The Effects of Insulin-Like Growth Factor I and BTP-2 on Acute Lung Injury

Acute lung injury (ALI) afflicts approximately 200,000 patients annually and has a 40% mortality rate. The COVID-19 pandemic has massively increased the rate of ALI incidence. The pathogenesis of ALI involves tissue damage from invading microbes and, in severe cases, the overexpression of inflammatory cytokines such as tumor necrosis factor-α (TNF-α) and interleukin-1β (IL-1β). This study aimed to develop a therapy to normalize the excess production of inflammatory cytokines and promote tissue repair in the lipopolysaccharide (LPS)-induced ALI. Based on our previous studies, we tested the insulin-like growth factor I (IGF-I) and BTP-2 therapies. IGF-I was selected, because we and others have shown that elevated inflammatory cytokines suppress the expression of growth hormone receptors in the liver, leading to a decrease in the circulating IGF-I. IGF-I is a growth factor that increases vascular protection, enhances tissue repair, and decreases pro-inflammatory cytokines. It is also required to produce anti-inflammatory 1,25-dihydroxyvitamin D. BTP-2, an inhibitor of cytosolic calcium, was used to suppress the LPS-induced increase in cytosolic calcium, which otherwise leads to an increase in proinflammatory cytokines. We showed that LPS increased the expression of the primary inflammatory mediators such as toll like receptor-4 (TLR-4), IL-1β, interleukin-17 (IL-17), TNF-α, and interferon-γ (IFN-γ), which were normalized by the IGF-I + BTP-2 dual therapy in the lungs, along with improved vascular gene expression markers. The histologic lung injury score was markedly elevated by LPS and reduced to normal by the combination therapy. In conclusion, the LPS-induced increases in inflammatory cytokines, vascular injuries, and lung injuries were all improved by IGF-I + BTP-2 combination therapy.     

An SDP Primal-Dual Algorithm for Approximating the Lovász-Theta Function

The Lovász ?-function (Lovász in IEEE Trans. Inf. Theory, 25:1–7, 1979) of a graph G=(V,E) can be defined as the maximum of the sum of the entries of a positive semidefinite matrix X, whose trace Tr(X) equals 1, and X _ij =0 whenever {i,j}∈E. This function appears as a subroutine for many algorithms for graph problems such as maximum independent set and maximum clique. We apply Arora and Kale’s primal-dual method for SDP to design an algorithm to approximate the ?-function within an additive error of δ>0, which runs in time $O(\frac{\vartheta ^{2} n^{2}}{\delta^{2}} \log n \cdot M_{e})$ , where ?=?(G) and M _e =O(n ³) is the time for a matrix exponentiation operation. It follows that for perfect graphs G, our primal-dual method computes ?(G) exactly in time O(? ² n ⁵logn). Moreover, our techniques generalize to the weighted Lovász ?-function, and both the maximum independent set weight and the maximum clique weight for vertex weighted perfect graphs can be approximated within a factor of (1+?) in time O(? ^?2 n ⁵logn).     

A Comparison of the Levels of Lutein and Zeaxanthin in Corn Germ Oil,Corn Fiber Oil and Corn Kernel Oil

All commercial corn oil is obtained by pressing corn germ and/or extracting the germ with hexane. In the current study, six types of corn oil were prepared by extracting corn germ, corn fiber and ground corn, each with hexane or with ethanol. The levels of lutein, zeaxanthin and other carotenoids were quantitatively analyzed in the six corn oils. The levels of lutein + zeaxanthin in the oil ranged from 2.3 μg/g for hexane-extracted corn germ oil to 220.9 μg/g for ethanol-extracted ground corn oil. These results indicate that a diet that includes 30 g (~2 tbsp) per day of the unrefined corn oil obtained by extracting ground corn with ethanol would provide ~6 mg of lutein + zeaxanthin, the daily dosage that is currently considered to be necessary to slow the progression of age-related macular degeneration. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture.     

Toward seed-insensitive solutions to local community detection

Local community detection aims at finding a community structure starting from a seed which is a given vertex in a network without global information, such as online social networks that are too large and dynamic to ever be known fully. Nonetheless, the existing approaches to local community detection are usually sensitive to seeds, i.e., some seeds may lead to missing of some true communities. In this paper, we present a seed-insensitive method called GMAC and its variation iGMAC for local community detection. They estimate the similarity among vertices by investigating vertices’ neighborhoods, and reveal a local community by maximizing its internal similarity and minimizing its external similarity simultaneously. Extensive experimental results on both synthetic and real-world data sets verify the effectiveness of our algorithms.     

Summarizing high-level scene behavior

We present several novel techniques to summarize the high-level behavior in surveillance video. Our proposed methods can employ either optical flow or trajectories as input, and incorporate spatial and temporal information together, which improve upon existing approaches for summarization. To begin, we extract common pathway regions by performing graph-based clustering on similarity matrices describing the relationships between location/orientation states. We then employ the activities along the pathway regions to extract the aggregate behavioral patterns throughout scenes. We show how our summarization methods can be applied to detect anomalies, retrieve video clips of interest, and generate adaptive-speed summary videos. We examine our approaches on multiple complex urban scenes and present experimental results.     

