dataesr/scientific-paragraphs-categorization huggingface dataset:
Patient had no access to this function for the present study. Three different user profiles exist: 1) for patients; 2) for caregivers/family; and 3) for mental health professionals. For the purposes of this study we only used the mental health professional profile (Fig  1 ). During this study, patients did not have access to the web application. If they agreed to participate to the study, they only agreed to allow their clinician to enter their personal data into the MEmind web application. The patients were still treated as usual. Each patient was identified by a numeric code that ensures patient anonymity. This code is encrypted in the database that remained the same throughout all contact with patients cared for during the study.
Special mention is needed for asenapine, an antipsychotic approved in Spain only for manic episodes in bipolar disorder. This narrow indication probably reflects its low dose usage. Information for this study was obtained with a novel web tool, the mental state tracker MEmind. This device also has an interesting potential use in clinical research. Data collected by the provider are instantaneously transmitted to the database and made available for data mining. The system is also able to deliver alarms. In this pilot study we only made both raw data and graphic information about medical prescription available for the provider. We are currently assessing the possibility of incorporating, in the analysis, data proceeding directly from the patient that uses the EMA function of the program.
They all consist of software tools that, upon the use of digital image processing techniques, are capable of simulating myopia, macular degeneration, cataract, glaucoma, etc. [1, 11, 13]  as well as different levels of color blindness  [26, 21]. The user normally selects the eye pathology to apply over 2D static images and visualizes the results on the computer's screen. In the VR field, Jin et al. designed a virtual apartment that had to be explored experiencing visual impairment  [14]. Similarly, Lewis et al. proposed in  [16]  a virtual restaurant that users had to navigate under low vision conditions.
Note that the system is totally wearable. Perimetry studies carried out with an automated Humphrey Field Analyzer (HFA) reveal that the prototype's attainable visual field is 56 •. Fig. 2  compares some visual fields of interest with the simulator's one: the human field of view is approximately 190 •. However, a correct discrimination of objects requires some visual acuity which does not occur in all this range. Discrimination of forms is accomplished with a visual field of 60 • while reading text with one of 20 •. A self-developed software in C++ and OpenCV  [19]  modifies the VR headset's input image/video to simulate eight different types of eye pathologies. The operation principle is shown in fig. 3. Consider an RGB image of dimensions MxNx3 denoted by matrix A and a binary image of dimensions MxN denoted by matrix P (the mask).
Comparing the simulator with the works described in  [1, 11, 13] , the prototype here presented provides realtime video of the surrounding environment which is undoubtedly a great advantage over static images on the computer's screen. Concerning the low vision simulators in virtual environments  [14, 16]  it can be concluded that although they offer realistic graphics, they offer a limited version of the environment for users to explore and interact. The simulator presented in this paper is designed to work in real environments. The simulator was experimentally evaluated with a group of five normally sighted volunteers in a task involving reading texts. Data from this experiment allow us to determine the impact of these impairments on the task. Results obtained suggest that reading speed depends on peripheral vision (in agreement with  [4] ).
The main goal of our system is to educate and sensitize normally sighted about low vision and the daily challenges the visually impaired face. This is particularly useful for professionals involved in the field such as special education teachers, Braille teachers, psychologists, orientation and mobility specialists, low vision specialists, and vision rehabilitation therapists. A second goal is to have a wearable technological platform that simulates low vision conditions for the normally sighted. This is useful for the design and evaluation of new concepts of assistive devices. Future applications of the simulator will assist the design of software tools that address the problem of digital information access for people with visual impairment. The simulator will undoubtedly provide helpful hints on how to adjust the text displayed on the computer's screen to fit the particular needs of low vision readers.
