Multi-Granularity Neighborhood Fuzzy Rough Set Model on Two Universes

The two universes multi-granularity fuzzy rough set model is an effective tool for handling uncertainty problems between two domains with the help of binary fuzzy relations. This article applies the idea of neighborhood rough sets to two universes multi-granularity fuzzy rough sets, and discusses the two-universes multi-granularity neighborhood fuzzy rough set model. Firstly, the upper and lower approximation operators are defined in the two universes multi-granularity neighborhood fuzzy rough set model. Secondly, the properties of the upper and lower approximation operators are discussed. Finally, the properties of the two universes multi-granularity neighborhood fuzzy rough set model are verified through case studies.

Universes Being Invisible on Earth outside the Portals Are Visible in Portals

The authors of the existing version of the special theory of relativity had to use the princi-ple of light speed non-exceedance to explain relativistic formulas obtained therein within the space of real numbers. The principle implied existence of only our visible universe and absence of physical content in imaginary numbers. However, since the principle is just a postulate, i.e. an unproven assumption, it has always carried little credibility. The paper refutes the principle by the experimentally proven principle of physical reality of imagi-nary numbers. As follows from the principle of physical reality of imaginary numbers, relativistic formulas of the existing version of the STR are wrong and incorrectly ex-plained, and conclusions drawn from them are misguided. In other words, this version is incorrect1 and, thus, the STR was not actually created in the 20th century. Moreover, it could not be created in the 20th century, as its creation required experimental data ob-tained in the 21st century. The paper provides an alternative version of the STR contain-ing relativistic formulas corrected given experimental data obtained in the 21st century. These formulas imply that instead of the Monoverse, whose existence is supposed in the existing version of the STR, there is a Multiverse, whose universes are mutually invisible (and the invisibility is explainable) and therefore it has been referred to as hidden. The paper explains that existence of invisible universes of the hidden Multiverse gives rise to the phenomenon of dark matter and dark energy that is actually a sort of optical effect (however, not electromagnetic, but gravitational), a shadow, rather than some physical substance2. It also explains that existence of other invisible universes outside the hidden Multiverse gives rise to the phenomenon of dark space. Invisible universes are claimed to really exist, which can be experimentally proved by astronomical observations in portals, where universes not visible outside portals become partially visible. Therefore, constella-tions observed in the starry sky inside the portals are different from those observed in our visible universe. The alternative version of the special theory of relativity can also suc-cessfully solve other issues of astrophysics. In particular, it can explain where antimatter is located and why it does not annihilate with matter, as well as where tachyons are locat-ed and why they don’t violate the principle of causality, etc.

How to See Invisible Universes

The article shows that the special theory of relativity (STR) was not actually created in the 20th century, since: 1) the relativistic formulas presented therein are incorrect;2) the relativistic formulas presented therein are explained incorrectly using the incorrect principle of light speed non-exceedance refuted in the article;3) the relativistic formulas presented therein rise to incorrect conclusions about physical unreality of imaginary numbers and existence of only our visible universe. Moreover, the STR could not even have been created in the 20th century since: 1) experimental data on the six-dimensional space of our hidden Multiverse, which allowed to derive the correct relativistic formulas, were obtained by the WMAP and Planck spacecraft only in the 21st century;2) the principle of physical reality of imaginary numbers, which allowed to refute the principle of not exceeding the speed of light and correctly explain the new relativistic formulas, was experimentally proved only in the 21st century. Therefore, the new relativistic formulas obtained given these circumstances allow to state that, in addition to our visible universe, there are numerous other mutually invisible universes, which together form the hidden Multiverse. Existence of invisible universes explains the phenomenon of dark matter and dark energy. Their existence also explains why antimatter in the hidden Multiverse does not annihilate with matter, and tachyons do not violate the principle of causality. The existence of these invisible universes can be proved by astronomical observations in the portals, since in them the constellations of the starry sky will differ from the constellations observed from existing observatories on Earth.

