Miracle-dz/UniFAR-FTUs huggingface dataset:
A beam position monitor for electron bunch detection in the presence of a more intense proton bunch for the AWAKE Experiment

The Advanced Proton Driven Plasma Wakefield Experiment (AWAKE) at CERN uses 6 cm long proton bunches extracted from the Super Proton Synchrotron (SPS) at 400 GeV beam energy to drive high gradient plasma wakefields for the acceleration of electron bunches to 2 GeV within a 10 m length. Knowledge and control of the position of both copropagating beams is crucial for the operation of the experiment. Whilst the current electron beam position monitoring system at AWAKE can be used in the absence of the proton beam, the proton bunch signal dominates when both particle bunches are present simultaneously. A new technique based on the generation of Cherenkov diffraction radiation (ChDR) in a dielectric material placed in close proximity to the particle beam has been designed to exploit the large bunch length difference of the particle beams at AWAKE, 200 ps for protons versus a few ps for electrons, such that the electron signal dominates. Hence, this technique would allow for the position measurement of a short electron bunch in the presence of a more intense but longer proton bunch. The design considerations, numerical analysis and plans for tests at the CERN Linear Electron Accelerator for Research (CLEAR) facility are presented.
Breast Cancer Detection based on 3-D Mammography Images using Deep Learning Strategies

In recent scenario, women are suffering from breast cancer disease across the world. Mammography is one of the important methods to detect breast cancer early; that to reduce the cost and workload of radiologists. Medical image processing is a tremendous technique used to determine the disease in advance to reduce the risk factor. To predict the disease from 2-D mammography images for diagnosing and detecting based on advanced soft computing paradigm. Still, to get more accuracy in all coordinate axes, 3-D mammography imaging is used to capture depth information from all different angles. After the reconstruction of this process, a better quality of 3D mammography is obtained. It is useful for the experts to identify the disease in well advance. To improve the accuracy of disease findings, deep convolution neural networks (CNN) can be applied for automatic feature learning, and classifier building. This work also presents a comparison of the other state of art methods used in the last decades.
Diagnosing modeling errors in global terrestrial water storage interannual variability

Abstract. Terrestrial water storage (TWS) is an integrative hydrological state that is key for our understanding of the global water cycle. The TWS observation from the GRACE missions has, therefore, been instrumental in the calibration and validation of hydrological models and understanding the variations in the hydrological storage. The models, however, still show significant uncertainties in reproducing observed TWS variations, especially for the interannual variability (IAV) at the global scale. Here, we diagnose the regions dominating the variance in globally integrated TWS IAV and the sources of the errors in two data-driven hydrological models that were calibrated against global TWS, snow water equivalent, evapotranspiration, and runoff data. We used (1) a parsimonious process-based hydrological model, the Strategies to INtegrate Data and BiogeochemicAl moDels (SINDBAD) framework and (2) a machine learning, physically based hybrid hydrological model (H2M) that combines a dynamic neural network with a water balance concept. While both models agree with the Gravity Recovery and Climate Experiment (GRACE) that global TWS IAV is largely driven by the semi-arid regions of southern Africa, the Indian subcontinent and northern Australia, and the humid regions of northern South America and the Mekong River basin, the models still show errors such as the overestimation of the observed magnitude of TWS IAV at the global scale. Our analysis identifies modeling error hotspots of the global TWS IAV, mostly in the tropical regions including the Amazon, sub-Saharan regions, and Southeast Asia, indicating that the regions that dominate global TWS IAV are not necessarily the same as those that dominate the error in global TWS IAV. Excluding those error hotspot regions in the global integration yields large improvements in the simulated global TWS IAV, which implies that model improvements can focus on improving processes in these hotspot regions. Further analysis indicates that error hotspot regions are associated with lateral flow dynamics, including both sub-pixel moisture convergence and across-pixel lateral river flow, or with interactions between surface processes and groundwater. The association of model deficiencies with land processes that delay the TWS variation could, in part, explain why the models cannot represent the observed lagged response of TWS IAV to precipitation IAV in hotspot regions that manifest as errors in global TWS IAV. Our approach presents a general avenue to better diagnose model simulation errors for global data streams to guide efficient and focused model development for regions and processes that matter the most.
A Modular Approach for the Analysis of Blockchain Consensus Protocol Under Churn (Poster)

Blockchain is an emerging technology that gained a lot of attention in the last years. Many different consensus protocols have been proposed to improve both the scalability and the resilience of existing blockchain. However, all these solutions have been defined for rather static settings. We propose a modular approach for analysing and comparing different consensus protocols used in blockchain under churn.
Effect of different concentrations of plant growth hormones on callus induction and regeneration of Shea tree ( Vitellaria paradoxa )

The slow natural regeneration pattern of the Shea tree due to the long gestation period and intense harvest has limited the domestication and genetic improvement of this tree. These limitations have necessitated the need for an alternative method of conserving the Shea tree outside the natural habitat. The propagation of the Shea tree by the in-vitro clonal technique presents such an alternative method. The purpose of this study was to determine the optimal concentration of 2, 4-dichlorophenoxyacetic acid (2, 4-D) and Picloram in Murashige and Skoog medium for callus formation and regeneration. The first experiment was done to achieve the best surface sterilization method and the effect of different concentrations of 2, 4-D or Picloram on callus formation. Callus induction percentage (CI%) of the explants in Murashige and Skoog medium were evaluated. The basal media were supplemented with 30 g/L of sucrose, 2.8 g/L phytagel and combinations of 2, 4-D or Picloram in various concentrations (1.5, 2.0, 2.5, 3.0, 3.5, 4.0, and 4.5 mg/L) replicated four times with five explants in each bottle. From the result, the leaf explants soaked in 70% ethanol for 1 min and 1% sodium hypochlorite for 15 min with 1 µl of tween 20 had the highest percentage (100%) of sterile leaf explants and showed no contaminations both in the leaf and media. Callus was induced at 2 weeks of culturing in all the treatments except for MS basal without growth hormone which induced no callus. A concentration of 1.5 mg/ L 2, 4-D gave the best callus. The highest CI% (100%) was shown at 4 weeks in MS + 3.5 mg/L picloram media. The callus was light in colour and friable in texture. The result indicated that Picloram gave better callus compared to other treatments and will give a better response for regeneration of Shea tree.
A Bose‐Einstein condensate in a 𝒫𝒯 symmetric double well

The existence of 𝒫𝒯 symmetric wave functions describing Bose‐Einstein condensates in a one‐dimensional and a fully three‐dimensional double‐well setup is investigated theoretically. When particles are removed from one well and coherently injected into the other the external potential is 𝒫𝒯 symmetric. We solve the underlying Gross‐Pitaevskii equation by way of the time‐dependent variational principle (TDVP) and show that the 𝒫𝒯 symmetry of the external potential is preserved by both the wave functions and the nonlinear Hamiltonian as long as eigenstates with real eigenvalues are obtained. 𝒫𝒯 broken solutions of the time‐independent Gross‐Pitaevskii equation are also found but have no physical relevance. To prove the applicability of the TDVP we compare its results with numerically exact solutions in the one‐dimensional case. The linear stability analysis and the temporal evolution of condensate wave functions demonstrate that the 𝒫𝒯 symmetric condensates are stable and should be observable in an experiment.
Large-Scale Daily Snow Density Mapping with Spatiotemporally Aware Model and Multi-Source Data”

