Miracle-dz/UniFAR-FTUs huggingface dataset:
BAYESIAN TECHNIQUES FOR ACCELERATOR CHARACTERIZATION AND CONTROL

Accelerators and other large experimental facilities are complex, noisy systems that are difficult to characterize and control efficiently. Bayesian statistical modeling techniques are well suited to this task, as they minimize the number of experimental measurements needed to create robust models, by incorporating prior, but not necessarily exact, information about the target system. Furthermore, these models inherently take into account noisy and/or uncertain measurements and can react to time-varying systems. Here we will describe several advanced methods for using these models in accelerator characterization and optimization. First, we describe a method for rapid, turn-key exploration of input parameter spaces using little-to-no prior information about the target system. Second, we highlight the use of Multi-Objective Bayesian optimization towards efficiently characterizing the experimental Pareto front of a system. Throughout, we describe how unknown constraints and parameter modification costs are incorporated into these algorithms.
The history of cerebral PET scanning

Objective: To review the discoveries underpinning the introduction of cerebral PET scanning and highlight its modern applications. Background: Important discoveries in neurophysiology, brain metabolism, and radiotracer development in the post–World War II period provided the necessary infrastructure for the first cerebral PET scan. Methods: A complete review of the literature was undertaken to search for primary and secondary sources on the history of PET imaging. Searches were performed in PubMed, Google Scholar, and select individual journal Web sites. Written autobiographies were obtained through the Society for Neuroscience Web site at www.sfn. org. A reference book on the history of radiology, Naked to the Bone, was reviewed to corroborate facts and to locate references. The references listed in all the articles and books obtained were reviewed. Results: The neurophysiologic sciences required to build cerebral PET imaging date back to 1878. The last 60 years have produced an evolution of technological advancements in brain metabolism and radiotracer development. These advancements facilitated the development of modern cerebral PET imaging. Several key scientists were involved in critical discoveries and among them were Angelo Mosso, Charles Roy, Charles Sherrington, John Fulton, Seymour Kety, Louis Sokoloff, David E. Kuhl, Gordon L. Brownell, Michael Ter-Pogossian, Michael Phelps, and Edward Hoffman. Conclusions: Neurophysiology, metabolism, and radiotracer development in the postwar era synergized the development of the technology necessary for cerebral PET scanning. Continued use of PET in clinical trials and current developments in PET-CT/MRI hybrids has led to advancement in diagnosis, management, and treatment of neurologic disorders.
Area and Power Efficient Trellis Computational Blocks in 0 . 13 μ m CMOS

Improved add-compare-select and branch metric units are presented to reduce the complexity in the implementation of trellis-based decoding architectures. These units use a complementary property of the best rate1/2 convolutional codes to reduce both area requirements and power consumption in a silicon implementation with no loss in decoding performance. For a 0. 13μm CMOS process, synthesized computational blocks for decoders that can process codes from memory 2 up to 7 show up to 17% savings in both cell area and power consumption. I. I NTRODUCTION Trellis-based decoding is a popular method to recover encoded information corrupted during transmission over a noisy channel. For example, the Viterbi algorithm (VA) [1] and the BCJR algorithm [2] are two schemes that work on an underlying trellis description of the encoded sequence. Note that the BCJR in the logarithmic domain (logMAP algorithm [3]) is commonly used in turbo decoding schemes. Basic computations in either algorithm involve branch metric (BM) calculations and add-compare-select (ACS) operations. In case of the VA, an ACS operation successively discards branches that are not part of the survivor path. In case of the logMAP, this operation corresponds to an Add-MAX ? operation [4] to recursively calculate forward and backward state metrics. However, this is basically an ACS operation with an added offset (ACSO) to correct for the Jacobian logarithm. Thus, the presented results for the ACS hold for the ACSO as well. Almost all good rate1/n convolutional codes, n an integer, have the property that the code symbol labels on the two branches into each trellis node are complementary. In an earlier paper [5], we used this property and presented architectural simplifications for these units. Here, we apply this idea to see how these arithmetic savings translate into area and power savings in a silicon implementation. We start by briefly reviewing notation and necessary modifications in the following section. Then, architectural issues for a hardware realization are addressed in Section III. We also present a variation that trades area for speed. As a case study, a computational kernel for Viterbi decoding is synthesized. The synthesis results in Section IV confirm the benefits of these approaches compared to a traditional setup. Also, power savings are estimated at gate level. λ(s′ → s)
The polynomial approach to the LQ non-Gaussian regulator problem

