Miracle-dz/UniFAR-FTUs huggingface dataset:
Mesopic and Photopic Rod and Cone Photoreceptor-Driven Visual Processes in Mice With Long-Wavelength-Shifted Cone Pigments.

Purpose The clearer divergence in spectral sensitivity between native rod and human L-cone (L*-cone) opsins in the transgenic Opn1lwLIAIS mouse (LIAIS) allows normal visual processes mediated by these photoreceptor subtypes to be isolated effectively using the silent substitution technique. The objective of this study was to further characterize the influence of mean luminance and temporal frequency on the functional properties of signals originating in each photoreceptor separately and independently of adaptation state in LIAIS mice. Methods Electroretinographic (ERG) recordings to sine-wave rod and L*-cone modulation at different mean luminances (0.1-130.0 cd/m2) and temporal frequencies (6-26 Hz) were examined in anesthetized LIAIS (N = 17) and C57Bl/6 mice (N = 8). Results We report maximum rod-driven response with 8-Hz modulation at 0.1 to 0.5 cd/m2, which was almost four times larger than maximum cone-driven response at 8 Hz, 21.5 to 130 cd/m2. Over these optimal luminances, both rod- and cone-driven response amplitudes exhibited low-pass functions with similar frequency resolution limits, albeit their distinct luminance sensitivities. There were, however, two distinguishing features: (1) the frequency-dependent amplitude decrease of rod-driven responses was more profound, and (2) linear relationships describing rod-driven response phases as a function of stimulus frequency were steeper. Conclusions Employing the silent substitution method with stimuli of appropriate luminance on the LIAIS mouse (as on human observers) increases the specificity, robustness, and scope to which photoreceptor-driven responses can be reliably assayed compared to the standard photoreceptor isolation methods.
Investigating the role of entropy in sentence processing

We outline four ways in which uncertainty might affect comprehension difficulty in human sentence processing. These four hypotheses motivate a self-paced reading experiment, in which we used verb subcategorization distributions to manipulate the uncertainty over the next step in the syntactic derivation (single step entropy) and the surprisal of the verb’s complement. We additionally estimate wordby-word surprisal and total entropy over parses of the sentence using a probabilistic context-free grammar (PCFG). Surprisal and total entropy, but not single step entropy, were significant predictors of reading times in different parts of the sentence. This suggests that a complete model of sentence processing should incorporate both entropy and surprisal.
Light and the City: Breast Cancer Risk Factors Differ Between Urban and Rural Women in Israel

Women are exposed to indoor and outdoor artificial light at night (ALAN) in urban and rural environments. Excessive exposure to hazardous ALAN containing short wavelength light may suppress pineal melatonin production and lead to an increased breast cancer (BC) risk. Our objective was to address the differences in BC risks related to light exposure in urban and rural communities. We examined indoor and outdoor light habits of BC patients and controls that had lived in urban and rural areas in a 5-year period, 10 to 15 years before the time of the study. Individual data, night time sleeping habits and individual exposure to ALAN habits were collected using a questionnaire. A total of 252 women (110 BC patients and 142 controls) participated in this study. The sample was divided to subgroups according to dwelling area and disease status. Age matching was completed between all subgroups. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated for urban and rural women separately, using binary logistic regression. OR results of urban population (92 BC patients and 72 control) revealed that BC risk increases with daily use of cellphone (OR = 2.13, 95% CI = 1.01-4.49, P < .05) and residence near strong ALAN sources (OR = 1.51, 95% CI = 0.99-2.30, P < .06). Nevertheless, BC risk decreases if a woman was born in Israel (OR = 0.44, 95% CI = 0.21-0.93, P < .03), longer sleep duration (OR = 0.75, 95% CI = 0.53-1.05, P < .1), and reading with bed light illumination before retiring to sleep (OR = 0.77, 95% CI = 0.61-0.96, P < .02). Furthermore, in the rural population (18 BC patients and 66 control) BC risk increases with the number of years past since the last menstruation (OR = 1.12, 95% CI = 1.03-1.22, P < .01). However, BC risk decreases with longer sleep duration (OR = 0.53, 95% CI = 0.24-1.14, P < .1), reading with room light illumination before retiring to sleep (OR = 0.55, 95% CI = 0.29-1.06, P < .07), and sleeping with closed shutters during the night (OR = 0.66, 95% CI = 0.41-1.04, P < .08). These data support the idea that indoor and outdoor nighttime light exposures differ between urban and rural women. Therefore, we suggest that women can influence BC risk and incidence by applying protective personal lighting habits. Further studies with larger sample sizes are needed to strengthen the results.
A collaborative exploration of the reasons for lower satisfaction with services among Bangladeshi and Pakistani† social care users

