bluuebunny/crossref_metadata_2025 huggingface dataset:
Minimize inventory deviations in the Konimex technical warehouse through the implementation of the DMAIC concept
Authors: Anindya Putri Pramesti , Mahachandra Manik
Published: April 2024

PT Konimex is a manufacturing company that focuses on the pharmaceutical sector and is supported by an Engineering warehouse for machine maintenance during operation. However, during its run, there were problems in the form of discrepancies between the stock stored in the warehouse and those recorded in the company’s system which had a negative impact in the form of losses for the company. Therefore, a step-by-step analysis is carried out to provide solutions that are in accompanying circumstances using the DMAIC (define-measurement-analyze-improve-control) concept. The data collection method carried out is carried out directly and produces data in the form of primary data and indirect data collection, which uses the company’s historical data and produces secondary data. Data processing using the DMAIC concept then obtained the root of the problem and improvement solutions in the form of container redesign and the application of 5S as well as the addition of warehouse personnel which is expected to reduce the company’s stock-taking discrepancies.
Flexion contracture can cause component mismatch in the Prophecy® preoperative patient-specific instrumentation for Evolution® medial-pivot knee system
Authors: Hiyama Shuhei , Takahashi Tsuneari , Handa Mikiko , Takeshita Katsushi
Published: April 2024

Introduction: Patient-specific instrumentation (PSI) systems are used to conduct total knee arthroplasty. PSI reduces operative time, is less invasive and easier to use, and minimizes the risk of errors by providing precise measurements and reducing operating room turnover time. However, a study on the accuracy of Prophecy Evolution PSI (Microport Inc., Arlington, TN, USA) reported that 94% were below the error margin of 1.5 mm and 90% had error margins of 1 mm. This study aimed to evaluate the accuracy of the Prophecy Evolution PSI system in terms of the thickness of “total” bony resection required to achieve adequate extension/flexion gaps and the component match ratio between preoperative planning and actual component size inserted. Methods: Comparisons were made between the sizes of femoral and tibial components planned with PSI and those inserted. The primary outcome was the average preoperative range of motion with and without matched femoral/tibial components. The study further analyzed the proportions of cases in which both the femoral and tibial components matched, neither matched, and only one of the femoral or tibial components matched. Results: The ratio of the same sizes between the PSI planning and those inserted was 50.8% (33 patients) for both the femoral and tibial components. For the femoral component alone, the ratio was 84.6% (55 patients), and for the tibial component, it was 58.4% (38 patients). A receiver-operating characteristic curve analysis indicated that flexion contracture greater than 20° was a significant prognostic factor for the PSI component match group versus the mismatch group. Discussion: Flexion contracture may cause PSI mismatch. Notably, flexion contracture greater than 20° was a significant risk factor for the PSI component match group versus the mismatch group. During preoperative planning for a patient with flexion contracture, surgeons should prepare for the possibility of inserting an undersized tibial component.
Artificial intelligence for ultrasound microflow imaging in breast cancer diagnosis
Authors: Eun Na Lae , Lee Eunjung , Park Ah Young , Son Eun Ju , Kim Jeong-Ah , Youk Ji Hyun
Published: April 2024

Purpose To develop and evaluate artificial intelligence (AI) algorithms for ultrasound (US) microflow imaging (MFI) in breast cancer diagnosis.

Materials and Methods We retrospectively collected a dataset consisting of 516 breast lesions (364 benign and 152 malignant) in 471 women who underwent B-mode US and MFI. The internal dataset was split into training (n = 410) and test datasets (n = 106) for developing AI algorithms from deep convolutional neural networks from MFI. AI algorithms were trained to provide malignancy risk (0–100%). The developed AI algorithms were further validated with an independent external dataset of 264 lesions (229 benign and 35 malignant). The diagnostic performance of B-mode US, AI algorithms, or their combinations was evaluated by calculating the area under the receiver operating characteristic curve (AUROC).

Results The AUROC of the developed three AI algorithms (0.955–0.966) was higher than that of B-mode US (0.842, P < 0.0001). The AUROC of the AI algorithms on the external validation dataset (0.892–0.920) was similar to that of the test dataset. Among the AI algorithms, no significant difference was found in all performance metrics combined with or without B-mode US. Combined B-mode US and AI algorithms had a higher AUROC (0.963–0.972) than that of B-mode US (P < 0.0001). Combining B-mode US and AI algorithms significantly decreased the false-positive rate of BI-RADS category 4A lesions from 87% to 13% (P < 0.0001).

Conclusion AI-based MFI diagnosed breast cancers with better performance than B-mode US, eliminating 74% of false-positive diagnoses in BI-RADS category 4A lesions.
Sleep Status and Chronotype in University Athletes with and without Chronic Low Back Pain: A Cross-Sectional Study
Authors: Ansari Sumbul , Sharma Saurabh
Published: April 2024

Objective This study aimed to evaluate the status of sleep, chronotype, and related variables of university athletes with and without chronic low back pain (CLBP), to find the correlation between CLBP, sleep difficulty score (SDS), and chronotype, and to determine if SDS and chronotype predict CLBP.

Methods Ninety-two university athletes [46 with CLBP (Age: 22.08±2.74 years) and 46 healthy athletes (Age: 22.32±3.11 years) completed the athlete sleep screening questionnaire (ASSQ), also, their demographic, anxiety, depression, and sports-related details were collected. A Pearson correlation and logistic regression models (univariate and multivariate) were used for the statistical analysis.

