Miracle-dz/UniFAR-FTUs huggingface dataset:
Growth and Ecology of a Multi-branched Ediacaran Rangeomorph from the Mistaken Point Assemblage, Newfoundland

Abstract Pectinifrons abyssalis new genus and species is an early Ediacaran (ca. 565 Ma) rangeomorph from the Avalon Peninsula of Newfoundland. It is known from more than 200 specimens from the Mistaken Point and Trepassey formations, and is typically preserved as a comb-shaped ridge on the top of mudstone beds beneath volcanic ashfall tuffs. Morphologic and taphonomic features suggest that the living organism consisted of two parallel series of soft rangeomorph fronds, alternately branching in an opposite arrangement from an elongate, tubular pedicle rod. The pedicle rod and the struts that represent the central stalks of the fronds were originally composed of resistant material that did not decompose until after lithification of the overlying ash bed. The fronds themselves were originally composed of a soft, non-resistant material that readily degraded, resulting in their extremely rare preservation as impressions on the bedding surface. Biometric analysis implies that Pectinifrons grew primarily by strut/frond addition, with later inflation of these elements. Pectinifrons is one of the first rangeomorph taxa to display evidence of possible age cohorts comparable to those observed in modern macrobenthic organisms.
Chemical constituents of Cinnamomum septentrionale leaf litter and its allelopathic activity on the growth of maize (Zea mays)

Abstract A pot experiment was conducted to study the effect of decomposing Cinnamomum septentrionale leaf litter on the growth of maize. In this study, the morphological traits of maize were significantly inhibited when the leaf litter amount reached or exceeded 40 g per pot; Furthermore, during the early growth stage or with a large amount of litter addition, the pigment contents were inhibited by C. septentrionale leaf litter. Gas chromatography–mass spectrometry was used to determine the volatile substances of leaf litter and 34 compounds were identified, several of which were reported to be phytotoxic. In conclusion, the leaf litter of C. septentrionale showed a strong allelopathic effect on the growth of maize. Thus, it is better to avoid the growing of maize under or near the C. septentrionale plantation unless the leaf litter could be eliminated in time or other effective leaf litter processing methods could be implemented.
Perceived Threat Had a Greater Impact Than Contact with Immigrants on Brexit Vote

In the early 21st century, the United Kingdom (UK) witnessed a significant rise in net immigration, partly caused by freedom of movement within the European Union (EU). In response to political pressures, a referendum on EU membership was held in June 2016, resulting in a narrow majority for leaving the EU. This paper analyses the relative impact of contact and perceived threat on prejudice and voting behaviour in the referendum based on a sample of 1127 UK adults. While racial prejudice was a significant predictor of stated voting behaviour in the referendum, the relationship of voting with perceived threat was greater. Both factors were around five times more predictive of voting behaviour than contact. Both prejudice towards and perceived threat from EU immigrants was significantly more predictive than the same measures across all immigrants, suggesting that the impact of these variables on voting behaviour was more nuanced than a general negativity towards immigrants. There was no evidence that any positive effect of contact in reducing prejudice cumulates over multiple touchpoints.
Stress Testing Chain-of-Thought Prompting for Large Language Models

This report examines the effectiveness of Chain-of-Thought (CoT) prompting in improving the multi-step reasoning abilities of large language models (LLMs). Inspired by previous studies \cite{Min2022RethinkingWork}, we analyze the impact of three types of CoT prompt perturbations, namely CoT order, CoT values, and CoT operators on the performance of GPT-3 on various tasks. Our findings show that incorrect CoT prompting leads to poor performance on accuracy metrics. Correct values in the CoT is crucial for predicting correct answers. Moreover, incorrect demonstrations, where the CoT operators or the CoT order are wrong, do not affect the performance as drastically when compared to the value based perturbations. This research deepens our understanding of CoT prompting and opens some new questions regarding the capability of LLMs to learn reasoning in context.
STAG: Enabling Low Latency and Low Staleness of GNN-based Services with Dynamic Graphs