This study explored underlying reasons for the expression of dissatisfaction with services among Bangladeshi and Pakistani social care users in England and investigated, using a collaborative approach, how these could be addressed. In-depth interviews were conducted in Birmingham, Leeds and London during 2012-2013 with 63 Bangladeshi, Pakistani and white British service users and 24 social care managers, social workers and care workers. A further 34 cognitive interviews were conducted within the same study. Following data analysis, three collaborative workshops involving service users and providers were held to validate the findings and to draw out policy and practice recommendations. Analysis of the cognitive interviews showed that higher dissatisfaction among Bangladeshi and Pakistani service users reported in social care surveys was not due to questionnaire design. Instead in-depth interviews showed that dissatisfaction across all three groups was expressed along the social care journey, including accessing care, communication with social workers and the nature of care received. While many issues were common to all three groups, cultural differences also emerged as affecting experiences of social care. These included misunderstandings about family roles in care; gender issues, especially relating to women; language and communication barriers, alongside the need for a more nuanced approach to ethnic 'matching'; and continuing limited cultural understanding among care workers. The collaborative workshops identified practical actions that could address some of the issues identified. These covered raising awareness of services within communities; improving support for informal carers; service user input to assessments; consistent and ongoing sharing of information; improving access; and more efforts to diversify and appropriately train the social care workforce. In conclusion, the paper presents the reality of dissatisfaction among these groups and argues for more action involving communities and service providers to address these persistent issues collaboratively.
Evaluating the Drivers to Information and Communication Technology for Effective Sustainability Initiatives in Supply Chains

Supply chain (SC) sustainability has become a global issue. To develop sustainability focused SC networks, the role of Information and Communication Technologies (ICTs) is of great significance. An effective information system and management can help not only in improving better customer service and in cost control, but also can assist planning to achieve the three pillars of sustainability (ecological, economic, and societal development), thereby enhancing business efficiency. This paper aims to identify and evaluate the drivers relevant to ICT for sustainability initiatives in SCs. The drivers are finalized through a literature survey and use of the Delphi technique. The finalized drivers are analyzed by a procedure using the fuzzy DEMATEL approach. The research findings suggest that “Government support systems and subsidies”, “Knowledge and awareness of ICT tools and techniques,” and “Information systems network design” drivers have the most significant influences in the implementation of ICT for incorporating sustainability in SCs. This work may help practitioners and researchers in strategic decision-making and in formulating effective plans for the implementation of ICT and for incorporating sustainable concepts in SCs.
Reference Diaries

When we make a definite reference to a thing, we normally make sure that our audience "shares" with us certain knowledge about that thing. To refer to a woman as she, the woman, or Nancy, we usually have good evidence that our audience knows about her too. But exactly what "shared" knowledge is required? This question is critical if we are ever to discover how people make or interpret definite reference--how they represent knowledge in memory and consult it in uttering and interpreting expressions like she, the woman, or Nancy. The question is critical if we are ever to characterize the mental archive people have for storing the facts they need to know for definite reference. We will argue that this archive has to be another detailed diary, or reference diary, supplemented by atlases, histories, and certain other reference texts. To make this argument, and to see what goes into the archive, we will examine the prior question, What "shared" knowledge is required for definite reference? As it happens, this question leads directly to a puzzle we will call the mutual knowledge paradox. It is in the solution of this puzzle that we get our best clues as to what the reference diary must be like.
Short-term traffic flow prediction with LSTM recurrent neural network

Accurate and timely short-term traffic flow prediction plays an important role in intelligent transportation management and control. Traffic flow prediction has a long history and is still a difficult problem due to intrinsically highly nonlinear and stochastic characteristics of complex transportation systems. In this paper, we employ the long short-term memory (LSTM) recurrent neural network to analyze the effects of various input settings on the LSTM prediction performances. Flow, speed, and occupancy at the same detector station are used as inputs to predict traffic flow. The results show that the inclusion of occupancy/speed information may help to enhance the performance of the model overall. Further, we include as inputs traffic variables from the upstream and/or downstream detector stations for traffic flow prediction. The evaluation of such spatial-temporal input interactions show that the inclusion of both downstream and upstream traffic information is useful in improving prediction accuracy.
Algorithms for active learning

