Incorrect Connections Research Articles

User behavior during functional testing of the ventilator: analysis of the use of the QUICKcheck and detection of misconnected ventilation tubes

While patient safety during general anesthesia has improved in recent years, incidents still occur in anesthesia, particularly in the area of airway management and ventilation. In addition to amandatory daily system test before using aventilator, aQUICK check is recommended by the German Society of Anesthesiology and Intensive Care Medicine (DGAI) before connecting apatient; however, misconnections of breathing tubes are still possible and not necessarily detected by the device self-test. The aim of the present study was to analyze user behavior at modern anesthesia workstations regarding the verification and functionality of the QUICK check. Amonocentric prospective recording of user behavior in handling the QUICKcheck was carried out as part of amedical simulation training course as well as aprospective, multicenter, explorative, anonymous survey of anesthesiology staff in various German hospitals. Out of 30 participating physicians 93.3% (n = 28) carried out aQUICK check immediately before connecting the simulation patient to the ventilator. Only 1 (96.6%) of the physicians did not recognize the incorrect connection of the ventilation tubes during their QUICK check. Of the participating physicians, 80% did not use the separate bag valve mask despite persistent ventilation problems on the ventilator. The online survey was answered by n = 187 participants, 64.7% of the participants stated that they always carry out the QUICK check, 31.5% sometimes and 3.7% never. The presence of aseparate bag valve mask is always checked by 66.3% of respondents, by 29.8% sometimes and by 3.8% never. Of the physicians, 32% believed that the integrated self-test always recognizes amisconnection of the ventilation tubes. The present study reveals aheterogeneous picture of the application and understanding of the QUICK check as recommended by the DGAI. The lack of understanding of astandardized implementation of the check can be seen as further evidence of the importance of interdisciplinary training with afocus on human factors, communication and cooperation as opposed to a mere procedural implementation of established tools.

P-255. Evaluation of automated disinfectant dispenser systems in 6 hospitals demonstrates a need for improved monitoring to ensure that correct disinfectant concentrations are delivered

Abstract Background Automated dispensers that dilute concentrated disinfectants with water are commonly used in healthcare facilities. However, most facilities do not perform routine monitoring to ensure that the dispensers are functioning correctly and being used as recommended by the manufacturer.Table 1.Concentrations of disinfectant measured in samples obtained from automated dispensers and from in-use buckets on environmental services carts in 6 hospitalsQA, quaternary ammonium disinfectant; PA, peracetic acid-based disinfectant.a. Expected concentrations, ∼1,300 parts per million (PPM) for PA and ∼800 PPM for QA; higher-than-expected concentration of peracetic acid, >1,800 ppm; b. Lower than expected concentration, 300-900 PPM for PA and 200-400 PPM for QA; cNo disinfectant detected, limit of detection (∼300 PPM for PA and ∼150 PPM for QA); d. Wrong product, the in-use product that was supposed to be PA or QA was a detergent intended for floors. Methods In 6 acute care hospitals in Northeast Ohio, we tested disinfectant concentrations and pH of products obtained from automated dispensers and in-use containers from environmental services (EVS) personnel carts. The disinfectants included quaternary ammonium (800 parts per million [ppm]; pH 8) and peracetic acid-based products (∼1300 ppm; pH 3). Results All 6 hospitals had 1 or more malfunctioning dispensers (Table 1). Of 57 systems assessed, 14 (25%) dispensed products with lower-than-expected concentrations, including 8 (14%) with no detectable disinfectant (i.e., water). Nine of 62 (15%) in-use products had no detectable disinfectant, and 4 (7%) were the wrong product (i.e., a detergent for floors used for high-touch surfaces). Reasons for dispenser malfunction included incorrect connection of the concentrate container, dysfunction of a low-product indicator, and failure to change the concentrate container when indicated. pH measurements identified disinfectants with lower-than-expected concentrations, and an intervention that included monitoring was effective in ensuring that the dispensers were operating correctly. Conclusion Improved monitoring of automated disinfectant dispenser systems in healthcare facilities is needed to ensure patient safety. pH measurements could provide a simple means to ensure that dispensers are functioning correctly. Disclosures Elie Saade, MD, MPH, FIDSA, Janssen Global Services: Advisor/Consultant|Janssen Global Services: Advisor/Consultant|Janssen Research and Development: Advisor/Consultant|Janssen Research and Development: Advisor/Consultant Curtis Donskey, MD, Clorox: Grant/Research Support|Pfizer: Grant/Research Support

