Squeezing More Past Knowledge for Online Class-Incremental Continual Learning

Continual learning(CL)studies the problem of learning to accumulate knowledge over time from a stream of data.A crucial challenge is that neural networks suffer from performance degradation on previously seen data,known as catastrophic forgetting,due to allowing parameter sharing.In this work,we consider a more practical online class-incremental CL setting,where the model learns new samples in an online manner and may continuously experience new classes.Moreover,prior knowledge is unavailable during training and evaluation.Existing works usually explore sample usages from a single dimension,which ignores a lot of valuable supervisory information.To better tackle the setting,we propose a novel replay-based CL method,which leverages multi-level representations produced by the intermediate process of training samples for replay and strengthens supervision to consolidate previous knowledge.Specifically,besides the previous raw samples,we store the corresponding logits and features in the memory.Furthermore,to imitate the prediction of the past model,we construct extra constraints by leveraging multi-level information stored in the memory.With the same number of samples for replay,our method can use more past knowledge to prevent interference.We conduct extensive evaluations on several popular CL datasets,and experiments show that our method consistently outperforms state-of-the-art methods with various sizes of episodic memory.We further provide a detailed analysis of these results and demonstrate that our method is more viable in practical scenarios.

On the realization of seismic microzonation of Almaty (Kazakhstan) in ground accelerations based on the “continual” approach

Seismic microzonation for Almaty city for the first time use probabilistic approach and hazard is expressed in terms of not only macroseismic intensity,but also Peak Ground Acceleration(PGA).To account for the effects of local soil conditions,the continual approach proposed by A.S.Aleshin[1,2]was used,in which soil coefficients are a function of the continuously changing seismic rigidity.Soil coefficients were calculated using the new data of geological and geophysical surveys and findings of previous geotechnical studies.The used approach made it possible to avoid using soil categories and a jump change in characteristics of soil conditions and seismic impact.The developed seismic microzonation maps are prepared for further introduction into the normative documents of the Republic of Kazakhstan.

CONTINUAL CONDITIONS BETWEEN LAYERS FOR LAMINATED PLATES

In this paper, various forms of functional on blending energy principles of composite laminated plates are gir en, which guarantee satisfied continual conditions of displacements and stress between layers, and then the reliability of the functional are proved by the computing example.

THE CONTINUAL DIFFERENTIABLE PEAK-UNIMODAL SOLUTIONS OF FEIGENBAUM’S FUNCTIONAL EQUATIONS

For the famous Feigenbaum's equations, in this paper, we established its constructive theorem of the peak-unimodal, then we found out other paths to explore the peak-unimodal solutions. For example, we proceed on the direction to try the non-symmetrical continuous peak-unimodal solutions and C1 solutions.

是continual还是continuous?——一组英语同源形容词辨析

英语中一些与动词有关的形容词变化比较复杂,除了一些可以用作形容词的现在分词与过去分词有些规律以外,其它与动词有关的一些形容词的构成就没什么规律。有时与一个动词相联的形容词往往有二个或二个以上,而且其意义也有不同,本文将列举一些常用的这一类形容词以及它们的辨析。

The Paradigm of the Seismic Zonation Continuality

Basic concepts of seismic zonation in Russia are the degree of intensity and soil categories that correspond to discrete structure in the ratio “seismic impact-ground reaction”. Meanwhile, the parameters of seismic effects, and the parameters of soil properties are continuous in the space. The report expounds the basic theory, adequately representing the above mentioned continuality. Thus, many the concepts of seismic zonation, used now, become either more correct, or unnecessary.

Enforcement of Regulations of the People's Republic of China on Disclosure of Government Information and Continual Development of a Group of Basic Human Rights

Introduction 2013 saw the sixth anniversary of the formulation of Regulations of the People＇s Republic of China on Disclosure of Government Information （hereinafter referred to as the Regulations） and the fifth anniversary of their being put into effect. As the Regulations were stipulated and put into force,

Parametric Selection and Continual Combination of Building Surface

A method to reparametrize G retional curve to obtain a C^1 curve is given. A practical G^1 continual connective between adjacent NURUS patches along common guadratic boundary curve is presented in this paper, and a specific algorithm for control points and weights of NURBS patches is discussed.

