The Role and Place of Artificial Neural Network Architectures Structural Redundancy in the Input Data Prototypes and Generalization Development

Neural Networks (NN) are the functional unit of Deep Learning and are known to mimic the behavior of the human brain to solve complex data-driven problems. Whenever we train our own neural networks, we need to take care of something called the generalization of the neural network. The performance of Artificial Neural Networks (ANN) mostly depends upon its generalization capability. In this paper, we propose an innovative approach to enhance the generalization capability of artificial neural networks (ANN) using structural redundancy. A novel perspective on handling input data prototypes and their impact on the development of generalization, which could improve to ANN architectures accuracy and reliability is described.

Mathematical Definitions of Operators for Cartographic Generalization

This paper puts forword 11 cartographic generalization operator models and introduces their mathematical definitions,and thus a precise mathematical form and quantitative description has been given to these formerly limited qualitative concepts.The meaning of mathematical definition of operators for cartographic generalization and the application prospect in computer_aided cartography (CAC) is stated.ract The Jurassic strata in Jingyan of Sichuan containing the Mamenchinsaurus fauna are dealt with and divided in this paper. The Mamenchisaurus fossils contained there are compared in morphological features and stratigraphically with other types of the genus on by one. The comprehensive analysis show that the Mamenchisaurus fauna of Jingyan appeared in the early Late Jurassic and is primitive in morphology. The results of the morphological identification and stratigraphical study agree with each other. Their evolutionary processes in different apoches of the Late Jurassic also made clear. Key words Jingyan, Sichuan, Mamenchisaurus Fauna, stratigraphy, evolution

Using Entropy Penalty Term for Improving the Generalization Ability of Multilayer Feedfoward Networks *

Generalization ability is a major problem encountered when using neural networks to find the structures in noisy data sets. Controlling the network complexity is a common method to solve this problem. In this paper, however, a novel additive penalty term which represents the features extracted by hidden units is introduced to eliminate the overtraining of multilayer feedfoward networks. Computer simulations demonstrate that by using this unsupervised fashion penalty term, the generalization ability is greatly improved.

Generalization Rough Set Theory

In order to avoid the discretization in the classical rough set theory, a generlization rough set theory is proposed. At first, the degree of general importance of an attribute and attribute subsets are presented. Then, depending on the degree of general importance of attribute, the space distance can be measured with weighted method. At last, a generalization rough set theory based on the general near neighborhood relation is proposed. The proposed theory partitions the universe into the tolerant modules, and forms lower approximation and upper approximation of the set under general near neighborhood relationship, which avoids the discretization in Pawlak's rough set theory.

Internal Defects Detection Method of the Railway Track Based on Generalization Features Cluster Under Ultrasonic Images

There may be several internal defects in railway track work that have different shapes and distribution rules,and these defects affect the safety of high-speed trains.Establishing reliable detection models and methods for these internal defects remains a challenging task.To address this challenge,in this study,an intelligent detection method based on a generalization feature cluster is proposed for internal defects of railway tracks.First,the defects are classified and counted according to their shape and location features.Then,generalized features of the internal defects are extracted and formulated based on the maximum difference between different types of defects and the maximum tolerance among same defects’types.Finally,the extracted generalized features are expressed by function constraints,and formulated as generalization feature clusters to classify and identify internal defects in the railway track.Furthermore,to improve the detection reliability and speed,a reduced-dimension method of the generalization feature clusters is presented in this paper.Based on this reduced-dimension feature and strongly constrained generalized features,the K-means clustering algorithm is developed for defect clustering,and good clustering results are achieved.Regarding the defects in the rail head region,the clustering accuracy is over 95%,and the Davies-Bouldin index(DBI)index is negligible,which indicates the validation of the proposed generalization features with strong constraints.Experimental results prove that the accuracy of the proposed method based on generalization feature clusters is up to 97.55%,and the average detection time is 0.12 s/frame,which indicates that it performs well in adaptability,high accuracy,and detection speed under complex working environments.The proposed algorithm can effectively detect internal defects in railway tracks using an established generalization feature cluster model.

