Rip currents near coastal structures in Lake Michigan: Characterization and assessment for warnings

Rip currents near coastal structures commonly occur in Lake Michigan in the Great Lakes region of the United States. Lack of timely warning due to undocumented characteristics of rip currents and no assessment tool can contribute to tragic drownings incidents. In this paper, we characterized rip current occurrences near breakwater structures and developed an assessment tool for providing timely rip current warnings to beachgoers at the study site, City of Port Washington, WI. Characteristics of rip currents near the structure were observed from field measurements or visual images. Deflection rip currents had speeds of ～ 0.2 m/s and lasted for several hours. The rip current occurrences were associated with environmental proxies. It was found that rip currents can occur even when the water appears calm near the structure. A Structure Rip Checklist and Assessment Matrix (SRiCAM) with a four-tiered risk was developed and validated using observations. Furthermore, the SRiCAM was integrated into cyberinfrastructure with a data contingency plan to provide real-time warnings to the public. The applicability of the SRiCAM to other locations across Lake Michigan was further tested and results are promising. Overall, the SRiCAM has the potential to be widely extended to foster recreational water safety and resilience to rip current hazards in the Great Lakes.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

A Review of Ultrasonic Reflectometry for the Physical Characterization of Lubricated Tribological Contacts: History,Methods, Devices,and Technological Trends

Tribology Letters - The tribological behavior of a nickel-based single crystal superalloy treated by shot-peening has been investigated. Friction tests under three normal loads and three...     

Assessing the expectations associated with pharmaceutical pill colour and shape

Two experiments are reported in which people’s sensory, hedonic, and efficacy expectations associated with pharmaceutical pills of differing colour and shape were assessed. In Experiment 1, 101 participants from the USA viewed online photos of tablets having one of 7 colours and 3 shapes. The participants had to arrange the 21 tablets based on the expectations generated solely by the tablets’ visual properties. The results revealed that the colour of the tablets influenced expected bitterness, expected alertness, and expected efficiency in combating headaches, whereas the shape of the tablets influenced the expected difficulty of swallowing. In Experiment 2, the major findings of Experiment 1 were replicated while using a greater variety of colours, in 358 participants from China, Colombia, and the USA. Importantly, the results revealed some shared expectations across cultures, such as the high expected efficacy of white tablets in combating headaches, or the high expected difficulty of swallowing the diamond-shaped tablets. The results also revealed some differences among the three groups, such as that the colour of the pills influenced how difficult the Chinese participants (but not the other two groups) expected the pills would be to swallow. These findings clearly demonstrate that the differing colours and shapes of pharmaceutical pills set-up significantly different expectations which likely play an important role in terms of people’s subsequent experience.     

Study of MW-scale biogas-fed SOFC-WGS-TSA-PEMFC hybrid power technology as distributed energy system: Thermodynamic,exergetic and thermo-economic evaluation

Advanced biogas power generation technology has been attracting attentions, which contributes to the waste disposal and the mitigation of greenhouse gas emissions. This work proposes and models a novel biogas-fed hybrid power generation system consisting of solid oxide fuel cell, water gas shift reaction, thermal swing adsorption and proton exchange membrane fuel cell (SOFC-WGS-TSA-PEMFC). The thermodynamic, exergetic, and thermo-economic analyses of this hybrid system for power generation were conducted to comprehensively evaluate its performance. It was found that the novel biogas-fed hybrid system has a gross energy conversion efficiency of 68.63% and exergy efficiency of 65.36%, indicating high efficiency for this kind of hybrid power technology. The market sensitivity analysis showed that the hybrid system also has a low sensitivity to market price fluctuation. Under the current subsidy level for the distributed biogas power plant, the levelized cost of energy can be lowered to 0.02942 $/kWh for a 1 MW scale system. Accordingly, the payback period and annual return on investment can reach 1.4 year and about 20%, respectively. These results reveal that the proposed hybrid system is promising and economically feasible as a distributed power plant, especially for the small power scale (no more than 2 MW).     

PMU based voltage security assessment of power systems exploiting principal component analysis and decision trees

The need for feature selection and dimension reduction is felt as a fundamental step in security assessment of large power systems in which the number of features representing the state of power grids dramatically increases. These large amounts of attributes are not proper to be used for computational intelligence (CI) techniques as inputs, because it may lead to a time consuming procedure with insufficient results and they are not suitable for on-line purposes and updates.This paper proposes a combined method for an online voltage security assessment in which the dimension of the token data from phasor measurement units (PMUs) is reduced by principal component analysis (PCA). Then, the features with different stability indices are put into several categories and feature selection is done by correlation analysis in each category. These selected features are then given to decision trees (DTs) for classification and security assessment of power systems.The method is applied to 39-bus test system and a part of Iran power grid. It is seen from the results that the DTs with reduced data have simpler splitting rules, better performance in saving time, reasonable DT error and they are more suitable for constant updates.     

Intrinsic dielectric behavior of Mg2TiO4 spinel ceramic

In the work, we focused on the intrinsic dielectric behavior of Mg₂TiO₄ spinel ceramic by P–V–L theory and infrared spectra analysis. Ti–O bonds have larger bond ionicity values, thus playing an important role in dielectric polarization. The theoretical dielectric constant was predicted by calculating the bond susceptibility of each chemical bond. Furthermore, Ti(1)–O bonds are responsible for the structural stability of Mg₂TiO₄ ceramic. Based on classical dispersion theory, permittivity and loss corresponding to each infrared active mode were quantified, and then the crucial contribution of low-frequency modes to intrinsic dielectric properties were determined.     

Tribological behavior of Zr-based bulk metallic glass sliding against polymer,ceramic, and metal materials

The tribological properties of zirconium-based bulk metallic glass (BMG) sliding against polymers, steels, and ceramics at different loads and speeds were investigated. Acoustic emission (AE) technology was used to analyze wear states. The frictional coefficients of the BMG slid against the steel and ceramic balls were high but decreased with increased applied normal load and sliding speed. As the steel balls were more ductile than the ceramic ones, the steel–BMG sliding pairs generated weaker AE signals and exhibited larger wear rates. The BMG tested against the polymer balls had much lower and more stable frictional coefficients than the ones against the steel or ceramic balls because of transferred polymer layers on the BMG surfaces. The BMG against the polymer balls also exhibited the highest AE signals among the three types of counter materials used, indicating that abrasive wear dominated in the polymer-BMG sliding pairs. These results demonstrated the potential application of the BMG as a new tribomaterial that could be an alternative to the traditional crystalline metals for various counter materials.