The Cyclic Universes Model Based on the Split Division Algebras

The proposed cyclic universes model based on the split division algebras accounts for the inflation, the Big Bang, gravity, dark energy, dark matter, the standard model, and the masses of all elementary particles. The split algebras (complex quaternion and complex octonion) as the Furey model generate the fixed spacetime dimension number for the observable universe with the fixed 4-dimensional spacetime (4D) standard model particles and the oscillating spacetime dimension number for the oscillating universes (hidden or dark energy) with the oscillation between 11D and 11D through 10D and between 10D and 10D through 4D. 11D has the lowest rest mass, the highest speed of light, and the highest vacuum energy, while 4D has the highest rest mass, the lowest (observed) speed of light, and zero vacuum energy. In the cyclic universes model, the universes start with the positive-energy and the negative-energy 11D membrane-antimembrane dual universes from the zero-energy inter-universal void, and are followed by the transformation of the 11D membrane-antimembrane dual universes into the 10D string-antistring dual universes and the external dual gravities as in the Randall-Sundrum model, resulting in the four equal and separate universes consisting of the positive-energy 10D universe, the positive-energy external gravity, the negative-energy 10D universe, and the negative-energy external gravity. Under the fixed spacetime dimension number, the positive-energy 10D universe is transformed into 4D standard model particles through the inflation and the Big Bang. Dark matter is the right-handed neutrino, exactly five times of baryonic matter in total mass in the universe. Under the oscillating spacetime dimension number, the other three universes oscillate between 10D and 10D through 4D, resulting in the hidden universes when D > 4 and dark energy (the maximum dark energy = 3/4 = 75%) when D = 4. Eventually, all four universes return to the 10D universes.

Multiple Production of Bianchi Type-I Universes

The procedure similar to an ordinary quantum held theory in curved spacetime is applied to study the Bianchi type-I universes with a radiation field source.The Wheeler-De Witt equation satisfied by the cosmological wave function is found.After the wave function was regarded as a universe held in the minisuperspace,not only the difficulty in a probabilistic interpretation in the quantum cosmology can be circumvented,but also the conclusion of the multiple production of universes is obtained,and the average number of various universes created from‘nothing’is estimated.

Cosmic String Universes Embedded with Viscosity

We study string cosmological models with attached particles in LRS BI type space time. The dynamical and physical properties of such universes are studied, and the possibility that during the evolution of the universe the strings disappear, leaving only the particles, is also discussed. It is found that bulk viscosity plays a large role in the evolution of the universe. In these models we find critical instances of when there was a "Bounce". The studied models are found to be of an inflationary type, and since a desirable feature of a meaningful string cosmological model is the presence of an inflationary epoch in the very early stages of evolution, our models can be thought of as realistic universes.

THE EINSTEIN AND DE SITTER UNIVERSES UNDER THE HARMONIC CONDITION

Under the harmonic condition the Einstein and the static de Sitter universes in relativistic cosmology are again solved.According to the view that the harmonic condition is a physical one,the size of the static de Sitter universe is infinite.

Bianchi Type- III and Kantowski-Sachs Universes with wet Dark Fluid

The Bianchi type- III and Kantowski-Sachs (KS) Universes filled with dark energy from a wet dark fluid has been considered. A new equation of state for the dark energy component of the universe has been used. It is modeled on the equation of state ρ=γ(ρ -ρ *) , which can describe a liquid, for example water. The exact solutions to the corresponding field equations are obtained in quadrature form. The solution for constant deceleration parameter have been studied in detail for power-law and exponential forms both. The case γ = 0,γ =1,and γ =1/3have been also analysed.

Five Dimensional String Universes in Lyra Manifold

Considering five dimensional plane symmetric metric, we discuss a model universe with different situations, by solving the modified Einstein field equations within the framework of Lyra geometry. We obtain many interesting realistic solutions governing the present day model of the universe. Physical and kinematical properties of the models are discussed in detail.

Floquet spectrum and universal dynamics of a periodically driven two-atom system

We investigate the Floquet spectrum and excitation properties of a two-ultracold-atom system with periodically driven interaction in a three-dimensional harmonic trap.The interaction between the atoms is changed by varying the s-wave scattering length in two ways,the cosine and the square-wave modulations.It is found that as the driving frequency increases,the Floquet spectrum exhibits two main features for both modulations,the accumulating and the spreading of the quasienergy levels,which further lead to different dynamical behaviors.The accumulation is associated with collective excitations and the persistent growth of the energy,while the spread indicates that the energy is bounded at all times.The initial scattering length,the driving frequency and amplitude can all significantly change the Floquet spectrum as well as the dynamics.However,the corresponding relation between them is valid universally.Finally,we propose a mechanism for selectively exciting the system to one specific state by using the avoided crossing of two quasienergy levels,which could guide preparation of a desired state in experiments.

