bluuebunny/crossref_metadata_2025 huggingface dataset:
Dissimilarity Space Based Multi-Source Cross-Project Defect Prediction
Authors: Ren Shengbing , Zhang Wanying , Munir Hafiz Shahbaz , Xia Lei
Published: January 2019

Software defect prediction is an important means to guarantee software quality. Because there are no sufficient historical data within a project to train the classifier, cross-project defect prediction (CPDP) has been recognized as a fundamental approach. However, traditional defect prediction methods use feature attributes to represent samples, which cannot avoid negative transferring, may result in poor performance model in CPDP. This paper proposes a multi-source cross-project defect prediction method based on dissimilarity space (DM-CPDP). This method not only retains the original information, but also obtains the relationship with other objects. So it can enhances the discriminant ability of the sample attributes to the class label. This method firstly uses the density-based clustering method to construct the prototype set with the cluster center of samples in the target set. Then, the arc-cosine kernel is used to calculate the sample dissimilarities between the prototype set and the source domain or the target set to form the dissimilarity space. In this space, the training set is obtained with the earth mover’s distance (EMD) method. For the unlabeled samples converted from the target set, the k-Nearest Neighbor (KNN) algorithm is used to label those samples. Finally, the model is learned from training data based on TrAdaBoost method and used to predict new potential defects. The experimental results show that this approach has better performance than other traditional CPDP methods.
Modeling Yields Response to Shading in the Field-to-Forest Transition Zones in Heterogeneous Landscapes
Authors: Schmidt Martin , Nendel Claas , Funk Roger , Mitchell Matthew G. E. , Lischeid Gunnar
Published: January 2019

In crop modeling and yield predictions, the heterogeneity of agricultural landscapes is usually not accounted for. This heterogeneity often arises from landscape elements like forests, hedges, or single trees and shrubs that cast shadows. Shading from forested areas or shrubs has effects on transpiration, temperature, and soil moisture, all of which affect the crop yield in the adjacent arable land. Transitional gradients of solar irradiance can be described as a function of the distance to the zero line (edge), the cardinal direction, and the height of trees. The magnitude of yield reduction in transition zones is highly influenced by solar irradiance—a factor that is not yet implemented in crop growth models on a landscape level. We present a spatially explicit model for shading caused by forested areas, in agricultural landscapes. With increasing distance to forest, solar irradiance and yield increase. Our model predicts that the shading effect from the forested areas occurs up to 15 m from the forest edge, for the simulated wheat yields, and up to 30 m, for simulated maize. Moreover, we estimated the spatial extent of transition zones, to calculate the regional yield reduction caused by shading of the forest edges, which amounted to 5% to 8% in an exemplary region.
Determination of Insecticide Susceptibility of Field Populations of Tomato Leaf Miner (Tuta absoluta) in Northern Nigeria
Authors: Bala Ibrahim , Mukhtar Muhammad M. , Saka Habeeb K. , Abdullahi Nasiru , Ibrahim Sulaiman S.
Published: January 2019

In 2016, northern Nigeria experienced a devastating infestation by the tomato leaf miner, leading to soaring in prices of tomatoes across the country. Unfortunately, information on the resistance status of this pest is lacking in northern Nigeria, hampering appropriate control measures. Here, we identified to species level and, using bioassays, characterised insecticide susceptibility profile of a field population of a tomato leaf miner from northern Nigeria. Highest resistance was observed with λ-cyhalothrin (a Type II pyrethroid) with a low mortality (18.52% at 56 h) and LD50 of 7461.474 ppm. Resistance was also established toward propoxur and chlorpyrifos-methyl with average mortalities each of 56% and LD50s of 1023.51 ppm and 106.351 ppm, respectively. Highest susceptibility was observed from abamectin with mortality of 86% and LD50 of 0.034 ppm. Pre-exposure to the synergist piperonylbutoxide significantly recovered λ–cyhalothrin susceptibility ((mortality~90%, χ2 = 98.35, p < 0.0001) and LD50 = 0.92 ppm) implicating P450 monoxygenases. No significant changes were observed on pre-exposure to diethyl maleate and triphenylphosphate-inhibitors of glutathione S-transferases and carboxylesterases, respectively. Sequencing of domain II of the voltage-gated sodium channel established 1014F kdr mutation 100% fixed in both λ-cyhalothrin-alive and dead larvae. These findings highlight the challenges for control of this invasive agricultural pest in northern Nigeria.
Evaluating Soybean Cultivars for Low- and High-Temperature Tolerance During the Seedling Growth Stage
Authors: Alsajri Firas Ahmed , Singh Bhupinder , Wijewardana Chathurika , Irby J. Trenton , Gao Wei , Reddy Kambham Raja
Published: January 2019