Many emerging user-facing services adopt Graph Neural Networks (GNNs) to improve serving accuracy. When the graph used by a GNN model changes, representations (embedding) of nodes in the graph should be updated accordingly. However, the node representation update is too slow, resulting in either long response latency of user queries (inference is performed after update completes) or high staleness problem (inference is performed based on stale data). Our in-depth analysis shows that the slow update is mainly due to neighbor explosion problem in graphs and duplicated computation. Based on such findings, we propose STAG, a GNN serving framework that enables low latency and low staleness of GNN-based services. It comprises a collaborative serving mechanism and an additivity-based incremental propagation strategy. With collaborative serving mechanism, only part of node representations are updated during the update phase, and the final representations are calculated in the inference phase. It alleviates the neighbor explosion problem. The additivity-based incremental propagation strategy reuses intermediate data during update phase, eliminating duplicated computation. Experimental results show that STAG greatly reduces staleness time with a slight increase in response latency, and support 2.7~27x workload compared to existing approaches.
Title of the Deliverable: Demonstration of Learning Disparity-tuned Feature Selective Cells

This deliverable provides information and first obtained results of the developed software module called PVCStereo that allows for learning binocular receptive fields based on Hebbian learning. The software module is written in C++, using an artificial neural-network architecture (ANNarchy) library, developed in our lab. The learning algorithm has been demonstrated to learn from stereo images of natural scenes. The set of stereo images was taken from a two-camera system mounted in our lab. We tested if the model learns disparity-tuned and feature selective cells from this set of stereo images. As expected, the cells learn localized, oriented, disparity tuned and bandpass filtering receptive fields, comparable to those in area V1 of the primate brain. The detailed comparison with physiological data and the analysis of the determination of the disparity tuning curves is ongoing and will be reported in D 3.1b.
SPATIAL AND TEMPORAL ANALYSIS OF ANNUAL RAINFALL VARIATIONS IN TURKEY

This paper presents the spatial and temporal characteristics of Turkey's annual rainfall data in the context of climatic variability. Basic data consists of the monthly rainfall totals from 91 stations with a record length ranging from 54 to 64 years, during the period 1930–1993. Basic elements of the rainfall climatology have been examined and then normalized rainfall anomaly series have been analysed for long-term trend and fluctuation and changes in runs of dry and wet years, for all of Turkey, rainfall regime regions, and individual stations. All regional mean rainfall anomalies have tended to vary in a statistically coherent manner over the rainfall regions. Area-averaged annual rainfall series have decreased slightly over all of Turkey and apparently over the Black Sea and Mediterrane an rainfall regions. Results of the Mann–Kendall test, however, have indicated that none of the decreasing trends in the area-averaged rainfall series were significant. Annual series of 17 stations showed a significant trend in the mean and a majority of these trends are downward. Many of the stations have experienced marked low-frequency fluctuations in the annual rainfall. The concurrences of the dry conditions between the rainfall regions and the rest of Turkey have appeared generally during the early 1930s, the late 1950s, the early 1970s, around the 1980s and the early 1990s and of wet conditions generally during the period 1935–1945, around the 1960s and the late 1970s. The change points for the beginning of drier than normal conditions occurred in the early 1970s and early 1980s over most of the country. Annual rainfall variations over the rainfall regions except the Black Sea region were related closely to those of the rest of Turkey.
Lectio Praecursoria: Memory Meanders—Place, home and commemoration in an ex-Rhodesian diaspora community

A lectio præcursoria is a short presentation read out loud by a doctoral candidate at the start of a public thesis examination in Finland. It introduces the key points or central argument of the thesis in a way that should make the ensuing discussion between the examinee and the examiner apprehensible to the audience, many of whom may be unfamiliar with the candidate’s research or even anthropological research in general.
MotionLM: Multi-Agent Motion Forecasting as Language Modeling

