Average Percentage Deviation Research Articles

Experimental investigation of parameters and surface integrity of die steel based on MR fluid finishing process

The main aim of the this work is to design and develop a suitable mechanism to finish the hard surfaces and improve the performance of finishing processes based on MR fluid using external magnetic field. This work is carried out by considering the significant process parameters like the concentration ratio of CIPs to aluminum oxide (Al2O3) as an abrasives, magnetizing current, the rotating speed of the tool, feed rate of workpiece, working gap and hardness of work pieces to know the response as a percentage change in surface roughness Ra. SEM technique is employed to know the surface integrity and understand the performance of MR fluid based finishing process over the surface of die steel materials. While, performing the experimental work, a full factorial design is applied and the results are characterized using regression and ANOVA technique. It is revealed from the results that the foremost contribution of the factors in the highest order are working gap, magnetizing current and the hardness of the work piece followed by the ratio of CIP to Al2O3 abrasives, feed rate and rotating speed of the tool in improving the surface roughness Ra. The regression model confirms the linear relationship between observed Ra and the predicted Ra and its correlation coefficient is + 0.85. The average percentage deviation is 3.56 within 5% error band. Thus, this method is capable to obtain the Nano finishing over the surface of hardened materials.

An Immune Genetic Algorithm for Solving NPV-Based Resource Constrained Project Scheduling Problem

The net present value (NPV)-based resource constrained project scheduling problem (RCPSP) is a well-known scheduling problem in many industries, such as construction, software development, and manufacturing. Over the last five decades, although different approaches have been proposed to solve the problem, no single approach has been shown to achieve satisfactory performances with quality solutions for a wide range of problems. This study presents a hybrid immune genetic algorithm (IGA) to solve NPV-based RCPSPs. Hybridizing a genetic algorithm (GA) with an immune algorithm (IA) enhances the overall performance of their standalone components (i.e., only GA or IA). Performance of the proposed IGA is further improved by applying a variable insertion based local search (VINS) and forward-backward improvement (FBI). A restart mechanism is presented to the algorithm which induces diversity and helps to avoid becoming trapped in local optima. Moreover, an activity move rule (AMR) is implemented to shift the negative cash flow associated activities to further improve the NPV. Taguchi Design of Experiment (DOE) is conducted to investigate the impact of various parameters and to determine the appropriate set of parameters for the proposed IGA. The performances of the proposed algorithms are tested on 17,280 standard benchmark instances ranging from 25 to 100 activities. Comparison with the state-of-art algorithms through extensive numerical experiments reveal the effectiveness of the proposed algorithms. Overall, the proposed algorithm outperforms existing algorithms, particularly the projects with 0% and 100% negative cash flow associated activities, the 75-activity instances, and the projects with two resources usage in terms of a lower value of average percentage deviation.

An empirical approach of modeling and assessment for the safe use of commercial electric detonators in radio frequency radiation hazards

In the modern era of communication technologies using amplitude modulation (AM) and frequency modulation (FM) the transmitting antenna of radio, television, radar, cellular phones, wireless data acquisition systems and global positioning systems (GPS) are the main sources of radio frequency radiation hazards. The transmitting antennas of these communication devices generate electromagnetic fields (EMFs). Electric detonator wires, under certain circumstances work as receiving antenna and pickup enough electrical energy from such fields to initiate unexpected explosion. There have been many cases of detonators being fired accidentally by radio frequency pick up. In this work an attempt has been made to minimize such explosions and to provide a basis for assessing and modeling the parameters of radio frequency radiation hazards associated with commercial electric detonators. This research examines the radiated powers of various frequency bands to determine the safe distance from transmitting antenna. Based on mathematical simulation, two empirical relations have been proposed for the calculation of minimum safe distance (MSD). Using these relations desired MSDs have been calculated for the relevant frequency bands. The obtained values have been compared with the available experimental values showing good agreement between them. The average percentage deviations of calculated MSDs from proposed relations are found between 0.096% and 10.718%, with regression coefficient 0.970 ≤ R ≤ 1. This reflects the soundness of the proposed empirical relations. The blasting engineers, detonator designers and researchers may use these relations as a handy tool to prevent undesired explosions by maintaining minimum safe distance in radio frequency prone hazardous areas.

