Miracle-dz/UniFAR-FTUs huggingface dataset:
PHIPS-HALO: the airborne Particle Habit Imaging and Polar Scattering probe - Part 1: Design and operation

The number and shape of ice crystals present in mixed-phase and ice clouds influence the radiation properties, precipitation occurrence and lifetime of these clouds. Since clouds play a major role in the climate system, influencing the energy budget by scattering sunlight and absorbing heat radiation from the earth, it is necessary to investigate the optical and microphysical properties of cloud particles particularly in situ. The relationship between the microphysics and the single scattering properties of cloud particles is usually obtained by modelling the optical scattering properties from in situ measurements of ice crystal size distributions. The measured size distribution and the assumed particle shape might be erroneous in case of non-spherical ice particles. There is a demand to obtain both information correspondently and simultaneously for individual cloud particles in their natural environment. For evaluating the average scattering phase function as a function of ice particle habit and crystal complexity, in situ measurements are required. To this end we have developed a novel airborne optical sensor (PHIPS-HALO) to measure the optical properties and the corresponding microphysical parameters of individual cloud particles simultaneously. PHIPS-HALO has been tested in the AIDA cloud simulation chamber and deployed in mountain stations as well as research aircraft (HALO and Polar 6). It is a successive version of the laboratory prototype instrument PHIPS-AIDA. In this paper we present the detailed design of PHIPS-HALO, including the detection mechanism, optical design, mechanical construction and aerodynamic characterization.
Natural history of Rathke's cleft cysts: A retrospective analysis of a two centres experience

Rathke's cleft cyst (RCC) is a common sellar lesion which may cause visual impairment, hypopituitarism and headaches from mass effect. The natural history of these lesions is currently unclear. We investigated the natural history of RCCs and compared surgically treated patients with those treated conservatively.
Neuro‐Oncology Nurse Navigation: Developing the role for a unique patient population

&NA; Navigation seeks to assess and address barriers that hinder a patient's access to care. With the success of the nurse navigation program at Penn Medicine's Abramson Cancer Center, leadership expanded navigation to neuro‐oncology. The purpose of this article is to describe this population's unique needs and the effect of nurse navigation. Although the navigation role maintains integrity with regard to scope of practice, specialized navigation strategies are tailored to the neuro‐oncology population and are different from other disease sites. AT A GLANCEPatients diagnosed with a primary brain tumor experience unique complexity in their disease site with the cognitive and physical impact of the disease trajectory.Nurse navigation has an opportunity to intervene early for patients and families to ensure coordinated, timely care by collaborating with the interprofessional team, rehabilitation services, and family members.Success of a neuro‐oncology navigation program can be measured in number of patients navigated, number of patient encounters, and time to the start of treatment.
Determinants of Attendance at a Physical Activity Focused Afterschool Program in Elementary School Children

Afterschool youth physical activity (PA) programs provide opportunities for increasing children’s time engaged in moderate-to-vigorous physical activity (MVPA). However, low program attendance reduces the benefits of participating in these programs. The purpose of this study was to determine if enjoyment, athletic competence and motivation for PA predict youth attendance at a free afterschool PA program from 3rd to 5th grade. Data were collected from a larger randomized community trial examining the effectiveness of an afterschool program for increasing opportunities to engage in MVPA. Data were collected twice annually (fall/spring) over 3 school years (3rd – 5th grade) in 9 schools. Analyses were stratified by grade and sex, and a series of multi-level linear regression models were utilized to determine if baseline levels of the psychosocial determinants predicted annual attendance as a percentage of afterschool sessions attended. Amotivation for PA was negatively associated with attendance in boys and non-self-determined extrinsic motivation was positively associated with attendance in girls in the 5th grade. Age was associated with a 13.72% reduction in attendance in the 3rd grade, a 12.87% attendance reduction in the 4th grade, and a 7.93% attendance in reduction in the 5th grade. Race was also associated with attendance. Non-White youth attended the program 13.56% less in the 3rd grade, 17.35% less in the 4th grade, and 21.53% less in the 5th grade than White youth. The findings suggest that attendance to PA afterschool programming may be associated with children’s motivational characteristics, but that other variables should be identified for further research.
Prediction of mortality in pediatric traumatic brain injury: Implementations from a tertiary pediatric intensive care facility.