Development and Application of A Wearable Technology Product That Detects and Informs The Presence of Electrical Energy

Electrical energy has both positive and negative effects nowadays, with the potential to cause property and human loss. Technical professionals working at electrical energy generation, distribution, and utilization points may die due to carelessness or neglect. Although there are protection elements (fuses, residual current protection relays, etc.) in electrical panels that interrupt the flow of electrical energy in the event of a shock, there may be working areas where energy cannot be cut off due to incorrect electrical connections caused by unauthorized people interacting with the panel. Existing protective components may be insufficient. The experiments include both wired protection elements and wireless detection elements. However, they need to be enhanced because they have limited detection distances. Furthermore, using an ergonomic design can improve operability. New protection and warning features must be designed using developing technology. To prevent employees from being shocked by being exposed to electrical energy in the workplace, AC voltage can be detected without contact using this study, which includes the design and test results of a wearable technology product that warns when electricity is present. An electrical circuit that technical staff can wear on their finger detects voltage without contact and displays the existence of energy with a red LED. It was discovered that the test circuit detects 230V AC electrical energy up to 8 cm away and warns with light.

Detecting and Classifying Problematic Behavior: A Method Based on Multi-Dimensional Software Modeling Behavioral Characteristics

Understanding software modelers’ difficulties and evaluating their performance is crucial to Model-Driven Engineering (MDE) education. The software modeling process contains fine-grained information about the modelers’ analysis and thought processes. However, existing research primarily focuses on identifying obvious issues in the software modeling process, such as incorrect connections or misunderstandings, but neglects the behavioral patterns that can reveal underlying, unaddressed modeling problems. This oversight fails to identify deeper problems that do not manifest as obvious issues but still represent significant potential problems in the software modeling process. Our research concentrates on detecting and classifying problematic modeling behaviors from software modeling process data, revealing the potential problems hidden in the process for MDE education. Specifically, we first construct problematic modeling behavior patterns from three dimensions, including anomalous time intervals, repetitions, and frequencies, to further identify characteristics and priorities relevant to problematic modeling behaviors. Then, we design rules with characteristics and priorities to detect and classify problematic modeling behaviors from problematic patterns. To evaluate the effectiveness of our proposal, we apply it to a data-flow diagram modeling platform. This platform can record modelers’ processes and has been practically used in software engineering courses for five years. We have conducted a case study with 12 participants. The macro F1 of detection and classification problematic modeling behaviors is 82.3%, which shows the effectiveness of our approach. Then, to evaluate the usefulness of our proposal for assisting modeling instructors in MDE education, we conducted another case study with 5 modeling instructors. The results show that our approach can help instructors uncover problems hidden in the software modeling process. The results of two case studies demonstrate that our approach effectively detects and classifies problematic modeling behaviors, enabling instructors to better adjust their instructional plans and improve MDE education.

Designing a recombinant coat protein to reduce tobacco mosaic virus infection in plants

The Tobacco Mosaic Virus (TMV) is a critical plant virus that can cause a significant drop in crop yield. To understand how recombinant coat-protein impacts the affinity and assembly of TMV’s subunits, research is being conducted to assess the effect of recombinant protein on virus resistance. To develop a recombinant coat-protein that can lower TMV infection rates in plants, a design strategy was employed that involves creating defective viral subunits leading to incorrect assembly. This method is similar to using defective puzzle pieces that form incorrect connections resulting in disrupted viral assembly, ultimately affecting the production of mature virus particles. The study investigated the effect of mutations on one side of the Tobacco mosaic virus coat-protein using molecular modeling and dynamics simulation techniques. The simulation showed that the recombinant subunit had lower flexibility (between 0.15 to 0.20 nm) compared to the other subunits (between 0.45 to 0.75 nm), which was attributed to the smaller loop area. The study suggests an effective recombinant coat-protein with the potential to prevent virus infection by disrupting the coat-protein assembly process. This approach can be used to design a plant vaccine against viruses. Developing a recombinant protein can also provide benefits to plants such as protection from pests and enhancement of growth and productivity.

Polyethylene glycol fusion repair of severed sciatic nerves accelerates recovery of nociceptive sensory perceptions in male and female rats of different strains.