A new approach for the solution of the regulator problem for linear discrete-time dynamical systems with non-Gaussian disturbances is proposed. This approach generalizes a previous result concerning the definition of the quadratic optimal regulator. It consists of the definition of the polynomial optimal algorithm of an order /spl nu/ for the solution of the linear quadratic non-Gaussian stochastic regulator problem for systems with partial state information. The validity of the separation principle has also been proved in this case. Numerical simulations show the high performance of the proposed method with respect to the classical linear regulation techniques.
Overstory density and disturbance impacts on the resilience of coniferous forests of western Oregon

approved: _____________________________________________________________________ Klaus J. Puettmann A trait based approach was used to assess impacts of overstory density and thinning on understory vegetation components related to wildlife habitat. The relationship between overstory basal area and understory vegetation for species grouped by traits, such as production of flowers, fleshy-fruit and palatable leaves, was characterized in thinned and unthinned stands at seven Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) forests in western Oregon six years following harvests. The ranges of overstory densities within thinned and unthinned stands represent gradients of resource availability and thinning disturbance. Lower overstory densities and thinnings were associated with improved ecosystem functions, specifically the provision of wildlife habitat, as evident by higher cover of flowering and fleshy-fruit and palatable leaf producing species. Greater cover of drought, fire and heat tolerant species in low density stands and after thinnings suggested that these ecosystem functions are more likely to be maintained under climate change conditions, indicating higher resilience. The response of specific functions and response types reflect the traits characteristic for each species group and the impact of these traits on sensitivity to resource availability and disturbances. Thus, the correlation between grouping criteria and the main gradients created by management activities can provide an indication of the expected vegetation response, and therefore the impact of management practices on resilience. ©Copyright by Andrew R. Neill March 9, 2012 All Rights Reserved Overstory Density and Disturbance Impacts on the Resilience of Coniferous Forests of Western Oregon
The Macroeconomic Uncertainty Premium in the Corporate Bond Market—Corrigendum

We investigate the role of economic uncertainty in the cross-section of corporate bonds and document significant uncertainty premium for both investment-grade (0.42% per month) and non-investment-grade (0.94% per month) bonds. The bond uncertainty premium is not a manifestation of equity uncertainty premium and is driven by the outperformance of corporate bonds with high uncertainty risk. We also introduce an uncertainty beta factor and show that the newly proposed factor has significant risk premia that cannot be explained by long-established stock and bond market factors. We examine the cross-sectional relation between uncertainty and firm fundamentals and find that firms with higher exposure to economic uncertainty have lower profitability and lower net income. This Version: June 2018
Homocysteine as a potential biochemical marker for depression in elderly stroke survivors

Background Elderly stroke survivors have been reported to be at risk of malnutrition and depression. Vitamin B-related metabolites such as methylmalonic acid and homocysteine have been implicated in depression. Objective We conducted a study exploring the relationship between homocysteine and post-stroke depression. Design Three methodologies were used: Observational cohort study of elderly Swedish patients (n=149) 1.5 years post-stroke, assessed using Diagnostic and Statistical Manual of Mental Disorders, Montgomery Åsberg Depression Rating Scale and serum blood levels of methylmalonic acid and homocysteine. Results Homocysteine significantly correlated with depressive symptomatology in stroke survivors (β=0.18*). Individuals with abnormal levels of methylmalonic acid and homocysteine were almost twice more likely to show depressive symptomatology than those with normal levels (depressive symptoms 22%; no depressive symptoms 12%). Comparison of methylmalonic acid and homocysteine levels with literature data showed fewer stroke survivors had vitamin deficiency than did reference individuals (normal range 66%; elevated 34%). Conclusions Homocysteine is significantly associated with depressive symptomatology in elderly Swedish stroke survivors.
Lucas-Kanade 20 Years On: A Unifying Framework: Part 3

