Coverage Of Region Research Articles

Level Up with ML Vulnerability Identification: Leveraging Domain Constraints in Feature Space for Robust Android Malware Detection

Machine Learning (ML) promises to enhance the efficacy of Android Malware Detection (AMD); however, ML models are vulnerable to realistic evasion attacks—crafting realizable Adversarial Examples (AEs) that satisfy Android malware domain constraints. To eliminate ML vulnerabilities, defenders aim to identify susceptible regions in the feature space where ML models are prone to deception. The primary approach to identifying vulnerable regions involves investigating realizable AEs, but generating these feasible apps poses a challenge. For instance, previous work has relied on generating either feature-space norm-bounded AEs or problem-space realizable AEs in adversarial hardening. The former is efficient but lacks full coverage of vulnerable regions while the latter can uncover these regions by satisfying domain constraints but is known to be time-consuming. To address these limitations, we propose an approach to facilitate the identification of vulnerable regions. Specifically, we introduce a new interpretation of Android domain constraints in the feature space, followed by a novel technique that learns them. Our empirical evaluations across various evasion attacks indicate effective detection of AEs using learned domain constraints, with an average of 89.6%. Furthermore, extensive experiments on different Android malware detectors demonstrate that utilizing our learned domain constraints in Adversarial Training (AT) outperforms other AT-based defenses that rely on norm-bounded AEs or state-of-the-art non-uniform perturbations. Finally, we show that retraining a malware detector with a wide variety of feature-space realizable AEs results in a 77.9% robustness improvement against realizable AEs generated by unknown problem-space transformations, with up to 70 × faster training than using problem-space realizable AEs.

Decoding complexity: The role of long-read sequencing in unraveling genetic disease etiologies.

In recent years, next-generation high-throughput sequencing technology has been widely used in clinical practice for the identification and diagnosis of Mendelian diseases as an auxiliary detection method. Nevertheless, due to the limitations in read length and poor coverage of complex genomic regions, the etiology of many genetic diseases is unclear. Long-read sequencing (LRS) addresses these limitations of next-generation sequencing. LRS is an effective tool for the clinical study of the etiology of complex genetic diseases. In this review, we summarized the current research on the application of LRS in diseases across various systems. We also reported the improvements in the diagnostic rate and common variant types of LRS in different studies, providing a foundation for the discovery of new disease mechanisms, which is anticipated to play a crucial role in future research on genetic diseases.

Regional disparities of full pentavalent vaccine uptake and the determinants in Ethiopia: Mapping and spatial analysis using the EDHS data.

The full pentavalent (DPT-HepB-Hib) vaccination is the main strategy to prevent five communicable diseases in early childhood, especially in countries with huge communicable disease burdens like Ethiopia. Exploring spatial distributions and determinants of full pentavalent vaccination status in minor ecological areas in Ethiopia is crucial for creating targeted immunization campaigns and monitoring the advancement of accomplishing sustainable development goals. This study aimed to investigate the spatial disparities and determinants of full pentavalent vaccination among 12-23-month-old children in Ethiopia. The data on pentavalent vaccine uptake was found in the Ethiopian Health and Demographic Survey (EDHS, 2019). A two-stage cluster sampling method was applied to collect the EDHS data. The enumeration area was the primary sample unit while the household served as the secondary sampling unit. The geographical variations of full pentavalent vaccine uptake were explored using Quantum Geographic Information System (QGIS) software. The significant predictors of full pentavalent vaccination were identified using a simple logistic regression model through R version 4.1 software. The national full pentavalent vaccine uptake was 59.2%. The spatial distribution of full pentavalent vaccine uptake was not uniform in Ethiopia. Spatial cluster analysis revealed that most of low coverage regions for full pentavalent vaccine uptake were Afar, Somali, and Harari. The regions with the highest and lowest rates of vaccine uptake were Tigray and Harari region, respectively. Maternal age of 35-49 years (AOR = 3.42; 95% CI: 1.99, 5.87), and 25-34 years (AOR = 1.55; 95% CI: 1.17, 2.19), primary education attended (AOR = 1.51; 95%CI: 1.07, 2.11), richness wealth index (AOR = 1.96; 95% CI: 1.40, 2.75), birth order of 1-3 (AOR = 1.88; 95% CI: 1.19, 2.96), and delivery in the health facility (AOR = 3.41: 95% CI: 2.52, 4.61) were the determinants of full pentavalent vaccine uptake in Ethiopia. Ethiopia's full pentavalent vaccine uptake was far lower than the global target. Older maternal age, maternal education, wealth index, birth order, and giving birth in a health facility were the determinants of full pentavalent vaccine uptake. Special attention should be given to Afar, Somali, and Harari regions, to strengthen the vaccine uptake. Moreover, improved socioeconomic status and getting maternal health services during delivery are necessary to enhance vaccine uptake.

