Functional Model Research Articles

The imprint of the first stars on the faint end of the white dwarf luminosity function

ABSTRACT Population III stars are characterized by extremely low metallicities as they are thought to be formed from a pristine gas in the early Universe. Although the existence of Population III stars is widely accepted, the lack of direct observational evidence hampers the study of the nature of the putative stars. In this article, we explore the possibilities of constraining the nature of the oldest stars by using the luminosity function of their remnants – white dwarfs. We study the formation and evolution of white dwarf populations by following star formation in a Milky Way-like galaxy using the semi-analytic model a-sloth. We derive the white dwarf luminosity function by applying a linear initial-final mass relation and Mestel’s cooling model. The obtained luminosity function is generally in agreement with available observations and theoretical predictions – with an exponential increase to a maximum of $M_{\mathrm{abs}} = 16$ and a sudden drop for $M_{\mathrm{abs}} \gt 16$. We explore the uncertainties of our model and compare them to the observational estimates. We adopt two different models of the initial mass function of Population III stars to show that the faint end of the luminosity function imprints the signature of Population III remnants. If the feature is detected in future observations, it would provide a clue to Population III stars and would also be an indirect evidence of low- to intermediate-mass Population III stars. We discuss the challenges and prospects for detecting the signatures.

3D printed gelatin methacryloyl hydrogels for perfusion culture of human trabecular meshwork cells and glaucoma studies.

Glaucoma, a progressive eye disease leading to irreversible blindness, currently affects over 70 million people globally. Elevated intraocular pressure (IOP) is implicated in its development. IOP is carefully regulated by the trabecular meshwork (TM). However, studying TM behavior has been limited to traditional tissue culture studies or costly ex vivo cultures of animal and donor eyes. Developing novel functional TM models could enhance cell/tissue behavior understanding and aid therapeutic development for glaucoma. In this study, we 3D printed a simplified and reproducible model of the human TM (hTM) and studied hTM cell behavior under static and dynamic cultures. Gelatin Methacryloyl bioinks proved suitable for printing with viable and proliferative hTM cells expressing crucial marker genes in response to glucocorticoid induction. This, to our knowledge, is the first functional 3D printed hTM model and aims to facilitate TM research. Moreover, this easily reproducible model could also be applicable in the study of numerous other cell types throughout the body.

Examining the Equivalence Between Imagery and Execution—Does Imagery Comprise the Intended Spatial Trajectory?

The functional equivalence model suggests a common internal representation initiates both imagery and execution. This suggestion is supported by the mental chronometry effect, where there is a positive relation between task difficulty (as defined by the Index of Difficulty; ID) and imagined movement time. The present study extends this logic by examining whether imagery captures the spatial trajectory. Participants were initially tasked with the imagery and execution of a rapid aiming movement under different IDs. These initial attempts were adapted to configure auditory tones at early (25%) and late (75%) intervals for a separate set of imagery trials. If a tone had sounded, participants had to estimate post-trial where their imagined limb would have been located. The findings revealed increases in ID that coincided with increases in imagined and executed movement times. However, participant mean and standard deviation of estimated locations revealed limited differences between the early and late tones. Further inspection revealed some evidence for these estimated locations shifting further along in space following more rapid imagined movements. While equivalence is clearly evident within the temporal domain, there is comparatively little to suggest that this logic extends to the resolution required for simulating the spatial characteristics of movement.

Epoxidation at Isolated Titanium Site Modeled by Ti‐Siloxy‐Polyoxometalates Built on [α–A–XW9O34]n− and [α–B–YW9O33]9−: Comparative Study of Their Hydrolytic Stability

AbstractThis report investigates the structural differences in a series of titanium complexes constructed from silanol functionalized polyoxometalate (SiloxPOMs) derivatives, designed to create a constrained coordination site for titanium (IV) cations, namely (THA)3[PW9O34(tBuSiO)3Ti(OiPr)] and (THA)3[SbW9O33(tBuSiO)3Ti(OiPr)]. The complexes serve as structural and functional models for titanium silicates, facilitating the epoxidation of allylic alcohols and alkenes by aqueous hydrogen peroxide solutions. The different activity and selectivity observed between the two derivatives are attributed to variations in the polyoxotungstic platform used, A‐type–[XW9O34]n− versus B‐type –[YW9O33]3−. A combined experimental and theoretical investigation highlights the influence of these structural differences on water interaction and hydrolytic stability, with A‐type structures proving more susceptible to hydrolysis. In addition, the study also delves into the nuclearity of the active sites, a monomeric titanium (IV)‐hydroperoxide [Ti]–(OOH) active species evidenced by diffusion NMR spectroscopy, and the influence of the presence of water on catalytic performance in epoxidation reaction, thus shedding light on the relationship between catalyst stability, intermediates formed and reaction pathway. The study finally demonstrates the suitability of B‐type SiloxPOM derivatives as models for titanium silicates, offering insights into their stability and catalytic activity for epoxidation reactions.

