bluuebunny/crossref_metadata_2025 huggingface dataset:
A Transactional Analysis of Occupational Therapy in an Equine Environment for Youth with Autism Spectrum Disorder
Authors: Peters B. Caitlin , Bentele Christof , Wood Wendy
Published: October 2022

Existing empirical investigations of occupational therapy services that incorporate horses for youth with autism spectrum disorder (ASD) are limited by a lack of standardized protocols. The current study sought to support manualization of one approach to occupational therapy in an equine environment for youth with ASD (OTeeHORSPLAY), by vividly describing the intervention from a transactional perspective. Direct, real-time videos plus field notes of OTeeHORSPLAY were collected and then subjected to qualitative content analysis and descriptive statistical analysis. Analytical methods followed Ricoeur’s hermeneutic arc of naïve interpretation, explanation through structural analyses, and comprehensive description. Following this arc, we found many architectural spaces, sequences of occupational opportunities, and actions of practitioners and youth that fluidly shifted in relationship to one another. The results of this study will inform the development of intervention protocols that will be tested for feasibility, acceptability, and preliminary efficacy in future investigations of OTeeHORSPLAY.
Impacts of Dog Ownership and Attachment on Total and Dog-related Physical Activity in Germany
Authors: Benedikt Hielscher , Udo Ganslosser , Ingo Froboese
Published: October 2022

Dog ownership is related to physical activity. There could, however, be variances in the strength of this relationship between different cultures. The objective of the present study was to investigate activity behavior in dog owners (DOs) in Germany. Further, the association between dog ownership, attachment and physical activity was examined. Total physical activity, dog walking, and other dog-related activities were investigated using an online survey that was promoted in several social media groups. A German physical activity questionnaire (BSA-F) and the Lexington Attachment to Pets Scale (LAPS) were used. DOs display higher levels of total physical activity, total walking, and other physical activities than non-dog owners (nDOs). Several other dog-related activities were reported by DOs. The most prominent were retrieve work, ball games and agility. Attachment to one’s dogs was not related to total physical activity. However, attachment correlated with higher levels of time spent in dog-related physical activity and dog walking. It can be concluded that, in a German population, DOs are more physically active than nDOs. Attachment seems to correlate with type, but not quantity, of exercise in dog enthusiasts. Several dog-related activities were reported but information about them is still very limited. Therefore, future studies are needed to focus on the intensity and occurrence of these activities in a representative population of DOs in Germany.
Noah’s Syndrome: Systematic Review of Animal Hoarding Disorder
Authors: Nadal Zaida , Ferrari Mónica , Lora Julián , Revollo Alicia , Nicolas Florencia , Astegiano Santiago , Díaz Videla Marcos
Published: October 2022

Animal Hoarding Disorder (AHD) is a recently acknowledged psychiatric syndrome regarded as a form of Hoarding Disorder. Despite its great complexity, AHD has been underestimated both within and outside the academic community. This systematic review of the literature will assess some features to give a description of the syndrome. We have selected 26 empirical investigations which have been analyzed for such purpose. Moreover, we have estimated the mean values of some variables such as age (55.6 years old), gender (74.9% women), households (51.8% single-person), unemployment (53.6%), number of animals per case (64.1), presence of dead animals (32.9%) and object hoarding co-morbidity (59.5%). Results will be discussed to highlight AHD particular features, the need for an integrated view around the One Welfare concept and the need for an interdisciplinary approach. Given its complexity, we recommend acknowledging AHD as a separate nosographic entity.
The Human-Dog Bond as a Mediator in the Relationship Between Loneliness and Emotional Well-Being
Authors: Jane Allen Caroline , Hogg Rachel Caroline
Published: October 2022

Loneliness is prevalent in contemporary Western society and although it is commonly believed that pets can buffer owners against the effects of loneliness on emotional well-being, empirical research is limited. This study addressed the question of whether loneliness positively predicts the strength of the human-dog bond, and whether the human-dog bond mitigates the deleterious effects of loneliness on emotional well-being. A community sample of Australian pet-dog owners (
N
=639: 123 men, 516 women) aged 18-80 participated in the study. Loneliness was conceptualised as a tri-dimensional construct comprised of social-, family-, and romantic-loneliness, while emotional well-being was operationalised in terms of positive and negative affect. Higher social-loneliness and family-loneliness predicted higher negative affect, and higher levels of all three types of loneliness predicted lower positive affect. Higher levels of family-loneliness and romantic-loneliness predicted a stronger human-dog bond, which in turn predicted higher positive affect. No relationship was evident between the human-dog bond and either social-loneliness or negative affect. The human-dog bond mediated the relationship between family-loneliness and positive affect as well as the relationship between romantic-loneliness and positive affect. These mediating effects were of the suppressor-type, indicating that the human-dog bond mitigated the deleterious effects of family-loneliness and romantic-loneliness on positive affect. These findings demonstrate the importance of conceptualising loneliness as a multi-dimensional construct in future studies regarding loneliness and human-animal relationships.
Personal and Professional Perspectives on the Protective Role of Animals for Transgender Youth: A Qualitative Analysis
Authors: Wenocur Katharine , Matthews Michelle , Kotak Noopur
Published: October 2022

