Miracle-dz/UniFAR-FTUs huggingface dataset:
Bioactivation of the Pulmonary Toxicants Naphthalene and 1-Nitronaphthalene by Rat CYP2F4

Naphthalene, a ubiquitous environmental contaminant, produces cytotoxicity in nonciliated bronchiolar epithelial (Clara) cells in mice; rats are refractory to lung cytotoxicity from naphthalene. In contrast, 1-nitronaphthalene is a potent toxicant in both species. Naphthalene is metabolized by CYP2F to a 1,2-epoxide, the first and obligate step in events leading to cytotoxicity. 1-Nitronaphthalene is metabolized to both the 5,6- and the 7,8-epoxides with the 7,8-epoxide predominating in lung. Previous studies have demonstrated recombinant CYP2F2 (mouse) to efficiently metabolize both naphthalene and 1-nitronaphthalene. To better understand the mechanism for the unique toxicity profiles for both compounds, a CYP2F ortholog (CYP2F4) was isolated from rat lung and expressed using a baculovirus system. Recombinant CYP2F4 efficiently generates 1R,2S-naphthalene oxide (Km = 3 μM, Vmax = 107 min-1) and the 5,6- and 7,8-epoxides of 1-nitronaphthalene (Km = 18 μM, Vmax = 25 min-1 based on total generated glutathione conjugates). Kinetics and regio/stereoselectivity of rat CYP2F4 were indistinguishable from mouse CYP2F2. These results, combined with our recent immunomapping studies demonstrating minimal pulmonary CYP2F expression in rats, indicate that CYP2F expression is the factor most clearly associated with susceptibility to naphthalene-induced pneumotoxicity. CYP2F4 failed to display an enhanced ability to bioactivate 1-nitronaphthalene, an ability that could have potentially compensated for the lower CYP2F pulmonary expression levels in the rat, yet equal species susceptibilities. These results suggest the importance of other P450 enzymes in the epoxidation/bioactivation of 1-nitronaphthalene. Expression of recombinant CYP2F1 (human) yielded an immunoreactive protein with no detectable CO-difference spectrum suggesting inadequate heme incorporation.
The Effects of Service Encounters in a Family Restaurant on Customer Value and Behavioral Intent

This study was undertaken to understand the interrelationships among customer’s perceptions of service encounters, customer value, and behavioral intent in a family restaurant. Based on 331 samples obtained from empirical research, we reviewed the reliability and fitness of a research model and verified three hypotheses using a structural equation model. The results showed that physical environment (β = .418) and a customer interaction with the service provider (β = .265) had a significant effect on the customer’s hedonic value. Additionally, physical environment (β = .126) and customer interaction with service providers (β = .264) had a significant effect on customer utilitarian value. Customer’s hedonic (β = .538) and utilitarian value (β = .382) triggered by service encounters had a significant effect on their behavioral intent. Limitations and future research directions are discussed.
Multi-shot Pedestrian Re-identification via Sequential Decision Making

Multi-shot pedestrian re-identification problem is at the core of surveillance video analysis. It matches two tracks of pedestrians from different cameras. In contrary to existing works that aggregate single frames features by time series model such as recurrent neural network, in this paper, we propose an interpretable reinforcement learning based approach to this problem. Particularly, we train an agent to verify a pair of images at each time. The agent could choose to output the result (same or different) or request another pair of images to verify (unsure). By this way, our model implicitly learns the difficulty of image pairs, and postpone the decision when the model does not accumulate enough evidence. Moreover, by adjusting the reward for unsure action, we can easily trade off between speed and accuracy. In three open benchmarks, our method are competitive with the state-of-the-art methods while only using 3% to 6% images. These promising results demonstrate that our method is favorable in both efficiency and performance.
Foreground segmentation using GMM combined temporal differencing

Various computer vision applications like biometric identification, analysis of traffic, face detection techniques, video analysis, and surveillance require the use of moving object identification as a fundamental step. A lot of efforts have been made in the past to find approaches which can detect motion but most methods are limited to particular situations and are not applicable everywhere. This paper proposes another, more robust approach towards object detection using Gaussian Mixture Model for background subtraction and temporal differencing for foreground segmentation that provides a promising result with the application of morphological operations and filtering. The GMM approach is a multimodal approach that faces the constraint of outlier pixels because of sudden illumination changes and commonage pixels among object and background. Other limitations of GMM include its learning rate and the number of models. This paper includes use of GMM and information about temporal gradient using temporal differencing for object detection. By use of adaptive GMM along with temporal differencing methods and filtering in post processing results in successful and robust object detection. This paper also compares the approach we have taken to other approaches by comparing the results obtained using a standard video dataset.
Precipitation drives global variation in natural selection

