Specific Component Research Articles

Maintenance Strategy of a Preheat Train of a Crude Oil Distillation Unit Based on Exergy and Exergoeconomic Analysis

Abstract Established or create new ones to plan the cleaning tasks of the heat exchangers. In this work, a maintenance strategy is developed for a preheating train under the Maintenance Centered on Energy Efficiency (MCEE) methodology, where it is sought to integrate the information of the principles of the second law of thermodynamics with economic variables to use parameters. The modification of the maintenance justification parameter (J) is proposed, adding two new maintenance indicators (W and X). Each one seeks to evaluate an essential criterion for the maintenance area: economic viability, technical feasibility, and benefits, toward the other exchangers in the network after cleaning a specific component. A criticality diagram and a criticality matrix are used. The heat exchangers are grouped into subassemblies, with the leading group consisting of the key heat exchangers (KHEX), the elements of which have a significant impact on the efficiency of the preheat train. For their part, the regions are composed of components whose performance is less considerable than that of the KHEX. In total, 34 maintenance activities will be carried out, distributed among the 25 interchanges of the network. The planning of a program of cleaning activities according to the maintenance strategy based on the methodology of the MCEE establishes a substantial scientific contribution due to the almost null existence of exergetic studies applied to the management of maintenance tasks and focused mainly on the preheating of trains.

Between psychopathy and deviant socialization: A close look at the mafia men

The Italian mafia organizations represent a subculture with values, beliefs and goals that are antithetical to and undermining of the predominant society. The conduct of individual members includes such extreme violence for material gain, it may at least superficially suggest a severe personality disorder. Since the first edition of the DSM and into the 21st century, various terms have been used, sometimes interchangeably, but over time inconsistently, to designate the mentality and practices of mafia members. Only recently has the psychology of mafia members become a focus of serious scientific study. Following broader national multicenter research, the present study aimed at investigating the possible differences in psychopathy between those mafia associates who had been convicted only of mafia association (Group A, bosses), and those who were also convicted of violent crimes (Group B, soldiers). The Psychopathy Checklist-Revised (PCL-R) was administered to n = 48 male inmates convicted of mafia association (Mage 45.0 years, SD 10.9, range 20–80 years); Group A consisted of n = 26 (54%) subjects, Group B n = 22 (46%). Most of the sample (73%) did not manifest psychopathy (PCL-R ≥ 25) nor Mann-Whitney U test disclosed significant differences in the total PCL-R scores between the study groups. We found significantly higher scores of PCR-R factor 1 (interpersonal / affective) in the members of the mafia association also convicted of violent crimes (PCL-R F1, group A: 5.8 ± 3.7; group B: 7.9 ± 3.5; p < 0.05), this difference appeared explainable on the basis of a higher component of affective psychopathy. These initial results add to the limited literature on mafia and psychopathy and seem to suggest the existence of a specific component of psychopathy in the subgroup of mafiosi with overtly violent conduct.

Modeling of dynamic recrystallization texture in hot extruded Mg

Because of the strong effect of texture on the properties of alloys, the evolution of texture during hot extrusion of Mg has been studied through experiments and simulations. For a better understanding of the texture evolution at high processing temperatures, the model based on viscoplastic formulation was extended to a cellular automaton procedure to consider the recrystallization mechanisms. Texture evolution was simulated for the basal, prismatic and pyramidal 2nd order slip systems. Twinning was not considered because no twins were observed in the microstructural investigation. In the experimental investigations, the samples were extruded to a strain of ε = 2.7 at different temperatures, namely 180 °C, 280 °C, and 380 °C. The microstructure, texture, and hardness were evaluated by optical and electron microscopy using EBSD, X-ray diffraction, and Vickers tests, respectively. The main textural components were identified for each deformation temperature. Based on the simulations, a mechanism for the formation of a specific component was proposed. It was found that the change in the main texture component depends not only on the critical resolved shear stress for a specific slip system but also on the recrystallization parameters. The vpsc model has been shown to predict only the deformation texture components because the temperature is accounted for in accordance with the critical resolved shear stress and rate sensitivity. These two parameters affect the slip system activity. The new model using the cellular automaton procedure, which covers recrystallization processes, produces textures that fall in line with the experimental results.