BACKGROUND To explore the mortality risk factors of traumatic brain injury in pediatric intensive care unit admissions. METHODS Eighty-eight children (categorized using the Glasgow Coma Scale) between September 2014 and December 2016 were analyzed. Emergency department and intensive care course, treatment strategies, axonal injury, intubation and tracheostomy rates, length of intensive care and hospitalization, Rotterdam-CT scores, injury severity scores, and PRISM-III scores were recorded. RESULTS Older age was associated with trauma severity (p=0.010). Target serum osmolality was reached at 8.5 (3.5-40) hours in patients undergoing anti-edema therapy. ICP-monitoring rates was 8%; in absence of ICP-monitorization clinical follow-up was performed through repeated brain tomographies. Axonal injury was associated with prolonged intubation, intensive care and hospital stay (p<0.001, p<0.001, p=0.030). Six children required tracheostomy at 14.33±1.03 days; decannulations were performed within 6 months in five children. CONCLUSION Mortality rate was 12.5%; six patients progressed to brain death with organ donor approvals in five. Initial hypotension, lung contusion, injury severity scores and Rotterdam-CT scores were related with mortality. Rotterdam-CT score was determined as the independent risk factor for mortality; one increment in the score increased the odd of recovery by 20.334 times (%95 CI 1.999-206.879). ISS score was also borderline significant (p=0.052; OR:1.195 %95 CI 0.999-1.430).
Nomogram Integrating Genomics with Clinicopathologic Features Improves Prognosis Prediction for Colorectal Cancer

The current tumor staging system is insufficient for predicting the outcomes for patients with colorectal cancer because of its phenotypic and genomic heterogeneity. Integrating gene expression signatures with clinicopathologic factors may yield a predictive accuracy exceeding that of the currently available system. Twenty-seven signatures that used gene expression data to predict colorectal cancer prognosis were identified and re-analyzed using bioinformatic methods. Next, clinically annotated colorectal cancer samples (n = 1710) with the corresponding expression profiles, that predicted a patient's probability of cancer recurrence, were pooled to evaluate their prognostic values and establish a clinicopathologic–genomic nomogram. Only 2 of the 27 signatures evaluated showed a significant association with prognosis and provided a reasonable prediction accuracy in the pooled cohort (HR, 2.46; 95% CI, 1.183–5.132, P < 0.001; AUC, 60.83; HR, 2.33; 95% CI, 1.218–4.453, P < 0.001; AUC, 71.34). By integrating the above signatures with prognostic clinicopathologic features, a clinicopathologic–genomic nomogram was cautiously constructed. The nomogram successfully stratified colorectal cancer patients into three risk groups with remarkably different DFS rates and further stratified stage II and III patients into distinct risk subgroups. Importantly, among patients receiving chemotherapy, the nomogram determined that those in the intermediate- (HR, 0.98; 95% CI, 0.255–0.679, P < 0.001) and high-risk (HR, 0.67; 95% CI, 0.469–0.957, P = 0.028) groups had favorable responses. Implications: These findings offer evidence that genomic data provide independent and complementary prognostic information, and incorporation of this information refines the prognosis of colorectal cancer. Mol Cancer Res; 16(9); 1373–84. ©2018 AACR.
Reference Based LSTM for Image Captioning

Image captioning is an important problem in artificial intelligence, related to both computer vision and natural language processing. There are two main problems in existing methods: in the training phase, it is difficult to find which parts of the captions are more essential to the image; in the caption generation phase, the objects or the scenes are sometimes misrecognized. In this paper, we consider the training images as the references and propose a Reference based Long Short Term Memory (R-LSTM) model, aiming to solve these two problems in one goal. When training the model, we assign different weights to different words, which enables the network to better learn the key information of the captions. When generating a caption, the consensus score is utilized to exploit the reference information of neighbor images, which might fix the misrecognition and make the descriptions more natural-sounding. The proposed R-LSTM model outperforms the state-of-the-art approaches on the benchmark dataset MS COCO and obtains top 2 position on 11 of the 14 metrics on the online test server.
Metastatic colorectal cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up.