Analysis of Bright Source Hardness Ratios in the 4 yr Insight-HXMT Galactic Plane Scanning Survey Catalog

We conduct a statistical analysis of the hardness ratio(HR)for bright sources in the 4 yr Galactic Plane Scanning Survey catalog of Insight-HXMT.Depending on the stable(variable)flux F_(s)(F_(v))or spectrum S_(s)(S_(v))of each source,the bright sources are classified into three groups:F_(v)&S_(v),F_(v)&S_(s),and F_(s)&_(s).Our study of the HR characteristics in different types of sources reveals that accretion-powered neutron star(NS)low-mass X-ray binaries(LMXBs)exhibit softer energy spectra than NS high-mass X-ray binaries(HMXBs),but harder energy spectra than black hole binaries in most cases.This difference is probably due to their different magnetic field strengths.Additionally,Fv&Sv LMXBs tend to be harder than Fv&Ss LMXBs below 7 keV,while the opposite is true for HMXBs.Our results suggest that LMXBs may dominate unclassified sources,and NS binaries are likely to be the primary type of X-ray binaries with ambiguous compact stars.By comparing the HR of transient sources in their outburst and low-flux states,it is found that the averaged HR of four sources in the two states are roughly comparable within uncertainties.We also investigate the spatial properties of the three groups and find that Fv&Sv sources are mainly located in the longitude of-20°<l<9°,Fv&Ss sources cross the Galactic Plane,and Fs&Ss sources are predominantly concentrated in 19°<l<42°.In addition,analyzing the HR spatial distributions shows the absorption of soft X-rays(primarily below 2 keV)in the Galactic Plane.

Very Original Proofs of Two Famous Problems: “Are There Any Odd Perfect Numbers?” (Unsolved until to Date) and “Fermat’s Last Theorem: A New Proof of Theorem (Less than One and a Half Pages) and Its Generalization”

This article presents very original and relatively brief or very brief proofs about of two famous problems: 1) Are there any odd perfect numbers? and 2) “Fermat’s last theorem: A new proof of theorem and its generalization”. They are achieved with elementary mathematics. This is why these proofs can be easily understood by any mathematician or anyone who knows basic mathematics. Note that, in both problems, proof by contradiction was used as a method of proof. The first of the two problems to date has not been resolved. Its proof is completely original and was not based on the work of other researchers. On the contrary, it was based on a simple observation that all natural divisors of a positive integer appear in pairs. The aim of the first work is to solve one of the unsolved, for many years, problems of the mathematics which belong to the field of number theory. I believe that if the present proof is recognized by the mathematical community, it may signal a different way of solving unsolved problems. For the second problem, it is very important the fact that it is generalized to an arbitrarily large number of variables. This generalization is essentially a new theorem in the field of the number theory. To the classical problem, two solutions are given, which are presented in the chronological order in which they were achieved. Note that the second solution is very short and does not exceed one and a half pages. This leads me to believe that Fermat, as a great mathematician was not lying and that he had probably solved the problem, as he stated in his historic its letter, with a correspondingly brief solution. To win the bet on the question of whether Fermat was telling truth or lying, go immediately to the end of this article before the General Conclusions.

General anesthetic agents induce neurotoxicity through oligodendrocytes in the developing brain

General anesthetic agents can impact brain function through interactions with neurons and their effects on glial cells.Oligodendrocytes perform essential roles in the central nervous system,including myelin sheath formation,axonal metabolism,and neuroplasticity regulation.They are particularly vulnerable to the effects of general anesthetic agents resulting in impaired proliferation,differentiation,and apoptosis.Neurologists are increasingly interested in the effects of general anesthetic agents on oligodendrocytes.These agents not only act on the surface receptors of oligodendrocytes to elicit neuroinflammation through modulation of signaling pathways,but also disrupt metabolic processes and alter the expression of genes involved in oligodendrocyte development and function.In this review,we summarize the effects of general anesthetic agents on oligodendrocytes.We anticipate that future research will continue to explore these effects and develop strategies to decrease the incidence of adverse reactions associated with the use of general anesthetic agents.

Point Set Generalization Based on the Kohonen Net

Point set generalization is one of the essential problems in map generalization. On the demands analysis of point set generalization, this paper proposes a method to generalize point sets based on the Kohonen Net model; the standard SOM algorithm has been improved so as to preserve the spatial distribution properties of the original point set. Examples illustrate that this method suits the generalization of point sets.

Hierarchical Merging &Generalization Method of Three-Dimension City Model Group Based on the Theory of Spatial Visual Cognition

In order to simplify the three-dimensional building group model, this paper proposes a clustering generalization method based on visual cognitive theory. The method uses road elements to roughly divide scenes, and then uses spatial cognitive elements such as direction, area, height and their topological constraints to classify them precisely, so as to make them conform to the urban morphological characteristics. Delaunay triangulation network and boundary tracking synthesis algorithm are used to merge and summarize the models, and the models are stored hierarchically. The proposed algorithm should be verified experimentally with a typical urban complex model. The experimental results show that the efficiency of the method used in this paper is at least 20% higher than that of previous one, and with the growth of test data, the higher efficiency is improved. The classification results conform to human cognitive habits, and the generalization levels of different models can be relatively unified by adaptive control of each threshold in the clustering generalization process.

