Level Of Resolution Research Articles

A Technical Analysis of Digital Image and Video Processing

Video processing is the most emergent area of image processing in Research and Development. This paper, we present some advanced technology interrelated to video and image processing, which will provide a super-resolution high-quality most prominent visible light video for better human visualization and background motions or gesticulations of the human brain. There are two approaches for increasing the current resolution level of an image. The first one is the improvement of spatial resolution by reducing the size of pixels through the techniques of sensor manufacturing by about 40 M m 2 for a 0.35 M m CMOS process and the second approach is the enhancement of chip size that also enhances the capacitance. In video processing, we mainly focus on object images, i.e. any form of signal processing in which the input is an image and the output is a photograph or a frame of video. So, it will be better to converge over techniques of digital image processing. In the proposed algorithm (MHI Simulink model), edge extraction is performed to find the precious area of MRI and CT-Scan images. Using FPGA, edge detection methods have been implemented over scanned images to get better accuracy. The accuracy of the proposed method has been compared with Prewitt and Sobel’s edge detection techniques. The proposed method has given better accuracy than Prewitt and Sobel methods. Finally, this paper shows future directions for researchers to enhance the characteristics of digital image and video processing.

Development of new analytical methods for the quantification of organic acids, chlorogenic acids and caffeine in espresso coffee by using solid-phase extraction (SPE) and high-performance liquid chromatography-diode array detector (HPLC-DAD)

Acidity is an important parameter in coffee, contributing to aroma and flavor, imparting fruity notes, and improving the gloss of the coffee, making the beverage more interesting. In this study, two analytical methods were proposed to quantify the content of nine organic acids, caffeine, phenolic acids, and four chlorogenic acids in espresso coffee using an HPLC-DAD instrument. In addition, a new solid-phase extraction (SPE) sample clean-up procedure for organic acids has been optimized. The newly developed analytical methods were characterized by satisfactory recovery levels of sample clean-up procedure (41.798.6%) and good resolution of all peaks in both chromatography separations. In addition, the investigated validation parameters implied good repeatability, sensitivity and linearity. These methods were applied to espresso samples with three different roasting degrees (light, medium, and dark) of the same coffee variety (100% Arabica) to study the effects of the roasting process on the content of caffeine, organic and chlorogenic acids. The caffeine content was relatively stable to heat. The concentration of chlorogenic acids decreased due to roasting while the total organic acid content increased, with the formation of acetic and lactic acids in medium and dark roasting. Therefore, these new approaches can be considered as reference methods for the determination of carboxylic acids in coffee.

Forming Gas Giants around a Range of Protostellar M-dwarfs by Gas Disk Gravitational Instability

Recent discoveries of gas giant exoplanets around M-dwarfs from transiting and radial velocity surveys are difficult to explain with core-accretion models. We present here a homogeneous suite of 162 models of gravitationally unstable gaseous disks. These models represent an existence proof for gas giants more massive than 0.1 Jupiter masses to form by the gas disk gravitational instability (GDGI) mechanism around M-dwarfs for comparison with observed exoplanet demographics and protoplanetary disk mass estimates for M-dwarf stars. We use the Enzo 2.6 adaptive mesh refinement (AMR) 3D hydrodynamics code to follow the formation and initial orbital evolution of gas giant protoplanets in gravitationally unstable gaseous disks in orbit around M-dwarfs with stellar masses ranging from 0.1 M ⊙ to 0.5 M ⊙. The gas disk masses are varied over a range from disks that are too low in mass to form gas giants rapidly to those where numerous gas giants are formed, therefore revealing the critical disk mass necessary for gas giants to form by the GDGI mechanism around M-dwarfs. The disk masses vary from 0.01 M ⊙ to 0.05 M ⊙ while the disk to star mass ratios explored the range from 0.04 to 0.3. The models have varied initial outer disk temperatures (10–60 K) and varied levels of AMR grid spatial resolution, producing a sample of expected gas giant protoplanets for each star mass. Broadly speaking, disk masses of at least 0.02 M ⊙ are needed for the GDGI mechanism to form gas giant protoplanets around M-dwarfs.

