Miracle-dz/UniFAR-FTUs huggingface dataset:
Lois de variations et ordre de grandeur de la conductivité alternative des chalcogénures massifs non cristallins.

2014 The a.c. conductivity 03C3(03C9) of bulk amorphous chalcogenides (Se, As2S3, As2Se3, (As2Te3)1-xGex, Se1-xGex) is investigated at variable frequency, from 1 kHz to 35 GHz, and at variable temperature, from 77 to 300 K. Two contact effects are disclosed, one at low frequencies, the other in the radiofrequency range. The real dependences of the a.c. conductivity obey the following common laws : (i) 03C3(03C9) is proportional to 03C9 in the frequency range scanned ; (ii) 03C3(03C9) is temperature independent at low frequencies ; (iii) the order of magnitude of 03C3(03C9) is independent of the material investigated. The electronic hopping models as they are actually defined, cannot explain the experimental frequency variation. Our results seem in good agreement with the model of two level systems. and this concordance would imply a potential barrier distribution independent of the energy and a quasisymmetric double well configuration. According to our investigation, the number of systems per cubic centimeter is estimated to be (1019-1020). LE JOURNAL DE PHYSIQUE TOME 40, AVRIL 1979,
Authentication with Keystroke Dynamics on Touchscreen Keypads - Effect of different N-Graph Combinations

—The security and access protection on mobile devices have become an important topic due to the increasing amount of personal and sensitive data stored on these devices. The traditional security techniques based on PIN ( Personal Identiﬁcation Number )-input are insufﬁcient and do not correspond to the present password standards. An authentication with usage of keystroke behavior could increase the security and a lot of research has been published based on traditional PC keypads. Keystroke behavior on touchscreen keypads, as they are nowadays installed on smartphones, enables adding additional features for the authentication. For example, pressure, size or exact coordinates of keystroke can be used. The focus of this paper is that several time differences (e.g. digraph) are examined and checked for suitability for a keystroke authentication. For that, data of 152 subjects were classiﬁed. With additional features of the touchscreen, an error rate of false rejected persons of only 4.59% and false accepted persons of only 4.19% could be reached.
Fatigue Life extension in HMA Concretes through the inclusion of Candle Wax as modifier for heavy trafficked Pavement

Highway flexible pavements, probably the largest infrastructural components in many developed nations today are a complex system having multiple layers made up of different materials. However, this very large infrastructural component during use suffer many drawbacks resulting from different adverse conditions such as irregular traffic loading, and varying environmental conditions like temperature, moisture and oxidation rates. Therefore, a realistic prediction of the long-term service life of flexible pavements is one of the most challenging tasks for pavement engineers in Highway Engineering. Generally, there are two main types of distresses that impede the performance of flexible pavement – fatigue cracking and rutting deformations. The former generally associated with stiffness and horizontal tensile strains at the bottom of the asphalt concrete layer was the focus of the present study since it is the most significant factor controlling pavement life. In this study hot mix asphalt concretes were prepared and modified at optimum asphalt content using non bituminous modifier – candle wax. The results obtained revealed that the candle wax modified asphalt concrete produced pavements with extended pavement life for all loading frequencies considered for the given traffic category. Overall the addition of candle wax produced pavement having average stiffness increase of 8%, average strain reduction of 27% and average fatigue extension of 171%.
CRME Working Paper 2-2015; Laasch Responsible Management Learning 1 RESPONSIBLE MANAGEMENT LEARNING: REFLECTING ON THE ROLE AND USE OF PARADIGMS IN SUSTAINABILITY, RESPONSIBILITY, ETHICS RESEARCH

