Production Mechanism of the Charmed Baryon Λc+

As the lightest charmed baryon, precision measurement of the pair production cross section of Λc+ provides unprecedented experimental information for the investigation of baryon production mechanism. In addition, the extraction of the polar angle distributions of the outgoing Λc+ in the annihilation of the electron–positron help to determine its electromagnetic form factors, which is currently the unique key to access the internal structure of the baryons. In this article, the measurement of e+e−→Λc+Λ¯c− process via the initial state radiation technique at Belle detector and direct electron–positron annihilation at BESIII with discrete center-of-mass energies near threshold are briefly reviewed. In addition, the electromagnetic form factor ratios of Λc+ measured by BESIII are also investigated. A few theoretical models that parameterize the center-of-mass energy dependence of the cross section and electromagnetic form factors of baryon are introduced and the contributions of Λc+ data to them are discussed

Experimental Review of ΛΛ¯ Production

Exclusive hyperon-antihyperon production provides a unique insight for understanding of the intrinsic dynamics when strangeness is involved. In this paper, we review the results of ΛΛ¯ production via different reactions from various experiments, e.g., via p¯p annihilation from the LEAR experiment PS185, via electron-positron annihilation using the energy scan method at the CLEO-c and BESIII experiments and the initial-state-radiation approach utilized at the BaBar experiment. The production cross section of ΛΛ¯ near the threshold is sensitive to QCD based prediction. Experimental high precision data for p¯p→Λ¯Λ close to the threshold region is obtained. The cross section of e+e−→ΛΛ¯ is measured from its production threshold to high energy. A non-zero cross section for e+e−→ΛΛ¯ near threshold is observed at BaBar and BESIII, which is in disagreement with the pQCD prediction. However, more precise data is needed to confirm this observation. Future experiments, utilizing p¯p reaction such as PANDA experiment or electron-positron annihilation such as the BESIII and BelleII experiments, are needed to extend the experimental data and to understand the ΛΛ¯ production

A real-time, practical sensor fault-tolerant module for robust EMG pattern recognition

BACKGROUND: Unreliability of surface EMG recordings over time is a challenge for applying the EMG pattern recognition (PR)-controlled prostheses in clinical practice. Our previous study proposed a sensor fault-tolerant module (SFTM) by utilizing redundant information in multiple EMG signals. The SFTM consists of multiple sensor fault detectors and a self-recovery mechanism that can identify anomaly in EMG signals and remove the recordings of the disturbed signals from the input of the pattern classifier to recover the PR performance. While the proposed SFTM has shown great promise, the previous design is impractical. A practical SFTM has to be fast enough, lightweight, automatic, and robust under different conditions with or without disturbances. METHODS: This paper presented a real-time, practical SFTM towards robust EMG PR. A novel fast LDA retraining algorithm and a fully automatic sensor fault detector based on outlier detection were developed, which allowed the SFTM to promptly detect disturbances and recover the PR performance immediately. These components of SFTM were then integrated with the EMG PR module and tested on five able-bodied subjects and a transradial amputee in real-time for classifying multiple hand and wrist motions under different conditions with different disturbance types and levels. RESULTS: The proposed fast LDA retraining algorithm significantly shortened the retraining time from nearly 1 s to less than 4 ms when tested on the embedded system prototype, which demonstrated the feasibility of a nearly “zero-delay” SFTM that is imperceptible to the users. The results of the real-time tests suggested that the SFTM was able to handle different types of disturbances investigated in this study and significantly improve the classification performance when one or multiple EMG signals were disturbed. In addition, the SFTM could also maintain the system’s classification performance when there was no disturbance. CONCLUSIONS: This paper presented a real-time, lightweight, and automatic SFTM, which paved the way for reliable and robust EMG PR for prosthesis control

A real-time, practical sensor fault-tolerant module for robust EMG pattern recognition

