Difficulties In Maintenance Research Articles

Data Driven and Fuzzy Synthetic Evaluation Based Submarine Cable Health State Assessment

—Health state assessment is of great importance to ensure the safe and stable operation of submarine cables. Submarine cables have composite structural characteristics and work in complex and influential environments, which hinders manual inspection, arouses difficulties in maintenance, and causes challenges on health state assessment. To this end, a data driven and fuzzy synthetic evaluation based submarine cable health state assessment method is proposed in this paper. Firstly, following the technical guidelines of submarine cable health state assessment, dynamic submarine cable online monitoring data and static data including periodic preventive test and operation inspection results are integrated to build a three-layer index system. In addition, long and short-term memory (LSTM) neural network based ultra-short-term prediction models are built to obtain the predictions of online monitoring indices. On this basis, together with the static data, a fuzzy synthetic evaluation method is used to establish a two-stage state evaluation process to obtain the multi-period health states of submarine cables. The effectiveness of the proposed method is verified with an actual submarine cable from an offshore platform in an oilfield of China National Offshore Oil Corporation (CNOOC).

Pushing the Boundaries of Solar Panel Inspection: Elevated Defect Detection with YOLOv7-GX Technology

During the maintenance and management of solar photovoltaic (PV) panels, how to efficiently solve the maintenance difficulties becomes a key challenge that restricts their performance and service life. Aiming at the multi-defect-recognition challenge in PV-panel image analysis, this study innovatively proposes a new algorithm for the defect detection of PV panels incorporating YOLOv7-GX technology. The algorithm first constructs an innovative GhostSlimFPN network architecture by introducing GSConv and depth-wise separable convolution technologies, optimizing the traditional neck network structure. Then, a customized 1 × 1 convolutional module incorporating the GAM (Global Attention Mechanism) attention mechanism is designed in this paper to improve the ELAN structure, aiming to enhance the network’s perception and representation capabilities while controlling the network complexity. In addition, the XIOU loss function is introduced in the study to replace the traditional CIOU loss function, which effectively improves the robustness and convergence efficiency of the model. In the training stage, the sample imbalance problem is effectively solved by implementing differentiated weight allocations for different images and categories, which promotes the balance of the training process. The experimental data show that the optimized model achieves 94.8% in the highest mAP value, which is 6.4% higher than the original YOLOv7 network, significantly better than other existing models, and provides solid theoretical and technical support for further research and application in the field of PV-panel defect detection.

Therapy program assisted with therapy dogs for children with Autism Spectrum Disorder (ASD)

IntroductionAutism spectrum disorders (ASD) is a neurodevelopmental disorder with an estimated lifetime prevalence of at least 1%. Some studies suggest that approximately 60% of children with ASD show emotional dysregulation and 44-86% sleeping disorders.Studies suggest that cognitive behavioral therapy and animal-assisted therapy AAT can be an intervention strategy to promote emotional and behavioral dysregulation and sleep disturbances.ObjectivesThe purpose of this study was to investigate the effect of a therapy program assisted with dogs (AAT) together with cognitive behavioral therapy (CBT) on behavioral and emotional regulation and sleep disorders in children diagnosed with ASD.MethodsThe sample was composed of 24 children between 7 and 10 years old diagnosed with ASD randomized into two groups (CGT group (control group) and AAT + CBT group (experimental group). Inclusion criteria: communication level of simple sentences, mild-moderate difficulties in behavioral and emotional regulation and sleep disturbances. Exclusion criteria: intellectual disability, children with specific dogs phobia. Assessment included ADOS-2, WISC-V, CGAS. dysregulation profile of Achenbach scale and Sleep Disturbance Scale for Children-Bruni. A program of 12 sessions (weekly one-hour sessions) focusing emotional and behavioral regulation and sleep disturbance was designed (Behavior Emotional Sleep Treatment Program. A pre-post evaluation was performed.ResultsParticipants were 20 boys and 2 girls (2 participants dropped out), with a mean age of 9. Regarding the socio-demographic and clinical characteristics, no significant differences has been observed between both groups in the global functioning measured with the Children’s Global Assessment scale (CGAS) (p=0.832), nor in the cognitive capacity (QI ) neither in reference to the associated comorbidities (p=0.103) nor in the variable prescription pharmacological treatment (p= 0.142). In emotional self-regulation, a significant improvement in emotional regulation difficulties was observed after treatment in both groups (experimental group: p=0.014; control group: p=0.012). However, the comparison between the pre-post intervention results between groups, regarding the emotional regulation variable, a greater improvement is observed in the experimental group (p=0.013). Significant improvements were also observed in sleep disorders (Bruni scale total score and in the sleep conciliation and maintenance difficulties scale) in both groups.ConclusionsTo conclude, although this is a pilot study with a small sample size and further research is needed, results suggest that a therapy program assisted with therapy dogs and CBT have positive effects on emotional dysregulation and sleep disturbances in children with ASD and offers a possible intervention strategy.Disclosure of InterestNone Declared

