High Level Of Precision Research Articles

Analysis of flexural behavior of one-way reinforced concrete slab casted by shotcrete contain various types of plastic fibers

The design of reinforced concrete structures has traditionally relied on empirical techniques based on experience or experimental research on actual structural members. Although this approach produces a high level of precision, it is usually exceedingly costly and time-consuming. This paper studied the convergence between theoretical analysis (ACI 318-19 Equations) and numerical analysis (FEM) of eleven one way reinforced concrete slab specimens casted by shotcrete contains three types of plastic fibers including waste plastic (PET), polypropylene (PP), and hybrid (PET+PP) fibers with three addition ratios (0.35%, 0.7%, and 1%) for each type. The results concluded that the numerical analysis (ANSYS FE model) showed a good agreement with the theoretical (ACI 318-19) of one-way slab in terms of ultimate load, with a variance, and standard deviation equal to 0.00076, and 0.027 respectively. Hence, ANSYS v15 software can be used for the analysis of reinforced concrete slabs casted by shotcrete contain waste plastic fibers and polypropylene fibers.

Quality assessment of fresh meat cuts as a performance indicator of knives specifically adapted for robot-assisted operations

Manual labour in slaughterhouses is hazardous work. Workers suffer from injuries and occupational illnesses resulting from repetitive movements with sharp knives. There is a need for a robotic tool which can perform versatile tasks with a high level of precision. This knife must be able to imitate the same primary cuttings of a professional butcher and produce meat products which are acceptable to the end-market. This paper reports the results of a world-wide assessment of the fresh pork meat cuts as a performance indicator of knives specifically adapted for automated operation. These knives included Victorinox knife, bespoke double bladed Uddeholm knife, vibrating knife and novel smart knife with built-in sensing mechanism that detects in real time the contact with meat and cut depth. Physical appearances of cuts were assessed anonymously by independent responders with different backgrounds. All knives were deemed acceptable in terms of cutting quality. There was also no discernible difference of opinion between manual and robot cuts. This indicates that the new knife for robot-assisted cutting is acceptable by market.

Determination of Proinflammatory and Antiinflammatory Cytokines by ELISA Technique.

The main objective of this chapter is to determine inflammatory and anti-inflammatory cytokines in patients with or without preeclampsia by means of the enzyme-linked immunosorbent assay (ELISA) technique. In this chapter, 16 cell cultures were obtained from different patients admitted to the hospital with term vaginal delivery or cesarean section. Here, we describe the ability to quantify the presence of cytokines in cell culture supernatants. The supernatants of the cell cultures were collected and concentrated. The concentration of IL-6 and VEGF-R1 was measured by ELISA to determine the prevalence of alterations in the samples studied. We observed that the sensitivity of the kit allowed the detection of several cytokines in a range between 2 and 200pg/mL. The test was performed using the ELISpot method (5×), which allowed a higher level of precision.

Application of Multi-objective Differential Evolution Algorithm in Computer Network Intrusion Detection System

With the rise and development of computer networks, network security has become a major issue, and intrusion detection has emerged as a crucial aspect of network security. However, traditional intrusion detection methods suffer from issues like slow detection rates and low accuracy. This necessitates the exploration and development of optimized algorithms for improving intrusion detection efficiency and accuracy. Recently, the multi-objective differential evolution algorithm has shown promising results in the field of intrusion detection. This paper explored the application of the multi-objective differential evolution algorithm in computer network intrusion detection systems. The experimental results on the KDDCUP'99 dataset demonstrated that the algorithm delivers high levels of precision and recall, outperforming other intrusion detection methods. Therefore, combining the multi-objective differential evolution algorithm with traditional intrusion detection methods can lead to significant improvements in intrusion detection efficiency and accuracy. Further optimization of this algorithm can be required to meet complex intrusion detection requirements. The multi-objective differential evolution algorithm presents exciting prospects, which can help enhance the efficiency and accuracy of intrusion detection, and provide strong technical support for ensuring network security and preventing cyber-attacks.

