Miracle-dz/UniFAR-FTUs huggingface dataset:
Thesis proposal : A study on the discriminatory capacity of the temporal information on supervised time series classification problems

Time series classification has been always categorized as a particular case of classification in which the input objects are ordered sequences. As such, the research community has assumed that specific methods are required for dealing with this type of data, without really analysing this hypothesis. Specific methods are usually computationally expensive or demand some semantic treatment of the series that may turn the method cumbersome. In this thesis time series classification is addressed from a new point of view: the discriminatory power of the temporal information. In other words, given a dataset, we want to analyse the relevance of the temporal information (the order of the elements of a series, for instance) for classification and explore in which cases the specific methods are necessary and why in depth. Departing from distance based time series classification, the goal of this thesis is to explore which are the temporal characteristic of the time series data in order to measure how relevant they are for classification.
Ophthalmic Imaging Interspecies Variation of Outer Retina and Choriocapillaris Imaged With Optical Coherence Tomography

Petr Soukup, Peter Maloca, Bernd Altmann, Matthias Festag, Elke-Astrid Atzpodien, and Simon Pot Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center, Basel, Switzerland Ophthalmology Section, Equine Department, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland Institute of Molecular and Clinical Ophthalmology Basel (IOB), Basel, Switzerland OCTlab Research Laboratory, Department of Ophthalmology, University of Basel, Basel, Switzerland Moorfields Eye Hospital, London, United Kingdom
Satellite glial cells can promote the extension of neuronal axons in vitro

Satellite glial cells (SGCs) usually form envelopes around single neurons, which create a distinct functional unit consisting of a neuron and its attending SGCs[1]. SGCs can supply nutritions to neurons and mediate neuronal responses to inflammation; SGCs also play a role in pain modulation[2]. SGCs can support the survival of neurons via expressing a variety of neurotrophic factors[3,4]. Those findings suggested that SGCs are sensitive to nerve injury. However, the actual influence of SGCs on nerve regeneration has not been clear. In this study, we plan to use DRGs culture and immunofluorescence technique to observe the influence of SGCs and the contact with neurons on nerve regeneration in vitro. 2. Materials and methods
Retina Light Sensitivity Within Areas of Geographic Atrophy Secondary to Age-Related Macular Degeneration

Maximilian Pfau, Leon von der Emde, Chantal Dysli, Sarah Thiele, Philipp T. Möller, Moritz Lindner, Jennifer Nadal, Matthias Schmid, Steffen Schmitz-Valckenberg, Frank G. Holz, and Monika Fleckenstein University of Bonn, Department of Ophthalmology, Bonn, Germany GRADE Reading Center, Bonn, Germany Department of Ophthalmology and Department of Clinical Research, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland The Nuffield Laboratory of Ophthalmology, Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom Institute for Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Germany
Ja n 20 03 The capacity of hybrid quantum memory

The general stable quantum memory unit is a hybrid consistin g of a classical digit with a quantum digit (qudit) assigned to each classical state. The shape of the me mory is the vector of sizes of these qudits, which may differ. We determine when N copies of a quantum memory A embed inN(1+o(1)) copies of another quantum memoryB. This relationship captures the notion that B is as at least as useful as A for all purposes in the bulk limit. We show that the embeddings exist if and onl y if for all p≥ 1, thep-norm of the shape of A does not exceed the p-norm of the shape of B. The log of thep-norm of the shape of A can be interpreted as the maximum of S(ρ)+H(ρ)/p (quantum entropy plus discounted classical entropy) taken ov r all mixed statesρ onA . We also establish a noiseless coding theorem that justifies these entropies. The noiseless coding theorem and the bulk embedding theorem together say that eit erA blindly bulk-encodes intoB with perfect fidelity, or A admits a state that does not visibly bulk-encode into B with high fidelity. In conclusion, the utility of a hybrid quantum memory is dete rmined by its simultaneous capacity for classical and quantum entropy, which is not a finite list of numbers, but rather a convex region in the classical-quantum entropy plane.
The Nucleocapsid Protein Gene as Excellent target for Detection of Canine Distemper Virus by Reverse Transcriptase-Polymerase Chain Reaction

