Corrosion and corrosion-fatigue behavior of magnesium metal matrix composites for bio-implant applications:A review

Recently,the topic of bioresorbable metals,with much focus on magnesium for bone implant applications,has been an area of considerable investigation.Indeed,it could be argued that magnesium is the most promising biodegradable material currently being studied for use as an orthopedic skeletal fixation and joint replacement hardware.However,the fast degradation rate of magnesium-based materials in the physiological environment negatively affects their mechanical integrity and hence limits their biomedical use.The most critical conditions may occur when the implant is subjected to a corrosive physiological environment and a fluctuating load during daily activities.Hence,numerous studies have been published on the synthesis,alloying,and coating of magnesium to control degradation rate and increase strength and durability.Among the materials and strategies employed to achieve these goals,magnesium-based biocomposites have exhibited superior mechanical properties and acceptable biocompatibility.However,there is a lack of understanding of their corrosion and corrosion-fatigue behavior.Such understanding is necessary to qualify these new materials for various bio-implant applications.To this end,this paper reviews the recent advances in the corrosion and corrosion-fatigue behavior of magnesium-based biocomposites.It also provides a comprehensive discussion of different factors that influence the biocompatibility,corrosion,fatigue,and corrosion-fatigue of magnesium-based biocomposites as potential implant materials.This study emphasizes that despite the abundance of various studies on the corrosion behavior of magnesium-based biocomposites,there is an imperative need for more fatigue and corrosion-fatigue studies.

Spatiotemporal Analysis and Predictive Modeling of Rabies in Tennessee

Among viruses, Rhabdovirus, more commonly known as rabies, is largely monitored throughout landscapes because of its known risks and deadliness. While vaccination and education efforts have been enforced and apparently successful in the past decades, many questions still exist in some regions about the virus’s spread and potential. In the United States, the state of Tennessee’s Department of Health has documented rabies reports from the 1940s-2010s, but not as many spatial analyses have been performed to further map and assess rabid animals in this variable landscape. Our study proposed to create distribution and density models to give an idea of the types of locations rabid animals have consistently been found. A predictive model was also created using software that simulated landscape fragmentation and habitat connectivity, to provide further insight for potential disease spread. Our results display that Tennessee’s central region, which is a more homogenous landscape, tended to host a lot of rabid animals and maintained a rather consistent distribution throughout the years. The predictive model was simulated on a less homogenous landscape and displayed that spread potential can be affected by natural barriers. Each of these spatial results could be of service in future disease monitoring, hopefully for the benefit of wildlife and people alike.

Modeling Enhanced Adsorption of Explosive Molecules on a Hydroxylated Graphene Pore

The possibility of a graphene bilayer nanosensor for the detection of explosive molecules was modeled using computational chemistry. A pore was designed on a graphene bilayer structure with three strategically placed perimeter hydroxyl (OH) groups built around the edge of an indented, two-dimensional hexagonal pore. This hydroxylated pore and models of various explosive molecules were optimized using MM2 molecular mechanics parameters. Values were calculated for the molecule-surface interaction energy (binding energy), E, for 22 explosive molecules on a flat graphene bilayer and on the specially designed hydroxylated pore within the bilayer. The molecule-surface binding energy for trinitrotoluene (TNT) increased from 17.9 kcal/mol on the flat graphene bilayer to 42.3 kcal/mol on the hydroxylated pore. Due to the common functionality of nitro groups that exist on many explosive molecules, the other explosive molecules studied gave similar enhancements based on the specific hydrogen bonding interactions formed within the pore. Each of the 22 explosive adsorbate molecules showed increased molecule-surface interaction on the bilayer hydroxylated pore as compared to the flat bilayer. For the 22 molecules, the average E for the flat graphite surface was 15.8 kcal/mol and for the hydroxylated pore E was 33.8 kcal/mol. An enhancement of adsorption should make a detection device more sensitive. Nanosensors based on a modified graphene surface may be useful for detecting extremely low concentrations of explosive molecules or explosive signature molecules.

