An Adaptive Transmission Mode Selection Scheme for Cellular Underlaid D2D Communication

In this paper, we propose to use Artificial Bee Colony (ABC) optimization to solve the joint mode selection, channel assignment, and power allocation (JMSCPA) problem to maximize system throughput and spectral efficiency. JMSCPA is a problem where the allocation of channel and power depends on the mode selection. Such problems require two step solution and are called bi-level optimization problems. As bi-level optimization increases the complexity and computational time, we propose a modified version of single-level ABC algorithm aided with the adaptive transmission mode selection algorithm to allocate the cellular, reuse, and dedicated modes to the DUs along with channel and power allocation based on the network traffic load scenarios. A single variable, represented by the users (CUs and DUs) is used to allocate mode selection, and channel allocation to solve the JMSCPA problem, leading to a simpler solution with faster convergence, and significant reduction in the computational complexity which scales linearly with the number of users. Further, the proposed solution avoids premature stagnation of conventional ABC into local minima by incorporating a modification in its update procedure. The efficacy of the ABC-aided approach, as compared to the results reported in the literature, is validated by extensive numerical investigations under different simulation scenarios.

     

Idiosyncratic Drug-Induced Liver Injury: Mechanistic and Clinical Challenges

Idiosyncratic drug-induced liver injury (IDILI) remains a significant problem for patients and drug development. The idiosyncratic nature of IDILI makes mechanistic studies difficult, and little is known of its pathogenesis for certain. Circumstantial evidence suggests that most, but not all, IDILI is caused by reactive metabolites of drugs that are bioactivated by cytochromes P450 and other enzymes in the liver. Additionally, there is overwhelming evidence that most IDILI is mediated by the adaptive immune system; one example being the association of IDILI caused by specific drugs with specific human leukocyte antigen (HLA) haplotypes, and this may in part explain the idiosyncratic nature of these reactions. The T cell receptor repertoire likely also contributes to the idiosyncratic nature. Although most of the liver injury is likely mediated by the adaptive immune system, specifically cytotoxic CD8+ T cells, adaptive immune activation first requires an innate immune response to activate antigen presenting cells and produce cytokines required for T cell proliferation. This innate response is likely caused by either a reactive metabolite or some form of cell stress that is clinically silent but not idiosyncratic. If this is true it would make it possible to study the early steps in the immune response that in some patients can lead to IDILI. Other hypotheses have been proposed, such as mitochondrial injury, inhibition of the bile salt export pump, unfolded protein response, and oxidative stress although, in most cases, it is likely that they are also involved in the initiation of an immune response rather than representing a completely separate mechanism. Using the clinical manifestations of liver injury from a number of examples of IDILI-associated drugs, this review aims to summarize and illustrate these mechanistic hypotheses.     

Are multimodal travelers more satisfied with their lives? A study of accessibility and wellbeing in the Denver,Colorado metropolitan area

In this study, we ask how the ability to use multiple transportation options affects one's subjective wellbeing (SWB), including aspects such as physical health, financial security, standard of living, and personal relationships. A clearer understanding of these associations can inform investments in multimodal infrastructure. We draw on 232 surveys from a diverse set of residents in the Denver, Colorado metropolitan area and find that having more transportation choices can improve standard of living for low- and middle-income residents. Multimodal middle-income residents are also more satisfied with their health and what they are achieving in life. Vehicle owners report higher levels of satisfaction with their standard of living, health, and achievements, compared to non-owners, unless auto is their only travel mode. Only low-income respondents had significant differences in standard of living by where they lived, with greatest satisfaction in the urban core. These results confirm the relationship between public transit and SWB, and contribute to our understanding of how the concept of motility (social and spatial mobility) shapes one's quality of life. The findings have implications for investments in transportation modes across neighborhood types and populations, so that people have a range of travel options to meet their needs and increase their satisfaction with their goals through improved daily travel.     

Seasonal movements of muskellunge in the St. Clair – Detroit River System: Implications for multi-jurisdictional fisheries management

The St. Clair-Detroit River System contains a world-class Great Lakes muskellunge (Esox masquinongy) fishery that has avoided the declines observed in many Great Lakes muskellunge populations. Muskellunge are an upper trophic level predator, and therefore a naturally low-density species. Limited fishery-independent data exist on which to base management decisions. To remedy this, we initiated an acoustic telemetry study in May of 2016, in collaboration with the Great Lakes Acoustic Telemetry Observation System. Our objective was to describe patterns of movement of muskellunge in this large and open system to better understand their spatial ecology. We acoustically tagged 133 muskellunge in the Detroit River and Lake St. Clair, and movements of 58 fish that passed our data quality control screens were analyzed. We utilized mixed modelling to assess the effects of sex, length, release location, and season on daily movement rates. We found that movement rates only differed among seasons, with highest movement rates occurring in the fall and lowest movement rates in the winter. Muskellunge tagged at different locations exhibited distinct residency patterns, and fish frequently crossed jurisdictional and waterbody boundaries. Ultimately our study highlights the scope and patterns of muskellunge movement in a large, unimpounded system and demonstrates that management of these fish would benefit from consideration of their full distribution covering multiple management jurisdictions.     

