Miracle-dz/UniFAR-FTUs huggingface dataset:
The prediction to Beijing water shortage risk

In this paper,the authors apply the variable combination of grey system and index smoothing prediction model to predict 2010 Beijing water shortage amount and water resource amount,and calculate the accuracy of single prediction and combination prediction.Through the comparison,theresults show the combination prediction is with ahigher accuracy.At last,by the model of combination prediction we get the prediction of the amounts to 2010 Beijing water shortage,and water resources.We first make the prediction of water shortage risk of each year in Beijing from 2001 to 2010 by fuzzy probability,then by fast clustering analysis method identify the water shortage level in Beijing in 2010 to be mediation.So it is necessary to take action to discriminate the risk.
Quest for the golden ratio universality class

Using mode coupling theory the conditions for all allowed dynamical universality classes for the conserved modes in one-dimensional driven systems are presented in closed form as a function of the stationary currents and their derivatives. With a view on the search for the golden ratio universality class the existence of some families of microscopic models is ruled out a priori by using an Onsager-type macroscopic current symmetry. At equal mean densities of the conserved quantities the golden modes can only appear if the currents are antisymmetric under interchange of the conserved densities and if these densities are correlated, but not in the symmetric case where at equal densities one mode is always diffusive and the second may be either Kardar-Parisi-Zhang (KPZ), modified KPZ, 3/2-L\'evy, or also diffusive. We also show that the predictions of mode coupling theory for a noisy chain of harmonic oscillators are exact.
Mycotoxin Occurrence in Milk and Durum Wheat Samples from Tunisia Using Dispersive Liquid–Liquid Microextraction and Liquid Chromatography with Fluorescence Detection

Food and feed contamination with mycotoxins is a major public health concern. Humans and animals are exposed to these toxins by consuming contaminated products throughout their lives. In this study, a method based on dispersive liquid–liquid microextraction (DLLME), followed by liquid chromatography with fluorescence detection (LC-FLD), was validated for the determination of aflatoxins (AFs) M1, B1, B2, G1, G2, zearalenone (ZEN), and ochratoxin A (OTA). The method was applied to 150 raw cow milk samples and 90 market durum wheat samples from two Tunisian climatic regions: the littoral region (Mahdia) and the continental region (Béja). This work was carried out to obtain more surveillance data to support rapid initiatives to assure safe foods and protect consumer health and to estimate the daily exposure of the Tunisian population consuming those products. AFG2 and OTA were found in wheat with incidences of 54.4 and 11.1%, respectively. On the other side, milk samples were contaminated by AFG2, AFB1, and AFB2 with incidences of 8.7%, 2.0%, and 0.67%, respectively. Some of the samples showed OTA concentrations above the maximum limit allowed by the European Union, which represents a health risk for consumers in Tunisia, where no legislation exists about the maximum content of mycotoxins in food.
Cohesive Zone Modelling and the Fracture Process of Cement-Based Composites

Computational modelling of quasi-brittle fracture in cement-based composites needs to cover both i) the damage caused by micro-fractured zones, referring to some nonlocal strain-stress relations, respecting quite different behaviour of such composites in tension and compression, and ii) the initiation and propagation of macroscopic cracks, exploiting the cohesive zone model, handled by some modification of the finite element technique, together with the discretization in time. A fundamental issue for such model is the introduction of a traction-separation (stress-displacement) relationship. This contribution pays particular attention to the design, identification and estimation of material parameters for the traction separation law suitable for predicting the deformation behaviour of samples of materials and structures.
Protective Effect of Polyherbal Composition against Hemorrhagic Shock Condition in an Experimental Rat Model