Wind Tunnel and Grid Resolution Effects in Large-Eddy Simulations of the High-Lift Common Research Model

This paper describes the application of a compressible large-eddy simulation (LES) solver to the flow over the High-Lift Common Research Model (CRM-HL) in landing configuration, a complex external aerodynamic flow configuration with deployed slats, flaps, a flow-through nacelle, and the associated brackets/fairings on the high-lift devices. The bulk Mach number is (0.2) and the mean-aerodynamic-chord-based Reynolds number is typical of a wind tunnel experiment (5.49E6). A key development in these simulations relative to previous work is that this work serves to establish robustness of LES methods to Reynolds number and aircraft configuration. Previous studies focused on the Japan Aerospace Exploration Agency Standard Model, which featured a nearly 3× lower Reynolds number than the present CRM-HL investigation and less aggressive wing/slat leading-edge curvature than the CRM-HL geometry, which led to lower leading-edge pressure suction peak magnitudes, both of which led to less stringent grid resolution requirements. In these LES simulations, an algebraic equilibrium wall modeling approach is employed along with a dynamic implementation of the Smagorinsky subgrid-scale model. The calculations are carried out in both a free air setting and one that includes the wind tunnel facility at seven angles of attack at five grid resolution levels, ranging from ≈10 to 1500 million control volumes. In free air, the solutions show decreasing sensitivity to the grid with each successive refinement level and systematically approach the experimental lift coefficient data as the grid is refined, with the 1.5 billion control volume case showing excellent agreement with the corrected experimental data. The simulations in both free air and in the wind tunnel predict a stall mechanism featuring a large inboard juncture stall and a nose-down break in the pitching moment curve, both of which agree with the experimental observations. The accuracy of the simulations is assessed via comparisons of integrated forces/moments, surface pressures, and surface skin friction visualizations. Graphics processing unit (GPU) acceleration of the charLES solver results in tractable turnaround times that make LES a useful tool in the aerospace industry design cycle. Recent GPU acceleration of the flow solver has made LES solutions that are highly accurate in lift/drag/moment for relevant high-lift aircraft flows achievable within about 5 h of wall time on 600 GPU cores.

Alternative molecular and genomic strategies to provide a rapid response to alerts concerning the introduction of new emerging SARS-CoV-2 variants: the Omicron alert.

During the COVID-19 pandemic, several SARS-CoV-2 variants of concern (VOCs) of particular relevance emerged. Early detection of VOCs entering a country is essential to control spread. The alert triggered by the first suspected case of the Omicron variant in Spain in a traveler arriving from South Africa in November 2021 provided a unique opportunity to evaluate four different methodological strategies tailored to rapid identification of Omicron. The different approaches were designed to respond to the different technical resources available in different settings. First, we used melting probes in RT-PCR to determine the presence of four Omicron signatures (K417N, E484A, P681H, and absence of L452R): three probes showed deviations in temperature (Tm) values relative to the reference codons (E484K-15.8°C, P681H-5.2°C, and L452R-7.2°C) and one maintained the reference value (K417N). The deviation in Tm of P681H suggested the presence of the characteristic Omicron N679K mutation in the probe hybridization region; these data pointed to the presence of Omicron alleles. Second, the presence of 29 of the 33 characteristic single nucleotide polymorphisms (SNPs) in the Omicron variant S-gene was identified by Sanger sequencing of nine amplicons. The final two strategies involved identification of 47 of the 50 non-synonymous and indel mutations attributed to Omicron by rapid nanopore whole genome sequencing (WGS) and by Illumina WGS technology. These strategies enabled us to pre-assign the first Omicron case in Spain with high certainty 2 h after receipt of RNA and to confirm it genomically 3 h later, so that the Public Health authorities could be rapidly notified. IMPORTANCE The study presents different experimental alternatives to identify new variants of concern (VOCs) of SARS-CoV-2 entering a certain population. Early detection of a new VOC is crucial for surveillance and control of spread. The objective is to provide laboratories with tools adapted to their resource capabilities that offer a sufficient level of resolution to rule out, confirm, or pre-assign the presence of a suspected VOC. The study describes four different techniques that were applied simultaneously to the first suspected Omicron case in Spain, highlighting the level of resolution and response time achieved in each case. These techniques are based on the detection of mutations in the S-gene of the virus that can easily adapt to potential emerging variants. The results of the study allow any laboratory to prepare for new alerts of SARS-CoV-2 VOCs.

