Circular-Polarization Dependent Cyclotron Resonance in Large-Area Graphene in Ultrahigh Magnetic Fields

Using ultrahigh magnetic fields up to 170 T and polarized midinfrared radiation with tunable wavelengths from 9.22 to 10.67 um, we studied cyclotron resonance in large-area graphene grown by chemical vapor deposition. Circular-polarization dependent studies reveal strong p-type doping for as-grown graphene, and the dependence of the cyclotron resonance on radiation wavelength allows for a determination of the Fermi energy. Thermal annealing shifts the Fermi energy to near the Dirac point, resulting in the simultaneous appearance of hole and electron cyclotron resonance in the magnetic quantum limit, even though the sample is still p-type, due to graphene's linear dispersion and unique Landau level structure. These high-field studies therefore allow for a clear identification of cyclotron resonance features in large-area, low-mobility graphene samples.Comment: 9 pages, 3 figure

Identifying discrete behavioural types: A re-analysis of public goods game contributions by hierarchical clustering

We propose a framework for identifying discrete behavioural types in experimental data. We re-analyse data from six previous studies of public goods voluntary contributions games. Using hierarchical clustering analysis, we construct a typology of behaviour based on a simi- larity measure between strategies. We identify four types with distinct sterotypical behaviours, which together account for about 90% of participants. Compared to previous approaches, our method produces a classification in which different types are more clearly distinguished in terms of strategic behaviour and the resulting economic implications

Reciprocity and the tragedies of maintaining and providing the commons

Social cooperation often requires collectively beneficial but individually costly restraint to maintain a public good, or it needs costly generosity to create one. Status quo effects predict that maintaining a public good is easier than providing a new one. Here, we show experimentally and with simulations that even under identical incentives, low levels of cooperation (the ‘tragedy of the commons’) are systematically more likely in maintenance than provision. Across three series of experiments, we find that strong and weak positive reciprocity, known to be fundamental tendencies underpinning human cooperation, are substantially diminished under maintenance compared with provision. As we show in a fourth experiment, the opposite holds for negative reciprocity (‘punishment’). Our findings suggest that incentives to avoid the ‘tragedy of the commons’ need to contend with dilemma specific reciprocity

Unlocking the power of nanomedicine: the future of nutraceuticals in oncology treatment

Cancer, an intricate and multifaceted disease, is characterized by the uncontrolled proliferation of cells that can lead to serious health complications and ultimately death. Conventional therapeutic strategies mainly target rapidly dividing cancer cells, but often indiscriminately harm healthy cells in the process. As a result, there is a growing interest in exploring novel therapies that are both effective and less toxic to normal cells. Herbs have long been used as natural remedies for various diseases and conditions. Some herbal compounds exhibit potent anti-cancer properties, making them potential candidates for nutraceutical-based treatments. However, despite their promising efficacy, there are considerable limitations in utilizing herbal preparations due to their poor solubility, low bioavailability, rapid metabolism and excretion, as well as potential interference with other medications. Nanotechnology offers a unique platform to overcome these challenges by encapsulating herbal compounds within nanoparticles. This approach not only increases solubility and stability but also enhances the cellular uptake of nutraceuticals, allowing for controlled and targeted delivery of therapeutic agents directly at tumor sites. By harnessing the power of nanotechnology-enabled therapy, this new frontier in cancer treatment presents an opportunity to minimize toxicity while maximizing efficacy. In conclusion, this manuscript provides compelling evidence for integrating nanotechnology with nutraceuticals derived from herbal sources to optimize cancer therapy outcomes. We explore the roadblocks associated with traditional herbal treatments and demonstrate how nanotechnology can help circumvent these issues, paving the way for safer and more effective cancer interventions in future oncological practice.</jats:p

Programmable antivirals targeting critical conserved viral RNA secondary structures from influenza A virus and SARS-CoV-2