JOURNAL/nrgr/04.03/01300535-202509000-00028/figure1/v/2024-11-05T132919Z/r/image-tiff Successful polyethylene glycol fusion (PEG-fusion) of severed axons following peripheral nerve injuries for PEG-fused axons has been reported to: (1) rapidly restore electrophysiological continuity; (2) prevent distal Wallerian Degeneration and maintain their myelin sheaths; (3) promote primarily motor, voluntary behavioral recoveries as assessed by the Sciatic Functional Index; and, (4) rapidly produce correct and incorrect connections in many possible combinations that produce rapid and extensive recovery of functional peripheral nervous system/central nervous system connections and reflex (e.g., toe twitch) or voluntary behaviors. The preceding companion paper describes sensory terminal field reorganization following PEG-fusion repair of sciatic nerve transections or ablations; however, sensory behavioral recovery has not been explicitly explored following PEG-fusion repair. In the current study, we confirmed the success of PEG-fusion surgeries according to criteria (1-3) above and more extensively investigated whether PEG-fusion enhanced mechanical nociceptive recovery following sciatic transection in male and female outbred Sprague-Dawley and inbred Lewis rats. Mechanical nociceptive responses were assessed by measuring withdrawal thresholds using von Frey filaments on the dorsal and midplantar regions of the hindpaws. Dorsal von Frey filament tests were a more reliable method than plantar von Frey filament tests to assess mechanical nociceptive sensitivity following sciatic nerve transections. Baseline withdrawal thresholds of the sciatic-mediated lateral dorsal region differed significantly across strain but not sex. Withdrawal thresholds did not change significantly from baseline in chronic Unoperated and Sham-operated rats. Following sciatic transection, all rats exhibited severe hyposensitivity to stimuli at the lateral dorsal region of the hindpaw ipsilateral to the injury. However, PEG-fused rats exhibited significantly earlier return to baseline withdrawal thresholds than Negative Control rats. Furthermore, PEG-fused rats with significantly improved Sciatic Functional Index scores at or after 4 weeks postoperatively exhibited yet-earlier von Frey filament recovery compared with those without Sciatic Functional Index recovery, suggesting a correlation between successful PEG-fusion and both motor-dominant and sensory-dominant behavioral recoveries. This correlation was independent of the sex or strain of the rat. Furthermore, our data showed that the acceleration of von Frey filament sensory recovery to baseline was solely due to the PEG-fused sciatic nerve and not saphenous nerve collateral outgrowths. No chronic hypersensitivity developed in any rat up to 12 weeks. All these data suggest that PEG-fusion repair of transection peripheral nerve injuries could have important clinical benefits.

Standard technical specifications for methacholine chloride (Methacholine) bronchial challenge test (2023)

Standard technical specifications for methacholine chloride (Methacholine) bronchial challenge test (2023)

Hardware Trojan Attacks on the Reconfigurable Interconnections of Field-Programmable Gate Array-Based Convolutional Neural Network Accelerators and a Physically Unclonable Function-Based Countermeasure Detection Technique.

Convolutional neural networks (CNNs) have demonstrated significant superiority in modern artificial intelligence (AI) applications. To accelerate the inference process of CNNs, reconfigurable CNN accelerators that support diverse networks are widely employed for AI systems. Given the ubiquitous deployment of these AI systems, there is a growing concern regarding the security of CNN accelerators and the potential attacks they may face, including hardware Trojans. This paper proposes a hardware Trojan designed to attack a crucial component of FPGA-based CNN accelerators: the reconfigurable interconnection network. Specifically, the hardware Trojan alters the data paths during activation, resulting in incorrect connections in the arithmetic circuit and consequently causing erroneous convolutional computations. To address this issue, the paper introduces a novel detection technique based on physically unclonable functions (PUFs) to safeguard the reconfigurable interconnection network against hardware Trojan attacks. Experimental results demonstrate that by incorporating a mere 0.27% hardware overhead to the accelerator, the proposed hardware Trojan can degrade the inference accuracy of popular neural network architectures, including LeNet, AlexNet, and VGG, by a significant range of 8.93% to 86.20%. The implemented arbiter-PUF circuit on a Xilinx Zynq XC7Z100 platform successfully detects the presence and location of hardware Trojans in a reconfigurable interconnection network. This research highlights the vulnerability of reconfigurable CNN accelerators to hardware Trojan attacks and proposes a promising detection technique to mitigate potential security risks. The findings underscore the importance of addressing hardware security concerns in the design and deployment of AI systems utilizing FPGA-based CNN accelerators.

