Miracle-dz/UniFAR-FTUs huggingface dataset:
Ensemble Transformer-Based Neural Networks Detect Heart Murmur in Phonocardiogram Recordings

Cardiac auscultation through phonocardiogram (PCG) is still the most commonly used approach for evaluating the mechanical functionality of the heart when diagnosing congenital heart disease. Despite of its time- and cost-effectiveness, it is still limited due to the extensive need for clinical expertise for interpretation. In this study, we propose the use of ensemble transformer-based neural networks to aid in the detection of heart murmur in PCG recordings and for the prediction of clinical outcomes of patients as part of George B. Moody PhysioNet 2022 Challenge. Our team, Care4MyHeart, developed an approach that transforms the raw PCG recordings into wavelet power features signals for the use within the proposed deep learning models. We have achieved a maximum accuracy of 0.855, 0.761, and 0.757 for murmur detection in the training, hidden validation, and hidden testing datasets, respectively. In addition, we had an overall clinical outcome cost of 9980, 11490, and 14410 for the three datasets, respectively. Our team was ranked 6th/40 for murmur detection and 29th/40 for clinical outcome predictions. We had the lowest clinical outcome cost on the validation set of 9737 with a murmur detection score of 0.730 when reducing the number of features used to train the models.
The life and work of Joseph Fraunhofer (1787−1826)

Fraunhofer perfected methods for making optical glass and for testing its quality. He studied the dark lines in the spectrum of sunlight and used them to chart the dispersion of optical material with a precision spectrometer. He used scientific methods to produce truly excellent achromatic and aplanatic lenses, and optical instruments including astronomical refracting telescopes of large aperture. He analyzed diffraction patterns with precision; discovered the spectroscopic uses of gratings; made gratings ruled with up to 7670 lines/in. , and determined wavelengths of Fraunhofer lines to four significant figures. He also noted the phenomenon of grating blaze, the polarizing effect of gratings, and effects of periodic errors in the rulings.
Herbivore assemblages affect soil microbial communities by altering root biomass and available nutrients in an alpine meadow

Three different herbivore grazing assemblages, namely, yak grazing (YG), Tibetan sheep grazing (SG) and yak and Tibetan sheep co-grazing (MG), are practiced in alpine meadows on the Qinghai-Tibetan Plateau (QTP), but the effects of the different herbivore assemblages on soil microbes are relatively unknown. The microbial community plays an important role in the functional stability of alpine grassland ecosystems. Therefore, it is important to understand how the microbial community structure of grassland ecosystems changes under different herbivore grazing assemblages to ensure their sustainable development. To fill this gap, a field study was carried out to investigate the effects of YG, SG, and MG on plant communities, soil physico-chemical properties and microbial communities under moderate grazing intensity in alpine meadows. Grazing increased the β-diversity of the bacteria community and decreased the β-diversity of the fungal community. The herbivore assemblage affected the microbial community diversity, but not the plant community diversity. Total phosphorus, soil bulk density, root biomass, and plant α-diversity were correlated with both the bacterial and fungal community composition, available phosphorus and soil moisture were correlated only with the bacterial community composition, while available potassium and above-ground net primary production (ANPP) were correlated only with the fungal community composition. Soil available nitrogen, soil available phosphorus and soil bulk density were highest in SG, while ANPP was highest in MG. It was concluded that MG can improve ANPP and stabilize the soil microbial community, suggesting that MG is an effective method for sustainable use and conservation of alpine meadows on the QTP.
GPTree Cluster: phylogenetic tree cluster generator in the context of supertree inference

Abstract Summary For many years, evolutionary and molecular biologists have been working with phylogenetic supertrees, which are oriented acyclic graph structures. In the standard approaches, supertrees are obtained by concatenating a set of phylogenetic trees defined on different but overlapping sets of taxa (i.e. species). More recent approaches propose alternative solutions for supertree inference. The testing of new metrics for comparing supertrees and adapting clustering algorithms to overlapping phylogenetic trees with different numbers of leaves requires large amounts of data. In this context, designing a new approach and developing a computer program to generate phylogenetic tree clusters with different numbers of overlapping leaves are key elements to advance research on phylogenetic supertrees and evolution. The main objective of the project is to propose a new approach to simulate clusters of phylogenetic trees defined on different, but mutually overlapping, sets of taxa, with biological events. The proposed generator can be used to generate a certain number of clusters of phylogenetic trees in Newick format with a variable number of leaves and with a defined level of overlap between trees in clusters. Availability and implementation A Python script version 3.7, called GPTree Cluster, which implements the discussed approach, is freely available at: https://github.com/tahiri-lab/GPTree/tree/GPTreeCluster
Establishment and application of the performance appraisal system for hierarchical diagnosis and treatment in China: A case study in Fujian province