Development and Comprehensive Evaluation of Culture-Independent, Long Amplicon-Based Targeted Next-Generation Sequencing Methods for Predicting Antimicrobial Resistance in Tuberculosis.

The great variety of antimicrobial resistance (AMR) profiles among tuberculosis (TB) patients necessitates a comprehensive detection method. This study developed culture-independent, long amplicon-based targeted next-generation sequencing (tNGS) methods for predicting AMR across 16 drugs within the Mycobacterium tuberculosis complex (MTBC). Multiplex PCR amplification was employed to enrich 20 gene regions, with sequencing performed on either the Oxford Nanopore Technologies (ONT) or Illumina platforms. Customized bioinformatics pipelines provide a streamlined process from raw data to clinician-friendly reports. The ONT tNGS method has been optimized, and its performance has been thoroughly evaluated, utilizing Q20+ chemistry in combination with the R10.4.1 flow cell. It requires only 15 high-quality reads per target gene to accurately identify all variants, with the turnaround time taking 4 h and 50 min. Studies confirmed that this method effectively identifies Mycobacterium species and was highly resistant to interference from other clinical pathogens. To ensure optimal coverage, it is recommended to input at least 500 copies of the genome and sequence 500MB of high-quality FASTQ data. Diagnostic performance evaluations demonstrate that this method achieves 98.35% concordance with phenotypic drug susceptibility testing (pDST) and is consistent with the results obtained from Xpert MTB/RIF assays. The design of long amplicons not only ensures comprehensive coverage of target regions but also simplifies primer design, facilitating compatibility with various sequencing platforms. Compared with previous studies, the optimized ONT tNGS method in this study significantly improves turnaround time, detection accuracy, and the comprehensive coverage of mutations associated with AMR.

Emergency Department Use Within 90 Days After Single-Level Posterior Cervical Foraminotomy.

This study sought to characterize the incidence of, timing of, predictive factors for, and reasons for emergency department (ED) visits within 90 days of single-level posterior cervical foraminotomy (PCF). These visits, after PCF, have received limited attention. The 2010-2022 M161 PearlDiver database was queried for elective single-level PCFs, excluding multilevel procedures, midline laminectomies, fusions, or other posterior/anterior procedures, as well as indications of trauma, infection, or neoplasm. Patient age, sex, Elixhauser Comorbidity Index (ECI), insurance, and region were extracted. Weekly ED use after PCF was calculated. Multivariate analyses were used to identify predictive factors for ED use, and primary ED diagnoses were categorized. Of 10,588 PCF patients, 9.09% (n=962) visited the ED within 90 days after surgery, mostly in the first 4 weeks. Multivariate analysis identified that predictors included younger age (odds ratio [OR], 1.02 per decade decrease), female sex (OR, 1.19), higher ECI (OR, 1.28 for ECI 1-2; OR, 1.41 for ECI 3-4; OR, 1.51 for ECI ≥5), Midwest (OR, 1.16) or Northeast (OR, 1.19) region, and Medicare (OR, 1.09) or Medicaid (OR, 1.57) coverage. In the first 4 weeks, 69.9% of ED visits were related to the surgical site; this decreased to 27.1% thereafter. Almost one-tenth of PCF patients visited the ED within 90 days after surgery. Specific patient characteristics were associated with ED visits, with surgical site-related diagnoses predominating in the acute postoperative period. Tailoring health care interventions based on timing of, risk factors for, and causes of ED visits may enhance outcomes and reduce costs. [Orthopedics. 202x;4x(x):xx-xx.].

