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The CLIC Tracker Detector (CLICTD) is a monolithic pixel sensor. It is fabricated in a 180 nm CMOS imaging process, modified with an additional deep low-dose n-type implant to obtain full lateral depletion. The sensor features a small collection diode, which is essential for achieving a low input capacitance. The CLICTD sensor was designed as a technology demonstrator in the context of the tracking detector studies for the Compact Linear Collider (CLIC). Its design characteristics are of broad interest beyond CLIC, for HL-LHC tracking detector upgrades. It is produced in two different pixel flavours: one with a continuous deep n-type implant, and one with a segmented n-type implant to ensure fast charge collection. The pixel matrix consists of $16\times128$ detection channels measuring $300 \times 30$ microns. Each detection channel is segmented into eight sub-pixels to reduce the amount of digital circuity while maintaining a small collection electrode pitch. This paper presents the characterisation results of the CLICTD sendor in a particle beam. The different pixel flavours are compared in detail by using the simultaneous time-over-threshold and time-of-arrival measurement functionalities. Most notably, a time resolution down to $(5.8 \pm 0.1)$ ns and a spatial resolution down to $(4.6 \pm 0.2)$ microns are measured. The hit detection efficiency is found to be well above 99.7% for thresholds of the order of several hundred electrons.

In recent years, streaming music platforms have become very popular mainly due to the huge number of songs these systems make available to users. This enormous availability means that recommendation mechanisms that help users to select the music they like need to be incorporated. However, developing reliable recommender systems in the music field involves dealing with many problems, some of which are generic and widely studied in the literature, while others are specific to this application domain and are therefore less well-known. This work is focused on two important issues that have not received much attention: managing gray-sheep users and obtaining implicit ratings. The first one is usually addressed by resorting to content information that is often difficult to obtain. The other drawback is related to the sparsity problem that arises when there are obstacles to gather explicit ratings. In this work, the referred shortcomings are addressed by means of a recommendation approach based on the users' streaming sessions. The method is aimed at managing the well-known power-law probability distribution representing the listening behavior of users. This proposal improves the recommendation reliability of collaborative filtering methods while reducing the complexity of the procedures used so far to deal with the gray-sheep problem., Comment: Accepted in Complexity (ISSN: 1099-0526)

In order to achieve the challenging requirements on the CLIC vertex detector, a range of technology options have been considered in recent years. One prominent idea is the use of active sensors implemented in a commercial high-voltage CMOS process, capacitively coupled to hybrid pixel readout chips. Recent results have shown the approach to be feasible, though more detailed studies of the performance of such devices, including simulation, are required. The CLICdp collaboration has developed a number of ASICs as part of its vertex detector R&D programme, and here we present results on the performance of a CCPDv3 active sensor glued to a CLICpix readout chip. Charge collection characteristics and tracking performance have been measured over the full expected angular range of incident particles using 120 GeV/c secondary hadron beams from the CERN SPS. Single hit efficiencies have been observed above 99% in the full range of track incidence angles, down to shallow angles. The single hit resolution has also been observed to be stable over this range, with a resolution around 6 $\mu$m. The measured charge collection characterstics have been compared to simulations carried out using the Sentaurus TCAD finite-element simulation package combined with circuit simulations and parametrisations of the readout chip response. The simulations have also been successfully used to reproduce electric fields, depletion depths and the current-voltage characteristics of the device, and have been further used to make predictions about future device designs.

