Miracle-dz/UniFAR-FTUs huggingface dataset:
Class-Incremental Learning via Dual Augmentation

Deep learning systems typically suffer from catastrophic forgetting of past knowledge when acquiring new skills continually. In this paper, we emphasize two dilemmas, representation bias and classiﬁer bias in class-incremental learning, and present a simple and novel approach that employs explicit class augmentation (classAug) and implicit semantic augmentation (semanAug) to address the two biases, respectively. On the one hand, we propose to address the representation bias by learning transferable and diverse representations. Speciﬁcally, we investigate the feature representations in incremental learning based on spectral analysis and present a simple technique called classAug, to let the model see more classes during training for learning representations transferable across classes. On the other hand, to overcome the classiﬁer bias, semanAug implicitly involves the simultaneous generating of an inﬁnite number of instances of old classes in the deep feature space, which poses tighter constraints to maintain the decision boundary of previously learned classes. Without storing any old samples, our method can perform comparably with representative data replay based approaches.
Reliability of targets in a picture naming task

The Words in Game (WinG) test is a tool for assessing language development in children, two versions of this test have been developed, one in Italy (Bello et al., 2012) and one in England (Cattani et al., 2019). The present research consists of two studies aiming to determine the reliability of the targets used in the English WinG cards. Study One uses 17 adult participants to rate each set of cards (Italian and English) on how well they represent target constructs, to see if one set is rated as ‘better’ than the other. Study Two consists of the WinG test being run with 34 child participants to determine if there is a difference in the scores of the two groups of children when one group is tested using the English cards and the other using the Italian cards. Study One finds that the adults rate the English WinG cards as significantly better than the Italian cards in three subtests, it also finds that there are some significant differences in the ratings of individual cards within the test, this suggests that there will be some differences between the scores of the children. However, in Study Two no significant differences are found between the two sets of cards in any subtest, suggesting that changing stimuli does not influence children in the same way as adults. This therefore demonstrates that the targets used in the English WinG cards are reliable when assessing children and that it is appropriate to use this tool for assessing language development in children.
Classification Analysis of Genetic Variations In Cancer Diagnosis By Multiclass Classifiers

: M achine learning in medical imaging plays the greatest disruptive technology in decades. It is being emerged not only to identify cancerous tumors at an earlier stage, but also detect and classify lesions, analyze data, reconstruct images, and more. Cancer is one of the heterogeneous disease consists of many different subclasses. The early diagnosis and prognosis of a cancer type have become a necessity in cancer research for facilitating the subsequent clinical management of patients. Researchers, healthcare organizations, companies from biomedical and bioinformatics look forward for improving clinical outcomes for cancer patients and those who may not by using diagnostic and prognostic biomarkers. But the challenge is distinguishing the mutations that contribute to tumor growth (drivers) from the neutral mutations (passengers). Currently this interpretation of genetic mutations is being done manually based on evidence from text-based clinical literature. This article is focusing on analyzing the performance of multiclass classification algorithms for genetic features.
E FFECT OF MODEL AND PRETRAINING SCALE ON CATASTROPHIC FORGETTING IN NEURAL NETWORKS

Catastrophic forgetting presents a challenge in developing deep learning models capable of continual learning, i.e. learning tasks sequentially. Recently, both computer vision and natural-language processing have witnessed great progress through the use of large-scale pretrained models. In this work, we present an empirical study of catastrophic forgetting in this pretraining paradigm. Our experiments indicate that large, pretrained ResNets and Transformers are signiﬁcantly more resistant to forgetting than randomly-initialized, trained-from-scratch models; this robustness systematically improves with scale of both model and pre-training dataset size. We take initial steps towards characterizing what aspect of model representations allows them to perform continual learning so well, ﬁnding that in the pretrained models, distinct class representations grow more orthogonal with scale. Our results suggest that, when possible, scale and a diverse pretraining dataset can be useful ingredients in mitigating catastrophic forgetting. Continual learning is a current challenge in designing
A Review of Digital FIR Filter Design in Communication Systems

: In signal processing, a finite impulse response (FIR) filter settles to zero in finite time. FIR filters can be discrete-time or continuous-time, and digital or analog. FIR filter is widely used in various signal processing and image processing applications because of less area, low cost, low power, and high operation speed. An FIR filter is usually implemented by using a series of delays, multipliers, and adders to create the filter's output. We concentrate on the following three categories: frequency sampling methods, windowing-based methods, and optimization-based methods. We also focus on the communications system, including transmissions equipment, relay stations, tributary stations, and other data terminal equipment. A communications system can even include other communications systems.A good example would be a regional emergency response communications system that connects several different cities and allows them to respond to a disaster by integrating systems they have installed for their police and firefighters. In the end,theperformances of severalFIR design methods are assessed. This article provides a comprehensive overview of the latest developments in finite impulse response (FIR) filter design methods in communication systems.
AP-PSPJ210003 23..42