E. Van Cutsem1, A. Cervantes2, B. Nordlinger3 & D. Arnold4, on behalf of the ESMO Guidelines Working Group* Digestive Oncology, University Hospitals Leuven, Leuven, Belgium; Department of Hematology and Medical Oncology, INCLIVA, University of Valencia, Valencia, Spain; Department of General Surgery and Surgical Oncology, Hopital Ambroise Pare, Assistance Publique – Hopitaux de Paris, Paris, France; Klinik fur Tumorbiologie, Freiburg, Germany
Asynchronous Mini-Batch Gradient Descent with Variance Reduction for Non-Convex Optimization

We provide the first theoretical analysis on the convergence rate of asynchronous mini-batch gradient descent with variance reduction (AsySVRG) for non-convex optimization. Asynchronous stochastic gradient descent (AsySGD) has been broadly used for deep learning optimization, and it is proved to converge with rate of O(1/\sqrt{T}) for non-convex optimization. Recently, variance reduction technique is proposed and it is proved to be able to accelerate the convergence of SGD greatly. It is shown that asynchronous SGD method with variance reduction technique has linear convergence rate when problem is strongly convex. However, there is still no work to analyze the convergence rate of this method for non-convex problem. In this paper, we consider two asynchronous parallel implementations of mini-batch gradient descent method with variance reduction: one is on distributed-memory architecture and the other is on shared-memory architecture. We prove that both methods can converge with a rate of O(1/T) for non-convex optimization, and linear speedup is accessible when we increase the number of workers. We evaluate our methods by optimizing multi-layer neural networks on two real datasets (MNIST and CIFAR-10), and experimental results demonstrate our theoretical analysis.
Should Cookie Monster Adopt a Healthy Lifestyle or Continue to Indulge? Insights into Brand Icons

Developing a brand icon has been a way for marketers to humanize and forge relationships with consumers.Icondevelopmenttakestime. Duringthistime,marketershavetofacehowmuchthey stay true and consistent with their icons and how much they allow their icons to adapt to cultural changes in the marketplace. Little is known about how consumers respond to changing icons, and even less is known about whether there may be certain consumer groups that are more or less receptive to such changes. Four experiments and qualitative interviews were undertaken to gain insights into these issues. People who have a low need to belong were most impacted by changes in the icon, with effects most evident among consumers with a fearful attachment style. Feelings of rejection were found to amplify these effects. These findings have implications both for theory and practice.
Hierarchical Reinforcement Learning with Hindsight

Reinforcement Learning (RL) algorithms can suffer from poor sample efficiency when rewards are delayed and sparse. We introduce a solution that enables agents to learn temporally extended actions at multiple levels of abstraction in a sample efficient and automated fashion. Our approach combines universal value functions and hindsight learning, allowing agents to learn policies belonging to different time scales in parallel. We show that our method significantly accelerates learning in a variety of discrete and continuous tasks.
Grating-Coupled Surface Plasmon Resonance (GC-SPR) Optimization for Phase-Interrogation Biosensing in a Microfluidic Chamber

Surface Plasmon Resonance (SPR)-based sensors have the advantage of being label-free, enzyme-free and real-time. However, their spreading in multidisciplinary research is still mostly limited to prism-coupled devices. Plasmonic gratings, combined with a simple and cost-effective instrumentation, have been poorly developed compared to prism-coupled system mainly due to their lower sensitivity. Here we describe the optimization and signal enhancement of a sensing platform based on phase-interrogation method, which entails the exploitation of a nanostructured sensor. This technique is particularly suitable for integration of the plasmonic sensor in a lab-on-a-chip platform and can be used in a microfluidic chamber to ease the sensing procedures and limit the injected volume. The careful optimization of most suitable experimental parameters by numerical simulations leads to a 30–50% enhancement of SPR response, opening new possibilities for applications in the biomedical research field while maintaining the ease and versatility of the configuration.
Atmospheric Moisture Sources, Paths, and the Quantitative Importance to the Eastern Asian Monsoon Region

