Permeability of OSB. Part I. The Effects of Core Fines Content and Mat Density on Transverse Permeability

This paper reports on the effects of density and core fines content on the transverse permeability, K, of oriented strandboard (OSB), with the aim of using fines generated during the log stranding process to improve mat permeability and possibly press efficiency. Forty-five OSB panels were made in the laboratory containing five levels of fines content (0, 25, 50, 75, and 100%) and compressed to three target density levels (low—450, medium—550, and high—650 kg/m3). Both density and fines content and their interaction significantly influenced Kcore, which increased exponentially with fines content at each density level. Above 75% fines, density level no longer had any significant effect on Kcore, indicating that as the mat is compressed, the presence of fines maintains a more interconnected void system through which gas can pass. The rate of heat transfer to the core was affected by board thickness but contrary to expectations, not by fines content. Fines content did, however, affect the accumulation of gas pressure in the high target density heavily compressed boards; maximum core gas pressure was significantly reduced if core fines content was greater than 50%

Transverse Permeability of OSB. Part II. Modeling the Effects of Density and Core Fines Content

In this work a simple rule of mixtures model to characterize the permeability of an OSB composite as a function of fines contents and density is presented. Strands and fines in the core of the board are considered to lie between two extremes, either stacked in a series configuration (series model) or side by side in a parallel configuration (parallel model), with the permeability of the composite, Ksystem, being a function of relative permeabilities of the series and parallel models. Equations for the permeability of these two configurations, Kparallel and Kseries, are developed as functions of the known permeability of 100% strands, Ks, and 100% fines, Kf, and the mass fraction of fines, Mf. Data on the permeability of the core of OSB compressed to three density classes and made with 0 and 100% fines content are used to determine the permeability of the parallel and series models, respectively. The series coefficient, α, which represents the contribution from the series model, is determined using least squares fits to the permeability data for different target densities and 25%, 50%, and 75% fines contents. α was fairly consistent, ranging from 0.47 to 0.49 for these fines contents. Kparallel increases linearly with increasing fines content and Kseries increases exponentially, in accord with the actual data. The data for the low and medium target density boards were well described by the Ksystem predictions, whereas the model underestimates the permeability of boards containing 75% or 100% fines and compressed to high target density. The model was most sensitive to changes in Mf, Kf, and Ks, with other parameters, α and density ratio (ρs/ρf), having smaller effects. The proposed model is general and could be applied to other composites of mixed particle sizes such as particleboard

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Effect of Extended Mat Open Assembly Time on Properties of OSB Bonded With PMDI

In this study, the effect of increasing mat open assembly time on the strength properties of oriented strandboards bonded with polymeric methylene diphenol di-isocyanate (pMDI) resin was examined. Isocyanates are more sensitive to open assembly times than other resin systems such as phenol formaldehyde (PF), and the storage capacity of pMDI-blended wood furnish is believed to be no more than about 5 h. On the other hand, previous research works on bonding of wood elements with pMDI allude to the growth of an interpenetrating network (IPN) of cross-linked polyurea as being responsible for the high bonding capacity with pMDI and that this is enhanced with long pre-cure times (greater than 10-15 h). There was no evidence that this effect enhances the strength of OSB made from shortleaf pine, as boards pressed after a delay of 10 or more hours after blending were significantly lower in internal bond (IB) strength than those pressed within half an hour of blending. However, after a reduction of approximately 28% between 0 and 10 h, IB remained relatively stable with open assembly times up to 18 h, suggesting the potential for recycling such strands by partial substitution of them with freshly blended strands. The discrepancy between our findings and the pMDI bonding theory based on previous small-scale laboratory experiments was thought to have arisen from differences in resin distribution on the strands due to their different methods of application, and the cure temperature and moisture conditions in the core of boards being sub-optimal for the formation of an extensive network of fully cross-linked polyurea

(Benzyl isocyanide)gold(I) pyrimidine‐2‐thiolate complex: Synthesis and biological activity

The reaction of [(Me2S)AuCl] with an equimolar amount of benzyl isocyanide (PhCH2NC) ligand led to the formation of complex [(PhCH2NC)AuCl] (1). The solid‐state structure of 1 was determined using the X‐ray diffraction method. Through a salt metathesis reaction, the chloride ligand in 1 was replaced by pyrimidine‐2‐thiolate (SpyN−) to afford the complex [(PhCH2NC)Au(η1‐S‐Spy)] (2), which was characterized spectroscopically. The cytotoxic activities of 1 and 2 were evaluated against three human cancer cell lines: ovarian carcinoma (SKOV3), lung carcinoma (A549) and breast carcinoma (MCF‐7). Complex 2 showed higher cytotoxicity than cisplatin against SKOV3 and MCF‐7 cancer cell lines. It showed a strong anti‐proliferative activity with IC50 of 7.80, 6.26 and 6.14 μM, compared with that measured for cisplatin which was 7.62, 12.36 and 11.47 μM, against A549, SKOV3 and MCF‐7 cell lines, respectively. The induction of cellular apoptosis by 2 was also studied on MCF‐7 cell line. Our results indicated that 2 could induce apoptosis in cancerous cells in a dose‐dependent manner