Snow density plays a critical role in the estimation of snow water equivalent (SWE). Predicting a temporally and spatially variant snow density is not trivial and is usually assume constant for SWE estimates. This study presents a geographically and temporally weighted neural network (GTWNN) model to predict daily snow density across China. This work relies on empirical relations with influencing variables and machine learning algorithm, to predict density over time and space. This work proposes a great way to map 15 snow density over China, but further clarifications are needed before publications. In general, no physical understanding of snow density with influencing variable was explored or used in the modelling. This method relies purely on empirical relations. Not those empirical relations cannot be used but perhaps adding a bit more physical understanding in the variables selection or using a physical model at the regional scale could improve this work. 20
An Ideal Observer for Appearance: Reconstruction from Samples

Note: This report provides additional technical detail related to the Bayesian demosaicing method outlined in Brainard, D. H. (1994) Bayesian method for reconstructing color images from trichromatic samples. (1995) Reconstructing images from trichromatic samples: from basic research to practical applications. Image representation. I represent an image by the discrete function i(x i , y j , λ k). The coordinates x i (1 ≤ i ≤ N rows) and y j (1 ≤ j ≤ N cols) represent N rows N cols evenly spaced sample locations on a rectangular grid. This grid should be much denser than the sampling array being studied. The λ k (1 ≤ k ≤ N wls) represent the different color bands in the image. The λ k represent evenly spaced sample wavelengths throughout the visible spectrum, so that the entire function i(x i , y j , λ k) represents the spectrum at each image location. The use of discrete representations for both spatial position and wavelength has been discussed extensively elsewhere. i =1 +((n–1)moduloN rows) j =1 +((n–1)/N rows moduloN cols) k =1 + (n–1)/(N rows N cols) (1) This choice of indexing enumerates all of the values of the discrete function i(x i , y j , λ k). Sampling. Consider the relation between the response of a single receptor and the image data. Each receptor is completely characterized by a polychromatic receptive field, which specifies how strongly it responds to light from each color band at each location in the image. The receptive field of a single sensor may be described by a function s(x i , y j , λ k). The response r of the receptor is given by Σ i,j,k +e (2) Reconstruction from samples 3 where e is a random variable representing sensor noise. Note that this receptive field specification allows us to handle any optical blurring that precedes spatial samping, arbitrary sampling geometry, and the fact that different photoreceptors have different spectral sensitivities. We can rewrite Eq. 2 as r= s i+e (3) where the N rows N cols N wls dimensional row vector s is the vector representation of s(x i , y j , λ k). Suppose there are N rec sensors in the overall camera array, enumerated by the index m. The responses of all the sensors can be represented by a single N rec dimensional column vector r whose m th entry is …
A Study of Width Bounded Arithmetic Circuits and the Complexity of Matroid Isomorphism[HBNI TH 17]

The subject of computational complexity theory deals with characterization of computational problems with respect to various resource measures. This thesis can broadly be divided into two parts: (1) Study of width bounded arithmetic circuits and (2) Computational complexity of matroid isomorphism problems. In the first part of the thesis we further the study of various arithmetizations of boolean complexity class NC. In particular, we propose constant width arithmetic circuits of polynomial degree as a new possible arithmetization of NC. Among the candidate arithmetizations of NC, constant width arithmetic circuits seem to be the larger ones. In particular, it is not known if constant width arithmetic circuits of polynomial size and degree can be efficiently simulated by arithmetic formulas of polynomial size. However, the situation changes when we restrict ourselves to syntactic multilinear circuits. We show that constant width syntactic multilinear circuits are equivalent to constant width syntactic multilinear branching programs at polynomial size and hence contained inside syntactic multilinear polynomial size formulas. This makes syntactic multilinear formulas as the stronger one among the competent classes in the syntactic multilinear world. Moving a step further, we show that the only known technique of simulating arithmetic formulas by constant width algebraic branching programs due to Ben-Or and Cleve does not preserve syntactic multilinearity. Moreover, for a generalized version of Ben-Or and Cleve’s technique, we show a linear lower bound on the number of registers if it is to preserve syntactic multilinearity. Also, we propose width of the arithmetic circuit as a possible measure of space for arithmetic computations. This definition gives a reasonable definition of lower space complexity classes compared to the existing notions of space. We also define and propose read-once certificates as a natural model of nondeterminism for space bounded arithmetic computations. In the second part we study the complexity of isomorphism problem on matroids. We classify the problems according to how the input matroids are represented. In the most general case, when the matroids are given as independent set oracles, the problem is in Σp2, the second level of the polynomial hierarchy. For linear matroids, we show that isomorphism testing is in Σp2, and is unlikely to be Σp2 complete. However when the rank of the given input matroid is a constant, the problem is polynomial timemany-one equivalent to the graph isomorphism problem. For the case of matroids represented by graphs, we show that the isomorphism testing problem is polynomial time equivalent to the graph isomorphism problem. Along the way, we develop colouring techniques for handling coloured instances of matroid isomorphism problems. We also prove polynomial time equivalence of isomorphism testing problem and the problem of computing automorphism groups for the case of linear and graphic matroids.
Effect of Medicinal Plants and Natural Products on Liver Enzymes in Non-alcoholic Fatty Liver Patients in Iran: A Systematic Review and Meta-Analysis

