Miracle-dz/UniFAR-FTUs huggingface dataset:
Complex SUMO-1 Regulation of Cardiac Transcription Factor Nkx2-5

Reversible post-translational protein modifications such as SUMOylation add complexity to cardiac transcriptional regulation. The homeodomain transcription factor Nkx2-5/Csx is essential for heart specification and morphogenesis. It has been previously suggested that SUMOylation of lysine 51 (K51) of Nkx2-5 is essential for its DNA binding and transcriptional activation. Here, we confirm that SUMOylation strongly enhances Nkx2-5 transcriptional activity and that residue K51 of Nkx2-5 is a SUMOylation target. However, in a range of cultured cell lines we find that a point mutation of K51 to arginine (K51R) does not affect Nkx2-5 activity or DNA binding, suggesting the existence of additional Nkx2-5 SUMOylated residues. Using biochemical assays, we demonstrate that Nkx2-5 is SUMOylated on at least one additional site, and this is the predominant site in cardiac cells. The second site is either non-canonical or a “shifting” site, as mutation of predicted consensus sites and indeed every individual lysine in the context of the K51R mutation failed to impair Nkx2-5 transcriptional synergism with SUMO, or its nuclear localization and DNA binding. We also observe SUMOylation of Nkx2-5 cofactors, which may be critical to Nkx2-5 regulation. Our data reveal highly complex regulatory mechanisms driven by SUMOylation to modulate Nkx2-5 activity.
Reinforcement Learning from Demonstration through Shaping

Reinforcement learning describes how a learning agent can achieve optimal behaviour based on interactions with its environment and reward feedback. A limiting factor in reinforcement learning as employed in artificial intelligence is the need for an often prohibitively large number of environment samples before the agent reaches a desirable level of performance. Learning from demonstration is an approach that provides the agent with demonstrations by a supposed expert, from which it should derive suitable behaviour. Yet, one of the challenges of learning from demonstration is that no guarantees can be provided for the quality of the demonstrations, and thus the learned behavior. In this paper, we investigate the intersection of these two approaches, leveraging the theoretical guarantees provided by reinforcement learning, and using expert demonstrations to speed up this learning by biasing exploration through a process called reward shaping. This approach allows us to leverage human input without making an erroneous assumption regarding demonstration optimality. We show experimentally that this approach requires significantly fewer demonstrations, is more robust against suboptimality of demonstrations, and achieves much faster learning than the recently developed HAT algorithm.
Eutrophication has no short-term effect on the Cymbastela stipitata holobiont

Levels of nitrogen in coastal areas have been rapidly increasing due to accumulative inputs of sewage and terrigenous sediments carrying fertilizers. Sponges have an immense filtering capacity and may be directly impacted (positively or negatively) by elevated concentrations of nitrogen. Sponges also host a wide diversity of microbes involved in nitrogen metabolism, yet little is known about the effects of nitrogen loading on these symbiotic partnerships. Manipulative experiments were undertaken to examine the potential effects of excess nitrogen (up to 240 μM) on microbial symbiosis in the abundant sponge species Cymbastela stipitata. Microbial composition and activity were examined using 454-pyrotag sequencing of DNA- and RNA-derived samples. Despite the high levels of nitrogen exposure (up to 124-fold above ambient), sponges appeared visibly unaffected at all treatment concentrations. At the phylum level, the microbial community was consistent between all sponge samples regardless of nitrogen treatment, with Cyanobacteria and Thaumarchaeota being the dominant taxa. Higher microbial diversity was observed at the operational taxonomic units (OTU) level (97% sequence similarity), with only 40% of OTUs shared between samples from all treatments. However, a single cyanobacterial OTU dominated the community of all individuals (average 73.5%) and this OTU did not vary with nitrogen treatment. The conserved microbial community in all sponges irrespective of nitrogen treatment highlights the stability of the sponge-microbe relationship and indicates that the holobiont is resistant to short pulses of nitrogen at levels mimicking sewage effluent.
A CMOS interface circuit for piezoresistive accelerometer

