Internal State Research Articles

Parents’ cultural beliefs about maladaptive behavior in young children: A comparison of across two cultures

Parents’ cultural beliefs are associated with their children’s socialization and development. Researchers have examined these associations through the lens of parents’ ethnotheories, which refer to parents’ implicit beliefs about children’s developmentally appropriate behavior. In contrast to prior work focused on parents’ ethnotheories of desirable behaviors and qualities, there has been a considerable lack of research examining ethnotheories about children’s maladaptive behavior. In this article, we address this gap in knowledge by examining cultural differences and similarities in Spanish and American parents’ beliefs about the causes of children’s maladaptive behaviors. A semi-structured interview was used to assess parents’ causal attributions of children’s internalizing and externalizing behaviors in a sample of 50 parents from the United States and 51 parents from Spain. Results revealed that US parents made more attributions to children’s internal states, social learning, and power motives than Spanish parents for externalizing behaviors. Conversely, Spanish parents made more attributions to attention seeking and material gains than US parents for the same behaviors. There were no cross-cultural differences in attributions for internalizing behaviors. Parents had strikingly different theories of children’s disruptive behaviors than they did for children’s internalizing behaviors. Differences in parents’ explanatory styles may reflect and maintain broader cultural differences between Spain and the United States. This study lends evidence to the growing literature on the relevance of parents’ ethnotheories in the context of child development and extends it to the topic of parental attributions regarding maladaptive child behaviors.

Optimization of pump transient energy characteristics based on response surface optimization model and computational fluid dynamics

The global energy shortage is increasingly becoming a problem of major concern worldwide. Since the pumps represent the largest part in the energy conversion devices, improving their energy characteristics is very important for energy conservation and efficiecy. However, the traditional pump design methods have generally overlooked the transient flow characteristics inside the pumps leading to high hydraulic losses and low operatinal efficiency, especially in applications that have pronounced transient effects. To address this problem, a novel approach is proposed in this paper which combines the response surface optimization method with the computational fluid dynamics (CFD) technology to optimize the energy characteristics of pumps during the transient processes. The main objective of the study is to enhance the internal flow state and the transient energy performance of the pump during the start-up process. A comparative analysis is conducted on the energy characteristics and the internal flow field of a model pump before and after the optimization, thereby validating the effectiveness of the proposed energy characteristics optimization method. The numerical results reveal that the inlet placement angle (α), the outlet placement angle (β), the blade envelope angle (φ), and the blade thickness coefficient (θ) significantly impact the weighted average head and weighted average efficiency of the pump. After optimization, the weighted average head and the weighted average efficiency of the pump increase by 2.97% and 8.91% respectively, while the transient efficiency of the pump at all times surpasses that of the traditional, non-otimized design approach. These research findings provide valuable insights for enhancing the performance of the pumps oerating in the transient flow conditions.

Multiscale Thermodynamics-Informed Neural Networks (MuTINN) towards fast and frugal inelastic computation of woven composite structures

The complex behavior of inelastic woven composites stems primarily from their inherent heterogeneity. Achieving accurate predictions of their linear and nonlinear responses, while considering their microstructures, appears feasible through the application of multi-scale modeling approaches. However, effectively incorporating these methodologies into real-scale applications, particularly within FE2 analyses, remains challenging due to the significant computational requirements they entail. To overcome this issue, while considering the scale effects, this study introduces an alternative approach based on Artificial Neural Networks (ANNs) to perform a macroscopic surrogate model of composites. This model, referred to as Multiscale Thermodynamics Informed Neural Networks (MuTINN), is founded on thermodynamic principles and introduces specific quantities of interest that serve as internal state variables at the macroscopic level. This captures efficiently the state and evolution laws governing the history-dependent behavior of these composites while retaining the thermodynamic admissibility and the physical interpretability of their overall responses. Moreover, to facilitate its numerical implementation within a FE code, a Meta-UMat has been developed, streamlining the application of multiscale FE×MuTINN approach for composite structure computations. The prediction capabilities of the proposed approach is demonstrated across the material scales, exemplified through diverse instances of woven composite structures. These applications account for anisotropic yarn damage and an elastoplastic polymer matrix behavior. The numerical results and the related comparison with experimental findings and FE computations demonstrate remarkable consistency across a wide range of non-proportional loading paths. This promises a potential solution to alleviate the computational challenges associated with multiscale simulations of large-scale composite structures.