Storage and Timed Release of Acetaminophen from Porous Carbonaceous Materials

Six carbon powders with varied surface areas and porosities were used to store and release acetaminophen (ACT). A 10 mg/mL solution of acetaminophen in phosphate buffer solution (pH = 7.0) at 25℃ with exposure to carbon powder for 72 hours was used to drive the maximum loading of acetaminophen into the powders. Carboxen 1012 (BET surface area of1500 m2/g) powder exhibited the greatest maximum adsorption of ACT (up to 62% by mass). The maximum ACT adsorption was correlated with surface area and porosity. The most effective carbon powders for binding ACT were ones containing high mesopore volumes. Loaded carbon powder was separated from the ACT solution and then phosphate buffer solution (pH = 7.0) was combined with the loaded carbon powder and ACT absorbance readings at 243 nm were taken over time. The various carbon powders were able to release a portion of the ACT that they originally adsorbed. The Carboxen 1012 powder displayed the greatest ACT release with a rapid initial release followed by a steady but slightly declining release over a time period of 2 to 11 weeks. The results were supportive of mesoporous carbons such as Carboxen 1012 being suitable for drug loading and release.

Biological implications of 2-chlorocyclohexa-2,5-diene-1,4-dione toward ribonuclease A

2-Chlorocyclohexa-2,5-diene-1,4-dione (CBQ) or 2-chloro1,4-benzquinone is one of the common metabolites of polycyclic aromatic hydrocarbons generated through industrial processes. This report describes the biological effects of CBQ toward ribonuclease A (RNase). We also investigated the inhibition of RNase modifications and the reactivity of CBQ toward selected amino acids. The study was carried out by incubating RNase or amino acids with CBQ in a concentration- and a time-dependent manner at 37&degC and pH 7.0. SDS-PAGE results showed oligomerization as well as polymeric aggregation of RNase when incubated with CBQ as early as in 10 min. CBQ-induced RNase modifications were inhibited in the presence of NADH or ascorbic acid. CBQ reactivity toward selected amino acids was also evaluated by determining the second-order rate constants for the reactions of CBQ with selected amino acids. It was found that the reactivity toward CBQ decreased in the order of lysine > threonine > serine >> aspartate > cysteine.

Detecting Photoacoustic Signals of Sulfur Hexafluoride at Varying Microphone Positions

Photoacoustic spectroscopy was used to test the photoacoustic properties of sulfur hexafluoride, an optically thick and potent greenhouse gas. While exploring the photoacoustic effect of sulfur hexafluoride, the effects of the position of the microphone within a gas cell were determined. Using a 35 cm gas cell, microphones were positioned at 17.5 cm, the middle of the gas cell, 12.5 cm, 7.5 cm, and 2.5 cm from the window of the cell. From the photoacoustic signal produced for each resonance frequency at each microphone position, the effects of acoustic pressure produced at each position on the signal recorded were observed. This is the first study done by experimentation with the photoacoustic effect to show that standing waves have different amplitudes at different microphone positions.

Big data-enabled multiscale serviceability analysis for aging bridges

This work is dedicated to constructing a multi-scale structural health monitoring system to monitor and evaluate the serviceability of bridges based on the Hadoop Ecosystem （MS-SHM-Hadoop）. By taking the advantages of the fault-tolerant distributed file system called the Hadoop Distributed File System （HDFS） and high-performance parallel data processing engine called MapReduce programming paradigm, MS- SHM-Hadoop features include high scalability and robustness in data ingestion, fusion, processing, retrieval, and analytics. MS-SHM-Hadoop is a multi-scale reliability analysis framework, which ranges from nationwide bridge-surveys, global structural integrity analysis, and structural component reliability analysis. This Nationwide bridge survey uses deep-learning techniques to evaluate the bridge service- ability according to real-time sensory data or archived bridge-related data such as traffic status, weather conditions and bridge structural configuration. The global structural integrity analysis of a targeted bridge is made by processing and analyzing the measured vibration signals incurred by external loads such as wind and traffic flow. Component-wise reliability analysis is also enabled by the deep learning technique, where the input data is derived from the measured structural load effects, hyper-spectral images, and moisture measurement of the structural components. As one of its major contributions, this work employs a Bayesian network to formulate the integral serviceability of a bridge according to its components serviceability and inter-component correlations. Here the inter-component correlations are jointly specified using a statistics-oriented machine learning method （e.g., association rule learning） or structural mechanics modeling and simulation.

