bluuebunny/crossref_metadata_2025 huggingface dataset:
Inverse distance ladder method for determining $$H_0$$ from angular diameter distances of time-delay lenses and supernova observations
Authors: Gong Xiaolong , Liu Tonghua , Wang Jieci
Published: August 2024

Time-delay measurements from strong lensing systems combined with spectroscopic measurements of stellar kinematics in deflecting galaxies provide a natural way to infer absolute distances (lensing distances). This means that it can be used to anchor the relative distances of Type Ia supernovae (SNe Ia), and further infer the Hubble constant $$H_0$$

H
0

in a cosmological model-independent way, while avoiding the assumptions of curvature and the equation of state of dark energy. Indeed, observations based on gravitational lensing time delays can measure $$H_0$$

H
0

directly, but usually require assumptions about the specific cosmological models. Meanwhile, this method suffers the mass-sheet degeneracy obstacle. These factors may induce the bias on determination of $$H_0$$

H
0

. However, the inverse distance ladder method we use avoids these assumptions altogether. In this study, we seek for the Pantheon and Pantheon plus datasets and use Gaussian process regression to reconstruct the unanchored distance to match the distance at the redshift of the lens to determine $$H_0$$

H
0

, respectively. Based on the four H0LiCOW lenses, the unanchored distances reconstructed by combining the Pantheon and Pantheon plus datasets yielded $$H_0=80.1^{+7.0}_{-6.9} \mathrm {~km/s/Mpc}$$

H
0

=
80
.

1

-
6.9

+
7.0

km
/
s
/
Mpc

and $$H_0=81.2^{+7.1}_{-7.0} \mathrm {~km/s/Mpc}$$

H
0

=
81
.

2

-
7.0

+
7.1

km
/
s
/
Mpc

with $$1 \sigma $$

1
σ

observational uncertainty, respectively. All the lenses show the measured $$H_0$$

H
0

is in good agreement with the local measurement results reported by the SH0ES collaboration within $$\sim $$
∼
$$1.3 \sigma $$

1.3
σ

confidence level.
$$J/\psi $$ polarization in relativistic heavy ion collisions
Authors: Zhao Jiaxing , Chen Baoyi
Published: August 2024

Understanding the polarization property of $$J/\psi $$

J
/
ψ

is critical to constrain its production mechanism. In addition, the polarization of $$J/\psi $$

J
/
ψ

can reveal the impact of strong electromagnetic and vorticity fields in relativistic heavy ion collisions. In this study, we analyzed the yield and polarization of $$J/\psi $$

J
/
ψ

in relativistic heavy ion collisions at different centrality and transverse momentum regions, using three different reference frames: the Collins–Soper frame, the helicity frame, and the event plane frame. The polarization of initially produced $$J/\psi $$

J
/
ψ

is determined by the NRQCD calculation and is similar to that of pp collisions. However, both unpolarization and transverse polarization are considered for the regenerated $$J/\psi $$

J
/
ψ

. Our results indicate that the polarization at high $$p_T$$

p
T

is similar to that observed in pp collisions. However, at low $$p_T$$

p
T

, where regenerated $$J/\psi $$

J
/
ψ

dominates, it is likely that the polarized charm quarks in the rotational QGP medium are responsible for this phenomenon. Our study supplies a baseline for future research on the effects of strong electromagnetic and vorticity fields on $$J/\psi $$

J
/
ψ

polarization.
Localised particles and fuzzy horizons: a tool for probing quantum black holes
Authors: Casadio Roberto
Published: August 2024

The horizon is a classical concept that arises in general relativity and is therefore not clearly defined when the source cannot be reliably described by classical physics. To any (sufficiently) localised quantum mechanical wavefunction, one can associate a horizon wavefunction which yields the probability of finding a horizon of given radius centred around the source. We can then associate to each quantum particle a probability that it is a black hole, and the existence of a minimum black hole mass follows naturally, which agrees with the one obtained from the hoop conjecture and the Heisenberg uncertainty principle.
Chinese Medicine-Derived Salvianolic Acid B for Disease Therapy: A Scientometric Study
Authors: Zhao Meina , Mu Fei , Lin Rui , Gao Kai , Zhang Wei , Tao Xingru , Xu Dong , Wang Jingwen
Published: August 2024

Salvianolic acid B (SalB), among the most abundant bioactive polyphenolic compounds found in Salvia miltiorrhiza Bge., exerts therapeutic and protective effects against various diseases. Although some summaries of the activities of SalB exist, there is lack of a scientometric and in-depth review regarding disease therapy. In this review, scientometrics was employed to analyze the number of articles, publication trends, countries, institutions, keywords, and highly cited papers pertaining to SalB research. The scientometric findings showed that SalB exerts excellent protective effects on the heart, lungs, liver, bones, and brain, along with significant therapeutic effects against atherosclerosis (AS), Alzheimer’s disease (AD), liver fibrosis, diabetes, heart/brain ischemia, and osteoporosis, by regulating signaling pathways and acting on specific molecular targets. Moreover, this review delves into in-depth insights and perspectives, such as the utilization of SalB in combination with other drugs, the validation of molecular mechanisms and targets, and the research and development of novel drug carriers and dosage forms. In conclusion, this review aimed to offer a comprehensive scientometric analysis and in-depth appraisal of SalB research, encompassing both present achievements and future prospects, thereby providing a valuable resource for the clinical application and therapeutic exploitation of SalB.
Weyl fermions in a (2+1)-dimensional gravitational wave spacetime
Authors: Guvendi Abdullah , Ahmed Faizuddin
Published: August 2024