Results The results demonstrated a higher SDS and evening type preference in CLBP athletes, a significant negative correlation between CLBP and chronotype (r = −0.40, p<0.01), a significant correlation between SDS and CLBP (r = 0.25, p = 0.01). SDS and chronotype were not found to be significant independent predictors of CLBP.

Conclusion This study concludes that there exists a correlation of CLBP, SDS, and chronotype However, despite the relationship, SDS and chronotype cannot predict CLBP.
Immigration and integration policy change in France during Sarkozy’s era
Authors: McKeever Anna
Published: April 2024

This paper sheds light on the factors behind the introduction of restrictive immigration and integration policy in France between 2002 and 2012, which is closely associated with Nicholas Sarkozy and his party Union for a Popular Movement (UMP). Using the evidence from semi-structured interviews, conducted with The Republicans (UMP) elected representatives, political advisors and civil servants, the paper argues that the introduction of restrictive immigration policies is explained not only through electoral pressure from the radical right Front National, but also by publics’ perceived economic concerns, cultural anxieties around Islam, as well as the effects of the EU integration. The paper also contributes to immigration policy liberalisation scholarship, by highlighting the importance of non-economic benefits migration brings, which take a form of soft power, as a way to increase French influence (rayonnement) in the world, contrary to the previous literature that explains liberalisation from economic advantages of skilled migration.
Time-dependent electron transfer and energy dissipation in condensed media
Authors: Arguelles Elvis F. , Sugino Osamu
Published: April 2024

We study a moving adsorbate interacting with a metal electrode immersed in a solvent using the time-dependent Newns–Anderson–Schmickler model Hamiltonian. We have adopted a semiclassical trajectory treatment of the adsorbate to discuss the electron and energy transfers that occur between the adsorbate and the electrode. Using Keldysh Green’s function scheme, we found a non-adiabatically suppressed electron transfer caused by the motion of the adsorbate and coupling with bath phonons that model the solvent. The energy is thus dissipated into electron–hole pair excitations, which are hindered by interacting with the solvent modes and facilitated by the applied electrode potential. The average energy transfer rate is discussed in terms of the electron friction coefficient and given an analytical expression in the slow-motion limit.
Insights into elastic properties of coarse-grained DNA models: q-stiffness of cgDNA vs cgDNA+
Authors: Laeremans Wout , Segers Midas , Voorspoels Aderik , Carlon Enrico , Hooyberghs Jef
Published: April 2024

Coarse-grained models have emerged as valuable tools to simulate long DNA molecules while maintaining computational efficiency. These models aim at preserving interactions among coarse-grained variables in a manner that mirrors the underlying atomistic description. We explore here a method for testing coarse-grained vs all-atom models using stiffness matrices in Fourier space (q-stiffnesses), which are particularly suited to probe DNA elasticity at different length scales. We focus on a class of coarse-grained rigid base DNA models known as cgDNA and its most recent version, cgDNA+. Our analysis shows that while cgDNA+ closely follows the q-stiffnesses of the all-atom model, the original cgDNA shows some deviations for twist and bending variables, which are rather strong in the q → 0 (long length scale) limit. The consequence is that while both cgDNA and cgDNA+ give a suitable description of local elastic behavior, the former misses some effects that manifest themselves at longer length scales. In particular, cgDNA performs poorly on twist stiffness, with a value much lower than expected for long DNA molecules. Conversely, the all-atom and cgDNA+ twist are strongly length scale dependent: DNA is torsionally soft at a few base pair distances but becomes more rigid at distances of a few dozen base pairs. Our analysis shows that the bending persistence length in all-atom and cgDNA+ is somewhat overestimated.
Molecular modeling of the carbohydrate corona formation on a polyvinyl chloride nanoparticle and its impact on the adhesion to lipid bilayers
Authors: Angelescu Daniel G.
Published: April 2024

The pervasive presence of nanoplastics (NPs) in the environment has gained increasing attention due to their accumulation in living organisms. These emerging contaminants inevitably interact with extracellular polymeric substances along respiratory or gastrointestinal tracts, and diverse organic coating on the surface of NPs, known as bio- or eco-corona, is formed. Although its impact on altering the NP properties and potential cell internalization has been extensively examined, studies on its role in NP partitioning in the cell membrane are elusive yet. In this work, molecular dynamics is used to investigate the formation of chitosan (CT) corona centered on a polyvinyl chloride (PVC) nanoparticle and the uptake of the resulting complex onto lipid membranes. Coarse-grained models compatible with the newly developed Martini 3.0 force field are implemented for the two polymers employing the atomistic properties as targets in the parameterization. The reliability of the coarse-grained polymer models is demonstrated by reproducing the structural properties of the PVC melt and of solvated CT strands, as well as by determining the conformation adopted by the latter at the NP surface. Results show that the spontaneous binding of CT chains of high and intermediate protonation degrees led to the formation of soft and hard corona that modulates the interaction of PVC core with model membranes. The structural changes of the corona adsorbed at the lipid–water interface enable a subsequent transfer of the NP to the center of the saturated lipid membranes and a complete or partial transition to a snorkel conformation depending on the hydrophilic/hydrophobic balance in the CT–PVC complex. Overall, the computational investigation of the coarse-grained model system provides implications for understanding how the eco-corona development influences the uptake and implicit toxicology of NPs.
Finding the differences: Classical nucleation perspective on homogeneous melting and freezing of hard spheres
Authors: Gispen Willem , Dijkstra Marjolein
Published: April 2024