A Novel Approach to Node Coverage Enhancement in Wireless Sensor Networks Using Walrus Optimization Algorithm

Wireless Sensor Networks (WSNs) are crucial components of modern technology, supporting applications like healthcare, industrial automation, and environmental monitoring. This research aims to design intelligent and adaptive sensor networks by integrating metaheuristics with node coverage optimization in WSNs. By incorporating metaheuristics and optimizing node coverage, WSNs can become more resilient and robust, leading to the development of self-adapting, self-organizing networks capable of efficiently covering dynamic and diverse environments. This research introduces the Walrus Optimization Algorithm for Node Coverage Enhancement in WSNs, called the WaOA-NCEWSN technique. The primary goal of this technique is to optimize the coverage of a target region using a limited number of Sensor Nodes (SNs) and by improving their placement. The WaOA is inspired by walrus behaviours like feeding, migrating, breeding, escaping, roosting, and gathering in response to environmental signals. The WaOA-NCEWSN technique uses an objective function that defines the coverage ratio, representing the maximum probability of coverage in a 2D-WSN monitoring area. Comparative analysis with other models using 50, 75, 100, and 200 nodes shows that the WaOA-NCEWSN technique performs better. The compilation times for the WaOA-NCEWSN technique are 5.14s, 6.48s, 6.54s, and 7.47s for 50, 75, 100, and 200 nodes, respectively. Experimental results indicate that the WaOA-NCEWSN technique offers superior coverage performance compared to other models.

Scholarship with a Purpose: Frontiers of Gender Equality Pushes the Boundaries for Students and Scholars Alike

Abstract This review article critiques Frontiers of Gender Equality: Transnational Legal Perspectives, edited by Rebecca J Cook. Composed of chapters centred on advancing gender equality, Frontiers differs from the typical edited collection because the authors worked collaboratively and shared a common purpose. They are all strongly committed to substantive equality (as opposed to formal equality) and recognise the importance of addressing intersectional discrimination. In their respective chapters the authors expand the discourse surrounding gender equality law by envisioning transformative approaches to righting gendered wrongs in domestic, regional and international human rights systems. While the collection is certainly valuable for scholars and legal practitioners, this review article considers its value for a different audience – that of graduate students in law and gender studies. Because the book is far more structured and unified than the typical edited collection, it could serve as a foundational textbook for an advanced comparative course on gender equality and the law. This review article – authored by a professor and a law student – analyses the book’s considerable strengths as a textbook. However, it also identifies certain weaknesses and suggests supplementary materials, in order to provide better coverage of the Asia-Pacific region.

Aggressive driving behavior: road rage incidents in Athens from the clinical forensic point of view

BackgroundAggressive driving behavior may lead to interpersonal violence. The Athens Metropolitan area has over four million inhabitants. Public transportation has improved over the last decades, mainly due to the work performed before the 2004 Olympic Games but is still lacking in the coverage of the Attica region with fixed track transportation. Thus, traffic in Athens is usually heavy during the day, a fact that combined with limited parking spaces available, acts as fuel to aggressive driving behaviors.For this retrospective study, data from forensic clinical examinations performed at our department by the authors were reviewed. More specifically, cases examined from January 1st, 2012, to September 30rd, 2021, all concerning allegations for road rage were included, totally 177 cases. The data obtained was analyzed by utilizing SPSS Statistics.ResultsMost victims and perpetrators were drivers of their vehicles. In most cases (85.3%), perpetrators acted alone. 80.2% of victims reported that the incident was triggered by a minor conflict. Perpetrators used mostly just their hands and feet, or even their head as a blunt force instrument to inflict injuries (72.3%). Hammers, crowbars, and brass knuckles were used in 12.4% of cases, while in 9.6% the vehicle was used to overrun the victim. In 2.8% of cases, perpetrators attempted to strangulate the victims, while in 1.7% they used a sharp force instrument. In 9.6% of cases, victims did not sustain any visible external injury. 18.1% of victims sustained just a single injury, while in 72.3% multiple injuries were observed. 69.5% victims sustained merely external injuries, while in 20.2% at least one internal organ injury was sustained. The predominant injury site was by far the head-neck region. In more than one third of the road rage incidents, the injuries could be characterized as grievous.ConclusionsMost people involved were male motorists. Females are rarely victims of road traffic violence, and even more rarely act as perpetrators. Commonest injury site was the head-neck region, with second commonest the upper extremities.

