Adiabatic two-qubit gates in capacitively coupled quantum dot hybrid qubits

The ability to tune qubits to flat points in their energy dispersions ("sweet spots") is an important tool for mitigating the effects of charge noise and dephasing in solid-state devices. However, the number of derivatives that must be simultaneously set to zero grows exponentially with the number of coupled qubits, making the task untenable for as few as two qubits. This is a particular problem for adiabatic gates, due to their slower speeds. Here, we propose an adiabatic two-qubit gate for quantum dot hybrid qubits, based on the tunable, electrostatic coupling between distinct charge configurations. We confirm the absence of a conventional sweet spot, but show that controlled-Z (CZ) gates can nonetheless be optimized to have fidelities of $\sim$99% for a typical level of quasistatic charge noise ($\sigma_\varepsilon$$\simeq$1 $\mu$eV). We then develop the concept of a dynamical sweet spot (DSS), for which the time-averaged energy derivatives are set to zero, and identify a simple pulse sequence that achieves an approximate DSS for a CZ gate, with a 5$\times$ improvement in the fidelity. We observe that the results depend on the number of tunable parameters in the pulse sequence, and speculate that a more elaborate sequence could potentially attain a true DSS.Comment: 14 pages, 9 figure

Choices and trade-offs in inference with infectious disease models.

Inference using mathematical models of infectious disease dynamics can be an invaluable tool for the interpretation and analysis of epidemiological data. However, researchers wishing to use this tool are faced with a choice of models and model types, simulation methods, inference methods and software packages. Given the multitude of options, it can be challenging to decide on the best approach. Here, we delineate the choices and trade-offs involved in deciding on an approach for inference, and discuss aspects that might inform this decision. We provide examples of inference with a dataset of influenza cases using the R packages pomp and rbi

Comparative Analysis and Fusion of MRI and PET Images based on Wavelets for Clinical Diagnosis

Nowadays, Medical imaging modalities like Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), Single Photon Emission Tomography (SPECT), and Computed Tomography (CT) play a crucial role in clinical diagnosis and treatment planning. The images obtained from each of these modalities contain complementary information of the organ imaged. Image fusion algorithms are employed to bring all of this disparate information together into a single image, allowing doctors to diagnose disorders quickly. This paper proposes a novel technique for the fusion of MRI and PET images based on YUV color space and wavelet transform. Quality assessment based on entropy showed that the method can achieve promising results for medical image fusion. The paper has done a comparative analysis of the fusion of MRI and PET images using different wavelet families at various decomposition levels for the detection of brain tumors as well as Alzheimer’s disease. The quality assessment and visual analysis showed that the Dmey wavelet at decomposition level 3 is optimum for the fusion of MRI and PET images. This paper also compared the results of several fusion rules such as average, maximum, and minimum, finding that the maximum fusion rule outperformed the other two

ENSO teleconnections in terms of non-NAO and NAO atmospheric variability

The validity of the long-held understanding or assumption that El Niño-Southern Oscillation (ENSO) has a remote influence on the North Atlantic Oscillation (NAO) in the January–February–March (JFM) months has been questioned recently. We examine this claim further using atmospheric data filtered to separate the variability orthogonal and parallel to NAO. This decomposition of the atmospheric fields is based on the Principal Component/Empirical Orthogonal Function method whereby the leading mode of the sea-level pressure in the North Atlantic sector is recognised as the NAO, while the remaining variability is orthogonal (unrelated) to NAO. Composite analyses indicate that ENSO has statistically significant links with both the non-NAO and NAO variability at various atmospheric levels. Additional bootstrap tests carried out to quantify the uncertainty and statistical significance confirm these relationships. Consistent with previous studies, we find that an ENSO teleconnection in the NAO-related variability is characterised by lower-stratospheric eddy heat flux anomalies (related to the vertical propagation of planetary waves) which appear in November–December and strengthen through JFM. Under El Niño (La Niña), there is constructive (destructive) interference of anomalous eddy heat flux with the climatological pattern, enhancing (reducing) fluxes over the northern Pacific and Barents Sea areas. We further show that the teleconnection of extreme El Niño is essentially a non-NAO phenomenon. Some non-linearity of the teleconnections is suggested, with El Niño including more NAO-related variability than La Niña, but the statistical significance is degraded due to weaker signals and smaller sample sizes after the partitioning. Our findings have implications for the general understanding of the nature of ENSO teleconnections over the North Atlantic, as well as for refining methods to characterise and evaluate them in models.publishedVersio

A Fuzzy Classification Framework to Identify Equivalent Atoms in Complex Materials and Molecules

The nature of an atom in a bonded structure -- such as in molecules, in nanoparticles or solids, at surfaces or interfaces -- depends on its local atomic environment. In atomic-scale modeling and simulation, identifying groups of atoms with equivalent environments is a frequent task, to gain an understanding of the material function, to interpret experimental results or to simply restrict demanding first-principles calculations. While routine, this task can often be challenging for complex molecules or non-ideal materials with breaks of symmetries or long-range order. To automatize this task, we here present a general machine-learning framework to identify groups of (nearly) equivalent atoms. The initial classification rests on the representation of the local atomic environment through a high-dimensional smooth overlap of atomic positions (SOAP) vector. Recognizing that not least thermal vibrations may lead to deviations from ideal positions, we then achieve a fuzzy classification by mean-shift clustering within a low-dimensional embedded representation of the SOAP points as obtained through multidimensional scaling. The performance of this classification framework is demonstrated for simple aromatic molecules and crystalline Pd surface examples.Comment: Accepted manuscript in Journal of Chemical Physics. Repositories of the package (DECAF): DOI:10.17617/3.U7VKBM or https://gitlab.mpcdf.mpg.de/klai/deca

An archetypical analysis of chief executive officers in the mining sector according to their remuneration and company performance: a resource based view

The growth in the mining sector post 1994 saw many CEO s enjoy exorbitant levels of financial prosperity particularly in relation to th e mining workforce . The pay disparity between the remuneration of CEO s and the average worker contributed to instability and labour unrest. While there has been extensive research conducted on the relationship between CEO remuneration and company performance, questions around the justification of exorbitant CEO remuneration levels have persisted. One of the shortcomings of these studies have been understanding company performance as limited to financial indicators. For this reason, Resource - Based theory was used in this study to focus on CEOs as tangible, heterogeneous and immobile assets, who could influence company performance by creating a firm’s competitive advantage. In order to investigate this, a mixed - method research design was utilised to ascertain the relationship between CEO remune ration and company performance. The data for the quantitative study was collected using an archival method by sourcing secondary data obtained from the sampled companie s’ annual integrated reports. Statistical tests were performed to test the relationsh ip between CEO remuneration and company performance of mining companies listed on the JSE over the period of 2014 to 2018. This was followed by the qualitative thematic analysis which utilised online information published about four CEOs sampled according to their pay/performance relationships (namely high earning/high performing; high earning/low performing; low earning/high performing and low earning/low performing). The VRIO framework was utilised in conjunction with the thematic analysis to assess the extent to which each of the selected CEOs could be identified as valuable, rare, inimitable and organised. Finally, t he demographic characteristics and leadership attributes of these CEOs were collectiv ely aligned to particular l eadership archetype s. This study found that despite company performance levels experiencing negative growth and volatility, CEO remuneration remained stable and experienced positive growth throughout the period . The qualitative analysis and the application of the VRIO framework wa s conducted in order to explor e reasons why this disparity may continue to exist. The analysis of the differences in demographic characteristics and leadership attributes between these four CEOs provided a possible j ustification for the disparity in t he levels of remuneration. It was found that some CEOs high levels of remuneration could be justified by virtue of their well - developed leadership skills. In particular CEOs need softer skills (such as communication, openness, relationship - building and stakeholder engagement) and to draw on the communicator, builder and coach archetypes in order to create a sustained competitive advantage within companies

An archetypical analysis of chief executive officers in the mining sector according to their remuneration and company performance: a resource based view

The growth in the mining sector post 1994 saw many CEO s enjoy exorbitant levels of financial prosperity particularly in relation to th e mining workforce . The pay disparity between the remuneration of CEO s and the average worker contributed to instability and labour unrest. While there has been extensive research conducted on the relationship between CEO remuneration and company performance, questions around the justification of exorbitant CEO remuneration levels have persisted. One of the shortcomings of these studies have been understanding company performance as limited to financial indicators. For this reason, Resource - Based theory was used in this study to focus on CEOs as tangible, heterogeneous and immobile assets, who could influence company performance by creating a firm’s competitive advantage. In order to investigate this, a mixed - method research design was utilised to ascertain the relationship between CEO remune ration and company performance. The data for the quantitative study was collected using an archival method by sourcing secondary data obtained from the sampled companie s’ annual integrated reports. Statistical tests were performed to test the relationsh ip between CEO remuneration and company performance of mining companies listed on the JSE over the period of 2014 to 2018. This was followed by the qualitative thematic analysis which utilised online information published about four CEOs sampled according to their pay/performance relationships (namely high earning/high performing; high earning/low performing; low earning/high performing and low earning/low performing). The VRIO framework was utilised in conjunction with the thematic analysis to assess the extent to which each of the selected CEOs could be identified as valuable, rare, inimitable and organised. Finally, t he demographic characteristics and leadership attributes of these CEOs were collectiv ely aligned to particular l eadership archetype s. This study found that despite company performance levels experiencing negative growth and volatility, CEO remuneration remained stable and experienced positive growth throughout the period . The qualitative analysis and the application of the VRIO framework wa s conducted in order to explor e reasons why this disparity may continue to exist. The analysis of the differences in demographic characteristics and leadership attributes between these four CEOs provided a possible j ustification for the disparity in t he levels of remuneration. It was found that some CEOs high levels of remuneration could be justified by virtue of their well - developed leadership skills. In particular CEOs need softer skills (such as communication, openness, relationship - building and stakeholder engagement) and to draw on the communicator, builder and coach archetypes in order to create a sustained competitive advantage within companies

