Dependence Behavior Research Articles

Unveiling the impact of Ni doping on the structural, electronic, and magnetic properties of nanocrystalline FeCo2O4spinel oxide: a combined experimental andab initioinvestigations.

In the present work, nanocrystalline samples of compositionsNixFe1-xCo2O4(x= 0.0, 0.25, 0.50, and 0.75) have been synthesized via co-precipitation method by annealing at 900 °C. The nanocrystalline samples of compositions Ni0.25Fe0.75Co2O4(D0.25) and Ni0.5Fe0.5Co2O4(D0.5) crystallizes in a pure spinel phase, whereas Ni0.75Fe0.25Co2O4(D0.75) show the existence of secondary phase of NiO, as confirmed by the x-ray diffraction analysis. The particle size and lattice strain in the samples both decrease as Ni substitution has increased. The field-dependent dc magnetizationM(H) virgin curve measured at 5 K for sample D0.75shows the existence of field-induced metamagnetic transition, while this behavior is absent in samples D0.5and D0.25. Dynamic magnetic properties have been investigated by ac susceptibility measurement, which shows a strong frequency dependence behavior resulting from the blocking/spin-glass freezing states depending upon the amount of Ni substitution and the range of measurement temperature. High-resolution x-ray photoelectron spectroscopy analysis reveals the presence of mixed valence states of Fe2+/Fe3+, Co2+/Co+3, and Ni2+/Ni+3in all samples. Using first principles-based density functional theory calculations with HSE06 exchange-correlation functional predicts the correct description of the ground state, which is ferrimagnetic and insulating in their inverse spinel case for D0.25, D0.5, and D0.75samples that agreed well with our experimental observations. A closer look at the electronic structure near the Fermi level (EF) of Ni-doped samples suggests a typical Mott-Hubbard insulating state while it is found to be a mixture of charge-transfer and Mott-Hubbard insulating state for parent compound FeCo2O4. The obtained spin-dependent gap hierarchy can have possible applications in spintronics. We have studied a detailed correlation between experiment and theory.

Smartphone Addiction Reviewed from Big Five Personality in College Students

Smartphones have many advantages, but can also cause detrimental effects, namely addiction. Smartphone addiction is a behavior of dependence on smartphones which can cause various problems in students' lives. Personality traits are closely related to addictive behavior. The personality theory most used to uncover addiction is the Big Five Personality. This research aims to determine the relationship between the Big Five personality dimensions and smartphone addiction in students. This research is a quantitative correlation research. The sample in this study amounted to 325 respondents obtained using purposive sampling. Data was taken using the SAS (Smartphone Addiction Scale) and BFI (Big Five Inventory) scales. The analysis technique uses the Spearman rank test. The results show that the dimensions of conscientiousness (0.001<0.05), extraversion (0.006<0.05), and neuroticism (0.001<0.05) have a significant relationship with smartphone addiction while Openness to experience (0.175>0.05) and agreeableness (0.367>0.05) doesn't have a significant relationship with smartphone addiction in students.

Driving factors for the peculiar bond length dependence and tetragonal distortion of (Ag,Cu)(In,Ga)Se2 and other chalcopyrites

