Miracle-dz/UniFAR-FTUs huggingface dataset:
How health professionals facilitate parents’ involvement in decision-making at the hospital: A parental perspective

In many western countries, parents have a legal right to influence and be involved in decision-making (DM) surrounding their children’s healthcare. This ensures that the healthcare is customized as far as possible to meet the children’s and families’ needs and preferences. However, parental involvement in such DM is not sufficiently implemented and the parental role during hospitalizations has become demanding. More knowledge is required to inform health professionals (HPs) about how to improve parental involvement in DM from a health-promoting perspective. The aims of this study were to explore parents’ experiences of how HPs facilitate their involvement in the DM surrounding their child’s healthcare and to identify how HPs can improve parental involvement at the hospital. This was an explorative, descriptive qualitative study within a constructivist research paradigm, comprising a purposive sample of 12 parents participating in individual semi-structured interviews. Qualitative content analysis was performed. The findings showed that HPs’ sensitivity to parents’ capacity, resources and needs was essential in order to facilitate the latter’s involvement in DM. HPs’ sensitivity also seemed to influence the quality of communication and the HP-parent relationship. Moreover, these factors appeared to affect parents’ coping ability during their children’s hospitalization.
Impact of London's road traffic air and noise pollution on birth weight: retrospective population based cohort study

Abstract Objective To investigate the relation between exposure to both air and noise pollution from road traffic and birth weight outcomes. Design Retrospective population based cohort study. Setting Greater London and surrounding counties up to the M25 motorway (2317 km2), UK, from 2006 to 2010. Participants 540 365 singleton term live births. Main outcome measures Term low birth weight (LBW), small for gestational age (SGA) at term, and term birth weight. Results Average air pollutant exposures across pregnancy were 41 μg/m3 nitrogen dioxide (NO2), 73 μg/m3 nitrogen oxides (NOx), 14 μg/m3 particulate matter with aerodynamic diameter <2.5 μm (PM2.5), 23 μg/m3 particulate matter with aerodynamic diameter <10 μm (PM10), and 32 μg/m3 ozone (O3). Average daytime (LAeq,16hr) and night-time (Lnight) road traffic A-weighted noise levels were 58 dB and 53 dB respectively. Interquartile range increases in NO2, NOx, PM2.5, PM10, and source specific PM2.5 from traffic exhaust (PM2.5 traffic exhaust) and traffic non-exhaust (brake or tyre wear and resuspension) (PM2.5 traffic non-exhaust) were associated with 2% to 6% increased odds of term LBW, and 1% to 3% increased odds of term SGA. Air pollutant associations were robust to adjustment for road traffic noise. Trends of decreasing birth weight across increasing road traffic noise categories were observed, but were strongly attenuated when adjusted for primary traffic related air pollutants. Only PM2.5 traffic exhaust and PM2.5 were consistently associated with increased risk of term LBW after adjustment for each of the other air pollutants. It was estimated that 3% of term LBW cases in London are directly attributable to residential exposure to PM2.5>13.8 μg/m3during pregnancy. Conclusions The findings suggest that air pollution from road traffic in London is adversely affecting fetal growth. The results suggest little evidence for an independent exposure-response effect of traffic related noise on birth weight outcomes.
The role of ions in new particle formation in the CLOUD chamber