The genome consists of about 15.7 kilobases (kb), which codes for six structural proteins: the nucleocapsid protein (N), the phosphoprotein (P), the matrix protein (M), the polymerase (L) and the envelope glycoproteins, the fusion protein (F) and the haemagglutinin (H). These last two, located in the lipid envelope surrounding the virion, are responsible for the recognition and entry of the virus into the host cell [1-4]. The helical nucleocapsid contains the N, P and L proteins, which initiate intracellular replication. The M protein connects the glycoproteins of the surface and nucleocapsid during viral maturation [1,5].
TRANSGENIC MOSQUITOES

For transmission of dengue virus and malaria pathogens occur, the causing agents of these diseases have to complete their developmental cycle inside the mosquitoes Aedes and Anopheles, respectively. Mosquitoes are therefore potentialweak links in dengue and malaria transmission. Genetically modified mosquitoes have been created aiming of either reducing their ability to transmit disease or suppressing target mosquito population by releasing transgenic males carrying a lethal dominant gene. There has been considerable progress over the last decade towards developing the tools for generating transgenic mosquitoes. These tools have provided researchers with the ability to engineer refractory mosquito vectors and transgenic mosquitoes carrying lethal genes, but there are fundamental gaps in our knowledge of how to transfer this technology safely and effectively into field.
Vitamin D-binding protein ( rs 4588 ) T / T genotype is associated with anteroseptal myocardial infarction in coronary artery disease patients

Department of Medical Rehabilitation, Medical Faculty, University of Rijeka, Rijeka, Croatia; Division of Cardiology, Hospital for Medical Rehabilitation of the Heart and Lung Diseases and Rheumatism “Thalassotherapia-Opatija”, Opatija, Croatia; Department of Biotechnology, Centre for High-throughput Technologies, University of Rijeka, Rijeka, Croatia Contributions: (I) Conception and design: S Kraljević Pavelić, V Peršić; (II) Administrative support: V Peršić, S Kraljević Pavelić, D Raljević; (III) Provision of study materials or patients: V Peršić, D Raljević, R Miškulin; (IV) Collection and assembly of data: All authors; (V) Data analysis and interpretation: All authors; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors. These authors contributed equally to this work. Correspondence to: Prof. Sandra Kraljević Pavelić. Department of Biotechnology, Centre for High-throughput Technologies, University of Rijeka, Radmile Matejčić 2, 51000 Rijeka, Croatia. Email: sandrakp@biotech.uniri. hr.
COMPUTATIONAL CLUSTERS

This paper presents a detailed design of a decentralised agent-based scheduler, which can be used to manage workloads within the computing cells of a Cloud system. This scheme in based on the concept of service allocation negotiation, whereby all system nodes communicate between themselves and scheduling logic is decentralised. The architecture presented has been implemented, with multiple simulations run using real-word workload traces from the Google Cluster Data project. The results were then compared to the scheduling patterns of Google’s Borg system.
Towards a taxonomy of algorithmic attribution models – Which is the right model to measure , manage and optimize multiple campaigns ?

Algorithmic attribution describes the attribution of marketing value to various channels in an algorithmic or statistical way. This discipline is growing in importance rapidly. This growth is due to an increasing number of potential advertising channels, with an increasing ability to track users along the whole customer journey. In this research in progress paper we develop a morphological box of the various algorithmic attribution models. This box is meant as a first step in the iterative development of a full taxonomy, which we intent to use to identify which models various attribution vendors use. This taxonomy will also be useful for the future development of marketing attribution solutions.
Face Alignment Using a Three Layer Predictor

Face alignment is an important feature for most facial images related algorithms such as expression analysis, face recognition or detection etc. Also, some images lose information due to factors such as occlusion and lighting and it is important to obtain those lost features. This paper proposes an innovative method for automatic face alignment by utilizing deep learning. First, we use second order gaussian derivatives along with RBF-SVM and Adaboost to classify a first layer of landmark points. Next, we use branching based cascaded regression to obtain a second layer of points which is further used as input to a parallel and multi-scale CNN that gives us the complete output. Results showed the algorithm gave excellent results in comparison to state-of-the-art algorithms.
Feature Selection Techniques for Automated Facial Action Coding

