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Abstract Powerline communication (PLC) channels are known to exhibit multipath propagation behaviour. The authors present a model-based framework to address the challenge of clustering multipath propagation components (MPCs) in PLC channels for indoor low-voltage (LV) environments. The framework employs a range of finite-mixture models (FMMs), including the gamma mixture model, the inverse gamma mixture model, the Gaussian mixture model, the inverse Gaussian mixture model, the Nakagami mixture model, the inverse Nakagami mixture model (INMM) and the Rayleigh mixture model, to identify clusters of MPCs. A measurement campaign of an unknown indoor LV PLC channel is conducted to obtain a channel response. From the channel response, the delay and magnitude parameters of the MPCs are extracted using the space-alternating generalised expectation maximisation algorithm adopted only for these parameters. A maximum likelihood approach and the expectation–maximisation algorithm are employed to fit the FMMs to the MPC delay-magnitude dataset to cluster MPCs in the delay domain. The results of the model-fitting process are then evaluated using the corrected Akaike information criterion (AICc), which enables a fair comparison of the candidate models over the feasible and finite range of clusters. A novel algorithm is introduced for estimating the feasible and finite range of clusters using the extracted delay and magnitude MPC parameters. The AICc’s ranking results show that the INMM model provides the best fit. Davies–Bouldin (DB) and Calinski–Harabasz (CH) indexes are used to compare the model-based clustering approach to the conventional distance-based clustering methods. Validation results show that CH and DB indexes closely agree in the optimal number of MPC clusters for model-based clustering, which corresponds to the most within-cluster compactness of MPCs and to the most between-cluster separation in the delay domain.

Exact state-of-charge estimation is necessary for every application related to energy storage systems to protect the battery from deep discharging and overcharging. This leads to an improvement in discharge efficiency and extends the battery lifecycle. Batteries are a main source of energy and are usually monitored by management systems to achieve optimal use and protection. Coming up with effective methods for battery management systems that can adequately estimate the state-of-charge of batteries has become a great challenge that has been studied in the literature for some time. Hence, this paper analyses the different energy storage technologies, highlighting their merits and demerits. The various estimation methods for state-of-charge are discussed, and their merits and demerits are compared, while possible applications are pointed out. Furthermore, factors affecting the battery state-of-charge and approaches to managing the same are discussed and analysed. The different modelling tools used to carry out simulations for energy storage experiments are analysed and discussed. Additionally, a quantitative comparison of different technical and economic modelling simulators for energy storage applications is presented. Previous research works have been found to lack accuracy under varying conditions and ageing effects; as such, integrating hybrid approaches for enhanced accuracy in state-of-charge estimations is advised. With regards to energy storage technologies, exploring alternative materials for improved energy density, safety and sustainability exists as a huge research gap. The development of effective battery management systems for optimisation and control is yet to be fully exploited. When it comes to state-of-the-art simulators, integrating multiscale models for comprehensive understanding is of utmost importance. Enhancing adaptability across diverse battery chemistries and rigorous validation with real-world data is essential. To sum up the paper, future research directions and a conclusion are given.

Abstract Previous studies show increased sensitivity of older mice (28–29 months) compared with young adult mice (3 months, possessing a mature immune system) to radiation-induced GI lethality. Age-dependent lethality was associated with higher levels of apoptotic stem cells in small intestinal crypts that correlated with sphingomyelinase activity, a source of pro-apoptotic ceramide. The objective of this study is to determine whether the cycling crypt base columnar cells (CBCs) in aging animals are specifically more sensitive to radiation effects than the CBCs in young adult mice, and to identify factors that contribute to increased radiosensitivity. Mortality induced by subtotal body radiation was assessed at different doses (13 Gy, 14 Gy, and 15 Gy) in young adult mice versus older mice. Each dose was evaluated for the occurrence of lethal GI syndrome. A higher death rate due to radiation-induced GI syndrome was observed in older mice as compared with young adult mice: 30 vs. 0% at 13 Gy, 90 vs. 40% at 14 Gy, and 100 vs. 60% at 15 Gy. Radiation-induced damage to crypts was determined by measuring crypt regeneration (H&E staining, Ki67 expression), CBC biomarkers (lgr5 and ascl2), premature senescence (SA-β-gal activity), and apoptosis of CBCs. At all three doses, crypt microcolony survival assays showed that the older mice had fewer regenerating crypts at 3.5 days post-radiation treatment. Furthermore, in the older animals, baseline CBCs numbers per circumference were significantly decreased, correlating with an elevated apoptotic index. Analysis of tissue damage showed an increased number of senescent CBCs per crypt circumference in older mice relative to younger mice, where the latter was not significantly affected by radiation treatment. It is concluded that enhanced sensitivity to radiation-induced GI syndrome and higher mortality in older mice can be attributed to a decreased capacity to regenerate crypts, presumably due to increased apoptosis and senescence of CBCs.

