Miracle-dz/UniFAR-FTUs huggingface dataset:
Bone marrow mesenchymal stem cell donors with a high body mass index display elevated endoplasmic reticulum stress and are functionally impaired

Bone marrow mesenchymal stem cells (BM‐MSCs) are promising candidates for regenerative medicine purposes. The effect of obesity on the function of BM‐MSCs is currently unknown. Here, we assessed how obesity affects the function of BM‐MSCs and the role of endoplasmic reticulum (ER) stress and the unfolded protein response (UPR) therein. BM‐MSCs were obtained from healthy donors with a normal (<25) or high (>30) body mass index (BMI). High‐BMI BM‐MSCs displayed severely impaired osteogenic and diminished adipogenic differentiation, decreased proliferation rates, increased senescence, and elevated expression of ER stress–related genes ATF4 and CHOP. Suppression of ER stress using tauroursodeoxycholic acid (TUDCA) and 4‐phenylbutyrate (4‐PBA) resulted in partial recovery of osteogenic differentiation capacity, with a significant increase in the expression of ALPL and improvement in the UPR. These data indicate that BMI is important during the selection of BM‐MSC donors for regenerative medicine purposes and that application of high‐BMI BM‐MSCs with TUDCA or 4‐PBA may improve stem cell function. However, whether this improvement can be translated into an in vivo clinical advantage remains to be assessed.
Kinetic and structural comparison of a protein’s cotranslational folding and refolding pathways

Kinetic and structural comparison of the cotranslational and refolding pathways of HaloTag reveals how translation reroutes the folding pathway to avoid aggregation. Precise protein folding is essential for the survival of all cells, and protein misfolding causes a number of diseases that lack effective therapies, yet the general principles governing protein folding in the cell remain poorly understood. In vivo, folding can begin cotranslationally and protein quality control at the ribosome is essential for cellular proteostasis. We directly characterize and compare the refolding and cotranslational folding trajectories of the protein HaloTag. We introduce new techniques for both measuring folding kinetics and detecting the conformations of partially folded intermediates during translation in real time. We find that, although translation does not affect the rate-limiting step of HaloTag folding, a key aggregation-prone intermediate observed during in vitro refolding experiments is no longer detectable. This rerouting of the folding pathway increases HaloTag’s folding efficiency and may serve as a general chaperone-independent mechanism of quality control by the ribosome.
Objective Function Learning to Match Human Judgements for Optimization-Based Summarization

Supervised summarization systems usually rely on supervision at the sentence or n-gram level provided by automatic metrics like ROUGE, which act as noisy proxies for human judgments. In this work, we learn a summary-level scoring function \theta including human judgments as supervision and automatically generated data as regularization. We extract summaries with a genetic algorithm using \theta as a fitness function. We observe strong and promising performances across datasets in both automatic and manual evaluation.
Thermal, Structural and Morphological Characterisation of Freeze-dried Copper(II) Acetate Monohydrate and its Solid Decomposition Products

In the present study the thermal decomposition of a freeze-dried copper(II) acetate monohydrate powder, (CH3COO)2Cu.H2O, (FDCuAcH2O), was analysed by a combination of high-temperature X-ray diffractometry; differential scanning calorimetry and thermogravimetry, up to 700 °C. The structure and morphology of the calcined freeze-dried powders were analysed by scanning electron microscopy and X-ray diffractometry. The results showed that FDAcCuH2O decomposes during heating in two stages: I) (25-225 °C) FDCuAcH2O dehydrates giving rise to copper(II) acetate, (CH3COO)2Cu, (AcCu), and II) (225-525 °C) AcCu decomposes to CuO through complex oxidation reactions of Cu and Cu2O, simultaneously. SEM showed that FDCuAcH2O powder has a scale-like morphology, which is created in the freezing stage and retained after freeze-drying. After calcination at 125 and 225 °C, clusters of elongated tubes (or filaments) compose the resulting powder (AcCu). Subsequent calcination at temperatures above 325 °C resulted in hard clusters of spheroid-like CuO particles.
Organization and Business-IT Power Sharing for the Ability to Manage IT Complexity : An Agenda for Action