Soybean (Glycine max L.) seedlings may be exposed to low or high temperatures under early or conventional soybean production systems practiced in the US Midsouth. However, a wide range of soybean cultivars commonly grown in the region may inherit diverse tolerance to degrees of temperatures. Therefore, a study was conducted in a controlled-environment facility to quantify 64 soybean cultivars from Maturity Group III to V, to low (LT; 20/12 °C), optimum (OT; 30/22 °C), and high (HT; 40/32 °C) temperature treatments during the seedling growth stage. Several shoot, root, and physiological parameters were assessed at 20 days after sowing. The study found a significant decline in the measured root, shoot, and physiological parameters at both low and high temperatures, except for root average diameter (RAD) and lateral root numbers under LT effects. Under HT, shoot growth was significantly increased, however, root growth showed a significant reduction. Maturity group (MG) III had significantly lower values for the measured root, shoot, and physiological traits across temperature treatments when compared with MG IV and V. Cultivar variability existed and reflected considerably through positive or negative responses in growth to LT and HT. Cumulative stress response indices and principal component analysis were used to identify cultivar-specific tolerance to temperatures. Based on the analysis, cultivars CZ 5225 LL and GS47R216 were identified as most sensitive and tolerant to LT, while, cultivars 45A-46 and 5115LL identified as most tolerant and sensitive to HT, respectively. The information on cultivar-specific tolerance to low or high temperatures obtained in this study would help in cultivar selection to minimize stand loss in present production areas.
Application of Logistic Regression Models for the Marketability of Cucumber Cultivars
Authors: Díaz-Pérez Manuel , Carreño-Ortega Ángel , Salinas-Andújar José-Antonio , Callejón-Ferre Ángel-Jesús
Published: January 2019

The aim of this study is to establish a binary logistic regression method to evaluate and select cucumber cultivars (Cucumis sativus L.) with a longer postharvest shelf life. Each sample was evaluated for commercial quality (fruit aging, weight loss, wilting, yellowing, chilling injury, and rotting) every 7 days of storage. Simple and multiple binary logistic regression models were applied in which the dependent variable was the probability of marketability and the independent variables were the days of storage, cultivars, fruit weight loss, and months of evaluation. The results showed that cucumber cultivars with a longer shelf life can be selected by a simple and multiple binary logistic regression analysis. Storage time was the main determinant of fruit marketability. Fruit weight loss strongly influenced the probability of marketability. The logistic model allowed us to determine the cucumber weight loss percentage over which a fruit would be rejected in the market.
Garlic (Allium Sativum) Supplementation Improves Respiratory Health but Has Increased Risk of Lower Hematologic Values in Horses
Authors: Saastamoinen Markku , Särkijärvi Susanna , Hyyppä Seppo
Published: January 2019

Garlic (Allium sativum) is claimed to have numerous beneficial properties to the health of humans and animals. It is commonly used for example to treat respiratory diseases and infections in horses’ lungs. However, in addition to its possible positive influences, garlic may also have adverse health effects. The hypotheses of this study were that garlic supplementation may help to clear mucus in the airways, but also causes declining hematologic values in prolonged feeding. To our knowledge, this is the first organized study in controlled conditions to show the health effects of garlic supplementation for horses so far. The results show that long-term supplementation of dried garlic on the level of 32 mg/kg BW seemed to reduce the amount of tracheal symptoms and accumulation of tracheal exudates. Additionally, the number of neutrophil cells in the tracheal mucus was numerically smaller in the garlic supplemented horses. However, the garlic supplemented horses showed slightly declining Hb, HcT and RBC values during an 83-day study period. Consequently, it is possible that even low garlic supplementation levels can be detrimental to the horse’s hematology when the supplementation period is long.
Current Approaches and Future Perspectives for Nanobodies in Stroke Diagnostic and Therapy
Authors: Jank Larissa , Pinto-Espinoza Carolina , Duan Yinghui , Koch-Nolte Friedrich , Magnus Tim , Rissiek Björn
Published: January 2019

Antibody-based biologics are the corner stone of modern immunomodulatory therapy. Though highly effective in dampening systemic inflammatory processes, their large size and Fc-fragment mediated effects hamper crossing of the blood brain barrier (BBB). Nanobodies (Nbs) are single domain antibodies derived from llama or shark heavy-chain antibodies and represent a new generation of biologics. Due to their small size, they display excellent tissue penetration capacities and can be easily modified to adjust their vivo half-life for short-term diagnostic or long-term therapeutic purposes or to facilitate crossing of the BBB. Furthermore, owing to their characteristic binding mode, they are capable of antagonizing receptors involved in immune signaling and of neutralizing proinflammatory mediators, such as cytokines. These qualities combined make Nbs well-suited for down-modulating neuroinflammatory processes that occur in the context of brain ischemia. In this review, we summarize recent findings on Nbs in preclinical stroke models and how they can be used as diagnostic and therapeutic reagents. We further provide a perspective on the design of innovative Nb-based treatment protocols to complement and improve stroke therapy.
Characterization of Two New Multidrug-Resistant Strains of Mycobacterium smegmatis: Tools for Routine In Vitro Screening of Novel Anti-Mycobacterial Agents
Authors: Arthur Patrick K. , Amarh Vincent , Cramer Precious , Arkaifie Gloria B. , Blessie Ethel J. S. , Fuseini Mohammed-Sherrif , Carilo Isaac , Yeboah Rebecca , Asare Leonard , Robertson Brian D.
Published: January 2019

