Miracle-dz/UniFAR-FTUs huggingface dataset:
Beyond Supervised Continual Learning: a Review

Continual Learning (CL, sometimes also termed incremental learning) is a flavor of machine learning where the usual assumption of stationary data distribution is relaxed or omitted. When naively applying, e.g., DNNs in CL problems, changes in the data distribution can cause the so-called catastrophic forgetting (CF) effect: an abrupt loss of previous knowledge. Although many significant contributions to enabling CL have been made in recent years, most works address supervised (classification) problems. This article reviews literature that study CL in other settings, such as learning with reduced supervision, fully unsupervised learning, and reinforcement learning. Besides proposing a simple schema for classifying CL approaches w.r. t. their level of autonomy and supervision, we discuss the specific challenges associated with each setting and the potential contributions to the field of CL in general.
The SPDE approach for spatio-temporal datasets with advection and diffusion

In the task of predicting spatio-temporal fields in environmental science using statistical methods, introducing statistical models inspired by the physics of the underlying phenomena that are numerically efficient is of growing interest. Large space-time datasets call for new numerical methods to efficiently process them. The Stochastic Partial Differential Equation (SPDE) approach has proven to be effective for the estimation and the prediction in a spatial context. We present here the advection-diffusion SPDE with first order derivative in time which defines a large class of nonseparable spatio-temporal models. A Gaussian Markov random field approximation of the solution to the SPDE is built by discretizing the temporal derivative with a finite difference method (implicit Euler) and by solving the spatial SPDE with a finite element method (continuous Galerkin) at each time step. The ''Streamline Diffusion'' stabilization technique is introduced when the advection term dominates the diffusion. Computationally efficient methods are proposed to estimate the parameters of the SPDE and to predict the spatio-temporal field by kriging, as well as to perform conditional simulations. The approach is applied to a solar radiation dataset. Its advantages and limitations are discussed.
An Algorithm-Hardware Co-design Framework to Overcome Imperfections of Mixed-signal DNN Accelerators

In recent years, processing in memory (PIM) based mixedsignal designs have been proposed as energy- and area-efficient solutions with ultra high throughput to accelerate DNN computations. However, PIM designs are sensitive to imperfections such as noise, weight and conductance variations that substantially degrade the DNN accuracy. To address this issue, we propose a novel algorithm-hardware co-design framework hereafter referred to as HybridAC that simultaneously avoids accuracy degradation due to imperfections, improves area utilization, and reduces data movement and energy dissipation. We derive a data-movement-aware weight selection method that does not require retraining to preserve its original performance. It computes a fraction of the results with a small number of variation-sensitive weights using a robust digital accelerator, while the main computation is performed in analog PIM units. This is the first work that not only provides a variation-robust architecture, but also improves the area, power, and energy of the existing designs considerably. HybridAC is adapted to leverage the preceding weight selection method by reducing ADC precision, peripheral circuitry, and hybrid quantization to optimize the design. Our comprehensive experiments show that, even in the presence of variation as high as 50%, HybridAC can reduce the accuracy degradation from 60 - 90% (without protection) to 1 - 2% for different DNNs across diverse datasets. In addition to providing more robust computation, compared to the ISAAC (SRE), HybridAC improves the execution time, energy, area, power, area-efficiency, and power-efficiency by 26%(14%), 52%(40%), 28%(28%), 57%(45%), 43%(5x), and 81%(3.9x), respectively
Estimating Travel Speed of a Road Section Through Sparse Crowdsensing Data

The average travel speed on certain road sections is an important piece of information for the intelligent transportation system. Traditional ways for estimating travel speed usually depend on dedicated sensors or infrastructures, which is financially costly. Alternatively, as an infrastructure-free way, vehicular crowdsensing can be used to collect data including real-time locations and velocities of vehicles, which is quite low cost and effective. This paper aims to produce a fully covered distribution of average travel speeds for road sections both in time and space domains based on vehicular crowdsensing data. However, due to the uneven spatial-temporal distribution of vehicles and the variation of their data-offering intervals, vehicular crowdsensing data are usually coarse grained. This coarseness leads to missing travel speed values of vehicles on some road sections. To handle this problem, we propose an approach that exploits the spatial-temporal causality among travel speeds of road sections by a time-lagged correlation coefficient function. We use a time-lagging factor to quantify the time consumption of vehicles traveling along road sections. Then, we utilize the local stationarity of correlation coefficient to estimate the travel speeds of road sections. Experiments based on real taxi trace data show that the proposed method performs better than some methods in use.
Health-Related Quality of Life of Patients Presenting to the Emergency Department with a Musculoskeletal Disorder