The rise of social media has led to unprecedented opportunities for individuals to share, or express, their attitudes on social and political issues. What factors affect whether individuals choose to share? This research identifies a novel determinant of attitude sharing—support-oppose framing, defined as whether individuals think of their own attitude in terms of what they support or what they oppose. Supportoppose framing is distinct from attitude valence, as the same attitude can be framed in terms of support (e.g., I support that this policy is bad) or opposition (e.g., I oppose that this policy is good). Seven experiments, two correlational studies, and one field study provide evidence for a support-oppose framing effect, whereby individuals are more likely to share attitudes framed in terms of positions they support rather than positions they oppose. This effect occurs via two pathways. In the first, support-framed attitudes are viewed as more value expressive, which facilitates greater attitude sharing. In the second, support-framed attitudes are believed to promote more positive impressions, which also leads to greater sharing. This effect is attenuated when individuals’ typical impression-management goals are relaxed.
Effects of a 12-Week Detraining Period on Physical Capacity, Power and Speed in Elite Swimmers

This study aims to evaluate the effects of a prolonged transition period (detraining) on the physical capacity, power, and speed parameters of elite swimmers. Fourteen swimmers (seven females and seven males) aged 20.4 ± 1.7 years participated in the study. The athletes were subjected to two rounds of identical tests at 12-week intervals during the detraining period (DP), which consisted of an evaluation of the athletes’ body weight and composition, a measurement of the power of their lower limbs (Keiser squat, countermovement jump (CMJ), akimbo countermovement jump (ACMJ)) and upper limbs (Keiser arms) on land, and 20-m swimming using the legs only (Crawl Legs test), arms only (Crawl Arms test), and full stroke (Front Crawl test). An analysis of variance revealed a significant effect of the main factor, Gender, on all the measured parameters, while for the factor Detraining, except for Front Crawl (W) (F = 4.27, p = 0.061), no significant interaction effect (Gender × Detraining) was revealed. Among both the male and the female participants, a reduction in lactate-threshold swimming speed (LT Dmax) and a reduction in swimming speed and power on the Crawl Arms, Crawl Legs, and Front Crawl tests was observed after 12 weeks. There were also statistically significant reductions in ACMJ and CMJ jump height and upper-limb power (Keiser squat) among the female and male swimmers. There were no significant changes in body weight or body composition. The study showed a clear deterioration in results for most of the parameters, both for those measured on land and for those measured in water.
Late maturation of executive control promotes conceptual development

Control processes are critical for the generation of task-appropriate behaviour across cognitive domains, yet children have a long developmental period with reduced executive control. Traditionally, this is viewed as a negative but necessary consequence of the time taken to learn control processes and develop the prefrontal cortex. Here, we exploit a recent computational model of controlled semantic cognition to formally test an alternative (yet perhaps complementary) view that a developmental period without control promotes conceptual knowledge acquisition. Our simulations show that maturational delay and anatomical connectivity conspire to promote conceptual learning. Learning conceptual structure necessitates a connection from control to more peripheral regions rather than the deep multimodal hub. Delayed control speeds conceptual learning without compromising conceptual representations, particularly when control connects to intermediate layers. These results are counterintuitive as delayed control onset can produce overall faster mastery of controlled behaviours. To assess whether delayed semantic control is also observed over development, we conducted a metaanalysis of the classic triadic matching task where participants decide which of two options best matches a third. Matching can be based on taxonomic or thematic relations, and when these conflict, participants must use task context to determine which relation to choose—that is, they must exert semantic control. Children aged 2 have the representations to identify both relations when distractors are unrelated, but when relations conflict, they cannot use context to guide their choices. Context-sensitivity develops later than conceptual structure and shows large increases around 6, a critical time for executive function across domains.
ScholarWorks at WMU ScholarWorks at WMU COVID-19: Coping Strategies Predicting Mental Health Outcomes COVID-19: Coping Strategies Predicting Mental Health Outcomes