The non-ideal effect generated by piezoresistive accelerometer with Favors Stone electric bridge structure has a sever negative effect on the performance of the whole system. How to suppress or compensate this non-ideal effect with the interface circuit attracts great attention but remains a big challenge. A novel interface circuit for piezoresistive accelerometer which calibrates zero offset of the sensor is designed for this aim. It is based on successive approximation. Comparer, counter and DAC are adopted to reduce the offset of the system and to enhance dynamic range. Trans-conductance with capacitances feedback compensation technology is used in the design of low-power three-stage amplifier to reduce the power consumption of the system. The power of counter and comparer is cut off after auto-zeroing to further reduce power dissipation. The circuit is fabricated with 0. 5µm CMOS standard process. The testing results exhibit a max auto-zeroing voltage of 500mV, with 4mV resolution and 4.62mW power consumption.
TATUBOT – Robotic System for Inspection of Undergrounded Cable System

In this paper, it is presented the development of an innovative and low-cost robotic mobile system to be employed in inspection of underground electrical distribution lines and pipes. The system is composed of a robot with different sensors (infrared, acoustic, and FEF) which permit to move inside pipes and detect overheated points, partial electrical discharges and the occurrence of cable treeing. It is showed the mechanical structure of the robot, the overall architecture of the system and preliminary results.
Forward error correction of FSK alphabets for noncoherent transmissions over AWGN channel

We show that several coding schemes, in particular turbo encoding, dramatically improve the performance of a noncoherently detected frequency shift-keying modulation with correlated signals. The proposed a posteriori probability (APP) decoder based on bit-by-bit decisions proves to be highly flexible and more efficient than a classical block decisions decoding scheme. Moreover, the choice of the FSK modulation tone spacing is important. Simulation results show that the turbo-coded FSK exhibits the lowest error probability when compared to TCM, convolutional and lattice encoding schemes.
Dislocation Driven Problems in Atomistic Modelling of Materials

Understanding the mechanical properties of technologically advanced materials from quantum mechanical predictions based on electronic structure calculations remains one of the most challenging problems in modern computational materials science. In this paper, we illustrate this challenge from our current investigations on dislocation behaviour in bcc transition metals that are promising candidates for materials subject to fast neutron irradiations in future fusion power plants. Starting with the relationship between the brittleness and the negative Cauchy pressure of elastic constants in materials within the so-called Harris-Foulkes approximation to the density functional theory (DFT), we briefly discuss the importance of the generic form of interatomic potentials in order to reproduce a correct Cauchy pressure. The latter in turn plays an important role in predicting dislocation properties in fcc iridium and therefore allows us to explain experimental observation of the intrinsic brittleness of this material. We then investigate the behaviour of the (1/2)[111] screw dislocation that controls plastic deformation in bcc metals from atomistic simulation. Here we show the atomic phenomena associated with the non-planar core structure of dislocations in bcc iron from the Stoner tight-binding bond model. The crucial point comes from the accurate evaluation of forces implemented within the charge neutrality conditions in the treatment of the spin-polarized dependence in the electronic structure calculations. In agreement with DFT studies, the magnetic bond-order potentials predict a non-degenerate core structure for screw dislocations in Fe. Finally, a new analytic expression has been derived for the migration energy barrier for the one-dimensional (1D) motion of crowdions, which are the most stable self-interstitial atom (SIA) defects predicted by our DFT calculations. Importantly, the latter study is strongly supported by the recent observation of 1D diffusion of nanometer-sized dislocation loops, observed very recently under in situ electron microscope irradiation for bcc transition metals.
Authentication in the Taos operating system

