Miracle-dz/UniFAR-FTUs huggingface dataset:
An Instrumented Urethral Catheter With Supercapacitor Based Force Sensor

BACKGROUND Urinary incontinence (UI), defined by the International Continence Society as “the complaint of any involuntary leakage of urine” [1], is believed to affect at least 13 million people in the United States. Around 80% of people affected are women [2,3]. The most common type of UI in women is stress urinary incontinence (SUI) [4]. Although not identified as lifethreatening, UI may lead to withdrawal from social situations and reduced life quality. The cause of SUI can be diagnosed using urodynamics [5]. Urodynamic testing normally consists of two phases: filling cystometry to investigate storage of urine in the bladder, and pressure-flow measurement to examine urine voiding performance. During these tests, a Foley catheter is inserted into the bladder through the urethra (Fig. 1) to fill and empty the bladder. Various force/contact pressure sensing mechanisms could be explored for use on the Foley catheter. Piezoelectric sensors [6] are typically not utilized for this application, since typical piezoelectric materials do not measure static forces and the urethral pressure distribution to be measured in this application is either static or slowly varying. Piezoresistive sensors [7] are not typically used either, since they are susceptible to drift and require calibration just before the measurement. Capacitive pressure sensors are highly sensitive and have low-drift properties with temperature and humidity. However, capacitive sensors suffer from an inherent problem for in vivo applications – they suffer from significant parasitic capacitance induced by the body and body fluids [8]. The interference from human tissues on the electric field of the sensor can cause dynamic parasitic noise, which can greatly pollute the sensor signal. The parasitic capacitance for in vivo use is of the order of femto or pico Farads according to previous research of our group ([3,8,9]) and is hard to eliminate by estimation and subtraction.
Isolation of Lignin from Masson Pine by Liquid-Liquid Extraction Based on Complete Dissolution in NaOH Aqueous Solution

A method for lignin isolation from softwood based on complete dissolution in NaOH aqueous solution and liquid-liquid extraction was introduced. The structural features of milled alkali-soluble lignin (MAL) were comparatively analyzed with those of classical milled wood lignin (MWL) by means of alkaline nitrobenzene oxidation (NBO) and molecular weight, as well as Fourier transform infrared (FTIR) and nuclear magnetic resonance (NMR) spectra analyses. The results showed that the yield of crude MAL (34.2%) was about twice as much as that of MWL (16.4%). The NBO product yields of MWL and MAL were quite similar. The weight-average molecular weight of MAL (10,400 g mol-1) was much higher than for MWL (6,970 g mol-1). Both MWL and MAL displayed similar FTIR, UV, 1H NMR, and 1H-13C HSQC NMR spectra. The total OH content of MAL (4.48 mmol g-1) was higher than that of MWL (3.89 mmol g-1). Compared with MWL, MAL showed similar structural characteristics but better isolation yield and higher molecular weight.
A Tractable State-Space Model for Symmetric Positive-Definite Matrices

The Bayesian analysis of a state-space model includes computing the posterior distribution of the system's parameters as well as its latent states. When the latent states wander around R n there are several well-known modeling components and computational tools that may be protably combined to achieve this task. When the latent states are constrained to a strict subset of R n these models and tools are either impaired or break down completely. State-space models whose latent states are covariance matrices arise in nance and exemplify the challenge of devising tractable models in the constrained setting. To that end, we present a state-space model whose observations and latent states take values on the manifold of symmetric positive-denite matrices and for which one may easily compute the posterior distribution of the latent states and the system's parameters as well as ltered distributions and one-step ahead predictions. Employing the model within the context of nance, we show how one can use realized covariance matrices as data to predict latent time-varying covariance matrices. This approach out-performs factor stochastic volatility.
On the Analysis of IP Traffic Distribution in the Network of Suranaree University of Technology

