Miracle-dz/UniFAR-FTUs huggingface dataset:
Habitat Use by Forest Bats in South Carolina in Relation to Local, Stand, and Landscape Characteristics

Abstract Knowledge and understanding of bat habitat associations and the responses of bats to forest management are critical for effective bat conservation and management. Few studies have been conducted on bat habitat use in the southeast, despite the high number of endangered and sensitive species in the region. Our objective was to identify important local, stand, and landscape factors influencing bat habitat use in northwestern South Carolina, USA. We hypothesized that use would be greatest 1) at points with relatively sparse vegetation, 2) in early successional and mature stands, and 3) at points close to streams. We also predicted that species would exhibit different patterns of habitat use based on morphology. We placed Anabat II bat detectors at points located in 3 forest types and 3 age classes to record bats from May–August 2004 and 2005. We used an information theoretic approach to determine the variables that best predicted use by bats. Vegetation density at the sample point was the best predictor of overall bat presence in 2004. In 2005 vegetation density and distance to the closest road were the best predictors of overall bat use; the model containing age class also had good support. Bats were more likely to be recorded at points with sparse vegetation, farther from roads, and in early successional stands. Vegetation density was also the best predictor of habitat use by big brown bats (Eptesicus fuscus) and red bats (Lasiurus borealis); both species were far more likely to be recorded at points with sparse vegetation at the sample point. Eastern pipistrelles (Pipistrellus subflavus) were also more likely to be recorded at points with sparse vegetation and in early successional stands. The best predictors of northern long-eared bat (Myotis septentrionalis) habitat use were vegetation density and age class. Northern long-eared bats were more likely to be recorded at points with sparse vegetation and in mature stands. Our results suggest that early successional habitats and small openings and gaps within forest stands provide suitable commuting and foraging bat habitat in northwestern South Carolina. However, mature forests are also important for some species. Forest management practices that provide a variety of age classes across the landscape and that create gaps and openings within mid- and late-successional stands will likely provide suitable habitat for bats in the mountains of South Carolina.
Towards End-to-end Spoken Language Understanding

Spoken language understanding system is traditionally designed as a pipeline of a number of components. First, the audio signal is processed by an automatic speech recognizer for transcription or n-best hypotheses. With the recognition results, a natural language understanding system classifies the text to structured data as domain, intent and slots for down-streaming consumers, such as dialog system, hands-free applications. These components are usually developed and optimized independently. In this paper, we present our study on an end-to-end learning system for spoken language understanding. With this unified approach, we can infer the semantic meaning directly from audio features without the intermediate text representation. This study showed that the trained model can achieve reasonable good result and demonstrated that the model can capture the semantic attention directly from the audio features.
Expression of the intracisternal A-particle is elevated during differentiation of embryonal carcinoma cells

Three cDNA clones coding for the 3' region of the intracisternal A-particle (IAP), a mouse endogenous retrovirus, were isolated during screening of a library for genes whose expression was modulated during the retinoic acid-induced differentiation of the embryonal carcinoma cell line F9 into parietal endoderm-like (PE-like) cells. In contrast to previously reported results, no IAP transcripts were detected in either F9 cells or two pluripotent cell lines tested. Instead, IAP transcripts as well as IAPs were abundant in the PE-like cells PYS-2 and F9AcCl 9 and in retinoic acid-induced F9 cells but not in the other differentiated cell types of teratocarcinoma origin which were examined. A comparison of the nucleotide sequences of the three IAP cDNA clones with a genomically integrated proviral sequence (MIA14) demonstrated heterogeneity in both length and sequence among the clones. The position of the poly(A) addition site was determined to be 15 nucleotides from the proposed poly(A) addition signal and to occur after the sequence CAGA, not CA, as previously proposed. Length heterogeneity was greatest in a region of TC repeats 80 base pairs 5' to the poly(A) addition site. Additionally, the putative TATAA box found in MIA14 was deleted in the cDNA clones and in the long terminal repeat regions from two other genomic clones examined. The heterogeneity evident among the cDNA clones further demonstrated that at least two distinct IAP genes are activated during differentiation. An analysis of the rate of transcription in isolated nuclei indicated that the activation of expression of IAP genes in PE-like cells is the result of transcriptional regulation. Together, these observations suggest that the modulation of IAP transcription is regulated autonomously rather than by the fortuitous integration of an IAP sequence adjacent to a developmentally regulated cellular gene.
miR-208a-3p suppresses cell apoptosis by targeting PDCD4 in gastric cancer

