Creating stable Floquet-Weyl semimetals by laser-driving of 3D Dirac materials

Tuning and stabilising topological states, such as Weyl semimetals, Dirac semimetals, or topological insulators, is emerging as one of the major topics in materials science. Periodic driving of many-body systems offers a platform to design Floquet states of matter with tunable electronic properties on ultrafast time scales. Here we show by first principles calculations how femtosecond laser pulses with circularly polarised light can be used to switch between Weyl semimetal, Dirac semimetal, and topological insulator states in a prototypical 3D Dirac material, Na$_3$Bi. Our findings are general and apply to any 3D Dirac semimetal. We discuss the concept of time-dependent bands and steering of Floquet-Weyl points (Floquet-WPs), and demonstrate how light can enhance topological protection against lattice perturbations. Our work has potential practical implications for the ultrafast switching of materials properties, like optical band gaps or anomalous magnetoresistance. Moreover, we introduce Floquet time-dependent density functional theory (Floquet-TDDFT) as a general and robust first principles method for predictive Floquet engineering of topological states of matter.Comment: 21 pages, 4 figure

Cost-benefit Analysis of a Genetic Marker on Cow-calf Operations Differentiated by Pasture and Breed

Genetic sequencing in beef cattle (Bos taurus L.) is expected to aid producers with selecting breeding stock. Using data from experimental trials conducted with Angus, Brahman, and their reciprocal cross, the single nucleotide polymorphism (SNP) P450 C994G marker expression was investigated for use in selecting genetics suited to grazing endophyte-infected tall fescue (Festuca arundinacea Schreb. L.) compared to bermudagrass (Cynodon dactylon L.) pasture. The study is unique in the sense that actual cow-calf breeding failure rates (open cows were not culled) were tracked from 1991 to 1997 on herds that were bred to calf in spring and were either exposed to fungal endophyte-infected (Acremonium coenophialum L.) tall fescue grazing and hay or not. The study used the Forage and Cattle Analysis and Planning (FORCAP) decision support software to assess economic performance driven by birth weight, weaning weight, and breeding failure rate differences across treatment. Results suggest that for reciprocal cross herds primarily grazing bermudagrass pastures, the P450 C994C genotype (CC) was most favorable; whereas, the P450 G994C genotype (GC) was more profitable with tall fescue. Adding genetic market information when selecting a production strategy led to approximately $15/head in added profitability. In comparison to the prorated cost of$2.40/head over the life of a dam, the collection, interpretation, and management of genetic information under the conditions observed in this study may be worthwhile

All-optical nonequilibrium pathway to stabilizing magnetic Weyl semimetals in pyrochlore iridates

Nonequilibrium many-body dynamics is becoming one of the central topics of modern condensed matter physics. Floquet topological states were suggested to emerge in photodressed band structures in the presence of periodic laser driving. Here we propose a viable nonequilibrium route without requiring coherent Floquet states to reach the elusive magnetic Weyl semimetallic phase in pyrochlore iridates by ultrafast modification of the effective electron-electron interaction with short laser pulses. Combining \textit{ab initio} calculations for a time-dependent self-consistent reduced Hubbard $U$ controlled by laser intensity and nonequilibrium magnetism simulations for quantum quenches, we find dynamically modified magnetic order giving rise to transiently emerging Weyl cones that are probed by time- and angle-resolved photoemission spectroscopy. Our work offers a unique and realistic pathway for nonequilibrium materials engineering beyond Floquet physics to create and sustain Weyl semimetals. This may lead to ultrafast, tens-of-femtoseconds switching protocols for light-engineered Berry curvature in combination with ultrafast magnetism.Comment: 27 pages including methods and supplementary information, 4 figures, 4 supplementary figure

The ICT convergence discourse in the information systems literature - A second-order observation

The growing relevance, scale, and complexity of Business Intelligence (BI) entails the need to find agile and efficient solutions for the coordination of maintenance and release processes – under consideration of the heterogeneity of the involved units on the IT and the business side. The finance industry with its mature BI infrastructures and its highly turbulent business environment is a forerunner for these developments. Based on a survey among BI users in the finance sector, relevant problem areas in the BI service provision are identified and structured. A series of qualitative interviews among banks and insurance companies is used to gain further insights into approaches for dealing with the related issues. The studies uncover several advantages of a central “BI Competency Centre” (BICC) as well as levers for effectively structuring the interfaces between BICC, IT, and user interface

How to Build a Sufi Empire? The Strategies of the Daghestani Shaykh Said-Afandi

-This paper briefly discusses the rise of the Mahmudiyya in post-Soviet Daghestan, and the political strategies of its leading authority, Shaykh Said-Afandi Chirkeevskii (Atsaev, 1937-2012). How did the Said-Afandi's Mahmudiyya branch of the Naqshbandiyya khalidiyya Sufi brotherhood become a state-supporting and state-supported institution in contemporary Daghestan? I argue that key elements of Said-Afandi's rise into the spotlight were his take-over of the republican Muftiate in the period when the old Soviet Muftiate for the North Caucasus was disintegrating, and the subsequent establishment of a network of Islamic teaching institutes that reached out to both Kumyks and Avars. Here the Mahmudiyya competes with another Khalidiyya branch and especially with the Salafi groups; the latter now appear as the major threat to the secular and multinational republic, while Said-Afandi's propagation of a conservative ethos matched the general conservative stance of the Daghestani and Russian leaderships. Also of importance is the integration of Shadhiliyya elements into Mahmudiyya teaching and practice that make the group's appeal more diverse. Said-Afandi's writings (originally written in Avar) were professionally translated into Russian, with a broad Islamic discourse for the masses and a specialized Sufi discourse for the inner circle. With these missionary policies Said-Afandi reached out not only to the Daghestani nationalities but also to Muslims in other parts of the Russian Federation, from Moscow over Tatarstan to Siberia. At the same not only the Salafi challenge but also the ethnic cleavages in Daghestan itself pose serious limitations to the Mahmudiyya success,and the question remains whether the current leadership of the brotherhood - after Said-Afandi's tragic death at the hands of a female suicide bomber in the summer of 2012 - will be able to hold the group together.222-23

Forecasting of residential unit's heat demands: a comparison of machine learning techniques in a real-world case study

A large proportion of the energy consumed by private households is used for space heating and domestic hot water. In the context of the energy transition, the predominant aim is to reduce this consumption. In addition to implementing better energy standards in new buildings and refurbishing old buildings, intelligent energy management concepts can also contribute by operating heat generators according to demand based on an expected heat requirement. This requires forecasting models for heat demand to be as accurate and reliable as possible. In this paper, we present a case study of a newly built medium-sized living quarter in central Europe made up of 66 residential units from which we gathered consumption data for almost two years. Based on this data, we investigate the possibility of forecasting heat demand using a variety of time series models and offline and online machine learning (ML) techniques in a standard data science approach. We chose to analyze different modeling techniques as they can be used in different settings, where time series models require no additional data, offline ML needs a lot of data gathered up front, and online ML could be deployed from day one. A special focus lies on peak demand and outlier forecasting, as well as investigations into seasonal expert models. We also highlight the computational expense and explainability characteristics of the used models. We compare the used methods with naive models as well as each other, finding that time series models, as well as online ML, do not yield promising results. Accordingly, we will deploy one of the offline ML models in our real-world energy management system in the near future

Genetic architecture of body size in mammals

Much of the heritability for human stature is caused by mutations of small-to-medium effect. This is because detrimental pleiotropy restricts large-effect mutations to very low frequencies