Background: Nonalcoholic fatty liver is the most common chronic liver disease. Regarding the side effects of synthetic medicines and the variety of natural products in Iran climate, the present study aimed to investigate the effect of medicinal plants and natural products on liver enzymes in patients with non-alcoholic fatty liver disease in Iran using meta-analysis. Methods: To extract the intended studies, internal and external databases, including SID, Magiran, IranDoc, PubMed, Scopus, Web of Science, Embase, Cochrane, and Clinical Trial Registration System of Clinical trial.gov, the ISRCTN system, as well as Clinical Trial Registration System affiliated to the World Health Organization were searched. The obtained data were analyzed in STATA.14 software. A P value less than 0.05 was considered statistically significant. Results: A total of 44 rstudies were reviewed with a sample size of 1298 participant; they were published in the period from 2009 to 2018, silymarin had the highest effect on the reduction of AST (SMD = -2.68), cinnamon excreted the most profound effect on ALT (SMD = -2.69). In addition, cinnamon had the highest effect on gamma-glutamyl transferase (GGT) (SMD:-3.17), and curcumin had the highest effect on alkaline phosphatase (ALP) (SMD = -1.88). In the lipid profile, the effect of medicinal herbs and natural products on lowering total cholesterol and LDL was statistically significant. In the glycemic profile, the effect of medicinal plants and natural products on the reduction of fasting blood sugar, insulin, and hemoglobin A1c levels was statistically significant. Conclusions: As evidenced by the obtained results, the highest effect of using natural products was observed in the reduction of GGT, aspartate aminotransferase (AST), and alanine aminotransferase (ALT) levels, respectively; nonetheless, the effect of natural products on ALP reduction was not statistically significant.
Anti-Inflammatory and Phytochemical Analysis of the Crude Leaves Extracts of Boscia Coriacea Graells and Uvaria Leptocladon Oliv

Background The objective of this study was to evaluate the anti-inflammatory activities and phytochemical composition of the leaves extracts of Boscia coriacea Graells and Uvaria leptocladon Oliv. Methods The powdered leaves of Boscia coriacea Graells and Uvaria leptocladon Oliv were extracted by maceration and soxhlet extraction methods. Anti-inflammatory activity of the leaves extracts of Boscia coriacea Graells and Uvaria leptocladon Oliv were evaluated using carrageenan-induced paw edema model. Standard methods were used for analysis of phytochemical composition of the leaves extracts of Boscia coriacea Graells and Uvaria leptocladon Oliv. Data analysis was done using one way analysis of variance. Results U. leptocladon Oliv (200 mg/kg) and B. coriacea Graells (200 mg/kg) showed percent inhibition on mice paw edema of 86% and 75% after six hours of carrageenan injection, respectively. The ethanol fraction (100 mg/kg) of U. leptocladon Oliv showed the highest anti-inflammatory effect after six hours of carrageenan injection. The phytochemical analysis of the leaves extracts of B. coriacea and U. leptocladon revealed the presence of tannins, alkaloids, cardiac glycoside, flavonoids, phenols, quinones, and saponins. Conclusion The crude leaves extracts of B. coriacea Graells and U. leptocladon Oliv contain phytochemicals with anti-inflammatory activities.
A brief transdiagnostic psychological intervention for Afghan asylum seekers and refugees in Austria: a randomized controlled trial