Purpose Hierarchical diagnosis and treatment, as an important measure and direction for China's medical reform, are conducive to improving the capacity of medical services and the national level of health. In this study, a hierarchical diagnosis and treatment performance evaluation index system is established to identify the effects of different influencing factors on developing hierarchical diagnosis and treatment. Methods In this study, samples collected from 23 representative integrated medical institutions in nine Fujian cities from 2018 to 2020 are taken as subjects. A hierarchical diagnosis and treatment performance appraisal system is established based on the mechanism of research on the operation of hierarchical diagnosis and treatment. This is combined with the evaluation index system established by the Health Development Research Center, the National Health Commission of the People's Republic of China for the evaluation of hierarchical diagnosis and treatment and the construction of the medical treatment alliance, including studies carried out by related scholars. The weight of each evaluation index is determined with the CRITIC method, and the hierarchical diagnosis and treatment effects on 23 subjects are quantitatively evaluated by the Gray correlation method based on the weight of each index. Results The hierarchical diagnosis and treatment performance evaluation index system is established from three aspects, namely allocation of hierarchical diagnosis and treatment resources, establishment of the hierarchical diagnosis and treatment management system, and hierarchical diagnosis and treatment implementation effect; 27 tertiary indexes are formed in total. The Gray correlation of each year in Fujian exceeds 0.5, but <0.53. Conclusion Gray correlation of each year in Fujian has gradually increased. But there is still room for improvement. The government departments must improve the investment in medical resources with measures adjusted according to local conditions, promote a balanced allocation of resources for hierarchical diagnosis and treatment, increase communication and interaction between upper and lower medical institutions, and optimize the allocation of resources for hierarchical diagnosis and treatment. Then determine the types of disease to be treated, expand the coverage of chronic disease management, establish standardized chronic disease health management, and strengthen training of health management staff.
An LSTM-based Listener for Early Detection of Heart Disease

As a contribution to the George B. Moody PhysioNet Challenge 2022 we (team listNto_urHeart) propose a phonocardiogram classifier. Based on the assumption that these recordings bear similarity to music, we borrow methods from the field of computational music analysis. In contrast to end-to-end machine learning approaches, we propose a carefully-crafted processing pipeline for automatically detecting single heartbeats in phonocardiogram recordings which are then classified by a bi-directional long short-term memory network. Our approach has the advantage of not requiring manual annotations during training, therefore alleviating the lack of annotated training data. In murmur detection, we reached a weighted accuracy of 0.68 in validation, 0.668 in test (rank: 25/40) and 0.64 $\pm 0.08$ during training. In predicting patient outcome, we reached 10,362 in validation, 13,866 in test (rank: 27 /39) and 11, $386\pm 2,108$ during training. The results indicate that borrowing algorithms from computational music analysis could bear the potential to address challenges in phonocardiogram classification successfully.
A Review of Low-Density Lipoprotein-Lowering Diets in the Age of Anti-Sense Technology

This narrative review discusses an important issue, the primary role of diet in reducing low-density lipoprotein cholesterol (LDLc) concentrations in polygenic hypercholesterolemia. Two effective drugs, statins, and ezetimibe, that lower LDLc > 20% are relatively inexpensive and potential competitors to strict dieting. Biochemical and genomic studies have shown that proprotein convertase subtilisin kexin type 9 (PCSK9) plays an important role in low-density lipoprotein (LDL) and lipid metabolism. Clinical trials have demonstrated that inhibitory monoclonal antibodies of PCSK9 dose-dependently lower LDLc up to 60%, with evidence of both regression and stabilization of coronary atherosclerosis and a reduction in cardiovascular risk. Recent approaches using RNA interference to achieve PCSK9 inhibition are currently undergoing clinical evaluation. The latter presents an attractive option of twice-yearly injections. They are, however, currently expensive and unsuitable for moderate hypercholesterolemia, which is largely due to inappropriate patterns of eating. The best dietary approach, the substitution of saturated fatty acids by polyunsaturated fatty acids at 5% energy, yields > 10% lowering of LDLc. Foods such as nuts and brans, especially within a prudent, plant-based diet low in saturates complemented by supplements such as phytosterols, have the potential to reduce LDLc further. A combination of such foods has been shown to lower LDLc by 20%. A nutritional approach requires backing from industry to develop and market LDLc-lowering products before pharmacology replaces the diet option. Energetic support from health professionals is vital.
Cascading Dynamics of Heterogenous Scale-Free Networks with Recovery Mechanism