Vibration anomaly detection of wind turbine based on temporal convolutional network and support vector data description

Due to the complex working conditions and harsh environment, wind turbines often encounter abnormalities, resulting in great operation and maintenance difficulties. As nacelle vibration signals reveal the structure's dynamic characteristics and the interaction between components, vibration anomaly detection has a strong potential. However, vibration anomaly detection is challenging due to the complex characteristics and non-stationarity of high dynamic nacelle vibration signals. To solve this problem, this paper proposed a semi-supervised vibration anomaly detection approach for wind turbines, combining deep learning and one-class classification. Firstly, a healthy behavior model (HBM) for predicting wind turbine nacelle vibration based on the temporal convolutional network (TCN) is developed. To use all available information, a Hilbert spectrum fusion technology (HSFT) was proposed to enhance model performance. Then, based on the support vector data description (SVDD) algorithm, we established a one-class classifier of vibration prediction residual and realized the vibration anomaly detection. The proposed approach can be trained on the healthy dataset to provide accurate detection of different abnormal types. The effectiveness of the proposed anomaly detection approach was verified on simulated and actual monitoring datasets.

Preliminary thermal performance characterization of a flexible separate heat pipe used for the tracking-type photovoltaic/thermal system

In the solar heating field, the separate heat pipe-based photovoltaic/thermal technology can improve the comprehensive utilization efficiency of solar energy and reduce the maintenance difficulty in long-term outdoor operation by preventing freezing and scaling problems. Its promotion and application are of great significance for reducing fossil energy consumption and carbon emissions, and thus have attracted much attention. However, the performance of conventional photovoltaic/thermal modules is limited by their frame shadow due to the insulation demand, which leaves plenty of room for overall efficiency gains. To solve this problem, a novel separate heat pipe-based photovoltaic/thermal system is proposed by introducing a dual-axis tracking method through a flexible separate heat pipe and side-altitude inclination. To preliminarily characterize the thermal performance of the flexible separate heat pipe in dual-axis tracking conditions, an indoor experimental platform of the flexible separate heat pipe using the solar collector and finned-tube heat exchanger in the water tank as the evaporator and condenser was set up. The effects of side inclination angle, altitude angle of the solar collector and solar irradiance on the thermal efficiency, mass flow rate, and thermal resistance of the system are investigated in detail. The experimental results show the system can generally maintain effective heat transfer in side inclination states, with thermal efficiency mostly ranging from 44.68% to 86.12%. The proposed flexible separate heat pipe is qualified for the dual-axis tracking of photovoltaic/thermal system and shows great potential in improving the utilization of solar energy.