A New Battery SOC/SOH/eSOH Estimation Method Using a PBM and Interconnected SPKFs: Part I. SOC and Internal Variable Estimation

Battery management systems (BMSs) are required to estimate many non-measurable values that describe the actual operating condition of batteries; such as the state of charge (SOC) or the state of health (SOH). In order to improve this evaluation, many physical states and parameters can be estimated using physics-based models (PBMs). These estimates could be used to improve the control and prognosis of batteries. In a series of papers we propose a new method to estimate the internal physical states, the SOC, the SOH and the electrode-specific state of health (eSOH) parameters of a lithium-ion battery, using interconnected sigma-point Kalman filters (SPKFs) and a single-particle model with electrolyte dynamics (SPMe). This first paper focuses on state estimation for non-aged cells. To begin, we describe and validate our electrochemical model against a high-fidelity P2D model. The interconnected SPKF algorithm is then described and the observability of our system is analyzed, showing that the interconnected estimator approach improves an observability measure of the system. Finally, the results of the estimator are discussed, comparing the estimated variables with the truth values under initialization, measurement and modeling uncertainties. The results show that the algorithm can estimate the internal battery states with high accuracy.

Conditioned preferences: Gated by experience, context, and endocrine systems

Central to the navigation of an ever-changing environment is the ability to form positive associations with places and conspecifics. The functions of location and social conditioned preferences are often studied independently, limiting our understanding of their interplay. Furthermore, a de-emphasis on natural functions of conditioned preferences has led to neurobiological interpretations separated from ecological context. By adopting a naturalistic and ethological perspective, we uncover complexities underlying the expression of conditioned preferences. Development of conditioned preferences is a combination of motivation, reward, associative learning, and context, including for social and spatial environments. Both social- and location-dependent reward-responsive behaviors and their conditioning rely on internal state-gating mechanisms that include neuroendocrine and hormone systems such as opioids, dopamine, testosterone, estradiol, and oxytocin. Such reinforced behavior emerges from mechanisms integrating past experience and current social and environmental conditions. Moreover, social context, environmental stimuli, and internal state gate and modulate motivation and learning via associative reward, shaping the conditioning process. We highlight research incorporating these concepts, focusing on the integration of social neuroendocrine mechanisms and behavioral conditioning. We explore three paradigms: 1) conditioned place preference, 2) conditioned social preference, and 3) social conditioned place preference. We highlight nonclassical species to emphasize the naturalistic applications of these conditioned preferences. To fully appreciate the complex integration of spatial and social information, future research must identify neural networks where endocrine systems exert influence on such behaviors. Such research promises to provide valuable insights into conditioned preferences within a broader naturalistic context.

Sound elicits stereotyped facial movements that provide a sensitive index of hearing abilities in mice

Sound elicits rapid movements of muscles in the face, ears, and eyes that protect the body from injury and trigger brain-wide internal state changes. Here, we performed quantitative facial videography from mice resting atop a piezoelectric force plate and observed that broadband sounds elicited rapid and stereotyped facial twitches. Facial motion energy (FME) adjacent to the whisker array was 30 dB more sensitive than the acoustic startle reflex and offered greater inter-trial and inter-animal reliability than sound-evoked pupil dilations or movement of other facial and body regions. FME tracked the low-frequency envelope of broadband sounds, providing a means to study behavioral discrimination of complex auditory stimuli, such as speech phonemes in noise. Approximately 25% of layer 5-6 units in the auditory cortex (ACtx) exhibited firing rate changes during facial movements. However, FME facilitation during ACtx photoinhibition indicated that sound-evoked facial movements were mediated by a midbrain pathway and modulated by descending corticofugal input. FME and auditory brainstem response (ABR) thresholds were closely aligned after noise-induced sensorineural hearing loss, yet FME growth slopes were disproportionately steep at spared frequencies, reflecting a central plasticity that matched commensurate changes in ABR wave 4. Sound-evoked facial movements were also hypersensitive in Ptchd1 knockout mice, highlighting the use of FME for identifying sensory hyper-reactivity phenotypes after adult-onset hyperacusis and inherited deficiencies in autism risk genes. These findings present a sensitive and integrative measure of hearing while also highlighting that even low-intensity broadband sounds can elicit a complex mixture of auditory, motor, and reafferent somatosensory neural activity.