Abstract The chalcopyrite alloy (Ag,Cu)(In,Ga)Se2 is a highly efficient thin film solar cell absorber, reaching record efficiencies above 23%. Recently, a peculiar behavior in the bond length dependence of (Ag,Cu)GaSe2 was experimentally proven. The common cation bond length, namely Ga–Se, decreases with increasing Ag/(Ag + Cu) ratio even though the crystal lattice expands. This is opposite to the behavior observed for Cu(In,Ga)Se2, where all bond lengths increase with increasing lattice size. To better understand this peculiar bond length behavior, element-specific bond lengths of (Ag,Cu)InSe2 and Ag(In,Ga)Se2 alloys are determined using extended x-ray absorption fine structure spectroscopy. They show that the peculiar bond length dependence occurs only for (Ag,Cu) alloys, independent of the species of common cation (In or Ga). The bond lengths are used to determine the anion displacements and to estimate their contribution to the bandgap bowing. Again, both behaviors differ significantly depending on the type of alloyed cation. A valence force field approach, relaxing bond lengths and bond angles, is used to describe the structural distortion energy for a comprehensive set of I–III–VI2 and II–IV–V2 chalcopyrites. The model reveals bond angle distortions as main driving factor for the tetragonal distortion and reproduces the literature values with less than 10% deviation. In contrast, the peculiar bond length dependence is not reproduced, demonstrating that it originates from electronic effects beyond the scope of this structural model. Thus, a fundamental understanding of bond length behavior and tetragonal distortion is achieved for chalcopyrite materials, benefiting their technological applications such as high efficiency thin film photovoltaics.

Quantitative theoretical analysis of the electrostatic force between a metallic tip and semiconductor surface in Kelvin probe force microscopy

Theoretical analysis of the electrostatic force between a metallic tip and semiconductor surface in Kelvin probe force microscopy (KPFM) measurements has been challenging due to the complexity introduced by tip-induced band bending (TIBB). In this study, we present a method for numerically computing the electrostatic forces in a fully three-dimensional (3D) configuration. Our calculations on a system composed of a metallic tip and GaAs(110) surface revealed deviations from parabolic behavior in the bias dependence of the electrostatic force, which is consistent with previously reported experimental results. In addition, we show that the tip radii estimated from curve fitting of the theory to experimental data provide reasonable values, consistent with the shapes of tip apex observed using scanning electron microscopy. The 3D simulation, which accounted for the influence of TIBB, enables a detailed analysis of the physics involved in KPFM measurements of semiconductor samples, thereby contributing to the development of more accurate measurement and analytical methods.&#xD.

Stability of the first-order character of phase transition in HoCo2

HoCo2 exhibits a giant magnetocaloric (MC) effect at its first-order magnetostructural phase transition around 77 K, and understanding the thermodynamic nature of this transition in response to external magnetic fields is crucial for its MC applications. In this study, we present a comprehensive investigation of specific heat and magnetization measurements of HoCo2 under varying magnetic fields. The specific heat measurements qualitatively indicate a transformation from first- to second-order behavior of this phase transition at higher magnetic fields. However, analysis of the power-law dependence of the magnetic entropy change (ΔSM∝Hn) and the breakdown of universal behavior in the temperature dependence of ΔSM suggest that the first-order nature remains intact, even up to 7 T. This stability of the first-order nature is further manifested through the distinctive non-linear behavior of modified Arrott plots, with a negative slope in the 6–7 T range.

State of Health Prediciton Model for LFP/Graphite Type Lithium-Ion Batteries Based on Discharge Curve Analysis

