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Energy efficiency and renewable energy are the main pillars of sustainability and environmental compatibility. This study presents an overview of sustainable and green cellular base stations (BSs), which account for most of the energy consumed in cellular networks. We review the architecture of the BS and the power consumption model, and then summarize the trends in green cellular network research over the past decade. As its major contribution, this study highlights the uses of renewable energy in cellular communication by: (i) investigating the system model and the potential of renewable energy solutions for cellular BSs; (ii) identifying the potential geographical locations for renewable-energy-powered BSs; (iii) performing case studies on renewable-energy-powered cellular BSs and suggesting future research directions based on our findings; (iv) examining the present deployment of sustainable and green BSs; and (v) studying the barriers that prevent the widespread use of renewable-energy-powered BSs and providing recommendations for future work.

This paper develops a new approach to band subset selection (BSS) for hyperspectral image classification (HSIC) which selects multiple bands simultaneously as a band subset, referred to as simultaneous multiple band selection (SMMBS), rather than one band at a time sequentially, referred to as sequential multiple band selection (SQMBS), as most traditional band selection methods do. In doing so, a criterion is particularly developed for BSS that can be used for HSIC. It is a linearly constrained minimum variance (LCMV) derived from adaptive beamforming in array signal processing which can be used to model misclassification errors as the minimum variance. To avoid an exhaustive search for all possible band subsets, two numerical algorithms, referred to as sequential (SQ) and successive (SC) algorithms are also developed for LCMV-based SMMBS, called SQ LCMV-BSS and SC LCMV-BSS. Experimental results demonstrate that LCMV-based BSS has advantages over SQMBS.

In contemporary days, the research and development enterprises have been focusing to design intelligently the battery swap station (BSS) architecture having the prospects of providing a consistent platform for the successful installation of the large-scale fleet of hybrid and electric vehicles (i.e. xEVs). The BSS may calibrate its subsystem for the electric vehicle (EV) deployment by accomplishing similar idea as in existing gasoline refuelling stations, in which the discharged batteries are being replaced or swapped by partially or fully charged ones by spending a few minutes. The BSS approach has arisen as a promising technology to the traditional EV recharging station approach as it provides a broader experience of business prospects for the specific stakeholders. This work deals with the introduction to BSS including infrastructure, techniques, benefits over charging station and key challenges associated with BSS. Furthermore, an S34X-smart swapping station for xEVs is proposed and finally, the key thrust is research for BSS is discussed. To the authors’ knowledge, this is the first kind of review work on BSS.

Independent component analysis (ICA) is a widely-used blind source separation technique. ICA has been applied to many applications. ICA is usually utilized as a black box, without understanding its internal details. Therefore, in this paper, the basics of ICA are provided to show how it works to serve as a comprehensive source for researchers who are interested in this field. This paper starts by introducing the definition and underlying principles of ICA. Additionally, different numerical examples in a step-by-step approach are demonstrated to explain the preprocessing steps of ICA and the mixing and unmixing processes in ICA. Moreover, different ICA algorithms, challenges, and applications are presented.

A simplicial cone can be employed in nonnegative blind source separation (N-BSS). Nevertheless, the coordinate origin may not be a dark-point, and in this case, it is challenging to implement N-BSS with a simplicial cone. We propose an algorithm for finding dark-points based on the minimum Jaccard index (MJI) criterion-dark-point component analysis (DCA). This method only needs to assume source boundedness and nonnegativity instead of local dominance, full additivity, and sparsity. On the other hand, mixing data scatter plots are usually confined as tear-drop-shaped or deltoid. However, DCA does not need such restrictions. DCA can also be applied to blind source separation (BSS) in which the sources are strictly positive, and the result is the same as that of N-BSS.

Key factors driving eating behavior are hunger and satiety, which are controlled by a complex interplay of central neurotransmitter systems and peripheral stimuli. The lipid-derived messenger oleoylethanolamide (OEA) is released by enterocytes in response to fat intake and indirectly signals satiety to hypothalamic nuclei. Brain histamine is released during the appetitive phase to provide a high level of arousal in anticipation of feeding, and mediates satiety. However, despite the possible functional overlap of satiety signals, it is not known whether histamine participates in OEA-induced hypophagia. Using different experimental settings and diets, we report that the anorexiant effect of OEA is significantly attenuated in mice deficient in the histamine-synthesizing enzyme histidine decarboxylase (HDC-KO) or acutely depleted of histamine via interocerebroventricular infusion of the HDC blocker α-fluoromethylhistidine (α-FMH). α-FMH abolished OEA-induced early occurrence of satiety onset while increasing histamine release in the CNS with an H ₃ receptor antagonist-increased hypophagia. OEA augmented histamine release in the cortex of fasted mice within a time window compatible to its anorexic effects. OEA also increased c-Fos expression in the oxytocin neurons of the paraventricular nuclei of WT but not HDC-KO mice. The density of c-Fos immunoreactive neurons in other brain regions that receive histaminergic innervation and participate in the expression of feeding behavior was comparable in OEA-treated WT and HDC-KO mice. Our results demonstrate that OEA requires the integrity of the brain histamine system to fully exert its hypophagic effect and that the oxytocin neuron-rich nuclei are the likely hypothalamic area where brain histamine influences the central effects of OEA.