Models and P4R asset description for digital twin-based advanced planning and scheduling using cyber-physical integration for resilient production operation

Advanced planning and scheduling (APS) addresses the complex and uncertain nature of production control. A digital twin (DT), which incorporates simulations through cyber-physical integration, provides an advanced functionality for APS. To facilitate efficient design and implementation, a DT-based APS must satisfy three requirements: technical functionalities for resilience, robust models for diverse operational constraints, and efficient interoperability through cyber-physical integration. Although several studies have proposed the use of DT as a primary technology for APS, proposals that address the process, functionality, integration, and information models are lacking. Additionally, the existing asset descriptions cannot adequately capture the sophisticated characteristics of DT and necessary informational elements for APS. Thus, this study designed a process model, functionalities, and integration models for the DT-based APS and asset descriptions for snapshot synchronization. Crucial service-compositions and functionalities were defined using work-center-level lifecycles. Consequently, a process model was developed, which focused on core activities for resilience. Moreover, horizontal integration between DT and control functionalities and vertical integration between DT and standards, were proposed to enhance the DT-based APS. The proposed method effectively managed the product, process, plan, plant, and resource classes by ensuring adherence to asset administration shell principles. To validate the effectiveness of the proposed methods, two work centers with distinctly different characteristics were employed and demonstrated dominant preventive measures compared to static functionality-based methods. The primary contributions encompass the facilitation of integration and interoperability within a DT-based APS. The proposed methods support the advanced characteristics of DT, ensuring robustness and neutrality across heterogeneous operational contexts.

Understanding surfaces and interfaces in nanocomposites of silicone and barium titanate through experiments and modeling

AbstractBarium titanate (BTO) is a ferroelectric perovskite used in electronics and energy storage systems because of its high dielectric constant. Decreasing the BTO particle size was shown to increase the dielectric constant of the perovskite, which is an intriguing but contested result. We investigated this result by fabricating silicone-matrix nanocomposite specimens containing BTO particles of decreasing diameter. Furthermore, density functional theory modeling was used to understand the interactions at the BTO particle surface. Combining results from experiments and modeling indicated that polymer type, particle surface interactions, and particle surface structure can influence the dielectric properties of polymer-matrix nanocomposites containing BTO. Graphical abstract

Density functional theory (DFT) study of water autoionization in solvated clusters.

We have implemented a cluster-continuum method using density functional theory to model water clusters and various charged species derived from water. The two aims of this study are to determine the minimal basis required for proper modeling of water autoionization and to determine the minimum number of explicit water molecules required to properly model the energetics of solvation. The thermodynamics of water autoionization converge following a modified power law to deliver chemically accurate values of the Gibbs energy change for autoionization with tractably small clusters. Convergence is slower and not exponential as assumed in previous work. We identify the n = 21 set of clusters as the first effectively bulk water like clusters that can capture the energetic influence of both the first and second solvation shells. In this cluster, a water molecule is encapsulated in the center of a closed shell of other water molecules that hydrogen bond to form five-membered rings. The total energy change for clusters with n ≥ 21 calculated using both the RPBE-D3 and ωB97X-D exchange-correlation functionals with the 6-311+G** basis set is shown to deliver good approximations to the free energy change at 298K. This is true even though neither functional models the individual enthalpy or entropy contributions particularly well.

Legal and Administrative Factors of the Transformation of the Content of Education under the Pressure of the COVID-19 Pandemic

The objective of this study is to examine the administrative and legal aspects impacting the transformation of educational content and form during the COVID-19 pandemic, with the aim of understanding their role in adapting educational systems to crisis conditions. This research is grounded in administrative law and educational theory, exploring how legal frameworks and administrative policies have shaped educational transformations during the pandemic. The IDEF0 method, a functional modeling methodology, provides a structured approach to analyzing these transformations. The methodology adopted for this research utilizes the IDEF0 method to model the administrative and legal influences on education during the pandemic. This approach involves a detailed analysis of existing legal documents, administrative guidelines, and educational policies that have been implemented in response to COVID-19. The analysis resulted in the development of an IDEF0 model that maps the key administrative and legal factors influencing educational transformation. The discussion contextualizes these findings within the broader framework of emergency education response and administrative law, highlighting the dynamic interplay between legal mandates and educational practices. The implications of this research are significant for policymakers and educational administrators as they provide insights into the effective legal and administrative strategies that can support educational continuity in crisis situations. These findings can inform future legislative and policy-making processes to enhance the resilience of educational systems. This study contributes to the literature by employing the IDEF0 method to model the influence of administrative and legal frameworks on education during a global health crisis.