Comprehensive evaluation of the impact of whole-genome bisulfite sequencing (WGBS) on the fragmentomic characteristics of plasma cell-free DNA

BackgroundCell-free DNA (cfDNA) is non-randomly fragmented in human body fluids. Analyzing such fragmentation patterns of cfDNA holds great promise for liquid biopsy. Whole-genome bisulfite sequencing (WGBS) is widely used for cfDNA methylation profiling. However, its applicability for studying fragmentomic characteristics remains largely unexplored. MethodsWe performed paired WGBS and whole-genome sequencing (WGS) on 66 peripheral plasma samples from 58 pregnant women. Then, we systematically compared the fragmentation patterns of cell-free nuclear DNA and mitochondrial DNA (mtDNA) sequenced from these two approaches. Additionally, we evaluated the extent of the size shortening in fetal-derived cfDNA and estimated the fetal DNA fraction in maternal plasma using both sequencing methods. ResultsCompared to WGS samples, WGBS samples demonstrated a significantly lower genome coverage and higher GC content in cfDNA. They also showed a significant decrease in the size of cell-free nuclear DNA, along with alterations in the end motif pattern that were specifically associated with CpG and “CC” sites. While there was a slight shift in the inferred nucleosome footprint from cfDNA coverages in WGBS samples, the cfDNA coverage patterns in CTCF and TSS regions remained highly consistent between these two sequencing methods. Both methods accurately reflected gene expression levels through their TSS coverages. Additionally, WGBS samples exhibited an increased abundance and longer length of mtDNA in plasma. Furthermore, we observed the size shortening of fetal cfDNA in plasma consistently, with a highly correlated fetal DNA fraction inferred by cfDNA coverage between WGBS and WGS samples (r = 0.996). However, the estimated fetal cfDNA fraction in WGBS samples was approximately 7 % lower than in WGS samples. ConclusionsWe confirmed that WGBS can introduce artificial breakages to cfDNA, leading to altered fragmentomic patterns in both nuclear and mitochondrial DNA. However, WGBS cfDNA remains suitable for analyzing certain cfDNA fragmentomic characteristics, such as coverage in genome regulation regions and the essential characteristics of fetal DNA in maternal plasma.

