Final Location Research Articles

Context matters during pick-and-place in VR: Impact on search and transport phases.

When considering external assistive systems for people with motor impairments, gaze has been shown to be a powerful tool as it is anticipatory to motor actions and is promising for understanding intentions of an individual even before the action. Up until now, the vast majority of studies investigating the coordinated eye and hand movement in a grasping task focused on single objects manipulation without placing them in a meaningful scene. Very little is known about the impact of the scene context on how we manipulate objects in an interactive task. In the present study, it was investigated how the scene context affects human object manipulation in a pick-and-place task in a realistic scenario implemented in VR. During the experiment, participants were instructed to find the target object in a room, pick it up, and transport it to a predefined final location. Thereafter, the impact of the scene context on different stages of the task was examined using head and hand movement, as well as eye tracking. As the main result, the scene context had a significant effect on the search and transport phases, but not on the reach phase of the task. The present work provides insights into the development of potential supporting intention predicting systems, revealing the dynamics of the pick-and-place task behavior once it is realized in a realistic context-rich scenario.

How to locate urban–rural transit hubs from the viewpoint of county integration?

Chinese new urbanization requires the integration of urban and rural transportation, especially at the county level. Establishing a reliable and practical method to locate urban–rural transit hubs becomes a key issue in transportation planning. To solve the issue that existing methods lack applicability in practices due to the need for costly data collection, this study develops an application-oriented model. First, we generate basic nodes with traffic analysis zones in both urban and rural areas. Second, the node importance evaluation model is established to identify potential hub zones based on socioeconomic and topological factors. Third, we optimize the final hub locations to maximize the served population and urban transit accessibility. To reflect passenger characteristics, accessibility to opportunities is defined in terms of weighted land-use areas within a walking distance. ArcGIS software is applied to improve the efficiency of data processing and to improve the accuracy of the calculated network distances. A case study is conducted in Gaoping, China, to confirm the validity of the proposed approach. The results indicate that the optimal hub locations are effectively aligned with the practical conditions, thus improving travel convenience. The proposed approach has the potential for broader use by transport planners and policymakers in developing people-oriented and integrated urban–rural transit hubs.

A multi-scale multi-model deep neural network via ensemble strategy on high-throughput microscopy image for protein subcellular localization

Protein subcellular locations are closely related to the function of proteins. By detecting the abnormalities in subcellular locations, we can infer the occurrence of some diseases and mine new drug targets. A large number of single-cell high-throughput microscopy images provide us with relevant resources for studying protein distribution patterns. However, in the existing image-based protein subcellular localization methods, the traditional techniques are lack of efficiency and accuracy, and the potential of deep learning methods has not been fully tapped. So in this study, we propose a multi-scale multi-model deep neural network via ensemble strategy for protein subcellular localization on single-cell high-throughput images. First of all, we employ a deep convolutional neural network as multi-scale feature extractor and use global average pooling to map extracted features at different stages into feature vectors, then concatenate these multi-scale features to form a multi-model structure for image classification. In addition, we add Squeeze-and-Excitation Blocks to the network to emphasize more informative features. What is more, we use an ensemble method to fuse the classification results from the multi-model structure to obtain the final subcellular location of each single-cell image. Experiments show the validity and effectiveness of our method on yeast cell images, it can significantly improve the accuracy of high-throughput microscopy image-based protein subcellular localization, and we achieve the classification accuracy of 0.9098 on the high-throughput microscopy images of yeast cells. In the work of protein subcellular localization, our method provides a framework for processing and classifying microscope images, and further lays the foundation for the study of protein and gene functions.

Energy-Aware Trajectory Design for Outage Minimization in UAV-Assisted Communication Systems

This paper studies the flight trajectory of unmanned aerial vehicles (UAV) to provide fifth-generation (5G) cellular service in a given area. We consider a single UAV launched from the fixed initial to the final location, during which it serves the ground users that are distributed in a circular field. UAV’s limited on-board energy has been a major concern affecting the system’s performance. Therefore, in this work, we minimize the average outage probability of the system by optimizing the three-dimensional (3D) trajectory of the UAV while considering the velocity and on-board energy as constraints. To solve this problem, we propose two approaches: the low-complexity <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">vertex</i> and the high-performance <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sequential approach</i> . The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">vertex approach</i> involves two steps. Firstly, it obtains the optimal solution while relaxing the velocity and on-board energy constraints. Secondly, a greedy solution is proposed for the original problem. The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sequential approach</i> finds the optimal location in each time slot sequentially. Simulation results compare the two approaches and show that our proposed strategies provide on an average 41% improvement in average outage probability over the benchmark schemes. Additionally, we show that the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sequential approach</i> is better than the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">vertex approach</i> , though at the cost of high computational complexity.