Psychotherapy unchained: The Comprehend, Cope and Connect approach

The role of the Comprehend, Cope and Connect model in embedding a psychotherapeutic approach throughout a team, and making such an approach available to those with severe mental health problems, is outlined. The model is explained: its starting point in felt sense; its distributed model of the self, and its co-produced, trauma informed formulation that leads to new ways of coping with the internal state, which can be supported by a wider team. The way in which this makes a psychotherapeutic approach, with emphasis on the power of relationship, available to acute psychiatric and other services providing for those with severe mental health problems, is outlined. The inclusion of spirituality and its applicability to diverse populations is also covered, along with its, so far limited, research base.

Compaction elastoplastic damage constitutive model of rock under hydro-mechanical coupling: A heuristic modeling method based on internal state variables theory

Based on the internal state variables (ISV) theory, this paper employs a heuristic modeling approach to investigate the compaction elastoplastic damage constitutive model of rocks under hydro-mechanical coupling. The heuristic modeling method demonstrated herein can seamlessly integrate with existing constitutive theories, facilitating a broader spectrum of research on hydro-mechanical coupling constitutive models. Furthermore, a numerical solution was conducted in the principal axes via stress spectrum decomposition, which can well reflect the distinct characteristics of compaction deformation and the influence of water pressure on rock stress distribution. Utilizing the classic Drucker-Prager (D-P) criterion, the modeling method and numerical algorithm were implemented to derive a hydro-mechanical coupling compaction elastic–plastic damage constitutive model. This contribution expands the application domain of the classic D-P criterion within the context of hydro-mechanical coupling environments. The rationality of the model was confirmed through compression test data under various water pressures and confining pressures. Water pressure increases nonlinear compaction deformation by changing the opening degree of microcracks under low confining pressure, which has not been paid enough attention in existing research. This study thoroughly considers the influence of water pressure on compaction deformation. The developed process of “heuristic modeling method-numerical method-model application” is helpful for enriching the constitutive theory of rock under hydro-mechanical coupling.

Defects engineering and interface regulation on nickel-rich sulphides promoting water/urea/ethanol electrooxidation

Design and fabrication of high-efficiency nickel-rich electrocatalytic materials for sluggish oxygen evolution reaction (OER) remains a tremendous challenge. Modulating internal electronic state and accelerating charge transfer are two of vital means to optimizing electrocatalysts. In this work, nanoparticles-rich Fe-(CeS2/Ni3S2) hybrid material with abundant heterointerfaces and sulfur-defects are facilely synthesized. The strategy of iron dopant is conducive to induce more sulfur defects. The cerium species can modulate the internal electronic state and stabilize some of the surface sulphide against self-oxidation during OER process. This self-supported heterogeneous material requires overpotentials of 254 and 372 mV to reach the current densities of 100 and 500 mA cm−2 in alkaline condition. The addition of urea or ethanol to the bath solution has been demonstrated as an efficient strategy for reducing the onset potential and decreasing energy consumption, thereby confirming the feasibility of applying this approach to energy-saving hydrogen production through electrolysis wastewater splitting.

Novel hyper-viscoelastic approach to modelling elastomer mechanic behaviour with relaxation spectrum

Elastomers, such as polyurethane, exhibit hyperelastic behaviour and distinct rate dependence under a wide range of strain rates. Herein, a methodology for developing a hyper-viscoelastic constitutive model for succinctly characterising the mechanical behaviour of polyurethane under large deformations and a wide range of strain rates is proposed. The model is constructed using a long-term hyperelastic formulation combined with a rate-dependent viscoelastic model. This model is based on internal state variables and a finite strain formulation. A polyurethane elastomer was used as a sample to develop this model, by way of testing wide strain-rate mechanical behaviour (0.001–5000s−1) and viscoelastic behaviour. The viscoelastic behaviour was obtained using the equivalent time–temperature superposition relation. A parameter-fitting algorithm was adopted to separate the long-term behaviour from the viscoelastic behaviour. The long-term behaviour was modelled using a Mooney–Rivlin hyperelastic model, and its parameters were identified using the least-squares method. The time-dependent viscous effect calculated using the Prony series-based model was approximately determined based on the continuous relaxation spectrum. The characterisation capacity was confirmed through a thorough comparison with experimental curves. This model can be extended to other elastomers, even under tension, without any specific limitations of the internal components.