FunFuzz : Greybox Fuzzing with Function Significance

Greybox fuzzing is dedicated to revealing software bugs by maximizing code coverage. Concentrating on code coverage, greybox fuzzing effectively exposes bugs in real-world programs by continuously executing the program under test (PUT) with the test inputs generated from initial seeds, making it a popular software testing technique. Although powerful, the effectiveness of greybox fuzzing can be restricted in some cases. Ignoring the significant degrees of executed functions, traditional greybox fuzzing usually fails to identify significant seeds that execute more significant functions, and thus may assign similar energy to significant and trivial seeds when conducting power scheduling. As a result, the effectiveness of greybox fuzzing can be degraded due to wasting too much energy on trivial seeds. In this paper, we introduce function significance (FS) to measure the significant degrees of functions. Our key insight is that the influential functions that connect to many other functions are significant to greybox fuzzing as they provide more probabilities to reach previously unexplored code regions. To quantify FS, we conduct influence analysis upon the call graphs extracted from the PUTs to obtain the centrality values of function nodes. With FS as the significance measurement, we further propose FunFuzz , an FS-aware greybox fuzzing technique, to optimize significant seeds and tackle the aforementioned restriction. To this end, FunFuzz dynamically tracks the functions executed by a seed during fuzzing, and computes the significance score for the seed by accumulating the FS values of the functions executed by it. Based on the computed FS values, FunFuzz then takes an estimation-based power scheduling to assign more (or less) energy to seeds that achieve over-estimated (or under-estimated) significance scores. Specifically, the seed energy is adjusted by multiplying with a scale factor computed regarding the ratio of the actual significance score achieved by executing the seed and the estimated significance score predicted by a linear model constructed on-the-fly. To evaluate FunFuzz , we prototype it on top of AFL++ and conduct experiments with 15 programs, of which 10 are from common real-world projects and five are from Magma, and compare it to seven popular fuzzers. The experimental results obtained through fuzzing exceeding 40,800 CPU hours show that: (1) In terms of covering code, FunFuzz outperforms AFL++ by achieving 0.1% \(\sim\) 18.4% more region coverage on 13 out of 15 targets. (2) In terms of finding bugs, FunFuzz unveils 114 unique crashes and 25 Magma bugs (which are derived from CVEs) in 20 trials of 24-hour fuzzing, which are the most compared to the competitor fuzzers and include 32 crashes and 1 Magma bug that the other fuzzers fail to discover. Besides the experiments focusing on code coverage and bug finding, we evaluate the key components of FunFuzz , namely the FS-centered estimation-based power scheduling and the lazy FS computation mechanism. The extensive evaluation not only suggests FunFuzz ’s superiority in code coverage and bug finding, but also demonstrates the effectiveness of the two components.

Efficient Stochastic Template Bank Using Inner Product Inequalities

Gravitational wave searches are crucial for studying compact sources such as neutron stars and black holes. Many sensitive modeled searches use matched filtering to compare gravitational strain data to a set of waveform models known as template banks. We introduce a new stochastic placement method for constructing template banks, offering efficiency and flexibility to handle arbitrary parameter spaces, including orbital eccentricity, tidal deformability, and other extrinsic parameters. This method can be computationally limited by the ability to compare proposal templates with the accepted templates in the bank. To alleviate this computational load, we introduce the use of inner product inequalities to reduce the number of required comparisons. We also introduce a novel application of Gaussian Kernel Density Estimation to enhance waveform coverage in sparser regions. Our approach has been employed to search for eccentric binary neutron stars, low-mass neutron stars, primordial black holes, and supermassive black hole binaries. We demonstrate that our method produces self-consistent banks that recover the required minimum fraction of signals. For common parameter spaces, our method shows comparable computational performance and similar template bank sizes to geometric placement methods and stochastic methods, while easily extending to higher-dimensional problems. The time to run a search exceeds the time to generate the bank by a factor of O(105) for dedicated template banks, such as geometric, mass-only stochastic, and aligned spin cases, O(104) for eccentric and O(103) for the tidal deformable bank. With the advent of efficient template bank generation, the primary area for improvement is developing more efficient search methodologies.

ТЕЛЕМЕДИЦИНСКОЕ КОНСУЛЬТИРОВАНИЕ ПО ПРОФИЛЮ «АНЕСТЕЗИОЛОГИЯ И РЕАНИМАТОЛОГИЯ (для взрослых)»: основные целевые направления и фактическая обеспеченность административно-территориальных и медико-социальных групп

New digital technologies including telemedicine consultations are not only methods of diagnostics and treatment but also instruments of organizational and methodological support in adopting tactical decisions both in anesthesiology and resuscitation and in other branches of medicine. The national medical research center in the field of «anesthesiology and resuscitation (adult)» of the Sechenov University as a head institution providing organizational and methodological support to the regions presents in this paper analysis of real coverage of the Russian regions with telemedicine consultations in the field of anesthesiology and resuscitation.