We present a novel feature selection technique that selects small models prior to classification by SVM. This technique was applied to the problem of fully automated recognition of facial actions. We report results on a series of experiments comparing the use of different sets of features. Best results were obtained by selecting a subset of Gabor Filters trained with Support Vector Machines using a Genetic Algorithm. The system was tested on recognition of 3 action units from the facial action coding system (FACS). It was trained on FACS-coded facial expressions from the Cohn-Kanade and Ekman Hager databases and tested using cross-validation. With this approach we obtained 94% correct recognition of facial action units of novel subjects from both data sets. The system was also applied to spontaneous facial expressions with unconstrained head motion. For spontaneous expressions we obtained 76% correct classification of the action units. The system performed 3-4% better than a previous system that selected Gabor features with Adaboost prior to classification by Support Vector Machines. The performance was about 6% better than no feature selection. Currently the system is being extended to more action units.
Retina Apratoxin S 4 Inspired by a Marine Natural Product , a New Treatment Option for Ocular Angiogenic Diseases

Beiying Qiu, Alison Tan, Amutha Barathi Veluchamy, Yong Li, Hannah Murray, Wei Cheng, Chenghao Liu, Joanna Marie Busoy, Qi-Yin Chen, Srivani Sistla, Walter Hunziker, Chui Ming Gemmy Cheung, Tien Yin Wong, Wanjin Hong, Hendrik Luesch, and Xiaomeng Wang Institute of Molecular and Cell Biology, Agency for Science Technology & Research, Singapore Singapore Eye Research Institute, Singapore National Eye Center, Singapore Duke-NUS Medical School, National University of Singapore, Singapore Department of Ophthalmology, Yong Loo Lin School of Medicine, Singapore Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore Department of Medicinal Chemistry and Center for Natural Products, Drug Discovery and Development (CNPD3), University of Florida, Gainesville, Florida, United States Department of Physiology, National University Singapore, Singapore Oceanyx Pharmaceuticals, Inc., Woburn, Massachusetts, United States Institute of Ophthalmology, University College London, United Kingdom
Weighted sum model for Spatial Analysis in Classification of Areas Prone to Diphtheria Tetanus

The health sector in developing countries such as the State of Indonesia is still experiencing problems to find out the distribution of areas prone to tropical infectious diseases, including diphtheria and tetanus. The purpose of the discussion in this paper is to perform spatial analysis of geographical information system (GIS) fields through spatial data modeling for classification of diphtheria and tetanus-prone areas based on spatial parameters of datasets such as immunization status coverage, PD3I, epidemics, nutrition status, and population density. The Weighted sum model (WSM) method is used in the process of spatial analysis which is a multiple criteria decision making (MCDM). The classification results of diphtheria and tetanus-prone areas consist of good, fair, and poor categories. Preference values are generated using the Guttman method as a basis for spatial analysis in the next series of data. The test results can be used as recommendations in policymaking to anticipate the distribution of areas in the poor category.
How can the poor be better integrated into health insurance programs in Africa ? An overview of possible strategies

Health insurance is among the solutions promoted in developing countries since the 1990s to improve access to health care services because it avoids direct payment of fees by patients and spreads the financial risk among all the insured. Many mutual health insurance organization have been developed in sub-Saharan Africa, and over the past several years some African countries have set up national health insurance systems. However, in those countries that elect to give an important role to health insurance, it remains to be verified whether such insurance really reaches those who are most vulnerable in terms of access to services: the poor. In fact, lack of funds creates problems at two levels: when it comes time to pay the premium, and when the insured need to use health care services. On these two levels, this policy brief assesses the situation of the poor, examines the problems they encounter and presents measures taken by some insurance organization to remedy these problems.
Understanding network dynamics of a bike-sharing system to enhance inventory self-balancing ∗ CS 5834 Intro to Urban Computing-Project †

