Marginal Deviation Research Articles

Yttrium-encapsulated fullerene (Y@C80) mono-doping with As, Bi, Sb, and P for the enhanced sensing of methylmalonic acid (MMA) as a biomarker for vitamin B12 deficiency: A DFT study

The development of new approaches or approaches for the detection of methylmalonic acid from biological samples is now necessary for early diagnosis of vitamin B12 deficiency and appropriate treatment. In this study, Yttrium-encapsulated fullerene (Y@C80) doped with arsenic (As), bismuth (Bi), phosphorous (P), and antimony (Sb) was investigated for its ability to sense methylmalonic acid (MMA) as a biomarker using M06-2X/GenECP/def2svp/LanL2DZ method. The nanostructural analysis showed a marginal deviation in the bond lengths between atoms of the structure upon optimization of the structures interacting with the MMA biomarker, which demonstrated the stability of the system for sensing. The HOMO-LUMO reactivity descriptor revealed that the compound was reactive toward the sensing of the MMA biomarker, as the various systems MMA_As_Y@C80, MMA_Bi_Y@C80, MMA_P_Y@C80, and MMA_Sb_Y@C80 demonstrated relatively short energy gaps of 2.039 eV, 2.025 eV, 2.135 eV, and 2.023 eV, respectively. The nanomaterial strongly adsorbed the biomarker, as indicated by the negative adsorption energies of −0.47075 eV, −0.70478 eV, 0.9034 eV, and −0.5388 eV corresponding to MMA_As_Y@C80, MMA_Bi_Y@C80, MMA_P_Y@C80, and MMA_Sb_Y@C80, respectively; however, MMA-P-Y@C80 showed a weaker ability to sense the biomarker. Additionally, the recovery time after the detection of the biomarker was relatively short, comparable to the increase in the adsorption strength, with MMA-Bi-Y@C80 having the shortest recovery time (3.829 × 10−37). This is significant for the development of a highly sensitive and efficient technique for methylmalonic acid (MMA) biomarker sensing.

Automatic Negation Detection for Semantic Analysis in Arabic Hotel Reviews Through Lexical and Structural Features: A Supervised Classification

One significant challenge in sentiment analysis is the presence of negation, which reverses the meanings of sentences, transformingpositive statements into negative ones and impacting the sentiment conveyed in the text. This issue is particularly pronounced in Arabic, a language known for its complex morphology. Detecting negation is crucial for enhancing sentiment analysis performance and various natural language processing applications. This paper presents an approach for automatically detecting negation in user-generated Arabic hotel reviews through lexical and structural features. It comprises several stages: data collection, text pre-processing, feature extraction, supervised learning classification, and evaluation. The study employed multiple supervised classification techniques, including naïve Bayes, random forest, logistic regression, support vector machines, and deep learning, to analyse lexical and structural features extracted from the dataset. The results of the experiments yielded promising outcomes, demonstrating the feasibility of the approach for practical applications. The classifiers exhibited highly comparable performance in identifying negation, with only marginal deviations in their performance metrics. Notably, the deep learning classifier consistently emerged as the top performer, achieving an exceptionally high overall accuracy rate of 99.24 percent, surpassing established benchmarks in Arabic text processing and underscoring its potential for practical applications. These findings hold significant implications for advancing Arabic text processing, particularly in sentiment analysis and related NLP tasks. The high accuracy of 99.24 percent achieved by the deep learning classifier highlights its robustness in accurately detecting negation, a critical challenge in sentiment analysis. This classifier performance demonstrates the potential to be integrated into real-world applications, such as automated review systems and opinion mining tools, where accurate sentiment interpretation is essential.

Tuning diagonal scale matrices for HMC

Three approaches for adaptively tuning diagonal scale matrices for HMC are discussed and compared. The common practice of scaling according to estimated marginal standard deviations is taken as a benchmark. Scaling according to the mean log-target gradient (ISG), and a scaling method targeting that the frequency of when the underlying Hamiltonian dynamics crosses the respective medians should be uniform across dimensions, are taken as alternatives. Numerical studies suggest that the ISG method leads in many cases to more efficient sampling than the benchmark, in particular in cases with strong correlations or non-linear dependencies. The ISG method is also easy to implement, computationally cheap and would be relatively simple to include in automatically tuned codes as an alternative to the benchmark practice.