Introduction To improve reliability and maximize lifespan of products loading lithium-ion batteries (LIBs), development of internal state diagnosis and life prediction technology for LIBs are desired. In our previous research, we reported discharge curve analysis (DCA) as diagnosis method for internal state of LIBs and life prediction technique based on DCA results 1), 2). In DCA, by separating discharge capacity (Q) – open circuit voltage (OCV) curve and Q – resistance (R) curve of a battery into those of positive and negative electrode, we can quantitatively evaluate how positive and negative electrodes and electrolyte are degraded. Since development of DCA has focused on NMC/graphite type LIBs whose voltage change continuously over SOC, it is necessary to extend the DCA methodology to two-phase coexisting materials which have plateau potential, such as LFP/graphite type LIBs that have been attracting attention recently.Based on the above background, we developed extended DCA, which can be applicable to two-phase coexisting materials by combining Q-OCV curve and Q-R curve analysis3). In this paper, we report the results of constructing state of health (SOH) prediction model based on the extended DCA results. Experimental Commercially available LFP/graphite type cylindrical cells were tested in various calendric and cycling aging conditions. Then, galvanostatic intermittent titration technique (GITT) measurement was performed regularly which repeat pulse discharge and rest from SOC=100% to 0%. By analyzing the GITT measurement data, Q-OCV curve V(Q) and Q-R curve R(Q) of cells were obtained in each test period. LFP and graphite half cells with Li metal as counter electrode were manufactured and tested similar GITT measurement. Then Q-OCV curves (Vp (qp ) and Vn (qn )) and Q-R curves (rp (qp ) and rn (qn )) of each LFP and graphite were obtained. In the extended DCA, Q-OCV curve of a cell was calculated from Eq. (1) and (2) and Q-R curve of a cell was calculated form Eq. (1) and (3). Then each calculated curve was fitted to the actual measured curve with mp , mn , δp , δn , ap , an and R0 as variable parameters and the values of those parameters were determined. Q = mpqp - δp = mnqn - δn -Eq. (1) V(Q) = Vp (qp ) - Vn (qn )-Eq. (2) R(Q) = ap /mp *rp (qp ) + an /mn *rn (qn ) + R0 -Eq. (3) mp, mn Amount of active materials [g]δp, δn Electrode capacity outside of cell voltage [Ah]qp, qn Discharge capacity of electrodes [Ah/g]ap, an Coefficent of rp and rn [-]Vp, Vn OCV of electrodes [V]R0 Ohmic resistance [Ω]rp, rn Resistance of electrodes [Ωg]-- *p or n as a subscription represent positive or negative electrode. SOH prediction model was constructed by modeling the time series data of above seven parameters determined by extended DCA. Each parameter was fitted with a time function using a power law and the coefficients within the function were expressed as polynomials with the test conditions (temperature, SOC and C-rate). Using the predicted values of each parameter obtained from time functions, SOHQ and SOHR were predicted. Results and Discussions The SOHQ and SOHR prediction accuracy of LFP/graphite type cells is shown in Fig. 1. The time dependence behavior of SOHQ and SOHR prediction error in calendric aging is shown in (a) and (b) and in cycling aging is shown in (c) and (d). As shown in (a) and (b), both SOHQ and SOHR can be predicted with an error less than 5pt in calendric aging by constructing the model using the first half of test period as training data. As shown in (c) and (d), developed model can predict SOHQ with a prediction error less than 5pt and SOHR with a prediction error under 7pt in cycling aging. Conclusion In this report, we developed SOH prediction model for LFP/graphite type cells by converting quantitative parameters obtained by extended DCA into time functions. As a result, the developed SOH prediction model could predict SOHQ and SOHR with an error less than 5pt in calendric aging, and less than 5pt for SOHQ and 7pt for SOHR in cycling aging.In the poster session, we will also report about the details of extended DCA method, aging trends of cells and the evaluation results of the time-split cross-validation of the developed SOH prediction model. References 1)K. Honkura et al., J. Power Sources, 196, 10141-10147(2011)2)K. Honkura et al., The Electrochemical Society of Japan, 89(2), 133-139 (2021)3)S. Nishijima et al., “Degradation state diagnosis of lithium-ion batteirs based on internal resistance properties”, The 63rd Battery Symposium in Japan, Fukuoka, Japan, Nov 2022 Figure 1

Individual Characteristics and Operator Dependence Behaviors in Human-Automation Interaction: An Exploratory Study

Understanding the impact of operator characteristics on human-automation interaction (HAI) is crucial as automation becomes pervasive. Despite extensive HAI research, the association between operator characteristics and their dependence on automation has not been thoroughly examined. This study, therefore, examines how individual characteristics affect operator dependence behaviors when interacting with automation. Through a controlled experiment involving 52 participants in a dual-task scenario, we find that operators’ decision-making style, risk propensity, and agreeableness are associated with their dependence behaviors when using automation. This research illuminates the role of personal characteristics in HAI, facilitating personalized team interactions, trust building, and enhanced performance in automated settings.