Mycobacterium tuberculosis is a pathogen of global public health concern. This threat is exacerbated by the emergence of multidrug-resistant and extremely-drug-resistant strains of the pathogen. We have obtained two distinct clones of multidrug-resistant Mycobacterium smegmatis after gradual exposure of Mycobacterium smegmatis mc2 155 to increasing concentrations of erythromycin. The resulting resistant strains of Mycobacterium smegmatis exhibited robust viability in the presence of high concentrations of erythromycin and were found to be resistant to a wide range of other antimicrobials. They also displayed a unique growth phenotype in comparison to the parental drug-susceptible Mycobacterium smegmatis mc2 155, and a distinct colony morphology in the presence of cholesterol. We propose that these two multidrug-resistant clones of Mycobacterium smegmatis could be used as model organisms at the inceptive phase of routine in vitro screening of novel antimicrobial agents targeted against multidrug-resistant Mycobacterial tuberculosis.
NADPH Oxidase (Rboh) Activity is Up Regulated during Sweet Pepper (Capsicum annuum L.) Fruit Ripening
Authors: Chu-Puga Ángela , González-Gordo Salvador , Rodríguez-Ruiz Marta , Palma José M. , Corpas Francisco J.
Published: January 2019

In plants, NADPH oxidase (NOX) is also known as a respiratory burst oxidase homolog (Rboh). This highly important enzyme, one of the main enzymatic sources of superoxide radicals (O2•−), is involved in the metabolism of reactive oxygen and nitrogen species (ROS and RNS), which is active in the non-climacteric pepper (Capsicum annuum L.) fruit. We used sweet pepper fruits at two ripening stages (green and red) to biochemically analyze the O2•−-generating Rboh activity and the number of isozymes during this physiological process. Malondialdehyde (MDA) content, an oxidative stress marker, was also assayed as an index of lipid peroxidation. In red fruits, MDA was observed to increase 2-fold accompanied by a 5.3-fold increase in total Rboh activity. Using in-gel assays of Rboh activity, we identified a total of seven CaRboh isozymes (I–VII) which were differentially modulated during ripening. CaRboh-III and CaRboh-I were the most prominent isozymes in green and red fruits, respectively. An in vitro assay showed that CaRboh activity is inhibited in the presence of nitric oxide (NO) donors, peroxynitrite (ONOO−) and glutathione (GSH), suggesting that CaRboh can undergo S-nitrosation, Tyr-nitration, and glutathionylation, respectively. In summary, this study provides a basic biochemical characterization of CaRboh activity in pepper fruits and indicates that this O2•−-generating Rboh is involved in nitro-oxidative stress associated with sweet pepper fruit ripening.
Direct Multistep Wind Speed Forecasting Using LSTM Neural Network Combining EEMD and Fuzzy Entropy
Authors: Qin Qiong , Lai Xu , Zou Jin
Published: January 2019

Accurate wind speed forecasting is of great significance for a reliable and secure power generation system. In order to improve forecasting accuracy, this paper introduces the LSTM neural network and proposes a wind speed statistical forecasting method based on the EEMD-FuzzyEn-LSTMNN model. Moreover, the MIC is used to analyze the autocorrelation of wind speed series, and the predictable time of wind speed statistical forecasting method for direct multistep forecasting is taken as four hours. In the EEMD-FuzzyEn-LSTMNN model, the original wind speed series is firstly decomposed into a series of components by using EEMD. Then, the FuzzyEn is used to calculate the complexity of each component, and the components with similar FuzzyEn values are classified into one group. Finally, the LSTMNN model is used to forecast each subsequence after classification. The forecasting result of the original wind speed series is obtained by aggregating the forecasting result of each subsequence. Three forecasting cases under different terrain conditions were selected to validate the proposed model, and the BPNN model, the SVM model and the LSTMNN model were used for comparison. The experimental results show that the forecasting accuracy of the EEMD-FuzzyEn-LSTMNN model is much higher than that of the other three models.
Distributed Dynamic Cluster-Head Selection and Clustering for Massive IoT Access in 5G Networks
Authors: Zhao Yifeng , Liu Kai , Xu Xueting , Yang Huayu , Huang Lianfen
Published: January 2019

With the rapid growth of Internet-of-things (IoT) devices, IoT communication has become an increasingly crucial part of 5G wireless communication systems. The large-scale IoT devices access results in system overload and low utilization of energy efficiency under the existing network framework. In this paper, the cluster head uses the LTE-M protocol, and the intra-cluster uses the low-power wide-area network (LPWAN) self-networking protocol in the wireless sensor network. By a detailed analysis of the messages exchanged between the device and the base station, we describe the causes of overload and the steps of data aggregate combined with the physical channel. Then, we explore the cluster head quantity and the optimal scale in the intra-cluster under the traditional K-mean algorithm. When K is 30 under specific resources, the simulation results show that the system’s access success probability and resource utilization are optimal. Also, we propose a distributed dynamic cluster-head selection and clustering scheme based on an improved K-means algorithm. Simulation results show that the proposed scheme can reach 88.07% on the access success probability. The throughput and resource utilization are 3.5 times high than that of the optimal K-means.
Optimization of Shape Design of Grommet through Analysis of Physical Properties of EPDM Materials
Authors: Kim Young , Hwang Eui , Jeon Euy
Published: January 2019