Column flotation hydrodynamics operating in the heterogeneous regime estimated by electrical resistance tomography and multi-phase CFD model

ABSTRACT This paper investigates the two-phase flow hydrodynamics of a column flotation operated from a homogeneous to a heterogeneous flow regimes using experimental and computational fluid dynamics (CFD) techniques. Experiments were conducted in a lab scale column flotation of 0.1 m internal diameter and 2.5 m length at various superficial gas velocities using a dual plane electrical resistance tomography (ERT). The mean gas holdup increased from 2 to 18% with the increase in superficial gas velocity from 0.6 to 7.2 cm/s. The gas holdup-based bubble swarm velocity method identified four distinct flow regimes, i.e. homogeneous bubbling regime, narrow discrete bubbling regime, a sustained helical flow regime and churn turbulent flow regime in the column. Further, transient simulations were conducted using a two-fluid model coupled with a population balance model to assess the flow behavior inside the column. Virtual mass, lift and drag forces were incorporated into the model to account for the interphase forces. Numerical simulations predicted mean gas holdup was matching with the experimental data at low gas velocities (<2.4 cm/s), and a marginal deviation was noted at higher gas velocities (>2.4 cm/s). The predicted radial gas holdup profiles were found to change from flatter to parabolic with the increase in gas velocities, i.e. similar to the experiments. The effect of particle size on the rate constant and recovery was estimated with Luttrell and Yoon’s performance model using the particle floatability input data and the two-phase experimental data. The developed CFD model can be useful to optimize the operating and design parameters for efficient operation of the column flotation process.

Computational and experimental substantiation of the operability of seals of localizing safety system elements of power units with VVER

The relevance of this work is determined by the need to predict the operation of sealing assemblies for elements of localizing safety systems (LSSs) of power units with VVER, which include (penetrations, hatches, locks, doors and other elements of hermetic fencing (GF) in operational modes. Operational modes are understood as modes of normal operation, modes of violation of normal operation, as well as emergency situations. During the manufacture and operation of LSS elements, the problem arises of uneven protrusion of a double-row rubber seal from the grooves in the web of the LSS element, which leads to the need to clarify the integral compression force of the seal as a whole for this element. The problem is caused by the imperfection of the manufacturing technology of large canvases for LSS elements (doors, hatches, locks: the perimeter of the seals can reach 10-20 m, the diameter of the canvas 2-6 m) and the need to withstand stringent technological requirements for flatness, parallelism and marginal deviations in linear and angular dimensions. The manufacture of overall structures is complicated by the presence of welded joints, heat treatment, and the complexity of metalworking. Compression force of the PNAE rubber gasket-7-002-86 it is not regulated, therefore, for the reliable design of gasket compression mechanisms, the magnitude of this force was determined. Based on the obtained results of tests of rubber seals for tightness and cyclic loading [7], an assessment of the tightness of the applied rubber seals is performed, calculations of deformations of rubber seals are performed using the FEM software package. Recommendations have been developed to increase the reliability of seal assemblies for elements of localizing safety systems (LSSs) of VVER power units in operational modes and to select the compression value to determine the necessary force to ensure tightness at the beginning of operation and after 5000 opening-closing cycles.

SPICE Modelling-Assisted evaluation of dynamic on-resistance characterization in Schottky p-GaN HEMTs amid synchronous buck transient instabilities