The rates of COVID-19 cases and deaths caused are increasing. Studies have been reporting the inclining rate of psychological distress during the pandemic, which calls for attention to how the pandemic has impacted mental health outcomes. Coping strategies are helpful when it comes to predicting mental health outcomes. However, limited studies looked at coping strategies predicting mental health outcomes longitudinally. The study hypothesized that psychological distress would decrease during mid-pandemic and adaptive coping strategies such as active coping, acceptance, positive reframing, instrumental support, emotional support, religion, humor, and planning decrease psychological distress while maladaptive included denial and venting, behavioral disengagements, substance use, self-blame, self-distraction. Current study collected participants from social media platform and university students since April to June 2020 via online survey. A series of linear mixed models expressed the relationship between coping strategies and psychological distress during the pandemic. Results found statistical significance in denial, substance use, behavioral disengagement, venting, humor, and self-blame as maladaptive ( p < .001). No coping strategies that associated with decreased psychological distress was found. However, exploratory results showed that acceptance, active coping, and positive reframing had different positive predictions on depression, anxiety, and stress. The study implies that coping strategies during a pandemic, alternative to denial, substance use, behavioral disengagement, venting, humor, and self-blame, should be further explored. It also informs the need to appraise the situation before deploying certain coping strategies.
Separation Control by Slot Jet in a Critically Loaded Compressor Cascade

Abstract Separation in compressor cascade triggers flow loss and instability. This paper presents a passive flow control method by introducing a slot into the blade. The slot induces self-adapted jet, while the jet flow is used to suppress cascade’s separation. To study the flow control effect, experiments were conducted and flow field details were given by validated numerical simulations. The results show that a well-designed slot carries adequate jet airflow from pressure side (PS) to suction side (SS) due to the great pressure fall between the two sides. The jet airflow delays suction side separation within specific incidence angles, so the performance of cascade achieves considerable improvements. It enables to be concluded that the slot carries jet flow to SS separation zone, and then the self-adapted jet flow re-energizes low momentum fluid and suppresses vortices in the separation which are negative to the cascade flow.
Quiescent Body as a Reversible Subcellular Structure Formed in Non-growing Bacterial Cells

Bacterial cells take a variable lag time and maintain a multi-drug tolerant non-growing state before resuming growth when encountering growth-supportive conditions. Some of them exhibit an extraordinarily long lag, as pathogenic persisters do. It remains unknown on what determines lag time duration. Here, we unveiled a subcellular structure, termed quiescent body, that is formed in bacterial cells entering non-growing state and sequesters selected proteins essential for cell growth. Their formation occurs progressively in each cell and heterogeneously among individual cells. They only dissolve in re-growing cells to release proteins for immediate re-functioning when conditions become fit. Quiescent body, whose degree of formation is highly correlated with duration of lag time or level of antibiotic tolerance, apparently functions as a biological timer for bacterial growth resumption. Further, suppressing their formation, which directly relies on cellular respiration complexes, or promoting their dissolution might be a viable strategy to eradicate persisters.
Essays on Financial Intermediation

Zaici Li1 In the first two chapters of the dissertation, I address the research question: why does the issuance of private-label mortgage back securities in the US remain stagnant while all other types of securitization recovered with the economic fundamental years ago? The first chapter presents the static model and the second chapter presents the dynamic model. The third chapter addresses the research question: Why do credit and liquidity conditions vary at the same time and how do they interact along with the business cycle? I provide a dynamic model of shadow banking and securitization in which short-lived shocks can generate slow recovery. In the model, intermediaries’ capital and risk perceptions play key roles in driving securitization dynamics. The model features a self-reinforcing effect between high risk perceptions and low securitization. High risk perceptions reduce intermediaries’ willingness to hold junior tranches, leading to low levels of securitization. Since securitization generates a positive informational externality, low issuance slows down learning and risk perception remains high, resulting in very slow recovery. The model can explain why the private label residential mortgage backed securities (PL RMBS) market remains stagnant. During the financial crisis, the massive write-downs of subprime mortgage related securities not only wiped out intermediaries’ capital, leading to the collapse of issuance in all major securitization markets but also sharply increased risk perception in PM RMBS market. The higher risk perceptions in PL RMBS market have kept issuance low until now while other securitization markets recovered after intermediaries’ recapitalization. Why do credit and liquidity conditions vary at the same time and how do they interact along with the business cycle? To address these questions, we propose an dynamic equilibrium model where risk-averse banks originate long-term projects and distribute them to risk-neutral investors. The key friction is the information asymmetry between banks and investors. During recession, credit quality deteriorates, making it more costly for banks with good projects to distribute and increasing the severity of information asymmetry. JEL classification: E44, G01, G23
The impact of design for consumers in the food and beverage industry : design value and measurement

