Neuro-symbolic Models for Interpretable Time Series Classification using Temporal Logic Description

Most existing Time series classification (TSC) models lack interpretability and are difficult to inspect. Interpretable machine learning models can aid in discovering patterns in data as well as give easy-to-understand insights to domain specialists. In this study, we present Neuro-Symbolic Time Series Classification (NSTSC), a neuro-symbolic model that leverages signal temporal logic (STL) and neural network (NN) to accomplish TSC tasks using multi-view data representation and expresses the model as a human-readable, interpretable formula. In NSTSC, each neuron is linked to a symbolic expression, i.e., an STL (sub)formula. The output of NSTSC is thus interpretable as an STL formula akin to natural language, describing temporal and logical relations hidden in the data. We propose an NSTSC-based classifier that adopts a decision-tree approach to learn formula structures and accomplish a multiclass TSC task. The proposed smooth activation functions for wSTL allow the model to be learned in an end-to-end fashion. We test NSTSC on a real-world wound healing dataset from mice and benchmark datasets from the UCR time-series repository, demonstrating that NSTSC achieves comparable performance with the state-of-the-art models. Furthermore, NSTSC can generate interpretable formulas that match with domain knowledge

The Activity of Small Urea‐γ‐AApeptides Toward Gram‐Positive Bacteria

Host Defense Peptides (HDPs) have gained considerable interest due to the omnipresent threat of bacterial infection as a serious public health concern. However, development of HDPs is impeded by several drawbacks, such as poor selectivity, susceptibility to proteolytic degradation, low‐to‐moderate activity and requiring complex syntheses. Herein we report a class of lipo‐linear α/urea‐γ‐AApeptides with a hybrid backbone and low molecular weight. The heterogeneous backbone not only enhances chemodiversity, but also shows effective antimicrobial activity against Gram‐positive bacteria and is capable of disrupting bacterial membranes and killing bacteria rapidly. Given their low molecular weight and ease of access via facile synthesis, they could be practical antibiotic agents.Double‐AA peptides: We investigated a new class of small linear molecules as potential antibiotic agents against Gram‐positive bacteria. Our studies suggest that these compounds can disrupt bacterial membranes and kill bacteria rapidly. Given their low molecular weight and ease of accessibility through a facile synthesis approach, they are good candidates for development into antibiotic agents.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152544/1/cmdc201900520-sup-0001-misc_information.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152544/2/cmdc201900520.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/152544/3/cmdc201900520_am.pd

Broadband and continuous wave pumped second-harmonic generation from microfiber coated with layered GaSe crystal

The conversion-efficiency for second-harmonic (SH) in optical fibers is significantly limited by extremely weak second-order nonlinearity of fused silica, and pulse pump lasers with high peak power are widely employed. Here, we propose a simple strategy to efficiently realize the broadband and continuous wave (CW) pumped SH, by transferring a crystalline GaSe coating onto a microfiber with phase-matching diameter. In the experiment, high efficiency up to 0.08 %W-1mm-1 is reached for a C-band pump laser. The high enough efficiency not only guarantees SH at a single frequency pumped by a CW laser, but also multi-frequencies mixing supported by three CW light sources. Moreover, broadband SH spectrum is also achieved under the pump of a superluminescent light-emitting diode source with a 79.3 nm bandwidth. The proposed scheme provides a beneficial method to the enhancement of various nonlinear parameter processes, development of quasi-monochromatic or broadband CW light sources at new wavelength regions

3,5,4′-Tri-O-acetylresveratrol Attenuates Lipopolysaccharide-Induced Acute Respiratory Distress Syndrome via MAPK/SIRT1 Pathway

The aim of the present research was to investigate the protecting effects of 3,5,4′-tri-O-acetylresveratrol (AC-Rsv) on LPS-induced acute respiratory distress syndrome (ARDS). Lung injuries have been evaluated by histological examination, wet-to-dry weight ratios, and cell count and protein content in bronchoalveolar lavage fluid. Inflammation was assessed by MPO activities and cytokine secretion in lungs and cells. The results showed that AC-Rsv significantly reduced the mortality of mice stimulated with LPS. Pretreatment of AC-Rsv attenuated LPS-induced histological changes, alleviated pulmonary edema, reduced blood vascular leakage, and inhibited the MPO activities in lungs. What was more, AC-Rsv and Rsv treatment reduced the secretion of TNF-α, IL-6, and IL-1β in lungs and NR8383 cells, respectively. Further exploration revealed that AC-Rsv and Rsv treatment relieved LPS-induced inhibition on SIRT1 expression and restrained the activation effects of LPS on MAPKs and NF-κB activation both in vitro and in vivo. More importantly, in vivo results have also demonstrated that the protecting effects of Rsv on LPS-induced inflammation would be neutralized when SIRT1 was in-hibited by EX527. Taken together, these results indicated that AC-Rsv protected lung tissue against LPS-induced ARDS by attenuating inflammation via p38 MAPK/SIRT1 pathway

Ecological vulnerability assessment of coral islands and reefs in the South China Sea based on remote sensing and reanalysis data

