dataesr/scientific-paragraphs-categorization huggingface dataset:
In both cases BlockIP outperforms the CPLEX available LP methods. It is worth noting that BlockIP uses an out-of-date sparse linear algebra package for the Cholesky factorization  [24] , while CPLEX implements highly tuned state-of-the-art factorization routines. Therefore, the performance of BlockIP could be significantly improved by the use of a more Table  7  Average principal angles between the subspaces generated by the columns of L ⊤ and N ⊤ , for each instance of multi-commodity network flow problems with nodal capacities in Tables  3, 4 , 5 and 6. n average principal angles Table  3  Table  4  Table  5   recent Cholesky solver. The information of the average principal angles between the subspaces generated by the columns of L ⊤ and N ⊤ of the instances of Tables 3-6 is reported in Table  7 , differentiating for the 150 and 300 nodes instances.
Articles reporting about specimens collected as larvae that were subsequently grown in insectaries were not included in the analysis to avoid biases due to rearing in artificial conditions. As the status and nomenclature of the taxonomic subdivisions within An. gambiae s. s. have changed, we chose to classify results from articles that did not distinguish between the M and S molecular forms of An. gambiae s. s. (e. g. , all those published before 2001) as An. gambiae (Giles), and results from studies referring to the M and S forms as An. coluzzii and An. gambiae s. s. , respectively. When only the chromosomal form-not the molecular form-was defined, results were classified as An. gambiae (Giles) as the taxonomic subdivisions within each of these two classification systems do not coincide. Four data sets were assembled, two sets to study the prevalence of An.
We have assessed the degree of assortative mating from indices of pair sexual isolation (I PSI ) using the software JMATING  (Carvajal-Rodriguez & Rolan-Alvarez, 2006). I PSI is a safe estimator of sexual isolation for field samples, as it is not affected by small variances across different scenarios of frequencies of the taxa considered, nor by mate propensity, that is the intrinsic tendency for some individuals/populations/taxa to mate more frequently than others  (Pérez-Figueroa, Cruz, Carvajal-Rodríguez, Rolán-Alvarez, & Caballero, 2005). Mean bootstrap values, standard deviations and two-tail probabilities for rejecting the null hypothesis (I PSI = 0, i. e. , random mating) were calculated by bootstrap (100,000 resamplings, also for premating frequencies). If two taxa mate partially at random, the frequency of homogamous mating depends on the probability of meeting between sexes of the same taxon.
| Spatial and temporal patterns of hybridization in a "contact zone" We exploited the large data set available along an urbanization gradient in the capital of Cameroon-Yaoundé  (Kamdem et al. , 2012) , to analyse in more detail the spatial and temporal distribution of An. coluzzii × gambiae s. s. larval and adult hybrids. The aim was to investigate whether hybridization clustered in space and/or time at a microgeographical scale, according to the relative frequency and population dynamics of the parental species. This area falls out of the geographical distribution range of An. arabiensis, so hybrids resulting from hybridization with this species could not be observed. (Bartels, 1982)  using the R package lawstat  (Hui, Gel, & Gastwirth, 2008).
| Frequency of hybrids at a regional scale in populations from Burkina Faso and Cameroon Similarly, we aimed to investigate how the spatial distribution of hybridization relates to the relative frequency of the parental species at a larger (regional) spatial scale using extensive data sets collected in Burkina Faso and Cameroon during independent surveys performed between 2005 and 2012 in about 600 localities sampled within the framework of several research projects. Mosquitoes were collected by any of two methods (indoor-resting adult females caught by insecticide spray-sheet collections, and larvae by dipping), identified morphologically as An. gambiae s. l. and preserved in microtubes containing either a desiccant (silica gel) or 70% ethanol. Molecular identification of individual specimens was performed using one of several possible diagnostic PCR protocols  (Fanello et al.
