Evaluating system architectures for driving range estimation and charge planning for electric vehicles

Due to sparse charging infrastructure and short driving ranges, drivers of battery electric vehicles (BEVs) can experience range anxiety, which is the fear of stranding with an empty battery. To help eliminate range anxiety and make BEVs more attractive for customers, accurate range estimation methods need to be developed. In recent years, many publications have suggested machine learning algorithms as a fitting method to achieve accurate range estimations. However, these algorithms use a large amount of data and have high computational requirements. A traditional placement of the software within a vehicle's electronic control unit could lead to high latencies and thus detrimental to user experience. But since modern vehicles are connected to a backend, where software modules can be implemented, high latencies can be prevented with intelligent distribution of the algorithm parts. On the other hand, communication between vehicle and backend can be slow or expensive. In this article, an intelligent deployment of a range estimation software based on ML is analyzed. We model hardware and software to enable performance evaluation in early stages of the development process. Based on simulations, different system architectures and module placements are then analyzed in terms of latency, network usage, energy usage, and cost. We show that a distributed system with cloud‐based module placement reduces the end‐to‐end latency significantly, when compared with a traditional vehicle‐based placement. Furthermore, we show that network usage is significantly reduced. This intelligent system enables the application of complex, but accurate range estimation with low latencies, resulting in an improved user experience, which enhances the practicality and acceptance of BEVs.     

Hyperspectral face recognition with histogram of oriented gradient features and collaborative representation-based classifier

Multimedia Tools and Applications - Hyperspectral face recognition plays an important role in remote sensing. However, it faces many challenges such as difficulty in data acquisition, low signal to...     

Polymers for dye transfer inhibition in laundry applications

The deposition of dyes onto lightly colored garments, or onto lighter sections of multicolored garments, during laundry results in fabric discoloration. In particular, there is a requirement to restrict indigo dye transfer between garments. Polymers may be added to detergent formulations as dye transfer inhibitors to prevent dye transfer by blocking the deposition of fugitive dyes in aqueous solution. This article reports the generation of a range of dye transfer inhibitors produced by condensation reactions that are effective in preventing the transfer of unbound indigo dye to a variety of fiber types. Key design rules relating to polymer hydrophilicity and pendant polymer functionality were established for the creation of effective dye transfer inhibitors. Remarkably, polymers at concentrations as low as 0.1 mg/ml were found to be effective in inhibiting indigo deposition on a variety of fiber types, offering great promise for their inclusion within laundry detergent formulations as dye transfer inhibitors.     

Synthesis of Carboxamide-Containing Tranylcypromine Analogues as LSD1 (KDM1A) Inhibitors Targeting Acute Myeloid Leukemia

Lysine-specific demethylase 1 (LSD1/KDM1A) oxidatively removes methyl groups from histone proteins, and its aberrant activity has been correlated with cancers including acute myeloid leukemia (AML). We report a novel series of tranylcypromine analogues with a carboxamide at the 4-position of the aryl ring. These compounds, such as 5 a and 5 b with benzyl and phenethylamide substituents, respectively, had potent sub-micromolar IC₅₀ values for the inhibition of LSD1 as well as cell proliferation in a panel of AML cell lines. The dose-dependent increase in cellular expression levels of H3K4me2, CD86, CD11b and CD14 supported a mechanism involving LSD1 inhibition. The tert-butyl and ethyl carbamate derivatives of these tranylcypromines, although inactive in LSD1 inhibition, were of similar potency in cell-based assays with a more rapid onset of action. This suggests that carbamates can act as metabolically labile tranylcypromine prodrugs with superior pharmacokinetics.     

Exploring the Potential of Drug Response Assays for Precision Medicine in Ovarian Cancer

One of the major challenges in the treatment of cancer are differential responses of patients to existing standard of care anti-cancer drugs. These differential responses may, in part, be due to a diverse range of genomic, epigenomic, proteomic, and metabolic alterations among individuals suffering from the same type of cancer. Precision medicine is an emerging approach in cancer therapeutics that takes into account specific molecular alterations, environmental factors as well as lifestyle of individual patients. This approach allows clinicians and researchers to select or predict treatments that would most likely benefit the patient based on their individual tumor characteristics. One class of precision medicine tools are predictive, in vitro drug-response assays designed to test the sensitivity of patient tumor cells to existing or novel therapies. These assays have the potential to rapidly identify the most effective treatments for cancer patients and thus hold great promise in the field of precision medicine. In this review, we have highlighted several drug-response assays developed in ovarian cancer and discussed the current challenges and future prospects of these assays in the clinical management of this disease.     