BackgroundUnreliability of surface EMG recordings over time is a challenge for applying the EMG pattern recognition (PR)-controlled prostheses in clinical practice. Our previous study proposed a sensor fault-tolerant module (SFTM) by utilizing redundant information in multiple EMG signals. The SFTM consists of multiple sensor fault detectors and a self-recovery mechanism that can identify anomaly in EMG signals and remove the recordings of the disturbed signals from the input of the pattern classifier to recover the PR performance. While the proposed SFTM has shown great promise, the previous design is impractical. A practical SFTM has to be fast enough, lightweight, automatic, and robust under different conditions with or without disturbances.MethodsThis paper presented a real-time, practical SFTM towards robust EMG PR. A novel fast LDA retraining algorithm and a fully automatic sensor fault detector based on outlier detection were developed, which allowed the SFTM to promptly detect disturbances and recover the PR performance immediately. These components of SFTM were then integrated with the EMG PR module and tested on five able-bodied subjects and a transradial amputee in real-time for classifying multiple hand and wrist motions under different conditions with different disturbance types and levels.ResultsThe proposed fast LDA retraining algorithm significantly shortened the retraining time from nearly 1s to less than 4ms when tested on the embedded system prototype, which demonstrated the feasibility of a nearly “zero-delay” SFTM that is imperceptible to the users. The results of the real-time tests suggested that the SFTM was able to handle different types of disturbances investigated in this study and significantly improve the classification performance when one or multiple EMG signals were disturbed. In addition, the SFTM could also maintain the system’s classification performance when there was no disturbance.ConclusionsThis paper presented a real-time, lightweight, and automatic SFTM, which paved the way for reliable and robust EMG PR for prosthesis control

Virulence Attributes and Hyphal Growth of C. neoformans Are Quantitative Traits and the MATα Allele Enhances Filamentation

Cryptococcus neoformans is a fungal human pathogen with a bipolar mating system. It undergoes a dimorphic transition from a unicellular yeast to hyphal filamentous growth during mating and monokaryotic fruiting. The traditional sexual cycle that leads to the production of infectious basidiospores involves cells of both α and a mating type. Monokaryotic fruiting is a modified form of sexual reproduction that involves cells of the same mating type, most commonly α, which is the predominant mating type in both the environment and clinical isolates. However, some a isolates can also undergo monokaryotic fruiting. To determine whether mating type and other genetic loci contribute to the differences in fruiting observed between α and a cells, we applied quantitative trait loci (QTL) mapping to an inbred population of F(2) progeny. We discovered that variation in hyphal length produced during fruiting is a quantitative trait resulting from the combined effects of multiple genetic loci, including the mating type (MAT) locus. Importantly, the α allele of the MAT locus enhanced hyphal growth compared with the a allele. Other virulence traits, including melanization and growth at 39 °C, also are quantitative traits that share a common QTL with hyphal growth. The Mac1 transcription factor, encoded in this common QTL, regulates copper homeostasis. MAC1 allelic differences contribute to phenotypic variation, and mac1Δ mutants exhibit defects in filamentation, melanin production, and high temperature growth. Further characterization of these QTL regions will reveal additional quantitative trait genes controlling biological processes central to fungal development and pathogenicity

Ferroelectric higher-order topological insulator in two dimensions

The interplay between ferroelectricity and band topology can give rise to a wide range of both fundamental and applied research. Here, we map out the emergence of nontrivial corner states in two-dimensional ferroelectrics, and remarkably demonstrate that ferroelectricity and corner states are coupled together by crystallographic symmetry to realize the electric control of higher-order topology. Implemented by density functional theory, we identify a series of experimentally synthesized two-dimensional ferroelectrics, such as In$_2$Se$_3$, BN bilayers, and SnS, as realistic material candidates for the proposed ferroelectric higher-order topological insulators. Our work not only sheds new light on traditional ferroelectric materials but also opens an avenue to bridge the higher-order topology and ferroelectricity that provides a nonvolatile handle to manipulate the topology in next-generation electronic devices