The Compact Linear Collider (CLIC) is a proposed future high-luminosity linear electron-positron collider operating at three energy stages, with nominal centre-of-mass energies: 380 GeV, 1.5 TeV, and 3 TeV. Its aim is to explore the energy frontier, providing sensitivity to physics beyond the Standard Model (BSM) and precision measurements of Standard Model processes with an emphasis on Higgs boson and top-quark physics. The opportunities for top-quark physics at CLIC are discussed in this paper. The initial stage of operation focuses on top-quark pair production measurements, as well as the search for rare flavour-changing neutral current (FCNC) top-quark decays. It also includes a top-quark pair production threshold scan around 350 GeV which provides a precise measurement of the top-quark mass in a well-defined theoretical framework. At the higher-energy stages, studies are made of top-quark pairs produced in association with other particles. A study of ttH production including the extraction of the top Yukawa coupling is presented as well as a study of vector boson fusion (VBF) production, which gives direct access to high-energy electroweak interactions. Operation above 1 TeV leads to more highly collimated jet environments where dedicated methods are used to analyse the jet constituents. These techniques enable studies of the top-quark pair production, and hence the sensitivity to BSM physics, to be extended to higher energies. This paper also includes phenomenological interpretations that may be performed using the results from the extensive top-quark physics programme at CLIC., Comment: 86 pages, accepted for publication in JHEP

Structural relationships among proteins are important in the study of their evolution as well as in drug design and development. The protein 3D structure has been shown to be effective with respect to classifying proteins. Prior work has shown that the Double Centroid Reduced Representation (DCRR) model is a useful geometric representation for protein structure with respect to visual models, reducing the quantity of modeled information for each amino acid, yet retaining the most important geometrical and chemical features of each: the centroids of the backbone and of the side-chain. DCRR has not yet been applied in the calculation of geometric structural similarity. Meanwhile, multi-dimensional indexing (MDI) of protein structure combines protein structural analysis with distance metrics to facilitate structural similarity queries and is also used for clustering protein structures into related groups. In this respect, the combination of geometric models with MDI has been shown to be effective. Prior work, notably Distance and Density based Protein Indexing (DDPIn), applies MDI to protein models based on the geometry of the CA backbone. DDPIn distance metrics are based on radial and density functions that incorporate spherical-based metrics, and the indices are built from metric tree (M-tree) structures. This work combines DCRR with DDPIn for the development of new DCRR centroid-based metrics: spherical binning distance and inter-centroid spherical distance. The use of DCRR models will provide additional significant structural information via the inclusion of side-chain centroids. Additionally, the newly developed distance metric functions combined with DCRR and M-tree indexing attempt to improve upon the performance of prior work (DDPIn), given the same data set, with respect to both individual k-nearest neighbor (kNN) search queries as well as clustering all proteins in the index., Comment: 48 pages, 8 figures, 6 tables

Cancer Biotherapy (CB), as opposed to cancer chemotherapy, is the use of macromolecular, biological agents instead of organic chemicals or drugs to treat cancer. Biological agents usually have higher selectivity and have less toxic side effects than chemical agents. The I.S.B.T.C., being the only major information database for CB, seems lacking in some crucial information on various cancer biotherapy regimens. It is thus necessary to have a comprehensive curated CB database. The database accessible to cancer patients and also should be a sounding board for scientific ideas by cancer researchers. The database/web server has information about main families of cancer biotherapy regimens to date, namely, Protein Kinase Inhibitors, Ras Pathway Inhibitors, Cell-Cycle Active Agents, MAbs (monoclonal antibodies), ADEPT (Antibody-Directed Enzyme Pro-Drug Therapy), Cytokines, Anti-Angiogenesis Agents, Cancer Vaccines, Cell-based Immunotherapeutics, Gene Therapy, Hematopoietic Growth Factors, Retinoids, and CAAT. For each biotherapy regimen, we will extract the following attributes in populating the database: Cancer type, Gene/s and gene product/s involved, Gene sequence, Organs affected, Reference papers, Clinical phase/stage, Survival rate, Clinical test center locations, Cost, Patient blogs, Researcher blogs, and Future work. The database will be accessible to public through a website and had FAQs for making it understandable to the laymen and discussion page for researchers to express their views and ideas. In addition to information about the biotherapy regimens, the website will link to other biologically significant databases like structural proteomics, metabolomics, glycomics, and lipidomics databases, as well as to news around the world regarding cancer therapy results. The database attributes would be regularly updated for novel attributes as discoveries are made., Comment: 65 pages, 30 figures, 1 table

