bluuebunny/crossref_metadata_2025 huggingface dataset:
Single field inflation in the light of Pulsar Timing Array Data: quintessential interpretation of blue tilted tensor spectrum through Non-Bunch Davies initial condition
Authors: Choudhury Sayantan
Published: March 2024

In this work, we present a quintessential interpretation of having a blue-tilted tensor power spectrum for canonical single-field slow-roll inflation to explain the recently observed Pulsar Timing Array (NANOGrav 15-year and EPTA) signal of Gravitational Waves (GW). We formulate the complete semi-classical description of cosmological perturbation theory in terms of scalar and tensor modes using the Non-Bunch Davies initial condition. We found that the existence of the blue tilt $$(n_t)$$

(

n
t

)

within the favoured range $$1.2<n_t<2.5$$

1.2
<

n
t

<
2.5

can be explained in terms of a newly derived consistency relation. Further, we compute a new field excursion formula using the Non-Bunch Davies initial condition, that validates the requirement of Effective Field Theory in the sub-Planckian regime, $$|\Delta \phi |\ll M_{\textrm{pl}}$$

|
Δ
ϕ
|

≪

M
pl

for the allowed value of the tensor-to-scalar ratio, $$r<0.06$$

r
<
0.06

from CMB observations. In our study, we refer to this result as Anti Lyth bound as it violates the well-known Lyth bound originally derived for Bunch Davies initial condition. Further, we study the behaviour of the spectral density of GW and the associated abundance with the frequency, which shows that within the frequency domain $$10^{-9}~{\textrm{Hz}}<f<10^{-7}~{\textrm{Hz}}$$

10

-
9

Hz
<
f
<

10

-
7

Hz

the outcome obtained from our analysis is completely consistent with the Pulsar Timing Array (NANOGrav 15-year and EPTA) signal. Also, we found that the behaviour of GW spectra satisfies the CMB constraints at the low frequency, $$f_*\sim 7.7\times 10^{-17}~{\textrm{Hz}}$$

f

∗

∼
7.7
×

10

-
17

Hz

corresponding to the pivots scale wave number, $$k_*\sim 0.05~{\textrm{Mpc}}^{-1}.$$

k

∗

∼
0.05

Mpc

-
1

.

Finally, the sharp falling behaviour of the GW spectra within the frequency domain $$10^{-7}~{\textrm{Hz}}<f<1~{\textrm{Hz}}$$

10

-
7

Hz
<
f
<
1

Hz

validates our theory in the comparatively high-frequency regime as well.
Electric and dilatonic fields of a charged massive particle at rest in the field of a charged dilaton black hole
Authors: Kan Nahomi , Shiraishi Kiyoshi
Published: March 2024

We study linear-perturbation equations for the two-body system of a charged dilaton black hole, of which dilaton coupling constant is $$\alpha $$
α
, and a static particle with mass m, electric charge q, and dilatonic charge $$\beta m$$

β
m

. We find that a consistent condition for the coupled equations corresponds to the equilibrium condition of the test particle. The expressions of classical fields are given in closed analytical formulas in the most interesting case with $$\beta =\alpha $$

β
=
α

. We examine the electrical field around a charged dilaton black hole especially in the limit of the maximum electric charge and we find the electric Meissner effect which has been found for the Reissner–Nordström black hole in the Einstein–Maxwell system.
Little rip, pseudo rip and bounce cosmology with generalized equation of state in non-standard backgrounds
Authors: Trivedi Oem , Timoshkin Alexander V.
Published: March 2024

The discovery of universe’s late-time acceleration and dark energy has overseen a great deal of research into cosmological singularities and particularly future singularities. Perhaps the most extreme of such singlarities is the big rip, which has propelled a lot of work into ways of moderating it or seeking out alternatives to it and two such alternatives to the big rip are the Little rip and Pseudo rip. Another possibility to consider the far future of the universe is through bounce cosmologies, which presents its own interesting ideas. So in this work we investigate the Little rip, Pseudo rip and Bounce cosmology in non-standard cosmological backgrounds with a generalized equation of state in the presence of a viscous fluid. In particular we discuss about Chern-Simons cosmology and the RS-II Braneworld and discuss how the exotic and non-conventional nature of gravity in such cosmologies affect universal evolution in these scenarios. We find out that there are very significant differences in the behaviour of such cosmic scenarios in these universes in comparison to how they appear in the simple general relativistic universe.
Design and optimization of high-performance eco-friendly perovskite solar cells: Utilizing FAMASnGeI3 and CsGeI3 as absorbers and tuning HTL and interface parameters
Authors: Kumar Pritam , Sengar Brajendra Singh , Kumar Amitesh
Published: March 2024