This study addresses the critical gap in dynamic on-resistance characterization for GaN HEMTs within the initial unstable state in a non-isolated DC-DC converter, where the output voltage and currents fluctuate and exhibit overshoots or undershoots before stabilizing to their steady-state values, a domain within solar photovoltaic (PV) Maximum Power Point Tracking (MPPT) implementations which is crucial yet insufficiently examined. The authors present a novel multi-pulse test circuit within a synchronous buck converter configuration, complemented by SPICE simulation. This combination allows for the accurate assessment of clamping circuits' performance during transient states, significantly improving the precision of RDS(ON) measurements in unsteady phases. The approach deviates from conventional methods by merging empirical data with simulation insights to validate the efficacy of clamping circuits. The experimental results affirm the methodology's precision, with the highlighted Circuit V showcasing a marginal deviation of 2.32 % from existing benchmarks. This finding substantiates the method's dependability and practicality contributing to the GaN power electronics field. In addition, this research provides a powerful analytical tool for RDS(ON) evaluation, culminating in the design of a test PCB that synergizes with both simulated and empirical evidence, contributing future research in GaN HEMT power converter applications.

A step toward simplified dosimetry of radiopharmaceutical therapy via SPECT frame duration reduction

Despite being time-consuming, SPECT/CT data is necessary for accurate dosimetry in patient-specific radiopharmaceutical therapy. We investigated how reducing the frame duration (FD) during SPECT acquisition can simplify the dosimetry workflow for [177Lu]Lu-PSMA radioligand therapy (RLT). We aimed to determine the impact of shortened acquisition times on dosimetric precision. Three SPECT scans with FD of 20, 10, and 5 second/frame (sec/fr) were obtained 48 h post-RLT from one metastatic castration-resistant prostate cancer (mCRPC) patient's pelvis. Planar images at 4, 48, and 72 h post-therapy were used to calculate time-integrated activities (TIAs). Using accurate activity calibrations and GATE Monte Carlo (MC) dosimetry, absorbed doses in tumor lesions and kidneys were estimated. Dosimetry precision was assessed by comparing shorter FD results to the 20 sec/fr reference using relative percentage difference (RPD). We observed consistent calibration factors (CFs) across different FDs. Using the same CF, we obtained marginal RPD deviations less than 4% for the right kidney and tumor lesions and less than 7% for the left kidney. By reducing FD, simulation time was slightly decreased. This study shows we can shorten SPECT acquisition time in RLT dosimetry by reducing FD without sacrificing dosimetry accuracy. These findings pave the way for streamlined personalized internal dosimetry workflows.

Quantitative assessment and objective improvement of the accuracy of neurosurgical planning through digital patient-specific 3D models.

Neurosurgical patient-specific 3D models have been shown to facilitate learning, enhance planning skills and improve surgical results. However, there is limited data on the objective validation of these models. Here, we aim to investigate their potential for improving the accuracy of surgical planning process of the neurosurgery residents and their usage as a surgical planning skill assessment tool. A patient-specific 3D digital model of parasagittal meningioma case was constructed. Participants were invited to plan the incision and craniotomy first after the conventional planning session with MRI, and then with 3D model. A feedback survey was performed at the end of the session. Quantitative metrics were used to assess the performance of the participants in a double-blind fashion. A total of 38 neurosurgical residents and interns participated in this study. For estimated tumor projection on scalp, percent tumor coverage increased (66.4 ± 26.2%-77.2 ± 17.4%, p = 0.026), excess coverage decreased (2,232 ± 1,322 mm2-1,662 ± 956 mm2, p = 0.019); and craniotomy margin deviation from acceptable the standard was reduced (57.3 ± 24.0 mm-47.2 ± 19.8 mm, p = 0.024) after training with 3D model. For linear skin incision, deviation from tumor epicenter significantly reduced from 16.3 ± 9.6 mm-8.3 ± 7.9 mm after training with 3D model only in residents (p = 0.02). The participants scored realism, performance, usefulness, and practicality of the digital 3D models very highly. This study provides evidence that patient-specific digital 3D models can be used as educational materials to objectively improve the surgical planning accuracy of neurosurgical residents and to quantitatively assess their surgical planning skills through various surgical scenarios.

