Miracle-dz/UniFAR-FTUs huggingface dataset:
Dilated Convolution Layers U-Net Generator Conv Feature DeConv Feature Attention Feature DenseNet Discriminator VGG 16 Feature Extrator L 1 Loss Adversarial Loss Perceptual Loss Style Loss Skip Connections

We study the task of image inpainting, where an image with missing region is recovered with plausible context. Recent approaches based on deep neural networks have exhibited potential for producing elegant detail and are able to take advantage of background information, which gives texture information about missing region in the image. These methods often perform pixel/patch level replacement on the deep feature maps of missing region and therefore enable the generated content to have similar texture as background region. However, this kind of replacement is a local strategy and often performs poorly when the background information is misleading. To this end, in this study, we propose to use a multi-scale image contextual attention learning (MUSICAL) strategy that helps to flexibly handle richer background information while avoid to misuse of it. However, such strategy may not promising in generating context of reasonable style. To address this issue, both of the style loss and the perceptual loss are introduced into the proposed method to achieve the style consistency of the generated image. Furthermore, we have also noticed that replacing some of the down sampling layers in the baseline network with the stride 1 dilated convolution layers is beneficial for producing sharper and fine-detailed results. Experiments on the Paris Street View, Places, and CelebA datasets indicate the superior performance of our approach compares to the state-of-the-arts.
TWELVE Markets for Pharmaceutical Products 1

This chapter describes the market for pharmaceuticals, which exceeded $500 million in sales in 2010. The industry is also characterized by extensive regulation of almost every activity, from product development through manufacturing and marketing, which we summarize. We next describe the industry's market structure. Large, fully integrated, multinational firms that develop and market new drugs have historically dominated the industry, but the emergence of smaller firms focused on the application of biotechnology to drug development as well as firms that specialize in low-cost production of off-patent “generic” drugs has had an important impact on the market structure of the industry. The last two decades have seen a shift towards vertical specialization as well as many horizontal mergers. We discuss trends in the productivity of pharmaceutical research and incentives for innovation. We then summarize the pricing and marketing of drugs in the US and several other countries.
Data parallel algebraic multigrid

Algebraic multigrid methods for large, sparse linear systems are central to many computational simulations. Parallel algorithms for such solvers are generally decomposed into coarse-grain tasks suitable for distributed computers with traditional processing cores. Accelerating multigrid methods on massively parallel throughput-oriented processors, on the other hand, demands algorithms with abundant fine-grained parallelism. In this dissertation we analyze and decompose the smoothed aggregation algebraic multigrid method into parallel primitives effectively mapped to emerging architectures. Our formulation is performed in two phases, the first building on high-level generic abstractions to construct our solver in a architecture agnostic manner. Though effective we show that performance is severely limited by irregular sparse matrix operations, most notably sparse matrix-matrix multiplication. In the second phase, we address this performance bottleneck using novel techniques to optimize irregular sparse matrix operations. This dissertation is also concerned with irregular graph operations necessary to partition sparse matrices into disjoint sets for parallel processing. We apply our solver to accelerate eigenvector computations necessary during spectral partitioning methods and find that performance is limited by multigrid construction. We propose and analyze a novel strategy to accelerate graph Laplacian eigenvector computations by combining iterative methods, namely blocked Lanczos, with breadth first search operations on graphs. By basing our partitioner on primitives with substantial parallelism we demonstrate notable performance improvement compared with generic eigensolvers.
An assessment of the impact of the first Italian Research Evaluation Exercise on student enrollment choices ∗

