Miracle-dz/UniFAR-FTUs huggingface dataset:
Patient Satisfaction After Treatment of Nonmelanoma Skin Cancer

BACKGROUND Patient satisfaction is an important aspect of patient‐centered care but has not been systematically studied after treatment of nonmelanoma skin cancer (NMSC), the most prevalent cancer. OBJECTIVE To compare patient satisfaction after treatment for NMSC and to determine factors associated with better satisfaction. METHODS We prospectively measured patient, tumor, and care characteristics in 834 consecutive patients at two centers before and after destruction, excision, and Mohs surgery. We evaluated factors associated with short‐term and long‐term satisfaction. RESULTS In all treatment groups, patients were more satisfied with the interpersonal manners of the staff, communication, and financial aspects of their care than with the technical quality, time with the clinician, and accessibility of their care (p<.05). Short‐term satisfaction did not differ across treatment groups. In multivariable regression models adjusting for patient, tumor, and care characteristics, higher long‐term satisfaction was independently associated with younger age, better pretreatment mental health and skin‐related quality of life, and treatment with Mohs surgery (p<.05). CONCLUSIONS Long‐term patient satisfaction after treatment of NMSC is related to pretreatment patient characteristics (mental health, skin‐related quality of life) and treatment type (Mohs) but not tumor characteristics. These results can guide informed decision‐making for treatment of NMSC. The authors have indicated no significant interest with commercial supporters.
Not All Fluctuations are Created Equal: Spontaneous Variations in Thermodynamic Function

Almost all processes -- highly correlated, weakly correlated, or correlated not at all---exhibit statistical fluctuations. Often physical laws, such as the Second Law of Thermodynamics, address only typical realizations -- as highlighted by Shannon's asymptotic equipartition property and as entailed by taking the thermodynamic limit of an infinite number of degrees of freedom. Indeed, our interpretations of the functioning of macroscopic thermodynamic cycles are so focused. Using a recently derived Second Law for information processing, we show that different subsets of fluctuations lead to distinct thermodynamic functioning in Maxwellian Demons. For example, while typical realizations may operate as an engine -- converting thermal fluctuations to useful work -- even "nearby" fluctuations (nontypical, but probable realizations) behave differently, as Landauer erasers -- converting available stored energy to dissipate stored information. One concludes that ascribing a single, unique functional modality to a thermodynamic system, especially one on the nanoscale, is at best misleading, likely masking an array of simultaneous, parallel thermodynamic transformations. This alters how we conceive of cellular processes, engineering design, and evolutionary adaptation.
Insights into Diagenesis and Pore Structure of Opalinus Shale Through Comparative Studies of Natural and Reconstituted Materials

Shales have undergone a complex burial diagenesis that involved a severe modification of the pore structure. Reconstituted shales can provide new insights into the nature of the pore structure in natural materials. The effects of diagenesis on the microfabric, pore size distribution, and porosity of Opalinus shale were measured by comparing the behavior of natural and reconstituted specimens. The parent material (Opalinus shale) was reconstituted through multiple grinding operations, sedimentation from a dispersed slurry, and one-dimensional isothermal consolidation. This process produced uniform specimens that were not cemented and had replicable microfabric and engineering properties. The microfabric and mineralogy of the materials were examined using high-resolution scanning/backscattered electron microscopy (SEM/BSEM) and energy-dispersive X-ray spectroscopy (EDS) for specimens with broken and milled surfaces. Mercury intrusion porosimetry (MIP) and N2 adsorption were used to assess the pore size distributions and specific surface areas of the materials. The microstructure of natural shale was characterized to be highly heterogeneous with significant concentrations of calcareous microfossils, calcite, and quartz particles embedded within the clay matrix. The microfossils were observed to be locally infilled and rimmed by a calcite cement that showed evidence of dissolution. The reconstituted specimens showed a double-structure microfabric that evolved with the level of consolidation stress and converged into a single-structure material (comparable to the natural shale) at a consolidation stress of more than twice the estimated maximum in situ effective stress. The natural shale had a lower specific surface area in comparison to the reconstituted material, which was consolidated at large effective stresses. These differences can be attributed to cementation at a submicron pore scale and highlight chemical diagenesis effects that were not replicated in the reconstituted specimens.
Maximizing Capacity in the SINR Model in Wireless Networks with Successive Interference Cancellation

Successive interference cancellation (SIC) is an effective way of multipacket reception to combat interference. We consider the problem of maximizing the number of successful transmissions based on the physical model in wireless networks with SIC at the physical layer. We propose weighted simultaneity graph to characterize the sequential detection nature of SIC and the accumulative effect of multiple interfering signals. A context-aware metric, transmission price, is defined to measure the interference of a link set. As maximizing the number of supported links is NP-hard, a greedy scheme is proposed to efficiently construct a near-optimal maximal feasible set of links. We show that the approximation performance is bounded by the transmission price of the constructed link set. The performance of the proposed scheme is further verified by simulation.
Predicting radiation protection and toxicity of p53 targeting radioprotectors using machine learning