We conceptualize responsible management learning (RML) as process through which SRE knowledge is embedded into practice; through which SRE knowledge becomes socially relevant. Accordingly, creating knowledge suitable for RML is crucial. A first step for creating such knowledge is the application of research paradigms that match typical SRE research settings. We conduct a review of ‘mainstream’ research paradigms (positivism, rational choice theory) and ‘alternative’ paradigms (critical theory, critical realism, pragmatism, and social constructionism) and their applications in SRE research. We provide literature exemplars to illustrate how alternative research paradigms’ have been used in SRE research, and we empirically explore paradigm choice through the case of a RML research project. We find that the ‘domains of ideal use’ of conventional research paradigms have remarkable blind spots as they cover only a minor part of typical SRE research settings. This implies for SRE researchers to reflect on the adequateness of our paradigm choices, and on the implications for the relevance of SRE knowledge creation. We introduce a matrix tool to support researchers’ reflection on paradigm choice in SRE research.
Quotation for Real-Time Metacognition

Meta-reasoning about entities internal to agents themselves (such as their own beliefs) is a well-recognized ability, and leads to the need to quantify over propositions or formulas, especially in time-varying settings. In this position paper we sketch desiderata and a potential solution, via integrating a quotation-based, syntactic approach in the time-sensitive context of active logic
Women to the Rescue: Is There a Glass Cliff in Politics?

Over the past decade, organisational research has found that women do not only face invisible obstacles as they climb up the career ladder, but that, even when they shatter the glass ceiling, they tend to be preferentially selected to precarious leadership positions. This phenomenon has been called the ”glass cliff,” alluding to the idea that women are perched on an (invisible) cliff and may fall off at any point. This thesis contributes to the existing research by examining whether women also face a glass cliff in the political sphere. More precisely, I argue that women are more likely to be selected as local and national party leaders when a party has been performing poorly in previous elections. However, I expect the glass cliff effect to vanish when female leaders are associated with that poor performance. To test these hypotheses, I use archival data on national party leaders in fourteen countries as well as data from an experiment on Amazon MechanicalTurk on local party leader elections. The generalised estimating equation models (GEE) of the archival data do not provide sufficient evidence for the existence of a glass cliff. The same applies to the experimental study which finds a difference in the choice of party leaders between men and women, but that effect is not dependent on the performance of a party. The candidate evaluations provide some preliminary evidence that female candidates are evaluated more positively when a party is performing poorly. iii C E U eT D C ol le ct io n
Multi-Sensor Scene Segmentation for Unmanned Air and Ground Vehicles using Dynamic Mode Decomposition

Situational awareness is the key to safe navigation and operation in autonomous air and ground systems. Multi-sensor scene segmentation can facilitate situational awareness for autonomous navigation. In this work, we introduce an alternative to learning-based approaches for scene segmentation based on dynamical systems theory. The streaming dynamic mode decomposition (DMD) algorithm is tailored to isolate moving foreground objects from stationary background objects in the scene. We show that LiDAR point cloud data can be transformed into a cylindrical depth map that is amenable to analysis within the DMD framework. We further extend the streaming DMD algorithm to adapt to changes in the scene by introducing a forgetting factor that weights the relative importance of past versus present information in the data stream. The proposed streaming DMD methods are applied for on-the-ﬂy scene segmentation of video and LiDAR data streams from the KITTI Dataset. We ﬁnd that the approach is able to distinguish between stationary background and moving foreground objects in a consistent and reliable manner across various scenes.
Effect of the graphene oxide reduction method on the photocatalytic and electrocatalytic activities of reduced graphene oxide/TiO2 composite

Graphene oxide (GO) was synthesized from commercial graphite using a modified Hummers' method. Three different methods were used to prepare reduced GO/TiO2 composites. GO was (i) initially impregnated over TiO2 (GOTi) and then reduced using a stream of hydrogen gas at 450 °C (H2RGOTi), (ii) reduced using hydrazine hydrate solution (HH) in a 1000 W microwave oven (HHRGO) and then loaded on the TiO2 (HHRGOTi) or (iii) hydrothermally reduced (RGO) then loaded on TiO2 (RGOTi). Different characterization techniques were used e.g. X-ray photoelectron spectroscopy (XPS), X-ray diffraction patterns (XRD) and UV-Vis, Fourier transform infrared (FT-IR) and Raman spectroscopy. The effect of the GO reduction method on the photocatalytic activity of the aforementioned composites towards the degradation of phenol in the presence and absence of (i) UV and (ii) H2O2 was examined. High phenol degradation rates were achieved using the RGOTi photocatalyst, compared to the TiO2 nanoparticles, under UV illumination. On the other hand, the H2RGOTi composite has shown the highest electrocatalytic activity towards the oxygen reduction reaction under UV illumination.
MONITORING VEGETATION PHENOLOGY IN THE BRAILA PLAIN USING SENTINEL 2 DATA

