The grand challenges of contemporary fundamental physics—dark matter, dark energy, vacuum energy, inflation and early universe cosmology, singularities and the hierarchy problem—all involve gravity as a key component. And of all gravitational phenomena, black holes stand out in their elegant simplicity, while harbouring some of the most remarkable predictions of General Relativity: event horizons, singularities and ergoregions. The hitherto invisible landscape of the gravitational Universe is being unveiled before our eyes: the historical direct detection of gravitational waves by the LIGO-Virgo collaboration marks the dawn of a new era of scientific exploration. Gravitational-wave astronomy will allow us to test models of black hole formation, growth and evolution, as well as models of gravitational-wave generation and propagation. It will provide evidence for event horizons and ergoregions, test the theory of General Relativity itself, and may reveal the existence of new fundamental fields. The synthesis of these results has the potential to radically reshape our understanding of the cosmos and of the laws of Nature. The purpose of this work is to present a concise, yet comprehensive overview of the state of the art in the relevant fields of research, summarize important open problems, and lay out a roadmap for future progress. This write-up is an initiative taken within the framework of the European Action on ‘Black holes, Gravitational waves and Fundamental Physics’.

Streaming over the wireless channel is challenging due to rapid fluctuations in available throughput. Encouraged by recent advances in cellular throughput prediction based on radio link metrics, we examine the impact on Quality of Experience (QoE) when using prediction within existing algorithms based on the DASH standard. By design, DASH algorithms estimate available throughput at the application level from chunk rates and then apply some averaging function. We investigate alternatives for modifying these algorithms, by providing the algorithms direct predictions in place of estimates or feeding predictions in place of measurement samples. In addition, we explore different prediction horizons going from one to three chunk durations. Furthermore, we induce different levels of error to ideal prediction values to analyse deterioration in user QoE as a function of average error. We find that by applying accurate prediction to three algorithms, user QoE can improve up to 55% depending on the algorithm in use. Furthermore having longer horizon positively affects QoE metrics. Accurate predictions have the most significant impact on stall performance by completely eliminating them. Prediction also improves switching behaviour significantly and longer prediction horizons enable a client to promptly reduce quality and avoid stalls when the throughput drops for a relatively long time that can deplete the buffer. For all algorithms, a 3-chunk horizon strikes the best balance between different QoE metrics and, as a result, achieving highest user QoE. While error-induced predictions significantly lower user QoE in certain situations, on average, they provide 15% improvement over DASH algorithms without any prediction.

In this paper, we present a 4G trace dataset composed of client-side cellular key performance indicators (KPIs) collected from two major Irish mobile operators, across different mobility patterns (static, pedestrian, car, bus and train). The 4G trace dataset contains 135 traces, with an average duration of fifteen minutes per trace, with viewable throughput ranging from 0 to 173 Mbit/s at a granularity of one sample per second. Our traces are generated from a well-known non-rooted Android network monitoring application, G-NetTrack Pro. This tool enables capturing various channel related KPIs, context-related metrics, downlink and uplink throughput, and also cell-related information. To the best of our knowledge, this is the first publicly available dataset that contains throughput, channel and context information for 4G networks. To supplement our real-time 4G production network dataset, we also provide a synthetic dataset generated from a large-scale 4G ns-3 simulation that includes one hundred users randomly scattered across a seven-cell cluster. The purpose of this dataset is to provide additional information (such as competing metrics for users connected to the same cell), thus providing otherwise unavailable information about the eNodeB environment and scheduling principle, to end user. In addition to this dataset, we also provide the code and context information to allow other researchers to generate their own synthetic datasets.

Many manufacturing cost reduction initiatives have been introduced over past three decades including lean manufacturing. Waste reduction and efficiency improvement are the main objectives of this initiative. It is developed from a set of tools and techniques and can fit nicely in cost focus or cost leadership competitive advantage strategies. But, keeping competitive advantage under the market circumstances are getting harder with growth of production quantity and product diversity. Therefore, paper's focus is lean manufacturing implementation trends and issues within the various manufacturing sector. Successes and failures of implementation of lean manufacturing in some industries are discussed. It was found that lean principles are good source of competitive advantage, it is applicable for many industries and its expansion and discussion are significantly progressing. The biggest threat in implementing lean is lack of understanding the concept but those who engage consultants were more successful.

Immune-checkpoint inhibitors (ICPIs), including antibodies against cytotoxic T-lymphocyte associated antigen 4 and programmed cell death protein 1, have been shown to induce durable complete responses in a proportion of patients in the first-line and refractory setting in advanced melanoma and renal cell carcinoma. In fact, there are several lines of both targeted agents and ICPI that are now feasible treatment options. However, survival in the metastatic setting continues to be poor and there remains a need for improved therapeutic approaches. In order to enhance patient selection for the most appropriate next line of therapy, better predictive biomarkers of responsiveness will need to be developed in tandem with technologies to identify mechanisms of ICPI resistance. Adaptive, biomarker-driven trials will drive this evolution. The combination of ICPI with specific chemotherapies, targeted therapies and other immuno-oncology (IO) drugs in order to circumvent ICPI resistance and enhance efficacy is discussed. Recent data support the role for both targeted therapies and ICPI in the adjuvant setting of melanoma and targeted therapies in the adjuvant setting for renal cell carcinoma, which may influence the consideration of treatment on subsequent relapse. Approaches to select the optimal treatment sequences for these patients will need to be refined.

Time reversal of waves has been successfully used in communications, sensing and imaging for decades. The application in underwater acoustic communications is of our special interest, as it puts together a reversible process (allowing a reversible software or hardware realisation) and a reversible medium (allowing a reversible model of the environment). This work in progress report addresses the issues of modelling, analysis and implementation of acoustic time reversal from the reversible computation perspective. We show the potential of using reversible cellular automata for modelling and quantification of reversibility in the time reversal communication process. Then we present an implementation of time reversal hardware based on reversible circuits.

The Vijenac limestone quarry, near Tuzla in Bosnia and Herzegovina, is composed of carbonate rocks locally embedding tectonically disturbed siltite and sandstone with Fe-Mn concretions. The quarry itself represents a part of Dinaric overstep sequences (the Pogari Formation) unconformably overlying ophiolite melange and ophiolite trust-scheets. Petrographic, chemical and mineralogical analyses had shown that the concretions may be divided into two types: (i) Mn-rich concretions with ≈ 17 wt.% of Mn and compact texture and (ii) Mn–poor with ≈ 8 wt.% of Mn and porous texture. The amount of Ca, Fe and Mg in both concretion types are similar. Nickel and Cr positively correlate with Fe and Mn, respectively. According to petrographic and mineralogical analyses, concretions are composed of calcite, dolomite, hematite, todorokite and takanelite. Petrographic study confi rmed the development of concretions within three stages including two generations of calcite. Studied concretions are formed within consolidated sandstones inheriting their sedimentary textures – therefore a late diagenetic process is assumed.