Youth who identify as transgender, gender non-conforming, or non-binary (TGNC) are at increased risk for mental health challenges including anxiety, depression, and suicidality; and social challenges including bullying, isolation, and lack of familial support. Best practices in promoting the social and emotional health of TGNC youth are continually evolving, and Animal Assisted Therapy (AAT) presents a compelling yet untested approach to meeting mental health needs of this population; a group AAT intervention might help TGNC youth who feel isolated to feel more connected and supported. This exploratory study sought to identify thematic content to be included in a future AAT group intervention geared towards TGNC youth, considering both the potential role of human-animal interactions and the identified needs of this population. Three focus groups were convened; one comprised of TGNC adults (N = 8), one of mental health clinicians with advanced training related to transgender mental health (N = 4), and one of certified Animal Assisted Play Therapists® (N = 5). The content of each group was coded thematically using modified grounded theory, and several subthemes emerged under broader themes of 1) the importance of animals in providing emotional support in general and 2) desired social supports that might be beneficial for TGNC youth. These themes inform discussion of possible next steps in the development of an AAT group for TGNC youth.
The Perception and Effect of Aggressive Dog Breeds on Human Social Interactions
Authors: Briones Elizabeth M. , Marshall Philip H.
Published: October 2022

During social interactions, one must be able to interpret social signals that convey information and respond appropriately to interactants. Several factors have been shown to influence decisions of interpersonal distance preferences; however, research has yet to determine the associative effects companion animals may have on social information processing during intended interactions. Previous research (
Briones et al., 2022
) distinguished between various breeds of dogs perceived to be higher or lower in aggression, and further showed that people had a greater tendency to interact with dogs perceived to be lower in aggression. The current studies (Study 1
n
= 174; Study 2
n
= 229) were an extension of that research and used computer-simulated avatar interactions to assess the influence of dog breeds and other factors on actual proxemic behavior during goal-related social interactions. Results showed that during social interactions, (a) interactants associated with dog breeds perceived higher in aggressiveness elicited larger interpersonal spaces; (b) closer interpersonal distances are maintained with friends than strangers; (c) greater affinity for dogs, in general, was related to closer proxemic distances; and (d) dog handlers taking the perspective of the approaching interactant results in greater interpersonal distances.
Effects of Human-Animal Interactions on Affect and Cognition
Authors: Thayer Elise R. , Stevens Jeffrey R.
Published: October 2022

Human-animal interaction has clear positive effects on people’s affect and stress. But less is known about how animal interactions influence cognition. We draw parallels between animal interactions and exposure to natural environments, a research area that shows clear improvements in cognitive performance. The aim of this study is to investigate whether interacting with animals similarly enhances cognitive performance, specifically executive functioning. To test this, we conducted two experiments in which we had participants self-report their affect and complete a series of cognitive tasks (long-term memory, attentional control, and working memory) before and after either a brief interaction with a dog or a control activity. We found that interacting with a dog improved positive affect and decreased negative affect (in one of the two experiments), stress, and anxiety compared to the control condition. However, we did not find effects of animal interaction on long-term memory, attentional control, or working memory. Thus, we replicated existing findings providing evidence that interacting with animals can improve affect, but we did not find similar improvements in cognitive performance. These results suggest that either our interaction was not of sufficient dose or timed appropriately to elicit effects on cognition or the mechanisms underlying effects of human-animal interaction on cognition differ from effects generated by other cognition-enhancing interventions such as exposure to nature. Future research should continue to increase knowledge of the connection between nature exposure and human-animal interaction studies to build our understanding of cognition in response to animal interactions.
Strengthening Zooeyia: Understanding the Human-Animal Bond between Veterans Living with Comorbid Substance Use and Posttraumatic Stress Disorder and their Service Dogs
Authors: Williamson L. E. , Dell C. A. , Chalmers D. , Cruz M. , De Groot P.
Published: October 2022

Zooeyia includes the potential benefits that interactions and relationships with companion animals can bring to human health. These potential benefits have been grouped into four components to describe the means through which they may occur: pets as builders of social capital, agents of harm reduction, motivators for health behavior change, and active participants in treatment plans. This construct has been used to examine the human-animal bond (HAB) and understand animal-assisted interventions. It has not, however, been intentionally applied within the context of military Veterans with posttraumatic stress disorder and comorbid substance use paired with Service Dogs (SD). A qualitative approach to analysis using zooeyia was applied to data collected during an exploratory patient-oriented, time-series research design with Veterans teamed with SDs through a national holistic Canadian training program. All four components of zooeyia were present in the experiences of Veterans with SDs; SDs were builders of social capital, agents of harm reduction, motivators for health behavior change, and active participants in treatment plans. While Veterans working with SDs reported many benefits, the pairs also experienced specific complex challenges, beyond the expected concerns for a household pet. The human-animal relationship between Veterans in this study and their SDs, and the subsequent growing bond, is a key contributing component and step to the strengthening of zooeyia. This analysis of zooeyia extends our understanding of how SDs support veterans’ health, including better management of PTSD and problematic substance use. Because the HAB is reciprocal, this analysis also challenges One Health to recognize and embrace concerns for animal welfare.
All-dielectric ultra broadband MIMO Luneburg lens with sub-diffraction resolution
Authors: He Xudong , Chen Jin , Chen Mingji , Chu Hongchen , Lai Yun , Fang Daining
Published: October 2022