Invariant neural dynamics drive commands to control different movements.

It has been proposed that the nervous system has the capacity to generate a wide variety of movements because it reuses some invariant code. Previous work has identified that dynamics of neural populationactivity are similar during different movements, where dynamics refer to how the instantaneous spatialpattern of population activity changes in time. Here, we test whether invariant dynamics of neural populations are actually used to issue the commands that direct movement. Using a brain-machine interface (BMI) that transforms rhesus macaques' motor-cortex activity into commands for a neuroprosthetic cursor, we discovered that the same command is issued with different neural-activity patterns in different movements. However, these different patterns were predictable, as we found that the transitionsbetween activity patterns are governed by the same dynamics across movements. These invariant dynamics are low dimensional, and critically, they align with the BMI, so that they predict the specific component of neural activity that actually issues the next command. We introduce a model of optimal feedback control (OFC) that shows that invariant dynamics can help transform movement feedback into commands, reducing the input that the neural population needs to control movement. Altogether our results demonstrate that invariant dynamics drive commands to control a variety of movements and show how feedback can be integrated with invariant dynamics to issue generalizable commands.

Development of Innovative Competence Model and Its Testing in the Course “Techno-Startup”

Introduction. Innovative evolution of the country requires preparing students for innovative activity and developing their innovative competence. But there is still no clear understanding as to how to effectively form and measure it. This article offers a model of innovation competence in the area of techno-innovation, which is based on the analysis of existing summarized models of innovation competence and consists of cognitive and non-cognitive components, each of which already has diagnostic tools. The purpose of the article is to describe the results of testing the proposed model of innovation competence in the process of specially organized training, as well as to identify effective teaching methods and tools for assessing innovation competence in higher engineering education. Materials and Methods. The article describes a comprehensive toolkit for assessing the changing of each component of innovation competence in the area of techno-innovation. It was used to identify the teaching methods most effective for the developing innovative competence in the process of teaching future techno-innovators at university. A quasi-experimental plan of research was used with the participation of 521 HSE students, who during a semester learned a specially created training course “Techno-Startup”. 58 trackers participated in the data collection. The results were subjected to statistical analysis: mean values, standard deviation values were calculated, linear regression model was applied. Results. It is found that the proposed toolkit has reliability and validity. On average, statistically significant improvement of studentʼs innovative competence in the focused learning of the course “Techno-Startup” was recorded relative to the control group. However, in 11–13% of students, motivation and personal attitudes decreased. It has been revealed that individual methods of teaching donʼt significantly influence the development of innovative competence of students, and it is necessary to use different methods in combination, each of which influences a specific component of competence. In the process of studying, the components of competence develop differently: the most noticeable growth of knowledge and skills, while personal attitudes and qualities practically does not change. Discussion and Conclusion. The obtained results contribute to the development of ideas about innovation competence, which can be useful in creating training programs for engineers and entrepreneurs in the technological sphere. Practical value has recommendations on the construction and content of the course, in the scope of which innovation competence is purposefully forms on the example of the discipline “Techno-Startup”.

Plastic waste: assessment of the prosesses of its formation and management in the North-Western Black Sea Coast Regions