The continuous crop condition monitoring at a regional scale is critical especially for private investors which should apply land reclamations measures regarding the soil degradation and modern methods of irrigation for optimizing the water use efficiency and crop yield production. Benefiting from the newest European remote sensing technology, in particular the Sentinel 2 imagery, the paper investigates the crop vegetation status during the 2016’s growing season and covers the Cazasu agricultural area, located in the Braila Plain. Red edge bands have been exploited in order to correlate the spectral indices with chlorophyll and the plant water content. Thus, the wheat biophysical variables, as leaf area index (LAI), leaf chlorophyll (CAB), canopy water content (CWC), normalized differential vegetation index (NDVI), fraction of vegetation cover (FCOVER) and fraction of absorbed photosynthetically active radiation (FAPAR) have been retrieved by inversion of PROSAIL canopy radiative transfer model. This model, focused on the red edge which stimulates the whole spectro-directional canopy field between red and near infrared, is sensitive to the variations in leaf chlorophyll, leaf area index, soil substrate and atmospheric conditions. A good synergy between vegetation variables was obtained, confirming the Sentinel 2 capabilities to monitor crops and to develop useful products to be offered as services to the farmers.
Soybean yield and quality as affected by spraying NPK fertilizers compound with amino acids and micronutrients

This study aimed to investigation the effects of foliar NPK fertilizers compound with micronutrients spraying at different levels and amino acids on soybean plants. The field experiment was conducted at Al Sharkia Governorate, Egypt in a private farm through a project of soil and water use Dept. of the National Research Center This experiment design with three replicates. Soybean seeds (Giza 21) were sown on the 15 th of June, 2014. The NPK fertilizers contain macronutrients from N, P and K as (2020 -20) foliar application. The micronutrients were mixed from (Fe, Zn, Mn, Mg and B) and added every 15 days with irrigation at two levels 1.5 and 2.0 Kgfed -1 . The amino acids were applied at two levels as 1.5 and 2.0 g/l. The results are as follows: 1-The application of foliar NPK fertilizers with amino acids at 2.0g/l compound with mixed micronutrients as 2.0 Kgfed-1 increased the vegetative growth of soybean plants compared with control. 2The best results of yield and its compound and concentrations of N, P and K were recorded with foliar NPK application compound with increasing the rate of amino acids and mixed micronutrients. Key word : Soybean, foliar fertilization, NPK, Micronutrients, Amino acids.
Host plant resistance to cotton leaf crumple disease transmitted by whitefly

Cotton, Gossypium hirsutum L. , cultivars and breeding lines were evaluated in the field for resistance to the Cotton Leaf Crumple disease caused by Cotton Leaf Crumple Virus (CLCrV, Genus Begomovirus, Family Geminiviridae) transmitted by silverleaf whitefly, Bemisia argentifolii (Bellows and Perring). Cultivars and breeding lines were evaluated in field plots during 1999 through 2001 in the Imperial Valley, CA. Cotton entries were rated for severity of CLCrV disease symptoms, and the titer of CLCrV in leaves of selected plants of each cultivar/breeding-line was determined by dot blot hybridization with a CLCrV DNA probe and/or PCR analysis. DNA sequencing of geminivirus DNA-A and DNA-B fragments, PCR-amplified from symptomatic cotton plants, confirmed geminivirus infection and allowed for partial characterization of CLCrV in the Imperial Valley. Differences in whitefly infestation levels and virus disease severity were detected among cotton entries. The breeding lines NK 2387C and DPX 1883 had the lowest CLCrV disease severity ratings and viral titers, suggesting a high level of virus resistance. Lines DG 2165 and DG 2383 had few or no CLCrV symptoms and low viral titers, and are moderately resistant. Stoneville 474 and NK 2207 had visible CLCrV symptoms and higher virus titers, and cultivars AP 4103 and AP 6101 had the highest CLCrV disease ratings and high levels of CLCrV; these cultivars/lines are susceptible. These results indicate that there are promising sources of resistance available for CLCrV disease in the United States; it will be important to ascertain whether these sources are resistant to the devastating cotton leaf curl disease in Asia, which is caused by a different
Presentation Attacks and Detection in Finger- and Hand-Vein Recognition