Optic nerve head factors associated with initial central visual field defect in primary open-angle glaucoma

We investigated optic nerve head factors associated with initial parafoveal scotoma (IPFS) in primary open-angle glaucoma. Eighty (80) patients with an IPFS and 84 patients with an initial nasal step (INS) were compared. Central retinal vascular trunk (CRVT) deviation from the Bruch’s membrane opening (BMO) center was measured as a surrogate of lamina cribrosa (LC)/BMO offset, and its obliqueness was defined as the absolute value of angular deviation from the fovea-BMO axis. Proximity of retinal nerve fiber layer defect (RNFLD) was defined as the angular deviation of the inner RNFLD margin from the fovea-BMO axis. Microvasculature dropout (MvD) was defined as a focal sectoral capillary dropout with no visible microvascular network identified in the choroidal layer. Factors associated with IPFS, as compared with INS, were assessed using logistic regression analyses and conditional inference tree analysis. The IPFS group had more oblique CRVT offset (P < 0.001), RNFLD closer to the fovea (P < 0.001), more MvD (P < 0.001), and more LC defects (P < 0.001) compared to the INS group. In logistic regression analyses, obliqueness of CRVT offset (P = 0.002), RNFLD proximity (P < 0.001), and MvD (P = 0.001) were significant factors influencing the presence of IPFS. Conditional inference tree analysis showed that RNFLD closer to the fovea (P < 0.001) in the upper level, more oblique CRVT offset (P = 0.013) and presence of MvD (P = 0.001) in the lower level were associated with the probability of having IPFS. IPFS was associated with closer RNFLD location to the fovea when assessed from the BMO. Oblique LC/BMO offset may not only mask RNFLD proximity to the fovea due to a deviated funduscopic disc appearance, but also potentiate IPFS via focal LC defect and MvD.

Influence of coaxiality on internal mixing of coflow generated droplets

Efficient internal mixing stands as a pivotal requirement for droplet-based micro-reactors/micro-mixers facilitated by microfluidic systems. Among the various methods for their production, capillary-generated droplets emerge as a notable approach. Understanding the role of coaxiality within coflow microfluidic devices in influencing internal mixing remains a crucial aspect for optimizing these systems. Coaxiality within inserted cylindrical capillaries significantly affects mixing efficiency according to our experimental observations. Through numerical simulations, the intricate mixing dynamics of reagents inside droplet generated via a coflow capillary microfluidic system has been investigated. We demonstrate that coaxiality profoundly impacts the initial distribution of disperse phases within droplets, shaping subsequent internal mixing dynamics. Contrary to previous assumptions, our findings highlight the substantial impact of marginal deviations in coaxiality, around 20%, on optimizing mixing efficiency. This challenges prior beliefs and emphasizes the nuanced role of coaxiality in microfluidic systems. These insights advance our understanding of coaxiality's critical influence on enhancing mixing efficiency within coflow microfluidic devices, paving the way for improved design strategies and applications in diverse scientific fields.

Development of an efficient vehicle-to-grid method for massive electric vehicle aggregation

The growing adoption of renewable energy and electric vehicles (EVs) has contributed to environmental sustainability; nevertheless, integration of these products into the power grid has become complex owing to their unpredictable nature and variable energy demands. A significant challenge lies in the realization of large-scale, coordinated control of EVs to serve as an alternative to traditional energy storage systems. This challenge is underscored by the complexity of optimization in large-scale cooperative control problems and the difficulty in reducing such problems to an easily manageable and practical level in real-world application. In response to these challenges, a practical mechanism for the integration of EVs into a vehicle-to-grid concept is proposed in this study. In this approach, the constraints involved in merging multiple EVs into a fictitious clustered energy storage unit, which are often neglected, are given renewed focus. An iterative multi-stage optimization method is introduced that includes an EV aggregation clustering model, multi-tier optimization model, and recursive framework. Here, marked efficacy for larger EV fleets is demonstrated for this method, providing optimal charging and discharging schedules for each vehicle while a high degree of precision is maintained. With the proposed technique, validated through numerous case studies using historical data, the global optimum solution is largely approximated, with a marginal deviation of 4 %. In addition, robustness of the model is demonstrated under varying pricing scenarios, with a computation time that increases in a linear manner, rather than exponentially, as the number of EVs increases. Meanwhile, compared with conventional methods, the technique proposed in this study has the capacity to fulfill the charging demands of all users with reduced charging expense, demonstrating the high precision and efficacy of the technique.