Users ought to decide how to operate and manage power systems in order to achieve various goals. As a result, many strategies have been developed to aid in this regard. Optimal power flow management is one such strategy that assists users in properly operating and managing the supply and demand of power in an optimal way under specified constraints. However, in-depth research on optimal power flow management is yet to be explored when it comes to the supply and demand of power for the bulk of standalone renewable energy systems such as solar photovoltaics, especially when it comes to specific applications such as powering military soldier-level portable electronic devices. This paper presents an optimal power flow management modelling and optimisation approach for solar-powered soldier-level portable electronic devices. The OPTI toolbox in MATLAB is used to solve the formulated nonlinear optimal power flow management problem using SCIP as the solver. A globally optimal solution was arrived at in a case study in which the objective function was to minimise the difference between the power supplied to the portable electronic device electronics and the respective portable electronic device power demands. This ensured that the demand for solar-powered soldier-level portable electronic devices is met at all times in spite of the prohibitive case scenarios’ circumstances under the given constraints. This resolute approach underscores the importance placed on satisfying the demand needs of the specific devices while navigating and addressing the limitations posed by the existing conditions or constraints. Soldiers and the solar photovoltaic user fraternity at large will benefit from this work as they will be guided on how to optimally manage their power systems’ supply and demand scenarios. The model developed herein is applicable to any demand profile and any number of portable electronic device and is adaptable to any geographical location receiving any amount of solar radiation.

Body condition scoring is an objective scoring method used to evaluate the health of a cow by determining the amount of subcutaneous fat in a cow. Automated body condition scoring is becoming vital to large commercial dairy farms as it helps farmers score their cows more often and more consistently compared to manual scoring. A common approach to automated body condition scoring is to utilise a CNN-based model trained with data from a depth camera. The approaches presented in this paper make use of three depth cameras placed at different positions near the rear of a cow to train three independent CNNs. Ensemble modelling is used to combine the estimations of the three individual CNN models. The paper aims to test the performance impact of using ensemble modelling with the data from three separate depth cameras. The paper also looks at which of these three cameras and combinations thereof provide a good balance between computational cost and performance. The results of this study show that utilising the data from three depth cameras to train three separate models merged through ensemble modelling yields significantly improved automated body condition scoring accuracy compared to a single-depth camera and CNN model approach. This paper also explored the real-world performance of these models on embedded platforms by comparing the computational cost to the performance of the various models.

Road scene understanding, as a field of research, has attracted increasing attention in recent years. The development of road scene understanding capabilities that are applicable to real-world road scenarios has seen numerous complications. This has largely been due to the cost and complexity of achieving human-level scene understanding, at which successful segmentation of road scene elements can be achieved with a mean intersection over union score close to 1.0. There is a need for more of a unified approach to road scene segmentation for use in self-driving systems. Previous works have demonstrated how deep learning methods can be combined to improve the segmentation and perception performance of road scene understanding systems. This paper proposes a novel segmentation system that uses fully connected networks, attention mechanisms, and multiple-input data stream fusion to improve segmentation performance. Results show comparable performance compared to previous works, with a mean intersection over union of 87.4% on the Cityscapes dataset.

The performance of most face recognition systems (FRSs) in unconstrained environments is widely noted to be sub-optimal. One reason for this poor performance may be the lack of highly effective image pre-processing approaches, which are typically required before the feature extraction and classification stages. Furthermore, it is noted that only minimal face recognition issues are typically considered in most FRSs, thus limiting the wide applicability of most FRSs in real-life scenarios. Therefore, it is envisaged that installing more effective pre-processing techniques, in addition to selecting the right features for classification, will significantly improve the performance of FRSs. Hence, in this paper, we propose an FRS, which comprises an effective image enhancement technique for face image preprocessing, alongside a new set of hybrid features. Our image enhancement technique adopts the use of a metaheuristic optimization algorithm for effective face image enhancement, irrespective of the conditions in the unconstrained environment. This results in adding more features to the face image so that there is an increase in recognition performance as compared with the original image. The new hybrid feature is introduced in our FRS to improve the classification performance of the state-of-the-art convolutional neural network architectures. Experiments on standard face databases have been carried out to confirm the improvement in the performance of the face recognition system that considers all the constraints in the face database.

