Experimental investigation and development of new correlation for influences of temperature and concentration on dynamic viscosity of MWCNT-SiO2 (20-80)/20W50 hybrid nano-lubricant

In current research, MWCNT-SiO_2/oil hybrid nano-lubricant viscosity is experimentally examined. By dispersing 0.05%, 0.1%, 0.2%, 0.4%, 0.8% and 1% volume of MWCNTs and SiO_2 nanoparticle into the engine oil SAE 20W50, the temperature and solid volume fraction consequences were studied. At 40 to 100 ℃ temperature, the viscosities were assessed. The results indicated Newtonian behavior for the hybrid nano-lubricant. Moreover, solid volume fraction augmentation and temperature enhanced the viscosity enhancement of hybrid nano-lubricant. At highest solid volume fraction and temperature, nano-lubricant viscosity was 171% greater compared to pure 20W50. Existed models lack the ability to predict the hybrid nano-lubricant viscosity. Thus, a new correlation regarding solid volume fraction and temperature was suggested with R-squared of 0.9943.     

Mercury(II) selective membrane electrode based on 1,3-bis(2-methoxybenzene)triazene

A plasticized poly (vinyl chloride) membrane electrode based on 1,3-bis(2-methoxybenzene)triazene (MBT) for highly selective determination of mercury(II) has been developed. The electrode showed a good Nernstian response (30.2 ± 0.3 mV decade^− 1) over a wide concentration range (1.0 × 10^− 7−1.0 × 10^− 2 mol L^− 1). The limit of detection was 5.0 × 10^− 8 mol L^− 1. The electrode has a response time about 15 s and can be used for at least 1 month without observing any deviation from Nernstain response. The proposed electrode revealed an excellent selectivity toward mercury(II) ion over a wide variety of alkali, alkaline earth, transition, and heavy metal ions and could be used in the pH range 2.6–4.2. The electrode was used in the determination of Hg²⁺ in aqueous samples and as an indicator electrode in potentiometric titration of Hg(II) ions.     

LRED: A Robust and Responsive AQM Algorithm Using Packet Loss Ratio Measurement

Active queue management (AQM) is an effective means to enhance congestion control, and to achieve trade-off between link utilization and delay. The de facto standard, random early detection (RED), and many of its variants employ queue length as a congestion indicator to trigger packet dropping. Despite their simplicity, these approaches often suffer from unstable behaviors in a dynamic network. Adaptive parameter settings, though might solve the problem, remain difficult in such a complex system. Recent proposals based on analytical TCP control and AQM models suggest the use of both queue length and traffic input rate as congestion indicators, which effectively enhances stability. Their response time generally increases however, leading to frequent buffer overflow and emptiness. In this paper, we propose a novel AQM algorithm that achieves fast response time and yet good robustness. The algorithm, called Loss Ratio-based RED (LRED), measures the latest packet loss ratio, and uses it as a complement to queue length for adaptively adjusting the packet drop probability. We develop an analytical model for LRED, which demonstrates that LRED is responsive even if the number of TCP flows and their persisting times vary significantly. It also provides a general guideline for the parameter settings in LRED. The performance of LRED is further examined under various simulated network environments, and compared to existing AQM algorithms. Our simulation results show that, with comparable complexities, LRED achieves shorter response time and higher robustness. More importantly, it trades off the goodput with queue length better than existing algorithms, enabling flexible system configurations     

POLYNUCLEAR AROMATIC COMPOUNDS IN COAL AND OIL SHALE WASTEWATER: AN ENVIRONMENTAL CONCERN

ABSTRACT

A solvent refining coal liquefaction process recycle water (No. 3) from Du Pont, Washington, a true in-situ oil shale retort water (Omega-9) from Rock Springs, Wyoming, and a ten-ton unit simulated in-situ oil shale retort water (No, 16) from Laramie, Wyoming, were subjected to solvent extraction procedure and subsequent instrumental analysis including: (a) high performance liquid chromatography (HPLC) of polynuclear aromatics (PNA's) having more than four rings; (b) capillary gas chromatography (GC) of low molecular weight volatile PNA's; and (c) gas chromatography-mass spectrometry (GC-MS) for complementary identification of PNA's having functional and heterocyclic modifications.

A total of 41 PNA's were identified. Identification of 28 PNA's in the coal derived water (No. 3) was attained, whereas that of the true in-situ retort water (Omega-9) and the simulated retort water (No. 16) were 24 and 18, respectively. Thirteen PNA's were found to be common to all three wastewater samples. Thirteen PNA's were exclusively found in sample No. 3 whereas that of samples Omega-9 and No. 16 were 8 and 4, respectively. It was estimated that the concentration of PNA's in all samples ranged from traces to 30.0 ppb.     

Seismic flexural behavior of concrete connections reinforced with CFRP bars and grids

The corrosion of steel reinforcement in concrete and the resulting deterioration of structures prompted research on fiber reinforced polymers (FRP) as potential reinforcement for concrete members, for use in new construction. FRPs have more favorable advantages for new concrete buildings subjected to seismic loads particularly in corrosive environment.     

A generalized common-ground single-switch continuous input-current boost converter favourable for DC microgrids

The conventional DC‑DC converters have limited voltage gain at moderate duty cycles. In theory, the large duty cycles should be adopted to reach large boosting factors. But in reality, at extreme duty cycles, the effect of parasitic components become dominant, which leads to increased voltage drops on devices, increased total loss and reduced efficiency. This paper proposes a single-switch (requiring single gate-driver circuit) diode-inductor-capacitor (DLC) cell-based basic boost configuration that can solve the abovementioned issues. The employment of single-switch has led to only two operational modes (in continuous conduction mode [CCM]) and easy control strategy. The continuous input-current and large step-up capability make the proposed configuration favourable for renewable or hybrid energy systems in DC microgrids. The simple configuration, modularity, moderate blocking voltage on semiconductors, wide duty-cycle range, large voltage gains at low duty cycles, common-ground between source and load are some profits of suggested configuration. The basic topology can be expanded by addition of DLC cells. Based on comparative analysis, the proposed configuration has larger step-up capability per required components and lesser average normalized blocking voltage on semiconductors compared with other single-switch topologies. This leads to smaller and cheaper structure with fewer losses. The configuration and operational modes of proposed basic topology (and its extended version) have been explained. Then, the design considerations and small-signal modelling of basic topology have been investigated. Finally, the effectiveness and correct operation of proposed topology have been certified by comparative analysis and experimental results.     

Multi-market energy procurement for a large consumer using a risk-aversion procedure

This paper provides a technique to derive the bidding strategy in the day-ahead market of a large consumer that procures its electricity demand in both the day-ahead market and a subsequent adjustment market. Price uncertainty is modeled using concepts derived from information gap decision theory, which allows deriving robust decisions with respect to price volatility. Risk aversion is built implicitly within the proposed model. Correlations among prices in the day-ahead and the adjustment markets are properly modeled. The proposed technique is illustrated through a realistic case study.     

Neurotrauma investigation through spatial omics guided by mass spectrometry imaging: Target identification and clinical applications

Traumatic brain injury (TBI) represents one of the major public health concerns worldwide due to the increase in TBI incidence as a result of injuries from daily life accidents such as sports and motor vehicle transportation as well as military-related practices. This type of central nervous system trauma is known to predispose patients to several neurological disorders such as Parkinson's disease, Alzheimer's disease, chronic trauamatic encephalopathy, and age-related Dementia. Recently, several proteomic and lipidomic platforms have been applied on different TBI studies to investigate TBI-related mechanisms that have broadened our understanding of its distinct neuropathological complications. In this study, we provide an updated comprehensive overview of the current knowledge and novel perspectives of the spatially resolved microproteomics and microlipidomics approaches guided by mass spectrometry imaging used in TBI studies and its applications in the neurotrauma field. In this regard, we will discuss the use of the spatially resolved microproteomics and assess the different microproteomic sampling methods such as laser capture microdissection, parafilm assisted microdissection, and liquid microjunction extraction as accurate and precise techniques in the field of neuroproteomics. Additionally, we will highlight lipid profiling applications and their prospective potentials in characterizing molecular processes involved in the field of TBI. Specifically, we will discuss the phospholipid metabolism acting as a precursor for proinflammatory molecules such as eicosanoids. Finally, we will survey the current state of spatial neuroproteomics and microproteomics applications and present the various studies highlighting their findings in these fields.