Structural analysis and optimal design of a spherical thin-walled stainless steel water tank without reinforced tie ribs

A spherical thin-walled stainless steel water tank without reinforced tie ribs has been designed to address the issues of easy fracture and corrosion of the ribs, difficulty in maintenance and cleaning, and short service life exposed during the use of thin-walled stainless steel water tanks with reinforced tie ribs. Firstly, an analytical model of a flat steel thin-walled water tank without reinforced tie ribs was established and subjected to static analysis under water pressure. The deformation and stress distribution patterns of the side molded plate of the flat box were obtained. Secondly, a spherical non ribbed thin-walled stainless steel water tank structure was designed with circular cross-section under different box bulge parameters, and its mechanical response characteristics under water pressure load were analyzed. A strengthening scheme was designed for the bottom box molded plate. Once again, optimize the combination design of the box scheme and the reinforcement scheme, and analyze their static, thermodynamic, and thermal solid coupling performance. Finally, the Latin Hypercube Sampling method was used to generate experimental design samples, and a response surface approximation model of a spherical thin-walled stainless steel water tank without reinforced tie ribs was constructed. The wall thickness of the box molded plate, skeleton, and reinforcement were used as design variables, and the maximum deformation and maximum equivalent stress were used as constraints. The lightweight design was carried out with the goal of minimizing mass. The research results indicate that the design program and parameter selection method for spherical thin-walled stainless steel water tanks without reinforced tie ribs proposed in the article are efficient and feasible, and can provide technical reference and theoretical support for the layout and overall optimization design of non ribbed thin-walled stainless steel water tank structures.

Reliability of permanent downhole systems: Minimum sample and quality index

Permanent downhole monitoring systems are responsible for measuring pressure and temperature time series and enable uninterrupted reservoir characterization during the oil field production period, playing a key role in the oil and gas industry. Located in hostile pressure and temperature environments (i) close to the reservoir, in the case of the PDG (Permanent Downhole Gauge) sensor, and (ii) at the wellhead, in the case of the TPT (Pressure and Temperature Transducer) and PT (Pressure Transducer), its data are transmitted from the subsea environment to the Floating Production Storage and Offloading (FPSO), where the Master Control System (MCS) provides the information in engineering format. This information fulfills its function in the FPSO plant and finally is stored in an onshore data historian. Such complexity, importance, and maintenance difficulty of this system make it necessary to control and manage its reliability. Therefore, the objective of this work is to increase the availability and maximize the useful life of the downhole permanent monitoring system through the reliability calculation, using the Weibull estimate with 2 parameters, and the application of an index quality of statistical inferences. The proposed method for estimating reliability uses a database containing information from permanent downhole monitoring systems of the PDG, TPT, and PT type, from January 1st, 2008 to January 9th, 2014, and considers only the failures that occur until the arrival of the data in the MCS. From the reliability results, it can be observed that stratifications of this database could generate samples with a smaller number of observations, thus inferring reliability even with a small number of samples. The deepening of this method results in the definition of the minimum sample that allows removing reliability inferences without statistical significance and a quality index that allows classifying the reliability estimates of stratified sets of the largest sample of a database. It is worth mentioning here that both methodologies developed in this work are inserted in a well monitoring system that intends to contribute to increasing the availability of pressure and temperature data for the management of well operations.

Prevalence and severity of design anti-patterns in open source programs—A large-scale study

Context:Design anti-patterns can be symptoms of problems that lead to long-term maintenance difficulty. How should development teams prioritize their treatment? Which ones are more severe and deserve more attention? Does the impact of anti-patterns and general maintenance efforts differ with different programming languages? Objective:In this study, we assess the prevalence and severity of anti-patterns in different programming languages and the impact of dynamic typing in Python, as well as the impact scopes of prevalent anti-patterns that manifest the violation of design principles. Method:We conducted a large-scale study of anti-patterns using 1717 open-source projects written in Java, C/C++, and Python. For the 288 Python projects, we extracted both explicit and dynamic dependencies and compared how the detected anti-patterns and maintenance costs changed. Finally, we removed anti-patterns involving five or fewer files to assess the impact of trivial anti-patterns. Results:The results reveal that 99.55% of these projects contain anti-patterns. Modularity Violation – frequent co-changes among seemingly unrelated files – is most prevalent (detected in 83.54% of all projects) and costly (incurred 61.55% of maintenance effort on average). Unstable Interface and Crossing, caused by influential but unstable files, although not as prevalent, tend to incur severe maintenance costs. Duck typing in Python incurs more anti-patterns, and the churn spent on Python files multiplies that of C/C++ and Java files. Several prevalent anti-patterns have a large portion of trivial instances, meaning that these common symptoms are usually not harmful. Conclusion:Implicit and visible dependencies are the most expensive to maintain, and dynamic typing in Python exacerbates the issue. Influential but unstable files need to be monitored and rectified early to prevent the accumulation of high maintenance costs. The violations of design principles are widespread, but many are not high-maintenance.