In the Greek New Testament, relative sentences that are introduced by relative pronouns alone, apart from the adverbial uses, are the most frequent subordinate sentence type. The research reported on in this paper aimed to investigate and describe a number of syntactic features of relative constructions in the Greek New Testament, taking account, among others, of some typological parameters that have been developed in the general linguistics literature for these constructions.The results indicate that relative constructions in the Greek New Testament have a variety of features, all of which have counterparts in some modern (or other ancient) languages, despite the differences. The relative sentence in the Greek New Testament is mostly postnominal, and the relative pronoun-type is used in those cases for encoding the role of the coreferential element in the relative sentence. Phrases expressing a variety of syntactic functions in a sentence (e.g. subject, direct object, etc.) are accessible to relativisation, that is, they can be represented by relative pronouns. Nominal elements serve mostly as antecedents of relative sentences, although sentences appear in that function as well.A variety of syntactic types of relative sentences can be distinguished, including the prenominal participial, postnominal finite/participial, circumnominal, free relative, adverbial, prejoined, postjoined, sentential and conjoined types. These can be linked in a systematic way to the four functions of relative sentences in the New Testament, i.e. identifying, appositive, adverbial and continuative.Relative sentences also play a role in communicative strategies. Prejoined relative sentences, for example, are most suitable for exposition and theme-building, especially in the correlative diptych construction.

There is a large amount of research currently being done on autonomous micro-aerial vehicles (MAV), such as quadrotor helicopters or quadcopters. The ability to create a working autonomous MAV depends mainly on integrating a simultaneous localization and mapping (SLAM) solution with the rest of the system. This paper provides an introduction for creating an autonomous MAV for enclosed environments, aimed at students and professionals alike. The standard autonomous system and MAV automation are discussed, while we focus on the core concepts of SLAM systems and trajectory planning algorithms. The advantages and disadvantages of using remote processing are evaluated, and recommendations are made regarding the viability of on-board processing. Recommendations are made regarding best practices to serve as a guideline for aspirant MAV designers.

Cila HermanDepartment of Mechanical Engineering, Johns Hopkins University, Baltimore, MD, USAAbstract: Every year around 2.5–3 million skin lesions are biopsied in the US, and a fraction of these – between 50,000 and 100,000 – are diagnosed as melanoma. Diagnostic instruments that allow early detection of melanoma are the key to improving survival rates and reducing the number of unnecessary biopsies, the associated morbidity, and the costs of care. Advances in technology over the past 2 decades have enabled the development of new, sophisticated test methods, which are currently undergoing laboratory and small-scale clinical testing. This review highlights and compares some of the emerging technologies that hold the promise of melanoma diagnosis at an early stage of the disease. The needs for detection at different levels (patient, primary care, specialized care) are discussed, and three broad classes of instruments are identified that are capable of satisfying these needs. Technical and clinical requirements on the diagnostic instruments are introduced to aid the comparison and evaluation of new technologies. White- and polarized-light imaging, spatial and spectroscopic multispectral methods, quantitative thermographic imaging, confocal microscopy, Optical Coherence Tomography (OCT), and Terahertz (THZ) imaging methods are highlighted in light of the criteria identified in the review. Based on the properties, possibilities, and limitations of individual methods, those best suited for a particular setting are identified. Challenges faced in development and wide-scale application of novel technologies are addressed.Keywords: Infrared imaging, thermography, melanoma detection and diagnosis, quantitative imaging, in vivo diagnostics