In this work, several designs of lead-based and lead-free perovskite solar cells (PSCs) have been developed and investigated. For the proposed designs, CH3NH3PbI3 (lead-based), FAMASnGeI3, and CsGeI3 (lead-free) are used as absorber materials, [Formula: see text] and NiO have been used as Hole Transport Layer (HTL) materials and TiO2 as Electron Transport Layer (ETL) materials. ETL materials, in general, have more concern with stability issues and HTL materials have more issues with efficiency improvements. The effect of changing thickness, doping density and defect density of the absorber layer, as well as HTL, defect density of absorber/HTL interface and work functions of front and back contacts on the performance of the proposed devices, are investigated. To enhance the device performance, optimization of the device parameters is performed. After optimization of different parameters, it is observed that the lead-based device structure TiO2/CH3NH3PbI3/NiO has a maximum efficiency of 29.94%. Even the corresponding lead-free device structure TiO2/CsGeI3/NiO exhibits a maximum efficiency of 29.19%. Additionally, this study delved into the influence of altering series and shunt resistances, as well as temperature on the operational characteristics of the lead-free optimized device. Such eco-friendly and cost-effective alternatives as lead-free perovskite cells can be very promising for future work.
Nonlinear Dynamic Analysis and Forecasting of Symmetric Aerostatic Cavities Bearing Systems
Authors: Peng Ta-Jen , Kuo Ping-Huan , Huang Wei-Cheng , Wang Cheng-Chi
Published: March 2024

Symmetric Aerostatic Cavities Bearing (SACB) systems have attracted increasing attention in the field of high-precision machinery, particularly rotational mechanisms applied at ultra-high speeds. In an air bearing system, the air bearing serves as the main support, and the load-carrying capacity is not as high as that of oil film bearings. However, the aero-spindle can operate at considerably high rotational speeds with relatively lower heat generated from rotation compared with that of oil film bearings. In addition, the operating environment of air bearings does not easily cause the rotor to deform. Hence, through adequate design, air pressure systems exhibit a certain level of stability. In general, the pressure distribution function of air bearings exhibits strong nonlinearity when there are changes in the rotor mass or rotational speed, or when the bearing system is inadequately designed. These issues may lead to instabilities in the rotor, such as unpredictable nonperiodic movements, rotor collisions, or even chaotic movements under certain parameters. In this study, rotor oscillation was analyzed using the maximum Lyapunov exponent to identify whether chaotic behavior occurred. Machine learning methods were then used to establish models and predict the rotor behavior. Especially, random forest and extreme gradient boosting were combined to develop a new model and confirm whether this model offered higher prediction performance and more accurate results in predicting tendencies with considerable changes compared with other models. The results can be effectively used to predict the SACB system and prevent nonlinear behavior from occurring.
Generalization of arc shift for twisted knots
Authors: Negi Komal , Prabhakar Madeti
Published: March 2024

In this paper, we study the invariants of twisted knots derived from the invariants of virtual knots such as the arc shift number and the odd writhe. We provide a class of twisted knots such that the arc shift number of every member is 1.
Effects of free parameterized TOV equations on properties of neutron stars with hyperons
Authors: Li Miao , Ding Wen-Bo , Wei Jin-Ming , Du Jin-Fang
Published: March 2024

In view of the crucial role of the structure in neutron star (NS) research, parameterized TOV (PTOV) equations are used to calculate the static NS sequence with five parameters including [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text], which represent the five factors that impact the NS structure. In order to promote the efficiency in the combination of astronomical observations and the theory, we investigate the meticulous influences of the five factors on NS structure with various hyperons in this work. Results show that the maximum masses of NSs are reduced with the free parameters, respectively, whereas the variation trend of corresponding radii is wavy in some cases. Especially, when hyperons are included, the macroscopic properties of NSs, except redshift, are relatively smaller than those in conventional NS matter. The effects on conventional NSs and hyperonic NSs are quite different in the high NS mass area but diminish when the stellar mass is lower than approximately 1.5 times solar mass. Finally, comparing with observations, we predict constraints on the free parameters.
Quantum analogues of white noise delta functions
Authors: Accardi Luigi , Ji Un Cig , Saitô Kimiaki
Published: March 2024

In this paper, we construct a quantum analogue of a white noise delta function. For our main purpose, we first discuss several white noise delta functions, specially, an infinite-dimensional analogue of Donsker’s delta function. Then as a general setting, we construct white noise delta functions on white noise test functionals and we derive a Cauchy problem whose solution is given by the white noise delta function. Also, we prove that the white noise delta function is an eigenvector of the exotic Laplacian. By applying the canonical topological isomorphisms between the spaces of white noise operators and the spaces of white noise functionals, we formulate a quantum analogue of the white noise delta function which satisfies a quantum white noise differential equation associated with the quantum Volterra Laplacian. Finally, we prove that quantum analogue of the white noise delta function is an eigenoperator of the quantum exotic Laplacian.
Dynamic Oligopolistic Competition with Uncertainty and Supply Disruption Effects
Authors: Parilina Elena M. , Wrzaczek Stefan , Zaccour Georges
Published: March 2024

We consider a finite-horizon discrete-time dynamic model of oligopolistic competition, with uncertain supply. The firms (retailers) make their decisions on quantities (sales) and orders of goods from a nonstrategic manufacturer taking into account uncertainty in demand parameters and available supply capacity. The retailers need to satisfy the joint available supply capacity constraint. The model is described as a game played over an event tree with given transition probabilities. We find a normalized equilibrium for the game with coupling constraints. The two-step procedure to find this equilibrium is described. We provide the necessary conditions of the equilibrium and examine different scenarios of uncertainties in the model by numerical simulations.
Unsupervised Color-Based Nuclei Segmentation in Histopathology Images with Various Color Spaces and K Values Selection
Authors: Zhang Qi , Ying Zuobin , Shen Jian , Kou Seng-Ka , Sun Jingzhang , Zhang Bob
Published: March 2024