In this study, we work on understanding the behavior of relativistic fermions within the framework of a (2+1)-dimensional gravitational wave environment. Our main objective is to uncover an analytical solution for the massless Dirac equation in this particular scenario. Initially, we derive a set of coupled equations that describe the quantum dynamics of the system under consideration. Subsequently, we embark on finding an analytical solution for the resulting wave equation governing Weyl fermions by utilizing the generators associated with the [Formula: see text] algebra. This approach enables us to determine the relativistic frequency modes of the system. We then delve into examining how the parameters of the gravitational wave spacetime influence the real oscillation modes of Weyl fermions. Our findings highlight the sensitivity of Weyl fermions to the specific gravitational wave spacetime background being considered.
Higgs physics at ILC
Authors: Božović-Jelisavcić I.
Published: August 2024

International Linear Collider (ILC) is a viable option for realization of a future Higgs factory. With proven accelerator technology and technically mature detector design, ILC offers well-understood physics program in the top, EW and Higgs sectors. Clean environment of electron–positron collisions, together with beam polarization of both beams and center-of-mass reach at a TeV scale, will make ILC a precision tool to probe realizations of new physics. The above will be illustrated on examples of fully simulated measurements in the Higgs sector, including Higgs couplings, Higgs self-coupling, CP violation measurements and Higgs exotic decay studies at ILC.
Internal Combustion Engine Fault Detection Based on Random Convolutional Neural Networks
Authors: Zhang Xiaojing , Shi Ruixia
Published: August 2024

The internal combustion engine plays a very important role in many fields, and when the internal combustion engine fails, if it is not found in time, it may cause continuous damage to the internal combustion engine, and further affect the life of the entire mechanical system. To solve the above problems, this paper proposes fault detection of internal combustion engines based on a random convolutional neural network. The cylinder burst noise signal of the internal combustion engine is decomposed by a stationary wavelet, and the inclusion matrix is composed of partial decomposition coefficients. Using singular value theory, the singular value containing matrix is extracted as the characteristic of cylinder burst noise signal. The singular value is used as the input of a random convolutional neural network to train and identify faults. The AdaBound optimizer was then applied to adapt the learning rate to changes, thereby accelerating the weight update of the model. At the same time, the neurons in the structure are randomly deactivated by dropout technology to prevent complex collaborative responses to the training data, and the diagnosis results of each network model are integrated by Dempster synthesis rules. The experimental results show that the minimum mean square error of 0.00165 is achieved when there are 15 neurons in the hidden layer, and it gradually increases as the number of neurons increases. Therefore, it is determined that there should be 15 neurons in the hidden layer, and the trainLM algorithm is used. The decision factors for training, validation, cross-validation, and overall data are 0.98947, 0.98597, 0.97738, and 0.9801, respectively, all reaching the control accuracy of 0.95, which indicates that the random convolutional neural network proposed has a high accuracy for internal combustion engine fault detection. For the main bearing Y-directional force, as the gap increases, its fluctuation trend strengthens; the main bearing force changes within a small range at first, then increases sharply when the gap reaches 0.2[Formula: see text]mm, and some main bearings even experience significant impact loads.
Design and Analysis of Optimized Approximate Multiplier Using Novel Higher-Order Compressor
Authors: Thakur Garima , Jain Shruti
Published: August 2024

The energy-efficient error-tolerant circuits have paved the way for a whole new area in low-power consumption applications with approximate computing. The approximate computing fulfills the trade-off requirement of exact computation and provides efficient performance. In this paper, a novel energy-efficient multiplier has been proposed for image processing applications. In the multiplication process, compressors are used as an important component for the reduction of partial products. Higher-order approximate 5:2 and 6:2 compressors are also designed and simulated in VIVADO using Verilog coding. The proposed higher-order compressors result in less area and low-power consumption in comparison with the existing state-of-the-art technique. These high-performance compressors are used at the multipliers’ reduction stage, resulting in an energy-efficient circuit for error-tolerant applications. All the simulations were carried out in VIVADO considering 8-bit inputs. Multiplication performance shows 37.77 % (8-bit) improvement in terms of power consumption in comparison to the conventional multiplier. The multiplication process has been done on the original, negative, and sharpened images using their masks. The proposed multiplier shows 51.36% (original image), 6.04% (negative image), and 22.44% (sharpened image) PSNR improvement in comparison to state-of-the-art work.
A Mobile Opportunistic Routing Algorithm Based on Mobility Classification
Authors: Tu Jinbin , Li Qing , Wang Yun
Published: August 2024