Coral reefs are ecosystems that are highly vulnerable to external environmental impacts, including changes associated with ocean acidification and global warming. Assessing the vulnerability of coral reef growth environments over large areas of the sea is a difficult and complex process, as it is influenced by many variables. There are few studies on environmental vulnerability assessment of coral islands and reefs in the South China Sea. It is therefore particularly important to understand the environmental sensitivity of corals and how coral communities respond to changes in climate-related environmental variables. In this study, indicators were selected mainly from natural environmental factors that hinder the development of coral reefs. The sea surface temperature (SST), sea surface salinity (SSS), wind velocity (WV) and direction, sea level height (SL), ocean currents (OC), and chlorophyll concentration (Chl) of coral reefs in South China Sea Island were integrated to calculate the coral reef environmental vulnerability region. In a GIS environment, Spatial Principal Component Analysis (SPCA) was used to develop sensitivity models and evaluate the ecological vulnerability of coral reefs. Based on the Environmental vulnerability indicator (EVI) values, the study area was classified as 5 grades of ecological vulnerability: Potential (0.000–0.577), Light (0.577–0.780), Medium (0.780–0.886), Heavy (0.886–0.993) and Very Heavy (0.993–1.131). Sensitivity models identified regional gradients of environmental stress and found that some coral reefs in western Malaysia and southwestern Philippines have higher vulnerability. Meanwhile, the study found that the reefs of Paracel Islands and Macclesfield Bank areas of medium vulnerability. Future use of high-precision data from long time series will allow better estimates of site-specific vulnerability and allow for the precise establishment of marine protected areas so that the ecological diversity of coral reefs can be sustained

SoccerNet 2023 Challenges Results

peer reviewedThe SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vision-based tasks split into three main themes. The first theme, broadcast video understanding, is composed of three high-level tasks related to describing events occurring in the video broadcasts: (1) action spotting, focusing on retrieving all timestamps related to global actions in soccer, (2) ball action spotting, focusing on retrieving all timestamps related to the soccer ball change of state, and (3) dense video captioning, focusing on describing the broadcast with natural language and anchored timestamps. The second theme, field understanding, relates to the single task of (4) camera calibration, focusing on retrieving the intrinsic and extrinsic camera parameters from images. The third and last theme, player understanding, is composed of three low-level tasks related to extracting information about the players: (5) re-identification, focusing on retrieving the same players across multiple views, (6) multiple object tracking, focusing on tracking players and the ball through unedited video streams, and (7) jersey number recognition, focusing on recognizing the jersey number of players from tracklets. Compared to the previous editions of the SoccerNet challenges, tasks (2-3-7) are novel, including new annotations and data, task (4) was enhanced with more data and annotations, and task (6) now focuses on end-to-end approaches. More information on the tasks, challenges, and leaderboards are available on https://www.soccer-net.org. Baselines and development kits can be found on https://github.com/SoccerNet

Role mining based on weights

Role mining from the existing permissions has been widely applied to aid the process of migrating to an RBAC system. While all permissions are treated evenly in previous approaches, none of the work has employed the weights of permissions in role mining to our knowledge, thus providing the motivation for this work. In this paper, we generalize this to the case where permissions are given weights to reflect their importance to the system. The weights can correspond to the property of operations, the sensitive degree of objects, and the attribute of users associated with permissions. To calculate the weight of permissions, we introduce the concept of similarity between both users and permissions, and use a similarity matrix to reinforce the similarity between permissions. Then we create a link between the reinforced similarity and the weight of permissions. We further propose a weighted role mining algorithm to generate roles based on weights. Experiments on performance study prove the superiority of the new algorithm

Analyst optimism, information disclosure, and stock price collapse risk: Empirical insights from China's A-share market.

This study selects stock data of listed companies in China's A-share stock market from 2011 to 2020 as research samples. Using a fixed-effects model, it examines the impact of analyst optimism on stock price collapses and the moderating effect of information disclosure quality. Simultaneously, it conducts additional research to explore the potential transmission mechanisms involved. The main findings are as follows: Firstly, a positive correlation exists between analyst optimism and the risk of stock price collapse. Secondly, improving information disclosure quality of listed companies can enhance the positive impact of analyst optimism on the risk of stock price collapses and expedite the market's adjustment of overly optimistic valuations of listed companies. Additionally, analyst optimism can increase the risk of stock price collapses by affecting institutional ownership. These findings provide theoretical support for regulatory authorities to revise and improve the "information disclosure evaluation" system, regulate the analyst industry, guide analyst behavior, and encourage listed companies to enhance internal governance and improve information disclosure practices

Predictors of Clinical Outcomes in Adult Laryngotracheal Stenosis

OBJECTIVESSequelae of laryngotracheal stenosis (LTS) can be devastating, often necessitating tracheostomy. This study aims to describe the characteristics and outcomes of patients with LTS and identify risk factors for long-term tracheostomy dependence stratified by etiology. METHODSA retrospective chart review was performed on 215 patients diagnosed with LTS from 09/01/2011 to 12/31/2020. Patients were grouped based on the cause of LTS. Patient factors were compared to evaluate risk factors for long-term tracheostomy dependence. RESULTSOf the 215 patients, 129 (60%) were classified as iatrogenic, 41 (19%) idiopathic, 10 (4.7%) cancer treatment, 18 (8.3%) autoimmune, and 17 (8%) patients unknown. Idiopathic patients were significantly less likely to be tracheostomy-dependent compared with iatrogenic patients (p < 0.001) and cancer patients (p < 0.05). The mortality rate did not significantly differ among the categories (p = 0.1078). Significant improvement was seen after treatment, as the median percent of stenosis at presentation was 52.5%, and the median percent of stenosis at the most recent visit was 10% (p < 0.001). The autoimmune group received the most steroid injections (mean = 6.56; SD = 11.96). The idiopathic group had the longest surgery-free interval (mean = 30.8 months; SD = 27.7). CONCLUSIONIatrogenic and cancer patients were more likely to be tracheostomy-dependent. There was a significant improvement in percent and length of stenosis after treatment, with the idiopathic group having the longest surgery-free interval. Mortality risk did not differ among the different etiologies of LTS. LEVEL OF EVIDENCELevel 3 Laryngoscope, 2023