Miracle-dz/UniFAR-FTUs huggingface dataset:
Poly(3,4-ethylenedioxythiophene): Poly(styrenesulfonate)/Carbon Nanotube-Coated Electrically Conducting Fabrics With High Strain Sensitivity

Knitted fabrics are widely used in smart textiles due to their great elasticity and reversibility, which make them good platforms for multifunctional fabrics, such as wearable strain sensors. In this study, a new method to make high strain-sensing knitted fabrics was proposed by coating the carbon nanotube solution first and then spraying the poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) solution on 1 × 1 rib knitted fabric. The results showed that 0.1 wt% PEDOT:PSS/3 wt% carbon nanotube-coated knitted fabrics exhibited the best comprehensive performance. Their gauge factor reached 18.3 in the linear rising strain stage and showed excellent stability in cyclic stretching with a strain of 5%. Furthermore, the knitted fabric strain sensor exhibited a quick and precise response to the knee joint motion detection, demonstrating its potential in wearable applications.
hMENA isoforms regulate cancer intrinsic type I IFN signaling and extrinsic mechanisms of resistance to immune checkpoint blockade in NSCLC

Background Understanding how cancer signaling pathways promote an immunosuppressive program which sustains acquired or primary resistance to immune checkpoint blockade (ICB) is a crucial step in improving immunotherapy efficacy. Among the pathways that can affect ICB response is the interferon (IFN) pathway that may be both detrimental and beneficial. The immune sensor retinoic acid-inducible gene I (RIG-I) induces IFN activation and secretion and is activated by actin cytoskeleton disturbance. The actin cytoskeleton regulatory protein hMENA, along with its isoforms, is a key signaling hub in different solid tumors, and recently its role as a regulator of transcription of genes encoding immunomodulatory secretory proteins has been proposed. When hMENA is expressed in tumor cells with low levels of the epithelial specific hMENA11a isoform, identifies non-small cell lung cancer (NSCLC) patients with poor prognosis. Aim was to identify cancer intrinsic and extrinsic pathways regulated by hMENA11a downregulation as determinants of ICB response in NSCLC. Here, we present a potential novel mechanism of ICB resistance driven by hMENA11a downregulation. Methods Effects of hMENA11a downregulation were tested by RNA-Seq, ATAC-Seq, flow cytometry and biochemical assays. ICB-treated patient tumor tissues were profiled by Nanostring IO 360 Panel enriched with hMENA custom probes. OAK and POPLAR datasets were used to validate our discovery cohort. Results Transcriptomic and biochemical analyses demonstrated that the depletion of hMENA11a induces IFN pathway activation, the production of different inflammatory mediators including IFNβ via RIG-I, sustains the increase of tumor PD-L1 levels and activates a paracrine loop between tumor cells and a unique macrophage subset favoring an epithelial-mesenchymal transition (EMT). Notably, when we translated our results in a clinical setting of NSCLC ICB-treated patients, transcriptomic analysis revealed that low expression of hMENA11a, high expression of IFN target genes and high macrophage score identify patients resistant to ICB therapy. Conclusions Collectively, these data establish a new function for the actin cytoskeleton regulator hMENA11a in modulating cancer cell intrinsic type I IFN signaling and extrinsic mechanisms that promote protumoral macrophages and favor EMT. These data highlight the role of actin cytoskeleton disturbance in activating immune suppressive pathways that may be involved in resistance to ICB in NSCLC.
Model Counting Meets Distinct Elements