Исследование хода фокусирующей линзы зрительных труб цифровых нивелиров

To ensure the required accuracy of elevation and angle measurements, measures are taken at the station to rectification or significant reduce of the influence of the main instrumental errors. With regard to leveling, main errors are the violation of the main condition of the level (the influence of the constant component of the angle i), as well as the incorrect course (oscillations) of the spotting scope focusing lens when it is refocused (the variable component of the angle i). In this regard, in order to significantly reduce their influence, leveling at the station is carried out by the middle with an acceptable shoulder difference. The influence and magnitude of the focusing lens travel on the measurement, as well as methods for reducing the errors, are well covered for instruments with visual reading. With regard to the spotting scope of digital levels, which have different design and shorter focal length, the nature and magnitude of this influence is not covered enough. This circumstance is important when performing measurements with the instruments in terms of the possible expansion of technological tolerances for the inequality of the shoulders at the leveling station when performing geometric leveling.Therefore, the purpose of this research is to determine the nature and magnitude of stroke of the focusing lens of digital levels and, taking into account its influence, to make recommendations to existing measurement methods. To solve this problem, a verification technique was implemented by leveling the excesses from two stations. Studies have established that in high-precision digital levels, the amount of stroke of the focusing lens does not exceed 0.14 mm. This allows, when performing high-precision leveling, to increase the inequality of the shoulders at the station with virtually no loss of measurement accuracy.

New Structural Complexity Metrics for Forests from Single Terrestrial Lidar Scans

We developed new measures of structural complexity using single point terrestrial laser scanning (TLS) point clouds. These metrics are depth, openness, and isovist. Depth is a three-dimensional, radial measure of the visible distance in all directions from plot center. Openness is the percent of scan pulses in the near-omnidirectional view without a return. Isovists are a measurement of the area visible from the scan location, a quantified measurement of the viewshed within the forest canopy. 243 scans were acquired in 27 forested stands in the Pacific Northwest region of the United States, in different ecoregions representing a broad gradient in structural complexity. All stands were designated natural areas with little to no human perturbations. We created “structural signatures” from depth and openness metrics that can be used to qualitatively visualize differences in forest structures and quantitively distinguish the structural composition of a forest at differing height strata. In most cases, the structural signatures of stands were effective at providing statistically significant metrics differentiating forests from various ecoregions and growth patterns. Isovists were less effective at differentiating between forested stands across multiple ecoregions, but they still quantify the ecological important metric of occlusion. These new metrics appear to capture the structural complexity of forests with a high level of precision and low observer bias and have great potential for quantifying structural change to forest ecosystems, quantifying effects of forest management activities, and describing habitat for organisms. Our measures of structure can be used to ground truth data obtained from aerial lidar to develop models estimating forest structure.

3PCD-TP: A 3D Point Cloud Descriptor for Loop Closure Detection with Twice Projection

Loop closure detection (LCD) can effectively eliminate the cumulative errors in simultaneous localization and mapping (SLAM) by detecting the position of a revisit and building interframe pose constraint relations. However, in real-world natural scenes, driverless ground vehicles or robots usually revisit the same place from a different position, meaning that the descriptor cannot give a uniform description of similar scenes, failing LCD. Against this problem, this paper proposes a 3D point cloud descriptor with Twice Projection (3PCD-TP) for the calculation of the similarities between scenes. First, we redefined the origin and primary direction of point clouds according to their distribution and unified their coordinate system, thereby reducing the interference in position recognition due to the rotation and translation of sensors. Next, using the semantic and altitudinal information of point clouds, we generated the 3D descriptor 3PCD-TP with multidimensional features to enhance its ability to describe similar scenes. Following this, we designed a weighting similarity calculation method to reduce the false detection rate of LCD by taking advantage of the property that 3PCD-TP can be projected from multiple angles. Finally, we validated our method using KITTI and the Jilin University (JLU) campus dataset. The experimental results show that our method demonstrated a high level of precision and recall and exhibited greater performance in the face of scenes with reverse loop closure, such as opposite lanes.

Комплексный мониторинг геологической среды в пределах горного отвода строящегося тоннеля

Purpose: To consider the example of the implementation of integrated monitoring based on various information collection and analysis on soil environment movements for further prognosis on massif state and timely corrections of construction decisions. To establish sequence and rhythm of monitoring implementation stages for to obtain timely information on soil massif state. To reveal possible ways of statistical processing of observation results for to ensure deformation development prediction reliability. Methods: No-touch registration method for electromagnetic emission, ground penetrating radar method, seismic-acoustics method, geodetic method, strain gauge method, statistical methods. Results: Possibility to embody deformation complex monitoring on certain example has been studied. Possible sequence of monitoring stages with the use of modern methods and technologies has been described. It has been shown that the collection of data on soil massif state from various sources makes it possible to make reliable conclusions on mining operation safety and to verify them by using statistical analysis methods. The results of real observations of deformations in the limits of mining allotment have been considered. Recommendations are given on observation organization during flank process activation. It has been described the possibility of deformation monitoring organization with complex use of various means for measurement such as inclinometric probes, high precision levels, electronic tacheometers, load cells. Geodetic monitoring (geodetic measurements) of deformations during tunnel construction should be carried out. The paper considers the need to project and create geodetic monitoring planned-altitude networks serving as a base to make observations with required accuracy on offset of construction’s structures and objects surrounding the construction. Practical significance: The results can be used in job organization to monitor offsets in excavation outputs, day surface (surrounding buildings) deformations, in the design of observation stations.