University campus network planning and design based on GPON technology

With the continuous development of Internet applications, in order to meet the increasing demands of teachers and students for the campus network in teaching, scientific research, office work and daily life, it is necessary to build a network environment that can meet the needs of smart campuses and future new applications. This paper makes an in-depth analysis of the current situation of campus networks, uses Gigabit Passive Optical Network (GPON) technology to upgrade and transform the existing network, reduces the cost of switching equipment and maintenance difficulty, improves the network transmission rate, increases the upper limit of campus network user access, and effectively solves the problem of separation between wired and wireless networks.

Relationship experiences of transgender and non-binary adults: exploring dating goals, relationship structures, minority stress, sexual fetishization, and relationship victimization

Objective Here we investigate the relationship experiences of TNB individuals, with a particular focus on (1) relationship status and structure; (2) dating motivations and dating app use; (3) minority stress in relational contexts, including rates and experiences of fetishization, and minority stress-related difficulties in relationship formation and maintenance; (4) rates of relationship violence, victimization, and online harassment; and (5) relationship outcomes, namely sexual and relationship satisfaction. Method 316 TNB adults (M age = 26.84 years, SD = 7.47) completed a survey to assess their relationship experiences. Results Just over half the sample was in a romantic relationship; 68% were monogamous and 32% were consensually non-monogamous (CNM). Almost 75% of partnered individuals were satisfied in their relationship, and neither sexual nor relationship satisfaction differed by gender or relationship structure (monogamous vs. CNM). The highest rated motivation for dating was to find a love relationship, and the lowest rated motivation was for casual sex. Almost 70% reported difficulties finding a partner because of their gender identity or expression, and 63% reported having experienced fetishization. Compared with men and non-binary individuals, rates of fetishization were highest for women. Finally, high rates of online and in-person victimization were found, including verbal abuse (52%), sexual coercion (44%) and physical violence (34%). Conclusion Results provide new evidence about the relationship experiences of TNB adults. Results suggest that many TNB individuals form and maintain satisfying relationships, but also face significant minority stress-related challenges in relational contexts. More research into relationship interventions to better support TNB individuals is warranted.

Common Childhood Sleep Problems and Disorders.

Sleep insufficiency and disturbances affect the physical, cognitive, and emotional well-being of children. To perform a narrative review on common sleep problems and disorders encountered in primary care for children and adolescents. A search of English literature in the Pubmed and Google Scholar databases published from 1 January 2000 till 31 October 2021 was conducted with the keywords "sleep problem" or "sleep disorder" and "child" or "adolescent". Findings in the relevant articles and cross-references were compiled. Sleep duration and habits of children vary widely across countries with different cultural backgrounds. There is robust evidence to support the promotion of positive bedtime routines and sleep hygiene as prevention and management of sleep problems. 15-70% of parents reported their children having sleep problems or disturbances. Common sleep complaints include difficulty in initiation or maintenance of sleep, abnormal behaviors or movements, snoring or abnormal breathing, and excessive daytime sleepiness. Comprehensive sleep history and a sleep diary are the first steps for evaluation. Home video and actigraphy may be used as preliminary tools to confirm the history. Referrals to a sleep specialist for polysomnography and other tests are needed, if suspecting specific sleep disorders, such as obstructive sleep apnea and narcolepsy, needs timely intervention. Common sleep disorders in different age groups encountered in primary care are reviewed with clinical features, indications for evaluation, and treatment options summarized. Screening for sleep problems shall be an integral part of each child's health care visit. It is important to evaluate the impact of common sleep problems and identify specific sleep disorders for early intervention to prevent long-term adverse outcomes.

