dataesr/scientific-paragraphs-categorization huggingface dataset:
A reanalysis dataset for the solar wind would be invaluable for connecting remote solar observations with in situ solar-wind observations. This is a key goal of the Parker Solar Probe (PSP,  Fox et al. , 2016)  and Solar Orbiter  (Müller et al. , 2013)  missions, which seek to understand how the solar wind is formed. Recently, we have demonstrated some of the challenges to routine assimilation of in situ solar-wind observations with three-dimensional magnetohydrodynamic (MHD) models of the solar wind  (Lang et al. , 2017). In addition to the sparse spatial sampling and highly localised information provided by in situ observations, the supersonic solar-wind flow means any local improvements to the model state imposed by, e. g. near-Earth observations, are quickly lost from the system as they are never propagated to < 1 AU.
In situ 1-AU Solar Wind Observations In this study, we use in situ solar-wind radial speed (V R ) observations from two heliospheric positions; at the L1 point just upstream of Earth using data from the Deep Space Climate Observatory (DSCOVR) spacecraft as part of the Omni dataset  (King and Papitashvili, 2005)  and at the position of the Solar Terrestrial Relations Observatory (STEREO) Ahead spacecraft (hereafter, STA)  (Kaiser, 2005) , which was at a radial distance of 0. 96 AU and was approximately 102 • behind Earth in its orbit during  Carrington rotation 2210 (27 Oct. to 23 Nov. 2018). Hourly V R data are averaged to approximately 5-hour cadence to match the 128 equally-spaced Carrington longitudinal bins used in the MHD model described in Section 3. For convenience, in the remainder of the study we refer to the heliocentric distances of L1 and STA as 1 AU, though values are extracted from the models at the exact radial positions.
Acknowledgements Work was part-funded by  Science and Technology Facilities Council (STFC)  grant numbers  ST/M000885/1  and  ST/R000921/1 , and  Natural Environment Research Council (NERC)  grant number  NE/P016928/1. David Stansby is supported by  STFC  grant  ST/N000692/1. PR gratefully acknowledges support from  NASA  ( 80NSSC18K0100  and  NNX16AG86G ) and  NOAA  ( NA18NWS4680081 ). The heliospheric MAS solutions used in this study can be visualised at http://www. predsci. com/mhdweb/plot_2d. php and downloaded at http://www. predsci. com/mhdweb/data_access. php. We are grateful for the availability of HMI magnetograms (from http://hmi. stanford. edu/),and DSCOVR/STEREO in situ observations (from https://cdaweb. gsfc. nasa. gov/index. html/).
Research Methods Tema is a typical major Ghanaian city that is privy to and epitomizes an urban setting. It articulates the deepened prong of age reduction among the populace, including workers vis-àvis retirement planning. This study is a part of a larger Doctor of Philosophy degree project in which the explanatory sequential mixed methods strategy was employed. Using a three-phase approach comprising first qualitative, second quantitative, and third qualitative phases, the study gathered both qualitative and quantitative data collected between mid-2016 and early 2017. The second phase ascertained workers' specific views on age reduction and the prospect of retirement planning as its remedy. As a result, the following hypotheses were explored: (1) there is a relationship between retirement planning and remedying the issue of age reduction or cheating; and (2) there is an association between retirement age and age reduction or cheating.
Data Collection Institutional Review Board (IRB) approval was attained by the researcher from the University of Ghana. Confidentiality and anonymity were ensured. A questionnaire was used in the process of data collection. The administration of this questionnaire took the form of face-to-face interviews to eliminate the situation of unreturned questionnairesthe main strategies for finding appropriate respondents comprised of contacting key players in different organizations. Initially, the researcher reminded participants about the aims of the study and that the discussion would be used to suggest future directions. The survey interviews were designed to gain an understanding of the connection between age reduction and retirement planning. Face-to-face interviews were used in gathering data.
