbit about the ℒ 2 libration point) using observational features, including uncertainties, generated from the synodic positions and velocities. Additionally, various methods are investigated to allow for “null” membership where the observation is assessed to not belong to any of the periodic orbit families. The machine-learning algorithms investigated include k-nearest neighbor, support vector machines, decision tree ensembles, random forests, and deep neural networks. The features used include combinations of right ascension, declination, range, their associated rates, and visual magnitude. Individual and integrated performance results are reported and, as expected, vary depending on the features used and uncertainty in the features. Performance accuracy of up to 98% is possible.
Networked Restless Multi-Armed Bandits for Mobile Interventions

Motivated by a broad class of mobile intervention problems, we propose and study restless multi-armed bandits (RMABs) with network effects. In our model, arms are partially recharging and connected through a graph, so that pulling one arm also improves the state of neighboring arms, significantly extending the previously studied setting of fully recharging bandits with no network effects. In mobile interventions, network effects may arise due to regular population movements (such as commuting between home and work). We show that network effects in RMABs induce strong reward coupling that is not accounted for by existing solution methods. We propose a new solution approach for networked RMABs, exploiting concavity properties which arise under natural assumptions on the structure of intervention effects. We provide sufficient conditions for optimality of our approach in idealized settings and demonstrate that it empirically outperforms state-of-the art baselines in three mobile intervention domains using real-world graphs.
Biometric Recognition of Finger Knuckle Print Based on the Fusion of Global Features and Local Features

Compared with the most traditional fingerprint identification, knuckle print and hand shape are more stable, not easy to abrase, forge, and pilfer; in aspect of image acquisition, the requirement of acquisition equipment and environment are not high; and the noncontact acquisition method also greatly improves the users' satisfaction; therefore, finger knuckle print and hand shape of single-mode identification system have attracted extensive attention both at home and abroad. A large number of studies show that multibiometric fusion can greatly improve the recognition rate, antiattack, and robustness of the biometric recognition system. A method combining global features and local features was designed for the recognition of finger knuckle print images. On the one hand, principal component analysis (PCA) was used as the global feature for rapid recognition. On the other hand, the local binary pattern (LBP) operator was taken as the local feature in order to extract the texture features that can reflect details. A two-layer serial fusion strategy is proposed in the combination of global and local features. Firstly, the sample library scope was narrowed according to the global matching result. Secondly, the matching result was further determined by fine matching. By combining the fast speed of global coarse matching and the high accuracy of local refined matching, the designed method can improve the recognition rate and the recognition speed.
A novel machine learning derived RNA-binding protein gene–based score system predicts prognosis of hepatocellular carcinoma patients

Background Although the expression of RNA-binding protein (RBP) genes in hepatocellular carcinoma (HCC) varies and is associated with tumor progression, there has been no overview study with multiple cohorts and large samples. The HCC-associated RBP genes need to be more accurately identified, and their clinical application value needs to be further explored. Methods First, we used the robust rank aggregation (RRA) algorithm to extract HCC-associated RBP genes from nine HCC microarray datasets and verified them in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort and International Cancer Genome Consortium (ICGC) Japanese liver cancer (ICGC-LIRI-JP) cohort. In addition, the copy number variation (CNV), single-nucleotide variant (SNV), and promoter-region methylation data of HCC-associated RBP genes were analyzed. Using the random forest algorithm, we constructed an RBP gene–based prognostic score system (RBP-score). We then evaluated the ability of RBP-score to predict the prognosis of patients. The relationships between RBP-score and other clinical characteristics of patients were analyzed. Results The RRA algorithm identified 30 RBP mRNAs with consistent expression patterns across the nine HCC microarray datasets. These 30 RBP genes were defined as HCC-associated RBP genes. Their mRNA expression patterns were further verified in the TCGA-LIHC and ICGC-LIRI-JP cohorts. Among these 30 RBP genes, some showed significant copy number gain or loss, while others showed differences in the methylation levels of their promoter regions. Some RBP genes were risk factors or protective factors for the prognosis of patients. We extracted 10 key HCC-associated RBP genes using the random forest algorithm and constructed an RBP-score system. RBP-score effectively predicted the overall survival (OS) and disease-free survival (DFS) of HCC patients and was associated with the tumor, node, metastasis (TNM) stage, α-fetoprotein (AFP), and metastasis risk. The clinical value of RBP-score was validated in datasets from different platforms. Cox analysis suggested that a high RBP-score was an independent risk factor for poor prognosis in HCC patients. We also successfully established a combined RBP-score+TNM LASSO-Cox model that more accurately predicted the prognosis. Conclusion The RBP-score system constructed based on HCC-associated RBP genes is a simple and highly effective prognostic evaluation tool. It is suitable for different subgroups of HCC patients and has cross-platform characteristics. Combining RBP-score with the TNM staging system or other clinical parameters can lead to an even greater clinical benefit. In addition, the identified HCC-associated RBP genes may serve as novel targets for HCC treatment.
Screening and Identification of Key Biomarkers in Lower Grade Glioma via Bioinformatical Analysis

