Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Methodologies for Quantifying the Health Impacts of Active Travel

In the past several years, active travel (walking and cycling) has been increasingly recognised as an effective means of increasing physical activity and mitigating negative external impacts of motorised transport. As a result of this recognition, a range of methodologies for quantifying the benefits and risks of active travel have emerged in the literature. This review critically assesses studies which quantify the health impacts of transport scenarios involving increased active travel. It was found that the choice of methodology and assumptions employed in such studies may have a significant impact on the results and so care must be taken when planning these studies or interpreting their results. Increases in physical activity are the most important determinant of the health impacts of active travel but different methodologies for quantifying the health impacts of this physical activity can lead to substantial differences in the scale of the impact. Therefore, further research is required into the relationship between increased physical activity and health effects. Particular attention should also be paid to ensure that health impacts are assessed for both the individuals changing their travel behaviour and all other individuals in the study area. Where relative risk relationships are used to estimate health impacts, researchers should be mindful of the specific exposures used to develop these relationships in order to prevent double counting of health impacts. Extensive sensitivity analysis is necessary to compensate for the uncertainty inherent in models for predicting health
CORPORATE GOVERNANCE, DISCLOSURE QUALITY, AND COST OF EQUITY: EVIDENCE FROM PAKISTAN

To be successful in the financial world, you must know how the public disclosure of business information affects stock prices. Specifically for Pakistan, this research will help us better understand the relationship between corporate governance, disclosure quality, and equity cost The Sys-GMM model has been employed by 167 non-financial enterprises listed on the Pakistan Stock Exchange since 2017. (PSX). Research shows it was in use between 2018 and 2020. The Sys-GMM technique for estimating may be used to account for endogeneity in corporate governance problems. We discovered that GMM projections failed to account for endogeneity, resulting in inaccurate conclusions, using pooled OLS and fixed-effect estimates. According to the research, the cost of equality and financial transparency are mutually incompatible. All of these factors contribute to the PSE's stock price decline, including board size, concentrated ownership, and CEO duality. The research es-tablishes a relationship between independent audit committees and high-quality audits and reduced equity expenses. Independent directors and competent auditors command a premium on the PSX. The duration of the approval process for financial statements has no bearing on the board's independence. Due to the scarcity of information disclosed in annual reports, investors anticipate a higher rate of return. The conclu-sions of the research may be beneficial to Pakistan's corporate govern-ance authorities and investors.
Two New Bottle Gourd Fruit Rot Causing Pathogens from Sub-Himalayan West Bengal

Colletotrichum sp.and Fusarium sp. are the two major fungi that cause bottle gourd fruit rot. Typical fruit symptoms include hard, sunken, and dark brown to black patches gradually covering entirely the whole fruit. Pathogen isolates were obtained from diseased bottle gourd fruits, on PDA medium forming a white to gray colonies. The conidia of Colletotrichum sp. were hyaline in color, cylindrical with both apices rounded. On the other hand the conidia of Fusarium sp. were also hyaline, beaked and having transverse septa. Pathogenicity tests with representative isolates were conducted on symptomless fresh bottle gourd fruits. Both the tested fungal pathogen caused fruit rot on bottle gourd fruit. Koch’s postulates were fulfilled by reisolation of the pathogens from the test fruits. PCR analysis (using universal primer set ITS1/ ITS4) of genomic DNA from the pathogens and bioinformatic analysis further confirmed presence of the pathogens. These two fungi as fruit rot causing pathogens in bottle gourd are being reported for the first time.
A Corpus-Based Study on Japanese EFL Learners’ Use of Relative Clause Constructions: CEFR Criterial Feature and Error Analysis