A 3D-printed ultra-broadband planar Luneburg lens composed of periodic gradient structures is proposed in this paper. Compared to the previous studies, the proposed lens has a pretty large operating frequency range, spanning from 5 to 22 GHz. The measured results of the near-field and far-field illustrate the feasibility and validity of this lens antenna. High efficiency achromatic sub-diffraction focusing with a full-width at half-maximum of 0.3λ and a highly directive far-field radiation pattern with side lobes below −10 dB are achieved. Triple input and triple output function is also realized experimentally.
Role of dopants and defects on the photocatalytic performance of g-C3N4 under visible light and sub-band gap excitation
Authors: Jaiswal Manju Kumari , Choudhury Biswajit
Published: October 2022

Here, we report the photocatalytic (PC) activity of graphitic carbon nitride (g-C3N4) doped with potassium (K), magnesium (Mg), and boron (B) under visible (>390 nm), green (532 nm), and red (660 nm) light. Doped g-C3N4 has an improved band structure, high carrier density, and tunable band-edge absorption as compared to pure g-C3N4. An atomic force microscope shows a decrease in layer thickness that follows the order: g-C3N4 > K/g-C3N4 > Mg/g-C3N4 > B/g-C3N4. The evolution of nitrogen vacancies in doped g-C3N4 was identified via x-ray photoelectron spectroscopy (XPS) and CHNS/O analyses. The red-shift in the absorption spectrum of K/g-C3N4 and the emission spectrum of B/g-C3N4 is caused by the band gap renormalization (BGR) effect. Quantum confinement and a possible Burstein–Moss (BM) effect both contribute to the spectral blue shift in the absorption spectra of Mg/g-C3N4 and B/g-C3N4. The BM effect, quantum confinement, and dopant-induced lattice strain might all alter the band structure and move the conduction band edge away from the valence band zone centre, causing an above band gap emission in K/g-C3N4 and Mg/g-C3N4. All samples degraded methylene blue (MB) under visible light with outstanding results, but they responded poorly to methyl orange (MO) and rhodamine B (RhB). With 83.59% MB degradation at a rate constant of 1.1 × 10−2 min−1, Mg/g-C3N4 recorded the best PC, which was three times quicker than g-C3N4 (3.7 × 10−3 min−1). When compared to g-C3N4, the doped samples’ current density (both anodic and cathodic) and carrier density were almost two times greater. The mechanism demonstrated how active edge sites, defects, and dopants contributed to the remarkable PC activity in the doped samples.
Bounds on anomalous quartic WWZγ couplings in e
–
p collisions at the FCC-he
Authors: Gurkanli E
Published: October 2022

Non-Abelian structure of the standard model (SM) predicts the self-interactions of gauge bosons triple gauge couplings (TGC) and quartic gauge couplings (QGC). On the other hand, it is also important to determine the deviations from SM via anomalous triple gauge couplings and anomalous quartic gauge couplings (aQGC) to test the nature of the SM and to see the effects of new physics arising from the beyond the standard model. In this study, we focus on the e
−
p → jZ
γ
ν

e
→ j(l
+
l
−)γ
ν

e
process to examine the WWZ
γ aQGC at the Future Circular Collider-hadron electron with center-of-mass energy

s

=
5.29

TeV using a model-independent way in the effective theory approach. A Cut-based method is applied to analyse the signal and relevant SM background. Using the total cross-sections, we constrained the anomalous f

T,i=0,1,2,5,6,7/Λ4 couplings arising from dimension-8 operators at 95% confidence level for the dilepton decay of the Z-boson. The results are composed of integrated luminosities of


=
1
,
2

and 3 ab
−1 under the systematic uncertainties of 0%, 5% and 10%. In the calculations, we use the form factor to eliminate the effects of the violation of unitarity. With this, we obtained the limits for the energy scale of the form factor Λ = 1 TeV. In addition to all this, we use the advantages of ep collisions for analysing the process with much cleaner environment and lower background effects compared with the pp collisions. The obtained sensitivities on f

T, i=0, 1, 2, 5, 6, 7/Λ4 are comparable with the experimental results and related phenomenological studies in the literature.
Numerical study of non-adiabatic quantum thermodynamics of the driven resonant level model: non-equilibrium entropy production and higher order corrections
Authors: Tong Kaiyi , Dou Wenjie
Published: October 2022

