Terms Of Behavior Research Articles

Thermal management inside a discretely heated rectangular cuboid using P, PI and PID controllers

This study investigates the viability of three different continuous (P, PI, and PID) controllers to meet specific thermal requirements at a desired location in a cooling system with discrete heat sources. The system is a rectangular cuboid with three discrete heat sources placed on the bottom surface at periodic intervals, and the rest of the walls are insulated. A temperature probe is installed in the system's center to monitor the temperature and provide feedback to the flow controllers in a continuous manner. The velocity of air entering from the inlet port varies in response to the controller feedback and discharge through the outlet port at atmospheric condition. The Galerkin finite element technique solves the governing Navier-Stokes and energy equations and the appropriate initial and boundary conditions. The simulations consist of testing the system's response at the probe point using different combinations of proportional (P), integral (I), and derivative (D) controllers with varied gains to analyze and compare the system's steady-state error and transient behavior in terms of overshoot, oscillation, and settling time. The results indicate that the P controller cannot eliminate steady-state error, while the PI controller achieves zero steady-state error and faster settling. However, if appropriately tuned, the PID controller enhances oscillation control and response time.

Evaluating Player Experience in Stealth Games: Dynamic Guard Patrol Behavior Study

In stealth games, guard patrol behavior constitutes one of the primary challenges players encounter. While most stealth games employ hard-coded guard behaviors, the same approach is not feasible for procedurally generated environments. Previous research has introduced various dynamic guard patrol behaviors; however, there needs to be more play-testing to quantitatively measure their impact on players. This research paper presents a user study to evaluate players' experiences in terms of enjoyment and difficulty when playing against several dynamic patrol behaviors in a stealth game prototype. The study aimed to determine whether players could differentiate between different guard behaviors and assess their impact on player experience. We found that players were generally capable of distinguishing between the various dynamic guard patrol behaviors in terms of difficulty and enjoyment when competing against them. The study sheds light on the nuances of player perception and experience with different guard behaviors, providing valuable insights for game developers seeking to create engaging and challenging stealth gameplay.

Exothermic barrier-free carboxylation of alkali methylates. The highest-yield synthesis of dialkyl carbonates out of alcohols and carbon dioxide rationalized and reformulated through quantum-chemical simulations

While the Earth’s atmosphere represents an abundant source of CO2, its valorization by humanity remains at a nascent stage. Synthesizing added-value products out of CO2 and suitable co-reactants is an urgent and appealing chemical challenge to pursue in our busy times. Herein, we perform a rationalization, extension, and ultimate reformulation of the recently proposed highest-yield synthesis of dimethyl carbonate (DMC) and generally dialkyl carbonates out of alcohols and CO2 employing quantum-chemical reaction modeling. The carboxylation of pure methanol (CH3OH) by CO2 is thermochemically prohibited (+33 kJ/mol) and hindered by a heavy activation energy barrier (160 kJ/mol). The existing catalysts decrease the above barrier twice. The catalyzed carboxylation exhibits yields of 5–15 % of DMC depending on a specific catalyst, dehydration agents, and pressure elevation. In turn, the usage of alkali metal methylates – such as CH3OLi, CH3ONa, CH3OK, and CH3ORb – as reactants, instead of CH3OH, fully eliminates the activation barrier. Furthermore, alcoholates make carboxylation exothermic. We stepwise rationalize the origin of such a desirable behavior in terms of thermochemistry, molecular geometries, atomic nucleophilicities, potential energy landscapes, and computed vibrational spectra. All methylates perform decently and exhibit reasonable similarities as reactants. The most favorable reaction was recorded in the case of sodium alcoholate (according to Gibbs free energy) and lithium alcoholate (according to enthalpy). Since the carboxylation smoothly proceeds with the methylates, the synthesis can be carried out under normal conditions. This is contrary to the elevated temperatures and pressures, which have to be routinely supplied to implement the presently known catalytic schemes. Apart from an organic carbonate, the novel reactions produce LiI, NaI, KI, and RbI as major products. The consumed alkali metals need to be restored, for instance, by utilizing electrolysis, for their repetitive usages. The theoretical results are discussed tightly in the context of the recent experiments. The reactions can take place in liquid CH3OH. Exemplified computationally for the methyl radical, the invented scheme must generally work for larger hydrocarbon moieties. This report will interest synthetic chemists, whose work is devoted to the valorization of CO2.

