Explore the vast range of titles available.

The latest tape drive technologies (LTO-9, IBM TS1170) impose new constraints on the management of data archived to tape. In the past, new drives could read/write the previous one or even two generations of media, but this is no longer the case. This means that repacking older media to new media must be carried out on a more aggressive schedule than in the past. An additional challenge is the large capacity of the newer media. A 50 TB tape can contain a vast number of files, whose metadata must be tracked during repacking. Repacking an entire tape also requires a significant amount of disk storage. At CERN Tier-0, these challenges have created new operational problems to solve, in particular contention for resources between physics archival and repack operations. This contribution details these problems and describes the various approaches we have taken to mitigate and solve them. We include a roadmap for future repack developments.

Fermilab is the first High Energy Physics institution to transition from X.509 user certificates to authentication tokens in production systems. All the experiments that Fermilab hosts are now using JSON Web Token (JWT) access tokens in their grid jobs. The tokens are defined using the WLCG Common JWT Profile. Many software components have been either created or updated for this transition, and the changes to those components are described. Most of the software is available to others as open source. There have been some glitches and learning curve issues but in general the system has been performing well and is being improved as operational problems are addressed.

The growing uncertainty associated with the increasing penetration of wind and solar power generation has presented new challenges to the operation of large-scale electric power systems. Motivated by these challenges, we present a multistage adaptive robust optimization model for the most critical daily operational problem of power systems, namely, the unit commitment (UC) problem, in the situation where nodal net electricity loads are uncertain. The proposed multistage robust UC model takes into account the time causality of the hourly unfolding of uncertainty in the power system operation process, which we show to be relevant when ramping capacities are limited and net loads present significant variability. To deal with large-scale systems, we explore the idea of simplified affine policies and develop a solution method based on constraint generation. Extensive computational experiments on the IEEE 118-bus test case and a real-world power system with 2,736 buses demonstrate that the proposed algorithm is effective in handling large-scale power systems and that the proposed multistage robust UC model can significantly outperform the deterministic UC and existing two-stage robust UC models in both operational cost and system reliability.

Optically pumped magnetometers (OPMs) have recently become so sensitive that they are suitable for use in magnetoencephalography (MEG). These sensors solve operational problems of the current standard MEG, where superconducting quantum interference device (SQUID) gradiometers and magnetometers are being used. The main advantage of OPMs is that they do not require cryogenics for cooling. Therefore, they can be placed closer to the scalp and are much easier to use. Here, we measured auditory evoked fields (AEFs) with both SQUID- and OPM-based MEG systems for a group of subjects to better understand the usage of a limited sensor count OPM-MEG. We present a theoretical framework that transforms the within subject data and equivalent simulation data from one MEG system to the other. This approach works on the principle of solving the inverse problem with one system, and then using the forward model to calculate the magnetic fields expected for the other system. For the source reconstruction, we used a minimum norm estimate (MNE) of the current distribution. Two different volume conductor models were compared: the homogeneous conducting sphere and the three-shell model of the head. The transformation results are characterized by a relative error and cross-correlation between the measured and the estimated magnetic field maps of the AEFs. The results for both models are encouraging. Since some commercial OPMs measure multiple components of the magnetic field simultaneously, we additionally analyzed the effect of tangential field components. Overall, our dual-axis OPM-MEG with 15 sensors yields similar information to a 62-channel SQUID-MEG with its field of view restricted to the right hemisphere.

Rapid population growth and urbanization are two main drivers for the over-abstraction of conventional freshwater resources in various parts of the world, which leads to the situation of water scarcity (per capita availability <1000 m3/year). Predictions based on the World Bank projected population data and the FAO AQUASTAT database for freshwater availability show that by 2050, 2 billion people living in 44 countries will likely suffer from water scarcity, of which 95% may live in developing countries. Among these, the countries that will likely be most strongly hit by water scarcity by 2050 are Uganda, Burundi, Nigeria, Somalia, Malawi, Eritrea, Ethiopia, Haiti, Tanzania, Niger, Zimbabwe, Afghanistan, Sudan, and Pakistan. Currently, these countries have not yet established desalination to meet their freshwater demand. However, the current global trend shows that membrane-based desalination technology is finding new outlets for supplying water to meet growing water demand in most of the water-scarce countries. These 14 water-scarce countries will demand an additional desalination capacity of 54 Mm3/day by 2050 in order to meet the standard of current municipal water demand and to compensate for the withdrawal of renewable resources. Case studies from India, China, and South Africa have highlighted that other countries may apply the strategy of using desalinated water for industrial users. Moreover, challenges to the widespread adoption of desalination exist such as expense, significant energy use, the need for specialized staff training, the large carbon footprint of facilities, environmental issues such as greenhouse gas emission (GHGs), chemical discharge, and operational problems such as membrane fouling.