Background: Musculoskeletal disorders (MSKDs) are among the most disabling and costly non-fatal health conditions. They may lead to long-term consequences such as chronic pain, physical limitations, and poorer quality of life. They also account for a significant proportion of emergency department visits, representing between 18% and 25% of all visits, depending on country. Purpose: To assess the health-related quality of life of patients presenting to the emergency department with a MSKD, to convert their answers to utility scores and to explore the association between diverse socio-demographic and clinical variables and patients’ health-related quality of life. Patients and Methods: This is an analysis of cross-sectional data obtained during the baseline assessment performed as part of a 6-month pragmatic randomized controlled trial conducted in an academic emergency department. We included patients aged 18–80 years with a minor MSKD. The main outcome measures were health-related quality of life (five dimensions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression) and utility scores (−0.148 – worse than death, 0 – dead, 0.949 – perfect health) measured with the EQ-5D-5L. Possible associations were explored by comparing scores across subgroups based on certain socio-demographic (eg, age, gender, triage score) and clinical factors (eg, pain interference on function, pain intensity) and with reference values using descriptive statistics (mean, median), rankFD ANOVAs, and χ 2 tests. Results: Sixty-nine participants completed the EQ-5D-5L. Mean and median utility scores were, respectively, 0.536 (95% CI: 0.479–0.594) and 0.531 (IQR: 0.356–0.760). Participants with higher levels of pain (<4/10: 0.741, 95% CI: 0.501–0.980; 4–7/10: 0.572, 0.500–0.644; >7/10: 0.433, 0.347–0.518) or pain interference on function (<4/10: 0.685, 95% CI: 0.605–0.764; 4–7/10: 0.463, 0.394–0.533; >7/10: 0.294, 0.126– 0.463) presented significantly lower utility scores. No significant differences were found for other socio-demographic characteristics. Conclusion: In patients with MSKDs who present to the emergency department, higher levels of pain or pain interference are associated with decreased health-related quality of life. These findings need to be confirmed on a larger scale.
Improvd Algorithm for Second Generation Wavelet Transform and Image Denosing

An improved algorithm for second generation wavelet transform is proposed by adopting the lifting scheme and least square orthogonal polynomial fitting. For designing predicting (or updating) coefficients of the lifting scheme, the orthogonal polynomials are taken as a basis, and the predicting (or updating) coefficients are solved by using least square curve fitting to fit the apoximate signals (or detail signals) of wavelet transform. The numerical experiment shows the method is a powerful method for denoising image, which combines second wavelet transform based on optimum fitting estimation and image nonlinear enhancement algorithm, but also it can compensate the foible of soft threshold denoising and keep the feature of image edge well. The proposed method is proved to be effectivly.
Postharvest Spoilage Incidence and Prestorage Treatment in Chinese Chestnut and Complex Hybrid Cultivars