Parameter Estimation of AC Transmission Line Considering Different Bundle Conductors Using Flux Linkage Technique

The transmission line is the backbone of the power system. A transmission-line working principle is based on its components: inductance, capacitance, and resistance. These components are important in operation, and designing transmission lines as the voltage drop in the power transmission lines depends on these components. In this research work, the flux linkage technique has been proposed to calculate the transmission line's parameters. The transmission-line conductor's resistance has a vital role in calculating power losses in the transmission line. The capacitance and inductance are formed in the transmission line due to the magnetic field of the conductor. For the precise calculation of transmission-line parameters, the temperature correction resistance will improve power-flow efficiency in the power system using power-flow equations. This research work aims to identify the transmission-line parameters and analyze the effect of different bundle conductors, such as two, three, and four bundle conductors. It is observed that when the conductor area is increased in square millimeters (mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), the inductance is decreased, and the capacitance is increased in both single- and three-phase transmission lines, the average percent difference of capacitance and inductance is 99.55% and 55.49%, respectively. The simulation results are provided to show how the proposed techniques can work successfully under various bundle conductors.

The Effects of Different Storage Conditions and Repeated Freeze/Thaw Cycles on the Concentration, Purity and Integrity of Genomic DNA

The crucial requirement of molecular genetic methods is high-quality input material. The key question is “how to preserve DNA during long-term storage.” Biobanks are recommended to aliquot isolated DNA into provided volumes. The aim of this study was to analyse the effect of repeated freezing and thawing on the genomic DNA integrity, quality and concentration. The aliquoted DNA isolated from blood cells using the automatic MagNA system and manual salting out method underwent freeze/thaw cycles at different storage conditions (−20 °C, −80 °C and liquid nitrogen). The average initial concentrations were 270.6 ng/μl (salting out method) and 125.0 ng/μl (MagNA). All concentration deviations relative to the concentration after the first freeze/ thaw cycle were less than 5 % for −20 °C and −80 °C cycling with both isolation methods. The average percentage differences of liquid nitrogen samples were higher, and the MagNA isolation method showed significant differences. There were no significant changes in the DNA purity or quality. The repeating freeze/ thaw up to 100 cycles (through −20 °C and −80 °C, respectively) did not significantly influence the integrity, concentration, or purity of genomic DNA, suggesting that storage of samples in high-volume pools without multiple aliquoting is possible. Storage in a freezer seems to be the most suitable way of long-term DNA preservation, because liquid nitrogen storage leads to formation of DNA clumps.

Investigation of tooth crack opening state on time varying meshing stiffness and dynamic response of spur gear pair

In the traditional calculation model of mesh stiffness, the tooth root crack is commonly assumed to be in a closed state. However, the gear tooth crack will open under the action of mesh force in the meshing process, the mesh stiffness of the cracked tooth and the dynamic response of gear system is thus different from the closed crack case. There almost no studies have been done to investigate the influence of tooth crack open state on mesh stiffness and dynamic response. Thus, this paper presents an improved mesh stiffness calculation model of the cracked gear, in which the effective compression section and the neutral layer of the cracked tooth are re-evaluated considering the crack opening state. Then, the accuracy of the proposed model is verified by the finite element method (FEM), and the differences of mesh stiffness and statistical indicators of the dynamic response between the proposed and traditional models are further studied. The mesh stiffness calculation results show that the proposed model achieves a higher accuracy than the traditional model. And its precision gradually increases as the crack grows, which can be improved by 2.35% in the case of large crack (48.38% crack) when compared to the traditional model. The fault response signal obtained from the traditional model yields a larger amplitude than the actual situation, which will lead to errors of the statistical indicators used for fault diagnosis, in particular, the RMS value can be up to an average percentage difference of 11.98% under the large crack (48.38% crack). It is concluded that the proposed model has a higher accuracy for calculating the mesh stiffness of the cracked gear and can be further used to serve the fault diagnosis and detection of the gear system.