JustSTART: How to Find an RSA Authentication Bypass on Xilinx UltraScale(+) with Fuzzing

Fuzzing is a well-established technique in the software domain to uncover bugs and vulnerabilities. Yet, applications of fuzzing for security vulnerabilities in hardware systems are scarce, as principal reasons are requirements for design information access, i.e., HDL source code. Moreover, observation of internal hardware state during runtime is typically an ineffective information source, as its documentation is often not publicly available. In addition, such observation during runtime is also inefficient due to bandwidth-limited analysis interfaces, i.e., JTAG, and minimal introspection of hardware-internal modules.In this work, we investigate fuzzing for Xilinx 7-Series and UltraScale(+) FPGA configuration engines, the control plane governing the (secure) bitstream configuration within the FPGA. Our goal is to examine the effectiveness of fuzzing to analyze and document the opaque inner workings of FPGA configuration engines, with a primary emphasis on identifying security vulnerabilities. Using only the publicly available hardware chip and dispersed documentation, we first design and implement ConFuzz, an advanced FPGA configuration engine fuzzing and rapid prototyping framework. Based on our detailed understanding of the bitstream file format, we then systematically define 3 novel key fuzzing strategies for Xilinx FPGA configuration engines. Moreover, our strategies are executed through mutational structure-aware fuzzers and incorporate various novel custom-tailored, FPGA-specific optimizations to reduce search space. Our evaluation reveals previously undocumented behavior within the configuration engine, including critical findings such as system crashes leading to unresponsive states of the whole FPGA. In addition, our investigations not only lead to the rediscovery of the recent starbleed attack but also uncover a novel unpatchable vulnerability, denoted as JustSTART (CVE-2023-20570), capable of circumventing RSA authentication for Xilinx UltraScale(+). Note that we also discuss effective countermeasures by secure FPGA settings to prevent aforementioned attacks.

Automatic Railway Gate Controlling and Smart System Railway Gate Crossing System

Internet of Things (IOT) is the network of physical objects that contain embedded technology to communicate and sense or interact with their internal states or the external environment and transfers data over a network without requiring human- to-human or human-to-computer interaction. This paper presents a highly sensitive and more secure management system for bus transport with a help of PIC microcontroller and various sensors. The proposed system provides information regarding moving bus to the owner of bus who is located outside the bus based on IOT. Major aim is to transport information like number of non-ticket holders in a bus, accident occurrent places, location of moving bus, fuel level in bus and running speed of bus, pressure level in tires to a bus owner who is outside the bus based on IOT.

Multisource disturbances rejection control for linear systems with unmeasured states under process and measurement disturbances

In this paper, a multisource disturbances attenuation and rejection control method is proposed for linear systems with unmeasured states under process and measurement disturbances. Since some internal states of control systems are hard to be measured via sensors in the realistic engineering process, a novel output feedback control scheme is proposed for designing the anti-disturbance controller by using measurement outputs, although these outputs mix with measurement disturbances. In addition, the dynamics of control system states also suffer from the influence of multiple process disturbances. To enhance the anti-disturbance ability of control systems, two kinds of disturbance observers are adopted to estimate process and measurement disturbances, respectively. And the anti-disturbance output feedback controller is constructed based on the process disturbance observer, state observer and H∞ control theory. In which the state observer is built via the measurement outputs and measurement disturbance observer. Then, the linear matrix inequality technology is used for analyzing the stability of closed-loop systems and decoupling the observers and the controller. Finally, the effectiveness of proposed control scheme is verified by using a numerical example.

Internal state language factor structure and development in toddlerhood: Insights from WordBank.

Internal state language (ISL) research contains knowledge gaps, including dimensionality and predictors of growth, addressed here in a two-aim study. Parent-reported expressive language from N = 6,373 monolingual, English-speaking toddlers (Mage = 23.5mos, 46% male, 57% white) was collected using cross-sectional and longitudinal data in WordBank. Exploratory and confirmatory factor analyses suggested a best-fitting one-factor model of ISL. The single-factor model of ISL was then submitted to hierarchical linear modeling to evaluate predictors of ISL development. Age 2 ISL production was predicted by child sex, wherein females outperform males, and maternal education, wherein higher education contributes to higher ISL. Only maternal education emerged as a significant predictor of ISL growth. These results provide support to theory suggesting a unitary construct of ISL, as opposed to considering ISL as categorical, and further illustrate linear growth through the second postnatal year that varies as a function of child sex and maternal education.

