Prediction of Remaining Useful Life of anAircraft Engine under Unknown Initial Wear

Abstract Effectiveness of Condition Based Maintenance (CBM) strategy depends on accuracy in prediction of Remaining Useful Life (RUL).Data driven prognosisapproaches are generally used to estimate the RUL of the system. Presence of noise in the system monitored data may affect the accuracy of prediction. One of the sources of data noise is the presence of unknown initial wear in the samples. Present paper illustrates the effect of such initial wear on prediction accuracy and presents the guidelines to handle such initial wears. Two Artificial Neural Network (ANN)models are developed. First model is developed with the help of completedata; while the second model is developed after removing samples with abnormal initial wear.‫̅ݔ‬ and R control chart is used to screen the samples with abnormal initial wear. It is found that the presence of initial wear significantly affects the prediction accuracy. Also, it is found that RUL estimation for a unit with short history tends to produce great uncertainty.Hence, it is recommended that RUL prediction should be continuously updated with age of the unit to increase the effectiveness of CBM policy

SDFA: Statistical-Differential Fault Attack on Linear Structured SBox-Based Ciphers

At Asiacrypt 2021, Baksi et al. proposed DEFAULT, the first block cipher which provides differential fault attack (DFA) resistance at the algorithm level, with 64-bit DFA security. Initially, the cipher employed a simple key schedule where a single key was XORed throughout the rounds, and the key schedule was updated by incorporating round-independent keys in a rotating fashion. However, at Eurocrypt 2022, Nageler et al. presented a DFA that compromised the claimed DFA security of DEFAULT, reducing it by up to 20 bits for the simple key schedule and allowing for unique key recovery in the case of rotating keys. In this work, we present an enhanced differential fault attack (DFA) on the DEFAULT cipher, showcasing its effectiveness in uniquely recovering the encryption key. We commence by determining the deterministic computation of differential trails for up to five rounds. Leveraging these computed trails, we apply the DFA to the simple key schedule, injecting faults at different rounds and estimating the minimum number of faults required for successful key retrieval. Our attack achieves key recovery with minimal faults compared to previous approaches. Additionally, we extend the DFA attack to rotating keys, first recovering equivalent keys with fewer faults in the DEFAULT-LAYER, and subsequently applying the DFA separately to the DEFAULT-CORE. Furthermore, we propose a generic DFA approach for round-independent keys in the DEFAULT cipher. Lastly, we introduce a new paradigm of fault attack that combines SFA and DFA for any linear structured SBOX based cipher, enabling more efficient key recovery in the presence of both rotating and round-independent key configurations. We call this technique Statistical-Differential Fault Attack (SDFA). Our results shed light on the vulnerabilities of the DEFAULT cipher and highlight the challenges in achieving robust DFA protection for linear structure SBOX-based ciphers

Unusual Renal Tumors — Report of Four Cases

Collecting duct carcinoma, plasmocytoma and malignant fibrous histocytoma are rare but aggressive tumors of the kidneys. We present four cases we have recently encountered in our practice. In most of the cases imaging did not help in the pre-operative diagnosis. Surgery is the mainstay of treatment when recognized early. Clinician should be aware about these rare varieties of renal tumors whose prognoses may be worse than that of renal cell carcinoma. The Annals of African Surgery, Volume 6, 201

Transmissibility in Interactive Nanocomposite Diffusion: The Nonlinear Double-Diffusion Model

Model analogies and exchange of ideas between physics or chemistry with biology or epidemiology have often involved inter-sectoral mapping of techniques. Material mechanics has benefitted hugely from such interpolations from mathematical physics where dislocation patterning of platstically deformed metals and mass transport in nanocomposite materials with high diffusivity paths such as dislocation and grain boundaries, have been traditionally analyzed using the paradigmatic Walgraef-Aifantis (W-A) double-diffusivity (D-D) model. A long standing challenge in these studies has been the inherent nonlinear correlation between the diffusivity paths, making it extremely difficult to analyze their interdependence. Here, we present a novel method of approximating a closed form solution of the ensemble averaged density profiles and correlation statistics of coupled dynamical systems, drawing from a technique used in mathematical biology to calculate a quantity called the basic reproduction number R0, which is the average number of secondary infections generated from every infected. We show that the R0 formulation can be used to calculate the correlation between diffusivity paths, agreeing closely with the exact numerical solution of the D-D model. The method can be generically implemented to analyze other reaction-diffusion models

A simple ethanol wash of the tissue homogenates recovers high-quality genomic DNA from Corchorus species characterized by highly acidic and proteinaceous mucilages

A simple miniprep based on early elimination of highly acidic and proteinaceous mucilages through ethanol washing of the tissue homogenates has been developed for the extraction of genomic DNA from mature leaves and seeds of Corchorus spp. As compared to high cetyltrimethylammonium bromide (CTAB)-NaCl DNA extraction followed by ethanol-based removal of remnant mucilages from the DNA pellet, this simple miniprep consistently and reproducibly recovers high amounts of DNA with good spectral qualities at A260/A280 and A260/A230. The purified DNA is efficiently digested by restriction endonucleases, and is suitable for PCR amplification of nuclear microsatellites with expected allele sizes

An Oligopeptide Transporter of Mycobacterium tuberculosis Regulates Cytokine Release and Apoptosis of Infected Macrophages

Background: The Mycobacterium tuberculosis genome encodes two peptide transporters encoded by Rv3665c-Rv3662c and Rv1280c-Rv1283c. Both belong to the family of ABC transporters containing two nucleotide-binding subunits, two integral membrane proteins and one substrate-binding polypeptide. However, little is known about their functions in M. tuberculosis. Here we report functional characterization of the Rv1280c-Rv1283c-encoded transporter and its substrate-binding polypeptide OppA(MTB). Methodology/Principal Findings: OppA(MTB) was capable of binding the tripeptide glutathione and the nonapeptide bradykinin, indicative of a somewhat broad substrate specificity. Amino acid residues G109, N110, N230, D494 and F496, situated at the interface between domains I and III of OppA, were required for optimal peptide binding. Complementaton of an oppA knockout mutant of M. smegmatis with OppA(MTB) confirmed the role of this transporter in importing glutathione and the importance of the aforesaid amino acid residues in peptide transport. Interestingly, this transporter regulated the ability of M. tuberculosis to lower glutathione levels in infected compared to uninfected macrophages. This ability was partly offset by inactivation of oppD. Concomitantly, inactivation of oppD was associated with lowered levels of methyl glyoxal in infected macrophages and reduced apoptosis-inducing ability of the mutant. The ability to induce the production of the cytokines IL-1 beta, IL-6 and TNF-alpha was also compromised after inactivation of oppD. Conclusions: Taken together, these studies uncover the novel observations that this peptide transporter modulates the innate immune response of macrophages infected with M. tuberculosis

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

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed