Miracle-dz/UniFAR-FTUs huggingface dataset:
Coordinate Embedding Transformer Model for Optical Music Recognition on Monophonic Scores

Optical Music Recognition (OMR) is an image recognition task that researchers try to teach computers to read music notation. In recent years, the convolution recursive neural network algorithm achieves great success in music symbols recognition tasks, especially in the monophonic score. However, some challenges remain in music symbol recognition, such as the notes in different positions of the staff which have the same image features represent different meanings. It is hard to distinguish the notes only with the way of convolution. In addition, context relationship is usually used to improve the overall accuracy of the music symbol recognition. In this paper, we propose a Coordinate Embedding Transformer model(CETr). We add pixel coordinates into feature patches to make the note positions of the staff participate in training and predicting, which can increase the difference between two notes with the different positions of the staff. Due to the Transformer which is designed for sequence modeling and transduction tasks being reliable to deal with the context relationship in a music score, we leverage the Transformer architecture for symbols-level score generation. Experiments show that the CETr model outperforms the current state-of-the-art models on both clean and distorted monophonic scores.
Development of a Redundant Humanoid Lower Limb With Whole-Foot Tactile Perception

The physical basis of human erect and motion balance includes flexible multi-DoF lower limbs and foot tactile perception. Most existing humanoid lower limbs focus on providing physical support and mobility, with little work on more bionic DoFs or tactile sensing abilities that are more than significant for a fully humanoid system. This study developed a redundant humanoid lower limb with whole-foot tactile sensing capability. An eight-DoF mechanism with humanoid joints was designed, and a tactile sensor with electric double-layer capacitors (EDLC) principle wrapped the 3D-curved foot surface. An STM32-based circuitry integrating tactile perception and control with an inverse kinematics algorithm was experimentally demonstrated. A mapping relationship between tactile information and control commands (Z-CMD) was established. The effectiveness and feasibility of the robotic system were verified by an obstacle avoidance experiment with a teaching-playback function. This work provides novel insight and methodology for humanoid robots and tactile-based bionic intelligence.
Extending the compression range of biomedical images for machine vision analysis

The growing adoption of biomedical machine vision algorithms to perform detection, segmentation, and classification tasks, is driving a shift in compression paradigms, progressively replacing perceptual quality by performance of machine vision tasks as the target encoding optimization. Therefore, improving task performance rather than image quality has become a new research problem in biomedical image compression. This paper presents a contribution to extend the useful compression range from lossless to lossy while keeping the performance of biomedical machine vision algorithms. Automatic detection of mitochondrias in electron microscopy images, using a learning-based network (YOLO), is the case-study investigated in this work. Two types of new results are presented in regard to detection performance. In the first one, it is shown that compression ratios up to 15 can be used, for a maximum of 3% of detection loss. Then in the second one, by using compressed images for training, it is shown that the compression range can be increased up to 135 times, while missing less than 5% of the detections.
Power Coordinated Control of Microgrid Based on Sequence Model Predictive Control

In this paper, the overall structure of the microgrid and the power coordination strategy control method are firstly determined. The photovoltaic cell is used as the representative of the distributed power in the microgrid; the energy storage battery is connected to the microgrid through a buck-boost circuit of model predictive control; the diesel generator is connected to the microgrid through a model predictively controlled active front end rectifier is connected to the DC bus. Then, in view of the difficulty in setting the weighting factors of multiple objective functions in traditional model predictive control, a model predictive control with a sequence structure is introduced in this paper, which can greatly reduce the switching frequency on the premise of ensuring the stable operation of the system. At the same time, a crowbar circuit is added to ensure a stable voltage output for the problem of DC overvoltage that may exist in the system. Finally, an experimental platform based on TMS320F28335 is built to verify the correctness and feasibility of the proposed method.
A Convenient and Reliable Multi-Class Classification Model based on Explainable Artificial Intelligence for Alzheimer’s Disease

There is no cure for Alzheimer’s disease (AD) yet. The best treatment available is early detection and early intervention. However, most patients have not been detected in time, let alone timely intervention. So, the World Health Organization (WHO) calls for an increase in the screening rate of AD. Cognitive scores (CS) have great potential in the detection of AD and are easy to obtain, but there are fewer researches based only on CS for classification for screening. Current machine learning models often have good performance but are non-transparent, which makes them difficult to be accepted by physicians. To address the above problems, we propose a solution (RN-SSAS) for data sets with small sample size, multi-category and category-imbalanced, and prove that it is more robust than Cross-Validation (CV), more importantly, it can still achieve classifications under extreme data dilemmas. Then, based on the solution and CS, a multi-class classification model for AD is established, supplemented by single and global instance interpretations based on SHapley Additive exPlanations (SHAP). Finally, our model achieves an F-measure of 0.878 based on four different cognitive scores. In conclusion, our model is convenient, reliable and trustworthy, thus it can contribute to improving the screening rate of AD.
Battery cycler to generate open li-ion cell aging data and models

Battery degradation is relevant for the lifetime, cost, and life cycle analysis of electric vehicles and stationary storages. Publicly available, reusable battery aging data is scarce and aging experiments are time-consuming and expensive. This paper starts with an overview of existing battery aging data and models. We then present our battery cycler hardware, which we intend to use to generate open battery degradation data and models. After analyzing the switching behavior, efficiency, and control behavior of the hardware, this paper gives an overview of the generated data and the user interface of the battery cycler. Finally, we provide an outlook on the further development of the project.
Genome-Wide Identification, Characterization and Expression Analysis of Mango (Mangifera indica L.) chalcone synthase (CHS) Genes in Response to Light

Light is one the most important environmental factors regulating the accumulation of specific metabolites in plants, such as flavonoid. Chalcone synthase (CHS) is the key rate-limiting enzyme of the flavonoid biosynthesis pathway, while little is known about the CHS genes in mango (Mangifera indica L.). Therefore, the aim of the study was to obtain the genome-wide identification of the CHS genes in mango and screen the light-responsive family members. In this study, a total of 21 CHS genes were identified from the mango genome, and most of the members contained the Cys-His-Asn triad and the CHS/STS signature motif. Most of the MiCHS genes were located on chromosomes 2 and 4, and seven pairs of tandem duplication genes and five pairs of segmental duplication genes were detected among the MiCHS members. The expression of MiCHSs showed a tissue-specific pattern and was not correlated with the flavonoid or anthocyanin accumulation in cultivars with different peel colors. MiCHS4, MiCHS16 and MiCHS17 were found to respond to preharvest and postharvest UV-B plus visible light treatments, which exhibited no significant relationship with the light-responsive cis-acting element distribution in the promoter region. Our results are helpful and can be used to further study the function of MiCHS genes in light-induced flavonoid biosynthesis in mango.
Solution of Spatial Transformation Relationship of Similar Ruled Surfaces Based on Registration of Divided Regions

Since the geometric transformation relationship of similar surfaces with complex features, such as local deformation and curvature changes, is hard to be solved through global registration, this paper proposes a method for solving the spatial transformation relationship of similar ruled surfaces based on registration of divided regions. First, an adaptive region division algorithm is proposed to divide similar surfaces, and then, an improved registration algorithm is proposed by adding two constraints which are the curvature feature and differential geometric features of point clouds. Through this improved registration algorithm, the geometric transformation relationship of each sub-region can be solved, and then the spatial geometric transformation relationship of the overall similar surface can be established. Moreover, the improved registration algorithm can ensure that the differential geometric properties of corresponding points are similar after registration, which may provide a basis for mapping and reuse of process knowledge between corresponding points on similar surfaces. Finally, two similar ruled surface blades are taken as examples for simulation verification, the results show that the maximum registration error of each sub-region is 0.025 mm, which is within the allowable error range, and the registration speed of the proposed algorithm is better than the S-ICP algorithm. This proves that the method in this paper is feasible and effective.
Purdue e-Pubs Purdue e-Pubs Quantitative Comparison of the Performance of Vapor Quantitative Comparison of the Performance of Vapor Compression Cycles with Various Means of Compressor Flooding Compression Cycles with Various Means of Compressor Flooding

Increasing the Coefficient of performance (COP) of vapor compression cycles has been a major focus for decades. Significant improvements can be brought by modifying multistage compressor to flooded single-stage compressor in order to approach isothermal compression, which reduces compressor work and improves COP. This work presents the comparative analysis of the cycle performance of a 3 stage compression system (3SCS), multiple refrigerant injection system (MRIS) and an oil flooded system (OFS). Thermodynamic models of each of these systems using ideal mixing models of refrigerants with the flooding agents is presented. Results show that in an MRIS, an increase in the number of injection ports significantly increases the COP of the cycle between 18% and 51% for air conditioning and refrigeration applications. The OFS shows that increasing the oil mass flow rate increases the COP significantly above the baseline cycle, benefiting higher temperature lift applications. At evaporating temperature of -40℃, relative COP for MRIS with 3 injection points is 3.5% higher than 3SCS and 5.88% higher than OFS. Further, quantification of the influence of the non-ideal mixing model showed that dropping mixing effectiveness from 100% to 80% results in 21% degradation of COP.
R High-Efficiency Battery Charging With Switching Resonant Converter