Wi-Fi indoor 3D localization algorithm based on multi-classifier fusion

Indoor localization technology based on Received Signal Strength (RSS) fingerprint is widely used in life and industry. Compared with the traditional localization methods, the localization technology integrating multiple machine learning methods has better localization accuracy. However, in multi-floor localization, the existing fusion localization technology ignores the interaction between different floors in the localization process, resulting in low indoor localization accuracy. This paper proposes a Wi-Fi indoor 3D localization method based on multi-classifier fusion named FLMCF. Firstly, floor classification training is carried out to reduce the location deviation in the vertical direction. Secondly, for each floor, multiple classifiers are used for model training and training the optimal weight set by minimizing the average localization error. In this case, the advantages of each classifier can be fully integrated to improve the localization accuracy. Finally, the Reliability Fusion Weight Selection (RFWS) algorithm determines the weight and calculates the final location estimation. The experimental results indicate that FLMCF is nearly 14.1% better than DIFMIC in the 90th percentile of CDF.

Evaluation of solid biomedical waste management practices in six health facilities in southern Benin

Introduction: Health care generates biomedical waste that present risks to humans and the environment if poorly managed. The objective of this study was to assess the management practices of solid biomedical waste in southern Benin. Methods: This was a descriptive cross-sectional study conducted in six health facilities. The study included 12 administrative agents selected by reasoned choice and 431 health care agents selected by convenience. The data were collected by questionnaire, interview, and observation. They concerned variables related to the production, the practice of managing, knowledge of the impact of solid biomedical waste on the environment and health, training and protection of personnel. Data analysis was done with R 4.5.0 software. Quantitative variables were described by median and interquartile range. Proportions were compared with the chi-square test or that of Fisher at the threshold of 0.05. Results: The health facilities did not have solid biomedical waste management database. Sorting was not systematic in 59.5 %. Final storage locations did not meet standards. Almost one in four health workers (24.4 %) were injured by biomedical waste. Overall, 45.8 % of the staff had been trained at least once on biomedical waste management. 61 % of the staff surveyed were vaccinated, hepatitis B (41.3 %), tetanus (32.9 %). Conclusion: In view of the results, it is necessary to ensure the on ongoing awareness and training of medical staff in the sorting and packaging of biomedical waste and to set up an efficient and sustainable solid biomedical waste management system with effective monitoring mechanisms.

Molecular Basis of the Schuurs-Hoeijmakers Syndrome: What We Know about the Gene and the PACS-1 Protein and Novel Therapeutic Approaches.

The Schuurs–Hoeijmakers syndrome (SHMS) or PACS1 Neurodevelopment Disorder (PACS1-NDD) is a rare autosomal dominant disease caused by mutations in the PACS1 gene. To date, only 87 patients have been reported and, surprisingly, most of them carry the same variant (c.607C>T; p.R203W). The most relevant clinical features of the syndrome include neurodevelopment delay, seizures or a recognizable facial phenotype. Moreover, some of these characteristics overlap with other syndromes, such as the PACS2 or Wdr37 syndromes. The encoded protein phosphofurin acid cluster sorting 1 (PACS-1) is able to bind to different client proteins and direct them to their subcellular final locations. Therefore, although its main function is protein trafficking, it could perform other roles related to its client proteins. In patients with PACS1-NDD, a gain-of-function or a dominant negative mechanism for the mutated protein has been suggested. This, together with the fact that most of the patients carry the same genetic variant, makes it a good candidate for novel therapeutic approaches directed to decreasing the toxic effect of the mutated protein. Some of these strategies include the use of antisense oligonucleotides (ASOs) or targeting of its client proteins.