The advancement of novel technologies has positioned mobile wireless networks as the central focus of computer technology research. The selection process for the subsequent relay node in message forwarding holds paramount importance and is deemed critical. Drawing inspiration from Social Mobility theory, this paper presents a pioneering node classification model that categorizes all nodes into three distinct types. Furthermore, we introduce the concept of Active Entropy, where the numerical value of Active Entropy serves as a metric for message forwarding. Consequently, the routing algorithm transforms into a limited set of strategies between nodes belonging to different types. This routing algorithm offers numerous advantages including enhanced delivery rate, reduced network overhead ratio and decreased transmission delay. We evaluate and compare the performance of our proposed algorithm with that of DFDL algorithm and Prophet algorithm on the ONE simulation platform. Experimental results demonstrate that our proposed algorithm achieves a delivery rate at least 15% higher compared to the other two algorithms while also reducing overhead ratio.
Conant-independence and generalized free amalgamation
Authors: Mutchnik Scott
Published: August 2024

We initiate the study of a generalization of Kim-independence, Conant-independence, based on the notion of strong Kim-dividing of Kaplan, Ramsey and Shelah. A version of Conant-independence was originally introduced to prove that all [Formula: see text] theories are [Formula: see text]. We introduce an axiom on stationary independence relations, essentially generalizing the “freedom” axiom in some of the free amalgamation theories of Conant, and show that this axiom provides the correct setting for carrying out arguments of Chernikov, Kaplan and Ramsey on [Formula: see text] theories relative to a stationary independence relation. Generalizing Conant’s results on free amalgamation to the limits of our knowledge of the [Formula: see text] hierarchy, we show using methods from Conant as well as our previous work that any theory where the equivalent conditions of this local variant of [Formula: see text] holds is either [Formula: see text] or [Formula: see text] and is either simple or [Formula: see text]. We observe that these theories give an interesting class of examples of theories where Conant-independence is symmetric. This includes all of Conant’s examples, the small cycle-free random graphs of Shelah, and the (finite-language) [Formula: see text]-categorical Hrushovski constructions of Evans and Wong. We then answer Conant’s question on the existence of non-modular free amalgamation theories. We show that the generic functional structures of Kruckman and Ramsey are examples of non-modular free amalgamation theories. We also show that any free amalgamation theory is [Formula: see text] or [Formula: see text], while an [Formula: see text] free amalgamation theory is simple if and only if it is modular. Finally, we show that every theory where Conant-independence is symmetric is [Formula: see text]. Therefore, symmetry for Conant-independence gives the next known neostability-theoretic dividing line on the [Formula: see text] hierarchy beyond [Formula: see text]. We explain the connection to some established open questions.
Multiobjective Optimization Design of a MDOF Structure with Attached Nonlinear Gas–Spring Damper
Authors: Rong Kunjie , Tian Li , Meng Xiangrui , Wu Siyuan
Published: August 2024

To maximize vibration reduction efficiency and reduce the risk of detuning, this study proposes a multiobjective optimization design method for shape parameters affecting the nonlinear characteristics of nonlinear gas-spring damper (NGSD) based on the NSGA-II algorithm. A numerical model of a MDOF structure with attached NGSD is developed and optimized under white noise excitation, and the effectiveness of the optimized NGSD in mitigating structural seismic responses is validated through shaking table tests. By comparing with the optimal TMD, the control effectiveness and parameter sensitivity of the optimized NGSD under various near- and far-field seismic excitations are investigated. Results show that the optimization design is carried out with the performance objective of minimizing the RMS of structural displacement and acceleration response, and a set of relatively optimal piston radius and initial volume parameters are obtained, resulting in the control effectiveness of NGSD on the RMS response of MDOF structure’s displacement and acceleration as high as 77% and 39%, respectively. The maximum reduction effectiveness of optimized NGSD on the peak structural acceleration and displacement response under seismic excitation is 18% and 19% respectively, and the RMS reduction ratios are even as high as 56% and 61%, indicating the efficacy of using NSGA-II for parameter optimization. Moreover, the optimized NGSD demonstrates comparable control effectiveness to the optimal TMD with a shorter stroke and stable performance across different seismic excitations, indicating low sensitivity of optimal parameters to excitation frequency.
Theoretical Predictions and Computational Verifications on the Instability Responses of FGP-GPLS Subsea Pipelines with Egg-Shaped Cross-Sections
Authors: Zhang Qian , Bu Rui , Shen Meiling , Li Zhaochao
Published: August 2024

This paper primarily refers to the nonlinear instability of functionally graded porous (FGP) egg-shaped subsea pipelines mixed with graphene platelets (GPLs) under pressure and thermal environments. The FGP-GPLs egg-shaped subsea pipeline deflects radially inward since the pipeline is confined tightly and rigidly by the medium (soils/rocks). This deflection may be represented by a refined available displacement formula. The response curves are effectively traced by associating the computational calculus and the thin-walled shell theory. Furthermore, numerical verifications are completed to validate the analytical schemes. It is seen that the numerical curves are closely fitted to the theoretical ones. Moreover, the current study is validated efficiently by other results. Finally, evaluations are conducted on some parameters that affect the instability of the FGP-GPLs subsea pipeline with an egg-shaped profile, including the porosity coefficient, geometric shapes, weight fraction, temperature variations, etc.
Algebraic algorithms for vector bundles over curves
Authors: Montessinos Mickaël
Published: August 2024