Variation in communicative complexity has been conceptually and empirically attributed to social complexity, with animals living in more complex social environments exhibiting more signals and/or more complex signals than animals living in simpler social environments. As compelling as studies highlighting a link between social and communicative variables are, this hypothesis remains challenged by operational problems, contrasting results, and several weaknesses of the associated tests. Specifically, how to best operationalize social and communicative complexity remains debated; alternative hypotheses, such as the role of a species’ ecology, morphology, or phylogenetic history, have been neglected; and the actual ways in which variation in signaling is directly affected by social factors remain largely unexplored. In this review, we address these three issues and propose an extension of the “social complexity hypothesis for communicative complexity” that resolves and acknowledges the above factors. We specifically argue for integrating the inherently multimodal nature of communication into a more comprehensive framework and for acknowledging the social context of derived signals and the potential of audience effects. By doing so, we believe it will be possible to generate more accurate predictions about which specific social parameters may be responsible for selection on new or more complex signals, as well as to uncover potential adaptive functions that are not necessarily apparent from studying communication in only one modality.

Carbon neutrality goals are driving the increased use of renewable energy (RE). Large-scale use of RE requires accurate energy generation forecasts; optimized power dispatch, which minimizes costs while satisfying operational constraints; effective system control to ensure a stable power supply; and electricity markets that support bidding and trading decisions associated with RE. However, the uncertainties in RE generation make renewable power systems challenging to operate. For example, the intermittent nature of wind power can make it difficult to balance the supply and demand of electricity in real time; therefore, traditional power sources could be needed to meet the demand, which can increase electricity prices. This Review outlines the potential of artificial intelligence-based methods for supporting renewable power system operation. We discuss the ability of machine learning, deep learning and reinforcement learning methods to facilitate power system forecasts, dispatch, control and markets to support the use of RE. We also emphasize the applicability of these techniques to different operational problems. Finally, we discuss potential trends in renewable power system development and approaches to address the associated operational challenges such as the increasingly distributed nature of RE installations, diversification of energy storage systems and growing market complexity.The increasing integration of renewable energy technologies into power systems poses challenges owing to the large uncertainties associated with renewable energy production. This Review investigates the ability of artificial intelligence-based methods to improve forecasts, dispatch, control and electricity markets in renewable power systems.

Purpose - The purpose of this paper is to analyze and investigate analyzed core operational problems of aquatic products with food traceability system and their performance in the Taiwanese market and to develop the marketing strategies to solve these core operational problems.Design methodology approach - Based on all of the core operational problems derived from the literature, the paper interviewed distributors and aquatic product producers and collected their ideas to resolve the above problems. Then, the study applies the TRIZ theory to find the improving and worsening parameters for those issues, based on which the study can develop strategies to improve the marketing model of aquatic products with food traceability systems to solve operational problems.Findings - The findings of the study are of three fold: identified seven core problems of aquatic products with food traceability systems; identified seven strategies for improving marketing model to solve operational problems of aquatic products with food traceability systems and developed the new marketing model to solve operational problems for aquatic products with food traceability systems.Practical implications - Promoting the food traceability certification comprehensively cannot only improve the food safety in Taiwan but also improve the competitiveness of Taiwanese industries as well as help to expand to the international market.Originality value - The contribution of this study lies in extending the body of knowledge of application of TRIZ methodology in marketing model for aquatic products with food traceability systems. The findings of this study can be used as a reference for aquaculture products with traceability systems in other countries, as food safety is a globally growing trend.

The article presents a comparative characterization of the structural materials (composites and metals) used in modern aviation structures, focusing on the airframe structure of the most modern aircraft (Airbus A-380, Boeing B-787, and JSF F-35). Selected design and operational problems were analysed, with particular emphasis on composites and light metals (aluminium). For this purpose, the Shore’s method was used for the analysis of the obtained strength results and the programming environment (ANSYS, SolidWorks) required to simulate the GLARE 3 2/1-04 composite. The focus was on highlighting the differences in the construction and modelling of these materials resulting from their various structures (isotropy and anisotropy), e.g., by analyzing the mechanics of metal destruction and comparing it with the composite material. In terms of solving the problems of finite element analysis FEM, tests have been carried out on two samples made of an aluminium alloy and a fiberglass composite. The focus was on highlighting the differences in the construction and modelling of these materials resulting from their various structures (isotropy and anisotropy), e.g., by analyzing the mechanics of metal destruction and comparing it with the composite material. On the basis of the obtained results, the preferred variant was selected, in terms of displacements, stresses, and deformations. In the final part of the work, based on the conducted literature analysis and the conducted research (analysis, simulations, and tests), significant observations and final conclusions, reflected in practical applications, were formulated.

The rapid development of intelligent warehouse systems is resulting in the realization of automation in warehouse activities and raising awareness of decarbonization, particularly the need to reduce carbon emissions from electricity consumption. Driven by the decarbonization trend, microgrid systems with rooftop photovoltaic panels are becoming more popular in warehouses and are providing zero-carbon electricity for warehouse operations. How to make better use of microgrid systems and reduce the consumption of electricity generated from traditional energy sources is becoming increasingly important in warehouse systems. This paper investigates an operational problem in a warehouse system equipped with a shuttle-based storage and retrieval system, in which a microgrid system acts as the main electricity source. Power-load management is applied to avoid peaks of energy consumption, and a mixed linear programming model is developed to optimize task sequencing and scheduling with decarbonization awareness. To solve the proposed problem, a data-driven variable neighbourhood search algorithm is built. Numerical experiments are conducted to validate the model and algorithm. Sensitivity analysis shows the effectiveness of power-load management and the influence of system configuration on energy consumption.