We describe a design for security in a distributed system and its implementation. In our design, applications gain access to security services through a narrow interface. This interface provides a notion of identity that includes simple principals, groups, roles, and delegations. A new operating system component manages principals, credentials, and secure channels. It checks credentials according to the formal rules of a logic of authentication. Our implementation is efficient enough to support a substantial user community.
Stitching and Surface Reconstruction From Endoscopic Image Sequences: A Review of Applications and Methods

Endoscopic procedures form part of routine clinical practice for minimally invasive examinations and interventions. While they are beneficial for the patient, reducing surgical trauma and making convalescence times shorter, they make orientation and manipulation more challenging for the physician, due to the limited field of view through the endoscope. However, this drawback can be reduced by means of medical image processing and computer vision, using image stitching and surface reconstruction methods to expand the field of view. This paper provides a comprehensive overview of the current state of the art in endoscopic image stitching and surface reconstruction. The literature in the relevant fields of application and algorithmic approaches is surveyed. The technological maturity of the methods and current challenges and trends are analyzed.
Voiceless voice: An intelligent communication system for physically retarded communities

Speech is one of the common modes of communication and it is a process of transferring information from one entity to another but people who are paralyzed like amyotrophic lateral sclerosis (ALS) and disability like communication disorder are finding difficulties in communication with the external world. Studies show that Brain machine interface (BMI) provides a communication channel between the human brain and an external device. In this research work, a possible option for rehabilitation of such patients through brain machine interfaces which uses their active cognition capabilities to convey the imaginary thoughts in vocalized form has been proposed. EEG signals collected from 12 subjects during 19 mental tasks are used to test the classifiers. Spectral energy on the band power of the EEG signals is extracted for each frame. PCA features extracted from the spectral energy features are used the neural net to classify different mental tasks. Results obtained show average classification rates ranging from 93.15% to 94.74 %.
Analysis of Radiation Response and Recovery Characteristics of Amorphous Silicon Solar Cells

The radiation response and recovery characteristics of amorphous silicon (a-Si) thin-film solar cells were investigated. The solar cells studied were a-Si/a-Si dual-junction cell and a-Si/a-SiGe cell. The cells were irradiated with monoenergetic protons from 0.05 to 10 MeV to several fluences. For the cells, the displacement damage effects could model the proton-induced degradation much better than the ionizing radiation effects could. Thus, the changes in photovoltaic parameters could be plotted by a single characteristic curve against the displacement damage dose (Dd) even if the proton energy was low enough to create local damage in the active layers. The results indicated that the proton-induced degradations of the a-Si solar cell correlated with the displacement damage effects. In addition, we have reported the recovery characteristics by thermal annealing and light illumination. The electrical outputs of the cells significantly recovered at 70 and 130 degC but were not restored by light illumination
Electricity load forecasting using non-decimated wavelet prediction methods with two-stage feature selection

We present a new approach for electricity load forecasting based on non-decimated multilevel wavelet transform, in combination with two-stage feature selection and machine learning prediction algorithm. The key idea is to decompose the non-stationary and noisy electricity load data into sub-series of different frequencies, analyse and predict them separately. The feature selection integrates autocorrelation and ranking-based methods. We evaluate the predictive performance of our approach using two years of Australian electricity data. The results show that it provides accurate predictions, outperforming exponential smoothing with single and double seasonality, the industry model and all other baselines.
Hospital Information Technology and Positive Financial Performance: A Different Approach to Finding an ROI