Impact of Spectral Resolution and Signal-to-Noise Ratio in Vis–NIR Spectrometry on Soil Organic Matter Estimation

Recently, considerable efforts have been devoted to the estimation of soil properties using optical payloads mounted on drones or satellites. Nevertheless, many studies focus on diverse pretreatments and modeling techniques, while there continues to be a conspicuous absence of research examining the impact of parameters related to optical remote sensing payloads on predictive performance. The main aim of this study is to evaluate how the spectral resolution and signal-to-noise ratio (SNR) of spectrometers affect the precision of predictions for soil organic matter (SOM) content. For this purpose, the initial soil spectral library was partitioned into to two simulated soil spectral libraries, each of which were individually adjusted with respect to the spectral resolutions and SNR levels. To verify the consistency and generality of our results, we employed four multiple regression models to develop multivariate calibration models. Subsequently, in order to determine the minimum spectral resolution and SNR level without significantly affecting the prediction accuracy, we conducted ANOVA tests on the RMSE and R2 obtained from the independent validation dataset. Our results revealed that (i) the factors significantly affecting SOM prediction performance, in descending order of magnitude, were the SNR levels > spectral resolutions > estimation models, (ii) no substantial difference existed in predictive performance when the spectral resolution fell within 100 nm, and (iii) when the SNR levels exceeded 15%, altering them did not notably affect the SOM predictive performance. This study is expected to provide valuable insights for the design of future optical remote sensing payloads aimed at monitoring large-scale SOM dynamics.

Determination of the factors responsible for the tropism of SARS-CoV-2-related bat coronaviruses to Rhinolophus bat ACE2.

The efficiency of infection receptor use is the first step in determining the species tropism of viruses. After the coronavirus disease 2019 pandemic, a number of SARS-CoV-2-related coronaviruses (SC2r-CoVs) were identified in Rhinolophus bats, and some of them can use human angiotensin converting enzyme 2 (ACE2) for the infection receptor without acquiring additional mutations. This means that the potential of certain SC2r-CoVs to cause spillover from bats to humans is "off-the-shelf." However, both SC2r-CoVs and Rhinolophus bat species are highly diversified, and the host tropism of SC2r-CoVs remains unclear. Here, we focus on two Laotian SC2r-CoVs, BANAL-20-236 and BANAL-20-52, and determine how the tropism of SC2r-CoVs to Rhinolophus bat ACE2 is determined at the amino acid resolution level.

Rapid, high-throughput phenotypic profiling of endosymbiotic dinoflagellates (Symbiodiniaceae) using benchtop flow cytometry.

Endosymbiotic dinoflagellates (Family Symbiodiniaceae) are the primary producer of energy for many cnidarians, including corals. The intricate coral-dinoflagellate symbiotic relationship is becoming increasingly important under climate change, as its breakdown leads to mass coral bleaching and often mortality. Despite methodological progress, assessing the phenotypic traits of Symbiodiniaceae in-hospite remains a complex task. Bio-optics, biochemistry, or "-omics" techniques are expensive, often inaccessible to investigators, or lack the resolution required to understand single-cell phenotypic states within endosymbiotic dinoflagellate assemblages. To help address this issue, we developed a protocol that collects information on cell autofluorescence, shape, and size to simultaneously generate phenotypic profiles for thousands of Symbiodiniaceae cells, thus revealing phenotypic variance of the Symbiodiniaceae assemblage to the resolution of single cells. As flow cytometry is adopted as a robust and efficient method for cell counting, integration of our protocol into existing workflows allows researchers to acquire a new level of resolution for studies examining the acclimation and adaptation strategies of Symbiodiniaceae assemblages.

Resonant Auger spectromicroscopy in ultrathin Fe films on W(110)

L3MM Auger transition is measured near the L3 resonance of ferromagnetic Fe films on W(110). The kinetic energies of the Auger peaks display the typical Raman behaviour for photon energies well below the absorption threshold, where the Auger energy follows the changes in the photon energy. Classical Auger behaviour with constant kinetic energy sets in at about 1.5 eV below the L3 resonance independently from the number of Fe layers down to the monolayer thickness. Strong x-ray circular magnetic dichroism is observed at the L3 edge in the entire L3MM Auger spectrum. Different Auger features originating from the final state with two 3p core holes show slight variations in the dichroic signal, which is attributed to the exchange interaction between the core holes and the valence band. Finally, XMCD-PEEM magnetic domain imaging using Auger electrons is demonstrated with a high level of contrast and lateral resolution approaching that of imaging with secondary photoelectrons.