This paper presents the IP traffic analysis. The traffic was collected from the network of Suranaree University of Technology using the software based on the Simple Network Management Protocol (SNMP). In particular, we analyze the distribution of the aggregated traffic during the hours of peak load and light load. The traffic profiles including the parameters described the traffic distributions were derived. From the statistical analysis applying three different methods, including the Kolmogorov Smirnov test, Anderson Darling test, and Chi-Squared test, we found that the IP traffic distribution is a non-normal distribution and the distributions during the peak load and the light load are different. The experimental study and analysis show high uncertainty of the IP traffic. Keywords—IP traffic analysis, IP traffic distribution, Traffic uncertainty
SOLUTION FOR N QUEENS PROBLEM USING A PHOTOSYNTHETIC ALGORITH

Abstract The process of the reaction of carbon molecules in the dark reaction of photosynthesis was chosen as a BDA (Biosystem-Derived Algorithm). In this study, the BDA was referred to as the 'Photosynthetic Algorithm (PA)'. The PA utilizes the rules governing the conversion of carbon molecules from one substance to another in the Benson-Calvin cycle and Photorespiration reactions. In this paper, the principles of the PA are presented in detail. The Queen's problem was selected as a typical optimization problem to demonstrate the performance of the PA.
Evaluation of the Mountain Wave Forecast Model's Stratospheric Turbulence Simulations

Abstract : Stratospheric turbulence (Stratoturb) is a well-known hazard to aircraft in flight. Forecasting mountain waves, specifically the breaking of these waves, is necessary to accurately predict the presence of Stratoturb. The Air Force Weather Agency (AFWA) requested a product with the capability of forecasting Stratoturb at 30, 50, and 70 mb using model data currently available, To facilitate their request, the Mountain Wave Forecast Model (MWFM) was acquired from the Naval Research Laboratory. MWFM turbulence forecasts generated twice daily over East Asia, using the AVN and MM5 models for initialization, were compared to S' layer turbulence analyses from the Rawinsonde Observation (RAOB) program, currently used operationally to warn aircrews. Actual verification of the MWFM forecasts was unachievable since in situ turbulence observations were not available, and as a result only subjective assessments of the MWFM's capabilities were possible. The MWFM was determined to be the superior forecast tool based on the temporal and spatial coverage provided when compared to RAOB as well as its promising ability to alleviate the reported overforecasting inherent to the RAOB analyses. Therefore, the MWFM, including code modifications made at AFIT, was recommended for use by AFWA. Further objective analysis of the model's accuracy should be conducted.
Trading Off Power Consumption and Prediction Performance in Wearable Motion Sensors

Power consumption is identified as one of the main complications in designing practical wearable systems, mainly due to their stringent resource limitations. When designing wearable technologies, several system-level design choices, which directly contribute to the energy consumption of these systems, must be considered. In this article, we propose a computationally lightweight system optimization framework that trades off power consumption and performance in connected wearable motion sensors. While existing approaches exclusively focus on one or a few hand-picked design variables, our framework holistically finds the optimal power-performance solution with respect to the specified application need. Our design tackles a multi-variant non-convex optimization problem that is theoretically hard to solve. To decrease the complexity, we propose a smoothing function that reduces this optimization to a convex problem. The reduced optimization is then solved in linear time using a devised derivative-free optimization approach, namely cyclic coordinate search. We evaluate our framework against several holistic optimization baselines using a real-world wearable activity recognition dataset. We minimize the energy consumption for various activity-recognition performance thresholds ranging from 40% to 80% and demonstrate up to 64% energy savings.
THE STRUCTURE OF SOUTH AFRICAN MILK PRODUCTION TECHNOLOGY: A PARAMETRIC APPROACH TO SUPPLY ANALYSIS

A parametric approach was followed in this study to analyse the structure of milk production and supply systems based on farm level data from a cross-section of dairy farms in South Africa (SOUTH AFRICA) for the 1997/1998 production year. The results show that convexity of the profit function in all prices holds in milk production in South Africa. Milk production and livestock trading activities are complements in the multi-input, multi-output dairy farms studied. Both activities used purchased and self produced feed inputs intensively, with a higher intensity in purchased feed use. The two variable inputs are gross complements in the long-run and net substitutes in the short term. The long-term expansion effects overshadow short-term substitution between these inputs. The high intensity of purchased feed use has implications for the animal feed sector in terms of facing increased competition for already limited natural animal protein sources (fish meal, bone meal, etc).
Developing Better Public Policy to Motivate Responsible Environmental Behavior–An Examination of Managers' Attitudes and Perceptions Towards Controlling Introduced Species