In network security, how to use efficient response methods against cascading failures of complex networks is very important. In this paper, concerned with the highest-load attack (HL) and random attack (RA) on one edge, we define five kinds of weighting strategies to assign the external resources for recovering the edges from cascading failures in heterogeneous scale-free (SF) networks. The influence of external resources, the tolerance parameter, and the different weighting strategies on SF networks against cascading failures is investigated carefully. We find that, under HL attack, the fourth kind of weighting method can more effectively improve the integral robustness of SF networks, simultaneously control the spreading velocity, and control the outburst of cascading failures in SF networks than other methods. Moreover, the third method is optimal if we only knew the local structure of SF networks and the uniform assignment is the worst. The simulations of the real-world autonomous system in, Internet have also supported our findings. The results are useful for using efficient response strategy against the emergent accidents and controlling the cascading failures in the real-world networks.
The matching conditions of controlled Lagrangians and IDA-passivity based control

This paper discusses the matching conditions resulting from the controlled Lagrangians method and the interconnection and damping assignment passivity based control (IDA-PBC) method. Both methods have been presented recently in the literature as means to stabilize a desired equilibrium point of an Euler-Lagrange, respectively Hamiltonian, system. In the context of mechanical systems with symmetry, the original controlled Lagrangians method is reviewed, and an interpretation of the matching assumptions in terms of the matching of kinetic and potential energy is given. Secondly, both methods are applied to the general class of underactuated mechanical systems and it is shown that the controlled Lagrangians method is contained in the IDA-PBC method. The u -method as described in recent papers for the controlled Lagrangians method, transforming the matching conditions (a set of non-linear PDEs) into a set of linear PDEs, is discussed. The method is used to transform the matching conditions obtained in the IDA-PBC method into a set of quadratic and linear PDEs. Finally, the extra freedom obtained in the IDA-PBC method (with respect to the controlled Lagrangians method) is used to discuss the integrability of the closed-loop system. Explicit conditions are derived under which the closed-loop Hamiltonian system is integrable, leading to the introduction of gyroscopic terms.
Equivariant method for periodic maps

The notion of coherency with submanifolds for a Morse function on a manifold is introduced and discussed in a general way. A Morse inequality for a given periodic transformation which compares the invariants called qth Euler numbers on fixed point set and the invariants called qth Lefschetz numbers of the transformations is thus obtained. This gives a fixed point theorem in terms of qth Lefschetz number for arbitrary q. Letf be a periodic transformation of a closed m-dimensional manifold M with fixed point set N. We develop in this note an equivariant approach using Morse theory. We introduce in ? 2 the notion of coherency with a submanifold S of M for a Morse function and show that such S-coherent Morse functions are dense in C (M). Furthermore, in this approximation f-invariance will be preserved (? 3). The coherency with the fixed point set N of f makes it possible to compare the difference of qth Euler number of N and qth Lefschetz number of f. More precisely, let /8q(N) and Aq(f) be respectively the qth Betti numbers of N and the trace of f* on the qth homology group Hq(M) with real coefficients. Let Bq(N) and Aq(f) be their alternative sums respectively, i.e., 13q(N) = Aq(N) 13q_j(N) + _. + (_1)qpo3(N), Aq(f) = Xq(fq) -X l (q) + *_* * + (-l)qXo(f), where 0 < q < m. We establish in ? 5 an inequality for arbitrary q that I 1q(N) Aq(f A) is no greater than the qth Morse difference of an arbitrary finvariant N-coherent Morse function. We obtain as corollaries a fixed point theorem in terms of arbitrary Aq (when q = m, this is the Lefschetz fixed point theorem) and a more geometric proof of the fact that P. (N) = An(f), i.e., the Euler number of N is equal to the Lefschetz number of f. The Lemma 1 (? 1) which states that a smooth function can be approximated by a Morse function with prescribed "boundary value" is essential to the construction of the approximations. 1. A Morse extension. For a real-valued smooth function F on M, let C(F) denote the set of all critical points of F. F is called a Morse function if for any p E C(F), the determinant of the Hessian at p does not vanish. We assume without loss of generality that M is a riemannian manifold with a metric g. Let g,j be the metric tensor of g with respect to a local coordinate (xi) Received by the editors November 12, 1971 and, in revised form, June 24, 1972. AMS (MOS) subject classifications (1970). Primary 57D70, 53C99.
Investigating the Extracellular-Electron-Transfer Mechanisms and Kinetics of Shewanella decolorationis NTOU1 Reducing Graphene Oxide via Lactate Metabolism