Effects of compression ratio on the performance and emission levels of a CI engine fueled with safflower oil methyl ester through an engine simulation approach

In recent years, the research community has shown significant interest in the potential of biodiesel as a renewable alternative to conventional fossil-based fuels. Nevertheless, the experimental investigation of the effects of diverse biodiesel formulations on internal combustion engines demands a significant investment of time and financial resources. Consequently, the numerical alternative methodologies are advocated as a viable substitute for practical experiments. Numerical simulations offer the opportunity for a meticulous examination of the characteristics of internal combustion engines under diverse operational conditions and various biodiesel blends, thereby optimizing efficiency and cost-effectiveness. This study focused on the simulation of performance and emission characteristics of a diesel engine running on safflower (Carthamus tinctorius L.) oil methyl ester (SOME) and traditional diesel fuel using AVL simulation software. Furthermore, the simulation results were compared with a laboratory study carried out under identical conditions. The simulated engine underwent testing across various compression ratios (CRs) (ranging from 12:1 to 18:1) and engine loads (from 25% to full load) while sustaining a consistent speed of 1500 rpm. The simulation findings revealed that the engine exhibited its highest BSFC as 0.495 kg/kWh with SOME fuel, at a CR of 12:1, modestly lower than the corresponding experimental observation of 0.520 kg/kWh. Concurrently, the lowest value of BSFC, recorded as 0.267 kg/kWh with diesel fuel and a CR of 18:1, demonstrated a marginal deviation from the experimental result of 0.281 kg/kWh. Additionally, SOME fuel usage was correlated with diminished CO and HC emissions. The experimental findings indicated the lowest value of CO and HC emissions, as 0.14% and 21.7 ppm, respectively, with SOME fuel at a CR of 18:1, marginally below the simulation-derived values of 0.13% and 20.8 ppm. Conversely, diesel fuel at a CR of 12:1 exhibited maximal CO and HC emissions, registering 0.38% and 199.5 ppm, respectively, in the experimental study. In comparison, the simulation values were slightly lower at 0.36% and 194.1 ppm. Moreover, the experimental investigation identified SOME fuel as yielding the highest CO2 emission, reaching a peak of 11.9% under a CR of 18:1, while the simulation showed a slightly lower value of 11.2%. In contrast, diesel fuel at a CR of 12:1 resulted in the lowest CO2 emission at 3.85% in the experiment, with the simulation reporting a slightly reduced value of 3.77%. Regarding NOx emissions, the experiment recorded the peak at 1687 ppm with SOME fuel and a CR of 18:1, slightly surpassing the simulation’s value of 1643 ppm. Conversely, the experimental data indicated the lowest NOx emission as 103 ppm with diesel fuel and a CR of 12:1, with the simulation suggesting a slightly lower value of 98.2 ppm under identical conditions. The simulation results demonstrated favorable concordance with experimental findings, notably strengthening with an increase in CR.

Effect of scan powder and scanning technology on measured deviations of complete-arch implant supported frameworks digitized with industrial and intraoral scanners