Unified interpretation of MAOS responses via experimentally decomposed material functions

Oscillatory shear testing, used to characterize the viscoelastic response of soft materials, is often divided into small, medium, and large amplitude oscillatory shear (SAOS, MAOS, and LAOS) regions. SAOS is a common test that gives us a unified analysis and interpretation of linear viscoelastic behavior, whereas understanding MAOS and LAOS is still an active area of research. While numerous mathematical techniques have been proposed, a consensus interpretation is still missing. Recently, our understanding of nonlinear behavior in the LAOS regime has been developed using iterative recovery tests. Recovery rheology decomposes the strain into two components, allowing an unambiguous interpretation of the nonlinear behavior in terms of sequences of recoverable and unrecoverable processes. In this work, we revisit the MAOS material functions for polyvinyl alcohol-borax hydrogel and worm-like micelles using recovery rheology. We show that two mathematical formalisms, the Chebyshev and sequence of physical processes analyses, provide competing physical interpretations when they are derived from the total strain, but provide unified interpretations when describing the decomposed strains. We, therefore, show that what has often been treated as a mathematical problem can instead be solved experimentally by acknowledging the extra information provided by recovery rheology.

Modelling taxpayers’ behaviour based on prediction of trust using sentiment analysis

Fiscal systems depend on taxpayer's behaviour in terms of their willingness to comply or engage in fraud, deeply rooted in trustworthiness. To gain insights into taxpayers' perceptions and their influence on trust within taxation system, we use survey data to analyse word frequencies, sentiments, attitudes. Our approach utilizes natural language processing in conjunction with machine learning techniques. We highlight a notable correlation: taxpayers who lack trust in fiscal system tend to employ a higher frequency of negative words and exhibit limited word diversity in their expressions. The presence of negative sentiments may potentially foster fraudulent behaviours in the future.

Impact of vaccination in the mortality of Colombian adults with acute respiratory distress syndrome due to SARS-CoV-2 who required invasive mechanical ventilation

IntroductionVaccination for SARS-CoV-2 made it possible to reduce severe cases that require invasive mechanical ventilation (IMV) and care in the ICU. However, its impact on severe disease is not clear. The objective was to assess whether adults with severe SARS-CoV-2 pneumonia who required mechanical ventilation had a different clinical behaviour in terms of mortality, depending on their vaccination status. MethodologyRetrospective cohort study, in adults with severe pneumonia due to SARS-CoV-2 requiring IMV and ICU. Clinical outcomes were evaluated according to vaccination status, controlling for comorbidities. ResultsTwo hundred patients (24% vaccinated, age 61±13 years, men 68%) were analysed. The vaccinated had lower CRP at admission, distension pressure and PEEP requirement for IMV. Mortality (43.8 vs 36.8%, P: .335), hospital stay, ICU stay, and time on IMV were similar between groups. Acute kidney injury and haemodialysis requirement (0 vs 9.2%, P: .03) were more frequent in the unvaccinated. There was no association between mortality and receiving at least one dose of vaccination (RR 1.21; CI 95% 0.829–1.774, P: .335). ConclusionsVaccination did not impact mortality. However, our data suggest that it may reduce the inflammatory state produced by the disease and the occurrence of acute kidney injury and the requirement for haemodialysis. Future studies will be required to assess the impact of the type of vaccine and/or the number of doses received.

Recurrence Quantification Analysis of Crowd Sound Dynamics.