to 1) evaluate spoilage incidence on the interior (i.e., pellicle, kernel) and exterior (i.e., nutshell) of the nut over the course of 200 days of cold storage on eight cultivars and 2) assess the impact of food contact-approved chlorine solution and 2% peracetic acid (PAA) with 27% hydrogen peroxide prestorage treatments for spoilage suppression on ‘ Qing ’ nuts. Fourteen timepoints were observed during the study period, each with four replications of 16 nuts. An additional four replicates of 16 ‘ Qing ’ nuts were treated prestorage and observed over seven time points. The incidence of spoilage was reported as the percentage of nonsellable nuts for each treatment and cultivar at four timepoints. The nut interior showed the highest spoilage incidence after 200 days, with four cultivars having > 30% nonsellable nuts. Overall, the cultivars had an average of 10% nonsellable nuts from interior spoilage after 60 days in storage. ‘ Hong Kong ’ had the highest percentage of nonsellable nuts by the end of the study at 60%, whereas ‘ Qing ’ and ‘ Mossbarger ’ had the lowest rates, with only 14% nonsellable nuts. Spoilage of the exterior, although less frequent, is visible to buyers and impacts nut marketability. ‘ Kohr ’ had the highest percentage of nonsellable nuts because of exterior spoilage (35.9%). ‘ Mossbarger ’ had the lowest percentage of nonsellable nuts because of exterior spoilage (3.1%). ‘ Qing ’ nuts treated with 500 ppm chlorine and 100/200 ppm PAA demonstrated reduced exterior spoilage with longer storage times. Prestorage treatment did not show ef ﬁ cacy for reducing interior spoilage. This study provides a preliminary report of evidence that cultivar differences in ﬂ uence the spoilage incidence and supports taking nuts to market within 60 days of harvesting. These preliminary data also inform breeding parent combinations and studies of inheritance for postharvest spoilage tolerance at the University of Missouri Center for Agroforestry breeding program.
SOME BOUNDS AND THE CONDITIONAL MAXIMUM BOUND FOR RESTRICTED ISOMETRY CONSTANTS

Compressed sensing seeks to recover an unknown sparse signal with entries by making far fewer than measurements. The restricted isometry Constants (RIC) has become a dominant tool used for such cases since if RIC satisfies some bound then sparse signals are guaranteed to be recovered exactly when no noise is present and sparse signals can be estimated stably in the noisy case. During the last few years, a great deal of attention has been focused on bounds of RIC, see, e. g. , Candes (2008), Foucart et al (2009), Foucart (2010), Cai et al (2010), Mo et al (2011), Ji et al (2012) . Finding bounds of RIC has theoretical and applied significance. In this paper, we obtain a bound of RIC. It improves the results by Cai et al (2010) and Ji et al (2012) . Further, we discuss the problems related larger bound of RIC, and give the conditional maximum bound.
Optimal linear fitting for objective determination of ocean mixed layer depth from glider profiles (Proof)

A new optimal linear fitting method has been developed to determine mixed layer depth from profile data. This methodology includes three steps: 1) fitting the profile data from the first point near the surface to a depth using a linear polynomial, 2) computing the error ratio of absolute bias of few data points below that depth versus the root-mean-square error of data points from the surface to that depth between observed and fitted data, and 3) finding the depth (i.e., the mixed layer depth) with maximum error ratio. Temperature profiles in the westernNorthAtlanticOcean over 14November–5December 2007, collected from two gliders (Seagliders) deployed by the Naval Oceanographic Office (NAVOCEANO), are used to demonstrate the capability of this method. The mean quality index (1.0 for perfect determination) for determining mixed layer depth is greater than 0.97, which is much higher than the critical value of 0.8 for well-defined mixed layer depth with that index.
Reverse-bias-induced bipolar resistance switching in Pt∕TiO2∕SrTi0.99Nb0.01O3∕Pt devices

Stoichiometric single-crystalline TiO2 thin films were grown on SrTi0.99Nb0. 01O3 (Nb:STO) substrates by oxygen plasma-assisted molecular beam epitaxy. The Pt∕TiO2∕Nb:STO∕Pt devices showed extremely weak resistance switching hysteresis without applying reverse bias. However, when the reverse bias increased above −2V, the hysteresis became more and more prominent. Further, it was found that the low (high) resistance state can be set by applying sufficient reverse (forward) bias. The origin of the reverse-bias-induced bipolar switching behavior should be attributed to the modulation of Schottky-like barrier width by electrochemical migration of oxygen vacancies.
Multirate diversity strategy of fractal modulation