By employing brute-force molecular dynamics, umbrella sampling, and seeding simulations, we investigate homogeneous nucleation during melting and freezing of hard spheres. We provide insights into these opposing phase transitions from the standpoint of classical nucleation theory. We observe that melting has both a lower driving force and a lower interfacial tension than freezing. The lower driving force arises from the vicinity of a spinodal instability in the solid and from a strain energy. The lower interfacial tension implies that the Tolman lengths associated with melting and freezing have opposite signs, a phenomenon that we interpret with Turnbull’s rule. Despite these asymmetries, the nucleation rates for freezing and melting are found to be comparable.
Wafer-scale development, characterization, and high temperature stabilization of epitaxial Cr2O3 films grown on Ru(0001)
Authors: Cumston Quintin , Patrick Matthew , Hegazy Ahmed R. , Zangiabadi Amirali , Daughtry Maximillian , Coffey Kevin R. , Barmak Katayun , Kaden William E.
Published: April 2024

This work outlines conditions suitable for the heteroepitaxial growth of Cr2O3(0001) films (1.5–20 nm thick) on a Ru(0001)-terminated substrate. Optimized growth is achieved by sputter deposition of Cr within a 4 mTorr Ar/O2 20% ambient at Ru temperatures ranging from 450 to 600 °C. The Cr2O3 film adopts a 30° rotated honeycomb configuration with respect to the underlying Ru(0001) substrate and exhibits a hexagonal lattice parameter consistent with that for bulk Cr2O3(0001). Heating to 700 °C within the same environment during film preparation leads to Ru oxidation. Exposure to temperatures at or above 400 °C in a vacuum, Ar, or Ar/H2 3% leads to chromia film degradation characterized by increased Ru 3d XPS intensity coupled with concomitant Cr 2p and O 1s peak attenuations when compared to data collected from unannealed films. An ill-defined but hexagonally well-ordered RuxCryOz surface structure is noted after heating the film in this manner. Heating within a wet Ar/H2 3% environment preserves the Cr2O3(0001)/Ru(0001) heterolayer structure to temperatures of at least 950 °C. Heating an Ru–Cr2O3–Ru heterostacked film to 950 °C within this environment is shown by cross-sectional scanning/transmission electron microscopy (S/TEM) to provide clear evidence of retained epitaxial bicrystalline oxide interlayer structure, interlayer immiscibility, and epitaxial registry between the top and bottom Ru layers. Subtle effects marked by O enrichment and O 1s and Cr 2p shifts to increased binding energies are noted by XPS in the near-Ru regions of Cr2O3(0001)/Ru(0001) and Ru(0001)/Cr2O3(0001)/Ru(0001) films after annealing to different temperatures in different sets of environmental conditions.
An evolutionarily conserved ubiquitin ligase drives infection and transmission of flaviviruses
Authors: Wu Linjuan , Zhang Liming , Feng Shengyong , Chen Lu , Lin Cai , Wang Gang , Zhu Yibin , Wang Penghua , Cheng Gong
Published: April 2024

Mosquito-borne flaviviruses such as dengue (DENV) and Zika (ZIKV) cause hundreds of millions of infections annually. The single-stranded RNA genome of flaviviruses is translated into a polyprotein, which is cleaved equally into individual functional proteins. While structural proteins are packaged into progeny virions and released, most of the nonstructural proteins remain intracellular and could become cytotoxic if accumulated over time. However, the mechanism by which nonstructural proteins are maintained at the levels optimal for cellular fitness and viral replication remains unknown. Here, we identified that the ubiquitin E3 ligase HRD1 is essential for flaviviruses infections in both mammalian hosts and mosquitoes. HRD1 directly interacts with flavivirus NS4A and ubiquitylates a conserved lysine residue for ER-associated degradation. This mechanism avoids excessive accumulation of NS4A, which otherwise interrupts the expression of processed flavivirus proteins in the ER. Furthermore, a small-molecule inhibitor of HRD1 named LS-102 effectively interrupts DENV2 infection in both mice and
Aedes aegypti
mosquitoes, and significantly disturbs DENV transmission from the infected hosts to mosquitoes owing to reduced viremia. Taken together, this study demonstrates that flaviviruses have evolved a sophisticated mechanism to exploit the ubiquitination system to balance the homeostasis of viral proteins for their own advantage and provides a potential therapeutic target to interrupt flavivirus infection and transmission.
Symbolic boundaries and the negative classifications of the ‘Successful Other’ at the intersection of ethnicity, religion, gender, and refugeeness
Authors: Mijić Ana , Parzer Michael
Published: April 2024

Our paper focuses on how members of the national ingroup respond when confronted with ‘successful others’ who challenge prevailing perceptions of immigrants and national belonging. We empirically investigate this through a case study on Alma Zadić, Austria’s Minister of Justice since January 2020. Her non-Austrian origin initiated a heated public debate on the legitimacy of an immigrant or refugee holding one of the country’s most important political positions. We analyse public discourse using interpretive analysis of online newspaper forum comments, employing the symbolic boundaries approach combined with the concept of negative classifications. The results reveal the cultural repertoires that members of the arrival society make use of when they negatively categorise an alleged newcomer of taking up a position that is considered exclusively reserved for the established. We contribute to the cultural sociology of social inequality and advocate for greater consideration of the intersectional entanglement of symbolic boundaries.
Distance-guided domain adaptation for bearing fault diagnosis under variable operating conditions
Authors: Hei Zhendong , Shi Qiang , Fan Xuefeng , Qian Feifei , Kumar Anil , Zhong Meipeng , Zhou Yuqing
Published: April 2024