This paper explores machine learning application in the case of drug discovery. We apply extreme gradient boosting and K-nearest neighbor to biomedical data and it signiflcantly outperform former studies using feature selection and proper tuning parameters. The novel application motivated by a recent circumstance that there is a need for rapid development of radio-protectors. It mainly targets the DNA of growing cancer cells, whereas it has adverse side effects, including p53-induced apoptosis of normal tissues and cells. It considered that p53 would be a target for therapeutic and mitigated radioprotection to escape from the apoptotic fate. On the other hand, many types of compounds contain several level of toxicity, so it is important to consider not only radiation protection but also the level of toxicity of candidate compounds for radioprotectors. Compounds of radio-protectors that have low toxicity and high radiation protection are expected. It is possible to do efficiently the compounds discovery using machine learning. This study predicts compounds of radioprotectors using plural machine learning methods, Extreme Gradient Boosting, K-nearest neighbor, SVM and Random Forest. We compare these methods and suggest proper methods to predict radioprotectors.
Automatic Extraction of Polar Adjectives for the Creation of Polarity Lexicons

Automatic creation of polarity lexicons is a crucial issue to be solved in order to reduce time and efforts in the first steps of Sentiment Analysis. In this paper we present a methodology based on linguistic cues that allows us to automatically discover, extract and label subjective adjectives that should be collected in a domain-based polarity lexicon. For this purpose, we designed a bootstrapping algorithm that, from a small set of seed polar adjectives, is capable to iteratively identify, extract and annotate positive and negative adjectives. Additionally, the method automatically creates lists of highly subjective elements that change their prior polarity even within the same domain. The algorithm proposed reached a precision of 97.5% for positive adjectives and 71.4% for negative ones in the semantic orientation identification task.
A Study of the Built Environment Design Elements Embedded into the Multiple Criteria Strategic Planning Model for an Urban Renewal

The link between urban planning and design principles and the built environment of an urban renewal area is of interest to the field of urban studies. During the past decade, there has also been increasing interest in urban planning and design; this interest is motivated by the possibility that design policies associated with the built environment can be used to control, manage, and shape individual activity and behavior. However, direct assessments and design techniques of the links between how urban planning design policies influence individuals are still rare in the field. Recent research efforts in urban design have focused on the idea that land use and design policies can be used to increase the quality of design projects for an urban renewal area’s built environment. The development of appropriate design techniques for the built environment is an essential element of this research. Quality function deployment (QFD) is a powerful tool for improving alternative urban design and quality for urban renewal areas, and for procuring a citizen-driven quality system. In this research, we propose an integrated framework based on QFD and an Analytic Network Process (ANP) approach to determine the Alternative Technical Requirements (ATRs) to be considered in designing an urban renewal planning and design alternative. We also identify the research designs and methodologies that can be used to evaluate the performance of urban built environment projects. An application in an urban renewal built environment planning and design project evaluation is presented to illustrate the proposed framework. Keywords—Analytic Network Process, Built Environment, Quality Function Deployment, Urban Design, Urban Renewal.
Location-Based Activity Recognition using Relational Markov Networks

In this paper we define a general framework for activity recognition by building upon and extending Relational Markov Networks. Using the example of activity recognition from location data, we show that our model can represent a variety of features including temporal information such as time of day, spatial information extracted from geographic databases, and global constraints such as the number of homes or workplaces of a person. We develop an efficient inference and learning technique based on MCMC. Using GPS location data collected by multiple people we show that the technique can accurately label a person's activity locations. Furthermore, we show that it is possible to learn good models from less data by using priors extracted from other people's data.
Monte Carlo simulation on a gold nanoparticle irradiated by electron beams