—The high-frequency resonant converter has numer- ous well-known advantages over the traditional hard-switching converters. The most important advantage is that it offers a lower switching loss and a higher power density. Additionally, the soft-switching current waveform characterizes a lower electromagnetic interference (EMI). This study presents the circuit configuration with the least components to realize a highly efficient solar energy battery charger with a zero-voltage-switching resonant converter. The optimal values of the resonant components are determined by applying the characteristic curve and the electric functions de-rived from the circuit configuration. The experiment demonstrates the switching on and off of the main switches in a solar energy battery charger with a zero-voltage-switching resonant converter, wherein the switches are all operated using zero-voltage switching. The circuit efficiency in the overall charging process exceeds 80%.
Transmorphic phage‐guided systemic delivery of TNFα gene for the treatment of human pediatric medulloblastoma

Medulloblastoma is the most common childhood brain tumor with an unfavorable prognosis and limited options of harmful treatments that are associated with devastating long-term side effects. Therefore, the development of safe, non-invasive and effective therapeutic approaches is required to save the quality of life of young medulloblastoma survivors. We postulated that therapeutic targeting is a solution. Thus, we used a recently designed tumor-targeted bacteriophage (phage)-derived particle, named transmorphic phage/AAV, TPA, to deliver a transgene expressing the tumor necrosis factor alpha (TNFα) for targeted systemic therapy of medulloblastoma. This vector was engineered to display the double cyclic RGD4C peptide to selectively target tumors after intravenous administration. Furthermore, the lack of native phage tropism to mammalian cells warrants safe and selective systemic delivery to the tumor microenvironment. In vitro RGD4C.TPA. TNFα treatment of human medulloblastoma cells generated efficient and selective TNFα expression, subsequently triggering cell death. Combination with the chemotherapeutic drug cisplatin, used clinically against medulloblastoma, resulted in augmented effect through the enhancement of TNFα gene expression. Systemic administration of RGD4C.TPA. TNFα to mice bearing subcutaneous medulloblastoma xenografts resulted in selective tumor homing of these particles, and consequently targeted tumor expression of TNFα, apoptosis, and destruction of the tumor vasculature. Thus, our RGD4C.TPA. TNFα particle provides selective and efficient systemic delivery of TNFα to medulloblastoma, yielding a potential TNFα anti-medulloblastoma therapy while sparing healthy tissues from the systemic toxicity of this cytokine.
Is Asymmetry Different Depending on How It Is Calculated?

This study aimed to (1) determine the magnitude and direction of asymmetry in volleyball players, (2) establish asymmetry thresholds, and (3) explore differences depending on the test used and the players’ category. Twenty-nine junior and senior male volleyball players were assessed through a muscle asymmetry battery test: active knee extension test (AKE), single-leg countermovement jump (SL-CMJ), single-leg squat jump (SL-SJ), triple hop test for distance (THTD), modified 20-yard shuttle run, Y-balance test, single-leg one-repetition maximum in leg press test (1RM-SL), and lateral symmetry in radial muscle belly displacement through Tensiomyography in the biceps femoris and rectus femoris. A two-way ANOVA alongside an individual analysis of asymmetry thresholds was used to analyze the test and categorize the influence on the magnitude and the direction of asymmetry. The 1RM-SL, SL-SJ, and the lateral symmetry in radial muscle belly displacement showed a clear asymmetry towards the non-dominant side, while the AKE, SL-CMJ, and THTD showed an asymmetry towards the dominant side. The magnitude of the asymmetry was highly variable between tests (1.46–30.26%). The individualized asymmetry thresholds revealed that the percentage of asymmetrical players varied depending on the type of test used. In conclusion, the type of test used determines the magnitude and direction of asymmetry in well-trained volleyball players.
Computational speed-up of large-scale, single-cell model simulations via a fully integrated SBML-based format

Summary Large-scale and whole-cell modeling has multiple challenges, including scalable model building and module communication bottlenecks (e.g. between metabolism, gene expression, signaling, etc). We previously developed an open-source, scalable format for a large-scale mechanistic model of proliferation and death signaling dynamics, but communication bottlenecks between gene expression and protein biochemistry modules remained. Here, we developed two solutions to communication bottlenecks that speed up simulation by ~4-fold for hybrid stochastic-deterministic simulations and by over 100-fold for fully deterministic simulations. Availability and Implementation Source code is freely available at https://github.com/birtwistlelab/SPARCED/releases/tag/v1.1. 0 implemented in python, and supported on Linux, Windows, and MacOS (via Docker). Contact Marc Birtwistle mbirtwi@clemson.edu Supplementary information N/A
Women's Path to Tenure: Analysis of the Leaky Pipeline Phenomenon

