Miracle-dz/UniFAR-FTUs huggingface dataset:
Personalized Federated Learning for Text Classification with Gradient-Free Prompt Tuning

In this paper, we study personalized federated 001 learning for text classification with Pretrained 002 Language Models (PLMs). We identify two 003 challenges in efficiently leveraging PLMs for 004 personalized federated learning: 1) Communi-005 cation. PLMs are usually large in size, e.g. , 006 with hundreds of millions of parameters, induc-007 ing huge communication cost in a federated 008 setting. 2) Local Training. Training with PLMs 009 generally requires back-propagation, during 010 which memory consumption can be several 011 times that of the forward-propagation. This 012 may not be affordable when the PLMs are 013 trained locally on the clients, since the clients 014 may be resource constrained, e.g. , mobile de-015 vices with limited access to memory resources. 016 Additionally, the PLMs can be provided as con-017 cealed APIs, for which the back-propagation 018 operations may not be available. For the first 019 challenge, we adopt prompt tuning for PLMs 020 that only train with the prompt parameters, 021 while the pretrained parameters are frozen. 022 We further propose a compression method for 023 the learned prompts to reduce communication 024 cost. For the second challenge, we propose 025 a gradient-free approach based on discrete lo-026 cal search with natural language tokens, cir-027 cumventing gradient computation with back-028 propagation, while also reducing the communi-029 cation cost. Experiments on multiple datasets 030 demonstrates the effectiveness of our method. 031
Limited Mitigation Potential of Forestation Under a High Emissions Scenario: Results From Multi‐Model and Single Model Ensembles

Forestation is a major component of future long‐term emissions reduction and CO2 removal strategies, but the viability of carbon stored in vegetation under future climates is highly uncertain. We analyze the results from seven CMIP6 models for a combined scenario with high fossil fuel emissions (from SSP5‐8.5) and forest expansion (from SSP1‐2.6) which has ∼4.8% increase in global total forest cover relative to 2015. This scenario aims to demonstrate the ability of forestation strategies to mitigate climate change under continued increasing CO2 emissions and includes the potential impacts of increased CO2 concentration and a warming climate on vegetation growth. The model intercomparison shows that forestation as a CO2 removal strategy has limited impact on global climate under a high global warming scenario, despite generating a substantial cumulative carbon sink of 10–60 Pg C over the period 2015–2100. Using a single model ensemble, we show that there are local increases in warm extremes in response to forestation associated with decreases in the number of cool days. Furthermore, we find evidence of a shift in the global carbon balance, whereby increased carbon storage on land of ∼25 Pg C by 2100 associated with forestation has a concomitant decrease in the carbon uptake by the ocean due to reduced atmospheric CO2 concentrations.
A theoretical asperity contact creep model of interfacial friction for geomaterials

How to reveal the physical mechanism affecting the contact and friction behavior of geomaterials is still a challenging problem in predicting geological disasters, such as landslides and earthquakes. We develop a multiscale friction model that describes the microscopic creep behavior of asperities and the macroscopic sliding friction behavior of geomaterial. The theoretical asperities contact creep model can characterize the random contact process of the interface friction through porosity which can successfully capture the transition from the mechanical properties of microscopic asperities to the macroscopic interface friction-slip behavior. The theoretical model also verifies that the friction behavior of the geomaterials is closely related to their temperature, activation energy, and saturation. Thus, the developed mode offers a theoretical basis for better understanding the mechanical mechanism affecting the contact and friction behavior of the geomaterials. Meanwhile, it would considerably help to predict future geological disasters quantitatively.
What aspect of model performance is the most relevant to skillful future projection on regional scale?

Weighting models according to their performance has been used to produce multi-model climate change projections. But the added value of model weighting for future projection is not always examined. Here we apply an imperfect model framework to evaluate the added value of model weighting in projecting summer temperature changes over China. Members of large ensemble simulations by three climate models of different climate sensitivities are used as pseudo-observations for the past and the future. Performance of the models participating in the 6th phase of the coupled model intercomparison project (CMIP6) are evaluated against the pseudo-observations based on simulated historical climatology, trends in global, regional and local temperatures, to determine the model weights for future projection. The weighted projections are then compared with the pseudo-observations in the future period. We find that regional trend as a metric of model performance yields generally better skill for future projection, while past climatology as performance metric does not lead to a significant improvement to projection. Trend at the grid-box scale is also not a good performance indicator as small-scale trend is highly uncertain. For the model weighting to be effective, the metric for evaluating the model’s performance must be relatable to future changes, with response signal separable from internal variability. Projected summer warming based on model weighting is similar to that of unweighted projection but the 5th-95th uncertainty range of the weighted projection is 38% smaller with the reduction mainly in the upper bound, with the largest reduction appears in the Southeast China.
Jacdac: Service-based Prototyping of Embedded Systems