Biometric recognition systems, especially vascular pattern based ones, are becoming more popular. However, these systems are still susceptible to so called presentation attacks, where a forged representation of the original biometric is presented to the system trying to mimic the original biometric and fool the system. We propose a presentation attack approach for ﬁnger-and hand-vein recognition systems using paper prints as well as wax and silicone artefacts. We further develop a suitable presentation attack detection (PAD) scheme based on natural scene statistics and acquire a corresponding hand vein presentation attack dataset. Evaluating the PAD scheme on the dataset conﬁrmed its success in the detection of the forged samples.
RANDOMISED CONTROL TRIALS In a Randomised Control Trial

The purpose of a Randomised Control trial (RCT) is to test the extent to which planned changes have been achieved within a target population receiving a development intervention. RCTs are a type of experimental approach. Experimental approaches work by comparing changes in a group that receives a development intervention with a similar group that does not. The difference is then attributed to the intervention.
Tensor Network for Supervised Learning at Finite Temperature

The large variation of datasets is a huge barrier for image classification tasks. In this paper, we embraced this observation and introduce the finite temperature tensor network (FTTN), which imports the thermal perturbation into the matrix product states framework by placing all images in an environment with constant temperature, in analog to energy-based learning. Tensor network is chosen since it is the best platform to introduce thermal fluctuation. Different from traditional network structure which directly takes the summation of individual losses as its loss function, FTTN regards it as thermal average loss computed from the entanglement with the environment. The temperature-like parameter can be automatically optimized, which gives each database an individual temperature. FTTN obtains improvement in both test accuracy and convergence speed in several datasets. The non-zero temperature automatically separates similar features, avoiding the wrong classification in previous architecture. The thermal fluctuation may give a better improvement in other frameworks, and we may also implement the temperature of database to improve the training effect.
Inverse Reinforcement Learning with Graphical Models

The goal of this project is to better understand the underlying mechanisms and decision making process of the brain by characterizing the predictive latent variables and their relationship to recorded neural responses. Behavioral experiments show that our brain uses latent variables to make decisions, but this process remains poorly understood. An agent in control system can only partially observe any environment and works with an estimated model (what it believes) of the environment. We will use graphical models and reinforcement learning as a means for identifying state and latent variables of the system and to ﬁnd the belief model (infer the latent dynamics) assumed by the (agent)
Seductive Experience of Contemporary Shopping Environments: A Multi-sensory Perspective

Through theoretical discourses of power and multi-sensory experience, this paper traces manifestations and implications of seductive design strategies employed in contemporary shopping spaces. The premise is that seduction should not be understood as necessarily negative strategy, but rather a mode of power manifested in pleasant sensual dialogue with space ambience. On-site experiments were conducted in 4 shopping malls in Singapore and Belgrade, Serbia, comprising purposeful photo-journeys, interviews and questionnaires, sensory mapping, photo and narrative analyses. Key findings indicate that, besides consumption, shopping spaces are also perceived as pleasant settings for recreation and social interaction. Seductive experience considerably depends on quantity, intensity and arrangement of overall sensory information in space.
THE PRESENCE OF INTERLOCKING DIRECTORATES IN LATIN AMERICA: A COMPARATIVE OVERVIEW