Since the Lucas-Kanade algorithm was proposed in 1981 image alignment has become one of the most widely used techniques in computer vision. Applications range from optical flow, tracking, and layered motion, to mosaic construction, medical image registration, and face coding. Numerous algorithms have been proposed and a variety of extensions have been made to the original formulation. We present an overview of image alignment, describing most of the algorithms in a consistent framework. We concentrate on the inverse compositional algorithm, an efficient algorithm that we recently proposed. We examine which of the extensions to the Lucas-Kanade algorithm can be used with the inverse compositional algorithm without any significant loss of efficiency, and which cannot. In this paper, Part 3 in a series of papers, we cover the extension of image alignment to allow linear appearance variation. We first consider linear appearance variation when the error function is the Euclidean L2 norm. We describe three different algorithms, the simultaneous, project out, and normalization inverse compositional algorithms, and empirically compare them. Afterwards we consider the combination of linear appearance variation with the robust error functions described in Part 2 of this series. We first derive robust versions of the simultaneous and normalization algorithms. Since both of these algorithms are very inefficient, as in Part 2 we derive efficient approximations based on spatial coherence. We end with an empirical evaluation of the robust algorithms.
Variogram Analyses of Soil Characters in Glacial Moraine Landscapes

The objective of this research is to analyze variogram analyses of soil characters in Glacial Moraine Landscapes. The research site is located in sloping landscapes, Kuehren, North Germany. The survey method was detailed using maps with scales of 1:5,000. Soil sampling was performed by soil pits and borings and completely analyzed in laboratory. Collected data were evaluated by geostatistics program for spatial soil variability analyses. The variogram models show that spatial soil variability ranges between 70-120 m (mean: 85 m). Effective distances of sampling are calculated at around 50 m. The range values of soil characters are proportional with the range of elevation (range: 70 m, effective distance: 40 m). The relief determines mainly the spatial variability of soil characters.
For the Greater Good? The Devastating Ripple Effects of the Covid-19 Crisis

As the crisis around Covid-19 evolves, it becomes clear that there are numerous negative side- effects of the lockdown strategies implemented by many countries. Currently, more evidence becomes available that the lockdowns may have more negative effects than positive effects. For instance, many measures taken in a lockdown aimed at protecting human life may compromise the immune system, and purpose in life, especially of vulnerable groups. This leads to the paradoxical situation of compromising the immune system and physical and mental health of many people, including the ones we aim to protect. Also, it is expected that hundreds of millions of people will die from hunger and postponed medical treatments. Other side effects include financial insecurity of billions of people, physical and mental health problems, and increased inequalities. The economic and health repercussions of the crisis will be falling disproportionately on young workers, low-income families and women, and thus exacerbate existing inequalities. As the virus outbreak and media coverage spread fear and anxiety, superstition, cognitive dissonance reduction and conspiracy theories are ways to find meaning and reduce anxiety. These behavioral aspects may play a role in the continuance of lockdown decisions. Based on theories regarding agnotology (i.e. the ways ignorance or doubt about certain topics is created by means of withholding or presenting information in a certain way), social influence, superstition and stress and coping, I seek to explain the social and behavioral aspects of human behavior in times of crises. Both the Covid-19 crisis itself as well as the resulting economic and (mental) health crisis are global problems that may require global solutions. I present a model of drivers and outcomes of lockdown behaviors and offer suggestions and a tool to counteract the negative psychological effects by means of online life crafting therapeutic writing interventions.
The impact of sea ice on the periodic shallow water dynamics in the Laptev Sea (Siberian Arctic)