Constraint satisfaction problems (CSPs) and data stream models are two powerful abstractions to capture a wide variety of problems arising in different domains of computer science. Developments in the two communities have mostly occurred independently and with little interaction between them. In this work, we seek to investigate whether bridging the seeming communication gap between the two communities may pave the way to richer fundamental insights. To this end, we focus on two foundational problems: model counting for CSPs and the computation of the number of distinct elements in a data stream, also known as the zeroth frequency moment (F0) of a data stream. Our investigations lead us to observe striking similarity in the core techniques employed in the algorithmic frameworks that have evolved separately for model counting and distinct elements computation. We design a recipe for the translation of algorithms developed for distinct elements estimation to that of model counting, resulting in new algorithms for model counting. We then observe that algorithms in the context of distributed streaming can be transformed into distributed algorithms for model counting. We next turn our attention to viewing streaming from the lens of counting and show that framing distinct elements estimation as a special case of #DNF counting allows us to obtain a general recipe for a rich class of streaming problems, which had been subjected to case-specific analysis in prior works.
Two-Way Coupling of Skinning Transformations and Position Based Dynamics

Skinning transformations enable digital characters to be animated with minimal user input. Physics simulations can improve the detailed dynamic movement of an animated character; however, such details are typically added in the post-processing stage after the overall animation is specified. We propose a novel interactive framework that unifies skinning transformations and kinematic simulations using position-based dynamics (PBD). Our framework allows an arbitrarily skinned character to be partially manipulated by the user, and a kinematic physics solver automatically complements the behavior of the entire character. This is achieved by introducing new steps into the PBD algorithm: (i) lightweight optimization to identify the skinning transformations, which is similar to inverse kinematics, and (ii) a position-based constraint to restrict the PBD solver to the complementary subspace of the skinning deformation. Our method combines the best of the two methods: the controllability and shape preservation of the skinning transformation, and the efficiency, simplicity, and unconditional stability of the PBD solver. Our interface allows novices to create vibrant animations without tedious editing.
A Design Vocabulary for Data Physicalization

Although physical artifacts that represent data have been used for centuries, the research field—known as data physicalization—has only recently gained traction. Compared to data visualization, there is no established vocabulary for analyzing and discussing the properties of physicalizations. Through a grounded analysis of examples and literature, we propose a comprehensive design vocabulary, which consist of three separate, but connected parts: explicit variables, implicit properties, and consequential aspects. Explicit variables build on visual variables known from visualization and extend it to account for physicalization’s multi-modal nature. Implicit properties concern elements which are central to the design intention and user experience of physicalizations, yet are not a result of “explicit” encoding strategies. Finally, consequential aspects refer to unintentional effects of design decisions, that influence how a physicalization is experienced. Our work illustrates how physicalizations incorporate opportunities and challenges that are not afforded in other data representations, such as embodiment and imagined touch. With this, we contribute to generating theory on physicalization. Our design vocabulary can support (1) creators through informing their design processes and highlighting design strategies, (2) educators, and (3) academics and practitioners to analyse existing physicalizations, and reflect on the impact of design decisions on interpretation and experience.
Self Adaptive Logical Split Cache Techniques for Delayed Aging of NVM LLC

Due to the technological advancements in the last few decades, several applications have emerged that demand more computing power and on-chip and off-chip memories. However, the scaling of memory technologies is not at par with computing throughput of modern day multi-core processors. Conventional memory technologies such as SRAM and DRAM have technological limitations to meet large on-chip memory requirements owing to their low packaging density and high leakage power. In order to meet the ever-increasing demand for memory, researchers came up with alternative solutions, such as emerging non-volatile memory technologies such as STT-RAM, PCM, and ReRAM. However, these memory technologies have limited write endurance and high write energy. This emphasizes the need for a policy that will reduce the writes or distribute the writes uniformly across the memory thereby enhancing its lifetime by delaying the early wear out of memory cells due to frequent writes. We propose two techniques, Enhanced-Virtually Split Cache (E-ViSC) and Protean-Virtually Split Cache (P-ViSC), which dynamically adjust the cache configuration to distribute the writes uniformly across the memory to enhance the lifetime. Experimental studies show that E-ViSC and P-ViSC improve lifetime of NVM L2 caches by upto 2.31× and 1.97× respectively.
MFD: Multi-object Frequency Feature Recognition and State Detection Based on RFID-single Tag