The traditional approach to programming embedded systems is monolithic: firmware on a microcontroller contains both application code and the drivers needed to communicate with sensors and actuators, using low-level protocols such as I2C, SPI and RS232. In comparison, software development for the cloud has moved to a service-based development and operation paradigm: a service provides a discrete unit of functionality that can be accessed remotely by an application program, or other service, but independently managed and updated. We propose, design, implement and evaluate a service-based approach to prototyping embedded systems called Jacdac. With Jacdac, each sensor/actuator in a system is paired with a low-cost microcontroller that advertises the services that represent the functionality of the underlying hardware over an efficient and low-cost wire protocol (bus). A separate microcontroller executes the user’s application program, which is a client of the Jacdac services on the bus. Our evaluation shows that Jacdac supports a service-based abstraction for sensors/actuators at low cost and reasonable performance, with many benefits for prototyping: ease of use via the automated discovery of devices and their capabilities, substitution of same-service devices for each other, as well as high-level programming, monitoring, and debugging. We also report on the experience of bringing Jacdac to commercial availability via a third-party manufacturer.
C LASSIFIER - FREE GUIDANCE MAKES IMAGE CAPTION - ING MODELS MORE DESCRIPTIVE

Image captioning is conventionally formulated as the task of generating captions that are similar to a set of human-generated reference captions, as measured using evaluation metrics such as CIDEr, ROUGE, and BLEU. Recent work has also explored reference-free captioning metrics based on the distance between generated captions and the corresponding images in the embedding space of a contrastively-trained image-text model such as CLIP. Here, we show that it is possible to trade off between reference-free and reference-based captioning metrics by decoding from a single autoregressive captioning model using classiﬁer-free guidance (Ho & Salimans, 2021). Compared to standard greedy decoding, decoding from the same model with a guidance scale of 3 substantially improves caption → image retrieval performance when captions and images are embedded using CLIP (re-call@1 49.4% vs. 26.5%) and CLIPScore (0.808 vs. 0.775), but greatly worsens standard reference-based captioning metrics (e.g., CIDEr 41.7 vs 126.1). Manual inspection reveals that higher guidance scales produce more descriptive but less grammatical captions.
A definable relation between c.e. sets and ideals

The P01 classes have become important structures in computability theory. Related to the study of properties of individual classes is the study of the lattice of all P01 classes, denoted EP . We define a substructure of EP , G = [N, 2ω] for N non-principal, and a quotient structure of G, denoted Gd and thought of as G modulo principal classes disjoint from N. Using the setting of computably enumerable ideals, we present basic results for G and Gd and show that Gd is isomorphic to E *, the lattice of computably enumerable sets modulo finite difference. This isomorphism allows us to transfer invariant classes from E * to EP . However, it does not in general allow the transfer of orbits. We give the conditions under which an orbit could transfer and an example of one which does, and conclude with open questions related to degree-theoretic properties.
Bayesian Design Principles for Frequentist Sequential Learning

We develop a general theory to optimize the frequentist regret for sequential learning problems, where efficient bandit and reinforcement learning algorithms can be derived from unified Bayesian principles. We propose a novel optimization approach to generate"algorithmic beliefs"at each round, and use Bayesian posteriors to make decisions. The optimization objective to create"algorithmic beliefs,"which we term"Algorithmic Information Ratio,"represents an intrinsic complexity measure that effectively characterizes the frequentist regret of any algorithm. To the best of our knowledge, this is the first systematical approach to make Bayesian-type algorithms prior-free and applicable to adversarial settings, in a generic and optimal manner. Moreover, the algorithms are simple and often efficient to implement. As a major application, we present a novel algorithm for multi-armed bandits that achieves the"best-of-all-worlds"empirical performance in the stochastic, adversarial, and non-stationary environments. And we illustrate how these principles can be used in linear bandits, bandit convex optimization, and reinforcement learning.
Regimes of tonal noise on an airfoil at moderate Reynolds number

Tonal noise generated by airfoils at low to moderate Reynolds number is relevant for applications in, for example, small-scale wind turbines, fans and unmanned aerial vehicles. Coherent and convected vortical structures scattering at the trailing edge from the pressure or suction sides of the airfoil have been identified to be responsible for such tonal noise generation. Controversy remains on the respective significance of pressure- and suction-side events, along with their interaction for tonal noise generation. The present study surveys the regimes of tonal noise generation for low to moderate chord-based Reynolds number between $\mathit{Re}_{c}=0.3\times 10^{5}$ and $2.3\times 10^{5}$ and effective angle of attack between $0^{\circ }$ and $6.3^{\circ }$ for the NACA 0012 airfoil profile. Extensive acoustic measurements with smooth surface and with transition to turbulence forced by boundary layer tripping are presented. Results show that, at non-zero angle of attack, tonal noise generation is dominated by suction-side events at low Reynolds number and by pressure-side events at high Reynolds number. At smaller angle of attack, interaction between events on the two sides becomes increasingly important. Particle image velocimetry measurements complete the information on the flow field structure in the source region around the trailing edge. The influences of both angle of attack and Reynolds number on tonal noise generation are explained by changes in the mean flow topology, namely the presence and location of reverse flow regions on the two sides. Data gathered from experimental and numerical studies in the literature are reviewed and interpreted in view of the different regimes.
Ethnoscience Studies in Making of Bale Adat: Literature Review