Enhancing Economic and Legal Frameworks for Artificial Intelligence Technologies in Remote Education

In essence, enhancing economic and legal frameworks for artificial intelligence technologies in remote education is a multifaceted endeavor that requires concerted efforts from all stakeholders. By focusing on educator training, equitable access, adaptable legal regulations, ethical development practices, sustainable economic models, international collaboration, private sector involvement, public transparency, and continuous evaluation, we can create an educational environment where artificial intelligence serves as a powerful tool for learning. Such an environment not only improves educational outcomes but also prepares students to navigate and contribute to a world increasingly shaped by advanced technologies. This paper explores vital improvements in the economic and legal frameworks governing the application of artificial intelligence technologies within distance learning. The focus of the study is on how these regulations are shaped and implemented. The main objective is to develop a methodological approach that enhances these frameworks. The research utilizes the IDEF0 methodology to propose a functional model that refines the economic and legal controls of artificial intelligence use in remote education settings. Innovations within the IDEF0 model segments are discussed, aiming to bolster these frameworks effectively. Future research directions are suggested, including the integration of socio-psychological factors.

A Digital Twin System for Adaptive Aligning of Large Cylindrical Components

Most large aerospace cylindrical components still adopt a manual aligning method with low automation, large manual intervention, and heavy dependence on operator workers, resulting in the low quality and efficiency of large component aligning, which seriously prolongs the manufacturing time of aerospace products. To cope with this issue, based on closed-loop adaptive control and digital twin (DT) technologies, an adaptive aligning system for large cylindrical components, i.e., the DT aligning system, is proposed in this study. For the DT aligning system, through the DT multi-dimensional modeling, i.e., geometric modeling, physical modeling, functional modeling, and data modeling, it can be divided into a physical space, a virtue space, and twin data. Note that the association, mapping, and interaction between physical space and virtual space of the aligning system can be realized via the twin data, thereby realizing real-time virtual display, monitoring, and control of the large component aligning. In addition, based on the measured pose data, aligning stress, and predicted aligning error, an adaptive force/position control method for large component aligning is proposed, and it can achieve real-time decision-making and precise execution of the aligning process. Finally, through application validation, the DT process system can realize the real-time status perception and process execution decision during the large component aligning. Finally, through experimental validation, it is found that the proposed system, i.e., the DT aligning system, can improve the quality and efficiency of the large aerospace cylindrical component aligning, as well as the automation and intelligent level of the aligning system.

A 'Problematic' Pattern of Power-system Functioning and its Association with psychopathological Symptoms.

Following the well-researched two-dimensional model of attachment-system functioning, based on the concepts of hyperactivation and deactivation, a two-dimensional model of the power behavioral system has recently been proposed. The power system is aimed at activating, organizing, and implementing action patterns that protect or restore a sense of power or dominance. Here, we tested predictions derived from the two-dimensional model of power-system functioning regarding the contribution of a 'problematic' high-high pattern, characterized by the coexistence of both hyperactivating and deactivating strategies, to psychopathological symptoms. A non-clinical sample of Italian adults (N = 385) completed the Power Behavioral System Scale together with self-report measures of anxiety and depression symptoms and difficulties in executive control. Multiple regression analyses showed that higher deactivation and hyperactivation scores, characteristic of the 'problematic' pattern, significantly predicted anxiety and depression symptoms as well as executive function difficulties. These results provide initial support for the pathogenic implications of the 'problematic' high-high pattern of power-system functioning.

Endothelial Cells Increase Mesenchymal Stem Cell Differentiation in Scaffold-Free 3D Vascular Tissue.