Microbial graphene oxide reduction is a developing method that serves to reduce both production costs and environmental impact in the synthesis of graphene. This study demonstrates microbial graphene oxide reduction using Shewanella decolorationis NTOU1 under neutral and mild conditions (pH = 7, 35 °C, and 1 atm). Graphene oxide (GO) prepared via the modified Hummers’ method is used as the sole solid electron acceptor, and the characteristics of reduced GO (rGO) are investigated. According to electron microscopic images, the surface structure of GO was clearly changed from smooth to wrinkled after reduction, and whole cells were observed to be wrapped by GO/rGO films. Distinctive appendages on the cells, similar to nanowires or flagella, were also observed. With regard to chemical-bonding changes, after a 24-h reaction of 1 mg mL−1, GO was reduced to rGO, the C/O increased from 1.4 to 3.0, and the oxygen-containing functional groups of rGO were significantly reduced. During the GO reduction process, the number of S. decolorationis NTOU1 cells decreased from 1.65 × 108 to 1.03 × 106 CFU mL−1, indicating the bactericide effects of GO/rGO. In experiments adding consistent concentrations of initial bacteria and lactate, it was shown that with the increase of GO additions (0.5–5.0 mg mL−1), the first-order reaction rate constants (k) of lactate metabolism and acetate production increased accordingly; in experiments adding consistent concentrations of initial bacteria and GO but different lactate levels (1 to 10 mM), the k values of lactate metabolism did not change significantly. The test results of adding different electron transfer mediators showed that riboflavin and potassium ferricyanide were able to boost GO reduction, whereas 2,6-dimethoxy-1,4-benzoquinone and 2,6-dimethyl benzoquinone completely eliminated bacterial activity.
Toward a standardized methodology for sampling dung beetles (Coleoptera: Scarabaeinae) in the Neotropics: A critical review

Introduction The standardization of sampling protocols is imperative for robustly studying any taxonomic group. Replicable methods allow the comparison of data between different spatial and temporal studies. In the case of dung beetles, one of the best-studied indicator groups in analyses of environmental disturbance, a wide range of collection methodologies are used, from basic pitfall traps to more complex or complementary methods such as mini-Winkler extractor. Also, different types of attractive baits, sampling effort, durations, and designs are used in dung beetle studies. Variations in methodological approaches are particularly noted in the Neotropics, which may be related to the vast number of biological strategies and behavior of dung beetles that inhabit this region. A lack of methodological unification for the Neotropical region makes a cross-sectional analysis of the information impossible. Methods We performed a compilation and analytical review of the existing literature for dung beetle sampling in the Neotropics, discussing the most used methodologies, their advantages and disadvantages, and specific cases in which particular models are more efficient. Results Pitfall traps baited with human excrement are the most common sampling method, but there is a wide range of models and variations in the structure of this trap. The complementary effect generated by flight interception traps, light traps, and direct collections, particularly within microhabitats, is exciting for the potential of finding new species. Some methodologies, such as mini-Winkler extractor, fogging, or very specific baits, are infrequently used. Discussion There was a lack of inclusion of spatial and temporal variation among studies. Therefore, it is necessary to consider broader sampling windows, which include different spatial scales, seasons, and years. Finally, we propose a standard protocol for sampling dung beetles in the Neotropics, depending on each objective, and including a basic methodology for obtaining complete local inventories.
Influence of pressurization rate and mode on cell damage of Escherichia coli and Staphyloccocus aureus by high hydrostatic pressure

As a non-thermal technology, high hydrostatic pressure (HHP) has been widely investigated for inactivating microorganisms in food. Few studies have been presented on the pressurization/depressurization rate and mode of microbial inactivation. In this study, effect of pressurization rate and mode on Escherichia coli and Staphylococcus aureus cell damage during HHP treatment was investigated. The results showed that fast pressurization + linear mode (FL) treatment has the best bactericidal effect on E. coli and S. aureus, followed by fast pressurization + stepwise mode (FS) and slow pressurization + stepwise mode (SS) treatments. FL treatment caused more morphological damage to the cell wall, cell membrane, and cytoplasmic components compared with FS and SS treatment detected by SEM and TEM. Additionally, the damage to membrane permeability of them was also enhanced after FL treatment. Therefore, our results indicated that FL treatment could be applied to enhance the bactericidal effect of HHP on bacteria by increasing the damage to cell morphological structure and membrane integrity.
Murmur Detection and Clinical Outcome Classification Using a VGG-like Network and Combined Time-Frequency Representations of PCG Signals

For the George B. Moody PhysioNet Challenge 2022, our team, PhysioDreamfly, developed a deep neural network approach for detecting murmurs and identifying abnormal clinical outcomes from phonocardiograms (PCGs). In our approach, a VGG-like CNN model is used as the classifier. Images consisting of Log-Mel spectrograms and wavelet scalogram that transformed from unsegmented PCGs are used as model inputs. We combined the murmur and outcome labels to address the two tasks as one multi-label task, and introduced a weighted focal loss function to optimize the model. Our murmur detection classifier received a weighted accuracy score of 0.752 (ranked 11th out of 40 teams) and Challenge cost score of 12831(ranked 18th out of 39 teams) on the hidden test set.