Ethylene propylene diene monomer (EPDM) has superior mechanical properties, water resistance, heat resistance, and ozone resistance. It can be applied to various products owing to its low hardness and high slip resistance properties. A grommet is one of the various products made using EPDM rubber. It is a main component of automobiles, in which it protects wires throughout the inside and outside of a vehicle body. The grommet, made of EPDM, has different mounting performance depending on the process parameters and the shape of the grommet. This study conducted optimization to improve the mounting performance of a grommet using EPDM materials. The physical properties of the main molding materials were investigated according to process parameters. A grommet was fabricated according to the process parameters of fabrication. Insertion force and separation force were examined through experiments. Nonlinear material constants were determined through uniaxial and biaxial tensile tests. The nonlinear analysis of the grommet was conducted, and a compound design that incorporated the shape parameters for the minimum load of each part was derived. Then, additional nonlinear analysis was performed. This was followed by a comparative analysis of the actual model through experimental evaluation.
Use of Fiber-Optic Sensors for the Detection of the Rail Vehicles and Monitoring of the Rock Mass Dynamic Response Due to Railway Rolling Stock for the Civil Engineering Needs
Authors: Nedoma Jan , Stolarik Martin , Fajkus Marcel , Pinka Miroslav , Hejduk Stanislav
Published: January 2019

The paper describes the original results of a comparative study of the standard seismic station vs. a novel interferometric sensor for civil engineering needs. The presented results showed that to implement seismic measurements using standard seismic stations, a method using a fiber optic interferometer may serve as an alternative. We presented time records and the frequency spectra obtained from experimental measurements of the dynamic response of the upper rock mass beneath passing tram vehicles (a total of 769 passes) over a period of five months of practical measurements under various climatic conditions. The fiber-optic sensor detected all phenomena at a 100% rate, and the recorded results were compared to the results from a standard seismic station. Both sets of results were recorded simultaneously and agreed significantly, especially in terms of frequency. With regard to time, all tram vehicle axles were detected in individual time records. With regard to frequency, the results detected in the bandwidth generally correlated to rail transport for individual types of tram vehicles.
A Deep Similarity Metric Method Based on Incomplete Data for Traffic Anomaly Detection in IoT
Authors: Kang Xu , Song Bin , Sun Fengyao
Published: January 2019

In recent years, with the development of the Internet of Things (IoT) technology, a large amount of data can be captured from sensors for real-time analysis. By monitoring the traffic video data from the IoT, we can detect the anomalies that may occur and evaluate the security. However, the number of traffic anomalies is extremely limited, so there is a severe over-fitting problem when using traditional deep learning methods. In order to solve the problem above, we propose a similarity metric Convolutional Neural Network (CNN) based on a channel attention model for traffic anomaly detection task. The method mainly includes (1) A Siamese network with a hierarchical attention model by word embedding so that it can selectively measure similarities between anomalies and the templates. (2) A deep transfer learning method can automatically annotate an unlabeled set while fine-tuning the network. (3) A background modeling method combining spatial and temporal information for anomaly extraction. Experiments show that the proposed method is three percentage points higher than deep convolutional generative adversarial network (DCGAN) and five percentage points higher than AutoEncoder on the accuracy. No more time consumption is needed for the annotation process. The extracted candidates can be classified correctly through the proposed method.
Real-Time Vision through Haze Based on Polarization Imaging
Authors: Wang Xinhua , Ouyang Jihong , Wei Yi , Liu Fei , Zhang Guang
Published: January 2019

Various gases and aerosols in bad weather conditions can cause severe image degradation, which will seriously affect the detection efficiency of optical monitoring stations for high pollutant discharge systems. Thus, penetrating various gases and aerosols to sense and detect the discharge of pollutants plays an important role in the pollutant emission detection system. Against this backdrop, we recommend a real-time optical monitoring system based on the Stokes vectors through analyzing the scattering characteristics and polarization characteristics of both gases and aerosols in the atmosphere. This system is immune to the effects of various gases and aerosols on the target to be detected and achieves the purpose of real-time sensing and detection of high pollutant discharge systems under bad weather conditions. The imaging system is composed of four polarizers with different polarization directions integrated into independent cameras aligned parallel to the optical axis in order to acquire the Stokes vectors from various polarized azimuth images. Our results show that this approach achieves high-contrast and high-definition images in real time without the loss of spatial resolution in comparison with the performance of conventional imaging techniques.
Improvement of Electro-Optical Properties of PSLC Devices by Silver Nanowire Doping
Authors: Yan Xudong , Liu Wei , Zhou Yong , Yuan Dong , Hu Xiaowen , Zhao Wei , Zhou Guofu
Published: January 2019

Polymer stabilized liquid crystal (PSLC) devices modulating the light that goes through them have broad applications. In this study, to improve the electro-optical properties of a PSLC device, Ag nanowires with diameter about 20 nm were doped into PSLC active layer with different concentrations. The influence of Ag nanowires concentration on the driving voltage, on-state response time and frequency modulation characteristics of a PSLC device were studied. The results indicate that the doping of Ag nanowires can reduce the driving voltage of PSLC cell up to 42%. The response time of the PSLC cell can decrease by about 41%. Meanwhile, frequency modulation does not show significant improvement upon Ag nanowire doping. Overall, Ag nanowire doping can improve the electro-optical properties of PSLC device effectively.
Parametric PSpice Circuit of Energy Saving Lamp Emulating Current Waveform
Authors: Raciti Angelo , Rizzo Santi Agatino , Susinni Giovanni
Published: January 2019