Objective Assessment in Continual Medical Education (CME) Medical Objective Assessment in System Control

Existing examinations in postgraduate education and continuing medical education (CME) are not perfect. Modern assessment does not reflect disadvantages of older responders, for whom more time for reply is needed. Specialists with wide clinical experience may choose more than one correct answer in alternative questions. Reduced ability to remember in older people restricts examination without additional sources of information. We offer an individualised system for testing doctors. It provides personalised choice of examination questions using multiple choice questions with weight characteristics and absence of distractors, interactive cooperation in case of negative answers and the final decision of an expert in relation to the person tested. A special algorithm is proposed for typical questions that combines the advantages of known approaches to testing. The questioning system is complex for the creators of tests, but is more convenient and objective than existing ones for medical doctors.

Continual learning fault diagnosis:A dual-branch adaptive aggregation residual network for fault diagnosis with machine increments

As a data-driven approach, Deep Learning(DL)-based fault diagnosis methods need to collect the relatively comprehensive data on machine fault types to achieve satisfactory performance. A mechanical system may include multiple submachines in the real-world. During condition monitoring of a mechanical system, fault data are distributed in a continuous flow of constantly generated information and new faults will inevitably occur in unconsidered submachines, which are also called machine increments. Therefore, adequately collecting fault data in advance is difficult. Limited by the characteristics of DL, training existing models directly with new fault data of new submachines leads to catastrophic forgetting of old tasks, while the cost of collecting all known data to retrain the models is excessively high. DL-based fault diagnosis methods cannot learn continually and adaptively in dynamic environments. A new Continual Learning Fault Diagnosis method(CLFD) is proposed in this paper to solve a series of fault diagnosis tasks with machine increments. The stability–plasticity dilemma is an intrinsic issue in continual learning. The core of CLFD is the proposed Dual-branch Adaptive Aggregation Residual Network(DAARN).Two types of residual blocks are created in each block layer of DAARN: steady and dynamic blocks. The stability–plasticity dilemma is solved by assigning them with adaptive aggregation weights to balance stability and plasticity, and a bi-level optimization program is used to optimize adaptive aggregation weights and model parameters. In addition, a feature-level knowledge distillation loss function is proposed to further overcome catastrophic forgetting. CLFD is then applied to the fault diagnosis case with machine increments. Results demonstrate that CLFD outperforms other continual learning methods and has satisfactory robustness.

Continual driver behaviour learning for connected vehicles and intelligent transportation systems: Framework, survey and challenges

Modelling,predicting and analysing driver behaviours are essential to advanced driver assistance systems(ADAS)and the comprehensive understanding of complex driving scenarios.Recently,with the development of deep learning(DL),numerous driver behaviour learning(DBL)methods have been proposed and applied in connected vehicles(CV)and intelligent transportation systems(ITS).This study provides a review of DBL,which mainly focuses on typical applications in CV and ITS.First,a comprehensive review of the state-of-the-art DBL is presented.Next,Given the constantly changing nature of real driving scenarios,most existing learning-based models may suffer from the so-called“catastrophic forgetting,”which refers to their inability to perform well in previously learned scenarios after acquiring new ones.As a solution to the aforementioned issue,this paper presents a framework for continual driver behaviour learning(CDBL)by leveraging continual learning technology.The proposed CDBL framework is demonstrated to outperform existing methods in behaviour prediction through a case study.Finally,future works,potential challenges and emerging trends in this area are highlighted.

持续气道正压通气治疗重症阻塞性睡眠呼吸暂停低通气综合征伴黏多糖病患儿1例

1临床资料患儿,男,6岁,因“睡眠打鼾2年余,加重伴憋气2 d”于2022-09-09就诊于甘肃省人民医院。患儿自幼体格生长和智力发育较同龄儿落后,面容特殊;入院前2年无明显诱因出现鼻塞、睡眠时张口呼吸,打鼾憋气,感冒时鼻塞、打鼾症状尤为明显,有时伴有耳痛。入院前1周患儿感冒后鼻塞加重,近两日夜间睡眠打鼾加重,伴明显憋气,夜间口唇青紫。患儿父母非近亲婚配,其家族中未发现类似情况。查体:身高63 cm,体重22 kg,特殊面容.

