Bounds on the lightest Higgs boson mass with three and four fermion generations

We present lower bounds on the Higgs boson mass in the Standard Model with three and four fermion generations SM(3,4), as well as upper bounds on the lightest Higgs boson mass in the minimal supersymmetric extension of the SM with three and four generations MSSM(3,4). Our analysis utilizes the SM(3,4) renormalization-group-improved one-loop effective potential of the Higgs boson to find the upper bounds on the Higgs mass in the MSSM(3,4) while the lower bounds in the SM(3,4) are derived from considerations of vacuum stability. All the bounds increase as the degenerate fourth generation mass increases, providing more room in theory space that respects the increasing experimental lower limit of the Higgs mass.Comment: 24 pages, 10 figures, Some additional discussion added. Final version to be published in International Journal of Modern Physics

NAIP proteins are required for cytosolic detection of specific bacterial ligands in vivo.

NLRs (nucleotide-binding domain [NBD] leucine-rich repeat [LRR]-containing proteins) exhibit diverse functions in innate and adaptive immunity. NAIPs (NLR family, apoptosis inhibitory proteins) are NLRs that appear to function as cytosolic immunoreceptors for specific bacterial proteins, including flagellin and the inner rod and needle proteins of bacterial type III secretion systems (T3SSs). Despite strong biochemical evidence implicating NAIPs in specific detection of bacterial ligands, genetic evidence has been lacking. Here we report the use of CRISPR/Cas9 to generate Naip1(-/-) and Naip2(-/-) mice, as well as Naip1-6(Δ/Δ) mice lacking all functional Naip genes. By challenging Naip1(-/-) or Naip2(-/-) mice with specific bacterial ligands in vivo, we demonstrate that Naip1 is uniquely required to detect T3SS needle protein and Naip2 is uniquely required to detect T3SS inner rod protein, but neither Naip1 nor Naip2 is required for detection of flagellin. Previously generated Naip5(-/-) mice retain some residual responsiveness to flagellin in vivo, whereas Naip1-6(Δ/Δ) mice fail to respond to cytosolic flagellin, consistent with previous biochemical data implicating NAIP6 in flagellin detection. Our results provide genetic evidence that specific NAIP proteins function to detect specific bacterial proteins in vivo

Lean Improvements to Passenger Departure Flow in Abu Dhabi Airport: Focus on Data from the Check-in Element

This is the second paper of three which concerns improving Passenger Departure Flow. The main aim of this paper is provide a summary of the research results, which includes both the reporting of empirical data collected at the Airport and the results obtained from simulation of existing flow for passenger departure process. The large quantity of data means this paper focuses on reporting data for the economy check-in element only. The project led towards development of rules for process of improvement for the entire departure process and explored the benefits of using the Lean philosophy for improving a range of airport processes. Airport processes are completely different than the manufacturing and other service sectors due to the complex interlinking between different stake holders such as airline regulations, national/international law etc

The sterlet sturgeon genome sequence and the mechanisms of segmental rediploidization

Sturgeons seem to be frozen in time. The archaic characteristics of this ancient fish lineage place it in a key phylogenetic position at the base of the ~30,000 modern teleost fish species. Moreover, sturgeons are notoriously polyploid, providing unique opportunities to investigate the evolution of polyploid genomes. We assembled a high-quality chromosome-level reference genome for the sterlet, Acipenser ruthenus. Our analysis revealed a very low protein evolution rate that is at least as slow as in other deep branches of the vertebrate tree, such as that of the coelacanth. We uncovered a whole-genome duplication that occurred in the Jurassic, early in the evolution of the entire sturgeon lineage. Following this polyploidization, the rediploidization of the genome included the loss of whole chromosomes in a segmental deduplication process. While known adaptive processes helped conserve a high degree of structural and functional tetraploidy over more than 180 million years, the reduction of redundancy of the polyploid genome seems to have been remarkably random

Prediction of Pavement Maintenance Performance Using an Expert System

The pavement experiences deterioration due to traffic and environment, i.e., unsatisfactory riding quality and structural inadequacy, over time. Thus, predicting pavement performance over time is one of the key elements of any pavement maintenance management system (PMMS). It can be used as an efficient tool to program/schedule the maintenance applications and expenditures, and thus the necessary funds can be allocated. Using a combination of independent variables for any selected pavement section can generate section-wise condition assessment and prediction models. Moreover, these models can be used to select the most cost-effective maintenance alternative to be applied to that pavement section. The present study developed an expert system based on pavement performance models which combines the available maintenance data with the knowledge acquired from the experts of the General Administration of Operation and Maintenance in Riyadh, Saudi Arabia. Eight regression models were first developed for four maintenance and rehabilitation (M&R) strategies, i.e., no maintenance, routine maintenance, overlay, and reconstruction for low and high traffic. Then, a practical expert system was developed to aid pavement maintenance engineers in finding the most effective and efficient M&R strategies and suitable time for the application. The regression models revealed that the effect of routine maintenance and reconstruction is greater in low traffic than in high traffic, while the effect of overlay is greater in high traffic than in low traffic. Based on this initial system, another improved one can be developed using the machine learning technique