Energy-saving lamps are equipped with converters enabling high energy efficiency at the cost of injecting very distorted currents on the mains. The problem is more complex in the emerging smart-lighting scenario where these lamps are also used to perform additional tasks. Harmonics mitigation at the lamp level is expensive; consequently, an optimal lighting system design aiming at reducing both costs and current distortion of the whole lighting system is necessary. A tool able to emulate the current drawn from the lamps is necessary for optimal design. Such a tool has also to consider the fluctuations of the voltage on the mains that usually occur throughout the day. In this perspective, a parametric PSpice circuit is proposed and the netlist is reported in this work. Moreover, the simple procedure to be adopted for computing the parameters is also described. The validation has confirmed the ability of the proposed circuit in emulating the current drawn from various CFLs and LED lamps under different supplying voltage.
Don’t Be Afraid of the Digital
Authors: De Vletter Martien
Published: January 2019

The Canadian Centre for Architecture (CCA) in Montreal started to receive born digital material in the late 1990s. Not knowing what to do with it, typically only the physical appearance was described. Since 2012, the CCA has seriously started to look into its born digital collections and actively started to acquire more. CCA was not very interested in how to overcome the technocratic question as to how to preserve and give access to born digital material, but wanted to understand how the digital technology has changed and shaped architecture. The curatorial approach and the investment in staff and expertise led to success: the CCA is now able to preserve its born digital collections, to describe it, to access nearly all files, to make it accessible for research, and to share this with the community. How? By just doing it, making mistakes, and learning by doing.
Thermochemical Non-Equilibrium in Thermal Plasmas
Authors: Bultel Arnaud , Morel Vincent , Annaloro Julien
Published: January 2019

In this paper, we analyze the departure from equilibrium in two specific types of thermal plasmas. The first type deals with the plasma produced during the atmospheric entry of a spatial vehicle in the upper layers of an atmosphere, specifically the one of Mars. The second type concerns the plasma produced during the laser-matter interaction above the breakdown threshold on a metallic sample. We successively describe the situation and give the way along which modeling tools are elaborated by avoiding any assumption on the thermochemical equilibrium. The key of the approach is to consider the excited states of the different species as independent species. Therefore, they obey to conservation equations involving collisional-radiative contributions related to the other excited states. These contributions are in part due to the influence of electrons and heavy particles having a different translation temperature. This ‘state-to-state’ approach then enables the verification of the excitation equilibrium by analyzing Boltzmann plots. This approach leads finally to a thorough analysis of the progressive coupling until the equilibrium asymptotically observed.
Two-Level Fault Diagnosis of SF6 Electrical Equipment Based on Big Data Analysis
Authors: Miao Hongxia , Zhang Heng , Chen Minghua , Qi Bensheng , Li Jiyong
Published: January 2019

With the increase of the operating time of sulphur hexafluoride (SF6) electrical equipment, the different degrees of discharge may occur inside the equipment. It makes the insulation performance of the equipment decline and will cause serious damage to the equipment. Therefore, it is of practical significance to diagnose fault and assess state for SF6 electrical equipment. In recent years, the frequency of monitoring data acquisition for SF6 electrical equipment has been continuously improved and the scope of collection has been continuously expanded, which makes massive data accumulated in the substation database. In order to quickly process massive SF6 electrical equipment condition monitoring data, we built a two-level fault diagnosis model for SF6 electrical equipment on the Hadoop platform. And we use the MapReduce framework to achieve the parallelization of the fault diagnosis algorithm, which further improves the speed of fault diagnosis for SF6 electrical equipment.
Non-Curcuminoids from Turmeric and Their Potential in Cancer Therapy and Anticancer Drug Delivery Formulations
Authors: Nair Akhila , Amalraj Augustine , Jacob Joby , Kunnumakkara Ajaikumar B. , Gopi Sreeraj
Published: January 2019

Over the past decades curcuminoids have been extensively studied for their biological activities such as antiulcer, antifibrotic, antiviral, antibacterial, antiprotozoal, antimutagenic, antifertility, antidiabetic, anticoagulant, antivenom, antioxidant, antihypotensive, antihypocholesteremic, and anticancer activities. With the perception of limited toxicity and cost, these compounds forms an integral part of cancer research and is well established as a potential anticancer agent. However, only few studies have focused on the other bioactive molecules of turmeric, known as non-curcuminoids, which are also equally potent as curcuminoids. This review aims to explore the comprehensive potency including the identification, physicochemical properties, and anticancer mechanism inclusive of molecular docking studies of non-curcuminoids such as turmerones, elemene, furanodiene (FN), bisacurone, germacrone, calebin A (CA), curdione, and cyclocurcumin. An insight into the clinical studies of these curcumin-free compounds are also discussed which provides ample evidence that favors the therapeutic potential of these compounds. Like curcuminoids, limited solubility and bioavailability are the most fragile domain, which circumscribe further applications of these compounds. Thus, this review credits the encapsulation of non-curcuminoid components in diverse drug delivery systems such as co-crystals, solid lipid nanoparticles, liposomes, microspheres, polar-non-polar sandwich (PNS) technology, which help abolish their shortcomings and flaunt their ostentatious benefits as anticancer activities.
Mechanical Modeling of Healthy and Diseased Calcaneal Fat Pad Surrogates
Authors: Chanda Arnab , McClain Stephen
Published: January 2019