Data Analysis The answered questionnaire were cleaned and serialized for easy identification. The survey data were entered into the Statistical Package for Social Science (SPSS) and were analyzed with selected descriptive statistics, namely frequencies, percentages, Chi-square statistics, and Cramer's V test. Utilizing a 2 tailed test at 5% level of significance, the data were subjected to Pearson Chi-square statistics and Cramer's V test for purposes of ascertaining the relationship between retirement planning and remedying the issue of age reduction or cheating on one hand; and on the other, the association between retirement age and age reduction or cheating.
Methods and Data Analysis The research project began with some concerns and questions about older adults' needs in contemporary Ghana. The study used quantitative and qualitative datasets to investigate the social care needs of older people, while the questionnaire survey provided the necessary data for the development of an understanding of Ghana's older adults' repertoire of care needs. The qualitative (key) interview data provided an explication of questionnaire-based issues. A total of 131 respondents were selected as adequate for the study. The proportion of individuals in the present sample reflects those of the population aged 15+ in Accra, using the mixed methods approach. This composition of the study sample was utilized because younger generations live with and participate in the care of older people in their respective residences and thus have knowledge of their needs inasmuch as the older adults themselves do.
The questionnaire was tested on a small sample of 30 individuals following the guidelines of  (Perneger, Courvoisier, Hudelson, and Gayet-Ageron, 2015). Subsequently, a pilot test among the intended respondents was undertaken. The survey questionnaire instrument's reliability was ensured in diverse ways, namely, facilitation by clear instructions and wording of questions. The questionnaire contained standardized instructions, namely, "please tick where appropriate. " Also, trait sources of error were minimized through interviewing respondents at their convenience. The validity of the survey data was attained following  Nardi's (2006)  guidelines. The validity of the data was obtained from face-to-face interviews. The administration of the questionnaire took the form of face-to-face interviews, including self-administration.
Data Analysis Methodological triangulation was deployed to include the combination of methods to understand and explain  (Greenstein, Roberts and Sitas, 2003)  the social care needs of older adults. The answered questionnaire were cleaned and serialized for easy identification. A data entry template for the quantitative data was developed in the Statistical Package for Social Science (SPSS). Subsequently, the responses were entered into SPSS and were analyzed with selected descriptive statistics, namely frequencies and percentages. Analysis of the qualitative data was undertaken along with six distinct steps. The first step involved the transcription of interviews, with the majority done alongside data collection (Bryman 2008). The second step entailed reading through all the data in order to obtain a general sense of the information; reflect on its overall meaning; ascertain the general ideas emanating from the participants (Creswell 2009).
Literature Review Under the circumstances of the convergence of factors such as before getting rich and before getting old, urban-rural dual structure, family miniaturization, and empty nest trend  (Yu, Liu, 2013 , Feng, Nie, 2016) , ageing is showing the characteristics of large base, fast growth and apparent ageing trend, which poses a severe challenge to the current the elderly care policies in China  (Wang, Zhang, 2013). At present, research on the elderly care policies have entered the up more than 7% of the total population, it is called an ageing society. If it is over 14%, it is called an aged society, and if it is over 21%, it is called a super-aged society. The older people in this chapter refer to those over 60 years of age stipulated by Chinese law. substantive stage, and there are 2115 articles on the elderly care policies and the elderly care security in China Academic Journals full-text database (CNKI) from 2005 to 2016  (Wu, Tang, 2018) , which have achieved fruitful research achievements.
It is, of course somewhat more complicated to operate such a system than the realized PAYG system because more data needs to be kept on file, not just the contribution payments and service period. Questions are also raised in relation to the fair level of contributions, the extent of the contribution payment period, and based on what principled should the paid contributions be distributed between old parents/guardians. These are problems that can be solved, however, and it is still possible to determine general principles today that grasp the essence of the system and do not consider less important individual details. Furthermore, such a system is capable of operating for a long time such that it begins with generous estimates, and the details are continuously refined, parallel to the collection and processing of the required data.