Hydrogen solubility in bio-based furfural and furfuryl alcohol at elevated temperatures and pressures relevant for hydrodeoxygenation

Biomass conversion into fuels and added-value chemicals, in high yield and with good selectivity, is still a great issue and an attractive research topic. The design and the optimization of defunctionalisation processes require accurate kinetic models that take into account the solubility of various gases in the bio-based chemicals present in the process.Some of the promising platform bio-based compounds that can be further converted to valuable chemicals are furfural and furfuryl alcohol. Hydrogen solubility in furfural and furfuryl alcohol was studied at three temperatures from the range (323.15–423.15) K and at pressures up to 25 MPa. Hydrogen dissolves better in furfural than in furfuryl alcohol, for about 15 %.The obtained experimental data were modelled using the Soave-Redlich-Kwong and Peng-Robinson cubic equations of state, as well as the PC-SAFT equation of state. The parameters of the PC-SAFT equation of state for pure compounds were defined for furfural and furfuryl alcohol. The binary interaction parameters, crucial for the prediction of phase-equilibrium behaviour, were determined for both examined systems. The interaction parameters obtained for the cubic equations of state were temperature dependent, while the interaction parameters optimized for the PC-SAFT equation of state were almost the same at all three temperatures for each studied system. The average absolute percentage deviations between the measured equilibrium pressures and those calculated using the mentioned models were under 4 %.

Application of Transfer Effect Models for Predicting Growth and Survival of Genetically Selected Scots Pine Seed Sources in Sweden

We used a regression model approach to examine transferability of the 1.5-generation Swedish Scots pine orchard plus trees using the estimated coefficients of the transfer models recently developed for growth and survival of unimproved Scots pine in Sweden and Finland. Differences between observed and predicted values obtained for height and survival of 3214 plus tree progenies, tested at 58 progeny trials, were regressed on latitudinal transfers (∆LAT). In order to evaluate rates of improvement in height and survival of selected progenies over unimproved trees, average percentage differences in performances (∆g%) between the tree groups were calculated. Results indicate that the adopted models can further predict performances of more advanced-generation orchard trees, as there was no evidence of any systematic pattern in the slope of regression functions. Overall, ∆g% estimates obtained for height of progenies were greater than those of survival, suggesting Swedish Scots pine breeding activities are generating gain in the height growth. Moreover, ∆g% estimates obtained for height and survival of half-sib progenies were higher than those of full-sib ones, as a result of response to higher selection intensity applied in the reselection of their parents. This indicates that, in addition to the gain in growth, a gain in survival is also achievable from 1.5-generation seed orchards, depending on the intensity of selection and intended deployment site.

Finite element validation of 3D American football faceguard structural stiffness models

Despite continued efforts to improve American football headgear technology, minimal structural changes have been made to faceguard design in the past 20 years. Although each new helmet system has its own compatible faceguard series, the primary design components have changed little between helmet systems. Additionally, little is known about specific parameters that influence faceguard performance, largely due to the variation inherent in laboratory impact testing. The goal of this study was two-fold: to validate a reverse engineering method for developing a library of faceguard models; and to validate the finite element simulation of three common American football faceguards subject to a quasi-static structural stiffness test. Three common Riddell® Speedflex™ (Des Plaines, IL) faceguard styles were modeled using a novel reverse engineering approach. Within ANSYS® Mechanical™ (ANSYS, Inc., Canonsburg, PA), the faceguards were modeled as stainless steel (elastic modulus = 193 GPa, Poisson’s ratio = 0.31). A displacement of 5 mm was prescribed in the posterior (z) direction. Boundary conditions were applied to accommodate the coronal plane (x, y) translation at clip attachment locations. The computational results correlated to the experimental results with statistical significance ( p value = 0.001). The Nose location was the most reliable with an average percent difference from experimental results of 2.7%, compared to 10.8% and 9.9% at the Mouth and Chin locations, respectively. Many studies utilizing computational models of protective headgear lack reported validation of headgear components. This study has validated the structural stiffness of three common faceguards to be used in future computational analyses. Furthermore, advancements in additive manufacturing technologies have opened the door to increasingly complex faceguard design capabilities; however, little is known about specific parameters that influence faceguard performance. With the models validated in this study, parameterized faceguard models should be used to iterate between design variables and assess the contribution of each variable on faceguard structural stiffness.