In this paper, we represent vector bundles over a regular algebraic curve as pairs of lattices over the maximal orders of its function field and we give polynomial time algorithms for several tasks: computing determinants of vector bundles, kernels and images of global homomorphisms, isomorphisms between vector bundles, cohomology groups, extensions, and splitting into a direct sum of indecomposables. Most algorithms are deterministic except for computing isomorphisms when the base field is infinite. Some algorithms are only polynomial time if we may compute Hermite forms of pseudo-matrices in polynomial time. All algorithms rely exclusively on algebraic operations in function fields. For applications, we give an algorithm enumerating isomorphism classes of vector bundles on an elliptic curve, and to construct algebraic geometry codes over vector bundles. We implement all our algorithms into a SageMath package.
Dirac oscillator in the background of a minimal surface
Authors: Guvendi Abdullah , Ahmed Faizuddin
Published: August 2024

This study focuses on investigating the relativistic quantum dynamics of a fermionic oscillator field in the background of a minimal surface, specifically a catenoid bridge. Our primary objective is to analyze the bound-state solutions of this system by solving the non-perturbative radial wave equation. To achieve this, we consider two distinct scenarios. First, we explore the case where the particle is located inside the catenoid bridge and search for solutions to the wave equation. Subsequently, we extend our analysis to scenarios where the particle is positioned at a significant distance from the origin, comparable to the size of the catenoid bridge. In this regime, we obtain solutions to the wave equation to understand the behavior of the fermionic oscillator field. By examining these solutions, we investigate the influence of both the oscillator coupling and the spacetime background on the system.
Fractal modeling of non-integer Newtonian fluid through comparison of Sumudu and Laplace transforms
Authors: Akhund Amarah , Abro Kashif Ali
Published: August 2024

The exploration for knowing the complexity of fractal patterns (Koch snowflake, Julia shape, Chaos pro, Sierpinski triangle and Mandelbrot shape) among the rheological fluid models enables self-similar structures at different scales. In this paper, a fractal–fractional modeling of Newtonian fluid flow is developed for the velocity field by invoking power law kernel. In order to envisage the distinct computational characteristics and applications, the comparative analysis for the Sumudu transform and Laplace transform is investigated for fractal–fractional model of Newtonian fluid under exact analytical solutions. By employing fractal versus non-fractal parameters, analytical solutions for fractal–fractional model of Newtonian fluid by means of fractal Sumudu transform and fractal Laplace transform have been deduced by substituting [Formula: see text]. The sensitivity analysis for fractal–fractional model of Newtonian fluid is also emphasized for the sake of rheological phenomenon via multiple regression, Pearson correlation and probable error. Our results suggest that variations of viscosity depicted the behavior of shear stress on Newtonian fluid and predicted the complex motion under resistance of Newtonian fluid.
Magnetic black holes in 4D Einstein–Gauss–Bonnet massive gravity coupled to nonlinear electrodynamics
Authors: Paul Prosenjit , Kruglov S. I.
Published: August 2024

We investigated Einstein–Gauss–Bonnet (EGB) 4D massive gravity coupled to nonlinear electrodynamics (NED) in an anti-de Sitter (AdS) background and found an exact magnetically charged black hole solution. The metric function was analyzed for different values of massive gravity parameters. The first law of black hole thermodynamics and generalized Smarr formula were verified, where we treated the cosmological constant as thermodynamic pressure. We defined vacuum polarization as the conjugate to NED parameter. To analyze the local stability of the black hole, we computed specific heat. We investigated the van der Waals-like/re-entrant phase transition of the black holes and estimated the critical points. We observed small black hole (SBH)/large black hole (LBH) and SBH/intermediate black hole (IBH)/LBH phase transitions. The Joule–Thomson coefficient, inversion, and isenthalpic curves were discussed. Finally, the minimum inversion temperature and the corresponding event horizon radius were obtained using numerical techniques.
Binary Operations on Directed Fuzzy Graphs
Authors: Keerthana D. , Visalakshi V.
Published: August 2024

In this paper, the newly directed fuzzy graphs are generated using the operations such as union, join, composition and cartesian product of two directed fuzzy graphs, accompanied by their illustrative analysis. The degree of vertices in the newly generated directed fuzzy graphs is defined, and properties based on vertex degree are established. Additionally, the degrees of corresponding vertices in the composition and cartesian product of two directed fuzzy graphs are compared. The orientation of defined operations on fuzzy graphs is compared with the corresponding operations on directed fuzzy graphs and analyzed through illustrative examples.
Effects of Thermal Radiation and Magnetic Flux on MgO–Au–Ag/Blood Tri-Nanohybrid Fluid Flow in Arteries
Authors: Gangadhar Kotha , Ananda Vardhana K. , Venkata Subba Rao M. , Wakif Abderrahim
Published: August 2024