Climate-driven selection Climate change will fundamentally alter many aspects of the natural world. To understand how species may adapt to this change, we must understand which aspects of the changing climate exert the most powerful selective forces. Siepielski et al. looked at studies of selection across species and regions and found that, across biomes, the strongest sources of selection were precipitation and transpiration changes. Importantly, local and regional climate change explained patterns of selection much more than did global change. Science, this issue p. 959 Local and regional climate changes in rainfall explain patterns of species selection across biomes more than global change. Climate change has the potential to affect the ecology and evolution of every species on Earth. Although the ecological consequences of climate change are increasingly well documented, the effects of climate on the key evolutionary process driving adaptation—natural selection—are largely unknown. We report that aspects of precipitation and potential evapotranspiration, along with the North Atlantic Oscillation, predicted variation in selection across plant and animal populations throughout many terrestrial biomes, whereas temperature explained little variation. By showing that selection was influenced by climate variation, our results indicate that climate change may cause widespread alterations in selection regimes, potentially shifting evolutionary trajectories at a global scale.
Extension of relay feedback identification

This paper introduces a simple technique extending possibilities of the relay feedback identification. The approach enables to estimate five parameters of the transfer function from a single test using an asymmetric relay to generate sustained oscillations. The method offers a tool for a large class of common control problems. The applicability of the suggested simple technique is demonstrated by estimating five parameters of the anisochronic model. All simulations were performed in the Matlab/Simulink programming environment.
Optimal Operation for Green Supply Chain with Quality of Recyclable Parts and Contract for Recycling Activity

This study discusses a contract to promote collection and recycling of used products in a green supply chain (GSC). A collection incentive contract is combined with a reward-penalty contract. The collection incentive contract for used products is made between a retailer and a manufacturer. The reward-penalty contract for recycling used products is made between a manufacturer and an external institution. A retailer pays an incentive for collecting used products from customers and delivers them to a manufacturer with a product order quantity under uncertainty in product demand. A manufacturer remanufactures products using recyclable parts with acceptable quality levels and covers a part of the retailer’s incentive from the recycled parts by sharing the reward from an external institution. Product demand information is assumed as (i) the distribution is known (ii) mean and variance are known. Besides, the optimal decisions for product quantity, collection incentive of used products and lower limit of quality level for recyclable parts under decentralized integrated GSCs. The analysis numerically investigates how (1) contract for recycling activity, (ii) product demand information and (iii) quality of recyclable parts affect the optimal operation for each GSC. Supply chain coordination to shift IGSC is discussed by adopting Nash Bargaining solution.
A Framework for Earthquake Risk Assessment for Developing Countries

An Earthquake Risk Assessment (ERA) framework that can provide acceptable estimates based on the limited data available in developing countries is developed for probabilistic earthquake risk assessment of building structures. A region of Pakistan of known geological and building inventory was selected as case study to demonstrate the efficiency of the proposed ERA framework. Based on a GIS-based software, spatial analyses are performed to develop the seismic hazard map of the selected region by using a new modified probabilistic earthquake risk assessment method. Basic seismic vulnerability assessment relationships are used in the development of the ERA framework but these may be easily upgraded to a more sophisticated vulnerability assessment in future. The ERA framework developed in this project can be easily extended to consider different hazards associated with earthquakes such as tsunami, liquefaction and landslides. This paper presents an outline of this framework and some preliminary results. Introduction The effects of earthquakes on the behaviour of structures are considered in modern design codes but these codes are not always implemented, especially in developing countries. The majority of the existing infrastructure is either pre-code, or has not been designed and constructed according to seismic codes. Hence, the vulnerability for most of the existing building stock in developing countries is very high. The high vulnerability, coupled with population expansion and constructions in areas with high seismic hazard is the root cause of highly increasing earthquake risk in developing countries. Previous works done on Earthquake Risk Assessment (ERA) for example HAZUS in USA (FEMA 1999), RADIUS in Japan (Cardona et al. 2000) and RISK-UE in Europe (Mouroux and Burn 2006) are focused on developed countries and little work has been done on the vulnerability of substandard construction typically found in developing countries. With Cyprus as case study Kythreoti (2002) and Kyriakides (2008), at the University of Sheffield, have developed an ERA framework suitable for developing countries. Kythreoti implemented a Probabilistic Seismic Hazard Assessment (PSHA) method, which assumes that the historical seismicity levels of the past century will continue into the future. In this method Monte Carlo simulations are used by partially randomising the historical data which leads to determination of acceleration probability distributions for specific locations. Kythreoti assumed that low magnitude earthquakes have relatively small rupture length and they spread from the focal point. This simplification is valid for low magnitude earthquake regions such as
The severity of cognitive deficits predicts return to work after a first-ever ischaemic stroke