A general synthetic strategy for N, P co-doped graphene supported metal-rich noble metal phosphides for hydrogen generation

The exploitation of electrocatalysts with high activity and durability for HER is desirable for future energy systems,but it is still a challenge.NMPs have attracted increasing attentions,but the preparation process often needs toxic regents or dangerous reaction conditions.Herein,we develop a general green method to fabricate metal-rich NMPs anchored on NPG through pyrolyzing DNA cross-linked complexes.The obtained Ru_(2) P-NPG exhibits an ultrasmall overpotential of 7 mV at 10 mA cm^(2) and ultralow Tafel slope of 33 mV dec^(-1) in 1.0 mol L?1 KOH,even better than that of commercial Pt/C.In addition,Ru 2 P-NPG also shows low overpotentials of 29 and 78 mV in 0.5 mol L^(-1) H_(2)SO_(4) and 1.0 mol L^(-1) PBS,respectively.The superior activity can be attributed to the ultrafine dispersion of Ru 2 P nanoparticles for more accessible sites,more defects formed for abundant active sites,the two-dimensional plane structure for accelerated electron transfer and mass transport,as well as the regulation of electron distribution of the catalyst.Moreover,the synthetic method can also be applied to prepare other metal-rich noble metal phosphides(Pd_(3)P-NPG and Rh_(2)P-NPG),which also exhibits high activity for HER.This work provides an effective strategy for designing NMP-based electrocatalysts.

Comparison of vergence mechanisms between university students with good and poor sleep quality

AIM:To compare the vergence mechanisms between good and poor sleepers in university students.METHODS:A total of 64 university students were recruited in this study.The validated Malay version of Pittsburgh Sleep Quality Index questionnaire(PSQI-M)was used to measure the participants’sleep quality over the past month.Participants were categorized as good sleepers(n=32)and poor sleepers(n=32)based on the PSQI-M scores.Heterophoria and fusional vergences were measured at distance and near.Mann-Whitney U test was used to compare heterophoria,negative fusional vergence(NFV),and positive fusional vergence(PFV)at distance and near between good and poor sleepers.Spearman correlation analysis was used to study the relationship between PSQI-M score and PFV at distance.RESULTS:Both distance and near heterophorias were not significantly different between good and poor sleepers(P>0.05).There was a difference in distance PFV(P<0.05)between good and poor sleepers,but not in distance NFV,near NFV,and near PFV(P>0.05).Distance PFV was negatively correlated with PSQI-M score(rs=-0.33,P<0.05).CONCLUSION:University students with poor sleep quality demonstrates a reduced ability to maintain fusion with increasing convergence demand at distance.Sleep quality assessment during binocular vision examination in university students is recommended.

Intelligent Recognition Using Ultralight Multifunctional Nano‑Layered Carbon Aerogel Sensors with Human‑Like Tactile Perception

Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.

A core-satellite self-assembled SERS aptasensor containing a“biological-silent region”Raman tag for the accurate and ultrasensitive detection of histamine

Herein,a novel interference-free surface-enhanced Raman spectroscopy(SERS)strategy based on magnetic nanoparticles(MNPs)and aptamer-driven assemblies was proposed for the ultrasensitive detection of histamine.A core-satellite SERS aptasensor was constructed by combining aptamer-decorated Fe_(3)O_(4)@Au MNPs(as the recognize probe for histamine)and complementary DNA-modified silver nanoparticles carrying 4-mercaptobenzonitrile(4-MBN)(Ag@4-MBN@Ag-c-DNA)as the SERS signal probe for the indirect detection of histamine.Under an applied magnetic field in the absence of histamine,the assembly gave an intense Raman signal at“Raman biological-silent”region due to 4-MBN.In the presence of histamine,the Ag@4-MBN@Ag-c-DNA SERS-tag was released from the Fe_(3)O_(4)@Au MNPs,thus decreasing the SERS signal.Under optimal conditions,an ultra-low limit of detection of 0.65×10^(-3)ng/mL and a linear range 10^(-2)-10^5 ng/mL on the SERS aptasensor were obtained.The histamine content in four food samples were analyzed using the SERS aptasensor,with the results consistent with those determined by high performance liquid chromatography.The present work highlights the merits of indirect strategies for the ultrasensitive and highly selective SERS detection of small biological molecules in complex matrices.

Enhanced Temporal Correlation for Universal Lesion Detection

Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks.However,3D CT blocks necessitate significantly higher hardware resources during the learning phase.Therefore,efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks.In this paper,we propose a ULD network with the enhanced temporal correlation for this purpose,named TCE-Net.The designed TCE module is applied to enrich the discriminate feature representation of multiple sequential CT slices.Besides,we employ multi-scale feature maps to facilitate the localization and detection of lesions in various sizes.Extensive experiments are conducted on the DeepLesion benchmark demonstrate that thismethod achieves 66.84%and 78.18%for FS@0.5 and FS@1.0,respectively,outperforming compared state-of-the-art methods.

