Miracle-dz/UniFAR-FTUs huggingface dataset:
GJFusion: A Channel-Level Correlation Construction Method for Multimodal Physiological Signal Fusion

Physiological signal based ubiquitous computing has garnered significant attention. However, the heterogeneity among multimodal physiological signals poses a critical challenge to practical applications. To traverse this heterogeneity gap, recent studies have focused on establishing inter-modality correlations. Early works only consider coarse-level correlations between the embeddings of each modality. More recent graph-based approaches incorporate prior knowledge-based correlations, although they may not be entirely accurate. In this article, we propose the Graph Joint Fusion (GJFusion) network, which leverages channel-level inter-modality correlations based on a graph joint to mitigate the heterogeneous gap. Our proposed GJFusion first represents each modality as a graph, with each vertex corresponding to a signal channel, and the edges denoting their functional connectivity. We then join each modality by constructing inter-modality correlations for each salient channel using a sampling-based matching method. Discarded channels are transformed into a virtual vertex through a lightweight pooling operation. Subsequently, the fusion network integrates intra- and inter-modality features, enabling multimodal physiological signal fusion. To validate the effectiveness of our method, we select emotional state recognition as the downstream task and conduct comprehensive experiments on two benchmark datasets. The results demonstrate that our proposed GJFusion network surpasses the latest state-of-the-art methods, achieving relative accuracy improvements of 1.22% and 0.81% on the DEAP and MAHNOB-HCI datasets, respectively. Furthermore, visualization experiments of the salient brain regions reveal the presence of interpretable knowledge within the proposed GJFusion model.
Evaluation of Vessel CO2 Emissions Methods using AIS Trajectories

Accurate estimation of shipping CO2 emissions is important for developing regulations to combat the greenhouse effect. Many shipping CO2 emissions models have been proposed in the past decades. However, most of them are only validated for a few specific ships, and there is a lack of data-driven validation and comparison of these models on a large scale. To fill this gap, this study proposes a general evaluation framework to quantitatively validate and compare different emission models. This framework is based on data integration of three types of data sources: ship technical details, AIS trajectory, and weather. Along with emission models, these data are fed into three carefully-designed modules that perform analysis at both grid and trajectory level as well as use annually aggregated fuel consumption ground truth. Extensive experiments are conducted on one-month data from 1,571 ships passing Danish waters to demonstrate the utility of the framework and insights into the accuracy of five popular CO2 emission models are presented.
Harmonization-guided deep residual network for imputing under clouds with multi-sensor satellite imagery

Multi-sensor spatiotemporal satellite images have become crucial for monitoring the geophysical characteristics of the Earth’s environment. However, clouds often obstruct the view from the optical sensors mounted on satellites and therefore degrade the quality of spectral, spatial, and temporal information. Though cloud imputation with the rise of deep learning research has provided novel ways to reconstruct the cloud-contaminated regions, many learning-based methods still lack the capability of harmonizing the differences between similar spectral bands across multiple sensors. To cope with the inter-sensor inconsistency of overlapping bands in different optical sensors, we propose a novel harmonization-guided residual network to impute the areas under clouds. We present a knowledge-guided harmonization model that maps the reflectance response from one satellite collection to another based on the spectral distribution of the cloud-free pixels. The harmonized cloud-free image is subsequently exploited in the intermediate layers as an additional input, paired with a custom loss function that considers image reconstruction quality and inter-sensor consistency jointly during training. To demonstrate the performance of our model, we conducted extensive experiments on a multi-sensor remote sensing imagery benchmark dataset consisting of widely used Landsat-8 and Sentinel-2 images. Compared to the state-of-the-art methods, results show at least a 22.35% improvement in MSE.
Differentiated Location Privacy Protection in Mobile Communication Services: A Survey from the Semantic Perception Perspective