This paper investigates the impact of the first Italian Research Evaluation Exercise (VTR 2001-2003) on university students’ enrollment choices. A before-after estimator with differential treatment intensities is used to investigate whether subject-groupHigher Education Institutions (HEIs) that received a better score also benefited from more student enrollments and enrollments of students with better entry qualifications after the VTR. This identification strategy enables us to control for both subjectgroup-HEI specific time invariant unobservable heterogeneity and pre-existing trends. Our analysis demonstrates that increasing the percentage of excellent research products by one standard deviation (19 percentage points) increases student enrollments by 6.3 percent. Effects are larger for high quality students, namely those with better high school final marks (10.3 percent) or coming from the academic track (11.8 percent). Effects are larger for subject-group-HEIs in the top quartile of the VTR quality distribution. Effect magnitudes appear to be similar across all macro-regions (North, Center and South and Islands), but are precisely estimated only for universities in Northern Italy. When HEIs are divided into new and old universities, only the former, which have a less established reputation in teaching and research, appear to have gained from a good performance in the VTR. ∗We gratefully acknowledge comments received at the 3rd Workshop on Education Economics (Leuven), the Eighth International Workshop on Applied Economics of Education (IWAEE, Catanzaro), the University of Milan, the National Agency for the Evaluation of the University System (ANVUR) and IRVAPP (Trento). The information and views set out in this paper are those of the authors and do not reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein. †University of Milan, DEMM, via Conservatorio, 7, 20122 Milan, Italy; daniele.biancardi@unimi.it. ‡European Commission, DG Joint Research Center, Via E. Fermi 2749, TP 361 Ispra (VA), I-21027, Italy; University of Milan (Italy); IZA (Bonn); LdA (Milan). massimiliano.bratti@ec.europa. eu. JEL Numbers: I21 I23
Corporate Social Responsibility and Inter-Organisational Trust in a B2B Context

Purpose: The purpose of the paper to reveal the linkage between the customer perception of the supplier’s CSR and inter-organisational trust in a B2B context.Methodology/Approach: The paper conceptualises the customer perception of CSR activities as a latent second-order factor composed of three dimensions: CSR towards environment and community; CSR towards employees; and CSR towards customers. Three-dimensional understanding of inter-organisational trust, is applied in this paper. A quantitative study was conducted.Findings: As it was expected, the findings revealed that the customer perception of supplier’s CSR, namely CSR towards environment and community, towards employees and customers, generates inter-organisational trust that could be divided into competence trust, benevolence trust and integrity trust.Research Limitation/implication: Seeing that the paper uses a sample from a single country, it has a limitation due to its restrictive generalisability (especially having in mind that the research was done in a low-trust societal context). Moreover, the paper does not incorporate the characteristics of organisations, and the future research could elaborate on the issues of how the perceived CSR and its impacts on inter-organisational trust vary depending on organisational financial performance, market share, and so forth.Originality/Value of paper: The paper challenges the researchers and managers to move towards more sophisticated assessments concerning the way the customer perception of CSR affects inter-organisational trust in a B2B context, which might lead to improved organisational performance and sustainability.
Collie Eye Anomaly Prevalence of the NHEJ 1 gene mutation in the Danish Shetland Sheepdog and the effects on vision in dogs diagnosed with collie eye anomaly

Background: Collie Eye Anomaly is a congenital, inherited ocular disorder with very variable phenotypic expression. CEA has primarily been demonstrated in herding breeds such as the Shetland Sheepdog. Reports on visional effects ranging from no obvious signs of affliction to complete blindness have been made, but scientific studies on the subject are utterly sparse. Recently, a commercially available genetic test for CRD has been developed. The DNA-test tests for a 7,8 bp deletion in the NHEJ1 gene on canine chromosome 37. The compliance between the genetic test and the clinical diagnosis of CRD have previously been investigated in Danish Rough Collies and found to be poor. Further studies of the association are therefore indicated. Objective: The aims of the study were to further investigate the compliance between the genetic test and the clinical diagnosis of CRD, by testing another known-affected breed, the Shetland Sheepdog. Also the prevalence of the mutation in the breed were sought to be established. Moreover, insight into the visional effects of the anomaly was desired. Methods: The study was conducted partially as a case-control study and partially by use of a questionnaire. The case-control study population consisted of unrelated, clinically affectedand unaffected Shetland Sheepdogs which were eye examined before 12 weeks of age. The study population for the questionnaire was owners of dogs participating in the current casecontrol study, and those who participated in the previous study in Rough Collies. DNA samples from the buccal mucosa of selected dogs were collected on FTA cards and subsequently genotyped. Genotyping was done by the use of a two-step PCR program. Questionnaires were distributed either via mail or via letter. Responses were collected and analyzed.
Chapter 2 The Problem of Good ( and Evil ) : Arguing about Axiological Originsin Science and Religion