Relative clause (RC) constructions are considered some of the most difficult grammatical items for Japanese EFL (English as a Foreign Language) learners. This study investigates the use of relative clauses by Japanese EFL learners at CEFR, A1 to B2 levels, using L2 learner corpora: the Japanese EFL Learner Corpus (JEFLL: Tono, 2007) and the NICT JLE Corpus (NICT JLE: Izumi, Isahara, & Uchimoto, 2005). The types of RCs were categorized based on the SO Hierarchy Hypothesis (SOHH: Hamilton, 1994) and the frequencies of each RC type were compared against those from a CEFR-based Coursebook Corpus. Error analysis was also conducted for learner corpora. Results show that the frequency order of RCs followed the order predicted by the SOHH at each CEFR level across three corpora and that the frequency increased along the CEFR levels. The error analysis identified various types of structure errors, which are the most frequent error types in both JEFLL and NICT JLE.
PHYLOGENETIC GROUPING OF THE PATHOGENIC E . COLI ISOLATED FROM COMMERCIAL BROILER CHICKEN IN PAKISTAN

E. coli isolates can be classified into four different phylogenetic groups on the basis of chuA, yjaA and TspE4.C2 biomarkers via multiplex PCR. Current study investigated the presence of various phylogenetic groups in clinical samples of collibacillosis from commercial broiler chicken in Pakistan. A total of 84 E. coli isolates out of 200 swab sample (n = 25 cloacal; n = 27 fibrinous layer of peri-hepatitis of clinically infected broiler chicken; and n = 32 cloacal swabs from clinically healthy chicken) were recovered. Out of 25 pathogenic E. coli isolates from cloacal swabs, 12%, 4%, 72% and 0% isolates belonged to group A, B1, D and B2, respectively. Out of 27 pathogenic E. coli isolates from swab of fibrinous layer,18.5%, 29.6%, 44.4% and 0% isolates belonged to group A, B2, D and B1, respectively. While out of 32 non pathogenic E. coli isolates from healthy birds, 21.8%, 9.3%, 46.8% and 18.7% isolates belonged to group A, B2, D, and B1, respectively. There were 06 uncategorized E. coli isolates, which amplified both yjaA and TspE4.C2 biomarkers. This study helped to categorize the E. coli isolates into intestinal and extra intestinal origin on the basis of phylogenetic grouping.
Three dimensional numerical simulations of fiber orientation in injection molding

Composite materials made of glass fibers and thermoplastics matrix and obtained by injection molding are widely used in the industry. The fiber reinforcement improves the properties of the material such as the specific stiffness, the specific strength or the specific toughness, etc. The injection process, which is almost the same as the one used for non reinforced thermoplastics, allows the production of parts with an optimized total cost.
Dynamic Resource Provisioning for Energy Efficient Cloud Radio Access Networks

Energy saving is critical for the cloud radio access networks (C-RANs), which are composed by massive radio access units (RAUs) and energy-intensive computing units (CUs) that host numerous virtual machines (VMs). We attempt to minimize the energy consumption of C-RANs, by leveraging the RAU sleep scheduling and VM consolidation strategies. We formulate the energy saving problem in C-RANs as a joint resource provisioning (JRP) problem of the RAUs and CUs. Since the active RAU selection is coupled with the VM consolidation, the JRP problem shares some similarities with a special bin-packing problem. In this problem, the number of items and the sizes of items are correlated and are both adjustable. No existing method can be used to solve this problem directly. Therefore, we propose an efficient low-complexity algorithm along with a context-aware strategy to dynamically select active RAUs and consolidate VMs to CUs. In this way, we can significantly reduce the energy consumption of C-RANs, while do not incur too much overhead due to VM migrations. Our proposed scheme is practical for a large-size network, and its effectiveness is demonstrated by the simulation results.
Interactive comment on “ Note on the directional properties of meter-scale gravity waves ” by Charles

1) The manuscript seems to conclude that bound waves do not play a role on high wavenumber bimodality and this is consistent with a numerical investigation in Toffoli, A. , M. Onorato, E. M. Bitner-Gregersen, and J. Monbaliu (2010), Development of a bimodal structure in ocean wave spectra, J. Geophys. Res., 115, C03006, doi:10.1029/2009JC005495, where they showed that free wave nonlinearity is causing the bimodal lobes to form. However, the Authors mention in
Carotenoids in Foods and their Effects on Human Health