Previous analyses of fractal modulation were carried out mostly from a signle perspective or a subband, but the analyses from the perspective of multiscale synthesis have not been found yet; while multiscale synthesis is just the essence of the mutlirate diversity which is the most important characteristic of fractal modulation. As for the mutlirate diversity of fractal modulation, previous studies only dealt with the general outspread of its concept, lacked the thorough and intensive quantitative comparison and analysis. In light of the above fact, from the perspective of multiscale synthesis, in this paper we provide a comprehensive analysis of the multirate diversity of fractal modulation and corresponding quantitative analysis. The results show that mutlirate diversity, which is a fusion of frequency diversity and time diversity, pays an acceptable price in spectral efficiency in exchange for a significant improvement in bit error rate. It makes fractal modulation particularly suitable for the channels whose bandwidth and duration parameters are unknown or cannot be predicted to the transmitter. Surely it is clearly of great significance for reliable communications. Moreover, we also attain the ability to flexibly make various rate-bandwidth tradeoffs between the transmitter and the receiver, to freely select the reception time and to expediently control the total bandwidth. Furthermore, the acquisitions or improvements of these fine features could provide support of the technical feasibility for the electromagnetic spectrum control technology in a complex electromagnetic environment.
Indexicality and (im)politeness

If we were to adopt Leech’s (1983, p. 104) framework, we might argue that the exchange contains an instance of the speech act of ‘criticism’, and we might categorise it as a conflictive kind of act. And if we were adopting Brown and Levinson’s (1978 [1987]) framework we might categorise this as a threat to the hearer’s positive face. Beyond the identification of ‘face-threatening acts’ and ‘impoliteness’, however, other important aspects of the interaction could be scrutinized. For example, we could investigate the transparency of the criticism, i.e. the degree to which the formula ‘that wasn’t funny’, is recognized as meaningful across social groups, investigating what ‘type’ of people use it, with which addressees and in which social contexts it is likely to occur; or in which registers it is likely to interact with other (co-occurring) signs. We could explore how each sign contributes to the overall effect. For example the deictic ‘that’ in Flo’s first turn, which, though not obviously or conventionally associated with criticism, might be seen to reinforce the criticism if it was categorized as a marker of empathetic distancing (Levinson, 1983, p. 81; Lyons, 1977, p. 677). We could also speculate about a possible hidden agenda in Flo’s utterance, effectively a self-positioning act, through which she projects herself as a ‘considerate/caring’ person. Through Andy’s retort, i.e. his laying
The Mathematical Models for Different Start Video Broadcasting

—The different start video broadcasting is a new approach to improve the service of P2P video streaming applications. This approach allows unpunctual users to view broadcast programs from the beginning during server broadcast time. This paper proposes the non-cluster and cluster model for different start video broadcasting. The buffer management and mathematical model are proposed to estimate the performance of non-cluster and cluster model. These models are based on an application layer MESH network. These models are composed of five processes: peer join/leave, peer exchange information, peer selection, buffer organization and segment scheduling. The proposed models are simulated and verified by using NS-2. Moreover, the mathematical model is proposed to evaluate the performance metrics of server load, peer load, control message and buffer size. The results show that (i) the unpunctual users with different joining time are able to view the first video frame, (ii) the video server load is reduced drastically, (iii) the peer load is also reduced, (iv) the number of control messages exchanged between the nodes is reduced, and (v) the buffer size is constant. Moreover, the performance of cluster model is better than the non-cluster model.
Institutional Knowledge at Singapore Management University Institutional Knowledge at Singapore Management University On Modeling Virality of Twitter Content On Modeling Virality of Twitter Content

Twitter is a popular microblogging site where users can eas-ily use mobile phones or desktop machines to generate short messages to be shared with others in realtime. Twitter has seen heavy usage in many recent international events including Japan earthquake, Iran election, etc. In such events, many tweets may become viral for diﬀerent reasons. In this paper, we study the virality of socio-political tweet content in the Singapore’s 2011 general election (GE2011). We collected tweet data generated by about 20K Singapore users from 1 April 2011 till 12 May 2011, and the follow relationships among them. We introduce several quantitative indices for measuring the virality of tweets that are retweeted. Using these indices, we identify the most viral messages in GE2011 as well as the users behind them.
TRANSCRIPTOMIC AND METABOLIC PATHWAY ANALYSIS REVEALS THE MUTATED GENES P53 AND TP53 AND THEIR ROLE IN DIFFERENT TYPES OF CANCER