Plastic waste represents a specific component within the municipal solid waste structure because of the peculiarities of its formation, possibility of reuse and ecological consequences of environmental pollution. In particular, growing consumption of plastic is accompanied by a constant level of recycling (4-8%). This leads to accumulation of plastic waste in the environment. The article presents data on the content of plastic waste in the municipal solid waste of Ukrainian cities. According to the data the content of plastic waste within the municipal solid waste amounts to 10-12%. Plastic waste is mainly represented by polyethylene and polyethylene terephthalate (more than 60%). It was discovered that plastic recycling companies import almost a third of recycled materials from Europe, while almost 84% of plastic is still ends brought to landfills. The analysis of the situation with separate collection of the municipal solid waste in the North-Western Black Sea Coast Region (namely Odesa, Mykolaiv and Kherson Regions) indicates a low level of secondary raw materials extraction. It is also exacerbated by the fact that only 75% of the population receives services for centralized collection of the municipal solid waste. It is estimated that almost 160,000 tons of plastic waste were brought to the landfills of Odesa Region in 2019. This volume is equal to the workload of existing plastic processing enterprises of Ukraine. So, as exemplified by Odesa Region, the research aimed at assessing the resource potential of plastic waste by main categories and in terms of clustering of the region, in accordance with the Regional Waste Management Plan project. It also describes the environmental consequences of leaving waste plastic materials in the environment – contamination with microplastics and formation of persistent organic pollutants. Moreover, it indicates that the municipal plastic waste is a significant source for such substances formation during thermal and mechanical destruction processes taking place within a landfill's body or marine environment. The research analyzes the main reasons for a low level of plastic waste use in the region. One of them is a lack of conditions allowing the citizens to collect plastic waste separately from the rest of their waste.

On-Demand Transient Paper Substrate for Selective Disposability of Thin-Film Electronic Devices.

This study demonstrates a novel approach to creating a thin-film electronic device that offers selective or complete disposability only in on-demand conditions while maintaining stable operation reliability during everyday use. The approach involves a transient paper substrate, combined with phase change encapsulation and highly bendable planarization materials, achieved through a simple solution process. The substrate used in this study offers a smooth surface morphology that enables the creation of stable multilayers for thin-film electronic devices. It also exhibits superior waterproof properties, which allows the proof-of-concept organic light-emitting device to function even when submerged in water. Additionally, the substrate provides controlled surface roughness under repeated bending, demonstrating reliable folding stability for 1000 cycles at 10 mm of curvature. Furthermore, a specific component of the electronic device can be selectively made to malfunction through predetermined voltage input, and the entire device can be fully disposed of via Joule-heating-induced combustion.

Concept of NORTH in Artistic Worldview of Chukotka Poet Victor Keulkut

This research aims to model the concept of the North in Victor Keulkut’s artistic worldview as part of the conceptual sphere of Arctic discourse. The authors of the article analyzed the poems of this Chukotka author. The study of artistic concepts enables the identification of the influence of cultural context on the perception of creative individuals. The relevance of this study lies in its inclusion in the paradigm of cognitive-linguistic research. The concept under investigation belongs to the category of discourse-forming concepts. The continuous sampling method was used to select 540 lexical markers, which were then distributed into nine lexical-semantic thematic groups (LSTG): ‘Industry’ (187 markers), ‘Cold’ (103), ‘Fauna’ (77), ‘Landscape’ (42), ‘Climate’ (42), ‘Sea’ (32), ‘House’ (27), ‘Tundra’ (18), and ‘Flora’ (12). The distribution of markers in LSTG was based on criteria of semantic and thematic similarity. Based on the study, a model of the artistic concept of the North in Victor Keulkut’s poetry was constructed, with the core formed by the LSTG ‘Industry’ (187 markers), the near-nuclear zone containing LSTG ‘Cold’ (103 markers), and the close periphery containing LSTG ‘Fauna’, ‘Landscape’, and ‘Climate’, while the distant periphery was represented by LSTG ‘Sea’, ‘House’, and ‘Tundra’. In analyzing the structure of the concept of the North, a specific component unique to northern linguistic culture was identified, called ‘nordicity’, expressing the idea of northern identity.