This study investigated the secondary electron production from a gold nanoparticle (GNP) irradiated by monoenergetic electron beams using Monte Carlo (MC) simulation. Spherical GNPs with diameters of 2, 50 and 100 nm in water were irradiated by monoenergetic electron beams with energies equal to 50 keV, 250 keV, 1 MeV and 4 MeV. MC simulations were performed using the Geant4 toolkit to determine the energy of the secondary electrons emitted from the GNPs. The mean effective range and deflection angle of the secondary electrons were tracked. Energy depositions inside and outside the nanoparticles due to the secondary electrons were also calculated. For comparisons, simulations were repeated by replacing the GNPs with water. Our results show that the mean effective range of secondary electrons increased with an increase of the GNP size and electron beam energy. For the electron beam energy and GNP size used in this study, the mean effective range was 0.5–15 µm outside the nanoparticle, which is approximately within the dimension of a living cell. The mean deflection angles varied from 78 to 83 degrees as per our MC results. The proportion of energy deposition inside the GNP versus that outside increased with the GNP size. This is different from the results obtained from a previous study using photon beams. The secondary electron energy deposition ratio (energy deposition for GNP/energy deposition for water) was found to be highest for the smallest GNP of 2 nm diameter in this study. For the energy deposited by the secondary electron, we concluded that the addition of GNPs can increase the secondary electron energy deposition in water, though most of the energy was self-absorbed by the large nanoparticles (50 and 100 nm). In addition, an electron source in the presence of GNPs does not seem to be better than photons as the yield of secondary electrons per unit mass of gold is less than water.
Risk Mapping Assessment by Means of Probabilistic Storm Scenarios in a Partially Engineered Beach: Anglet, France

ABSTRACT de Santiago, I. ; Morichon, D. ; Arnoux, F. ; Delpey, M. , and Epelde, I. , 2018. Risk mapping assessment by means of probabilistic storm scenarios in a partially engineered beach: Anglet, France. In: Shim, J.-S. ; Chun, I. , and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 796–800. Coconut Creek (Florida), ISSN 0749-0208. The characterisation of storms and the associated damage level is essential to design correct risk mitigation strategies. The study site, an engineered beach located in the South West of France, is exposed to frequent storm events. The objective of the present work is twofold: (1) to obtain a risk map along the different sectors of the beach and (2) to find risk indicators suitable for the present study site. The storm scenarios are obtained from a hindcast database that includes 66 years of wave parameters. Six storm types have been chosen to be representative of the extreme wave climate of the study site based on the energy flux (EF) threshold. The beach response to storm events is alongshore non-uniform and closely linked to the cross-shore position of the seawall. Total storm power combined with water level and beach volume/width seems to be the best set of risk indicators for the present study site.
Comparison of mesh generation algorithms for railroad reconstruction

Inspection of railroad tracks is still predominantly performed visually by human inspectors. Due to the extension of the tracks this is a slow and tedious operation, significantly subjected to human errors and inconsistency. In this context, computer vision systems, composed of field-acquired images and processing algorithms, have a great potential to improve efficiency and to offer systematic inspection methodologies. In this paper the use of available point cloud and mesh generation algorithms to construct 3D surface of railroad tracks is investigated. To achieve this goal, images of a small track were acquired from several points-of-view. Next a comparison between several open and closed-source algorithms was performed, evaluating the number of 3D points, time consumption, RAM memory, GPU memory, number of faces, and the generated mesh. The results obtained demonstrate that with the right setup, current image processing methodologies can be used to construct 3D surfaces of uncontrolled scenarios, such as those of a real railroad environment. Regarding the comparison, SURE and Poisson presented the most accurate meshes. When comparing quantitative measures, though, Poisson presented a slightly better performance in time consumption, but SURE had a better RAM memory usage and a greater level of details.
CONSORT-EHEALTH Checklist V1.6.2 Report

Psyfit, Internet-based intervention to promote mental fitness for mildly depressed adults: results of a randomized controlled trial TITLE 1a-i) Identify the mode of delivery in the title Yes, we call the mode of delivery 'Internet-based intervention'. E-mail reminding is part of the intervention. 1a-ii) Non-web-based components or important co-interventions in title No, the e-mail reminding is not mentioned because it is an element in the intervention, though not a central element. 1a-iii) Primary condition or target group in the title Yes: 'for mildly depressed adults' is in the title. ABSTRACT 1b-i) Key features/functionalities/components of the intervention and comparator in the METHODS section of the ABSTRACT Yes, but not in a elaborate way: Psyfit ('mental fitness online') is a fully automated self-help intervention based on positive psychology with the aim of improving well-being. ' The comparator condition is called the 'a waiting list control condition'. 1b-ii) Level of human involvement in the METHODS section of the ABSTRACT Yes, in the abstract is stated: 'Psyfit ('mental fitness online') is a fully automated self-help intervention. '. 1b-iii) Open vs. closed, web-based (self-assessment) vs. face-to-face assessments in the METHODS section of the ABSTRACT Yes: 'Online measurements were taken at baseline, 2 months and 6 months after baseline. '
c-Jun N-terminal kinase-dependent mechanisms in respiratory disease

