Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy of sulfuric acid sodium sulfate on inoculated populations of Salmonella spp. and Campylobacter spp. on pork subprimals, and its effects on natural spoilage microflora, lean discoloration and off-odors

ii ACKNOWLEDGEMENTS.v LIST OF TABLES.viii LIST OF FIGURES.xii I) INTRODUCTION.1 II) REVIEW OF LITERATURE.4 Introduction.4 Foodborne Illness.5 The United States Pork Industry.7 Food Safety in the Pork Industry.8 Pork Pre-Harvest Food Safety.8 Pork Post-Harvest Food Safety.10 Pork Bacterial Pathogens of Concern.11 Salmonella.11 Campylobacter.12 Pathogen Control Methods.13 Pre-Harvest Interventions.14 Post-Harvest Interventions.15 Pork Spoilage Indicators.17 Spoilage Bacteria Effecting Pork.18 Pork Color Stability.19
Optimization Design of a Small-Sized Cruciform Specimen for Biaxial Fatigue Testing

The in-plane biaxial specimen can well reflect the complex stress state of sheet metal. However, there is no standard for small-sized specimens used in the low-power biaxial fatigue testing machine. The main goal of this paper is to apply the finite element method and orthogonal experiment method to design the cruciform specimen, considering the influence of three main parameters including the diameter of the central semispherical thinning area, the minimum thickness of the center and the arm thickness of the specimen. According to the central strain dispersion coefficient and the strain concentration coefficient proposed in this paper, we ensured that the distribution of strain in the gauge area is uniform and the strain it at its maximum value at the same time. The optimized specimen is verified by a biaxial fatigue test with the digital image correlation (DIC) technique. It is found that the fatigue crack appears in the center region, which proves that the optimized specimen can be effectively used for biaxial fatigue test.
Misbehavior-Aware On-Demand Collaborative Intrusion Detection System Using Distributed Ensemble Learning for VANET

Vehicular ad hoc networks (VANETs) play an important role as enabling technology for future cooperative intelligent transportation systems (CITSs). Vehicles in VANETs share real-time information about their movement state, traffic situation, and road conditions. However, VANETs are susceptible to the cyberattacks that create life threatening situations and/or cause road congestion. Intrusion detection systems (IDSs) that rely on the cooperation between vehicles to detect intruders, were the most suggested security solutions for VANET. Unfortunately, existing cooperative IDSs (CIDSs) are vulnerable to the legitimate yet compromised collaborators that share misleading and manipulated information and disrupt the IDSs’ normal operation. As such, this paper proposes a misbehavior-aware on-demand collaborative intrusion detection system (MA-CIDS) based on the concept of distributed ensemble learning. That is, vehicles individually use the random forest algorithm to train local IDS classifiers and share their locally trained classifiers on-demand with the vehicles in their vicinity, which reduces the communication overhead. Once received, the performance of the classifiers is evaluated using the local testing dataset in the receiving vehicle. The evaluation values are used as a trustworthiness factor and used to rank the received classifiers. The classifiers that deviate much from the box-and-whisker plot lower boundary are excluded from the set of the collaborators. Then, each vehicle constructs an ensemble of weighted random forest-based classifiers that encompasses the locally and remotely trained classifiers. The outputs of the classifiers are aggregated using a robust weighted voting scheme. Extensive simulations were conducted utilizing the network security laboratory-knowledge discovery data mining (NSL-KDD) dataset to evaluate the performance of the proposed MA-CIDS model. The obtained results show that MA-CIDS performs better than the other existing models in terms of effectiveness and efficiency for VANET.
Uncertainty quantification and global sensitivity analysis of piezoelectric energy harvesting using macro fiber composites