The development of digital pathology offers a significant opportunity to evaluate and analyze the whole slides of disease tissue effectively. In particular, the segmentation of nuclei from histopathology images plays an important role in quantitatively measuring and evaluating the acquired diseased tissue. There are many automatic methods to segment cell nuclei in histopathology images. One widely used unsupervised segmentation approach is based on standard k-means or fuzzy c-means (FCM) to process the color histopathology images to segment cell nuclei. Compared with the supervised learning method, this approach can obtain segmented nuclei without annotated nuclei labels for training, which saves a lot of labeling and training time. The color space and [Formula: see text] value among this method plays a crucial role in determining the nuclei segmentation performance. However, few works have investigated various color spaces and [Formula: see text] value selection simultaneously in unsupervised color-based nuclei segmentation with [Formula: see text]-means or FCM algorithms. In this study, we will present color-based nuclei segmentation methods with standard [Formula: see text]-means and FCM algorithms for histopathology images. Several color spaces of Haematoxylin and Eosin (H&E) stained histopathology data and various [Formula: see text] values among [Formula: see text]-means and FCM are investigated correspondingly to explore the suitable selection for nuclei segmentation. A comprehensive nuclei dataset with 7 different organs is used to validate our proposed method. Related experimental results indicate that [Formula: see text] and the YCbCr color spaces with a [Formula: see text] of 4 are more reasonable for nuclei segmentation via [Formula: see text]-means, while the [Formula: see text] color space with [Formula: see text] of 4 is useful via FCM.
The behavior of low-symmetry penta(chloro)cyclotriphosphazene-substituted monophthalocyanines in the oriented external electric fields
Authors: Tolbin Alexander Yu.
Published: March 2024

Electric field-mediated chemistry provides fertile ground for interdisciplinary research, where theoretical ideas and experimental data converge to unravel the complexities of molecular behavior under the influence of electric fields, offering unprecedented opportunities for scientific research and technological innovation. Thus, this work is devoted to the study underscoring the importance of oriented external electric fields (OEEFs) in modulating the structural and electronic properties of low-symmetry monophthalocyanines, which is crucial for enhancing their reactivity and nonlinear optical response. The highlight of this article is that the OEEFs lead to molecular conductivity due to reduced energy gap and electron density shifting towards the phosphazene ring. Additionally, there is a tendency for the elimination of chlorine atoms in the trans- position relative to the phthalocyanine macrocycle. Also, the use of the previously created CORRELATO algorithm has allowed the demonstration of the relationship between structural changes and microscopic parameters responsible for the appearance of NLO properties of final dye materials.
On Influence of Several Factors on Development of Tumors
Authors: Pankratov E. L.
Published: March 2024

A model to describe tumor development was introduced in the paper. The model takes into account division, nutrition and dying of the considered cells. An analytical approach for analysis of the introduced model has also been introduced. The approach gives a possibility of taking into account changes of conditions of the considered processes. The possibility of changing of their rates is being considered.
The comparing analysis of two parallelization schemes for computations with round memory
Authors: Kolpakov Roman
Published: March 2024

In this paper, we consider a tree-like recursion procedure of solving of binary decomposable problems. More specifically, we study some questions of parallelization of this procedure with using of shared round memory. We consider two parallelization schemes for parallel solving of binary decomposable problems by tree-like recursion procedures on a parallel computing system with shared round memory. We call these schemes the TAN-scheme and the TON-scheme of parallelization. We compare the efficiency of these schemes, using different parameters of parallelization. Based on this comparative analysis, we conclude the TON-scheme to be more effective.
Advancements in epidemiological modeling: Bayesian regularization neural networks for smoke dynamics
Authors: Bilal Muhammad , Rocha Eugenio , Raja Muhammad Asif Zahoor , Bilal Shafia , Ahmad Iftikhar , Usman Muhammad , Shoaib Muhammad
Published: March 2024

Using an artificial neural network and the Bayesian Regularization Technique (NNs-BRT), the stochastic method’s strength is used to analyze the differential system, illustrating a nonlinear smoke epidemic differential model (NSED). This allows for a more precise, dependable, cost-effective, dynamic calculating approach. In addition to experiments utilizing nonlinear mathematical structures through five distinct classes of differential operators-smokers contemplating quitting, infrequent smokers, regular smokers, those who have temporarily abstained from smoking, and those who have permanently quit smoking the NSED framework has been established. By allocating 25% of the data for testing and validation and 75% for training, the proposed NNs-BRT can determine the estimated solutions of five different examples based on the numerical computation of the NSED system employing Adams techniques. To prove the accuracy of the given NNs-BRTs, a comparison of the results from the dataset obtained using the Adam method for different scenarios reflecting variance in recruitment rate, effective contact rate between C and A, natural death rate, how quickly occasional smokers become regular smokers, contact rate between smokers, and temporary quitters, number of smokers quitting, and percentage of smokers who are still leaving for good is made. The use of error histograms, mean square error, regression, correlation, and state transitions is also examined in numerical replications of the NNs-BRTs to verify their competence, dependability, accuracy, consistency, and proficiency.
Modeling the spread of rice blast in rice plant group based on cellular automata
Authors: Ding Wei-Long , Zhu Wei , Fan Cheng-Cheng , Xu Li-Feng , Zhang Yu-Ping
Published: March 2024