Introduction Low-Power and Lossy Networks (LLN) are a new class of constrained wireless networks that allow a set of objects (sensors, actuators, etc. ) to exchange relevant data in a multi-hop fashion. Interconnecting LLNs together with Internet opened the road to a large variety of applications and gave birth to what is now called the Internet of Things. In this context, seamless mobility support is one of the keys to a widespread adoption of LLNs. First, a large variety of applications, ranging from target tracking  [1]  to wildlife monitoring  [2]  require the support of node mobility. Additionally, LLNs will be fully integrated into the future 5G networks and as such should cope with the notion of ubiquitous connectivity. In a general view, node mobility can be managed with three different approaches: relaying, Software Defined Networking (SDN) and routing  [3].
Acknowledging P0 preambles by fixed nodes is done with PK0 acknowledgment, when the P0 preamble is received but not destined to them. In this situation the fixed node acts as an opportunistic forwarder which is ready to receive data from a mobile node. Preamble received by the intended destination will be acknowledged by PK1 type acknowledgment. More in depth information about how X-Machiavel works is available in  [9]. Next, we will present how information from X-Machiavel is used at RPL to create MT-RPL.
Mobile nodes randomly draw q ∈ [0; T [ and waits for the expiration of q before transmitting the data. If the channel is busy during this period of time, the mobile node considers that the channel was stolen by another mobile node and postpones its transmission. This procedure allows collision avoidance (to a certain extent) between multiple mobile nodes trying to steal the channel from the same fixed node at the same time. The fixed node, after receiving a data packet between two P1 preamble strobes, will first acknowledge the successful reception of the data then advertise P2 preamble for both the mobile node data packet and its own data packet, which still needs to be sent. Upon reception of the acknowledgment, the mobile node updates its RPL parent. Further along the path, X-Machiavel principles apply.
The fixed nodes will serve the mobile nodes between 3-5 minutes, then they will stop serving the mobile node between 1-4 minutes. With these values of service provision, the mobile node will always find a fixed node that can serve as preferred parent in the network. A more detailed view of the different parameters of experimentation can be explored in Table  1. NUD and BFD are analyzed using X-MAC protocol so that only the receiving node can acknowledge the data packet. Once the preferred parent is considered as unreachable, the parent set is dropped and new DIO are requested from the neighborhood. These DIO are requested by sending multicast DIS messages from the mobile node. On the other hand, MT-RPL uses X-Machiavel protocol, where any node with a better rank than the parent of the node can act as an opportunistic forwarder, or where a mobile node can steal the channel from a fixed node.
Since the value of composition x and the strain ε c can be derived from both EDX and NBD data independently (S2 presents details of this calcualtion) equations (  4 ) and (  6 ) can be derived independently by both methods. Now, the total polarization (P tot ) is the sum of the two polarizations (P pz + P sp ). Figure  4  shows P pz and P sp determined using the NBD measurements along with the total polarization deduced from strain measurements extracted from both NBD and EDX independently. Both measurements give reasonably identical values for the total polarization. To measure the electric field directly, the deflection of the central beam was calculated from its position which has been calibrated by using the 0002 reflection and the known Bragg angle of 7. 905 mrad in pure AlN. The field E is then δθ ⋅ ⋅ ⋅ - m v e t tan( ) 2 where m is the relativistic mass of the electron, e -and v its charge and velocity respectively, and t the thickness of the specimen.
In equation (  8 ) L b and L w are the barrier and well heights, respectively and ε 0 is the permittivity of free space, ε AlGaN and ε AIN are the relative permittivity of AlGaN and AlN respectively. This gives a field magnitude of 6. 44 MV/cm, which is slightly larger than our measurement of 3 MV/cm for the reasons mentioned above. ε ε ε = - + E L P P L L ( ) ( ) (8) Finally, to compare our method to DPC which is an accepted and established method for measuring electric fields, using MATLAB, we created a mask which simulates the function of a two arm segmented detector. This mask can be considered a virtual detector it has a width of 1. 55 mrad and an inner angle of 6. 85 mrad. The virtual detector subtends an angle of 90° from the centre of 0000-reference disc. Figure  7a  shows the image of the virtual detector used for 'digital-DPC' measurements, the two arms of the detector are labelled V and W.