Piezoelectric macro fiber composites (MFCs) are widely used for energy harvesting due to their flexibility and high electromechanical conversion efficiency. In previous research studies, numerical and analytical models have been developed for MFC-harvesters using homogenized electromechanical properties. In this paper, an analytical electroelastic coupled model, based on the mixing rules, is used to predict the output responses of an MFC-harvester coupled in 33-mode of the PZT fibers. The predicted responses exhibit variation because of the uncertainty of the parameters used in the proposed model. The research reported in this paper aims to estimate the effect of the uncertainty in the physical properties of both piezoelectric fibers and epoxy matrix on the model responses and to identify the parameters which cause large output variability. The uncertainties of the parameters are defined as the variability bounds based on the tolerances reported by the manufacturers. Global sensitivity analysis (GSA) is an appropriate method to study the effect of the uncertainty of parameters on the electromechanical response of the harvester. Two GSA are applied in this paper: (i) the Morris method based on the elementary effects measures and (ii) the variance method which consists in computing the Sobol’ indices, whose goal is to identify systems parameters which have significant impact on the voltage and the power outputs of a bimorph MFC-harvester. This study leads to a qualitative comparison between the two methods which are strategically different. Both methods indicate that the elastic modulus and the density of the piezoelectric fibers, the length and the thickness of the representative volume element of the MFC-patch are the most influential parameters that affect the output voltage. It has also been shown that the order of importance of the parameters can change from the short-circuit to the open-circuit condition. Furthermore, Monte Carlo simulations are used to propagate the uncertainties of the parameters in order to determine the envelope of the variability of the responses. This study reveals the importance of considering model parameter uncertainties in the development of robust prediction tools for piezoelectric energy harvesting devices.
Supplement of biochar and vermicompost amendments in coir and peat growing media improves N management and yields of leafy vegetables

Abstract: A greenhouse trial assessed the effects of biochar and vermicompost as partial substitutes of conventional growing media on leafy vegetables’ yields and changes of NH4+-N and NO3−-N in growing medium and leachates. Six growing media mixtures [(a) coir, (b) coir + biochar, (c) coir + vermicompost, (d) peat, (e) peat +vermicompost, (f) peat + biochar] combined with three nitrogen (N) rates [0% (0 g N·pot−1), 50% (0.5 g N·pot−1), and 100% (1.0 g N·pot−1) commercial recommendation] were arranged in a split-plot design with three replicates. On average, the yield gap between 100% N and 50% N was improved when biochar and vermicompost were used as substitutes of coir (32% and 28% vs. 49%) and peat (14% and 18% vs. 27%). The concentrations of NH4+-N in the leachates for peat + biochar varied between 17.20 and 1.00 mg·L−1. The concentrations of NO3−-N in the leachates varied between 130.0 and 1.0 mg·L−1 for coir + vermicompost, and 60 and 1.0 mg·L−1 for peat + vermicompost. The residual NO3−-N in peat + biochar growing media and the leachates did not match the changes observed for NH4+-N, and the much lower residual NH4+-N indicates possible NH4+-N retention by biochar and loss through volatilization in the early growth stages. Our results show that partial substitution of peat with biochar and coir with vermicompost maintained acceptable crop yield at 50% N due probably to N supply by vermicompost and decreased residual mineral N and loss by biochar in the leachates which could be beneficial for the environment.
Considerations Regarding Inflation Ranges

We consider three ways that a monetary policy framework may employ a range for inflation outcomes: (1) ranges that acknowledge uncertainty about inflation outcomes (uncertainty ranges), (2) ranges that define the scope for intentional deviations of inflation from its target (operational ranges), and (3) ranges over which monetary policy will not react to inflation deviations (indifference ranges). After defining these three ranges, we highlight a number of costs and benefits associated with each. Our discussion of the indifference range is accompanied by simulations from the FRB/US model, illustrating the potential for long-term inflation expectations to drift within the range.
Ultra-Low-Voltage Inverter-Based Operational Transconductance Amplifiers with Voltage Gain Enhancement by Improved Composite Transistors

This paper proposes topological enhancements to increase voltage gain of ultra-low-voltage (ULV) inverter-based OTAs. The two proposed improvements rely on adoption of composite transistors and forward-body-biasing. The impact of the proposed techniques on performance figures is demonstrated through simulations of two OTAs. The first OTA achieves a 39 dB voltage gain, with a power consumption of 600 pW and an active area of 447 μm2. The latter allies the forward-body-bias approach with the benefit of the independently biased composite transistors. By combining both solutions, voltage gain is raised to 51 dB, consuming less power (500 pW) at the cost of an increased area of 727 μm2. The validation has been performed through post-layout simulations with the Cadence Analog Design Environment and the TSMC 180 nm design kit, with the supply voltage ranging from 0.3 V to 0.6 V.
Underground Barrier Wall Evaluation for Controlling Saltwater Intrusion in Sloping Unconfined Coastal Aquifers