Transfer learning (TL) has demonstrated effective application in diagnosing bearing faults under varying operating conditions. The current TL methods achieve domain alignment by minimizing the variation in the marginal distribution of data between the source and target domains in the feature space. However, this approach yields incomplete similarity, leading to domain shift and a decrease in diagnostic performance. To overcome this problem, this paper proposes a new distance-guided domain adaptation method that consists of two modules: deep domain adaptive correlation alignment (Deep CORAL) combined with joint maximum mean discrepancy (JMMD) for guided domain adaptation. Deep CORAL employs nonlinear transformations to synchronize second-order statistical correlations across source and target domains, thus ensuring feature-level alignment between these domains. JMMD is utilized to align the joint distribution of input features and output labels within the activation layer in the deep network, thereby bolstering domain alignment. Building on this, we propose a network structure that merges ResNet and bidirectional long short-term memory, powered by wavelet kernels, serving as a feature extractor. This structure is designed to learn domain-invariant features and incorporates attention mechanisms to amplify important information while diminishing the impact of redundant data. An analysis of bearing experiments is used to demonstrate the effectiveness of this method, and the proposed method significantly outperforms several popular methods in diagnostic performance.
Image quality evaluation of a new high-performance ring-gantry cone-beam computed tomography imager
Authors: Lustermans Didier , Fonseca Gabriel Paiva , Taasti Vicki Trier , van de Schoot Agustinus , Petit Steven , van Elmpt Wouter , Verhaegen Frank
Published: April 2024

Objective. Newer cone-beam computed tomography (CBCT) imaging systems offer reconstruction algorithms including metal artifact reduction (MAR) and extended field-of-view (eFoV) techniques to improve image quality. In this study a new CBCT imager, the new Varian HyperSight CBCT, is compared to fan-beam CT and two CBCT imagers installed in a ring-gantry and C-arm linear accelerator, respectively. Approach. The image quality was assessed for HyperSight CBCT which uses new hardware, including a large-size flat panel detector, and improved image reconstruction algorithms. The decrease of metal artifacts was quantified (structural similarity index measure (SSIM) and root-mean-squared error (RMSE)) when applying MAR reconstruction and iterative reconstruction for a dental and spine region using a head-and-neck phantom. The geometry and CT number accuracy of the eFoV reconstruction was evaluated outside the standard field-of-view (sFoV) on a large 3D-printed chest phantom. Phantom size dependency of CT numbers was evaluated on three cylindrical phantoms of increasing diameter. Signal-to-noise and contrast-to-noise were quantified on an abdominal phantom. Main results. In phantoms with streak artifacts, MAR showed comparable results for HyperSight CBCT and CT, with MAR increasing the SSIM (0.97–0.99) and decreasing the RMSE (62–55 HU) compared to iterative reconstruction without MAR. In addition, HyperSight CBCT showed better geometrical accuracy in the eFoV than CT (Jaccard Conformity Index increase of 0.02–0.03). However, the CT number accuracy outside the sFoV was lower than for CT. The maximum CT number variation between different phantom sizes was lower for the HyperSight CBCT imager (∼100 HU) compared to the two other CBCT imagers (∼200 HU), but not fully comparable to CT (∼50 HU). Significance. This study demonstrated the imaging performance of the new HyperSight CBCT imager and the potential of applying this CBCT system in more advanced scenarios by comparing the quality against fan-beam CT.
Hysteresis modeling and analysis of piezoelectric actuators using a modified LuGre model at different preloads and frequencies
Authors: Gan Jinqiang , Zhang Xudong , Xu Jie , Shan Yilin , Zhou Peng , Wu Chuan
Published: April 2024

Despite a large of models proposed to characterize the nonlinear hysteresis of piezoelectric actuators, few of them can show the effects of different preloads on the nonlinear hysteresis. In this paper, a modified LuGre model (MLM) is presented for piezoelectric actuators under different preloads to accurately characterize its dynamic hysteresis nonlinearity at different frequencies. Based on the classical LuGre model (CLM), the presented model introduces infinite impulse response filters and smoothness coefficient to simplify it. The parameters of the models were identified by the non-linear least squares method. A series of experiments were conducted to verify the validity of the MLM under different preloads at different frequencies excitation signals.In the constant frequency experiments under different preloads, the MLM reduces the mean error by

68.1
%
−
81.9
%

compared with the CLM; In the constant preload experiments at different frequencies, the MLM reduces the mean error by

72.2
%
−
83.0
%

and

65.9
%
−
83.2
%

compared with the classical Bouc–Wen model (CBM) and the CLM.
Probing the structural, electronic and optical properties of pure and B, N, or Li substituted Cyclo-18 ring: density functional theory investigations
Authors: Trivedi Ravi , Garg Nandini , Jha Prafulla , Chakraborty Brahmananda
Published: April 2024