When multiple individuals interact in a conversation or as part of a large crowd, emergent structures and dynamics arise that are behavioral properties of the interacting group rather than of any individual member of that group. Recent work using traditional signal processing techniques and machine learning has demonstrated that global acoustic data recorded from a crowd at a basketball game can be used to classify emergent crowd behavior in terms of the crowd's purported emotional state. We propose that the description of crowd behavior from such global acoustic data could benefit from nonlinear analysis methods derived from dynamical systems theory. Such methods have been used in recent research applying nonlinear methods to audio data extracted from music and group musical interactions. In this work, we used nonlinear analyses to extract features that are relevant to the behavioral interactions that underlie acoustic signals produced by a crowd attending a sporting event. We propose that recurrence dynamics measured from these audio signals via recurrence quantification analysis (RQA) reflect information about the behavioral dynamics of the crowd itself. We analyze these dynamics from acoustic signals recorded from crowds attending basketball games, and that were manually labeled according to the crowds' emotional state across six categories: angry noise, applause, cheer, distraction noise, positive chant, and negative chant. We show that RQA measures are useful to differentiate the emergent acoustic behavioral dynamics between these categories, and can provide insight into the recurrence patterns that underlie crowd interactions.

Impacto de la vacunación en la mortalidad de adultos colombianos con síndrome de dificultad respiratoria aguda por SARS-CoV-2 que requirieron ventilación mecánica invasiva

IntroductionVaccination for SARS-CoV-2 made it possible to reduce severe cases that require invasive mechanical ventilation (IMV) and care in the ICU. However, its impact on severe disease is not clear. The objective was to assess whether adults with severe SARS-CoV-2 pneumonia who required mechanical ventilation had a different clinical behavior in terms of mortality, depending on their vaccination status. MethodologyRetrospective cohort study, in adults with severe pneumonia due to SARS-CoV-2 requiring IMV and ICU. Clinical outcomes were evaluated according to vaccination status, controlling for comorbidities. ResultsTwo hundred patients (24% vaccinated, age 61 ± 13 years, men 68%) were analyzed. The vaccinated had lower CRP at admission, distension pressure and PEEP requirement for IMV. Mortality (43.8 vs 36.8%, p: 0.335), hospital stay, ICU stay, and time on IMV were similar between groups. Acute kidney injury and hemodialysis requirement (0 vs 9.2%, p: 0.03) were more frequent in the unvaccinated. There was no association between mortality and receiving at least one dose of vaccination (RR 1.21; CI 95% 0.829–1.774, p: 0.335). ConclusionsVaccination did not impact mortality. However, our data suggest that it may reduce the inflammatory state produced by the disease and the occurrence of acute kidney injury and the requirement for hemodialysis. Future studies will be required to assess the impact of the type of vaccine and/or the number of doses received.

Using the ACT matrix to improve sleep: A practical guide for implementing the "what" and the "how" of sleep hygiene

Insufficient sleep duration and quality among adults is a growing public health concern. While cognitive behavioural therapy for insomnia is effective in treating clinical levels of sleep difficulty, intervention for subclinical sleep difficulty has been lacking. The "What" and the "How" of Sleep Hygiene is an Acceptance and Commitment Therapy-based (ACT) psychoeducation group focused on improving sleep hygiene and supporting long term behaviour change. The group involved 8 sessions, each focused on a different aspect of sleep hygiene throughout the day (e.g., morning routine). Three behaviour change principles and the well-established ACT tool, the Matrix, were central to the intervention designed to help implement sleep hygiene. The session summaries are intended to provide clinicians with a practical guide for implementation.

İnfertil Kadınlara Değişim Aşamaları Modeli ile Yapılan Bireysel Danışmanlık Girişiminin Kilo Yönetimine Etkisi

Objective: Evaluate the effect of individual counseling intervention on weight management based on Stages of Change Model conducted on infertile women Methods: This study consisted of two stages: counseling and follow-up. The research population consisted of 146 infertile women who applied to the in vitro fertilization center of a state hospital in İzmir between January 4, 2019, and June 22, 2019. Among the 104 infertile women who met the inclusion criteria and declared their willingness to participate in the study, 51 women constituted the intervention group, and 53 women constituted the control group. While an individual counseling program based on Stages of Change Model was conducted on the initiative group, the control group was followed routinely. Research data were analyzed using SPSS 22.0 software. Results: Most recent follow-up anthropometric values of infertile women in the intervention group were lower compared to the pre-follow-up values. The difference between these two data was statistically significant (p = 0.000). Infertile women in the intervention group tended to increase their consumption of daily milk and dairy products and vegetable and fruits in their most recent follow-up stage compared to that in the pre-follow-up stage, whereas their consumption of and daily calories from meat products, sugary products, fats, cereals, and bread decreased. The difference between these two data was statistically significant (p = 0.000). Conclusion: Individual counseling intervention based on Stages of Change Model aiming to evaluate the weight management caused infertile women to adopt healthy behaviors in terms of physical activity and nutritional habits.