ОЦЕНКА ВЕРОЯТНОСТИ НЕСАНКЦИОНИРОВАННОЙ ПОДАЧИ НАПРЯЖЕНИЯ В СЕЛЬСКИХ ЭЛЕКТРИЧЕСКИХ СЕТЯХ 0,4-10 КВ

One of the causes of electrical injuries in rural power grids of 0.4-10 kilovolts is the unauthorized power supply, which is caused by various causes: the fall of a wire from one power line to another (disconnected), incorrect connection of an electric generator in a private household, etc. At the same time, the occurrence of a power supply in the 0.4 kilovolt grid due to reverse transformation at the 10/0.4 kilovolt transformer substation leads to the appearance of a voltage in the 10 kilovolt grid and poses a danger of electric shock both in 0.4 and 10 kilovolt grid. However, it is not possible to identify the number of cases of unauthorized power supply based on statistics or other data due to the fact that this information is not recorded until the accident occurs. Therefore, the definition of cases of unauthorized voltage supply is actual. (Research Purpose) The research purpose is estimating the probability of unauthorized power supply in electrical grids of 0.4-10 kilovolts. (Materials and methods) Methods of expert survey and processing of its results were applied. 74 experts serving rural power grids of 0.4-10 kilovolts were interviewed, who were asked questions about actual cases of unauthorized power supply and the expectation of meeting with such cases. Based on the results of the survey, the specific probabilities of the unauthorized power supply per kilometer of the line were determined (Results and discussion) The actual number of cases of unauthorized power supply recorded by experts has been determined, which amounted to 91 cases over five years, and the specific value is 0.011 cases per kilometer of lines per year. The assessment was carried out taking into account the total length of the grid serviced by experts - 1704 kilometers. The specific value of the probability of unauthorized power supply was determined according to experts (0.0056 cases per kilometer of lines per year). (Conclusions) The number of cases of unauthorized power supply predicted by experts is lower than the actual one, which confirms the need for additional training of personnel of power grid organizations on this issue.

Smart Grid Outlier Detection Based on the Minorization-Maximization Algorithm.

Outliers can be generated in the power system due to aging system equipment, faulty sensors, incorrect line connections, etc. The existence of these outliers will pose a threat to the safe operation of the power system, reduce the quality of the data, affect the completeness and accuracy of the data, and thus affect the monitoring analysis and control of the power system. Therefore, timely identification and treatment of outliers are essential to ensure stable and reliable operation of the power system. In this paper, we consider the problem of detecting and localizing outliers in power systems. The paper proposes a Minorization-Maximization (MM) algorithm for outlier detection and localization and an estimation of unknown parameters of the Gaussian mixture model (GMM). To verify the performance of the method, we conduct simulation experiments by simulating different test scenarios in the IEEE 14-bus system. Numerical examples show that in the presence of outliers, the MM algorithm can detect outliers better than the traditional algorithm and can accurately locate outliers with a probability of more than 95%. Therefore, the algorithm provides an effective method for the handling of outliers in the power system, which helps to improve the monitoring analyzing and controlling ability of the power system and to ensure the stable and reliable operation of the power system.

Combination of Non-contact and Contact Measuring Methods for Analyzing Structural Conditions of Dry Transformers

Abstract The article describes the non-contact and contact analysis of 1-MVA dry power transformers with epoxy-resin insulation using an acoustic camera and frequency analyzer with automatic sweeping for low-middle frequency areas. Power transformers are most commonly used for construction component (core, windings, taps) analysis. The electrical, non-rotating machine generates electromagnetic and acoustic emissions that can be used to analyze dry transformers during their operation. Non-contact online diagnostic methods have many advantages over offline methods because it is not necessary to shut down the transformer, and also, the condition and behaviour of the machine are analyzed during its normal operation. The article presents the analysis and comparison of structural parts of the distribution dry transformers of the same type and power. The problem of insufficient or incorrect clamp-screw connection was identified using the SFRA (Sweep Frequency Response Analysis) method.

Onto-semiotic analysis of one teacher’s and university students’ mathematical connections when problem-solving about launching a projectile

An onto-semiotic analysis of the mathematical connections established by one in-service mathematics teachers and university students when solving a problem about launching a projectile using the derivative was carried out. Theoretically, this research was based on the articulation between the Extended Theory of Mathematical Connections and the Onto-semiotic Approach. The methodology was qualitative-descriptive where data was collected through interviews based on a task. Subsequently, following the joint analysis method of both theories, the mathematical activity of the participants when they solved the task was analyzed. The results show that, teacher and students established a system of connections of feature type, different representations, meanings, part-whole, procedural and implications in terms of practices, processes, objects, and semiotic functions that relate them. However, some students presented difficulties caused by some incorrect mathematical connection such as stating that the maximum height of the projectile is the time obtained with the critical number, errors in performing arithmetic calculations when evaluating the function, graphically representing the quadratic function as a straight line and use the general formula in an inappropriate way that prevents the procedural connection from being made.