Transcriptional and epigenetic decoding of the microglial aging process

As important immune cells, microglia undergo a series of alterations during aging that increase the susceptibility to brain dysfunctions. However, the longitudinal characteristics of microglia remain poorly understood. In this study, we mapped the transcriptional and epigenetic profiles of microglia from 3- to 24-month-old mice. We first discovered unexpected sex differences and identified age-dependent microglia (ADEM) genes during the aging process. We then compared the features of aging and reactivity in female microglia at single-cell resolution and epigenetic level. To dissect functions of aged microglia excluding the influence from other aged brain cells, we established an accelerated microglial turnover model without directly affecting other brain cells. By this model, we achieved aged-like microglia in non-aged brains and confirmed that aged-like microglia per se contribute to cognitive decline. Collectively, our work provides a comprehensive resource for decoding the aging process of microglia, shedding light on how microglia maintain brain functions.

Analysis and elimination of translation disturbance for patch effect measurement with a torsion pendulum

Patch effect on conductive surfaces is one of the critical noise sources in many scientific experiments like space gravity programs and gravitational wave detection missions. A high-precision probe-torsion instrument has been developed on ground for measuring patch effect. However, the translation mode of the probe resulting from the environmental disturbance will inevitably affect the measurement in the concerned torsion degree of freedom. In this paper, combining the theoretical analysis as well as the confirmatory experiment, the method based on data analysis is adopted to eliminate the translation effect, finally realizing the best surface potential resolution level of 20 µV Hz.

A Multi-Framework of Google Earth Engine and GEV for Spatial Analysis of Extremes in Non-Stationary Condition in Southeast Queensland, Australia

The frequency and severity of extremes, including extreme precipitation events, extreme evapotranspiration and extreme water storage deficit events, are changing. Thus, the necessity for developing a framework that estimates non-stationary conditions is urgent. The aim of this paper is to develop a framework using the geeSEBAL platform, Generalised Extreme Value (GEV) models and spatiotemporal analysis techniques that incorporate the physical system in terms of cause and effect. Firstly, the geeSEBAL platform has enabled the estimation of actual evapotranspiration (ETa) with an unprecedented level of spatial-temporal resolution. Following this, the Non-stationary Extreme Value Analysis (NEVA) approach employs the Bayesian method using a Differential Evolution Markov Chain technique to calculate the frequency and magnitude of extreme values across the parameter space. Station and global climate datasets have been used to analyse the spatial and temporal variation of rainfall, reference evapotranspiration (ETo), ETa and water storage (WS) variables in the Lockyer Valley located in Southeast Queensland (SEQ), Australia. Frequency analysis of rainfall, ETa, and water storage deficit for 14 stations were performed using a GEV distribution under stationary and non-stationary assumptions. Comparing the ETa, ETo and ERA5 rainfall with station data showed reasonable agreement as follows: Pearson correlation of 0.59–0.75 for ETa, RMSE of 45.23–58.56 mm for ETa, Pearson correlation of 0.96–0.97 for ETo, RMSE of 73.13–87.73 mm for ETo and Pearson correlation of 0.87–0.92 for rainfall and RMSE of 37.53–57.10 mm for rainfall. The lower and upper uncertainty bounds between stationary and non-stationary conditions for rainfall station data of Gatton varied from 550.98 mm (stationary) to 624.97 mm (non-stationary), and for ERA5 rainfall datasets, 441.30 mm (stationary) to 450.77 mm (non-stationary). The results demonstrate that global climate datasets underestimate the difference between stationary and non-stationary conditions by 9.47 mm compared to results of 73.99 mm derived from station data. Similarly, the results demonstrate less variation between stationary and non-stationary conditions in water storage, followed by a sharp variation in rainfall and moderate variation in evapotranspiration. The findings of this study indicate that neglecting the non-stationary condition in some hydrometeorological variables can lead to underestimating their amounts. This framework can be applied to any geographical area for estimating extreme conditions, providing valuable insights for infrastructure planning and design, risk assessment and disaster management.