Employing the quantum computational approach by using the Density Functional Theory along with GGA exchange correlation functional, we have investigated the structural, electronic, and optical properties of Cyclo-18 ring containing 18 sp hybridized carbon atoms and substituted Cyclo-C17X (X = B, N, and Li) ring. The Cyclo-18 ring has two opposite π electron system that can be organized as a D9h polyynic and D18h cumulene form. Our computational simulations suggest that D9h polyynic structure is minimum energy structure. Alkali metal doping makes C18 metallic by lowering the band gap when compared to the pure C18 (5.02eV). The strength of the chemical bonding analyzed using average binding energies for the Li, B, and N substituted Cyclo-C18 ring which are −4.58 eV, −4.65 eV, and −2.83 eV respectively. The positive charges on B, N and Li and negative charges on the Cyclo-18 ring demonstrate the partial Coulomb interactions and also charge transfer from B, N, and Li to Cyclo-18 ring. It is also found that the dominant adsorption IR peak at 2049 cm−1, 1329 cm−1, and 1011 cm−1 for B, N, and Li substituted C18 ring. There is an enhancement in optical absorption in the visible region due to doping which makes the system suitable for photo-catalytic applications.
Band convergence strategy to improve thermoelectric performance in Ti-Doped AgSbTe2
Authors: Hao Min , Lv Haojie , Du Rui , Yang Gui , Xuan Xiaowei , Wang Chunhui , Cui Shengqiang , Huang Xudong , Wang Chao
Published: April 2024

AgSbTe2 is one of promising material for waste heat recovery in the lower-medium (450–600 K) temperature range. However, its development is hindered by the formation of Ag2Te. In this study, we employed a mechanical alloying method to synthesize samples, significantly reducing the Ag2Te. Density functional theory (DFT) confirms that Ti doping in AgSbTe2 samples leads to the involvement of multiple valence bands in transport and decrease the energy offset between the light valence band and the primary valence band. Therefore, the Seebeck coefficient (S) increases from the value of 245 μV/K in Ag1.05SbTe2 to 270 μV/K in the Ag1.05Sb0.98Ti0.02Te2 samples at 473 K. A maximum ZT value of ∼1.28 at 523 K and an average ZT value of ∼0.97 within 323–548 K are obtained in Ag1.05Sb0.99Ti0.01Te2.
Chaotic dynamics of a three-species food chain model
Authors: Abbas Ansar , Khaliq Abdul
Published: April 2024

An analysis of a discrete-time food chain model is presented in this paper to investigate the effects of strong prey pressure on the chain. A bifurcation and stability theory is used to analyze equilibrium formation in system. It is shown by numerical simulations that chaos occurs as a result of the bifurcation of invariant curves following Neimark-Sacker (NS) bifurcation rules. The OGY method on stable periodic orbits of period 1 further controls chaos. Stability is achieved through iterations for chaotic motion controlled by different regulator poles. Numerical simulations are performed to examine the effects of the control method along with the results of our theoretical analysis.
Supplementation of deep neural networks with simplified physics-based features to increase accuracy of plate fundamental frequency predictions
Authors: Clinkinbeard Nicholus R , Hashemi Nicole N
Published: April 2024

To improve predictive machine learning-based models limited by sparse data, supplemental physics-related features are introduced into a deep neural network (DNN). While some approaches inject physics through differential equations or numerical simulation, improvements are possible using simplified relationships from engineering references. To evaluate this hypothesis, thin rectangular plates were simulated to generate training datasets. With plate dimensions and material properties as input features and fundamental natural frequency as the output, predictive performance of a data-driven DNN-based model is compared with models using supplemental inputs, such as modulus of rigidity. To evaluate model accuracy improvements, these additional features are injected into various DNN layers, and the network is trained with four different dataset sizes. When evaluated against independent data of similar features to the training sets, supplementation provides no statistically-significant prediction error reduction. However, notable accuracy gains occur when independent test data is of material and dimensions different from the original training set. Furthermore, when physics-enhanced data is injected into multiple DNN layers, reductions in mean error from 33.2% to 19.6%, 34.9% to 19.9%, 35.8% to 22.4%, and 43.0% to 28.4% are achieved for dataset sizes of 261, 117, 60, and 30, respectively, demonstrating potential for generalizability using a data supplementation approach. Additionally, when compared with other methods—such as linear regression and support vector machine (SVM) approaches—the physics-enhanced DNN demonstrates an order of magnitude reduction in percentage error for dataset sizes of 261, 117, and 60 and a 30% reduction for a size of 30 when compared with a cubic SVM model independently tested with data divergent from the training and validation set.
Abundant optical soliton solutions to the fractional perturbed Chen-Lee-Liu equation with conformable derivative
Authors: Islam Aminul , Sagib Md. , Mamunur Rashid Md. , Al Amin Md.
Published: April 2024

This research focuses on the space-time fractional nonlinear perturbed Chen-Lee-Liu model, which describes the propagation behavior of optical pulses in the fields of optical fiber and plasma. The equation is considered with respect to the conformable derivative, and a composite fractional wave transformation is employed to reformulate it into a nonlinear equation with a single variable. The improved tanh method has been applied to derive novel analytical wave solutions for the given equation. Consequently, various types of solitonic wave patterns emerge, including but not limited to periodic, bell-shaped, anti-bell-shaped, V-shaped, kink, and compacton solitonic structures. The acquired solutions could potentially aid in the analysis of signal transmission in optical fibers and the characterization of plasma properties. The physical interpretations of the solutions are investigated using three-dimensional surface plots and two-dimensional density plots. Additionally, combined two-dimensional plots are being used to discuss the effects of the order of the fractional derivative on the generated wave patterns. Moreover, this study demonstrates the efficacy and reliability of the chosen technique.
Effect of mutual interaction of two cosh-Gaussian laser beams on upper hybrid wave excitation and subsequent electron acceleration
Authors: Purohit Gunjan
Published: April 2024