Nanoparticles such as magnesium oxide (MgO), silver (Ag) and gold (Au) can be used in conjunction with therapeutic agents, including anticancer drugs, gene therapy and antibiotics, to enable precise and controlled delivery. Recently, there has been significant interest in modifying biological fluid flow over arteries, particularly for drug delivery applications. This study aims to develop a comprehensive numerical model to investigate the flow dynamics of a hybrid nanofluid, specifically using pure blood as the base fluid and incorporating magnesium oxide (MgO), gold (Au) and silver (Ag) nanoparticles. The primary focus of this research is to explore the potential applications of this model in drug delivery systems, highlighting its promising capabilities for controlled and targeted drug release. The governing equations were transformed using the comparison transformation approach to address the system of nonlinear ordinary differential equations (ODEs). MATLAB’s BVP4C program was used to mathematically solve this problem and analyze the effects of relevant parameters. The findings show that the tri-hybrid nanofluid (MgO, Au and Ag) is extremely effective for heat control and medication transport within arterial channels. Specifically, under conditions of strong thermal radiation, the heat transfer rate at the lower wall increased by 83.924%, while at the upper wall, it increased by 72.098% for the tri-hybrid nanofluids.
The Evolving Regional Strategic Environment and Pakistan’s Quest for Strategic Equilibrium
Authors: Iqbal Rahat , Mir Mobeen Jafar , Muhammadi
Published: August 2024

China’s emergence as a key player in global politics and the declining role of the United States as a superpower are two greatest developments of the 21st century. This geopolitical transformation has compelled Washington to reconsider its traditional Eurocentric and Middle East-focused approach and shift strategic attention and resources to the Asia-Pacific region. In a bid to keep its superpower status, the United States is bolstering India as a bulwark against China. To balance China’s growing influence, the United States has upgraded ties with India and other major players on China’s periphery. The U.S-India strategic partnership is among the most visible result of these efforts. At the same time, this strategic realignment has serious consequences for regional stability in South Asia. India’s military buildup rattles neighbors, particularly Pakistan, as it increases the risk of confrontation between the two nuclear-armed states. This changing strategic environment leaves Pakistan with no option but to look for new ways to maintain strategic equilibrium. This study provides an overview of the India-U.S. partnership and its impact on South Asian strategic stability. It also highlights various challenges Pakistan will likely face due to regional realignment and discusses possible options for Pakistan to maintain a favorable strategic equilibrium.
China’s Rise and U.S.–Iran Standoff: An American Perspective
Authors: Tofik Ranj
Published: August 2024

There has been a notable link/correlation between the rise of China and U.S.–Iran standoff in recent years. The year 2012 marks a watershed moment in U.S. strategic calculation on its relations with China and Iran. Before that year, China was not a peer competitor capable of challenging U.S. preeminence on the world stage and Iran was merely a regional adversary. After 2012, U.S. intelligence reports have consistently assess that China is the only great power with the intent and ability to undermine the liberal world order and its growing ties with U.S. adversaries, Iran included, will pose the biggest threat to U.S. and Western interests. The China factor has become an independent variable in U.S.–Iran relation, and as Beijing continues to grow its economic and military power, the United States will resort to more hawkish policy toward China and Iran, further escalating the U.S.–Iran standoff. Tehran will continue to play a crucial role in its asymmetrical relationships with Beijing and Washington as the two superpowers seek their respective leverage in the triangular relationship to outcompete the other party.
New Era of Pakistan’s Embrace of China: Impact on Pakistan-U.S. Relations
Authors: Ali Iftikhar , Arshad Noraiz , Rogers Roy Anthony
Published: August 2024

This paper delves into the interdependent relationship between China and Pakistan and its implications for regional interests. It centers on China’s expanding economic clout in South Asia, primarily through its collaboration with Pakistan. Using the theoretical framework of “hedging,” the paper examines Pakistan’s strategy for balancing its connections with both China and the United States. It also explores the role of small powers in alliance politics and how China’s growing economic and military sway in Pakistan may affect Pakistan-U.S. relations. Ultimately, the paper contends that the United States can mitigate the perceived risk of a Pakistan-China partnership by considering Pakistan’s unique geopolitical position and its intricate association with India.
From Silent to Authoritarian Revolution: Modi, Hindu Rashtra and the Paradox of Indian Democracy
Authors: NAKAMIZO KAZUYA
Published: August 2024

India is currently undergoing an authoritarian revolution. During the 10 years of Narendra Modi’s rule, liberal aspects of India’s democracy were attacked by malpractices and the institutionalization of illiberal laws under his government. Additionally, the freedom of the media has been seriously damaged by the arrests of journalists who have criticized Modi’s government, which was, in particular, enabled by the amendment of the Unlawful Activities (Prevention) Act (UAPA) in 2019. The nation-wide anti-Citizenship Amendment Act (CAA) was crushed by the sudden declaration of the All-India Lockdown under the guise of an anti-COVID-19 measure, which I have termed the practice of “Disaster Authoritarianism”. After the crackdown on the anti-CAA movement, its participants were arrested under the provisions of a renewed UAPA. These are representative examples of Modi’s authoritarian revolution. Before this authoritarian revolution, India had been a democratic country for 70 years, a rarity among the countries of the so-called Global South. Why and how is this authoritarian revolution happening? Indian democracy underwent democratization that empowered the lower sections of society in the 1990s in what has been called the “Silent Revolution”. I hypothesize that this “Silent Revolution” invited Modi’s Authoritarian Revolution, which would constitute the paradox of Indian democracy. In this article, I seek to analyze the political process that led to the current Authoritarian Revolution and how it could occur without formal regime change.
Differentially Expressed Genes in Lung Cancer: Molecular Docking of Hypoxanthine Guanine-Phosphoribosyl Transferase with Dibutyl Phthalate
Authors: Naveed Muhammad , Saleem Ayesha , Aziz Tariq , Naveed Rida , Din Maida Salah Ud , Shabbir Muhammad Aqib , Khan Ayaz Ali , Alamri Abdulhakeem S. , Alsanie Walaa F. , Alhomrani Majid
Published: August 2024