How does the network dynamics from a bike-share system provide insights to enhance its inventory self-balance? In this work, we model station demand and route flow across time and weather considerations. These models are used to make long term and real-time decisions about incentives for riders. Such incentives aim to improve inventory self-balancing, which increments service satisfaction and company’s profit. Therefore, we propose using a visualization to support decision making related to these incentives across different times of the day.
VALIDATING 3 D GEOPHYSICAL MODELS FOR USE IN GLOBAL TRAVEL-TIME CALCULATION FOR IMPROVED EVENT LOCATIONS

Towards developing a fully global, seamless travel-time calculation and event location capability, we evaluate existing 3D velocity models to test their ability to correctly predict travel times for ground-truth (GT) data. We have identified 513 GT5 or better events within the Los Alamos National Laboratory (LANL) seismic database, which provide us with 58,970 arrivals for our study. We first verify that calculated travel times through our global, 3D ellipsoidal parameterization of the AK135 model are within our tolerance of 0.2 s to Tau-P predictions. Subsequently, we compare observed teleseismic P-wave travel times for our GT dataset to those predicted by dynamic ray tracing through a variety of crustal models superimposed on an AK135 mantle. These models were developed either through ad hoc combination of regional models, or through fitting of straight-ray propagation through a Cartesian system with smoothing over 1 to 3 degree grids. We examine the improvement to travel-time predictions for these models compared to the AK135 alone. We next examine a recently published 3D, global mantle model (MITP08). This model was developed by inverting travel-time residuals along fixed rays for an AK135 model, with a Crust2.0 correction. When we adhere to the AK135 ray paths to calculate our GT event residuals, we find that the MITP08 model provides significant improvement to travel-time prediction compared to other models tested to date. Not surprisingly, when we calculate the travel times using dynamic rays, the performance is poorer. GT travel times are best predicted through any given model when the calculation is performed using a method close to that used in generation of the model, as expected. Such considerations as Earth ellipticity correction, fixed ray vs. dynamic ray tracing, crustal corrections (for mantle models) and mantle values (for crustal models) need to be applied appropriately for a fair evaluation. Conversely, any model made available to the community is of little practical use unless the method of its derivation is also provided, or clearly explained so that it may be replicated for travel-time calculation and location procedures. Due to the existing heterogeneity in models and their methods of derivation, we conclude that towards our development of a seamless, global model and locator, existing models may best serve as starting models for a global inversion using a single, consistent ray tracing and travel-time calculation approach. 2009 Monitoring Research Review: Ground-Based Nuclear Explosion Monitoring Technologies
Making (More) Sense of Destruction — A Comprehensive Geochemical Investigation of Chicxulub Impactites Recovered During IODP-ICDP Expedition 364

INVESTIGATION OF CHICXULUB IMPACTITES RECOVERED DURING IODP-ICDP EXPEDITION 364. S. J. de Graaff, P. Kaskes, T. Déhais, S. Goderis, V. Debaille, J.-G. Feignon, L. Ferrière, C. Koeberl, C.H. Ross and Ph. Claeys, Analytical, Environmental and Geo-Chemistry, Vrije Universiteit Brussel, Belgium (sietze.de.graaff@vub.be), Laboratoire G-Time, Université Libre de Bruxelles, Brussels, Belgium, Department of Lithospheric Research, University of Vienna, Austria, Natural History Museum, Vienna, Austria, Department of Geological Sciences, University of Texas at Austin, Austin, TX, Institute for Geophysics, University of Texas at Austin, Austin, TX.
Predicting Grasp Success with a Soft Sensing Skin and Shape-Memory Actuated Gripper