Data collection Distress calls were collected in all-occurrence fashion  (Altmann 1974). Given their clear acoustic differences with other infant vocalizations (grunts, barks) and despite their acoustical variability, distress calls can be clearly identified by trained listeners due to their short, tonal, and sequential production pattern (see SI Supplementary Figure  1  for a spectrogram and SI for video and audio examples). Call episodes were video-recorded using a Panasonic HC X909/V700 video-camera, with the sound captured by a Sennheiser MKE-400 shotgun microphone. To account for any missing information in the videos, AUTHOR1 recorded all potential causes of infant calls, the reactions of the mother, and the distance between them. In our study, the infants' perceived needs were classified according to their situation and problems (see SI Supplementary Table  2 ).
Quantification and statistical analysis Acoustic analysis was performed with Matlab (Mathworks Inc. , Natick, MA, USA) and contained the following steps: (1) call extraction, (2) features extraction, (3) feature selection, (4) call classification, and (5) feature evaluation. Call extraction We first pre-processed the raw audio files by applying a band pass filter from 100 to 700 Hz and filtering out background noise using a Vuvuzela denoising algorithm  (Boll 1979; Ephraim and Malah 1984). Distress calls can grade beyond a frequency of 750 Hz but this was the maximal value of the peak fundamental frequency at mid-call of the first distress call of the series we collected. This pass band was, therefore, appropriate for the localization of calls and to avoid false positives. We used a voice-activity detection (VAD) algorithm to read out vocalization on-and offsets.
Call classification For the classification of calls, we implemented support vector machines (SVMs) using the LIBSVM toolbox  (Chang and Lin 2011). Classification routines consisted of training and testing phases: First, separate training samples (i. e. feature vectors of extracted calls) were labelled with an attribute (e. g. Situation A = 0, Situation B = 1) and used to build a model of support vectors that optimally separate the two classes. Testing samples without attribute labels were then used to measure the model's performance to generalize for novel samples. We used a radial basis function (RBF) kernel and 5-fold cross-validated the parameters C and gamma with separate smaller data sets (see  (Fedurek et al. 2016)  for details on the procedure). Training was performed on 80% of the data samples, testing with the remaining 20%.
Acknowledgments We thank the  Ugandan Widlife Authority (UWA)  and the  Ugandan National Council for Science and Technology (UNCST)  for permission to conduct the study,  Geoffrey Muhanguzi ,  Caroline Asiimwe ,  Sam Adue  and  Monday M'Botella  for their support in the field. We are grateful to the  Royal Zoological Society of Scotland  for providing core funding to the  Budongo Conservation Field Station. This research was supported by a  Fyssen fellowship  awarded to GD, funding from the  European Union 's  Seventh Framework Programme for research, technological development and demonstration  (grant agreement no  283871 ), and the  Swiss National Science Foundation  ( PZ00P3_154741 ) awarded to CDD.
However, in order to gain a deeper understanding on the photochemical mechanisms, it would be necessary to understand the role of the higher ESs. This lack of information has motivated the development of the new formalism presented in this article to compare different ES of TMC (or any other chemical system). This formalism has been implemented in an external tool which interfaces with the GAUSSIAN quantum package so that TMC ES optimizations can be performed. Although the overlap  [41] [42] [43] [44] [45]  and the NTOs  [46]  are used in many other quantum chemistry applications, to the best of our knowledge, this approach addressing the ES optimization issue by combining these simple concepts has never been tested to date. This article is organized as follows: In Theoretical Background section, a general overview of the new method and a detailed description of the algorithm behind the external tool developed are given.
Theoretical Background In order to perform ES tracking optimizations an in-house code named "Steepest Descent minimization using Natural Transition Orbitals" (SDNTO) has been developed. The code is written in Fortran90 and acts as an external tool, perfectly interfaced with the GAUSSIAN quantum package. Thanks to this program, it is possible to perform an ES minimization by means of a steepest descent algorithm,  [47]  following an ES characterized by a specific electronic arrangement (diabatic state). For convenience, this state will be considered as the reference state (RS). The SDNTO code calls GAUSSIAN at every step to perform a vertical ES calculation in order to obtain the excitation energies and the coefficients of the NTOs  [46]  for all of the considered transitions. In addition, it requires the calculation of the gradient of the ES of interest.