Este trabalho descreve a preparação e caracterização do híbrido celulose/fosfato de nióbio hidratado (Cel/NbOPO4.nH2O) utilizando como material de partida a celulose branqueada de bagaço de cana-de-açúcar e o nióbio metálico. O híbrido foi preparado por dois métodos: denominados métodos I e II. O método I consistiu na dissolução do nióbio metálico em solução de ácido fluorídrico/nítrico (100:10), com tempo de contato de 16 horas entre a celulose branqueada do bagaço de cana-de-açúcar e a solução ácida. Adicionou-se a essa solução ácido fosfórico para precipitação do material. O método II foi semelhante, com proporções diferentes da solução ácida fluorídrico/nítrico (160/100), sem tempo de contato da celulose com a solução ácida. Os métodos I e II utilizaram as seguintes proporções de cel/ Nb2O5.nH2O: (10:10);(10:6) e (10:2). Os materiais preparados pelos métodos I e II foram caracterizados por difração de raios X (DRX), termogravimetria (TG/DTG) e microscopia eletrônica de varredura (MEV). Observou-se aumento do índice do grau de cristalinidade e mudanças na morfologia dos materiais preparados.This work describes the preparation and characterization of cellulose/hydrous niobium phosphate hybrid with bleached cellulose from sugarcane bagasse. The hybrid was prepared in two different forms: named methods I and II. Method I consisted in dissolving metallic niobium in a fluoridric/nitric (100:10) mixture, with aging time of 16 hours in which the sugarcane bagasse was in contact with the acid solution. Phosphoric acid was then added to the solution for precipitation of the material. Method II was similar, but metallic niobium was diluted in a fluoridric /nitric (160/100) solution without aging time. In both methods different proportions of Cel/NbOPO4.nH2O were used: (10:10); (10:6) and (10:2). These materials were characterized by X-ray diffraction (XRD), thermogravimetry (TG/DTG) analysis and scanning electronic microscopy (SEM). The deposition of niobium phosphate and an increase in crystallinity were observed.

The traditional view of the function of relative sentences in the Greek New Testament differed markedly from that in many modern languages. This view was challenged in the mid-1980s and a number of striking correspondences with a variety of modern (and some classical) languages were pointed out, despite some differences. The purpose of this article is, amongst others, to explore functional aspects of the relative sentence against this background, and to provide further substantiation for the new view and some new perspectives in the light of recent literature. The conclusion is that the view of the functions of the relative sentence, as developed in the mid-1980s, still seems valid. The view is also supported to a large extent by recent literature, especially with respect to the relative sentence’s adjectival use, despite differences relating to nuances and terminology. However, recent New Testament grammars still distinguish so-called ‘conditional’, ‘concessive’, ‘causal’, ‘final’ and ‘resultative’ relative sentences as part of their adverbial use, despite strong evidence to the contrary. The conclusion reached is that relative sentences seem to have the following functions in New Testament Greek, which correspond to their functions in numerous modern languages: (1) Identifying a referent(s) with or without an overt nominal antecedent. (2) Providing background or additional information for a nominal or sentential antecedent in the form of a parenthesis, explanation or concession, or some combination of these. (3) Qualifying a verb with regard to time, location or manner. (4) Functioning as a conjoined sentence.

Again and again throughout the historyof Christian thought theological apologetics has dissolved the great ironic paradox of Jesus Christ into binary oppositions. In these historical contexts cultural relevancy has prevailed, and the underlying philosophical ideology has generated a disastrous subversion of the apologetic formulations of Christology in the New Testament. By calling this dichotomization into question, this essay intends to promote a postmodern hermeneutics that preserves the christological paradox and orients the constituting consciousness of theologians and scholars to both a spirituality of "being-affected-by" the biblical witness to Jesus Christ and a faith that will initiate action toward the transformation of society.

No abstract available.

Exact state-of-charge estimation is necessary for every application related to energy storage systems to protect the battery from deep discharging and overcharging. This leads to an improvement in discharge efficiency and extends the battery lifecycle. Batteries are a main source of energy and are usually monitored by management systems to achieve optimal use and protection. Coming up with effective methods for battery management systems that can adequately estimate the state-of-charge of batteries has become a great challenge that has been studied in the literature for some time. Hence, this paper analyses the different energy storage technologies, highlighting their merits and demerits. The various estimation methods for state-of-charge are discussed, and their merits and demerits are compared, while possible applications are pointed out. Furthermore, factors affecting the battery state-of-charge and approaches to managing the same are discussed and analysed. The different modelling tools used to carry out simulations for energy storage experiments are analysed and discussed. Additionally, a quantitative comparison of different technical and economic modelling simulators for energy storage applications is presented. Previous research works have been found to lack accuracy under varying conditions and ageing effects; as such, integrating hybrid approaches for enhanced accuracy in state-of-charge estimations is advised. With regards to energy storage technologies, exploring alternative materials for improved energy density, safety and sustainability exists as a huge research gap. The development of effective battery management systems for optimisation and control is yet to be fully exploited. When it comes to state-of-the-art simulators, integrating multiscale models for comprehensive understanding is of utmost importance. Enhancing adaptability across diverse battery chemistries and rigorous validation with real-world data is essential. To sum up the paper, future research directions and a conclusion are given. [ABSTRACT FROM AUTHOR]