Studying and modeling the process of the disease and spread of blast can guide fertilization and reduce the amount of pesticide application. Since most of the existing research focuses on the pathogenesis of the rice blast fungus and the interaction between the plant structure and the fungus, this paper presents a method to simulate the spread of rice blast among rice populations. The method is divided into the following processes. First, based on the cellular automata grid dynamics model, the cell state corresponds to the degree of infection of the rice blast fungus, and its ability to simulate the spatiotemporal evolution of complex systems is used to simulate the spread of disease spots on the surface of rice leaves. Second, according to the biological mechanism of the rice blast fungus and the position of the first infected leaf in a single rice plant, the normal distribution function is used to calculate the infection probability of the remaining leaves, and then the transmission mode of the disease inside a single rice plant is simulated. Then, in view of the natural phenomenon that the blast fungus spores spread with the wind, the wind factor is added to propose a method for the spread of the rice blast fungus among the population of rice plants, and thus a model for the spread of the pathogen among the entire plant population was established. Finally, we set up a simulation system for the spread of rice blasts in rice fields and visualized the spread and spread trend of rice blasts in rice populations. In the simulation experiment, the infection process of rice blast on the surface of the rice leaf was simulated, and the change process of the shape of the diseased spot can be visually seen. This paper not only provides a new idea for the research on pathogen propagation and diffusion between plants in agricultural production but also provides a reference for how to realistically visualize the pathogen propagation model in the virtual agricultural scene.
Green Synthesis and Characterization of Alocasia indica Assisted Zirconium Dioxide Nanoparticles for Improved Antimicrobial Application
Authors: Hossain Nayem , Chowdhury Mohammad Asaduzzaman , Hossain Amran , Mobarak Md Hosne , Islam Md. Aminul , Abdullah Md. , Rahman Md. Majibur
Published: March 2024

Nanoparticles (NPs) are synthesized in different methods such as physical or chemical which are costly and harmful to the environment. However, green synthesis is a cost-effective and environment-friendly NPs synthesis approach. Green-synthesized NPs are highly effective against various bacterial strains. Zirconium dioxide nanoparticles ([Formula: see text]) have been synthesized in this research using a cost-effective green synthesis approach for improved antimicrobial activity. For the synthesis of the NPs, Alocasia indica has been used as a reducing agent. The extract of Alocasia indica was prepared and reacted with the light solution of ZrOCl2 ⋅ 8H2O. The successful formation of [Formula: see text] was confirmed by the color change in the solution. Some analytical techniques, including Ultraviolet-visible (UV) spectroscopy, Fourier Transformed Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Energy Dispersive X-ray (EDX), X-ray diffraction (XRD), and bacterial inhibition analyses have been performed to analyze the performance of the synthesized NPs. The peaks formed in the UV analysis also confirmed the formation of NPs in the solution. The presence of various functional groups in the synthesized [Formula: see text] has been confirmed by the FTIR analysis. TEM analysis revealed that the synthesized NPs were almost circular. The formation of peak confirmed the crystalline structure of the NPs. Impressively; a 99.99% bacterial inhibition rate was obtained against the gram-positive bacteria strain. The synthesized [Formula: see text] have great potential for biomedical applications such as medicine and implants for its excellent antimicrobial applications.
Extraction of Nano Hydroxyapatite from Eggshell and Characterization for Biomedical Applications
Authors: Hossain Nayem , Tajim Tanjid Al , Islam Safiul , Mim Juhi Jannat , Abdullah Md. , Chowdhury Mohammad Asaduzzaman , Rahman Md. Majibur
Published: March 2024

Because of the exceptional qualities, nano-hydroxyapatites, or n-HA, are excellent materials for diverse applications. It is simple and convenient to synthesize from various natural ingredients. The synthesis of n-HA from eggshells, a typical domestic waste product in the neighborhood, was the primary goal of this study project. This synthesis of n-HA was performed using ammonia and orthophosphoric acid as chemical reagents. The synthesized n-HA have been characterized by UV (Ultraviolet), FTIR (Fourier Transformed Infrared Spectroscopy), SEM (Scanning Electron Microscopy), TEM (Transmission Electron Microscopy), and XRD (X-ray diffraction) analysis. The peak formed by the UV analysis verified the successful formation of n-HA in the solution. The bandgap has been determined through additional research on the UV data. The SEM and TEM images show the size and form of the synthesized n-HA. Based on TEM observations, the synthesized n-HA has a size in the range of 10 to 40 nm. The peak ensures the n-HA’s crystallinity that the XRD analysis produced. The obtained crystallinity was 74%.
Degradation Profiles of MgO@Graphene Nanocomposite Photocatalyst for Organic and Antibiotic Pollutants: Novel Approaches
Authors: Fouda Safaa R. , Yehia I. S.
Published: March 2024