Barrier walls are considered one of the most effective methods for facilitating the retreat of saltwater intrusion (SWI). This research plans to examine the effect of using barrier walls for controlling of SWI in sloped unconfined aquifers. The sloping unconfined aquifer is considered with three different bed slopes. The SEAWAT model is implemented to simulate the SWI. For model validation, the numerical results of the seawater wedge at steady state were compared with the analytical solution. Increasing the ratio of flow barrier depth (db/d) forced the saltwater interface to move seaward and increased the repulsion ratio (R). With a positive sloping bed, further embedding the barrier wall from 0.2 to 0.7 caused R to increase from 0.3% to 59%, while it increased from 1.8% to 41.7% and from 3.4% to 46.9% in the case of negative and horizontal slopes, respectively. Embedding the barrier wall to a db/d value of more than 0.4 achieved a greater R value in the three bed-sloping cases. Installing the barrier wall near the saltwater side with greater depth contributed to the retreat of the SWI. With a negative bed slope, moving the barrier wall from Xb/Lo = 1.0 toward the saltwater side (Xb/Lo = 0.2) increased R from 7.21% to 68.75%, whereas R increased from 5.3% to 67% for the horizontal sloping bed and from 5.1% to 64% for the positive sloping bed. The numerical results for the Akrotiri coastal aquifer confirm that the embedment of the barrier wall significantly affects the controlling of SWI by increasing the repulsion ratio (R) and decreasing the SWI length ratio (L/La). Cost-benefit analysis is recommended to determine the optimal design of barrier walls for increasing the cost-effectiveness of the application of barrier walls as a countermeasure for controlling and preventing SWI in sloped unconfined aquifers.
Open-Circuit Fault Diagnosis of Power Rectifier Using Deep Convolutional Neural Network

Aimed to automatically provide accurate fault diagnosis of data from failed power electronics, various studies have been researched based on different approaches. Recently, data driven methods based on deep learning have required increasing attention because of their automatic feature learning abilities. Nonetheless, one of the challenges using these methods in practice is how to obtain the most representative fault features and ensure the better predication performances at the same time. This paper is in respect of the open-circuit fault diagnosis of the phase-controlled three-phase full-bridge power rectifier using deep convolutional neural network (DCNN) for extracting and further classifying fault features. The process mainly includes four steps. Firstly, a presupposed approach of DCNN which is applied to automatically capture the paramount fault features from the raw data is briefly introduced. Then a structure of DCNN is designed to extract the features from output data. Furthermore, the model and framework of the fault diagnosis system are developed to diagnose the open-circuit fault of the power rectifier. Finally, the effectiveness of the proposed method is validated using simulation results. Experiments illustrate that the DCNN model can achieve high accuracy in different fault cases and present great capability of diagnosing fault types in open-circuit fault of power rectifiers.
Assessment of Genotoxic and Cytogenetic Effects of Aflatoxin B1 in Mouse Bone Marrow Cells

Aflatoxins refer to a cluster of difuranocoumarin compounds which are mainly produced by Aspergillus flavus and Aspergillus parasiticus fungi species (Steyn, 1995). These chemicals can contaminate human consumption crops such as corn, peanut, sorghum, rice, wheat, and nut (Cleveland et al., 2003). The most common aflatoxins are B1, B2, G1 and G2 which are naturally present in many food products and affect several organ systems simultaneously. This produces a cascade of responses in the affected organism (Ferenčík and Ebringer, 2003; Herzallah, 2013). Human beings are mainly exposed to aflatoxins through secondary sources after the consumption of animal products that had previously ingested contaminated feed. Aflatoxins are highly lipophilic and are therefore quickly absorbed via the alimentary canal. Moreover, they can enter the bloodstream directly through inhalation (Bbosa et al., 2013). It is estimated that approximately 4.5 billion people across the globe, especially in low-income countries are exposed to food that is contaminated with aflatoxin (Williams et al., 2004). Among the International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 7 Number 04 (2018) Journal homepage: http://www.ijcmas. com
Measurement of Overconfidence, Illusion of Control and Optimism in the Context of Behavioral Finance: Case of University Students