A Clinical Evaluation of the Accuracy of an Intrathecal Drug Delivery Device

IntroductionImplantable intrathecal drug delivery (ITDD) devices are used to treat severe pain and spasticity refractory to conventional medical management. Although off-label medications and drug admixtures are commonly used in clinical practice and recommended by international guidelines, manufacturers state that this practice can result in device failure. The impact of off-label drugs and drug combinations on pump accuracy has hitherto never been assessed. Materials and MethodsA multinational, three-center, retrospective review of patient records was undertaken. The inclusion criterion was the presence of an ITDD device implantation in adult patients, with the pump in situ for the expected battery lifespan. Residual drug volumes at each refill, drug mixtures and concentrations, and rate and flow pattern of the pump (simple or flex) were recorded. A normalized flow rate ratio was calculated (actual to theoretical flow rate). The impact of nonapproved drugs, battery life, pump size, and flow program on drug delivery accuracy was assessed. ResultsData from 1402 pump refills were collected (73 patients). The overall mean accuracy ratio was 0.995 (95% CI = 0.986–1.004). The ratio for approved drug status was 0.990 vs 0.997 in nonapproved, with a difference of −0.007 (−0.032 to 0.017). At the tenth centile for remaining battery life (14 months), the ratio was 0.983 vs 1.009 for the 90th centile (69 months), with a difference of −0.026 (−0.038 to −0.014). The ratio for flex administration was 0.982 vs 1.006 for simple, with a difference of −0.024 (−0.040 to −0.008). For pump size of 40 mL, the ratio was 0.975 vs 1.010 for 20 mL, with a difference of −0.035 (−0.063 to −0.008). The 95% prediction interval for individual refill ratios was ±0.15. ConclusionIn a clinical setting, the ITDD pumps retained high levels of accuracy and acceptable precision across their lifespan despite using unapproved drugs or admixtures and under various flow modes and rates.

Artificial Intelligence Algorithms for Detecting and Classifying MQTT Protocol Internet of Things Attacks

The Internet of Things (IoT) grew in popularity in recent years, becoming a crucial component of industrial, residential, and telecommunication applications, among others. This innovative idea promotes communication between physical components, such as sensors and actuators, to improve process flexibility and efficiency. Smart gadgets in IoT contexts interact using various message protocols. Message queuing telemetry transfer (MQTT) is a protocol that is used extensively in the IoT context to deliver sensor or event data. The aim of the proposed system is to create an intrusion detection system based on an artificial intelligence algorithm, which is becoming essential in the defense of the IoT networks against cybersecurity threats. This study proposes using a k-nearest neighbors (KNN) algorithm, linear discriminant analysis (LDA), a convolutional neural network (CNN), and a convolutional long short-term memory neural network (CNN-LSTM) to identify MQTT protocol IoT intrusions. A cybersecurity system based on artificial intelligence algorithms was examined and evaluated using a standard dataset retrieved from the Kaggle repository. The dataset was injected by five attacks, namely brute-force, flooding, malformed packet, SlowITe, and normal packets. The deep learning algorithm achieved high performance compared with the developing security system using machine learning algorithms. The performance accuracy of the KNN method was 80.82%, while the accuracy of the LDA algorithm was 76.60%. The CNN-LSTM model attained a high level of precision (98.94%) and is thus very effective at detecting intrusions in IoT settings.