Enhanced heart rate prediction model using damped least-squares algorithm

Monitoring a patient’s vital signs is considered one of the most challenging problems in telehealth systems, especially when patients reside in remote locations. Companies now use IoT devices such as wearable devices to participate in telehealth systems. However, the steady adoption of wearables can result in a significant increase in the volume of data being collected and transmitted. As these devices run on limited battery power, they can run out of power quickly due to the high processing requirements of the device for data collection and transmission. Given the importance of medical data, it is imperative that all transmitted data adhere to strict integrity and availability requirements. Reducing the volume of healthcare data and the frequency of transmission can improve a device’s battery life via an inference algorithm. Furthermore, this approach creates issues for improving transmission metrics related to accuracy and efficiency, which are traded-off against each other, with increasing accuracy reducing efficiency. This paper demonstrates that machine learning (ML) can be used to overcome the trade-off problem. The damped least-squares algorithm (DLSA) is used to enhance both metrics by taking fewer samples for transmission whilst maintaining accuracy. The algorithm is tested with a standard heart rate dataset to compare the metrics. The results showed that the DLSA provides the best performance, with an efficiency of 3.33 times for reduced sample data size and an accuracy of 95.6 %, with similar accuracies observed in seven different sampling cases adopted for testing that demonstrate improved efficiency. This proposed method significantly improve both metrics using ML without sacrificing one metric over the other compared to existing methods with high efficiency

Perilipin 2 downregulation in β cells impairs insulin secretion under nutritional stress and damages mitochondria

Perilipin 2 (PLIN2) is a lipid droplet (LD) protein in β cells that increases under nutritional stress. Downregulation of PLIN2 is often sufficient to reduce LD accumulation. To determine whether PLIN2 positively or negatively affects β cell function under nutritional stress, PLIN2 was downregulated in mouse β cells, INS1 cells, and human islet cells. β Cell-specific deletion of PLIN2 in mice on a high-fat diet reduced glucose-stimulated insulin secretion (GSIS) in vivo and in vitro. Downregulation of PLIN2 in INS1 cells blunted GSIS after 24-hour incubation with 0.2 mM palmitic acid. Downregulation of PLIN2 in human pseudoislets cultured at 5.6 mM glucose impaired both phases of GSIS, indicating that PLIN2 is critical for GSIS. Downregulation of PLIN2 decreased specific OXPHOS proteins in all 3 models and reduced oxygen consumption rates in INS1 cells and mouse islets. Moreover, we found that PLIN2-deficient INS1 cells increased the distribution of a fluorescent oleic acid analog to mitochondria and showed signs of mitochondrial stress, as indicated by susceptibility to fragmentation and alterations of acyl-carnitines and glucose metabolites. Collectively, PLIN2 in β cells has an important role in preserving insulin secretion, β cell metabolism, and mitochondrial function under nutritional stress

Loss of Katnal2 leads to ependymal ciliary hyperfunction and autism-related phenotypes in mice

Autism spectrum disorders (ASD) frequently accompany macrocephaly, which often involves hydrocephalic enlargement of brain ventricles. Katnal2 is a microtubule-regulatory protein strongly linked to ASD, but it remains unclear whether Katnal2 knockout (KO) in mice leads to microtubule- and ASD-related molecular, synaptic, brain, and behavioral phenotypes. We found that Katnal2-KO mice display ASD-like social communication deficits and age-dependent progressive ventricular enlargements. The latter involves increased length and beating frequency of motile cilia on ependymal cells lining ventricles. Katnal2-KO hippocampal neurons surrounded by enlarged lateral ventricles show progressive synaptic deficits that correlate with ASD-like transcriptomic changes involving synaptic gene down-regulation. Importantly, early postnatal Katnal2 re-expression prevents ciliary, ventricular, and behavioral phenotypes in Katnal2-KO adults, suggesting a causal relationship and a potential treatment. Therefore, Katnal2 negatively regulates ependymal ciliary function and its deletion in mice leads to ependymal ciliary hyperfunction and hydrocephalus accompanying ASD-related behavioral, synaptic, and transcriptomic changes