Honest confidence regions and optimality in high-dimensional precision matrix estimation

We propose methodology for estimation of sparse precision matrices and statistical inference for their low-dimensional parameters in a high-dimensional setting where the number of parameters p can be much larger than the sample size. We show that the novel estimator achieves minimax rates in supremum norm and the low-dimensional components of the estimator have a Gaussian limiting distribution. These results hold uniformly over the class of precision matrices with row sparsity of small order \(\sqrt{n}/\log p\) and spectrum uniformly bounded, under a sub-Gaussian tail assumption on the margins of the true underlying distribution. Consequently, our results lead to uniformly valid confidence regions for low-dimensional parameters of the precision matrix. Thresholding the estimator leads to variable selection without imposing irrepresentability conditions. The performance of the method is demonstrated in a simulation study and on real data.     

The Genetic Heterogeneity among Different Mouse Strains Impacts the Lung Injury Potential of Multiwalled Carbon Nanotubes

Genetic variation constitutes an important variable impacting the susceptibility to inhalable toxic substances and air pollutants, as reflected by epidemiological studies in humans and differences among animal strains. While multiwalled carbon nanotubes (MWCNTs) are capable of causing lung fibrosis in rodents, it is unclear to what extent the genetic variation in different mouse strains influence the outcome. Four inbred mouse strains, including C57Bl/6, Balb/c, NOD/ShiLtJ, and A/J, to test the pro‐fibrogenic effects of a library of MWCNTs in vitro and in vivo are chosen. Ex vivo analysis of IL‐1β production in bone marrow‐derived macrophages (BMDMs) as molecular initiating event (MIE) is performed. The order of cytokine production (Balb/c > A/J > C57Bl/6 > NOD/ShiLtJ) in BMDMs is also duplicated during assessment of IL‐1β production in the bronchoalveolar lavage fluid of the same mouse strains 40 h after oropharyngeal instillation of a representative MWCNT. Animal test after 21 d also confirms a similar hierarchy in TGF‐β1 production and collagen deposition in the lung. Statistical analysis confirms a correlation between IL‐1β production in BMDM and the lung fibrosis. All considered, these data demonstrate that genetic background indeed plays a major role in determining the pro‐fibrogenic response to MWCNTs in the lung.     

Hybrid Nanoscopy of Hybrid Nanomaterials

The combination of complementary techniques to characterize materials at the nanoscale is crucial to gain a more complete picture of their structure, a key step to design and fabricate new materials with improved properties and diverse functions. Here it is shown that correlative atomic force microscopy (AFM) and localization‐based super‐resolution microscopy is a useful tool that provides insight into the structure and emissive properties of fluorescent β‐lactoglobulin (βLG) amyloid‐like fibrils. These hybrid materials are made by functionalization of βLG with organic fluorophores and quantum dots, the latter being relevant for the production of 1D inorganic nanostructures templated by self‐assembling peptides. Simultaneous functionalization of βLG fibers by QD655 and QD525 allows for correlative AFM and two‐color super‐resolution fluorescence imaging of these hybrid materials. These experiments allow the combination of information about the topography and number of filaments that compose a fibril, as well as the emissive properties and nanoscale spatial distribution of the attached fluorophores. This study represents an important step forward in the characterization of multifunctionalized hybrid materials, a key challenge in nanoscience.     

Lateral Magnetically Modulated Multilayers by Combining Ion Implantation and Lithography

The combination of lithography and ion implantation is demonstrated to be a suitable method to prepare lateral multilayers. A laterally, compositionally, and magnetically modulated microscale pattern consisting of alternating Co (1.6 µm wide) and Co‐CoO (2.4 µm wide) lines has been obtained by oxygen ion implantation into a lithographically masked Au‐sandwiched Co thin film. Magnetoresistance along the lines (i.e., current and applied magnetic field are parallel to the lines) reveals an effective positive giant magnetoresistance (GMR) behavior at room temperature. Conversely, anisotropic magnetoresistance and GMR contributions are distinguished at low temperature (i.e., 10 K) since the O‐implanted areas become exchange coupled. This planar GMR is principally ascribed to the spatial modulation of coercivity in a spring‐magnet‐type configuration, which results in 180° Néel extrinsic domain walls at the Co/Co‐CoO interfaces. The versatility, in terms of pattern size, morphology, and composition adjustment, of this method offers a unique route to fabricate planar systems for, among others, spintronic research and applications.     