Influenza A virus’s (IAV’s) frequent genetic changes challenge vaccine strategies and engender resistance to current drugs. We sought to identify conserved and essential RNA secondary structures within IAV’s genome that are predicted to have greater constraints on mutation in response to therapeutic targeting. We identified and genetically validated an RNA structure (packaging stem–loop 2 (PSL2)) that mediates in vitro packaging and in vivo disease and is conserved across all known IAV isolates. A PSL2-targeting locked nucleic acid (LNA), administered 3 d after, or 14 d before, a lethal IAV inoculum provided 100% survival in mice, led to the development of strong immunity to rechallenge with a tenfold lethal inoculum, evaded attempts to select for resistance and retained full potency against neuraminidase inhibitor-resistant virus. Use of an analogous approach to target SARS-CoV-2, prophylactic administration of LNAs specific for highly conserved RNA structures in the viral genome, protected hamsters from efficient transmission of the SARS-CoV-2 USA_WA1/2020 variant. These findings highlight the potential applicability of this approach to any virus of interest via a process we term ‘programmable antivirals’, with implications for antiviral prophylaxis and post-exposure therapy

Lattice Dynamics of II-VI materials using adiabatic bond charge model

We extend the adiabatic bond charge model, originally developed for group IV semiconductors and III-V compounds, to study phonons in more ionic II-VI compounds with a zincblende structure. Phonon spectra, density of states and specific heats are calculated for six II-VI compounds and compared with both experimental data and the results of other models. We show that the 6-parameter bond charge model gives a good description of the lattice dynamics of these materials. We also discuss trends in the parameters with respect to the ionicity and metallicity of these compounds.Comment: 16 pages of RevTex with 3 figures submitted as a uuencode compressed tar fil

Renal Cell Carcinoma with Unusual Metastasis to the Small Intestine Manifesting as Extensive Polyposis: Successful Management with Intraoperative Therapeutic Endoscopy

We present here a rare clinical case of a 53-year-old gentleman with metastasis from renal cell carcinoma (RCC) to the small intestine presenting with extensive polyposis and massive gastrointestinal bleeding which was successfully managed with intraoperative endoscopic polypectomy and segmental small bowel resection. The patient presented with melena 2 weeks after right nephrectomy for RCC. Capsule endoscopy found extensive polyposis throughout the small bowel, and the histological features confirmed the diagnosis of metastatic RCC. The patient eventually underwent laparotomy with intraoperative endoscopy of the entire small bowel. Most of the polyps were removed by snare polypectomy. Three segments of the small bowel with extensive transmural involvement had to be resected with primary anastomosis. In the 2 months following his surgery, the patient had no further evidence of gastrointestinal bleeding. The decision of meticulously removing close to 100 polyps by intraoperative endoscopy prevented the patient from requiring total small bowel resection and lifelong dependence on parenteral nutrition. In conclusion, gastrointestinal bleeding in a patient with known RCC should always trigger full gastrointestinal work-up including capsule endoscopy and, if necessary, double balloon enteroscopy

Efficient Learning and Feature Selection in High Dimensional Regression

We present a novel algorithm for efficient learning and feature selection in high-dimensional regression problems. We arrive at this model through a modification of the standard regression model, enabling us to derive a probabilistic version of the well-known statistical regression technique of backfitting. Using the expectation-maximization algorithm, along with variational approximation methods to overcome intractability, we extend our algorithm to include automatic relevance detection of the input features. This variational Bayesian least squares (VBLS) approach retains its simplicity as a linear model, but offers a novel statistically robust black-box approach to generalized linear regression with high-dimensional inputs. It can be easily extended to nonlinear regression and classification problems. In particular, we derive the framework of sparse Bayesian learning, the relevance vector machine, with VBLS at its core, offering significant computational and robustness advantages for this class of methods. The iterative nature of VBLS makes it most suitable for real-time incremental learning, which is crucial especially in the application domain of robotics, brain-machine interfaces, and neural prosthetics, where real-time learning of models for control is needed. We evaluate our algorithm on synthetic and neurophysiological data sets, as well as on standard regression and classification benchmark data sets, comparing it with other competitive statistical approaches and demonstrating its suitability as a drop-in replacement for other generalized linear regression techniques