Streptomycin was chosen as the test species, and MgO@graphene nanocomposites were created and assessed for their catalytic activity towards the breakdown of 4-NP. As a new catalyst with strong catalytic activity and good stability, MgO@graphene was used. It was discovered that this catalyst’s catalytic activity was much increased in an acidic environment. It is suggested that the degradation mechanism is caused by MgO@graphene nanocomposites reacting with dissolved oxygen. This further demonstrates the obvious significance of graphene in serving as the MgO nanocatalyst’s support. XRD results indicated that the majority of G species in MgO@ (0.25 g) G more strongly interacted with the MgO surface. The doped catalyst MgO@ (0.25 g) G reached its steady state activity faster than the other catalysts. The degree of MgO@G interaction decreased in the following S4 > S[Formula: see text] > S[Formula: see text] > S[Formula: see text] > S[Formula: see text] > S5 > S[Formula: see text] > S[Formula: see text]. High degradation rate constants were found, and the amounts of streptomycin and 4-nitrophenol vary exponentially over time. It was demonstrated that, in most situations, the pseudo-first- order equation fits the degradation kinetics. Hence, in degrading systems, MgO NPs@Graphene nanostructures are thought to be a very effective and promising catalyst.
On the Dependence of Acoustic Modes on Media Parameters in the Pekeris-Airy Waveguide
Authors: Petrov Pavel S. , Zakharenko Alena D. , Matskovskiy Andrey A. , Zavorokhin German L. , Dosso Stan E.
Published: March 2024

A waveguide consisting of an isospeed water layer overlying a halfspace with a sound speed gradient is considered. The dependence of horizontal wavenumbers of normal modes in such a waveguide on the sound frequency, water depth and geoacoustic parameters of the bottom are investigated. It is shown that these dependencies are described by ordinary differential equations that can be solved numerically at very low computational cost providing a substantial increase in the efficiency of broadband modelling of sound propagation. The explicit formulae for the derivatives of horizontal wavenumbers with respect to the bottom parameters can be also used in dispersion-based geoacoustic inversion methods. This approach can be extended to the case of a waveguide consisting of several layers of Airy-type media. We also propose a new and concise proof that the spectrum of the Sturm-Liouville problem from which the modes are found for this waveguide is purely discrete.
Aggregating, Summarizing, and Restructuring News-Related Tweets into Compositions Using Deep Learning
Authors: Sharma Richa , Thukral Anjali , Kapoor Yatin , Varshney Ashwani , Bedi Punam
Published: March 2024

With the advent of microblogging platforms like Twitter, there has been a substantial shift toward digital media for getting acquainted with ongoing global issues. Although Twitter is an incredible source of information for real-time news, the information is widely scattered, opinionated, and unorganized, making it tedious for users to apprise themselves of the latest issues. Therefore, this study proposes a framework to automatically generate short news compositions from tweets utilizing state-of-the-art artificial intelligence techniques. The proposed framework scrapes tweets from authentic news Twitter handles, semantically analyzes and clusters them, predicts sentence ordering of the formed clusters, and summarizes the text of the clusters to produce structured compositions automatically. The generated compositions are further augmented with their corresponding sentiment scores to provide an overall perspective to the end-user toward the news topic in consideration. Evaluating the automatically generated compositions shows that the proposed framework is 77.5% efficient in generating quality compositions.
NAVIDRO, a CARES architectural style for configuring drone co-simulation
Authors: Salmon Loic , Pillain Pierre-Yves , Guillou Goulven , Babau Jean-Philippe
Published: March 2024

One primary objective of drone simulation is to evaluate diverse drone configurations and contexts aligned with specific user objectives. The initial challenge for simulator designers involves managing the heterogeneity of drone components, encompassing both software and hardware systems, as well as the drone’s behavior. To facilitate the integration of these diverse models, the Functional Mock-Up Interface (FMI) for co-simulation proposes a generic data-oriented interface. However, an additional challenge lies in simplifying the configuration of co-simulation, necessitating an approach to guide the modeling of parametric features and operational conditions such as failures or environment changes.

The article addresses this challenge by introducing CARES, a model-driven engineering and component-based approach for designing drone simulators, integrating the FMI for co-simulation. The proposed models incorporate concepts from component-based software engineering and FMI. The NAVIDRO architectural style is presented for designing and configuring drone co-simulation. CARES utilizes a code generator to produce structural glue code (Java or C++), facilitating the integration of FMI-based domain-specific code. The approach is evaluated through the development of a simulator for navigation functions in an autonomous underwater vehicle, demonstrating its effectiveness in assessing various autonomous underwater vehicle configurations and contexts.
Perceiving Actions via Temporal Video Frame Pairs
Authors: Li Rongchang , Xu Tianyang , Wu Xiao-Jun , Shen Zhongwei , Kittler Josef
Published: March 2024