This paper presents the excitation of an upper hybrid wave by resonant excitation of two intense cosh-Gaussian laser beams of frequencies ω
1 and ω
2 in a collisionless plasma. The excited upper hybrid wave is used for electron acceleration which accelerates the electrons towards higher energy. The acceleration of electrons through an excited upper hybrid wave has also been studied. This study has been analysed using the Wentzel Kramers Brillouin (WKB) and paraxial-ray approximation, where relativistic and ponderomotive nonlinearities are employed together. Analytical expressions for the beam width/intensity of the cosh-Gaussian laser beams, the electric field/power of the excited upper hybrid wave and the electron acceleration have been derived, which have been solved numerically for an established set of laser and plasma parameters. The results are also compared to relativistic nonlinearity. It has been observed that the mutual interaction of two cosh-Gaussian laser beams at a difference frequency significantly affects the self-focusing of each beam, leading to an increase in the amplitude/power of the upper hybrid wave as well as energy gain by the electrons. The effect of the magnetic field (ωc) and decentered parameter (b) on the power of the excited upper hybrid wave and the energy gain by the electrons are also explored. The results show that the power of upper hybrid wave and the energy gain by the electrons increase at higher values ​​of b and ω
c.
Microstructural, morphological and magnetic behaviour of Al3+ replaced BaFe11.5Co0.5O19 hexaferrites synthesized via sol-gel auto combustion route
Authors: Ijaz Muhammad , Asif Sana Ullah , Solre Gideon F B , Al-Asbahi Bandar Ali , Ullah Hafeez
Published: April 2024

In this work, polycrystalline BaFe11.5-xAlxCo0.5O19 (0≤x≤2) hexaferrite samples were synthesised by means of the sol–gel technique. Thereafter, the magnetic and structural properties are thoroughly examined. Cell refinement and XRD examination verified a magnetoplumbite hexaferrite arrangement with a space group of P63/mmc for each sample. The parameters ‘a’ and ‘c’ in the lattice fall in value from 5.885 Å to 5.875 Å and from 23.117 Å to 23.049 Å, respectively. Both the average crystallite size and the unit cell volume exhibit a declining trend as the doping level increases. For M-type hexaferrites, the optimal range of c/a values is determined to be 3.923–3.928. X-ray density (dx) and bulk density (db) decline with rising doping contents until x=1.5 doping content, at which point they exhibit an increasing trend. The results showed that as the doping amount increased, the saturation and remanence magnetizations decreased. Coercivity and magnetocrystalline anisotropy are rising together. Both the anisotropy field (Ha) and the anisotropy parameter (B) exhibit a rising trend with doping content. Coercivity of 5.896 kOe, anisotropic applied field of 1.84 kOe, saturation magnetization of 42.68 emu g−1, remanence magnetization of 24.414 (emu/g), and magnetic moment per formula unit-(mB) of 11.19 μ
B are the best magnetic properties obtained for the BaFe10Al1.5Co0.5O19 sample.
Revelations of vortex phases and pinning mechanism in GdBa2Cu3O7-δ
superconductors: a magneto-electric and magnetization study
Authors: Shit Subhasis , Namburi Devendra K , Das S D , Nath T K
Published: April 2024

Rare earth (RE) and barium (Ba) based cuprate superconductors have garnered considerable attention in both fundamental research and a wide array of engineering and technological applications. Examining the impact of magnetic Gd3+ ions on the GdBa2Cu3O7-δ
(GdBCO) system, this study reveals that the presence of Gd3+ ion has tilted the magnetic hysteresis loop, thereby affecting the critical current density (J

c
) at low temperatures. Through comprehensive magnetic and magneto-transport data analyses of the GdBCO sample, we have thoroughly explored the intricate behavior of vortices in response to magnetic fields and temperature variations, providing insight into the governing mechanism of vortex pinning. Remarkably, the absolute zero temperature pinning potential (U
0) experiences a significant reduction from a very high value of 3.18 eV to 0.45 eV with a magnetic field increase to 40 KOe, following a H
−0.53 law, indicating 3D plastically crippled vortices in weak pinning sites due to point defects. In various technological domains, particularly those involving high temperatures and strong magnetic fields, understanding and optimizing the pinning force (F

p
) and the pinning potential (U) of the vortices are pivotal for enhancing performance and efficiency. Consequently, we have meticulously analyzed the nature of F

p
and U with the aid of the thermally activated flux flow (TAFF) model. Ultimately, we compiled a comprehensive phase diagram delineating the evolution of various vortex phases.
Supermassive primordial black holes from inflation
Authors: Hooper Dan , Ireland Aurora , Krnjaic Gordan , Stebbins Albert
Published: April 2024

