Miracle-dz/UniFAR-FTUs huggingface dataset:
Simple Semiparametric Estimation of Ordered Response Models: With an Application to the Interdependent Durations Model

We propose two simple semiparametric estimation methods for ordered response models with an unknown error distribution. The proposed methods do not require users to choose any tuning parameter and they automatically incorporate the monotonicity restriction of the unknown distribution function. Fixing finite dimensional parameters in the model, we construct nonparametric maximum likelihood estimates (NPMLE) for the error distribution based on the related binary choice data or the entire ordered response data. We then obtain estimates for finite dimensional parameters based on moment conditions given the estimated distribution function. Our semiparametric approaches deliver root-n consistent and asymptotically normal estimators of the regression coefficient and threshold parameter. We also develop valid bootstrap procedures for inference. We apply our methods to the interdependent durations model in Honore and de Paula (2010), where the social interaction effect is directly related to the threshold parameter in the corresponding ordered response model. The advantages of our methods are borne out in simulation studies and a real data application to the joint retirement decision of married couples.
Relationships between Drosophila Suzukii and grapevine in North-Western Italy: Seasonal presence and cultivar susceptibility

Drosophila suzukii (Matsumura) is an Asian species, and is now widespread also in America and Europe. While it is acknowledged as a serious pest to many soft fruits, its impact on viticulture needs further investigation. This study focused on the relationships between D. suzukii and grapevine in Piedmont (North-western Italy), and was conducted for three seasons in 10 vineyards of six different grape varieties, surrounded by different crops and/or vegetation. Flies were collected using food traps, and grape berries were sampled to assess oviposition. The susceptibility of grape cultivars was analysed in the laboratory by exposing intact berries with a known skin hardness (i.e. skin break force mechanical property) and injured berries to female flies. A choice test was also performed to investigate the preference of D. suzukii for grape juice of different cultivars. Capture of adults in vineyards depended on sampling dates, surrounding vegetation, and years, but few eggs were observed in field-collected berries. Overall, in laboratory experiments, cultivars with soft-skinned berries were more exploited for egg-laying. However, among cultivars, the susceptibility changed depending on whether the berries were intact or injured. Concerning the latter, the most infested cultivars were also the most attractive to flies in the choice test. At present, D. suzukii may not be considered a threat to viticulture in Piedmont. However, considering the influence of grape skin hardness on oviposition and the attractiveness of some grape cultivars, further studies are needed to better understand the relationship between D. suzukii and grapevine.
A CASE FOR ADVANCING POLITICAL LEADERSHIP FOR DOMESTIC INVESTMENT IN SUSTAINING THE AIDS RESPONSE IN AFRICA

TABLE OF CONTENTS Introduction . 2 Changing landscape . 2 Demographic changes and new infections . 2 Changing priorities . 3 Options for increasing resources for HIV/AIDS . 5 Economic growth and stronger systems for increasing government spending.5 More money for health and HIV/AIDS . 6 Improving efficiency. 14 Role of political leadership in reprioritizing HIV/AIDS . 15 Key arguments . 15 Annex 1: Recent Key Outcomes . 18 Annex 2: Resource availability and expenditures . 19 Bibliography . 24
STATUS AND PERSPECTIVE OF THE NB3AL DEVELOPMENT IN JAPAN

The RHQT process enables to form a stoichiometric Nb3Al with fine-grain structures via a bcc supersaturated solid solution and so that a large Jc is achieved over the whole range of magnetic fields without trading off the excellent strain tolerance. A long-length of RHQ processing has been established, and a rectangular but Cu stabilized Nb3Al strand is about to be commercially available for NMR uses. Another stabilization technique has been developed and likely applicable to accelerator uses. Research activities at the KEK with respect to the low field Jc characterization are also described.
ZrCl4-catalyzed one-pot multi-component synthesis of hexahydropyrano pyrimidinone derivatives

In this study, zirconium tetrachloride is used as a highly efficient catalyst for the one-pot three component reaction of 3,4-dihydro(2H)-pyran, urea and benzaldehyde in ethanol, producing corresponding hexahydropyrano pyrimidinone derivatives in good yields, with excellent diastereoselectivity. This method has various benefits such as easy availability of starting materials, lower cost, higher yield and shorter reaction time.
Optimization of anaesthesia care for “total” awake craniotomy with brain tumour resection in a pregnant patient. A case report with a review of the literature

