Investigations upon the Improvement of Dermatophyte Identification Using an Online Mass Spectrometry Application

Online MALDI-TOF mass spectrometry applications, such as MSI-2, have been shown to help identify dermatophytes, but recurrent errors are still observed between phylogenetically close species. The objective of this study was to assess different approaches to reduce the occurrence of such errors by adding new reference spectra to the MSI-2 application. Nine libraries were set up, comprising an increasing number of spectra obtained from reference strains that were submitted to various culture durations on two distinct culture media: Sabouraud gentamicin chloramphenicol medium and IDFP Conidia medium. The final library included spectra from 111 strains of 20 species obtained from cultures on both media collected every three days after the appearance of the colony. The performance of each library was then analyzed using a cross-validation approach. The spectra acquisitions were carried out using a Microflex Bruker spectrometer. Diversifying the references and adding spectra from various culture media and culture durations improved identification performance. The percentage of correct identification at the species level rose from 63.4 to 91.7% when combining all approaches. Nevertheless, residual confusion between close species, such as Trichophyton rubrum, Trichophyton violaceum and Trichophyton soudanense, remained. To distinguish between these species, mass spectrometry identification should take into account basic morphological and/or clinico-epidemiological features.

Individual coactivation patterns improve the subject identification and their behavior association

Brain states can be characterized by recurring coactivation patterns (CAPs). Traditional CAP analysis is performed at the group-level, while the human brain is individualized and the functional connectome has shown the uniqueness as fingerprint. Whether stable individual CAPs could be obtained from a single fMRI scan and could individual CAPs improve the identification is unclear. An open dataset, the midnight scan club was used in this study to answer these questions. Four CAP states were identified at three distinct levels (group-, subject- and scan-level) separately, and the CAPs were then reconstructed for each scan. Identification rate and differential identifiability were used to evaluate the identification performance. Our results demonstrated that the individual CAPs were unstable when using a single scan. By maintaining high intra-subject similarity and inter-subject differences, subject-level CAPs achieved the best identification performance. Brain regions that contributed to the identifiability were mainly located in higher-order networks (e.g., frontal-parietal network). Besides, head motion reduced the intra-subject similarity, while its impact on identification rate was non-significant. Finally, a pipeline was developed to depict brain-behavior associations in dataset with few samples but dense sampling, and individualized CAP dynamics showed an above-chance level correlation with IQ.

Research on RFID Anticollision Algorithms in Industrial Internet of Things

As a perception enabling technology of the Internet of Things, RFID can quickly identify target objects. The tag-to-tag collision problem seriously affects the identification performance of the RFID system, which causes the reader to be unable to accurately identify any tag within the specific time. The mainstream anticollision algorithms are limited by the performance bottleneck under the standard framework. In this paper, we analyze the features and merits of three kinds of algorithms in detail and propose a new algorithm architecture for RFID anticollision. Through the extensive experimental results comparison, we prove that the new architecture is effective to improve the performance of DFSA algorithms. Finally, we summarize the future research trends in the RFID anticollision algorithms.

Adaptive Identification and Application of Flow Mapping and Inverse Flow Mapping for Electrohydraulic Valves

Good estimation of flow mapping (FM) and inverse flow mapping (IFM) for electrohydraulic valves are important in automation of fluid power system. The purpose of this paper is to propose adaptive identification methods based on LSM, BPNN, RBFNN, GRNN, LSSVM and RLSM to estimate the uncertain structure and parameters in flow mapping and inverse flow mapping for electrohydraulic valves. In order to reduce the complexity and improve the identification performance, model structures derived from new algorithm are introduced. The above identification methods are applied to map the flow characteristic of an electrohydraulic valve. With the help of novel simulation architecture via OPC UA, the accuracy and efficiency of these algorithms could be verified. Some issues like invertibility of flow mapping are discussed. At last, places and suggestions to apply these methods are made.