Effectiveness of Wavelet Denoising on Secondary Ion Mass Spectrometry Signals

Wavelet theory has already achieved huge success. For Secondary Ions Mass Spectrometry (SIMS) signals, denoising the secondary signal, which is altered by the measurement, is considered that an essential step prior to applying such a signal processing technique that aims enhance the SIMS signals.The most efficient and widely used wavelet denoising method is based on wavelet coefficient thresholding. This process involves three important steps; wavelet decomposition: the input signals are decomposed into wavelet coefficients, thresholding: the wavelet coefficients are modified according to a threshold, and reconstruction: the modified coefficients are used in an inverse transform to obtain the noise-free-signal. Several researchers have used thresholding wavelet denoising techniques.
 The choice of wavelet type and the level of resolution can have a significant influence; it is important to note that the choice of resolution level depends on the type of signal we are dealing with, the nature of the present noise, and our specific goals for the denoised signal. It is generally recommended to test different resolution levels and evaluate their impact on the quality of the denoised signal before making a final decision. Moreover, the results obtained in wavelet denoising can be significantly influenced by the selection of wavelet types. The chosen wavelet type plays a crucial role in the extraction of signal details. Indeed, the effectiveness of denoising the MD6 sample has been demonstrated by the results obtained with sym4, db8, Haar and coif5 wavelets? These wavelets have effectively reduced noise while preserving crucial signal information, leading to an enhancement in the quality of the denoised signal.

Abstract 22 Anomalous HLA-A Typing Found in Patient Using PacBio Sequencing Technology

Abstract Introduction Labcorp’s DNA Identification division offers HLA typing at various levels of resolution using commercially available kits as well as lab developed assays. A patient sample was received by the lab requiring HLA typing for a disease association screen, and was found to have anomalous HLA-A results. Objectives To investigate a patient typing with results initially showing multiple variants to any known reference sequence. Methods This sample was sequenced using a lab developed whole gene assay that utilizes Pacific Biosciences’s® (PacBio) SMRT® NGS sequencing technology on a Sequel® I with LAA2 contig generation. Due to ambiguous results, the sample was repeated for confirmation using the same test, but a more sensitive data pipeline was used. Subreads coming off of the sequencer were converted to high fidelity or Closed Circular Consensus (CCS) reads using the PBAA tool from PacBio®. The sample was also processed with the GenDx NGSgo®-MX11-3 HLA typing kit with Illumina® sequencing, and the results were sent to GenDx for analysis. Results Initial testing yielded a high resolution fourth field result for HLA Class I, though the result remained ambiguous. Repeat sequencing resulted three HLA-A alleles with a similar number of CCS reads. The sample was typed as A*01:01:01:01, A*02:01:01:01, and A*02:New which contained a large exonic deletion compared to the A*02:01:01:01 reference. GenDX output confirmed previous findings, indicating a clear first allele of A*01:01:01:01, and reads for the second allele split between A*02:01:01:01 and A*02:New. Discussion Using Pacbio® sequencing technology with CCS analysis, and confirmation with GenDx technology, it was determined that this individual possesses 3 HLA-A alleles. When aligned with 02:01:01:01, both Pacbio® and GenDx assays determined the A*02:New allele to have a 34bp deletion in exon 2 (position 196-229). As a result of the frame shift caused by this deletion, a premature stop codon was found 43bp downstream from the anomaly, potentially rendering this allele null. Possible explanations for the presence of three HLA-A alleles in one patient include partial allele loss during an autoimmune event, a mutation within a chromosomal duplication of the region, or the patient has undergone a hematopoietic stem cell transplant.

Reconciling the variability in the biological response of marine invertebrates to climate change.

As climate change increases the rate of environmental change and the frequency and intensity of disturbance events, selective forces intensify. However, given the complicated interplay between plasticity and selection for ecological - and thus evolutionary - outcomes, understanding the proximate signals, molecular mechanisms and the role of environmental history becomes increasingly critical for eco-evolutionary forecasting. To enhance the accuracy of our forecasting, we must characterize environmental signals at a level of resolution that is relevant to the organism, such as the microhabitat it inhabits and its intracellular conditions, while also quantifying the biological responses to these signals in the appropriate cells and tissues. In this Commentary, we provide historical context to some of the long-standing challenges in global change biology that constrain our capacity for eco-evolutionary forecasting using reef-building corals as a focal model. We then describe examples of mismatches between the scales of external signals relative to the sensors and signal transduction cascades that initiate and maintain cellular responses. Studying cellular responses at this scale is crucial because these responses are the basis of acclimation to changing environmental conditions and the potential for environmental 'memory' of prior or historical conditions through molecular mechanisms. To challenge the field, we outline some unresolved questions and suggest approaches to align experimental work with an organism's perception of the environment; these aspects are discussed with respect to human interventions.