This study aimed to identify differentially expressed genes (DEGs) by molecular docking of the hypoxanthine guanine-phosphoribosyl transferase (HGPRT) protein with pulmonary toxins i.e., dibutyl phthalate (DBP) and its metabolites, responsible for the induction of lung cancer. The highest binding affinity of −7.0 kcal/mol obtained was of monobutyl phthalate acyl-A-D-glucuronide. DBP and the protein HGPRT have a strong binding affinity of −7.0 kcal/mol, indicating the possibility of interrupting important biochemical pathways in the treatment of lung cancer. The development of targeted medicines may be guided by this relationship. A total of 120 samples were obtained from the GSE19804 expression profile out of which 60 samples from lung cancer and 60 from normal patients were selected as experimental and control groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses elaborated that the gene is involved in purine metabolism, nucleotide metabolism, drug metabolism and the synthesis of several enzymes. The protein–protein interaction (PPI) was assessed using the Search Tool for the Retrieval of Interacting Genes (STRING) database using Cytoscape software. The PPI enrichment [Formula: see text]-value was obtained as <1.0e−16. The docking result of the protein encoded by the AGER gene with DBP was obtained with a minimum binding affinity of up to −6.8 kcal/mol. The soluble receptor for advanced glycation end-products (sRAGE) was found to be involved in inhibiting the activation of oxidative stress and apoptotic pathways. Lung cancer is mostly dependent on the AGER gene and its soluble receptor sRAGE. sRAGE functions as a ruse to counteract the pro-inflammatory effects of AGER signaling and may be a therapeutic target to slow the growth of the malignancy. This study lays the framework for future research and offers novel insights into the role of HGPRT and DBP in the development of lung cancer and targeted therapy.
Cross-Modal Contrastive Learning with a Style-Mixed Bridge for Single Image 3D Shape Retrieval
Authors: Song Dan , Huo Shumeng , Fu Xinwei , Zhang Chumeng , Li Wenhui , Liu An-An
Published: August 2024

Image-based 3D shape retrieval (IBSR) is a cross-modal matching task which searches similar shapes from a 3D repository using a natural image. Continuous attention has been paid to this topic, such as joint embedding, adversarial learning, and contrastive learning. Modality gap and diversity of instance similarities are two obstacles for accurate and fine-grained cross-modal matching. To overcome the two obstacles, we propose a style-mixed contrastive learning method (SC-IBSR). On one hand, we propose a style transition module to mix the styles of images and rendered shape views to form an intermediate style and inject it into image contents. The obtained style-mixed image features serve as a bridge for later contrastive learning in order to alleviate the modality gap. On the other hand, the proposed strategy of fine-grained consistency constraint aims at cross-domain contrast and considers the different importance of negative (positive) samples. Extensive experiments demonstrate the superiority of the style-mixed cross-modal contrastive learning on both the instance-level retrieval benchmark (i.e., Pix3D, Stanford Cars, and Comp Cars that annotate shapes to images), and the unsupervised category-level retrieval benchmark (i.e., MI3DOR-1 and MI3DOR-2 with unlabeled 3D shapes). Moreover, experiments are conducted on Office-31 dataset to validate the generalization capability of our method. Code and pretrained models will be available at
https://github.com/honoria0204/SC-IBSR
.
Developing an AI-based Explainable Expert Support System for Art Therapy
Authors: Kim Jiwon , Kang Jiwon , Yang Migyeong , Park Chaehee , Kim Taeeun , Song Hayeon , Han Jinyoung
Published: August 2024

Sketch-based drawing assessments in art therapy are widely used to understand individuals’ cognitive and psychological states, such as cognitive impairments or mental disorders. Along with self-reported measures based on questionnaires, psychological drawing assessments can augment information regarding an individual’s psychological state. Interpreting drawing assessments demands significant time and effort, particularly for large groups such as schools or companies, and relies on the expertise of art therapists. To address this issue, we propose an artificial intelligence (AI)-based expert support system called
AlphaDAPR
to support art therapists and psychologists in conducting large-scale automatic drawing assessments. In Study 1, we first investigated user experience in
AlphaDAPR
. Through surveys involving 64 art therapists, we observed a substantial willingness (64.06% of participants) in using the proposed system. Structural equation modeling highlighted the pivotal role of explainable AI in the interface design, affecting perceived usefulness, trust, satisfaction, and intention to use. However, our interviews unveiled a nuanced perspective: while many art therapists showed a strong inclination to use the proposed system, they also voiced concerns about potential AI limitations and risks. Since most concerns arose from insufficient trust, which was the focal point of our attention, we conducted Study 2 with the aim of enhancing trust. Study 2 delved deeper into the necessity of clear communication regarding the division of roles between AI and users for elevating trust. Through experimentation with another 26 art therapists, we demonstrated that clear communication enhances users’ trust in our system. Our work not only highlights the potential of
AlphaDAPR
to streamline drawing assessments but also underscores broader implications for human-AI collaboration in psychological domains. By addressing concerns and optimizing communication, we pave the way for a symbiotic relationship between AI and human expertise, ultimately enhancing the efficacy and accessibility of psychological assessment tools.
Ultra-Low On-Resistance W/β-Ga2O3 Junction Barrier Schottky Rectifiers
Authors: Chiang Chao-Ching , Li Jian-Sian , Wan Hsiao-Hsuan , Ren Fan , Pearton Stephen J.
Published: August 2024