To motivate the research topic, the paper will begin with a case study. It will further contain an extensive state-of-the-art review, including a brief overview of IT Governance frameworks focusing on the aspects of IT Organization and business-IT power sharing (IT O&P), complexity theory and current research in IT complexity management. Following this, the research gap will be highlighted. Subsequently, the steps to go will be shown. Finally, the current status of the research will be discussed and a conclusion will be given.
Particle-based Shallow Water Simulation with Splashes and Breaking Waves

We propose a fast method of simulating large-scale liquid phenomena by coupling 2D and 3D smoothed particle hydrodynamics (SPH). Our method combines 2D SPH-based shallow water simulation with 3D SPH simulation to effectively treat complex behaviors, such as splashes and breaking waves. To achieve realistic animation, we generate 3D particles from 2D particles by categorizing these particles according to motion and position. One-way interactions between both types of particles are described by the conservation of momentum. We demonstrate the effectiveness of our approach in various graphical scenes.
AuthStore: Password-Based Authentication and Encrypted Data Storage in Untrusted Environments

Passwords are widely used for client to server authentication as well as for encrypting data stored in untrusted environments, such as cloud storage. Both, authentication and encrypted cloud storage, are usually discussed in isolation. In this work, we propose AuthStore, a flexible authentication framework that allows users to securely reuse passwords for authentication as well as for encrypted cloud storage at a single or multiple service providers. Users can configure how secure passwords are protected using password stretching techniques. We present a compact password-authenticated key exchange protocol (CompactPAKE) that integrates the retrieval of password stretching parameters. A parameter attack is described and we show how existing solutions suffer from this attack. Furthermore, we introduce a password manager that supports CompactPAKE.
Homogenized funtf varieties and algebraic frame completion Extended Abstract : ISSAC ’ 18 Poster Session

We introduce homogenized funtf varieties and study the degrees of its coordinate projections. These varieties compactify the affine funtf variety differently from the projectivizations studied in [11]. Each are the closures (Zariski) of the set of finite tight unit normal frames. Our motivation comes from studying the frame completion problem.
Error-Correction Processing in Timing Lights for Measuring Sprint Performance: Does It Work?

PURPOSE To investigate if error-correction-processing (ECP) algorithms in timing lights are able to eliminate or reduce measurement errors (MEs) and false signals due to swinging arms or legs. METHODS First, a dummy was used to check if ECP generally works. Second, 15 male sport students performed sprints over 5 and 10 m. Timing lights with ECP and a high-speed camera as a gold standard were used to simultaneously capture the athletes when passing the timing lights at start, 5 m, and 10 m. MEs of the timing lights were calculated for hip and upper body. RESULTS The dummy condition revealed that ECP is able to eliminate MEs. In real sprint conditions, MEs were highest for timing light at start and when using the hip as a reference. Overall, out of 120 trials, only 4 false signals were not detected by ECP. They all occurred at the start timing light, with highest MEs being 0.263 s (hip) and 0.134 s (upper body). Regarding 5 and 10 m, all false signals were eliminated. CONCLUSIONS As proven through video analyses, ECP eliminated almost all false signals. The largest MEs at the start timing light were associated with a distinct forward leaning of the athletes. Therefore, clear instructions concerning starting posture should be given to further improve measurement accuracy of the start timing light. This approach could also enhance comparisons between athletes. Nevertheless, based on the results, timing lights employing ECP can be recommended for measuring short sprints.
Fast dynamic routing based on weighted kernel density estimation