Generalization of PhaseNet in Shandong and its application to the Changqing M4.1 earthquake sequence

Waveforms of seismic events,extracted from January 2019 to December 2021 were used to construct a test dataset to investigate the generalizability of PhaseNet in the Shandong region.The results show that errors in the picking of seismic phases(P-and Swaves)had a broadly normal distribution,mainly concentrated in the ranges of−0.4–0.3 s and−0.4–0.8 s,respectively.These results were compared with those published in the original PhaseNet article and were found to be approximately 0.2–0.4 s larger.PhaseNet had a strong generalizability for P-and S-wave picking for epicentral distances of less than 120 km and 110 km,respectively.However,the phase recall rate decreased rapidly when these distances were exceeded.Furthermore,the generalizability of PhaseNet was essentially unaffected by magnitude.The M4.1 earthquake sequence in Changqing,Shandong province,China,that occurred on February 18,2020,was adopted as a case study.PhaseNet detected more than twice the number of earthquakes in the manually obtained catalog.This further verified that PhaseNet has strong generalizability in the Shandong region,and a high-precision earthquake catalog was constructed.According to these precise positioning results,two earthquake sequences occurred in the study area,and the southern cluster may have been triggered by the northern cluster.The focal mechanism solution,regional stress field,and the location results of the northern earthquake sequence indicated that the seismic force of the earthquake was consistent with the regional stress field.

On the Generalization of Integrator and Integral Control Action

This paper provides a solution to generalize the integrator and the integral control action. It is achieved by defining two function sets to generalize the integrator and the integral control action, respectively, resorting to a stabilizing controller and adopting Lyapunov method to analyze the stability of the closed-loop system. By originating a powerful Lyapunov function, a universal theorem to ensure regionally as well as semi-globally asymptotic stability is established by some bounded information. Consequently, the justification of two propositions on the generalization of integrator and integral control action is verified. Moreover, the conditions used to define the function sets can be viewed as a class of sufficient conditions to design the integrator and the integral control action, respectively.

In vivo imaging reveals a synchronized correlation among neurotransmitter dynamics during propofol and sevoflurane anesthesia

General anesthesia is widely applied in clinical practice.However,the precise mechanism of loss of consciousness induced by general anesthetics remains unknown.Here,we measured the dynamics of five neurotransmitters,includingγ-aminobutyric acid,glutamate,norepinephrine,acetylcholine,and dopamine,in the medial prefrontal cortex and primary visual cortex of C57BL/6 mice through in vivo fiber photometry and genetically encoded neurotransmitter sensors under anesthesia to reveal the mechanism of general anesthesia from a neurotransmitter perspective.Results revealed that the concentrations of γ-aminobutyric acid,glutamate,norepinephrine,and acetylcholine increased in the cortex during propofol-induced loss of consciousness.Dopamine levels did not change following the hypnotic dose of propofol but increased significantly following surgical doses of propofol anesthesia.Notably,the concentrations of the five neurotransmitters generally decreased during sevoflurane-induced loss of consciousness.Furthermore,the neurotransmitter dynamic networks were not synchronized in the non-anesthesia groups but were highly synchronized in the anesthetic groups.These findings suggest that neurotransmitter dynamic network synchronization may cause anesthetic-induced loss of consciousness.

The GECAM Real-time Burst Alert System

Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor(GECAM),consisting of two microsatellites,is designed to detect gamma-ray bursts associated with gravitational-wave events.Here,we introduce the real-time burst alert system of GECAM,with the adoption of the BeiDou-3 short message communication service.We present the post-trigger operations,the detailed ground-based analysis,and the performance of the system.In the first year of the in-flight operation,GECAM was triggered by 42 gamma-ray bursts.The GECAM real-time burst alert system has the ability to distribute the alert within~1 minute after being triggered,which enables timely follow-up observations.

APPLICATIONS OF STAIR MATRICES AND THEIR GENERALIZATIONS TO ITERATIVE METHODS

Stair matrices and their generalizations are introduced. The definitions and some properties of the matrices were first given by Lu Hao. This class of matrices provide bases of matrix splittings for iterative methods. The remarkable feature of iterative methods based on the new class of matrices is that the methods are easily implemented for parallel computation. In particular, a generalization of the accelerated overrelaxation method （GAOR） is introduced. Some theories of the AOR method are extended to the generalized method to include a wide class of matrices. The convergence of the new method is derived for Hermitian positive definite matrices. Finally, some examples are given in order to show the superiority of the new method.