Video action recognition aims at classifying the action category in given videos. In general, semantic-relevant video frame pairs reflect significant action patterns such as object appearance variation and abstract temporal concepts like speed, rhythm, and so on. However, existing action recognition approaches tend to holistically extract spatiotemporal features. Though effective, there is still a risk of neglecting the crucial action features occurring across frames with a long-term temporal span. Motivated by this, in this article, we propose to perceive actions via frame pairs directly and devise a novel Nest Structure with frame pairs as basic units. Specifically, we decompose a video sequence into all possible frame pairs and hierarchically organize them according to temporal frequency and order, thus transforming the original video sequence into a Nest Structure. Through naturally decomposing actions, the proposed structure can flexibly adapt to diverse action variations such as speed or rhythm changes. Next, we devise a Temporal Pair Analysis module (TPA) to extract discriminative action patterns based on the proposed Nest Structure. The designed TPA module consists of a pair calculation part to calculate the pair features and a pair fusion part to hierarchically fuse the pair features for recognizing actions. The proposed TPA can be flexibly integrated into existing backbones, serving as a side branch to capture various action patterns from multi-level features. Extensive experiments show that the proposed TPA module can achieve consistent improvements over several typical backbones, reaching or updating CNN-based SOTA results on several challenging action recognition benchmarks.
A Novel Framework for Joint Learning of City Region Partition and Representation
Authors: Deng Mingyu , Zhang Wanyi , Zhao Jie , Wang Zhu , Zhou Mingliang , Luo Jun , Chen Chao
Published: March 2024

The proliferation of multimodal big data in cities provides unprecedented opportunities for modeling and forecasting urban problems, such as crime prediction and house price prediction, through data-driven approaches. A fundamental and critical issue in modeling and forecasting urban problems lies in identifying suitable spatial analysis units, also known as city region partition. Existing works rely on subjective domain knowledge for static partitions, which is general and universal for all tasks. In fact, different tasks may need different city region partitions. To address this issue, we propose
JLPR
, a task-oriented framework for
J
oint
L
earning of region
P
artition and
R
epresentation. To make partitions fit tasks, JLPR integrates the region partition into the representation model training and learns region partitions using the supervision signal from the downstream task. We evaluate the framework on two prediction tasks (i.e., crime prediction and housing price prediction) in Chicago. Experiments show that JLPR consistently outperforms state-of-the-art partitioning methods in both tasks, which achieves above 25% and 70% performance improvements in terms of mean absolute error for crime prediction and house price prediction tasks, respectively. Additionally, we meticulously undertake three visualization case studies, which yield profound and illuminating findings from diverse perspectives, demonstrating the remarkable effectiveness and superiority of our approach.
Fine-grained Cryptanalysis: Tight Conditional Bounds for Dense
k
-SUM and
k
-XOR
Authors: Dinur Itai , Keller Nathan , Klein Ohad
Published: March 2024

An average-case variant of the
k
-SUM conjecture asserts that finding
k
numbers that sum to 0 in a list of
r
random numbers, each of the order
r

k

, cannot be done in much less than

\(r^{\lceil k/2 \rceil }\)

time. However, in the
dense regime
of parameters, where the list contains more numbers and many solutions exist, the complexity of finding one of them can be significantly improved by Wagner’s
k
-tree algorithm. Such algorithms for
k
-SUM in the dense regime have many applications, notably in cryptanalysis.

In this article, assuming the average-case
k
-SUM conjecture, we prove that known algorithms are essentially optimal for
k
= 3,4,5. For
k
> 5, we prove the optimality of the
k
-tree algorithm for a limited range of parameters. We also prove similar results for
k
-XOR, where the sum is replaced with exclusive or.

Our results are obtained by a self-reduction that, given an instance of
k
-SUM that has a few solutions, produces from it many instances in the dense regime. We solve each of these instances using the dense
k
-SUM oracle and hope that a solution to a dense instance also solves the original problem. We deal with potentially malicious oracles (that repeatedly output correlated useless solutions) by an obfuscation process that adds noise to the dense instances. Using discrete Fourier analysis, we show that the obfuscation eliminates correlations among the oracle’s solutions, even though its inputs are highly correlated.
Diversifying Sequential Recommendation with Retrospective and Prospective Transformers
Authors: Shi Chaoyu , Ren Pengjie , Fu Dongjie , Xin Xin , Yang Shansong , Cai Fei , Ren Zhaochun , Chen Zhumin
Published: March 2024

Previous studies on sequential recommendation (SR) have predominantly concentrated on optimizing recommendation accuracy. However, there remains a significant gap in enhancing recommendation diversity, particularly for short interaction sequences. The limited availability of interaction information in short sequences hampers the recommender’s ability to comprehensively model users’ intents, consequently affecting both the diversity and accuracy of recommendation. In light of the above challenge, we propose
reTrospective and pRospective Transformers for dIversified sEquential Recommendation (TRIER)
. The TRIER addresses the issue of insufficient information in short interaction sequences by first retrospectively learning to predict users’ potential historical interactions, thereby introducing additional information and expanding short interaction sequences, and then capturing users’ potential intents from multiple augmented sequences. Finally, the TRIER learns to generate diverse recommendation lists by covering as many potential intents as possible.