This is ⟨A × B⟩ i ∼ Binomial(⟨A + B + A × B⟩ i ,h i ) , where A and B represent the absolute frequencies of the parental species. The models assume that the logarithm of the odds of the probability of hybridization h i is a linear function of the relative frequency of the parental taxa p i in each locality, that is: log e (h i ∕(1 -h i )) = α+ϕ(p i ) + , where ϕ is a nonparametric smoothed function, and ε represent the sampling error. We estimated h i and p i from the sample estimates ĥi = ⟨A × B⟩ i ∕⟨A + B + A × B⟩ i and pi = ⟨A⟩ i ∕⟨A + B⟩ i. Because hybridization in these regions is rare, we did not take into account the frequency of hybrids in the denominator of pi. We fitted GAM with the R package mgcv  (Wood, 2006) , specifying a binomial error structure and a logit link function. This approach has the added benefit of weighing each locality by its sample size.
The parameters s and s* of the H-W model provide measures of the "strength" of reproductive isolation independent of the local frequency of the parental taxa, thereby allowing more meaningful comparisons of reproductive isolation across locales. We estimated the parameters s and s* by fitting nonlinear weighted least-squares regressions to the observed frequency of heterogamous mating or hybrids in a population, according to the equations h = 2s (p -p 2 ) or h = 2s* (p -p 2 ) using the function nls in R. We used different data sets to estimate s and s*. Estimates of premating isolation (s) and hybridization (s*) were calculated from the frequency of heterogamous insemination and prevalence of hybrids in either adult or larval populations from Burkina Faso and Cameroon, except for An. arabiensis × An.
A value of 0 suggests that the two species do not share resources (max ecological divergence), while 1 indicates complete overlap (no ecological divergence). Here, we assume that species use all resources proportionally to their relative frequency in each locality. Thus, p ji and p ki were estimated by the relative proportion of each species (An. arabiensis, An. coluzzii, An. gambiae s. s. ) and their hybrids (An. arabiensis × coluzzii, An. arabiensis × gambiae s. s. , An. coluzzii × gambiae s. s. ) co-occurring in areas of sympatry. This assumption is obviously an approximation; accordingly, the index is intended mostly as a proxy resuming the ecological niche of these species based on a global assessment of resource use. The data used for the calculation of the index come from the systematic literature review and original data from the surveys in Burkina Faso and Cameroon.
We have found no such studies from the systematic literature review, but have original data from two independent surveys, one each in Burkina Faso and Cameroon. In Burkina Faso, larvae and adult An. gambiae s. l. were collected in parallel during September-October 2000 from the village of Goundry, about 35 km north-east of the capital Ouagadougou. Overall, 76 larval habitats and 89 human dwellings were sampled across an area of ~4 km 2. In Cameroon, parallel larval and adult collections were carried out along an 18-km urbanization gradient in Yaoundé.
| RESULTS We examined reproductive isolation among An. coluzzii, An. gambiae s. s. and An. arabiensis with a multipronged approach, taking as indicator of hybrid genotypes the heterozygous patterns of species-specific diagnostic markers in the pericentric region of chromosome-X  (Fanello et al. , 2003; Favia et al. , 2001; Santolamazza et al. , 2008). First, we performed a systematic review and meta-analysis of published surveys reporting on hybrid prevalence, which overall showed strong reproductive isolation at a continental scale despite geographically restricted exceptions. Second, we exploited our own extensive field data sets collected at a regional scale in two contrasting environmental settings, that is in the arid savannah of Burkina Faso in West Africa, and in the moist rainforest of Cameroon in Central Africa, to analyse: (i) levels of premating isolation in the species triplet; (ii) the spatio/ temporal and frequency-dependent dynamics of hybridization, (iii) the relationship between postmating isolation and ecological divergence and (iv) hybrid viability penalty.