Deep learning-based thigh muscle segmentation for reproducible fat fraction quantification using fat\u2013water decomposition MRI

BackgroundTime-efficient and accurate whole volume thigh muscle segmentation is a major challenge in moving from qualitative assessment of thigh muscle MRI to more quantitative methods. This study developed an automated whole thigh muscle segmentation method using deep learning for reproducible fat fraction quantification on fat–water decomposition MRI.ResultsThis study was performed using a public reference database (Dataset 1, 25 scans) and a local clinical dataset (Dataset 2, 21 scans). A U-net was trained using 23 scans (16 from Dataset 1, seven from Dataset 2) to automatically segment four functional muscle groups: quadriceps femoris, sartorius, gracilis and hamstring. The segmentation accuracy was evaluated on an independent testing set (3 × 3 repeated scans in Dataset 1 and four scans in Dataset 2). The average Dice coefficients between manual and automated segmentation were > 0.85. The average percent difference (absolute) in volume was 7.57%, and the average difference (absolute) in mean fat fraction (meanFF) was 0.17%. The reproducibility in meanFF was calculated using intraclass correlation coefficients (ICCs) for the repeated scans, and automated segmentation produced overall higher ICCs than manual segmentation (0.921 vs. 0.902). A preliminary quantitative analysis was performed using two-sample t test to detect possible differences in meanFF between 14 normal and 14 abnormal (with fat infiltration) thighs in Dataset 2 using automated segmentation, and significantly higher meanFF was detected in abnormal thighs.ConclusionsThis automated thigh muscle segmentation exhibits excellent accuracy and higher reproducibility in fat fraction estimation compared to manual segmentation, which can be further used for quantifying fat infiltration in thigh muscles.

A Drought Monitoring Method Based on Precipitable Water Vapor and Precipitation

AbstractPrecipitable water vapor (PWV) with high precision and high temporal resolution can be obtained based on the global navigation and satellite positioning system (GNSS) technique, which is important for GNSS in disaster prevention and mitigation. However, related studies on drought monitoring using PWV have rarely been performed before, which becomes the focus of this paper. This paper proposes a novel drought monitoring method using GNSS-derived PWV and precipitation, and a multi-time-scale standardized precipitation conversion index (SPCI) is established. This index is different from the traditional index in terms of expression, standardization, and time scale. The proposed SPCI is then compared with the standardized precipitation index/standardized precipitation evapotranspiration index/self-calibrating Palmer drought severity index (SPI/SPEI/scPDSI) and applied to local and global drought monitoring. Validated results show that multi-time-scale SPCI has good consistency with the corresponding SPI/SPEI/scPDSI. The correlation between SPCI and SPEI is the strongest (more than 0.96) on a 12-month scale, which indicates the application potential of SPCI in drought monitoring. In addition, applications for regional (Queensland, Australia) and global drought/wet monitoring further verify the capability of the proposed SPCI. The average percentage deviations of drought/wet monitoring between SPCI and SPEI are 2.77% and 3.75%, respectively on a global scale. The above results show that the SPCI developed in this study is efficiently applied to global flood/wet studies.