Neurobehavioral features in medication-overuse headache

BackgroundMedication-overuse headache (MOH) has been related to the spectrum of dependence behavior and impaired orbitofrontal cortex function. Alexithymia is a trait comprising deficits in identifying self-emotions and perception. It was the aim of the study to investigate impulsivity and alexithymia, in patients with MOH and perform correlations with cerebral grey matter. Material and methodsPatients with chronic migraine and MOH according to ICHD criteria from a tertiary headache clinic and healthy controls were investigated by a single psychiatrist, using clinical scales for self-control (BIS-11) and alexithymia (TAS-20) and screened for dependence based on DSM-IV criteria. Correlations of BIS-11 and TAS-20 with cerebral grey matter were analysed with the SPM based toolbox CAT12, using high resolution T1weighted MRI-Sequences acquired on a 3 T scanner. ResultsMRI data were available from 30 MOH patients (24 women) and 47 healthy controls (26 women). MOH patients had increased impulsivity (62.2 ± 11.1 vs. 55.7 ± 7.2; p = 0.007) and alexithymia (49.8 ± 14.8 vs. 38.0 ± 6.5; p < 0.001). Analyzing only women, the results remained significant. Ninety percent of patients fulfilled DSM-IV criteria for substance dependence. There was a positive correlation between impulsivity and grey matter in the left middle orbital gyrus in healthy controls but not in patients (p < 0.05, corrected). No correlations with alexithymia and cerebral grey matter were found. ConclusionsThe present study suggests a neurobehavioral basis for MOH, consisting of impaired impulse control, and self-perception along with features of substance dependence. Although decreased orbitofrontal cortex volume was confirmed in this MOH cohort, impulsivity and alexithymia were not correlated with this structural abnormality.

System and transcript dynamics of cells infected with severe acute respiratory syndrome virus 2 (SARS-CoV-2)

Statistical laws arise in many complex systems and can be explored to gain insights into their structure and behavior. Here, we investigate the dynamics of cells infected with severe acute respiratory syndrome virus 2 (SARS-CoV-2) at the system and individual gene levels; and demonstrate that the statistical frameworks used here are robust in spite of the technical noise associated with single-cell RNA sequencing (scRNA-seq) data. A biphasic fit to Taylor’s power law was observed, and it is likely associated with the larger sampling noise inherent to the measure of less expressed genes. The type of the distribution of the system, as assessed by Taylor’s parameters, varies along the course of infection in a cell type-dependent manner, but also sampling noise had a significant influence on Taylor’s parameters. At the individual gene level, we found that genes that displayed signals of punctual rank stability and/or long-range dependence behavior, as measured by Hurst exponents, were associated with translation, cellular respiration, apoptosis, protein-folding, virus processes, and immune response. Those genes were analyzed in the context of a protein-protein interaction network to find possible therapeutic targets.

Torque-speed relationship of the flagellar motor with dual-stator systems in Pseudomonas aeruginosa.

The single polar flagellar motor in Pseudomonas aeruginosa is equipped with two stator systems, MotAB and MotCD, both driven by H+ ions. The torque-speed relationship for flagellar motors with two stator systems has not been explored previously. In this study, we developed a method that utilizes optical trapping and fluorescence labeling to measure the torque-speed relationships for the wild-type P. aeruginosa motor with dual stators and mutant strains with a single stator system, revealing surprising differences in them. Moreover, we found that the MotAB stators exhibit slip-bond behavior in load dependence, contrasting with the catch-bond behavior of the MotCD stators and Escherichia coli stators. Further examination of the solvent isotope and pH effects on the torque-speed relationships of these stator systems provided additional insights into their dynamics. Interestingly, we discovered that the torque of the wild-type motor is similar to the combined torque of motors with MotAB or MotCD stators, indicating an additive contribution from the two stator types in the wild-type motors. These findings underscore the enhanced adaptability of P. aeruginosa to a wide range of external environments with varying load conditions.IMPORTANCEWe developed a novel method to measure the flagellar motor torque-speed relationship by trapping a swimming bacterium using optical tweezers. Using the P. aeruginosa flagellar motor as a model system to investigate motor dynamics with dual stator types, we measured the torque-speed relationships for wild-type motors with dual stator types and mutants with a single type. We found drastic differences that stem from the varying load dependencies of stator stability. These variations enable bacteria to rapidly adjust their stator composition in response to external load conditions. Interestingly, we observed that the torque of the wild-type motor is akin to the cumulative torque of motors with either stator type, indicating an additive contribution from the two stator types in wild-type motors. The methodology we established here can be readily employed to study motor dynamics in other flagellated bacteria.