In this study, we present a versatile, scaffold-free approach to create ring-shaped engineered vascular tissue segments using human mesenchymal stem cell-derived smooth muscle cells (hMSC-SMCs) and endothelial cells (ECs). We hypothesized that incorporation of ECs would increase hMSC-SMC differentiation without compromising tissue ring strength or fusion to form tissue tubes. Undifferentiated hMSCs and ECs were co-seeded into custom ring-shaped agarose wells using four different concentrations of ECs: 0%, 10%, 20%, and 30%. Co-seeded EC and hMSC rings were cultured in SMC differentiation medium for a total of 22 days. Tissue rings were then harvested for histology, Western blotting, wire myography, and uniaxial tensile testing to examine their structural and functional properties. Differentiated hMSC tissue rings comprising 20% and 30% ECs exhibited significantly greater SMC contractile protein expression, endothelin-1 (ET-1)-meditated contraction, and force at failure compared with the 0% EC rings. On average, the 0%, 10%, 20%, and 30% EC rings exhibited a contractile force of 0.745 ± 0.117, 0.830 ± 0.358, 1.31 ± 0.353, and 1.67 ± 0.351 mN (mean ± standard deviation [SD]) in response to ET-1, respectively. Additionally, the mean maximum force at failure for the 0%, 10%, 20%, and 30% EC rings was 88.5 ± 36. , 121 ± 59.1, 147 ± 43.1, and 206 ± 0.8 mN (mean ± SD), respectively. Based on these results, 30% EC rings were fused together to form tissue-engineered blood vessels (TEBVs) and compared with 0% EC TEBV controls. The addition of 30% ECs in TEBVs did not affect ring fusion but did result in significantly greater SMC protein expression (calponin and smoothelin). In summary, co-seeding hMSCs with ECs to form tissue rings resulted in greater contraction, strength, and hMSC-SMC differentiation compared with hMSCs alone and indicates a method to create a functional 3D human vascular cell coculture model.

Decision-Making with Predictions of Others' Likely and Unlikely Choices in the Human Brain.

For better decisions in social interactions, humans often must understand the thinking of others and predict their actions. Since such predictions are uncertain, multiple predictions may be necessary for better decision-making. However, the neural processes and computations underlying such social decision-making remain unclear. We investigated this issue by developing a behavioral paradigm and performing functional magnetic resonance imaging and computational modeling. In our task, female and male participants were required to predict others' choices in order to make their own value-based decisions, as the outcome depended on others' choices. Results showed, to make choices, the participants mostly relied on a value difference (primary) generated from the case where others would make a likely choice, but sometimes they additionally used another value difference (secondary) from the opposite case where others make an unlikely choice. We found that the activations in the posterior cingulate cortex (PCC) correlated with the primary difference while the activations in the right dorsolateral prefrontal cortex (rdlPFC) correlated with the secondary difference. Analysis of neural coupling and temporal dynamics suggested a three-step processing network, beginning with the left amygdala signals for predictions of others' choices. Modulated by these signals, the PCC and rdlPFC reflect the respective value differences for self-decisions. Finally, the medial prefrontal cortex integrated these decision signals for a final decision. Our findings elucidate the neural process of constructing value-based decisions by predicting others and illuminate their key variables with social modulations, providing insight into the differential functional roles of these brain regions in this process.

Daytime Dysfunction: Symptoms Associated with Nervous System Disorders Mediated by SIRT1.

Daytime dysfunction, including symptoms like sleepiness, poor memory, and reduced responsiveness, is not well researched. It is crucial to develop animal models and study the biological mechanisms involved. We simulated sleep disorders through sleep deprivation, and stressful stimuli were used to establish daytime functional animal models. We used tests like the sodium pentobarbital sleep synergy test and the DSI telemetry system to measure sleep duration and structure. We also used tests like the Morris water maze, open field test, grip test, and baton twirling test to assess mental and physical fatigue. To assess the intrinsic biological mechanisms, we measured sleep-wake-related neurotransmitters and related receptor proteins, circadian rhythm-related proteins and cognition-related proteins in hypothalamus tissue, and oxidative stress, inflammatory factors, S100β, and HPA axis-related indexes in serum. Multi-factor sleep deprivation resulted in the disruption of sleep-wakefulness structure, memory-cognitive function degradation, decreased grip coordination, and other manifestations of decreased energetic and physical strength. The intrinsic biological mechanisms were related to the disturbed expression of sleep-wake, circadian rhythm, memory-cognition-related proteins, as well as the significant elevation of inflammatory factors, oxidative stress, the HPA axis, and other related indicators. Intrinsically related biological mechanisms and reduced sirt1 expression can lead to disruption of circadian rhythms; resulting in disruption of their sleep-wake-related neurotransmitter content and receptor expression. Meanwhile, the reduced expression of sirt1 also resulted in reduced expression of synapse-associated proteins. This study prepared an animal model of daytime dysfunction by means of multi-factor sleep deprivation. With sirt1 as a core target, the relevant biological mechanisms of neurological disorders were modulated.