However, as stated earlier, it cannot be considered a direct technique and as in-line holography needs long exposure times (~10 s/image), this can create a problem while measuring the charge density or potential in a specimen due to radiation induced charge migration and a potential build up in the illuminated area of the sample  37. In contrast, the extraction of strain and electric field by the method discussed here are relatively simple. In the use of NBD this is not a problem as each pattern takes only a second at most and is a technique routinely used in electron microscopy. To conclude, this is the first method to be able to characterize both, the strain as well as electric field from one dataset and has overcome most limitations posed by the other techniques presented above. The experimentally measured electric field at the interface of the quantum well was of the order of 3 MV/cm and the polarization charge density is approximately 3 × 10 20 e/cm 3.
Methods The MQW sample was grown by molecular beam epitaxy (MBE) on the basal plane of an AlN/sapphire pseudosubstrate. The growth details are reported elsewhere  38. It was prepared for cross-sectional TEM investigation in a focused ion beam (FIB) facility using a lift-out technique, followed by Ar + etching at 350 V and a 20° oscillation angle with a Technoorg Linda (Model GM IV5) low energy ion milling system to remove the amorphization on the specimen surface due to the FIB etching. The local specimen thickness was determined by comparing the high-angle annular dark-field (HAADF) signal recorded with a detector acceptance angle range of 33-200 mrad (normalized to the intensity of the incoming beam) to the thickness-dependent frozen lattice multi-slice simulations for pure AlN carried out with the STEM simulation program STEMsim  39.
Acknowledgements The authors thank the  FEI company  for the EDX measurements and HR-BF-STEM data. This work was supported by the  MAT2010-15206  ( CICYT, Spain ),  EU-COST  Action  MP0805 , and  P09-TEP-5403  ( Junta de Andalucía  with  EU-FEDER participation). We acknowledge support by  FCT Portugal  ( PTDC/FIS-NAN/0973/2012 ,  SFRH/ BPD/74095/2010 ,  Investigador FCT) , and  Juan de la Cierva program  ( JCI-2012-14509 ). K. M. acknowledges support from the  Deutsche Forschungsgemeinschaft (DFG)  under contract No. MU 3660/1-1. T. G: acknowledges support from  DFG  ( R02051/11-1 ).
Method and analysis: This is a prospective, longitudinal, exploratory, open study with a 6-month follow-up period. Data will be recorded longitudinally over multiple weeks under natural conditions. The factors affecting the quality of life and anxiety of parents of children with ASD and the children's functional symptoms will be examined, and the feasibility of using a smartphone application designed for parents of ASD patients will be assessed. Primary objective: Explore the evolution of a child's behaviour over 6 months and the ( psychological and social) effects of these changes on the family. Secondary objective: Assess the feasibility of our application by examining the filling rate and application usage by parents for 6 months. 100 families containing 1 child diagnosed with ASD will be included.
2 pps may also be helpful in remote support via SMS, voice or visual phone consultations for medical purpose. More importantly, medicine, as well as psychiatry, requires data from patients or their families. These data might be obtained from questionnaires that can be completed under natural conditions; this technique is referred to as ecological momentary assessment (EMA 3 ) or the experience sampling method. 4 The first EMA experiments used beepers to remind users to complete the questionnaires on a computer; in general, the results for compliance and quality were disappointing, and the filling schedules were not respected. 5 Since the release of PDAs and smartphones, individuals are carrying their device everywhere. This is a breakthrough for medical research in various fields, but psychological status and behaviour, including behavioural addictions,  6  eating behaviors, 7 anxiety 8 and severe psychiatric disorders, such as bipolar disorder  9  or schizophrenia, appear to be particularly appropriate topics for applicationbased studies.