We present our numerical study on quantum thermodynamics of the resonant level model subjected to non-equilibrium condition as well as external driving. Following our previous work on non-equilibrium quantum thermodynamics (Dou et al 2020 Phys. Rev. B 101 184304), we expand the density operator into a series of power in the driving speed, where we can determine the non-adiabatic thermodynamic quantities. Particularly, we calculate the non-equilibrium entropy production rate as well as higher order non-adiabatic corrections to the energy and/or population, which is not determined previously in Dou et al (2020 Phys. Rev. B 101 184304). In the limit of weak system-bath coupling, our results reduce to the one from the quantum master equation.
Whole surface defect detection method for bearing rings based on machine vision
Authors: Ping Zhou , Chuangchuang Zhang , Gongbo Zhou , Zhenzhi He , Xiaodong Yan , Shihao Wang , Meng Sun , Bing Hu
Published: October 2022

As an important part of a bearing, a bearing ring (BR) is prone to producing various defects on each surface in the production process, which seriously affects the reliability of the bearing. To solve the problem in which multiple defects are randomly distributed on multiple surfaces and manual detection is difficult, an automatic method for detecting defects on the whole surface of BRs based on machine vision is proposed. Firstly, the characteristics of the BR’s surface defects are analyzed, and an efficient scheme for acquiring the whole surface image of the BR is designed. Then, the method for detecting the defects on the whole surface of BRs is developed, and the corresponding image preprocessing, region of interest extraction and defect recognition algorithms are designed. Finally, a visual inspection system to identify the defects on the whole surface of BRs based on a multi-station turnover process is developed. On the premise of determining the key parameters of the detection algorithm, the performance of the detection method is analyzed through the experimental method. The results show that the comprehensive accuracy of the proposed detection method is 95%, which meets the detection requirements. On this basis, the detection strategy is optimized, and the best parameter combination is obtained through the experiments, which further reduces the false detection rate of good products and the missed detection rate of defective products, both of which are less than 3.5%.
Effect of magnetic resonance imaging pre-processing on the performance of model-based prostate tumor probability mapping
Authors: Alley Stephanie , Jackson Edward , Olivié Damien , Van der Heide Uulke A , Ménard Cynthia , Kadoury Samuel
Published: October 2022

Objective. Multi-parametric magnetic resonance imaging (mpMRI) has become an important tool for the detection of prostate cancer in the past two decades. Despite the high sensitivity of MRI for tissue characterization, it often suffers from a lack of specificity. Several well-established pre-processing tools are publicly available for improving image quality and removing both intra- and inter-patient variability in order to increase the diagnostic accuracy of MRI. To date, most of these pre-processing tools have largely been assessed individually. In this study we present a systematic evaluation of a multi-step mpMRI pre-processing pipeline to automate tumor localization within the prostate using a previously trained model. Approach. The study was conducted on 31 treatment-naïve prostate cancer patients with a PI-RADS-v2 compliant mpMRI examination. Multiple methods were compared for each pre-processing step: (1) bias field correction, (2) normalization, and (3) deformable multi-modal registration. Optimal parameter values were estimated for each step on the basis of relevant individual metrics. Tumor localization was then carried out via a model-based approach that takes both mpMRI and prior clinical knowledge features as input. A sequential optimization approach was adopted for determining the optimal parameters and techniques in each step of the pipeline. Main results. The application of bias field correction alone increased the accuracy of tumor localization (area under the curve (AUC) = 0.77; p-value = 0.004) over unprocessed data (AUC = 0.74). Adding normalization to the pre-processing pipeline further improved diagnostic accuracy of the model to an AUC of 0.85 (p-value = 0.000 12). Multi-modal registration of apparent diffusion coefficient images to T2-weighted images improved the alignment of tumor locations in all but one patient, resulting in a slight decrease in accuracy (AUC = 0.84; p-value = 0.30). Significance. Overall, our findings suggest that the combined effect of multiple pre-processing steps with optimal values has the ability to improve the quantitative classification of prostate cancer using mpMRI. Clinical trials: NCT03378856 and NCT03367702.
Dynamics of a charged Thomas oscillator in an external magnetic field
Authors: Vijayan Vinesh , Pratik Das Pranaya
Published: October 2022

In this letter, we provide a detailed numerical examination of the dynamics of a charged Thomas oscillator in an external magnetic field. We do so by adopting and then modifying the cyclically symmetric Thomas oscillator to study the dynamics of a charged particle in an external magnetic field. These dynamical behaviours for weak and strong field strength parameters fall under two categories; conservative and dissipative. The system shows a complex quasi-periodic attractor whose topology depends on initial conditions for high field strengths in the conservative regime. There is a transition from adiabatic motion to chaos on decreasing the field strength parameter. In the dissipative regime, the system is chaotic for weak field strength and weak damping but shows a limit cycle for high field strengths. Such behaviour is due to an additional negative feedback loop that comes into action at high field strengths and forces the system dynamics to be stable in periodic oscillations. For weak damping and weak field strength, the system dynamics mimic Brownian motion via chaotic walks. We claim that the modified Thomas oscillator is a prototypical model to understand the dynamics of an active particle.
A stable and causal model of magnetohydrodynamics
Authors: Armas Jay , Camilloni Filippo
Published: October 2022

