Effective spin physics in two-dimensional cavity QED arrays

We investigate a strongly correlated system of light and matter in two-dimensional cavity arrays. We formulate a multimode Tavis–Cummings (TC) Hamiltonian for two-level atoms coupled to cavity modes and driven by an external laser field which reduces to an effective spin Hamiltonian in the dispersive regime. In one-dimension we provide an exact analytical solution. In two-dimensions, we perform mean-field study and large scale quantum Monte Carlo simulations of both the TC and the effective spin models. We discuss the phase diagram and the parameter regime which gives rise to frustrated interactions between the spins. We provide a quantitative description of the phase transitions and correlation properties featured by the system and we discuss graph-theoretical properties of the ground states in terms of graph colourings using Pólya's enumeration theorem

Technology Readiness Levels for Machine Learning Systems

The development and deployment of machine learning (ML) systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. The lack of diligence can lead to technical debt, scope creep and misaligned objectives, model misuse and failures, and expensive consequences. Engineering systems, on the other hand, follow well-defined processes and testing standards to streamline development for high-quality, reliable results. The extreme is spacecraft systems, where mission critical measures and robustness are ingrained in the development process. Drawing on experience in both spacecraft engineering and ML (from research through product across domain areas), we have developed a proven systems engineering approach for machine learning development and deployment. Our "Machine Learning Technology Readiness Levels" (MLTRL) framework defines a principled process to ensure robust, reliable, and responsible systems while being streamlined for ML workflows, including key distinctions from traditional software engineering. Even more, MLTRL defines a lingua franca for people across teams and organizations to work collaboratively on artificial intelligence and machine learning technologies. Here we describe the framework and elucidate it with several real world use-cases of developing ML methods from basic research through productization and deployment, in areas such as medical diagnostics, consumer computer vision, satellite imagery, and particle physics

Redox, haem and CO in enzymatic catalysis and regulation

The present paper describes general principles of redox catalysis and redox regulation in two diverse systems. The first is microbial metabolism of CO by the Wood–Ljungdahl pathway, which involves the conversion of CO or H2/CO2 into acetyl-CoA, which then serves as a source of ATP and cell carbon. The focus is on two enzymes that make and utilize CO, CODH (carbon monoxide dehydrogenase) and ACS (acetyl-CoA synthase). In this pathway, CODH converts CO2 into CO and ACS generates acetyl-CoA in a reaction involving Ni·CO, methyl-Ni and acetyl-Ni as catalytic intermediates. A 70 Å (1 Å=0.1 nm) channel guides CO, generated at the active site of CODH, to a CO ‘cage’ near the ACS active site to sequester this reactive species and assure its rapid availability to participate in a kinetically coupled reaction with an unstable Ni(I) state that was recently trapped by photolytic, rapid kinetic and spectroscopic studies. The present paper also describes studies of two haem-regulated systems that involve a principle of metabolic regulation interlinking redox, haem and CO. Recent studies with HO2 (haem oxygenase-2), a K+ ion channel (the BK channel) and a nuclear receptor (Rev-Erb) demonstrate that this mode of regulation involves a thiol–disulfide redox switch that regulates haem binding and that gas signalling molecules (CO and NO) modulate the effect of haem.National Institutes of Health (U.S.) (NIH grant GM69857)National Institutes of Health (U.S.) (NIH grant GM39451)National Institutes of Health (U.S.) (NIH grant HL 102662)National Institutes of Health (U.S.) (NIH grant GM65440)National Institutes of Health (U.S.) (NIH grant GM48242)National Institutes of Health (U.S.) (NIH grant Y1-GM- 1104)National Institutes of Health (U.S.) (NIH grant GM065318)National Institutes of Health (U.S.) (NIH grant AG027349)National Science Foundation (U.S.) (grant number CHE-0745353)United States. Dept. of Energy. Office of Biological and Environmental ResearchHoward Hughes Medical Institute (Investigator

Distributive politics and regional development: assessing the territorial distribution of Turkey’s public investment

Turkey is often perceived as a country with low bureaucratic capacity and prone to political manipulation and ‘pork-barrel’. This article tests whether this is the case, by analysing the extent to which politics, rather than equity and efficiency criteria, have determined the geographical allocation of public investment across the 81 provinces of Turkey between 2005 and 2012. The results show that although the Turkish government has indeed channelled public expenditures to reward its core constituencies, socioeconomic factors remained the most relevant predictors of investment. Moreover, in contrast to official regional development policy principles, we uncover the concentration of public investment in areas with comparatively higher levels of development. We interpret this as the state bureaucracy’s intentional strategy of focussing on efficiency by concentrating resources on ‘the better off among the most in need’

Examination Of The Teacher Self-Efficacy Of Pre-Service Biology And Science Teachers In Terms Of Different Variables

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Incidence and possible sources of Tomato spotted wilt virus in tobacco grown in Denizli Province, Turkey

Tomato spotted wilt virus (TSWV) is economically prominent disease for its impact on tobacco {Nicotiana tabacum L.) production worldwide. An increase of the incidence of symptoms typical ofTSWV has been observed in tobacco production areas in Denizli province of Turkey where tobacco is significantly grown. Surveys were conducted to determine the prevalence status of TSWV in tobacco cultivars and its possible sources of infections in four tobacco growing districts of Denizli province. A total of 501 plant samples from field-grown tobaccos, weeds, potential intermediate hosts, seedlings and seeds were collected during 2019 and tested by DAS-ELISA. Of these plants, 243 belong to 55 dififerent weed species from 26 dififerent families with intermediate host potential. Throughout the study, 40 crop plant samples which could be intermediate hosts and 39 tobacco seed samples were also taken for testing. Adult thrips specimens were picked up from the fields and brought to the laboratory for preparations. Four vector virus species were detected when adult thrips individuals were diagnosed: Thrips tabaci Lindeman (Thysanoptera: Thripidae), Franklimella occidentals (Pergande) (Thysanoptera: Thripidae), Aeolothrips intermedius Bagnall (Thysanoptera: Aeolothripidae) and Thrips major Uzel (Thysanoptera: Thripidae). Of the 179 tobaccos sampled, 31.2% was positive; besides, of 243 weeds tested 10 were found to be infected. Echinochloa crus-galli and Tordylium apulum were determined to be new host recordings for TSWV infection. Only one tomato plant from the crop plants as intermediate hosts was infected. Cucumber mosaic virus (CMV), Alfalfa mosaic virus (AMV) and Potato virus Y (PVY) was also confirmed in tobacco fields © Articles by the authors; UASVM, Cluj-Napoca, Romania. The journal allows the author(s) to hold the copyright/to retain publishing rights without restrictionThis work was supported by Aegean Exporter's Association