How can one justify the investment in design? By considering the relatively frequent modifications of design aspects in the service industry, the significance of justifying design investment should be addressed. In order to be a successful service business, it is critical to manage the design resources and report the outcome appropriately. Given that the main contribution of design can be the role of adding value, this study attempted to interpret the impact of design through the concept of value. Among various value theories, this study determined to utilise Holbrook’s typology of consumer value for embedding design perspectives. Holbrook’s value typology is an emotional-based holistic understanding of value which can apprehend the root causes of the preference from the customer perspective. In this context, the application of Holbrook’s value typology can contribute to the in-depth understanding of design and be extended to the other stakeholders within a business in order to understand a service business holistically for the future study. However, the greater value for a consumer is arguably not sufficient to argue the importance of design for a business. If design contributes to the greater value, value created by design activities should lead to the greater outcomes of key business phases (such as greater customer satisfaction and loyalty). This study employed statistical approaches to confirm the positive impacts of design upon key business phases quantitatively. As a result, the key findings and contributions of this study are: (1) proposing Design Value Typology which enables a better understanding of design value from customers’ emotional causes, and (2) confirming the positive influence of design to the key business phases (in other words, the investigation about a company’s efforts for improving design elements and principles can enhance the performance of the company).
Title: Obesity blocks oligodendrocyte precursor cell differentiation and impedes repair after white matter stroke Abbreviated title: Obesity blocks OPC differentiation

Affiliations: 1 Department of Neurology, David Geffen School of Medicine, University of California Los Angeles 2 Institut Jean-Pierre Bourgin, INRA, AgroParisTech, CNRS, Université Paris-Saclay, 78000 Versailles, France 3 Department of Psychiatry, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles 4 Department of Neurobiology, David Geffen School of Medicine, University of California Los Angeles
Hearing impairment is associated with enhanced neural tracking of the speech envelope

Elevated hearing thresholds in hearing impaired adults are usually compensated by providing amplification through a hearing aid. In spite of restoring hearing sensitivity, difficulties with understanding speech in noisy environments often remain. One main reason is that sensorineural hearing loss not only causes loss of audibility but also other deficits, including peripheral distortion but also central temporal processing deficits. To investigate the neural consequences of hearing impairment in the brain underlying speech-in-noise difficulties, we compared EEG responses to natural speech of 14 hearing impaired adults with those of 14 age-matched normal-hearing adults. We measured neural envelope tracking to sentences and a story masked by different levels of a stationary noise or competing talker. Despite their sensorineural hearing loss, hearing impaired adults showed higher neural envelope tracking of the target than the competing talker, similar to their normal-hearing peers. Furthermore, hearing impairment was related to an additional increase in neural envelope tracking of the target talker. Since no relation was found between this enhanced envelope tracking in hearing impaired adults and cognitive function, our results suggest that neural changes with hearing impairment originate from different neural mechanisms than those related with aging. Highlights Adults with hearing impairment can neurally segregate speech from background noise Hearing loss is related to enhanced neural envelope tracking of the target talker Neural envelope tracking has potential to objectively measure speech understanding
Semi-automated socio-anthropologic analysis of the medical discourse on rheumatoid arthritis: Potential impact on public health

The debilitating effects of non-communicable diseases (NCDs) and the accompanying chronic inflammation, represent a significant obstacle for the sustainability of our development, with efforts being spread worldwide to contrast NCDs' diffusion, as per the United Nations Sustainable Development Goals (SDG 3). In fact, despite efforts of variable intensities in numerous directions (from innovations in biotechnology to lifestyle modifications), NCDs' incidence remains pandemic. The present work wants to contribute to this major concern with a specific focus on the fragmentation of the medical approaches, via an interdisciplinary analysis of the medical discourse, i.e. the heterogenous reporting that biomedical scientific literature uses to describe the anti-inflammatory therapeutic landscape in NCDs. The aim is to better capture the roots of this compartmentalization and the power relations existing among three segregated pharmacological, experimental and unstandardized biomedical approaches, to ultimately empower collaboration beyond medical specialties and possibly untap a more ample and effective reservoir of integrated therapeutic opportunities. Using as exemplar disease rheumatoid arthritis (RA), twenty-eight articles were manually translated each into a nine-dimensional categorical variable of medical socio-anthropological relevance, relating in particular (but not only) to legitimacy, temporality and spatialization. This digitalized picture (9 x 28 table) of the medical discourse was further analyzed by simple automatic learning approaches to identify differences and highlight commonalities among the biomedical categories. Interpretation of these results gives original insights including the suggestion to: empower scientific communication between unstandardized approaches and basic biology; promote non-pharmacological therapies repurposing to enhance robustness of experimental approaches; align the spatial representation of diseases and therapies in pharmacology to effectively embrace the systemic approach promoted by modern personalized and preventive medicines. We hope this original work may expand and foster interdisciplinarity among public health stakeholders, ultimately contributing to the achievement of SGD3.