: Somatic TP53 gene mutations are common in different cancers, occurring in almost half of ovarian tumors. These mutations result in the p53 protein, which is less able to control cell proliferation. In particular, it failed to induce apoptosis in cells with mutated or damaged DNA. An inherited TP53 mutation is known as LiFraumeni syndrome. Li-Fraumeni syndrome is a rare genetic disorder that can increase the risk of certain types of cancer. These cancers include breast cancer, bone cancer, leukemia, and soft tissue cancer, also known as sarcomas. Mutations (changes) in the p53 gene can cause cancer cells to grow and spread throughout the body. These changes have been found in a genetic disorder known as Li-Fraumeni syndrome and in many types of cancer. The p53 gene is a tumor suppressor gene. Also called TP53 gene and tumor protein p53 gene. P53 mutations are associated with breast, colorectal, liver, lung, and ovarian cancers. Environ Health Perspect. Frequent p53 mutations (mutp53) not only end tumor suppressor capacities but confer various gain-of-function (GOF) activities that impact molecules and pathways now regarded as central for tumor development and progression. Although the complete impact of GOF is still far from being fully understood, the effects on proliferation, migration, metabolic reprogramming, and immune evasion, among others, certainly constitute major driving forces for human tumors harboring them. I In particular, the increased lipogenic activity through the mevalonate pathway (MVA) and the alteration of metabolic homeostasis due to interactions between mutp53 and AMP-activated protein kinase (AMPK) and Sterol regulatory element-binding protein 1 (SREBP1) that impact anabolic pathways and favor metabolic reprogramming. We address, in detail, the impact of mutp53 over metabolic reprogramming and the Warburg effect observed in cancer cells as a consequence, not only of loss-of-function of p53, but rather as an effect of GOF that is crucial for the imbalance between glycolysis and oxidative phosphorylation. Analysis of worldwide cancer exponent values for IARC GLOBOCAN incidence age-standardized rates of cancer (6 five-year age groups; both sexes except for SRT) and IARC TP53 mutation rates, for various types of cancer by topographic or morphologic sites
Programming physical realizations of quantum computers

We study effects of the physical realization of quantum computers on their logical operation. Through simulation of physical models of quantum computer hardware, we analyze the difficulties that are encountered in programming physical realizations of quantum computers. Examples of logically identical implementations of the controlled-NOT operation and Grover's database search algorithm are used to demonstrate that the results of a quantum computation are unstable with respect to the physical realization of the quantum computer. We discuss the origin of these instabilities and discuss possibilities to overcome this, for practical purposes, fundamental limitation of quantum computers.
Strategic Market Analysis in an Electronic Service Market

- The electronic-book (e-book) is one of the new technological changes that have significantly influenced the publishing industry in the last century. This has forced publishers to reconsider their distribution channels, since the Internet has provided a new means with which to serve readers. In this paper, a strategic market analysis is proposed from the perspective of a traditional publisher that needs to decide whether to switch to e-publishing business. The analysis framework determines the publishing market equilibrium in three different market scenarios. Besides, it shows the impact of readers’ choices and price sensitivities on the profits of publishers. The proposed framework has its basis on game theory and it is built in an oligopoly setting to reflect the severe market competition. The readers’ utilities and demands are modeled using the multinomial logit model. Although the first scenario possesses a global optimum solution, in the remaining two market scenarios genetic algorithms are used in order to find the sub-optimal solutions of the oligopolies.
PID Control for Takagi-Sugeno Fuzzy Model

In this chapter, we deal with the problem of controlling Takagi-Sugeno (TS) fuzzy model by PID controllers using the particle swarm optimization (PSO). Therefore, a new algorithm is proposed. This algorithm relies on the use of a new objective function taking into account both the performance indices and the error signal. The advantages of this approach are discussed through simulations on a numerical example.