Unveiling the Dominant Factors in Subthalamic Stimulation for Improving Depression in Parkinson's Disease.

Currently, the conclusions of studies on subthalamic nucleus (STN) deep brain stimulation (DBS) for improving Parkinson's disease (PD) with depression are inconsistent, and the reasons for improvement or deterioration remain unclear. The aim was to investigate the prognosis of PD with depression after bilateral STN-DBS and the factors related to the improvement in depression. The local and network effects of DBS on depression in PD (DPD) were further explored based on the volume of tissue activation (VTA). The study analyzed 80 primary PD patients who had undergone bilateral STN-DBS, comprising 47 patients with improved depression and 33 patients without improvement. Two groups of clinical profiles and stimulation parameters were compared, and the network models for improving depression were constructed. The improvement in depression was closely associated with improvement in anxiety (odd rate [OR] = 1.067, P = 0.006) and the standardized space left y-coordinate (OR = 0.253, P = 0.005). The VTA overlapping with the left motor STN subregion is most significantly associated with improvement in depression (RSpearman = 0.53, P < 0.001; RPearson = 0.43, P < 0.001). The y-coordinates in the improvement group were closer to the optimal stimulation site for improving motor symptoms. Finally, both the structural and functional network models indicate a positive correlation between depression improvement and the connectivity of the sensorimotor cortex. The amelioration of DPD is primarily attributed to the stimulation of bilateral motor STN, particularly on the left. However, this stimulatory effect manifests as an indirect influence.

Enabling the vision of a perpetual innovative product – predicting function fulfillment of new product generations in a circular factory

Abstract The need for sustainability is driving the transition from linear to circular production. Customers, driven by the desire for innovation, prefer new products with the latest cutting-edge functions and design. The problem is that used products from older product generations are hence less attractive, leading to a limited market for remanufactured products and generating less revenue than their new counterparts. Therefore, this research addresses the problem of reprocessing and technologically updating used products into the newest product generation. To address this problem of reprocessing and technological updating with a Circular Factory, the product’s function fulfillment must be predicted in different situations in a Circular Factory. Three key challenges in which the function fulfillment must be predicted are identified as: Analysis and Diagnostics of Used Products and Subsystems, Prediction for Pairing and Reprocess of the Embodiment and Design for Circular Factory. A model-based approach is presented to address these three key challenges by predicting product function fulfillment to enable cross-generational use of subsystems and components. Five different types of models are proposed: A Functional Model, a Reliability Model and a Reference Architecture Model at the high level of general product modeling, as well as a Digital Twin of an object instance and a Tolerance Scheme at the level of individual instances. A theoretical case study shows the possible application in a Circular Factory using the example of an angle grinder. However, it’s essential to acknowledge that substantial work is needed for the enhancement or development of these models before practical application. Successful application of these models allows the Circular Factory not only to maintain but also to increase the value of reprocessed products to enable offering on the primary market and contribute to the vision of realizing a perpetual innovative product.

Electrochemical flow-through disinfection of Escherichia coli versus Staphylococcus aureus: Identifying impacts of flow patterns on efficiency

While Ti4O7 reactive electrochemical membrane (REM) treatment exhibits high efficiency in inactivating bacteria, it remains obscure about the disinfection and antifouling mechanism. Herein, we highlighted the decisive impact of flow patterns on the electrochemical inactivation of both Escherichia coli and Staphylococcus aureus during dead-end filtration mode. Specifically, 5.22 and 5.47 log removal for E. coli and S. aureus were achieved by a single pass under anode-to-cathode (AC) flow pattern at 7 mA cm−2 respectively, while the inactivation rates immediately decreased to less than one log for cathode-to-anode (CA) flow pattern. Further analysis demonstrated that the remarkable inactivation efficiency in neutral condition, the complete inactivation of E. coli and S. aureus in the parallel plate batch mode were achieved in 15 min and 30 min at 7 mA cm−2 respectively, was significantly inhibited during alkaline and acidic exposure, thereby which explained the slow disinfection rates in CA flow pattern due to the formed alkaline experiment near anodic reaction section. The disinfection efficiency and comparative differences of E. coli and S. aureus were also affected by their hydraulic condition and cell wall structure. Functional groups model substances experiments and molecular dynamics simulation elucidated that the response changes of cell structure especially denser membrane protein complex under alkaline and acidic exposure resisted electrooxidation attack to the membrane structure. These findings here provide insights into the application of Ti4O7 REM technologies in controlling waterborne disease transmission.