Adhesiveness of the specific phages to yersiniae cells assessed by optical trapping

In recent years, there has been increasing interest in using bacteriophages in the complex therapy of some infectious diseases. Objectively, it is related to the spread of antibiotic resistance and a small number of side effects triggered by phages applied locally and parenterally. Yersiniae are no exception to this rule, but their interaction with virions has not been studied thoroughly. In three types of lytic Yersiniae bacteriophages are used for diagnostic purposes, which differ in specificity, virulence, and morphological features. We evaluated the interaction force between phages and bacteriae by optical trapping.&#x0D; Materials and methods. Live Yersinia pseudotuberculosis and Y. pestis cells with different LPS structure and preparations of three bacteriophages Pokrovskayas phage, dHerelles phage (also named as the pseudotuberculosis phage) and the phage L-413C were used. The Pokrovskayas phage is well studied and widely used in diagnostics, but the mechanism of its adsorption on Y. pestis and Y. pseudotuberculosis cells is not well-understood. The phage L-413C lyses plague bacteria, while dHerrels phage can lyse both pathogens. Virions were linked to the surface of aminated glass. Optically trapped microbial cells were approached to the glass surface and then retracted in the opposite direction. The amplitude of the leap was recalculated into force through calibration coefficients. The primary data were processed in the program R; statistical analysis was performed using Matlab 7.0 and Statistica 12&#x0D; Results and discussion. The analysis of histograms revealed the presence of a specific component in the Y. pseudotuberculosisdHerrells phage (Fmean = 7.463.52 pN) system, as well as in all pairs involving plague microbe. In the latter case, the interaction forces were comparable: 8.643.83 pN for dHerelles phage,11.034.22 pN for Pokrovskayas phage, and 10.424.79 pN for phage L-413C. The average detachment force from the substrate treated with bovine serum albumin (BSA) was comparable for both cell types. Our results convincingly prove an opportunity for using the optical trapping to estimate interaction force in other bacteriumphage systems.

Biological light-weight materials: The endoskeletons of cephalopod mollusks

Structural biological hard tissues fulfill diverse tasks: protection, defence, locomotion, structural support, reinforcement, buoyancy. The cephalopod mollusk Spirula spirula has a planspiral, endogastrically coiled, chambered, endoskeleton consisting of the main elements: shell-wall, septum, adapical-ridge, siphuncular-tube. The cephalopod mollusk Sepia officinalis has an oval, flattened, layered-cellular endoskeleton, formed of the main elements: dorsal-shield, wall/pillar, septum, siphuncular-zone. Both endoskeletons are light-weight buoyancy devices that enable transit through marine environments: vertical (S. spirula), horizontal (S. officinalis). Each skeletal element of the phragmocones has a specific morphology, component structure and organization. The conjunction of the different structural and compositional characteristics renders the evolved nature of the endoskeletons and facilitates for Spirula frequent migration from deep to shallow water and for Sepia coverage over large horizontal distances, without damage of the buoyancy device.Based on Electron-Backscatter-Diffraction (EBSD) measurements and TEM, FE-SEM, laser-confocal-microscopy imaging we highlight for each skeletal element of the endoskeleton its specific mineral/biopolymer hybrid nature and constituent arrangement. We demonstrate that a variety of crystal morphologies and biopolymer assemblies are needed for enabling the endoskeleton to act as a buoyancy device. We show that all organic components of the endoskeletons have the structure of cholesteric-liquid-crystals and indicate which feature of the skeletal element yields the necessary mechanical property to enable the endoskeleton to fulfill its function. We juxtapose structural, microstructural, texture characteristics and benefits of coiled and planar endoskeletons and discuss how morphometry tunes structural biomaterial function. Both mollusks use their endoskeleton for buoyancy regulation, live and move, however, in distinct marine environments.