Modeling the Evolution of the Dislocation Density and Yield Stress of Al over a Wide Range of Temperatures and Strain Rates

This paper introduces an extended model for the evolution of internal and wall dislocation densities in pure aluminum during plastic deformation. The approach takes the three internal state variables (3IVM) model as a starting point and advances it by taking into account the dynamic annihilation of immobile/locked dislocations as well as dislocations stored in the subgrain/cell walls. The strength of the material, as one of the properties affected by dislocation density, is used to validate the model. Experimental flow curves for pure Al are taken as the basis for calibration. Compression tests are performed at temperatures from − 196 °C to 500 °C with strain rates of 1, 0.1, and 0.01 s−1. The effect of temperature and strain rate on each state parameter is illustrated and discussed.

A comprehensive assessment indicator of the water-energy-food nexus system based on the material consumption relationship

The input–output relationships among material, energy, and information within the water, energy, and food subsystems are intricately interwoven, constituting an integrated system vital for sustainable development. Various water-energy-food (WEF) nexus indicators have been applied to evaluate the system's internal relationships and state. Nevertheless, these methods fail to aggregate the internal relationships into an indicator. This study proposes a WEF nexus indicator that incorporates the interconsumption into the system using the material flow analysis. The interconsumption consists of energy consumption in the food and water subsystems, water consumption in the energy and food subsystems, and food consumption in the energy subsystem. Moreover, the major factors were identified by the sensitivity factor method. The three countries (Tajikistan, Uzbekistan and Turkmenistan) in the Amu Darya River (ADR) basin exhibit strong interactions in the WEF nexus system, are chosen as a case study. Our results show that in 1992–2018, Uzbekistan's food subsystem consumed the most energy among the three countries; the energy consumption within the water subsystem displays an upward trend across all three countries; the water consumption in the energy subsystem of Tajikistan and Uzbekistan is 2–4 times greater than that in Turkmenistan; and the water withdrawals for agriculture within the three countries have remained relatively stable. The composite index in three countries exhibits an upward trend, with the most pronounced increase occurring in Turkmenistan. Uzbekistan has the strongest WEF nexus relationship, with a WEF nexus index that was 2–3 times greater than that of Tajikistan and Turkmenistan. The most important subsystem of Tajikistan and Turkmenistan is the energy subsystem; however, water resources are the major factors in Uzbekistan. The introduced indicator enables a comparison of the WEF system between regions and temporal variations in a certain region. It can provide intuitive and effective data support for WEF nexus system management.

Self‐objectification and sexual dysfunction among women: Testing and extending objectification theory

AbstractObjectification theory predicts that women's self‐objectification should lead to sexual dysfunction, yet previous studies failed to provide consistent support for this prediction. The present research—which used two sufficiently powered samples and a self‐objectification measurement (SOBBS) with improved psychometric qualities and content validity than previous measurements—found support for the expected association between self‐objectification and sexual dysfunction among heterosexual women in Israel and the United States (N = 404 and 366, Mage = 30.59 and 36.93, respectively). We also examined two novel potential mediators of this association, entitlement for pleasure and sexual agency (i.e., the capability to express sexual desires and boundaries), and found that the latter mediated the link between self‐objectification and sexual dysfunction. The mediators originally proposed by objectification theory (i.e. appearance anxiety, body shame, awareness of internal body states and flow) failed to mediate this link. Theoretical and methodological implications are discussed.