Carotenoids, responsible for the red, orange and yellow color in foods, consist a part of the pigment family that naturally present in vegetables and fruits. Six main carotenoids found in human blood serum and taken with the diet are βand α-carotenes, lycopene, lutein, zeaxanthin, and β–cryptoxanthin. Many studies suggest that carotenoids have a positive effect on several diseases such as certain type of cancers, cardiovascular and ocular diseases, especially age related macular degeneration and cataract. The antioxidant properties of carotenoids may be responsible for their beneficial influence on human health. Human organisms are unable to synthesize carotenoids, therefore these compounds have to be supplied with the diet. Main carotenoid sources include carrots, green leafy vegetables, tomatoes, sweet potatoes, egg yolk and corn. In this study, carotenoids in foods and their effects on human health are reviewed.
Morphological Investigations and Infection Studies of the Rust-Causing Fungi of Roses

Rose rust is caused by members of the genus Phragmidium, four of which are: P. mucronatum (Pers.) Schlect. , P. tuberculatum Mull. , P. fusiforme Schroet. and P. rosae-pimpinellifoliae (Rabh.) Diet. In the present study, preliminary identification of Phragmidium species was based on host range. Identification was then supported by measuring the dimensions of urediospores and teliospores. Axenic cultures of P. tuberculatum were initiated on culture media but these cultures were unable to reinfect rose leaves, therefore cultures of P. tuberculatum on leaf discs of ‘Mme. Grégoire Staechelin’ were initiated from urediospores. The infectivity of dry spores and spore suspensions of urediospores of P. tuberculatum directly from host tissue did not differ significantly; however, spore density of 30 × 10 per ml proved to be more infective than higher or lower densities. Surface-sterilized detached leaves showed significantly lower infection rates than leaves that were not surface sterilized. The urediospores on the leaf discs, survived when stored at 4°C for four weeks, but when stored for 12 weeks at the same temperature, they lost their viability and were not able to infect leaf discs. _____________________________________________________________________________________________________________
Characteristics of carbon storage and sequestration in different age Robiniapsedudoacia plantations

In order to identify the age-sequence of Robiniapsedudoacia plantations on ecosystem carbon storage, a survey was conducted in 8-, 15and 22-year-old Robiniapsedudoacia plantations and shrubwood in Luoning County, Henan Province. The carbon content in the arborous layer (different organs), shrub-grass layer, litter layer and soil layer (0-50 cm) was determined. The ecosystem carbon storage along with characteristics was analyzed based on the biomass and the data analysisi of the soils. The result showed that the carbon content in Robiniapsedudoacia organs ranged from 42.60% to 50.92%, with an ascending order of trunk, bark, branch, rootstock, leaf, thick root, rootlet, big root, medium root, and fine root. There was no significant difference in carbon content in the shrub layer, herb layer and litter layer among the four stands. The carbon storage in these four ecosystems was 78.96, 99.78, 110.85 and 132.75 t.hm, respectively. Compared with the shrub wood, the annual mean increments of carbon pool in the 8-, 15and 22-year-old Robiniapsedudoacia plantations were 2.60, 2.13 and 2.44 t·hm·a respectively.The arbor and soil layers were the main carbon pools, which contributed 85.14%-96.63% of the total. The carbon content in the arbor layer increased with an increase of the stand age, while it decreased in the soil layer. In other layers, however, no significant changes were observed in this study.
A Methodological Note on Mean Growth and Stability in Endogenous Stochastic Growth Models ∗

Mean growth of wealth (or GDP) is generally defined as the growth rate of average wealth, but it can alternatively be defined as the average growth rate of wealth. While this raises an important conceptual issue, we argue that stochastic stability should be used as a guide to safely discriminate between the two notions of mean growth. Our discussion is illustrated on the class of continuous time AK-type models subject to geometric Brownian motions. First, stability concepts are introduced and applied to stochastic linear homogenous differential equations. Second, a preliminary application to the canonical AK model is provided. It is readily shown that in this case exponential balanced paths are not robust to uncertainty. Third, and more importantly, we evaluate the quantitative implications of the alternative definition of mean growth on the seminal global diversification model due to Obstfeld (1994).
ALICE HLT Run 2 performance overview.