There is controversy surrounding the origin and evolution of our universe's largest supermassive black holes (SMBHs). In this study, we consider the possibility that some of these black holes formed from the direct collapse of primordial density perturbations. Since the mass of a primordial black hole is limited by the size of the cosmological horizon at the time of collapse, these SMBHs must form rather late, and are naively in conflict with constraints from CMB spectral distortions. These limits can be avoided, however, if the distribution of primordial curvature perturbations is highly non-Gaussian. After quantifying the departure from Gaussianity needed to evade these bounds, we explore a model of multi-field inflation — a non-minimal, self-interacting curvaton model — which has all the necessary ingredients to yield such dramatic non-Gaussianities. We leave the detailed model building and numerics to a future study, however, as our goal is to highlight the challenges associated with forming SMBHs from direct collapse and to identify features that a successful model would need to have. This study is particularly timely in light of recent observations of high-redshift massive galaxy candidates by the James Webb Space Telescope as well as evidence from the NANOGrav experiment for a stochastic gravitational wave background consistent with SMBH mergers.
Literature classification and its applications in condensed matter physics and materials science by natural language processing
Authors: Wu 吴 Siyuan 思远 , Zhu 朱 Tiannian 天念 , Tu 涂 Sijia 思佳 , Xiao 肖 Ruijuan 睿娟 , Yuan 袁 Jie 洁 , Wu 吴 Quansheng 泉生 , Li 李 Hong 泓 , Weng 翁 Hongming 红明
Published: April 2024

The exponential growth of literature is constraining researchers’ access to comprehensive information in related fields. While natural language processing (NLP) may offer an effective solution to literature classification, it remains hindered by the lack of labelled dataset. In this article, we introduce a novel method for generating literature classification models through semi-supervised learning, which can generate labelled dataset iteratively with limited human input. We apply this method to train NLP models for classifying literatures related to several research directions, i.e., battery, superconductor, topological material, and artificial intelligence (AI) in materials science. The trained NLP ‘battery’ model applied on a larger dataset different from the training and testing dataset can achieve F1 score of 0.738, which indicates the accuracy and reliability of this scheme. Furthermore, our approach demonstrates that even with insufficient data, the not-well-trained model in the first few cycles can identify the relationships among different research fields and facilitate the discovery and understanding of interdisciplinary directions.
The Multi-parameter Test of Gravitational Wave Dispersion with Principal Component Analysis
Authors: Ma Zhi-Chu , Niu Rui , Zhao Wen
Published: April 2024

In this work, we consider a conventional test of gravitational wave (GW) propagation which is based on the phenomenological parameterized dispersion relation to describe potential departures from General Relativity (GR) along the propagation of GWs. But different from tests conventionally performed previously, we vary multiple deformation coefficients simultaneously and employ the principal component analysis (PCA) method to remedy the strong degeneracy among deformation coefficients and obtain informative posteriors. The dominant PCA components can be better measured and constrained, and thus are expected to be more sensitive to potential departures from the waveform model. Using this method we analyze ten selected events and get the result that the combined posteriors of the dominant PCA parameters are consistent with GR within 99.7% credible intervals. The standard deviation of the first dominant PCA parameter is three times smaller than that of the original dispersion parameter of the leading order. However, the multi-parameter test with PCA is more sensitive to not only potential deviations from GR but also systematic errors of waveform models. The difference in results obtained by using different waveform templates hints that the demands of waveform accuracy are higher to perform the multi-parameter test with PCA. Whereas, it cannot be strictly proven that the deviation is indeed and only induced by systematic errors. It requires more thorough research in the future to exclude other possible reasons in parameter estimation and data processing.
Iterative addition of parallel non-local effects to full wave ICRF finite element models in axisymmetric tokamak plasmas
Authors: Zaar B. , Johnson T. , Bilato R. , Vallejos P.
Published: April 2024

The current response of a hot magnetized plasma to a radio-frequency wave is non-local, turning the electromagnetic wave equation into an integro-differential equation. Non-local physics gives rise to wave physics and absorption processes not observed in local media. Furthermore, non-local physics alters wave propagation and absorption properties of the plasma. In this work, an iterative method that accounts for parallel non-local effects in 2D axisymmetric tokamak plasmas is developed, implemented, and verified. The iterative method is based on the finite element method and Fourier decomposition, with the advantage that this numerical scheme can describe non-local effects while using a high-fidelity antenna and wall representation, as well as limiting memory usage. The proposed method is implemented in the existing full wave solver FEMIC and applied to a minority heating scenario in ITER to quantify how parallel non-local physics affect wave propagation and dissipation in the ion cyclotron range of frequencies (ICRF). The effects are then compared to a reduced local plane wave model, both verifying the physics implemented in the model, as well as estimating how well a local plane wave approximation performs in scenarios with high single pass damping. Finally, the new version of FEMIC is benchmarked against the ICRF code TORIC.
Entropic relations for indistinguishable quantum particles
Authors: Lemm Marius
Published: April 2024

The von Neumann entropy of a k-body-reduced density matrix γ

k
quantifies the entanglement between k quantum particles and the remaining ones. In this paper, we rigorously prove general properties of this entanglement entropy as a function of k; it is concave for all

1
⩽
k
⩽
N

and non-decreasing until the midpoint

k
⩽
⌊

N

/

2

⌋

. The results hold for indistinguishable quantum particles and are independent of the statistics.
Analysis of 70 - 300 MeV Proton Energy on Homogeneous and Inhomogeneous Phantoms using PHITS Monte Carlo Package
Authors: Fitria A , Sumaryada T , Yani S
Published: April 2024