The application of optical coherence tomography to image subsurface tissue structure of Antarctic krill Euphausia superba

Many small open ocean animals, such as Antarctic krill, are an important part of marine ecosystems. To discover what will happen to animals such as krill in a changing ocean, experiments are run in aquaria where conditions can be controlled to simulate water characteristics predicted to occur in the future. The response of individual animals to changing water conditions can be hard to observe, and with current observation techniques it is very difficult to follow the progress of an individual animal through its life. Optical coherence tomography (OCT) is an optical imaging technique that allows images at high resolution to be obtained from depths up to a few millimeters inside biological specimens. It is compatible with in vivo imaging and can be used repeatedly on the same specimens. In this work, we show how OCT may be applied to post mortem krill samples and how important physiological data such as shell thickness and estimates of organ volume can be obtained. Using OCT we find an average value for the thickness of krill exoskeleton to be (30±4) µm along a 1 cm length of the animal body. We also show that the technique may be used to provide detailed imagery of the internal structure of a pleopod joint and provide an estimate for the heart volume of (0.73±0.03) mm3

Edge selective gas detection using Langmuir films of graphene platelets

Recent advances in large-scale production of graphene have led to the availability of solution processable platelets at the commercial scale. Langmuir-Schaefer (L-S) deposition is a scalable process for forming a percolating film of graphene platelets which can be used for electronic gas sensing. Here, we demonstrate the use of this deposition method to produce functional gas sensors, using a chemiresistor structure from commercially-available graphene dispersions. The sensitivity of the devices and repeatability of the electrical response upon gas exposure has been characterized. Raman spectroscopy and Kelvin probe force microscopy (KPFM) show doping of the basal plane using ammonia (n-dopant) and acetone (p-dopant). The resistive signal is increased upon exposure to both gases showing that sensing originates from the change in contact resistance between nanosheets. We demonstrate that Arrhenius fitting of the desorption response potentially allows measurements of the desorption process activation energies for gas molecules adsorbed onto the graphene nanosheets

Comparison of Home-Blenderized Formula and Commercial Enteral Formulas for Gastrostomy Tube-Fed Children: A Retrospective, Prospective Cohort Study.

Background Blenderized gastrostomy tube feedings (BGTFs) consist of pureed table foods and liquids that are administered as enteral tube feedings. Compared to commercial enteral formulas (CEFs), BGTF has been shown to have fewer side effects. Despite these results, apprehensions have been raised about microbial contamination, nutritional deficiencies or surplus, risk of gastrostomy tube (GT) blockages, and lack of consistency in clinical outcomes. The goal of this retrospective, prospective, 18-month-long study is to report the clinical and nutritional outcomes of GT-dependent pediatric patients who attended a multidisciplinary feeding clinic. Methodology After Institutional Review Board (IRB) approval and consent were obtained, 25 children who were receiving tube feeding via G were enrolled in a retrospective, prospective, observational, cohort study from August 2019 to February 2021. A multidisciplinary team was formed, and multivariate logistic regression was performed comparing subjects on BGTF versus CEF, per os diet versus nil per os, CEF versus homemade blenderized tube feeding (HBTF) versus blenderized tube feeding (BTF), and how they compared at the beginning and end of the study. Results The mean age of the patients was 4.4 years (SD ±2.2). Gastroesophageal reflux disease (GERD) and short bowel syndrome (SBS) were the most common comorbid gastrointestinal (GI) conditions. Of the 25 patients enrolled in the study, seven were initially on BGTF, while 14 ended the study on BGTF. There were no statistically significant differences in malnutrition status, feeding intolerance, emergency room visits, hospitalizations, and GT blockages between all different comparison groups when comparing between the CEF versus HBTF versus commercial blenderized tube feeding (CBTF) groups. Of the patients who were in the BGTF group, there was a resolution of vitamin A deficiency, vitamin D deficiency, and anemia (n = 1). In total, two patients had resolved vitamin deficiencies, namely, vitamins A and D. Conclusions When comparing BGTF and CEF, there was no statistically significant difference in outcomes. This study suggests that BGTF is at least equivalent to CEF in clinical outcomes, meaning BGTF should be considered standard nutrition for GT-dependent patients