Mobile communication services raise user privacy concerns in sharing the traveling trajectories while facilitating people’s daily lives. According to these shared trajectories, adversaries can dig users’ multi-modal behavioral semantics by combining with extensive open-source web information. These behavioral semantics have differentiated privacy sensitivity, raising different levels of privacy concerns. It makes users have personalized requirements for protecting their travelings. Resulting in the inevitable evolutionary trend from location privacy protection to differentiated location privacy protection (DLPP). DLPP digs into mobile semantics and characterizes the differentiated location sensitivity by simulating the potential attacks. It provides the privacy protection with differentiated strength to each location. Differentiated and appropriate strength well balances the tradeoff between privacy protection and data availability for the quality of application service. We are motivated to conduct a comprehensive survey on DLPP from the semantic perception perspective. It forms a complete overview of the mobile semantics-aware differentiation in location privacy protection. Specifically, we first review the research works on multi-modal mobile semantic representation. Then, taking the dug semantics as a clue, we summarize the basic principles of DLPP research systematically. To complete the overview, we also summarize their design modes and discuss the open opportunities and challenges for future works.
Stochastic Routing with Arrival Windows

Arriving at a destination within a specific time window is important in many transportation settings. For example, trucks may be penalized for early or late arrivals at compact terminals, and early and late arrivals at general practitioners, dentists, and so on, are also discouraged, in part due to COVID. We propose foundations for routing with arrival-window constraints. In a setting where the travel time of a road segment is modeled by a probability distribution, we define two problems where the aim is to find a route from a source to a destination that optimizes or yields a high probability of arriving within a time window while departing as late as possible. In this setting, a core challenge is to enable comparison between paths that may potentially be part of a result path with the goal of determining whether a path is uninteresting and can be disregarded given the existence of another path. We show that existing solutions cannot be applied in this problem setting and instead propose novel comparison methods. Additionally, we introduce the notion of Stochastic Arrival-Window Contraction Hierarchies that enable accelerated query processing in the article’s setting. Next, we present routing algorithms that exploit the above comparison methods in combination with so-called pivot paths and contraction hierarchies to enable efficient processing of the two types of queries. Finally, a detailed experimental study provides empirical insights that justify the need for the two types of routing and also offers insight into key characteristics of the problem solutions.
Dialects , Cultural Identity , and Economic Exchange

We study the effect of cultural ties on economic exchange using a novel measure for cultural identity: dialect similarity across regions of the same country. We evaluate linguistic microdata from a unique language survey conducted between 1879 and 1888 in about 45,000 German schools. The recorded geography of dialects comprehensively portrays local cultural ties that have been evolving for centuries, and provides an ideal opportunity to measure cultural barriers to economic exchange. In a gravity analysis, we then show that cross-regional migration flows in the period 2000–2006 are positively affected by historical dialect similarity. Using different empirical strategies, we show that this finding indicates highly timepersistent cultural borders that impede economic exchange even at a fine geographical scale. JEL Codes: R23; Z10; J61
Consumer Acceptance of Recommendations by Interactive Decision Aids: The Joint Role of Temporal Distance and Concrete Versus Abstract Communications

Interactive decision aids (IDAs) typically use concrete, feature-based approaches to interact with consumers. Recently, however, interaction designs that focus on communicating abstract consumer needs have been suggested as a promising alternative. This paper investigates how temporal distance moderates the effectiveness of these two competing IDA communication designs by its effect on consumers' mental representation of the product decision problem. Temporal distance is inherently connected to IDAs in two ways. Congruency between consumption timing (immediate versus distant) and IDA communication design (concrete versus abstract, respectively) increases the likelihood to accept the IDA's advice. This effect is also achieved by congruency between IDA process timing (immediate versus delayed delivery of recommendations) and IDA communication design (concrete versus abstract, respectively). We further show that this process is mediated by the perceived transparency of the IDA process. Managers and researchers need to take into account the importance of congruency between the user and the interface through which companies interact with their users and can further optimize IDAs so that they better match consumers' mental representations.
Rutting and soil displacement caused by 450C Timber Jack wheeled skidder (Asalem forest northern Iran)