Capsules as well as dynamic routing between them are most recently proposed structures for deep neural networks. A capsule groups data into vectors or matrices as poses rather than conventional scalars to represent specific properties of target instance. Based on pose, a capsule should be attached to a probability (often denoted as activation) for its presence. The dynamic routing helps capsule network achieve more generalization capacity with fewer model parameters. However, the bottleneck, which prevents widespread applications of capsule, is the expense of computation during routing. To address this problem, we generalize existing routing methods within the framework of weighted kernel density estimation, proposing two fast routing methods with different optimization strategies. Our methods prompt the time efficiency of routing by nearly 40% with negligible performance degradation. By stacking a hybrid of convolutional layers and capsule layers, we construct a network architecture to handle inputs at a resolution of 64 × 64 pixels. The proposed models achieve a parallel performance with other leading methods in multiple benchmarks.
TakeLab at SemEval-2018 Task12: Argument Reasoning Comprehension with Skip-Thought Vectors

This paper describes our system for the SemEval-2018 Task 12: Argument Reasoning Comprehension Task. We utilize skip-thought vectors, sentence-level distributional vectors inspired by the popular word embeddings and the skip-gram model. We encode preprocessed sentences from the dataset into vectors, then perform a binary supervised classification of the warrant that justifies the use of the reason as support for the claim. We explore a few variations of the model, reaching 54.1% accuracy on the test set, which placed us 16th out of 22 teams participating in the task.
Which Parts of Search Results do Researchers Check when Selecting Academic Documents?

Our goal is to propose an alternative retrieval system of academic documents based on researcher's behavior in practice. In this study, a questionnaire survey was conducted. Question items were developed from findings in the previous observational study for researcher's behavior. From the results of 46 respondents, the top three elements checked in the search results were title, abstract, and the full-text version. They also checked structure "Introduction" in the full-text rather than other structures when they found previous research in an unfamiliar field. These results indicate that researchers use different ways for selecting documents based on the type of documents they look for.
Mitochondrial Variants in Pompe Disease: A Comparison between Classic and Non-Classic Forms

Objective Pompe disease (PD) is a progressive neuromuscular disorder that is caused by glucosidase acid alpha (GAA) deleterious mutations. Mitochondrial involvement is an important contributor to neuromuscular diseases. In this study the sequence of MT-ATP 6/8 and Cytochrome C oxidase I/II genes along with the expression levels of the former genes were compared in classic and non-classic patients. Materials and Methods In this case-control study, the sequence of MT-ATP 6/8 and Cytochrome C oxidase was analyzed by polymerase chain reaction (PCR)-Sanger sequencing and expression of MT-ATP genes were quantified by real time-PCR (RT-PCR) in 28 Pompe patients. The results were then compared with 100 controls. All sequences were compared with the revised Cambridge reference sequence as reference. Results Screening of MT-ATP6/8 resulted in the identification of three novel variants, namely T9117A, A8456C and A8524C. There was a significant decrease in MT-ATP6 expression between classic (i.e. adult) and control groups (P=0.030). Additionally, the MT-ATP8 expression was significantly decreased in classic (P=0.004) and non-classic (i.e. infant) patients (P=0.013). In total, 22 variants were observed in Cytochrome C oxidase, five of which were non- synonymous, one leading to a stop codon and another (C9227G) being a novel heteroplasmic variant. The A8302G in the lysine tRNA gene was found in two brothers in a pedigree, while a T7572C variant in the aspartate tRNA gene was observed in two brothers in another pedigree. Conclusion The extent of mitochondrial involvement in the classic group was more significant than in the non-classic form. Beside GAA deleterious mutations, it seems that mtDNA variants have a secondary effect on PD. Understanding, the role of mitochondria in the pathogenesis of Pompe may potentially be helpful in developing new therapeutic strategies.
Nicotinamide Nucleotide Transhydrogenase as a Novel Treatment Target in Adrenocortical Carcinoma

