Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Causal Bandits for Linear Models

Sequential design of experiments for optimizing a reward function in causal systems can be effectively modeled by the sequential design of interventions in causal bandits (CBs). In the existing literature on CBs, a critical assumption is that the causal models remain constant over time. However, this assumption does not necessarily hold in complex systems, which constantly undergo temporal model fluctuations. This paper addresses the robustness of CBs to such model fluctuations. The focus is on causal systems with linear structural equation models (SEMs). The SEMs and the time-varying pre- and post-interventional statistical models are all unknown. Cumulative regret is adopted as the design criteria, based on which the objective is to design a sequence of interventions that incur the smallest cumulative regret with respect to an oracle aware of the entire causal model and its fluctuations. First, it is established that the existing approaches fail to maintain regret sub-linearity with even a few instances of model deviation. Specifically, when the number of instances with model deviation is as few as $T^\frac{1}{2L}$, where $T$ is the time horizon and $L$ is the longest causal path in the graph, the existing algorithms will have linear regret in $T$. Next, a robust CB algorithm is designed, and its regret is analyzed, where upper and information-theoretic lower bounds on the regret are established. Specifically, in a graph with $N$ nodes and maximum degree $d$, under a general measure of model deviation $C$, the cumulative regret is upper bounded by $\tilde{\mathcal{O}}(d^{L-\frac{1}{2}}(\sqrt{NT} + NC))$ and lower bounded by $\Omega(d^{\frac{L}{2}-2}\max\{\sqrt{T},d^2C\})$. Comparing these bounds establishes that the proposed algorithm achieves nearly optimal $\tilde{\mathcal{O}}(\sqrt{T})$ regret when $C$ is $o(\sqrt{T})$ and maintains sub-linear regret for a broader range of $C$.
SHORT COMMUNICATION HYDROLOGIC SPIRALLING: THE ROLE OF MULTIPLE INTERACTIVE FLOW PATHS IN STREAM ECOSYSTEMS y,z

We develop and illustrate the concept of ‘hydrologic spiralling’ using a high-resolution (2 � 2 m grid cell) simulation of hyporheic hydrology across a 1.7 km 2 section of the sand, gravel and cobble floodplain aquifer of the upper Umatilla River of northeastern Oregon, USA. We parameterized the model using a continuous map of surface water stage derived from LIDAR remote sensing data. Model results reveal the presence of complex spatial patterns of hyporheic exchange across spatial scales. We use simulation results to describe streams as a collection of hierarchically organized, individual flow paths that spiral across ecotones within streams and knit together stream ecosystems. Such a view underscores the importance of: (1) gross hyporheic exchange rates in rivers, (2) the differing ecological roles of short and long hyporheic flow paths, and (3) the downstream movement of water and solutes outside of the stream channel (e.g. in the alluvial aquifer). Hydrologic spirals underscore important limitations of empirical measures of biotic solute uptake from streams and provide a needed hydrologic framework for emerging research foci in stream ecology such as hydrologic connectivity, spatial and temporal variation in biogeochemical cycling rates and the role of stream geomorphology as a dominant control on stream ecosystem dynamics. Copyright # 2008 John Wiley & Sons, Ltd.
Mood Disorders in Adolescents Diagnosis , Treatment , and Suicide Assessment in the Primary Care Setting

Four million children and adolescents in the United States suffer from a serious mental illness that causes significant impairments at home, at school, and with peers. Moreover, half of all lifetime cases of mental disorders begin at 14 years of age. Despite effective treatments, only 20% of youths with mental illnesses are identified and receive mental health services. Undiagnosed mental illness can progress to more severe, difficult-to-treat illness and to the development of comorbid mental health disorders. Compared with their peers, youths with mental illness are more likely to be high utilizers of primary care services. Hence, primary care providers are strategically poised
Online Conversion with Switching Costs: Robust and Learning-Augmented Algorithms

We introduce and study online conversion with switching costs, a family of online problems that capture emerging problems at the intersection of energy and sustainability. In this problem, an online player attempts to purchase (alternatively, sell) fractional shares of an asset during a fixed time horizon with length $T$. At each time step, a cost function (alternatively, price function) is revealed, and the player must irrevocably decide an amount of asset to convert. The player also incurs a switching cost whenever their decision changes in consecutive time steps, i.e., when they increase or decrease their purchasing amount. We introduce competitive (robust) threshold-based algorithms for both the minimization and maximization variants of this problem, and show they are optimal among deterministic online algorithms. We then propose learning-augmented algorithms that take advantage of untrusted black-box advice (such as predictions from a machine learning model) to achieve significantly better average-case performance without sacrificing worst-case competitive guarantees. Finally, we empirically evaluate our proposed algorithms using a carbon-aware EV charging case study, showing that our algorithms substantially improve on baseline methods for this problem.
Sim2Real for Environmental Neural Processes