EXECUTIVE SUMMARY This empirical study examined the relationship between information technology (IT) utilization and hospital financial performance. Using primary and secondary data, we specified and tested a series of regression models that examined this relationship in Florida hospitals. In addition, we employed performance group analysis for a select group of operational performance indicators. Findings suggested a significant and positive relationship between increased levels of IT use and various measures of financial performance, even after controlling for case‐mix acuity and bed size. Regardless of the analysis or method employed, the results indicated that IT adoption is consistently related to improved financial outcomes both overall and operationally. This relationship was present when examining IT collectively and for clinical IT, administrative IT, and strategic IT as individual measures. Lastly, although higher IT use was associated with a higher level of revenues, income, or cash flow, higher use was also associated with ratios based on higher expenses. This probably reflects the relatively high acquisition costs associated with obtaining and maintaining sophisticated IT systems. Given that a true return on investment is so difficult to obtain for many individual hospitalwide IT systems, our data can serve as a proxy for hospital leaders and policymakers who want to understand the potential financial effects of investing in IT in the acute care setting.
Combining Statistical Techniques and Lexico-syntactic Patterns for Semantic Relations Extraction from Text

We describe here a methodology to combine two different techniques for Semantic Relation Extraction from texts. On the one hand, generic lexicosyntactic patterns are applied to the linguistically analyzed corpus to detect a first set of pairs of co-occurring words, possibly involved in “syntagmatic” relations. On the other hand, a statistical unsupervised association system is used to obtain a second set of pairs of “distributionally similar” terms, that appear to occur in similar contexts, thus possibly involved in “paradigmatic” relations. The approach aims at learning ontological information by filtering the candidate relations obtained through generic lexico-syntactic patterns and by labelling the anonymous relations obtained through the statistical system. The resulting set of relations can be used to enrich existing ontologies and for semantic annotation of documents or web pages.
Respiratory health effects among schoolchildren and their relationship to air pollutants in Korea

The objective of this study is to investigate the relationship between five air pollutants (PM10, SO2, NO2, O3, CO) measured on the daily basis, and adverse health symptoms using epidemiological surveillance data. The generalized estimated equation (GEE) model, a logistic regression analysis model, was used to estimate the effects of air pollution on children's daily health symptoms, focusing on the morbidity including both respiratory and allergic symptoms in four different cities. Analysis of the effects of each pollutant on children's respiratory and allergic symptoms demonstrated that CO affected all symptoms in all the study areas. When the concentration of SO2 and NO2 was elevated, upper respiratory symptoms increased significantly. In contrast, when the concentration of O3 rose, the symptoms decreased significantly. The relationship between measured concentrations and health symptoms was site-dependent for each pollutant.
Development and Evaluation of a Parenting Intervention Program: Integration of Scientific and Practical Approaches

This article presents a case study describing practical and scientific strategies that were applied to assess human-computer interaction, with the foci on software content development (i.e., content validation and interface comparisons), evaluation (i.e., different types of criteria, effect sizes, effect ratios, targeted goals met), and user acceptability. A parenting intervention program entitled Parenting Adolescents Wisely (PAW) was delivered to 42 parents in community settings via two formats: noninteractive videotape and interactive multimedia. Based on a content validation model developed in this study, both formats consisted of critical skills identified from past empirical studies. Results of applying both formats to at-risk families showed improvements on three types of evaluative criteria: reaction, learning, and behavior. Improvements in children's problem behaviors were clinically significant for 33% to 48% of the children whose parents used the program. Finally, the PAW program showed a substantial cost benefit based on effect ratios, compared with other parenting interventions.
A novel large signal modelling and dynamic analysis of paralleled DC/DC converters with automatic load sharing control

This paper presents a unified method for developing power stage transfer functions of paralleled DC/DC converters employing automatic load sharing control. The proposed technique uses large signal averaged models to derive the steady-state and small signal transfer functions, instead of employing small signal modeling technique used widely in literatures. The proposed approach is general and can be applied to any number of paralleled modules. For illustration purpose, this modeling method is applied to two paralleled buck converters with automatic load sharing control, and the corresponding large signal characteristics are analyzed. Moreover, a design methodology for the current share (CS) compensator based on the current share loop gain has been presented. Stability and dynamic performance of the CS control are studied. Simulation results of two paralleled buck converter converting the input DC voltage of 12 V, to 5 V DC at 2/spl times/20 A are presented in order to verify the theoretical approach reported in the paper.
Diabetic Neuropathies: Update on Definitions, Diagnostic Criteria, Estimation of Severity, and Treatments