Vibration is a normal reaction that occurs during the operation of machinery and is very common in industrial systems. How to turn fine-grained vibration perception into visualization, and further predict mechanical failures and reduce property losses based on visual vibration information, which has aroused our thinking. In this article, the phase information generated by the tag is processed and analyzed, and MFD is proposed, a real-time vibration monitoring and fault-sensing discrimination system. MFD extracts phase information from the original RF signal and converts it into a Markov transition map by introducing White Gaussian Noise and a low-pass filter for denoising. To accurately predict the failure of machinery, a deep and machine learning model is introduced to calculate the accuracy of failure analysis, realizing real-time monitoring and fault judgment. The test results show that the average recognition accuracy of vibration can reach 96.07%, and the average recognition accuracy of forward rotation, reverse rotation, oil spill, and screw loosening of motor equipment during long-term operation can reach 98.53%, 99.44%, 97.87%, and 99.91%, respectively, with high robustness.
LPATH: A semi-automated Python tool for clustering molecular pathways

The pathways by which a molecular process transitions to a target state are highly sought-after as direct views of a transition mechanism. While great strides have been made in the physics-based simulation of such pathways, the analysis of these pathways can be a major challenge due to their diversity and variable lengths. Here we present the LPATH Python tool, which implements a semi-automated method for linguistics-assisted clustering of pathways into distinct classes (or routes). This method involves three steps: 1) discretizing the configurational space into key states, 2) extracting a text-string sequence of key visited states for each pathway, and 3) pairwise matching of pathways based on a text-string similarity score. To circumvent the prohibitive memory requirements of the first step, we have implemented a general two-stage method for clustering conformational states that exploits machine learning. LPATH is primarily designed for use with the WESTPA software for weighted ensemble simulations; however, the tool can also be applied to conventional simulations. As demonstrated for the C7eq to C7ax conformational transition of alanine dipeptide, LPATH provides physically reasonable classes of pathways and corresponding probabilities. TOC Graphic
The Significance and Limited Influence of Cerebrovascular Reactivity on Age and Sex Effects in Task- and Resting-State Brain Activity

Functional MRI (fMRI) measures the blood-oxygen-level dependent (BOLD) signals, which provide an indirect measure of neural activity mediated by neurovascular responses. Cerebrovascular reactivity affects both task-induced and resting-state BOLD activity and may confound inter-individual effects observed in BOLD-based measures, such as those related to aging and biological sex. To investigate this, we examined a large open-access fMRI dataset containing a breath-holding task, checkerboard task, and resting-state scans. We used the breath-holding task to measure cerebrovascular reactivity, used the checkerboard task to obtain task-based activations, and from the resting-state data, we quantified the resting-state amplitude of low-frequency fluctuations (ALFF), and resting-state regional homogeneity (ReHo). We hypothesized that cerebrovascular reactivity would be correlated with BOLD measures and that accounting for these correlations would result in better estimates of age and sex effects. Our analysis showed that cerebrovascular reactivity was correlated with checkerboard task activations in the visual cortex and with ALFF and ReHo in widespread fronto-parietal regions, as well as regions with large vessels. We also found significant age and sex effects in cerebrovascular reactivity, some of which overlapped with those observed in ALFF and ReHo scores. Finally, we demonstrated that correcting for the effects of cerebrovascular reactivity had very limited influence on the estimates of age and sex. Our results highlight the limitations of accounting for cerebrovascular reactivity with the current breath-holding task.
Phenotypic lags influence rapid evolution throughout a drought cycle

