Addressing cultural, social and environmental sustainability in architecture. The approach of five contemporary Australian architects

Regionalist architecture offers a promising and conscientious response to the present scenario of growing trend toward cultural, social and technical globalization. It has a great potential to preserve local cultural identities, despite the spread of global culture, to define possible relationships between construction and natural, cultural, political, economic and social factors, to combine traditional approaches and technical skills creatively and to suggest a new role for designers, as active subjects in dialogue with the manufacturing sector. An exemplary regionalist approach to contemporary architecture is given by a niche of Australian architects sensitive to the relation between communities and technical skills, dwelling patterns and building techniques, who tend to reduce the environmental load of construction through the use of local resources, who adopt community design processes and combine tradition with creative innovation. Glenn Murcutt, Richard Leplastrier, Peter Stutchbury, Gregory Burgess and Troppo Architects, who, learning from Aboriginal people's sacred respect for the land, balance the tension between global needs and local expressions, by listening to people and place, preserving traditional lifestyle preferences and combining new technologies with historic building types

A unified approach to pricing and risk management of equity and credit risk

We propose a unified framework for equity and credit risk modeling, where the default time is a doubly stochastic random time with intensity driven by an underlying affine factor process. This approach allows for flexible interactions between the defaultable stock price, its stochastic volatility and the default intensity, while maintaining full analytical tractability. We characterize all risk-neutral measures which preserve the affine structure of the model and show that risk management as well as pricing problems can be dealt with efficiently by shifting to suitable survival measures. As an example, we consider a jump- to-default extension of the Heston stochastic volatility model

DG-CST (Disease Gene Conserved Sequence Tags), a database of human�mouse conserved elements associated to disease genes

The identification and study of evolutionarily conserved genomic sequences that surround disease-related genes is a valuable tool to gain insight into the functional role of these genes and to better elucidate the pathogenetic mechanisms of disease. We created the DG-CST (Disease Gene Conserved Sequence Tags) database for the identification and detailed annotation of human–mouse conserved genomic sequences that are localized within or in the vicinity of human disease-related genes. CSTs are defined as sequences that show at least 70% identity between human and mouse over a length of at least 100 bp. The database contains CST data relative to over 1088 genes responsible for monogenetic human genetic diseases or involved in the susceptibility to multifactorial/polygenic diseases. DG-CST is accessible via the internet at http://dgcst.ceinge.unina.it/ and may be searched using both simple and complex queries. A graphic browser allows direct visualization of the CSTs and related annotations within the context of the relative gene and its transcripts

Forging consensus: an integrated view of how categories shape the perception of organizational identity

This paper integrates two approaches – the “categorization as a theoretical tool” and the “typicality judgment” – which both emphasize audience confusion as a mechanism through which category spanners become devalued or ignored. However, the two perspectives differ in their specification of why confusion will likely lead to devaluation or ignoring. In this study, we consider the interplay of these two approaches in the setting of corporate law market. We find that spanning product categories has a U-shaped relationship with perceived clarity of law firm identity. While none of the two perspectives alone can explain our findings, they can do so together

“Dead Lithium” Formation and Mitigation Strategies in Anode-Free Li-Metal Batteries

Thin lithium-metal foil is a promising anode material for next-generation batteries due to its high theoretical specific capacity and low negative potential. However, safety issues linked to dendrite growth, low-capacity retention, and short cycle life pose significant challenges. Also, it has excess energy that must be minimized in order to reduce the battery costs. To limit excess lithium, practical lithium metal batteries need a negative-to-positive electrode ratio as close to 1 : 1 as possible, which can be achieved through limiting excess lithium or using an “anode-free” metal battery design. However, both designs experience fast capacity fade due to the irreversible loss of active lithium in the cell, caused by the formation of the solid electrolyte interphase (SEI), dendrite formation and “dead lithium,” – refers to lithium that has lost its electronic connection to the anode electrode or current collector. The presence of dead lithium in batteries negatively affects their capacity and lifespan, while also raising internal resistance and generating heat. Additionally, dead lithium encourages the growth of lithium dendrites, which poses significant safety hazards. Within this fundamental review, we thoroughly address the phenomenon of dead lithium formation, assessing its origins, implications on battery performance, and possible strategies for mitigation. The transition towards environmentally friendly and high-performance metal batteries could be accelerated by effectively tackling the challenge posed by dead lithium