Abstract. The formation of secondary particles in the atmosphere accounts for more than half of global cloud condensation nuclei. Experiments at the CERN CLOUD (Cosmics Leaving OUtdoor Droplets) chamber have underlined the importance of ions for new particle formation, but quantifying their effect in the atmosphere remains challenging. By using a novel instrument setup consisting of two nanoparticle counters, one of them equipped with an ion filter, we were able to further investigate the ion-related mechanisms of new particle formation. In autumn 2015, we carried out experiments at CLOUD on four systems of different chemical compositions involving monoterpenes, sulfuric acid, nitrogen oxides, and ammonia. We measured the influence of ions on the nucleation rates under precisely controlled and atmospherically relevant conditions. Our results indicate that ions enhance the nucleation process when the charge is necessary to stabilize newly formed clusters, i.e., in conditions in which neutral clusters are unstable. For charged clusters that were formed by ion-induced nucleation, we were able to measure, for the first time, their progressive neutralization due to recombination with oppositely charged ions. A large fraction of the clusters carried a charge at 1.5 nm diameter. However, depending on particle growth rates and ion concentrations, charged clusters were largely neutralized by ion–ion recombination before they grew to 2.5 nm. At this size, more than 90 % of particles were neutral. In other words, particles may originate from ion-induced nucleation, although they are neutral upon detection at diameters larger than 2.5 nm. Observations at Hyytiala, Finland, showed lower ion concentrations and a lower contribution of ion-induced nucleation than measured at CLOUD under similar conditions. Although this can be partly explained by the observation that ion-induced fractions decrease towards lower ion concentrations, further investigations are needed to resolve the origin of the discrepancy.
PHD3 is a transcriptional coactivator of HIF‐1α in nucleus pulposus cells independent of the PKM2‐JMJD5 axis

The role of prolyl hydroxylase (PHD)‐3 as a hypoxia inducible factor (HIF)‐1α cofactor is controversial and remains unknown in skeletal tissues. We investigated whether PHD3 controls HIF‐1 transcriptional activity in nucleus pulposus (NP) cells through the pyruvate kinase muscle (PKM)‐2‐Jumonji domain–containing protein (JMJD5) axis. PHD3−/− mice (12.5 mo old) showed increased incidence of intervertebral disc degeneration with a concomitant decrease in expression of the HIF‐1α targets VEGF‐A, glucose transporter‐1, and lactate dehydrogenase A. PHD3 silencing decreased hypoxic activation of HIF‐1α C‐terminal transactivation domain (C‐TAD), but not HIF‐1α‐N‐terminal‐(N)‐TAD or HIF‐2α‐TAD. Moreover, PHD3 suppression in NP cells resulted in decreased HIF‐1α enrichment on target promoters and lower expression of select HIF‐1 targets. Contrary to other cell types, manipulation of PKM2 and JMJD5 levels had no effect on HIF‐1 activity in NP cells. Likewise, stabilization of tetrameric PKM2 by a chemical approach had no effect on PHD3‐dependent HIF‐1 activity. Coimmunoprecipitation assays showed lack of association between HIF‐1α and PKM2 in NP cells. Results support the role of the PHD3 as a cofactor for HIF‐1, independent of PKM2‐JMJD5. —Schoepflin, Z. R. , Silagi, E. S. , Shapiro, I. M. , Risbud, M. V. PHD3 is a transcriptional coactivator of HIF‐1α in nucleus pulposus cells independent of the PKM2‐JMJD5 axis. FASEB J. 31, 3831–3847 (2017). www.fasebj. org—Schoepflin, Zachary R. , Silagi, Elizabeth S. , Shapiro, Irving M. , Risbud, Makarand V. PHD3 is a transcriptional coactivator of HIF‐1α in nucleus pulposus cells independent of the PKM2‐JMJD5 axis. FASEB J. 31, 3831–3847 (2017)
New pediatric vision screener employing polarization-modulated, retinal-birefringence-scanning-based strabismus detection and bull’s eye focus detection with an improved target system: opto-mechanical design and operation