The calcaneal fat pad is a major load bearing component of the human foot due to daily gait activities such as standing, walking, and running. Heel and arch pain pathologies such as plantar fasciitis, which over one third of the world population suffers from, is a consequent effect of calcaneal fat pad damage. Also, fat pad stiffening and ulceration has been observed due to diabetes mellitus. To date, the biomechanics of fat pad damage is poorly understood due to the unavailability of live human models (because of ethical and biosafety issues) or biofidelic surrogates for testing. This also precludes the study of the effectiveness of preventive custom orthotics for foot pain pathologies caused due to fat pad damage. The current work addresses this key gap in the literature with the development of novel biofidelic surrogates， which simulate the in vivo and in vitro compressive mechanical properties of a healthy calcaneal fat pad. Also, surrogates were developed to simulate the in vivo mechanical behavior of the fat pad due to plantar fasciitis and diabetes. A four-part elastomeric material system was used to fabricate the surrogates, and their mechanical properties were characterized using dynamic and cyclic load testing. Different strain (or displacement) rates were tested to understand surrogate behavior due to high impact loads. These surrogates can be integrated with a prosthetic foot model and mechanically tested to characterize the shock absorption in different simulated gait activities, and due to varying fat pad material property in foot pain pathologies (i.e., plantar fasciitis, diabetes, and injury). Additionally, such a foot surrogate model, fitted with a custom orthotic and footwear, can be used for the experimental testing of shock absorption characteristics of preventive orthoses.
Ethanol Conditioned Taste Aversion in High Drinking in the Dark Mice
Authors: Crabbe John C. , Metten Pamela , Savarese Antonia M. , Ozburn Angela R. , Schlumbohm Jason P. , Spence Stephanie E. , Hack Wyatt R.
Published: January 2019

Two independent lines of High Drinking in the Dark (HDID-1, HDID-2) mice have been bred to reach high blood alcohol levels after a short period of binge-like ethanol drinking. Male mice of both lines were shown to have reduced sensitivity to develop a taste aversion to a novel flavor conditioned by ethanol injections as compared with their unselected HS/NPT founder stock. We have subsequently developed inbred variants of each line. The current experiments established that reduced ethanol-conditioned taste aversion is also seen in the inbred variants, in both males and females. In other experiments, we asked whether HDID mice would ingest sufficient doses of ethanol to lead to a conditioned taste aversion upon retest. Different manipulations were used to elevate consumption of ethanol on initial exposure. Access to increased ethanol concentrations, to multiple tubes of ethanol, and fluid restriction to increase thirst motivation all enhanced initial drinking of ethanol. Each condition led to reduced intake the next day, consistent with a mild conditioned taste aversion. These experiments support the conclusion that one reason contributing to the willingness of HDID mice to drink to the point of intoxication is a genetic insensitivity to the aversive effects of ethanol.
Early Identification of Fragile X Syndrome through Expanded Newborn Screening
Authors: Okoniewski Katherine C. , Wheeler Anne C. , Lee Stacey , Boyea Beth , Raspa Melissa , Taylor Jennifer L. , Bailey Donald B.
Published: January 2019

Over the past 20 years, research on fragile X syndrome (FXS) has provided foundational understanding of the complex experiences of affected individuals and their families. Despite this intensive focus, there has been little progress on earlier identification, with the average age of diagnosis being 3 years. For intervention and treatment approaches to have the greatest impact, they need to begin shortly after birth. To access this critical timespan, differential methods of earlier identification need to be considered, with an emerging focus on newborn screening practices. Currently, barriers exist that prevent the inclusion of FXS on standard newborn screening panels. To address these barriers, an innovative program is being implemented in North Carolina to offer voluntary screening for FXS under a research protocol, called Early Check. This program addresses the difficulties observed in prior pilot studies, such as recruitment, enrollment, lab testing, and follow-up. Early Check provides an opportunity for stakeholders and the research community to continue to gain valuable information about the feasibility and greater impact of newborn screening on the FXS population.
Impact of Service Life on the Environmental Performance of Buildings
Authors: Janjua Shahana , Sarker Prabir , Biswas Wahidul
Published: January 2019

The environmental performance assessment of the building and construction sector has been in discussion due to the increasing demand of facilities and its impact on the environment. The life cycle studies carried out over the last decade have mostly used an approximate life span of a building without considering the building component replacement requirements and their service life. This limitation results in unreliable outcomes and a huge volume of materials going to landfill. This study was performed to develop a relationship between the service life of a building and building components, and their impact on environmental performance. Twelve building combinations were modelled by considering two types of roof frames, two types of wall and three types of footings. A reference building of a 50-year service life was used in comparisons. Firstly, the service life of the building and building components and the replacement intervals of building components during active service life were estimated. The environmental life cycle assessment (ELCA) was carried out for all the buildings and results are presented on a yearly basis in order to study the impact of service life. The region-specific impact categories of cumulative energy demand, greenhouse gas emissions, water consumption and land use are used to assess the environmental performance of buildings. The analysis shows that the environmental performance of buildings is affected by the service life of a building and the replacement intervals of building components.
Rac-Mediated Macropinocytosis of Extracellular Protein Promotes Glucose Independence in Non-Small Cell Lung Cancer
Authors: Hodakoski Cindy , Hopkins Benjamin D. , Zhang Guoan , Su Taojunfeng , Cheng Zhe , Morris Roxanne , Rhee Kyu Y. , Goncalves Marcus D. , Cantley Lewis C.
Published: January 2019