Investigation of the hydrogen-induced cracking of E690 steel welded joint in simulated seawater

Hydrogen-induced cracking (HIC) behavior and mechanism of E690 welded joint in simulated seawater were studied via microstructure observations, electrochemical hydrogen charging, slow strain rate tension (SSRT) tests and hydrogen content measurement. The results show that the welded joint of E690 steel has a higher HIC susceptibility than that of base metal, in which the inter-critical heat affected zone (ICHAZ) is composed of polygonal ferrite and granular bainite is the final fracture location in the joint. ICHAZ with the lowest yield strength deformed preferentially under the tensile stress, and subsequently, the proliferating dislocations with the deformation strengthening and the continuously charged hydrogen led to the HIC and brittle fracture at the ICHAZ of the welded joint. Moreover, the HIC susceptibility was linearly dependent on the logarithm of total hydrogen concentration in the steel, and the hydrogen concentration had a more obvious effect on the welded joint than the base metal. The higher density of piled dislocations adjoining the M/A islands in the welded joint exhibited a significant effect on the hydrogen agglomeration and diffusion, which enhanced the HIC susceptibility.

Neuroblast migration along cellular substrates in the developing porcine brain.

SummaryIn the past decade it has become evident that neuroblasts continue to supply the human cortex with interneurons via unique migratory streams shortly following birth. Owing to the size of the human brain, these newborn neurons must migrate long distances through complex cellular landscapes to reach their final locations. This process is poorly understood, largely because of technical difficulties in acquiring and studying neurotypical postmortem human samples along with diverging developmental features of well-studied mouse models. We reasoned that migratory streams of neuroblasts utilize cellular substrates, such as blood vessels, to guide their trek from the subventricular zone to distant cortical targets. Here, we evaluate the association between young interneuronal migratory streams and their preferred cellular substrates in gyrencephalic piglets during the developmental equivalent of human birth, infancy, and toddlerhood.

Relationship between Concrete Hole Shape and Meso-Crack Evolution Based on Stereology Theory and CT Scan under Compression.

To achieve more accurate prediction of the potential failure location and to conduct a deeper analysis of the failure mechanism of concrete constructions, it is critical to probe the evolution process of internal meso-cracks that bear various intensities of load. While a computer Tomography (CT) test provides a non-destructive detection technique for obtaining the internal meso-damage state of concrete, traditional image processing and Digital Image Correlation (DIC) are ineffective in extracting meso-damage information from concrete CT images. On the other hand, by observing the shape change law of concrete’s internal holes under load, it is proposed to use the hole roundness and area fraction formula, developed based on the stereology principle and morphology, to characterize and predict the potential failure location. Four features particularly addressed include the CT image as a whole, image equal partitioning, crack and non-crack areas, and representative holes. The approach is to explore the variation law of critical hole shape parameters, especially the hole roundness under different loading stages, and analyze the relationship between the change in hole shapes and the final macro-crack positions. It is found that compared with the average area fraction, the average hole roundness value of cross section images is more sensitive to the change in stress. In both uniform partitioning and non-uniform partitioning, the average hole roundness value near the final macro-crack location exhibits an increase trend with the stress, while the smoothing effect caused by the hole roundness averaging always exists. Near the final macro-crack location, the roundness of each individual hole is positively associated with the stress, while away from the final macro-crack location such a relation may not be observed. This trend expounds the evolution process of meso-damage in concrete, and the finding can be used to predict the accurate locations of macro-cracks.

Risk factors and diagnosis of iatrogenic damage of periodontal structures and roots during orthodontic Mini-Implants implantation procedures - a systematic literature review

Introduction and purpose&#x0D; In recent years, Mini-Implants (MI) have gained popularity and new complications have emerged with them. The article assesses the current reports on the scale of the problem, factors and diagnostic possibilities related to iatrogenic injuries of periodontal tissues and roots.&#x0D; &#x0D; Description of the state of knowledge&#x0D; The incidence of complications was estimated to be 13.5%. Complications are more common in the mandible and are estimated at 20-27.1%. Periodontal and root damage are an important risk factor for treatment failure. The fact that the implant does not interfere with the alveolus structure gives the treatment effectiveness in 90%, and the contact with the alveolar “lamina dura” is 62.5%. Interference with the root structure is successful in only 31.2%.&#x0D; Risk factors for failure include: young age, poor hygiene, smoking, area of mandibular molars, contact with the root, thickness of the bone and lack of experience. The implant between the roots is a risk of root trauma, as the location close to the tooth cemento-enamel junction, no preparation for surgery, not using surgical templates, strenuous implantation or implant migration under the influence of orthodontic forces. Radiographs are the gold standard in the diagnosis of complications, but they do not allow for a full assessment of the three-dimensional structures of the implant. A promising method is the evaluation of the torque as the implant is placed in its final location. The patient's subjective feelings are questionable in diagnosis and require further research.&#x0D; Summary&#x0D; There are many complications in using MI and the most important of these is damage to the structures of the periodontium and the tooth root. Despite the low failure rate, failure should be prevented by pre-operative evaluation, in-operative monitoring, and post-operative diagnostics.