| Hybrid prevalence at a continental scale To assess the level of hybridization among An. coluzzii, An. gambiae s. s. and An. arabiensis in the African continent, we performed a systematic review of field studies reporting the occurrence and frequency of populations in sympatry that were published between 1964 and March 2013. Table  1  summarizes the results of the meta-analyses based on 99 studies (retrieved from 94 published articles, Appendix S2) that satisfied the inclusion criteria, and whose ancillary data are collated in Tables  S1-S4. The analyses pertaining to adult hybrids covered 25 countries with a total of ~135,000 and ~20,000 specimens identified to investigate rates of hybridization between An. arabiensis and An. gambiae (Giles), or An. coluzzii and An. gambiae s. s. , respectively.
| Postmating isolation and ecological divergence at regional scales First, we have performed a systematic review and meta-analysis of published surveys reporting on hybrids prevalence, which has also served to evaluate the variability and strength of reproductive isolation at a continental scale. Then, we have analysed our own field data sets collected at a regional scale in two contrasting environmental settings, that is in the arid savannah of Burkina Faso in West Africa, and in the rainforest of Cameroon in Central Africa. In this way, we have gathered the most exhaustive data set to date of hybrids occurrence and frequency in this species triplet, which has facilitated comparisons of the expected prevalence of hybrids in locales where we also obtained field measures of interspecific mating events.
Introduction Three Dimensional printing technology has made a breakthrough in recent years as many applications are being developed based around it. The ability to design a digital concept and physically print the results of that concept is a promising technology that will only become more commonplace as it continues to be refined  [1]. The combination of both technologies, 3D reconstruction and 3D printing, into a general 3D copy machine bears an enormous economical potential for the future  [2]. In paper  [3] , authors proposed that for obtaining a full human body scan with good quality, three camera sensors must be used. In their work, two of these sensors were used to record the raw data for the upper and lower parts of the body while ensuring that the areas of scanning for the different sensors do not overlap in order to avoid complications in registering process.
In paper  [6] , a human body reconstruction method depending on a noisy monocular image and range data acquired using Microsoft Kinect sensor is proposed. The 3D shape is estimated by integrating multiple monocular views of a human subject moving in front of the camera sensor. To solve the problem related to varying body pose, authors use a SCAPE body model which expresses the 3D body shape in different mathematical quantities and detect the variations occurring. Further, they explain a novel method to reduce the distance between the projected 3D body contour and the image silhouette which depends on analytic derivatives of the objective function. They suggest a simple approach to estimate body measurements from the recovered SCAPE model and then they calculate the accuracy of the method they used in their approach to prove that it is competitive compared to the commercial body scanning systems available in the market.
To this date, there are several softwares already available that can take 3D scans and export models for 3D printing using various types of sensors and various algorithms to get to the end results. Softwares such 'ReconstructMe', 'Skanect', 'Microsoft 3D Scan' uses Kinect as their primary sensor. Hence, we will be making a product similar to them. Furthermore, the target of this research work was to develop something as close to Skanect. The main motivation of this work was to develop a total low-cost system for 3D scanning. Using open source libraries allows our complete software to be free of charge to the consumers and the use of cheap sensors makes the whole system cost effective. To make the system even more easy to use, integration was done with a lowcost turntable to finally output a total low-cost end-to-end solution for 3D scanning.
Compared to other available software, most require a purchase and either expensive sensors or expensive turntables to output and print scans. In this work, an end-to-end 3D reconstruction software was developed using Kinect and Point Cloud Library (PCL) for scanning, reconstructing and exporting a 3D model of any object into a 3D printer. First, a brief introduction to 3D reconstruction and an explanation of the depth measuring technology utilized by the Kinect v2. 0 is given. This project is based on open source libraries and frameworks, thus, a presentation of the tools and libraries utilized during the design of the software is provided. The main library used for this project is the Point Cloud Library (PCL). Being an open source library, free for commercial use and with wide contents of online documentation, PCL is one of the key core elements for the development of this project.