New Insights of Infiltration Process of Argyrodite Li6PS5Cl Solid Electrolyte into Conventional Lithium-Ion Electrodes for Solid-State Batteries

All-solid-state lithium-ion batteries based on solid electrolytes are attractive for electric applications due to their potential high energy density and safety. The sulfide solid electrolyte (e.g., argyrodite) shows a high ionic conductivity (10−3 S cm−1). There is an open question related to the sulfide electrode’s fabrication by simply infiltrating methods applied for conventional lithium-ion battery electrodes via homogeneous solid electrolyte solutions, the structure of electrolytes after drying, chemical stability of binders and electrolyte, the surface morphology of electrolyte, and the deepening of the infiltrated electrolyte into the active materials to provide better contact between the active material and electrolyte and favorable lithium ionic conduction. However, due to the high reactivity of sulfide-based solid electrolytes, unwanted side reactions between sulfide electrolytes and polar solvents may occur. In this work, we explore the chemical and electrochemical properties of the argyrodite-based film produced by infiltration mode by combining electrochemical and structural characterizations

ARCHModels.jl: Estimating ARCH Models in Julia

This paper introduces ARCHModels.jl, a package for the Julia programming language that implements a number of univariate and multivariate autoregressive conditional heteroskedasticity models. This model class is the workhorse tool for modeling the conditional volatility of financial assets. The distinguishing feature of these models is that they model the latent volatility as a (deterministic) function of past returns and volatilities. This recursive structure results in loop-heavy code which, due to its just-in-time compiler, Julia is well-equipped to handle. As such, the entire package is written in Julia, without any binary dependencies. We benchmark the performance of ARCHModels.jl against popular implementations in MATLAB, R, and Python, and illustrate its use in a detailed case study

ARCHModels.jl: Estimating ARCH Models in Julia

This paper introduces ARCHModels.jl, a package for the Julia programming language that implements a number of univariate and multivariate autoregressive conditional heteroskedasticity models. This model class is the workhorse tool for modeling the conditional volatility of financial assets. The distinguishing feature of these models is that they model the latent volatility as a (deterministic) function of past returns and volatilities. This recursive structure results in loop-heavy code which, due to its just-in-time compiler, Julia is well-equipped to handle. As such, the entire package is written in Julia, without any binary dependencies. We benchmark the performance of ARCHModels.jl against popular implementations in MATLAB, R, and Python, and illustrate its use in a detailed case study

Determinants of Deep Gray Matter Atrophy in Multiple Sclerosis: A Multimodal MRI Study

Deep gray matter involvement is a consistent feature in multiple sclerosis. The aim of this study was to evaluate the relationship between different deep gray matter alterations and the development of subcortical atrophy, as well as to investigate the possible different substrates of volume loss between phenotypes. Seventy-seven patients with MS (52 with relapsing-remitting and 25 with progressive MS) and 41 healthy controls were enrolled in this cross-sectional study. MR imaging investigation included volumetric, DTI, PWI and Quantitative Susceptibility Mapping analyses. Deep gray matter structures were automatically segmented to obtain volumes and mean values for each MR imaging metric in the thalamus, caudate, putamen, and globus pallidus. Between-group differences were probed by ANCOVA analyses, while the contribution of different MR imaging metrics to deep gray matter atrophy was investigated via hierarchic multiple linear regression models. Patients with MS showed a multifaceted involvement of the thalamus and basal ganglia, with significant atrophy of all deep gray matter structures (P.001). In the relapsing-remitting MS group,WMlesion burden proved to be the main contributor to volume loss for all deep gray matter structures (P .006), with a minor role of local microstructural damage, which, in turn, was the main determinant of deep gray matter atrophy in patients with progressive MS (P .01), coupled with thalamic susceptibility changes (P .05). Our study confirms the diffuse involvement of deep gray matter in MS, demonstrating a different behavior between MS phenotypes, with subcortical GM atrophy mainly determined by global WM lesion burden in patients with relapsing-remitting MS, while local microstructural damage and susceptibility changes mainly accounted for the development of deep gray matter volume loss in patients with progressive MS