Abstract. Amblyopia (“lazy eye”) is a major public health problem, caused by misalignment of the eyes (strabismus) or defocus. If detected early in childhood, there is an excellent response to therapy, yet most children are detected too late to be treated effectively. Commercially available vision screening devices that test for amblyopia’s primary causes can detect strabismus only indirectly and inaccurately via assessment of the positions of external light reflections from the cornea, but they cannot detect the anatomical feature of the eyes where fixation actually occurs (the fovea). Our laboratory has been developing technology to detect true foveal fixation, by exploiting the birefringence of the uniquely arranged Henle fibers delineating the fovea using retinal birefringence scanning (RBS), and we recently described a polarization-modulated approach to RBS that enables entirely direct and reliable detection of true foveal fixation, with greatly enhanced signal-to-noise ratio and essentially independent of corneal birefringence (a confounding variable with all polarization-sensitive ophthalmic technology). Here, we describe the design and operation of a new pediatric vision screener that employs polarization-modulated, RBS-based strabismus detection and bull’s eye focus detection with an improved target system, and demonstrate the feasibility of this new approach.
Profiling of OCR'ed Historical Texts Revisited

In the absence of ground truth it is not possible to automatically determine the exact spectrum and occurrences of OCR errors in an OCR'ed text. Yet, for interactive postcorrection of OCR'ed historical printings it is extremely useful to have a statistical profile available that provides an estimate of error classes with associated frequencies, and that points to conjectured errors and suspicious tokens. The method introduced in [3] computes such a profile, combining lexica, pattern sets and advanced matching techniques in a specialized Expectation Maximization (EM) procedure. Here we improve this method in three respects: First, the method in [3] is not adaptive: user feedback obtained by actual postcorrection steps cannot be used to compute refined profiles. We introduce a variant of the method that is open for adaptivity, taking correction steps of the user into account. This leads to higher precision with respect to recognition of erroneous OCR tokens. Second, during postcorrection often new historical patterns are found. We show that adding new historical patterns to the linguistic background resources leads to a second kind of improvement, enabling even higher precision by telling historical spellings apart from OCR errors. Third, the method in [3] does not make any active use of tokens that cannot be interpreted in the underlying channel model. We show that adding these uninterpretable tokens to the set of conjectured errors leads to a significant improvement of the recall for error detection, at the same time improving precision.
Occlusion robust face recognition based on mask learning

Face occlusion has been a long standing challenging issue in face recognition. In the state-of-the-art deep Convolutional Neural Network (CNN) face recognition models, occluded facial parts are generally embedded into the learned features together with the non-occluded parts in an equivalent manner. As such, the discriminative power of the generated face representation may be weakened for occluded face images. To address this problem, we propose the MaskNet, a trainable module which can be included in existing CNN architectures. With end-to-end training supervised by only the personal identity labels, MaskNet learns a proper way of adaptively generating different feature map masks for different occluded face images. Intuitively, MaskNet automatically assigns higher weights to the hidden units activated by the non-occluded facial parts and lower weights to those that are activated by the occluded facial parts. Experiments on datasets consisting of real-life and synthetic occluded faces demonstrate that MaskNet can effectively improve the robustness of CNN models towards occlusions in face recognition.
Analytical Modeling of Switched Flux Memory Machine

This paper presents the simple analytical modeling for switched flux memory machine to provide in-depth insight into its working mechanism. The analytical approach is based on the slotless open-circuit air-gap flux density and the slotted air-gap relative permeance calculations for a doubly salient structure. In addition, due to low coercivity and highly nonlinear hysteresis curve at the second quadrant, the piecewise and virtual-linear hysteresis models of AlNiCo permanent magnet (PM) are presented to determine the PM working point. This combined analytical solution allows rapid calculation of several electromagnetic characteristics, e.g., air-gap flux density and back electromotive force. The effectiveness of the analytical method is validated by both finite-element results and measurements.
A high volume precision compression molding process of glass diffractive optics by use of a micromachined fused silica wafer mold and low Tg optical glass

Recent advances in compression molding of glass optical elements for mass production offer the potential of extending this technology to elements with micro and nano scale features. In this research, glass diffractive optical elements (DOEs) with lateral features in the order of 10 µm and vertical height of 330 nm were fabricated using a fused silica glass mold and a special low Tg (glass transition temperature) glass material K-PG325. Molded DOEs were studied using an atomic force microscope (AFM) and scanning electron microscope (SEM) to evaluate the glass molding process capability. Optical testing of the molded DOEs was a further demonstration of the effectiveness of the molding process for high volume micro and diffractive optical component fabrication. The combination of two high-precision, high-volume processes, i.e., semiconductor batch process for optical mold making and glass molding for DOE replication, is an effective alternative manufacturing method for high-quality, low-cost optical components. The reported experiment is a detailed illustration of the glass molding process capability. With further process optimization a robust manufacturing process can be developed for mass production of diffractive and micro glass optical elements.
Cross-range scaling of ISAR based on phase frequency modulation parameter estimation

To solve the problem of cross-range scaling of noncooperative target ISAR imaging, a corresponding analysis method is proposed based on phase frequency modulation parameter estimation. Doppler expression of the echo is deduced and the demodulation frequency method is used to estimate the parameters of the LFM signal, and then estimation of the frequency response of the echo signal in the longitudinal distance unit can be obtained. Finally, the slope of the echo signal is calculated by linear fitting. The radar echo data can be calculated to obtain the imaging target rotation speed of the estimated value. Simulation results compared with other classic methods confirm the feasibility and timeliness of the algorithm.
A Study on Evaluation Technique for the Fatigue Life Scatter of Lead-Free Solder Joints

The electronic device equipments using a lot of semiconductors are widespread to all industrial fields. Solder joints are used to mount the electronic chips, such as ceramic resistors and capacitors, on the printed-circuit boards in almost all electronic devices. However, since in many cases the thermal expansion coefficients of electronic parts and PCBs have mismatch, cyclic thermal stress and strain causes solder fatigue. Especially in the power electronic module and car electric module, the evaluation of thermal fatigue life for the chip components is important. It is understood that the fatigue lives of some electronic devices show large scatter in the thermal cycle test, even if their design is the same. The dispersion of main design factors of solder joints is thought as one of these reasons. Moreover, the influence of the dispersion grows when the lead-free solder materials are used in the devices. Therefore, it cannot be bypassed as the main issue for the reliability evaluation in the solder joints. In this study, how the dispersion of design factors influences the fatigue life in lead-free solder joint was investigated by the analytical approach. At first, sensitivity analyses were carried out to study the main effect of the dispersion of each factor on solder joints. And then, the interacting effects between the factors on the reliability were studied by considering the structural asymmetry due to the unbalanced solder joints. FEM analyses were carried out, and the fatigue life in solder joints was calculated from the inelastic strain range. As a result, practical evaluating approach for the fatigue life scatter of solder joints was proposed.Copyright © 2007 by ASME
Computational models of perceptual organization

Perceptual organization refers to the process of organizing sensory input into coherent and interpretable perceptual structures. This process is challenging due to the chicken-and-egg nature between the various sub-processes such as image segmentation, figure-ground segregation and object recognition. Low-level processing requires the guidance of high-level knowledge to overcome noise; while high-level processing relies on low-level processes to reduce the computational complexity. Neither process can be sufficient on its own. Consequently, any system that carries out these processes in a sequence is bound to be brittle. An alternative system is one in which all processes interact with each other simultaneously. In this thesis, we develop a set of simple yet realistic interactive processing models for perceptual organization. We model the processing in the framework of spectral graph theory, with a criterion encoding the overall goodness of perceptual organization. We derive fast solutions for near-global optima of the criterion, and demonstrate the efficacy of the models on segmenting a wide range of real images. Through these models, we are able to capture a variety of perceptual phenomena: a unified treatment of various grouping, figure-ground and depth cues to produce popout, region segmentation and depth segregation in one step; and a unified framework for integrating bottom-up and top-down information to produce an object segmentation from spatial and object attention. We achieve these goals by empowering current spectral graph methods with a principled solution for multiclass spectral graph partitioning; expanded repertoire of grouping cues to include similarity, dissimilarity and ordering relationships; a theory for integrating sparse grouping cues; and a model for representing and integrating higher-order relationships. These computational tools are also useful more generally in other domains where data need to be organized effectively.
Multi-Fingered Grasping and Manipulation in Virtual Environments Using an Isometric Finger Device