Based on overall 3D structure, proteins may be grouped into two broad categories, namely, globular proteins (spheroproteins), and elongated or rod-shaped proteins (RSP). The former comprises a significant majority of proteins. This work concerns the second category. Unlike a spheroprotein, an RSP possesses a conspicuous axis along its longest dimension. To take advantage of this symmetry element, we decided to represent RSPs using cylindrical coordinates, (rho, theta, z), with the z-axis as the main axis, and one tip of the protein at the origin. A "tip" is one of two extreme points in the protein lying along the protein axis along its longest dimension. We first identify the two tips, T1 and T2, of the RSP using a protein graphics software, then determine their (Cartesian) coordinates, (h, k, l) and (m, n, o), respectively. Arbitrarily selecting T1 as the tip at the origin, we translate the protein by subtracting (h, k, l) from all structural coordinates. We then find the angle alpha between vector T1-T2 and the positive z-axis by computing the scalar product of vectors T1- T2 and OP where P is an arbitrary point along the positive z-axis. We typically use (0, 0, p) where p is a suitable positive number. Then we compute the cross product of the two vectors to determine the axis about which we should rotate vector T1-T2 to make it coincide with the positive z-axis. We use a matrix form of Rodrigues' formula to do the rotation. We then apply the Cartesian to cylindrical coordinate transformation equations to the system. We have applied the above transformation to 15 RSPs: 1QCE, 2JJ7, 2KPE, 3K2A, 3LHP, 2LOE, 2L3H, 2L1P, 1KSG, 1KSJ, 1KSH, 2KOL, 2KZG, 2KPF and 3MQC. We have also created a web server that can take the PDB coordinate file of an RSP and output its cylindrical coordinates. The URL of our web server will be announced publicly in due course., Comment: 40 pages, 14 figures, 1 table

A pharmacophore consists of the parts of the structure of the ligand that are sufficient to express the biological and pharmacological effects of the ligand. It is usually a substructure of the entire structure of the ligand. Small organic molecules called ligands or metabolites in the cell form complexes with biomolecules (usually proteins) to serve different purposes. The sites at which the ligands bind are known as ligand binding sites, which are essentially "pockets" which have complementary shapes and patterns of charge distribution with the ligands. Sometimes a pocket is induced by the ligand itself. If we study different bound conformations of ligands it is found that they share a specific three- dimensional pattern that is more or less common and is responsible for its binding and which is complementary in three-dimensional geometry and charge distribution pattern with its cognate binding site in the protein. This work studies the three dimensional structure of the consensus ligand binding site for the ligand FMN. A training set for the ligand binding sites was made and a 3D consensus binding site motif was determined for FMN. The FMN system was studied and its binding sites in its respective regulator proteins. The ability to identify ligand binding site by scanning the 3D binding site consensus motif in protein 3D structures is an important step in drug target discovery. Once a pharmacophore template is found it can also be used to design other potential molecules that can bind to it and thus serve as novel drugs., Comment: 72 pages, 19 figures, 6 tables

Protein structure representation is an important tool in structural biology. There exists different methods of representing the protein 3D structures and different biologists favor different methods based on the information they require. Currently there is no available method of protein 3D structure representation which captures enough chemical information from the protein sequence and clearly shows the intra-molecular and the inter-molecular H-bonds and VDW interactions at the same time. This project aims to reduce the 3D structure of a protein and display the reduced representation along with intermolecular and the intra- molecular H-bonds and van der Waals interactions. A reduced protein representation has a significantly lower atomicity (i.e., number of atom coordinates) than one which is in all- atom representation. In this work, we transform the protein structure from all-atom representation" (AAR) to double-centroid reduced representation (DCRR), which contains amino acid backbone (N, CA, C', O) and side chain (CB and beyond) centroid coordinates instead of atomic coordinates. Another aim of this project is to develop a visualization interface for the reduced representation. This interface is implemented in MATLAB and displays the protein in DCRR along with its inter-molecular, as well as intra-molecular, interaction. Visually, DCRR is easier to comprehend than AAR. We also developed a Web Server called the Protein DCRR Web Server wherein users can enter the PDB id or upload a modeled protein and get the DCRR of that protein. The back end to the Web Server is a database which has the reduced representation for all the x-ray crystallographic structure in the PDB., Comment: 72 pages, 24 figures, 2 tables