The popularity of electric vehicles has been limited by factors such as range, long charging times and fast power failure in winter. In order to overcome these challenges, battery swapping stations (BSS) have been constructed and greatly promoted in recent years. In this paper, the related literature on electric vehicle service is reviewed and the co-occurrence of keywords is analyzed using CiteSpace. The literature is classified according to clustering results and recurring themes, such as the location of BSS, inventory decisions, charging strategies and BSS assignment. In each topic, typical optimization models and algorithms proposed in previous studies are summarized. Then, this paper gives a case about the business model and revenue capacity calculation of BSS. Finally, it points out the future research direction of battery swapping stations for electric vehicles.

Further popularisation of electric vehicles (EVs) is hindered by their relatively short driving distance and long battery charging time. To overcome these shortcomings, the battery swapping station (BSS) has been proposed as a means of satisfying the increasing demands for fast EV battery recharging. At a BSS, (partially) depleted batteries from EVs can be replaced with partially or fully charged ones almost instantaneously. Recharging scheduling and maintenance of batteries are done by the operator of BSS, with the target of minimising electrical energy costs while satisfying customer demands. In this study, the authors consider a realistic BSS framework in which EVs can arrive at BSS with time of day dependent rates having different battery state-of-charges. They investigate the battery charging scheduling problem in the BSS under a dynamic energy pricing. They solve (i) an online optimal BSS control problem to minimise the energy cost with a quality-of-service (QoS) guarantee, and (ii) an offline optimal BSS design problem to determine the optimal number of stored batteries so as to achieve a desirable tradeoff between flexibility in charging and amortised battery costs. The experimental results show that the total charging energy cost can be reduced significantly under different traffic scenarios.

Executive SummaryThe EC Directive 2013/59/Euratom states in article 56 that exposures of target volumes in nuclear medicine treatments shall be individually planned and their delivery appropriately verified. The Directive also mentions that medical physics experts should always be appropriately involved in those treatments. Although it is obvious that, in nuclear medicine practice, every nuclear medicine physician and physicist should follow national rules and legislation, the EANM considered it necessary to provide guidance on how to interpret the Directive statements for nuclear medicine treatments.For this purpose, the EANM proposes to distinguish three levels in compliance to the optimization principle in the directive, inspired by the indication of levels in prescribing, recording and reporting of absorbed doses after radiotherapy defined by the International Commission on Radiation Units and Measurements (ICRU): Most nuclear medicine treatments currently applied in Europe are standardized. The minimum requirement for those treatments is ICRU level 1 (“activity-based prescription and patient-averaged dosimetry”), which is defined by administering the activity within 10% of the intended activity, typically according to the package insert or to the respective EANM guidelines, followed by verification of the therapy delivery, if applicable.Non-standardized treatments are essentially those in developmental phase or approved radiopharmaceuticals being used off-label with significantly (> 25% more than in the label) higher activities. These treatments should comply with ICRU level 2 (“activity-based prescription and patient-specific dosimetry”), which implies recording and reporting of the absorbed dose to organs at risk and optionally the absorbed dose to treatment regions.The EANM strongly encourages to foster research that eventually leads to treatment planning according to ICRU level 3 (“dosimetry-guided patient-specific prescription and verification”), whenever possible and relevant.Evidence for superiority of therapy prescription on basis of patient-specific dosimetry has not been obtained. However, the authors believe that a better understanding of therapy dosimetry, i.e. how much and where the energy is delivered, and radiobiology, i.e. radiation-related processes in tissues, are keys to the long-term improvement of our treatments.

Recently, cellular networks’ energy efficiency has garnered research interest from academia and industry because of its considerable economic and ecological effects in the near future. This study proposes an approach to cooperation between the Long-Term Evolution (LTE) and next-generation wireless networks. The fifth-generation (5G) wireless network aims to negotiate a trade-off between wireless network performance (sustaining the demand for high speed packet rates during busy traffic periods) and energy efficiency (EE) by alternating 5G base stations’ (BSs) switching off/on based on the traffic instantaneous load condition and, at the same time, guaranteeing network coverage for mobile subscribers by the remaining active LTE BSs. The particle swarm optimization (PSO) algorithm was used to determine the optimum criteria of the active LTE BSs (transmission power, total antenna gain, spectrum/channel bandwidth, and signal-to-interference-noise ratio) that achieves maximum coverage for the entire area during the switch-off session of 5G BSs. Simulation results indicate that the energy savings can reach 3.52 kW per day, with a maximum data rate of up to 22.4 Gbps at peak traffic hours and 80.64 Mbps during a 5G BS switched-off session along with guaranteed full coverage over the entire region by the remaining active LTE BSs.