For the LHC Run 2 the ALICE HLT architecture was consolidated to comply with the upgraded ALICE detector readout technology. The software framework was optimized and extended to cope with the increased data load. Online calibration of the TPC using online tracking capabilities of the ALICE HLT was deployed. Offline calibration code was adapted to run both online and offline and the HLT framework was extended to support that. The performance of this schema is important for Run 3 related developments. An additional data transport approach was developed using the ZeroMQ library, forming at the same time a test bed for the new data flow model of the O2 system, where further development of this concept is ongoing. This messaging technology was used to implement the calibration feedback loop augmenting the existing, graph oriented HLT transport framework. Utilising the online reconstruction of many detectors, a new asynchronous monitoring scheme was developed to allow real-time monitoring of the physics performance of the ALICE detector, on top of the new messaging scheme for both internal and external communication. Spare computing resources comprising the production and development clusters are run as a tier-2 GRID site using an OpenStack-based setup. The development cluster is running continuously, the production cluster contributes resources opportunistically during periods of LHC inactivity.
1 LH Transition Trigger Physics in ITER-Similar EXC Plasmas with Applied n = 3 Magnetic Perturbations

In ITER-similar-shape (ISS) plasmas with balanced torque injection in DIII-D, the L-H transition power threshold PLH is observed to increase with applied n=3 Resonant Magnetic Perturbations (RMP), and this increase is most pronounced with added ECH. PLH also increases with decreasing plasma collisionality as PLH ~ (ν*). This result raises concerns for H-mode access in ITER, where resonant magnetic perturbations (RMP) may have to be applied before the L-H transition to safely suppress the first ELM. Non-axisymmetric modifications with RMP include a simultaneous reduction of the radial electric field (Er) well and E×B shear due to increasing edge toroidal rotation, and substantially increased local long-wavelength turbulence [measured via Beam Emission Spectroscopy (BES)]. Two-fluid MHD modeling with the M3D-C1 code shows only moderate (20%) toroidal modulation of the normalized L-mode radial density gradient a/Ln with large applied RMP field, in agreement with reflectometry data. At high RMP perturbation strength the edge electric field reverses sign locally (becomes positive). Edge magnetic stochasticity provides an attractive explanation of the observed edge plasma modifications, and the observed edge Er and toroidal rotation changes are consistent with a simple fluid model describing stochastic electron current flow. The observed collisionality dependence of the L-mode edge electric field with applied RMP is also consistent with this model. Initial experiments indicate that non-resonant n=3 magnetic perturbations lead only to relatively small changes in Er and E×B shear and fluctuation characteristics, and have less effect on the L-H transition power threshold, motivating further exploration of the RMP spectrum dependence of PLH for possible mitigation of the observed threshold increase.
Integral identities for 3 d dualities with SP ( 2 N ) gauge groups

In this note we study the reduction of 4d Seiberg duality to 3d for SP(2N) SQCD with an adjoint field. We follow a general prescription that consists in compactifying the dual 4d theories on the circle. This generates an effective 3d duality. The pure 3d duality is obtained by combining the zero radius limit with a real mass flow. Here we perform this limit by a double scaling procedure: we turn on real masses proportional to the radius before shrinking the circle. We apply this mechanism to the reduction of the 4d superconformal index to the three sphere partition function. While the reduction of the 4d index on the circle is straightforward, the 3d limit necessitates the double scaling. We describe this limit on the index, finding the integral identity for the partition functions of the 3d dual theories. ar X iv :1 50 9. 02 19 9v 3 [ he pth ] 2 5 M ay 2 01 7
Title Self-affirmation and affective forecasting : Affirmation reduces the anticipated impact of negative events Permalink