Polycyclic Aromatic Hydrocarbon Molecule-Surface Binding Energies in Site Specific Graphene Bilayer Nanopores: A Puzzle-ene Force Field Calculation

Two-dimensional molecular recognition studies of the six polyaromatic hydro-carbons that can be formed from the combination of four benzene rings: tetracene, pyrene, 1,2-benzanthracene, 3,4-benzphenanthrene, triphenylene, and chrysene were explored for each of these six molecules interacting with six different graphene layer site-specific nanopores. Computational studies were done for the gas phase adsorption on single layer graphene, bilayer graphene, and six molecule-specific graphene bilayer nanopores. Molecular mechanics MM2 parameters have been shown previously to provide good comparisons to experimental adsorption energies for aromatic hydrocarbons adsorption on graphitic surfaces. These binding energies are dominated by van der Waals forces. Just as a jigsaw puzzle hole can accommodate only a specific piece, two-dimensional shape specific sites were created in the top layer of a graphene bilayer to match each one of the six adsorbate molecules. The purpose of this study was to examine the molecular recognition possibilities of site specific adsorption in these simple two-dimensional nanopores based on dispersion forces and molecular shape. For example, triphenylene has a calculated surface binding energy of 24.5 kcal/mol on the graphene bilayer and 30.2 kcal/mol in its own site specific pore. The interaction energy of this molecule in the other five sites ranged from 17.6 to 23.8 kcal/mol. All the molecules tetracene, pyrene, 1,2-benzanthracene, triphenylene and chrysene had higher binding energies in their matched molecule bilayer sites than on either single or double layer graphene. In addition, each one of these five molecules had a stronger binding in their own shape specific (puzzle-ene) site than any of the other molecular sites. The results suggest that two-dimensional molecular recognition based on shape specific pores may allow selectivity useful for applications such as sensors, separations, nanofabrication, or information storage.

Adsorption of Cholesterol on Carbon Powders

Carbon powders have the ability to remove cholesterol from solution by adsorption. Various combinations from among 12 different types of carbon powders （including two medical carbons）, having a wide range of surface area and porosity, were used to perform cholesterol adsorption experiments. The cholesterol concentration in a cyclohexane solvent （37 ~C, shaking 200 rpm） was detected at 215 nm using ultraviolet spectroscopy. Most adsorption occurred in the first 30 to 60 minutes. A Langmuir model was used to fit the amount of cholesterol adsorbed per gram of carbon. The medical carbon, Natural Elements Activated Charcoal, adsorbed 234 mg of cholesterol adsorption per gram of carbon. The experimental percentages of cholesterol removed from solution （maximum 98%） were correlated with nitrogen Branauer-Emmett-Teller （BET） surface areas and micro, meso, and macropore volume distributions. Surface area alone was not a suitable predictor of cholesterol adsorption. However, carbon powders exhibiting a large surface area along with significant meso and macropores were shown to be effective in adsorbing cholesterol from a nonpolar environment. Ingestion of a medically approved carbon powder with a large surface area and sufficient meso and macroporosity may be able to adsorb cholesterol in the intestinal tract and thereby lower cholesterol levels in the body.

Promoting Active Living and Healthy Eating among Inner-City Youth through Community Health Workers: From Clinic to Neighborhood

The promotion of physical activity and healthy eating to prevent obesity among youth is a pressing challenge. The current study examined the feasibility of community health workers (CHWs) conducting a physical activity (PA) and healthy eating intervention strategy with links to community supports and programs. Youth aged 10 - 18 years were recruited from three clinical sites serving inner-city families. Trained CHWs conducted assessment and counseling for PA and healthy eating among youth and their families and provided customized plans and navigation to neighborhood PA and nutrition programs. Measures of daily PA by self-report, weekday and weekend day sedentary behaviors, fruit and vegetable intake, avoidance of fatty foods, and avoidance of sugary drinks were assessed at baseline and follow-up. Twenty-five patients (mean age = 12.9 years) were exposed to ~9 months of intervention from baseline. Pre- and post-assessments revealed significant changes in reported PA, sedentary behaviors on weekdays, sedentary behaviors on weekend days, fruit and vegetable intake, avoidance of fatty foods, and avoidance of sugary drinks. Results demonstrated the feasibility of having CHWs effectively influenced the PA and eating behaviors of inner-city youth. Greater success was evident when assessment and counseling for PA and healthy eating were accompanied by navigation to neighborhood resources. The use of CHWs may be a cost-effective approach impacting the PA, sedentary, and dietary behaviors of youth.