COMPACTNESS DEGREE AND A GENERALIZATION OF THE TYCHONOFF THEOREM

The most interesting result of this paper is the following generalization of the Tychonoff theorem: [GRAPHICS].

General anesthetic agents induce neurotoxicity through astrocytes

Neuroscientists have recognized the importance of astrocytes in regulating neurological function and their influence on the release of glial transmitters.Few studies,however,have focused on the effects of general anesthetic agents on neuroglia or astrocytes.Astrocytes can also be an important target of general anesthetic agents as they exert not only sedative,analgesic,and amnesic effects but also mediate general anesthetic-induced neurotoxicity and postoperative cognitive dysfunction.Here,we analyzed recent advances in understanding the mechanism of general anesthetic agents on astrocytes,and found that exposure to general anesthetic agents will destroy the morphology and proliferation of astrocytes,in addition to acting on the receptors on their surface,which not only affect Ca^(2+)signaling,inhibit the release of brain-derived neurotrophic factor and lactate from astrocytes,but are even involved in the regulation of the pro-and anti-inflammatory processes of astrocytes.These would obviously affect the communication between astrocytes as well as between astrocytes and neighboring neurons,other neuroglia,and vascular cells.In this review,we summarize how general anesthetic agents act on neurons via astrocytes,and explore potential mechanisms of action of general anesthetic agents on the nervous system.We hope that this review will provide a new direction for mitigating the neurotoxicity of general anesthetic agents.

Application value of dexmedetomidine in anesthesia for elderly patients undergoing radical colon cancer surgery

BACKGROUND Colon cancer presents a substantial risk to the well-being of elderly people worldwide.With advancements in medical technology,surgical treatment has become the primary approach for managing colon cancer patients.However,due to age-related physiological changes,especially a decline in cognitive function,older patients are more susceptible to the effects of surgery and anesthesia,increasing the relative risk of postoperative cognitive dysfunction(POCD).There-fore,in the surgical treatment of elderly patients with colon cancer,it is of pa-ramount importance to select an appropriate anesthetic approach to reduce the occurrence of POCD,protect brain function,and improve surgical success rates.METHODS One hundred and seventeen patients with colon cancer who underwent elective surgery under general anesthesia were selected and divided into two groups:A and B.Group A received Dex before anesthesia induction,and B group received an equivalent amount of normal saline.Changes in the mini-mental state exami-nation,regional cerebral oxygen saturation(rSO2),bispectral index,glucose uptake rate(GluER),lactate production rate(LacPR),serum S100βand neuron-specific enolase(NSE),POCD,and adverse anesthesia reactions were compared between the two groups.RESULTS Surgical duration,duration of anesthesia,and intraoperative blood loss were comparable between the two groups(P>0.05).The overall dosage of anesthetic drugs used in group A,including propofol and remifentanil,was significantly lower than that used in group B(P<0.05).Group A exhibited higher rSO2 values at the time of endotracheal intubation,30 min after the start of surgery,and immediately after extubation,higher GluER values and lower LacPR values at the time of endotra-cheal intubation,30 min after the start of surgery,immediately after extubation,and 5 min after extubation(P<0.05).Group A exhibited lower levels of serum S100βand NSE 24 h postoperatively and a lower incidence of cognitive dysfunction on the 1st and 5th postoperative days(P<0.05).CONCLUSION The use of Dex in elderly patients undergoing radical colon cancer surgery helps maintain rSO2 Levels and reduce cerebral metabolic levels and the incidence of anesthesia-and surgery-induced cognitive dysfunction.

An Exceptional Generalization of the Poisson Distribution

A new two-parameter count distribution is derived starting with probabilistic arguments around the gamma function and the digamma function. This model is a generalization of the Poisson model with a noteworthy assortment of qualities. For example, the mean is the main model parameter;any possible non-trivial variance or zero probability can be attained by changing the other model parameter;and all distributions are visually natural-shaped. Thus, exact modeling to any degree of over/under-dispersion or zero-inflation/deflation is possible.

The Research on the negative impact of the efficiency of the generalization performance in privatization of public utilities

Since the last century, China has carried out the reform of public utilities in the ninety time, and has achieved many positive results. The quality and efficiency of public goods supply is greatly improved. The government has changed the role of producer and provider from the past to the role of provider and regulator, which effectively promoted the development of the privatization of public utilities. However, in the achievements there has also been some problems, such as too much emphasis on efficiency to the neglect of social justice and the government＇s public responsibility ＂efficiency generalization＂ problem that requires our attention.