Why do bad things happen to good people? Answers to this kind of question in religious contexts generally involve some reference to supernatural agents, whose relation to a coalition helps to explain why misfortune befalls its members. In monotheistic religions such as the Abrahamic traditions of Judaism, Christianity, and Islam, this question is complicated by the idea of a single supranatural agent who is believed to be omnipotent, omniscient, and omnibenevolent. This leads to the well-known “problem of evil. ” If all things are conditioned by a good God, then why are there evils in the world? For evolutionary scientists, however, it is quite easy to explain happenings that people consider bad for them. The answer is natural selection. Organisms that live long enough to reproduce pass on those variable traits that gave them a competitive advantage for survival in a particular environment. Competition often, indeed usually, means that one organism behaves badly toward another. Why, then, do naturally egoistic people do good things? Altruistic behavior toward other people, especially toward those who are not probable caregivers, appears to lessen one’s chances for survival. Evolutionary theories have to address what we might call “the problem of good. ” In this chapter, I explore different ways in which these problems are addressed within science and religion. It may appear that these intellectual
Explaining Inflation Persistence by a Time-Varying Taylor Rule

In a simple New Keynesian model, we derive a closed form solution for the inflation persistence parameter as a function of the policy weights in the central bank’s Taylor rule. By estimating the time-varying weights that the FED attaches to inflation and the output gap, we show that the empirically observed changes in U.S. inflation persistence during the period 1975 to 2010 can be well explained by changes in the conduct of monetary policy. Our findings are in line with Benati’s (2008) view that inflation persistence should not be considered a structural parameter in the sense of Lucas.
Analysis of Submicron Adder Circuits

With the revolution in integrated circuits, great emphasis was given on performance and miniaturization. Speed, area and power became the main criterion upon which a VLSI system is measured in terms of its efficiency. In any VLSI system, a full adder is widely component, which also decides the performance criteria of the system. The analysis and design of Modified Carry Select Adder (MCSLA) is analysed. Basically the adder circuit is designed to achieve low power and less delay and by logic gate of the circuit improves the performances. For speed process high logic circuit is implemented and also to have less propagation. In hybrid CMOS design style various adder cells and transistor is used, but in proposed circuit Dual Rail Signal System (DRPTL) is implemented with the load condition and the clock signal to manage the power flow in the circuit and the process is performed in an efficient way in terms of its gate count and thereby on power and speed.
ArticleISSN : 2638-6070 Complementary and Alternative Medicine : Impact of Consciousness Energy Healing Treatment on the Cholecalciferol ( Vitamin D 3 )