When forecasting how they will feel in the future, people overestimate the impact that imagined negative events will have on their affective states, partly because they underestimate their own psychological resiliency. Because self-affirmation enhances resiliency, two studies examined whether self-affirmation prior to forecasting reduces the extremity of affective forecasts. Participants in self-affirmation conditions completed a values scale or wrote an essay asserting their most important value, whereas participants in the no-affirmation condition asserted a relatively unimportant value. Participants then predicted their affective reactions to a negative or positive imagined event. In both studies, self-affirmation reduced the unpleasant affect expected to result from a negative event, but had no impact on affective forecasts for a positive event. This pattern was mediated by participants’ cognitive appraisals of the imagined event, but not by differential focus on that event. Results are consistent with self-affirmation activating or enhancing psychological resiliency to counteract immune neglect during affective forecasting of a negative event.
A DIFFUSION APPROACH FOR ORIENTED VOLUME DATA DENOISING

This paper proposes a new method for denoising non-time dependent volumetric oriented data blocks. The method is developed under the partial differential equations theoretical framework and it is defined on orthogonal section planes of the threedimensional space. The efficiency of the method in denoising oriented volume data is proven using an extensive experimental part involving several random computer-generated synthetic data blocks and statistical interpretations. In the experimental section we also provide a result obtained on real data.
9. Co-design, organisational creativity and quality improvement in the healthcare sector: ‘designerly’ or ‘design-like’?

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Influence of genetic background of the host on Tregs following chlamydia muridarum respiratory tract infection

We discussed the influence of genetic background of the host on regulatory T cells (Tregs) following Chlamydia muridarum (Cm) respiratory tract infection. C57BL/6 (C57) and C3H/HeN (C3H) mice showing obvious differences in susceptibility to Chlamydia trachomatis (Ct) infection were intranasally administered with 1×103 IFU Cm. The mice were sacrificed at different days after infection. Intracellular cytokine staining was performed to detect the percentages of CD4+CD25+ T cells and Foxp3+CD4+CD25+ T cells in the spleen. The mRNA expressions of Tregs-related cytokines IL-10 and IL-2 in lung tissues were detected by RT-PCR. The differences in Treg-mediated immune response between C57 and C3H mice at different stages after Cm respiratory tract infection were compared. Cm infection induced high levels of CD4+CD25+ T cells and Foxp3+CD4+CD25+ T cells in both groups as well as high mRNA expressions of IL-10 and IL-2. The levels of CD4+CD25+ T cells and Foxp3+CD4+CD25+ T cells in the spleen and mRNA expression of IL-2 in the lung were higher in C3H mice with a higher susceptibility than in C57 mice at 3 d and 7 d post-infection; the mRNA expression of IL-10 in C3H mice was obviously higher than that in C57 mice. Cm respiratory tract infection promoted Treg proliferation and production of IL-10 and IL-2 in C3H mice. As a result, the inhibition of Th1-mediated immune response specific to Chlamydia was enhanced. This mechanism plays a crucial role in the difference in susceptibility to Cm respiratory tract infection between the two mice.
A novel deep hybrid recommender system based on auto-encoder with neural collaborative filtering

Due to the widespread availability of implicit feedback (e.g., clicks and purchases), some researchers have endeavored to design recommender systems based on implicit feedback. However, unlike explicit feedback, implicit feedback cannot directly reflect user preferences. Therefore, although more challenging, it is also more practical to use implicit feedback for recommender systems. Traditional collaborative filtering methods such as matrix factorization, which regards user preferences as a linear combination of user and item latent vectors, have limited learning capacities and suffer from data sparsity and the cold-start problem. To tackle these problems, some authors have considered the integration of a deep neural network to learn user and item features with traditional collaborative filtering. However, there is as yet no research combining collaborative filtering and contentbased recommendation with deep learning. In this paper, we propose a novel deep hybrid recommender system framework based on auto-encoders (DHA-RS) by integrating user and item side information to construct a hybrid recommender system and enhance performance. DHA-RS combines stacked denoising auto-encoders with neural collaborative filtering, which corresponds to the process of learning user and item features from auxiliary information to predict user preferences. Experiments performed on the real-world dataset reveal that DHA-RS performs better than state-of-the-art methods.