Application of AHP algorithm on power distribution of load shedding in island microgrid

This paper proposes a method of load shedding in a microgrid system operated in an Island Mode, which is disconnected with the main power grid and balanced loss of the electrical power. This proposed method calculates the minimum value of the shed power with reference to renewable energy sources such as wind power generator, solar energy and the ability to control the frequency of the generator to restore the frequency to the allowable range and reduce the amount of load that needs to be shed. Computing the load importance factor (LIF) using AHP algorithm supports to determine the order of which load to be shed. The damaged outcome of load shedding, thus, will be noticeably reduced. The experimental results of this proposed method is demonstrated by simulating on IEEE 16-Bus microgrid system with six power sources

Addressing climate change with behavioral science: a global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors

Reading high breast density mammograms : differences in diagnostic performance between radiologists from Hong Kong SAR/guangdong province in China and Australia

Background: Variations in the performance of radiologists reading mammographic images are well reported, but key parameters explaining such variations in different countries are not fully explored. The main aim of this study is to investigate performances of Chinese (Hong Kong SAR and Guangdong Province) and Australian radiologists in interpreting dense breast mammographic images. Methods: A test set, contained 60 mammographic examinations with high breast density, was used to assess radiologists' performance. Twelve Chinese and thirteen Australian radiologists read all the cases independently and were asked to identify all lesions and provide a grade from 1 to 5 to each lesion. Case sensitivity, specificity, lesion sensitivity, AUC and JAFROC were used to assess radiologists' performances. Demographic information and reading experience were also collected from the readers. Performance scores were compared between the two populations and the relationships between performance scores and their reading experience were discovered. Results: For radiologists who were less than 40-year-old, lesion sensitivity, AUC and JAFROC were significantly lower in Chinese radiologists than those in Australian (52.10% vs 71.45%, p=0.043; 0.76 vs 0.84, p=0.031; 0.59 vs 0.72, p=0.045; respectively). Australian radiologists with less than 10 years of reading experience had higher AUC and JAFROC scores compared with their Chinese counterparts (0.83 vs 0.76, p=0.039; 0.70 vs 0.56, p=0.020, respectively). Conclusions: We found that younger Australian radiologists performed better at reading dense breast cases which is likely to be linked to intensive fellowship training, immersion in a screening program and exposure to the benefits of a performance-measuring education tool

The Stability and Complexity of Antibody Responses to the Major Surface Antigen of Plasmodium falciparum Are Associated with Age in a Malaria Endemic Area*

Individuals that are exposed to malaria eventually develop immunity to the disease with one possible mechanism being the gradual acquisition of antibodies to the range of parasite variant surface antigens in their local area. Major antibody targets include the large and highly polymorphic Plasmodium falciparum Erythrocyte Membrane Protein 1 (PfEMP1) family of proteins. Here, we use a protein microarray containing 123 recombinant PfEMP1-DBLα domains (VAR) from Papua New Guinea to seroprofile 38 nonimmune children (<4 years) and 29 hyperimmune adults (≥15 years) from the same local area. The overall magnitude, prevalence and breadth of antibody response to VAR was limited at <2 years and 2–2.9 years, peaked at 3–4 years and decreased for adults compared with the oldest children. An increasing proportion of individuals recognized large numbers of VAR proteins (>20) with age, consistent with the breadth of response stabilizing with age. In addition, the antibody response was limited in uninfected children compared with infected children but was similar in adults irrespective of infection status. Analysis of the variant-specific response confirmed that the antibody signature expands with age and infection. This also revealed that the antibody signatures of the youngest children overlapped substantially, suggesting that they are exposed to the same subset of PfEMP1 variants. VAR proteins were either seroprevalent from early in life, (<3 years), from later in childhood (≥3 years) or rarely recognized. Group 2 VAR proteins (Cys2/MFK-REY+) were serodominant in infants (<1-year-old) and all other sequence subgroups became more seroprevalent with age. The results confirm that the anti-PfEMP1-DBLα antibody responses increase in magnitude and prevalence with age and further demonstrate that they increase in stability and complexity. The protein microarray approach provides a unique platform to rapidly profile variant-specific antibodies to malaria and suggests novel insights into the acquisition of immunity to malaria

Gain-of-function cardiomyopathic mutations in RBM20 rewire splicing regulation and re-distribute ribonucleoprotein granules within processing bodies.

Mutations in the cardiac splicing factor RBM20 lead to malignant dilated cardiomyopathy (DCM). To understand the mechanism of RBM20-associated DCM, we engineered isogenic iPSCs with DCM-associated missense mutations in RBM20 as well as RBM20 knockout (KO) iPSCs. iPSC-derived engineered heart tissues made from these cell lines recapitulate contractile dysfunction of RBM20-associated DCM and reveal greater dysfunction with missense mutations than KO. Analysis of RBM20 RNA binding by eCLIP reveals a gain-of-function preference of mutant RBM20 for 3' UTR sequences that are shared with amyotrophic lateral sclerosis (ALS) and processing-body associated RNA binding proteins (FUS, DDX6). Deep RNA sequencing reveals that the RBM20 R636S mutant has unique gene, splicing, polyadenylation and circular RNA defects that differ from RBM20 KO. Super-resolution microscopy verifies that mutant RBM20 maintains very limited nuclear localization potential; rather, the mutant protein associates with cytoplasmic processing bodies (DDX6) under basal conditions, and with stress granules (G3BP1) following acute stress. Taken together, our results highlight a pathogenic mechanism in cardiac disease through splicing-dependent and -independent pathways