Programmed cell death 4 (PDCD4) is a novel tumor suppressor gene and a promising target for anticancer therapies. PDCD4 is frequently downregulated in various human cancers; however, the molecular mechanism accounting for the loss expression of PDCD4 in cancers is not fully understood. In this study, we identified specific targeting sites for miR-208a-3p in the 3′-untranslated region (3′-UTR) of the PDCD4 gene which regulated PDCD4 expression. We demonstrated that miR-208a-3p suppressed apoptosis in gastric cancer cells by targeting PDCD4. We also showed that miR-208a-3p promoted the development of tumor growth in xenograft mice by negatively regulating PDCD4. Taken together, this study revealed a critical role for miR-208a-3p as an oncogenic miRNA in gastric carcinogenesis and it may provide a potential novel target for gastric cancer diagnosis and therapy.
The Alberta Workloads for the SPEC CPU 2017 Benchmark Suite

A proper evaluation of techniques that require multiple training and evaluation executions of a benchmark, such as Feedback-Directed Optimization (FDO), requires multiple workloads that can be used to characterize variations on the behaviour of a program based on the workload. This paper aims to improve the performance evaluation of computer systems — including compilers, computer architecture simulation, and operating-system prototypes — that rely on the industrystandard SPEC CPU benchmark suite. A main concern with the use of this suite in research is that it is distributed with a very small number of workloads. This paper describes the process to create additional workloads for this suite and offers useful insights in many of its benchmarks. The set of additional workloads created, named the Alberta Workloads for the SPEC CPU 2017 Benchmark Suite1 is made freely available with the goal of providing additional data points for the exploration of learning in computing systems. These workloads should also contribute to ameliorate the hidden learning problem where a researcher sets parameters to a system during development based on a set of benchmarks and then evaluates the system using the very same set of benchmarks with the very same workloads.
MIEN1 is tightly regulated by SINE Alu methylation in its promoter

Migration and invasion enhancer 1 (MIEN1) is a novel gene involved in prostate cancer progression by enhancing prostate cancer cell migration and invasion. DNA methylation, an important epigenetic regulation, is one of the most widely altered mechanisms in prostate cancer. This phenomenon frames the basis to study the DNA methylation patterns in the promoter region of MIEN1. Bisulfite pyrosequencing demonstrates the MIEN1 promoter contains a short interspersed nuclear Alu element (SINE Alu) repeat sequence. Validation of methylation inhibition on MIEN1 was performed using nucleoside analogs and non-nucleoside inhibitors and resulted in an increase in both MIEN1 RNA and protein in normal cells. MIEN1 mRNA and protein increases upon inhibition of individual DNA methyltransferases using RNA interference technologies. Furthermore, dual luciferase reporter assays, in silico analysis, and chromatin immunoprecipitation assays identified a sequence upstream of the transcription start site that has a site for binding of the USF transcription factors. These results suggest the MIEN1 promoter has a SINE Alu region that is hypermethylated in normal cells leading to repression of the gene. In cancer, the hypomethylation of a part of this repeat, in addition to the binding of USF, results in MIEN1 expression.
Spatial and temporal information structuring for natural risk monitoring

The work presented in this paper concerns Global Environment, focusing on Natural Risk Monitoring: our application is volcanic activity monitoring. The real-time data used in such a system generally comes from an array of sensors and are usually collected into a central database. With the now widespread addition of GPS, these data therefore have both temporal and spatial components. Therefore a major trouble encountered is the data structuring, so that it can store data effectively and process real-time queries on real-time objects. Our work offers a new indexing method dealing with multi-dimensional aspects of the data as well as storing and real-time querying
Making Sense of Video Analytics: Lessons Learned from Clickstream Interactions, Attitudes, and Learning Outcome in a Video-Assisted Course.

Online video lectures have been considered an instructional media for various pedagogic approaches, such as the flipped classroom and open online courses. In comparison to other instructional media, online video affords the opportunity for recording student clickstream patterns within a video lecture. Video analytics within lecture videos may provide insights into student learning performance and inform the improvement of video-assisted teaching tactics. Nevertheless, video analytics are not accessible to learning stakeholders, such as researchers and educators, mainly because online video platforms do not broadly share the interactions of the users with their systems. For this purpose, we have designed an open-access video analytics system for use in a video-assisted course. In this paper, we present a longitudinal study, which provides valuable insights through the lens of the collected video analytics. In particular, we found that there is a relationship between video navigation (repeated views) and the level of cognition/thinking required for a specific video segment. Our results indicated that learning performance progress was slightly improved and stabilized after the third week of the video-assisted course. We also found that attitudes regarding easiness, usability, usefulness, and acceptance of this type of course remained at the same levels throughout the course. Finally, we triangulate analytics from diverse sources, discuss them, and provide the lessons learned for further development and refinement of video-assisted courses and practices.
SPLATNet: Sparse Lattice Networks for Point Cloud Processing