The impact of sea ice on the periodic currents in the eastern Laptev Sea was evaluated in 19981999 within the framework of the Russian-German project Laptev Sea System 2000. Acoustic Doppler current profiler (ADCP) records from two moorings deployed for one year were analyzed. Ice conditions, as derived from remote sensing and ADCPdata, were shown to significantly affect surface circulation down into the pycnocline layer. With fall freeze-up, the tidal currents shift from a barotropic to a baroclinic regime and are furthermore amplified in the pycnocline. Opening of polynyas induces a return to the initial barotropic mode with surface water dynamics primarily controlled by atmospheric forcing.
Leveraging allelic heterogeneity to increase power of association testing

The standard genome-wide association studies (GWAS) detects an association between a single variant and a phenotype of interest. Recently, several studies reported that at many risk loci, there may exist multiple causal variants. For a locus with multiple causal variants with small effect sizes, the standard association test is underpowered to detect the associations. Alternatively, an approach considering effects of multiple variants simultaneously may increase statistical power by leveraging effects of multiple causal variants. In this paper, we propose a new statistical method, Model-based Association test Reflecting causal Status (MARS), that tries to find an association between variants in risk loci and a phenotype, considering the causal status of the variants. One of the main advantages of MARS is that it only requires the existing summary statistics to detect associated risk loci. Thus, MARS is applicable to any association study with summary statistics, even though individual level data is not available for the study. Utilizing extensive simulated data sets, we show that MARS increases the power of detecting true associated risk loci compared to previous approaches that consider multiple variants, while robustly controls the type I error. Applied to data of 44 tissues provided by the Genotype-Tissue Expression (GTEx) consortium, we show that MARS identifies more eGenes compared to previous approaches in most of the tissues; e.g. MARS identified 16% more eGenes than the ones reported by the GTEx consortium. Moreover, applied to Northern Finland Birth Cohort (NFBC) data, we demonstrate that MARS effectively identifies association loci with improved power (56% of more loci found by MARS) in GWAS studies compared to the standard association test.
Susceptibility of Raccoon Dogs for Experimental SARS-CoV-2 Infection

Animals and Study Design The experimental design followed the general setup of a previous study (1). Fourteen adult, male (n = 4) and female (n = 10) raccoon dogs originating from a commercial farm (Ferma Hodowlana Lisow, 64–050 Wielichowo, Poland) were used. Animals were transported according to European regulations by an international company specialized for transportation of zoo animals (MSO International Zoo Services GmbH; TRACES-No: DE 071. 380.450.267).
Joint effects of intensity and duration of cigarette smoking on the risk of head and neck cancer

Citation for published version (APA): Di Credico, G. , Edefonti, V. , Polesel, J., Pauli, F. , Torelli, N. , Serraino, D. , Negri, E. , Luce, D. , Stucker, I. , Matsuo, K. , Brennan, P. J., Vilensky, M. , Fernandez, L. , Curado, M. P., Menezes, A. , Daudt, A. W. , Koifman, R. , Wunsch-Filho, V. , Holcatova, I. , . Dal Maso, L. (2019). Joint effects of intensity and duration of cigarette smoking on the risk of head and neck cancer: A bivariate spline model approach. Oral Oncology, 94, 47-57. https://doi.org/10.1016/j.oraloncology. 2019.05. 006
Activation of mechanoreflex delays heart rate recovery after exercise in healthy men