Line Drawing Vectorization via Coarse‐to‐Fine Curve Network Optimization

AbstractVectorizing line drawings is a fundamental component of the workflow in various applications such as graphic design and computer animation. A practical vectorization tool is desired to produce high‐quality curves that are faithful to the original inputs and close to the connectivity of human drawings. The existing line vectorization approaches either suffer from low geometry accuracy or incorrect connectivity for noisy inputs or detailed complex drawings. We propose a novel line drawing vectorization framework based on coarse‐to‐fine curve network optimization. Our technique starts with an initial curve network generated by an existing tracing method. It then performs a global optimization which fits the curve network to image centrelines. Finally, our method performs a finer optimization in local junction regions to achieve better connectivity and curve geometry around junctions. We qualitatively and quantitatively evaluate our system on line drawings with varying image quality and shape complexity, and show that our technique outperforms existing works in terms of curve quality and computational time.

Evaluation and Solution Suggestions for Engineering and Workmanship Failures during Design and Installation of Solar Power Plants

Among the various renewable energy generation systems, the solar photovoltaic occupies a leading position today due to its simple structure. However, increasing the efficiency of solar photovoltaic systems is a highly researched topic. In this study, possible connection failures in maximum power inverters and other failures, which decrease the efficiency in solar power plants, are examined. Furthermore, the possible consequences of these losses and their effects on the performance of solar power plants are explained. Some missing-failure processes were identified and corrected in the field analysis of the solar power plant in Turkey. Detected missing failures include connection failures of solar inverters, incorrect network configuration of camera system, fixing lighting time settings. The inverter string connection failure made during the projecting and assembly phase was eliminated and the maximum output was determined as 584.25 kW after the DC string arrangement. An increase of approximately 10% was achieved in production. In the project and application phase, the connection details of the inverters should be drawn and given to the field application personnel as a full-fledged project. In this way, incorrect connections that are not shown in the project and made in the field are prevented. This ensures that the installed power plant operates more efficiently, and the budgetary payback period of the investments made is shortened.

Graph Neural Network Meets Sparse Representation: Graph Sparse Neural Networks via Exclusive Group Lasso.

Existing GNNs usually conduct the layer-wise message propagation via the 'full' aggregation of all neighborhood information which are usually sensitive to the structural noises existed in the graphs, such as incorrect or undesired redundant edge connections. To overcome this issue, we propose to exploit Sparse Representation (SR) theory into GNNs and propose Graph Sparse Neural Networks (GSNNs) which conduct sparse aggregation to select reliable neighbors for message aggregation. GSNNs problem contains discrete/sparse constraint which is difficult to be optimized. Thus, we then develop a tight continuous relaxation model Exclusive Group Lasso GNNs (EGLassoGNNs) for GSNNs. An effective algorithm is derived to optimize the proposed EGLassoGNNs model. Experimental results on several benchmark datasets demonstrate the better performance and robustness of the proposed EGLassoGNNs model.

Urban Building Mesh Polygonization Based on Plane-Guided Segmentation, Topology Correction and Corner Point Clump Optimization

The lightweight representation of 3D building models has played an increasingly important role in the comprehensive application of urban 3D models. Polygonization is a compact and lightweight representation for which a fundamental challenge is the fidelity of building models. In this paper, we propose an improved polyhedralization method for 3D building models based on guided plane segmentation, topology correction, and corner point clump optimization. Improvements due to our method arise from three aspects: (1) A plane-guided segmentation method is used to improve the simplicity and reliability of planar extraction. (2) Based on the structural characteristics of a building, incorrect topological connections of thin-plate planes are corrected, and the lamellar structure is recovered. (3) Optimization based on corner point clumps reduces redundant corner points and improves the realism of a polyhedral building model. We conducted detailed qualitative and quantitative analyses of building mesh models from multiple datasets, and the results show that our method obtains concise and reliable segmented planes by segmentation, obtains high-fidelity building polygonal models, and improves the structural perception of building polygonization.