Edukasi Tentang Pengelolaan Sampah Rumah Tangga Dalam Menjaga Kesehatan Lingkungan Kelurahan Manisa

Waste is a material that is discarded or discarded, which is the result of human or natural activities which is no longer used because its main elements or function have been taken away. Every human activity must generate waste or garbage. Sources of waste can come from households, agriculture, offices, companies, hospitals, markets and so on. Survey method by conducting observations at target locations and conducting interviews about community behavior in terms of managing waste and maintaining environmental cleanliness. The results of the evaluation of the counseling process showed that participants followed the counseling until completion and the counseling was carried out calmly and safely.

Pengaruh Penggunaan Media Sosial dan Komunikasi Keluarga Terhadap Perilaku Cyberbullying pada Anak

The use of social media is increasingly growing among the wider community, especially among children. The presence of social media can certainly have positive and negative impacts. This is what is worth paying attention to because the use of social media is widely used by children for various needs that have an impact on themselves. Not only that,family communication also greatly influences children’s behavior and attitudes in terms of good or bad, such as behavior that hurts other people or can be called cyber bullying behavior. The aim of this research is to determine the use of social media and family communication on cyber bullying behavior in children . the researcher used a quantitative method which will be carried out on 128 respondents who are elementary school children in Sidoarjo sub-district which has been carried out in two schools , namely SDN 1 celep Sidoarjo and SD cendekia Sidoarjo with each school taking classes 5 and 6 and analyzed by validity, reability and multiple linear regression tests using SPSS. The results showed that the use of social media by 8,92% and family communication by 60,40% had a significant effect on cyberbullying behavior in children.

Nonequilibrium kinetics effects in Richtmyer–Meshkov instability and reshock processes

Kinetic effects in the inertial confinement fusion ignition process are far from clear. In this work, we study the Richtmyer–Meshkov instability and reshock processes by using a two-fluid discrete Boltzmann method. The work begins by interpreting the experiment conducted by Collins and Jacobs (2002, J. Fluid Mech. 464, 113–136). It shows that the shock wave causes substances in close proximity to the substance interface to deviate more significantly from their thermodynamic equilibrium state. The thermodynamic non-equilibrium (TNE) quantities exhibit complex but inspiring kinetic effects in the shock process and behind the shock front. The kinetic effects are detected by two sets of TNE quantities. The first set includes , , , and , which correspond to the intensities of the non-organized momentum Flux (NOMF), Non-Organized Energy Flux (NOEF), the flux of NOMF and the flux of NOEF. All four TNE measures abruptly increase in the shock process. The second set of TNE quantities includes , and , which denote the entropy production rates due to NOMF, NOEF and their summation, respectively. The mixing zone is the primary contributor to , while the flow field region outside of the mixing zone is the primary contributor to . Additionally, each substance exhibits different behaviors in terms of entropy production rate, and the lighter fluid has a higher entropy production rate than the heavier fluid.

Big Data Aggregation, Visualization and Clustering for Smart Grid in Smart City using Machine Learning

Electrical energy is one of the most important components of life today where different fields depend on it. The field of electrical energy distribution (electricity network), which transmits electrical energy from sources to consumers, is one of the most important areas that need to be developed and improved. In addition to analyzing electrical energy consumption, it needs to forecast consumption and determine consumer behavior in terms of consumption and how to balance supply and demand. The research aims to analyze weather data and find the relation between the weather factors and energy consumption in order to prepare data to use as a suitable data in machine learning model for future use. This model analyzes the building consumption rate for a particular area and takes into account the weather factors that affect electrical energy consumption, where (temperature, dew point, ultraviolet index) are selects based on the correlation confidence and then divided these factors into a set of categories using the K-Means algorithm to show the effect of each factors on the other. Index Terms— Big data, IoT, smart city, smart grid, smart meter, clustering, k-means clustering.