We present a network architecture for processing point clouds that directly operates on a collection of points represented as a sparse set of samples in a high-dimensional lattice. NaÃ¯vely applying convolutions on this lattice scales poorly, both in terms of memory and computational cost, as the size of the lattice increases. Instead, our network uses sparse bilateral convolutional layers as building blocks. These layers maintain efficiency by using indexing structures to apply convolutions only on occupied parts of the lattice, and allow flexible specifications of the lattice structure enabling hierarchical and spatially-aware feature learning, as well as joint 2D-3D reasoning. Both point-based and image-based representations can be easily incorporated in a network with such layers and the resulting model can be trained in an end-to-end manner. We present results on 3D segmentation tasks where our approach outperforms existing state-of-the-art techniques.
Carcinogenesis and Reactive Oxygen Species Signaling: Interaction of the NADPH Oxidase NOX1–5 and Superoxide Dismutase 1–3 Signal Transduction Pathways

Abstract Significance: Reduction/oxidation (redox) balance could be defined as an even distribution of reduction and oxidation complementary processes and their reaction end products. There is a consensus that aberrant levels of reactive oxygen species (ROS), commonly observed in cancer, stimulate primary cell immortalization and progression of carcinogenesis. However, the mechanism how different ROS regulate redox balance is not completely understood. Recent Advances: In the current review, we have summarized the main signaling cascades inducing NADPH oxidase NOX1–5 and superoxide dismutase (SOD) 1–3 expression and their connection to cell proliferation, immortalization, transformation, and CD34+ cell differentiation in thyroid, colon, lung, breast, and hematological cancers. Critical Issues: Interestingly, many of the signaling pathways activating redox enzymes or mediating the effect of ROS are common, such as pathways initiated from G protein-coupled receptors and tyrosine kinase receptors involving protein kinase A, phospholipase C, calcium, and small GTPase signaling molecules. Future Directions: The clarification of interaction of signal transduction pathways could explain how cells regulate redox balance and may even provide means to inhibit the accumulation of harmful levels of ROS in human pathologies.
Voting for movies: the anatomy of a recommender system

Personal assistant agents embody a clearly beneficial application of intelligent agent technology. A particular kind of assistant agents, recommender systems (RSs), can be used to recommend items of interest to users [l]. To be successful, such systems should be able to model and reason with user preferences for items in the application domain. We are developing a movie recommender system that caters to the interests of a user. Our primary concern is to utilize a reasoning procedure that can meaningfully and systematically tradeoff between conflicting user preferences. We have adapted mechanisms from voting theory that have desirable guarantees regarding the recommendations generated from stored preferences. We provide multiple query modalities by which the user can pose unconstrained, constrained, or instance-based queries. Typically a domain has several features or dimensions. Each dimension consists of a collection of elements, and the preferences of a user are given by his/her ratings of those elements on some ordinal or cardinal scale. To obtain a recommendation rating for a given item, an RS considers the feature values of that item, obtains ratings for these values from corresponding dimensions, and then combines these ratings by some evaluation scheme.
Astragaloside II sensitizes human hepatocellular carcinoma cells to 5‐fluorouracil via suppression of autophagy

Inhibition of autophagy has been increasingly recognized as a potential therapeutic approach against cancer. Our previous reports showed that Astragaloside II improves hepatic cancer cells resistance by downregulating MDR1 and P‐gp . The purpose of this study was to further investigated the effect of autophagy on AS‐II reversing multidrug resistance and its molecular mechanism in hepatocellular carcinoma cells in vitro.
Trans-arterial radioembolization in intermediate-advanced hepatocellular carcinoma: systematic review and meta-analyses

Trans-arterial radioembolization (TARE) is a recognized, although not explicitly recommended, experimental therapy for unresectable hepatocellular carcinoma (HCC). A systematic literature review was performed to identify published studies on the use of TARE in intermediate and advanced stages HCC exploring the efficacy and safety of this innovative treatment. Twenty-one studies reporting data on overall survival (OS) and time to progression (TTP), were included in a meta-analysis. The pooled post-TARE OS was 63% (95% CI: 56-70%) and 27% (95% CI: 21-33%) at 1- and 3-years respectively in intermediate stage HCC, whereas OS was 37% (95% CI: 26-50%) and 13% (95% CI: 9-18%) at the same time intervals in patients with sufficient liver function (Child-Pugh A-B7) but with an advanced HCC because of the presence of portal vein thrombosis. When an intermediate and advanced case-mix was considered, OS was 58% (95% CI: 48-67%) and 17% (95% CI: 12-23%) at 1- and 3-years respectively. As for TTP, only four studies reported data: the observed progression probability was 56% (95% CI: 41-70%) and 73% (95% CI: 56-87%) at 1 and 2 years respectively. The safety analysis, focused on the risk of liver decompensation after TARE, revealed a great variability, from 0-1% to more than 36% events, influenced by the number of procedures, patient Child-Pugh stage and treatment duration. Evidence supporting the use of radioembolization in HCC is mainly based on retrospective and prospective cohort studies. Based on this evidence, until the results of the ongoing randomized trials become available, radioembolization appears to be a viable treatment option for intermediate-advanced stage HCC.
Depth Masked Discriminative Correlation Filter