Comparison of terrestrial exospheric hydrogen 3D distributions at solar minimum and maximum using TWINS Lyman-α observations

Remote sensing observations of far-ultraviolet (FUV) emissions have been used to estimate 3D neutral hydrogen (H) density models of the terrestrial exosphere under solar minimum (2008) and solar maximum (2013 and 2015) conditions. Specifically, we used Lyman-alpha (Lyman-α, FUV at 121.6 nm) radiance data acquired by the Lyman-alpha detectors (LADs) onboard NASA’s TWINS satellites, collected over several days for each of the 3 years to provide sufficient coverage of the exospheric region. The datasets included Lyman-α measurements taken only above Earth radii (Re) of 3.75, assumed to be the optically thin region of the exosphere, where the measured Lyman-α intensity along a line of sight (LOS) is linearly proportional to the atomic hydrogen column density. Based on the calibration using multiple UV-bright stars, a significant decrease in TWINS1 LAD1/2 sensitivities was found for 2013 (LAD2 ∼1/2, LAD ∼1/3) and 2015 (LAD2 ∼1/3, LAD ∼1/7) compared to 2008. The calibration uncertainty was derived to be, on average, 5%. We estimated the 3D global hydrogen density distributions from these radiance data using two different tomographic inversion methods: first, a parametric fitting method based on a spherical harmonic function of order 3 and second, a high degree-of-freedom retrieval approach to validate our retrievals of H density. Both inversion methods consistently incorporate the effects of Lyman-α absorption within the exosphere and Lyman-α re-emission from Earth’s albedo. Our results reveal that H densities during solar maximum conditions are, on average, 30%–40% higher than those during solar minimum. All models showed a high concentration of atomic H on the dayside and nightside near the Sun–Earth line, which determines a nose/geotail structure consistent with theoretical effects from the solar radiation pressure. Furthermore, we identified that H-density enhancements during solar maximum with respect to solar minimum conditions occur at mid-to-high latitudes, particularly on the dusk side, while no significant enhancement seems to occur near the dayside nose.

Gradient descent optimization of acoustic holograms for transcranial focused ultrasound

Acoustic holographic lenses, also known as acoustic holograms, can change the phase of a transmitted wavefront in order to shape and construct complex ultrasound pressure fields, often for focusing the acoustic energy on a target region. These lenses have been proposed for transcranial focused ultrasound (tFUS) to create diffraction-limited focal zones that target specific brain regions while compensating for skull aberration. Holograms are currently designed using time-reversal approaches in full-wave time-domain numerical simulations. Such simulations need time-consuming computations, which severely limits the adoption of iterative optimization strategies. In the time-reversal method, the number and distribution of virtual sources can significantly influence the final sound field. Because of the computational constraints, predicting these effects and determining the optimal arrangement is challenging. This study introduces an efficient method for designing acoustic holograms using a volumetric holographic technique to generate focused fields inside the skull. The proposed method combines a modified mixed-domain method for ultrasonic propagation with a gradient descent iterative optimization algorithm. The findings are further validated in underwater experiments with a realistic 3D-printed skull phantom. This approach enables substantially faster holographic computation than previously reported techniques. The iterative process uses explicitly defined loss functions to bias the ultrasound field’s optimization parameters to specific desired characteristics, such as axial resolution, transversal resolution, coverage, and focal region uniformity, while eliminating the uncertainty associated with virtual sources in time-reversal techniques. The proposed techniques enable more rapid hologram computation and more flexibility in tailoring ultrasound fields for specific therapeutic requirements.

Re-evaluating winter carbon sink in Southern Ocean by recovering MODIS-Aqua chlorophyll-a product at high solar zenith angles

Satellite ocean color observations are extensively utilized in global carbon sink evaluation. However, the valid coverage of chlorophyll-a concentration (Chla, mg m−3) measurements from these observations is severely limited during autumn and winter in high latitude oceans. The high solar zenith angle (SZA) stands as one of the primary contributors to the reduced quality of Chla products in the high-latitude Southern Ocean during these seasons. This study addresses this challenge by employing a random forest-based regression ensemble (RFRE) method to enhance the quality of Moderate Resolution Imaging Spectroradiometer (MODIS) Chla products affected by high SZA conditions. The RFRE model incorporates the color index (CI), band-ratio index (R), SZA, sensor zenith angle (senz), and Rayleigh-corrected reflectance at 869 nm (Rrc(869)) as predictors. The results indicate that the RFRE model significantly increased the MODIS observed Chla coverage (1.03 to 3.24 times) in high-latitude Southern Ocean regions to the quality of standard Chla products. By applying the recovered Chla to re-evaluate the carbon sink in South Ocean, results showed that the Southern Ocean’s ability to absorb carbon dioxide (CO2) in winter has been underestimated (5.9–18.6 Tg C year−1) in previous assessments. This study underscores the significance of improving the Chla products for a more accurate estimation of winter carbon sink in the Southern Ocean.