Reliability analysis for binary Lévy degradation processes using characteristic functions

AbstractMany engineering systems experience complex degradation processes along with random shocks that often pose a risk to the safe and reliable operations of the system. The analysis of dependence among multiple degradation processes has been a challenging task in the field of reliability engineering. To study dependence behaviors and jump uncertainties among degradation processes, one of the effective approaches is to model these degradation processes using multidimensional Lévy subordinators. However, a critical obstacle arises in determining the convergent mathematical form of the reliability function under Lévy measures and distributions. To obtain a closed form of reliability function, this study investigates the Lévy measure and the characteristic function of multiple dependent degradation processes. Each degradation process is modeled by a one‐dimensional Lévy subordinator utilizing the marginal Lévy measure and characteristic function. The dependence among all dimensions is described by the Lévy copula and the associated multidimensional Lévy measure. For a two‐dimensional case, we derive the reliability function and probability density function (PDF) from the characteristic function and the inverse Fourier transform. Numerical examples are provided to demonstrate the proposed models for reliability and lifetime analysis of multidimensional degradation processes in engineering systems.

Solar Activity Dependence of Traveling Ionospheric Disturbance Amplitudes Using a Rapid‐Run Ionosonde in High Latitudes

AbstractWe investigated the amplitude of medium scale traveling ionospheric disturbances (MSTIDs, with periods 25–100 min) and their dependence on the solar activity using 16 years data of the rapid run‐ionosonde operating at high latitudes (N, Sodankylä, Finland). A deep learning neural network was applied to ionograms to extract critical frequency of the F2 region (foF2) with a 1 min time resolution. Then, we analyzed the relative amplitude of MSTIDs (i.e., foF2/foF2), which corresponds to the amplitude of atmospheric gravity waves (AGWs) causing MSTIDs. The amplitude of AGWs propagating upward increases with height due to the decreasing density of the air, and hmF2 varies depending on local time, seasonal and solar activity conditions. To account for this effect, we calculated a corrected MSTID amplitude by normalizing the relative amplitude for the air density at the hmF2. The corrected amplitudes show no clear dependence on F10.7 during winter (0–12 UT), equinox (20‐01 UT) and summer (19‐01 UT), while a positive dependence of corrected amplitudes on F10.7 was observed during winter and equinox, in 14–22 UT and 15–19 UT, respectively. Corresponding to the dependence behaviors of corrected and relative amplitudes, two likely mechanisms of MSTIDs, AGWs from the lower atmosphere and auroral sources, are inferred. Their subsequent roles in the solar activity dependence of MSTID amplitudes were separately discussed, although in reality, the observed dependence is complex and often involves several mechanisms together.

The impact of smartphone dependence on college students' sleep quality: the chain-mediated role of negative emotions and health-promoting behaviors.