Machine learning (ML)-based weather models have recently undergone rapid improvements. These models are typically trained on gridded reanalysis data from numerical data assimilation systems. However, reanalysis data comes with limitations, such as assumptions about physical laws and low spatiotemporal resolution. The gap between reanalysis and reality has sparked growing interest in training ML models directly on observations such as weather stations. Modelling scattered and sparse environmental observations requires scalable and flexible ML architectures, one of which is the convolutional conditional neural process (ConvCNP). ConvCNPs can learn to condition on both gridded and off-the-grid context data to make uncertainty-aware predictions at target locations. However, the sparsity of real observations presents a challenge for data-hungry deep learning models like the ConvCNP. One potential solution is 'Sim2Real': pre-training on reanalysis and fine-tuning on observational data. We analyse Sim2Real with a ConvCNP trained to interpolate surface air temperature over Germany, using varying numbers of weather stations for fine-tuning. On held-out weather stations, Sim2Real training substantially outperforms the same model architecture trained only with reanalysis data or only with station data, showing that reanalysis data can serve as a stepping stone for learning from real observations. Sim2Real could thus enable more accurate models for weather prediction and climate monitoring.
The Emergence of Social Complexity in Optimizing Mechanical Design Problems via Cultural Learning

Previous work on global constrained optimization problems demonstrated that knowledge swarms or meta-level interaction of knowledge sources in the belief space produced emergent cultural transmission. The swarming of individuals in the population space, Knowledge Swarms, has emerged as a result of these meta-level swarms in the belief space. The interaction of the knowledge sources in the belief space produced emergent phases of problem solving that reflected a branch and bound algorithmic process. These phases result in the emergence of individual roles within the population that leads to organized swarming in the population level and knowledge swarms in the social belief space. In this paper we describe a new framework based on Cultural Algorithms enhanced with heterogeneous social networks guided by belief knowledge in order to solve constrained mechanical design optimization problems. We use it to solve Golinski’s Speed reducer problem here. We conclude by describing the emergent features that give cultural systems their power to learn and adapt. Key-Words: Cultural swarms; evolutionary computation; social influence.
Reducing food loss and waste

Sustainability Globally, about one-third of all food is lost during production, harvest, storage, transport, and processing or is wasted in the retail sector, food service, and households. Food waste is widely seen as unethical and negatively affects the environment. Wasting red meat is particularly detrimental because of its large carbon and environmental footprint. Yet, as Aschemann-Witzel explains in a Perspective, the numerous interconnected factors that cause food loss and waste make it challenging to address. Efforts to reduce food loss and waste must involve many stakeholders, from individual consumers to governments, as part of a wider move toward sustainable food production. Science , this issue p. [408][1] [1]: /lookup/doi/10.1126/science.aaf2978
Advances in Noninvasive Biomarkers for Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) currently represents one of the most common liver diseases worldwide. Early diagnosis and disease staging is crucial, since it is mainly asymptomatic, but can progress to nonalcoholic steatohepatitis (NASH) or cirrhosis or even lead to the development of hepatocellular carcinoma. Over time, efforts have been put into developing noninvasive diagnostic and staging methods in order to replace the use of a liver biopsy. The noninvasive methods used include imaging techniques that measure liver stiffness and biological markers, with a focus on serum biomarkers. Due to the impressive complexity of the NAFLD’s pathophysiology, biomarkers are able to assay different processes involved, such as apoptosis, fibrogenesis, and inflammation, or even address the genetic background and “omics” technologies. This article reviews not only the currently validated noninvasive methods to investigate NAFLD but also the promising results regarding recently discovered biomarkers, including biomarker panels and the combination of the currently validated evaluation methods and serum markers.
Soil Moisture Differences between Terracette Benches and Risers on Semiarid Rangeland Hillslopes

Hoof impact on terracetted hillslopes affects bulk density and compaction between bench and riser. Increased soil moisture is not plant available and doesn't increase forage production. Greater water content on benches is due to shifts to smaller pore sizes with compaction. Reduced vegetative cover due to root impedance results in greater water content.
Estimate and Analysis of Water Footprint in Northwest China, 2000

Water footprint is a new concept reflecting people's real consumption and usage of water resources. It profoundly posts the real water consumption of social-economic system and offers a new viewpoint for water resource management. In this paper, the concept of water footprint is put forward, together with its calculation methodologies. As a case, the water footprint of Northwest China including Xinjiang Region, Qinghai, Gansu and Shanxi provinces in 2000 is quantified and analyzed, mainly based on the concept of virtual water and its quantification methods. The result shows that citizens in these provinces (region) in 2000 have consumed 613.3×10~8m~3 water resource in total, which means 713.3 m~3/year per capita and 1952L /day per capital, exceeding the statistical volume of usage. The water footprint based on the virtual water not only reflects the actual water occupations of human beings, but also has great importance for water management in arid regions in Northwest China, and gives the water management decision-maker a bran-new thought of solving the water scarcity and innovation of water management mechanisms to balance the water deficit and achieve regional water and food security, by improving the water usage efficiency to changing living mode, and by applying virtual water import strategy instead of water supply-side management.
Study of the effects of local geological structure on seismic ground motion and building vulnerability with microtremors