Preceding the joint meeting of the 19th annual Diabetic Neuropathy Study Group of the European Association for the Study of Diabetes (NEURODIAB) and the 8th International Symposium on Diabetic Neuropathy in Toronto, Canada, 13–18 October 2009, expert panels were convened to provide updates on classification, definitions, diagnostic criteria, and treatments of diabetic peripheral neuropathies (DPNs), autonomic neuropathy, painful DPNs, and structural alterations in DPNs.
Block Triangular and Skew-Hermitian Splitting Methods for Positive-Definite Linear Systems

By further generalizing the concept of Hermitian (or normal) and skew-Hermitian splitting for a non-Hermitian and positive-definite matrix, we introduce a new splitting, called positive-definite and skew-Hermitian splitting (PSS), and then establish a class of PSS methods similar to the Hermitian (or normal) and skew-Hermitian splitting (HSS or NSS) method for iteratively solving the positive-definite systems of linear equations. Theoretical analysis shows that the PSS method converges unconditionally to the exact solution of the linear system, with the upper bound of its convergence factor dependent only on the spectrum of the positive-definite splitting matrix and independent of the spectrum of the skew-Hermitian splitting matrix as well as the eigenvectors of all matrices involved. When we specialize the PSS to block triangular (or triangular) and skew-Hermitian splitting (BTSS or TSS), the PSS method naturally leads to a BTSS or TSS iteration method, which may be more practical and efficient than the HSS and NSS iteration methods. Applications of the BTSS method to the linear systems of block two-by-two structures are discussed in detail. Numerical experiments further show the effectiveness of our new methods.
Music mood classification by rhythm and bass-line unit pattern analysis

This paper discusses an approach for the feature extraction for audio mood classification which is an important and tough problem in the field of music information retrieval (MIR). In this task the timbral information has been widely used, however many musical moods are characterized not only by timbral information but also by musical scale and temporal features such as rhythm patterns and bass-line patterns. In particular, modern music pieces mostly have certain fixed rhythm and bass-line patterns, and these patterns can characterize the impression of songs. We have proposed the extraction of rhythm and bass-line patterns, and these unit pattern analysis are combined with statistical feature extraction for mood classification. Experimental results show that the automatically calculated unit pattern information can be used to effectively classify musical mood.
The cyclicality of effective wages within employer-employee matches in a rigid labor market

The Cyclicality of Effective Wages within Employer-Employee Matches in a Rigid Labor Market This study analyzes real wage cyclicality for male full-time workers within employer-employee matches in Germany over the period 1984-2004. Five different wage measures are compared: the standard hourly wage rate; hourly wage earnings including overtime and bonus pay; the effective wage, which takes into account unpaid overtime; and monthly earnings, with and without additional pay. None of the hourly wage measures exhibits cyclicality except for the group of salaried workers with unpaid overtime. Their effective wages show a strongly procyclical reaction to changes in unemployment. Despite acyclical wage rates, salaried workers without unpaid overtime experienced procyclical earnings movements if they had income from extra pay. Monthly earnings were also procyclical for hourly paid workers with overtime pay. These findings suggest that cyclical earnings movements are generated by variable pay components, such as bonuses and overtime, and by flexible working hours. The degree of earnings procyclicality revealed for the German labor market is comparable to the United States. JEL Classification: E32, J31
Altered BCR and TLR signals promote enhanced positive selection of autoreactive transitional B cells in Wiskott-Aldrich syndrome

Kolhatkar et al. report that altered BCR and TLR signaling orchestrates increased positive selection of transitional B cells expressing low-affinity self-reactive BCRs, leading to their enrichment within the naive B cell compartment. These findings have important implications to understand events that promote altered B cell selection in both Wiskott-Aldrich syndrome patients and in other autoimmune-prone individuals.