ObjectivesTo evaluate the suitability of intraoral scanners (IOSs) to analyze the fabrication trueness of titanium complete-arch implant-supported frameworks by comparing with an industrial-grade scanner and investigate how anti-reflective scan powder affects measured deviations. MethodsTen titanium complete-arch implant-supported frameworks were milled from a reference standard tessellation language (STL) file. An industrial-grade blue light scanner (ATOS Core 80 (AT)) and three IOSs (Primescan (PS), TRIOS T3 (T3), and TRIOS T4 (T4)) with (PS-P, T3-P, and T4-P) or without (PS, T3, and T4) anti-reflective scan powder application were used to generate test STL (TSTL) files of the frameworks. Reference STL and TSTLs were imported into a metrology-grade analysis software (Geomagic Control X) and whole surface root mean square (RMS) values were calculated. Another software (Medit Link v 2.4.4) was used to virtually isolate marginal surfaces of all STL files and marginal RMS values were calculated by using the same metrology-grade analysis software. A linear mixed effects model was used to compare the transformed deviations of the scans performed by using each IOS (with or without powder) with the deviations of those performed by using the reference AT scanner within each surface, where a Box-Cox type transformation was used for variance stability. Bonferroni corrected post-hoc tests were used to compare conditions within each IOS (α=0.05). ResultsAll IOSs had significantly higher whole surface and marginal RMS values than AT, regardless of the condition (P≤.002). However, scan powder application did not affect the whole surface and marginal RMS values in scans of tested IOSs (P≥.054). ConclusionMeasured whole surface and marginal deviations in all IOS scans performed with or without the use of scan powder were higher than those in AT scans. The application of anti-reflective scan powder did not affect the deviations in scans of tested IOSs. Clinical SignificanceEven though deviations measured in the scans of tested scanners were significantly different than those in the reference scanner, the maximum raw mean difference was 37.33 µm and the maximum raw confidence interval value of estimated differences was 47.88 µm, which can be considered clinically small taking into account the size of the frameworks tested. Therefore, tested intraoral scanners may be feasible to scan prostheses similar to or smaller than tested frameworks for fabrication trueness analysis, which may facilitate potential clinical adjustments.

Influence of Self-Reported Health Impairments on German EQ-5D-5L Values

ObjectivesThe German EQ-5D-5L value set is based on the average preferences of the general population. Nevertheless, in Germany, there is an ongoing debate about the appropriateness of using general population preferences and whether patient preferences should be used instead. Thus, this research aimed to determine the robustness of the German EQ-5D-5L valuation data for the general population compared with those with health impairments. MethodsSubgroups were built on the self-reported quality of life, measured with the EQ-5D-5L. To identify which groups significantly influenced the value set, different regression models, including dummy variables for the subgroups, were tested while controlling for preference heterogeneity. Backward selection based on the Akaike information criterion led to significant subgroup dummies, which were analyzed in more detail. For each significant subgroup, the value set model was estimated separately. The models were then compared. Sociodemographics of the subgroups were considered. ResultsThree significant dummies were identified: state 11111, severity levels 5 to 7, and self-reported problems with pain/discomfort. The value sets for the 6 subgroups were compared with the national German value set, showing only marginal deviations. The mean absolute deviation ranged from 0.004 to 0.013. No different densities were identified for the decrements of the different value sets. ConclusionsPeople with self-reported health impairments do not have different EQ-5D-5L health state preferences compared with the German general population. Further research is needed to determine whether the presence of a chronic health condition has a larger influence on health state valuation than the general population.

Comparison of intraoral and laboratory scanners to an industrial-grade scanner while analyzing the fabrication trueness of polymer and titanium complete-arch implant-supported frameworks

ObjectivesTo compare the scans of different intraoral scanners (IOSs) and laboratory scanners (LBSs) to those of an industrial-grade optical scanner by measuring deviations of complete-arch implant-supported frameworks from their virtual design file. Material and methodsTen polyetheretherketone (PEEK) and 10 titanium (Ti) complete-arch implant-supported frameworks were milled from a master standard tessellation language (STL) file. An industrial-grade blue light scanner (AT), 2 LBSs (MT and E4), and 3 IOSs (PS, T3, and T4) were used to generate STL files of these frameworks. All STLs were imported into an analysis software (Geomagic Control X) and overall root mean square (RMS) values were calculated. Marginal surfaces of all STL files were then virtually isolated (Medit Link v 2.4.4) and marginal RMS values were calculated. Deviations in scans of tested scanners were compared with those in scans of AT by using a linear mixed effects model (α = 0.05). ResultsWhen the scans of PEEK frameworks were considered, PS and T3 had similar overall RMS to those of AT (p ≥ .076). However, E4 and T4 had higher and MT had lower overall RMS than AT (p ≤ .002) with a maximum estimated mean difference of 13.41 µm. When the scans of Ti frameworks were considered, AT had significantly lower overall RMS than tested scanners (p ≤ .010) with a maximum estimated mean difference of 31.35 µm. Scans of tested scanners led to significantly higher marginal RMS than scans of AT (p ≤ .006) with a maximum estimated mean difference of 53.90 µm for PEEK and 40.50 µm for Ti frameworks. ConclusionOnly the PEEK framework scans of PS and T3 led to similar overall deviations to those of AT. However, scans of all tested scanners resulted in higher marginal deviations than those of AT scans. Clinical SignificanceScans performed by using PS and T3 may be alternatives to those of tested reference industrial scanner AT, for the overall fabrication trueness analysis of complete-arch implant-supported PEEK frameworks.