Background. A pre-delivery urgent brain tumour resection may be required if a rapidly growing lesion is having a massive effect. Awake craniotomy is indicated for procedures requiring intraoperative cortical language and sensorimotor stimulation mapping. Speech function monitoring in a conscious and responding patient allows the evaluation of neurological dysfunction before the removal of tissue in order to minimize the risk of neurological complications. Case report. We describe a total awake craniotomy for the resection of a left parietal brain tumour with intra-procedural speech mapping in a 31-year-old woman in the 22 week of gestation. Throughout the surgical procedure, the patient was in monitored anaesthesia care (MAC) at minimal and moderate sedation. Intraoperative analgesia was maintained with infusion of remifentanil and a scalp block placed preoperatively using ropivacaine and lidocaine. Sedation was maintained with dexmedetomidine. Conclusion. No negative maternal or foetal side effects were noted during the intraoperative and (hospital) postoperative period. Anestezjologia i Ratownictwo 2018; 12: 70-74. Słowa kluczowe: awake craniotomy, scalp block, deksmedetomidyna, intra-procedural speech mapping
Spatial Evolution of Mixing Layers: Effects of Shear and Convection

This paper has reported the effects of shear velocity, convection velocity and shear rate on the spatial evolution of turbulent axisymmetric mixing layers. The types of mixing layers investigated are with the variation of convection velocity under the constant shear velocity, with the variation of shear velocity under the constant convection velocity and with the variation of shear or convection velocity under the constant shear rate. The closed form equations governing the mixing layer flows are obtained by the standard ε − k model and solved by using Fully Implicit Scheme and TDMA (Tridiagonal Matrix Algorithm). Obtained results show that the mixing layer thickness and momentum thickness evolve streamwise, and the shape and level of mean velocity, turbulent shear stress, mean vorticity and turbulence kinetic energy evolve streamwise but not radially with the changes in operating conditions at constant rate of shear. While changes in operating conditions affect the evolution of mixing layers in both directions under the constant shear or convection velocity. Key-Words: Axisymmetric mixing layer, Turbulent flow, Spatial evolution, Shear velocity, Convection velocity, Shear rate, Computational fluid dynamics.
1,3-THIAZOLIDIN-4-ONES AS HCV NS5B RNA POLYMERASE INHIBITORS

A novel series of 2-aryl-3-(5-phenyl[1,2,4]triazolo[4,3-c]quinazolin-3-yl)-1,3-thiazolidin-4-ones 4a-k with varied electronic environment due to aryl moiety present on 2 nd position of thiazolidinone has been designed, synthesized by one-pot three-component synthesis and characterized by their spectral data. In-silico molecular docking studies are carried out using low energy conformer of compounds 4a-k in the active domain of Hepatitis C virus NS5B RNA polymerase (protein ID: 3FRZ). Their aptness in regulating the functions were studied, from their interaction energies, calculated using the scoring functions, depicted that the ligands 4h (–7.813) and 4j (–7.885), bearing 2-chlorophenyl and 2-furyl substituents respectively, showed most fitting interactions than the standard filibuvir (–7.764), establishing as good inhibitors of HCV (Hepatitis C virus) and may evolve as potent antiviral agents.
REPRODUCTIVE PERFORMANCE OF HAIR GOAT AND GROWTH TRAITS OF HAIR GOAT AND SAANEN X HAIR (F1) CROSSBRED KIDS IN RURAL CONDITIONS