Flank wear prediction in tungsten carbide tool using acoustic signal amplitude in conventional turning operation

A tool wear prediction system that senses the cutting tool wear and allows for the optimum utilization of the tool is a deciding factor in achieving good surface quality of machined products. In recent years, the use of acoustic emission signals that emerged during machining operations has gained great significance in accurately predicting the tool condition. The objective of this work is to determine the variation in acoustic signal characteristics with tool flank wear in conventional turning process using Fast Fourier Transformation (FFT). Unlike the previous works, the experiments in this work were performed after optimizing the distance of the sensor position from the tip of the tool, since the optimum position of the sensor determines the transmission of the acoustic signals with minimum attenuation. The obtained raw signal output of the acoustic sensor is processed using FFT and the spectral analysis of the signal is carried out to determine the frequencies and also the magnitude of signal content at each frequency. This study establishes a correlation between the flank wear and the amplitude of acoustic signals. The model is validated using three sets of experiments at various cutting conditions. The average percentage deviation of the predicted tool wear from the experimental results is found to be 9.97%. This study indicates that the AE signals can be used to model the flank wear progression and can be useful for the accurate flank wear prediction in machining processes.

Lateral Torsional Buckling Strengths of Stepped Beams at Midspan Exposed to Elevated Temperature

The American Institute of Steel Construction provides design equations for the lateral torsional buckling (LTB) of beams under fire. However, these equations are limited only to prismatic beams. Stepped beam factors are introduced by researchers that accounts the change in cross-sections of beams to determine capacities of stepped beams under normal temperatures. This paper assesses the validity of the stepped beam factors for the LTB capacities of stepped I-beams located at its midspans integrated to the AISC equation for beams under high temperatures. A set of numerical studies using finite element analysis program, ABAQUS, was conducted to assess the buckling behavior of stepped beams. The analysis is composed of heat-transfer analysis that evaluates the change in material properties of steel as heat propagates the material from 20 °C to 800 °C; and Static Riks analysis where the beams are applied with uniform end moments. Correlation between the results from the stepped beam equations and the simulated data from ABAQUS has been done. The comparison between data showed that the proposed equation generated conservative estimates with an average percentage difference of 11.48% for inelastic LTB, whilst, 2.07% for the elastic LTB. In addition, the ratio of the increase in strength and increase in volume of stepping of beams shows that the flange width of the stepped beam controls its efficiency in lateral torsional buckling capacity. Overall, the results of this research proved that the existing stepped beam equations can be used in calculating the structural capacity of stepped beams at midspan under both normal and elevated temperatures.

Direct, Isomer-Specific Quantitation of Polycyclic Aromatic Hydrocarbons in Soils Using Membrane Introduction Mass Spectrometry and Chemical Ionization.

Polycyclic aromatic hydrocarbons (PAHs) are routinely screened for in soils, where quantitation of structural isomers is critical due to varying toxicity within PAH isomer classes. While chromatographic methods provide isomer resolution, such strategies are cost and time intensive. To address these challenges, we present condensed phase membrane introduction mass spectrometry using liquid electron ionization/chemical ionization (CP-MIMS-LEI/CI) as a direct mass spectrometry technique that provides rapid, quantitative results for PAH isomer measurements in soil samples. A methanol acceptor phase is flowed through a probe-mounted polydimethylsiloxane hollow fiber membrane directly immersed into a dichloromethane/soil slurry. PAHs and dichloromethane co-permeate the membrane into the acceptor solvent, whereas particulates and charged matrix components remain in the sample. A nanoflow of the membrane permeate is then directly infused into a LEI/CI interfaced triple quadrupole mass spectrometer. Diagnostic PAH adduct ions were formed at either M + 45 ([M + CH2Cl + CH3OH-HCl]+) or M + 47 ([M + CHCl2-HCl]+). This allowed the development of specific MS/MS transitions for individual PAH isomers. These transitions were subsequently used for the direct analyses of PAHs in real soils where CP-MIMS-LEI/CI was shown to be rapid (15 soil samples/h) and sensitive (ng/g level detection limits). CP-MIMS-LEI/CI results compared well to those obtained using GC-MS (average percent difference of -9% across 9 PAHs in 8 soil samples), presenting a compelling argument for direct, quantitative screening of PAHs in soils by CP-MIMS-LEI/CI, particularly given the simple workflow and short analytical duty cycle.