Background The inability of stroke patients to return to work contributes disproportionately to the socioeconomic impact of stroke and is best predicted by the severity of stroke. However, the role of cognitive deficits in stroke severity has not been scrutinised. We studied whether the initial cognitive severity of stroke, compared with other influential factors, predicts the inability to return to work after stroke. Methods Consecutive patients aged 18–65 with a first-ever ischaemic stroke, working full time previously, were assessed neuropsychologically within the first weeks after stroke and at the 6-month follow-up. Similarly, 50 healthy demographic controls were assessed twice. The cognitive severity of stroke was operationalised as the number of initial cognitive deficits. Cognitive severity as a predictor of the inability to return to work was compared with demographic, occupational, neurological, radiological and functional data, vascular risk factors and mood state. Results The mean age of the 140 patients assessed both initially and at follow-up was 52 years. They had a mean of 13 years of education and 59% were men. At 6 months, only 41% of the patients had returned to work despite the relatively minor neurological and functional impairments of the cohort. In our model, the number of early cognitive deficits (OR=2.252, CI 1.294 to 3.918) was the only significant predictor of the inability to return to work. Conclusions The initial cognitive severity of stroke predicts the later inability to return to work. The benefits of neuropsychological assessments within the first weeks after stroke are emphasised.
REREARCH ON A PROGNOSTIC AND HEALTH MONITORING APPROACH FOR EMAS IN THE FLIGHT CONTROL SYSTEM

For a more critical use in commercial aircraft, the Electromechanical Actuators (EMAs) technology must prove to be the same level of safety and reliability as systems based on Electrohydrostatic Actuators (EHA) and Hydraulics Actuators (HAs). The use of a Prognostic and Health Monitoring (PHM) is an additional way to secure the jamming free approach for EMA in flight control system and is becoming recognized as an efficient strategy for increasing reliability and improving maintenance of EMAs in this area. Firstly, does a detailed analysis of the multi-EMA system, and builds the fault tree of system, considering the three aspects of the control unit, electrical equipment and mechanical equipment; secondly, monitors the real state of the EMAs, relying on already existing sensors and signals, such as motor currents, temperature sensor and position sensors, according to the presented results, the current and position signals can provide useful information for monitoring the EMAs; in the end, assesses and forecasts the health status, the failure time, remaining life of the components and system, through the fast Fourier transform algorithm and intelligent fuzzy logic model(FLM).
Performance differences among strategic group members

Whether and why members of the same strategic group would experience different performance results has received little attention in previous research. These questions are addressed in this paper. First, conventional theory on the relationship between firm performance and strategic group membership is reviewed. Then a theory is developed as to how historical differences among strategic group members may result in performance differences. An empirical analysis of risk and return relationships is conducted, centered on the nature of environmental change characterizing the industry. The empirical setting throughout is the U.S. pharmaceutical industry over the period 1963–82.
Discriminating between behaviour using market data from panels

Considerable research exists on stochastic models of switching behaviour that uses sequences of individual-level purchase data. While at the individual level, sample size and sequence length are limiting factors, at the aggregate level, heterogeneity with respect to purchase sequences may assist in interpreting results. The authors propose an approach to discriminate between the switching behaviour of variety seeking, indifference and reinforcement. Only the proportion of 100% loyal customers, market share data and an estimation of the promotional effect -information all available from consumer panel data - are necessary to fit the model.
Sharp or Blur : A Fast No-Reference Quality Metric for Realistic Photos

There is an increasing demand on identifying the sharp and the blur photos from a burst of series or a mass of collection. Subjective assessment on image blurriness takes account of not only pixel variation but also the region of interest and the scene type. It makes measuring image sharpness in line with visual perception very challenging. In this paper, we devise a noreference image sharpness metric, which combines a set of gradient-based features adept in estimating Gaussian blur, out-of-focus blur and motion blur respectively. We propose a datasetadaptive logistic regression to build the metric upon multiple datasets, where over half of the samples are realistic blurry photos. Cross validation confirms that our metric outperforms thestate-of-the-art methods on the datasets with a total of 1577 images. Moreover, our metric is very fast, suitable for parallelization, and has the potential of running on mobile or embedded devices.
The spectrum of complement alternative pathway‐mediated diseases

