Electron Glass Dynamics

Examples of glasses are abundant, yet it remains one of the phases of matter whose understanding is very elusive. In recent years, remarkable experiments have been performed on the dynamical aspects of glasses. Electron glasses offer a particularly good example of the 'trademarks' of glassy behavior, such as aging and slow relaxations. In this work we review the experimental literature on electron glasses, as well as the local mean-field theoretical framework put forward in recent years to understand some of these results. We also present novel theoretical results explaining the periodic aging experiment.Comment: Invited review to appear in Annual Review of Condensed Matter Physic

Many-body localization in a quantum simulator with programmable random disorder

When a system thermalizes it loses all local memory of its initial conditions. This is a general feature of open systems and is well described by equilibrium statistical mechanics. Even within a closed (or reversible) quantum system, where unitary time evolution retains all information about its initial state, subsystems can still thermalize using the rest of the system as an effective heat bath. Exceptions to quantum thermalization have been predicted and observed, but typically require inherent symmetries or noninteracting particles in the presence of static disorder. The prediction of many-body localization (MBL), in which disordered quantum systems can fail to thermalize in spite of strong interactions and high excitation energy, was therefore surprising and has attracted considerable theoretical attention. Here we experimentally generate MBL states by applying an Ising Hamiltonian with long-range interactions and programmably random disorder to ten spins initialized far from equilibrium. We observe the essential signatures of MBL: memory retention of the initial state, a Poissonian distribution of energy level spacings, and entanglement growth in the system at long times. Our platform can be scaled to higher numbers of spins, where detailed modeling of MBL becomes impossible due to the complexity of representing such entangled quantum states. Moreover, the high degree of control in our experiment may guide the use of MBL states as potential quantum memories in naturally disordered quantum systems.Comment: 9 pages, 9 figure

Development of a liquid-liquid extraction method of resveratrol from cell culture media using solubility parameters

YesThe extraction of bioactive compounds, produced by plant cell cultures, directly from their culture medium, which contains other by-products, is a great challenge. Resveratrol extraction from its grapevine cell cultures is considered here as an example to improve the extraction processes from plant cell cultures using solubility parameters. Successive liquid-liquid extraction (LLE) processes were exploited to extract resveratrol from the culture medium with an extraction ratio approaching 100%, high selectivity and minimum amounts of solvents. The calculations of partition coefficients as a function of solubility parameters demonstrated that benzyl benzoate is the most suitable intermediate solvent to extract resveratrol from its aqueous medium. The calculations also illustrated the high ability of methanol and ethanol to extract resveratrol from benzyl benzoate. The physicochemical properties of benzyl benzoate and processing conditions were exploited to separate it from aqueous media and organic solvents. The agitation method, component ratios and extraction time were studied to maximize the extraction yield. Under the best studied conditions, the recovery of resveratrol from different culture media approached ∼100% with a selectivity of ∼92%. Ultimately, the improved extraction processes of resveratrol are markedly efficient, selective, rapid and economical.Mohammad Amin Mohammad gratefully acknowledges CARA (The Council for At-Risk Academics, Stephen Wordsworth and Ryan Mundy) for providing the financial support for an academic fellowship

Non-Chemical Stressors and Cumulative Risk Assessment: An Overview of Current Initiatives and Potential Air Pollutant Interactions

Regulatory agencies are under increased pressure to consider broader public health concerns that extend to multiple pollutant exposures, multiple exposure pathways, and vulnerable populations. Specifically, cumulative risk assessment initiatives have stressed the importance of considering both chemical and non-chemical stressors, such as socioeconomic status (SES) and related psychosocial stress, in evaluating health risks. The integration of non-chemical stressors into a cumulative risk assessment framework has been largely driven by evidence of health disparities across different segments of society that may also bear a disproportionate risk from chemical exposures. This review will discuss current efforts to advance the field of cumulative risk assessment, highlighting some of the major challenges, discussed within the construct of the traditional risk assessment paradigm. Additionally, we present a summary of studies of potential interactions between social stressors and air pollutants on health as an example of current research that supports the incorporation of non-chemical stressors into risk assessment. The results from these studies, while suggestive of possible interactions, are mixed and hindered by inconsistent application of social stress indicators. Overall, while there have been significant advances, further developments across all of the risk assessment stages (i.e., hazard identification, exposure assessment, dose-response, and risk characterization) are necessary to provide a scientific basis for regulatory actions and effective community interventions, particularly when considering non-chemical stressors. A better understanding of the biological underpinnings of social stress on disease and implications for chemical-based dose-response relationships is needed. Furthermore, when considering non-chemical stressors, an appropriate metric, or series of metrics, for risk characterization is also needed. Cumulative risk assessment research will benefit from coordination of information from several different scientific disciplines, including, for example, toxicology, epidemiology, nutrition, neurotoxicology, and the social sciences

Diagnosing mucopolysaccharidosis IVA

Mucopolysaccharidosis IVA (MPS IVA; Morquio A syndrome) is an autosomal recessive lysosomal storage disorder resulting from a deficiency of N-acetylgalactosamine-6-sulfate sulfatase (GALNS) activity. Diagnosis can be challenging and requires agreement of clinical, radiographic, and laboratory findings. A group of biochemical genetics laboratory directors and clinicians involved in the diagnosis of MPS IVA, convened by BioMarin Pharmaceutical Inc., met to develop recommendations for diagnosis. The following conclusions were reached. Due to the wide variation and subtleties of radiographic findings, imaging of multiple body regions is recommended. Urinary glycosaminoglycan analysis is particularly problematic for MPS IVA and it is strongly recommended to proceed to enzyme activity testing even if urine appears normal when there is clinical suspicion of MPS IVA. Enzyme activity testing of GALNS is essential in diagnosing MPS IVA. Additional analyses to confirm sample integrity and rule out MPS IVB, multiple sulfatase deficiency, and mucolipidoses types II/III are critical as part of enzyme activity testing. Leukocytes or cultured dermal fibroblasts are strongly recommended for enzyme activity testing to confirm screening results. Molecular testing may also be used to confirm the diagnosis in many patients. However, two known or probable causative mutations may not be identified in all cases of MPS IVA. A diagnostic testing algorithm is presented which attempts to streamline this complex testing process

Sustainable supply chain management towards disruption and organizational ambidexterity:A data driven analysis

Balancing sustainability and disruption of supply chains requires organizational ambidexterity. Sustainable supply chains prioritize efficiency and economies of scale and may not have sufficient redundancy to withstand disruptive events. There is a developing body of literature that attempts to reconcile these two aspects. This study gives a data-driven literature review of sustainable supply chain management trends toward ambidexterity and disruption. The critical review reveals temporal trends and geographic distribution of literature. A hybrid of data-driven analysis approach based on content and bibliometric analyses, fuzzy Delphi method, entropy weight method, and fuzzy decision-making trial and evaluation laboratory is used on 273 keywords and 22 indicators obtained based on the experts’ evaluation. The most important indicators are identified as supply chain agility, supply chain coordination, supply chain finance, supply chain flexibility, supply chain resilience, and sustainability. The regions show different tendencies compared with others. Asia and Oceania, Latin America and the Caribbean, and Africa are the regions needs improvement, while Europe and North America show distinct apprehensions on supply chain network design. The main contribution of this review is the identification of the knowledge frontier, which then leads to a discussion of prospects for future studies and practical industry implementation

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe