Miracle-dz/UniFAR-FTUs huggingface dataset:
RNA-Processing Protein TDP-43 Regulates FOXO-Dependent Protein Quality Control in Stress Response

Protein homeostasis is critical for cell survival and functions during stress and is regulated at both RNA and protein levels. However, how the cell integrates RNA-processing programs with post-translational protein quality control systems is unknown. Transactive response DNA-binding protein (TARDBP/TDP-43) is an RNA-processing protein that is involved in the pathogenesis of major neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here, we report a conserved role for TDP-43, from C. elegans to mammals, in the regulation of protein clearance via activation of FOXO transcription factors. In response to proteotoxic insults, TDP-43 redistributes from the nucleus to the cytoplasm, promoting nuclear translocation of FOXOs and relieving an inhibition of FOXO activity in the nucleus. The interaction between TDP-43 and the FOXO pathway in mammalian cells is mediated by their competitive binding to 14-3-3 proteins. Consistent with FOXO-dependent protein quality control, TDP-43 regulates the levels of misfolded proteins. Therefore, TDP-43 mediates stress responses and couples the regulation of RNA metabolism and protein quality control in a FOXO-dependent manner. The results suggest that compromising the function of TDP-43 in regulating protein homeostasis may contribute to the pathogenesis of related neurodegenerative diseases.
A 40-74 GHz amplitude/phase control MMIC using 90-nm CMOS technology

The design and measurement results of a continuous amplitude/phase control CMOS MMIC are presented in this paper. This circuit uses the vector sum method to achieve continuous phase and amplitude control. The phase shifter demonstrates all continuous phase control and an insertion loss of 17 dB with 30-dB dynamic range from 40 to 75 GHz. The chip size is only 0.7 mm times 0.6 nm. To the best of the authors' knowledge, this circuit is the first demonstration of millimeter-wave phase shifters MMIC using the vector sum method, with the smallest chip size for all MMIC phase shifters and 360deg phase-control circuits in frequencies above 5 GHz reported to date.
Prototype Extraction and Adaptive OCR

To maintain OCR accuracy with decreasing quality of page image composition, production, and digitization, it is essential to tune the system to each document. We propose a prototype extraction method for document-specific OCR systems. The method automatically generates training samples from unsegmented text images and the corresponding transcripts. It is tolerant of transcription errors, so a transcript produced automatically by an imperfect omnifont OCR system can be used. The method is based on new algorithms for estimating character widths, character locations in a word, and match/nonmatch probabilities from unsegmented text. An experimental word recognition system is designed and developed to combine prototype extraction algorithms and segmentation-free word recognition. The system can adapt itself to different page images and achieve high recognition accuracy on heavily degraded print.
Learning to Rank Challenge Future directions in learning to rank

The results of the learning to rank challenge showed that the quality of the predictions from the top competitors are very close from each other. This raises a question: is learning to rank a solved problem? On the on hand, it is likely that only small incremental progress can be made in the “core” and traditional problematics of learning to rank. The challenge was set in this standard learning to rank scenario: optimize a ranking measure on a test set. But on the other hand, there are a lot of related questions and settings in learning to rank that have not been yet fully explored. We review some of them in this paper and hope that researchers interested in learning to rank will try to answer these challenging and exciting research questions. 1. Learning Theory for Ranking Many learning to rank algorithms have been shown effective through benchmark experiments. However, sometimes benchmark experiments are not as reliable as expected due to the small scales of the training and test data. In this situation, a theory is needed to guarantee the performance of an algorithm on infinite unseen data. Statistical learning theory, specifically the generalization theory, investigates the bound between the risk on the finite training data and the risk on infinite test data. In learning to rank, the risk on the training data is defined with a surrogate loss function (e.g., the pairwise losses in Ranking SVM (Joachims, 2002) and RankBoost (Freund et al., 2003)), while the risk on the test set is measured by a ranking measure (e.g., 1-NDCG or 1-MAP). Therefore, to obtain a generalization bound in this setting, we need to address the following issues: (i) a reasonable assumption on the data generation (e.g., queries and documents), (ii) a generalization bound regarding the surrogate loss function; (iii) the relationship between the surrogate loss function and the ranking measure; (iv) and the existence of the limit of the ranking measure when the number of documents approaches infinity. As for these issues, there have been a number of attempts but still a large open space to explore. • Assumption on data generation. In (Agarwal and Niyogi, 2005; Clemencon and Vayatis, 2007) it is assumed that the documents in the training data are sampled in an i.i. d. manner, no matter which queries they are associated with. However, it is c © 2011 O. Chapelle, Y. Chang & T. -Y. Liu.
A Rule-Based Object-Oriented OWL Reasoner