We formulate the theory of first-order dissipative magnetohydrodynamics in an arbitrary hydrodynamic frame under the assumption of parity-invariance and discrete charge symmetry. We study the mode spectrum of Alfvén and magnetosonic waves as well as the spectrum of gapped excitations and derive constraints on the transport coefficients such that generic equilibrium states with constant magnetic fields are stable and causal under linearised perturbations. We solve these constraints for a specific equation of state and show that there exists a large family of hydrodynamic frames that renders the linear fluctuations stable and causal. This theory does not require introducing new dynamical degrees of freedom and therefore is a promising and simpler alternative to Müller-Israel-Stewart-type theories. Together with a detailed analysis of transport, entropy production and Kubo formulae, the theory presented here is well suited for studying dissipative effects in various contexts ranging from heavy-ion collisions to astrophysics.
Mass-derivative relations and unitarity constraints for CP asymmetries at finite temperature
Authors: Blažek Tomáš , Maták Peter , Zaujec Viktor
Published: October 2022

Within the seesaw type-I leptogenesis, we formulateCPTand unitarity constraints for the equilibrium reaction rateCPasymmetries and consider thermal mass and quantum statistics. We demonstrate that including higher-order perturbative corrections in the classical Boltzmann equation remarkably induces quantum effects into the kinetic theory.
Sliding of motor tails on cargo surface due to drift and diffusion affects their team arrangement and collective transport
Authors: Yadav Saumya , Kunwar Ambarish
Published: October 2022

Kinesin is a microtubule-associated motor protein which works in teams to carry the cellular cargo transport. Lipid rafts on membranous cargos reorganize, causing the motors present in these areas to physically cluster. Unregulated clustering of motors leads to diseases such as Leishmaniasis, Newmann-Pick disease, etc. Various in-vitro and computational studies have reported improved cargo velocity and travel distance of a fluid cargo as compared to a rigid cargo. However, only cargo velocity increases with increase in membrane fluidity of a fluid cargo. Thermal and motor forces acting tangentially on a cargo generate random torque and motor torque respectively, leading to cargo rotation and motor tail sliding on cargo surface. However, it is unknown which of these forces/torques play a crucial role in improving the transport properties. Here, we use computational models that incorporate random torque, motor torque, and combination of both random and motor torques to understand how they influence the clustering of Kinesin motors on cargo surface due to drift and diffusion of their tails. These studies were performed at varying tail diffusivity to understand their effect on clustering of tails in dispersed and clustered arrangement. We find that in dispersed arrangement, random torque does not cause clustering, whereas motor torque is crucial for clustering of tails on cargo surface, and tails sliding due to both random and motor torques have fastest cargo transport and maximum cooperativity. In clustered arrangement, tails slide to form a broad and steady cluster whose size increases with tail diffusivity resulting in decreased cargo runlength, velocity and cooperativity. These findings suggest that increased tail diffusivity negatively impacts the cluster and cargo transport of tails in the clustered arrangement, whereas it aids physical clustering of tails and cargo transport in dispersed arrangement.
High-sensitivity metamaterial sensor based on electromagnetically induced transparency (EIT) effect
Authors: Zhu Lei , Rong Miaoxin , Li Haodong , Dong Liang
Published: October 2022

We propose a metamaterial sensor based on electromagnetically induced transparency (EIT) effect, which is composed of two elliptical structures with splits. Based on the coupling of bright and dark modes, a low-loss transparent window is realized at 1.88 THz. Surface current distribution and equivalent circuit model are used to analyze the physical mechanism of the EIT effect. In addition, the sensitivity of the sensor is investigated for different thickness and refractive index for analyte. The simulation results show that when the analyte thickness is 15 μm and the refractive index is between 1 and 1.5, the sensitivity of the sensor is as high as 450.7 GHz/RIU, and the figure of merit (FOM) value is 7.7. And when the refractive index of analyte is 1.5 and its thickness is between 0 and 5 μm, the sensor can also be used for thickness sensing with a sensitivity of 40.8 GHz μm−1. In addition, the proposed metamaterial sensor can be used to simulate the detection of sodium chloride solution, and the sensitivity is 66.2 GHz/

mol

d

m

3

. These above features indicate that the proposed structure paves the way for designing high-sensitivity EIT sensors in the terahertz region, which plays important roles in promoting terahertz sensing and detection technology.
Electromagnetic multi-beam steering of matrix pattern-encoded metasurfaces
Authors: Chen Yi , Li Ruisi , Huang Wenkang , Wu Yinglai , Lu Jianxun , Ke Lan , Li Chenxia , Jing Xufeng
Published: October 2022