Climate anomalies pose strong selection which can lead to rapid evolution. These global mean trends occur on a backdrop of interannual variability that might weaken or even reverse selection. However, the impact of climatic interannual variability on rapid evolution is rarely considered. We study evolution through a seven-year period encompassing a severe drought across 12 populations of Mimulus cardinalis (scarlet monkeyflower). Plants were grown in a common greenhouse environment under wet and dry treatments, where specific leaf area and date of flowering were measured. We compare the ability of different climate metrics to explain the rapid evolution of trait values, examining different time-periods, including the collection year, prior years, and cumulative metrics across sequential years. We find that anomalies in mean annual precipitation best describe rapid evolution over our study period. Past climates, of one-to two-years ago, are often related to trait values in a conflicting direction to collection-year climate. Uncovering these complex climatic impacts on evolution is critical to better predict and interpret the impacts of climate change.
A suite of selective pressures supports the maintenance of alleles of a Drosophila immune peptide

The innate immune system provides hosts with a crucial first line of defense against pathogens. While immune genes are often among the fastest evolving genes in the genome, in Drosophila, antimicrobial peptides (AMPs) are notable exceptions. Instead, AMPs may be under balancing selection, such that over evolutionary timescales multiple alleles are maintained in populations. In this study, we focus on the Drosophila antimicrobial peptide Diptericin A, which has a segregating amino acid polymorphism associated with differential survival after infection with the Gram-negative bacteria Providencia rettgeri. Diptericin A also helps control opportunistic gut infections by common Drosophila gut microbes, especially those of Lactobacillus plantarum. In addition to genotypic effects on gut immunity, we also see strong sex-specific effects that are most prominent in flies without functional diptericin A. To further characterize differences in microbiomes between different diptericin genotypes, we used 16S metagenomics to look at the microbiome composition. We used both lab reared and wild caught flies for our sequencing and looked at overall composition as well as the differential abundance of individual bacterial families. Overall, we find flies that are homozygous serine for diptericin A are better equipped to survive a systemic infection from P. rettgeri, but in general homozygous arginine flies have a longer lifespan after being fed common gut commensals. Our results suggest a possible mechanism for the maintenance of genetic variation of diptericin A through the complex interactions of sex, systemic immunity, and the maintenance of the gut microbiome.
Experimental Diets Dictate the Metabolic Benefits of Lactobacillus Strains in Obesity

We thank Joanie Dupont-Morissette, Christine Dallaire, Jacinthe Laurence Morin, and Jenny Rancourt-Mercier from IUCPQ, Laval University, for excellent technical assistance for in vivo protocols. Sincere gratitude to Lea B. S. Hansen for essential bioinformatic input. Additionally, we thank Torsten Schröder from the Institute of Nutritional Medicine for data generation as well as Jeffrey Schultchen from NZ for providing the probiotic strains. Abstract Background: Growing evidence supports the use of probiotics to prevent or mitigate obesity-related dysmetabolism and non-alcoholic fatty liver disease (NAFLD). However, frequent reports of responders versus non-responders to probiotic treatment warrant a better understanding of key modifiers of host-microbe interactions. The influence of host diet on probiotic efficacy, in particular against metabolic diseases, remains elusive. Method: We fed C57BL6/J mice a low fat reference diet or one of two energy-matched high fat and high sucrose diets for 12 weeks; a classical high fat diet (HFD) and a customized fast food-mimicking diet (FFMD). During the studies, mice fed either obesogenic diet were gavaged daily with one of two probiotic Lactobacillus strains, namely Limosilactobacillus reuteri ( L. reuteri ) or Lacticaseibacillus paracasei subsp. paracasei ( L. paracasei ) , or vehicle. Results: The tested probiotics exhibited a reproducible efficacy but dichotomous response according to the obesogenic diets used. Indeed, L. paracasei prevented weight gain, improved insulin sensitivity, and protected against NAFLD development in mice fed HFD, but not FFMD. Conversely, L. reuteri improved glucoregulatory capacity, reduced NAFLD development, and increased distal gut bile acid levels associated with changes in predicted functions of the gut microbiota exclusively in the context of FFMD-feeding. Conclusion: We found that the probiotic efficacy of two Lactobacillus strains is highly dependent on experimental obesogenic diets. These findings highlight the need to carefully consider the confounding impact of diet in order to improve both the reproducibility of preclinical studies and their clinical research translatability.
Gamma music: a new acoustic stimulus for gamma-frequency auditory steady-state response