Development and validation of an age-scalable cardiac model with substructures for dosimetry in late-effects studies of childhood cancer survivors

Background and PurposeRadiation therapy is a risk factor for late cardiac disease in childhood cancer survivors. Several pediatric cohort studies have established whole heart dose and dose–volume response models. Emerging data suggest that dose to cardiac substructures may be more predictive than whole heart metrics. In order to develop substructure dose-response models, the heart model previously used for pediatric cohort dosimetry needed enhancement and substructure delineation. MethodsTo enhance our heart model, we combined the age-scalable capability of our computational phantom with the anatomically-delineated (with substructures) heart models from an international humanoid phantom series. We examined cardiac volume similarity/overlap between registered age-scaled phantoms (1, 5, 10, and 15 years) with the enhanced heart model and the reference phantoms of the same age; dice similarity coefficient (DSC) and overlap coefficient (OC) were calculated for each matched pair. To assess the accuracy of our enhanced heart model, we compared doses from computed tomography-based planning (ground truth) with reconstructed heart doses. We also compared doses calculated with the prior and enhanced heart models for a cohort of nearly 5000 childhood cancer survivors. ResultsWe developed a realistic cardiac model with 14-substructures, scalable across a broad age range (1–15 years); average DSC and OC were 0.84 ± 0.05 and 0.90 ± 0.05, respectively. The average percent difference between reconstructed and ground truth mean heart doses was 4.2%. In the cohort dosimetry analysis, dose and dose-volume metrics were approximately 10% lower on average when the enhanced heart model was used for dose reconstructions. ConclusionWe successfully developed and validated an anatomically realistic age-scalable cardiac model that can be used to establish substructure dose-response models for late cardiac disease in childhood cancer survivor cohorts.

Anthropomorphic Calcaneus Phantom for Microwave Bone Imaging Applications

Recent studies have found a significant dielectric contrast between healthy and osteoporotic human trabecular bones. This dielectric contrast can be exploited by microwave imaging for monitoring human bone health. The tissue-mimicking phantoms play a vital role in preclinical testing of the microwave imaging system. This paper presents anatomically realistic multi-layered 3D-printed and carbon black-based human calcaneus structure. The liquid and solid based tissue-mimicking mixtures are also proposed to mimic the dielectric properties of skin, muscle, cortical bone, and trabecular bone. The liquid tissue-mimicking mixtures are composed of Triton X-100, water, and salt, whereas the solid tissue-mimicking mixtures are composed of carbon black, graphite, polyurethane, and isopropanol. The dielectric properties of the tissue-mimicking mixtures were measured using an open-ended coaxial probe measurement technique across 0.5–8.5 GHz. The average percentage difference between the relative permittivity and conductivity of reference data and proposed liquid tissue-mimicking mixtures was found to be 7.8% and 9.6% for skin, 0.38% and 14% for muscle, 9.6% and 5% for cortical bone, and 3.4% and 2.4% for trabecular bone, respectively, across 0.5–8.5 GHz. For solid tissue-mimicking mixtures, this difference was found to be 3.93% and 0.64% for skin, 6.13% and 9.21% for cortical bone, and 10.66% and 41.82% for trabecular bone, respectively for relative permittivity and conductivity. The proposed tissue-mimicking mixtures along with 3D-printed structures can be used as a valuable test platform for microwave bone imaging system development.

Improved Prediction of Saturated and Single-Phase Liquid Densities of Water through Volume-Translated SRK EOS

The existing equation of states (EOSs) cannot well reconcile the calculation accuracy and the computational cost for reproducing liquid volumes of water. In this study, we propose a series of improved volume translated Soave-Redlich-Kwong (VT-SRK) EOSs to achieve more accurate volumetric calculation for water with little additional computational cost. The overall average absolute percentage deviation of the saturated liquid molar volume for water yielded by the proposed 4-parameter VT-SRK EOS is 0.26; this calculation error is much lower than the counterpart provided by our previously proposed 3-parameter VT-SRK EOS (1.24) and close to the uncertainty in the pseudo-experimental data reported by NIST (0.1%). After adopting the translated distance function, the proposed 5-parameter VT-SRK EOS provides a more accurate determination for the single-phase liquid volume of water over a wide temperature/pressure range and leads to the crossover of pressure-volume isotherms only at extremely high pressures. The proposed 4-parameter VT-SRK EOS also helps to improve the volumetric prediction for carbon dioxide, while the proposed 5-parameter VT-SRK EOS performs well in improving the density prediction for associating fluids. Moreover, we extend the proposed 5-parameter VT-SRK EOS to mixtures through conventional mixing rules, finding that the VT-SRK EOS provides reliable volume predictions for the aqueous solutions examined in this study.