An electromagnetically encoded metasurface is a synthetic surface based on subwavelength unit particles, which can freely control the amplitude, phase and polarization direction of electromagnetic waves. Using digital states to characterize electromagnetic parameters directly links digital technology at the information level with metasurface technology at the physical level. This paper proposes a matrix encoding mode to realize the flexible control of the number of scattering beams and the scattering angle of the encoding metasurface. In order to reduce the ohmic loss of the metal structure metasurface, we propose to use the all-dielectric material cylindrical structure to construct the coding unit. In view of the encoding of metasurface sequences in one-dimensional direction, the scattering angle of THz beam can only be controlled in a single direction, but not the scattering azimuth in three-dimensional (3D) space. We use different matrix encoding modes to achieve multi-beam and multi-angle control of terahertz beams in 3D space. Based on the cross-coding mode, the multi-beam separation of the beam scattering main lobe is obtained, and the azimuth angle of each separated main lobe beam is flexibly controlled.
The cavity method to protein design problem
Authors: Takahashi Tomoei , Chikenji George , Tokita Kei
Published: October 2022

In this study, we propose an analytic statistical mechanics approach to solve a fundamental problem in biological physics called protein design. Protein design is an inverse problem of protein structure prediction, and its solution is the amino acid sequence that best stabilizes a given conformation. Despite recent rapid progress in protein design using deep learning, the challenge of exploring protein design principles remains. Contrary to previous computational physics studies, we used the cavity method, an extension of the mean-field approximation that becomes rigorous when the interaction network is a tree. We found that for small two-dimensional lattice hydrophobic-polar protein models, the design by the cavity method yields results almost equivalent to those from the Markov chain Monte Carlo method with lower computational cost.
A simple Thermopower measurement model and related uncertainties
Authors: Jana A , Mahakal S , Sau S , Das Diptasikha , Malik K
Published: October 2022

Thermopower (S) is an important parameter to estimate efficiency of a thermoelectric material. Differential method is a well-known and reliable method to estimate S. Uncertainty in S may arise from several factors. A typical S measurement set-up has been considered to explain two processes of Data acquisition (DAQ) using differential method. Uncertainties in DAQ have been estimated for two processes. Numerical calculations have been carried out using developed theory of uncertainties.
Numerical calculation of RPC time resolution
Authors: Datta Jaydeep , Majumdar Nayana , Mukhopadhyay Supratik , Sarkar Sandip
Published: October 2022

Resistive Plate Chamber (RPC) is a gaseous detector, known for its good spatial resolution and excellent time resolution. Due to its fast response and excellent time resolution, it is used for both triggering and timing purpose. But the time resolution of RPC is dependent on the detector geometry, applied voltage and the gas mixture used for detector operation. In this work, we have tried to develop a numerical model to estimate the time resolution of the detector. The model is developed using COMSOL Multiphysics, a commercially available finite element method solver. Using the primary ionization information from HEED and the electron transport properties from MAGBOLTZ, the model solves the Boltzmann equations to simulate the avalanche in the detector and finds the time to cross a previously determined threshold current, which is used to measure the time resolution of the detector.
Physical property modifications with transition metal doping in nanostructured Zn1-xNixO (x = 0.03, 0.05); synthesized by chemical co-precipitation technique
Authors: Ghosh Soumyadev , Pramanik Subhamay , Kuiri Probodh K. , Samanta Saikat , Sen Rupam , Neogi Swarup Kumar
Published: October 2022

Present work demonstrate the structural and optical property study of Zn1-xNixO (x= 0.03, 0.05) nanoparticles (NPs). These samples have been prepared by simple chemical co-precipitation method. Finally these samples are annealed at 500°C for 3 hours. Structural characterization has been performed by doing X-Ray diffraction (XRD) at room temperature. The XRD patterns confirm the hexagonal wurzite structure for these samples. We have estimated the lattice parameters (a & c) and determine the c/a ratio of respective samples after structural analysis. Morphology of these nanoparticles has been investigated by performing SEM. In addition UV-visible and Photoluminescence (PL) study has been performed. PL emission spectra show a broad UV emission peak. Doping at the Zn-site by Ni ions could induce inter-band levels within the band gap. Transition between those levels may responsible for broadening of the UV peak. In addition defect mediated visible emission has also been observed in the PL study. Further to investigate the effect of doping on microstructure, Raman spectra of Zn1-xNixO samples are taken. Wurzite ZnO belongs to space group: C4
6v and consequently six first order phonon modes are expected to appear in the Raman spectra. Raman scattering has been analysed according to the existing literature and details of analysis are presented in this work.
Quark gluon plasma in the early universe expansion with quasi-particle approach
Authors: Kumar Y , Sharma R , Kuksal G , Jain P , Kumar V , Bangotra P
Published: October 2022

To understand the behaviour of Quark Gluon Plasma (QGP) in the early stages of universe, a precise temporal evolution of different thermodynamic parameters is studied. Out of many indirect signatures used for the detection of QGP, we compute the Equation of State (EoS) by solving the Friedmann equations. A phenomenological model is used with the value of thermal dependent finite quark mass. The variation of temperature, as well as the energy density with respect to time, are provided which predicts a suitable transition temperature for the phase transition. These results can also be used to calculate other thermodynamic observables. The evolution of early universe and its related properties are thus important in the detection of QGP.
Development of Micro-Pattern Gaseous Detectors for Nuclear Reaction Studies
Authors: Bhattacharya P , Sen A , Ghosh T K , Majumdar N , Mukhopadhyay S
Published: October 2022