An Enhanced Earthquake Risk Analysis using H3 Spatial Indexing

Risk assessment is the first step in disaster risk reduction and crucial for types of disasters with potentially significant impacts, such as earthquakes. Besides the direct impact of very devastating shocks, earthquakes can also trigger cascading events that are no less damaging such as landslides, liquefaction, and tsunamis. This study aims to apply the H3 spatial indexing system to improve earthquake risk assessment using Sorong City as a case study, and compare the result of H3-based risk assessment with the normative risk assessment in Indonesia as defined by relevant Perka BNPB (Badan Nasional Penanggulangan Bencana/National Disaster Management Authority) 2/2012. H3 is an open-source geospatial indexing system developed by Uber, which utilizes a hierarchical hexagonal grid for indexing, calculations, and visualization. The hexagonal cells in the grid have equidistant neighbors and possess the property of expanding neighboring rings, approximating circles and optimizing space filling. The H3 spatial index finds extensive applications in earthquake hazard, vulnerability, capacity, and risk assessment systems. The value of each parameter is entered into each hexagon so that in the end each hexagon has its risk index value. The study shows that the use of H3 in earthquake risk assessment can provide a more detailed level of analysis and indirectly does not depend on regional administrative boundaries. Technically, this advantage provides a more efficient calculation method and is also easier to modify partially both spatially and in terms of the parameters used. Based on the performance evaluation results on the spatial join aspect, H3 provides much faster performance compared to traditional indexing systems. Hence, the H3 spatial index will be very useful to meet the need for an earthquake risk assessment on a larger scale with a higher level of resolution.

Registration between 2D and 3D Ultrasound Images to Track Liver Blood Vessel Movement.

For the accurate positioning of surgical tools, conventional intraoperative navigation systems have been developed to recognize the relationship between target positions and the tools. However, since an internal organ is deformed during the operation, registration between realtime two-dimensional (2D) ultrasound images and three-dimensional (3D) CT or MRI images is not always effective. Therefore, this study developed image registration between 2D and 3D ultrasound images considering deformation for tracking target vessel movement in the liver. 3D ultrasound image was obtained in advance with 3D coordinates, including the target vessel. Then real-time 2D images and ultrasound probe position were simultaneously acquired using a 3D position sensor. We applied multiple image resolution registration, where rapid and fine optimizations can be expected at higher and lower levels, respectively. Meanwhile, the gradient descent method was adopted for the optimization, which determines the relative arrangements to obtain maximum similarity between 2D and 3D images. We experimentally established resolution level parameters using a phantom before applying it to track liver blood vessel movements in a normal healthy subject. Comparing the 2D images and the registered images, although the approach has some limitations in tracking large displacement, we confirmed that the cross-section of the target blood vessel was clearly visualized. This method has the potential for an ultrasound therapy targeting blood vessels under natural respiration conditions.

Quantization error for weak RF simultaneous signal estimation

In a congested signal environment, it is difficult to obtain estimates of weak RF signal parameters. Determining signal parameter estimates in real time is a challenge for electronic warfare receivers that aim to receive multiple simultaneous signals. Prior work provided estimates of weak signal parameters (weak signal frequency and weak signal amplitude) without taking into account any error introduced by analog-to-digital converters that are inherently part of digital signal processing systems. In order to obtain realistic estimates, we need to take error introduced by an ADC into account. The primary aim of this paper is to quantify error introduced by a single ideal ADC as a function of angle. This paper presents a method to estimate angle resolution and quantization levels in N-bit analog-to-digital converters (ADCs) for use in a weak radiofrequency (RF) simultaneous signal estimation process. The paper quantifies the error in the angle quantization of an N-bit ADC for an input complex signal that is the instantaneous frequency obtained for the situation in which there are two simultaneous signals (with one strong signal and one weak signal) in a weak RF simultaneous signal estimation process. The presented method describes the process to determine the angle quantization range, angle quantization uncertainty, and angle quantization error. This approach has potential applications in electronic warfare (EW) systems. The approach also has potential for assessing ADC performance for measurements that approach the quantum limit. Results are presented for 1-bit, 2-bit, 3-bit, and 10-bit ADCs.