The use of skidding machinery in logging operations causes destructive effects especially on soil but has many advantages such as extracting long and heavy logs, optimum use of useful logging time and absence of defect in wood production quality and thus an increase in the added value of wood. In this research compartment 40 of the second district of Nav-Asalem in northern Iran at an altitude of 1,050-1,450 m above sea level was chosen in order to assess the amount of displaced soil volume and depth of ruts due to the traffic of Timber Jack 450C rubber wheeled skidder along the skid trail. Therefore, the correlations between two independent variables, longitudinal slope and soil texture, with two dependent variables, displaced soil volume and average depth of rut, along the skid trail were examined after 20 passes of skidder machinery. The results of this research showed a significant difference between the longitudinal slope increase of skid trail and the amount of soil volume displaced ( P < 0.001). However, there was no significant cor - relation between the mean rut depth and different classification of longitudinal slope along the skid trail. The highest measured rut depth was 22 cm and occurred in the slope class of more than 25%. There was no significant correlation between the amount of displaced soil volume and rut depth with changes in soil texture along the skid trail.
Exploring the relationship between personality and work values with emerging adults

p. 3 Chapter One: Introduction p. 4 Chapter Two: Review of the Literature p. 7 Chapter Three: Method p. 22 Chapter Four: Results p. 27 Chapter Five: Discussion p. 30 References p. 34 Tables p. 37 Running head: EXPLORING THE RELATIONSHIP BETWEEN 3
E ﬀ ect of Weight Thresholding on the Robustness of Real-World Complex Networks to Central Node A tt acks

: In this study, we investigate the e ﬀ ect of weight thresholding (WT) on the robustness of real-world complex networks. Here, we assess the robustness of networks after WT against various node a tt ack strategies. We perform WT by removing a ﬁ xed fraction of weak links. The size of the largest connected component indicates the network’s robustness. We ﬁ nd that real-world networks subjected to WT hold a robust connectivity structure to node a tt ack even for higher WT values. In addition, we analyze the change in the top 30% of central nodes with WT and ﬁ nd a positive correlation in the ranking of central nodes for weighted node centralities. Di ﬀ erently, binary node centralities show a lower correlation when networks are subjected to WT. This result indicates that weighted node centralities are more stable indicators of node importance in real-world networks subjected to link sparsi ﬁ cation
Catalyzing the (3+2) Cycloaddition of Neutral TACs: Towards a Generalization of the CuAAC Reactivity Principles

: The introduction of the copper-catalyzed azide-alkyne coupling (CuAAC) to 1,3-dipolar cycloadditions was pivotal to their popularization in synthetic chemistry and to their application to multiple other domains of science. The reaction rate enhancement observed when coinage metal acetylide intermediates are involved in the cyclization process greatly expanded the structural and conditional range in which (3+2) cycloadditions may take place with terminal alkynes. Herein we report that comparable rate enhancements, in nature and level, can be observed in the intramolecular (3+2) cycloaddition of terminal alkynes with “neutral” three-atom components (TACs), specifically alkynyl sulfides. Through careful observations amidst reaction optimization, experimental and DFT mechanistic studies, a pathway involving a proton-coupled cyclometallation key step is proposed. The sets of catalytic conditions that have been developed allow to overcome several scope limitations previously presented by the thermally promoted (3+2) cycloaddition of “neutral” TACs, thus expanding their synthetic and applicative potential.
Observed and simulated variability of the AMOC at 26°N and 41°N

Time series of the observational estimate of the Atlantic meridional overturning circulation (AMOC) have recently become available, but so far, no contemporaneous relation has been documented between them. Here, we analyze the variability of the 26°N Rapid Climate Change programme (RAPID) and the 41°N Argo‐based AMOC estimates on seasonal timescales, and we compare them to a simulation from a high‐resolution National Centers for Environmental Prediction (NCEP)‐forced ocean model. In our analysis of the observed time series, we find that the seasonal cycles of the non‐Ekman component of the AMOC between 26°N and 41°N are 180‐degrees out‐of‐phase. Removing the mean seasonal cycle from each time series, the residuals have a non‐stationary covariability. Our results demonstrate that the AMOC is meridionally covariable between 26°N and 41°N at seasonal timescales. We find the same covariability in the model, although the phasing differs from the observed phasing. This may offer the possibility of inferring AMOC variations and associated climate anomalies throughout the North Atlantic from discontinuous observations.
Two to Tango: The Determinants of Workers’ and FIrms’ Willingness to Participate in Job-Related Training