Reliable forecasting of the future behavior of road agents is a critical component to safe planning in autonomous vehicles. Here, we represent continuous trajectories as sequences of discrete motion tokens and cast multi-agent motion prediction as a language modeling task over this domain. Our model, MotionLM, provides several advantages: First, it does not require anchors or explicit latent variable optimization to learn multimodal distributions. Instead, we leverage a single standard language modeling objective, maximizing the average log probability over sequence tokens. Second, our approach bypasses post-hoc interaction heuristics where individual agent trajectory generation is conducted prior to interactive scoring. Instead, MotionLM produces joint distributions over interactive agent futures in a single autoregressive decoding process. In addition, the model’s sequential factorization enables temporally causal conditional rollouts. The proposed approach establishes new state-of-the-art performance for multi-agent motion prediction on the Waymo Open Motion Dataset, ranking 1st on the interactive challenge leaderboard.
The Behavioralist Goes to School: Leveraging Behavioral Economics to Improve Educational Performance

Decades of research on behavioral economics have established the importance of factors that are typically absent from the standard economic framework: reference dependent preferences, hyperbolic preferences, and the value placed on non-financial rewards. To date, these insights have had little impact on the way the educational system operates. Through a series of field experiments involving thousands of primary and secondary school students, we demonstrate the power of behavioral economics to influence educational performance. Several insights emerge. First, we find that incentives framed as losses have more robust effects than comparable incentives framed as gains. Second, we find that non-financial incentives are considerably more cost-effective than financial incentives for younger students, but were not effective with older students. Finally, and perhaps most importantly, consistent with hyperbolic discounting, all motivating power of the incentives vanishes when rewards are handed out with a delay. Since the rewards to educational investment virtually always come with a delay, our results suggest that the current set of incentives may lead to underinvestment. For policymakers, our findings imply that in the absence of immediate incentives, many students put forth low effort on standardized tests, which may create biases in measures of student ability, teacher value added, school quality, and achievement gaps.
The Effect of Frozen Soil Depth on Winter Infiltration Hydrology in the Pataha Creek Watershed

The majority of the precipitation in the Pataha Creek watershed located in southeastern Washington occurs during winter in the form of rain and snow. The precipitation intensity typically is much lower than the soil’s infiltration capacity, but frozen soil acts as a barrier reducing the infiltration capacity significantly during the winter season causing surface runoff and soil erosion. This paper presents the findings from the studied watershed for the three winter seasons of 2000-2003. Infiltration plots with 1 m2 surface area were installed in the studied watershed during the period. Frost tubes were installed adjacent to these plots to monitor the frozen soil depth. The results showed clearly that plot runoff occurred only under frozen conditions and it increased with an increase in frozen depth. No till fields showed less frozen depth as compared to conventional tillage and hence less runoff. For the winter season of 2002-2003, soil moisture sensors and thermocouples were installed up to 30 cm in depth in no-till and conventional fields to run and verify the SHAW model. No runoff was found in the infiltration plots installed for this period due to a mild winter season characterized by low precipitation and shallow frozen soil depth. The SHAW model results showed a good match with observed data. The research findings showed that infiltration rate decreases with increase in frozen soil depth, and no-till showed higher infiltration rate due to less frozen soil depth as compared to conventional tillage.
Prompt-and-Align: Prompt-Based Social Alignment for Few-Shot Fake News Detection

Despite considerable advances in automated fake news detection, due to the timely nature of news, it remains a critical open question how to effectively predict the veracity of news articles based on limited fact-checks. Existing approaches typically follow a "Train-from-Scratch" paradigm, which is fundamentally bounded by the availability of large-scale annotated data. While expressive pre-trained language models (PLMs) have been adapted in a "Pre-Train-and-Fine-Tune" manner, the inconsistency between pre-training and downstream objectives also requires costly task-specific supervision. In this paper, we propose "Prompt-and-Align" (P&A), a novel prompt-based paradigm for few-shot fake news detection that jointly leverages the pre-trained knowledge in PLMs and the social context topology. Our approach mitigates label scarcity by wrapping the news article in a task-related textual prompt, which is then processed by the PLM to directly elicit task-specific knowledge. To supplement the PLM with social context without inducing additional training overheads, motivated by empirical observation on user veracity consistency (i.e., social users tend to consume news of the same veracity type), we further construct a news proximity graph among news articles to capture the veracity-consistent signals in shared readerships, and align the prompting predictions along the graph edges in a confidence-informed manner. Extensive experiments on three real-world benchmarks demonstrate that P&A sets new states-of-the-art for few-shot fake news detection performance by significant margins.
Fluid Flow in Fault Zones: Analysis of the Interplay of Convective Circulation and Topographically Driven Groundwater Flow