PUBLIC COMPLAINTS COMMISSION, CONFLICT RESOLUTIONS AND GOOD GOVERNANCE IN ADAMAWA STATE, NIGERIA, 2015- 2021

This Research is Appraisal of the Role of Public Complaints Commission (Ombudsman) on Conflict Resolution and Promotion of Good Governance in Adamawa State, Nigeria, 2015- 2021. The objective of the study is to find out the conflict resolution methods deploy by the Public Complaints Commission and also to determine its effectiveness. The study is found out the factors that hinders the activities of Public Complaints Commission and to determine whether the existing legal framework of Public Complaints Commission constitute an obstacle to the level of conflict resolution and promotion of good governance in Adamawa State. Relevant literatures were reviewed in line with the study objectives. The study also adopts mixed methods sampling techniques to select respondents from Adamawa State Ministries, Departments and Agencies and Local Government Councils. Total sample of 400 respondents were drawn from sample frame. Both quantitative and qualitative methods of data collection were employed for the study. Finding of the study reveals that there is little awareness on the activities of Adamawa State Public Complaints Commission on conflict resolution and promotion of good governance in Adamawa State. The study also reveals that mediation is the methods of conflict resolution mostly employed by the Adamawa State Public Complaints Commission and it was very effective during the period under review. It was also found out that inadequate funding is the major impediment to the effective and efficient performance of Adamawa State Public Complaints Commission on conflict resolution and promotion of good governance in Adamawa State. The finding of the study also shows that the existing legal framework of Public Complaints Commission constitutes an obstacle to the level of conflict resolution and promotion of good governance in Adamawa State. The findings of the study therefore reveal that the structural functional theory has not work in the effective and efficient performance of Public Complaints Commission, Adamawa State. These findings were very consistent with the overall objectives of the study. In view of these findings, the study recommends that the Commission should be adequately funded and the independence should be safeguarded. The government should also review and strengthen the legal framework of the Public Complaints Commission. Also, there is the need for aggressive public enlightenment through advocacy, seminars, workshops, mass and print media to propagate the activities and promote better understanding and public awareness on the activities of the Commission on conflict resolution and promotion of good governance in Adamawa State.

Neighbourhood watch: genomic epidemiology of SARS-CoV-2 variants circulating in a German federal state, Mecklenburg-Western Pomerania, in 2020–2022

ABSTRACT Global and even national genome surveillance approaches do not provide the resolution necessary for rapid and accurate direct response by local public health authorities. Hence, a regional network of microbiological laboratories in collaboration with the health departments of all districts of the German federal state of Mecklenburg-Western Pomerania (M-V) was formed to investigate the regional molecular epidemiology of circulating SARS-CoV-2 lineages between 11/2020 and 03/2022. More than 4750 samples from all M-V counties were sequenced using Illumina and Nanopore technologies. Overall, 3493 (73.5%) sequences fulfilled quality criteria for time-resolved and/or spatially-resolved maximum likelihood phylogenic analyses and k-mean/ median clustering (KMC). We identified 116 different Pangolin virus lineages that can be assigned to 16 Nextstrain clades. The ten most frequently detected virus lineages belonged to B.1.1.7, AY.122, AY.43, BA.1, B.1.617.2, BA.1.1, AY.9.2, AY.4, P.1 and AY.126. Time-resolved phylogenetic analyses showed the occurrence of virus clades as determined worldwide, but with a substantial delay of one to two months. Further spatio-temporal phylogenetic analyses revealed a regional outbreak of a Gamma variant limited to western M-V counties. Finally, KMC elucidated a successive introduction of the various virus lineages into M-V, possibly triggered by vacation periods with increased (inter-) national travel activities. The COVID-19 pandemic in M-V was shaped by a combination of several SARS-CoV-2 introductions, lockdown measures, restrictive quarantine of patients and the lineage specific replication rate. Complementing global and national surveillance, regional surveillance adds value by providing a higher level of surveillance resolution tailored to local health authorities.