The metabolomics approach used for halal authentication analysis of food and pharmaceutical products: a review

Motivated by economical profits, unethical producers may add or substitute halal components with non-halal ones, therefore some analytical techniques capable of detecting non-halal components is very urgent to be developed. Halal authentication analysis in the food and pharmaceutical sectors is intended to confirm that the products are free from non-halal components, especially pig derivatives (any substances derived from pig). Analysis of non-halal components in food and pharmaceutical products can be undertaken using three approaches namely specific component analysis by identifying specific marker, fingerprinting profile and metabolomics approach. The two later approaches typically need the use of some chemometrics techniques including pattern recognition and multivariate calibrations. Metabolomics is related to the science of investigating all metabolites with small molecules (&lt; 1500 kDa) in biological systems. Metabolomic studies either target or untarget the application of chemometric methods to extract valued information from metabolites. This review highlighted some analytical techniques, mainly spectroscopic and chromatographic methods to generate the fingerprinting and metabolomics profiles of non-halal components to be used as reliable halal authentication. The metabolomics approach in combination with chemometrics offered accurate and reliable methods for the authentication of halal products.

Future ocean conditions induce necrosis, microbial dysbiosis and nutrient cycling imbalance in the reef sponge Stylissa flabelliformis

Oceans are rapidly warming and acidifying in the context of climate change, threatening sensitive marine biota including coral reef sponges. Ocean warming (OW) and ocean acidification (OA) can impact host health and associated microbiome, but few studies have investigated these effects, which are generally studied in isolation, on a specific component of the holobiont. Here we present a comprehensive view of the consequences of simultaneous OW and OA for the tropical sponge Stylissa flabelliformis. We found no interactive effect on the host health or microbiome. Furthermore, OA (pH 7.6 versus pH 8.0) had no impact, while OW (31.5 °C versus 28.5 °C) caused tissue necrosis, as well as dysbiosis and shifts in microbial functions in healthy tissue of necrotic sponges. Major taxonomic shifts included a complete loss of archaea, reduced proportions of Gammaproteobacteria and elevated relative abundances of Alphaproteobacteria. OW weakened sponge-microbe interactions, with a reduced capacity for nutrient exchange and phagocytosis evasion, indicating lower representations of stable symbionts. The potential for microbially-driven nitrogen and sulphur cycling was reduced, as was amino acid metabolism. Crucially, the dysbiosis annihilated the potential for ammonia detoxification, possibly leading to accumulation of toxic ammonia, nutrient imbalance, and host tissue necrosis. Putative defence against reactive oxygen species was greater at 31.5 °C, perhaps as microorganisms capable of resisting temperature-driven oxidative stress were favoured. We conclude that healthy symbiosis in S. flabelliformis is unlikely to be disrupted by future OA but will be deeply impacted by temperatures predicted for 2100 under a “business-as-usual” carbon emission scenario.

A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning

Recently using machine learning (ML) based techniques to optimize the performance of modern database management systems (DBMSs) has attracted intensive interest from both industry and academia. With an objective to tune a specific component of a DBMS (e.g., index selection, knobs tuning), the ML-based tuning agents have shown to be able to find better configurations than experienced database administrators (DBAs). However, one critical yet challenging question remains unexplored -- how to make those ML-based tuning agents work collaboratively. Existing methods do not consider the dependencies among the multiple agents, and the model used by each agent only studies the effect of changing the configurations in a single component. To tune different components for DBMS, a coordinating mechanism is needed to make the multiple agents be cognizant of each other. Also, we need to decide how to allocate the limited tuning budget (e.g., time and resources) among the agents to maximize the performance. Such a decision is difficult to make since the distribution of the reward (i.e., performance improvement) corresponding to each agent is unknown and non-stationary. In this paper, we study the above question and present a unified coordinating framework to efficiently utilize existing ML-based agents. First, we propose a message propagation protocol that specifies the collaboration behaviors for agents and encapsulates the global tuning messages in each agent's model. Second, we combine Thompson Sampling, a well-studied reinforcement learning algorithm with a memory buffer so that our framework can allocate the tuning budget judiciously in a non-stationary environment. Our framework defines the interfaces adapted to a broad class of ML-based tuning agents, yet simple enough for integration with existing implementations and future extensions. Based on extensive evaluations, we show that this framework can effectively utilize different ML-based agents and find better configurations with 1.4~14.1x speedups on the workload execution time compared with baselines.