ABSTRACT This paper examines the application of public policy, including social marketing, to programs designed to control an environmentally harmful introduced species in Australia. Managers involved in dealing with the issue identify a range of factors that contribute to the lack of success of existing control programs. The results suggest that there needs to be a broad-based integrated program that incorporates changes in stakeholders' attitudes as well as governmental resources and support for implementation of relevant initiatives.
Dislocation of Type I Membrane Proteins from the ER to the Cytosol Is Sensitive to Changes in Redox Potential

The human cytomegalovirus (HCMV) gene products US2 and US11 dislocate major histocompatibility class I heavy chains from the ER and target them for proteasomal degradation in the cytosol. The dislocation reaction is inhibited by agents that affect intracellular redox potential and/or free thiol status, such as diamide and N-ethylmaleimide. Subcellular fractionation experiments indicate that this inhibition occurs at the stage of discharge from the ER into the cytosol. The T cell receptor α (TCR α) chain is also degraded by a similar set of reactions, yet in a manner independent of virally encoded gene products. Diamide and N-ethylmaleimide likewise inhibit the dislocation of the full-length TCR α chain from the ER, as well as a truncated, mutant version of TCR α chain that lacks cysteine residues. Cytosolic destruction of glycosylated, ER-resident type I membrane proteins, therefore, requires maintenance of a proper redox potential for the initial step of removal of the substrate from the ER environment.
Realization of some Galois representations of low degree in Mordell-Weil groups

For example, suppose that G ∼= S9 and H ∼= S8, where Sn denotes the symmetric group on n letters. Then ρ is one of the two irreducible representations of G of dimension 8, and according to our theorem there exists an elliptic curve E over M such that ρ occurs in Q⊗E(K). The other irreducible representation of G of dimension 8 is ρ⊗ , where is the “sign” character of G, and it too can be realized in a Mordell-Weil group: in fact a straightforward argument shows that if ρ occurs in Q⊗E(K) then ρ⊗ occurs in Q⊗E (K), where E denotes the quadratic twist of E by . The case G ∼= S9, H ∼= S8 just mentioned is actually the maximal instance of the theorem, in two respects: first, for any choice of G and H the dimension of ρ will be 8, and second, if we assume without loss of generality that K is the normal closure of L over M then G is always isomorphic to a subgroup of S9. It follows in particular that G is not isomorphic to one of the Weyl groups W (E6), W (E7), or W (E8), because these groups do not have embeddings in S9. Thus we do not recover the “biggest” examples of Shioda ([8], [9], [10]), whose work on Mordell-Weil lattices of elliptic surfaces yields examples of type E6, E7, and E8 by specialization. Here for a root system X the phrase “example of type X” means a Galois extension of number fields K/M together with an elliptic
IMMIGRATION IN CATALONIA

Since 2001 Catalonia has experienced a tremendous inflow of international immigrants, who at this moment account for about 14 per cent of the total population. Immigration however is not a new phenomenon in Catalonia. A close look at figure 1 shows that the immigration rate as a share of the total population in the second half of the 60 ́s was similar to the one experienced between 2001 and 2006. The main difference however is that while in the 60’s migration flows came mainly from elsewhere in Spain, in the last few years the migrants come from about everywhere in the world.
Longer RNNs

For problems with long range dependencies, training of Recurrent Neural Networks (RNNs) faces limitations because of vanishing or exploding gradients. In this work, we introduce a new training method and a new recurrent architecture using residual connections, both aimed at increasing the range of dependencies that can be modeled by RNNs. We demonstrate the effectiveness of our approach by showing faster convergence on two toy tasks involving long range temporal dependencies, and improved performance on a character level language modeling task. Further, we show visualizations which highlight the improvements in gradient propagation through the network.
SOLAR CYCLE DEPENDENCE OF THE DIURNAL ANISOTROPY OF 0.6 TeV COSMIC-RAY INTENSITY OBSERVED WITH THE MATSUSHIRO UNDERGROUND MUON DETECTOR