The on-resistance of Ga2O3 rectifiers with different metal anodes was measured from the forward current-voltage characteristics. The use of W anode metal produces low on-resistance of 0.34 mΩ.cm2 for W/Au/ β-Ga2O3 Schottky Barrier Diode (SBD) rectifiers and 0.22 mΩ.cm2 for heterojunction Diode (HJD) NiO/β-Ga2O3 rectifiers, overcoming the generally much larger values obtained using Ni or Pt metal. These are the lowest on-resistances reported for Ga2O3 rectifiers. The turn-on voltage was 0.22 V for SBD and 1.69 V for HJDs. By changing the anode metal, we varied the effective barrier height, which also affects reverse breakdown voltage. The switching characteristics were measured for the different device types, with reverse recovery times of 30.6 ns for SBDs and 33.0 ns for HJDs and slew rates of 2 A.μs−1 for both types of devices. Using a simple change of anode metal allows the achievement of a broad range of breakdown voltage and on-resistance, which allows for tailoring the rectifier performance depending on the application.
Prenatal stress induces sex- and tissue-specific alterations in insulin pathway of Wistar rats offspring
Authors: Mentzinger Juliana , Teixeira Gabriel Fernandes , Monnerat Juliana Arruda de Souza , Velasco Larissa Lírio , Lucchetti Bianca Bittencourt , Martins Matheus Azevedo Carvalho , Costa Viviane , Andrade Giovanna Palermo de , Magliano D’Angelo Carlo , Rocha Helena Naly Miguens , Nóbrega Antonio Claudio Lucas da , Medeiros Renata Frauches , Rocha Natália Galito
Published: August 2024

Prenatal stress may contribute to tissue-specific programming, especially in the liver. Our results showed that, although there were no repercussions to stress in cardiac tissue at 90 days old, prenatal stress induces a glucose intolerance phenotype with insulin signaling pathway alterations in the liver of male offspring at 90 days old. Furthermore, the prenatal stress altered lipid profile and increased cardiovascular risk in female offspring.
Biomarkers of intestinal permeability are associated with inflammation in metabolically healthy obesity but not normal-weight obesity
Authors: Keirns Bryant H. , Medlin Austin R. , Maki Katherine A. , McClanahan Kristen , Fruit Sarah E. , Sciarrillo Christina M. , Hart Samantha M. , Joyce Jill , Lucas Edralin A. , Emerson Sam R.
Published: August 2024

This is the first study to our knowledge to examine biomarkers of intestinal permeability in normal-weight obesity and one of few assessing microbiota compositions in this population. Additionally, we report that individuals with metabolically healthy obesity and metabolically unhealthy obesity displayed similar evidence of intestinal permeability, which was more strongly associated with systemic inflammation than total and visceral adipose tissue mass.
Fatty Acid Derivatization and Cyclization of the Immunomodulatory Peptide RP-182 Targeting CD206high Macrophages Improve Antitumor Activity
Authors: Singh Sitanshu S. , Calvo Raul , Kumari Anju , Sable Rushikesh V. , Fang Yuhong , Tao Dingyin , Hu Xin , Castle Sarah Gray , Nahar Saifun , Li Dandan , Major Emily , Sanchez Tino W. , Kato Rintaro , Xu Xin , Zhou Jian , Liu Liang , LeClair Christopher A. , Simeonov Anton , Baljinnyam Bolormaa , Henderson Mark J. , Marugan Juan , Rudloff Udo
Published: August 2024

As tumor-associated macrophages (TAM) exercise a plethora of protumor and immune evasive functions, novel strategies targeting TAMs to inhibit tumor progression have emerged within the current arena of cancer immunotherapy. Activation of the mannose receptor 1 (CD206) is a recent approach that recognizes immunosuppressive CD206high M2-like TAMs as a drug target. Ligation of CD206 both induces reprogramming of CD206high TAMs toward a proinflammatory phenotype and selectively triggers apoptosis in these cells. CD206-activating therapeutics are currently limited to the linear, 10mer peptide RP-182, 1, which is not a drug candidate. In this study, we sought to identify a better suitable candidate for future clinical development by synthesizing and evaluating a series of RP-182 analogs. Surprisingly, fatty acid derivative 1a [RP-182-PEG3-K(palmitic acid)] not only showed improved stability but also increased affinity to the CD206 receptor through enhanced interaction with a hydrophobic binding motif of CD206. Peptide 1a showed superior in vitro activity in cell-based assays of macrophage activation which was restricted to CD206high M2-polarized macrophages. Improvement in responses was disproportionally skewed toward improved induction of phagocytosis including cancer cell phagocytosis. Peptide 1a reprogrammed the immune landscape in genetically engineered murine KPC pancreatic tumors toward increased innate immune surveillance and improved tumor control and effectively suppressed tumor growth of murine B16 melanoma allografts.
Immunoproteasome Activation Expands the MHC Class I Immunopeptidome, Unmasks Neoantigens, and Enhances T-cell Anti-Myeloma Activity
Authors: Rana Priyanka S. , Ignatz-Hoover James J. , Guo Chunna , Mosley Amber L. , Malek Ehsan , Federov Yuriy , Adams Drew J. , Driscoll James J.
Published: August 2024