Abstract Adrenocortical carcinoma (ACC) is an aggressive malignancy with poor response to chemotherapy. In this study, we evaluated a potential new treatment target for ACC, focusing on the mitochondrial reduced form of NAD phosphate (NADPH) generator nicotinamide nucleotide transhydrogenase (NNT). NNT has a central role within mitochondrial antioxidant pathways, protecting cells from oxidative stress. Inactivating human NNT mutations result in congenital adrenal insufficiency. We hypothesized that NNT silencing in ACC cells will induce toxic levels of oxidative stress. To explore this, we transiently knocked down NNT in NCI-H295R ACC cells. As predicted, this manipulation increased intracellular levels of oxidative stress; this resulted in a pronounced suppression of cell proliferation and higher apoptotic rates, as well as sensitization of cells to chemically induced oxidative stress. Steroidogenesis was paradoxically stimulated by NNT loss, as demonstrated by mass spectrometry–based steroid profiling. Next, we generated a stable NNT knockdown model in the same cell line to investigate the longer lasting effects of NNT silencing. After long-term culture, cells adapted metabolically to chronic NNT knockdown, restoring their redox balance and resilience to oxidative stress, although their proliferation remained suppressed. This was associated with higher rates of oxygen consumption. The molecular pathways underpinning these responses were explored in detail by RNA sequencing and nontargeted metabolome analysis, revealing major alterations in nucleotide synthesis, protein folding, and polyamine metabolism. This study provides preclinical evidence of the therapeutic merit of antioxidant targeting in ACC as well as illuminating the long-term adaptive response of cells to oxidative stress.
Semantic Structural Evaluation for Text Simplification

Current measures for evaluating text simplification systems focus on evaluating lexical text aspects, neglecting its structural aspects. In this paper we propose the first measure to address structural aspects of text simplification, called SAMSA. It leverages recent advances in semantic parsing to assess simplification quality by decomposing the input based on its semantic structure and comparing it to the output. SAMSA provides a reference-less automatic evaluation procedure, avoiding the problems that reference-based methods face due to the vast space of valid simplifications for a given sentence. Our human evaluation experiments show both SAMSA’s substantial correlation with human judgments, as well as the deficiency of existing reference-based measures in evaluating structural simplification.
THU_NGN at SemEval-2018 Task 1: Fine-grained Tweet Sentiment Intensity Analysis with Attention CNN-LSTM

Traditional sentiment analysis approaches mainly focus on classifying the sentiment polarities or emotion categories of texts. However, they can’t exploit the sentiment intensity information. Therefore, the SemEval-2018 Task 1 is aimed to automatically determine the intensity of emotions or sentiment of tweets to mine fine-grained sentiment information. In order to address this task, we propose a system based on an attention CNN-LSTM model. In our model, LSTM is used to extract the long-term contextual information from texts. We apply attention techniques to selecting this information. A CNN layer with different size of kernels is used to extract local features. The dense layers take the pooled CNN feature maps and predict the intensity scores. Our system reaches average Pearson correlation score of 0.722 (ranked 12/48) in emotion intensity regression task, and 0.810 in valence regression task (ranked 15/38). It indicates that our system can be further extended.
Limitless HTTP in an HTTPS World: Inferring the Semantics of the HTTPS Protocol without Decryption

We present new analytic techniques for inferring HTTP semantics from passive observations of HTTPS that can infer the value of important fields including the status-code, Content-Type, and Server, and the presence or absence of several additional HTTP header fields, e.g., Cookie and Referer. Our goals are to improve the understanding of the confidentiality limitations of HTTPS, and to explore benign uses of traffic analysis that could replace HTTPS interception and static private keys in some scenarios. We found that our techniques increase the efficacy of malware detection, but they do not enable more powerful website fingerprinting attacks against Tor. Our broader set of results raises concerns about the confidentiality goals of TLS relative to a user's expectation of privacy, warranting future research. We apply our methods to the semantics of both HTTP/1.1 and HTTP/2 on data collected from automated runs of Firefox 58.0, Chrome 63.0, and Tor Browser 7.0. 11 in a lab setting, and from applications running in a malware sandbox. We obtain ground truth plaintext for a diverse set of applications from the malware sandbox by extracting the key material needed for decryption from RAM post-execution. We developed an iterative approach to simultaneously solve several multi-class (field values) and binary (field presence) classification problems, and we show that our inference algorithm achieves an unweighted $F_1$ score greater than 0.900 for most HTTP fields examined.
Biomechanics of rapid movements in plants: poroelastic measurements at the cell scale