Examples of several earthquakes in last decades have shown that the influence of local geological structure (site effects) on seismic ground motion was often underestimated; the effects of the earthquake were therefore greater than expected. Especially dangerous is the situation when both the fundamental frequency of sediments and of structures are similar and a resonance occurs. Among the other methods for assessing the effects of local geology the use of microtremors achieved a recognition in the last decade. The method is based on measurements of ambient vibration of natural and artificial origin with three-component sensor. Spectral ratio between the records on horizontal and vertical component yield fundamental frequency of soft sediments deposited over hard bedrock. By measurements inside buildings the main building frequency in longitudinal and transverse direction and consequently the range of increased vulnerability is determined. By comparison of the fundamental frequency map of sediments and measurements inside buildings, we can perform quantitative microzonation of urbane areas and identify areas where the danger of soil-structure resonance exists. In Slovenia microtremors investigations are carried out in the frame of a NATO Science for peace project. By measurements in a very dense grid of 200 m x 200 m a new microzonation of Ljubljana will be performed. In the Bovec basin, where the site effects were very prominent during 1998 and 2004 damaging earthquakes, we found out that relative high damage to some buildings were caused by soil-structure resonance effects. In Ilirska Bistrica, which is one of the most seismically active regions in Slovenia, we also established that most of the buildings damaged during stronger earthquakes are located in areas characterised by the fundamental frequency of soil which coincide with the range of the main building frequencies. doi:10.5474/geologija.2007. 006
Acrofacial vitiligo secondary to PI3KCA inhibitor, alpelisib: case report

Alpelisib plus fulvestrant is a valid second or advanced line of treatment for patients with metastatic hormone receptor (HR)-positive, HER2-negative breast cancer who harbor an activating PIK3CA mutation. The well-known side effects of alpelisib are hyperglycemia, rash, and diarrhea. Herein, we report a case of a woman who developed diffuse depigmented macules on the face, arms and legs, three months after initiating alpelisib. Both clinical and histopathological findings were consistent with new-onset vitiligo. To our knowledge, this is the first case described in literature which suggests a causal relationship between alpelisib and irreversible dermatological adverse effect.
Gauging the ecological capacity of southern Appalachian reserves: does wilderness matter?

A multi-unit wilderness system in the Southern Appa- lachians was evaluated for its long-term capacity to support biodi- versity and provide other forms of "ecological insurance. " Based on spatial thresholds for selected species, community and ecosystem level attributes, ecological capacity was found to be conditional, hierarchical and interactive. Existing reserves appear to have successfully maintained some ecological structure and processes for up to half-century. However, most reserves theoretically large enough to represent certain animal taxa were too small to sustain, in situ, all native habitats for these taxa. Designated wilderness did not represent all major forest types common to the bioregion. Additions to the network would enhance but not completely safe- guard the ecological capacity of this wilderness system. until the present. The second approach relies on projection of trends into the future to see how well ecological values are likely to be maintained given known rates of disturbance and other sources of natural or anthropogenic risk. Selected spatial thresholds in ecological structure or func- tion, including natural disturbance regimes, are used here to estimate adequacy in the size of wilderness and other pro- tected landscapes in the Southern Appalachians. We employ both retrospective and futuristic perspectives in these analy- ses. We also review evidence for the ability of the designated wilderness reserve system in this region to protect certain elements of biodiversity over the last half century. Finally, we examine whether and how the addition of lands adjacent to this wilderness system might enhance long-term sustain- ability. Our analyses used a combination of existing wilder- ness areas, nearby public lands and other land units that have been proposed recently for protection.
Length and and hip-joint angles THE ANTAGONIST MUSCLE PATTERN IN ELBOW EXTENSION OF A THROWING TASK 1

The myoelectric aetivity of agonist and antagonist muscles in fast human movements is eharacterised by a triphasie pattern. The mos\ important events are the first agonist activation (AG1) responsible for the initial Iimb aceeleration, and the antagonist aetivation (ANT), eoineident with the electrical silenee of the agonist muscle, and related with movement braklng. If the role of the first agonist burst to the initial limb acceleration is obvious, the accurate definition of the antagonist impulse function is not clearly definecl on the literature. The ongins of this EMG event have been attributed to both peripheral and central sources, but the relative participation of each one has also carrled out controversy (Angel, 1977, Marsden et a1., 1983). The purpose of the present study was (1) to eharacterise the antagonistie pattern on the elbow extension when subjects had to perform an overarm throw onto a target, and (2) to analyse the antagonist ehanges when subjects throw with different aecuracy/speed requirements.
Ochratoxin A Growth Probability Estimation in Wine Production Using AI-Powered IoT Devices