Çelik, H.T. and M. Olfaz, 2018. Reproductive performance of Hair goat and growth traits of Hair goat and Saanen x Hair (F1) crossbred kids in rural conditions. Bulg. J. Agric. Sci., 24 (2): 296–302 The goal of this study was to analyse Hair goats’ (Turkish Kil goat) reproductive performance and vitality, growth characteristics and some body measurements of Saanen x Hair (F1) crossbred and Hair goat kids raised in rural conditions in Turkey. The study was conducted under rural farm conditions in the province of Amasya in the Middle Black Sea region. Totally 287 goats, 143 does, 2 Hair bucks, 2 Saanen bucks, 37 Hair goat kids and 103 Saanen x Hair F1 crossbred kids were used. Mean reproductive values of the fl ocks were 9.09% for infertility rate, 90.91% for pregnancy rate, 1.03 for fecundity and 1.13 for prolifi cacy rate. The live weights for birth, 30th and 75th days were not affected by genotype but live weights of kids were signifi cantly affected (P < 0.05) by sex and birth type. Live weight gain and all the body measurements of kids in various periods were signifi cantly affected (P < 0.05) by sex and birth type. Growth rate of Saanen x Hair F1 crossbred kids were signifi cantly (P < 0.05) higher than Hair goat kids (175.49 g vs 157.57 g; 176.2 g vs 163.3 g) at 30th day and the weaning period (75th day), respectively. Daily weight gain was signifi cantly affected (P < 0.05) by genotype, gender, birth type and dams’ age. Signifi cant increases (P < 0.05) in wither height, chest width, chest depth, and chest circumference were noted for crossbred kids at 75th day when compared with the Hair goat kids. Survival rate of Saanen x Hair F1 crossbred kids had higher than those of Hair goat kids at 30th day and 75th day. These results suggest that growth rate and survival rate of kids are infl uenced from crossbreeding of Saanen dairy goat breed with the indigenous Hair goat breed at a signifi cant level.
Economic Policy Responses to a Pandemic: Developing the COVID-19 Economic Stimulus Index

In this paper, we conduct a comprehensive review of different economic policy measures adopted by 166 countries as a response to the COVID-19 pandemic and create a large database including fiscal, monetary and exchange rate measures. Furthermore, using the principle component analysis (PCA), we construct a COVID-19 Economic Stimulus Index (CESI) that combines all adopted policy measures. This index standardizes economic responses taken by governments, thus allows to study cross-country differences in policies. Finally, using simple cross-country OLS regressions we report that the median age of the population, the number of hospital beds per-capita, GDP per-capita and the number of total cases are significantly associated with the extent of countries’ economic policy responses.
A Decade of Learning: The Role of Beliefs in Oil Futures Markets During the 2000s

We examine the role of learning in accounting for the movements in oil price futures during the 2000s, a period during which the oil market experienced important changes. We show that a simple unobserved component model in which investors must form beliefs about whether the source of oil price movements is transitory or permanent accounts remarkably well for the fluctuations in oil price futures. Our simple framework notably accounts for the relatively slow increase in futures prices at the beginning of the past decade and their unprecedented run-up between 2004 and 2008. Even during the first half of 2008, a period during which oil prices reached historic highs, the model predicts a level of futures prices that is broadly in line with the data. Our estimates suggest that, through learning, investors revised up the contribution of permanent shocks to the variance of oil prices throughout this period. Using a DSGE model in which oil is storable and used in production, we then show that this learning process may have significantly muted the effects of oil shocks on the economy during that period. ∗The views in this paper are solely the responsibility of the authors and should not be interpreted as reflecting the views of the Board of Governors of the Federal Reserve System, any other person associated with the Federal Reserve System. †Comments and suggestions can be directed to robert.j.vigfusson@frb.gov.
In vitro antimicrobial activity and phytochemical analysis of two species of Saraca asoca

Saraca asoca is used worldwide to treat various kinds of human disorders and regarded as a universal panacea in the ayurvedic medicines. The present research evaluates the anti methanol and acetone) extracts of two plant species the agar well diffusion assay against E. coli Different fraction of both S. asoca species was tested of bark had showed the activity against both tested bacterial species. The phytochemical investigation of different fraction of bark extract shows the presence of tannins, phenols, s caesalpiniaceae bark extracts shows significant antibacterial activity as compared to might be due to the presence of higher concentration of phenolic compound which was estimated 1. 239μg/ml and 1.12 μg/ml respectively.
Decoupling Global and Local Representations from/for Image Generation

In this work, we propose a new generative model that is capable of automatically decoupling global and local representations of images in an entirely unsupervised setting. The proposed model utilizes the variational auto-encoding framework to learn a (low-dimensional) vector of latent variables to capture the global information of an image, which is fed as a conditional input to a flow-based invertible decoder with architecture borrowed from style transfer literature. Experimental results on standard image benchmarks demonstrate the effectiveness of our model in terms of density estimation, image generation and unsupervised representation learning. Importantly, this work demonstrates that with only architectural inductive biases, a generative model with a plain log-likelihood objective is capable of learning decoupled representations, requiring no explicit supervision. The code for our model is available at https://github.com/XuezheMax/wolf.
Diagnosis of Proteus mirabilis using PCR technique and determining their sensitivity to some antibiotics.