The S NTO has been defined as the pure overlap between pairs of NTOs weighted by the populations of the RS (holes and particles are analyzed independently). The orbitals, whose eigenvalue is below a given threshold, are neglected. By virtue of the overlap function S NTO , it is possible to keep track of an ES with the same electronic nature along the whole minimization procedure. It is worth noticing that two different types of overlap S NTO are available in the SDNTO code: the module of the integral eq. (  1 ) and the integral of the module eq. (  2 ). Both formulations avoid possible problems with the phase alignment of the wave functions involved. Furthermore, with the SDNTO program it is possible to compute the overlap using either two different molecular geometries (step n and step n+1) or only the geometry of step n.
In the latter case, all NTOs are centered on the "initial" geometry of the step n, that is, imposing x n+1 to be equal to x n. In the former case, the corresponding geometries computed at step n and n+1 are used. The flowchart describing the algorithm implemented in the SDNTO code is represented in Figure  1. The basic algorithm is composed as it follows: Step 1: The initial GAUSSIAN input file is given as an input to the SDNTO program. All options for a vertical TD-DFT calculation are directly read from this initial input file, and subsequently used at each step of the SDNTO optimization. The RS is initially read with the rest of the options and it is updated at each step. Step 2: At each optimization step n, a vertical TD-DFT calculation is performed in order to recover the energy (E n RS ), gradient (rE n RS ) and the NTOs of the RS.
The state with the larger S NTO value becomes the new RS. Clearly, a sufficient number of states should be kept during the optimization in order to allow a significant matching. Step 6: The SDNTO program checks whether the energy of the RS at step n+1 is greater than the one computed at step n. If so, α is halved. If the new α value is lower than a given threshold (β) the procedure stops, otherwise the program restarts the loop from step 3. Step 7: Once the energy has decreased, if the position of the RS among all the ESs at the optimization step n+1 is different than the one at optimization step n, then a supplementary SP TD-DFT calculation needs to be done in order to compute the energy gradient rE n RS of the correct RS at the new geometry x n+1. Step 8: The SDNTO program checks whether the maximum gradient associated to the new RS is lower than a given threshold (γ).
If so, the procedure stops and the optimization can be considered as finished, otherwise it restarts the loop from step 3. Overall, the SDNTO code computes, at each step, the overlap among the NTOs of the RS (computed in the previous step n) and the NTOs of all the other ESs (computed at step n+1). The state with the greater overlap will be the new RS. Once the new RS has been found, its gradient is computed. Finally, the new coordinates at step n+1 are generated following the steepest descent of the gradient. A constant α that multiplies the force is used in order to control the step size.
" The BS2 basis set has proven to be good enough to recover the main character of the brightest state, within the range from 300 to 500 nm, reported in Ref. 27 and yield a similar excitation energy (302. 5 nm). At the end of all the ES geometry optimizations performed with GAUSSIAN or with SDNTO, vibrational frequency analysis were performed at the same level of theory, in order to verify the nature of the stationary points. Cartesian coordinates and energies of all the optimized stationary points can be found in Tables S1-S7, Supporting Information. In the ES optimizations performed with the SDNTO program the convergence threshold for the maximum gradient (γ) and the threshold for the NTOs selection have been set to 4. 5 × 10 -4 Hartrees/Bohr and 0. 3, respectively. These parameters have been used for both systems, the cytosine molecule and the cis-(Cl,Cl)[RuCl 2 (NO)(tpy)] + complex.