Associations between adverse childhood experiences and history of weight cycling.

Adverse childhood experiences (ACEs) predict obesity onset; however, the relationship between ACEs and history of weight cycling has not been adequately explored. This gap is problematic given the difficulty in weight loss maintenance and the impact of ACEs on obesity development, chronicity, and associated weight stigma. The objective of this study was to examine associations between self-reported history of ACEs and weight cycling in a sample of weight loss treatment-seeking adults with overweight/obesity. The number of participants in the analyzed sample was 78, mostly white educated adult women (80% female, 81% Caucasian, 75%≥bachelor's degree) with excess adiposity enrolled in the Cognitive and Self-regulatory Mechanisms of Obesity Study. ACEs were measured at baseline using the ACEs Scale. History of weight cycling was measured using the Weight and Lifestyle Inventory that documented weight loss(es) of 10 or more pounds. Higher ACE scores were associated with a greater likelihood of reporting a history of weight cycling. Participants with four or more ACEs had 8 times higher odds (OR=8.301, 95% CI=2.271-54.209, p=0.027) of reporting weight cycling compared with participants with no ACEs. The association of weight cycling for those who endorsed one to three ACEs was not significant (OR=2.3, 95% CI=0.771-6.857, p=0.135) in this sample. The role of ACEs in health may be related to associations with weight cycling. Results indicated that those who reported four or more ACEs had significantly higher odds of reporting weight cycling compared with those with no ACEs. Further research is needed to further explore how ACEs predict the likelihood of weight cycling, which may be prognostic for sustained weight loss treatment response and weight stigma impacts.

Efficient Multi-Sound Source Localization Algorithm for Transformer Faults Based on Polyphase Filters.

Power transformers play a critical role in power systems, and the early detection of their faults and defects, accounting for over 30%, can be achieved through abnormal sound analysis. Sound source localization based on microphone arrays has proven effective in focusing on the troubleshooting scope, preventing potential severe hazards caused by delays in fault removal, and significantly reducing operational and maintenance difficulties and costs. However, existing microphone array-based sound source localization algorithms face challenges in maintaining both accuracy and simplicity and especially suffer from a sharp decrease in performance when dealing with multiple sound sources. This paper presents a multi-sound source localization algorithm for transformer faults based on polyphase filters, integrating the sum-difference monopulse angle measurement technique into the microphone array. Firstly, the signals received from the transformers are divided into multiple subbands using polyphase filters, allowing for multi-source separation and reducing the sampling rate of each subband. Next, the time-domain signals in subbands subject to noise suppression are processed into sum and difference beams. The resulting beam outputs are transformed into frequency-domain signals using the Fast Fourier Transform (FFT), effectively enhancing the signal-to-noise ratio (SNR) for separate sound sources. Finally, each subband undergoes sum-difference monopulse angle measurement in the frequency domain to achieve the high-precision localization of specific faults. The proposed algorithm has been demonstrated to be effective in achieving higher localization accuracy and reducing computational complexity in the presence of actual amplitude-phase errors in microphone arrays. These advantages can facilitate its practical applications. By enabling early targeting of fault sources when abnormalities occur, this algorithm provides valuable assistance to operation and maintenance personnel, thereby enhancing the maintenance efficiency of transformers.