Depth information provides a strong cue for occlusion detection and handling, but has been largely omitted in generic object tracking until recently due to lack of suitable benchmark datasets and applications. In this work, we propose a Depth Masked Discriminative Correlation Filter (DM-DCF) which adopts novel depth segmentation based occlusion detection that stops correlation filter updating and depth masking which adaptively adjusts the spatial support for correlation filter. In Princeton RGBD Tracking Benchmark, our DM-DCF is among the state-of-the-art in overall ranking and the winner on multiple categories. Moreover, since it is based on DCF, “DM-DCF” runs an order of magnitude faster than its competitors making it suitable for time constrained applications.
Prediction of Slag Occurrence in a Lignite-Fired Utility Boiler

Lignite from Mae Moh mine is the largest source of solid fuel for electricity generation in Thailand. It is used in pulverized coal-fired boilers of a 2400 MW thermal power plant. Its high CaO content in ash is a major concern that can affect severe slagging. In this paper, potential of slag occurrence in the power plant was investigated by numerical simulation. The FactSage thermochemical package was used to predict ash and slag behaviour, as well as ash fusion temperature. A commercial CFD package was also employed to simulate gas velocity and temperature distribution, particle trajectory and temperature, and wall heat flux in a utility boiler of the power plant. The results were found to show good quantitatively and qualitatively prediction of slag formation. They can be applied to predict slag deposition inside the boiler effectively. Key-Words: slag, lignite, pulverized coal-fired boiler, coal combustion, FactSage simulation, CFD simulation
Multimodal recognition of personality during short self-presentations

Personality plays an important role in the way people manage the images they convey in self-presentations and employment interviews, trying to affect the other's first impressions and increase effectiveness. This paper addresses the automatically detection of the Big Five personality traits from short self-presentations, by investigating the effectiveness of various simple non-verbal acoustic and visual social signals.
Covariance descriptor based convolution neural network for saliency computation in low contrast images

Saliency computational model with active environment perception can substantially facilitate a wide range of applications. Conventional saliency computational models primarily rely on hand-crafted low level image features, such as color or contrast. However, they may face great challenges in low lighting scenario, due to the lack of well-defined feature to represent saliency information in low contrast images. In this paper, we propose a novel deep neural network framework embedded with covariance descriptor for salient object detection in low contrast images. Several low-level features are extracted to compute their mutual covariance, which is then trained via a 7-layers convolutional neural network (CNN). The saliency map can be generated by estimating the final saliency score of each region via the pre-trained CNN model. Extensive experiments have been conducted on six challenging datasets to evaluate the performance of the proposed model against ten state-of-the-art models.
uPA/uPAR and SERPINE1 in head and neck cancer: role in tumor resistance, metastasis, prognosis and therapy

There is strong evidence supporting the role of the plasminogen activator system in head and neck squamous cell carcinoma (HNSCC), particularly of its uPA (urokinase plasminogen activator) / uPAR (urokinase plasminogen activator receptor) and SERPINE1 components. Overexpression of uPA/uPAR and SERPINE1 enhances tumor cell migration and invasion and plays a key role in metastasis development, conferring poor prognosis. The apparent paradox of uPA/uPAR and its inhibitor SERPINE1 producing similar effects is solved by the identification of SERPINE1 activated signaling pathways independent of uPA inhibition. Both uPA/uPAR and SERPINE1 are directly linked to the induction of epithelial-to-mesenchymal transition, the acquisition of stem cell properties and resistance to antitumor agents. The aim of this review is to provide insight on the deregulation of these proteins in all these processes. We also summarize their potential value as prognostic biomarkers or potential drug targets in HNSCC patients. Concomitant overexpression of uPA/uPAR and SERPINE1 is associated with a higher risk of metastasis and could be used to identify patients that would benefit from an adjuvant treatment. In the future, the specific inhibitors of uPA/uPAR and SERPINE1, which are still under development, could be used to design new therapeutic strategies in HNSCCs.