Equivalent Circuit Modelling of Li-S Batteries

The presented article describes a Multi-Scale Multi-Domain model of a Li-S battery using an equivalent circuit model consisting of R-C pairs. The parameters of the equivalent circuit model were obtained by fitting experimentally measured results from electrochemical impedance spectroscopy at various states of charge. Simulation were carried out for discharging as well as for charging of the battery. The presented model is able to capture characteristic behaviour of Li-S batteries.

Cell environment shapes TDP-43 function: implications in neuronal and muscle disease

ABSTRACTTDP-43 aggregation and redistribution have been recognised as a hallmark of amyotrophic lateral sclerosis, frontotemporal dementia and other neurological disorders. While TDP-43 has been studied extensively in neuronal tissues, TDP-43 inclusions have also been described in the muscle of inclusion body myositis patients, highlighting the need to understand the role of TDP-43 beyond the central nervous system. Using RNA-seq we performed the first direct comparison of TDP-43-mediated transcription and alternative splicing in muscle (C2C12) and neuronal (NSC34) mouse cells. Our results clearly show that TDP-43 displays a tissue-characteristic behaviour targeting unique transcripts in each cell type. This is not due to variable transcript abundance but rather due to cell-specific expression of RNA-binding proteins, which influences TDP-43 performance. Among splicing events commonly dysregulated in both cell lines, we identified some that are TDP-43-dependent also in human cells and show that inclusion levels of these alternative exons appear to be differentially altered in affected tissues of FTLD and IBM patients. We therefore propose that TDP-43 dysfunction, reflected in aberrant splicing, contributes to disease development but it does so in a tissue- and disease-specific manner.

The anatomy of non-Muslim consumers’ halal fashion buying behaviour: a quantitative approach

Purpose The purpose of this study is two-fold: classifying non-Muslim halal fashion buyers by applying quantitative techniques and identifying the persuading determinants of the non-Muslim women’ halal fashion buying behaviour (HFBB). Design/methodology/approach By adapting items from prior studies, a structured questionnaire was developed and distributed face-to-face to various Muslim fashion stores in Malaysia. After a one-month effort, 221 responses were obtained from non-Muslim consumers by using convenience sampling. Next, a clustering analysis was used to classify them from a contrasting perspective. Finally, regression and Andrew F. Hayes’s process procedures were applied to examine the three independent variables’ effect and the moderating variables. Findings The results revealed the characteristic behaviour of the non-Muslim women explicitly, which is related to their halal fashion purchasing decision. Based on the ANOVA results, there were different motives for buying halal fashion by non-Muslim women. Additionally, it was found that the most crucial determinants for non-Muslim’s HFBB are “cultural adaptation”, albeit, there is no substantial proof of a significant moderating effect of age and income on the consumers. Research limitations/implications These discoveries are advantageous for halal fashion retailers and provide an appealing domain for further investigations in the context of the global halal study. Practical implications This study provided an idea for an untapped segment on the halal fashion sellers’ segmentation and positioning strategy. The study’s results suggested specific managerial and practical recommendation that the sellers can use to attract non-Muslim consumers. Originality/value This study was amongst the uncommon investigations within the halal fashion context that will enlighten the managers’ selling strategy on the most neglected market segment. The results of this study provided an empirical understanding of how to sell halal fashion to non-Muslim consumers.

The relation between short- and long-term deformation in actively deforming plate boundary zones

Satellite-based measuring systems are making it possible to monitor deformation of the Earth's surface at a high spatial resolution over periods of several decades and a significant fraction of the seismic cycle. It is widely assumed that this short-term deformation directly reflects the long-term pattern of crustal deformation, although modified in detail by local elastic effects related to locking on individual faults. This way, short-term deformation is often jointly inverted with long-term estimates of fault slip rates, or even stress, over periods of 10 s to 100 s kyrs. Here, I examine the relation between these two timescales of deformation for subduction, continental shortening and rifting tectonic settings, with examples from the active New Zealand and Central Andean plate boundary zone. I show that the relation is inherently non-unique, and simple models of locking on a deep-seated megathrust or decollement, or mantle flow, provide excellent fits to the short-term observations without requiring any information about the geometry and rate of surface faulting. The short-term deformation, in these settings at least, cannot be used to determine the behaviour of individual faults, but instead places constraints on the forces that drive deformation. Thus, there is a fundamental difference between the stress loading and stress relief parts of the earthquake cycle, with failure determined by dynamical rather than kinematic constraints; the same stress loading can give rise to widely different modes of long-term deformation, depending on the strength and rheology of the deforming zone, and the role of gravitational stresses. The process of slip on networks of active faults may have an intermediate timescale of kyrs to 10 s kyrs, where individual faults fail piecemeal without any characteristic behaviour. Physics-based dynamical models of short-term deformation may be the best way to make full use of the increasing quality of this type of data in the future. This article is part of a discussion meeting issue ‘Understanding earthquakes using the geological record’.