AbstractA Lagrangian model [Flexible Particle dispersion model (FLEXPART)] was used to calculate the back trajectories of air parcels residing over the East Asian monsoon region (EAM) for a 4-yr period (2009–12). To detect the moisture source–sink relationships to the EAM, the moisture budgets [evaporation minus precipitation (E − P)] were evaluated by diagnosing the changes of specific humidity along the trajectories. A circulation constraint method was proposed to define the moisture sources of the EAM, to quantify their importance, to depict the moisture transport processes, and to reveal the fate of the moisture from different sources. The results indicated that in winter the largest airmass inflow is through the dry westerlies, but they do not form net precipitation. The much smaller contribution of the tropical oceans is more relevant to winter precipitation. In summer, the main contribution was through the southwest monsoon, with a mean specific humidity of 9.8 g kg−1 when entering the EAM, providi.
The Impact of Soil Temperature on Miscanthus ( Elephant ) Plant : A Case study of Compton Experimental Site , West Midlands , UK

The study explored the response of Miscanthus (elephant) plant to soil temperature at Compton, based on the statistical analysis of the database of (12,045) days of individual soil temperature measurement in sandy-loam of the salwick series soils. Soil temperature at Compton research site significantly increased between 1975-2008 at a rate of ~0.1C year – . However, the rate of increase in the mean annual soil temperature notably affect the growth and survival of Miscanthus (elephant) plant, this was due to the fact that the plant display structural dormancy behavior which is generally attributed to warming effect. Warming was found to exert a very severe problem to the plant. Similarly, it was found that the reaction of this plant to increase in soil temperature was clearly detected. It has been observed that changes of significant proportion in the morphology of the plant was evident. The changes include in active appearance and stunted growth during the early stage of it development while withering, yellowing discolouration and falling of leaves was apparent during the maturity stage. The study concludes that all these changes appeared to be essentially associated with increase in soil temperature.
Transfer learning for aluminium extrusion electricity consumption anomaly detection via deep neural networks

Effective anomaly detection can reduce the electricity consumption and carbon emissions in aluminium extrusion processes. The following two steps identify anomalies: electricity consumption forecasting and anomaly detection. Data-driven modelling is typical paradigm for building an accurate forecasting model. For a new extruding machine, there is insufficient extruded data for model training. The research objective of this work is to determine whether a forecasting model can be trained by transferring knowledge from a data-sufficient domain to a data-insufficient domain. A shared connected deep neural network is proposed for electricity consumption time-series anomaly forecasting. Anomalies are detected by the difference of predicted and measured values at a confidence interval. The experimental results show that the proposed approach can identify electricity anomaly events in real time. Furthermore, it is shown that transferring learning knowledge between domains significantly improves the forecasting results.
Comparative Effectiveness of Vancomycin and Metronidazole for the Prevention of Recurrence and Death in Patients With Clostridium difficile Infection