Creating a Dataset to Boost Civil Engineering Deep Learning Research and Application

With cutting edge deep learning breakthrough,numerous innovations in many fields including civil engineering are stimulated.However,a fundamental issue that civil engineering research community currently facing is lack of a publicly available,free,quality-controlled and human-annotated large dataset that supports and drives civil engineering deep learning research and applications on such as intelligent transportation including connected vehicle,structural health monitoring,and bridge inspection.This paper is a general discussion about demanding needs and construction of a long-anticipated dataset for researchers and engineers in civil engineering and beyond for providing critical training,testing and benchmarking data.The establishment of such a free dataset will remove a major hurdle and boost deep learning research in civil engineering and we hope this work will urge researchers,engineers,government agencies and even computer scientists to work together to start building such datasets.A framework has been developed for the proposed database.Also,some pilot study databases were developed for concrete crack detection,pavement crack detection using normal and infrared thermography,as well as pedestrian and bicyclist detection.A convolution neural network model called Faster RCNN was deployed to check the detection accuracy and a 98%detection accuracy of the proposed datasets was obtained.

Analysis of cost effective pavement treatment and budget optimization for arterial roads in the city of Chattanooga

Many transportation agencies lack sufficient funds to maintain and repair roads, which results into increased pavement maintenance cost. Pavement Management System （PMS） has demonstrated to be an essential tool for proper management of infrastructure and proper utilization of available funds. The University of Tennessee at Chattanooga utilized Micropaver software as PMS tool to conduct a pavement management analysis of principal arterials in the City of Chattanooga. The study used the City of Chattanooga pavement database to create the current and future pavement conditions. Maintenance and repair （M＆R） planning analysis was also performed in order to determine the most cost-effective treatment and suggest the optimum utilization of funds for the city. An analysis of five budget scenarios was conducted for a five-year plan using the critical pavement condition index （PCI） method （ASTM D6433）. Results show that the backlog elimination budget would be the best scenario because it increases the pavement condition and eliminates the backlog of major maintenance and repairs over the five-year period. The unlimited budget seems though ideal, it does not improve pavement condition. Maintaining current condition and limited budget scenarios would increase both the backlog and the total cost of maintenance and repairs over the analysis period.

Monitoring permeable paver runoff with an open-innovation geospatial sensor network

Sensor networks are an essential tool for environmental scientists.As scientists and engineers are beginning to utilize these new methods and devices in their fieldwork,they need to be actively involved in the future of sensor-networking development.Continued sensor network innovation is important for improved standardization,affordability,and interoperability.This article uses a storm water case study to outline an end-to-end open-innovation sensor network.Open innovation by scientists,engineers,and entities is the collaborative process of creating value for this project in permeable paver runoff data and advances within sensor networking.This article focuses on the technical implementation of the near–real-time location and temporally aware sensor network.Data are streamed in near–real-time with subliter precision to the cloud using common off-the-shelf routers.The sensors use Maxim’s 1-wire™protocol,and the unique digital serial numbers confirm the data.The data retrieved compare residence times within the permeable paver catchment basins and the control basin.Sensor network advances are made by bridging the gap between sensor protocols and communication systems.These advances enable the development of open-source representational state transfer web services.Our successful implementation serves as an example for others to study and expand upon for a variety of monitoring solutions.

Nordhaus-Gaddum Results for the Sum of the Induced Path Number of a Graph and Its Complement

The induced path number p（G） of a graph G is defined as the minimum number of subsets into which the vertex set of G can be partitioned so that each subset induces a path. Broere et hi. proved that if G is a graph of order n, then 〈 p（G） ＋ p（G） 〈3n/2] . In this paper,_we characterize [3n/2], improve the lower bound on p（G） ＋ p（G） by one when the graphs G for which p（G） -4- p（G） = 3n n is the square of an odd integer, and determine a best possible upper bound for p（G） ＋ p（G） when neither G nor G has isolated vertices.