A New Double Layer Multi-Secret Sharing Scheme

Cryptography is deemed to be the optimum strategy to secure the data privacy in which the data is encoded ahead of time before sharing it.Visual Secret Sharing(VSS)is an encryption method in which the secret message is split into at least two trivial images called’shares’to cover it.However,such message are always targeted by hackers or dishonest members who attempt to decrypt the message.This can be avoided by not uncovering the secret message without the universal share when it is presented and is typically taken care of,by the trusted party.Hence,in this paper,an optimal and secure double-layered secret image sharing scheme is proposed.The proposed share creation process contains two layers such as threshold-based secret sharing in the first layer and universal share based secret sharing in the second layer.In first layer,Genetic Algorithm(GA)is applied to find the optimal threshold value based on the randomness of the created shares.Then,in the second layer,a novel design of universal share-based secret share creation method is proposed.Finally,Opposition Whale Optimization Algorithm(OWOA)-based optimal key was generated for rectange block cipher to secure each share.This helped in producing high quality reconstruction images.The researcher achieved average experimental outcomes in terms of PSNR and MSE values equal to 55.154225 and 0.79365625 respectively.The average PSNRwas less(49.134475)and average MSE was high(1)in case of existing methods.

Detection Algorithm of Laboratory Personnel Irregularities Based on Improved YOLOv7

Due to the complex environment of the university laboratory,personnel flow intensive,personnel irregular behavior is easy to cause security risks.Monitoring using mainstream detection algorithms suffers from low detection accuracy and slow speed.Therefore,the current management of personnel behavior mainly relies on institutional constraints,education and training,on-site supervision,etc.,which is time-consuming and ineffective.Given the above situation,this paper proposes an improved You Only Look Once version 7(YOLOv7)to achieve the purpose of quickly detecting irregular behaviors of laboratory personnel while ensuring high detection accuracy.First,to better capture the shape features of the target,deformable convolutional networks(DCN)is used in the backbone part of the model to replace the traditional convolution to improve the detection accuracy and speed.Second,to enhance the extraction of important features and suppress useless features,this paper proposes a new convolutional block attention module_efficient channel attention(CBAM_E)for embedding the neck network to improve the model’s ability to extract features from complex scenes.Finally,to reduce the influence of angle factor and bounding box regression accuracy,this paper proposes a newα-SCYLLA intersection over union(α-SIoU)instead of the complete intersection over union(CIoU),which improves the regression accuracy while increasing the convergence speed.Comparison experiments on public and homemade datasets show that the improved algorithm outperforms the original algorithm in all evaluation indexes,with an increase of 2.92%in the precision rate,4.14%in the recall rate,0.0356 in the weighted harmonic mean,3.60%in the mAP@0.5 value,and a reduction in the number of parameters and complexity.Compared with the mainstream algorithm,the improved algorithm has higher detection accuracy,faster convergence speed,and better actual recognition effect,indicating the effectiveness of the improved algorithm in this paper and its potential for practical application in laboratory scenarios.

Extensive numerical simulations on competitive growth between the Edwards–Wilkinson and Kardar–Parisi–Zhang universality classes

Extensive numerical simulations and scaling analysis are performed to investigate competitive growth between the linear and nonlinear stochastic dynamic growth systems, which belong to the Edwards–Wilkinson(EW) and Kardar–Parisi–Zhang(KPZ) universality classes, respectively. The linear growth systems include the EW equation and the model of random deposition with surface relaxation(RDSR), the nonlinear growth systems involve the KPZ equation and typical discrete models including ballistic deposition(BD), etching, and restricted solid on solid(RSOS). The scaling exponents are obtained in both the(1 + 1)-and(2 + 1)-dimensional competitive growth with the nonlinear growth probability p and the linear proportion 1-p. Our results show that, when p changes from 0 to 1, there exist non-trivial crossover effects from EW to KPZ universality classes based on different competitive growth rules. Furthermore, the growth rate and the porosity are also estimated within various linear and nonlinear growths of cooperation and competition.

Investigating the Evolution of Amati Parameters with Redshift

Gamma-ray bursts(GRBs) are among the brightest objects in the Universe and, hence, can be observed up to a very high redshift. Properly calibrated empirical correlations between intensity and spectral correlations of GRBs can be used to estimate the cosmological parameters. However, the possibility of the evolution of GRBs with redshift is a long-standing puzzle. In this work, we used 162 long-duration GRBs to determine whether GRBs below and above a certain redshift have different properties. The GRBs are split into two groups, and we fit the Amati relation for each group separately. Our findings demonstrate that estimations of the Amati parameters for the two groups are substantially dissimilar. We perform simulations to investigate whether the selection effects could cause the difference. Our analysis shows that the differences may be either intrinsic or due to systematic errors in the data, and the selection effects are not their true origin. However, in-depth analysis with a new data set comprised of 119 long GRBs shows that intrinsic scatter may partly be responsible for such effects.

Short-term displacement prediction for newly established monitoring slopes based on transfer learning

This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.