This paper estimates the determinants of workers’ and ﬁrms’ willingness to train. <br>While previous studies imposed assumptions on ﬁrms’ ability to force workers into<br>training, I show that such assumptions are unnecessary for identiﬁcation, are rejected<br>by the data, and lead to biased estimates. I ﬁnd that diﬀerent training rates between<br>workers with various levels of education are mainly due to diﬀerences in workers’<br>willingness to participate in training. Diﬀerent training rates across age are primarily<br>driven by diﬀerences in ﬁrms’ willingness to train certain groups. These results give<br>clues about the successfulness of policies aimed at increasing training participation.Two to tango: the determinants of workers’ and ﬁrms’ willingness to participate in job-related training
'Fox Tots Attack Shock': Urban Foxes, Mass Media and Spacial Boundaries

On June 7, 2010, UK media outlets reported that 9-month-old twins living in East London had been rushed to hospital following a “suspected fox attack”: the babies had been seriously injured. This story received sustained coverage for several months, and became the focus of debate over the behavior of urban foxes, and how they and humans should coexist. Using textual analysis to unravel the various discourses surrounding this moment, this paper discusses how the incident became such a prominent “media event. ” Alongside the contexts of the “silly season” and a period of political transition, we argue that this incident breached a series of spatial boundaries that many societies draw between people and the “natural world,” from the “safest space” of a child's cot, to the categorizations made about animals themselves. We discuss the consequences of such boundary breaches, pointing to a deep confusion over the assignment of responsibility for, and expertise about, the figure of the “urban fox. ”
Basalts and Dolerites in the Sorachi-Yezo Belt, Central Hokkaido, Japan

Basalts and dolerites from the late Jurassic to early Cretaceous Sorachi Group and the Cretaceous melange complex in the central axial zone of Hokkaido are classified into the following three types: high K,O type alkaline basalts, characterized by high abundance in K,O, TiO" P,O, and normative nepheline, low K,O type alkaline basalts with high Na,O/ K,O ratio and normative nepheline, and MORB type tholeiites, poor in K,O, TiO" P,O,. The basaltic pillow lavas, dolerite dykes and sheets, observed as autochthonous members of the Upper Sorachi Group, correspond to the low K,O type alkaline basalts. The basaltic pillow lavas in the Lower Sorachi Group are of the MORB type tholeiites. Exotic blocks of basalt and dolerite in the Cretaceous accretionary melange complexes involve both the high K,O type alkaline basalts and the MORB type tholeiites.
Effect of magnetic activity on equatorial F region plasma drifts

Effect of magnetic activity, caused by complex interaction of solar wind and magnetosphere, on night time equatorial F region plasma drifts is studied using scintillation data recorded using spaced receivers at Tirunelveli (dip 0.4 0 ), for a 251 MHz signal transmitted from a geostationary satellite. Once the perturbation electric field associated with plasma bubbles are eroded, about two hours after the initiation of bubble growth, the irregularities simply drift across the signal path along with background plasma. Hence irregularity drift speed estimated from spaced receiver scintillation data is very close to the drift speed of the background plasma during this period. In order to obtain monthly average quiet time plasma drift pattern in the nighttime equatorial F region, the drifts estimated from scintillation data are averaged after 22LT for all quiet days (Ap < 18) of a month. Quantitative estimate of the effect of a disturbance dynamo produced by enhanced geomagnetic activity, on the nighttime equatorial F region plasma drift is obtained by removing monthly quiet time plasma drift pattern from disturbed time plasma drift pattern. The maximum effect of disturbance dynamo on equatorial F region plasma drift is observed around midnight for most of the magnetically disturbed days considered in the present study. An attempt is made here, (i) to relate the maximum deviation of the disturbed nighttime equatorial F region plasma drifts from quiet time pattern, with an empirical measure of the Joule energy input at high latitudes during magnetically active periods (ii) to investigate the time delays, which are required for obtaining the maximum disturbance dynamo effects observed in the night time equatorial F region plasma drifts, based on AE and Kp indices.
Human ecology : contemporary research and practice