Cholecalciferol is a steroid hormone (7-dehydroxycholesterol), which helps in the absorption of dietary minerals like zinc, calcium, magnesium, iron, and phosphate and also responsible for other biological activity. In this research study, the influence of the Trivedi Effect®-Consciousness Energy Healing Treatment on the physicochemical and thermal properties of cholecalciferol was evaluated using the modern analytical technique. The cholecalciferol test sample was divided into two parts. One of the test samples was considered as a control sample, which did not receive the Biofield Energy Treatment; whereas, the other part was treated with the Consciousness Energy Healing Treatment remotely by a well-known Biofield Energy Healer, Gopal Nayak and termed as a treated sample. The particle size values in the treated cholecalciferol powder sample were significantly decreased by 78.94% (d10), 26.21% (d50), 22.01% (d90), and 29.04% {D (4,3)}; thus, the specific surface area of the treated cholecalciferol was significantly increased by 174.12% compared to the control sample. The XRD peak intensities and crystallite sizes of the treated cholecalciferol powder sample were significantly altered ranging from -44.37% to 370.49% and -74.48% to 91.52%, respectively; therefore, the average crystallite size of the treated cholecalciferol was significantly decreased by 36.21% compared to the control cholecalciferol. The latent heat of fusion of the treated cholecalciferol was significantly increased by 25.89% compared to the control cholecalciferol. The weight loss was decreased by 1.48%; whereas, the residue amount was significantly increased by 107.02% in the treated sample compared with the control sample. Thus, the Trivedi Effect®-Consciousness Energy Healing Treatment generated a new polymorphic form of cholecalciferol which might offer better solubility, absorption, bioavailability, and be thermally more stable compared with the control sample. Henceforth, the Consciousness Energy Healing Treated cholecalciferol would be more beneficial to maintain the overall quality of life and it would be more useful in designing novel nutraceutical/pharmaceutical formulations for the better therapeutic responses against deficiency of vitamin D, osteoporosis, rickets, cardiovascular diseases, diabetes mellitus, cancer, mental disorders, multiple sclerosis, etc.
Hematopoietic Cell Transplantation for Central Nervous System Embryonal Tumors and Ependymoma

tumors have shown comparable or improved survival (both event-free survival and overall survival) compared with historical controls treated with conventional therapy, with or without radiotherapy, particularly in individuals with disease considered high risk. In a retrospective comparative study, survival in individuals receiving HDC with HCT and delayed craniospinal irradiation (CSI) was comparable with survival in those receiving upfront CSI. Overall, data from these observational studies have suggested HCT may allow reduced doses of craniospinal irradiation without worsening survival outcomes. The evidence is sufficient to determine that the technology results in a meaningful improvement in the net health outcome. For individuals who have recurrent or relapsed CNS embryonal tumors who receive autologous HCT, the evidence includes prospective and retrospective single-arm studies and a systematic review of these studies. The relevant outcomes are overall survival, disease-specific survival, and treatment-related mortality and morbidity. For recurrent/relapsed CNS embryonal tumors, survival outcomes after HCT vary, and survival is generally very poor for tumors other than medulloblastoma. Data from some single-arm studies using autologous HCT to treat recurrent CNS embryonal tumors have shown comparable or improved survival compared with historical controls treated with conventional therapy for certain individuals. The results of a 2012 systematic review of observational studies in individuals with relapsed supratentorial primitive neuroectodermal tumor suggested that a subgroup of infants with chemosensitive disease might benefit from autologous HCT, achieving survival without the use of radiotherapy, whereas outcomes in older children and/or in pineal location are poor with this modality. However, a relatively large prospective multicenter study has reported that HCT was not associated with improved survival outcomes in individuals who had a good response to therapy. Overall, data from these single-arm studies have suggested HCT may be associated with improved survival outcomes in select individuals, although data for some tumor types are limited (e.g., atypical teratoid/rhabdoid tumors). The evidence is sufficient to determine that the technology results in a meaningful improvement in the net health outcome.
EVALUATION OF HERBAGE YIELD AND NUTRITIVE VALUE OF EIGHT FORAGE CROP SPECIES