A ‘Dynamic Kibble’ mass balance for the undergraduate physics teaching laboratory

Originally envisaged in 1975 to realise the SI unit of electrical current, the Ampere, the Kibble balance has since developed into a powerhouse of modern scientific measurement. By combining theoretical simplicity with precision of measurement, it has enabled the redefinition of Planck’s constant, and subsequently a practical method of defining the kilogram in terms of fundamental constants. This article introduces a novel version of this classic apparatus, the ‘Dynamic Kibble’ Balance. Dynamic in this case because the magnet velocity is now 3 orders of magnitude higher than the original, but the same theory applies. The apparatus is simple in approach, robust, easy to set up, and capable of a high level of precision using only electrical measurements (plus length and time). The importance of this measurement to metrology re-enforces the link between what is measured in the laboratory via calibration, measurement standards, and traceability. Using the apparatus and measurements described in this paper, the mass of the magnet assembly was measured as 19.4 ± 0.3 g, which lies within one SEM of the known value. This paper describes an uncomplicated method with a clear focus on the key physics and theory required. This experiment is intended for use in a first-year undergraduate physics laboratory. Further potential for both more advanced theory demonstration and experimental work is discussed.

Density-Based Unsupervised Learning Algorithm to Categorize College Students into Dropout Risk Levels

Compliance with the basic conditions of quality in higher education implies the design of strategies to reduce student dropout, and Information and Communication Technologies (ICT) in the educational field have allowed directing, reinforcing, and consolidating the process of professional academic training. We propose an academic and emotional tracking model that uses data mining and machine learning to group university students according to their level of dropout risk. We worked with 670 students from a Peruvian public university, applied 5 valid and reliable psychological assessment questionnaires to them using a chatbot-based system, and then classified them using 3 density-based unsupervised learning algorithms, DBSCAN, K-Means, and HDBSCAN. The results showed that HDBSCAN was the most robust option, obtaining better validity levels in two of the three internal indices evaluated, where the performance of the Silhouette index was 0.6823, the performance of the Davies–Bouldin index was 0.6563, and the performance of the Calinski–Harabasz index was 369.6459. The best number of clusters produced by the internal indices was five. For the validation of external indices, with answers from mental health professionals, we obtained a high level of precision in the F-measure: 90.9%, purity: 94.5%, V-measure: 86.9%, and ARI: 86.5%, and this indicates the robustness of the proposed model that allows us to categorize university students into five levels according to the risk of dropping out.

Symbiotic microbiota and odor ensure mating in time for giant pandas.

To achieve reproduction, male solitary mammals need to locate females using chemical communication with high levels of precision. In the case of giant pandas, the total estrus period of females was usually 15 days each year, however, successful mating activity is finished within 3 days from respective home range. The mating pattern of giant pandas, where multiple males compete for each female requires females employ efficient systems to communicate their estrus phases. To verifying whether the scent secretions of giant pandas changes by gender and estrus progression, the microbiota and compounds in 29 anogenital gland samples from 14 individuals during estrus were analyzed by 16S rRNA sequencing and GC-MS. We show that the microbiota communities covary by gender with 4 particular compounds of scent secretions. Among 597 genera, 34 were identified as biomarkers that could be used to distinguish between different estrus phases. By bacterial-compounds co-analysis, 3 fatty ester acids and squalene compounds covaried with the development of estrus in the bacterial communities of female giant pandas. This study helps clarify how a large, solitary mammal expresses accurate information to improve the likelihood of successful reproduction by changing the composition of microbiota and odor compounds of anogenital glands during estrus.

Advancements in the Additive Manufacturing of Magnesium and Aluminum Alloys through Laser-Based Approach.

Complex structures can now be manufactured easily utilizing AM technologies to meet the pre-requisite objectives such as reduced part numbers, greater functionality, and lightweight, among others. Polymers, metals, and ceramics are the few materials that can be used in AM technology, but metallic materials (Magnesium and Aluminum) are attracting more attention from the research and industrial point of view. Understanding the role processing parameters of laser-based additive manufacturing is critical to maximize the usage of material in forming the product geometry. LPBF (Laser powder-based fusion) method is regarded as a potent and effective additive manufacturing technique for creating intricate 3D forms/parts with high levels of precision and reproducibility together with acceptable metallurgical characteristics. While dealing with LBPF, some degree of porosity is acceptable because it is unavoidable; hot ripping and cracking must be avoided, though. The necessary manufacturing of pre-alloyed powder and ductility remains to be the primary concern while dealing with a laser-based additive manufacturing approach. The presence of the Al-Si eutectic phase in AlSi10Mg and AlSi12 alloy attributing to excellent castability and low shrinkage, attaining the most attention in the laser-based approach. Related studies with these alloys along with precipitation hardening and heat treatment processing were discussed. The Pure Mg, Mg-Al alloy, Mg-RE alloy, and Mg-Zn alloy along with the mechanical characteristics, electrochemical durability, and biocompatibility of Mg-based material have been elaborated in the work-study. The review article also summarizes the processing parameters of the additive manufacturing powder-based approach relating to different Mg-based alloys. For future aspects, the optimization of processing parameters, composition of the alloy, and quality of powder material used will significantly improve the ductility of additively manufactured Mg alloy by the LPBF approach. Other than that, the recycling of Mg-alloy powder hasn't been investigated yet. Meanwhile, the post-processing approach, including a homogeneous coating on the porous scaffolds, will mark the suitability in terms of future advancements in Mg and Al-based alloys.