Further, the parents' quality of life is strongly affected by everyday life with their children with ASD. 21 22 Data on these behavioural disorders are currently being collected in a transverse manner using surveys, questionnaires and parental recall. This mode of data collection causes a clear, and classical, bias in all studies. Our goal is to study a child's ASD symptoms and their impact on a family's quality of life, psychological status and anxiety over a long time period (6 months) using a daily information source that includes parental observations. Moreover, our EMA application that includes feedback could be useful for facilitating parents' necessary adaptive educational behaviour and for informing the doctor (who will have access to the data during regular consultations). In addition to quality of life, anxiety of the parents is a dimension that we will consider.
Method At the inclusion visit, parents will receive a code to download the app from the 'application store' of their choice (depending on their smartphone) and sign an informed consent form (see flow chart, figure  4 ). All type 1 data from the inclusion visit will be stored in an electronic database and in the smartphone application (during the setup process). This initial evaluation by the investigator will include the following type 1 data: ▸ Sibling rank and marital status, ▸ Lifestyle: rural or urban; single or multiple occupants of the child's bedroom and housing type and surface, ▸ Educational and teaching load and conditions (special education, inclusive education, partial or full time, etc), and ▸ The therapeutic management (speech therapy, psychomotor therapy, etc). Type 2 data will be stored in the electronic database only: ▸ Age at diagnosis, ▸ Current drug treatments (name, starting date and dose), ▸ Comorbidities (associated epilepsy, mental retardation and organic pathology), ▸ Medical and psychiatric family ATCD, ▸ Original scores on the ADI-R and ADOS at the time of diagnosis, and ▸ Scores on the French version of the Childhood Autism Rating Scale 26 (CARS) (http://www.
autisme. qc. ca) at baseline and at the end of the study. A default schedule for filling out the routine application questions (as shown in figures 2 and 3) with notification reminders will then be proposed to the parents. The default settings can be modified by the parents if necessary but must include at least three fillings each week. Missing data will be included in the assessments. Each filling will require a short time period (<10 min in the longest configuration, if all answers are yes). The key questions are closed-ended (yes/no), and a VAS is primarily used to evaluate the degrees of statuses, symptoms and disorders. The first question concerns the environmental context in the days surrounding the filling date (unusual, holiday, etc). With respect to the children, the questions will focus on sleep, food and behaviour concerning themselves and others (such as aggressiveness, agitation, stereotypic behaviours or cries).
To avoid redundant or inappropriate questions, the questions will be presented as an algorithm (see figures 1 and 2). In cases in which both parents have a smartphone, both will have the application, and filling may be performed by either parent. The data will be aggregated per family. Simultaneous assessments by both parents are unnecessary in this study. During the 6-month inclusion period and the 6-month follow-up period, we will record encrypted data from the smartphone when the parents are connected to a Wi-Fi network using a secure medical server (16-digit encryption key+a personal temporary code for access to data). We have developed a qualitative questionnaire for the participants and the patients' doctors as well as a semidirected, face-to-face interview to assess the change in the doctor-patient relationship after using the application.
Statistical analysis For this feasibility study, the primary end point (which corresponds to the primary objective) will be the application filling rate, which is calculated relative to the ideal filling rate (3 days per week every week) and considers the number of fillings (of at least half of the items requested). The secondary end points will require more precise analyses, such as examination of the variation in the rate of responding to at least half of the requested items over time. We will collect a considerable amount of data due to the number of variables; as such, we will be able to perform exploratory epidemiology on this essential and unique database using descriptive and analytical statistics. Generally, we will compare two groups: the group with a single place of family life and the group with two places of family life.
The data encoded by the parents are subjective, but we do not distinguish the data on a child according to the parent. However, the quality of life data will be distinguished based on the parent who provided the rating. Thus, we will include 100 patients and more than 100 parents reporting on quality of life. The analysis will be performed in two stages: (1) a longitudinal data analysis of each group ( parents and children) and (  2 ) multivariate analyses on the relationships between variables specific to the parents and variables specific to the children.