Long-Range Dependence in Financial Markets: A Moving Average Cluster Entropy Approach

A perspective is taken on the intangible complexity of economic and social systems by investigating the dynamical processes producing, storing and transmitting information in financial time series. An extensive analysis based on the moving average cluster entropy approach has evidenced market and horizon dependence in highest-frequency data of real world financial assets. The behavior is scrutinized by applying the moving average cluster entropy approach to long-range correlated stochastic processes as the Autoregressive Fractionally Integrated Moving Average (ARFIMA) and Fractional Brownian motion (FBM). An extensive set of series is generated with a broad range of values of the Hurst exponent H and of the autoregressive, differencing and moving average parameters p , d , q . A systematic relation between moving average cluster entropy and long-range correlation parameters H, d is observed. This study shows that the characteristic behaviour exhibited by the horizon dependence of the cluster entropy is related to long-range positive correlation in financial markets. Specifically, long range positively correlated ARFIMA processes with differencing parameter d ≃ 0.05 , d ≃ 0.15 and d ≃ 0.25 are consistent with moving average cluster entropy results obtained in time series of DJIA, S&P500 and NASDAQ. The findings clearly point to a variability of price returns, consistently with a price dynamics involving multiple temporal scales and, thus, short- and long-run volatility components. An important aspect of the proposed approach is the ability to capture detailed horizon dependence over relatively short horizons (one to twelve months) and thus its relevance to define risk analysis indices.

Experimental Research on Flexural Behaviour of Filler Slab with Activated Carbon

Concrete is most frequently used composite material. Concrete is the combination of M-Sand, coarse aggregate and binding medium of concrete paste. Next to the water demand which is increased in concrete day by day, in this project we incorporate Activated carbon in Filler slabs. Filler slab is the sustainable concept which reduces unwanted concrete in the tension zone. The main perspective of this project is to study the characteristic behaviour of concrete with activated carbon. Also, to maximize the rate of Compressive strength of the concrete and to Filter air pollutants and to investigate the flexural behaviour of filler slab with activated carbon. Filler slab with Activated carbon in cement greatly increases the sustainability. Compression test and Flexural test were carried out by three different proportion of Activated carbon in cement from these mixes results are obtained. Further morphological arrangements are to be carried out

Using Sentinel-1 and -2 satellite time series to monitor crop phenology at the parcel level

<p>Phenology can contribute to many scientific disciplines from climate change, biodiversity, agriculture and forestry to human health. The knowledge of timing of phenological events and their variability can provide valuable data for agriculture. Accurate and timely information on the dates of specific stages of crop development is needed for various applications including crop yield forecasting. Despite the proven capabilities of Sentinel satellites for crop mapping and estimating phenology, they have not yet been applied effectively for tracking crop development across large areas. </p><p>A methodology is proposed to systematically identify phenology phases from time series generated by the Copernicus Sentinel-1 (S1) and Sentinel-2 (S2) sensors. This is done by linking specific agricultural-parcel temporal S1 and S2 signatures to phenology observations representative for 5-km buffers around the 6573 Deutscher Wetterdienst (DWD) stations spatially distributed across Germany. First, a S1-based 10-m crop type classification was made around each DWD station trained with LUCAS (Land Cover and Land Use Area frame Survey) 2018 data which allowed identifying parcels as well as crop types. Second, the average crop specific S1 (VV and VH) and S2 (NDVI) temporal signal is extracted for each DWD station and the correlation between the DWD BBCH event and characteristic behaviour in the satellite signals such as dips or peaks is systematically assessed for each crop. </p><p>This approach identified the unique and crop-specific temporal signatures of S1 and S2 associated with specific phenology events such as emergence, flowering or ripening. We further discuss the potential and limitations of S1 and S2 to extract this type of information. These temporal S1 and S2 signatures can contribute to a digital reference library that could be used to monitor crop phenology operationally for parcels across the globe. Moreover, it unveils the potential of S1 and S2 to study detailed spatial and temporal gradient of crop phenology in the light of climate change.</p>

DAMAGES OF THE KEEL BONE IN LAYING HENS – OVERVIEW OF THE ETIOLOGICAL ASPECTS

The damages of the locomotor system and the skeletal system, in particular, are one of the major problems in the industrial poultry farming. The topic for the pathological changes in the keel bone in oviparous birds has become especially popular among scientists and researchers in recent years. The high incidence of keel bone damage (KBD) of laying hens in industrial complexes is one of the biggest welfare problems facing the industry. They lead to disturbance of the animal welfare, causing pain, limiting the ability to move and to perform the characteristic behaviour of the species. This in turn causes a decrease in productivity and unacceptably large losses not only for the individual producer but also for the whole sector. The problem with the KBD is widespread in Switzerland, Great Britain, the Nederland, Belgium, Germany, and Canada. Different genetic lines of laying hens are affected, as well as all types of breeding systems. In general, the etiological factors are reduced to three main groups – genetic predisposition, unbalanced diet and imperfections in housing systems. The causes and influencing factors of KBD remain unknown to the research community - a circumstance that seriously complicates the development of effective strategies to reduce their occurrence and severity.