Mycotoxins are toxic compounds naturally produced by different ubiquitous filamentous fungi. Present in many foods, also colonize grapes during their growth in the vineyard. The production of mycotoxins by these fungi is heavily influenced by the substrate, and also by environmental factors such as high levels of temperature and humidity, conditions worsened nowadays by the ongoing climate change on a global scale. Ochratoxin A (OTA) is one of the most abundant food-contaminating mycotoxins produced by species belonging to Aspergillus and Penicillium genera and the main mycotoxin present in grapes on whose pericarp usually fungi are present. During the harvest, the permanence of the grapes in the field could induce the production of OTA which, consequently, may contaminate future grape products such as wine, grape juice and dried vine fruit. In this paper, we propose an electronic solution based on Internet of Things (IoT) devices and powered by artificial intelligence. The system exploits environmental sensor measurements to feed a neural network model that was designed and implemented on a microcontroller with the aim of classifying the probability of OTA growth during grape harvesting phases, according to the occurrence of specific harvesting conditions.
Loading of Silver (I) Ion in L-Cysteine-Functionalized Silica Gel Material for Aquatic Purification

The L-cysteine-functionalized silica (SG-Cys−Na+) matrix was effectively loaded with silver (I) ions using the batch sorption technique. Optimal Ag(I) loading into SG-Cys−Na+ reached 98% at pHi = 6, 80 rpm, 1 mg L−1, and a temperature of 55 °C. The Langmuir isotherm was found to be suitable for Ag(I) binding onto SG-Cys−Na+ active sites, forming a homogeneous monolayer (R2 = 0.999), as confirmed by FTIR spectroscopy. XRD analysis indicated matrix stability and the absence of Ag2O and Ag(0) phases, observed from diffraction peaks. The pseudo-second-order model (R2 > 0.999) suggested chemisorption-controlled adsorption, involving chemical bonding between silver ions and SG-Cys−Na+ surface. Thermodynamic parameters were calculated, indicating higher initial concentrations leading to increased equilibrium constants, negative ΔG values, positive ΔS values, and negative ΔH. This study aimed to explore silver ion saturation on silica surfaces and the underlying association mechanisms. The capability to capture and load silver (I) ions onto functionalized silica gel materials holds promise for environmental and water purification applications.
GESTIÓN DEL CONOCIMIENTO Y USO DE TICS EN LA EMPRESA PRIVADA Y ADMINISTRACIÓN PÚBLICA. KNOWLEDGE MANAGEMENT AND USE OF ICT'S IN PRIVATE AND PUBLIC COMPANY.

En la actualidad se puede afirmar que el éxito de una organización pública o privada es directamente proporcional al manejo de la gestión del conocimiento que se lleva a cabo dentro de sus instancias. La gestión del conocimiento no es más que gestionar los flujos de información y llevar la información correcta a las personas que las necesitan, ayudando de esta forma a las empresas a reaccionar con rapidez ante mercados cada vez mas cambiantes, siendo este el punto donde pasan a jugar un papel importante las tecnologías de la información y de la comunicación (TIC’s), como herramienta en la recolección, transferencia, seguridad y administración sistemática de la información, junto con los sistemas diseñados para ayudar a hacer el mejor uso de ese conocimiento. El artículo tiene como objetivo hacer reflexiones sobre la gestión de conocimiento a través del uso de las (TIC’s) en las organizaciones públicas y privadas. Se hizo una revisión documental en fuentes bibliográficas y electrónicas. Las conclusiones se orientan a entender la importancia de transferir la información con el uso de las TICs, para generar conocimiento como factor clave de éxito. Palabras Clave: Gestión del Conocimiento, Tecnologías de Información y Comunicación. Empresa Privada. Administración Pública.
A One-Bit Programmable Multi-Functional Metasurface for Microwave Beam Shaping

In this paper, we demonstrate a multi-functional metasurface for microwave beam-shaping application. The metasurface consists of an array of programmable unit cells, and each unit cell is integrated with one varactor diode. By turning the electrical bias on the diode on and off, the phase delay of the microwave reflected by the metasurface can be switched between 0 and π at a 6.2 GHz frequency, which makes the metasurface 1-bit-coded. By programming the 1-bit-coded metasurface, the generation of a single-focus beam, a double-focus beam and a focused vortex beam was experimentally demonstrated. Furthermore, the single-focus beam with tunable focal lengths of 54 mm, 103 mm and 152 mm was experimentally observed at 5.7 GHz. The proposed programmable metasurface manifests robust and flexible beam-shaping ability which allows its application to microwave imaging, information transmission and sensing applications.