Behavioural patterns discovery for lifestyle analysis from egocentric photo-streams

Automatic tools for the analysis of human behaviour are very important when aiming to understand the lifestyle of people. Egocentric wearable cameras allow the capture of images during long periods of time and in this way bring objective evidence of the experiences of the user.In this paper, we propose a novel framework to discover behavioural patterns following an unsupervised greedy approach based on extracted image descriptors. The method collects and constructs time-frames to extract the semantics of user behaviour in terms of contextual information, such as places, activity, present objects, and others. Later, the similarity among the user time-frames is computed to assess correlations and thus obtain the user’s routine descriptors. To evaluate the performance of our method, we present several score metrics and compare them to state-of-the-art works in the field. We validated our method on 315 days and more than 390,000 images extracted from 14 users. Results show that behavioural patterns can be successfully discovered and that they are able to characterize the routine of people bringing important information about their lifestyle and behaviour change.

Study of physical and rheological properties of modified bitumen prepared by blending non-metallicpart of e-waste

Electronic waste is known as e-waste. Literature showed that it contains many toxic and hazardous materials not only pollute the earth but also water and air too. Due to technological advancement, e-waste is increasing day by day and its disposal is becoming a challenge for our society. It contains plastic, metals and many other harmful and hazardous chemicals and materials. Based on the requirement of disposal of e-waste, the present study investigated the utilization of the non-metallic part of e-waste and its influence on the physical and rheological properties of modified bitumen. The study showed the preparation of five electronic waste-modified bitumens (e-WMBs): e-WMB1, e-WMB2, e-WMB3, e-WMB4 and e-WMB5 using a dry approach and four e-WMBs: e-WMB6, e-WMB7, e-WMB8, and e-WMB9. These e-WMBs were prepared by blending non-metallic parts of electronic waste material and its slurry in 80/100 base bitumen. The study revealed that an optimal 2.5 wt % e-waste not only illustrated the best blending in bituminous paves besides a profitable deployment of nonmetallic components of e-waste for augmented rheological properties of bitumen composite. The main objective of the study was to prepare VG40 equivalent bitumen as per Bureau of Indian Standard (BIS) specification IS: 73:2013 with the use of non-metallic parts of e-waste. The blending of 2.5 wt% e-waste slurry changes the penetration from 100 dmm to 40 dmm, and softening point from 47 to 50 °C. e-WMB7 meeting all specification of VG40 bitumen as per IS specification IS73:2013. The study revealed that the utilization of e-waste can be beneficial to enhance the rheological properties of base bitumen in terms of load-bearing capacity complex modulus (G*), and viscoelastic behavior in terms of phase angle (δ). The blending of 2.5 wt% e-waste slurry changes the penetration from 100 dmm to 40 dmm, and softening point from 47 to 50 °C. e-WMB7 meets all specifications of VG40 bitumen.

Mechanical behaviour of hybrid FFRP/aluminium honeycomb sandwich structures

The combination of lightweight properties and high energy absorption capacity makes sandwich structures suitable for applications in transportation industry, such as automotive, aerospace, and shipbuilding industry. In these fields, the gas emissions reduction, fuel saving, vehicle safety and load capacity increase are currently important requirements. This research deals with the study of the mechanical behaviour of a “green” hybrid honeycomb sandwich structure made by an aluminium honeycomb core and flax fibres reinforced skins. Specific interest has been addressed to their mechanical behaviour in terms of bending properties and low-velocity impact response. For the impact tests, two indenters having hemispherical geometry with a diameter of 10 mm (H10) and 20 mm (H20) were selected. The results were compared with other hybrid structures analysed in previous studies. The static three-point bending tests produced different collapse modes, depending on the support span distance. Non-destructive evaluation was carried out for failure mode analysis by optical microscopy and digital radiography (DR). In the aluminium-flax hybrid sandwich structures it is found an increase in the impact strength of 25 % compared to the unreinforced aluminium honeycomb sandwich structures. In terms of specific energy absorption (SEA), it is interesting to underline an increase of 50 % compared to traditional AHS structures.

The Influence of Beverages on Resin Composites: An In Vitro Study.

Dental composites, through their structural diversity, represent the biomaterials frequently used in dental reconstructive therapy. The aim of our study was to observe the influence of different beverage environment conditions on seven types of obturation dental materials with different compositions. Our research focused on the surface modification analysis of the materials after the immersion in the different beverages; in this regard, we used the EDAX technique correlated with the energy-dispersive X-ray fluorescence (XRF). The pH of the drinks and that of the simulated saliva solution were determined by the titrimetric method, a sodium hydroxide solution 0.1 mol/dm3 was prepared and used for the titration. An amount of 5 mL of each analyzed solution was added to 15 mL of distilled water to obtain a dilution, to which 3 drops of phenolphthalein (as a color indicator-Phenolphthalein, 3,3-Bis(4-hydroxyphenyl)-1(3H)-isobenzofuranone, C20H14O4 Mw: 318.32, purchased from Merck) were added for each analysis. For each solution, the experiment was repeated three times in order to obtain accurate results. The results of our study materialized into a real plea for modifying the patients' behavior in terms of diet and preferences for acidic drinks, so that their quality-of-life valence can be improved by keeping the composite materials in a long-term unalterable state on the one hand; on the other hand, systemic damage can be prevented as well.

The role of convection in the existence of wavefronts for biased movements

We investigate a model, inspired by Johnston et al. (2017) to describe the movement of a biological population which consists of isolated and grouped organisms. We introduce biases in the movements and then obtain a scalar reaction–diffusion equation that includes a convective term as a consequence of the biases. We focus on the case the diffusivity makes the parabolic equation of forward–backward–forward type and the reaction term models a strong Allee effect, with the Allee parameter lying between the two internal zeros of the diffusion. In such a case, the unbiased equation (i.e., without convection) possesses no smooth traveling‐wave solutions; on the contrary, in the presence of convection, we show that traveling‐wave solutions do exist for some significant choices of the parameters. We also study the sign of their speeds, which provides information on the long term behavior of the population, namely, its survival or extinction.

A self-supervised language model selection strategy for biomedical question answering

Large neural-based Pre-trained Language Models (PLM) have recently gained much attention due to their noteworthy performance in many downstream Information Retrieval (IR) and Natural Language Processing (NLP) tasks. PLMs can be categorized as either general-purpose, which are trained on resources such as large-scale Web corpora, and domain-specific which are trained on in-domain or mixed-domain corpora. While domain-specific PLMs have shown promising performance on domain-specific tasks, they are significantly more computationally expensive compared to general-purpose PLMs as they have to be either retrained or trained from scratch. The objective of our work in this paper is to explore whether it would be possible to leverage general-purpose PLMs to show competitive performance to domain-specific PLMs without the need for expensive retraining of the PLMs for domain-specific tasks. By focusing specifically on the recent BioASQ Biomedical Question Answering task, we show how different general-purpose PLMs show synergistic behaviour in terms of performance, which can lead to overall notable performance improvement when used in tandem with each other. More concretely, given a set of general-purpose PLMs, we propose a self-supervised method for training a classifier that systematically selects the PLM that is most likely to answer the question correctly on a per-input basis. We show that through such a selection strategy, the performance of general-purpose PLMs can become competitive with domain-specific PLMs while remaining computationally light since there is no need to retrain the large language model itself. We run experiments on the BioASQ dataset, which is a large-scale biomedical question-answering benchmark. We show that utilizing our proposed selection strategy can show statistically significant performance improvements on general-purpose language models with an average of 16.7% when using only lighter models such as DistilBERT and DistilRoBERTa, as well as 14.2% improvement when using relatively larger models such as BERT and RoBERTa and so, their performance become competitive with domain-specific large language models such as PubMedBERT.