Closed-Form Expressions of Upper Bound for Polarization-MDCSK System.

The performance analysis of polarization M-ary differential chaos shift keying (P-MDCSK) has been expressed using a tight upper bound with the Q-function. However, evaluating the Q-function directly is not a closed expression and there has been less work on closed expression for the upper bound. In order to solve the problem, this paper presents approximate closed-form expressions on the error probability of P-MDCSK. This expression is derived by employing a polynomial approximation of the Q-function. These closed-form expressions are verified through simulations conducted under both additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels. The simulation results reveal that there exists only a negligible gap between the simulations and the derived closed-form expressions. For example, it is observed that the theoretical approximate closed-form expressions exhibit a marginal deviation of approximately 0.4 dB from the simulations when the bit error rate (BER) reaches 10-4. Although the proposed method can only give approximate closed-form expressions of the upper bound, it provides an effective method for other communication schemes where the exact BER closed-form formula cannot be obtained.

Effect of analysis software program on measured deviations in complete arch, implant-supported framework scans

Implementation of fabrication trueness analysis by using a recently introduced nonmetrology-grade freeware program may help clinicians and dental laboratory technicians in their routine practice. However, knowledge of the performance of this freeware program when compared with the International Organization for Standardization recommended metrology-grade analysis software program is limited. The purpose of this in vitro study was to evaluate the effect of an analysis software program on measured deviations in the complete arch, implant-supported framework scans. A total of 20 complete arch, implant-supported frameworks were fabricated from a master standard tessellation language (STL) file from either polyetheretherketone (PEEK) or titanium (Ti) (n=10). All frameworks were then digitized by using different scanners to generate test STLs. All STL files were imported into a nonmetrology-grade freeware program (Medit Link) and a metrology-grade software program (Geomagic Control X) to measure the overall and marginal deviations of frameworks from the master STL file by using the root mean square (RMS) method. Data were analyzed by using the two 1-sided paired t test procedure, in which 50µm was considered as the minimal clinically meaningful difference (α=.05). When overall RMS values were considered, the nonmetrology-grade freeware program was not inferior to the metrology-grade software program (P<.05). When marginal RMS values were considered, the nonmetrology-grade freeware program was inferior to the metrology-grade software program only when PEEK frameworks were scanned with an E4 laboratory scanner (P>.05). The use of the tested nonmetrology-grade freeware program resulted in overall deviation measurements similar to those when a metrology-grade software program was used. The freeware program was inferior when marginal deviations were analyzed on E4 scans of a PEEK framework, which was the only scanner-material pair that led to a significant difference, among the 15 pairs tested.

FinFET 6T-SRAM All-Digital Compute-in-Memory for Artificial Intelligence Applications: An Overview and Analysis.