Importance Metronidazole hydrochloride has historically been considered first-line therapy for patients with mild to moderate Clostridium difficile infection (CDI) but is inferior to vancomycin hydrochloride for clinical cure. The choice of therapy may likewise have substantial consequences on other downstream outcomes, such as recurrence and mortality, although these secondary outcomes have been less studied. Objective To evaluate the risk of recurrence and all-cause 30-day mortality among patients receiving metronidazole or vancomycin for the treatment of mild to moderate and severe CDI. Design, Setting, and Participants This retrospective, propensity-matched cohort study evaluated patients treated for CDI, defined as a positive laboratory test result for the presence of C difficile toxins or toxin genes in a stool sample, in the US Department of Veterans Affairs health care system from January 1, 2005, through December 31, 2012. Data analysis was performed from February 7, 2015, through November 22, 2016. Exposures Treatment with vancomycin or metronidazole. Main Outcomes and Measures The outcomes of interest in this study were CDI recurrence and all-cause 30-day mortality. Recurrence was defined as a second positive laboratory test result within 8 weeks of the initial CDI diagnosis. All-cause 30-day mortality was defined as death from any cause within 30 days of the initial CDI diagnosis. Results A total of 47 471 patients (mean [SD] age, 68.8 [13.3] years; 1947 women [4.1%] and 45 524 men [95.9%]) developed CDI, were treated with vancomycin or metronidazole, and met criteria for entry into the study. Of 47 147 eligible first treatment episodes, 2068 (4.4%) were with vancomycin. Those 2068 patients were matched to 8069 patients in the metronidazole group for a total of 10 137 included patients. Subcohorts were constructed that comprised 5452 patients with mild to moderate disease and 3130 patients with severe disease. There were no differences in the risk of recurrence between patients treated with vancomycin vs those treated with metronidazole in any of the disease severity cohorts. Among patients in the any severity cohort, those who were treated with vancomycin were less likely to die (adjusted relative risk, 0.86; 95% CI, 0.74 to 0.98; adjusted risk difference, –0.02; 95% CI, –0.03 to –0.01). No significant difference was found in the risk of mortality between treatment groups among patients with mild to moderate CDI, but vancomycin significantly reduced the risk of all-cause 30-day mortality among patients with severe CDI (adjusted relative risk, 0.79; 95% CI, 0.65 to 0.97; adjusted risk difference, –0.04; 95% CI, –0.07 to –0.01). Conclusions and Relevance Recurrence rates were similar among patients treated with vancomycin and metronidazole. However, the risk of 30-day mortality was significantly reduced among patients who received vancomycin. Our findings may further justify the use of vancomycin as initial therapy for severe CDI.
The role of tomosynthesis in intraoperative specimen evaluation

To investigate the contribution of breast tomosynthesis to intraoperative specimen evaluation in subjects with breast cancer. Approval was obtained from the hospital ethics committee. Specimen mammography, tomosynthesis, and, if available, ultrasonography images were retrospectively assessed for 208 women who had undergone conservative surgery at our hospital between January 2013 and April 2016 after being diagnosed with breast cancer. The success of mammography, tomosynthesis, and ultrasonography in lesion detection and characterization was evaluated. Of 208 lesions, 142 (68.3%) and 198 (95.2%) were detected by mammography and tomosynthesis, respectively. All lesions were detected in 150 subjects undergoing ultrasonography (124 dense breasts, 26 fatty breasts). In 84 women who had fatty breasts, all lesions were detected both by mammography and by tomosynthesis. In 124 women with dense breasts, lesions were detected by mammography in 59 (48%) and in 114 (92%) by tomosynthesis. The success of tomosynthesis in lesion detection was found to be markedly higher than mammography (P = .00). In conclusion, tomosynthesis contributed to mammography in specimen evaluation in a total of 101 subjects. The success of tomosynthesis in lesion detection and characterization during intraoperative specimen evaluation is higher than mammography. In daily practice, ultrasonography is performed for lesions which cannot be evaluated by specimen mammography due to dense parenchymal pattern. Tomosynthesis may reduce the need for and the time and workforce allocated to specimen ultrasonography in an important group of subjects.
A new dataset and model for learning to understand navigational instructions

In this paper, we present a state-of-the-art model and introduce a new dataset for grounded language learning. Our goal is to develop a model that can learn to follow new instructions given prior instruction-perception-action examples. We based our work on the SAIL dataset which consists of navigational instructions and actions in a maze-like environment. The new model we propose achieves the best results to date on the SAIL dataset by using an improved perceptual component that can represent relative positions of objects. We also analyze the problems with the SAIL dataset regarding its size and balance. We argue that performance on a small, fixed-size dataset is no longer a good measure to differentiate state-of-the-art models. We introduce SAILx, a synthetic dataset generator, and perform experiments where the size and balance of the dataset are controlled.