This study aims to elaborate on indigenous science contained in the use of materials for making bale adat based on scientific concepts. This study is a literature study with data sources from previous research articles that have topics related to ethnoscience learning, indigenous science in the tradition of materials for making bale adat, and the potential for integration of indigenous science in learning natural sciences. The procedure in literature study research is carried out in stages, namely collecting library data, reading, taking notes, studying, collecting concepts or manuscripts, then carrying out elaboration and explanation of the collected data/text. The study results show that (1) bale adat typical of the Sasak tribe consists of several types, namely bale beleq bencingah, bale bonter, bale tani, bale jajar, bale tajuk, berugag (sekepat-sekenam); (2) Indigenous science in the materials for making bale adat, namely: a) the foundation for bale adat is made from a mixture of clay, tree sap, straw ash or rice husk, and buffalo dung mixed with water, b) floor of bale adat periodically smeared with buffalo dung mixed with water to reduce humidity, c) the walls of bale adat or room covering are made of woven bamboo slats known as the local term pager, d) woven pagers are made of ampel bamboo with various motifs and sometimes to beautify the pager , the material used is spotted bamboo which has colorful bark, d) teken, ampak, lampen, and langkar used in the bale adat are made from the part of the tree that is believed to be the strongest or known locally as kayu galih, e) roof made of weeds leaves woven into bamboo frame clips which are split into small pieces; (3) indigenous science in the materials for making bale adat can be integrated into the school science learning concept, namely in the material: a) material on network structure and function, as well as technology inspired by plant structure , b) material properties and utilization of materials in everyday life.
Jet Impingement Heat Sinks With Application Toward Power Electronics Cooling: A Review

As electrified vehicles grow in popularity, there is an increasing demand to improve the cost, reliability, power density, and efficiency of onboard power electronics. Conventional cooling techniques are reaching their cooling limitations, which calls for the need to improve thermal management solutions. Novel solutions must meet current cooling targets while remaining cost effective, efficient, and compact. Impinging jet technology has proven to be a promising solution that provides localized cooling and is simple to implement in an automotive cooling application. In this article, jet impingement and its application toward cooling power electronics are comprehensively reviewed. Key flow and heat transfer features of jet impingement, heat sink optimization, enhancement techniques, and limitations are addressed in this review to provide a clear depiction of the state-of-the-art.
Disentangling Reafferent Effects by Doing Nothing

An agent's ability to distinguish between sensory effects that are self-caused, and those that are not, is instrumental in the achievement of its goals. This ability is thought to be central to a variety of functions in biological organisms, from perceptual stabilisation and accurate motor control, to higher level cognitive functions such as planning, mirroring and the sense of agency. Although many of these functions are well studied in AI, this important distinction is rarely made explicit and the focus tends to be on the associational relationship between action and sensory effect or success. Toward the development of more general agents, we develop a framework that enables agents to disentangle self-caused and externally-caused sensory effects. Informed by relevant models and experiments in robotics, and in the biological and cognitive sciences, we demonstrate the general applicability of this framework through an extensive experimental evaluation over three different environments.
Spatial distribution of electric potential and electric intensity on charged ring

Applying elliptic integral to calculate the electric potential due to uniformly charged ring, and then gets the general expression of the electric intensity by using gradient operation. At the same time, the electric potential and the electric intensity at the central axes and in the distance area of the charged ring are discussed. Finally the spatial distribution figure for electric potential is plotted and analyzed. This method can be used in calculating many similar problems.
Improving Access to Credit for First-Time Home Buyers under Borrower-Based Measures

As a result of the dynamic rise in real estate prices in recent years, house prices, and therefore the minimum down payment required to obtain a mortgage, more than tripled by 2022 compared to 2014. This led to a deterioration of access to borrowing opportunities typically for young first-time home buyers aged 35 or younger, especially among clients who are not eligible for family support schemes. In this paper, we provide a detailed overview of the potential side effects of the borrower-based measure framework on first-time home buyers. Relative to their credit risk, these clients may be more severely affected by borrower-based measures, generating negative second-round effects. Therefore, in their case preferential limits may be applied, in line with international practice, notably on the level of down payment. However, when making such a decision, it is important to take into account the development of risks in the housing and credit markets and the macroeconomic environment.
Refractory and super-refractory status epilepticus and evidence for the use of ketamine: a scope review