We analyze the temporal variation of the diurnal anisotropy of sub-TeV cosmic-ray intensity observed with the Matsushiro (Japan) underground muon detector over two full solar activity cycles in 1985–2008. We find an anisotropy component in the solar diurnal anisotropy superimposed on the Compton–Getting anisotropy due to Earth's orbital motion around the Sun. The phase of this additional anisotropy is almost constant at ∼15:00 local solar time corresponding to the direction perpendicular to the average interplanetary magnetic field at Earth's orbit, while the amplitude varies between a maximum (0.043% ± 0.002%) and minimum (∼0.008% ± 0.002%) in a clear correlation with the solar activity. We find a significant time lag between the temporal variations of the amplitude and the sunspot number (SSN) and obtain the best correlation coefficient of +0.74 with the SSN delayed for 26 months. We suggest that this anisotropy might be interpreted in terms of the energy change due to the solar-wind-induced electric field expected for galactic cosmic rays (GCRs) crossing the wavy neutral sheet. The average amplitude of the sidereal diurnal variation over the entire period is 0.034% ± 0.003%, which is roughly one-third of the amplitude reported from air shower and deep-underground muon experiments monitoring multi-TeV GCR intensity suggesting a significant attenuation of the anisotropy due to the solar modulation. We find, on the other hand, only a weak positive correlation between the sidereal diurnal anisotropy and the solar activity cycle in which the amplitude in the “active” solar activity epoch is about twice the amplitude in the “quiet” solar activity epoch. This implies that only one-fourth of the total attenuation varies in correlation with the solar activity cycle and/or the solar magnetic cycle. We finally examine the temporal variation of the “single-band valley depth” (SBVD) quoted by the Milagro experiment and, in contrast with recent Milagro's report, we find no steady increase in the Matsushiro observations in a seven-year period between 2000 and 2007. We suggest, therefore, that the steady increase of the SBVD reported by the Milagro experiment is not caused by the decreasing solar modulation in the declining phase of the 23rd solar activity cycle.
Iterative learning control for varying tasks

1 Background Iterative Learning Control (ILC) [1] can significantly enhance the performance of systems that perform repeating tasks. However, small variations in the task often lead to a large performance deterioration. This leads to a trade-off between high performance and extrapolation properties, i.e., the ability to cope with reference variations. The goal of this research is to improve this trade-off in ILC.
Predictors of Successful Aging: Associations between Social Network Patterns, Life Satisfaction, Depression, Subjective Health, and Leisure Time Activity for Older Adults in India

Aging in the new millennium is greatly influenced by both global and region-specific factors. In Asia, the aged population is increasing at a faster rate than both Europe and North America, making issues related to older adults needing immediate attention of researchers & planners. This study aims at identifying the predictors of successful aging. Successful aging as a construct often has an integration of good social engagement, sense of purpose in life, maintaining cognitive capacity and functional autonomy. One hundred fifty participants in India completed the Life Satisfaction Questionnaire, Geriatric Depression Scale, Health Awareness Schedule, and the Leisure Time Activity Record. Firstly, it is mainly evident that social support network is larger for older adults residing in a joint family as compared to a nuclear family setup. Further, married males in a joint family have the largest network size compared to all the other groups. The study however, reveals an interesting reverse trend of widowed females having a larger network size compared to widowed males. Statistical analysis found measures of successful aging to be highly correlated with each other, with subjective health and depression being significant predictors of life satisfaction. Further, life satisfaction, depression levels, and leisure time activities were all significant predictors of subjective health. Significant gender differences were found on life satisfaction and subjective health with married males living in joint families reporting the highest scores on all the above measures. In addition, widowed women showed the highest levels of depression, which relates to their lower life satisfaction, poor ratings of health and low involvement in leisure activities. The study achieved a higher understanding of successful aging and presented a novel finding of educational level being significantly correlated with all measures of successful aging. This study is the first of its kind to measure successful aging in an urban Asian-Indian population. However, more research is needed to examine other age-related variations to enable generalization of results to a larger culturally diverse population.
Evolution of the energy band structure in chemical-bath-deposited CdS thin films studied by optical absorption spectroscopy