5 This study tested the hypotheses that activation of central command and muscle mechanoreflex during 6 post-exercise recovery delay fast-phase heart rate recovery with little influence on slow-phase. Twenty-7 five healthy men underwent three submaximal cycling bouts, each followed by a different 5-min 8 recovery protocol: active (cycling generated by the own subject), passive (cycling generated by external 9 force) and inactive (no-cycling). Heart rate recovery was assessed by the heart rate decay from peak 10 exercise to 30s and 60s of recovery (HRR 30s , HRR 60s -fast-phase) and from 60s-to-300s of recovery 11 (HRR 60-300s -slow-phase). The effect of central command was examined by comparing active and passive 12 recoveries (with and without central command activation) and the effect of mechanoreflex was assessed 13 by comparing passive and inactive recoveries (with and without mechanoreflex activation). Heart rate 14 recovery was similar between active and passive recoveries, regardless of the phase. Heart rate recovery 15 was slower in the passive than inactive recovery in the fast-(HRR 60s =20±8vs.27±10bpm, p<0.01), but 16 not in the slow-phase (HRR 60-300s =13±8vs.10±8bpm, p=0.11). In conclusion, activation of 17 mechanoreflex, but not central command, during recovery delays fast phase heart rate recovery. These 18 results elucidate important neural mechanisms behind heart rate recovery regulation. 19
Genetic diversity studies in groundnut genotypes (Arachis hypogaea L.)

The present study was done to study the extent of diversity among the released and popular varieties of India and advanced cultures in groundnut. D 2 analysis for 15 characters resulted in the formation of nine clusters among the 30 genotypes studied. Highest intra-cluster distance was recorded for cluster VI followed by III, V, II and VII. Maximum inter-cluster distance was recorded between clusters VIII and IX followed by between clusters III and IX and between clusters VII and VIII. Based on mean performance, intra and inter-cluster distance, the genotypes of cluster VI (ALR 1 and COG0539) could be used for increasing the shelling per cent, oil content, pod yield / plant and no. of primary branches / plant. The genotypes in cluster III (CO 1, COG0549 and BSR 2) can be used for improving number of mature pods/ plant, hundred kernel weight, leaf area index and cluster VIII (JL 24) for total biomass and kernel yield / plant for trait based improvement programme.
on the

In March 2020, to contain the spread of the COVID-19 pandemic, almost all educational ecosystems (school, universities and private centres) around the world were forced to cancel face-to-face classes and replace them with didactic instruction online. Various and diversified methods of teaching delivered remotely were activated quickly. These solutions have undoubtedly had the purpose of ensuring the continuity of basic education and institutional activities, but they also made it possible to experiment, on large scale, didactic solution, mediated by screen, at design and didactic mediation level and interaction. The debate around the way educational systems reacted to the emergency is probably going to be a proper theme of investigation for next years. In this respect, (14), argue that the infrastructures for digital education that have been chosen to give a reply to the pandemic crisis, will redefine public education for the future. In addition, other scholars, see for example (2) and (6), have already carried out researches on screen-mediated didactics in the pandemic context. Their studies highlighted some essential specificities for a positive teaching-learning process, mainly related to the sociality and the possibility of working in cooperative environments, the possibility of co-building knowledge in an active way, within a community of practice. Following these lines of research, in this paper, we are aimed at capturing students’ perspectives and perceptions on screen-mediated didactics during the pandemic emergency. Data have been collected through a survey, which consisted of open-ended questions administrated to students attending six teaching large courses, held by four professors in two different Italian universities (Macerata and Chieti-Pescara). In particular, in the research have been involved students who attended course of Educational Sciences degree (45 from the course of “Didactics” and 48 from the course of “Special Pedagogy”). The questionnaire was also administrated to students enrolled in the Primary Education degree programme: 230 from the course of “Technologies for Education and Learning”, 230 from the course “Laboratory of Technologies” and 230 from the course of “General Education”. Finally, there were students who attended the course “Didactics of Training”, enrolled in the Pedagogical Sciences degree. All courses refer to the year 2019/2020. To circumvent the dilemma between the benefit of having open-ended questions and the cost associated with their analysis, we adopt, in this work, an unsupervised topic modelling approach. More in detail, we focus on Structural Topic Modeling (10), which is deemed a variant of Latent Dirichlet Allocation (1), suited to address the strict statistical assumption that all texts in the modelled corpus are generated by the same underlying process. The remainder of the paper is organized as follows. Section 2 describes the unsupervised topic modelling adopted, while Section 3 presents the results. Section 4 contains an interpretation of the main findings and the conclusions.