Proton therapy is a radiotherapy technique using proton particles for reach the target in a straight line and minimize damage to the surrounding tissue. Proton particles that penetrate the body will be deposited at a certain depth and produce a Bragg peak. This study aims to determine the percentage depth dose (PDD) produced by proton radiation in homogeneous and inhomogeneous phantoms. Homogeneous phantom contains water, bone, or lungs material, while inhomogeneous phantom consists of several materials, namely water, bone, and lungs. The interaction of phantom and proton radiation was simulated using the Monte Carlo-based PHITS software. The result indicate that the material density and the proton energy were influencing the dept of Bragg peak. For energy 70 MeV, the Bragg peak position for the water phantom, bone phantom, and lung phantom were 3.80 cm, 2.60 cm, and 15.8 cm. The increase of proton energy causes a deeper Bragg peak position.
A Self-Construction of Automatic Crescent Detection Using Haar-Cascade Classifier and Support Vector Machine
Authors: Muztaba R , Malasan H L , Djamal M
Published: April 2024

Developing an automatic detection method based on computer vision applied to the moon crescent is an innovative concept that can be further developed. This program will be highly useful for observers during the Moon crescent observation because it can help them recognize objects quickly. This paper proposes an automatic crescent moon detection method based on visual mechanisms and training using the Cascade Classifier algorithm. The stages of this method consist of building Haar structural features, extracting feature samples using Haar structural features, and training 981 images consisting of 654 positive images and 327 negative images using the Cascade Classifier. The results show that the crescent moon detection performance is quite good at detecting the crescent Moon. The developed program can recognize crescent moon objects, although it is limited to relatively large lunar illumination in the range of greater than 10% to less than 50%. Furthermore, our program can be applied in real-time situations.
Resistivity Distribution of Lembang Fault Based on Magnetotelluric Data
Authors: Nurhasan  , Naufal Muhammad Risyad , Srigutomo Wahyu , Mustopa Enjang Jaenal , Diba Dieno , Ogawa Yasuo , Nada Qhathrin , Pratama Andika , Rusdiana Randi
Published: April 2024

The Lembang fault located 15 Km north of Bandung City is one of the active faults situated on Java Island, Indonesia. The Lembang fault is an extension of the Cimandiri fault that can be one of the potential sources of earthquakes in Indonesia. In this study, the Magnetotelluric method was used to model the subsurface resistivity at the Lembang Fault area. The data acquisition was conducted in 8 points of measurement forming a line perpendicular to the Lembang Fault. The analysis was performed using 1D inversion of apparent resistivity and phase with the frequency range of 1 Hz to 320 Hz. The contrast apparent resistivity has observed in two sites around the fault. The inversion results show resistivity contrasts around the LMB02 point that is suspected to be the Lembang Fault. These results are consistent with geological data in the Lembang Fault area. Aside from the LMB02 point, there are also resistivity contrasts around the LMB05 point. However, from a geological perspective, it is not yet known whether the area around the LMB05 point represents a fault.
Physical Properties of Varied Composition of Peanut Shell and Palm Oil Shell’s Briquettes
Authors: Dalimunthe Yusraida Khairani , Widayani  , Aditya Irfan Dwi
Published: April 2024

This research aims to determine the physical properties of briquettes made from peanut shell (KKT) and palm oil shell (CKS) waste. The manufacturing process is carried out using a briquette press with a pressure of 70 N/m2, and each KKT and CKS is measured at 100 mesh. Two grams of starch adhesive and 15 ml of water are used in the process. This research method involves varying the quantities of KKT and CKS with the following ratios: S1(18:0), S2(16:2), S3(14:4), S4(12:6), S5(10:8), S6(8:10), S7(6:12), S8(4:14), S9(2:16), S10(0:18). The results of this research show that the lowest density of briquettes, 708.38 kg/m3, was produced by sample S6, while the highest density, 876.91 kg/m3, was produced by sample S3. The lowest elastic modulus of briquettes, 7 MPa, was recorded for sample S6, and the highest elastic modulus, 60 MPa, was observed for sample S10. Similarly, the lowest ultimate strength of briquettes, 1.35 MPa, was found in sample S6, while the highest ultimate strength, 6.03 MPa, was achieved in sample S10.
Design of Liquid Refill Station for Dish Soap Product Based on Internet of Things
Authors: Nurrahmawati Aminah , Aminah Nina Siti , Kumar Rahul
Published: April 2024

The abundance of plastic waste from liquid products such as dish soap, shampoo, mineral water, etc., has been a big problem so far. Therefore, a liquid refill station for liquid products has been designed to reduce plastic waste, and in this research, we used dish soap as liquid product. The tool works equipped with two pumps and a water flow sensor. So that customers can choose the volume and type of dish soap they want to buy from the two available brands. All purchase data in the form of customer ID, the brand of dish soap purchased, the volume of dish soap bought, and the date of the purchase were saved in the database. The residual volume in the tank is monitored and displayed on the Grafana dashboard. The timeout of dish soap volume in the tank is predicted using linear regression with the independent variable in the form of time (days) of purchase and the dependent variable in the form of the remaining dish soap in the tank. The prediction uses training data taken from the remaining volume data in the tank when it is first filled until it is first used up. The training data found that the coefficient of determination R2= 0.99 for the two brands.