Force Field Based MM2 Molecule-Surface Binding Energies for Graphite and Graphene

The gas phase adsorption of 118 organic molecules on graphite and graphene was studied by calculating their molecule surface binding energies, Ecal*, using molecular mechanics MM2 parameters. Due to the general lack of reported experimental binding energy values for organic molecules with graphene, E*(graphene), it was considered desirable to have a simple but effective method to estimate these values. Calculated binding energy values using a three-layer model, Ecal*(3), were compared and correlated to published experimental values for graphitic surfaces, E*(graphite). Pub-lished values of experimental binding energies for graphite, E*(graphite), were available from gas-solid chromatogram-phy in the Henry’s Law region over a range of temperature. Calculated binding energy values using a one-layer model, Ecal*(1), were compared to the three-layer Ecal*(3) values and found to consistently be 93.5% as large. This relation along with an E*(graphite) and Ecal*(3) correlation was used to develop a means to estimate molecule-graphene bind-ing energies. Using this approach we report estimated values of 118 molecule-graphene binding energy values.

Optimal treatment strategy of an avian influenza model with latency

Avian influenza, caused by influenza A viruses, has received worldwide attention over recent years. In this study, we formulate a mathematical model for avian influenza that includes human human transmission and incorporates the effects of infection latency and treatments. We investigate the essential dynamics of the model through an equilibrium analysis. Meanwhile, we explore effective treatment strategies to control avian influenza outbreaks using optimal control theory. Our results show that strategically deployed medical treatments can significantly reduce the numbers of exposed and infection persons.

Ithamar Theodor, and Zhihua Yao, eds. Brahman and Dao： Comparative Studies of Indian and Chinese Philosophy and Religion （edited by Ethan Mills）

In recent decades much of what goes by the name ＂comparative philosophy＂ has focused on comparing Western philosophy with South Asian philosophy, or comparing Western philosophy with East Asian philosophy. While this approach has been beneficial both for cultural understanding and philosophical illumination, one might wonder why there have been so few comparisons between East Asian and South Asian traditions. The potential value of such comparisons becomes evident when considering the vast differences between these traditions （as a specialist in classical Indian philosophy, I sometimes find myself explaining to colleagues familiar only with Western philosophy that there is no single tradition called ＂Eastern philosophy＂）.

A degenerate elliptic system with variable exponents

We study a degenerate elliptic system with variable exponents. Using the variational approach and some recent theory on weighted Lebesgue and Sobolev spaces with variable exponents, we prove the existence of at least two distinct nontrivial weak solutions of the system. Several consequences of the main theorem are derived;in particular, the existence of at lease two distinct nontrivial non-negative solutions is established for a scalar degenerate problem. One example is provided to show the applicability of our results.

On the dynamics of a class of perturbed cyclic Lotka-Volterra systems

We consider a special class of Lotka-Volterra systems where the associated interaction matrix is cyclic, but asymmetric, with a perturbation term on each row. After some discussion of the dynamics under a general setting, we focus our attention on 3D systems for a more detailed study. We derive sufficient conditions for the existence and stability of the nontrivial interior equilibrium. We also show that Hopf bifurcation occurs when the size of the perturbation is large. Such analysis can be similarly extended to higher dimensional systems, and we mention some results in 4D case.

Many Healths： Nietzsche and Phenomenologies of Illness

This paper considers phenomenological descriptions of health in Gadamer, Heidegger, Merleau-Ponty, and Svenaeus. In these phenomenologies of health, health is understood as a tacit, background state that permits not only normal functioning but also philosophical reflection. Nietzsche＇s model of health as a state of intensity that is intimately connected to illness and suffering is then offered as a rejoinder. Nietzsche＇s model includes a more complex view of suffering and pain as integrally tied to health, and its language opens up the possibility of many ＂healths,＂ providing important theoretical support to phenomenological accounts of the diversity and complexity of health and illness.