Determining nutritional quality of indigenous forage species constitutes prerequisite to improve the productivity of ruminants. This research was carried out at the research field of the Agricultural Research and Application Center of Igdır University, Turkey in consecutive two years (2015 & 2016) to evaluate the herbage yield and nutritive value of eight forage species having diverse genetic make-up. Eight forage species such as Kentucky bluegrass (Poa pratensis var. Geromino), Perennial rye-grass (Lolium perenne var. Ovation), Red rescue (Festuca rubra rubra var. Corail), Slender creeping red fescue (Festuca rubra tricphylla var. Pinafore), Sheep fescue (Festuca ovina var. Ridu), Tall fescue (Festuca arundinaceae var. Jaguar 4G), Chewings fescue (Festuca comutata var. Longfellow II) and Colonial bentgras (Agrostis tenuis var. Aristata) were used as plant materials and the experiment was arranged in a randomized complete design with three replications. Data on biomass yield, crude ash, crude protein, crude oil, crude cellulose, net digestible fiber (NDF), acid detergent fiber (ADF), dry matter intake (DMI), digestible dry matter (DDM) and relative feed value (RFV) were recorded during the investigation. Results of the present study indicated that species ‘Tall fescue’ (Festuca arundinaceae var. Jaguar 4G) yielded the highest herbage yield, followed by cultivar ‘Perennial rye-grass’ (Lolium perenne var. Ovation). While, ‘Kentucky bluegrass’ (Poa pratensis var. Geromino) was found to be inferior to all other forage species in the studied years. When nutritional quality was observed, the species ‘Colonial bentgrass’ (Agrostis tenuis var. Aristata) had the maximum crude protein and RFV, while cultivar ‘Perennial rye-grass’ had significantly higher RFV, DMI, DMD and the minimum fiber content, which indicated its superior quality for milch animals.
Clozapine acute administration modified neuronal ATPase activity in spontaneously hypertensive rats

It has been previously reported that the peptide neurotensin (NT) produces an inhibitory effect on Na, K-ATPase (NKA) activity without changes in Mg-ATPase activity in Wistar rats. Clozapine i.p. administration, an atypical antipsychotic, 30 min before cortical membrane preparation produced a stimulatory effect at 10 mg/kg clozapine. Taking into account these results, it is of interest to study the effect of neurotensin after clozapine administration on spontaneously hypertensive (SH) and Wistar Kyoto (WKY) rats. Spontaneously hypertensive rat is considered as a model of schizophrenia because this strain develops behavioural deficits in a social context which are attenuated by acute clozapine administration. Experiments conducted in cortical synaptosomal membranes led to a significant increase in NKA activity in both SH and WKY rats after clozapine administration. Neurotensin only produced NKA inhibition in WKY rats, which were previously administered with clozapine. It was observed that this treatment increases the NKA activity values, making it possible to observe the inhibitory effect of neurotensin. But, the increase in NKA activity values were not enough to confirm the inhibitory effect of neurotensin on NKA activity in SH rats. The lack of this neurotensin effect can be explained by the existence of plasma membrane alteration due to hypertensive state, which resulted in modifications of enzymes or receptors inserted into the plasma membrane, and hence the ATPase modulation by the peptide was also modified.
9 No More than Meets the Eye Shadows as Pure Visibilia

Commonsense and traditional metaphysics alike accord shadows a secondary status in the order of things, relegating them from the first rank of genuine substances.1 Recall, for example, Shirley’s famous lyric: ‘The Glories of our blood and state / Are shadows, not substantial things’. Or how in Shakespeare’s play, Marcus Andronicus, bemoans of his brother, Titus, that ‘grief has so wrought on him, He takes false shadows for true substances’ (III.ii.79–80). Concerning metaphysics, consider this passage from P.M.S. Hacker:
A survey of game theoretic approach for adversarial machine learning

The field of machine learning is progressing at a faster pace than ever before. Many organizations leverage machine learning tools to extract useful information from a massive amount of data. In particular, machine learning finds its application in cybersecurity that begins to enter the age of automation. However, machine learning applications in cybersecurity face unique challenges other domains rarely do—attacks from active adversaries. Problems in areas such as intrusion detection, banking fraud detection, spam filtering, and malware detection have to face challenges of adversarial attacks that modify data so that malicious instances would evade detection by the learning systems. The adversarial learning problem naturally resembles a game between the learning system and the adversary. In such a game, both players would attempt to play their best strategies against each other while maximizing their own payoffs. To solve the game, each player would search for an optimal strategy against the opponent based on the prediction of the opponent's strategy choice. The problem becomes even more complicated in settings where the learning system may have to deal with many adversaries of unknown types. Applying game‐theoretic approach, robust learning techniques have been developed to specifically address adversarial attacks and the preliminary results are promising. In this review, we summarize these results.