One of the frontiers of today’s nuclear physics research is the synthesis of Super Heavy Elements (SHE). Fusion-fission dynamics, namely the competition between quasi fission and fusion is one of the key challenges to optimize the SHE. To have an insight into the dynamics, one requires the study of fission fragment mass and angular distribution near barrier energies for heavy-ion induced fission reactions. Recent successful installation of linear accelerators in India offers a unique opportunity to study the dynamics of nuclear reactions and formation process of SHE. For the effective utilization of these current, as well as upcoming facilities, development of novel detectors to study reaction dynamics, formation process of SHE with heavier projectiles and higher beam energies is needed. Gaseous detectors have undergone a rapid improvement in terms of spatial, temporal and energy resolution, rate capability, radiation hardness, ion feedback etc., ushering in a new genre of micro-structured devices based on semi-conductor technology, commonly known as Micro-Pattern Gaseous Detectors (MPGDs). Although many of the MPGD structures were primarily developed for high-rate tracking of charged particles in high energy physics experiments, stability of operation, simplicity of construction and relatively low cost make these detectors suitable for other applications, such as low-energy nuclear physics experiments. The present activities encompass a detailed evaluation of the operational conditions of Micromesh-Multi Wire and THGEM-Multi Wire hybrid detector operated in low-pressure isobutane gas with a view to optimizing their use in the detection of charged particles and fission fragments.
Effects of partial substitution of Co by Ni on structural and transport properties of TiCoSb-based half-Heusler compound
Authors: Mahakal S , Das Diptasikha , Singha P , Rana N , Mukherjee S , Banerjee Aritra , Malik K
Published: October 2022

Correlation amid structural and transport properties of TiCo(1−x)Ni
x
Sb, (x=0.00, 0.02, 0.04, 0.06) alloy have been investigated. Samples have been synthesized by solid state reaction method, followed by arc-melting. Minute amount of CoTi embedded phase has been revealed by in-depth structural characterization using Rietveld refinement. Unit cell volume decreases with increasing Ni in TiCo(1−x)Ni
x
Sb, indicate sucessful substitution. Lattice strain, crystalline size and dislocation density have been estimated from x-ray diffraction data. Temperature dependent resistivity (ρ(T)) measurements have been carried out down to 10 K. Transition from metallic to semiconducting behavior is observed in ρ(T) data for x=0.00, 0.02. ρ(T) for x=0.04 and 0.06 show metallic nature. Plausible explanation have been provided on the basis of position of Fermi surface and embedded phases.
Thermal-mechanical coupling simulation analysis of submarine armored cable soil environment
Authors: Huang Youcong , Fu Zhiwei , Zheng Zhongnan , Lv Tian , Zhang Ying , Li Yaowei , Xv Jun , Mao Yulin
Published: October 2022

Due to the complex and diverse seabed environment, the coupling effect of high depth and temperature will seriously affect the operation stability of submarine cables. Therefore, the thermal-mechanical coupling model and inherent characteristics of submarine armored cables in soil environment are simulated and analyzed. Firstly, the influence of different buried depth and surrounding seawater temperature on cable temperature in soil environment is studied. Then the natural frequency of the cable is obtained by modal analysis. Since the low frequency vibration mainly occurs in the operation process, the high frequency vibration is not easy to excite and decay quickly, only the first eight order vibration is considered. The results show that it is beneficial to avoid the vibration near the resonance frequency, to lay in the relatively shallow position and to reduce the buried depth appropriately.
Imaging of hydroxyl radical (·OH) distributions using luminol water during irradiation with low-energy X-rays
Authors: Yamamoto Seiichi , Yabe Takuya , Hirano Yoshiyuki , Kataoka Jun
Published: October 2022

Reactive hydroxyl radicals (·OH) play important roles
in the biological effects of radiation exposure or radiation
therapy, and the distribution of ·OH in water during
irradiation is of interest to researchers. However, real-time
·OH distribution measurement during irradiation has so far not
been achieved due to the difficulty of detecting ·OH. To make
these distribution measurements possible, we attempted the imaging
of light emitted from luminol water during irradiation with
low-energy X-rays. Imaging of the light emitted from luminol water
was conducted using a cooled charge-coupled device (CCD) camera
during X-ray irradiation to luminol water at lower energy than the
Cherenkov-light threshold. The light emission of luminol water was
25 times higher than that of water, and clear images of light
distributions were measured for the luminol water. By carrying out
the imaging of luminol water with the addition of a radical
scavenger to the luminol water, we could confirm that the emitted
light was from ·OH produced in water. With this addition of
the radical scavenger, the light intensity decreased as the weight
of the scavenger increased. With these results, we confirmed that
the detected light distribution in luminol water could be attributed
to the ·OH produced by the X-ray irradiation.
Historical evolution and new trends for soil-intruder interaction modeling
Authors: Pirrone Serena R M , Del Dottore Emanuela , Mazzolai Barbara
Published: October 2022