Respiratory diseases pose a multifaceted dilemma. Although the symptoms and pathology are obvious and provide multiple opportunities for therapeutic investigation, at the same time, the molecular complexities and prioritisation are overwhelming. Even within a disease such as asthma, the number of inducers, cell types, secondary mediators, chemical changes, immune responses and tissue modifications is remarkable. One means of therapeutically targeting this complexity is to identify individual factors responsible for regulating multiple disease processes. The mitogen-activated protein kinase family integrates multiple diverse stimuli, and, in turn, initiates a cell response by phosphorylating and thereby modulating the activity of many target proteins. The c-Jun N-terminal kinase is a critical regulator of pro-inflammatory genes, tissue remodelling and apoptosis, and, therefore, represents an attractive target for novel therapies. Pre-clinical and clinical investigation into the efficacy of c-Jun N-terminal kinase inhibitors has been ongoing since the late 1990s. Over the course of this work, hypotheses have shifted as to the role of c-Jun N-terminal kinase in the many processes that promote allergic, inflammatory, obstructive and fibrotic diseases of the lung. Inhibition of c-Jun N-terminal kinase may indeed provide a means of suppressing more pathological mechanisms in respiratory disease than first suspected.
MDTN: Mobile Delay/Disruption Tolerant Network

Infrastructure networks like Internet have some coverage gaps (e.g. rural areas) where no service connectivity is provided. Cellular networks could be used in alternative but they usually associate their services with a usage cost. Nowadays, the growing number of mobile devices equipped with a wireless interface and the end-user trend to shift toward wireless technology has opened new possibilities for networking. Opportunistic networking seems a feasible solution in filling in these coverage gaps by providing service connectivity where it is not sustained by an infrastructure. In this context we provide a delay tolerant platform that ensures service connectivity where it is absent. Our approach follows the Delay/Disruption Tolerant Networking (DTN) paradigm by implementing a store-and-forward communication model between mobile users and carrier entities (e.g. buses), where a user delegates the carrier a task (bundle), the carrier stores it locally and whenever service connectivity is available (e.g. wi-fi at the bus station) tries to accomplish it, successively notifying the user of the task output next time they encounter again.
Use of a Lidar Forward Model for Global Comparisons of Cloud Fraction between the ICESat Lidar and the ECMWF Model

The performance of the European Centre for Medium-Range Weather Forecasts (ECMWF) model in simulating clouds is evaluated using observations by the Geoscience Laser Altimeter System lidar on the Ice, Cloud, and Land Elevation Satellite (ICESat). To account for lidar attenuation in the comparison, model variables are used to simulate the attenuated backscatter using a lidar forward model. This generates a new model cloud fraction that can then be fairly compared with the ICESat lidar. The lidar forward model and ICESat comparison is performed over 15 days (equivalent to 226 orbits of Earth, or roughly 9 million km) of data. The model is assessed by cloud fraction statistics, skill scores, and its ability to simulate lidar backscatter. The results show that the model generally simulates the occurrence and location of clouds well but overestimates the mean amount when present of the ice cloud by around 10%, particularly in the tropics. The skill of the model is slightly better over the land than over the sea. The model also has some problems representing the amount when present in tropical boundary layer cloud, particularly over land, where there is an underestimate by as much as 15%. Calculations of backscatter reveal that the ECMWF model predicts the lidar backscatter to within 5% on average, for a lidar ratio of 20 sr, apart from in thick ice clouds. Sensitivity tests show that realistic variations in extinction-to-backscatter ratio and effective radius affect the forward modeled mean cloud fraction by no more than 10%.
Optimizing Long-Lived CloudNets with Migrations

This paper attends to the problem of embedding flexibly specified virtual networks connecting cloud resources (e.g, storage or computation) on a given substrate (e.g., a data center, an ISP backbone, a router site, or a virtual provider network). We study a scenario where a substrate provider (or a potential intermediate broker or reseller) wants to optimize the embedding of these so-called CloudNets by migrating them to more suitable locations. For instance, such re-embeddings can be useful if the CloudNets were requested at short notice and initially placed heuristically. Subsequent optimizations can, e.g., reduce the peak resource loads in the network by spreading CloudNets across the infrastructure or save energy by moving CloudNets together and switching off unused components. We present the generic mathematical programming algorithm used in our CloudNet prototype to compute optimal embeddings. For example, this algorithm supports different objective functions (such as load minimization or energy conservation), arbitrary resource combinations and the mapping of multiple virtual nodes of a CloudNet to a single substrate node, cost-aware migrations, and it can deal with all link types that arise in practice (e.g., fullduplex or even wireless or wired broadcast links with multiple endpoints). Of course, such rigorous CloudNet optimizations are time consuming, and we report on the time complexities obtained from our experiments with our network virtualization prototype architecture. It turns out that optimizing CloudNets over moderate sized infrastructures is feasible, even for scenarios with high flexibility and without tuning the solver software to speed up computations further.