Objective: Hemorrhagic shock (HS) is a condition which requires an immediate care and if not treated on time can result in death. Hence, we aim to study the protective role of fixed dose combination of polyherbal composition comprising of an equal amount of aqueous extracts of Azadirachta indica leaves, Carica papaya leaves, and methanolic extract of Andrographis paniculata against fixed volume bleed HS model. Materials and Methods: The study was conducted with 48 male and 48 female Wistar rats divided into 8 groups, normal control (G1), disease control (sublethal and lethal, G2 and G3) and 5 treatment groups (G4–G8). Treatment was initiated on the same day and continued for 14 days. At the end of 14 days, hemorrhage was induced by withdrawing 40% of circulatory blood volume for all groups and 60% of circulatory blood volume for G3. Treatment was continued further for 7 days. Complete blood count, serum levels of glucose, sodium, potassium, and rectal temperature were measured at before, 3 h, 24 h, 72 h, and 7 days post-hemorrhage, whereas interleukin (IL)-6, nuclear factor kappa B (NF-ƘB), and vasopressin levels were measured at 24 h time point. Serum lactate and bicarbonate levels were measured at 3 h and at the end of the study. Statistical analysis was done using one way ANOVA followed by Dunnett’s test. P < 0.05 was considered statistically significant. Results: At 24 h, glucose levels were high and hematocrit levels were low compared to NC group, which were recovered to normal in all treatment groups at the end of the experiment except in disease control group. Our findings were further supported by serum level of electrolytes as well as IL-6, NF-ƘB, and vasopressin levels which were elevated in response to HS condition at 24 h post-hemorrhage. We have seen significant ( P < 0.0001, P < 0.001, P < 0.01, P < 0.05) changes in the level of these parameters in disease control group compared to other groups. Recovery at the end of the experiment indicates that animals have responded to our treatments with maximum effect has been seen in G7 group. Conclusion: The polyherbal extracts used in this experiment have the potential to be used alone or in combination with available conventional medical therapy against HS condition to provide symptomatic relief, to improve quality of life and to promote the survival.
In Vivo Assessment of Laboratory-Grown Kidney Tissue Grafts

Directed differentiation of stem cells is an attractive approach to generate kidney tissue for regenerative therapies. Currently, the most informative platform to test the regenerative potential of this tissue is engraftment into kidneys of immunocompromised rodents. Stem cell-derived kidney tissue is vascularized following engraftment, but the connection between epithelial tubules that is critical for urine to pass from the graft to the host collecting system has not yet been demonstrated. We show that one significant obstacle to tubule fusion is the accumulation of fibrillar collagens at the interface between the graft and the host. As a screening strategy to identify factors that can prevent this collagen accumulation, we propose encapsulating laboratory-grown kidney tissue in fibrin hydrogels supplemented with candidate compounds such as recombinant proteins, small molecules, feeder cells, and gene therapy vectors to condition the local graft environment. We demonstrate that the AAV-DJ serotype is an efficient gene therapy vector for the subcapsular region and that it is specific for interstitial cells in this compartment. In addition to the histological evaluation of epithelial tubule fusion, we demonstrate the specificity of two urine biomarker assays that can be used to detect human-specific markers of the proximal nephron (CD59) and the distal nephron (uromodulin), and we demonstrate the deposition of human graft-derived urine into the mouse collecting system. Using the testing platform described in this report, it will be possible to systematically screen factors for their potential to promote epithelial fusion of graft and host tissue with a functional intravital read-out.
Reinforcers and control : towards a computational aetiology of depression

Depression, like many psychiatric disorders, is a disorder of affect. Over the past decades, a large number of affective issues in depression have been characterised, both in human experiments and animal models of the dis order. Over the same period, experimental neuroscience, helped by com putational theories such as reinforcement learning, has provided detailed descriptions of the psychology and neurobiology of affective decision mak ing. Here, we attempt to harvest the advances in the understanding of the brain's normal dealings with rewards and punishments to dissect out and define more clearly the components that make up depression. We start by exploring changes to primary reinforcer sensitivity in the learned helpless ness animal models of depression. Then, a detailed formalisation of control in a goal-directed decision making framework is presented and related to animal and human data. Finally, we show how serotonin's joint involve ment in reporting negative values and inhibiting actions may explain some aspects of its involvement in depression. Throughout, aspects of depres sion are seen as emerging from normal affective function and reinforcement learning, and we thus conclude that computational descriptions of normal affective function provide one possible avenue by which to define an aetiol ogy of depression.
Casting defect detection based on improved DETR