Davranissal finans, piyasa anomalilerinin yani sira bu animalilere neden olan onyargilarin incelenmesini de konu almaktadir. Literature bakildiginda kisilerin karar surecleri uzerinde etkisi oldugu belirtilen cok sayida onyargidan bahsedildigi gorulmektedir. Bunlar arasinda uzerinde ayrica durulan onyargilarin ise kendine asiri guven, kontrol yanilsamasi ve asiri iyimserlik oldugu dikkati cekmektedir. Bu calismada bu uc onyarginin olculmesini hedefleyen ifadelerden olusan olceklerin Turkiye’de universite ogrencileri uzerindeki guvenilirligi ve gecerliligi test edilmistir. Onyargilari olculmesini hedefleyen ve bu calismada kullanilan olcegin ilk halinde 19 madde yer almaktadir. Ogrencilerin demografik bilgilerini de iceren anket formu farkli universitelerde ogrenim goren toplam 522 ogrenciye uygulanmistir. Yapilan analizler sonucunda olcegin son halinin Cronbach Alfa degerinin 0,825 oldugu ve olcekte yer alan ifadelerin 4 faktor altinda toplandigi tespit edilmistir.
Competitiveness of Tea Exports in Asean: A Constant Market Share Analysis

This study was aimed to find out the competitiveness of tea exports in ASEAN during 2011-2014. Competitiveness indicates a country ability to compete with other countries in international trade activities. Constant Market Share (CMS) employed to understand the weaknesses and strengths of a country viewed from the effect of exports growth. CMS results showed that the major weakness of tea exports in Malaysia, Singapore, Thailand, and Vietnam is the effect of market distribution. Market distribution effect indicated that their exports to countries with a high demand for tea in the world. On the other hand, the strengths of tea exports in Malaysia, Singapore, Thailand, and Vietnam are the effect of world exports growth, commodity composition effect, and the competitiveness effect. Conversely, the major weakness of tea exports in Indonesia is competitiveness effect, while the strengths are the effect of world exports growth and the effect of market distribution.
Sensor scheduling for ground maneuvering target tracking in presence of detection blind zone

Continuous and stable tracking of the ground maneuvering target is a challenging problem due to the complex terrain and high clutter. A collaborative tracking method of the multisensor network is presented for the ground maneuvering target in the presence of the detection blind zone (DBZ). First, the sensor scheduling process is modeled within the partially observable Markov decision process (POMDP) framework. To evaluate the target tracking accuracy of the sensor, the Fisher information is applied to constructing the reward function. The key of the proposed scheduling method is forecasting and early decision-making. Thus, an approximate method based on unscented sampling is presented to estimate the target state and the multi-step scheduling reward over the prediction time horizon. Moreover, the problem is converted into a nonlinear optimization problem, and a fast search algorithm is given to solve the sensor scheduling scheme quickly. Simulation results demonstrate the proposed non-myopic scheduling method (Non-MSM) has a better target tracking accuracy compared with traditional methods.
Maturation but Not Survival Tamoxifen Blocks Estrogen-Induced B Cell