Concurrent AtC Multiscale Modeling of Material Coupled Thermo-Mechanical Behaviors: A Review

Advances in the field of processing and characterization of material behaviors are driving innovations in materials design at a nanoscale. Thus, it is demanding to develop physics-based computational methods that can advance the understanding of material Multiphysics behaviors from a bottom-up manner at a higher level of precision. Traditional computational modeling techniques such as finite element analysis (FE) and molecular dynamics (MD) fail to fully explain experimental observations at the nanoscale because of the inherent nature of each method. Concurrently coupled atomic to the continuum (AtC) multi-scale material models have the potential to meet the needs of nano-scale engineering. With the goal of representing atomistic details without explicitly treating every atom, the AtC coupling provides a framework to ensure that full atomistic detail is retained in regions of the problem while continuum assumptions reduce the computational demand. This review is intended to provide an on-demand review of the AtC methods for simulating thermo-mechanical behavior. Emphasis is given to the fundamental concepts necessary to understand several coupling methods that have been developed. Three methods that couple mechanical behavior, three methods that couple thermal behavior, and three methods that couple thermo-mechanical behavior is reviewed to provide an evolutionary perspective of the thermo-mechanical coupling methods.

Guided Access Cavity Preparation Using a New Simplified Digital Workflow

IntroductionThis study evaluated the precision of a simplified workflow using only preoperative cone-beam computed tomographic (CBCT) scans to gain guided access to root canals of extracted mandibular molars. A workflow using CBCT scanning associated with 3-dimensional oral scanning was used as a reference for comparison. The influence of the presence of coronal restoration in the simplified workflow was also evaluated. MethodsForty-five mandibular molars were randomized into 3 groups: a control group in which digital planning was performed with CBCT and oral scanning and 2 experimental groups in which digital planning was performed only with CBCT examination. In experimental group 1, teeth had no coronal restorations, whereas in group 2 teeth presented with coronal composite restorations. After digital planning, the teeth were accessed using the guides, and a new CBCT scan was made to overlap the pre- and postoperative examinations. Precision was measured by calculating the deviation between the planned and prepared cavities in millimeters and angle. Data were compared using 1-way analysis of variance (P < .05). ResultsAll root canals were accessible after access preparation in all tested groups. Deviations of the planned and prepared access cavities were low, with a mean value of 0.55, 0.58, and 0.47 mm and 1.98°, 2.45°, and 1.43° for the control group, group 1, and group 2, respectively. No significant differences in millimeters or angle were observed among the 3 tested groups (P > .05). ConclusionsThe simplified digital workflow using only CBCT examination allowed a high level of precision in obtaining access in extracted molars with and without coronal restoration, presenting similar results compared with the digital workflow using CBCT and 3-dimensional oral scanning.

Injury Biomechanics Evaluation of a Driver with Disabilities during a Road Accident-A Numerical Approach.

Numerical methods are often a robust way to predict how external mechanical loads affect individual biological structures. Computational models of biological systems have been developed over the years, reaching high levels of detail, complexity, and precision. In this study, two cases were analysed, differing in the airbag operation; in the first, the airbag was normally activated, and in the second case, the airbag was disabled. We analysed a model of a disabled person without a left leg who steers a vehicle using a specialized knob on the steering wheel. In both cases, a head-on collision between a car moving at an initial speed of 50 km/h and a rigid obstacle was analysed. We concluded that the activated airbag for a person with disabilities reduces the effects of asymmetries in the positioning of the belts and body support points. Moreover, all the biomechanical parameters, analysed on the 50th percentile dummy, i.e., HIC, seat belt contact force and neck injury criterion (Nij) support the use of an airbag. The resulting accelerations, measured in the head of the dummy, were induced into a finite element head model (YEAHM) to kinematically drive the head and simulate both accidents, with and without the airbag. In the latter, the subsequent head injury prediction revealed a form of contrecoup injury, more specifically cerebral contusion based on the intracranial pressure levels that were achieved. Therefore, based on the in-depth investigation, a frontal airbag can significantly lower the possibility of injuries for disabled drivers, including cerebral contusions.