Open NI 2. 0 The OpenNI 2. 0 Application Programming Interface (API) provides access to PrimeSense compatible depth sensors. It allows an application to initialize a sensor and receive depth, RGB, and IR video streams from the device. It provides a single unified interface to sensors and. ONI recording created with depth sensors. OpenNI also provides a uniform interface that third party middleware developers can use to interface with depth sensors. Applications are then able to make use of both the third party middleware, as well as underlying basic depth and video data provided directly by OpenNI.
Point Cloud Library (PCL) PCL is an open source project for point cloud processing written in C++. It is aimed to be a cross platform library which is why it can be successfully compiled and deployed on Linux, Windows, MacOS and Android  [14]. The PCL framework contains numerous state of the art algorithms for point cloud processing, including filtering, feature estimation, surface reconstruction, registration, model fitting and segmentation. These algorithms can be used, for example, to filter outliers from noisy data, stitch 3D point clouds together, segment relevant parts of a scene, extract key points and compute descriptors to recognize objects based on their geometric appearance, create surfaces from point clouds and visualize them  [19]. Since PCL provides all required functionality from the data acquisition to the surface creation and because it is free for commercial and research use, it was the selected library for the implementation of this project.
The idea was to use a simple twist board, as the twist board is already designed to support a person. A twist board is basically a round platform which rotates all the way to 360 degrees and it is used mainly for exercising purpose. The existing twist board was modified so a belt can be used to rotate it. For powering this twist board, a 12 V high torque 8 RPM DC gear motor was used. To control the motor, a L298N dual motor controller module was used. An industrial size belt was used to convey power from the motor to the twist board. Since the idea was to introduce an automated system that is user-friendly and can fully communicate with the software, we opted to use Arduino Microcontroller for controlling the motor from the finished software. Serial communication was used to talk back with the Arduino using our software.
3. For a measure of safety, an extra condition was set, that is when our software 4. An additional reset button is included to reset the turntable to its starting position. The function for capturing point cloud and rotating the turntable is integrated so they can work together hence meaning a full automation of grabbing point cloud data is achieved. In the acquisition part of the software, a 'timer' was used as a measure of control for the increments taken by the turn table. After every 1. 8 seconds, '0' was sent to the Arduino to stop the turntable. A point cloud of that frame was taken and then again a '1' was passed to turn on the turntable for 1. 8 seconds again. This way point clouds were taken at every 1. 8 second increments until a full 360 degrees of point cloud was obtained. Considering the speed of the motor, for every 1.
Overview of Graphical User Interface (GUI) For the software designed in this paper, a simple GUI was designed for ease of use. The GUI allows the user to take scans, enter parameters, generate 3D models, and also view previously made 3D models. QT does not have a widget dedicated to displaying point clouds. Therefore, Visualization Toolkit (VTK) was integrated with QT to display point clouds and mesh files. The GUI designed has different sets of windows which allow user to visualize and set the pass through filter window using sliders, it allows a user to register the set of point clouds under the models name, and finally it allows to reconstruct the point cloud to a final model using two techniques as preferred by the user. The different windows of the GUI are shown in Figure  3. 2. 1.
Statistical Outlier Removal Filter (SOR) Measurement errors cause sparsing outliers which destroy the results of scanning. This makes the estimation of the PCL characteristics like surface normal. It is also leading to erroneous values which might cause registration failures. These issues can be managed by applying a statistical analysis on each point's neighbourhood and removing those which do not meet certain conditions. The SOR (Figure  3. 4. 3) we are applying is based on the computation of the distribution of point to neighbour's distances in the input dataset. For each single point, it computes the mean distance from it to all its neighbours. As the resulted distribution is Gaussian with a mean and a standard deviation-all points whose mean distances are outside an interval defined by the global distances mean and standard deviation can be considered as outliers and trimmed from the dataset.