Sleep disturbances among college students have become a significant issue affecting their daily lives. This study aims to explore the relationship between smartphone dependence and sleep quality and examine the mediating roles of negative emotions and health-promoting behaviors. A total of 23,652 college students were included in the study, and 21,314 valid questionnaires were collected. The survey assessed demographic factors, smartphone dependence, sleep quality, negative emotions, and health-promoting behaviors. A chain mediation analysis was conducted to examine the relationships among these factors. Smartphone dependence was significantly positively correlated with sleep quality (r = 0.272, p < 0.001) and negative emotions (r = 0.414, p < 0.001), and significantly negatively correlated with health-promoting behaviors (r = -0.178, p < 0.001). Sleep quality was positively correlated with negative emotions (r = 0.472, p < 0.001) and negatively correlated with health-promoting behaviors (r = -0.218, p < 0.001).Smartphone dependence was a significant positive predictor of sleep quality. Moreover, negative emotions and health-promoting behaviors influenced the relationship between smartphone dependence and sleep quality. The total effect, direct effect, and indirect effect values were 0.304, 0.122, and 0.170, respectively. Different demographic factors (such as gender and place of residence) can lead to variations in different variables. Smartphone dependence and negative emotions have a positive impact on sleep quality among college students, while health-promoting behaviors have a negative impact. Smartphone dependence directly and positively affects sleep quality and can also influence it indirectly through the mediating effects of negative emotions and health-promoting behaviors, both individually and in a chain-like manner.

Modeling the Tourism Market Behavior Based on Discrete Equilibrium Models “Supply – Price – Demand”

Abstract The work is devoted to the modeling of the behavior of the tourism market in the conditions of a supply random lag, distributed according to normal and uniform distribution laws. The behavior of dependences on the tourist market of supply and demand on the price is considered. The modeling of the behavior of the tourism market was carried out using a market dynamic model in the plane of variables “supply – price – demand” taking into account the interests of different groups of consumers, primarily from the point of view of pricing. The delay between changes in supply and demand volumes is taken into account using a Cobweb model. To test this method, information was collected on family expenses when traveling abroad (outbound tourism, tourist vacations lasting 7-15 days) by surveying the employees of 38 travel organizations as of 2021. Three segments of the tourism market are identified: low ($2000 − 4000), medium ($4000 − 12000), and VIP-segment ($12,000 − 20,000). The analysis of the modeling results showed that the behavior of tourists of different segments can significantly influence the market dynamics. The use of a Cobweb model allowed for determining the level of stability of tourist behavior and assessing the possibility of consumer migration from one segment to another. Sensitivity to price changes and response to new offers from different segments can be different, which is important for determining pricing strategies, marketing, and the development of new tourism products.

Calibrating Trust, Reliance and Dependence in Variable-Reliability Automation.

Trust and system reliability can influence a user's dependence on automated systems. This study aimed to investigate how increases and decreases in automation reliability affect users' trust in these systems and how these changes in trust are associated with users' dependence on the system. Participants completed a color identification task with the help of an automated aid, where the reliability of this aid either increased from 50% to 100% or decreased from 100% to 50% as the task progressed, depending on which group the participants were assigned to. Participants' trust, self-confidence, and dependence on the system were measured throughout the experiment. There were no differences in trust between the two groups throughout the experiment; however, participants' dependence behavior did follow system reliability. These findings highlight that trust is not always correlated with system reliability, and that although trust can often influence dependence, it does not always determine it.

Investigation of linear energy transfer (LET)-dependence behavior and dosimetric response of a flat-panel detector in pencil beam scanning proton therapy

PurposeThis study aims to elucidate the dependence of the flat-panel detector’s response on the linear energy transfer (LET) and evaluate the practical viability of employing flat-panel detectors in proton dosimetry applications through LET-dependent correction factors. MethodsThe study assessed the flat-panel detector’s response across varying depths using solid water and distinct 100, 150, and 200 MeV proton beams by comparing the flat-panel readings against reference doses measured with an ionization chamber. A Monte Carlo code was used to derive LET values, and an LET-dependent response correction factor was determined based on the ratio of the uncorrected flat-panel dose to the ionization chamber dose. The implications of this under-response correction were validated by applying it to a measurement involving a spread-out Bragg peak (SOBP), followed by a comparative analysis against doses calculated using the Monte Carlo code and MatriXX ONE measurement. ResultsThe association between LET and the flat-panel detector’s under-response displayed a positive correlation that intensified with increasing LET values. Notably, with a 10 keV/µm LET value, the detector’s under-response reached 50 %, while the measurement points in the SOBP demonstrated under-response greater than 20 %. However, post-correction, the adjusted flat-panel profile closely aligned with the Monte Carlo profile, yielding a 2-dimensional 3 %/3mm gamma passing rate of 100 % at various verification depths. ConclusionThis study successfully defined the link between LET and the responsiveness of flat-panel detectors for proton dosimetric measurements and established a foundational framework for integrating flat-panel detectors in clinical proton dosimetry applications.