Casting products are widely used in many industrial fields. Castings are prone to defects in the production process. Due to the high utilization rate of castings, the quality of castings has become the focus of industrial production. Therefore, casting defect detection is very important in the production process. This paper proposes a casting defect detection method based on improved DETR to improve detection accuracy. Firstly, multi-scale feature fusion is added in the feature extraction stage; then, the ECA-NET attention mechanism module is introduced to improve the backbone network; secondly, the attention mechanism in the Transformer module is improved by using relative position encoding; finally, in the casting data, the improved algorithm is trained and tested on the set. The experimental results show that the accuracy of the improved DETR model proposed in this paper can reach 49.6%, which is 6.3% higher than the original DETR algorithm. Compared with other mainstream target detection algorithms, the casting defect detection model proposed in this paper can effectively identify Casting defects and achieve high detection accuracy.
The Effect of Foreign Direct Investment and Economic Development on Renewable Energy in Indonesia

The study aims to explore the indicators of foreign direct investment (FDI) and their impact on economic development, with a specific focus on renewable energy in Indonesia. It is well-known that FDI plays a significant role in the development of developing countries, and Indonesia, being one of them, still faces challenges in meeting the energy needs of its citizens. The empirical analysis utilizes the Multiple Regression approach with data spanning from 1981 to 2021. The results indicate a cointegration relationship between model parameters and cross-sectional dependence. Additionally, the study finds that FDI and inflation have a negative impact on renewable energy, while population and GDP have a positive and significant effect. Furthermore, economic growth and fossil fuel consumption also positively influence renewable energy consumption. In the long term, the estimation results suggest that FDI and financial development have a simultaneous effect on energy consumption, which aligns with economic growth but not necessarily with renewable energy consumption. This implies that while FDI and financial development contribute to overall energy consumption as the economy grows, they may not directly impact the adoption of renewable energy sources. Based on the research findings, policymakers in Indonesia are encouraged to focus on sustainable development and consider policy transformations that facilitate the transition from fossil fuels to renewable energy sources. Keywords: FDI, GDP, inflation, population, renewable energy, multiple regression
Lexical Resources for the Identification of Causative Relations in Portuguese Texts

The identification of causal relations from text is a mature problem in Natural Language Processing. There are a number of resources and tools to aid causative relation extraction in English, but there seems to be a limited number of resources for Portuguese. This paper presents a number of resources which are designed to aid the researcher and the practitioner to extract causative relations from Portuguese texts.
In Search of Lost Online Test-time Adaptation: A Survey

In this paper, we present a comprehensive survey on online test-time adaptation (OTTA), a paradigm focused on adapting machine learning models to novel data distributions upon batch arrival. Despite the proliferation of OTTA methods recently, the field is mired in issues like ambiguous settings, antiquated backbones, and inconsistent hyperparameter tuning, obfuscating the real challenges and making reproducibility elusive. For clarity and a rigorous comparison, we classify OTTA techniques into three primary categories and subject them to benchmarks using the potent Vision Transformer (ViT) backbone to discover genuinely effective strategies. Our benchmarks span not only conventional corrupted datasets such as CIFAR-10/100-C and ImageNet-C but also real-world shifts embodied in CIFAR-10.1 and CIFAR-10-Warehouse, encapsulating variations across search engines and synthesized data by diffusion models. To gauge efficiency in online scenarios, we introduce novel evaluation metrics, inclusive of FLOPs, shedding light on the trade-offs between adaptation accuracy and computational overhead. Our findings diverge from existing literature, indicating: (1) transformers exhibit heightened resilience to diverse domain shifts, (2) the efficacy of many OTTA methods hinges on ample batch sizes, and (3) stability in optimization and resistance to perturbations are critical during adaptation, especially when the batch size is 1. Motivated by these insights, we pointed out promising directions for future research. The source code is made available: https://github.com/Jo-wang/OTTA_ViT_survey.
An extended Fourier pseudospectral method for the Gross-Pitaevskii equation with low regularity potential