Dynamic distributed lanes: motion planning for multiple autonomous vehicles

Unorganized traffic is a generalized form of travel wherein vehicles do not adhere to any predefined lanes and can travel in-between lanes. Such travel is visible in a number of countries e.g. India, wherein it enables a higher traffic bandwidth, more overtaking and more efficient travel. These advantages are visible when the vehicles vary considerably in size and speed, in the absence of which the predefined lanes are near-optimal. Motion planning for multiple autonomous vehicles in unorganized traffic deals with deciding on the manner in which every vehicle travels, ensuring no collision either with each other or with static obstacles. In this paper the notion of predefined lanes is generalized to model unorganized travel for the purpose of planning vehicles travel. A uniform cost search is used for finding the optimal motion strategy of a vehicle, amidst the known travel plans of the other vehicles. The aim is to maximize the separation between the vehicles and static obstacles. The search is responsible for defining an optimal lane distribution among vehicles in the planning scenario. Clothoid curves are used for maintaining a lane or changing lanes. Experiments are performed by simulation over a set of challenging scenarios with a complex grid of obstacles. Additionally behaviours of overtaking, waiting for a vehicle to cross and following another vehicle are exhibited.     

Generating hydrogen-rich fuel-cell feeds from dimethyl ether (DME) using physical mixtures of a commercial Cu/Zn/Al2O3 catalyst and several solid–acid catalysts

Homogeneous physical mixtures containing a commercial Cu/ZnO/Al₂O₃ catalyst and a solid–acid catalyst were used to examine the acidity effects on dimethyl ether hydrolysis and their subsequent effects on dimethyl ether steam reforming (DME-SR). The acid catalysts used were zeolites Y [Si/Al = 2.5 and 15: denoted Y(Si/Al)], ZSM-5 [Si/Al = 15, 25, 40, and 140: denoted Z(Si/Al)] and other conventional catalyst supports (ZrO₂, and γ-Al₂O₃). The homogeneous physical mixtures contained equal amounts, by volume, of the solid–acid catalyst and the commercial Cu/ZnO/Al₂O₃ catalyst (BASF K3-110, denoted as K3). The steam reforming of dimethyl ether was carried out in an isothermal packed-bed reactor at ambient pressure.

The most promising physical mixtures for the low-temperature production of hydrogen from DME contained ZSM-5 as the solid–acid catalyst, with hydrogen yields exceeding 90% (T = 275 °C, S/C = 1.5, τ = 1.0 s and P = 0.78 atm) and hydrogen selectivities exceeding 94%, comparable to those observed for methanol steam reforming (MeOH-SR) over BASF K3-110, with values equaling 95% and 99%, respectively (T = 225 °C, S/C = 1.0, τ = 1.0 s and P = 0.78 atm). Large production rates of hydrogen were directly related to the type of acid catalyst used. The hydrogen production activity trend as a function of physical mixture was

     

Extension of Master Sintering Curve Theory to Organic Decomposition

The ability to predict and control organic decomposition of a material under arbitrary thermal treatments is one of the main objectives of thermogravimetric studies. The development of this ability provides significant potential to ensure reliability and reproducibility for a given processing method and can be used in planning optimized thermal treatment strategies. Based on this report, the master sintering curve theory has been successfully extended to similar kinetically controlled phenomena. The theory has been applied to organic decomposition reaction kinetics to develop a master organic decomposition curve. The fundamental kinetics are assumed to be governed by an Arrhenius-type reaction rate, making master sintering and decomposition curves analogous to one another. The formulation and construction of a master decomposition curve are given in this paper. Simultaneous thermogravimetric and differential thermal analysis of a low-temperature co-fire glass/ceramic dielectric tape (Dupont 951 Green Tape^TM) is analyzed and used to demonstrate this new concept. The results reveal two independent organic decomposition reactions, the first occurring at ≈245°C and the second at ≈365°C. The analysis is used to produce a master decomposition curve and to calculate the activation energy for these reactions, at 86±6 and 142±4 kJ/mol, respectively. In addition, the weight loss of product and the rate of decomposition can be predicted under varying thermal paths (time–temperature trajectories) following a minimal set of preliminary experiments.     

Substrate-mediated interactions and intermolecular forces between molecules adsorbed on surfaces

Adsorbate interactions and reactions on metal surfaces have been investigated using scanning tunneling microscopy. The manners in which adsorbates perturb the surface electronic structure in their vicinity are discussed. The effects these perturbations have on other molecules are shown to be important in overlayer growth. Interactions of molecules with surface steps are addressed, and each molecule's electron affinity is shown to dictate its adsorption sites at step edges. Standing waves emanating from steps are demonstrated to effect transient molecular adsorption up to 40 A away from the step edge. Halobenzene derivatives are used to demonstrate how the surface is important in aligning reactive intermediates.     

Analysis of impersonation attacks on systems using RF fingerprinting and low-end receivers

Recently, physical layer security commonly known as Radio Frequency (RF) fingerprinting has been proposed to provide an additional layer of security for wireless devices. A unique RF fingerprint can be used to establish the identity of a specific wireless device in order to prevent masquerading/impersonation attacks. In the literature, the performance of RF fingerprinting techniques is typically assessed using high-end (expensive) receiver hardware. However, in most practical situations receivers will not be high-end and will suffer from device specific impairments which affect the RF fingerprinting process. This paper evaluates the accuracy of RF fingerprinting employing low-end receivers. The vulnerability to an impersonation attack is assessed for a modulation-based RF fingerprinting system employing low-end commodity hardware (by legitimate and malicious users alike). Our results suggest that receiver impairment effectively decreases the success rate of impersonation attack on RF fingerprinting. In addition, the success rate of impersonation attack is receiver dependent.