Detecting Endotracheal Tube and Carina on Portable Supine Chest Radiographs Using One-Stage Detector with a Coarse-to-Fine Attention.

In intensive care units (ICUs), after endotracheal intubation, the position of the endotracheal tube (ETT) should be checked to avoid complications. The malposition can be detected by the distance between the ETT tip and the Carina (ETT–Carina distance). However, it struggles with a limited performance for two major problems, i.e., occlusion by external machine, and the posture and machine of taking chest radiographs. While previous studies addressed these problems, they always suffered from the requirements of manual intervention. Therefore, the purpose of this paper is to locate the ETT tip and the Carina more accurately for detecting the malposition without manual intervention. The proposed architecture is composed of FCOS: Fully Convolutional One-Stage Object Detection, an attention mechanism named Coarse-to-Fine Attention (CTFA), and a segmentation branch. Moreover, a post-process algorithm is adopted to select the final location of the ETT tip and the Carina. Three metrics were used to evaluate the performance of the proposed method. With the dataset provided by National Cheng Kung University Hospital, the accuracy of the malposition detected by the proposed method achieves and the ETT–Carina distance errors are less than mm.

PEMASARAN BAWANG MERAH RAMAH LINGKUNGAN DI KABUPATEN BANTUL

Environmentally friendly shallots in Bantul Regency have better quality than conventional systems. This study aims to (1) determine the marketing channels for environmentally friendly shallots in Bantul Regency and (2) analyze marketing costs, marketing margins, marketing benefits, and farmers' share of environmentally friendly shallots in Bantul Regency. The research method used is the descriptive analysis method. A sampling of farmers using proportional random sampling of as many as 62 environmentally friendly shallots. A sample of traders using snowball sampling of as many as 32 marketing institutions. The results showed six marketing channels in the local DIY market and four outside DIY. The highest marketing costs and margins for shallots are in marketing channel 8, with the final sales location in outside from DIY. The price of shallots and the highest marketing profit is found in marketing channel 6. The highest farmer's share value is found in marketing channel 2 with a value of 71.68% for local DIY and marketing channel 6 with 71.55% for marketing outside DIY.

The interactive dynamics of a binary asteroid and ejecta after medium kinetic impact

Kinetic impacts on a binary asteroid will produce ejecta debris as well as causing a disturbance to the spin-orbit motion of the binary components. Understanding the complex interactions between the ejecta and the binary system can be crucial to both theoretical study and mission design. In this paper, we develop a detailed model for the dynamical evolution of ejecta within a binary asteroid system, in which we combined various perturbations on the ejecta and considered the collisional process with the asteroid. Taking an example scenario like the DART impact, we calculated the fate of ejecta from size 0.01 mm to 10 m and analyzed the distribution of their final deposition locations. The results show that ejecta with diameter less than 0.1 mm escape quickly under the influence of solar radiation pressure, while ejecta of larger size survive longer, i.e., a few cycles in the binary system for more than 400 days. We analyzed the influence of the coefficient of restitution between ejecta and asteroid, and found more damped collisions would allow the ejecta to survive longer in orbit. We also studied the effect of the tumbling rotation of the secondary on the distribution of ejecta on the surface of the secondary, the results suggest that a tumbling rotational state causes obvious changes in Dimorphos’ surface slope, which, however, are not sufficient for triggering surface landslides. In addition, the influence of the internal structure of the primary on the evolution of the ejecta is studied, and we show it has little effect on the evolution of the ejecta but does affect the distribution of ejecta on the surface of the primary. This is due to the change of the distribution of relative acceleration on the surface of the primary, which changes the regions where the ejecta can remain.