This paper seeks to explain the leaky pipeline phenomenon at the University of Pennsylvania, characterized by the decreasing representation of women faculty at higher ranks of the professoriate. This study incorporates social role theory into its assessment of archival data on the composition of the faculty from 1999-2016. The paper finds no strong evidence of hiring discrimination; mixed evidence on the retention of women faculty, or that women are no less likely than men to leave the University; and little evidence of a positive trickle-down leadership effect, as universities who had never appointed a woman president had the greatest representation of women full professors in the years analyzed. The paper’s findings suggest that biased performance evaluations, unequal divisions of home responsibilities, and informal network exclusion of women faculty may contribute to the leaky pipeline, and highlight how historic gender roles continue to have salient consequences for women in the workforce
Supporting Make It Stereoscopic: Interfacial Design for Full-Temperature Adaptive Flexible Zinc-Air Batteries

Synthesis of Polypyrrole nanowire arrays (PPy NAs) precursor: PPy NAs were synthesized by a galvanostatic electrodeposition method using a three-electrode configuration with concentrate nitric acid pre-treated carbon cloth (CC), platinum mesh, and saturated calomel electrode as the working electrode, counter electrode, and reference electrode, respectively. Specifically, the electrolyte was prepared by dissolving 0.388 g sodium p-toluenesulfonate into 50 mL 1 M phosphate-buffered solution (pH=7), then 500 μL of pyrrole monomer was added under stirring at 0 oC. A piece of CC (1 × 4 cm) was immersed into the electrolyte (with an effective geometric area of 1 × 3 cm). The electrodeposition of the PPy NAs was achieved by applying a constant current of 8 mA to CC for 30 min. All operations were conducted at 0 oC. After that, the PPy NAs/CC was thoroughly washed and dried at 60 oC.
Catalysis Reaction: Can We Grow a Quantum Processor?

Alexei Marchenkov is an experimental physicist who has devoted most of his research career to studying quantum phenomena in materials and structures at cryogenic temperatures, including graphene, atomic-sized wires and con-tacts, and superconducting quantum bits and circuits. He is a former associate professor at the Georgia Institute of Technology and founder and chief execu-tive ofﬁcer of the Bleximo Corp., a startup developing application-speciﬁc superconducting quantum computers.
Atomic and electronic structures of Pd 13 and Pt 13 clusters

The electronic structures of ${\mathrm{Pd}}_{13}$ and ${\mathrm{Pt}}_{13}$ clusters of cuboctahedral and icosahedral symmetries are analyzed by the self-consistent spin-polarized density-functional scheme using the norm-conserving pseudopotential in the linear combination of atomic orbitals method. The electronic structure is discussed in relation to the shell structure of the giant atom. The stable atomic structure is discussed, considering the effects of the generalized gradient approximation of the exchange-correlation potential, the spin-orbit splitting, and the Jahn-Teller effect. The spin-orbit coupling effect depends on the symmetry of the whole cluster. It is the largest of these effects for Pt, and it is as large as the spin polarization effect for Pd. The electronic structure of Pd and Pt clusters of 13 atoms is comprehended as a complex of the shell structure and the localized Pd-$4d$ or Pt-$5d$ orbitals. The Jahn-Teller effect seems to be small to keep the shell structure. For both Pd and Pt metals the cuboctahedron clusters are more stable and have small spin polarization, $S=3$ for the Pd cluster and $S=4$ for the Pt cluster.
The Role of Reactive Species on Innate Immunity

This review examines the role of reactive species RS (of oxygen ROS, nitrogen RNS and halogen RHS) on innate immunity. The importance of these species in innate immunity was first recognized in phagocytes that underwent a “respiratory burst” after activation. The anion superoxide •O2− and hydrogen peroxide H2O2 are detrimental to the microbial population. NADPH oxidase NOx, as an •O2− producer is essential for microbial destruction, and patients lacking this functional oxidase are more susceptible to microbial infections. Reactive nitrogen species RNS (the most important are nitric oxide radical -•NO, peroxynitrite ONOO— and its derivatives), are also harmful to microorganisms, including bacteria, viruses, and parasites. Hypochlorous acid HOCl and hypothiocyanous acid HOSCN synthesized through the enzyme myeloperoxidase MPO, which catalyzes the reaction between H2O2 and Cl− or SCN−, are important inorganic bactericidal molecules, effective against a wide range of microbes. This review also discusses the role of antimicrobial peptides AMPs and their induction of ROS. In summary, reactive species RS are the heart of the innate immune system, and they are necessary for microbial lysis in infections that can affect mammals throughout their lives.