Artificial intelligence (AI) has revolutionized present-day life through automation and independent decision-making capabilities. For AI hardware implementations, the 6T-SRAM cell is a suitable candidate due to its performance edge over its counterparts. However, modern AI hardware such as neural networks (NNs) access off-chip data quite often, degrading the overall system performance. Compute-in-memory (CIM) reduces off-chip data access transactions. One CIM approach is based on the mixed-signal domain, but it suffers from limited bit precision and signal margin issues. An alternate emerging approach uses the all-digital signal domain that provides better signal margins and bit precision; however, it will be at the expense of hardware overhead. We have analyzed digital signal domain CIM silicon-verified 6T-SRAM CIM solutions, after classifying them as SRAM-based accelerators, i.e., near-memory computing (NMC), and custom SRAM-based CIM, i.e., in-memory-computing (IMC). We have focused on multiply and accumulate (MAC) as the most frequent operation in convolution neural networks (CNNs) and compared state-of-the-art implementations. Neural networks with low weight precision, i.e., <12b, show lower accuracy but higher power efficiency. An input precision of 8b achieves implementation requirements. The maximum performance reported is 7.49 TOPS at 330 MHz, while custom SRAM-based performance has shown a maximum of 5.6 GOPS at 100 MHz. The second part of this article analyzes the FinFET 6T-SRAM as one of the critical components in determining overall performance of an AI computing system. We have investigated the FinFET 6T-SRAM cell performance and limitations as dictated by the FinFET technology-specific parameters, such as sizing, threshold voltage (Vth), supply voltage (VDD), and process and environmental variations. The HD FinFET 6T-SRAM cell shows 32% lower read access time and 1.09 times better leakage power as compared with the HC cell configuration. The minimum achievable supply voltage is 600 mV without utilization of any read- or write-assist scheme for all cell configurations, while temperature variations show noise margin deviation of up to 22% of the nominal values.

Fabrication trueness and internal fit of hybrid abutment crowns fabricated by using additively and subtractively manufactured resins

ObjectivesTo evaluate the fabrication trueness and internal fit of hybrid abutment crowns fabricated by using additively and subtractively manufactured restorative materials. MethodsA maxillary first premolar crown with a screw access channel was designed onto a digitized master titanium base abutment. This file was used to fabricate 40 crowns additively (Crowntec (CT) and VarseoSmile Crown Plus (VS)) or subtractively (Brilliant Crios (BC) and Vita Enamic (EN)) (n = 10). Crowns were digitized with an intraoral scanner and root mean square method was used to evaluate fabrication trueness. Master abutment and the crowns when seated on the abutment were also digitized with the same intraoral scanner and triple scan method was used to evaluate internal fit. Data were analyzed either with 1-way ANOVA (surface deviations) or Kruskal-Wallis (internal fit) tests (α= 0.05). ResultsCT had the highest overall, external, and marginal surface deviations (P≤.030), whereas BC had the lowest external (P≤.001) and VS and EN had the lowest marginal surface deviations (P≤.007). BC had the highest intaglio surface deviations (P<.001). BC and EN had higher average gap values CT and VS (P≤.006); however, the differences within additively and subtractively manufactured materials were nonsignificant (P≥.858). ConclusionsOne of the tested additively manufactured resins (CT) resulted in mostly lower trueness than that of other materials. However, deviations at the intaglio and marginal surfaces were generally small and the maximum mean difference among test groups when average gap was considered was 17.4 µm. Therefore, clinical fit of hybrid abutment crowns fabricated with tested materials may be similar.

Implementation of a Neural Network Approach for Predicting Sales Profit

The term "artificial neural network" (ANN) refers, in the majority of cases, to a piece of computing hardware that is impacted by the process, function, and cognitive growth that are comparable to that of a human brain. It does this by simulating the way neurons in the human brain carry out their functions. It is able to solve complicated and dynamic issues in real time with some realistic probability constraints because it understands, observes, and recognises the patterns in the data. This paper implements the Microsoft neural network in Microsoft SQL Server Management using visual studio on a dataset that is accessible to the public in order to demonstrate the efficacy of neural networks in transforming raw data into an in-depth understanding of the trends in a dataset that is difficult to visualise. The dataset was chosen because it is readily available to the public. In addition to that, the error margin or standard deviation in the value prediction of the method that was carried out on the database is shown in this work. The selected dataset contains a significant volume of bike sale records from throughout Europe. As a result, it may be categorised as "big data," which cannot be resolved by utilising a standard paper record method or a typical data mining algorithm that is incapable of learning. Additionally, optimizers and modifiers that have an influence on the prediction value that is processed by the SQL database are investigated in this study. Traditional techniques of data analysis, on the other hand, are unable to correctly access or interpret data that is both so complicated and so dynamic as to be able to deliver quality forecasting. Neural networks, on the other hand, are able to resolve the information contained in big data into valuable knowledge in the form of predictions.