A tolerance limit is set against the mean and if any point lies outside the limit, the point is considered as an outlier, otherwise it remains. • Once the outliers and noise are removed, the ICP algorithm is performed on the Source and Target point cloud, and the two clouds after transformation are concatenated and then passed as a source for the next iteration. • This way all the point clouds from the set of acquired point clouds from the Kinect are aligned and combined to form a final point cloud for the 3D model. Before the final point cloud is passed over to the next step for Mesh Reconstruction, a series of MLS and LS is performed to further smooth the final point cloud. The parameters of the smoothing functions can be set by the user or the user can use the default values provided by the software.
Results To perform final scans from the Kinect, the turntable was set to turn every 1. 8 seconds, with an increment of approximately 10 degrees. After a full 360 degree rotation is completed, the turntable stops and the Kinect stops taking scans. In total, around 36 point clouds are generated from this process. An important remark to be made is that, although the software achieved its purpose of scanning and performing 3D reconstruction of a person, the final 3D model was lacking some fine details. This was due to the fact that during the scanning, the Kinect was positioned at least one meter away from the person. By increasing the distance between the Kinect and the person, a lot of information was lost and more noise is introduced. When the time to perform the reconstruction came, only a low percentage of data was left to work with.
Conclusion The designed software can successfully scan a person using a low-cost sensor, reconstruct a 3D model from the scans and export it for 3D printing. The source code for the fully developed software can be found in our GitHub repository, www. github. com/tazleef/Software-Engineering-Project. During the implementation of this project, a thorough research was performed in order to narrow down and find the final materials and methodologies which gave us the most optimal result. First of all, we had to decide which library to utilize. For this project, the PCL was chosen as the best option for achieving our goals. Second, as multiple research has been performed with Kinect and PCL, the Kinect v2. 0 was selected as the ideal sensor for the project. Then, for cleaning and filtering the data, a real time pass through filter and a statistical outlier removal was applied.
ACKNOWLEDGMENT This work was a semester project for the software engineering course at  University of Burgundy, France. Authors wish to thank  Katherine Sheran ,  Hassan Saeed ,  Islam Mokhtari ,  Ivan Mikhailov  and  Solene Guillaume  for their contributions to this project including coding and gathering information for the final software. In addition, authors would like to thank warmly  Prof. Fougerolle Yohan  and  PhD. Cansen Jiang  for their supervision and guidance. This work was supported by a grant from  Mr Alexander Hermanns  which made purchasing the camera sensors and the turntable equipment possible for us.
The AMMOS2 protocol employs atomic-level energy minimization of a large number of experimental or modeled protein-ligand complex structures that can be generated via a user-chosen docking program or via virtual screening web servers as e. g. MTiOpenScreen  (12). Two recent web servers, 3Drefine  (16)  and KoBaMIN  (17) , provide refinement of apo protein structures by energy minimization. The AM-MOS2 web server is based on the previously developed standalone software AMMOS (Automatic Molecular Mechanics Optimization for in silico Screening)  (18)  performing Nucleic Acids Research, 2017, Vol. 45, Web Server issue W351 minimization of protein-ligand interactions at five different levels of flexibility of the protein receptor. AMMOS has already been rigorously bench marked for virtual screening purposes  (19).
Output AMMOS2 returns the coordinates of the minimized ligands, the coordinates of the minimized protein-ligand complex and the minimized interaction energies. AMMOS2 provides an interactive page displaying the 100 top ligands ranked by the minimized protein-ligand binding energies, allowing the users to perform additional analysis. Protein-ligand complex structures before and after minimization are visualized in 3D. An image displaying the predicted minimized protein-ligand interactions in the binding site is generated using the PLIP software  (38). The reported interactions include hydrogen bonds, hydrophobic contacts, cation-pi and pi-stacking among others. The user can download the following results: the minimized ligands in mol2 format ranked by the interaction energies, the minimized protein-ligand complex in pdb format, the warning reported during the AMMOS2 minimization, the computed energies and the images and analysis report generated by the PLIP software.