In this paper, we describe O-DEVICE, a memory-based knowledge-based system for reasoning and querying OWL ontologies by implementing RDF/OWL entailments in the form of production rules in order to apply the formal semantics of the language. Our approach is based on a transformation procedure of OWL ontologies into an object-oriented schema and the application of inference production rules over the generated objects in order to implement the various semantics of OWL. In order to enhance the performance of the system, we introduce a dynamic approach of generating production rules for ABOX reasoning and an incremental approach of loading ontologies. O-DEVICE is built over the CLIPS production rule system, using the object-oriented language COOL to model and handle ontology concepts and RDF resources. One of the contributions of our work is that we enable a well-known and efficient production rule system to handle OWL ontologies. We argue that although native OWL rule reasoners may process ontology information faster, they lack some of the key features that rule systems offer, such as the efficient manipulation of the information through complex rule programs. We present a comparison of our system with other OWL reasoners, showing that O-DEVICE can constitute a practical rule environment for ontology manipulation.
MUGAMMA: Mutation Analysis of Deployed Software to Increase Confidence and Assist Evolution

This paper presents a novel approach to unit testing that lets users of deployed software assist in performing mutation testing of the software. Our technique, MUGAMMA, provisions a software system so that when it executes in the field, it will determine whether users' executions would have killed mutants (without actually executing the mutants), and if so, captures the state information about those executions. In the absence of bug reports, knowledge of executions that would have killed mutants provides additional confidence in the system over that gained by the testing performed before deployment. Captured information about the state before and after execution of units (e.g., methods) can be used to construct test cases for use in unit testing when changes are made to the software. The paper also describes our prototype MuGamma implementation along with a case study that demonstrates its potential efficacy.
Increased access to emergency contraception: why it may fail.

BACKGROUND To explore why increased access to emergency contraception (EC) failed to reduce pregnancies in a recent randomized controlled trial. METHODS We used multivariable logistic regression to identify risk factors for unintended pregnancy using data from a trial involving sexually active women (n = 1490, aged 14-24 years) randomly assigned to either increased access or standard access to EC. We used predictive modeling to generate estimated pregnancy risk scores for each participant. We then examined EC use among women at low or high baseline risk of pregnancy. RESULTS Gravidity, recent history of unprotected sex (within 14 days of enrollment to study) and lower aversion to pregnancy predicted unintended pregnancy. Women in the increased access group were more likely than women in the standard access group to use EC repeatedly. This difference was significantly stronger (P = 0.03) among low risk women than high risk women [Relative risk (RR) 10.0, 95% confidence interval (CI) 6.5-15.4 and RR 5.5, 95% CI 3.8-7.9, respectively]. CONCLUSIONS Increased access to EC had a greater impact on women who were at lower baseline risk of pregnancy. This may explain in part why increased access to EC has had no measurable benefit in clinical trials.
Using activity theory to evaluate a complex response to social exclusion

The social exclusion of children and young people is the product of complex sets of circumstances. One attack on the factors that lead to exclusion in England is the Children’s Fund. The time-limited Fund requires multi-agency working and the participation of children, young people and their families in the development of preventative services. The initiative also builds on local strengths to meet local needs. This intention presents considerable challenges to a national evaluation which needs to identify what leads to a disruption of trajectories of exclusion and to ensure on-going feedback so that local strategic policies and service provision can learn while the Fund is still available. In this paper we discuss how the conceptual framework offered by activity theory allows a research design, which can deal with diversity and complexity and also ensure feedback and learning. We discuss how ideas, derived from both Leont’ev and Engeström, have in different ways informed the evaluation and consider their suitability for the task in hand.
A class of square root and division free algorithms and architectures for QRD-based adaptive signal processing