To evaluate the effectiveness of TRIER, we conduct extensive experiments on three benchmark datasets. The experimental results demonstrate that TRIER significantly outperforms state-of-the-art methods, exhibiting diversity improvement of up to 11.36% in terms of intra-list distance (ILD@5) on the Steam dataset, 3.43% ILD@5 on the Yelp dataset and 3.77% in terms of category coverage (CC@5) on the Beauty dataset. As for accuracy, on the Yelp dataset, we observe notable improvement of 7.62% and 8.63% in HR@5 and NDCG@5, respectively. Moreover, we found that TRIER reveals more significant accuracy and diversity improvement for short interaction sequences.
Cerberus: Triple Mode Acceleration of Sparse Matrix and Vector Multiplication
Authors: Hwang Soojin , Baek Daehyeon , Park Jongse , Huh Jaehyuk
Published: March 2024

The multiplication of sparse matrix and vector (SpMV) is one of the most widely used kernels in high-performance computing as well as machine learning acceleration for sparse neural networks. The design space of SpMV accelerators has two axes: algorithm and matrix representation. There have been two widely used algorithms and data representations. Two algorithms, scalar multiplication and dot product, can be combined with two sparse data representations, compressed sparse and bitmap formats for the matrix and vector. Although the prior accelerators adopted one of the possible designs, it is yet to be investigated which design is the best one across different hardware resources and workload characteristics. This paper first investigates the impact of design choices with respect to the algorithm and data representation. Our evaluation shows that no single design always outperforms the others across different workloads, but the two best designs (i.e., compressed sparse format and bitmap format with dot product) have complementary performance with trade-offs incurred by the matrix characteristics. Based on the analysis, this study proposes Cerberus, a triple-mode accelerator supporting two sparse operation modes in addition to the base dense mode. To allow such multi-mode operation, it proposes a prediction model based on matrix characteristics under a given hardware configuration, which statically selects the best mode for a given sparse matrix with its dimension and density information. Our experimental results show that Cerberus provides 12.1× performance improvements from a dense-only accelerator, and 1.5× improvements from a fixed best SpMV design.
Generative Adversarial Networks with Learnable Auxiliary Module for Image Synthesis
Authors: Gan Yan , Yang Chenxue , Ye Mao , Huang Renjie , Ouyang Deqiang
Published: March 2024

Training generative adversarial networks (GANs) for noise-to-image synthesis is a challenge task, primarily due to the instability of GANs’ training process. One of the key issues is the generator’s sensitivity to input data, which can cause sudden fluctuations in the generator’s loss value with certain inputs. This sensitivity suggests an inadequate ability to resist disturbances in the generator, causing the discriminator’s loss value to oscillate and negatively impacting the discriminator. Then, the negative feedback of discriminator is also not conducive to updating generator’s parameters, leading to suboptimal image generation quality. In response to this challenge, we present an innovative GANs model equipped with a learnable auxiliary module that processes auxiliary noise. The core objective of this module is to enhance the stability of both the generator and discriminator throughout the training process. To achieve this target, we incorporate a learnable auxiliary penalty and an augmented discriminator, designed to control the generator and reinforce the discriminator’s stability, respectively. We further apply our method to the Hinge and LSGANs loss functions, illustrating its efficacy in reducing the instability of both the generator and the discriminator. The tests we conducted on LSUN, CelebA, Market-1501 and Creative Senz3D datasets serve as proof of our method’s ability to improve the training stability and overall performance of the baseline methods.
The Pupae of Culicomorpha—Morphology and a New Phylogenetic Tree
Authors: BORKENT ART
Published: March 2024

The pupae of each of the families of the Culicomorpha are described and, for the first time, their structures homologized.A glossary provides a standard set of terms to be applied to each structure, including a common chaetotaxy. A cladisticanalysis incorporates information from each life stage, including a number of new features discovered from the pupalstage, to provide a new phylogenetic hypothesis, as well as indicating autapomorphies for each family. Analysisincluded states for one egg, 21 larval, 33 pupal, and 37 adult characters. The Chironomidae is the sister group of allremaining Culicomorpha, the Ceratopogonidae is the sister group of Thaumaleidae + Simuliidae and these three arenewly recognized as members of the re-defined superfamily Simulioidea. The superfamily Culicoidea are the sistergroup of the Simulioidea and include, as previous work has already demonstrated, the Dixidae as the sister group ofCorethrellidae + Chaoboridae + Culicidae. Corethrellidae is the sister group of Chaoboridae + Culicidae. Thesuperfamily Chironomoidea now includes only Chironomidae.Analysis of the fossil record shows that the Chironomidae (and the Culicomorpha) originated in the Triassic andboth Simulioidea and Culicoidea were present by 176 million years ago in the Jurassic. Phylogenetic patterns are used tointerpret bionomic features such as differences in the nature of blood-feeding by adult females, daytime or nighttimefeeding by adult females, and occurrence of immature stages in aquatic habitats. Chironomidae do not feed on blood asadults and have likely diversified by invading virtually all aquatic habitats as larvae. Its sister group is more than twiceas diverse and feeding on vertebrate blood is strongly correlated with high diversification within the Simulioidea +Culicoidea (likely because a reliable source of protein was available to dispersing females since the Triassic fromterrestrial vertebrates). Families with blood-feeding females have larger numbers of species than do those without thisbehaviour. Each family in the Simulioidea + Culicoidea have specialized larval habitats or specialized habits, largely inaquatic habitats where Chironomidae are either not, or are marginally present, suggesting a level of competitive exclusion by the Chironomidae.
First record of the genus Chinapotamon Dai & Naiyanetr, 1994 (Crustacea: Decapoda: Brachyura: Potamidae) from northern Vietnam with description of one new species
Authors: ANH LE HUNG , DONG DANG VAN , TU DO VAN
Published: March 2024