Method using torque mode of motor for the shift of two-speed planetary CLAMT in bilateral electric drive tracked vehicle

For the shift control of clutchless automotive manual transmission (CLAMT) in electric vehicle, great difficulty is caused by the high level of precision and rapidity requirements of the speed and mode response of motor as well as the position response of gearshift sleeve, especially when confronted with off-road environment. To overcome the difficulty and achieve fast shift, a practical control method is proposed and applied to two-speed planetary CLAMT for off-road tracked vehicle with bilateral electric drive system, wire control system and unmanned driving purpose. In shift process, the method lets motor be controlled by applying torque mode and constant torque during active speed adjusting phase, lets gear engaging phase be started at the time when transmission ratio is regulated beyond a certain value close to target gear ratio – that is, at the time when the approach of synchronized state is achieved, lets synchronizer make a help for precise gear synchronization. Theoretical analysis of gear synchronization process is carried out. By increasing the level of motor torque, the duration of active speed adjusting phase can be obviously shortened. With the approach of synchronized state judged by using transmission ratio margin of small fixed positive value for reference, gear engaging phase can be achieved quickly. Off-road experiments show good performance of the shift control method. Experimental results and phenomena are discussed in detail for further and better understanding of real shift process.

Gene Editing in Cancer Therapy

The site-specific modification of an existing gene is known as gene editing. A section of DNA must be cut with an endonuclease (such as the CRISPR-Cas9 system) before the two severed ends are brought together, frequently with a new or improved sequence inserted between them. Somatic cell gene editing can be helpful in a variety of clinical contexts, and some preliminary preclinical and clinical trials have been carried out. Extremely high levels of precision are required for DNA recognition, excision, and repair; issues with publishing integrity must be resolved. Germline editing utilizing eggs, sperm, or embryos raises ethical concerns

Accuracy, precision, and safety of stereotactic, frame-based, intraoperative MRI-guided and MRI-verified deep brain stimulation in 650 consecutive procedures.

Suboptimal lead placement is one of the most common indications for deep brain stimulation (DBS) revision procedures. Confirming lead placement in relation to the visible anatomical target with dedicated stereotactic imaging before terminating the procedure can mitigate this risk. In this study, the authors examined the accuracy, precision, and safety of intraoperative MRI (iMRI) to both guide and verify lead placement during frame-based stereotactic surgery. A retrospective analysis of 650 consecutive DBS procedures for targeting accuracy, precision, and perioperative complications was performed. Frame-based lead placement took place in an operating room equipped with an MRI machine using stereotactic images to verify lead placement before removing the stereotactic frame. Immediate lead relocation was performed when necessary. Systematic analysis of the targeting error was calculated. Verification of 1201 DBS leads with stereotactic MRI was performed in 643 procedures and with stereotactic CT in 7. The mean ± SD of the final targeting error was 0.9 ± 0.3 mm (range 0.1-2.3 mm). Anatomically acceptable lead placement was achieved with a single brain pass for 97% (n = 1164) of leads; immediate intraoperative relocation was performed in 37 leads (3%) to obtain satisfactory anatomical placement. General anesthesia was used in 91% (n = 593) of the procedures. Hemorrhage was noted after 4 procedures (0.6%); 3 patients (0.4% of procedures) presented with transient neurological symptoms, and 1 experienced delayed cognitive decline. Two bleeds coincided with immediate relocation (2 of 37 leads, 5.4%), which contrasts with hemorrhage in 2 (0.2%) of 1164 leads implanted on the first pass (p = 0.0058). Three patients had transient seizures in the postoperative period. The seizures coincided with hemorrhage in 2 of these patients and with immediate lead relocation in the other. There were 21 infections (3.2% of procedures, 1.5% in 3 months) leading to hardware removal. Delayed (> 3 months) retargeting of 6 leads (0.5%) in 4 patients (0.6% of procedures) was performed because of suboptimal stimulation benefit. There were no MRI-related complications, no permanent motor deficits, and no deaths. To the authors' knowledge, this is the largest series reporting the use of iMRI to guide and verify lead location during DBS surgery. It demonstrates a high level of accuracy, precision, and safety. Significantly higher hemorrhage was encountered when multiple brain passes were required for lead implantation, although none led to permanent deficit. Meticulous audit and calibration can improve precision and maximize safety.