From a biomechanical perspective, plants offer a fascinat- ing example of living systems capable of producing non- muscular movements (Skotheim and Mahadevan 2005; Dumais and Forterre, to be published). Although most of these movements are slow, some compete in speed with those observed in the animal kingdom and are involved in essential functions such as seed/pollen dispersal, defence and nutrition. Of these spectacular examples that have long fascinated scientists, the Venus flytrap (Figure 1(a)), for which the leaves snap together in a fraction of second to capture insects, has long been a paradigm for study. Recently, we have shown that this motion involves a snap- buckling instability due to the shell-like geometry of the leaves of the trap (Forterre et al. 2005). However, the origin of the active movement used by the plant to cross the instability threshold remains unknown. More generally, the physical mechanisms involved in rapid plant movements remain poorly understood, especially at the cell and tissue scale. Two main assumptions are found in the literature: (i) a rapid flow between the cells due to changes in osmotic pressure (Hill and Findlay 1981), (ii) a rapid cell expansion due to mechanical modifications (softening) in the cell wall (Williams and Bennett 1982). In both cases, the high-water pressure inside the plant cells is believed to play a central role. Our aim in this study was to measure in real time in-vivo mechanical and hydraulic properties of Venus flytrap cells (cell wall elasticity, cell membrane per- meability and cell water pressure) and to investigate the possible mechanisms for movements at the cell scale. To this end, we use a microfluidic pressure probe device, which applies a water flux inside a single cell while measuring the cell water pressure simultaneously (Steudle 1993).
Multiple Manifolds Metric Learning with Application to Image Set Classification

In image set classification, a considerable advance has been made by modeling the original image sets by second order statistics or linear subspace, which typically lie on the Riemannian manifold. Specifically, they are Symmetric Positive Definite (SPD) manifold and Grassmann manifold respectively, and some algorithms have been developed on them for classification tasks. Motivated by the inability of existing methods to extract discriminatory features for data on Riemannian manifolds, we propose a novel algorithm which combines multiple manifolds as the features of the original image sets. In order to fuse these manifolds, the well-studied Riemannian kernels have been utilized to map the original Riemannian spaces into high dimensional Hilbert spaces. A metric Learning method has been devised to embed these kernel spaces into a lower dimensional common subspace for classification. The state-of-the-art results achieved on three datasets corresponding to two different classification tasks, namely face recognition and object categorization, demonstrate the effectiveness of the proposed method.
Characteristic Mode Design of Wide Band Circularly Polarized Patch Antenna Consisting of H-Shaped Unit Cells

This paper proposes a general characteristic mode-based design procedure of simple three steps for wideband circularly polarized (CP) antenna design. First of all, the characteristic mode analysis is carried out to understand the different modes of a proposed antenna geometry without feeding network. Second, modal currents and their corresponding modal fields (radiation patterns) are studied for choosing modes to shape the required radiation pattern. Finally, a suitable feeding structure is chosen to excite the desired modes at the same time owns a good impedance matching. As an example, a CP patch antenna fed with cross-shaped aperture is proposed and designed following the design procedure. Patch consisting of H-shaped unit cells is used as the radiator. Characteristic mode method is applied to analyze the modes of the proposed antenna and explains the property of wide band circular polarization. It is revealed that higher order modes of the patch can be used to achieve circular polarization over a wideband of frequency. The antenna is fabricated using printed circuit techniques. The return loss and radiation properties are measured and compared with simulation results. With the highly coupled units, a wide impedance bandwidth of 38.8% is obtained. Besides, a wide 3-dB axial ratio bandwidth of 14.3% is achieved.