High-permeability faults, acting as preferential pathways for fluid migration, are important geological structures for fluid, energy, and solute transport. This paper examines the interaction of thermally driven convective circulation in a steeply dipping fault zone and groundwater flow through the surrounding country rock that is driven by a regional topographic gradient. We consider a geometry where a fault zone with a homogeneous, isotropic permeability is located beneath a narrow valley in a region with substantial topographic relief. System behavior is best characterized in terms of the large-scale permeabilities of the country rock and the fault zone. Using three-dimensional numerical simulations, we map in permeability space four fluid flow and heat transfer regimes within a fault zone: conductive, advective, steady convective, and unsteady convective. The patterns of fluid flow and/or heat transfer are substantially different in each of these regimes. Maximum discharge temperatures can also be plotted in permeability space; the maximum discharge temperature in the advective regime is in general lower than that in the steady convective regime. A higher basal heat flux expands the convective regime in permeability space, as does a greater fault depth. Higher topographic relief on the regional water table compresses the convective regime, with the advective regime suppressing convective circulation at lower country rock permeabilities. If convective cells with aspect ratios close to 1 cannot form, the steady convective regime is smaller in permeability space, and the boundary between steady and unsteady convection occurs at lower values of fault zone permeability. At low country rock permeabilities a water table gradient along the surface trace of the fault of approximately 0.3% suppresses convective cells; at higher country rock permeabilities, convection can be suppressed by smaller gradients on the water table.
Experimental Constraints on TTG Petrogenesis: Implications for Archean Geodynamics

Archean TTGs (tonalite-trondhjemite-granodiorite) are sodic granitoids that represent the bulk of the Archean continental crust. They are formed by fluid-absent partial melting of amphibolites. A compilation of the published data on experimental melting of amphibolites allows a mineralogical model for amphibolite melting to be derived for three different starting lithologies. A major and trace element model for melt compositions is produced using the mineralogical model. This model suggests that TTGs formed at P > 15 kbar and T between 900°C and 1100°C, corresponding to low (15°C/km) geothermal gradients that are likely to be attained only in subduction zones. Furthermore, it appears that Nb/Ta, La/Yb, Eu/Eu*, Sr, and HREE contents are intercorrelated in TTGs and are indicators of the pressure of melting. TTGs were generated over a large range of depths, from at least 10 to 25 kbar, and this is reflected in TTG compositions.
The local power effects of a global governance discourse : 'community participation' in the protection of biodiversity

In the international relations literature, two large narratives of power are sustaining a bipolar polemic on global governance, which is either supposed to foster the dynamics of empowerment (emancipatory narrative) or domination (critical narrative). Yet such presentations rarely rely upon detailed empirical work. Remarkably, International Relations (IR) scholars are paying little attention to the local power effects of global discourses. This research takes issue with a key but under-studied discourse - Community Participation (CP) - in the protection of biodiversity. The first case study is located in the Caribbean island of Saint Lucia and relates to corals. The second is in the Brazilian Pantanal, the world's largest wetland. Data were collected over four months of fieldwork, using face-to-face interviews, participant observation, focus groups and written material. To capture a broader diversity of power mechanisms, a grid drawn from recent works in IR was mobilised for the first time in this type of study. An analytical framework was also built that allows testable implications to be derived from macro-narratives and compared with micro-data. Rather than engendering empowerment, it appears that CP has essentially set in motion various containment dynamics affecting local stakeholders. Yet, while our data impressively fit the critical narrative, they also underscore its fragilities and contingency. At local levels, global governance discourses can no longer be seen as "singular and accepted", but rather as "contested and reinterpreted". They do not produce either emancipation or domination per se. They are most fruitfully analysed as tools thrown into local arenas which rent-seeking actors scramble to seize and use for their own ends. This significance of local dynamics undermines notions of North-South dependency or global governmentality. Data favour a hegemony model of the exercise of power that works through alliances and compromises amongst global and local groups within what we call "power formations".
Menu of Coupled Velocity and Sediment‐Discharge Relations for Rivers