A pilot time-in-bed restriction intervention behaviorally enhances slow-wave activity in older adults

IntroductionIdentifying intervention methods that target sleep characteristics involved in memory processing is a priority for the field of cognitive aging. Older adults with greater sleep efficiency and non-rapid eye movement slow-wave activity (SWA) (0.5–4 Hz electroencephalographic activity) tend to exhibit better memory and cognitive abilities. Paradoxically, long total sleep times are consistently associated with poorer cognition in older adults. Thus, maximizing sleep efficiency and SWA may be a priority relative to increasing mere total sleep time. As clinical behavioral sleep treatments do not consistently enhance SWA, and propensity for SWA increases with time spent awake, we examined with a proof-of concept pilot intervention whether a greater dose of time-in-bed (TiB) restriction (75% of habitual TiB) would increase both sleep efficiency and SWA in older adults with difficulties staying asleep without impairing memory performance.MethodsParticipants were adults ages 55–80 with diary-reported sleep efficiency < 90% and wake after sleep onset (WASO) >20 min. Sleep diary, actigraphy, polysomnography (PSG), and paired associate memory acquisition and retention were assessed before and after a week-long TiB restriction intervention (n = 30). TiB was restricted to 75% of diary-reported habitual TiB. A comparison group of n = 5 participants repeated assessments while following their usual sleep schedule to obtain preliminary estimates of effect sizes associated with repeated testing.ResultsSubjective and objective sleep measures robustly improved in the TiB restriction group for sleep quality, sleep depth, sleep efficiency and WASO, at the expense of TiB and time spent in N1 and N2 sleep. As hypothesized, SWA increased robustly with TiB restriction across the 0.5–4 Hz range, as well as subjective sleep depth, subjective and objective WASO. Despite increases in sleepiness ratings, no impairments were found in memory acquisition or retention.ConclusionA TiB restriction dose equivalent to 75% of habitual TiB robustly increased sleep continuity and SWA in older adults with sleep maintenance difficulties, without impairing memory performance. These findings may inform long-term behavioral SWA enhancement interventions aimed at improving memory performance and risk for cognitive impairments.

Fault Diagnosis of Airborne Electronic Equipment Based on Dynamic Bayesian Networks

With the rapid development of the aerospace industry, the structure of airborne electronic equipment has become more complex, which to some extent increases the difficulty of fault detection and maintenance of airborne electronic equipment. Traditional manual fault diagnosis methods can no longer fully meet the diagnostic needs of airborne electronic equipment. Therefore, this chapter uses dynamic Bayesian network to diagnose the faults of airborne electronic equipment. The basic idea of using a dynamic Bayesian network-based fault diagnosis method for airborne electronic devices is to mine data based on historical fault data of airborne electronic devices, and obtain fault symptoms and training data of airborne electronic devices. For non-essential fault symptoms, rough set theory was introduced to reduce their attributes and obtain the simplest attribute set, thereby simplifying the network model.

A Comparative Study of Different Protocols for Isolation of Murine Neutrophils from Bone Marrow and Spleen.

Neutrophils are considered as the main player in innate immunity. In the last few years, it has been shown that they are involved in different physiological conditions and diseases. However, progress in the field of neutrophil biology is relatively slow due to existing difficulties in neutrophil isolation and maintenance in culture. Here we compare four protocols based on density-gradient and immunomagnetic methods for isolation of murine neutrophils from bone marrow and spleen. Neutrophil isolation was performed using Ficoll 1.077/1.119 g/mL density gradient, Ficoll 1.083/1.090/1.110 g/mL density gradient and immunomagnetic method of negative and positive selection. The different protocols were compared with respect to sample purity, cell viability, yield, and cost. The functionality of isolated neutrophils was checked by NETosis analysis and neutrophil oxidative burst test. Obtained data revealed that given purity/yield/viability/cost ratio the protocol based on cell centrifugation on Ficoll 1.077/1.119 g/mL density gradient is recommended for isolation of neutrophils from bone marrow, whereas immunomagnetic method of positive selection using Dynabeads is recommended for isolation of splenic neutrophils.