Multi‐component condition monitoring method for wind turbine gearbox based on adaptive noise reduction

AbstractWind turbine gearbox condition monitoring (C&amp;M) is a key technology to promote wind farm maintenance cost reduction and power generation improvement. Existing gearbox C&amp;M methods usually adopt the component‐by‐component modelling approach. Firstly, this approach is inefficient in modelling; secondly, due to the thermal conduction effect, abnormalities in one gearbox component usually affect other components, making it difficult to identify the source of faults. To solve these problems, a normal behaviour model (NBM) combining data adaptive noise reduction and an improved variational auto‐encoder (VAE) is proposed, which can monitor the operational condition of multiple components of one gearbox simultaneously and takes into account the correlation between components when warning of the specific abnormal component. As verified by practical cases, the method balances the modelling accuracy and efficiency of the multi‐component NBM and achieves effective early warning and accurate localization of gearbox abnormalities. The proposed model has lower false alarm and missed alarm rates compared to other single‐component and multi‐component NBMs.

PERCY: A post-hoc explanation-based score for logic rule dissemination consistency assessment in sentiment classification

Disseminating and incorporating logic rules into deep neural networks has been extensively explored for sentiment classification in recent years. In particular, most methods and algorithms proposed for this purpose rely on a specific component that aims to capture and model logic rules, followed by a sequence model to process the input sequence. While the authors of these methods claim that they effectively capture syntactic structures that affect sentiment classification, they only show improvement in accuracy to support their claims without further analysis. Focusing on various syntactic structures, particularly contrastive discourse relations such as the A-but-B structure, we introduce the PERCY score, a novel Post-hoc Explanation-based Rule ConsistencY Score to analyze and study the ability of several of these methods to identify these structures in a given sentence, and to make their classification decisions based on the appropriate conjunct. Specifically, we explore the use of model-agnostic post-hoc explanation frameworks to explain the predictions of any classifier in an interpretable and faithful manner. These model explainability frameworks provide feature attribution scores to estimate each word’s impact on the final classification decision. Then, they are combined to check whether the model has based its decision on the right conjunct. Our experiments show that (a) accuracy – or any other performance metric – can be misleading in assessing the ability of logic rule dissemination methods to base their decisions on the right conjunct, (b) not all analyzed methods effectively capture syntactic structures, (c) often, the underlying sequence model is what captures the structure, and (d) for the best method, less than 25% of the test examples are classified based on the appropriate conjunct, indicating that a lot of research needs to be done on this topic. Finally, we experimentally demonstrate that the PERCY scores calculated are robust and stable w.r.t. the feature-attribution frameworks used.

A Survey on EEG Data Analysis Software

Electroencephalography (EEG) is a mechanism to understand the brain’s functioning by analyzing brain electrical signals. More recently, it has been more commonly used in studies that are focused on the causation and effect of dementia. More tools are now available to gather EEG data. This brings about the challenge of understanding brain signals, which involves signal processing. Professionals with an electrical engineering background are very comfortable analyzing EEG data. Still, scientists in computer science and related fields need a source that can identify all the tools available and the process of analyzing the data. This paper deals specifically with the existing EEG data analysis tools and the processes involved in analyzing the EEG data using these tools. Furthermore, the paper goes in-depth into identifying the tools and the mechanisms of data processing techniques. In addition, it lists a set of definitions required for a better understanding of EEG data analysis, which can be challenging. The purpose of this paper is to serve as a reference for not only scientists that are new to EEG data analysis but also seasoned scientists that are looking for a specific data component in EEG and can go straight to the section of the paper that deals with the tool that they are using.

Towards a Theory of Morphology as Syntax

Abstract Phenomena traditionally thought of as morphological can be accounted for in terms of syntactic operations and principles, hence bringing forth questions that traditional morphology fails to ask (for instance, concerning the licensing of empty morphemes). The language faculty contains no specific morphological component, nor any post-syntactic morphological operations.