A 28/56 Gb/s NRZ/PAM-4 dual-mode transceiver with 1/4 rate reconfigurable 4-tap FFE and half-rate slicer in a 28-nm CMOS

A 28/56 Gb/s NRZ/PAM-4 dual-mode transceiver(TRx)designed in a 28-nm complementary metal-oxide-semiconduc-tor(CMOS)process is presented in this article.A voltage-mode(VM)driver featuring a 4-tap reconfigurable feed-forward equal-izer(FFE)is employed in the quarter-rate transmitter(TX).The half-rate receiver(RX)incorporates a continuous-time linear equal-izer(CTLE),a 3-stage high-speed slicer with multi-clock-phase sampling,and a clock and data recovery(CDR).The experimen-tal results show that the TRx operates at a maximum speed of 56 Gb/s with chip-on board(COB)assembly.The 28 Gb/s NRZ eye diagram shows a far-end vertical eye opening of 210 mV with an output amplitude of 351 mV single-ended and the 56 Gb/s PAM-4 eye diagram exhibits far-end eye opening of 33 mV(upper-eye),31 mV(mid-eye),and 28 mV(lower-eye)with an output amplitude of 353 mV single-ended.The recovered 14 GHz clock from the RX exhibits random jitter(RJ)of 469 fs and deterministic jitter(DJ)of 8.76 ps.The 875 Mb/s de-multiplexed data features 593 ps horizontal eye opening with 32.02 ps RJ,at bit-error rate(BER)of 10-5(0.53 UI).The power dissipation of TX and RX are 125 and 181.4 mW,respectively,from a 0.9-V sup-ply.

Continual Education is the Motivation of Sustainable Development of a Telecom Enterprise

The continuous investment into manpower resource, is the radical power toassure the sustainable development of enterprises. The enterprises both at home and abroad attachhigh importance to the continuous education of their employees and consolidate training to inspiretheir employees. In order to face increasingly drastic global competition, the telecom enterprisesin our country should consolidate continuous education, make training plans to adapt to thelong-term development of the enterprises and establish the effective mechanism of encouragement ofcontinuous education.

Threshold public key encryption scheme resilient against continual leakage without random oracles

Threshold public key encryption allows a set of servers to decrypt a ciphertext if a given threshold of authorized servers cooperate. In the setting of threshold public key encryption, we consider the question of how to correctly decrypt a ciphertext where all servers continually leak information about their secret keys to an external attacker. Dodis et al. and Akavia et al. show two concrete schemes on how to store secrets on continually leaky servers. However, their construc- tions are only interactive between two servers. To achieve continual leakage security among more than two servers, we give the first threshold public key encryption scheme against adaptively chosen ciphertext attack in the continual leak- age model under three static assumptions. In our model, the servers update their keys individually and asynchronously, without any communication between two servers. Moreover, the update procedure is re-randomized and the randomness can leak as well.

Estimation of the minimum effective dose of tramadol for postoperative analgesia in infants using the continual reassessment method

Tramadol is a potent analgesic.However,the analgesia efficacy of tramadol,particularly its minimum effective dose(MED),is not clear.The aim of this study is to find MED of tramadol for postoperative analgesia in infants.The continual reassessment method(CRM)was performed to find MED.Infants undergoing surgeries were included in the 3 phases of this series.In each phase,24 participants were allocated a different tramadol dose.Pain intensity was measured by face,legs,activity,cry,consolability(FLACC)measurement at 3-hour intervals.Tramadol was considered ineffective if the FLACC score was higher than 4 in 10 at anytime.In phase 1,seven dose levels were used within the range 0.1-0.4 mg·kg^(-1)·h^(-1).Phase 1 was insufficient to identify the MED,and we increased the dose to 0.4-0.8 mg·kg^(-1)·h^(-1) in phase 2.Phase 2 was insufficient to identify the MED.In phase 3,local anesthetic wound infiltration was introduced,and the tramadol dose levels tested were the same as in phase 1.The successful analgesia probability of tramadol 0.4 mg·kg^(-1)·h^(-1) was 82.1%(95%CI,0.742-0.925)in phase 1.In phase 2,it was 84.7%(95%CI,0.789-0.991)with the dose 0.8 mg·kg^(-1)·h^(-1).Phase 1 and phase 2 were insufficient to identify the MED.In phase 3,the successful analgesia probability for dose 0.35 mg·kg^(-1)·h^(-1) was 96.7%(95%CI,0.853-0.997).We have demonstrated that tramadol provides insufficient analgesia for surgeries considered to cause moderate-to-severe postoperative pain in infants if used as the sole analgesic,and that local anesthetic wound infiltration enhances the efficacy of tramadol.