Safety issues Protection of personal data is a very important issue with very restrictive regulations in France and Europe. Therefore, to obtain approval from the National Center for Informatics and Liberty (CNIL, http://www. cnil. fr), we have designed a secure pathway of data handling. Data will be stored in the application on the parents' smartphones and will be inaccessible by unauthorised people (an individual code will be required on application opening). In particular, there is no internet connection needed to run the application. As part of the research, and after considering the opinion of the CNIL, families included in this study will transmit these data to the investigators using a strict, secure, five-step process: 1. Encryption of data in the smartphone of the participant (in-app coding) with a 16-digit encryption key+a personal temporary code for access to data, 2.
Acknowledgements The authors would like to acknowledge  Julien Gachot  and  Matthieu Milliot , from  IVORY HEALTHCARE  for the development of the SMARTAUTISM App. Contributors OB, DB, PD and AD were involved in the conception and design of the study. OB drafted the article, DB, PD and AD revised it critically for important intellectual content. The figures were prepared by AD and OB. OB, DB, AD and PD were involved in the conception of the smartphone application. All authors gave final approval of the version to be published. Funding  Institut de Recherche en Epidémiologie et Santé Publique. Caisse Nationale de Solidarité pour l'Autonomie. Centre Ressource Autisme des Pays de la Loire.
The certificate is digitally signed by a CA. The user's browser is pre-configured to accept certificates from certain known CAs. A typical installation of Firefox has about 100 root certificates in its database. Unfortunately, numerous problems with the current CA model have been identified. Firstly, CAs must be assumed to be trustworthy. If a CA is dishonest or compromised, it may issue certificates asserting the authenticity of fake keys; those keys could be created by an attacker or by the CA itself. Secondly, the assumption of honesty does not scale up very well. As already mentioned, a browser typically has hundreds of CAs registered in it, and the user cannot be expected to have evaluated the trustworthiness and security of all of them. This fact has been exploited by attackers  [1, 2, 3, 4, 5, 6].
OVERVIEW OF DTKI Distributed Transparent Key Infrastructure (DTKI) is an infrastructure for managing keys and certificates on the web in a way which is transparent, minimises oligopoly, and allows verification of the behaviour of trusted parties. In DTKI, we mainly have the following agents: Certificate log maintainers (CLM): A CLM maintains a database of all valid and invalid (e. g. expired or revoked) certificates for a particular set of domains for which it is responsible. It commits to digests of its log, and provides efficient proofs of presence and absence of certificates in the log. CLMs behave transparently and their actions can be verified. A mapping log maintainer (MLM): To minimise oligopoly, DTKI does not fix the set of certificate logs. The MLM maintains association between certificate logs and the domains they are responsible for.
DISCUSSION Responding to incorrect proofs How should the browser (and the user) respond if a received proof (e. g. , a proof of presence in the log) is incorrect? Such situations should be handled in the background by the software in the browser that verifies proofs, and be sent to domain owners for further investigation. The browser can also present errors to the user in the same way as the current state of the art. So, the user interface will remain the same. For example, a user might be shown two options, i. e. either to continue anyway, or not to trust the certificate and abort this connection. Another possible way is to hard fail if the verification has not been successful, as suggested by Google certificate transparency. However, this might be an obstacle for deploying DTKI in early stages.
The blooming of different cloud data management infrastructures has turned multistore systems to a major topic in the nowadays cloud landscape. In this paper, we give an overview of the design of a Cloud Multidatastore Query Language (CloudMdsQL), and the implementation of its query engine. CloudMdsQL is a functional SQL-like language, capable of querying multiple heterogeneous data stores (relational, NoSQL, HDFS) within a single query that can contain embedded invocations to each data store's native query interface. The major innovation is that a CloudMdsQL query can exploit the full power of local data stores, by simply allowing some local data store native queries (e. g. a breadth-first search query against a graph database) to be called as functions, and at the same time be optimized.