Localization of seismic waves with submarine fiber optics using polarization-only measurements

Monitoring seismic activity on the ocean floor is a critical yet challenging task, largely due to the difficulties of physical deployment and maintenance of sensors in these remote areas. Optical fiber sensing techniques are well-suited for this task, given the presence of existing transoceanic telecommunication cables. However, current techniques capable of interrogating the entire length of transoceanic fibers are either incompatible with conventional telecommunication lasers or are limited in their ability to identify the position of the seismic wave. In this work, we propose and demonstrate a method to measure and localize seismic waves in transoceanic cables using only conventional polarization optics, by launching pulses of changing polarization. We demonstrate our technique by measuring and localizing seismic waves from a magnitude Mw 6.0 earthquake (Guerrero, Mexico) using a submarine cable connecting Los Angeles, California and Valparaiso, Chile. Our approach introduces a cost-effective and practical solution that can potentially increase the density of geophysical measurements in hard-to-reach regions, improving disaster preparedness and response, with minimal additional demands on existing infrastructure.

The causes of obesity relapse after weight loss

The main problem of obesity treatment is the difficulty of long-term weight maintenance. From one point of view, it can easily be explained by patients' low compliance and absence of self-control. From another point of view, body weight is regulated not only by persons will, but also by multiple physiological mechanisms. Moreover, studies demonstrate that theattempts to reduce body weight stimulate the activation of adaptive biological process that block weight reduction.Despite the variety of obesity treatment methods, only few patients are able to achieve significant (at least 5-7%) weight loss and maintain the result. In most cases people return to the initial weight in about 3-5 years. Therefore it is relevant to study weight regain mechanisms in order to identify new effective obesity treatment strategies.The objective of this review is to summarize the information about the main issues of central, peripheral and behavioral pathogenic mechanisms which lead to disease relapse after obesity treatment and ideas for future strategies to resolve them.

Interpersonal Characteristics and Binge Eating among Patients Pursuing Bariatric Surgery.

Preoperative binge eating behavior has been associated with difficulties in weight loss maintenance among patients pursuing bariatric surgery. However, limited data exists on the relationship between interpersonal difficulties and binge eating. To identify interpersonal factors linked with binge eating among bariatric surgery candidates. One hundred and seventeen adult bariatric surgery candidates (BMI = 42.2 ± 5.2) from three different hospitals completed questionnaires on the day of their bariatric committee meeting for operation approval. Binge eating was assessed using the Questionnaire on Eating and Weight Patterns-5 (QEWP-5) as a dichotomous variable. Self-esteem was measured using the Rosenberg Self-Esteem Scale (RSES), and interpersonal characteristics were evaluated using the short version of the Inventory of Interpersonal Problems (IIP-32). Sociodemographic variables (age, gender, income, education) and BMI were considered as confounders. Approximately 25% of bariatric surgery candidates reported experiencing binge eating episodes within the previous three months. Participants with binge eating exhibited significantly lower self-esteem and more interpersonal difficulties, particularly in the domains of aggressiveness and dependence, compared to those without binge eating. Logistic regression analysis revealed that aggressiveness was a significant predictor of binge eating in this sample. This study is the first, to the best of our knowledge, to investigate the relationship between interpersonal difficulties and binge eating among bariatric surgery candidates. The findings highlight the significant contribution of aggressiveness to binge eating and emphasize the importance of clinicians assessing patients' interpersonal functioning, particularly with regard to aggressiveness, as a factor that may contribute to the maintenance and occurrence of binge eating behaviors.

Prospects for the application of battery energy storage systems in NPP auxiliary power supply systems

One of the characteristics of energy strategy, which currently implementing is atomic energy elaboration and NPP development with rising part of atomic generation in national energy system. Of course one of the most important property of atomic generation is safety (Chernobyl, Three Mile Island, Fukushima Daiichi accidents). To maintain the operation of security systems in conditions of loss of external power supply, autonomous power sources - diesel-generator sets are used, but their use is associated with a number of difficulties of operation and maintenance, and currently developing technologies allow to realize new processes of energy transformation. And on the other hand modern technologies are providing access to new energy saving technologies. In this article we will try to compare energy storage systems, which use different physical principles and try to review their advantages and particularities. Also we especially explore operational advantages of battery energy storage systems and their influence on atomic safety and maintenance cycles and also integrating to digital control system and more effective generation and flexibility during NPP operation with conclusion about new business for «Rosatom» company.