Proteasomes generate antigenic peptides that are presented on the tumor surface to cytotoxic T-lymphocytes. Immunoproteasomes are highly specialized proteasome variants that are expressed at higher levels in antigen-presenting cells and contain replacements of the three constitutive proteasome catalytic subunits to generate peptides with a hydrophobic C-terminus that fit within the groove of MHC class I (MHC-I) molecules. A hallmark of cancer is the ability to evade immunosurveillance by disrupting the antigen presentation machinery and downregulating MHC-I antigen presentation. High-throughput screening was performed to identify compound A, a novel molecule that selectively increased immunoproteasome activity and expanded the number and diversity of MHC-I–bound peptides presented on multiple myeloma cells. Compound A increased the presentation of individual MHC-I–bound peptides by >100-fold and unmasked tumor-specific neoantigens on myeloma cells. Global proteomic integral stability assays determined that compound A binds to the proteasome structural subunit PSMA1 and promotes association of the proteasome activator PA28α/β (PSME1/PSME2) with immunoproteasomes. CRISPR/Cas9 silencing of PSMA1, PSME1, or PSME2 as well as treatment with immunoproteasome-specific suicide inhibitors abolished the effects of compound A on antigen presentation. Treatment of multiple myeloma cell lines and patient bone marrow–derived CD138+ cells with compound A increased the anti-myeloma activity of allogenic and autologous T cells. Compound A was well-tolerated in vivo and co-treatment with allogeneic T cells reduced the growth of myeloma xenotransplants in NOD/SCID gamma mice. Taken together, our results demonstrate the paradigm shifting impact of immunoproteasome activators to diversify the antigenic landscape, expand the immunopeptidome, potentiate T-cell–directed therapy, and reveal actionable neoantigens for personalized T-cell immunotherapy.
Figure 5 from Loss of STK11 Suppresses Lipid Metabolism and Attenuates KRAS-Induced Immunogenicity in Patients with Non–Small Cell Lung Cancer
Authors: Principe Daniel R. , Pasquinelli Mary M. , Nguyen Ryan H. , Munshi Hidayatullah G. , Hulbert Alicia , Aissa Alexandre F. , Weinberg Frank
Published: August 2024

Mutant KRAS-induced immunogenicity requires the transcriptional upregulation of lipid metabolism. A, Tissue biopsies from treatment-naïve patients with NSCLC were subjected to whole-transcriptome RNA-seq as described and representative heat maps shown for select genes involved in lipid metabolism. B and C, Focused heatmaps are shown for select, significantly altered genes involved in lipid metabolic processes using a FDR-adjusted P value of <0.05. The percent CD8+ T-cell infiltration for patients arranged by combined KRAS mutation and (D) LPL mRNA expression, (E) LDLR mRNA expression, or (F) LDLRAD4 mRNA expression. Kaplan–Meier plots indicating months of OS for patients with NSCLC arranged by (G) CD8 mRNA expression, (H) KRAS mutation status alone, (I) combined KRAS and STK11 mutation statuses, (J) KRAS mutation status and LPL mRNA expression, (K) KRAS mutation status and LDLR mRNA expression, and (L) KRAS mutation status and LDLRAD4 mRNA expression. High, above median; low, below median; MT, mutated; NS, nonsignificant.
Table S1 from Characterization of Non-Monotonic Relationships between Tumor Mutational Burden and Clinical Outcomes
Authors: Anaya Jordan , Kung Julia , Baras Alexander S.
Published: August 2024

Simulated step function metrics. Log-likelihood and C-indexes for the test folds of a simulated step function dataset for either a Cox model, a FCN neural network, and a neural network comprised of a single neuron with sigmoid activation.
Supplementary Figure 1 from KRAS Promotes GLI2-Dependent Transcription during Pancreatic Carcinogenesis
Authors: Sigafoos Ashley N. , Tolosa Ezequiel J. , Carr Ryan M. , Fernandez-Barrena Maite G. , Almada Luciana L. , Pease David R. , Hogenson Tara L. , Raja Arul Glancis L. , Mousavi Fatemeh , Sen Sandhya , Vera Renzo E. , Marks David L. , Flores Luis F. , LaRue-Nolan Kayla C. , Wu Chen , Bamlet William R. , Vrabel Anne M. , Sicotte Hugues , Schenk Erin L. , Smyrk Thomas C. , Zhang Lizhi , Rabe Kari G. , Oberg Ann L. , Zaphiropoulos Peter G. , Chevet Eric , Graham Rondell P. , Hagen Catherine E. , di Magliano Marina P. , Elsawa Sherine F. , Pin Christopher L. , Mao Junhao , McWilliams Robert R. , Fernandez-Zapico Martin E.
Published: August 2024

Supplementary Figure 1 shows correlation of SNP rs1992901 and GLI2 Transcript Expression.