We have developed a web server that implements two complementary methods to quantify the depth of ligand binding site (LBS) in protein-ligand complexes: the "secant plane" (SP) and "tangent sphere" (TS) methods. The protein molecular centroid (global centroid, GC), and the LBS centroid (local centroid, LC) are first determined. The SP is the plane passing through the LC and normal to the line passing through the LC and the GC. The "exterior side" of the SP is the side opposite GC. The TS is the sphere with center at GC and tangent to the SP at LC. The percentage of protein atoms inside the TS (TS index) and on the exterior side of the SP (SP index), are complementary measures of LBS depth. The SPi is directly proportional to LBS depth while the TSi is inversely proportional. We tested the two methods using a test set of 67 well-characterized protein-ligand structures (Laskowski, et al. 1996), as well as that of an artificial protein in the form of a grid of points in the overall shape of a sphere and in which LBS of any depth can be specified. Results from both the SP and TS methods agree well with reported data (ibid.), and results from the artificial case confirm that both methods are suitable measures of LBS depth. The web server may be used in two modes. In the "ligand mode", user inputs the protein PDB coordinates as well as those of the ligand. The "LBS mode" is the same as the former, except that the ligand coordinates are assumed to be unavailable; hence the user inputs what s/he believes to be the coordinates of the LBS amino acid residues. In both cases, the web server outputs the SP and TS indices. LBS depth is usually directly related to the amount of conformational change a protein undergoes upon ligand binding - ability to quantify it could allows meaningful comparison of protein flexibility and dynamics. The URL of our web server will be announced publicly in due course., Comment: 51 pages, 9 figures, 1 table

We previously described the representation of protein 3D structures in spherical coordinates (rho, phi, theta) and two of its applications: separation of the outer layer (OL) from the inner core (IC) of proteins, and assessment of protein surface protrusions and invaginations (Reyes, V.M., 2011& 2009). Here we present results demonstrating the performance success of the FORTRAN 77 and 90 programs used in the implementation of the two said applications, and how to implement both applications. In particular, we show here data that demonstrate the success of our OL-IC separation procedure using a subset of the Laskowski et al. (1996) dataset. Using a theoretical model protein in the form of a scalene ellipsoid grid of points with and without an artificially constructed protrusion or invagination, we also show results demonstrating that protrusions and invaginations on the protein surface maybe predicted. The nine programs we present here and their respective functions are: find_molec_centr.f: finds the x-, y- and z-coordinates of the protein molecular geometric centroid, cart2sphere_degrees.f90: converts PDB protein coordinates to spherical, with phi and theta in degrees, cart2sphere_radians.f90: does the same thing as the second program, but with phi and theta in radians, spher2cart_degrees.f90: converts the coordinates from spherical back to PDB, where input phi and theta are in degrees, spher2cart_radians.f90: does the same thing as the fourth program, but with phi and theta in radians, find_rho_cutoff.f: determines the rho cut-off for finding the boundary between OL and IC, phi6_theta8_binning.f90: performs the binning of phi in six- and theta in eight-degree increments, phi10_theta10_binning.f90: performs the binning of phi and theta both in ten-degree increments, and bin_rho.f90: performs the binning of rho values for plotting the frequency distribution of maximum rho values., Comment: 36 pages, 10228 words total (27 pages/9384 words text, 9 pages/844 words figures+tables+legends), 7 figures total (fig. 1: panels A, B & C, fig. 2: panels A, B, C & D), 6 tables total (tbl. 1, tbl. 2, tbl. 3: panels A, B & C, tbl. 4)