ABSTRACT Background: Afghan refugees often face hardship and traumatic experiences before, during, and after migration and frequently suffer from mental health burdens. Evidence based psychological treatments for refugees mostly focus on symptoms of posttraumatic stress disorder (PTSD), however, refugees often suffer from a variety of general health problems as well as depression and anxiety. We thus aimed to evaluate the effectiveness of a transdiagnostic psychological intervention. Objective: To investigate the effectiveness of an adapted version of Problem Management Plus (aPM+) delivered by mental health professionals to adult Afghan refugees and asylum seekers. Methods: We randomly allocated 88 Afghan refugees either to aPM+ in addition to treatment as usual (aPM+/TAU) or TAU alone. APM+ comprises of six weekly 90-minute individual sessions including strategies of stress management, problem solving, behavioural activation, strengthening social support and either anger regulation or increasing self-efficacy. The primary outcome was general health (GHQ-28) post intervention. Secondary outcome measures included distress by PMLD, Complex PTSD symptoms, quality of life, self-identified problems, and integration. Results: Attrition was high: 42% of the randomized participants did not participate in the post-treatment assessment. A repeated measures per-protocol (completers only) ANCOVA evidenced a significant group × timepoint interaction for GHQ total scores [F(1, 47) = 14.80, p < . 001, partial η2 = 0.24]. Post-hoc analyses showed significantly lower symptoms in the aPM+/TAU arm (n = 26) as compared to the TAU arm (n = 25) for the GHQ total scores (dz = 1.04). Most secondary outcomes significantly improved in the aPM+/TAU arm, but not in the TAU arm. Conclusion: APM+ was effective in reducing general health problems in Afghan refugees and might be considered as a first-line intervention. High drop-out rate limit the interpretations of our results, where future investigations should focus on possibilities to reduce these rates. Trial registration: Uniform Trial Number identifier: U1111-1226-3285. HIGHLIGHTS Refugees’ mental health can be strengthened with a brief psychological intervention that also focuses on skills in the context of post-migration stressors. High drop-out rates are a major challenge for future research and delivery of psychological interventions as part of health care systems to refugees and asylum seekers.
Effect of cyanocobalamin (vitamin B12) on paraquat-induced brain injury in mice

Objective(s): The goal of this study was to evaluate the neuroprotective effects of vit B12 on paraquat-induced neurotoxicity. Materials and Methods: Thirty-six male mice were randomly divided into six groups. Three groups were treated intraperitoneally with paraquat (10 mg/kg) twice a week (with a 3-day interval) for 3 weeks. Normal saline, vit B12 (1 mg /kg), or vit C (50 mg/kg) was injected 30 min before paraquat administration. Other groups only received normal saline (control), vit B12, or vit C in the same protocol. Motor performance and coordination were assayed by challenging beam traversal, pole, open field, and rotarod tests. The hippocampus and serum samples were isolated to evaluate the oxidative stress (GSH and ROS), apoptosis (caspase 3), and inflammatory markers (TNF-α and IL-1β). Results: Administration of paraquat leads to induction of motor deficits, which were improved by treatment with vit B12. In addition, vit B12 could prevent oxidative damage, apoptosis, and inflammation caused by paraquat. Conclusion: It seems that vit B12 could be a novel therapeutic agent in the management of paraquat induced-neurotoxicity.