The least squares (LS) minimization problem constitutes the core of many real-time signal processing problems, such as adaptive filtering, system identification and adaptive beamforming. Recently efficient implementations of the recursive least squares (RLS) algorithm and the constrained recursive least squares (CRLS) algorithm based on the numerically stable QR decomposition (QRD) have been of great interest. Several papers have proposed modifications to the rotation algorithm that circumvent the square root operations and minimize the number of divisions that are involved in the Givens rotation. It has also been shown that all the known square root free algorithms are instances of one parametric algorithm. Recently, a square root free and division free algorithm has also been proposed. In this paper, we propose a family of square root and division free algorithms and examine its relationship with the square root free parametric family. We choose a specific instance for each one of the two parametric algorithms and make a comparative study of the systolic structures based on these two instances, as well as the standard Givens rotation. We consider the architectures for both the optimal residual computation and the optimal weight vector extraction. The dynamic range of the newly proposed algorithm for QRD-RLS optimal residual computation and the wordlength lower bounds that guarantee no overflow are presented. The numerical stability of the algorithm is also considered. A number of obscure points relevant to the realization of the QRD-RLS and the QRD-CRLS algorithms are clarified. Some systolic structures that are described in this paper are very promising, since they require less computational complexity (in various aspects) than the structures known to date and they make the VLSI implementation easier. >
Improved Daytime Column-Integrated Precipitable Water Vapor from Vaisala Radiosonde Humidity Sensors

Accurate water vapor profiles from radiosondes are essential for long-term climate prediction, weather prediction, validation of remote sensing retrievals, and other applications. The Vaisala RS80, RS90, and RS92 radiosondes are among the more commonly deployed radiosondes in the world. However, numerous investigators have shown that the daytime water vapor profiles measured by these instruments present a significant dry bias due to the solar heating of the humidity sensor. This bias in the column-integrated precipitable water vapor (PWV), along with variability due to calibration, can be removed by scaling the humidity profile to agree with the PWV retrieved from a microwave radiometer (MWR), as has been demonstrated by several previous studies. Infrared radiative closure analyses have shown that the MWR PWV does not present daytime versus nighttime differences; thus, scaling by the MWR is a possible approach for removing the daytime dry bias. However, MWR measurements are not routinely available at all radiosonde launch sites. Starting from a long-term series of sonde and MWR PWV measurements from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site, the authors have developed a simple correction to the column-integrated sonde PWV, derived from an analysis of the ratio of the MWR and sonde measurements; this correction is a function of the atmospheric transmittance as determined by the solar zenith angle, and it effectively removes the daytime dry bias at all solar zenith angles. The correction was validated by successfully applying it to an independent dataset from the ARM tropical western Pacific (TWP) site.
A Novel Retrieval Oriented Robust Image Hashing Based on Fractional Fourier Transform

In order to improve the security and robustness of image retrieval, a novel image hashing algorithm based on fractional Fourier transform (FRFT) for content-based image retrieval (CBIR) application is proposed in this paper. By employing FRFT and normalized Hamming distance, a robust hashing sequence is obtained by preprocessing, feature extracting and post processing. The security of proposed algorithm is totally depended on the orders of FRFT which are saved as secret keys. For illustration, several benchmark images are utilized to show the feasibility of the image hashing algorithm. Experimental results show that the proposed scheme is robust against perceptually acceptable modifications to the image such as JPEG compression, mid-filtering, and rotation. Therefore, the scheme proposed in this paper is suitable for CBIR application.
Predicting the Academic Achievement of Disadvantaged College Bound Students.

In the study of the effectiveness of traditional methods of evaluation (high school GPA and SAT scores) and subjective methods of evaluation (self, peer, parent, counselor, and teacher perceptions) in predicting the academic performance of 47 disadvantaged college freshmen, traditional methods proved inadequate. Among the subjective methods, peer prediction was found to be significantly related to the disadvantaged student's academic performance. Counselors achieved the dubious distinction of having the poorest "track record" in estimating the academic performance of the students. Study results suggest that the more hours disadvantaged students attempt, the higher their achieved GPA. This finding tends to refute the assumption that disadvantaged students perform tetter academically when they carry reduced class loads. (Author)
Rescue of Synaptic Failure and Alleviation of Learning and Memory Impairments in a Trisomic Mouse Model of Down Syndrome

Abstract Down syndrome (DS) is caused by the triplication of ∼240 protein-coding genes on chromosome 21 and is the most prevalent form of developmental disability. This condition results in abnormalities in many organ systems, as well as in intellectual retardation. Many previous efforts to understand brain dysfunction in DS have indicated that cognitive deficits are coincident with reduced synaptic plasticity and decreased neuronal proliferation. One therapeutic strategy for optimizing the microenvironment for neuronal proliferation and synaptic plasticity in the brain is the use of neurotrophins to restore the homeostasis of the brain biochemical milieu. Here, we show that peripheral administration of Peptide 6, an 11-mer corresponding to an active region of ciliary neurotrophic factor, amino acid residues 146 to 156, can inhibit learning and memory impairments in Ts65Dn mice, a trisomic mouse model of DS. Long-term treatment with Peptide 6 enhanced the pool of neural progenitor cells in the hippocampus and increased levels of synaptic proteins crucial for synaptic plasticity. These findings suggest a therapeutic potential of Peptide 6 in promoting functional neural integration intonetworks, thereby strengthening biologic substrates of memory processing.
Non-invasive optical imaging of stroke