Status epilepticus (SE) is a neurological emergency with serious consequences for neuronal tissues, therefore, it is considered the most serious manifestation of epilepsy. The response to treatment, its evolution time and duration, and the need to use one or more antiseizure drugs define SE as refractory or super-refractory. Ketamine has been used in SE management since the 90s when an article describing its use in treating SE was published. Since then, at least 24 publications have reported the use of ketamine for the treatment of SE in both adult and pediatric patients. This scoping review seeks to synthesize information on the use of drugs in super-refractory SE, specifically ketamine. Twenty articles were chosen for the final document construction. Few studies have investigated the use of ketamine in refractory status epilepticus (RSE) and super-refractory status epilepticus (SRSE). Most of the information comes from retrospective case series studies, mostly with small sample sizes, and although the information is heterogeneous, it points to the efficacy of ketamine as a third-line drug in RES and SRSE, in controlling seizures.
Effects of the Co-Administration of Morphine and Lipopolysaccharide on Toll-Like Receptor-4/Nuclear Factor Kappa β Signaling Pathway of MDA-MB-231 Breast Cancer Cells

Background: The Toll-like receptor 4 (TLR4) gene promotes migration in adenocarcinoma cells. Morphine is an agonist for TLR4 that has a dual role in cancer development. The promoter or inhibitor role of morphine in cancer progression remains controversial. This study aims to evaluate the effects of morphine on the TLR4, myeloid differentiation primary response protein 88-dependent (MyD88), and nuclear factor-kappa B (NF-κB) expressions in the human MDA-MB-231 breast cancer cell line. Materials and Methods: The cells were examined after 24 hours of incubation with morphine using the Boyden chamber system. TLR4, MyD88, and NF-κB mRNA expressions were assessed using quantitative real-time polymerase chain reaction (RT-PCR). The concentration of interleukin-2 beta was also measured using the ELISA assay. Results: According to the findings, three doses of morphine (0.25, 1.25, and 0.025 μM) increased the expression of the TLR4 and NF-κB genes, whereas no significant change was observed in the mRNA expression of MyD88. Furthermore, treatment with morphine and lipopolysaccharide (LPS) significantly decreased the expression of TLR4, MyD88, and NF-κB. However, no significant change was observed in interleukin 2 beta concentration. Conclusions: These findings confirmed the excitatory effects of morphine on TRL4 expression and the MYD88 signaling pathway in vitro.
Flood capacity assessment of confined masonry school buildings for education disruption assessment

Flood is one of the most common natural hazards that causes fatalities and significant disruption to human life, including to the education delivery through schools. Although the functionality disruption is significant, standing floodwater also causes lateral hydrostatic thrust on outer walls of buildings. This study examines the physical capacity of school buildings against flood loads by means of numerical modelling using Applied Element Method. Masonry buildings with varying levels of confinement are subjected to out-of-plane hydrostatic pressure, to assess the failure mechanisms and to estimate the lateral load carrying capacity, thus identifying the critical collapse depth of water. The study also looks at the effect of material degradation on the ultimate flood capacity. This result is further utilized to estimate physical and functional disruption to education delivery at schools.
A New Matching Strategy for SIFT Based Copy-Move Forgery Detection

: SIFT-based techniques have achieved satisfying performance in detecting copy-move forgery (CMF). Typically, these techniques find the matched regions of an image and re-examine them using a variety of methods to determine whether CMF has occurred or not. However, these techniques have some shortcomings related to how they handle false matches, which usually occur due to image continuity or self-similarity. First, a spatial distance threshold or segmentation-based methods are commonly utilized to handle image continuity. Second, several external methods along with manually created thresholds are utilized to handle image self-similarity. In this paper, we propose a new matching strategy that is resistant to false matches while reducing reliance on external methods and thus avoiding several thresholds. We model the keypoint as a whole region rather than a single point and employ the intersection over union measure to deal with image continuity. To reduce false matches caused by image self-similarity, we combine the cross-matching test with a modified distance ratio test. This combination takes into account the ability to detect multiple cloning. Moreover, we utilize a support vector machine to learn the threshold(s) needed to decide if CMF has occurred or not. The proposed methodology is evaluated over three challenging datasets: MICC-F600, Coverage, and MICC-F220. On MICC-F600 dataset, our proposed methodology outperforms other state-of-art techniques and achieves high precision of 99.38%, recall of 97.5%, and 98.42% of F1 score. Additionally, the comparative evaluation using Coverage, and MICC-F220 datasets proved the effectiveness of the proposed methodology to handle a variety of attacks.