Lower-grade glioma (LGG) is a common type of central nervous system tumor. Due to its complicated pathogenesis, the choice and timing of adjuvant therapy after tumor treatment are controversial. This study explored and identified potential therapeutic targets for lower-grade. The bioinformatics method was employed to identify potential biomarkers and LGG molecular mechanisms. Firstly, we selected and downloaded GSE15824, GSE50161, and GSE86574 from the GEO database, which included 40 LGG tissue and 28 normal brain tissue samples. GEO and VENN software identified of 206 codifference expressed genes (DEGs). Secondly, we applied the DAVID online software to investigate the DEG biological function and KEGG pathway enrichment, as well as to build the protein interaction visualization network through Cytoscape and STRING website. Then, the MCODE plug is used in the analysis of 22 core genes. Thirdly, the 22 core genes were analyzed with UNCLA software, of which 18 genes were associated with a worse prognosis. Fourthly, GEPIA was used to analyze the 18 selected genes, and 14 genes were found to be a significantly different expression between LGGs and normal brain tumor samples. Fifthly, hierarchical gene clustering was used to examine the 14 important gene expression differences in different histologies, as well as analysis of the KEGG pathway. Five of these genes were shown to be abundant in the natural killer cell-mediated cytokines (NKCC) and phagosome pathways. The five key genes that may be affected by the immune microenvironment play a crucial role in LGG development.
Cascade testing for inherited arrhythmia conditions: Experiences and attitudes of family communication approaches for a Canadian cohort

Inherited arrhythmia conditions (IAC) can lead to sudden cardiac death at any age, and relatives of an affected person have up to a 50% chance of inheriting the condition and are at risk for developing features. Cascade testing is a stepwise approach for identifying relatives at risk for IACs through clinical screening and genetic testing. Early detection can reduce morbidity and mortality for affected individuals and determine potential risk mitigation strategies for relatives. However, cardiovascular genetic studies have reported an incomplete uptake of cascade testing in at‐risk relatives. We explored patient perspectives on cascade testing for IACs and alternative approaches to family communication. Twelve semi‐structured phone interviews were conducted with probands of the British Columbia Inherited Arrhythmia Program confirmed to carry a pathogenic or likely pathogenic variant in a gene associated with an IAC. Thematic analysis of transcripts through an iterative coding process revealed five main themes: (a) a stepwise approach is followed in disclosing risk to relatives, (b) relatives’ autonomy in cascade testing is supported, (c) lived experience with the condition influences disclosure and uptake of cascade testing, (d) collaborative approach to informing relatives reduces negative impact of disclosure, and (e) direct contact from a healthcare provider is viewed as acceptable. The findings highlight this patient cohort's experiences and opinions with approaches to disclosure and demonstrate their understanding and acceptance of their relatives’ approaches to cascade testing. In addition, while the notion of direct contact was generally accepted, a collaborative approach to contacting relatives between the proband and provider may be most effective.
HIV prevention: better choice for better coverage

Antiretroviral‐based pre‐exposure prophylaxis (PrEP) is today an established, effective and safe method of HIV prevention used in multiple countries worldwide by a broad range of populations at risk of HIV infection. Biomedical innovations are critical in supporting the primary prevention of HIV; however, their potential can only be maximized if end‐user challenges are recognized, described and used to develop next‐generation models.
Architectural Level Power Optimization Techniques for Multipliers

In this work, a new topology was proposed to optimize the power dissipation of Multipliers. Low power digital Multiplier Design based on bypassing technique mainly used to reduce the switching power dissipation. While this technique offers great dynamic power savings mainly in array multipliers, due to their regular interconnection scheme, it misses the reduced area and high speed advantages of tree multipliers. Therefore, mixed style architecture, using a traditional tree based part, combined with a bypass, array based part, is proposed. Prototyping of all these multiplier Architectures has been carried out on Spartan3E FPGA. By Evaluating the performance of these Multiplier architectures using Xilinx ISE tool suite , it has been found that while the bypass technique offers the minimum dynamic power consumption, the mixed architecture offers a delay*power product improvement , compared to all other architectures.
Calibrationless multi‐slice Cartesian MRI via orthogonally alternating phase encoding direction and joint low‐rank tensor completion

We propose a multi‐slice acquisition with orthogonally alternating phase encoding (PE) direction and subsequent joint calibrationless reconstruction for accelerated multiple individual 2D slices or multi‐slice 2D Cartesian MRI. Specifically, multi‐slice multi‐channel data are first acquired with random or uniform PE undersampling while orthogonally alternating PE direction between adjacent slices. They are then jointly reconstructed through a recently developed low‐rank multi‐slice Hankel tensor completion (MS‐HTC) approach. The proposed acquisition and reconstruction strategy was evaluated with human brain MR data. It effectively suppressed aliasing artifacts even at high acceleration factor, outperforming the existing MS‐HTC approach, where PE direction is the same between adjacent slices. More importantly, the new strategy worked robustly with uniform undersampling or random undersampling without any consecutive central k‐space lines. In summary, our proposed multi‐slice MRI strategy exploits both coil sensitivity and image content similarities across adjacent slices. Orthogonally alternating PE direction among slices substantially facilitates the low‐rank completion process and improves image reconstruction quality. This new strategy is applicable to uniform and random PE undersampling. It can be easily implemented in practice for Cartesian parallel imaging of multiple individual 2D slices without any coil sensitivity calibration.