Cancer cells can adapt to nutrient poor conditions by rewiring their metabolism and using alternate fuel sources. Identifying these adaptive metabolic pathways may provide novel targets for cancer therapy. Here, we identify a subset of non-small cell lung cancer (NSCLC) cell lines that survive in the absence of glucose by internalizing and metabolizing extracellular protein via macropinocytosis. Macropinocytosis is increased in these glucose independent cells, and is regulated by phosphoinositide 3-kinase (PI3K) activation of Rac-Pak signaling. Furthermore, inhibition of Rac-dependent macropinocytosis blocks glucose-independent proliferation. We find that degradation of internalized protein produces amino acids, including alanine, which generates TCA cycle and glycolytic intermediates in the absence of glucose. In this process, the conversion of alanine to pyruvate by alanine transaminase 2 (ALT2) is critical for survival during glucose starvation. Collectively, Rac driven macropinocytosis of extracellular protein is an adaptive metabolic pathway used by a subset of lung cancers to survive states of glucose deprivation, and may serve as a potential drug target for cancer therapy.
Recent Advances in the Catalytic Synthesis of Imidazolidin-2-ones and Benzimidazolidin-2-ones
Authors: Casnati Alessandra , Motti Elena , Mancuso Raffaella , Gabriele Bartolo , Della Ca’ Nicola
Published: January 2019

2-Imidazolidinone and its analogues are omnipresent structural motifs of pharmaceuticals, natural products, chiral auxiliaries, and intermediates in organic syntheses. Over the years, continuous efforts have been addressed to the development of sustainable and more efficient protocols for the synthesis of these heterocycles. This review gives a summary of the catalytic strategies to access imidazolidin-2-ones and benzimidazolidin-2-ones that have appeared in the literature from 2010 to 2018. Particularly important contributions beyond the timespan will be mentioned. The review is organized in four main chapters that identify the most common approaches to imidazolidin-2-one derivatives: (1) the direct incorporation of the carbonyl group into 1,2-diamines, (2) the diamination of olefins, (3) the intramolecular hydroamination of linear urea derivatives and (4) aziridine ring expansion. Methods not included in this classification will be addressed in the miscellaneous section.
Recent Progress in Application of Molybdenum-Based Catalysts for Epoxidation of Alkenes
Authors: Shen Yirui , Jiang Pingping , Wai Phyu , Gu Qian , Zhang Weijie
Published: January 2019

Epoxides are important industrial intermediates applied in a variety of industrial processes. During the production of epoxides, catalysts have played an irreplaceable and unique role. In this review, the historic progress of molybdenum-based catalysts in alkene epoxidation are covered and an outlook on future challenge discussed. Efficient catalysts are demonstrated including soluble molybdenum complexes, polyoxometalates catalysts, molybdenum-containing metal organic frameworks, silica supported molybdenum-based catalysts, polymer supported molybdenum-based catalysts, magnetic molybdenum-based catalysts, hierarchical molybdenum-based catalysts, graphene-based molybdenum containing catalysts, photocatalyzed epoxidation catalysts, and some other systems. The effects of different solvents and oxidants are discussed and the mechanisms of epoxidation are summarized. The challenges and perspectives to further enhance the catalytic performances in alkenes epoxidation are presented.
Enhancing the Ethynylation Performance of CuO-Bi2O3 Nanocatalysts by Tuning Cu-Bi Interactions and Phase Structures
Authors: Wang Zhipeng , Niu Zhuzhu , Hao Quanai , Ban Lijun , Li Haitao , Zhao Yongxiang , Jiang Zheng
Published: January 2019

Catalytic systems consisting of copper oxide and bismuth oxide are commonly employed for the industrial production of 1,4-butynediol (BD) through ethynylation. However, few studies have investigated the influence mechanism of Bi for these Cu-based catalysts. Herein, a series of nanostructured CuO-Bi2O3 catalysts were prepared by co-precipitation followed by calcination at different temperatures. The obtained catalysts were applied to the ethynylation reaction. The textural and crystal properties of the catalysts, their reduction behavior, and the interactions between copper and bismuth species, were found to strongly depend on temperature. When calcined at 600 °C, strong interactions between Cu and Bi in the CuO phase facilitated the formation of highly dispersed active cuprous sites and stabilized the Cu+ valency, resulting in the highest BD yield. Bi2O3 was completely absent when calcined at 700 °C, having been converted into the spinel CuBi2O4 phase. Spinel Cu2+ was released gradually to form active Cu+ species over eight catalytic cycles, which continuously replenished the decreasing activity resulting from the formation of metallic Cu and enhanced catalytic stability. Moreover, the positive correlation between the in-situ-formed surface Cu+ ions and BD yield suggests that the amount of Cu+ ions is the key factor for ethynylation of formaldehyde to BD on the as prepared CuO-Bi2O3 catalysts. Based on these results and the literature, we propose an ethynylation reaction mechanism for CuO-based catalysts and provide a simple design strategy for highly efficient catalytic CuO-Bi2O3 systems, which has considerable potential for industrial applications.
Relevance of Autophagy in Parenchymal and Non-Parenchymal Liver Cells for Health and Disease
Authors: Weiskirchen Ralf , Tacke Frank
Published: January 2019