Part 1: Philosophy, Theory, and Methods. There is no Mother Nature. Biocultural diversity. Causal explanations for forest fires, Indonesia. Knowledge & conservation practices. Levy flights. Fire, Senegal. LEK, Australia. Catch 22 conservation/LEK. Learning in the Pacific Northwest. Mediterranean landscapes. Mediterranean landscapes. Historical human ecology. Tobacco cultivation, West Honduras. - Part 2: Changing Subsistence Patterns. Gitksan landscapes. Without pigs in New Guinea. Ecology of rushes, Turkey. Agropastoralists, Siberia. Irrigation in Northern Spain. Pastoral production in Northern Kenya. Pastoral sedentarization & children's diet & health, N. Kenya. Impact of the ivory trade in E. Africa. Animal acquisition & herd demography, Turkana. Pastoralist response to flood plain rehab. , Cameroon. Aboriginal hunting, Western desert, Australia. Hunter-gatherer gardens, West Panama. Foraging in the Congo Basin. Bedouin tourist stations as response to drought. 1000 years in the Pacific Basin. - Part 3: Agricultural Intensification/Population Pressure. New Guinea populations. Boserup revisited. Maya Biosphere. Matrilineal fertility, China (social aspects of population dynamics). Agricultural intensification, Central Europe. Invasive species, South Africa. Climate change & warfare, China. Sustainability, agricultural development & LEK, Central America. Ecology of increasing diseases. Agricultural intensification & population growth, Amazon. - Part 4: Common Property Resources/Conservation. Clearcutting Maine. Andean irrigation. Borneo forests. Common property regimes, Ecuador. Hardin Revisited. Mali burning mosaic. Common property among the Tamir, Siberia. Forest conservation, Kalimantan. Fire use in South America. Fire Policy, Alaska. Coastal resource management. Families and firewood, sub-Saharan Africa. Rangelands as common property, South Africa. Private and communal forests, Guatemala. Glossary.
Universal spectral shape of high accretion rate agn

The spectra of quasars and NLS1 galaxies show surprising similarity in their spectral shape. They seem to scale only with the accretion rate. This is in contradiction with the simple expectations from the standard disk model which predicts lower disk temperature for higher black hole mass. Here we consider two mechanisms modifying the disk spectrum: the irradiation of the outer disk due to the scattering of the flux by the extended ionized medium (warm absorber) and the development of the warm Comptonizing disk skin under the eect of the radiation pressure instability. Those two mechanisms seem to lead to a spectrum which indeed roughly scales, as observed, only with the accretion rate. The scenario applies only to objects with relatively high Eddington ratio for which disk evaporation is inecient.
Logic Optimization Sequence Tuning Based on Policy Search Deep Reinforcement Learning

Logic optimization involves a set of Boolean transformations, and the different ways of permutation of Boolean transformations affect the circuit performance. The design space composed of these Boolean transformations is exponential. However, heuristic algorithms often need the guidance of human experience, and the result is not ideal for this large-scale search space problem. In this paper, the problem of logic synthesis optimization is mapped to the sequential decision process. We introduce policy search based reinforcement learning, which makes optimization decisions by analyzing data flow generated by synthesis tools, and find the optimal solution for logic synthesis. The evaluation of EPFL benchmark circuit shows that compared with the original design, the nodes are reduced by 19.60%, the depth is reduced by 13.76%. Compared with ABC script resyn2, the number of nodes is reduced by 6.70%, the depth is reduced by 7.76%. In addition, the performance of the scheme is successfully verified by the sequential circuit.