We propose and analyze an extended Fourier pseudospectral (eFP) method for the spatial discretization of the Gross-Pitaevskii equation (GPE) with low regularity potential by treating the potential in an extended window for its discrete Fourier transform. The proposed eFP method maintains optimal convergence rates with respect to the regularity of the exact solution even if the potential is of low regularity and enjoys similar computational cost as the standard Fourier pseudospectral method, and thus it is both efficient and accurate. Furthermore, similar to the Fourier spectral/pseudospectral methods, the eFP method can be easily coupled with different popular temporal integrators including finite difference methods, time-splitting methods and exponential-type integrators. Numerical results are presented to validate our optimal error estimates and to demonstrate that they are sharp as well as to show its efficiency in practical computations.
El Niño—The Dynamic Response of the Equatorial Pacific Oceanto Atmospheric Forcing

Abstract El Nino is the occasional appearance of warm water off the coast of Peru; its presence results in catastrophic consequences in the fishing industry. A new theory for the occurrence of El Nino is presented. It isshown that El Nino is not due to a weakening of the southeast trades over the waters off Peru, but that during the two years preceding El Nino, excessively strong southeast trades are present in the central Pacific.These strong southeast trades intensify the subtropical gyre of the South Pacific, strengthen the SouthEquatorial Current, and increase the east-west slope of sea level by building up water in the western equatorial Pacific. As soon as. the wind stress in the central Pacific relaxes, the accumulated water flows eastward,probably in the form of an internal equatorial Kelvin wave. This wave leads to the accumulation of warmwater off Ecuador and Peru and to a depression of the usually shallow thermocline. In total, El Nino is theresult of the response of the equatorial Pacific Ocea.
In the recovery of sparse vectors from quadratic measurements, the presence of linear terms breaks the square root bottleneck

Motivated by recent results in the statistical physics of spin glasses, we study the recovery of a sparse vector $\mathbf{x}_0\in \mathbb{S}^{n-1}$, $\|\mathbf{x}_0\|_{\ell_0} = k<n$, from $m$ quadratic measurements of the form $ (1-\lambda)\langle \mathbf{A}_i, \mathbf{x}_0\mathbf{x}_0^T \rangle + \lambda \langle\mathbf{c}_i,\mathbf{x}_0 \rangle $ where $\mathbf{A}_{i}, \mathbf{c}_{i}$ have i.i. d Gaussian entries. This can be related to a constrained version of the 2-spin Hamiltonian with external field for which it was recently shown (in the absence of any structural constraint and in the asymptotic regime) that the geometry of the energy landscape becomes trivial above a certain threshold $\lambda>\lambda_c\in (0,1)$. Building on this idea we study the evolution of the so-called square root bottleneck for $\lambda\in [0,1]$ in the setting of the sparse rank one matrix recovery/sensing problem. We show that recovery of the vector $\mathbf{x}_0$ can be guaranteed as soon as $m\gtrsim k^2 (1-\lambda)^2/\lambda^2$, $\lambda \gtrsim k^{-1/2}$ provided that this vector satisfies a sufficiently strong incoherence condition, thus retrieving the linear regime for an external field $(1-\lambda)/\lambda \lesssim k^{-1/2}$. Our proof relies on an interpolation between the linear and quadratic settings, as well as on standard convex geometry arguments.
New constrained generalized Killing spinor field classes in warped flux compactifications