Integrating ATM and air transport into multimodal transport system for Door-to-Door travel: the X-TEAM D2D project proposed approach

The project X-TEAM D2D (Extended ATM for Door-to-Door Travel) has been funded by SESAR JU in 2020 and completed its activities in 2022, pursuing and accomplishing the definition, development and initial assessment of a Concept of Operations (ConOps) for the seamless integration of ATM and air transport into an overall intermodal network, including other available transportation means (surface, water), to support the door-to-door connectivity, in up to 4 hours, between any location in Europe. The project addressed the ATM and air transport, including Urban Air Mobility (UAM), integration in the overall transport network serving urban and extended urban (up to regional level) mobility, specifically identifying and considering the transportation and passengers service scenarios expected for the near, medium and long-term future, i.e. for the project baseline (2025), intermediate (2035) and final (2050) time horizons. In this paper, the main outcomes from the project activities are summarized, with particular emphasis on the studies about the definition of future scenarios and use cases for the integration of the vertical transport with the surface transport towards integrated intermodal transport system and about identification of the barriers towards this goal. In addition, an outline is provided on the specific ConOps for the integration of ATM in intermodal transport infrastructure (i.e. the part of the overall ConOps devoted to integration of different transportation means) and on the specific ConOps for the integration of ATM in intermodal service to passengers (i.e. the specific component of the ConOps devoted to design of a unique service to passengers). Finally, the main outcomes are summarized from the validation of the proposed ConOps through dedicated simulations.

A Cluster Randomized Controlled Trial of a Multicomponent Positive Psychological Intervention: The Potential Mechanism of Altruism

Purpose: Although multicomponent positive psychological interventions (MPPIs) effectively improve well-being, it is crucial to examine which intervention component plays a critical role. Method: This cluster randomized controlled trial assigned 221 immigrants from mainland China to Hong Kong to either an MPPI arm ( n = 116, 11 clusters) or an MPPI + Information arm ( n = 105, 11 clusters). Both arms aimed to enhance three intervention outcomes: resilience, happiness, and mental health. The MPPI part in the two arms included four components: self-efficacy, positive thinking, altruism, and goal setting. The information part provided information about Hong Kong. Results: Both arms effectively improved the four intervention components and three intervention outcomes. MPPI + Information increased the immigrants’ knowledge of Hong Kong. The network analysis showed that altruism had the greatest strength in the network. Conclusions: Future studies should focus on the specific intervention component of altruism to understand how the MPPI works.

Inactivation of Minar2 in mice hyperactivates mTOR signaling and results in obesity

ObjectiveObesity is a complex disorder and is linked to chronic diseases such as type 2 diabetes. Major intrinsically disordered NOTCH2-associated receptor2 (MINAR2) is an understudied protein with an unknown role in obesity and metabolism. The purpose of this study was to determine the impact of Minar2 on adipose tissues and obesity. MethodWe generated Minar2 knockout (KO) mice and used various molecular, proteomic, biochemical, histopathology, and cell culture studies to determine the pathophysiological role of Minar2 in adipocytes. ResultsWe demonstrated that the inactivation of Minar2 results in increased body fat with hypertrophic adipocytes. Minar2 KO mice on a high-fat diet develop obesity and impaired glucose tolerance and metabolism. Mechanistically, Minar2 interacts with Raptor, a specific and essential component of mammalian TOR complex 1 (mTORC1) and inhibits mTOR activation. mTOR is hyperactivated in the adipocytes deficient for Minar2 and over-expression of Minar2 in HEK-293 cells inhibited mTOR activation and phosphorylation of mTORC1 substrates, including S6 kinase, and 4E-BP1. ConclusionOur findings identified Minar2 as a novel physiological negative regulator of mTORC1 with a key role in obesity and metabolic disorders. Impaired expression or activation of MINAR2 could lead to obesity and obesity-associated diseases.