Our recent surveys in North Vietnam found three species of the potamid genus Chinapotamon Dai & Naiyanetr, 1994. Two species may be identified as species described from Southern China, C. depressum (Dai, Song, Li & Liang, 1980) and C. pusillum (Song, 1984), and one species is new to science. The new species can be distinguished from other congeners by its smaller carapace size, more subquadrate carapace, strongly convex and rugose carapace dorsal, low epigastric and postorbital cristae, high epibranchial tooth, deep notch between epibranchial tooth and anterolateral margin, deep concavity between frontal margin lobes, stout last ambulatory merus, narrow telson, slender gonopod 1 terminal segment bent at about 10° inwards and a relatively short gonopod 2. It is the first record of this genus in Vietnam. The present study raises the total number of freshwater crab species belonging to Potamidae in Vietnam to 60.
Cryptonome beatrizae n. sp., from drifting wood in Western Mexico, with remarks on Pareurythoe Gustafson, 1930 (Annelida, Amphinomidae)
Authors: TOVAR-HERNÁNDEZ MARÍA ANA , GONZÁLEZ-VALLEJO NORMA EMILIA , SALAZAR-VALLEJO SERGIO I.
Published: March 2024

Only five species of fireworms (Annelida: Amphinomidae) belonging to the genera Cryptonome Borda, Kudenov, Bienhold & Rouse, 2012, Linopherus de Quatrefages, 1866 and Pareurythoe Gustafson, 1930 have been reported as xylophilic. In this study, a new species of Cryptonome is described from driftwood found in the southern Gulf of California, including a short comment on other associated stowaways. Cryptonome is amended based on the presence of dorsal cirri being cirriform, smooth or pseudarticulate; Pareurythoe is restricted to specify the presence of caruncle sigmoid without lateral lobes and parapodial cirri smooth; and a key for identifying the species in Cryptonome is also included. The holotype of Hipponoe elongata Treadwell, 1931 is redescribed and newly combined in Cryptonome, whereas the holotype of Eurythoe spirocirrata Essenberg, 1917 previously regarded as Pareurythoe is returned to its original genus, Eurythoe Kinberg, 1857, and some of its morphological features are clarified.
Two new species of the genus Megascolex Templeton, 1844 (Clitellata, Megascolecidae) from the Eastern Ghats of Odisha state, India
Authors: NAIK AYUSMITA , NARAYANAN S. PRASANTH , PALITA SHARAT KUMAR , THOMAS A.P. , PALIWAL R.
Published: March 2024

Two new earthworm species of Megascolex Templeton, 1844, M. quadripapillatus Narayanan & Paliwal, sp. nov. and M. jeyporeghatiensis Narayanan & Paliwal, sp. nov. are described from the under-explored Eastern Ghats Hills of Odisha state in Peninsular India. They belong to a group of species characterized by two pairs of spermathecal pores in intersegmental furrows 7/8/9, holandric, seminal vesicles in segments 9 and 12, absence of penial setae and calciferous glands. Megascolex ratus Cognetti, 1911, M. pumilio Stephenson, 1916 and the two new species described here are the members of this group. Megascolex quadripapillatus sp. nov. and M. jeyporeghatiensis sp. nov. occur in deciduous forests with brownish gravel-loamy soils. Here we provide the detailed description of the external and internal characteristics of the new species along with the illustrations of the key characters. With the new findings, the range of Megascolex genus has been extended further north in the less explored Eastern Ghats Hills of India. With this discovery, the total number of Megascolex species has increased to 70, of which 34 are found in India.
Discovery of the Japan-Nearctic genus Chasmatonotus from the Korean Peninsula, with description of a new species (Diptera, Chironomidae)
Authors: SAIGUSA TOYOHEI
Published: March 2024

A new species of the chironomid genus Chasmatonotus, C. yamamotoi sp. nov. is described from the southern mountainous area of the Korean Peninsula. This represents the first record of the genus from Continental Asia, hitherto known as Japan-Nearctic in distribution.
A new genus and species of Anisocerini (Coleoptera: Cerambycidae) from Ecuador
Authors: GARCÍA KIMBERLY , VLASAK JOSEF
Published: March 2024

Pachyforma rosacea gen. nov., sp. nov. (Anisocerini) is described from the tropical dry forest of southern Ecuador. A key to the related genera of Anisocerini is provided.
Book review: K. B. Saxena (Ed.), Private Sector Participation in Public Services: Health
Authors: Nagla Madhu
Published: March 2024

K. B. Saxena (Ed.), Private Sector Participation in Public Services: Health. Noida: Aakar Books, 2022, 293 pp., ₹995. ISBN 978-93-50002-761-5 (Hardbound).
The Chinese Pothi: A Missing Link in the History of the Chinese Book
Authors: Galambos Imre
Published: March 2024

This paper examines Chinese pothi manuscripts from Dunhuang, arguing that this book form played an important role in the history of the Chinese book. Ultimately emulating Indian palm leaf manuscripts, the few dozen examples of Chinese pothi come from Dunhuang, where they appeared during the Tibetan control of the region. Rather than being a local phenomenon, the pothi form was instrumental in the development of more mainstream book forms, most notably the concertina.