MOCLoc: Emerging Online Collaborative Localization Enhanced by Multidimensional Scaling

In human activity recognition, it is important to first recognize the position of a user. Although numerous fingerprinting schemes have been researched for indoor localization, they work in a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">stand-alone</i> mode without considering the potentials of exploiting multiple requesting users’ online fingerprints. In this paper, we propose an emerging online collaborative localization paradigm to serve the scenarios of multiple users requesting localizations at the same time, which enables a kind of collective calibration by exploiting latent relations in between requesting users in both the signal space and physical space. The proposed scheme is called MOCLoc, which first applies the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multidimensional scaling</i> (MDS) technique to compute online users’ virtual locations based on their online fingerprints. A new virtual location credibility is next computed for each selected <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">reference point</i> (RP) based on the similarity between its virtual distances and physical distances to other online users. We also compute a collaborative credibility and signal credibility and fuse all three kinds of credibilities to compute a new RP ranking weight that is used to output the user final location. Furthermore, we propose to include a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">device calibration</i> module based on the mean-subtraction fingerprint transformation to differentiate the collaborative calibration process for heterogeneous online devices. Experiments on field measurements validate the effectiveness of the proposed MOCLoc scheme in terms of further reduced localization errors.

An IoT Measurement System Based on LoRaWAN for Additive Manufacturing.

The Industrial Internet of Things (IIoT) paradigm represents a significant leap forward for sensor networks, potentially enabling wide-area and innovative measurement systems. In this scenario, smart sensors might be equipped with novel low-power and long range communication technologies to realize a so-called low-power wide-area network (LPWAN). One of the most popular representative cases is the LoRaWAN (Long Range WAN) network, where nodes are based on the widespread LoRa physical layer, generally optimized to minimize energy consumption, while guaranteeing long-range coverage and low-cost deployment. Additive manufacturing is a further pillar of the IIoT paradigm, and advanced measurement capabilities may be required to monitor significant parameters during the production of artifacts, as well as to evaluate environmental indicators in the deployment site. To this end, this study addresses some specific LoRa-based smart sensors embedded within artifacts during the early stage of the production phase, as well as their behavior once they have been deployed in the final location. An experimental evaluation was carried out considering two different LoRa end-nodes, namely, the Microchip RN2483 LoRa Mote and the Tinovi PM-IO-5-SM LoRaWAN IO Module. The final goal of this research was to assess the effectiveness of the LoRa-based sensor network design, both in terms of suitability for the aforementioned application and, specifically, in terms of energy consumption and long-range operation capabilities. Energy optimization, battery life prediction, and connectivity range evaluation are key aspects in this application context, since, once the sensors are embedded into artifacts, they will no longer be accessible.

Predicting larval alewife transport in Lake Michigan using hydrodynamic and Lagrangian particle dispersion models

AbstractSeveral species of fish in large lakes and marine environments have a pelagic larval stage, and are subject to variable transport that can ultimately regulate survival and recruitment success. Alewife, Alosa pseudoharengus, are subject to transport by complex coastal currents during their pelagic larval stage (~ 30 d). We assessed backward‐trajectory simulations, consisting of a Lagrangian particle dispersion model linked to the Finite Volume Community Ocean Model, to estimate likely hatch locations of aged larval alewife collected from locations on both the eastern and western sides of Lake Michigan during July 2015. We used four deployments of three satellite‐tracked drifter buoys in coastal waters to assess model skill in estimating the origin of a drifter from its final location. We found that the trajectories of drifters varied greatly, depending on wind events and associated coastal transport processes, including upwelling/downwelling and coastal jet currents. In 2 of 12 cases, the backward trajectory simulations failed to predict the drifter origin, associated with transport of 170 km in a narrow coastal jet current. In the remaining 10 cases, the known drifter origin was within 3.5 km of the spatial patch of predicted possible origins for a scenario of horizontal diffusivity (188 m2 s−1) consistent with the offshore model grid resolution. Modeled backward trajectories estimated that alewife originated from the same side of the lake where they were collected, within ~ 100 km of the collection site. Our paper demonstrates the utility of hydrodynamic models to estimate a region of origin for aged larval fish.

A Two-Stage Model with an Improved Clustering Algorithm for a Distribution Center Location Problem under Uncertainty

Distribution centers are quite important for logistics. In order to save costs, reduce energy consumption and deal with increasingly uncertain demand, it is necessary for distribution centers to select the location strategically. In this paper, a two-stage model based on an improved clustering algorithm and the center-of-gravity method is proposed to deal with the multi-facility location problem arising from a real-world case. First, a distance function used in clustering is redefined to include both the spatial indicator and the socio-economic indicator. Then, an improved clustering algorithm is used to determine the optimal number of distribution centers needed and the coverage of each center. Third, the center-of-gravity method is used to determine the final location of each center. Finally, the improved method is compared with the traditional clustering method by testing data from 12 cities in Inner Mongolia Autonomous Region in China. The comparison result proves the proposed method’s effectiveness.