This dissertation develops and analyzes active learning algorithms for binary classification problems. In passive (non-active) learning, a learner uses a random sample of labeled examples from a fixed distribution to select a hypothesis with low error. In active learning, a learner receives only a sample of unlabeled data, but has the option to query the label of any of these data points. The hope is that the active learner needs to query the labels of just a few, carefully chosen points in order to produce a hypothesis with low error. The first part of this dissertation develops algorithms based on maintaining a version space—the set of hypotheses still in contention to be selected. The version space is specifically designed to tolerate arbitrary label noise and model mismatch in the agnostic learning model. The algorithms maintain the version space using a reduction to a special form of agnostic learning that allows for example-based constraints; this represents a computational improvement over previous methods. The generalization behavior of one of these algorithms is rigorously analyzed using a quantity called the disagreement coefficient. This algorithm is shown to have label complexity that improves over that of previous methods, and matches known label complexity lower bounds in certain cases. The second part of this dissertation develops algorithms based on simpler reductions to agnostic learning that more closely match the standard abstraction of supervised learning procedures. The generalization behavior of these algorithms are also analyzed in the agnostic learning model, and are shown to have label complexity similar to the version space methods. Therefore, these algorithms represent qualitative improvements over version space methods, as strict version space methods can be risky to deploy in practice. The first of these algorithms is based on a relaxation of a version space method, and the second is based on an importance weighting technique. The second algorithm is also shown to automatically adapt to various noise conditions that imply a tighter label complexity analysis. Experiments using this algorithm are also presented to illustrate some of the promise of the method.
Incoherent Nature of M2 Internal Tides at the Hawaiian Ridge

AbstractMoored current, temperature, and conductivity measurements are used to study the temporal variability of M2 internal tide generation above the Kaena Ridge, between the Hawaiian islands of Oahu and Kauai. The energy conversion from the barotropic to baroclinic tide measured near the ridge crest varies by a factor of 2 over the 6-month mooring deployment (0.5–1.1 W m−2). The energy flux measured just off the ridge undergoes a similar modulation as the ridge conversion. The energy conversion varies largely because of changes in the phase of the perturbation pressure, suggesting variable work done on remotely generated internal tides. During the mooring deployment, low-frequency current and stratification fluctuations occur on and off the ridge. Model simulations suggest that these variations are due to two mesoscale eddies that passed through the region. The impact of these eddies on low-mode internal tide propagation over the ridge crest is considered. It appears that eddy-related changes in stratif.
Tissue Specificity and Sex-Specific Regulatory Variation Permit the Evolution of Sex-Biased Gene Expression

Genetic correlations between males and females are often thought to constrain the evolution of sexual dimorphism. However, sexually dimorphic traits and the underlying sexually dimorphic gene expression patterns are often rapidly evolving. We explore this apparent paradox by measuring the genetic correlation in gene expression between males and females (Cmf) across broad evolutionary timescales, using two RNA-sequencing data sets spanning multiple populations and multiple species. We find that unbiased genes have higher Cmf than sex-biased genes, consistent with intersexual genetic correlations constraining the evolution of sexual dimorphism. However, we found that highly sex-biased genes (both male and female biased) also had higher tissue specificity, and unbiased genes had greater expression breadth, suggesting that pleiotropy may constrain the breakdown of intersexual genetic correlations. Finally, we show that genes with high Cmf showed some degree of sex-specific changes in gene expression in males and females. Together, our results suggest that genetic correlations between males and females may be less important in constraining the evolution of sex-biased gene expression than pleiotropy. Sex-specific regulatory variation and tissue specificity may resolve the paradox of widespread sex bias within a largely shared genome.
Mammalian Cell Tissue Culture

Cultured mammalian cells are used extensively in the field of human genetics. It requires a number of special skills in order to be able to preserve the structure, function, behavior, and biology of the cells in culture. This unit describes the basic skills required to maintain and preserve cell cultures: maintaining aseptic technique, preparing media with the appropriate characteristics, passaging, freezing and storage, recovering frozen stocks, and counting viable cells. © 2017 by John Wiley & Sons, Inc.
Metabolic Oscillations in Co‐Cultures of Hepatocytes and Mesenchymal Stem Cells: Effects of Seeding Arrangement and Culture Mixing

In vitro assembly of functional liver tissue is a prerequisite for the transplantation of tissue‐engineered livers. There is an increasing demand for in vitro models that replicate complex events occurring in the liver. However, tissue engineering of implantable liver systems is currently limited by the difficulty of assembling three dimensional hepatocyte cultures of a useful size, while maintaining full cell viability. Recent reports have demonstrated that bone marrow mesenchymal stem cells (BM‐MSCs) can provide a number of cues promoting hepatocyte growth and development. In this study, the effects of BM‐MSCs co‐culture on hepatocyte metabolism were evaluated as a function of scaffold seeding arrangement. BM‐MSCs were co‐cultured with hepatocytes in porous chitosan‐heparin scaffolds using several seeding arrangements. The seeded scaffolds were subjected to orbital shaking to enhance mass transfer. BM‐MSC‐hepatocyte co‐cultures exhibited higher rates of hepatocyte‐specific functions, compared to hepatocyte‐only cultures, regardless of the seeding arrangement. Cells formed smaller‐compact spheroids in the heterotypic systems compared to mono‐cultures of hepatocytes only. The spheroids exhibited reduction in size with time in all conditions except for the condition where BM‐MSCs were seeded one day after seeding hepatocytes. In this condition, spheroids increased in size due to BM‐MSC proliferation. Spheroid size reduction was hypothesized to be the result of cyclic shear stresses generated by the orbital shaking. Furthermore, results suggested that BM‐MSC seeding onto preformed hepatocyte spheroids provide a degree of shear‐protection and trophic stimuli. Overall, the results indicate that co‐culturing hepatocytes with BM‐MSCs enhanced their metabolic functions for the first week of culture. J. Cell. Biochem. 118: 3003–3015, 2017. © 2017 Wiley Periodicals, Inc.
Imaging Lenticular Autofluorescence in Older Subjects