Tactile sensors have been increasingly used to support rigid robot grippers in object grasping and manipulation. However, rigid grippers are often limited in their ability to handle compliant, delicate, or irregularly shaped objects. In recent years, grippers made from soft and flexible materials have become increasingly popular for certain manipulation tasks, e.g., grasping, due to their ability to conform to the object shape without the need for precise control. Although promising, such soft robot grippers currently suffer from the lack of available sensing modalities. In this work, we introduce a soft and stretchable sensing skin and incorporate it into the two fingers of a shape-memory actuated soft gripper. The onboard sensing skin includes a 9-axis inertial measurement unit (IMU) and five discrete pressure sensors per finger. We use this sensorized soft gripper to study grasp success and stability of over 2585 grasps with various objects using several machine learning methods. Our experiments show that LSTMs were the most accurate predictors of grasp success and stability, compared to SVMs, FFNNs, and ST-HMP. We also evaluated the effects on performance of each sensor's data, and the success rates for individual objects. The results show that the accelerometer data of the IMUs has the largest contribution to the overall grasp prediction, which we attribute to its ability to detect precise movements of the gripper during grasping.
Collaborative Study on the Immunochemical Quantitation of Intact Gluten in Rice Flour and Rice-Based Products Using G 12 Sandwich ELISA

The AACC International (AACCI) Protein and Enzyme Methods Technical Committee initiated a collaborative study of a method for gluten quantitation in selected foods using a G12 antibody sandwich ELISA system. The method has been approved as AACCI Approved Method 38-52.01. The new method has been validated for testing rice flour and rice-based products to verify that they conform to the defined Codex threshold of ≤20 mg of gluten/kg in products labeled
0 WP / 17 / 3 SAMA Working Paper Commercial Bank Credit and Sectoral Economic Growth : Granger Causality Analysis November 2017 By Saudi Arabian Monetary Authority

This paper examines the long-run relationship between bank credit and economic growth across the sectors in the Saudi economy using panel data from 1970 to 2014. The analysis was carried out using panel co-integration and causality techniques controlling for the presence of cross-sectional dependence. The variables are determined to be panel I(1) and co-integrated . A uni-causal link from economic growth to bank credit can be deduced from Panel Granger causality tests. While further examination of long-run dynamics reveals a narrow causal link from bank credit to economic growth in the commerce sector, the results have been related to the literature and followed by policy recommendations.
Interactive comment on “ A Parallel Hybrid Intelligence Algorithm for Solving Conditional Nonlinear Optimal Perturbation to Identify Optimal Precursors of North Atlantic Oscillation ” by Bin

(2) In the studies of Jiang et al. (2013) and Dai et al. (2016), the algorithm they adopted to explore OPR is spectral projected gradient 2 (SPG2) [1]. The SPG2 was designed to solve the minimum problem of a nonlinear function under a set of constraints and has been widely used in the related research on CNOP [2-5]. The solving process using SPG2 needs to acquire the gradient information via the adjoint model. In their studies, they adopted the T21 quasigeostrophic (QG) global spectral model (T21L3), which is an ideal model with 3 layers, to simulate the NAO and selected the geopotential height as the variable to quantify the NAO. The adjoint model of the T21L3 is called to provide the gradient data for calculating extrema using SPG2. The description of the SPG2 is added to the section about related works in the revised version.
Medi-Test: Generating Tests from Medical Reference Texts

The Medi-test system we developed was motivated by the large number of resources available for the medical domain, as well as the number of tests needed in this field (during and after the medical school) for evaluation, promotion, certification, etc. Generating questions to support learning and user interactivity has been an interesting and dynamic topic in NLP since the availability of e-book curricula and e-learning platforms. Current e-learning platforms offer increased support for student evaluation, with an emphasis in exploiting automation in both test generation and evaluation. In this context, our system is able to evaluate a student’s academic performance for the medical domain. Using medical reference texts as input and supported by a specially designed medical ontology, Medi-test generates different types of questionnaires for Romanian language. The evaluation includes 4 types of questions (multiple-choice, fill in the blanks, true/false, and match), can have customizable length and difficulty, and can be automatically graded. A recent extension of our system also allows for the generation of tests which include images. We evaluated our system with a local testing team, but also with a set of medicine students, and user satisfaction questionnaires showed that the system can be used to enhance learning.