Based on coverage evaluation design method study of factor low-orbit infrared remote sensing constellation configuration

Abstract To satisfy the infrared detection coverage demands of Low Earth Orbit (LEO) satellites in global missile surveillance, we have devised a comprehensive evaluation system for global missile infrared remote sensing coverage performance. By referencing Walker’s extensive and uninterrupted global coverage constellation layout, we conducted a thorough analysis of various constellation configuration parameters. This analysis aimed to assess the coverage efficiency of differently configured LEO networking satellites. Following a detailed comparative analysis, we settled on an LEO infrared remote sensing constellation configuration featuring an orbit height of 1150 km and an orbit inclination of 60°. After an in-depth examination of the capabilities of the infrared remote sensing constellation and the characteristics of the detection zone, we constructed a Blind Spot Compensation Constellation. This was achieved by integrating four additional LEO satellites with a 0° orbit inclination to bolster coverage in low-latitude regions. Using our comprehensive coverage evaluation system, we rigorously evaluated the ground coverage capabilities of multiple constellations. Notably, the Blind Spot Compensation Constellation achieved impressive coverage, reaching 100%, and excelled particularly in the latitude belt of 20° or less. Although the Original Constellation performed better in the 40° latitude belt compared to the Blind Spot Compensation Constellation, it showed some deficiencies in coverage at a 50 km altitude. Specifically, it averaged 18.417 gaps per day, with a coverage rate slightly below 100%. However, it achieved full coverage at other altitudes. To validate our findings, we conducted scenario simulations. For missile targets, the Original Constellation offered a maximum coverage multiplicity of 6, with a total access duration of 4539.1 seconds. On the other hand, the Blind Spot Compensation Constellation boasted a maximum coverage multiplicity of 8, with a total access duration of 5465.9 seconds. Importantly, both constellations fully covered the missile’s entire 1056-second lifecycle, showcasing commendable performance. In conclusion, the LEO infrared remote sensing constellation and its complementary counterpart, developed and rigorously tested in this study, not only meet the demands of continuous global detection but also cater to the priority detection needs of diverse geographical regions.

Exploring key determinants of COVID-19 vaccine hesitancy among individuals: An exploratory study globally.

SARS-CoV-2 virus gave rise to COVID-19 in late 2019 in Wuhan, China, and it quickly spread over the world to become a pandemic. The virus, which is mostly carried by respiratory droplets, spread at an unprecedented rate, causing a large number of deaths and extensive illness, necessitating lockdowns, travel bans, and social distancing policies by governments across the globe in an attempt to stop the spread, which severely disrupted daily life, the healthcare system, and economies.COVID-19 vaccines are biological materials designed to offer protection against the organism that causes the COVID-19 pandemic, SARS-CoV-2 virus, played a crucial role in stopping the virus's spread and lowering the burden on healthcare systems around the globe. Although Covid-19 vaccines offers benefits which includes the prevention of severe illness and death through the reduction of the chance of COVID-19-related serious illness, hospital stays, and death, it was met with hesitancy by some population on the basis of a complex web of interrelated causes, such as political division, misinformation, socioeconomic inequities, and past mistrust of healthcare systems.Vaccine hesitancy contributed to lower-than-expected vaccination coverage in many regions, preventing the achievement of herd immunity and allowing the virus to continue spreading. Exploring this key determinants of Covid-19 vaccine hesitancy among individuals all over the world and possible solutions, is the focus of this research.

Phenotype-driven genomics enhance diagnosis in children with unresolved neuromuscular diseases.