The focus of this paper is to analyze the literature about how corporate elites tend to create collaborate ties among them through the establishment of shared directors who sits on more than one board. This manuscript also aims to find a place for Latin America in the current academic global discussion about these interlocking directorates (IDs), their presence, structure, configuration and reasons to exist. We conducted a literature review over 35 papers focused on IDs research and established four categories according to their most relevant findings. Then, we describe how these findings connect with the recent IDs research in Latin America. Finally, those four categories and the description of main findings on this organizational field permitted us propose six different metrics through which we can explain how the evolution of the global IDs research was, and its main comparative characteristics between Latin America and abroad. We found that Latin America have their own challenges for control and management because of family and small firms concentration, and due to its turbulent business environment as well. Furthermore, we described how Latin America start to take part of IDs research later than other regions in the world and how the use of technology foster research efforts in this field and opens new paths for worldwide comparative studies.
Cannabis in Veterinary Medicine: A Critical Review

This article is intended to provide the veterinary community with a concise, understandable, and clinically relevant review of cannabis medicine in companion animals. Included are descriptions of the structure and function of the endocannabinoid system (ECS), outlines of the pharmacologic effects of biologically active compounds produced by the cannabis plant (phytocannabinoids, terpenoids, flavonoids), potential clinical uses and toxicities, relevant legal updates, and an overview of the most relevant veterinary research. The ECS is a complex neuromodulatory signaling system that regulates multiple systems throughout the body and is often up-regulated or down-regulated in times of disease. Many cannabis-derived molecules have been Cannabis in Veterinary Medicine: A Critical Review Trina Hazzah, DVM, Casara Andre, DVM, Gary Richter, DVM, Stephanie McGrath, DVM, MS Abbreviations AEA Anandamide or N-arachidonoylethanolamide AUC Area under the curve CB1 Cannabinoid type 1 receptor CB2 Cannabinoid type 2 receptor CBC Cannabichromene CBD Cannabidiol CBDA Cannabidiolic acid CBDV Cannabidivarin CBG Cannabigerol CBN Cannabinol CBR Cannabinoid receptor Cmax Maximum concentration CoA Certificate of analysis COX-2 Cyclooxygenase-2 CYP Cytochrome P450 DDI Drug-drug interaction Author Contacts: Trina Hazzah, DVM Veterinary Cannabis Society Los Angeles, CA 90066 Email: drtrinahazzah@gmail.com Casara Andre, DVM Veterinary Cannabis Education and Consulting 10474 West 39th Ave. Wheat Ridge, CO 80033 Email: reception.desk@veterinarycannabis.org Gary Richter, DVM Veterinary Cannabis Society Oakland, CA 94611 Email: garyrichterdvm@gmail.com Stephanie McGrath, DVM, MS Department of Clinical Sciences College of Veterinary Medicine and Biomedical Sciences Colorado State University Fort Collins, CO 80523 Email: stephanie.mcgrath@colostate.edu eCB Endocannabinoid ECS Endocannabinoid system FABP Fatty acid–binding protein GPCR G protein–coupled receptor MCT Medium-chain triglyceride OA Osteoarthritis PD Pharmacodynamics PK Pharmacokinetics PPAR Peroxisome proliferator-activated receptor THC Delta-9-tetrahydrocannabinol THCA Tetrahydrocannabinolic acid THCV Tetrahydrocannabivarin Tmax Time to maximum concentration TRPV Transient receptor potential vanilloid 2-AG 2-arachidonoylglycerol
Fast convolutional deep learning for image segmentation

Recent work has shown potential for reducing total computational time when training a convolutional deep neural network for image segmentation, by processing each training image in a single pass rather than patch by patch, as demonstrated by Masci et al. [38]. This thesis will analyze and review the existing set of computing resources for and literature on deep learning to come up with the best possible solution for implementing deep convolutional neural networks for image segmentation on CPUs and GPUs. It will review the theory behind convolutional deep learning architecture, with special emphasis on its potential for speed. This thesis will also cover implementation of said convolutional deep learning for image segmentation on CPUs and GPUs, at such a quality that it can be distributed through github. The proposed implementation will be accomplished using the frameworks CUDArray and Deeppy, which together encompass a Python library, which has been developed in collaboration with Anders Boesen Lindbo Larsen, during this thesis period. The proposed implementation will be tested with respect to speed and predictive performance on the ISBI 2012 Electron Microscopy Segmentation Challenge [8]. Final testing demonstrated relatively short processing time without significant loss of performance on said challenge.