Incidence and Risk Factors for Spinal Cord Stimulator Lead Migration With or Without Loss of Efficacy: A Retrospective Review of 91 Consecutive Thoracic Lead Implants

ObjectiveLead migration after spinal cord stimulator (SCS) implant is a commonly reported complication and the most common reason for revision surgery in cases of loss of efficacy. The primary aims of this study are to describe the incidence and degree of lead migration in the subacute postoperative period after SCS implant and to report potential risk factors for lead migration. Materials and MethodsWe performed a retrospective chart review of all patients at a single academic center who received an SCS implant from January 1, 2020, to December 31, 2020. Information on patient (age, sex, weight, and height) and operative factors (device manufacturer, epidural access level and method, and implantable pulse generator location) were extracted from medical records. Intraoperative imaging was compared to subacute follow-up imaging obtained less than 20 days postimplant to measure lead migration distance. Regression models were fitted to determine associations between lead migration distance and potential clinical risk factors. ResultsA total of 91 cases (182 leads) were included in the study. Within 20 days of implantation, 88.5% of leads had migrated (86.3% caudal and 2.2% cephalad). Mean migration distance for leads with caudal migration only was 12.34 ± 12.19 mm based on anteroposterior radiographs and 16.95 ± 15.68 mm on lateral radiographs. There was an association of greater caudal lead migration as patient body mass index increased (β-coefficient 0.07 [95% confidence interval 0.01–0.13], p = 0.031). Within the entire cohort, one patient (1.1%) required lead revision for loss of efficacy. ConclusionsIn the subacute postoperative period after SCS implant, the majority of SCS leads migrated caudally with an average of two lead contacts. Knowledge of this expected migration and risk factors can better inform implanting physicians intraoperatively when deciding final lead placement location. The finding of high likelihood of caudal lead migration in the subacute postoperative period brings the need for a well-designed prospective study to the forefront of our field. This will allow implanting providers to make well-informed decisions for intraoperative lead placement.

Osteochondral Fractures in Acute Patellar Dislocations in Adolescents: Midterm Results of Surgical Treatment.

Background:Osteochondral fractures (OCFs) are common injuries during acute patellar dislocation (APD), carrying a high risk of early joint deterioration if left untreated. The recommended approach is reduction and stable fixation; however, data on the results of such treatment are limited.Purpose:To evaluate midterm results of fixation of APD-related OCFs in adolescents and to identify predictive factors for poor outcomes.Study Design:Case series; Level of evidence, 4.Methods:This was a retrospective analysis of adolescent patients who underwent internal fixation of APD-related OCFs between 2004 and 2015 at a single tertiary pediatric trauma center. The primary outcome variables included Knee injury and Osteoarthritis Outcome Score (KOOS), patient satisfaction (0-10 scale), and sports participation compared with preoperative level. Secondary outcome variables included relationship between final results and OCF location (patellofemoral vs tibiofemoral), surgical delay (>6 weeks), and patellar instability after OCF fixation. OCF healing was evaluated using magnetic resonance imaging (MRI).Results:Included were 40 patients (19 female, 21 male) with 42 OCFs (29 patellar OCFs, 13 lateral femoral condyle OCFs). The median patient age at surgery was 14.5 years (interquartile range [IQR], 13-15.5 years), and median follow-up was 76 months (IQR, 52.5-95 months). Recurrence of patellar instability occurred in 27.5% of patients. Median overall KOOS was 93.8 (IQR, 90.8-97.6); KOOS–Symptoms, 92.9 (IQR, 85.7-96.4); KOOS–Pain, 97.2 (IQR, 91.7-100); KOOS–Activities of Daily Living, 100 (IQR, 97.1-100); KOOS–Sports, 90 (IQR, 80-100); and KOOS–Quality of Life, 78.1 (IQR, 56.2-87.5). Median satisfaction score was 8 (IQR, 8-9), and 16 patients (40%) returned to sports participation at their preinjury level. MRI scans revealed a 100% rate of bone healing. Abnormalities exceeding the fracture area were evident on MRI scans in 86.5% of patients. Recurrence of patellar instability (even after surgical fixation) and unstable patella at final follow-up were independent predictors of worse results after OCF fixation.Conclusion:In the current study, reduction and internal fixation for APD-related OCF in adolescents yielded favorable midterm outcomes. Recurrence of dislocation and persistent patellar instability jeopardized clinical results.