Proteus mirabilis The samples of the study were collected from different clinical sources 185 isolates of hospitals, the Diwaniyah city during the period from October 2015 to April and divided the samples, according to sources collected into five groups (46 swab ear, 42 swab burns, 37 a stool sample, 59 urine sample and 1 blood sample), as results showed that cultural and biochemical tests 69 isolated belong to P.mirabilis, diagnosis was confirmed by api 20E and the use of polymerase chain reaction. Tested the sensitivity of isolates P.mirabilis about 15 types of antibiotics by disk diffusion method, and belonging to ten classes of antibiotics,That shown sensitivity first to isolates of P.mirabilis results, the proportion of resistant P.mirabils antimicrobial I²- lactam antibiotic represented in Amoxicillin resistance and Ampicillin 84.05%, Amoxicillin/cluvanic acid 47.82%, Ticarcillin and , Cefatozidime 66.66%, Cefotaxim 53.62%, Meropenem 5.6%. The rate of resistance to antibiotics aminoglycosides represented in Amikacin resistance 17.36 %, Gentamicin percentage resistance 33.33%, Quinolones represented in Nalidic acid resistance 75.36%, while the Ciprofloxacin counted lower proportion of resistance 4.34 %, Trimethoprim resistance75.36 %. Chloramphenicol have high resistance rate of 82.60 %, as well as all of the Tetracycline 82.60%, and Rifampin 91.30% .
Joint Learning of Probabilistic and Geometric Shaping for Coded Modulation Systems

We introduce a trainable coded modulation scheme that enables joint optimization of the bit-wise mutual information (BMI) through probabilistic shaping, geometric shaping, bit labeling, and demapping for a specific channel model and for a wide range of signal-to-noise ratios (SNRs). Compared to probabilistic amplitude shaping (PAS), the proposed approach is not restricted to symmetric probability distributions, can be optimized for any channel model, and works with any code rate $k/m, m$ being the number of bits per channel use and $k$ an integer within the range from 1 to $m-1$. The proposed scheme enables learning of a continuum of constellation geometries and probability distributions determined by the SNR. Additionally, the PAS architecture with Maxwell-Boltzmann (MB) as shaping distribution was extended with a neural network (NN) that controls the MB shaping of a quadrature amplitude modulation (QAM) constellation according to the SNR, enabling learning of a continuum of MB distributions for QAM. Simulations were performed to benchmark the performance of the proposed joint probabilistic and geometric shaping scheme on additive white Gaussian noise (AWGN) and mismatched Rayleigh block fading (RBF) channels.
Improved Residual Networks for Image and Video Recognition

Residual networks (ResNets) represent a powerful type of convolutional neural network (CNN) architecture, widely adopted and used in various tasks. In this work we propose an improved version of ResNets. Our proposed improvements address all three main components of a ResNet: the flow of information through the network layers, the residual building block, and the projection shortcut. We are able to show consistent improvements in accuracy and learning convergence over the baseline. For instance, on ImageNet dataset, using the ResNet with 50 layers, for top-1 accuracy we can report a 1.19% improvement over the baseline in one setting and around 2% boost in another. Importantly, these improvements are obtained without increasing the model complexity. Our proposed approach allows us to train extremely deep networks, while the baseline shows severe optimization issues. We report results on three tasks over six datasets: image classification (ImageNet, CIFAR-10 and CIFAR-100), object detection (COCO) and video action recognition (Kinetics-400 and Something-Something-v2). In the deep learning era, we establish a new milestone for the depth of a CNN. We successfully train a 404-layer deep CNN on the ImageNet dataset and a 3002-layer network on CIFAR-10 and CIFAR-100, while the baseline is not able to converge at such extreme depths. Code and models are publicly available at: https://github.com/iduta/iresnet
Neural network interpretation of the Parkinson's disease diagnosis from SPECT imaging