An analytical expression for R50% dependent on PTV surface area and volume: a lung SBRT comparison.

In stereotactic body radiation therapy (SBRT), R50% is a common metric for intermediate dose spill and is defined in RTOG 0915 as the ratio of 50% isodose cloud volume (IDC50%) to the planning target volume (PTV). By coupling sound physical principles with the basic definition of intermediate dose spill, we derive an exact analytical expression for R50% for the case of a spherical volume. This expression for R50% depends on three quantities: the surface area of PTV (SAPTV), the volume of PTV (VPTV), and the dose gradient Δr. Validity of our analytical expression for R50% was confirmed via direct comparison to peer‐reviewed, multi‐institutional, diverse clinical data. The comparison of our R50% values computed from our analytical expression to the clinical data yielded an average percent difference of 3.8 ± 4.5%.

Multimodal analgesia after thyroid or parathyroid surgery: A randomized controlled trial

BackgroundThe opioid epidemic prompted reevaluation of surgeons’ opioid prescribing practices. This study aimed to demonstrate noninferiority of a staged analgesic regimen after endocrine surgery. MethodsWe conducted a randomized controlled trial comparing analgesic regimens after thyroidectomy and/or parathyroidectomy. Adult patients (≥18 years) were randomized to study arm (A) as-needed acetaminophen + codeine or (B) scheduled acetaminophen/as-needed tramadol. Patients recorded pain scores and analgesics consumed in a study log. Clinical variables were collected from the medical record. ResultsTarget enrollment was achieved (n = 126), and randomization was even (A: 44.5%, B: 55.6%). There was no difference between enrolled patients and those who returned the study log (52.4%) by sex (P = .667), age (P = .513), final pathology (P = .137), procedure (P = .667), or randomization arm (P = .795). Most patients (50.8%) reported moderate pain scores (4–6) with no difference between study arms (P = .451). There was no difference in average consumption by morphine milligram equivalents (A: 11.5 ± 12.1 vs B: 12.49 ± 18.07; P = .792) nor total analgesic doses (A: 7.29 ± 7.48 vs B: 8.5 ± 5.36; P = .445). However, a significant difference in average percentage of opioid doses was noted (A: 79.71 ± 33.31 vs B: 27.38 ± 31.88; P < .001). ConclusionPatients reported moderate pain scores with low requirements for analgesics after endocrine surgery. The staged analgesic regimen is noninferior to combination opioids and led to reduced overall consumption.

Force prediction in ultrasonic vibration-assisted milling

The use of ultrasonic vibration on milling has several benefits including reduction of the machining forces. However, the mechanism behind this phenomenon is unclear, and reported analytical studies are quite limited. An analytical predictive modeling work is presented in the current study. To describe the intermittent contact between tool and workpiece due to vibration, conditions of tool-workpiece separation are described by three types of criteria. The first criterion checks the instantaneous moving direction of cutting edge. The second criterion examines the radial displacement of cutting edge under vibration. The third criterion considers the smaller chip thickness due to extra displacement from previous tool path. If the material is being removed, the force prediction is performed through transformation of milling configuration, calculation of shear flow stress by mechanics of machining, and calculation of feed, cutting and axial force after coordinate transformation. The predicted forces are compared with experimental measurements on Aluminum alloy 2A12 for validation. The average percentage difference is 13.6% in feed direction and 13.8% in cutting direction. This is the first approach to mathematically describe the intermittent contact between tool and workpiece and combine the kinematic analysis with mechanics of machining to predict cutting forces.