A frequency range exceeding approximately 30 Hz, denoted as the gamma frequency range, is associated with various cognitive functions, consciousness, sensory integration, short-term memory, working memory, encoding and maintenance of episodic memory, and retrieval processes. In this study, we proposed a new form of gamma stimulation, called gamma music, combining 40 Hz auditory stimuli and music. This gamma music consists of drums, bass, and keyboard sounds, each containing a 40 Hz frequency oscillation. Since 40 Hz stimuli are known to induce an auditory steady-state response (ASSR), we used the 40 Hz power and phase locking index (PLI) as indices of neural activity during sound stimulation. We also recorded subjective ratings of each sound through a questionnaire using a visual analog scale. The gamma music, gamma drums, gamma bass, and gamma keyboard sounds showed significantly higher values in 40 Hz power and PLI compared to the control music without a 40 Hz oscillation. Particularly, the gamma keyboard sound showed a potential to induce strong ASSR, showing high values in these indices. In the subjective ratings, the gamma music, especially the gamma keyboard sound, received more relaxed, comfortable, preferred, pleasant, and natural impressions compared to the control music with conventional gamma stimulation. These results indicate that our proposed gamma music has potential as a new method for inducing ASSR. Particularly, the gamma keyboard sound proved to be an effective acoustic source for inducing a strong ASSR while preserving the comfortable and pleasant sensation of listening to music.
Effectiveness and residual activity of four common insecticides used in the Mississippi Delta to control tarnished plant bugs in cotton

The tarnished plant bug, (TPB) Lygus lineolaris Palisot de Beauvois (Hemiptera: Miridae) is a key pest of cotton in the midsouth region and some areas of the eastern United States. Its control methods have been solely based on chemical insecticides which has contributed to insecticidal resistance and shortened residual periods for control of this insect pest. This study was conducted over a two-year period and examined the efficacy and residual effect of four commercial insecticides including lambda-cyhalothrin (pyrethroid), acephate (organophosphate), imidacloprid (neonicotinoid), and sulfoxaflor (sulfoxamine). The effectiveness and residual effects of these insecticides were determined by application on cotton field plots on four different dates during each season using three different concentrations (high: highest labeled commercial dose (CD), medium: 1/10 of the CD, low: 1/100 of the CD) on field cotton plots. Four groups of cotton leaves were randomly pulled from each treated plot and control 0-, 2-, 4-, 7-, and 9-days post treatment (DPT) and exposed to a lab colony of TPB adults. One extra leaf sample/ plot/ spray /DPT interval (0-2-4-7-9-11) during 2016 was randomly collected from the high concentration plots and sent to Mississippi State Chemical Laboratory for residual analysis. Mortality of TPB adults was greatest for those placed on leaves sprayed with the organophosphate insecticide with mortalities (%) of 81.7±23.4 and 63.3±28.8 (SE) 1-day after exposure (DAE) on leaves 0-DPT with the high concentration for 2016 and 2017, respectively, reaching 94.5±9.5 and 95.4±7.6 6-DAE each year. Mortality to all insecticides continued until 9 and 4-DPT for high and medium concentrations, respectively. However, organophosphate (39.4±28.6) and pyrethroid (24.4±9.9) exhibited higher mortality than sulfoxamine (10.6±6.6) and the neonicotinoid (4.0±1.5) 7-DAE on 9-DPT leaves with the high concentration. Based on our results using the current assay procedure, TPB adults were significantly more susceptible to contact than systemic insecticides and due to its residual effect, organophosphate could kill over 80% of the TPB population 7-DPT.