Dissociable encoding of motivated behavior by parallel thalamo-striatal projections

The successful pursuit of goals requires the coordinated execution and termination of actions that lead to positive outcomes. This process relies on motivational states that are guided by internal drivers, such as hunger or fear. However, the mechanisms by which the brain tracks motivational states to shape instrumental actions are not fully understood. The paraventricular nucleus of the thalamus (PVT) is a midline thalamic nucleus that shapes motivated behaviors via its projections to the nucleus accumbens (NAc)1,2,3,4,5,6,7,8 and monitors internal state via interoceptive inputs from the hypothalamus and brainstem.3,9,10,11,12,13,14 Recent studies indicate that the PVT can be subdivided into two major neuronal subpopulations, namely PVTD2(+) and PVTD2(-), which differ in genetic identity, functionality, and anatomical connectivity to other brain regions, including the NAc.4,15,16 In this study, we used fiber photometry to investigate the invivo dynamics of these two distinct PVT neuronal types in mice performing a foraging-like behavioral task. We discovered that PVTD2(+) and PVTD2(-) neurons encode the execution and termination of goal-oriented actions, respectively. Furthermore, activity in the PVTD2(+) neuronal population mirrored motivation parameters such as vigor and satiety. Similarly, PVTD2(-) neurons also mirrored some of these parameters, but to a much lesser extent. Importantly, these features were largely preserved when activity in PVT projections to the NAc was selectively assessed. Collectively, our results highlight the existence of two parallel thalamo-striatal projections that participate in the dynamic regulation of goal pursuits and provide insight into the mechanisms by which the brain tracks motivational states to shape instrumental actions.

Isotope data-constrained hydrological model improves soil moisture simulation and runoff source apportionment

Multiple-objective calibration helps constrain the parameter uncertainties and improve the performances of hydrological models. Previous studies have indicated that calibration toward soil moisture data could improve the streamflow simulation, but its influence on the runoff source apportionment quantification still needs to be analyzed. Meanwhile, although isotope calibration has proved to improve the representation of internal hydrological processes, the value of isotope on the simulation of internal state variables such as soil moisture has yet to be examined. This study utilized the tracer-aided hydrological model THREW-T (Tsinghua Representative Elementary Watershed – Tracer-aided version) in two mountainous basins on the Tibetan Plateau (The Upper Brahmaputra and Upper Yangtze basins) to evaluate the value of soil moisture and isotope data on model calibration. The result shows that: (1) The THREW-T model produced good simulation on streamflow, snow cover area, soil moisture, and stream water isotope simultaneously in the two study areas. Calibration toward soil moisture and isotope caused slight (∼0.03) but statistically significant (p < 0.01) decrease on the Nash-Sutcliffe coefficient of streamflow simulation compared to the baseline calibration variant only toward streamflow. (2) Calibration toward soil moisture brought no improvement to streamflow simulation for the validation period and stations in both basins, only improving soil moisture simulation. However, calibration toward the isotope improved the simulations of internal streamflow and soil moisture's spatiotemporal variation. (3) Different calibration variants resulted in different estimations of the runoff source apportionment, and independent evidence indicated that the results obtained by isotope calibration were most reasonable. Calibrations toward streamflow and soil moisture underestimated and overestimated the contributions from subsurface runoff, respectively. Isotope was the most sensitive objective to the runoff source apportionment and significantly reduced the uncertainty. Our study found a lower value of soil moisture data than the isotope on model calibration. However, we believe that the full potential of soil moisture data was not utilized due to the current limitations in soil moisture simulation and measurement methods, and the development of relevant technologies will make the soil moisture data more valuable for model calibration.

Dietary E. coli promotes age-dependent chemotaxis decline in C. elegans

An animal’s ability to sense odors declines during aging, and its olfactory drive is tuned by internal states such as satiety. However, whether internal states modulate an age-dependent decline in odor sensation is unknown. To address this issue, we utilized the nematode Caenorhabditis elegans and compared their chemotaxis abilities toward attractive odorants when aged under different dietary conditions. Feeding with the standard laboratory diet, Escherichia coli attenuated the chemotaxis ability toward diacetyl, isoamyl alcohol, and benzaldehyde when aged. On the other hand, feeding with either the lactic acid bacteria Lactobacillus reuteri or food deprivation selectively maintained the chemotaxis ability toward diacetyl. Our results suggest that ingestion of E. coli causes age-dependent chemotaxis decline. The changes in the chemotaxis behavior are attributed to the different expressions of diacetyl receptor odr-10, and the chemotaxis behavior of aged animals under food deprivation is shown to be dependent on daf-16. Our study demonstrates the molecular mechanism of how diet shapes the trajectory of age-dependent decline in chemosensory behaviors.