Autophagy is a highly conserved intracellular process for the ordered degradation and recycling of cellular components in lysosomes. In the liver, parenchymal cells (i.e., mainly hepatocytes) utilize autophagy to provide amino acids, glucose, and free fatty acids as sources of energy and biosynthesis functions, but also for recycling and controlling organelles such as mitochondria. Non-parenchymal cells of the liver, including endothelial cells, macrophages (Kupffer cells), and hepatic stellate cells (HSC), also employ autophagy, either for maintaining cellular homeostasis (macrophages, endothelium) or for providing energy for their activation (stellate cells). In hepatocytes, autophagy contributes to essential homeostatic functions (e.g., gluconeogenesis, glycogenolysis, fatty acid oxidation), but is also implicated in diseases. For instance, storage disorders (alpha 1 antitrypsin deficiency, Wilson’s disease), metabolic (non-alcoholic steatohepatitis, NASH), and toxic (alcohol) liver diseases may benefit from augmenting autophagy in hepatocytes. In hepatic fibrosis, autophagy has been implicated in the fibrogenic activation of HSC to collagen-producing myofibroblasts. In hepatocellular carcinoma (HCC), autophagy may contribute to tumor surveillance as well as invasiveness, indicating a dual and stage-dependent function in cancer. As many drugs directly or indirectly modulate autophagy, it is intriguing to investigate autophagy-targeting, possibly even cell type-directed strategies for the treatment of hereditary liver diseases, NASH, fibrosis, and HCC.
Sphingosine-1-Phosphate Receptor 2 Controls Podosome Components Induced by RANKL Affecting Osteoclastogenesis and Bone Resorption
Authors: Hsu Li-Chien , Reddy Sakamuri V. , Yilmaz Özlem , Yu Hong
Published: January 2019

Proinflammatory cytokine production, cell chemotaxis, and osteoclastogenesis can lead to inflammatory bone loss. Previously, we showed that sphingosine-1-phosphate receptor 2 (S1PR2), a G protein coupled receptor, regulates inflammatory cytokine production and osteoclastogenesis. However, the signaling pathways regulated by S1PR2 in modulating inflammatory bone loss have not been elucidated. Herein, we demonstrated that inhibition of S1PR2 by a specific S1PR2 antagonist (JTE013) suppressed phosphoinositide 3-kinase (PI3K), mitogen-activated protein kinases (MAPKs), and nuclear factor kappa-B (NF-κB) induced by an oral bacterial pathogen, Aggregatibacter actinomycetemcomitans, and inhibited the release of IL-1β, IL-6, TNF-α, and S1P in murine bone marrow cells. In addition, shRNA knockdown of S1PR2 or treatment by JTE013 suppressed cell chemotaxis induced by bacteria-stimulated cell culture media. Furthermore, JTE013 suppressed osteoclastogenesis and bone resorption induced by RANKL in murine bone marrow cultures. ShRNA knockdown of S1PR2 or inhibition of S1PR2 by JTE013 suppressed podosome components, including PI3K, Src, Pyk2, integrin β3, filamentous actin (F-actin), and paxillin levels induced by RANKL in murine bone marrow cells. We conclude that S1PR2 plays an essential role in modulating proinflammatory cytokine production, cell chemotaxis, osteoclastogenesis, and bone resorption. Inhibition of S1PR2 signaling could be a novel therapeutic strategy for bone loss associated with skeletal diseases.
Electrochemically Prepared Unzipped Single Walled Carbon Nanotubes-MnO2 Nanostructure Composites for Hydrogen Peroxide and Glucose Sensing
Authors: Zakaria A. B. M. , Leszczynska Danuta
Published: January 2019

Amperometric hydrogen peroxide (H2O2) and glucose biosensors based on unzipped carbon nanotubes with modified glassy carbon electrode (GCE) have been successfully fabricated via a facile electrochemical oxidative method. In this work, we investigated the feasibility of this new form of carbon nanomaterial as a substrate electrode material for fabricating sensitive platform for H2O2 and glucose sensors. For this purpose, the manganese oxide (MnO2)/unzipped single-walled carbon nanotubes (SWCNTs) film was synthesized by the cyclic voltammetry method. The developed sensing film, MnO2/unzipped SWCNTs/GCE, displayed a satisfactory analytical performance for H2O2, including a wide linear range of 2.0 × 10−6 to 5.0 × 10−3 M with a detection limit of 0.31 × 10−6 M (10.7 ppb). This film was further applied for glucose sensing with a linearity range of 0.01 to 1.2 mM with a correlation coefficient of 0.9822 in the physiological pH (7.4). This facile, fast, environmentally-friendly, and economical preparation strategy of carbon nanomaterial-based electrode materials opens up the possibility of developing high quality biocompatible hydrogen peroxide and glucose sensors.