Modeling the differential functional responses and selectivity of a marine copepod to nano/microplastics in mixture

Nano- and microplastics (NMPs) pollution is widespread in the oceans, posing potential risks to marine species. This study examined the accumulation capacity and selectivity potentials of NMPs by a marine copepod Parvocalanus crassirostris under different food mixtures by modeling the combined biokinetic and functional response. We investigated two sizes of NMPs (200 nm and 5 µm) across a concentration gradient (0 - 5000 µg/L) and varying diatom abundances (0, 104, 105 cells/mL). Fluorescence imaging and quantification revealed that P. crassirostris actively ingested NMPs at low concentration. Accumulation increased with NMPs concentration but eventually saturated due to gut capacity limits, following a Holling type II functional response (i.e., hyperbolic curve). Our novel functional response model estimated the key parameters and demonstrated that the maximum accumulation reached 5.3 % of dry weight with averaged half-saturation constants of 229 µg/L. The size of NMPs did not significantly affect the total accumulation or satiety levels. The presence of diatoms influenced the feeding selectivity and decreased the microplastic accumulation by 73 % at 105 cells/mL, while facilitating nanoplastic accumulation by 81 % at 104 cells/mL. This study enhanced our understanding of NMPs bioavailability and environmental fate in marine ecosystems.

GIS-technologies and algorithm for developing regional systems for handling medical waste on the example of three regions

Introduction. GIS is a modern computer technology designed for collecting, storing, analyzing and visualizing spatial data – mapping. GIS is also actively used in healthcare to solve many regional problems, including optimization and management of healthcare resources. Over last decade, many researchers have used mathematical software models for healthcare waste management. A review of the literature shows facility location, risk to the public, and economic feasibility to be among the issues that have been extensively covered in the literature. Designing a reverse logistics network using mathematical software tools is an efficient and effective way to manage healthcare waste. The objective of the study. To determine the optimal approach to creating a functional model of a system for managing medical waste of class B and C using GIS-technologies for each of the three regions, based on the characteristics of each. Materials and methods. Medical institutions in three regions (St. Petersburg, Leningrad Region and Krasnoyarsk Territory) as sources of medical waste generation were considered taking into account their capacity and specialization. The composition and volumes of waste by class were determined using a calculation method based on indicative waste generation standards. The identification of local technologies for the neutralization of medical waste existing in medical institutions was carried out. The obtained data was processed statistically and displayed on electronic maps for subsequent use in GIS technologies, as well as for the development and justification of a waste management system for medical institutions, taking into account the prospects for the development of healthcare. Results. Based on the analysis of data on medical waste of classes B and C in individual medical institutions, as well as an analysis of the power of existing technologies for neutralizing this waste using GIS technologies, proposals were developed to improve the medical waste management system in three regions. The proposals are aimed at improving the sanitary and epidemiological situation in the regions over a five-year period and take into account the features of the existing transport infrastructure and the requirements of sanitary legislation. Limitations. The model of a medical waste management system using GIS technologies was used only for managing waste of classes B and C. Conclusion. To ensure the safe and environmentally sustainable functioning of the waste management system of classes B and C in the regions, it is necessary to apply an integrated approach based on GIS technologies. This approach should take into account the regional characteristics of the management of the medical waste disposal system and its economic feasibility and take into account the regional characteristics of transport logistics and the prospects for the development of healthcare.

Behavioral Management in the Rehabilitation of a Person with Severe Mental Illness: The Path Less Travelled

In severe mental illness (SMI), such as schizophrenia, rehabilitation begins immediately. Aside from the token economy, there is limited literature on behavioral modification (BM), which is a crucial aspect of rehabilitation for person with severe mental illness (SMI). We demonstrate the implementation and effectiveness of BM for one year in managing behavioral difficulties in a person with SMI. The direct observation method and the ABC functional analysis model were used for evaluation. Management, such as reinforcement and punishment, was implemented. Pre- and postassessments revealed a considerable decrease in problematic behaviors. This article also highlights the obstacles faced while managing the case and caregiver burden in rehabilitation. In persons with SMI, the application of BM enhances the patient’s functionality and reduces the caregiver burden.