The generalized Fierz identities are addressed in the K\"ahler-Atiyah bundle framework from the perspective of the equations governing constrained generalized Killing spinor fields. We explore the spin geometry in a Riemannian 8-manifold composing a warped flux compactification AdS$_3\times M_8$, whose metric and fluxes preserve one supersymmetry in AdS$_3$. Supersymmetry conditions can be efficiently translated into spinor bilinear covariants, whose algebraic and differential constraints yield identifying new spinor field classes. Intriguing implications and potential applications are discussed.
Faster QUBO Brute-Force Solving using Gray Code

This article describes an improved brute-force solving strategy for Quadratic Unconstrained Binary Optimization (QUBO) problems that is faster than naive approaches and easily parallelizable. It exploits the Gray code ordering of natural numbers to allow for a more efficient evaluation of the QUBO objective function. The implementation in Python is discussed in detail, and an additional C implementation is provided.
Detection Threshold and Location Resolution of the Alberta Geological Survey Earthquake Catalogue

The Western Canada Sedimentary Basin (WCSB) is a low seismicity area, with fewer than fifteen cataloged M L>3.5 events since 1985 (Earthquakes Canada, 2013b). Since 1918, there have been more than 800 earthquakes reported in this region (Earthquakes Canada, 2013b), mainly clustered near the town of Rocky Mountain House (Rebollar et al. , 1982, 1984; Wetmiller, 1986), the Brazeau River (Schultz et al. , 2014), Fort St. John (Horner et al. , 1994), Turner Valley, Kinbasket Lake (Ellis and Chandra, 1981), and the Horn River Basin (BC Oil and Gas Commission, 2012); a single event larger than M L 4.5 was also reported near Snipe Lake (8 March 1970, 18:52:18 UTC; see Milne, 1970). The most active of these clusters is in the Strachan D‐3A gas field near Rocky Mountain House, where 146 events were recorded over a span of 23 days in 1980 (Wetmiller, 1986). Many of these aforementioned clusters have been conjectured as induced by gas extraction (Baranova et al. , 1999), waste water disposal (Horner et al. , 1994; Schultz et al. , 2014), or hydraulic fracturing operations (BC Oil and Gas Commission, 2012; Farahbod et al. , 2014). Historically, the compilation of the Earthquakes Canada Catalogue (EqCC) has been the responsibility of Natural Resources Canada (NRCan). More recently, a new initiative was taken by the Alberta Geological Survey (AGS) to improve the earthquake catalog in an effort to better understand the tectonics and seismicity of Alberta (AB). Interested readers are referred to Stern et al. (2013) for specific details on the methodology, station parameters, and earthquake locations of the AGS catalog. Overall, the quality and density of documented earthquakes is subject to the performance of the recording array (Fig. 1). Similar to the EqCC, the AGS catalog includes continuous waveform data from the Canadian National Seismic Network (CNSN); …
Building Real-World Meeting Summarization Systems using Large Language Models: A Practical Perspective

This paper studies how to effectively build meeting summarization systems for real-world usage using large language models (LLMs). For this purpose, we conduct an extensive evaluation and comparison of various closed-source and open-source LLMs, namely, GPT-4, GPT- 3.5, PaLM-2, and LLaMA-2. Our findings reveal that most closed-source LLMs are generally better in terms of performance. However, much smaller open-source models like LLaMA- 2 (7B and 13B) could still achieve performance comparable to the large closed-source models even in zero-shot scenarios. Considering the privacy concerns of closed-source models for only being accessible via API, alongside the high cost associated with using fine-tuned versions of the closed-source models, the opensource models that can achieve competitive performance are more advantageous for industrial use. Balancing performance with associated costs and privacy concerns, the LLaMA-2-7B model looks more promising for industrial usage. In sum, this paper offers practical insights on using LLMs for real-world business meeting summarization, shedding light on the trade-offs between performance and cost.