Soil is a crucial resource for life on Earth. Every activity, whether natural or man-made, that interacts with the sub or deep soil can affect the land at large scales (e.g. geological risks). Understanding such interactions can help identify more sustainable and less invasive soil penetration, exploration, and monitoring solutions. Over the years, multiple approaches have been used in modeling soil mechanics to reveal soil behavior. This paper reviews the different modeling techniques used to simulate the interaction between a penetrating tool and the soil, following their use over time. Opening with analytical methods, we discuss the limitations that have partially been overcome by the finite element method (FEM). FEM models are capable of simulating more complex conditions and geometries. However, they require the continuum mechanics assumption. Hence, FEM analysis cannot simulate the discrete processes occurring during soil deformation (i.e. the separation and mixing of soil layers, the appearance of cracks, or the flow of soil particles). The discrete element method (DEM) has thus been adopted as a more promising modeling technique. Alongside models, experimental approaches have also been used to describe soil-intruder interactions, complementing or validating simulation results. Recently, bioinspired approaches have been considered promising to improve sustainability and reduce the invasiveness of classical penetration strategies. This review highlights how DEM-based models can help in studying the interaction mechanisms between bioinspired root-like artificial penetrometers and the soil. Bioinspired designs and the merging of multiple analysis approaches can offer new perspectives. These may be pivotal in the design of highly optimized soil robotic explorers capable of adapting their morphology and penetration strategies based on their surrounding conditions.
Different characteristics of two surges in Weigeledangxiong Glacier, northeastern Tibetan Plateau
Authors: Pan Baotian , Guan Weijin , Shi Menghan , Wu Guangjian , Cheng Jiamei , Shangguan Donghui , Guo Wanqin , Cao Bo
Published: October 2022

Glacier surge is a special form of glacier displacement caused by the instability of the glacial dynamic system. It is a quasi-periodic oscillation behavior, which affects the estimation of the overall change of glaciers in the region and potentially threatens the infrastructure and human life in the downstream regions. Most glaciers experience a mass loss with rising air temperatures in recent decades, but little attention has been paid to the influence of climate change on glacial surges. This study identified two surges, triggered in 1992 and 2015 in Weigeledangxiong Glacier, Ányêmaqên Mountains, northeastern Tibetan Plateau, using multi-source remote sensing data (Landsat images, Sentinel-2 images, topographic map, shuttle radar topography mission digital elevation model [SRTM DEM], and the elevation change database). The 1992 surge accelerated abruptly with the maximum velocity of 350 ± 9 m a−1, and a large volume of ice transported downward, causing a sudden advance of 392 ± 42 m from 1992 to 1994, and clear thickening of the ice tongue. The recent surge is still in the active phase, exhibiting a gentler process of slower advance speed and lower peak velocity, as well as a smaller expansion zone than the previous one. These phenomena may be associated with the reduced glacier basal resistance and energy caused by rising temperatures in recent decades. Higher temperatures may cause the discharge of subglacial water through a more developed drainage system, leading to a longer active phase duration. Similar phenomena may exist widely in the Tibetan Plateau and its surrounding areas. Meanwhile, the frontal position of Weigeledangxiong Glacier advancing in the recent surge is not expected to threaten roads near the ice tongue.
Augmenting agroecosystem models with remote sensing data and machine learning increases overall estimates of nitrate-nitrogen leaching
Authors: Nowatzke Matthew , Damiano Luis , Miguez Fernando E , McNunn Gabe S , Niemi Jarad , Schulte Lisa A , Heaton Emily A , VanLoocke Andy
Published: October 2022

Process-based agroecosystem models are powerful tools to assess performance of managed landscapes, but their ability to accurately represent reality is limited by the types of input data they can use. Ensuring these models can represent cropping field heterogeneity and environmental impact is important, especially given the growing interest in using agroecosystem models to quantify ecosystem services from best management practices and land use change. We posited that augmenting process-based agroecosystem models with additional field-specific information such as topography, hydrologic processes, or independent indicators of yield could help limit simulation artifacts that obscure mechanisms driving observed variations. To test this, we augmented the agroecosystem model Agricultural Production Systems Simulator (APSIM) with field-specific topography and satellite imagery in a simulation framework we call Foresite. We used Foresite to optimize APSIM yield predictions to match those created from a machine learning model built on remotely sensed indicators of hydrology and plant productivity. Using these improved subfield yield predictions to guide APSIM optimization, total

N

O

3

−

N

loss estimates increased by 39% in maize and 20% in soybeans when summed across all years. In addition, we found a disproportionate total amount of leaching in the lowest yielding field areas vs the highest yielding areas in maize (42% vs 15%) and a similar effect in soybeans (31% vs 20%). Overall, we found that augmenting process-based models with now-common subfield remotely sensed data significantly increased values of predicted nutrient loss from fields, indicating opportunities to improve field-scale agroecosystem simulations, particularly if used to calculate nutrient credits in ecosystem service markets.