Parkinson's disease (PD) diagnosis mainly relies on the visual and semi-quantitative analysis of medical imaging using single-photon emission computed tomography (SPECT) with 123I-Ioflupane (DaTSCAN). The deep learning approach has benefits over other machine learning methods as the model does not rely on feature extraction. However, the complexity of the deep learning model usually results in the difficulty of model interpretation when used in the clinical settings. The model interpretability depends on the interpretation method to reveal the contribution of each pixel in the input image from an attention map. In this paper, we modify the architecture of six well-known interpretation methods to be applicable for 3-dimensional convolutional neural network (3D-CNN) and propose an evaluation method using the Dice coefficient to measure the interpretation performance. The four deep learning models based on the 3D-CNN with high accuracy were applied with our evaluation method. Guided backpropagation, which is one of the interpretation methods, showed the best interpretation performance when applied to the 3D-CNN model. Guided backpropagation generates the attention map that focuses on the location of striatal nuclei. By using the result from guided backpropagation, 3D-CNN architecture that displayed the highest classification and interpretation performance could be chosen for PD diagnosis.
The $H_0$ tension: $\Delta G_N$ vs. $\Delta N_{\rm eff}$

We investigate whether the $4.4\sigma$ tension on $H_0$ between SH$_{0}$ES 2019 and Planck 2018 can be alleviated by a variation of Newton's constant $G_N$ between the early and the late Universe. This changes the expansion rate before recombination, similarly to the addition of $\Delta N_{\rm eff}$ extra relativistic degrees of freedom . We implement a varying $G_N$ in a scalar-tensor theory of gravity, with a non-minimal coupling of the form $(M^2+\beta \phi^2)R$. If the scalar $\phi$ starts in the radiation era at an initial value $\phi_I \approx 0.3 \, M_{Pl}$ and with $\beta\approx-0.8$, a dynamical transition occurs naturally around the epoch of matter-radiation equality and the field evolves towards zero at late times. As a consequence the $H_0$ tension between SH$_{0}$ES (2019) and Planck 2018+BAO decreases, as in $\Delta N_{\rm eff}$ models. However, mostly due to late-time constraints from Post-Newtonian (PN) local gravity, the tension is reduced only to 3.5$\sigma$ level. When including also the SH$_{0}$ES data in the fit, the varying $G_N$ model has $H_0=69. 2_{-0.75}^{+0.62}$ and an improvement of $\Delta\chi^2=-3.6$ compared to $\Lambda$CDM, at the cost of 2 extra parameters. This corresponds to a decrease of $7_{-6}^{+3}$ percent in the value of $G_N$ from the radiation era to the present time. For comparison, we update the fit of the $\Delta N_{\rm eff}$ model to the same dataset. We find that the $\Delta N_{\rm eff}$ model performs better than the simplest varying $G_N$ scenario, with $H_0=70_{-0.95}^{+0.93}$ and $\Delta\chi^2=-5.5$. The $\Lambda$CDM limit of the $\Delta N_{\rm eff}$ model is disfavored at slightly more than 2$\sigma$, since $\Delta N_{\rm eff}=0.316_{-0.15}^{+0.15}$.
Effects of misalignment on response uniformity of SiPM-on-tile technology for highly granular calorimeters

The SiPM-on-tile technology, consisting of plastic scintillator tiles with typical sizes of a few cm2 mounted on top of SiPMs, has been developed within the CALICE collaboration to enable automatized mass production of active elements for scintillator-based highly granular calorimeters. We present a study of the impact of misalignment of the scintillator tile with respect to the photon sensor on the response uniformity and on the absolute light yield for square, hexagonal and rhomboidal scintillator tiles of different sizes. A misalignment results in the formation of a dipole asymmetry of the spatial distribution of the light yield, with a magnitude that scales linearly with the size of the displacement, while the average light yield over the full active area of the tile is not affected. These results provide guidance for the definition of tolerances for the production and assembly of large calorimeter systems, showing that an alignment precision of approximately 500 μm or better allows to limit the impact to acceptable levels.