Mind Over Matter: Effects of Digital Devices and Internet Dependence Perceptions and Behavior on Life Satisfaction in Singapore

Mind Over Matter: Effects of Digital Devices and Internet Dependence Perceptions and Behavior on Life Satisfaction in Singapore

Extracts of Prunella vulgaris Enhanced Pentobarbital-Induced Sleeping Behavior in Mice Potentially via Adenosine A2A Receptor Activity.

The increasing prevalence of sleep dysregulation cases has prompted the search for effective and safe sleep-enhancing agents. Numerous medications used in the treatment of sleep disorders function by enhancing γ-aminobutyric acid neurotransmitter activity. Unfortunately, these substances may induce significant adverse effects in chronic users, such as dependence and motor behavior impairments. Consequently, there is a growing interest in exploring therapeutic sleep-enhancing agents derived from natural sources, with the anticipation of causing less severe side effects. Prunella vulgaris (PV), a perennial plant indigenous to South Korea, exhibits various pharmacological effects, likely attributed to its chemical composition. Rosmarinic acid, one of its components, has previously demonstrated sleep-potentiating properties, suggesting the potential for PV to exhibit similar pharmacological effects. This study aims to investigate the potential effects of repeated administration of PV extract on the sleep behavior, brainwave activity, sleep-wake cycle, and physiological behavior of mice. Findings indicate that PV extracts exhibit sleep-enhancing effects in mice, characterized by prolonged sleep duration and a reduced onset time of pentobarbital-induced sleep. However, PV extracts only reduced alpha wave powers, with minor alterations in wakefulness and rapid-eye-movement sleep duration. In contrast to diazepam, PV extracts lack adverse effects on locomotor activity, motor coordination, or anxiety in mice. Receptor-binding assay and caffeine treatment support the potential involvement of adenosine A2A receptors in the effects of PV, suggesting distinct mechanisms of action compared to diazepam, despite both exhibiting sleep-altering effects. Overall, our results suggest that PV holds promise as a potential source of sleep-aiding agents.

Alcohol use and its associated factors among Ethiopian military personnel

BackgroundStudies indicate that alcohol use is more prevalent in the military and that such use is related to coping mechanisms for stress. Alcohol use could result in health and social...

Magnetization and exchange-stiffness constants of Fe–Al–Si alloys at finite temperatures: A first-principles study

We investigated the magnetic properties of Sendust (Fe-Al-Si) alloys not only at 0 K but also at finite temperatures by means of the first-principles calculations assuming A2, B2, and D03 structures. We confirmed that the itinerant characteristics of 3d electrons of Fe are not negligible and a significantly small exchange stiffness constant exists at zero temperature in a B2 structure. However, the calculated Curie temperatures are in the same order for all structures; this indicates that the Curie temperature cannot be determined only by the exchange interactions at zero temperature in itinerant electron systems. Temperature dependence of the exchange interaction, namely, spin configuration dependence, also might be important for determining it. In addition, this property might also be related to the unique behavior of the temperature dependence of the exchange stiffness constant for the B2 structure, which does not decrease monotonically as temperatures increase, contrary to the behavior expected from the Heisenberg model. In addition, we investigated composition dependence on the exchange stiffness constant at zero temperature and confirmed that the substitution of Si with Al could improve the amplitude of the exchange stiffness constant at zero temperature for all structures.