Nonlinear multiple‐regression analysis is used to derive relations among the velocity, sediment discharge, bed‐form geometry, and friction factor of alluvial rivers. A data base comprising 339 river flows and 608 flume flows is used in the analysis. A hierarchy of formulations involving progressively more interdependencies among velocity, depth, sediment discharge, and bed‐form geometry is developed. Procedures for computing velocity‐ and sediment‐rating curves are presented. A simplified procedure for preparing depth‐discharge relations for streams with strongly, discontinuous rating curves is also presented. Rating curves for four rivers, and computed depths and velocities for two others, are presented. The accuracies of the different methods are evaluated in terms of the mean normalized errors of predicted friction factors, depths, velocities, and sediment discharges. It is concluded that these formulations yield velocity‐ and sediment‐rating curves that are as reliable as is permitted by the accuracy .
Ammonite biostratigraphy of the uppermost Tithonian, Berriasian, and lower Valanginian along the Río Argos (Caravaca, SE Spain)

This paper deals with the ammonite biostratigraphy of the lower 312 m of the Miravetes Formation (sections Y and Z) exposed 500 m north and northwest of Los Miravetes along the Rio Argos, 3 km west of Caravaca (SE Spain). This sequence embraces the uppermost Tithonian, Berriasian, and lower Valanginian. The succession of ammonite assemblages is similar to the one described by Le Hegarat (1971) from SE France. Le Hegarat's results are, where possible, completed and, where necessary, corrected. Arguments are adduced for a stratigraphic position of the Tithonian-Berriasian boundary, which should also be the Jurassic-Cretaceous boundary, between the Pseudosubplanites grandis and Subthurmannia (Strambergella) subalpina subzones. The Berriasian was divided into two zones, the lower Subthurmannia (Strambergella) occitanica Zone and the upper Subthurmannia (Subthurmannia) rarefurcata Zone. The latter comprises only the Berriasella (Malbosiceras) paramimouna and Berriasella (Berriasella) picteti subzones. Also arguments were adduced for a stratigraphic position of the Berriasian-Valanginian boundary between the B. (B.) picteti Subzone and the here proposed Tirnovella alpillensis Subzone. The latter can be correlated with the 'Sous-zone a Callisto' of Le Hegarat & Remane (1968), which is inadequately characterized with respect to its ammonite association. The T. alpillensis Subzone is the lowest subzone of the Thurmanniceras (Kilianella) retrocostatum Zone, here proposed, which also encloses Le Hegarat's Tirnovella pertransiens Subzone in the middle and the here proposed Sarasinella trezanensis - Thurmanniceras (Kilianella) pexiptychum Assemblage-subzone at the top. The Pseudosubplanites euxinus Zone (Wiedmann in Allemann et al., 1975), which is shown to embrace the Berriasella (Hegaratella) jacobi and Pseudosubplanites grandis subzones, is adopted as the name for the topmost Tithonian zone. Finally Neumayr's (1871) Paraulacosphinctes transitorius Zone and Kilian's (1888) Subthurmannia (Subthurmannia) boissieri and Thurmanniceras (Kilianella) roubaudianum zones are reinstated in their original faunistical sense and treated as superzones. For a better understanding of the author's interpretation of some taxa, palaeontological notes are added. In these a new genus, Pseudoneocomites, is introduced.