Healing Effect of Controlled Anti‐Electromigration on Conventional and High‐Tc Superconducting Nanowires

The electromigration process has the potential capability to move atoms one by one when properly controlled. It is therefore an appealing tool to tune the cross section of monoatomic compounds with ultimate resolution or, in the case of polyatomic compounds, to change the stoichiometry with the same atomic precision. As demonstrated here, a combination of electromigration and anti‐electromigration can be used to reversibly displace atoms with a high degree of control. This enables a fine adjustment of the superconducting properties of Al weak links, whereas in Nb the diffusion of atoms leads to a more irreversible process. In a superconductor with a complex unit cell (La_2?x Ce_x CuO₄), the electromigration process acts selectively on the oxygen atoms with no apparent modification of the structure. This allows to adjust the doping of this compound and switch from a superconducting to an insulating state in a nearly reversible fashion. In addition, the conditions needed to replace feedback controlled electromigration by a simpler technique of electropulsing are discussed. These findings have a direct practical application as a method to explore the dependence of the characteristic parameters on the exact oxygen content and pave the way for a reversible control of local properties of nanowires.     

Heavy metal removal from simulated wastewater using electrochemical technology: optimization of copper electrodeposition in a membraneless fluidized bed electrode

Heavy metal removal from industrial wastewaters has been intensively studied, since it is well known that they can cause severe problems to human health and aquatic life, even at very low concentrations. In this work, it was demonstrated that electrodeposition in fluidized bed electrode (FBE) can be efficiently employed to remove metal ions from solution, avoid contamination, and recover the metal. Copper electrodeposition from diluted solutions was efficiently performed using a membraneless FBE. The average current efficiency (ACE), average energy consumption (AEC), and space–time yield (AY) was optimized taking into account the operational and process variables. It was noted that for all response variables studied, the raise of supporting electrolyte concentration (C _s) contributed to improvements in the process. The operational conditions current (I) and bed expansion (E) determined the values of CE, Y, and EC under activated control, but the initial copper concentration (C ₀) determined how long the electrodeposition process will work under activated or mass transfer control, thus affecting the average values of CE, Y, and EC. Considering C ₀ of 500 mg L^?1, copper can be optimally recovered with ACE >60 %, AY >38 kg h^?1 m^?3, and AEC <4.0 kWh kg^?1 by applying the lowest I and the highest levels of E and C _s. It was concluded that the electrochemical technology using a membraneless FBE reactor is economically competitive and be applied for the treatment of wastewaters contaminated with copper or other metals.     

Estimating vulnerability to risks: an application in a biofuel supply chain

In the present work, we propose a theoretical model to identify and prioritize risks involved in a biofuel supply chain. We adopt a set of indicators associated with determinant factors of the supply chain to identify risks that are characterized through a risk matrix. We consider the five largest world biodiesel producers and included China due to its global market importance and potential impacts of its growth on the environment and society. To determine the impacts and the probability of occurrence of risks, we use the Canberra distance, as metrics. To facilitate the analysis and interpretation, a convenient manner is to express the results in terms of matrices. To exemplify the potentiality of the scheme and for the sake of simplicity, a more comprehensive discussion is focused on the Brazilian case, restricted to the Technology and Innovation, and Integration, Logistics and Infrastructure determining factors (dimensions) of the biodiesel supply chain. Concerning these determining factors, the Brazilian biodiesel chain shows strong vulnerability when compared with developed and developing countries, despite that the evolution of the data over recent years indicates small improvements in Integration, Logistics and Infrastructure dimension. Although in this work the calculations are restricted to the Canberra distance, the present approach may be applied to other distances to compare or validate the results. This work presents a contribution to model vulnerability to risks, providing to policy makers and stakeholders a tool to design, analyze and improve sustainability system by measuring its risks. The study of the contribution of each indicator suggests corrections to be taken and which indicators should be prioritized.     

How can Cleaner Production practices contribute to meet ISO 14001 requirements? Critical analysis from a survey with industrial companies

The companies’ needs to adopt changes in their way of production to maximize the environmental performance required by their stakeholders, and at the same time, to maximize their economic and market performance, have made them seek for environmental strategies and certifications. In this sense, the Cleaner Production and the Environmental Management System based on ISO 14001 have been, respectively, presented, since the main objective of this research is to identify and analyze Cleaner Production contributions to comply with ISO 14001 requirements. For such, a survey research has been carried out in Brazilian industrial companies certified by ISO 14001. We have identified the main performance factors by leading practices and variables of Cleaner Production that contribute to the compliance with the standard requirements by companies. Thus, it has been noted that Cleaner Production is an important strategy for the preparation of companies for certification as well as for improving their environmental performance.