In all calculations, eq. (  1 ) was used to compute the S NTO. Likewise, the steepest descent algorithm as implemented in the GAUSSIAN quantum package has been used for all the ES optimizations performed with this program. The maximum size for the steepest descent steps has been set to 0. 01 Bohr. For all these GAUSSIAN ES optimizations, the maximum gradient and the threshold for the maximum displacement have been set to 4. 5 × 10 -4 Hartrees/ Bohr and 1. 8 × 10 -3 Bohr, respectively.
Taking this mechanism into account, we have performed a state-tracking geometry optimization of both ESs, using both the standard approach implemented in the GAUSSIAN quantum package and the SDNTO code. First, we discuss the optimization of the π ! π * state as it is the RS for the first optimization. In Figure  3 , the relative energies of the first two ESs (green circles and red triangles) and the energy of the RS (black line), computed along the minimization procedure, are reported. The NTOs computed at the FC geometry and after the S 1 /S 2 crossing point are also depicted in Figure  3. For this transition, we have reported only the NTOs that have a contribution greater than 0. 3. This particular transition is characterized by a single pair of hole-particle orbitals. Obviously, at the beginning of the minimization (first step), the RS is the first ES.
It remains the first state up to the fifth step, at the next point SDNTO changes the RS: it becomes the second transition (see the black line of Fig. 3 ). If we take a look at the NTOs of the second ES, computed at the ninth step (few steps further from the crossing point), we can see that the program correctly follows the same electronic state, since the transition is always characterized by the same pair of π ! π * orbitals. From here on, the π ! π * state becomes higher in energy compared to the n ! π * one: the ES ordering changes. Once the crossing has taken place, the π ! π * transition remains the second one up to the end of the minimization. Second, we analyze the optimization of the n ! π * state. Even in this case, SDNTO is able to track the right state during the optimization procedure (see Fig.
Video content is responsible for more than 70% of the global IP traffic. Consequently, it is important for content delivery infrastructures to rapidly detect and respond to changes in content popularity dynamics. In this paper, we propose the employment of on-line change point (CP) analysis to implement real-time, autonomous and low-complexity video content popularity detection. Our proposal, denoted as realtime change point detector (RCPD), estimates the existence, the number and the direction of changes on the average number of video visits by combining: (i) off-line and on-line CP detection algorithms; (ii) an improved time-series segmentation heuristic for the reliable detection of multiple CPs; and (iii) two algorithms for the identification of the direction of changes. The proposed detector is validated against synthetic data, as well as a large database of real YouTube video visits.
In this work, to address the aforementioned shortcomings of the commonly employed prediction algorithms, we propose a corresponding detector, referred to as the "real-time change point detector" (RCPD). The RCPD is compatible with modern, flexible networking and cloud approaches, that are highly adaptive and can respond to short-term network dynamics. With accurate, on-line content popularity detection, discrepancies between inaccurate predictions and actual changes can be alleviated. The RCPD is real-time, lightweight, accurate and is parameterized autonomously by analyzing historical data. In the RCPD, we employ the change point (CP) detection theory and algorithms; their suitability is confirmed against a large number of synthetic as well as real YouTube video datasets. In this contribution, the early detection of changes in the average content popularity is addressed with a novel CP detection methodology, consisting of a training phase, using historical data, and, an on-line phase.
Furthermore, our tests on real YouTube content views datasets show that: • YouTube video views match the underlying assumptions of the RCPD, i. e. , the content popularity time-series datasets can be modeled as t-dependent. • The RCPD can detect CPs in more than 70% of the videos in our dataset, implying a sufficiently high number of content popularity changes and the suitability of the CP theory framework for content popularity detection. • The successful CP direction identifications exceed 91%, i. e. , the proposed trend indicators work for real data. • The average dynamic time warping (DTW) distance  [12] ,  [13]  between the identified CPs and a benchmark offline algorithm was estimated to be 52 time instances on average, showcasing the rapid responsiveness of the RCPD. • The overall processing cost of the RCPD is very low; notably, it took less than one second to process 882 videos on a typical personal computer (PC).