Estrogen treatment has been shown not only to exacerbate disease activity and accelerate death in spontaneous murine models of lupus but also to induce a lupus-like phenotype in nonspontaneously autoimmune mice. In mice transgenic for the H chain of an anti-DNA Ab, estrogen rescues naive autoreactive B cells that normally are deleted and causes them to mature to a marginal zone phenotype. Estrogen further leads to the activation of this population causing an elevation of serum anti-DNA Ab titers and renal disease. This study was designed to evaluate the therapeutic potential of tamoxifen, a selective estrogen receptor modulator, on estrogen-induced lupus. Mice treated with both estradiol and tamoxifen showed no elevation in anti-DNA Ab titers and conse-quently no glomerular IgG. The DNA-reactive B cell population that is rescued by estrogen was present in an anergic state in mice treated with both estradiol and tamoxifen. Estradiol enhances transitional B cell resistance to apoptosis and expands the population of marginal zone B cells; tamoxifen did not impede the enhanced resistance to apoptosis, but prevented the development of autoreactive cells as marginal zone B cells. Thus, estrogen-induced autoimmunity proceeds through two distinct molecular pathways, one affecting survival and the other maturation. Activation, but not survival, of autoreactive B cells can be abrogated by tamoxifen. Drugs that modulate even some of the effects of estrogen may be beneﬁcial in patients with lupus. Eventually, understanding the pathways involved in survival and activation of autoreactive B cells will permit the development of therapeutics that target all relevant pathways. The Journal of Immunology, 2005, 175: 1415–1423.
Glucose transporter expression in lung granulomas from Mycobacterium tuberculosis-infected monkeys

TB remains to be one of the major threat to public health as it brings tremendous mobility and mortality in developing countries. Nevertheless, with the help from PET/CT imaging techniques, it provides a fast and sensitive way of diagnosing active TB and meanwhile, it proves to be valuable tool of studying TB inflammation and granuloma. Our study focused on glucose transporter expression in the granuloma tissues from infected monkeys as we believed their expression would be enhanced as a result of Warburg effect and increased inflammation. It can be the one of the major factors that drives uptake of 18F-FDG and give rise to high SUV from PET/CT results. However, our preliminary data did not fully support this hypothesis. Although initial RT-PCR data supported higher Glut1, Glut3, Glut8 and Glut14 expression from pooled granuloma tissue RNA, further quantification study from tissues with known SUV levels didn’t not show higher expression of glucose transporters in granuloma tissues in compare to normal tissues except Glut3. Individual comparison among glucose transporters in granuloma tissues showed lower expression relative to HPRT1 except Glut3 and most glucose transporter expression didn’t not show positive correlation with SUV levels. Although tissue staining experiment did confirmed higher expression of Glut1 and Glut3 in the granuloma tissues, MFI studies and statistical analysis didn’t not support expression of glucose transporters as a major contributor to the higher SUV levels. Therefore, there is not enough evidence to conclude glucose transporter expression in the granuloma tissues may be the main factor that drives FDG uptake and responsible for different SUV levels from PET/CT outcome.
Ownership, bank size, capitalization and bank performance: Evidence from India

Abstract This study focuses on assessing the role of various bank-specific, industry-specific and macroeconomic determinants in Indian commercial banks performance. Performance of the Indian banks has been measured by Return on Assets (ROA), Return on Equity (ROE) and Net Interest Margin (NIM) and Pre-provision profit ratio. The study analyses impact of various bank-specific factors like bank size, capital ratio, risk, cost to income ratio, funding cost, revenue diversification, labour productivity and bank age on bank performance. It also tries to assess the relationship between various bank-specific and industry-specific variables like bank concentration, inflation rate and GDP growth rate with bank performance. Fixed effects estimation model and Generalized Method of Moments (GMM) have been used on a panel data of 19 years for 64 commercial banks of India. The findings reveal that private sector banks are more profitable than the public sector banks. Additionally, the results of the study show that bank size, non-performing loan ratio and revenue diversification are the major determinants of the commercial banks performance in India. Furthermore, the results reveal that during the crisis period the impact of bank size, bank age, labour productivity and revenue diversification on the performance of the Indian banks is robust. The higher non-government stake leads to the enhanced performance of the commercial banks in India. The higher capital adequacy leads to the increase in the performance of the banks. The larger banks are less profitable. The results provide better insights about the determinants of Indian banks profitability.
Psychological barriers to urban recycled water acceptance: a review of relevant principles in decision psychology

ABSTRACT This paper reviews principles from decision psychology relevant to understanding and increasing acceptance of urban recycled water, and supplements existing literature by suggesting an additional factor: adaptation insensitivity. We integrate into our discussion previously unpublished results from a study conducted in 2007, which surveyed 2680 respondents in five American cities, identifying basic psychological features impacting resistance to recycled water. We focus on identifying targets for intervention, including the failure of respondents to realize that, with exposure, they would adapt to recycled water (adaptation insensitivity).