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Battery energy storage systems (BESS) coupled with rooftop-mounted residential photovoltaic (PV) generation, designated as PV-BESS, draw increasing attention and market penetration as more and more such systems become available. The manifold BESS deployed to date rely on a variety of different battery technologies, show a great variation of battery size, and power electronics dimensioning. However, given today’s high investment costs of BESS, a well-matched design and adequate sizing of the storage systems are prerequisites to allow profitability for the end-user. The economic viability of a PV-BESS depends also on the battery operation, storage technology, and aging of the system. In this paper, a general method for comprehensive PV-BESS techno-economic analysis and optimization is presented and applied to the state-of-art PV-BESS to determine its optimal parameters. Using a linear optimization method, a cost-optimal sizing of the battery and power electronics is derived based on solar energy availability and local demand. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, feed-in remuneration, and battery aging. Using up to date technology-specific aging information and the investment cost of battery and inverter systems, three mature battery chemistries are compared; a lead-acid (PbA) system and two lithium-ion systems, one with lithium-iron-phosphate (LFP) and another with lithium-nickel-manganese-cobalt (NMC) cathode. The results show that different storage technology and component sizing provide the best economic performances, depending on the scenario of load demand and PV generation.

Residential photovoltaic (PV) battery systems increase households’ electricity self-consumption using rooftop PV systems and thus reduce the electricity bill. High investment costs of battery systems, however, prevent positive financial returns for most present residential battery installations in Germany. Tesla Motors, Inc. (Palo Alto, CA, USA) announced a novel battery system—the Powerwall—for only about 25% of the current German average market price. According to Tesla’s CEO Elon Musk, Germany is one of the key markets for their product. He has, however, not given numbers to support his statement. In this paper, we analyze the economic benefit of the Powerwall for end-users with respect to various influencing parameters: electricity price, aging characteristics of the batteries, topology of battery system coupling, subsidy schemes, and retrofitting of existing PV systems. Simulations show that three key-factors strongly influence economics: the price gap between electricity price and remuneration rate, the battery system’s investment cost, and the usable battery capacity. We reveal under which conditions a positive return on invest can be achieved and outline that the Powerwall could be a worthwhile investment in multiple, but not all, scenarios investigated. Resulting trends are generally transferrable to other home storage products.

Battery energy storage systems (BESSs) are already being deployed for several stationary applications in a technically and economically feasible way. This paper focuses on the revenues of industrial BESSs built from electric vehicle lithiumion batteries with varying states of health. For this analysis, a stationary BESS simulation model is used, that is parameterised with parameters of a 22-kWh automotive battery. The comprehensive model consists of several detailed sub-models, considering battery characteristics, ageing and operating strategies, which allow technical assessment through time series simulation. Therefore, capacity fade and energy losses are considered in this techno-economic evaluation. Potential economically feasible applications of new and second-life batteries, such as photovoltaic home storage, intraday trading and frequency regulation as well as their combined operation are compared. The investigation includes different electricity price scenarios. The combined operation, followed by frequency regulation, is found to have the highest economic viability for the specified electric vehicle battery.

Self-consumption of household photovoltaic (PV) storage systems has become profitable for residential owners under the trends of limited feed-in power and decreasing PV feed-in tariffs. For individual PV-storage systems, the challenge mainly lies in managing surplus generation of battery and grid power flow, ideally without relying on error-prone forecasts for both generation and consumption. Considering the large variation in power profiles of different houses in a neighborhood, the strategy is also supposed to be beneficial and applicable for the entire community. In this study, an adaptable battery charging control strategy is designed in order to obtain minimum costs for houses without any meteorological or load forecasts. Based on fuzzy logic control (FLC), battery state-of-charge (SOC) and the variation of SOC (∆SOC) are taken as input variables to dynamically determine output charging power with minimum costs. The proposed FLC-based algorithm benefits from the charging battery as much as possible during the daytime, and meanwhile properly preserves the capacity at midday when there is high possibility of curtailment loss. In addition, due to distinct power profiles in each individual house, input membership functions of FLC are improved by particle swarm optimization (PSO) to achieve better overall performance. A neighborhood with 74 houses in Germany is set up as a scenario for comparison to prior studies. Without forecasts of generation and consumption power, the proposed method leads to minimum costs in 98.6% of houses in the community, and attains the lowest average expenses for a single house each year.

Magnetic stimulation is a standard tool in brain research and has found important clinical applications in neurology, psychiatry, and rehabilitation. Whereas coil designs and the spatial field properties have been intensively studied in the literature, the temporal dynamics of the field has received less attention. Typically, the magnetic field waveform is determined by available device circuit topologies rather than by consideration of what is optimal for neural stimulation. This paper analyzes and optimizes the waveform dynamics using a nonlinear model of a mammalian axon. The optimization objective was to minimize the pulse energy loss. The energy loss drives power consumption and heating, which are the dominating limitations of magnetic stimulation. The optimization approach is based on a hybrid global-local method. Different coordinate systems for describing the continuous waveforms in a limited parameter space are defined for numerical stability. The optimization results suggest that there are waveforms with substantially higher efficiency than that of traditional pulse shapes. One class of optimal pulses is analyzed further. Although the coil voltage profile of these waveforms is almost rectangular, the corresponding current shape presents distinctive characteristics, such as a slow low-amplitude first phase which precedes the main pulse and reduces the losses. Representatives of this class of waveforms corresponding to different maximum voltages are linked by a nonlinear transformation. The main phase, however, scales with time only. As with conventional magnetic stimulation pulses, briefer pulses result in lower energy loss but require higher coil voltage than longer pulses.