In this article we present a new isometric input device for multi-fingered grasping in virtual environments. The device was designed to simultaneously assess forces applied by the thumb, index, and middle finger. A mathematical model of grasping, adopted from the analysis of multi-fingered robot hands, was applied to achieve multi-fingered interaction with virtual objects. We used the concept of visual haptic feedback where the user was presented with visual cues to acquire haptic information from the virtual environment. The virtual object corresponded dynamically to the forces and torques applied by the three fingers. The application of the isometric finger device for multi-fingered interaction is demonstrated in four tasks aimed at the rehabilitation of hand function in stroke patients. The tasks include opening the combination lock on a safe, filling and pouring water from a glass, muscle strength training with an elastic torus, and a force tracking task. The training tasks were designed to train patients' grip force coordination and increase muscle strength through repetitive exercises. The presented virtual reality system was evaluated in a group of healthy subjects and two post-stroke patients (early post-stroke and chronic) to obtain overall performance results. The healthy subjects demonstrated consistent performance with the finger device after the first few trials. The two post-stroke patients completed all four tasks, however, with much lower performance scores as compared to healthy subjects. The results of the preliminary assessment suggest that the patients could further improve their performance through virtual reality training.
Modified particle swarm optimization for odor source localization of multi-robot

Odor source localization is very important in real-world applications. We studied the problem of odor source localization and presented a modified particle swarm optimization algorithm for odor source localization of multi-robot. The algorithm dynamically adjusts two learning factors in the velocity update equation based on the effect of wind on self-cognition and social cognition of a particle. In addition, an artificial potential field method is employed to improve the performance of our algorithm. We conducted various experiments in time-varying environments, and the experimental results confirm the superiority of our algorithm.
Mitochondria-specific photoactivation to monitor local sphingosine metabolism and function

Photoactivation ('uncaging’) is a powerful approach for releasing bioactive small-molecules in living cells. Current uncaging methods are limited by the random distribution of caged molecules within cells. We have developed a mitochondria-specific photoactivation method, which permitted us to release free sphingosine inside mitochondria and thereafter monitor local sphingosine metabolism by lipidomics. Our results indicate that sphingosine was quickly phosphorylated into sphingosine 1-phosphate (S1P) driven by sphingosine kinases. In time-course studies, the mitochondria-specific uncaged sphingosine demonstrated distinct metabolic patterns compared to globally-released sphingosine, and did not induce calcium spikes. Our data provide direct evidence that sphingolipid metabolism and signaling are highly dependent on the subcellular location and opens up new possibilities to study the effects of lipid localization on signaling and metabolic fate.
Breast Histopathological Image Retrieval Based on Latent Dirichlet Allocation

In the field of pathology, whole slide image (WSI) has become the major carrier of visual and diagnostic information. Content-based image retrieval among WSIs can aid the diagnosis of an unknown pathological image by finding its similar regions in WSIs with diagnostic information. However, the huge size and complex content of WSI pose several challenges for retrieval. In this paper, we propose an unsupervised, accurate, and fast retrieval method for a breast histopathological image. Specifically, the method presents a local statistical feature of nuclei for morphology and distribution of nuclei, and employs the Gabor feature to describe the texture information. The latent Dirichlet allocation model is utilized for high-level semantic mining. Locality-sensitive hashing is used to speed up the search. Experiments on a WSI database with more than 8000 images from 15 types of breast histopathology demonstrate that our method achieves about 0.9 retrieval precision as well as promising efficiency. Based on the proposed framework, we are developing a search engine for an online digital slide browsing and retrieval platform, which can be applied in computer-aided diagnosis, pathology education, and WSI archiving and management.