Establishing a molecular diagnosis remains challenging in half of individuals with childhood-onset neuromuscular diseases (NMDs) despite exome sequencing. This study evaluates the diagnostic utility of combining genomic approaches in undiagnosed NMD patients. We performed deep phenotyping of 58 individuals with unsolved childhood-onset NMDs that have previously undergone inconclusive exome studies. Genomic approaches included trio genome sequencing and RNASeq. Genetic diagnoses were reached in 23 out of 58 individuals (40%). Twenty-one individuals carried causal single nucleotide variants (SNVs) or small insertions and deletions, while 2 carried pathogenic structural variants (SVs). Genomic sequencing identified pathogenic variants in coding regions or at the splice site in 17 out of 21 resolved cases, while RNA sequencing was additionally required for the diagnosis of 4 cases. Reasons for previous diagnostic failures included low coverage in exonic regions harboring the second pathogenic variant and involvement of genes that were not yet linked to human diseases at the time of the first NGS analysis. In summary, our systematic genetic analysis, integrating deep phenotyping, trio genome sequencing and RNASeq, proved effective in diagnosing unsolved childhood-onset NMDs. This approach holds promise for similar cohorts, offering potential improvements in diagnostic rates and clinical management of individuals with NMDs.

International cooperation for the decarbonization of energy-intensive industries: unlocking the full potential

ABSTRACT This article investigates the state of global governance for the deep decarbonization of energy-intensive industries (EIIs) and identifies key options for mobilizing the so far underexploited potential of this global governance. Focusing on four main EIIs (i.e. iron and steel, cement and concrete, chemicals, and aluminium) the analysis is advanced in three steps. First, we establish the theoretical potential of international institutions to address the main barriers to EII decarbonization focusing on six main governance functions. Second, the article provides an up-to-date account of the global governance landscape for EII decarbonization and the contribution it has made to addressing the main barriers. This assessment also identifies major gaps and underexploited potentials of global governance. Finally, we systematically appraise key options for advancing global governance for EII decarbonization based on clear assessment criteria (membership, institutional capacity, legitimacy, feasibility). The major findings are that: (a) global governance has advanced significantly in the 2020s across all governance functions, in particular through the emergence of several initiatives focused on industrial decarbonization, including the recent Climate Club; (b) key priorities for advancing global EII decarbonization concern rules for collective action, means of implementation, landscape orchestration/coordination, and a more equal coverage of different sub-sectors and regions. We argue that the main barrier to addressing these priorities is rooted in (geo)politics rather than a lack of suitable institutions. Consequently, the global governance for EII decarbonization may best be advanced through incrementally developing existing rather than creating major new institutions.

AlScN-based quasi-static multi-degree-of-freedom piezoelectric MEMS micromirror with large mirror plate and high fill factor

A quasi-static multi-degree-of-freedom piezoelectric MEMS micromirror with large mirror plate and high fill factor based on AlScN is presented. It consists of two individual components, namely the mirror plate and the actuator. They are fabricated separately and vertically assembled together to form the final combination. In current case, a square mirror plate with side length of 5 mm is used. The actuator is designed into a gimbal-less structure, which involves a central connection platform with a mounting hole and four groups of piezoelectric actuators that are connected to the platform's corners via serpentine springs. This configuration provides multi-degree-of-freedom driving capabilities, allowing tip-tilt-piston mirror movement. The piezoelectric actuator is composed of three-stage cantilever-type actuation units that are connected in series, and they are intentionally arranged into S-shape so as to be completely hidden beneath the mirror plate. Moreover, the driving performance is further improved by optimizing the electrode coverage region on each actuation unit. As a result, not only large displacement but also nearly 100 % fill factor as well as high optical utilization efficiency can be achieved. From experimental results, the as-fabricated MEMS micromirror demonstrates static mechanical tilt angles of approximately ±2.2° about two orthogonal axes and piston vertical movement of ±54.9 μm within ±50 VDC driving voltage range with excellent linearity. Given the large mirror size, high fill factor and multi-degree-of-freedom motion advantages, the proposed micromirror could be found application perspective in light field shaping, free space optical communication and projection lithography areas.