Recent Highlights of Research on miRNAs as Early Potential Biomarkers for Cardiovascular Complications of Type 2 Diabetes Mellitus

Type 2 diabetes mellitus (T2DM) and its complications pose a serious threat to the life and health of patients around the world. The most dangerous complications of this disease are vascular complications. Microvascular complications of T2DM include retinopathy, nephropathy, and neuropathy. In turn, macrovascular complications include coronary artery disease, peripheral artery disease, and cerebrovascular disease. The currently used diagnostic methods do not ensure detection of the disease at an early stage, and they also do not predict the risk of developing specific complications. MicroRNAs (miRNAs) are small, endogenous, noncoding molecules that are involved in key processes, such as cell proliferation, differentiation, and apoptosis. Recent research has assigned them an important role as potential biomarkers for detecting complications related to diabetes. We suggest that utilizing miRNAs can be a routine approach for early diagnosis and prognosis of diseases and may enable the development of better therapeutic approaches. In this paper, we conduct a review of the latest reports demonstrating the usefulness of miRNAs as biomarkers in the vascular complications of T2DM.     

Interplay between Thyroid Hormones and Stearoyl-CoA Desaturase 1 in the Regulation of Lipid Metabolism in the Heart

Stearoyl-CoA desaturase 1 (SCD1), an enzyme that is involved in the biosynthesis of monounsaturated fatty acids, induces the reprogramming of cardiomyocyte metabolism. Thyroid hormones (THs) activate both lipolysis and lipogenesis. Many genes that are involved in lipid metabolism, including Scd1, are regulated by THs. The present study used SCD1 knockout (SCD1^−/−) mice to test the hypothesis that THs are important factors that mediate the anti-steatotic effect of SCD1 downregulation in the heart. SCD1 deficiency decreased plasma levels of thyroid-stimulating hormone and thyroxine and the expression of genes that regulate intracellular TH levels (i.e., Slc16a2 and Dio1-3) in cardiomyocytes. Both hypothyroidism and SCD1 deficiency affected genomic and non-genomic TH pathways in the heart. SCD1 deficiency is known to protect mice from genetic- or diet-induced obesity and decrease lipid content in the heart. Interestingly, hypothyroidism increased body adiposity and triglyceride and diacylglycerol levels in the heart in SCD1^−/− mice. The accumulation of triglycerides in cardiomyocytes in SCD1^−/− hypothyroid mice was caused by the activation of lipogenesis, which likely exceeded the upregulation of lipolysis and fatty acid oxidation. Lipid accumulation was also observed in the heart in wildtype hypothyroid mice compared with wildtype control mice, but this process was related to a reduction of triglyceride lipolysis and fatty acid oxidation. We also found that simultaneous SCD1 and deiodinase inhibition increased triglyceride content in HL-1 cardiomyocytes, and this process was related to the downregulation of lipolysis. Altogether, the present results suggest that THs are an important part of the mechanism of SCD1 in cardiac lipid utilization and may be involved in the upregulation of energetic metabolism that is associated with SCD1 deficiency.     

Molecular Aspects of Pruritus Pathogenesis in Psoriasis

Psoriasis is a chronic, systemic inflammatory disease with a genetic background that involves almost 3% of the general population worldwide. Approximately, 70–90% of patients with psoriasis suffer from pruritus, an unpleasant sensation that provokes a desire to scratch. Despite the enormous progress in understanding the mechanisms that cause psoriasis, the pathogenesis of psoriasis-related pruritus still remains unclear. In order to improve patients’ quality of life, development of more effective and safer antipruritic therapies is necessary. In turn to make it possible, better understanding of complexed and multifactorial pathogenesis of this symptom is needed. In this article we have systematized the current knowledge about pruritus origin in psoriasis.     

Influence of Alkyl Chain Length on Thermal Properties,Structure, and Self-Diffusion Coefficients of Alkyltriethylammonium-Based Ionic Liquids

The application of ionic liquids (ILs) has grown enormously, from their use as simple solvents, catalysts, media in separation science, or electrolytes to that as task-specific, tunable molecular machines with appropriate properties. A thorough understanding of these properties and structure–property relationships is needed to fully exploit their potential, open new directions in IL-based research and, finally, properly implement the appropriate applications. In this work, we investigated the structure–properties relationships of a series of alkyltriethylammonium bis(trifluoromethanesulfonyl)imide [TEA-R][TFSI] ionic liquids in relation to their thermal behavior, structure organization, and self-diffusion coefficients in the bulk state using DSC, FT-IR, SAXS, and NMR diffusometry techniques. The phase transition temperatures were determined, indicating alkyl chain dependency. Fourier-transformed infrared spectroscopy studies revealed the structuration of the ionic liquids along with alkyl chain elongation. SAXS experiments clearly demonstrated the existence of polar/non-polar domains. The alkyl chain length influenced the expansion of the non-polar domains, leading to the expansion between cation heads in polar regions of the structured IL. ¹H NMR self-diffusion coefficients indicated that alkyl chain elongation generally caused the lowering of the self-diffusion coefficients. Moreover, we show that the diffusion of anions and cations of ILs is similar, even though they vary in their size.