Hidden Service Circuit Reconstruction Attacks Based on Middle Node Traffic Analysis

Traffic analysis is widely considered as an attack posing a threat to anonymity of the communication and may reveal the real identity of the users. In this paper, a novel anonymous circuit reconstruction attack method that correlates the circuit traffic is proposed. This method then reconstructs a complete communication tunnel using the location of middle nodes found between the hidden and client services. The attack process includes independent determination of the location of the malicious nodes. A traffic correlation framework of AutoEncoder + CNN + BiLSTM is established, based on the Generative Adversarial Networks (GAN) model. BiLSTM applies the packet size and packet interval features of bidirectional traffic and combines the reconstruction loss function with the discrimination loss function to achieve correlated traffic evaluation. After balancing the reconstruction loss and discrimination loss scores, the simulation results confirm that the identification performance of the proposed system is higher than the advanced models.

Research on Secondary Cable Identification Based on the Principle of Electromagnetic Induction

When the operation and maintenance station performs cable maintenance, installation measures, etc., due to the lack of direct and effective tools, and the complicated wiring of the operation and maintenance station equipment, the wiring diagram is inconsistent with the actual situation, which brings risks to the removal of waste cables. As an indispensable safety tool in the power industry, the cable identification device is an important means to ensure the safety of maintenance personnel. In view of the current situation, this paper analyzes the electric field around the cable line of the operation and maintenance station, and simplifies the simulation of the line, and proposes a secondary cable identification device based on the principle of electromagnetic induction, which can quickly identify the target cable, which greatly improves the cable identification performance. Efficiency reduces the time for cable identification and improves safety.

Odor Identification and Regional Gray Matter Atrophy in Patients with Alzheimer’s Disease, Parkinson’s Disease, and the Healthy Elderly: A Cross-Sectional Structural MRI Study

Multiple associations between impaired olfactory performance and regional cortical and deep gray matter atrophy have been reported in separate studies of patients with Alzheimer’s disease (AD), Parkinson’s disease (PD), and of the healthy elderly. We aimed to evaluate such possible associations among these populations in a unified manner. Twenty AD, twenty PD patients’ and twenty healthy age- and sex-matched controls’ odor identification performance was assessed with the Lithuanian adaptation of the Sniffin’ Sticks 12 odor identification test, followed by morphometric gray matter analysis by MRI using FreeSurfer. AD patients had significantly lower cognitive performance than both PD patients and the healthy elderly, as evaluated with the Mini-Mental State Examination (MMSE). Odor identification performance was significantly worse in AD and PD patients compared with the healthy elderly; AD patients performed slightly worse than PD patients, but the difference was not statistically significant. Among patients with AD, worse odor identification performance was initially correlated with atrophy of multiple cortical and deep gray matter regions known to be involved in olfactory processing, however, only two measures—decreased thicknesses of the right medial and left lateral orbitofrontal cortices—remained significant after adjustment for possible confounders (age, MMSE score, and global cortical thickness). Among patients with PD and the healthy elderly we found no similar statistically significant correlations. Our findings support the key role of the orbitofrontal cortex in odor identification among patients with AD, and suggest that correlations between impaired odor identification performance and regional gray matter atrophy may be relatively more pronounced in AD rather than in PD.

Identifying unfamiliar voices: the influence of sample duration and parade size.

Voice identification parades can be unreliable due to the error-prone nature of earwitness responses. Home Office guidelines (2003) recommend that voice parades should consist of nine-voices, each played for 60-seconds. This makes parades resource-consuming to construct. In the present paper we conducted two experiments to see if voice parade procedures could be simplified. In Experiment 1, we investigated if reducing the duration of the voice samples on a nine-voice parade would negatively affect performance. In Experiment 2, we first explored if the same sample duration conditions used in Experiment 1 would lead to different outcomes if a six-voice parade were used. Following this, we investigated if there were any difference in identification performance based solely on whether a nine-voice (Experiment 1) or six-voice (Experiment 2) parade was used. Overall, the results suggest that voice durations can be safely reduced without disrupting listener performance. Performance on target-absent parades – which simulate an innocent suspect being apprehended – were at chance-levels in both parade sizes, but the increased number of foils in the nine-voice parade offers increased protection to an innocent suspect by virtue of statistical probability. Thus, we argue that the Home Office guidelines recommending a parade with nine-voices should be maintained.