Vertical oscillations of the thermocline caused by internal waves modify coldwater pelagic fish distribution: Results from a large stratified lake

Fishes typically occupy a species-specific temperature range, with their occupied depth being related to the lake’s temperature profile. When a fish’s preferred temperature range coincides with the thermocline, the location of their preferred thermal habitat is influenced by the rise and fall of internal waves, leading to possible changes in fish depth. These internal waves are common in large, stratified lakes, yet we do not know how they affect the spatial distribution and behavior of freshwater fishes. We conducted nighttime hydroacoustic surveys in a large, deep embayment of a large thermally stratified lake to observe whether pelagic fish respond to vertical oscillations of the thermocline caused by internal waves. The coldwater pelagic fish in our study (primarily cisco, Coregonus artedi) typically occupied a narrow vertical band approximately 5–8 m thick and temperatures between 10.8 ± 0.8–13.6 ± 1.6 °C (fishes sized 106–500 mm), just below the thermocline (centered around 15–17 °C). Importantly, the upper bound of fish depth varied in response to vertical thermocline movements associated with internal waves, suggesting fish respond to changes in their physical environment on timescales commensurate with basin-scale internal wave periods (hours to days), to remain within their preferred thermal habitat. Dissolved-oxygen levels were typically above avoidance thresholds of these fish, thus not likely exerting a strong influence on fish location. Our findings emphasize the need to account for internal waves when designing hydroacoustic and netting surveys, as thermocline movements can influence where fish are located.     

Mechanical and electrical properties of NbMoTaW refractory high-entropy alloy thin films

Refractory high-entropy alloys (RHEAs) have opened a new chapter in the development of structural materials for use at high temperatures owing to their outstanding mechanical properties and thermal stability. In this study, we developed a NbMoTaW RHEA thin film via direct current magnetron sputtering from a single target that was synthesized by sintering a mixture of multiple elemental powders. The as-deposited thin film exhibited a single nanocrystalline solid-solution phase with body-centered cubic structure. Moreover, the film had a high hardness of 12 GPa and electrical resistivity of 168 μΩ·cm due to severe lattice distortion and the presence of nanoscale grains. Hence, RHEA films can be used as a hard coating for protective layers and as electrical resistors in nanofabricated devices owing to their favorable combination of hardness and electrical resistivity.     

The effects of blast lag in abrasive jet machined micro-channel intersections

Abrasive jet micro-machining (AJM) uses compressed air carrying abrasive solid particles to micro-machine a variety of features into surfaces. If the feature sizes are less than the size of the abrasive jet footprint, then a patterned erosion-resistant mask is used to protect the substrate material, leaving exposed areas to define the features. Previous investigations have revealed a ‘blast lag’ phenomenon in which, for the same dose of abrasive particles, narrower mask openings lead to channels that are shallower than wider ones. Blast lag occurs when using AJM on brittle substrates because of the natural tendency to rapidly form a V-shaped cross-sectional profile which inhibits abrasive particle strikes on the narrow vertex at the feature centerline. In this paper, the blast lag phenomenon is studied when using AJM to machine a network of microfluidic channels. It is found that, in some cases, differences in blast lag occurring at channel intersections and within the channels themselves, can lead to channel networks of nonuniform depth. A previously developed surface evolution model is adapted to allow prediction of the onset of blast lag in the channels and intersections and thus explain these differences. Finally, methods to eliminate the differences are discussed.     

Quality of location-based crowdsourced speed data on surface streets: A case study of Waze and Bluetooth speed data in Sevierville,TN

Obtaining accurate speed and travel time information is a challenge for researchers, geographers, and transportation agencies. In the past, traffic data were usually acquired and disseminated by government agencies through fixed-location sensors. High costs, infrastructure demands, and low coverage levels of these sensor devices require agencies and researchers to look beyond the traditional approaches. With the emergence of smartphones and navigation apps, location-based and crowdsourced Big Data are receiving increased attention. In this regard, location-based big data (LocBigData) collected from probe vehicles and road users can be used to provide speed and travel time information in different locations. Examining the quality of crowdsourced data is essential for researchers and agencies before using them. This study assessed the quality of Waze speed data from surface streets and conducted a case study in Sevierville, Tennessee. Typically, examining the quality of these data in surface streets and arterials is more challenging than freeways data. This research used Bluetooth speed data as the ground truth, which is independent of Waze data. In this study, three steps of methodology were used. In the first step, Waze speed data was compared to Bluetooth data in terms of accuracy, mean difference, and distribution similarity. In the second step, a k-means algorithm was used to categorize Waze data quality, and a multinomial logistics regression model was performed to explore the significant factors that impact data quality. Finally, in the third step, machine learning techniques were conducted to predict the data quality in different conditions. The result of the comparison showed a similar pattern and a slight difference between datasets, which verified the quality of Waze speed data. The statistical model indicates that that Waze speed data are more accurate in peak hours than in night hours. Also, the traffic speed, traffic volume, and segment length have a significant association on the accuracy of Waze data on surface streets. Finally, the result of machine learning prediction showed that a KNN method performed the highest prediction accuracy of 84.5% and 82.9% of the time for training and test datasets, respectively. Overall, the study results suggest that Waze speed data is a promising data source for surface streets.     

High Electrical and Thermal Conductivity Cast Al-Fe-Mg-Si Alloys with Ni Additions

Metallurgical and Materials Transactions A - Aluminum alloys with transition metals Fe and Ni show potential to form the basis for castable alloys with high electrical and thermal conductivity for...