Keypoint-driven line drawing vectorization via PolyVector flow

Line drawing vectorization is a daily task in graphic design, computer animation, and engineering, necessary to convert raster images to a set of curves for editing and geometry processing. Despite recent progress in the area, automatic vectorization tools often produce spurious branches or incorrect connectivity around curve junctions; or smooth out sharp corners. These issues detract from the use of such vectorization tools, both from an aesthetic viewpoint and for feasibility of downstream applications (e.g., automatic coloring or inbetweening). We address these problems by introducing a novel line drawing vectorization algorithm that splits the task into three components: (1) finding keypoints, i.e., curve endpoints, junctions, and sharp corners; (2) extracting drawing topology, i.e., finding connections between keypoints; and (3) computing the geometry of those connections. We compute the optimal geometry of the connecting curves via a novel geometric flow --- PolyVector Flow --- that aligns the curves to the drawing, disambiguating directions around Y-, X-, and T-junctions. We show that our system robustly infers both the geometry and topology of detailed complex drawings. We validate our system both quantitatively and qualitatively, demonstrating that our method visually outperforms previous work.

Student Behavior Recognition System for the Classroom Environment Based on Skeleton Pose Estimation and Person Detection.

Human action recognition has attracted considerable research attention in the field of computer vision, especially for classroom environments. However, most relevant studies have focused on one specific behavior of students. Therefore, this paper proposes a student behavior recognition system based on skeleton pose estimation and person detection. First, consecutive frames captured with a classroom camera were used as the input images of the proposed system. Then, skeleton data were collected using the OpenPose framework. An error correction scheme was proposed based on the pose estimation and person detection techniques to decrease incorrect connections in the skeleton data. The preprocessed skeleton data were subsequently used to eliminate several joints that had a weak effect on behavior classification. Second, feature extraction was performed to generate feature vectors that represent human postures. The adopted features included normalized joint locations, joint distances, and bone angles. Finally, behavior classification was conducted to recognize student behaviors. A deep neural network was constructed to classify actions, and the proposed system was able to identify the number of students in a classroom. Moreover, a system prototype was implemented to verify the feasibility of the proposed system. The experimental results indicated that the proposed scheme outperformed the skeleton-based scheme in complex situations. The proposed system had a 15.15% higher average precision and 12.15% higher average recall than the skeleton-based scheme did.

A New Method for Connecting the Radiation Sources of Lightning Discharge Extension Channels

AbstractThe connections of lightning radiation sources along channels are greatly affected by the radiation source density, and the channel length is geometrically scaled when neglecting repeated discharges in the same channel. Based on lightning mapping array (LMA) three‐dimensional radiation source location data of two lightning flashes, this study presents a radiation source connection method considering the source density and repeated discharges in channels that includes two steps: the connection of radiation sources and the connection of segments. After increasing the spatial connection threshold determined by the source density, the stability of the channel scale under different detection capabilities (source densities) is improved compared with that of the traditional fixed spatial threshold method. The channel growth rate of the low‐density case reaches 120.99%, which is close to the real situation, and the connection shape is consistent with the real situation. For repeated discharge paths, by limiting the time interval of the radiation source connection, the optimized threshold obtained in this paper can distinguish between discharges occurring in the same channel at different times. Compared with the geometric scale, the discharge scale is significantly larger (∼2.8 times the geometric scale in one case) and can better characterize both the lightning discharge process and the affected area. These comprehensive results show that the proposed method can reduce the number of incorrect connections, increase the channel length, and obtain a more realistic discharge scale.

PTEN Expression Regulates Gap Junction Connectivity in the Retina.

Manipulation of the phosphatase and tensin homolog (PTEN) pathway has been suggested as a therapeutic approach to treat or prevent vision loss due to retinal disease. In this study, we investigated the effects of deleting one copy of Pten in a well-characterized class of retinal ganglion cells called α-ganglion cells in the mouse retina. In Pten+/– retinas, α-ganglion cells did not exhibit major changes in their dendritic structure, although most cells developed a few, unusual loop-forming dendrites. By contrast, α-ganglion cells exhibited a significant decrease in heterologous and homologous gap junction mediated cell coupling with other retinal ganglion and amacrine cells. Additionally, the majority of OFF α-ganglion cells (12/18 cells) formed novel coupling to displaced amacrine cells. The number of connexin36 puncta, the predominant connexin that mediates gap junction communication at electrical synapses, was decreased by at least 50% on OFF α-ganglion cells. Reduced and incorrect gap junction connectivity of α-ganglion cells will affect their functional properties and alter visual image processing in the retina. The anomalous connectivity of retinal ganglion cells would potentially limit future therapeutic approaches involving manipulation of the Pten pathway for treating ganglion cell degeneration in diseases like glaucoma, traumatic brain injury, Parkinson’s, and Alzheimer’s diseases.