Summary: The complement system has once again come into prominence in the therapeutic development arena. The recent approval of an inhibitory monoclonal antibody, eculizumab, which is directed against complement component C5 for the disease paroxysmal nocturnal hemoglobinuria has provided the initial validation of this system as a therapeutic target. Preclinical studies using animal models and human‐derived samples demonstrate that inhibition of complement ameliorates many inflammatory and autoimmune disease manifestations. Major efforts continue to define the most optimal means to block complement activation in a cost‐effective manner. Because the system is initiated through three pathways and generates at least six immunoregulatory and pro‐inflammatory mediators, there is substantial complexity to this problem. One pathway, designated the alternative pathway, has recently been shown to play a particularly important role in preclinical disease models. Further evidence of the importance of the alternative pathway has been provided by studies of human diseases, where mutations or dysfunctional polymorphisms that promote activation of this pathway are highly associated with the diseases atypical hemolytic uremic syndrome, dense deposit disease, and age‐related macular degeneration. This article reviews evidence in support of the essential role of the alternative pathway in the generation of tissue injury and the rationale for development of therapies that modulate its activity.
International Conference on Sustainability in Energy and Buildings , SEB-16 , 11-13 September 2016 , Turin , ITALY Phase Change Materials in glazing : implications on light distribution and visual comfort . Preliminary results

The visual comfort concerned with a technology with PCM embedded into a double glazing unit was analyzed, using the Daylight Probability Glare and the ‘Useful Illuminance’ (percent of workplane with an illuminance in the range 100-3000 lx). A sample office room was modeled using Radiance, under a clear sky and with the façade facing south. The visible transmittance of PCM was measured in laboratory and used as input in Radiance. The simulations were carried out for the two solstices and the Autumn equinox (four hours per day), for three sites (Östersund, 63.2°N; Turin, 45.2°N; Abu Dhabi, 24.4°N), considering the solid state of the PCM only.
Multi time-scale dynamic models for doubly-fed induction generator in DIgSILENT

The size and number of wind turbines are due to rise dramatically. Increasing dependence on wind generation requires suitable dynamic models of doubly-fed induction generator (DFIG) that can be easily deployed in power system studies. This paper presents the multi time-scale dynamic models of DFIG implemented in the power system simulation tool DIgSILENT. The response characteristics of the detailed DFIG models during normal operation of the wind turbine and during transient grid fault events are simulated and analyzed. The simulation results show that the established model is correct and DFIG possesses good dynamic characteristics.
Platelet-rich Plasma

Introduction As physicians continue to seek biologic solutions to improve healing of soft tissue pathologies, worldwide interest in the use of platelet rich plasma (PRP) for sports medicine applications has risen (14). PRP is a platelet concentrate derived from autologous whole blood, with platelet concentrations elevated several fold above baseline whole blood levels (4). PRP contains a high concentration of bioactive factors that are believed to impact healing (3). Although clinical evidence for PRP is still evolving, PRP has recently been widely applied in both surgical and non-surgical orthopedic applications including tendinopathy, acute and chronic soft-tissue injuries, enhancement of healing after ligament reconstruction, and knee osteoarthritis (1, 14).
A New Combined Measurement Method of the Electromagnetic Propagation Resistivity Logging

The electromagnetic propagation resistivity logging (EPRL) tool comprises one transmitter and a pair of receivers and measures the phase difference and the amplitude ratio (sometimes referred to as attenuation) across two receivers. Generally, the spatial response characteristics of the phase difference and the amplitude ratio can be summarized as follows: the amplitude ratio has large sensing volume and very low resolution than the phase difference. In this letter, a combined measurement method of the phase difference and the amplitude ratio (CPA) for EPRL is put forward by defining a new mathematical expression about the amplitude ratio. In this new mathematical expression, a so-called measure angle is introduced. By changing the measure angle, the CPA can provide a good tradeoff between the sensing volume and the resolution in the spatial response characteristics. Furthermore, the change of CPA curves that vary with the measure angle can be used to provide an alternative measurement which appears to be more applicable than the amplitude ratio.
Characterization of Mammalian Par 6 as a Dual-Location Protein

ABSTRACT Par 6 acts as a scaffold protein to facilitate atypical protein kinase C-mediated phosphorylation of cytoplasmic protein complexes, leading to epithelial and neuronal cell polarization. In addition to its location in the cytoplasm, Par 6 is localized to the nucleus. However, its organization and potential functions in the nucleus have not been examined. Using an affinity-purified Par 6 antibody and a chimera of Par 6 and green fluorescent protein, we show that Par 6 localizes precisely to nuclear speckles, but not to other nuclear structures, and displays characteristics of speckle proteins. We show that Par 6 colocalizes in the nucleus with Tax, a transcriptional activator of the human T-cell leukemia virus type 1 long terminal repeat, but multiple lines of evidence show that Par 6 is not directly involved in known functions of speckle proteins, including general transcription, splicing, or mRNA transport. Significantly, however, the structure of nuclear speckles is lost when Par 6 levels are reduced by Par 6-specific small interfering RNA. Therefore, we hypothesize that Par 6 in the nucleus acts as a scaffolding protein in nuclear speckle complexes, similar to its role in the cytoplasm.