Purpose To evaluate whether a practical method of imaging lenticular autofluorescence (AF) can provide an individualized measure correlated with age-related lens yellowing in older subjects undergoing tests involving shorter wavelength lights. Methods Lenticular AF was imaged with 488-nm excitation using a confocal scanning laser ophthalmoscope (cSLO) routinely used for retinal AF imaging. There were 75 older subjects (ages 47–87) at two sites; a small cohort of younger subjects served as controls. At one site, the cSLO was equipped with an internal reference to allow quantitative AF measurements; at the other site, reduced-illuminance AF imaging (RAFI) was used. In a subset of subjects, lens density index was independently estimated from dark-adapted spectral sensitivities performed psychophysically. Results Lenticular AF intensity was significantly higher in the older eyes than the younger cohort when measured with the internal reference (59.2 ± 15.4 vs. 134.4 ± 31.7 gray levels; P < 0.05) as well as when recorded with RAFI without the internal reference (10.9 ± 1.5 vs. 26.1 ± 5.7 gray levels; P < 0.05). Lenticular AF was positively correlated with age; however, there could also be large differences between individuals of similar age. Lenticular AF intensity correlated well with lens density indices estimated from psychophysical measures. Conclusions Lenticular AF measured with a retinal cSLO can provide a practical and individualized measure of lens yellowing, and may be a good candidate to distinguish between preretinal and retinal deficits involving short-wavelength lights in older eyes.
Exciting trajectories for extrinsic calibration of mobile robots with cameras

The paper presents a method to precompute the optimal (so-called exciting) trajectories for the extrinsic calibration of a mobile robot equipped with the wheel odometry and one or more cameras. Considering the fact that the calibration is formulated as a non-linear least-square problem, the method is based on the analysis of the cost function properties in the neighborhood of the solution. By maximizing the determinant of the Hessian matrix, one makes the problem better defined and improves its robustness with respect to the measurement noise. Another convenience of the method is the possibility to reinforce additional constraints, like the visibility of a calibration object and the trajectory feasibility. The source code of the application is publicly available as a part of visgeom project.
Computer Methods and Programs in Biomedicine

Background: Blood vessel segmentation is a topic of high interest in medical image analysis since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and evaluation of clinical outcomes in different ﬁelds, including laryngology, neurosurgery and ophthalmology. Automatic or semi-automatic vessel segmentation can support clinicians in performing these tasks. Different medical imaging techniques are currently used in clinical practice and an appropriate choice of the segmentation algorithm is mandatory to deal with the adopted imaging technique characteristics (e.g. resolution, noise and vessel contrast). Objective: This paper aims at reviewing the most recent and innovative blood vessel segmentation algorithms. Among the algorithms and approaches considered, we deeply investigated the most novel blood vessel segmentation including machine learning, deformable model, and tracking-based approaches. Methods: This paper analyzes more than 100 articles focused on blood vessel segmentation methods. For each analyzed approach, summary tables are presented reporting imaging technique used, anatomical region and performance measures employed. Beneﬁts and disadvantages of each method are highlighted. Discussion: Despite the constant progress and efforts addressed in the ﬁeld, several issues still need to be overcome. A relevant limitation consists in the segmentation of pathological vessels. Unfortunately, not consistent research effort has been addressed to this issue yet. Research is needed since some of the main assumptions made for healthy vessels (such as linearity and circular cross-section) do not hold in pathological tissues, which on the other hand require new vessel model formulations. Moreover, image intensity drops, noise and low contrast still represent an important obstacle for the achievement of a high-quality enhancement. This is particularly true for optical imaging, where the image quality is usually lower in terms of noise and contrast with respect to magnetic resonance and computer tomography angiography. Conclusion: No single segmentation approach is suitable for all the different anatomical region or imaging modalities, thus the primary goal of this review was to provide an up to date source of information about the state of the art of the vessel segmentation algorithms so that the most suitable methods can be chosen according to the speciﬁc task.