Planar lattice gases with nearest-neighbour exclusion

We discuss the hard-hexagon and hard-square problems, as well as the corresponding problem on the honeycomb lattice. The case when the activity is unity is of interest to combinatorialists, being the problem of counting binary matrices with no two adjacent 1's. For this case we use the powerful corner transfer matrix method to numerically evaluate the partition function per site, density and some near-neighbour correlations to high accuracy. In particular for the square lattice we obtain the partition function per site to 43 decimal places.Comment: 16 pages, 2 built-in Latex figures, 4 table

Sustainable synthesis of enantiopure fluorolactam derivatives by a selective direct fluorination – amidase strategy

Pharmaceutically important chiral fluorolactam derivatives bearing a fluorine atom at a stereogenic centre were synthesized by a route involving copper catalyzed selective direct fluorination using fluorine gas for the construction of the key C–F bond and a biochemical amidase process for the crucial asymmetric cyclisation stage. A comparison of process green metrics with reported palladium catalyzed enantioselective fluorination methodology shows the fluorination-amidase route to be very efficient and more suitable for scale-up

Quantum information processing in bosonic lattices

We consider a class of models of self-interacting bosons hopping on a lattice. We show that properly tailored space-temporal coherent control of the single-body coupling parameters allows for universal quantum computation in a given sector of the global Fock space. This general strategy for encoded universality in bosonic systems has in principle several candidates for physical implementation.Comment: 4 pages, 2 figs, RevTeX 4; updated to the published versio

Magnetization process of the spin-1/2 XXZ models on square and cubic lattices

The magnetization process of the spin-1/2 antiferromagnetic XXZ model with Ising-like anisotropy in the ground state is investigated. We show numerically that the Ising-like XXZ models on square and cubic lattices show a first-order phase transition at some critical magnetic field. We estimate the value of the critical field and the magnetization jump on the basis of the Maxwell construction. The magnetization jump in the Ising-limit is investigated by means of perturbation theory. Based on our numerical results, we briefly discuss the phase diagram of the extended Bose-Hubbard model in the hard-core limit.Comment: 13 pages, RevTex, 7 PostScript figures, to appear in Phys.Rev.

Positive impact of pre-stroke surgery on survival following transient focal ischemia in hypertensive rats

We describe a positive influence of pre-stroke surgery on recovery and survival in a commonly used experimental stroke model. Two groups of male, stroke-prone spontaneously hypertensive rats (SHRSPs) underwent transient middle cerebral artery occlusion (tMCAO). Group 1 underwent the procedure without any prior intervention whilst group 2 had an additional general anaesthetic 6 days prior to tMCAO for a cranial burrhole and durotomy. Post-stroke recovery was assessed using a 32 point neurological deficit score and tapered beam walk and infarct volume determined from haematoxylin–eosin stained sections. In group 2 survival was 92% (n = 12) versus 67% in group 1 (n = 18). In addition, post-tMCAO associated weight loss was significantly reduced in group 2. There was no significant difference between the two groups in experimental outcomes: infarct volume (Group 1 317 ± 18.6 mm<sup>3</sup> versus Group 2 332 ± 20.4 mm<sup>3</sup>), and serial (day 0–14 post-tMCAO) neurological deficit scores and tapered-beam walk test. Drilling a cranial burrhole under general anaesthesia prior to tMCAO in SHRSP reduced mortality and gave rise to infarct volumes and neurological deficits similar to those recorded in surviving Group 1 animals. This methodological refinement has significant implications for animal welfare and group sizes required for intervention studies

Pressure Induced Change in the Magnetic Modulation of CeRhIn5

We report the results of a high pressure neutron diffraction study of the heavy fermion compound CeRhIn5 down to 1.8 K. CeRhIn5 is known to order magnetically below 3.8 K with an incommensurate structure. The application of hydrostatic pressure up to 8.6 kbar produces no change in the magnetic wave vector qm. At 10 kbar of pressure however, a sudden change in the magnetic structure occurs. Although the magnetic transition temperature remains the same, qm increases from (0.5, 0.5, 0.298) to (0.5, 0.5, 0.396). This change in the magnetic modulation may be the outcome of a change in the electronic character of this material at 10 kbar.Comment: 4 pages, 3 figures include

AI-Assisted Cotton Grading: Active and Semi-Supervised Learning to Reduce the Image-Labelling Burden

The assessment of food and industrial crops during harvesting is important to determine the quality and downstream processing requirements, which in turn affect their market value. While machine learning models have been developed for this purpose, their deployment is hindered by the high cost of labelling the crop images to provide data for model training. This study examines the capabilities of semi-supervised and active learning to minimise effort when labelling cotton lint samples while maintaining high classification accuracy. Random forest classification models were developed using supervised learning, semi-supervised learning, and active learning to determine Egyptian cotton grade. Compared to supervised learning (80.20-82.66%) and semi-supervised learning (81.39-85.26%), active learning models were able to achieve higher accuracy (82.85-85.33%) with up to 46.4% reduction in the volume of labelled data required. The primary obstacle when using machine learning for Egyptian cotton grading is the time required for labelling cotton lint samples. However, by applying active learning, this study successfully decreased the time needed from 422.5 to 177.5 min. The findings of this study demonstrate that active learning is a promising approach for developing accurate and efficient machine learning models for grading food and industrial crops

An image processing and machine learning solution to automate Egyptian cotton lint grading

Egyptian cotton is one of the most important commodities for the Egyptian economy and is renowned globally for its quality, which is largely assessed and graded by manual inspection. This grading has several drawbacks, including significant labor requirements, low inspection efficiency, and influence from inspection conditions such as light and human subjectivity. This work proposes a low-cost solution to replace manual inspection with classification models to grade Egyptian cotton lint using images captured by a charge-coupled device camera. While this method has been evaluated for classifying US and Chinese upland cotton staples, it has not been tested on Egyptian cotton, which has unique characteristics and grading requirements. Furthermore, the methodology to develop these classification models has been expanded to include image processing techniques that remove the influence of trash on color measurements and extract features that capture the intra-sample variance of the cotton samples. Three different supervised machine learning algorithms were evaluated: artificial neural networks; random forest; and support vector machines. The highest accuracy models (82.13–90.21%) used a random forest algorithm. The models’ accuracy was limited by the human error associated with labeling the cotton samples used to develop the classification models. Unsupervised machine learning methods, including k-means clustering, hierarchical clustering, and Gaussian mixture models, were used to indicate where labeling errors occurred

Synthesis and characterisation of novel fluorescent imides by a rhodium(III)-catalysed C-H activation/annulation cascade

Regioselective rhodium(III)-catalysed C-H activation/annulation of O-pivaloyl benzoylhydroxamates with ortho-alkynylbenzoate esters facilitates the rapid preparation of a novel class of fluorophores based on the isoindolo[2,1-b]isoquinoline-5,7-dione core. The photophysical, electrochemical and coordination properties of these novel structures are investigated

Decay of the metastable phase in d=1 and d=2 Ising models

We calculate perturbatively the tunneling decay rate $\Gamma$ of the metastable phase in the quantum d=1 Ising model in a skew magnetic field near the coexistence line $0<h_{x}<1, h_{z}\to -0$ at T=0. It is shown that $\Gamma$ oscillates in the magnetic field $h_{z}$ due to discreteness of the excitation energy spectrum. After mapping of the obtained results onto the extreme anisotropic d=2 Ising model at $T<T_c$, we verify in the latter model the droplet theory predictions for the free energy analytically continued to the metastable phase. We find also evidence for the discrete-lattice corrections in this metastable phase free energy.Comment: 4 pages, REVTe