Inclusion body myositis: from genetics to clinical trials

Inclusion body myositis (IBM) belongs to the group of idiopathic inflammatory myopathies and is characterized by a slowly progressive disease course with asymmetric muscle weakness of predominantly the finger flexors and knee extensors. The disease leads to severe disability and most patients lose ambulation due to lack of curative or disease-modifying treatment options. Despite some genes reported to be associated with hereditary IBM (a distinct group of conditions), data on the genetic susceptibility of sporadic IBM are very limited. This review gives an overview of the disease and focuses on the current genetic knowledge and potential therapeutic implications

Walking the Talk? A Corporate Governance Perspective on Corporate Social Responsibility Decoupling

Information asymmetry and the pressure to conform to stakeholders’ expectations cause firms to engage in corporate social responsibility (CSR) decoupling – a practice that has severe socioeconomic consequences for firms. Adopting a corporate governance perspective, this paper answers a novel question: whether board gender diversity (BGD) curbs CSR decoupling. Using a battery of sophisticated analyses and robustness tests on 9276 firm-year observations for the period 2002–2017, our results confirm that BGD is negatively associated with CSR decoupling. Analysis of the composition of gender-diverse boards further reveals that this effect is stronger for balanced boards than for skewed and tilted boards. Furthermore, we note that independent female directors are more effective monitors of decoupling than executive female directors. We also document that the relationship between BGD and CSR decoupling is stronger when the overall governance is weak. This implies that gender-diverse boards could act as a substitute mechanism for corporate governance that would otherwise be weak. Our study offers important theoretical and policy implications for the field of corporate governance and CSR

NM-LEACH: A Novel Modified LEACH Protocol to Improve Performance in WSN

Saving energy and improving the lifetime of wireless sensor networks (WSNs) has remained as a key research challenge for some time. Low-energy adaptive clustering hierarchy (LEACH), a classical protocol is designed originally for the purpose of reducing and balancing the network’s energy consumption. However, as the distances between the cluster head (CH) and the member nodes are not taken into consideration, it results in the uneven distribution of the clusters and uneven consumption of the energy in the network. Choosing the CHs with no distinction is an issue as well. Based on the original algorithm, a novel modified LEACH (NM-LEACH) has been proposed, considering critical problems that exist in the network. NM-LEACH protocol is capable of reasonably solving the number of the CHs in each round and takes the energy as a factor of weight under consideration in selecting the CH. The proposed protocol enhances performance by extending the WSN lifecycle, which results in increasing the balance of the energy consumption in the network, and improving the efficiency of the network

Degradation mechanisms associated with metal pipes and the effective impact of LDMs and LLMs in water transport and distribution

The effective operation of water management systems is contingent upon leak localization and detection – a common problem that is more acute in large networks. This paper reviews the salient literature in this context and demonstrates the effectiveness of leakage location methods (LLMs) and leakage detection methods (LDMs). Although there is a significant amount of literature that discusses leakage localization and detection technologies, an academic lacuna still exists concerning the linkage between degradation mechanisms and LDMs and do not cover or connect past efforts from the start of a degradation mechanism that leads to changes in the mechanical strength (such as a reduction in fracture toughness) of pipes and results in crack propagation and leakage. This review focuses on these issues in the context of degradation mechanisms and common detection methods

Natural disasters and economic losses: controlling external migration, energy and environmental resources, water demand, and financial development for global prosperity

The objective of the study is to examine the impact of natural disasters on external migration, price level, poverty incidence, health expenditures, energy and environmental resources, water demand, financial development, and economic growth in a panel of selected Asian countries for a period of 2005–2017. The results confirm that natural disasters in the form of storm and flood largely increase migration, price level, and poverty incidence, which negatively influenced country’s economic resources, including enlarge healthcare expenditures, high energy demand, and low economic growth. The study further presented the following results: i) natural resource depletion increases external migration, ii) FDI inflows increase price level, iii) increase healthcare spending and energy demand decreases poverty headcount, iv) poverty incidence and mortality rate negatively influenced healthcare expenditures, v) industrialization increases energy demand, and vi) agriculture value added, fertilizer, and cereal yields required more water supply to produce greater yield. The study emphasized the need to magnify the intensity of natural disasters and create natural disaster mitigation unit to access the human and infrastructure cost and attempt quick recovery for global prosperity

Regional Frequency Analysis of Extremes Precipitation Using L-Moments and Partial L-Moments

Extremes precipitation may cause a series of social, environmental, and ecological problems. Estimation of frequency of extreme precipitations and its magnitude is vital for making decisions about hydraulic structures such as dams, spillways, and dikes. In this study, we focus on regional frequency analysis of extreme precipitation based on monthly precipitation records (1999–2012) at 17 stations of Northern areas and Khyber Pakhtunkhwa, Pakistan. We develop regional frequency methods based on L-moment and partial L-moments (L- and PL-moments). The L- and PL-moments are derived for generalized extreme value (GEV), generalized logistic (GLO), generalized normal (GNO), and generalized Pareto (GPA) distributions. The Z-statistics and L- and PL-moments ratio diagrams of GNO, GEV, and GPA distributions were identified to represent the statistical properties of extreme precipitation in Northern areas and Khyber Pakhtunkhwa, Pakistan. We also perform a Monte Carlo simulation study to examine the sampling properties of L- and PL-moments. The results show that PL-moments perform better than L-moments for estimating large return period events

The Efficacy of Error Mitigation Techniques for DRAM Retention Failures: A Comparative Experimental Study

As DRAM cells continue to shrink, they become more susceptible to retention failures. DRAM cells that permanently exhibit short retention times are fairly easy to identify and repair through the use of memory tests and row and column redundancy. However, the retention time of many cells may vary over time due to a property called Variable Retention Time (VRT). Since these cells intermittently transition between failing and non-failing states, they are particularly difficult to identify through memory tests alone. In addition, the high temperature packaging process may aggravate this problem as the susceptibility of cells to VRT increases after the assembly of DRAM chips. A promising alternative to manufacturetime testing is to detect and mitigate retention failures after the system has become operational. Such a system would require mechanisms to detect and mitigate retention failures in the field, but woul