Epigenetic memory of drug exposure history controls neural stem cell quiescence in the adult brain

Neural stem cells(NSCs)are the source of all neurons and glial cells(astrocytes and oligodendrocytes)in the central nervous system.The adult mammalian brain retains NSCs in the subgranular zone of the dentate gyrus in the hippocampus and ventricular subventricular zone lining the lateral ventricle(Olpe and Jessberger,2022).Adult NSCs in rodents are preserved throughout life and continuously produce new neurons that integrate into the pre-existing neuronal network.

Evaluation of ruminal methane and ammonia formation and microbiota composition as affected by supplements based on mixtures of tannins and essential oils using Rusitec

Background Dietary supplements based on tannin extracts or essential oil compounds(EOC)have been repeatedly reported as a promising feeding strategy to reduce the environmental impact of ruminant husbandry.A previous batch culture screening of various supplements identified selected mixtures with an enhanced potential to mitigate ruminal methane and ammonia formation.Among these,Q-2(named after quebracho extract and EOC blend 2,composed of carvacrol,thymol,and eugenol)and C-10(chestnut extract and EOC blend 10,consisting of oregano and thyme essential oils and limonene)have been investigated in detail in the present study with the semi-continuous rumen simulation technique(Rusitec)in three independent runs.For this purpose,Q-2 and C-10,dosed according to the previous study,were compared with a non-supplemented diet(negative control,NC)and with one supplemented with the commercial EOC-based Agolin^(R) Ruminant(positive control,PC).Results From d 5 to 10 of fermentation incubation liquid was collected and analysed for pH,ammonia,protozoa count,and gas composition.Feed residues were collected for the determination of ruminal degradability.On d 10,samples of incubation liquid were also characterised for bacterial,archaeal and fungal communities by high-throughput sequencing of 16S rRNA and 26S ribosomal large subunit gene amplicons.Regardless of the duration of the fermentation period,Q-2 and C-10 were similarly efficient as PC in mitigating either ammonia(-37%by Q-2,-34%by PC)or methane formation(-12%by C-10,-12%by PC).The PC was also responsible for lower feed degradability and bacterial and fungal richness,whereas Q-2 and C-10 effects,particularly on microbiome diversities,were limited compared to NC.Conclusions All additives showed the potential to mitigate methane or ammonia formation,or both,in vitro over a period of 10 d.However,several differences occurred between PC and Q-2/C-10,indicating different mechanisms of action.The pronounced defaunation caused by PC and its suggested consequences apparently determined at least part of the mitigant effects.Although the depressive effect on NDF degradability caused by Q-2 and C-10 might partially explain their mitigation properties,their mechanisms of action remain mostly to be elucidated.

Measurement,associations,patterns,and promotion:Unveiling vital areas in physical activity epidemiology

Physical activity(PA)epidemiology first emerged as a new field of study around the 1950s with publication of seminal investigations on London civil servants1 and has continued to evolve as a scientific discipline to present time.This subdiscipline of epidemiology studies the frequencies,distributions,and dynamics of PA and its impact on human health,morbidity,and mortality.Research over the past 75 years has demonstrated numerous health benefits of PA.Based on these research findings,the World Health Organization recommends adults aged 18-64 years engage in at least 150-300 min of moderate-intensity aerobic PA per week,or at least 75-150 min of vigorous-intensity aerobic PA per week,or a combination of both intensities.

Transforming agri-food systems for multiple wins in nutrition,inclusion and environment

The call for agri-food system transformation is urgent in many global development agendas(UN 2023).Food systems have contributed to economic prosperity and feeding the world,but they are also associated with numerous challenges,including climate change,continued hunger,poor diets and malnutrition,and increasing disparities(Webb et al.2020;Fanzo et al.2021).