Magnetic stimulation is a standard tool in brain research and has found important clinical applications in neurology, psychiatry, and rehabilitation. Whereas coil designs and the spatial field properties have been intensively studied in the literature, the temporal dynamics of the field has received less attention. Typically, the magnetic field waveform is determined by available device circuit topologies rather than by consideration of what is optimal for neural stimulation. This paper analyzes and optimizes the waveform dynamics using a nonlinear model of a mammalian axon. The optimization objective was to minimize the pulse energy loss. The energy loss drives power consumption and heating, which are the dominating limitations of magnetic stimulation. The optimization approach is based on a hybrid global-local method. Different coordinate systems for describing the continuous waveforms in a limited parameter space are defined for numerical stability. The optimization results suggest that there are waveforms with substantially higher efficiency than that of traditional pulse shapes. One class of optimal pulses is analyzed further. Although the coil voltage profile of these waveforms is almost rectangular, the corresponding current shape presents distinctive characteristics, such as a slow low-amplitude first phase which precedes the main pulse and reduces the losses. Representatives of this class of waveforms corresponding to different maximum voltages are linked by a nonlinear transformation. The main phase, however, scales with time only. As with conventional magnetic stimulation pulses, briefer pulses result in lower energy loss but require higher coil voltage than longer pulses.

The highly efficient HEP algorithm is a useful tool for mining High Occupancy (HO) item sets. Occupancy is an important measure that describes the interestingness of frequent item sets. The current study examines the efficiency problems in mining HO item sets and proposes an improved HEP algorithm, named advanced HEP (A–HEP), based on set theory rules which eliminate a large number of redundant iterations. The study also proposes a novel adaptive-and-modified HEP (NAM–HEP) algorithm that uses HO Set-Enumeration (SE) trees to store HO item sets. The study proposes definitions for adaptive thresholds such as support threshold and occupancy threshold based on the attributes of the transaction database for efficient pruning of the HO-SE tree. Two pseudo-code blocks are presented in addition to a detailed description of the A–HEP and NAM–HEP algorithms and their advantages. Using the A–HEP and NAM–HEP algorithms, HO item sets are investigated from the practical transaction databases named mushroom and retail. The results indicate that the proposed A–HEP and NAM–HEP algorithms enhance mining performance and runtime benchmarks.

Trastuzumab resistance in HER2-positive breast cancer is associated with a poorer prognosis. HSP90 is thought to play a major role in such resistance, but N-terminal inhibitors of this target have had little success. We sought to investigate the utility of NCT-547, a novel, rationally-designed C-terminal HSP90 inhibitor in the context of overcoming trastuzumab resistance. NCT-547 treatment significantly induced apoptosis without triggering the heat shock response (HSR), accompanied by caspase-3/− 7 activation in both trastuzumab-sensitive and -resistant cells. NCT-547 effectively promoted the degradation of full-length HER2 and truncated p95HER2, while also attenuating hetero-dimerization of HER2 family members. The impairment of cancer stem-like traits was observed with reductions in ALDH1 activity, the CD24 low /CD44 high subpopulation, and mammosphere formation in vitro and in vivo. NCT-547 was an effective inhibitor of tumor growth and angiogenesis, and no toxic outcomes were found in initial hepatic and renal analysis. Our findings suggest that NCT-547 may have applications in addressing trastuzumab resistance in HER2-positive breast cancer.

Despite recent advances, there remains a significant unmet need for the development of new targeted therapies for triple-negative breast cancer (TNBC). Although the heat shock protein HSP90 is a promising target, previous inhibitors have had issues during development including undesirable induction of the heat shock response (HSR) and off-target effects leading to toxicity. SL-145 is a novel, rationally-designed C-terminal HSP90 inhibitor that induces apoptosis in TNBC cells via the suppression of oncogenic AKT, MEK/ERK, and JAK2/STAT3 signaling and does not trigger the HSR, in contrast to other inhibitors. In an orthotopic allograft model incorporating breast cancer stem cell-enriched TNBC tumors, SL-145 potently suppressed tumor growth, angiogenesis, and metastases concomitant with dysregulation of the JAK2/STAT3 signaling pathway. Our findings highlight the potential of SL-145 in suppressing metastatic TNBC independent of the HSR.

We obtain rich measures of the risk preferences of a sample of Vietnamese farmers, and revisit the link between risk preferences and economic well-being. Far from being particularly risk averse, our farmers are on average risk neutral and, thus, more risk tolerant than typical Western subject populations. This generalises recent findings indicating that students in poorer countries are more risk tolerant than students in richer countries to a general population sample. Risk aversion is, furthermore, negatively correlated with income within our sample, but does not correlate with wealth. This also casts doubt on high levels of risk aversion causing failure to adopt new technologies, which we discuss.