The acute onset of a neurological deficit is the key clinical feature of stroke. In most cases, however, pathophysiological changes in the cerebral vasculature precede the event, often by many years. Persisting neurological deficits may also require long-term rehabilitation. Hence, stroke may be considered a chronic disease, and diagnostic and therapeutic efforts must include identification of specific risk factors, and the monitoring of and interventions in the acute and subacute stages, and should aim at a pathophysiologically based approach to optimize the rehabilitative effort. Non-invasive optical techniques have been experimentally used in all three stages of the disease and may complement the established diagnostic and monitoring tools. Here, we provide an overview of studies using the methodology in the context of stroke, and we sketch perspectives of how they may be integrated into the assessment of the highly dynamic pathophysiological processes during the acute and subacute stages of the disease and also during rehabilitation and (secondary) prevention of stroke.
A parallel architecture for hardware face detection

Face detection is a very important application in the field of machine vision. In this paper, we present a scalable parallel architecture which performs face detection using the AdaBoost algorithm. Experimental results show that the proposed architecture can detect faces with the same accuracy as the software implementation, on real-time video at a frame rate of 52 frames per second
Embodied display: A critical examination of the biopedagogical experience of wearing health

ABSTRACT Wearables, technological devices for promoting health, physical activity, and weight control, have become increasingly popular. However, debates are ongoing in popular and academic settings regarding their health potential and implications. This article contributes to these conversations, offering a reflexive, collaborative exploration into the experiences of four critical health scholars using wearable technology (Fitbits). Using biopedagogies, the authors explore their experiences with body-size, fatness, and physical activity in relation to healthist and dominant “obesity” discourses. The authors contend this approach could support educators to facilitate understanding of power and knowledge dynamics that infuse new media and reinforce weight stigma, fatphobia, and bullying.
Social Tourism Using Photos

Mobile phones are frequently used to determine one's location and navigation directions, and they can also provide a platform for connecting tourists with each other. This paper proposes a system that uses a set of geotagged photos to automatically compute the geographic location of another photo and then augment that photo with text and images that enable collaboration and enhance navigation. The system breaks up the world into smaller regions and then computes a geographic location using one method and a complete camera pose using a more complex method, both methods utilize robust local feature matching. Tourists can then add text and images to objects in a photo which are then augmented onto other photos viewing the same object, allowing them to share information linked to speci c objects in their environment. Navigation information in the form of arrows are projected onto photos pointing tourists in the direction of their selected destination. This system is particularly applicable to places such as malls, museums, and theme parks where photos can provide more information than GPS, but it can be applied anywhere.
On fitting power laws to ecological data

Heavy-tailed or power-law distributions are becoming increasingly common in biological literature. A wide range of biological data has been fitted to distributions with heavy tails. Many of these studies use simple fitting methods to find the parameters in the distribution, which can give highly misleading results. The potential pitfalls that can occur when using these methods are pointed out, and a step-by-step guide to fitting power-law distributions and assessing their goodness-of-fit is offered.
Time delay of SBS 0909+532

The time delays between the components of a lensed quasar are basic tools to analyze the expansion of the Universe and the structure of the main lens galaxy halo. In this paper, we focus on the variability and time delay of the double system SBS 0909+532A,B as well as the time behaviour of the field stars. We use VR optical observations of SBS 0909+532A,B and the field stars in 2003. The frames were taken at Cal ar Alto, Maidanak and Wise observatories, and the VR light curves of the field stars and quasar components are derived from aperture and point-spread function fitting met hods. We measure the R-band time delay of the system from the � 2 and dispersion techniques and 1000 synthetic light curves based on the observed records. One nearby field star (S BS 0909+532c) is found to be variable, and the other two nearby field stars are non-vari able sources. With respect to the quasar components, the R-band records seem more reliable and are more densely pop- ulated than the V-band ones. The observed R-band fluctuations permit a pre-conditioned measurement of the time delay. From the � 2 minimization, if we assume that the quasar emission is observed first in B and afterwards in A (in agreeme nt with basic observations of the system and the corresponding predictions), we obtain ��BA =− 45 +1 −11 days (95%