CdS thin films were grown on glass substrates by chemical bath deposition. Increasing deposition time from 10 to 200 min at an ultimate bath temperature of 60 °C gives rise to a red shift in optical absorption edge of ∼1 eV and a decrease in the Urbach tail width from 520 to 370 meV. A semi-empirical model was developed to account for the decrease of band gap energy with deposition time based on possible lattice contraction at the earlier stages of thin film growth. The degree of structural disorder related to the Urbach tail width was shown to be proportional to unharmonic terms in potential energy of atoms vibrating asymmetrically. An increase in band gap energy with increasing heat-treatment temperature was observed and explained by a quantized-state effective mass model in the strong confinement limit which predicts a blue shift in band gap energy of ∼0.5 eV as the grain size decreases from 7.6 to 2.2 nm due to a decrease in sulfur concentration in grains. Combined use of the Arrhenius plot and quantum size effect yields activation energy of 46 kJ mol−1 for the diffusion of sulfur during the heat treatment.
Heart Failure Management in Skilled Nursing Facilities

CORRINE Y. JURGENS, PhD, RN, FAHA, CHAIR, SARAH GOODLIN, MD, CO-CHAIR, MARY DOLANSKY, PhD, RN, CO-CHAIR, ALI AHMED, MD, MPH, FAHA, GREGG C. FONAROW, MD, FAHA, REBECCA BOXER, MD, ROSS ARENA, PhD, PT, FAHA, LENORE BLANK, NP, HARLEAH G. BUCK, PhD, RN, CHPN, KERRY CRANMER, MD, JEROME L. FLEG, MD, FAHA, RACHEL J. LAMPERT, MD, TERRY A. LENNIE, PhD, RN, FAHA, JOANN LINDENFELD, MD, FAHA, ILEANA L. PI~ NA, MD, MPH, FAHA, TODD P. SEMLA, MS, PharmD, BCPS, PATRICIA TREBBIEN, MS, RD, LMNT, AND MICHAEL W. RICH, MD, FAHA, ON BEHALF OF THE AMERICAN HEART ASSOCIATION COUNCIL ON QUALITY OF CARE AND OUTCOMES RESEARCH AND THE HEART FAILURE SOCIETY OF AMERICA
Machine Learning Models for Directed Curation of Design Solution Space

CHRISTIAN HUIE SJOBERG. Machine learning models for directed curation of design solution space. (Under the direction of ERIC SAUDA) The expanding role of computational models in the process of design is producing exponentially growing parameter spaces. As designers, we must create and implement new methods for searching these parameter spaces considering not only quantitative optimization metrics but also qualitative features. This paper proposes a methodology leveraging pattern modeling properties of artificial neural networks to capture designer’s inexplicit selection criteria and create user-selection based fitness functions for a genetic solver. Through emulation of learned selection patterns, fitness functions based on trained networks provide a method for qualitative evaluation of designs in the context of a given population. The application of genetic solvers for the generation of new populations based on the trained networks selections creates emergent high-density clusters in the parameter space, allowing for the identification of solutions which satisfy the designer’s inexplicit criteria.
Arousal and attraction: Evidence for automatic and controlled processes.

A meta-analysis, a review, and an experiment investigated the effect of arousal on attraction. The meta-analysis examined experiments that manipulated arousal level. Results indicated that arousal affects attraction even when the arousal source is relatively unambiguous. In contrast, a review of experiments that manipulated arousal source ambiguity suggested that arousal exerts a stronger influence on attraction when arousal sources are greater in ambiguity. The authors proposed a judgment and adjustment model that states that arousal automatically affects judgments of attraction but that individuals can correct (i.e., adjust) for this automatic effect when the arousal source is unambiguous. Consistent with this model, an experiment provided evidence that cognitive busyness interferes with the adjustment process.